**Introduction**

**1** 

*USA* 

Jimmy T. Efird

**Epidemiology of Glioma** 

*Brody School of Medicine Greenville, North Carolina* 

Giomas constitute a broad class of neuroectodermal tumours believed to originate from sustentacular neuroglial cells (Kleihues and Cavenee 2000). Astrocytomas form the largest group of gliomas (>75%) and glioblastoma multiforme (GBM) is the most common type of astrocytoma (CBTRUS 2011). Gliomas that share histologic characteristics with ependymal or oligodendrocyte cells are named ependymomas and oligodendrogliomas, but may not necessarily originate from the aforementioned cell types (Kleihues and Cavenee 2000). Mixed gliomas include those which consist of more than one glia cell type. For example, oligodendroglial glioblastoma multiforme (as defined by some neuropathologists) are GBM tumours with an oligodendroglioma component and generally have a significantly worse clinical outcome than GBM tumours overall (Louis et al 2007). Another mixed glioma is

The Third Edition of the International Classification of Diseases for oncology (ICD-O-3) is widely used to categorize gliomas by histology (e.g., malignant glioma=9380, ependymoma NOS=9391, astrocytoma=9430, glioblastoma NOS=9440, oligodendroglioma NOS=9450) (Fritz et al 2000). Furthermore, tumours are grouped by site in the ICD-O-3 system using Ccodes (e.g., cerebrum=C71.0, frontal lobal=C71.1, temporal lobe=C71.2, parietal lobe=C71.3, occipital lobe=C71.4, ventricle=C71.5, cerebellum=C71.6, spinal cord=C72.0). The World Health Organization (WHO) also has developed a classification index which grades gliomas by disease prognosis (I=best to IV=worst) (Kliehues et al 1993). Recent additions to the "WHO Classification of Tumours" include Grade I - angiocentric gliomas (predominantly occurring in children and young adults in the fronto-parietal cortex, temporal lobe, and hippocampal region), and Grade II – pilomyxoid astrocytoma (typically occurring in infants and children in the hypothalamic/chiasmatic region) (Louis et al 2007). Additionally, WHO has recognized a divergent pattern of gliomas named small cell glioblastoma characterized by EGFR amplification, p16INK4a homozygous deletion, PTEN mutations, and LOH 10q

Gliomas comprise more than 80% of brain tumours (CBTRUS 2011), therefore, descriptive epidemiology about gliomas often is framed in the broader context of brain tumours as a whole.

oligoastrocytoma, which contains both oligodendrocyte and astrocyte cells.

**1. Introduction** 

(Louis et al 2007).

**2. Incidence and death rates** 

*Center for Health Disparities Research* 

*Department of Public Health* 

## **Epidemiology of Glioma**

#### Jimmy T. Efird

*Center for Health Disparities Research Department of Public Health Brody School of Medicine Greenville, North Carolina USA* 

#### **1. Introduction**

Giomas constitute a broad class of neuroectodermal tumours believed to originate from sustentacular neuroglial cells (Kleihues and Cavenee 2000). Astrocytomas form the largest group of gliomas (>75%) and glioblastoma multiforme (GBM) is the most common type of astrocytoma (CBTRUS 2011). Gliomas that share histologic characteristics with ependymal or oligodendrocyte cells are named ependymomas and oligodendrogliomas, but may not necessarily originate from the aforementioned cell types (Kleihues and Cavenee 2000). Mixed gliomas include those which consist of more than one glia cell type. For example, oligodendroglial glioblastoma multiforme (as defined by some neuropathologists) are GBM tumours with an oligodendroglioma component and generally have a significantly worse clinical outcome than GBM tumours overall (Louis et al 2007). Another mixed glioma is oligoastrocytoma, which contains both oligodendrocyte and astrocyte cells.

The Third Edition of the International Classification of Diseases for oncology (ICD-O-3) is widely used to categorize gliomas by histology (e.g., malignant glioma=9380, ependymoma NOS=9391, astrocytoma=9430, glioblastoma NOS=9440, oligodendroglioma NOS=9450) (Fritz et al 2000). Furthermore, tumours are grouped by site in the ICD-O-3 system using Ccodes (e.g., cerebrum=C71.0, frontal lobal=C71.1, temporal lobe=C71.2, parietal lobe=C71.3, occipital lobe=C71.4, ventricle=C71.5, cerebellum=C71.6, spinal cord=C72.0). The World Health Organization (WHO) also has developed a classification index which grades gliomas by disease prognosis (I=best to IV=worst) (Kliehues et al 1993). Recent additions to the "WHO Classification of Tumours" include Grade I - angiocentric gliomas (predominantly occurring in children and young adults in the fronto-parietal cortex, temporal lobe, and hippocampal region), and Grade II – pilomyxoid astrocytoma (typically occurring in infants and children in the hypothalamic/chiasmatic region) (Louis et al 2007). Additionally, WHO has recognized a divergent pattern of gliomas named small cell glioblastoma characterized by EGFR amplification, p16INK4a homozygous deletion, PTEN mutations, and LOH 10q (Louis et al 2007).

#### **2. Incidence and death rates**

Gliomas comprise more than 80% of brain tumours (CBTRUS 2011), therefore, descriptive epidemiology about gliomas often is framed in the broader context of brain tumours as a whole.

Epidemiology of Glioma 5

higher IR rates than blacks by histologic group (e.g., IR=3.55, 95%CI=3.52-3.59 vs. 1.64, 95%CI=1.57-1.72 for glioblastoma; IR=0.47, 95%CI=0.45-0.48 vs. 0.19, 95%CI=0.17-0.22 for anaplastic astrocytoma; IR=0.29, 95%CI=0.27-0.30 vs. 0.17, 95%CI=0.15-0.19 for ependymoma/anaplastic ependymoma) (CBTRUS 2011). **Sex**. Similarly, men consistently have higher age-adjusted IRs than women by histology (e.g., IR=3.99, 95%CI=3.94-4.04 vs. IR=2.53, 95%CI=2.49-2.57 for glioblastoma; IR=0.48, 95%CI=0.46-0.50 vs. 0.35, 95%CI=0.33- 0.36 for anaplastic astrocytoma; and IR=0.27, 95%CI=0.26-0.29 vs. IR=0.25, 95%CI=0.24-0.27 for ependymoma/anaplastic ependymoma), although the latter difference is not statistically significant (CBTRUS 2011). Interestingly, the female prevalence rate (PR) for primary brain tumours per 100KP-Y (PR=264.8) is higher than males (PR=158.7), perhaps attributable to

\*Counts suppressed since fewer than 16 cases reported in specific area-sex-race category.

A higher male (IR=37) to female (IR=2.6) pattern also is observed internationally (Parkin et al 2005), although U.S. rates are higher in both men (IR=7.7, 95%CI=7.5-7.8) and women (IR=5.6., 95%CI=5.5-5.7) compared with international rates (NCI State Cancer Profiles 2011). Less developed countries tend to report lower rates (e.g., Africa, Pacific Islands; IR=3.0 per 100KP-Y for males and 2.1 for females) than more developed countries (e.g., Australia, New Zealand, Europe, North America; IR=5.8 per 100KP-Y for men and 4.1 for females), possibly reflecting less access to modern medical facilities (Parkin et al 2005, CBTRUS 2011). In contrast, the standardized (age, sex, site, year at diagnosis) IR for brain tumours in Japan, a

Fig. 2. Death rates (NCI State Cancer Profiles 2011).

survival bias among women (Porter et al 2010).

#### **2.1 Incidence**

Overall, brain tumors are relatively rare events. Only 1 in 165 men and women will be diagnosed with cancer of the brain and other nervous system tumours in their lifetime (Altekruse et al 2010). The incidence rate (IR) per 100,000 person-years (100KP-Y) for malignant adult brain tumours ranges from 5.4 (95%CI =4.7-6.1) for the state of Hawaii to 12 (95%CI=12-13) for Wisconsin. IRs by state among children 0-19 years are less variable, ranging from 2 to 4. While geographic differences in IRs might suggest an environmental etiology for brain tumours, ecologic comparisons often do not account for variations in quality of reporting, diagnostic practices, and access/utilization to health care. States falling into the highest quantile for both age-adjusted incidence and death rates (DR) per 100KP-Y include Kentucky (IR=7.9, 95%CI=7.0-8.7; DR=4.9, 95%CI=4.3-5.6), Iowa (IR=7.6, 95%CI=6.7- 8.6; DR=5.4, 95%CI=4.6-6.2), and Oregon (IR=7.5, 95%CI=6.7-8.4; DR=5.2, 95%CI=4.5-5.9) (Figures 1 and 2) (NCI State Cancer Profiles 2011). A noticeable cluster of states (depicted in red) with the highest death rates is located along the northern portion of the U.S. from Oregon to Iowa (Figure 2).

†Age-adjusted (2000 U.S. standard population) cases per 100,000 population per year. ◊Data not available for Nevada.

Fig. 1. Incidence rates (NCI State Cancer Profiles 2011).

Gliomas IRs vary by histology, race, and sex. **Histology**. For example, the age-adjusted rate per 100KP-Y for glioblastoma is 3.19 (95% CI=3.16-3.23) compared with less than 0.2 for anaplastic oligodendroglioma (IR=0.12, 95%CI=0.11-0.13) and protoplasmic/fibrillary astrocytoma (IR=0.11, 95%CI=0.10-0.11) (CBTRUS 2011). **Race**. Whites consistently have

Overall, brain tumors are relatively rare events. Only 1 in 165 men and women will be diagnosed with cancer of the brain and other nervous system tumours in their lifetime (Altekruse et al 2010). The incidence rate (IR) per 100,000 person-years (100KP-Y) for malignant adult brain tumours ranges from 5.4 (95%CI =4.7-6.1) for the state of Hawaii to 12 (95%CI=12-13) for Wisconsin. IRs by state among children 0-19 years are less variable, ranging from 2 to 4. While geographic differences in IRs might suggest an environmental etiology for brain tumours, ecologic comparisons often do not account for variations in quality of reporting, diagnostic practices, and access/utilization to health care. States falling into the highest quantile for both age-adjusted incidence and death rates (DR) per 100KP-Y include Kentucky (IR=7.9, 95%CI=7.0-8.7; DR=4.9, 95%CI=4.3-5.6), Iowa (IR=7.6, 95%CI=6.7- 8.6; DR=5.4, 95%CI=4.6-6.2), and Oregon (IR=7.5, 95%CI=6.7-8.4; DR=5.2, 95%CI=4.5-5.9) (Figures 1 and 2) (NCI State Cancer Profiles 2011). A noticeable cluster of states (depicted in red) with the highest death rates is located along the northern portion of the U.S. from

†Age-adjusted (2000 U.S. standard population) cases per 100,000 population per year.

Gliomas IRs vary by histology, race, and sex. **Histology**. For example, the age-adjusted rate per 100KP-Y for glioblastoma is 3.19 (95% CI=3.16-3.23) compared with less than 0.2 for anaplastic oligodendroglioma (IR=0.12, 95%CI=0.11-0.13) and protoplasmic/fibrillary astrocytoma (IR=0.11, 95%CI=0.10-0.11) (CBTRUS 2011). **Race**. Whites consistently have

**2.1 Incidence** 

Oregon to Iowa (Figure 2).

◊Data not available for Nevada.

Fig. 1. Incidence rates (NCI State Cancer Profiles 2011).

higher IR rates than blacks by histologic group (e.g., IR=3.55, 95%CI=3.52-3.59 vs. 1.64, 95%CI=1.57-1.72 for glioblastoma; IR=0.47, 95%CI=0.45-0.48 vs. 0.19, 95%CI=0.17-0.22 for anaplastic astrocytoma; IR=0.29, 95%CI=0.27-0.30 vs. 0.17, 95%CI=0.15-0.19 for ependymoma/anaplastic ependymoma) (CBTRUS 2011). **Sex**. Similarly, men consistently have higher age-adjusted IRs than women by histology (e.g., IR=3.99, 95%CI=3.94-4.04 vs. IR=2.53, 95%CI=2.49-2.57 for glioblastoma; IR=0.48, 95%CI=0.46-0.50 vs. 0.35, 95%CI=0.33- 0.36 for anaplastic astrocytoma; and IR=0.27, 95%CI=0.26-0.29 vs. IR=0.25, 95%CI=0.24-0.27 for ependymoma/anaplastic ependymoma), although the latter difference is not statistically significant (CBTRUS 2011). Interestingly, the female prevalence rate (PR) for primary brain tumours per 100KP-Y (PR=264.8) is higher than males (PR=158.7), perhaps attributable to survival bias among women (Porter et al 2010).

\*Counts suppressed since fewer than 16 cases reported in specific area-sex-race category.

Fig. 2. Death rates (NCI State Cancer Profiles 2011).

A higher male (IR=37) to female (IR=2.6) pattern also is observed internationally (Parkin et al 2005), although U.S. rates are higher in both men (IR=7.7, 95%CI=7.5-7.8) and women (IR=5.6., 95%CI=5.5-5.7) compared with international rates (NCI State Cancer Profiles 2011). Less developed countries tend to report lower rates (e.g., Africa, Pacific Islands; IR=3.0 per 100KP-Y for males and 2.1 for females) than more developed countries (e.g., Australia, New Zealand, Europe, North America; IR=5.8 per 100KP-Y for men and 4.1 for females), possibly reflecting less access to modern medical facilities (Parkin et al 2005, CBTRUS 2011). In contrast, the standardized (age, sex, site, year at diagnosis) IR for brain tumours in Japan, a

Epidemiology of Glioma 7

Survival rates for the majority of malignant gliomas remain disappointingly low, despite decades of advances in surgical, radiation, and chemical therapies, in contrast to improvements in many other cancers. GBMs, for example, typically present as highly aggressive, difficult to treat tumours without clinical, radiologic, or morphologic forewarning of a less virulent precursor tumour (Kanu et al 2009; Ostrom and Barnholtz-Sloan 2011). Secondary GBMs account for only about 10% of all GBMs, based on the presence of IDH1/2 mutations (Ohgaki and Kleihues 2011). The infiltrating nature of these tumours makes treatment difficult. Other obstacles to effective treatment and improved survival include multidrug resistance, radioresistance, an impermeable blood-brain barrier, a lack of preclinical

The relative survival percentages (RSP) for gliomas compared with the general U.S. population vary tremendously by histology and age at diagnosis. For example, the majority of patients diagnosed between age 0-14 years with pilocytic astrocytoma (RSP=97.3%), oligodendroglioma (RSP=95.3), protoplasmic & fibrillary astrocytoma (RSP=84.3%), and mixed glioma (RSP=75.6%) will live beyond 5 years, compared with anaplastic astrocytoma (RSP=32.0%) and glioblastoma (RSP=20.9%) (CBTRUS 2011). In contrast, 5-year relative RSPs are considerably lower across histologic types for those diagnosed between age 45-54 (e.g., RSP=82.4% for pilocytic astrocytoma; RSP=76.8% for oligodendroglioma; RSP=51.1% for mixed glioma; RSP=39.5% for protoplasmic & fibrillary astrocytoma; RSP=28.6% for anaplastic astrocytoma; and RSP=5.6% for glioblastoma). Only 0.8% of patients diagnosed

**5-Year Relative Survival (whites) by Year of Diagnosis** 

Fig. 4. Survival percent (whites) for cancers of the brain and other nervous system tumours

models, and a rudimentary understanding of neurooncogenetics (Kanu et al 2009).

between age 55-64 will be alive after 10 years.

(NCI-SEER 2011).

country well known for accessible MR-imaging, is relatively low (2.5 per 100KP-Y personyears) (Matsuda et al 2011). Similarly low rates have been observed in Korea (Lee et al 2010).

#### **2.2 Death rates and survival**

The annual number of brain tumour deaths at last count (2007) in the U.S. was n=7,315 for men and 5,919 for women. Age-adjusted rates steadily increased from 1975 to 1991, likely due to advances in neuroimaging, but have decreased linearly thereafter, with recent values on par with 1975 rates (Figure 3) (NCI State Cancer Profiles 2011). Overall DRs are higher among men (DR=5.1, 95%CI=5.0-5.2) than women (DR=3.5, 95%CI=3.4-3.6), however the difference is not statistically significant as was seen for IRs. The lowest DR for men and women combined was observed for the State of Hawaii (DR=2.1, 95%CI=1.4-3.0), which implemented almost complete universal health care coverage in 1994 under the Med-QUEST programme (Hawaii Department of Human Services 2011). However, Hawaii also has the largest non Caucasian population of any state (i.e., 72.8% Asian/Pacific Islander), a factor associated with lower brain tumour incidence and death rates (NCI State Cancer Profiles 2011).

Fig. 3. Mortality trends (NCI State Cancer Profiles 2011).

country well known for accessible MR-imaging, is relatively low (2.5 per 100KP-Y personyears) (Matsuda et al 2011). Similarly low rates have been observed in Korea (Lee et al 2010).

The annual number of brain tumour deaths at last count (2007) in the U.S. was n=7,315 for men and 5,919 for women. Age-adjusted rates steadily increased from 1975 to 1991, likely due to advances in neuroimaging, but have decreased linearly thereafter, with recent values on par with 1975 rates (Figure 3) (NCI State Cancer Profiles 2011). Overall DRs are higher among men (DR=5.1, 95%CI=5.0-5.2) than women (DR=3.5, 95%CI=3.4-3.6), however the difference is not statistically significant as was seen for IRs. The lowest DR for men and women combined was observed for the State of Hawaii (DR=2.1, 95%CI=1.4-3.0), which implemented almost complete universal health care coverage in 1994 under the Med-QUEST programme (Hawaii Department of Human Services 2011). However, Hawaii also has the largest non Caucasian population of any state (i.e., 72.8% Asian/Pacific Islander), a factor associated with lower brain tumour incidence and death rates (NCI State Cancer

**2.2 Death rates and survival** 

Fig. 3. Mortality trends (NCI State Cancer Profiles 2011).

Profiles 2011).

Survival rates for the majority of malignant gliomas remain disappointingly low, despite decades of advances in surgical, radiation, and chemical therapies, in contrast to improvements in many other cancers. GBMs, for example, typically present as highly aggressive, difficult to treat tumours without clinical, radiologic, or morphologic forewarning of a less virulent precursor tumour (Kanu et al 2009; Ostrom and Barnholtz-Sloan 2011). Secondary GBMs account for only about 10% of all GBMs, based on the presence of IDH1/2 mutations (Ohgaki and Kleihues 2011). The infiltrating nature of these tumours makes treatment difficult. Other obstacles to effective treatment and improved survival include multidrug resistance, radioresistance, an impermeable blood-brain barrier, a lack of preclinical models, and a rudimentary understanding of neurooncogenetics (Kanu et al 2009).

The relative survival percentages (RSP) for gliomas compared with the general U.S. population vary tremendously by histology and age at diagnosis. For example, the majority of patients diagnosed between age 0-14 years with pilocytic astrocytoma (RSP=97.3%), oligodendroglioma (RSP=95.3), protoplasmic & fibrillary astrocytoma (RSP=84.3%), and mixed glioma (RSP=75.6%) will live beyond 5 years, compared with anaplastic astrocytoma (RSP=32.0%) and glioblastoma (RSP=20.9%) (CBTRUS 2011). In contrast, 5-year relative RSPs are considerably lower across histologic types for those diagnosed between age 45-54 (e.g., RSP=82.4% for pilocytic astrocytoma; RSP=76.8% for oligodendroglioma; RSP=51.1% for mixed glioma; RSP=39.5% for protoplasmic & fibrillary astrocytoma; RSP=28.6% for anaplastic astrocytoma; and RSP=5.6% for glioblastoma). Only 0.8% of patients diagnosed between age 55-64 will be alive after 10 years.

#### **5-Year Relative Survival (whites) by Year of Diagnosis**

Fig. 4. Survival percent (whites) for cancers of the brain and other nervous system tumours (NCI-SEER 2011).

Epidemiology of Glioma 9

**Survival upon 2 years (95%CI)** 

45.4 (38.2-52.3)

53.7 (37.8-67.2)

53.6 (42.9-63.2)

26.2 (20.6-32.1)

93.9 (80.5-98.2)

68.6 (63.1-73.5)

95.9 (92.6-97.8)

Table 1. Relative probability of a patient living 10 years beyond their diagnosis date if they

The key epidemiologic determinants of glioma risk include advancing age, male sex, and Caucasian race (Bondy and Wrensch 1996). Few environmental or lifestyle exposures, except for ionising radiation, have been found to be consistently associated with glioma risk. Suspected risk factors include lifestyle behaviors (e.g., smoking, alcohol consumption, coffee drinking), infectious agents (e.g., polyomaviruses, cytomegaloviruses, influenza, varicella zoster, *Toxoplasma gondii*), diet/vitamins (e.g., nitrosamine compounds, vitamin C, vitamin D3), beauty products (e.g., hair dyes and lighteners, hair waving and straightening chemicals), industrial exposures (e.g., rubber manufacturing, petroleum products), mobile phones, electromagnetic fields, allergies/immunity, agricultural/farm animal exposures, handedness, birth weight/height, and various genetic polymorphisms. While the list is long, methodologic biases are believed to account for the bulk of observed associations. A comprehensive review of factors hypothesized to play a role in the etiology of brain tumors is beyond the intent of the current work and the reader is referred to several recent reviews on the topic (Ostrom and Barnholtz-Sloan 2011; Ohgaki 2009; Fisher et al 2007; Schwartzbaum et al 2006; Ohgaki and Kleihues 2005; Wrensch et al 2002). Rather, the aim of this section is to address the etiology of gliomas in the context of recent publications and

Mobile (cellular) phones initially appeared on the market in the late 1970's in Japan and soon thereafter were sold in Europe and the U.S. (Bellis 2011). The first commercial wireless

However, the widespread and frequent use of mobile phones on an affordable scale was not achieved until the earlier 2000's when unlimited usage service contracts became a viable

call originating in the U.S. occurred on 13 October 1983 (Green 2008).

**Survival upon 5 years (95%CI)** 

73.6 (62.7-81.8)

75.6 (51.2-89.0)

73.7 (59.6-83.6)

70.4 (55.6-81.2)

97.6 (69.3-99.8)

78.5 (72.5-83.3)

99.2 (91.6-99.9)

**Histologic Category** 

Anaplastic astrocytoma

Diffuse astrocytoma

Oligodendroglioma

Pilocytic astrocytoma

**3. Risk factors** 

Glioblastoma multiforme

Anaplastic oligodendroglioma

Hemangioblastoma/hemangioma

have already survived 2 and 5 years.

current scientific debate on the topic.

**3.1 Mobile phones** 

RSPs also vary by race and sex. Black women (44%) have the highest 5-year RSPs for cancers of the brain and other nervous system tumours, when compared with white women (36.5%), black men (34.8%), and white men (32.6%) (Altekruse et al 2010). When examined by year of diagnosis from 1975 to 2002, whites (Figure 4) consistently have lower 5-year RSPs than blacks independent of sex (Figure 5) (NCI-SEER 2011).

**5-Year Relative Survival (blacks) by Year of Diagnosis** 

Fig. 5. Survival percent (blacks) for cancers of the brain and other nervous system tumours (NCI-SEER 2011).

Among adults, other factors associated with poorer survival include tumour site (frontal, cerebellum, multilobular), and socioeconomic status (less affluent individuals have lower survival rates) (Tseng et al 2006). The latter suggests that socioeconomic inequalities play an important role in glioma outcome, perhaps due to chronic comorbidities, inadequate access and utilization of health care, and longer wait times after surgery for adjuvant therapies (Tseng et al 2006).

While population-based relative survival statistics paint a dismal prognostic picture for certain glioma types, conditional survival rates suggest a more favorable long term outcome for patients who have already survived for a specified amount of time after diagnosis (Table 1) (Porter et al 2011). For Example, a GBM patient has a 70.4% (95%CI=55.6-81.2) relative probability of living 10 years beyond their diagnosis date if they have already survived 5 years. In comparison, the 10-year unconditional probability for GBM is less than 3% (not shown in Table).

RSPs also vary by race and sex. Black women (44%) have the highest 5-year RSPs for cancers of the brain and other nervous system tumours, when compared with white women (36.5%), black men (34.8%), and white men (32.6%) (Altekruse et al 2010). When examined by year of diagnosis from 1975 to 2002, whites (Figure 4) consistently have lower 5-year RSPs than

**5-Year Relative Survival (blacks) by Year of Diagnosis** 

Fig. 5. Survival percent (blacks) for cancers of the brain and other nervous system tumours

Among adults, other factors associated with poorer survival include tumour site (frontal, cerebellum, multilobular), and socioeconomic status (less affluent individuals have lower survival rates) (Tseng et al 2006). The latter suggests that socioeconomic inequalities play an important role in glioma outcome, perhaps due to chronic comorbidities, inadequate access and utilization of health care, and longer wait times after surgery for adjuvant therapies

While population-based relative survival statistics paint a dismal prognostic picture for certain glioma types, conditional survival rates suggest a more favorable long term outcome for patients who have already survived for a specified amount of time after diagnosis (Table 1) (Porter et al 2011). For Example, a GBM patient has a 70.4% (95%CI=55.6-81.2) relative probability of living 10 years beyond their diagnosis date if they have already survived 5 years. In comparison, the 10-year unconditional probability for GBM is less than 3% (not

blacks independent of sex (Figure 5) (NCI-SEER 2011).

(NCI-SEER 2011).

(Tseng et al 2006).

shown in Table).


Table 1. Relative probability of a patient living 10 years beyond their diagnosis date if they have already survived 2 and 5 years.

#### **3. Risk factors**

The key epidemiologic determinants of glioma risk include advancing age, male sex, and Caucasian race (Bondy and Wrensch 1996). Few environmental or lifestyle exposures, except for ionising radiation, have been found to be consistently associated with glioma risk. Suspected risk factors include lifestyle behaviors (e.g., smoking, alcohol consumption, coffee drinking), infectious agents (e.g., polyomaviruses, cytomegaloviruses, influenza, varicella zoster, *Toxoplasma gondii*), diet/vitamins (e.g., nitrosamine compounds, vitamin C, vitamin D3), beauty products (e.g., hair dyes and lighteners, hair waving and straightening chemicals), industrial exposures (e.g., rubber manufacturing, petroleum products), mobile phones, electromagnetic fields, allergies/immunity, agricultural/farm animal exposures, handedness, birth weight/height, and various genetic polymorphisms. While the list is long, methodologic biases are believed to account for the bulk of observed associations. A comprehensive review of factors hypothesized to play a role in the etiology of brain tumors is beyond the intent of the current work and the reader is referred to several recent reviews on the topic (Ostrom and Barnholtz-Sloan 2011; Ohgaki 2009; Fisher et al 2007; Schwartzbaum et al 2006; Ohgaki and Kleihues 2005; Wrensch et al 2002). Rather, the aim of this section is to address the etiology of gliomas in the context of recent publications and current scientific debate on the topic.

#### **3.1 Mobile phones**

Mobile (cellular) phones initially appeared on the market in the late 1970's in Japan and soon thereafter were sold in Europe and the U.S. (Bellis 2011). The first commercial wireless call originating in the U.S. occurred on 13 October 1983 (Green 2008).

However, the widespread and frequent use of mobile phones on an affordable scale was not achieved until the earlier 2000's when unlimited usage service contracts became a viable

Epidemiology of Glioma 11

dose response pattern (i.e., consistently increasing risk estimates with dose) is a feature of many but not all known carcinogens and conveys greater weight for a causative association. An upward trend across deciles of cumulative call time was not observed in the above

However, in a second recently-conducted study of n=1251 maligant brain tumours (n=1148 gliomas) and n=1267 referents (aged 20-80 years at diagnosis), adjusted estimated risk (age, sex, socioeconomic index, and year of diagnosis) increased with cumulative hours (h) of mobile phone use (none, OR=1.0; 1-100 h, OR=1.2, 95%CI=0.98-1.4; 1001-2000 h, OR=1.5, 95%CI=11.1-2.1; >2000 h, OR=2.5, 95%CI=1.8-3.5) (Hardell et al 2011). Similarly, estimated risk (in the category with >74 hours cumulative use) increased with latency time [years (y) since first use of a cell phone until diagnosis] (none, OR=1.0; >1-5 y, OR=1.0, 95%CI=0.7-1.4; >5-10 y, OR=1.2, 95%CI=0.9-1.6; >10 y, OR=2.7, 95%CI=2.0-3.8), although the linear effect was less pronounce than for cumulative hours of exposure. A key advantage of this study was the use of a mailed questionnaire, which allowed participants to verify responses by checking telephone bills (Kundi 2010). Recall bias could have increased risk estimates in positive studies if more cases than referents believed mobile phone use to be the cause of

Studies of mobile phone use have been difficult to compare and interpret due to methodologic differences and the paucity of rigorous design. Background levels of electromagnetic radiation (e.g., power lines, fluorescent lights, computer monitors, televisions, and mobile phone base stations) may have confounded studies that did not account for such effects. A recent case-referent study conducted in Japan found a doseresponse pattern for increasing exposure to power-frequency magnetic fields (MF) measured in a child's bedroom and brain tumours (<0.1µT, OR=1.0; 0.1 to <0.2 µT, OR=0.74, 95%CI=0.17-3.18; 0.2 to <0.4 µT, OR=1.58, 95%CI=0.25-9.83; ≥0.4 µT, OR=10.9, 95%CI=1.05- 113). The OR reported for bedroom MF levels above 0.3 µT, as opposed to above 0.4 µT, was 16 (95%CI=1.85-153). Mobile phones emit both radiofrequency and extremely-low frequency electromagnetic fields (Sage et al 2007). The level of near-field electromagnetic radiation typically emitted on a continuous basis by smart mobile phones ranges from 0.5-0.1 µT (spikes up to 93.5 µT have been recorded during send/receive mode operations), which is above the highest exposure category reported in the Japanese study (Sage et al 2007; Stevenson 2011). Measurements could have been influenced by near-field interference (Silva 2007; Jaffa and Herz 2007), however readings were generally consistent with other independent sources (Sage and Johansson 2007). A large pooled analysis of low-frequency MFs and childhood brain tumors did not observe a dose-response relationship (Kheifets et al 2010). However, inconsistent/imprecise exposure measurements and low participation rates (40%-80%) across studies may have biased results. Furthermore, the actual exposure levels in brain tissue may not necessarily reflect the levels radiated by the mobile phone due to anatomic details and variations in tissue conductivity/permittivity (Kouveliotis et al 2006;

In March 2010, the Mobile Telecommunications and Health Research Programme (MTHR) initiated funding of a prospective cohort study that will follow approximately 250,000 mobile phone users across 5 European countries for up to 30 years (MTHR 2011; Stewart 2000). While MTHR concludes that short term (less than 10 years) exposure to mobile phone signals does not appear to be associated with an increase in brain and nervous system tumours, they emphasize that there remains "significant uncertainties that can only be resolved by monitoring the health of a large cohort of phone users over a long period of

their brain tumour (Sage and Carpenter 2009; Hepworth et al 2006).

study.

Kuster and Balzano 1992).

option to "pay by the minute" billing plans. By the end of 2010 there were approximately 303 million mobile phone subscribers in the U.S., representing 9 times the number in 1995 (CTIA 2011). The World Health Organization estimates 4.6 billion subscribers globally in 2010 (WHO 2011).

The main challenge of epidemiologic studies on mobile phone risk has been the lack of long term, frequent use exposure data (NRPB 2003), especially among users who may be genetically predisposed to brain tumours (Wrensch et al 2009; Shete et al 2009 ). Population stratification and gene-environment interactions may mask the risk of mobile phone use in insufficiently powered studies. Compounding the situation, the average latency period for many cancers is measured in decades, sometimes as long as 50-60 years, and similarly long intervals may apply to brain tumours (Challis 2007). The flat or declining brain tumour incidence trends observed in the population during the same time period of increasing mobile phone use would seem incongruent if mobile phones are a significant cause of brain tumours (Inskip et al 2010). However, competing risks could explain the effect if brain tumours are caused by more than one factor.

The majority of epidemiologic studies to date generally do not support a causative association between mobile phone use and brain tumours (Ahlbom et al 2009). However, methodologic concerns point to a cumulative underestimation of risk (Kundi 2010). Downward bias may have affected studies that excluded deceased and terminally ill patients, if mobile phone use presumably increases the case fatality rate vis-à-vis enhanced tumor progression. Pre-diagnostic effects of brain tumours may have reduced cell phone use and differentially resulted in lower risk estimates, since referents would not have been affected (NRPB 2003). The use of interviews rather than mailed questionnaire data collection (where it is possible to verify mobile phone use by checking billing records) may have decreased risk estimates due to non-differential exposure misclassification from relying on proxy information. Furthermore, participants tend to underestimate the prevalence of mobile phone use by up to 15% compared with non-participants, leading to a differential reduction in risk estimates for mobile phone use, since participation rates among cases typically are higher than referents by 10-15% (Vrijheid et al 2009; The INTERPHONE Study Group 2010). Risk estimates below unity for brain tumours have been reported in several analyses of mobile phone use (The INTERPHONE Study Group 2010; Inskip et al 2001; Johansen et al 2001; Muscat et al 2000; Hepworth et al 2006). A biologic basis for the results, particularly reports of deceased risk for contralateral use, is ambiguous. In many cases, the inverse associations likely are explained by the aforementioned factors that bias risk estimates in the downward direction. On the other hand, studies in which the participants' status was blinded at interview tended to yield positive risk estimates compared with those who were not blinded (Myung et al 2008).

Two large recent studies have reported increased risks for mobile phone use, especially among heavy users. A multicentric study (13 countries) with 2708 glioma cases and matched referents (age within 5 years, sex, and region of residence within each study centre) observed a 1.40 odds ratio (OR) [95% confidence interval (CI)=1.03-1.89] for glioma among those in the highest mobile phone exposure category (cumulative call time≥1640 hours) compared with the lowest category (never a regular user) (The INTERPHONE Study Group 2010). A subset analysis of the concordance between tumour and preferred side of phone use similarly showed an increased estimated risk among those in the highest decile of cumulative call time (OR=1.55, 95%CI=1.24-1.99). Risk estimates were not reduced for the contralateral side, suggesting against potential reporting bias (Kundi et al 2009). A linear

option to "pay by the minute" billing plans. By the end of 2010 there were approximately 303 million mobile phone subscribers in the U.S., representing 9 times the number in 1995 (CTIA 2011). The World Health Organization estimates 4.6 billion subscribers globally in

The main challenge of epidemiologic studies on mobile phone risk has been the lack of long term, frequent use exposure data (NRPB 2003), especially among users who may be genetically predisposed to brain tumours (Wrensch et al 2009; Shete et al 2009 ). Population stratification and gene-environment interactions may mask the risk of mobile phone use in insufficiently powered studies. Compounding the situation, the average latency period for many cancers is measured in decades, sometimes as long as 50-60 years, and similarly long intervals may apply to brain tumours (Challis 2007). The flat or declining brain tumour incidence trends observed in the population during the same time period of increasing mobile phone use would seem incongruent if mobile phones are a significant cause of brain tumours (Inskip et al 2010). However, competing risks could explain the effect if brain

The majority of epidemiologic studies to date generally do not support a causative association between mobile phone use and brain tumours (Ahlbom et al 2009). However, methodologic concerns point to a cumulative underestimation of risk (Kundi 2010). Downward bias may have affected studies that excluded deceased and terminally ill patients, if mobile phone use presumably increases the case fatality rate vis-à-vis enhanced tumor progression. Pre-diagnostic effects of brain tumours may have reduced cell phone use and differentially resulted in lower risk estimates, since referents would not have been affected (NRPB 2003). The use of interviews rather than mailed questionnaire data collection (where it is possible to verify mobile phone use by checking billing records) may have decreased risk estimates due to non-differential exposure misclassification from relying on proxy information. Furthermore, participants tend to underestimate the prevalence of mobile phone use by up to 15% compared with non-participants, leading to a differential reduction in risk estimates for mobile phone use, since participation rates among cases typically are higher than referents by 10-15% (Vrijheid et al 2009; The INTERPHONE Study Group 2010). Risk estimates below unity for brain tumours have been reported in several analyses of mobile phone use (The INTERPHONE Study Group 2010; Inskip et al 2001; Johansen et al 2001; Muscat et al 2000; Hepworth et al 2006). A biologic basis for the results, particularly reports of deceased risk for contralateral use, is ambiguous. In many cases, the inverse associations likely are explained by the aforementioned factors that bias risk estimates in the downward direction. On the other hand, studies in which the participants' status was blinded at interview tended to yield positive risk estimates compared with those

Two large recent studies have reported increased risks for mobile phone use, especially among heavy users. A multicentric study (13 countries) with 2708 glioma cases and matched referents (age within 5 years, sex, and region of residence within each study centre) observed a 1.40 odds ratio (OR) [95% confidence interval (CI)=1.03-1.89] for glioma among those in the highest mobile phone exposure category (cumulative call time≥1640 hours) compared with the lowest category (never a regular user) (The INTERPHONE Study Group 2010). A subset analysis of the concordance between tumour and preferred side of phone use similarly showed an increased estimated risk among those in the highest decile of cumulative call time (OR=1.55, 95%CI=1.24-1.99). Risk estimates were not reduced for the contralateral side, suggesting against potential reporting bias (Kundi et al 2009). A linear

2010 (WHO 2011).

tumours are caused by more than one factor.

who were not blinded (Myung et al 2008).

dose response pattern (i.e., consistently increasing risk estimates with dose) is a feature of many but not all known carcinogens and conveys greater weight for a causative association. An upward trend across deciles of cumulative call time was not observed in the above study.

However, in a second recently-conducted study of n=1251 maligant brain tumours (n=1148 gliomas) and n=1267 referents (aged 20-80 years at diagnosis), adjusted estimated risk (age, sex, socioeconomic index, and year of diagnosis) increased with cumulative hours (h) of mobile phone use (none, OR=1.0; 1-100 h, OR=1.2, 95%CI=0.98-1.4; 1001-2000 h, OR=1.5, 95%CI=11.1-2.1; >2000 h, OR=2.5, 95%CI=1.8-3.5) (Hardell et al 2011). Similarly, estimated risk (in the category with >74 hours cumulative use) increased with latency time [years (y) since first use of a cell phone until diagnosis] (none, OR=1.0; >1-5 y, OR=1.0, 95%CI=0.7-1.4; >5-10 y, OR=1.2, 95%CI=0.9-1.6; >10 y, OR=2.7, 95%CI=2.0-3.8), although the linear effect was less pronounce than for cumulative hours of exposure. A key advantage of this study was the use of a mailed questionnaire, which allowed participants to verify responses by checking telephone bills (Kundi 2010). Recall bias could have increased risk estimates in positive studies if more cases than referents believed mobile phone use to be the cause of their brain tumour (Sage and Carpenter 2009; Hepworth et al 2006).

Studies of mobile phone use have been difficult to compare and interpret due to methodologic differences and the paucity of rigorous design. Background levels of electromagnetic radiation (e.g., power lines, fluorescent lights, computer monitors, televisions, and mobile phone base stations) may have confounded studies that did not account for such effects. A recent case-referent study conducted in Japan found a doseresponse pattern for increasing exposure to power-frequency magnetic fields (MF) measured in a child's bedroom and brain tumours (<0.1µT, OR=1.0; 0.1 to <0.2 µT, OR=0.74, 95%CI=0.17-3.18; 0.2 to <0.4 µT, OR=1.58, 95%CI=0.25-9.83; ≥0.4 µT, OR=10.9, 95%CI=1.05- 113). The OR reported for bedroom MF levels above 0.3 µT, as opposed to above 0.4 µT, was 16 (95%CI=1.85-153). Mobile phones emit both radiofrequency and extremely-low frequency electromagnetic fields (Sage et al 2007). The level of near-field electromagnetic radiation typically emitted on a continuous basis by smart mobile phones ranges from 0.5-0.1 µT (spikes up to 93.5 µT have been recorded during send/receive mode operations), which is above the highest exposure category reported in the Japanese study (Sage et al 2007; Stevenson 2011). Measurements could have been influenced by near-field interference (Silva 2007; Jaffa and Herz 2007), however readings were generally consistent with other independent sources (Sage and Johansson 2007). A large pooled analysis of low-frequency MFs and childhood brain tumors did not observe a dose-response relationship (Kheifets et al 2010). However, inconsistent/imprecise exposure measurements and low participation rates (40%-80%) across studies may have biased results. Furthermore, the actual exposure levels in brain tissue may not necessarily reflect the levels radiated by the mobile phone due to anatomic details and variations in tissue conductivity/permittivity (Kouveliotis et al 2006; Kuster and Balzano 1992).

In March 2010, the Mobile Telecommunications and Health Research Programme (MTHR) initiated funding of a prospective cohort study that will follow approximately 250,000 mobile phone users across 5 European countries for up to 30 years (MTHR 2011; Stewart 2000). While MTHR concludes that short term (less than 10 years) exposure to mobile phone signals does not appear to be associated with an increase in brain and nervous system tumours, they emphasize that there remains "significant uncertainties that can only be resolved by monitoring the health of a large cohort of phone users over a long period of

Epidemiology of Glioma 13

2005; Turner et al 2005; Siegmund et al 2008; Eriksson et al 2005; Cicuttini et al 1997) epidemiologic studies of atopic diseases (e.g., asthma, allergies) have been negatively associated with glioma risk. The protective association has been suggested to reflect increased immune surveillance, although the exact biologic mechanism is unknown (Linos et al 2007; Carrozzi and Viegi 2005). Alterations of the immunological system can enhance the inflammatory response and promote tumor development (Carrozzi and Viegi 2005). The reduced association with allergies also may be due to reverse causality (i.e., immunosuppression induced by the tumor) (Wigertz et al 2007). Glioma patients are known to have an impaired immune system (Dix et al 1999). Interestingly, therapeutic immunity to intracranial tumors has been induced in the laboratory by peripheral immunization with

interleukin-4 (IL-4) transduced glioma cells [Okada et al 2001; Benedetti et al 1998].

antibodies (Klintberg et al 2001; Bråbäck 2002).

al 2004), but the period of greatest risk has varied between studies.

Farmers have been found to have an increased risk for brain cancer in some studies (Kristensen et al 1996; Reif et al 1989; Wingren et al 1992; Ahlbom et al 1986**;** Musicco et al 1982**;** Musicco et al 1988**;** Brownson et al 1990**;** Heineman et al 1995), although they generally are healthier than the population-at-large (Kristensen et al 1996; Bråbäck 2002; Population and Public Health Branch (PPHB) 1995; Blair et al 2005; Ronco et al 1992), live longer (Alavanja 1996), and die less frequently from cancer overall (Blair et al 1993). Being raised on a farm (Alfven et al 2006**;** Ege et al 2007**;** Riedler et al 2001; Braun-Fahrländer et al 1999; Riedler et al 2000**;** von Ehrenstein et al 2000; Kilpelainen et al 2000**;** Klintberg et al 2001**;** Ernst and Cormier 2000; Remes et al 2003**;** Leynaert et al 2001**;** Gassner-Bachmann and Wüthrich 2000**;** Vercelli 2008**)** or in a rural area (Godfrey 1975) has been shown to protect against asthma, hay fever, and atopic sensitization. Farm children are exposed to higher concentrations of airborne allergens, but paradoxically become sensitized less frequently and manifest a weaker sensitization response than non-farm controls (Gassner-Bachmann and Wüthrich 2000). The protective effect may be due to a form of "tolerance" that conceivably develops early in life, following repeated exposure to high levels of allergens (e.g., organic dusts, fungi, and endotoxins). Component lipopolysaccharides have been shown to excite Th1 responses and suppress the development of immunoglobulin-E (IgE)-

Specific determinants of asthma and atopy in the farm setting remain largely unknown. Any relationship with glioma risk likely is complex and must be interpreted in light of substantial heterogeneity in the protective ability of farming environments and differences in farming practices, especially with respect to microbial exposures (Alfven et al 2006; Ege et al 2007; Vercelli 2008). By self-selection, those who manifest allergies may choose a career path other than farming (i.e., healthy worker effect) (Bråbäck 2002). Farmers represent a diverse group (e.g., dairy, field crop, hog, beef cattle, poultry, fish, marijuana, cotton, and organic), and brain cancer risk, or lack thereof, for farmers could reflect differences in activities and the type, magnitude, and seasonality of exposures. In one report, marijuana smoking was associated with glioma risk, but the study did not specifically examine marijuana farming (Efird et al 2004). Farmers and their families have greater contact with seasonal elements. Season of birth has been associated with adult (Brenner et al 2004; Koch et al 2006; Mainio et al 2006; Efird 2009) and childhood brain tumours (Makino et al 2011; McNally et al 2002; Heuch et al 1998; Yamakawa et al 1979; Hoffman et al 2007; Halperin et

Differences in the definition and the lack of objective measures of atopy should be considered when interpreting the above studies (Wang and Diepgen 2005; Schoemaker et al 2006). Furthermore, there is no definitive trend toward a decreasing risk for glioma with

time (MTHR 2011)." Furthermore, the reactions of children to mobile phone emissions may be different and/or stronger than those of adults (as is the case for other environmental exposures such as lead, tobacco smoke, ultraviolet radiation, and ionising radiation) and very little research has been conducted so far to determine whether this is the case (MTHR 2011). No studies on mobile phone use and risk of brain tumours have been planned for the U.S. that are comparable in size and detail to the COSMOS.

The thermal radiation emitted during average mobile phone use is low and generally is not believed to cause direct DNA damage or any other significant deleterious biologic effects on the brain (Wainwright 2000; Johansen et al 2001; Sage and Carpenter 2009; NRPB 2003). However, questions remain regarding the non-thermal effects of non-ionising radiation from mobile phones. Using positron emission tomography (PET), a National Institutes of Health study of 47 participants demonstrated a 7% increase in brain glucose uptake (a measure of metabolic activity) in response to mobile phone signals, supposedly independent of any thermal effects (Volkow et al 2011). The increases in regional glucose metabolism induced by the mobile phone signals were similar in magnitude to those reported after suprathrehold transcranial magnetic stimulation of the sensorimotor cortex. The authors hypothesize that the non-thermal effects on neuronal activity may be mediated by changes in cell membrane permeability, calcium efflux, cell excitability, and/or neurotransmitter release. A significant change in cell proliferation in response to radiofrequency MFs, independent of thermal activity, has been reported in a cell culture experiment involving transformed human epithelial amnion cells (Velizarov et al 1999). Effects demonstrated in other studies include up-regulation of apoptosis genes, induction of reactive oxygen species, changes in protein conformation, the creation of stress proteins, and immune system disturbances (Zhao et al 2007; Sage and Carpenter 2009; NRPB 2003; Valentini et al 2007; Ruediger 2009). Caution is advised when interpreting these effects since numerous contradictory results are present in the literature.

The likelihood that mobile phone use has no impact on the brain is small. Yet, the exact biophysical/biologic mechanism(s), if any, underlying mobile phone effects on neuronal cells, especially in the context of cancer, remains to be confirmed. Additional research is needed to determine if mobile phone use specifically increases brain tumor risk, either independently or in combination with other potential risk factors. Until then, limiting exposure to potentially vulnerable populations (e.g., fetus, children) would seem to be prudent precautionary public health policy, especially given the unknown latency for the development of brain cancer (Kundi et al 2009; Sage and Carpenter 2009). Radiofrequency MF absorption rates are estimated to be two times higher in children than adults, due to the lower thickness of pinna, skin and skull of younger children (Wiart et al 2008). Accordingly, risk may be greater among individuals who use a mobile phone at younger ages, yet few studies have addressed this potential risk group as they age into adulthood. Based on an increased risk for glioma, the WHO/International Agency for Research on Cancer (IARC) has formally classified radiofrequency electromagnetic fields, such as those emitted by wireless communication devices, as "possibly carcinogic to humans (Group 2B) (WHO/IARC 2011)."

#### **3.2 Atopic diseases and farm exposures**

**Several** (Berg-Berkhoff et al 2009; Wigertz et al 2007; Schwartzbaum et al 2003; Hochberg et al 1990; Schlehofer et al 1992; Schlehofer et al 1999; Ryan et al 1992; Brenner et al 2002; Linos et al 2007; Wang and Diepgen 2005; Carrozzi and Viegi 2005) **but not all** (Hagströmer et al

time (MTHR 2011)." Furthermore, the reactions of children to mobile phone emissions may be different and/or stronger than those of adults (as is the case for other environmental exposures such as lead, tobacco smoke, ultraviolet radiation, and ionising radiation) and very little research has been conducted so far to determine whether this is the case (MTHR 2011). No studies on mobile phone use and risk of brain tumours have been planned for the

The thermal radiation emitted during average mobile phone use is low and generally is not believed to cause direct DNA damage or any other significant deleterious biologic effects on the brain (Wainwright 2000; Johansen et al 2001; Sage and Carpenter 2009; NRPB 2003). However, questions remain regarding the non-thermal effects of non-ionising radiation from mobile phones. Using positron emission tomography (PET), a National Institutes of Health study of 47 participants demonstrated a 7% increase in brain glucose uptake (a measure of metabolic activity) in response to mobile phone signals, supposedly independent of any thermal effects (Volkow et al 2011). The increases in regional glucose metabolism induced by the mobile phone signals were similar in magnitude to those reported after suprathrehold transcranial magnetic stimulation of the sensorimotor cortex. The authors hypothesize that the non-thermal effects on neuronal activity may be mediated by changes in cell membrane permeability, calcium efflux, cell excitability, and/or neurotransmitter release. A significant change in cell proliferation in response to radiofrequency MFs, independent of thermal activity, has been reported in a cell culture experiment involving transformed human epithelial amnion cells (Velizarov et al 1999). Effects demonstrated in other studies include up-regulation of apoptosis genes, induction of reactive oxygen species, changes in protein conformation, the creation of stress proteins, and immune system disturbances (Zhao et al 2007; Sage and Carpenter 2009; NRPB 2003; Valentini et al 2007; Ruediger 2009). Caution is advised when interpreting these effects since numerous

The likelihood that mobile phone use has no impact on the brain is small. Yet, the exact biophysical/biologic mechanism(s), if any, underlying mobile phone effects on neuronal cells, especially in the context of cancer, remains to be confirmed. Additional research is needed to determine if mobile phone use specifically increases brain tumor risk, either independently or in combination with other potential risk factors. Until then, limiting exposure to potentially vulnerable populations (e.g., fetus, children) would seem to be prudent precautionary public health policy, especially given the unknown latency for the development of brain cancer (Kundi et al 2009; Sage and Carpenter 2009). Radiofrequency MF absorption rates are estimated to be two times higher in children than adults, due to the lower thickness of pinna, skin and skull of younger children (Wiart et al 2008). Accordingly, risk may be greater among individuals who use a mobile phone at younger ages, yet few studies have addressed this potential risk group as they age into adulthood. Based on an increased risk for glioma, the WHO/International Agency for Research on Cancer (IARC) has formally classified radiofrequency electromagnetic fields, such as those emitted by wireless communication devices, as "possibly carcinogic to humans (Group 2B)

**Several** (Berg-Berkhoff et al 2009; Wigertz et al 2007; Schwartzbaum et al 2003; Hochberg et al 1990; Schlehofer et al 1992; Schlehofer et al 1999; Ryan et al 1992; Brenner et al 2002; Linos et al 2007; Wang and Diepgen 2005; Carrozzi and Viegi 2005) **but not all** (Hagströmer et al

U.S. that are comparable in size and detail to the COSMOS.

contradictory results are present in the literature.

(WHO/IARC 2011)."

**3.2 Atopic diseases and farm exposures** 

2005; Turner et al 2005; Siegmund et al 2008; Eriksson et al 2005; Cicuttini et al 1997) epidemiologic studies of atopic diseases (e.g., asthma, allergies) have been negatively associated with glioma risk. The protective association has been suggested to reflect increased immune surveillance, although the exact biologic mechanism is unknown (Linos et al 2007; Carrozzi and Viegi 2005). Alterations of the immunological system can enhance the inflammatory response and promote tumor development (Carrozzi and Viegi 2005). The reduced association with allergies also may be due to reverse causality (i.e., immunosuppression induced by the tumor) (Wigertz et al 2007). Glioma patients are known to have an impaired immune system (Dix et al 1999). Interestingly, therapeutic immunity to intracranial tumors has been induced in the laboratory by peripheral immunization with interleukin-4 (IL-4) transduced glioma cells [Okada et al 2001; Benedetti et al 1998].

Farmers have been found to have an increased risk for brain cancer in some studies (Kristensen et al 1996; Reif et al 1989; Wingren et al 1992; Ahlbom et al 1986**;** Musicco et al 1982**;** Musicco et al 1988**;** Brownson et al 1990**;** Heineman et al 1995), although they generally are healthier than the population-at-large (Kristensen et al 1996; Bråbäck 2002; Population and Public Health Branch (PPHB) 1995; Blair et al 2005; Ronco et al 1992), live longer (Alavanja 1996), and die less frequently from cancer overall (Blair et al 1993). Being raised on a farm (Alfven et al 2006**;** Ege et al 2007**;** Riedler et al 2001; Braun-Fahrländer et al 1999; Riedler et al 2000**;** von Ehrenstein et al 2000; Kilpelainen et al 2000**;** Klintberg et al 2001**;** Ernst and Cormier 2000; Remes et al 2003**;** Leynaert et al 2001**;** Gassner-Bachmann and Wüthrich 2000**;** Vercelli 2008**)** or in a rural area (Godfrey 1975) has been shown to protect against asthma, hay fever, and atopic sensitization. Farm children are exposed to higher concentrations of airborne allergens, but paradoxically become sensitized less frequently and manifest a weaker sensitization response than non-farm controls (Gassner-Bachmann and Wüthrich 2000). The protective effect may be due to a form of "tolerance" that conceivably develops early in life, following repeated exposure to high levels of allergens (e.g., organic dusts, fungi, and endotoxins). Component lipopolysaccharides have been shown to excite Th1 responses and suppress the development of immunoglobulin-E (IgE) antibodies (Klintberg et al 2001; Bråbäck 2002).

Specific determinants of asthma and atopy in the farm setting remain largely unknown. Any relationship with glioma risk likely is complex and must be interpreted in light of substantial heterogeneity in the protective ability of farming environments and differences in farming practices, especially with respect to microbial exposures (Alfven et al 2006; Ege et al 2007; Vercelli 2008). By self-selection, those who manifest allergies may choose a career path other than farming (i.e., healthy worker effect) (Bråbäck 2002). Farmers represent a diverse group (e.g., dairy, field crop, hog, beef cattle, poultry, fish, marijuana, cotton, and organic), and brain cancer risk, or lack thereof, for farmers could reflect differences in activities and the type, magnitude, and seasonality of exposures. In one report, marijuana smoking was associated with glioma risk, but the study did not specifically examine marijuana farming (Efird et al 2004). Farmers and their families have greater contact with seasonal elements. Season of birth has been associated with adult (Brenner et al 2004; Koch et al 2006; Mainio et al 2006; Efird 2009) and childhood brain tumours (Makino et al 2011; McNally et al 2002; Heuch et al 1998; Yamakawa et al 1979; Hoffman et al 2007; Halperin et al 2004), but the period of greatest risk has varied between studies.

Differences in the definition and the lack of objective measures of atopy should be considered when interpreting the above studies (Wang and Diepgen 2005; Schoemaker et al 2006). Furthermore, there is no definitive trend toward a decreasing risk for glioma with

Epidemiology of Glioma 15

(Wrensch et al 2005; Wrensch et al 2001). On the other hand, increased risk for childhood brain tumors has been associated with a history of chicken pox (Bithell et al 1973), influenza (Dickinson et al 2002; Linos et al 1998), measles (Dickinson et al 2002), general viral infections (Fear et al 2001; Linet et al 1996), and neonatal urinary tract infections (Linet et al 1996). A 7.5-fold OR (95% CI=1.3-44.9) for low grade astrocytoma has been observed for

A recent cohort study of 20,132 workers in poultry slaughtering and processing plants, a group with high potential exposures to avian leukosis/sarcoma, reticuloendothesliosis, and Marek's disease viruses, were observed to have a significant excess of brain cancer, compared with the U.S. population (standardized mortality ratio=1.7, 95% CI=1.1-2.4). Although the aforementioned poultry viruses are well established carcinogens in their

An infectious etiology for brain tumors is complicated by many factors (Naumova 2006). The same infectious agent may present a different pattern of incidence depending on the host location. A peak evident in the general population may not behave uniformly within certain subpopulations. Temperature, humidity, precipitation, and indoor air quality are among the mitigating factors that may affect the survival and transmissibility of a pathogen. Other factors include poor nutrition, population density, travel, hygiene practices, cultural practices in food consumption/preparation, changes in herd immunity, or evolution of the infectious agent over time. Furthermore, seasonal variation in immune function may increase host susceptibility to infections at certain times of the year (Melnikov et al 1987;

The vast majority of glioma cases are idiopathic in origin. Demographic differences in incidence by race, sex, and country suggests that genetics, hormones, and environmental risk factors may play a role in some gliomas. However, study bias (e.g., participation, information, survival), variations in health care access/utilization, residual confounding, and other yet-to-be realized influences may explain the differences in glioma incidence. Complicating matters, the etiology of glioma may be multifactor in nature. That is, several factors operating in unison may cumulatively increase/decrease risk or mask the effect of individual factors when examined in isolation. Additionally, gene-environment and genegene interactions may modify underlying risk. Future epidemiologic studies will benefit by improved measures of environmental exposures, more precise statistical methods for detecting interaction effects, and larger multicentre collaborations aimed at better

Katherine T. Jones (ECU) and Avima Ruder (CDC/NIOSH/DSHEFS) offered valuable comments during the writing of this manuscript. The author also thanks Tamara Sachs for

Ahlbom A, Feychting M, Green A, Kheifets L, Savitz D, Swerdlow A, and ICNIRP

(International Commission for Non-Ionizing Radiation Protection) Standing

natural species, it is not known if they cause cancer in humans (Johnson et al 2000).

neonatal urinary tract infections (Linet et al 1996).

understanding the impact of population stratification.

Carandente et al 1988).

**5. Acknowledgements** 

research assistance.

**6. References** 

**4. Discussion** 

younger ages at onset of the allergic condition, arguing against an immunologic cause for glioma (Schoemaker et al 2006). Paradoxically, increased risk for glioma has been observed in patients with AIDS-related immuno-suppression (Goedert et al 1998; Frisch et al 2001; Grulich et al 1999), but not in those with iatrogenic immuno-suppression (Schiff 2004). Many farm chemicals are classified as probable or likely human carcinogens by the US Environmental Protection Agency (EPA) (e.g., acephate, dichlorvos, dimethoate, lindane, parathion, phosmet, and tetrachlorvinphos) and these agents acting alone or in parallel with decreased atopic sensitization conceivably may increase glioma risk (US Environmental Protection Agency 2003).

#### **3.3 Infectious agents**

Polyomaviruses have been detected in the cancerous brain tissue of some patients diagnosed with gliomas (Rollison et al 2003). Polyomaviruses manifest a strong tropism for glial cells in vivo, possibly due to the interaction of glial transcription factors such as Tst-1/Ict6/SCIP with viral promoter sequences (Vasilyera et al 2004). The inoculation of immunologic immature neonate mice with human polyomavirus has been shown to readily cause tumor formation at multiple sites including the brain; older mice do not develop tumors in response to polyoma virus either in the laboratory or by natural infection (Nagashima et al 1984; Zu Rhein and Varakis 1979; London et al 1978; London et al 1983, Sanders 1977; Nagashima et al 1984; Zu Rhein and Varakis, 1979). Similarly, owl and squirrel monkeys injected (intracerebral, subcutaneous, or intravenous) with human JC polyomavirus have developed astrocytomas and glioblastomas (London et al 1978; London et al 1983). Recently, two new members of the *Polyomaviridae family*,*Karolinska Institutet* Virus (KIPyV) and *Washington Univerisity* virus (WUPyV), have been detected in samples from children with lower respiratory tract disease (Foulongne et al 2008).

Paradoxically, animals are not a permissive host for human JC virus replication, even though integrated JC viral DNA has been identified in the tumors of animals induced with the virus (White et al. 2005; Miller et al, 1984). Though monkeys themselves are not affected, simian virus (SV)-40 (extracted from monkey kidneys) gives cancer to hamsters (Rosenfeld 1962). Human adenovirus type 12 and Rous sarcoma virus are examples of other neurooncogenic viruses capable of causing gliomas under laboratory conditions (Zimmerman 1975). Yet, adenovirus in the worst case only causes respiratory disease in humans (Rosenfeld 1962). Some tumor viruses must be injected in animals on the first day of life to be effective, although they may not cause cancer until years later (Bailar and Gurian 1964).

Analogous to human and simian polyomaviruses causing brain tumours in non-permissive rodents, animal polyomaviruses conceivably may cause brain tumours in humans, yet little is understood about the latter topic. Polyomavirus are ubiquous among animals (e.g., cattle, birds, rodents,) (Ashok and Atwood 2006). For example, mouse polyomaviruses (*Mus musculus*) are capable of inducing a wide array of mesenchymal and epithelial cell type cancers in mice (Dawe et al 1987). Exposure to farm animals has been associated in some studies with childhood brain tumours (Efird et al 2003; Bunin et al 1994) but not adult brain tumors (Ménégoz et al 2002).

Epidemiologic evidence in support of a viral/pathogenic etiology for brain tumors remains controversial. In adults, *Toxoplasma gondii* infection has been associated with an increased prevalence of astrocytomas (Schuman et al 1967), while decreased glioma risk has been associated with a history of infections/colds (Schlehofer et al 1999), and chicken pox

younger ages at onset of the allergic condition, arguing against an immunologic cause for glioma (Schoemaker et al 2006). Paradoxically, increased risk for glioma has been observed in patients with AIDS-related immuno-suppression (Goedert et al 1998; Frisch et al 2001; Grulich et al 1999), but not in those with iatrogenic immuno-suppression (Schiff 2004). Many farm chemicals are classified as probable or likely human carcinogens by the US Environmental Protection Agency (EPA) (e.g., acephate, dichlorvos, dimethoate, lindane, parathion, phosmet, and tetrachlorvinphos) and these agents acting alone or in parallel with decreased atopic sensitization conceivably may increase glioma risk (US Environmental

Polyomaviruses have been detected in the cancerous brain tissue of some patients diagnosed with gliomas (Rollison et al 2003). Polyomaviruses manifest a strong tropism for glial cells in vivo, possibly due to the interaction of glial transcription factors such as Tst-1/Ict6/SCIP with viral promoter sequences (Vasilyera et al 2004). The inoculation of immunologic immature neonate mice with human polyomavirus has been shown to readily cause tumor formation at multiple sites including the brain; older mice do not develop tumors in response to polyoma virus either in the laboratory or by natural infection (Nagashima et al 1984; Zu Rhein and Varakis 1979; London et al 1978; London et al 1983, Sanders 1977; Nagashima et al 1984; Zu Rhein and Varakis, 1979). Similarly, owl and squirrel monkeys injected (intracerebral, subcutaneous, or intravenous) with human JC polyomavirus have developed astrocytomas and glioblastomas (London et al 1978; London et al 1983). Recently, two new members of the *Polyomaviridae family*,*Karolinska Institutet* Virus (KIPyV) and *Washington Univerisity* virus (WUPyV), have been detected in samples from

Paradoxically, animals are not a permissive host for human JC virus replication, even though integrated JC viral DNA has been identified in the tumors of animals induced with the virus (White et al. 2005; Miller et al, 1984). Though monkeys themselves are not affected, simian virus (SV)-40 (extracted from monkey kidneys) gives cancer to hamsters (Rosenfeld 1962). Human adenovirus type 12 and Rous sarcoma virus are examples of other neurooncogenic viruses capable of causing gliomas under laboratory conditions (Zimmerman 1975). Yet, adenovirus in the worst case only causes respiratory disease in humans (Rosenfeld 1962). Some tumor viruses must be injected in animals on the first day of life to be effective, although they may not cause cancer until years later (Bailar and Gurian 1964). Analogous to human and simian polyomaviruses causing brain tumours in non-permissive rodents, animal polyomaviruses conceivably may cause brain tumours in humans, yet little is understood about the latter topic. Polyomavirus are ubiquous among animals (e.g., cattle, birds, rodents,) (Ashok and Atwood 2006). For example, mouse polyomaviruses (*Mus musculus*) are capable of inducing a wide array of mesenchymal and epithelial cell type cancers in mice (Dawe et al 1987). Exposure to farm animals has been associated in some studies with childhood brain tumours (Efird et al 2003; Bunin et al 1994) but not adult brain

Epidemiologic evidence in support of a viral/pathogenic etiology for brain tumors remains controversial. In adults, *Toxoplasma gondii* infection has been associated with an increased prevalence of astrocytomas (Schuman et al 1967), while decreased glioma risk has been associated with a history of infections/colds (Schlehofer et al 1999), and chicken pox

children with lower respiratory tract disease (Foulongne et al 2008).

Protection Agency 2003).

**3.3 Infectious agents** 

tumors (Ménégoz et al 2002).

(Wrensch et al 2005; Wrensch et al 2001). On the other hand, increased risk for childhood brain tumors has been associated with a history of chicken pox (Bithell et al 1973), influenza (Dickinson et al 2002; Linos et al 1998), measles (Dickinson et al 2002), general viral infections (Fear et al 2001; Linet et al 1996), and neonatal urinary tract infections (Linet et al 1996). A 7.5-fold OR (95% CI=1.3-44.9) for low grade astrocytoma has been observed for neonatal urinary tract infections (Linet et al 1996).

A recent cohort study of 20,132 workers in poultry slaughtering and processing plants, a group with high potential exposures to avian leukosis/sarcoma, reticuloendothesliosis, and Marek's disease viruses, were observed to have a significant excess of brain cancer, compared with the U.S. population (standardized mortality ratio=1.7, 95% CI=1.1-2.4). Although the aforementioned poultry viruses are well established carcinogens in their natural species, it is not known if they cause cancer in humans (Johnson et al 2000).

An infectious etiology for brain tumors is complicated by many factors (Naumova 2006). The same infectious agent may present a different pattern of incidence depending on the host location. A peak evident in the general population may not behave uniformly within certain subpopulations. Temperature, humidity, precipitation, and indoor air quality are among the mitigating factors that may affect the survival and transmissibility of a pathogen. Other factors include poor nutrition, population density, travel, hygiene practices, cultural practices in food consumption/preparation, changes in herd immunity, or evolution of the infectious agent over time. Furthermore, seasonal variation in immune function may increase host susceptibility to infections at certain times of the year (Melnikov et al 1987; Carandente et al 1988).

#### **4. Discussion**

The vast majority of glioma cases are idiopathic in origin. Demographic differences in incidence by race, sex, and country suggests that genetics, hormones, and environmental risk factors may play a role in some gliomas. However, study bias (e.g., participation, information, survival), variations in health care access/utilization, residual confounding, and other yet-to-be realized influences may explain the differences in glioma incidence. Complicating matters, the etiology of glioma may be multifactor in nature. That is, several factors operating in unison may cumulatively increase/decrease risk or mask the effect of individual factors when examined in isolation. Additionally, gene-environment and genegene interactions may modify underlying risk. Future epidemiologic studies will benefit by improved measures of environmental exposures, more precise statistical methods for detecting interaction effects, and larger multicentre collaborations aimed at better understanding the impact of population stratification.

#### **5. Acknowledgements**

Katherine T. Jones (ECU) and Avima Ruder (CDC/NIOSH/DSHEFS) offered valuable comments during the writing of this manuscript. The author also thanks Tamara Sachs for research assistance.

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**2** 

*USA* 

**Molecular Etiology of Glioblastomas:** 

*2Department of Neurology, Moores UCSD Cancer Center, UCSD,* 

*3Center for Theoretic and Applied Neuro-Oncology, University of California San Diego, San Diego, CA 4Department of Surgery, Division of Neurosurgery, University of California San Dieog, San Diego, CA* 

**From the Cancer Genome Atlas Project** 

Kimberly Ng.1, Santosh Kesari2, Bob Carter3,4 and Clark C. Chen1,5 *1Department of Radiation Oncology, Dana-Farber Cancer Institute, Boston, MA* 

*5Division of Neurosurgery, Beth Israel Deaconess Medical Center, Boston, MA* 

In the landmark review by Hanahan and Weinberg1, the authors distilled the essence of cancer into six distinct phenotypes, including evasion of apoptosis, self-sufficiency in growth signals, insensitivity to anti-growth signals, tissue invasion and metastasis, limitless replicative potentials, and sustained angiogenesis. The widely accepted paradigm suggests that cancer arises as a result of mutations or epigenetic events, which alter function of genes critical for attaining these phenotypes. These gene functions are intimately linked to the regulation of developmental processes2, their aberrant function in tumor inevitably lead to cell states that resemble stages during normal development. These cell states can be captured using genomic technologies to define distinct molecular subtypes. With the advent of The Genome Cancer Atlas project for glioblastoma3,4, we now have a glimpse of the genetic events underlying glioblastoma pathogenesis as well as distinct molecular subtypes. In this review, the genomic profiles of glioblastoma will be reviewed in the context of the properties described by Hanahan and Weinberg. Molecular subtypes of glioblastoma will be

Glioblastoma is the most common form of primary brain tumor, with dismal prognosis. The incidence of this tumor is fairly low, with 2-3 cases per 100,000 people in Europe and North America. Despite its rarity, overall mortality related to glioblastoma is comparable to the more prevalent tumors5. This is, in large part, due to the near uniform fatality of the afflicted patients. Indeed, glioblastoma is one of the most aggressive of the malignant tumors. Without treatment, the median survival is approximately 3 months6. The current standard of treatment involves maximal surgical resection followed by concurrent radiation therapy and

discussed in the context of developmental biology and the cell of origin.

**1. Introduction** 

**2. Glioblastoma** 

**Implication of Genomic Profiling** 

Woodward A, Yamaguchi N, Cardis E. Quantifying the Impact of Selection Bias Caused by Nonparticipation in a Case–Control Study of Mobile Phone Use. *Ann Epidemiol* 2009;19:33–42.


## **Molecular Etiology of Glioblastomas: Implication of Genomic Profiling From the Cancer Genome Atlas Project**

Kimberly Ng.1, Santosh Kesari2, Bob Carter3,4 and Clark C. Chen1,5 *1Department of Radiation Oncology, Dana-Farber Cancer Institute, Boston, MA 2Department of Neurology, Moores UCSD Cancer Center, UCSD, 3Center for Theoretic and Applied Neuro-Oncology, University of California San Diego, San Diego, CA 4Department of Surgery, Division of Neurosurgery, University of California San Dieog, San Diego, CA 5Division of Neurosurgery, Beth Israel Deaconess Medical Center, Boston, MA USA* 

#### **1. Introduction**

24 Glioma – Exploring Its Biology and Practical Relevance

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Current Concepts in Biology, Diagnosis, and Therapy, Hekmatpanah J (eds). New

In the landmark review by Hanahan and Weinberg1, the authors distilled the essence of cancer into six distinct phenotypes, including evasion of apoptosis, self-sufficiency in growth signals, insensitivity to anti-growth signals, tissue invasion and metastasis, limitless replicative potentials, and sustained angiogenesis. The widely accepted paradigm suggests that cancer arises as a result of mutations or epigenetic events, which alter function of genes critical for attaining these phenotypes. These gene functions are intimately linked to the regulation of developmental processes2, their aberrant function in tumor inevitably lead to cell states that resemble stages during normal development. These cell states can be captured using genomic technologies to define distinct molecular subtypes. With the advent of The Genome Cancer Atlas project for glioblastoma3,4, we now have a glimpse of the genetic events underlying glioblastoma pathogenesis as well as distinct molecular subtypes. In this review, the genomic profiles of glioblastoma will be reviewed in the context of the properties described by Hanahan and Weinberg. Molecular subtypes of glioblastoma will be discussed in the context of developmental biology and the cell of origin.

#### **2. Glioblastoma**

Glioblastoma is the most common form of primary brain tumor, with dismal prognosis. The incidence of this tumor is fairly low, with 2-3 cases per 100,000 people in Europe and North America. Despite its rarity, overall mortality related to glioblastoma is comparable to the more prevalent tumors5. This is, in large part, due to the near uniform fatality of the afflicted patients. Indeed, glioblastoma is one of the most aggressive of the malignant tumors. Without treatment, the median survival is approximately 3 months6. The current standard of treatment involves maximal surgical resection followed by concurrent radiation therapy and

Molecular Etiology of Glioblastomas:

1989).

Implication of Genomic Profiling From the Cancer Genome Atlas Project 27

importance of growth factors in biology was recognized by a Nobel Prize in Physiology or Medicine to Stanley Cohen and Rita Levi-Montalcini in 1986. Subsequent identification that many oncogenes participate in cellular signaling related to growth factor function was also awarded a Nobel Prize in Physiology or Medicine (to Michael Bishop and Harold Varmus in

To abridge this stringent growth regulation, tumors often mutate the transmembrane receptors or their downstream effectors in ways that constitutively activate the pathway. The pathway most commonly mutated to achieve this end in glioblastoma involves the RTK-PI3K pathway9,10. RTKs are cell surface receptors that are normally activated only in response to growth factor binding9. Results from the TCGA revealed that nearly all glioblastomas harbor activating mutations or amplifications in genes required for this signaling cascade3,4,11,12. Epidermal Growth Factor Receptor (EGFR) and Platelet Derived

For EGFR and PDGFR, binding of the growth factor to the ligand leads to homo- or heterodimerization of the receptor. This dimerization facilitates autophosphorylation of the cytoplasmic domains of the dimerized receptor at select tyrosine residues9. The phosphorylated tyrosine residue, in turn, recruits and binds to other signaling proteins to the cell membrane. In some cases, the phospho-tyrosine bound proteins serve as a platform for the recruitment of other effector proteins. In other cases, the bound protein undergoes a conformational change upon binding to the RTK and becomes activated in the process9. One of the critical cellular kinases that become activated upon binding to RTK is PI3K13. PI3Ks catalyze the phosphorylation of a critical component of the cell surface, phosphatidylinositol-4,5-isphosphate (PI(4,5)P2). This phosphorylation generates phosphatidylinositol-1,4,5-isphosphate (PI(1,4,5)P3), which in turn serves as a docking site for pro-proliferative down-stream effector proteins 10. Thus, RTK activation transforms the cell membrane into a catalytic surface populated with a high density of pro-mitotic signaling

Expectedly, gene functions that inhibit the generation of this pro-proliferative "catalytic surface" function as tumor suppressors. For instance, the hydrolysis of (PI(1,4,5)P3) into (PI(4,5)P2) is catalyzed by a phosphatase termed Phosphatase and Tensin Homology (PTEN). PTEN inactivating mutations have been identified in up to 50% of tumor specimens 14. Similarly, one of the effector proteins recruited to a phosphorylated RTK is Ras. Ras encodes a monomeric G-protein that cycles between an active form bound to GTP and an inactive form that binds to GDP15. It functions as a critical component of the proproliferative "catalytic surface". Through a series of protein-protein interactions, RTK activation catalyzes the exchange of GDP for GTP in Ras, initiating signals required for cellular proliferation. The protein encoded by neurofibromatosis 1 (NF1) functions to catalyze the exchange of GTP for GDP in Ras, consequently preventing cell proliferation. In this context, it is not surprising that NF1 patients are predisposed to gliomagenesis 16. The TCGA results showed that approximately 20% of glioblastomas harbor loss of function mutations in NF13,4. TCGA additionally revealed gain of function mutations in K-ras have

In addition to receiving pro-growth signals from their environment, cells also receive multiple anti-proliferative signals to prevent cell growth. These anti-growth signals, like

Growth Factor Receptor (PDGFR) are two prototypical members of RTK3, 4, 12.

molecules, ultimately leading to cell proliferation.

also been identified in glioblastoma specimens 3.

**4.2 Insensitivity to anti-growth signals – The RB axis** 

chemotherapy with the DNA alkylating agent, temozolomide7. With this regimen, the median survival is approximately 14 months. For nearly all affected, the treatments available remain palliative.

Studies carried out over the past three decades suggest that glioblastomas, like other cancers, arise secondary to the accumulation of genetic alterations. These alterations can take the form of epigenetic modifications, point mutations, translocations, amplifications, or deletions, and modify gene function in ways that deregulate cellular signaling pathways leading to the cancer phenotype1. The exact number and nature of genetic alterations and deregulated signaling pathways required for tumorogenesis remains an issue of debate8, although it is now clear that CNS carcinogenesis requires multiple disruptions to the normal cellular circuitry3, 4.

#### **3. The Cancer Genome Atlas (TCGA) project**

The Cancer Genome Atlas (TCGA) is a comprehensive and coordinated effort to catalogue the genetic and epigenetic changes in the cancer genome, with goals of identifying those responsible for carcinogenesis. The project constitutes a joint effort of the National Human Genome Research Institute (NHGRI), National Cancer Institute (NCI), and the U.S. Department of Health and Human Services, and collects tumor specimen from major cancer centers spanning across the continental U.S. The project aims to provide the genomic profile of 500 specimens of various cancer types using state-of-the-art platforms for sequencing, microRNA, mRNA, single-nucleotide polymorphisms, and methylation profiling.

TCGA started as a pilot project in 2006 with focus on glioblastoma as the first cancer type for study. With the success of the pilot project, TCGA plans to expand its efforts to aggressively pursue 20 or more additional cancers. This article will review the major insights derived from the TCGA in the context of the cancer phenotypes proposed by Hanahan and Weinberg1.

#### **4. The cancer phenotype**

The aggregate of cancer research investigation spanning the past three decades suggest that cancer is a genetic disease characterized by mutations or epigenetic events that abrogate or compromise regulatory circuitry governing cell proliferation and homeostasis8. In the landmark review by Hanahan and Weinberg1, the authors distilled the essence of these regulatory circuits into six distinct phenotypes, including evading apoptosis, self-sufficiency in growth signals, insensitivity to anti-growth signals, tissue invasion and metastasis, limitless replicative potentials, and sustained angiogenesis. The following section will review the TCGA findings pertinent to these phenotypes.

#### **4.1 Self-sufficiency in growth signals – The Receptor Tyrosine Kinase (RTK)/PhosphoInosital 3 Kinase (PI3K) signaling cascade**

Active cellular proliferation in normal cells requires signals from its environment. These signals typically involve the binding of a transmembrane receptor to growth factors, extracellular matrix components, or cell surface components. This mitogenic signaling process is under stringent regulation in normal cells. Typically, multiple ligand-receptor interactions in a permissive cellular state are required before cellular proliferation can take place. This regulation minimizes the probability of dysregulated, autonomous cell growth1,9. The

chemotherapy with the DNA alkylating agent, temozolomide7. With this regimen, the median survival is approximately 14 months. For nearly all affected, the treatments

Studies carried out over the past three decades suggest that glioblastomas, like other cancers, arise secondary to the accumulation of genetic alterations. These alterations can take the form of epigenetic modifications, point mutations, translocations, amplifications, or deletions, and modify gene function in ways that deregulate cellular signaling pathways leading to the cancer phenotype1. The exact number and nature of genetic alterations and deregulated signaling pathways required for tumorogenesis remains an issue of debate8, although it is now clear that CNS carcinogenesis requires multiple disruptions to the normal

The Cancer Genome Atlas (TCGA) is a comprehensive and coordinated effort to catalogue the genetic and epigenetic changes in the cancer genome, with goals of identifying those responsible for carcinogenesis. The project constitutes a joint effort of the National Human Genome Research Institute (NHGRI), National Cancer Institute (NCI), and the U.S. Department of Health and Human Services, and collects tumor specimen from major cancer centers spanning across the continental U.S. The project aims to provide the genomic profile of 500 specimens of various cancer types using state-of-the-art platforms for sequencing,

TCGA started as a pilot project in 2006 with focus on glioblastoma as the first cancer type for study. With the success of the pilot project, TCGA plans to expand its efforts to aggressively pursue 20 or more additional cancers. This article will review the major insights derived from the TCGA in the context of the cancer phenotypes proposed by Hanahan and

The aggregate of cancer research investigation spanning the past three decades suggest that cancer is a genetic disease characterized by mutations or epigenetic events that abrogate or compromise regulatory circuitry governing cell proliferation and homeostasis8. In the landmark review by Hanahan and Weinberg1, the authors distilled the essence of these regulatory circuits into six distinct phenotypes, including evading apoptosis, self-sufficiency in growth signals, insensitivity to anti-growth signals, tissue invasion and metastasis, limitless replicative potentials, and sustained angiogenesis. The following section will

Active cellular proliferation in normal cells requires signals from its environment. These signals typically involve the binding of a transmembrane receptor to growth factors, extracellular matrix components, or cell surface components. This mitogenic signaling process is under stringent regulation in normal cells. Typically, multiple ligand-receptor interactions in a permissive cellular state are required before cellular proliferation can take place. This regulation minimizes the probability of dysregulated, autonomous cell growth1,9. The

microRNA, mRNA, single-nucleotide polymorphisms, and methylation profiling.

available remain palliative.

cellular circuitry3, 4.

Weinberg1.

**4. The cancer phenotype** 

**3. The Cancer Genome Atlas (TCGA) project** 

review the TCGA findings pertinent to these phenotypes.

**(RTK)/PhosphoInosital 3 Kinase (PI3K) signaling cascade** 

**4.1 Self-sufficiency in growth signals – The Receptor Tyrosine Kinase** 

importance of growth factors in biology was recognized by a Nobel Prize in Physiology or Medicine to Stanley Cohen and Rita Levi-Montalcini in 1986. Subsequent identification that many oncogenes participate in cellular signaling related to growth factor function was also awarded a Nobel Prize in Physiology or Medicine (to Michael Bishop and Harold Varmus in 1989).

To abridge this stringent growth regulation, tumors often mutate the transmembrane receptors or their downstream effectors in ways that constitutively activate the pathway. The pathway most commonly mutated to achieve this end in glioblastoma involves the RTK-PI3K pathway9,10. RTKs are cell surface receptors that are normally activated only in response to growth factor binding9. Results from the TCGA revealed that nearly all glioblastomas harbor activating mutations or amplifications in genes required for this signaling cascade3,4,11,12. Epidermal Growth Factor Receptor (EGFR) and Platelet Derived Growth Factor Receptor (PDGFR) are two prototypical members of RTK3, 4, 12.

For EGFR and PDGFR, binding of the growth factor to the ligand leads to homo- or heterodimerization of the receptor. This dimerization facilitates autophosphorylation of the cytoplasmic domains of the dimerized receptor at select tyrosine residues9. The phosphorylated tyrosine residue, in turn, recruits and binds to other signaling proteins to the cell membrane. In some cases, the phospho-tyrosine bound proteins serve as a platform for the recruitment of other effector proteins. In other cases, the bound protein undergoes a conformational change upon binding to the RTK and becomes activated in the process9.

One of the critical cellular kinases that become activated upon binding to RTK is PI3K13. PI3Ks catalyze the phosphorylation of a critical component of the cell surface, phosphatidylinositol-4,5-isphosphate (PI(4,5)P2). This phosphorylation generates phosphatidylinositol-1,4,5-isphosphate (PI(1,4,5)P3), which in turn serves as a docking site for pro-proliferative down-stream effector proteins 10. Thus, RTK activation transforms the cell membrane into a catalytic surface populated with a high density of pro-mitotic signaling molecules, ultimately leading to cell proliferation.

Expectedly, gene functions that inhibit the generation of this pro-proliferative "catalytic surface" function as tumor suppressors. For instance, the hydrolysis of (PI(1,4,5)P3) into (PI(4,5)P2) is catalyzed by a phosphatase termed Phosphatase and Tensin Homology (PTEN). PTEN inactivating mutations have been identified in up to 50% of tumor specimens 14. Similarly, one of the effector proteins recruited to a phosphorylated RTK is Ras. Ras encodes a monomeric G-protein that cycles between an active form bound to GTP and an inactive form that binds to GDP15. It functions as a critical component of the proproliferative "catalytic surface". Through a series of protein-protein interactions, RTK activation catalyzes the exchange of GDP for GTP in Ras, initiating signals required for cellular proliferation. The protein encoded by neurofibromatosis 1 (NF1) functions to catalyze the exchange of GTP for GDP in Ras, consequently preventing cell proliferation. In this context, it is not surprising that NF1 patients are predisposed to gliomagenesis 16. The TCGA results showed that approximately 20% of glioblastomas harbor loss of function mutations in NF13,4. TCGA additionally revealed gain of function mutations in K-ras have also been identified in glioblastoma specimens 3.

#### **4.2 Insensitivity to anti-growth signals – The RB axis**

In addition to receiving pro-growth signals from their environment, cells also receive multiple anti-proliferative signals to prevent cell growth. These anti-growth signals, like

Molecular Etiology of Glioblastomas:

defined murine models27.

**4.4 Replicative potential** 

tumor progression.

Implication of Genomic Profiling From the Cancer Genome Atlas Project 29

There are several lines of evidence that point to the importance of the p53 axis in glioblastoma pathogenesis. In the TCGA database, mutations that inactivate this axis are found in greater than 70% of glioblastoma specimens3,4. Patients harboring germ-line mutations in *TP53* are afflicted with cancer predisposition including increased risk for glioblastoma26. Finally, inactivation of p53 is required for glioma formation in genetically

The definition of cancer as a continuous growing entity implies that normal cells exhibit a limited capacity for proliferation. Indeed, estimates based on tissue culture work suggest that most normal cells have the capacity for 50 doublings 28. Studies over the past three decades suggest that the main reason for this limited life span involve progressive shortening of chromosomes due to loss of telomeres. Telomeres consist of thousands of six base pair sequence element of repeats that are located at the ends of every chromosome. Because of the inability of DNA polymerases to replicate the 3' ends of chromosomal DNA, approximately 60 base pairs of the telomeric sequence is lost with each replicative cycle29. With progressive erosion of the telomeric sequence, the unprotected chromosomal ends

To overcome this inherent limitation, most cancer cells activate an enzyme called telomerase. Telomerase is a reverse transcriptase capable of elongating telomeres31. Various mechanisms are employed by tumors to activate telomerase in order to sustain continued cell growth. Elizabeth Balckburn, Carol Greider, and Jack Szostak were awarded the Nobel

With regards to glioblastomas, single nucleotide polymorphisms in two genes encoding components of the telomerase (*RTEL1* and *TERT*) have been identified as risk factors for glioma development19, 20. Additionally, elevated expression level of *TERT* in glioblastoma is associated with decreased patient survival 32. These studies suggest a critical importance of

**Angiogenesis**. The intense proliferation of cancer cells require continued supply of oxygen and nutrients. Due to inherent limitations on the distance that oxygen and macromolecules can travel, virtually all cells in a tissue reside with 100 um of a capillary. In xenograft model systems, solid tumors can only proliferate up to a size of 1-2 mm without development of new blood supply33. Thus, angiogenesis necessarily constitutes a pre-requisite during solid

One way by which cancer cells signal angiogenesis is by secretion of soluble factors that bind to receptors present on the surface endothelial cells. A key soluble factor that functions in such capacity is the Vascular Endothelial Growth Factor (VEGF). VEGF binds to RTKs on the surface of endothelial cells to facilitate their proliferation – leading to angiogenesis34. In normal cells, transcription of VEGF and other pro-angiogenic signaling factors are under strict regulation. The induction of Hypoxia Inducible Factor I (HIF1) is a pivotal element in this regulatory network35. HIF1 encodes a dimeric transcription factor consisting of two subunits: HIF1 and HIF1. HIF1 is constitutively expressed irrespective of oxygen concentration, whereas HIF1 levels increase dramatically in response to hypoxia. The underlying mechanism for this regulation is that HIF1is hydroxylated by HIF Prolyl-4- Hydroxylase (HPH) in the presence of di-oxygen (O2), iron, and -ketoglutarate. The hydroxylated HIF1is targeted for proteasome degradation. Without molecular oxygen,

participate in aberrant fusion events that inevitably result in cell death30.

Prize in Physiology or Medicine in 2009 for their discovery of telomerase.

telomeric biology in glioblastoma growth and survival.

their pro-mitotic counterparts, are sensed by the binding of transmembrane receptors to soluble factors, extracellular matrix components, or cell surface components.

Most of these anti-proliferative signals operate at the G1 phase of the cell cycle to trigger either 1) entry into a transient quiescent (G0) state or 2) entry into a post-mitotic, differentiated state. The importance of cell cycle regulation in biology was recognized by a Nobel Prize in Physiology or Medicine to Leland Hartwell, Tim Hunt, and Sir Paul Nurse in 2001.

At the molecular level, nearly all of these signals converge at the retinoblastoma protein (RB) 1. In quiescent cells, the RB protein is hyper-phosphorylated. This form of RB binds and sequesters the E2F family of transcription factors17. The genes transcribed by these transcription factors are essential for the G1-S transition of the cell cycle18. Phosphorylation of RB releases the sequestered E2F transcription factors and allows for cell growth. During normal cell cycle progression, induction of cyclin D1 and its associated cyclin-dependent kinases, CDK4 and CDK6, at the G1-S transition is responsible for the phosphorylation of RB. The kinase activity of the CDK4/6-cyclin D complex is under complex regulation, including the critical negative regulators CDKN2A (p16Ink4a), CDKN2B, and CDKN2C. TCGA results showed that mutations and gene amplifications disrupting RB function are found in approximately 80% of glioblastomas, suggesting the critical importance of escaping anti-growth signals3,4. Additionally, single nucleotide polymorphisms in the *CDKN2A* and *CDKN2B* have been identified as risk factors for glioma development19,20.

#### **4.3 Evading apoptosis – The p53 axis**

Apoptotic programs are inherent in all normal cells. These programs are activated by a number of physiologic signals during development and/or in response to cellular stress. Since the tumor state is associated with cellular stress capable of activating apoptosis (e.g. increased oxidative stress, increased DNA damage accumulation), inactivation of these programs constitute a critical step during carcinogenesis. The importance of apoptosis as a fundamental biologic process was recognized by a Nobel Prize in Physiology or Medicine awarded to Sydney Brenner, Robert Horvitz, and John Sulston in 2002.

The regulation of apoptotic pathways is highly complex21. Broadly speaking, there are two pathways of apoptosis that converge on the activation of effector proteases (termed caspases), which ultimately trigger the pathognomonic DNA fragmentation, cell shrinkage, and membrane blebbing. The intrinsic cell death pathway (often termed the mitochondrial apoptotic pathway) involves the release of cytochrome c from the mitochondrial membrane space22. Binding of cytochrome c to a protein termed apoptosis protease-activating factor 1 (APAF-1), in turn, initiates the caspase cascade. In contrast, the extrinsic apoptotic pathway operates independently of mitochondria and is activated by direct signaling from cell surface receptors to the effector caspase23.

Both intrinsic and extrinsic apoptotic programs are profoundly influenced by the p53 tumor suppressor protein24. *TP53* encodes a transcription factor that regulates gene sets critical for cell cycle progression and apoptosis. Under normal conditions, p53 is a short-lived protein25. In response to cellular stress (for instance, DNA damage or oncogene expression), p53 undergoes post-translational modifications and protein-protein interactions that enhance its stability and transcriptional activity25. Key among the transcripts regulated by p53 are proapoptotic genes (including BAX and Puma) that facilitate both the intrinsic and extrinsic pathway24. Additionally, p53 interact with a number of anti-apoptotic proteins to inhibit their function24.

There are several lines of evidence that point to the importance of the p53 axis in glioblastoma pathogenesis. In the TCGA database, mutations that inactivate this axis are found in greater than 70% of glioblastoma specimens3,4. Patients harboring germ-line mutations in *TP53* are afflicted with cancer predisposition including increased risk for glioblastoma26. Finally, inactivation of p53 is required for glioma formation in genetically defined murine models27.

#### **4.4 Replicative potential**

28 Glioma – Exploring Its Biology and Practical Relevance

their pro-mitotic counterparts, are sensed by the binding of transmembrane receptors to

Most of these anti-proliferative signals operate at the G1 phase of the cell cycle to trigger either 1) entry into a transient quiescent (G0) state or 2) entry into a post-mitotic, differentiated state. The importance of cell cycle regulation in biology was recognized by a Nobel Prize in Physiology or Medicine to Leland Hartwell, Tim Hunt, and Sir Paul Nurse in

At the molecular level, nearly all of these signals converge at the retinoblastoma protein (RB) 1. In quiescent cells, the RB protein is hyper-phosphorylated. This form of RB binds and sequesters the E2F family of transcription factors17. The genes transcribed by these transcription factors are essential for the G1-S transition of the cell cycle18. Phosphorylation of RB releases the sequestered E2F transcription factors and allows for cell growth. During normal cell cycle progression, induction of cyclin D1 and its associated cyclin-dependent kinases, CDK4 and CDK6, at the G1-S transition is responsible for the phosphorylation of RB. The kinase activity of the CDK4/6-cyclin D complex is under complex regulation, including the critical negative regulators CDKN2A (p16Ink4a), CDKN2B, and CDKN2C. TCGA results showed that mutations and gene amplifications disrupting RB function are found in approximately 80% of glioblastomas, suggesting the critical importance of escaping anti-growth signals3,4. Additionally, single nucleotide polymorphisms in the *CDKN2A* and

Apoptotic programs are inherent in all normal cells. These programs are activated by a number of physiologic signals during development and/or in response to cellular stress. Since the tumor state is associated with cellular stress capable of activating apoptosis (e.g. increased oxidative stress, increased DNA damage accumulation), inactivation of these programs constitute a critical step during carcinogenesis. The importance of apoptosis as a fundamental biologic process was recognized by a Nobel Prize in Physiology or Medicine

The regulation of apoptotic pathways is highly complex21. Broadly speaking, there are two pathways of apoptosis that converge on the activation of effector proteases (termed caspases), which ultimately trigger the pathognomonic DNA fragmentation, cell shrinkage, and membrane blebbing. The intrinsic cell death pathway (often termed the mitochondrial apoptotic pathway) involves the release of cytochrome c from the mitochondrial membrane space22. Binding of cytochrome c to a protein termed apoptosis protease-activating factor 1 (APAF-1), in turn, initiates the caspase cascade. In contrast, the extrinsic apoptotic pathway operates independently of mitochondria and is activated by direct signaling from cell

Both intrinsic and extrinsic apoptotic programs are profoundly influenced by the p53 tumor suppressor protein24. *TP53* encodes a transcription factor that regulates gene sets critical for cell cycle progression and apoptosis. Under normal conditions, p53 is a short-lived protein25. In response to cellular stress (for instance, DNA damage or oncogene expression), p53 undergoes post-translational modifications and protein-protein interactions that enhance its stability and transcriptional activity25. Key among the transcripts regulated by p53 are proapoptotic genes (including BAX and Puma) that facilitate both the intrinsic and extrinsic pathway24. Additionally, p53 interact with a number of anti-apoptotic proteins to inhibit

soluble factors, extracellular matrix components, or cell surface components.

*CDKN2B* have been identified as risk factors for glioma development19,20.

awarded to Sydney Brenner, Robert Horvitz, and John Sulston in 2002.

**4.3 Evading apoptosis – The p53 axis** 

surface receptors to the effector caspase23.

their function24.

2001.

The definition of cancer as a continuous growing entity implies that normal cells exhibit a limited capacity for proliferation. Indeed, estimates based on tissue culture work suggest that most normal cells have the capacity for 50 doublings 28. Studies over the past three decades suggest that the main reason for this limited life span involve progressive shortening of chromosomes due to loss of telomeres. Telomeres consist of thousands of six base pair sequence element of repeats that are located at the ends of every chromosome. Because of the inability of DNA polymerases to replicate the 3' ends of chromosomal DNA, approximately 60 base pairs of the telomeric sequence is lost with each replicative cycle29. With progressive erosion of the telomeric sequence, the unprotected chromosomal ends participate in aberrant fusion events that inevitably result in cell death30.

To overcome this inherent limitation, most cancer cells activate an enzyme called telomerase. Telomerase is a reverse transcriptase capable of elongating telomeres31. Various mechanisms are employed by tumors to activate telomerase in order to sustain continued cell growth. Elizabeth Balckburn, Carol Greider, and Jack Szostak were awarded the Nobel Prize in Physiology or Medicine in 2009 for their discovery of telomerase.

With regards to glioblastomas, single nucleotide polymorphisms in two genes encoding components of the telomerase (*RTEL1* and *TERT*) have been identified as risk factors for glioma development19, 20. Additionally, elevated expression level of *TERT* in glioblastoma is associated with decreased patient survival 32. These studies suggest a critical importance of telomeric biology in glioblastoma growth and survival.

**Angiogenesis**. The intense proliferation of cancer cells require continued supply of oxygen and nutrients. Due to inherent limitations on the distance that oxygen and macromolecules can travel, virtually all cells in a tissue reside with 100 um of a capillary. In xenograft model systems, solid tumors can only proliferate up to a size of 1-2 mm without development of new blood supply33. Thus, angiogenesis necessarily constitutes a pre-requisite during solid tumor progression.

One way by which cancer cells signal angiogenesis is by secretion of soluble factors that bind to receptors present on the surface endothelial cells. A key soluble factor that functions in such capacity is the Vascular Endothelial Growth Factor (VEGF). VEGF binds to RTKs on the surface of endothelial cells to facilitate their proliferation – leading to angiogenesis34. In normal cells, transcription of VEGF and other pro-angiogenic signaling factors are under strict regulation. The induction of Hypoxia Inducible Factor I (HIF1) is a pivotal element in this regulatory network35. HIF1 encodes a dimeric transcription factor consisting of two subunits: HIF1 and HIF1. HIF1 is constitutively expressed irrespective of oxygen concentration, whereas HIF1 levels increase dramatically in response to hypoxia. The underlying mechanism for this regulation is that HIF1is hydroxylated by HIF Prolyl-4- Hydroxylase (HPH) in the presence of di-oxygen (O2), iron, and -ketoglutarate. The hydroxylated HIF1is targeted for proteasome degradation. Without molecular oxygen,

Molecular Etiology of Glioblastomas:

invasion.

interacts with extracellular matrix during cell migration47.

under transcriptional regulation by p53 and RB associated E2Fs49.

results from sequential inactivation of the p53, RB, and RTK/PI3K axes.

**4.6 Cross-talk between canonical pathways** 

**5. Pathway of glioblastoma progression** 

such a profile may be challenging.

**6. Molecular subtypes** 

Implication of Genomic Profiling From the Cancer Genome Atlas Project 31

To date, the TCGA has not uncovered gain of function mutations in these proteins. However, enhanced invasive properties have been associated with mutations establishing autonomous growth or suppressing apoptosis. For instance, aberrant EGFR activation results in increased expression and phosphorylation of cell adhesion molecules that ultimately lead to increased invasiveness46. Similarly, the p53 mutation drives cancer invasiveness by facilitating the recycling of integrin, a class of cell surface receptor that

The aggregate of the data suggest that both angiogenesis and cell migratory properties are intimately integrated into a master circuitry controlled by critical proteins that dictate cellular response to growth or apoptotic signals. In this context, mutations facilitating selfautonomous growth or suppression of apoptosis also contribute to angiogenesis and cell

The conceptualization of distinct pathways contributing to the various critical phenotypes constitutes a simplification aimed to consolidate distinct biological concepts. The reality is that pathways mediating the cancer phenotype exhibit high degrees of cross-talk and functional redundancy. For instance, EGFR hyperactivation is associated with increased tumor growth (replicative potential), angiogenesis, and increased tumor motility 48. Similarly, many genes mediating cell motility, telomere function, and angiogenesis are

It was previously thought that glioblastoma arises from the acquisition of a defined set of mutations that occur in a particular temporal order. This model is largely grounded on the framework established in colon cancer, where a series of genetic alterations characterizes different phases of neoplastic progression50. The framework is supported by the observation that Grade II astrocytomas typically harbor mutations in p53; Grade III astrocytomas harbor activating mutations/amplifications of CDKN2A (p16Ink4a); and Grade IV astrocytomas harbor mutations in PTEN and EGFR51. This data was interpreted to mean that glioblastoma

While such a paradigm may hold true for a subset of the secondary glioblastomas, the picture emerging from the genomic characterization of primary glioblastomas reveals a much more dynamic process3,4. The profile of somatic mutations in different glioblastomas is highly variable. These results suggest that most glioblastomas evolve along a multitude of pathways in response to differing selective pressures to achieve the phenotypes described by Hanahan and Weinberg52. This somewhat stochastic model of cancer progression further implies that mutations critical at one juncture in the neoplastic process may lose relevance as additional mutations are acquired. Thus, while a mutational profile constitutes an archeological profile of the history of the neoplasm, extrapolating therapeutic targets from

Genome-scale gene expression profiling using microarray technology have revealed distinct molecular subtypes within tumors previously classified as glioblastomas 12, 53-55. The number

HIF1is not hydroxylated and is free to dimerize with HIF1to activate the transcription of downstream pro-angiogenetic factors.

Integrated analysis of genomic data in glioblastoma revealed recurrent mutations in the R132 residue of isocitrate dehydrogenase 1 (IDH1)4, a gene largely responsible for the production of -ketoglutarate. The TCGA data revealed that the IDH1 mutation is predominantly found in one particular molecular subtype of glioblastoma12, 36 (see following section on **molecular subtypes**). The wildtype IDH1 normally functions as a homodimer that converts isocitrate to -ketoglutarate37. Biochemical characterization of the R132 mutated IDH1 revealed that it functions in a dominantly negative fashion to inhibit the process. Expectedly, glioblastoma harboring the *R132 IDH1* mutation harbor decreased levels of -ketoglutarate. Given the importance of -ketoglutarate in HIF1degradation, one would anticipate increased HIF1 accumulation and increased VEGF secretion in glioblastoma harboring the *IDH1* mutation. These observations were confirmed in a panel of primary glioblastoma specimens38. Thus, the *IDH1* mutation constitutes an example of how glioblastoma subverts the endogenous molecular circuit to facilitate angiogenesis. It should be noted that the effect of the *IDH1* mutation appears pleiotropic. Another study revealed that the R132 mutant IDH1 proteins exhibits a gain-of-function phenotype by generating R(-)-2-hydroxyglutarate, a carcinogenic metabolite39.

In glioblastomas without *IDH1* mutation, alternate mechanisms are utilized to facilitate angiogenesis. It is somewhat intuitive that during normal development, periods of cellular proliferation must be coordinated with angioogenesis. Indeed, a large body of work suggests that gene functions that facilitate cell-autonomous growth or insensitivity to growth inhibition and apoptosis also tend to facilitate angiogenesis40, 41. It is likely that most glioblastoma cells attain angiogenesis by aberrant activation of such coordinated developmental programs. For instance, EGFR activation has been shown to up-regulate VEGF in both HIF dependent and independent manner42. Inactivation of Rb increases VEGF expression and angiogenesis *in vivo*40. Similarly, p53 normally up-regulates thrombospondin 1, an inhibitor of angiogenesis43; inactivation of p53 can facilitate angiogenesis by ablation of this up-regulation.

#### **4.5 Invasion and metastasis**

The ability to invade and metastasize constitutes the fundamental distinction between benign and malignant tumors. It is important to note that invasion refers not just to distortion of normal tissue secondary to tumor growth. Instead, it refers to a coordinated set of cellular activities to destroy and migrate into the surrounding normal tissue. Metastasis refers to the capacity to travel via circulation to a distant tissue site33. Glioblastoma is unique in that while it is one of the most invasive of cancers, it rarely metastasizes outside of the central nervous system.

It is a truism that cancer cells generally retain some general properties of the cell of origin. Since glioblastoma originates from astrocytes, which normally possess significant migratory capacity, the invasive nature of glioblastoma would be anticipated. During normal development, astrocytes migrate in a centripetal manner to establish a scaffold for neuroblasts44. Additionally, in response to injury, astrocytes migrate to the affected region to form a gliotic scar45. This migratory capacity is the phenotypic expression of carefully orchestrated interactions between cellular cytoskeletal proteins, cell adhesion molecules, and extracellular matrix33.

To date, the TCGA has not uncovered gain of function mutations in these proteins. However, enhanced invasive properties have been associated with mutations establishing autonomous growth or suppressing apoptosis. For instance, aberrant EGFR activation results in increased expression and phosphorylation of cell adhesion molecules that ultimately lead to increased invasiveness46. Similarly, the p53 mutation drives cancer invasiveness by facilitating the recycling of integrin, a class of cell surface receptor that interacts with extracellular matrix during cell migration47.

The aggregate of the data suggest that both angiogenesis and cell migratory properties are intimately integrated into a master circuitry controlled by critical proteins that dictate cellular response to growth or apoptotic signals. In this context, mutations facilitating selfautonomous growth or suppression of apoptosis also contribute to angiogenesis and cell invasion.

#### **4.6 Cross-talk between canonical pathways**

30 Glioma – Exploring Its Biology and Practical Relevance

HIF1is not hydroxylated and is free to dimerize with HIF1to activate the transcription of

Integrated analysis of genomic data in glioblastoma revealed recurrent mutations in the R132 residue of isocitrate dehydrogenase 1 (IDH1)4, a gene largely responsible for the production of -ketoglutarate. The TCGA data revealed that the IDH1 mutation is predominantly found in one particular molecular subtype of glioblastoma12, 36 (see following section on **molecular subtypes**). The wildtype IDH1 normally functions as a homodimer that converts isocitrate to -ketoglutarate37. Biochemical characterization of the R132 mutated IDH1 revealed that it functions in a dominantly negative fashion to inhibit the process. Expectedly, glioblastoma harboring the *R132 IDH1* mutation harbor decreased levels of -ketoglutarate. Given the importance of -ketoglutarate in HIF1degradation, one would anticipate increased HIF1 accumulation and increased VEGF secretion in glioblastoma harboring the *IDH1* mutation. These observations were confirmed in a panel of primary glioblastoma specimens38. Thus, the *IDH1* mutation constitutes an example of how glioblastoma subverts the endogenous molecular circuit to facilitate angiogenesis. It should be noted that the effect of the *IDH1* mutation appears pleiotropic. Another study revealed that the R132 mutant IDH1 proteins exhibits a gain-of-function phenotype by generating

In glioblastomas without *IDH1* mutation, alternate mechanisms are utilized to facilitate angiogenesis. It is somewhat intuitive that during normal development, periods of cellular proliferation must be coordinated with angioogenesis. Indeed, a large body of work suggests that gene functions that facilitate cell-autonomous growth or insensitivity to growth inhibition and apoptosis also tend to facilitate angiogenesis40, 41. It is likely that most glioblastoma cells attain angiogenesis by aberrant activation of such coordinated developmental programs. For instance, EGFR activation has been shown to up-regulate VEGF in both HIF dependent and independent manner42. Inactivation of Rb increases VEGF expression and angiogenesis *in vivo*40. Similarly, p53 normally up-regulates thrombospondin 1, an inhibitor of angiogenesis43; inactivation of p53 can facilitate angiogenesis by ablation of

The ability to invade and metastasize constitutes the fundamental distinction between benign and malignant tumors. It is important to note that invasion refers not just to distortion of normal tissue secondary to tumor growth. Instead, it refers to a coordinated set of cellular activities to destroy and migrate into the surrounding normal tissue. Metastasis refers to the capacity to travel via circulation to a distant tissue site33. Glioblastoma is unique in that while it is one of the most invasive of cancers, it rarely metastasizes outside of the

It is a truism that cancer cells generally retain some general properties of the cell of origin. Since glioblastoma originates from astrocytes, which normally possess significant migratory capacity, the invasive nature of glioblastoma would be anticipated. During normal development, astrocytes migrate in a centripetal manner to establish a scaffold for neuroblasts44. Additionally, in response to injury, astrocytes migrate to the affected region to form a gliotic scar45. This migratory capacity is the phenotypic expression of carefully orchestrated interactions between cellular cytoskeletal proteins, cell adhesion molecules,

downstream pro-angiogenetic factors.

R(-)-2-hydroxyglutarate, a carcinogenic metabolite39.

this up-regulation.

**4.5 Invasion and metastasis** 

central nervous system.

and extracellular matrix33.

The conceptualization of distinct pathways contributing to the various critical phenotypes constitutes a simplification aimed to consolidate distinct biological concepts. The reality is that pathways mediating the cancer phenotype exhibit high degrees of cross-talk and functional redundancy. For instance, EGFR hyperactivation is associated with increased tumor growth (replicative potential), angiogenesis, and increased tumor motility 48. Similarly, many genes mediating cell motility, telomere function, and angiogenesis are under transcriptional regulation by p53 and RB associated E2Fs49.

#### **5. Pathway of glioblastoma progression**

It was previously thought that glioblastoma arises from the acquisition of a defined set of mutations that occur in a particular temporal order. This model is largely grounded on the framework established in colon cancer, where a series of genetic alterations characterizes different phases of neoplastic progression50. The framework is supported by the observation that Grade II astrocytomas typically harbor mutations in p53; Grade III astrocytomas harbor activating mutations/amplifications of CDKN2A (p16Ink4a); and Grade IV astrocytomas harbor mutations in PTEN and EGFR51. This data was interpreted to mean that glioblastoma results from sequential inactivation of the p53, RB, and RTK/PI3K axes.

While such a paradigm may hold true for a subset of the secondary glioblastomas, the picture emerging from the genomic characterization of primary glioblastomas reveals a much more dynamic process3,4. The profile of somatic mutations in different glioblastomas is highly variable. These results suggest that most glioblastomas evolve along a multitude of pathways in response to differing selective pressures to achieve the phenotypes described by Hanahan and Weinberg52. This somewhat stochastic model of cancer progression further implies that mutations critical at one juncture in the neoplastic process may lose relevance as additional mutations are acquired. Thus, while a mutational profile constitutes an archeological profile of the history of the neoplasm, extrapolating therapeutic targets from such a profile may be challenging.

#### **6. Molecular subtypes**

Genome-scale gene expression profiling using microarray technology have revealed distinct molecular subtypes within tumors previously classified as glioblastomas 12, 53-55. The number

Molecular Etiology of Glioblastomas:

**7. Summary** 

**8. References** 

1978;49(3):333-343.

2009;458(7239):719-724.

2007;318(5848):287-290.

996.

225.

Implication of Genomic Profiling From the Cancer Genome Atlas Project 33

pathway. Such functions may contribute to the distinct molecular subtypes. Still, it is conceivable that differences in signaling and cell of origin both contribute to subtype

The past three decades of work in cancer research has generated a sophisticated conceptual framework for the process of neoplastic transformation. The framework suggests that genetic and epigenetic events inactivating critical pathways that regulate several key aspects of cellular function are an etiology. These cellular functions can be categorized as selfsufficiency in growth signaling, evasion of apoptosis, insensitivity to anti-growth signals, tissue invasion, and limitless replicative potential and angiogenesis. This framework has largely been validated by a large scale, high-throughput characterization of the genomic and epigenomic landscape in glioblastomas. The picture emerging from these analyses suggests that most glioblastomas evolve along a multitude of pathways in response to differing selective pressures to achieve the cancer phenotypes. Transcript based analysis revealed distinct subtypes with potential implications with regards to the cell of origin. The dynamic interplay of growth dysregulation and the cell of origin during the neoplastic transformation process harbors vital implications with regards to therapeutic development.

[1] Hanahan D, Weinberg RA. The hallmarks of cancer. *Cell.* Jan 7 2000;100(1):57-70. [2] Zelenka PS. Proto-oncogenes in cell differentiation. *Bioessays.* Jan 1990;12(1):22-26. [3] TCGA. Comprehensive genomic characterization defines human glioblastoma genes and

glioblastoma multiforme. *Science.* Sep 26 2008;321(5897):1807-1812. [5] Wen PY, Kesari S. Malignant gliomas in adults. *N Engl J Med.* Jul 31 2008;359(5):492-507. [6] Walker MD, Alexander E, Jr., Hunt WE, et al. Evaluation of BCNU and/or radiotherapy

[4] Parsons DW, Jones S, Zhang X, et al. An integrated genomic analysis of human

[7] Stupp R, Mason WP, van den Bent MJ, et al. Radiotherapy plus concomitant and

[8] Stratton MR, Campbell PJ, Futreal PA. The cancer genome. *Nature.* Apr 9

[9] Schlessinger J. Cell signaling by receptor tyrosine kinases. *Cell.* Oct 13 2000;103(2):211-

[10] Hennessy BT, Smith DL, Ram PT, Lu Y, Mills GB. Exploiting the PI3K/AKT pathway for cancer drug discovery. *Nat Rev Drug Discov.* Dec 2005;4(12):988-1004. [11] Stommel JM, Kimmelman AC, Ying H, et al. Coactivation of receptor tyrosine kinases

[12] Verhaak RGW, Hoadley KA, Purdom E, et al. Integrated genomic analysis identifies

PDGFRA, IDH1, EGFR, and NF1. *Cancer Cell.* Jan 19 2010;17(1):98-110.

in the treatment of anaplastic gliomas. A cooperative clinical trial. *J Neurosurg.* Sep

adjuvant temozolomide for glioblastoma. *N Engl J Med.* Mar 10 2005;352(10):987-

affects the response of tumor cells to targeted therapies. *Science.* Oct 12

clinically relevant subtypes of glioblastoma characterized by abnormalities in

core pathways. *Nature.* Oct 23 2008;455(7216):1061-1068.

formation. This critical debate awaits experimental resolution.

of subtypes varies depending on the study, however, three subtypes consistently appear across independent studies and reflect distinct biologic and clinical behaviors 12, 55, 56. Importantly, the transcript signature parallels those obtained during distinct stages in neural development, suggesting the tumor may have arisen from different stages of neurogenesis55.

The first subtype is termed pro-neural. The transcript signature resembles those of neuroblasts and oligodendrocytes derived from fetal and adult brain55. This subtype harbors molecular and clinical features that closely mirror those previously classified as secondary glioblastomas. Molecularly, pro-neural glioblastomas harbor mutations classically associated with the secondary subtype, including p53 and PDGFR12. Accordingly, grade II and III gliomas harbor molecular signatures most reminiscent of the pro-neural subtype55. Clinically, this subtype typically affects younger patients, is associated with improved overall survival55, and responds poorly to concurrent radiation/temozolomide treatment upon disease progression12. Interestingly, mutations in the isocitrate **d**e**h**ydrogenase 1 gene (*IDH1*), a metabolic protein required for conversion of isocitrate to a-ketoglutamate during the citric acid cycle, is frequently observed in pro-neural glioblastomas (see section on glioblastoma predisposition syndromes). The molecular basis of how this mutation contributes to the cancer phenotype remains an active area of investigation.

Classical (also termed proliferative by some authors) constitutes the second molecular subtype. Transcript signature in the classical subtype resembles those observed in transit amplifying neural progenitor cells55 and murine astrocytes12. This subtype is exclusively found in WHO grade IV tumors and constitutes a form of primary glioblastoma57. Molecularly, this subtype is characterized by amplification of (or activating mutations in) EGFR and CDKN2A (p16Ink4a). Genes involved in pathways highly active in neural stem and progenitor cells (including the Notch and Sonic hedgehog pathway) are highly expressed in the classical subtype).58 The patients afflicted are typically older than those with the proneural subtype. Relative to the other subtype, patients afflicted with the classical subtype exhibit the worst prognosis, but the best therapeutic response to concurrent radiation/temozolomide treatment.

The mesenchymal subtype makes up the final category. The transcript signature in the mesenchymal subtype mirrors those observed in the neural stem cells of the forebrain55 and cultured astroglial cells59. Most cultured glioblastoma cell lines exhibit transcript signatures that fall into this subtype. Molecularly, the subtype is characterized by inactivating NF1 and PTEN mutations12. This subgroup also has the highest expression of angiogenesis markers including VEGF (Vascular Epithelial Growth Factor) transcripts and highest density of microvascular proliferation12. The patients afflicted are typically older than those with the pro-neural subtype. Relative to the other subtypes, mesenchymal glioblastomas exhibit clinical response similar to the classical subtype, and a trend toward slightly improved prognosis and response to radiation/temozolomide therapy12.

There is significant debate with regards to the origin of the distinct molecular subtypes. On one extreme is the thought that the subtypes originate from the same cell type with differences driven by distinct signaling pathways. The other extreme suggests that subtypes are determined by the same signaling pathways activated in a different cell of origin. The observation that the same canonical pathways are altered irrespective of subtype would tend to support the latter hypothesis. However, it is conceivable that different genes thought to participate in the same canonical pathway may modulate processes distinct of that pathway. Such functions may contribute to the distinct molecular subtypes. Still, it is conceivable that differences in signaling and cell of origin both contribute to subtype formation. This critical debate awaits experimental resolution.

#### **7. Summary**

32 Glioma – Exploring Its Biology and Practical Relevance

of subtypes varies depending on the study, however, three subtypes consistently appear across independent studies and reflect distinct biologic and clinical behaviors 12, 55, 56. Importantly, the transcript signature parallels those obtained during distinct stages in neural development, suggesting the tumor may have arisen from different stages of

The first subtype is termed pro-neural. The transcript signature resembles those of neuroblasts and oligodendrocytes derived from fetal and adult brain55. This subtype harbors molecular and clinical features that closely mirror those previously classified as secondary glioblastomas. Molecularly, pro-neural glioblastomas harbor mutations classically associated with the secondary subtype, including p53 and PDGFR12. Accordingly, grade II and III gliomas harbor molecular signatures most reminiscent of the pro-neural subtype55. Clinically, this subtype typically affects younger patients, is associated with improved overall survival55, and responds poorly to concurrent radiation/temozolomide treatment upon disease progression12. Interestingly, mutations in the isocitrate **d**e**h**ydrogenase 1 gene (*IDH1*), a metabolic protein required for conversion of isocitrate to a-ketoglutamate during the citric acid cycle, is frequently observed in pro-neural glioblastomas (see section on glioblastoma predisposition syndromes). The molecular basis of how this mutation

Classical (also termed proliferative by some authors) constitutes the second molecular subtype. Transcript signature in the classical subtype resembles those observed in transit amplifying neural progenitor cells55 and murine astrocytes12. This subtype is exclusively found in WHO grade IV tumors and constitutes a form of primary glioblastoma57. Molecularly, this subtype is characterized by amplification of (or activating mutations in) EGFR and CDKN2A (p16Ink4a). Genes involved in pathways highly active in neural stem and progenitor cells (including the Notch and Sonic hedgehog pathway) are highly expressed in the classical subtype).58 The patients afflicted are typically older than those with the proneural subtype. Relative to the other subtype, patients afflicted with the classical subtype exhibit the worst prognosis, but the best therapeutic response to concurrent

The mesenchymal subtype makes up the final category. The transcript signature in the mesenchymal subtype mirrors those observed in the neural stem cells of the forebrain55 and cultured astroglial cells59. Most cultured glioblastoma cell lines exhibit transcript signatures that fall into this subtype. Molecularly, the subtype is characterized by inactivating NF1 and PTEN mutations12. This subgroup also has the highest expression of angiogenesis markers including VEGF (Vascular Epithelial Growth Factor) transcripts and highest density of microvascular proliferation12. The patients afflicted are typically older than those with the pro-neural subtype. Relative to the other subtypes, mesenchymal glioblastomas exhibit clinical response similar to the classical subtype, and a trend toward slightly improved

There is significant debate with regards to the origin of the distinct molecular subtypes. On one extreme is the thought that the subtypes originate from the same cell type with differences driven by distinct signaling pathways. The other extreme suggests that subtypes are determined by the same signaling pathways activated in a different cell of origin. The observation that the same canonical pathways are altered irrespective of subtype would tend to support the latter hypothesis. However, it is conceivable that different genes thought to participate in the same canonical pathway may modulate processes distinct of that

contributes to the cancer phenotype remains an active area of investigation.

prognosis and response to radiation/temozolomide therapy12.

neurogenesis55.

radiation/temozolomide treatment.

The past three decades of work in cancer research has generated a sophisticated conceptual framework for the process of neoplastic transformation. The framework suggests that genetic and epigenetic events inactivating critical pathways that regulate several key aspects of cellular function are an etiology. These cellular functions can be categorized as selfsufficiency in growth signaling, evasion of apoptosis, insensitivity to anti-growth signals, tissue invasion, and limitless replicative potential and angiogenesis. This framework has largely been validated by a large scale, high-throughput characterization of the genomic and epigenomic landscape in glioblastomas. The picture emerging from these analyses suggests that most glioblastomas evolve along a multitude of pathways in response to differing selective pressures to achieve the cancer phenotypes. Transcript based analysis revealed distinct subtypes with potential implications with regards to the cell of origin. The dynamic interplay of growth dysregulation and the cell of origin during the neoplastic transformation process harbors vital implications with regards to therapeutic development.

#### **8. References**


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**3** 

*México* 

**Biological Markers of Recurrence** 

Alfonso Marhx-Bracho2 and Julio Sotelo1

*2Neurosurgery Department, Instituto Nacional de Pediatría 3Hospital General Naval de Alta Especialidad, Armada de México* 

**and Survival of High-Grade Gliomas:** 

**The Role of Hepatocyte Growth Factor** 

Roberto García-Navarrete1,2,3, Esperanza García Mendoza1,

*1Neuroimmunology Unit, Instituto Nacional de Neurología y Neurocirugía* 

Malignant gliomas – the most frequent glial tumor of Central Nervous System (CNS) anaplasic astrocytoma and glioblastoma multiforme, are regarded by the World Health Organization as the form of cancer with the worst prognosis in humans. Its biological behavior and severity are associated with increased concentrations of various growth factors, like fibroblastic growth factor (FGF), vascular endothelial growth factor (VEGF),

Hepatocyte growth factor (HGF) is a pleomorphic protein with several properties. It was described in 1996 as a protein related to cell proliferation and motility in the rat liver. It has also been associated with morphogenesis of the central nervous system in mammals. HGF has been associated with proliferation of several cell lines, for example carcinoma of colon, stomach, gallbladder, pancreas, and breast. In human gliomas high intratumoral concentrations of HGF and its receptor c-met are associated with poor prognosis; it has also been associated with long-time recurrence of meningioma. In vitro, transfer of the HGF gene increases tumorigenicity, growth, and angiogenesis; interestingly, inhibition of this gene

Human studies have shown that HGF contents in blood (Wen et al. 2011) are closely related with malignancy of glioma; low-grade glioma shows a lower intratumoral concentration of

Recently, we have found HGF directly related in human gliomas to increased angiogenesis, cellular proliferation, resistance to apoptosis induced by gamma radiation, and invasion of healthy tissue along white matter tracts. All of these features are characteristic of

In the clinical setting, high HGF levels in cerebrospinal fluid predict mortality and a short disease-free time in patients with malignant glioma, and helps to explain the great variance observed on survival of patients with malignant glioma, suggesting that HGF inhibition strategies could be a useful means of improving survival and disease-free time among

platelet-derived growth factor (PDGF) and hepatocyte growth factor (HGF).

reduces growth rate and malignancy in experimentally induced-glioma in rats.

**1. Introduction** 

HGF than high-grade glioma.

malignancy.

glioma patients.


## **Biological Markers of Recurrence and Survival of High-Grade Gliomas: The Role of Hepatocyte Growth Factor**

Roberto García-Navarrete1,2,3, Esperanza García Mendoza1, Alfonso Marhx-Bracho2 and Julio Sotelo1

*1Neuroimmunology Unit, Instituto Nacional de Neurología y Neurocirugía 2Neurosurgery Department, Instituto Nacional de Pediatría 3Hospital General Naval de Alta Especialidad, Armada de México México* 

#### **1. Introduction**

36 Glioma – Exploring Its Biology and Practical Relevance

[53] Nutt CL, Mani DR, Betensky RA, et al. Gene expression-based classification of

[54] Liang Y, Diehn M, Watson N, et al. Gene expression profiling reveals molecularly and

[55] Phillips HS, Kharbanda S, Chen R, et al. Molecular subclasses of high-grade glioma

[56] Brennan C, Momota H, Hambardzumyan D, et al. Glioblastoma subclasses can be

[57] Mischel PS, Shai R, Shi T, et al. Identification of molecular subtypes of glioblastoma by

[58] Bar EE, Chaudhry A, Lin A, et al. Cyclopamine-mediated hedgehog pathway inhibition

[59] Gunther HS, Schmidt NO, Phillips HS, et al. Glioblastoma-derived stem cell-enriched

gene expression profiling. *Oncogene.* Apr 17 2003;22(15):2361-2373.

*Cancer Res.* Apr 1 2003;63(7):1602-1607.

alterations. *PLoS One.* 2009;4(11):e7752.

*Oncogene.* May 1 2008;27(20):2897-2909.

in neurogenesis. *Cancer Cell.* Mar 2006;9(3):157-173.

Apr 19 2005;102(16):5814-5819.

2533.

malignant gliomas correlates better with survival than histological classification.

clinically distinct subtypes of glioblastoma multiforme. *Proc Natl Acad Sci U S A.* 

predict prognosis, delineate a pattern of disease progression, and resemble stages

defined by activity among signal transduction pathways and associated genomic

depletes stem-like cancer cells in glioblastoma. *Stem Cells.* Oct 2007;25(10):2524-

cultures form distinct subgroups according to molecular and phenotypic criteria.

Malignant gliomas – the most frequent glial tumor of Central Nervous System (CNS) anaplasic astrocytoma and glioblastoma multiforme, are regarded by the World Health Organization as the form of cancer with the worst prognosis in humans. Its biological behavior and severity are associated with increased concentrations of various growth factors, like fibroblastic growth factor (FGF), vascular endothelial growth factor (VEGF), platelet-derived growth factor (PDGF) and hepatocyte growth factor (HGF).

Hepatocyte growth factor (HGF) is a pleomorphic protein with several properties. It was described in 1996 as a protein related to cell proliferation and motility in the rat liver. It has also been associated with morphogenesis of the central nervous system in mammals. HGF has been associated with proliferation of several cell lines, for example carcinoma of colon, stomach, gallbladder, pancreas, and breast. In human gliomas high intratumoral concentrations of HGF and its receptor c-met are associated with poor prognosis; it has also been associated with long-time recurrence of meningioma. In vitro, transfer of the HGF gene increases tumorigenicity, growth, and angiogenesis; interestingly, inhibition of this gene reduces growth rate and malignancy in experimentally induced-glioma in rats.

Human studies have shown that HGF contents in blood (Wen et al. 2011) are closely related with malignancy of glioma; low-grade glioma shows a lower intratumoral concentration of HGF than high-grade glioma.

Recently, we have found HGF directly related in human gliomas to increased angiogenesis, cellular proliferation, resistance to apoptosis induced by gamma radiation, and invasion of healthy tissue along white matter tracts. All of these features are characteristic of malignancy.

In the clinical setting, high HGF levels in cerebrospinal fluid predict mortality and a short disease-free time in patients with malignant glioma, and helps to explain the great variance observed on survival of patients with malignant glioma, suggesting that HGF inhibition strategies could be a useful means of improving survival and disease-free time among glioma patients.

Biological Markers of Recurrence and

glioblastoma patients (Lois et al., 2007).

**3. Biological markers of glioblastoma activity** 

for surveillances of tumor activity by measuring their contents in serum.

growth and migration induced by EGF on human glioma cells (Ji et al., 2010).

with prognosis.

(Hormingo et al. 2006).

**3.1 Growth factors** 

malignant gliomas.

**3.2 Vascular endothelial growth factor** 

glioma cells are minor (Reux et al., 2006).

and angiogenesis (Mentlein et al., 2004; Reux et al., 2006).

Survival of High-Grade Gliomas: The Role of Hepatocyte Growth Factor 39

There is no consistent correlation of epidermal growth factor receptor (EGFR) amplification with survival largely irrespective of the age at first clinical manifestation. LOH 10 (Lois et al., 2007) is the most frequent genetic alteration in glioblastoma and is associated with reduced survival. The presence of PTEN mutations is not associated with prognosis of

Since the initial histological description of astrocytic neoplasms, several efforts have been made to identify biomarkers that could predict the biological behavior of the tumor. However, to date only few peptides been identified substances that show a weak association

The following paragraphs describe some substances that have been reported as candidates

A molecular event determining the development of malignancy is the activation of bcatenin, a protein necessary for the alignment and maintenance of epithelial cells by regulating cell growth and cell adhesion. The coexpression of -catenin reduces the cellular

A secreted protein of unknown function, YKL-40 (chitinase-3-like-1), is overexpressed in glioblastoma [4], its presence is associated with LOH 10q (Lois et al., 2007), poorer radiation response, shorter time to tumor progression and reduced overall survival (Ohgaki et al., 2004). It is typically coexpressed with matrix metalloproteinase-9 (MMP-9), and its detection in serum has been used to monitor patients with recurrent tumor growth (Pelloski et al., 2005). One report showed that increased expression of GD3 synthase mRNA, in combination with decreased GalNAcT, correlate with an increased survival of patients with glioblastoma

The expression of growth factors and their receptors are associated with glioma malignancy. Thus, their potential therapeutic importance has been demonstrated using specific inhibitors of growth factors in experimental and clinical studies. However, recent results have shown that glioma cells are resistant to this treatment and illustrate the therapeutic difficulties in

Vascular endothelial growth factor (VEGF) is a signal protein that stimulates vasculogenesis and angiogenesis; VEGF's normal function is to induce growth of vessels during early developmental stages, after injury, at muscle following exercise, and to generate new vessels to bypass blocked arteries. When VEGF is overexpressed, it can contribute to malignant glioma progression. Cancers that express VEGF grow and metastasize, VEGF belongs to platelet-derived growth factor family. They are involved in both, vasculogenesis, the novo,

Within the major growth factors related to angiogenesis, VEGF is one of the most important. In several tumors, VEGF plays a pivotal role for vascularization necessary to supply the malignant tissue with oxygen and nutrients. Human glioma cells are characterized by high production of VEGF, however, functional and autocrine growth stimulatory effects on

Thus, experimental and clinical findings suggest that HGF is a good target for therapeutic strategies with pharmacogenomic methods and could be useful as a biological marker for monitoring malignant gliomas activity.

### **2. Malignant glioma**

Intracranial neoplasms include a great diversity of tumors with different histopathologic origins, prognoses and treatments: Malignant gliomas such as anaplasic astrocytoma (AA) and glioblastoma multiforme (GM) are the most frequent glial tumors: their incidence is 4/100,000, and they account for 2% of all malignant tumors in adults. Malignant gliomas are associated with poor prognosis; the mean survival time of patients with GM is one year, this gloomy picture has not changed significantly for the last three decades. Similarly, the survival for patients with AA is minor than three years. Therefore, it is of paramount importance to understand the pathophysiology of malignant glial tumors and identify prognostic factors. Both GM and AA have high proliferation and intense vascularity, features closely related with malignant cell growth.

Malignant conditions are related to ability of malignant cells to produce growth factors such as vascular endothelial growth factor (VEGF), platelet derived growth factor (PDGF), and fibroblastic growth factor (FGF) (Arrieta et al., 2002).

Due to their invasive nature, glioblastomas cannot be resected completely by surgery and, despite the progress of neurosurgical techniques and radio/chemotherapy, less than a half of patients survive more than a year, aged subjects have the most significant adverse prognostic factor.

Glioblastoma is the most frequent malignant tumor of the brain, it account for approximately 12–15% of all intracranial neoplasms and 60-75% of astrocytic tumors (Lantos et al., 2002; Lois et al., 2007). In most European and North American countries, the yearly incidence is in the range of 3-4 new cases per 100 000 population (Lois et al., 2007).

#### **2.1 Prognostic factors**

Despite progress in surgery, radiotherapy and chemotherapy of brain tumors, the overall survival of patients with glioblastoma remains dismal. Population-based studies from Switzerland and Canada have shown that less than 20% of patients survive more than one year after diagnosis and less than 3% lived longer than 3 years (Lantos et al., 2002; Ohgaki et al., 2007). Clinical trials show a slightly better prognosis, with median survival rates of approximately 12 month; however, they have strong bias toward the recruitment of younger patients and those with higher preoperative Karnofsky performance scores, both are strong predictors of a more favorable clinical outcome.

Virtually all therapy trials have shown that younger glioblastoma patients (<50 years at diagnosis) have a significantly better prognosis (Lois et al., 2007). In a large populationbased study, age was the most significant prognostic factor; persisting through all age groups in a linear manner (Ohgaki et al., 2007). Patients with secondary glioblastoma survived significantly longer than those with primary glioblastoma, but this is likely due to their age rather than a reflection of a different biological behavior.

The prognostic value of TP53 mutations in glioblastomas is controversial, it either shows no association or the presence of TP53 mutations was a favorable prognostic factor. In a large population-based study, the presence of TP53 mutations was predictive of longer survival but this was not significant when adjusted for younger age.

There is no consistent correlation of epidermal growth factor receptor (EGFR) amplification with survival largely irrespective of the age at first clinical manifestation. LOH 10 (Lois et al., 2007) is the most frequent genetic alteration in glioblastoma and is associated with reduced survival. The presence of PTEN mutations is not associated with prognosis of glioblastoma patients (Lois et al., 2007).

Since the initial histological description of astrocytic neoplasms, several efforts have been made to identify biomarkers that could predict the biological behavior of the tumor. However, to date only few peptides been identified substances that show a weak association with prognosis.

### **3. Biological markers of glioblastoma activity**

The following paragraphs describe some substances that have been reported as candidates for surveillances of tumor activity by measuring their contents in serum.

A molecular event determining the development of malignancy is the activation of bcatenin, a protein necessary for the alignment and maintenance of epithelial cells by regulating cell growth and cell adhesion. The coexpression of -catenin reduces the cellular growth and migration induced by EGF on human glioma cells (Ji et al., 2010).

A secreted protein of unknown function, YKL-40 (chitinase-3-like-1), is overexpressed in glioblastoma [4], its presence is associated with LOH 10q (Lois et al., 2007), poorer radiation response, shorter time to tumor progression and reduced overall survival (Ohgaki et al., 2004). It is typically coexpressed with matrix metalloproteinase-9 (MMP-9), and its detection in serum has been used to monitor patients with recurrent tumor growth (Pelloski et al., 2005). One report showed that increased expression of GD3 synthase mRNA, in combination with decreased GalNAcT, correlate with an increased survival of patients with glioblastoma (Hormingo et al. 2006).

#### **3.1 Growth factors**

38 Glioma – Exploring Its Biology and Practical Relevance

Thus, experimental and clinical findings suggest that HGF is a good target for therapeutic strategies with pharmacogenomic methods and could be useful as a biological marker for

Intracranial neoplasms include a great diversity of tumors with different histopathologic origins, prognoses and treatments: Malignant gliomas such as anaplasic astrocytoma (AA) and glioblastoma multiforme (GM) are the most frequent glial tumors: their incidence is 4/100,000, and they account for 2% of all malignant tumors in adults. Malignant gliomas are associated with poor prognosis; the mean survival time of patients with GM is one year, this gloomy picture has not changed significantly for the last three decades. Similarly, the survival for patients with AA is minor than three years. Therefore, it is of paramount importance to understand the pathophysiology of malignant glial tumors and identify prognostic factors. Both GM and AA have high proliferation and intense vascularity,

Malignant conditions are related to ability of malignant cells to produce growth factors such as vascular endothelial growth factor (VEGF), platelet derived growth factor (PDGF), and

Due to their invasive nature, glioblastomas cannot be resected completely by surgery and, despite the progress of neurosurgical techniques and radio/chemotherapy, less than a half of patients survive more than a year, aged subjects have the most significant adverse

Glioblastoma is the most frequent malignant tumor of the brain, it account for approximately 12–15% of all intracranial neoplasms and 60-75% of astrocytic tumors (Lantos et al., 2002; Lois et al., 2007). In most European and North American countries, the yearly

Despite progress in surgery, radiotherapy and chemotherapy of brain tumors, the overall survival of patients with glioblastoma remains dismal. Population-based studies from Switzerland and Canada have shown that less than 20% of patients survive more than one year after diagnosis and less than 3% lived longer than 3 years (Lantos et al., 2002; Ohgaki et al., 2007). Clinical trials show a slightly better prognosis, with median survival rates of approximately 12 month; however, they have strong bias toward the recruitment of younger patients and those with higher preoperative Karnofsky performance scores, both are strong

Virtually all therapy trials have shown that younger glioblastoma patients (<50 years at diagnosis) have a significantly better prognosis (Lois et al., 2007). In a large populationbased study, age was the most significant prognostic factor; persisting through all age groups in a linear manner (Ohgaki et al., 2007). Patients with secondary glioblastoma survived significantly longer than those with primary glioblastoma, but this is likely due to

The prognostic value of TP53 mutations in glioblastomas is controversial, it either shows no association or the presence of TP53 mutations was a favorable prognostic factor. In a large population-based study, the presence of TP53 mutations was predictive of longer survival

incidence is in the range of 3-4 new cases per 100 000 population (Lois et al., 2007).

monitoring malignant gliomas activity.

features closely related with malignant cell growth.

fibroblastic growth factor (FGF) (Arrieta et al., 2002).

predictors of a more favorable clinical outcome.

their age rather than a reflection of a different biological behavior.

but this was not significant when adjusted for younger age.

**2. Malignant glioma** 

prognostic factor.

**2.1 Prognostic factors** 

The expression of growth factors and their receptors are associated with glioma malignancy. Thus, their potential therapeutic importance has been demonstrated using specific inhibitors of growth factors in experimental and clinical studies. However, recent results have shown that glioma cells are resistant to this treatment and illustrate the therapeutic difficulties in malignant gliomas.

#### **3.2 Vascular endothelial growth factor**

Vascular endothelial growth factor (VEGF) is a signal protein that stimulates vasculogenesis and angiogenesis; VEGF's normal function is to induce growth of vessels during early developmental stages, after injury, at muscle following exercise, and to generate new vessels to bypass blocked arteries. When VEGF is overexpressed, it can contribute to malignant glioma progression. Cancers that express VEGF grow and metastasize, VEGF belongs to platelet-derived growth factor family. They are involved in both, vasculogenesis, the novo, and angiogenesis (Mentlein et al., 2004; Reux et al., 2006).

Within the major growth factors related to angiogenesis, VEGF is one of the most important. In several tumors, VEGF plays a pivotal role for vascularization necessary to supply the malignant tissue with oxygen and nutrients. Human glioma cells are characterized by high production of VEGF, however, functional and autocrine growth stimulatory effects on glioma cells are minor (Reux et al., 2006).

Biological Markers of Recurrence and

2000; Arrieta et al., 2002).

Rac and CDC (Arrieta et al., 2002).

**3.2.2.1 Hepatocyte growth factor and malignant gliomas** 

survival (Abounander et al, 1999, 2002; Kim et al, 2006).

radiotherapy (Lal et al, 2005; Chu et al, 2006).

therapeutics.

Survival of High-Grade Gliomas: The Role of Hepatocyte Growth Factor 41

also been recently proposed due to mutations in the catalytic domain of c-Met from patients with renal carcinoma. Overexpression of HGF is present in various cells lines of leukemia and lymphoma and in solid tumors of the breast, prostate, colon, liver, kidney, uterine cervix, endometrium, and bladder (Arrieta et al., 2002). Hepatocyte growth factor also promotes adhesion and migration of cancer cells, due to the high affinity of integrins to their ligands, a phenomenon related to the metastatic tendency of carcinomas (Trussolino et al.,

Normal human astrocytes express HGF and its receptor c-Met (Yamada et al, 1994). Met is a proto-oncogene that when mutated can transform a variety of cell types; the Met receptor is a heterodimer consisting of an extracellular alpha chain and a trans-membrane beta chain, which is a tyrosine kinase, it is widely expressed by epithelial and endothelial cells as well as melanocytes, chondrocytes, skeletal muscle, hematopoietic, lymphoid, and neural cells. The activation of Met by HGF binding is linked to cell growth and survival, including the avoidance of anoikis which is apoptosis induced by insufficient association with cell-matrix, through activation of both the PI3-kinase/PDK/Akt and the Ras/Raf/MEK/ERK pathways and to cell mobility and cytoskeletal organization via activation of the Rho-GTPases, Rho,

Activation of Met tyrosine kinase also activates phospholipase C, resulting in the elevation of intracellular calcium and activation of conventional and novel protein kinase C pathways. HGF and Met have been associated with progression, invasiveness and metastasis in a number of neoplasms. Met is expressed in a wide variety of carcinomas, musculoskeletal tumors, soft tissue sarcomas, glioblastoma, astrosarcoma, and several hematopoietic malignancies. HGF Met signaling is a major potential target for the development of cancer

As HGF, its receptor c-met has been implicated in the genesis, malignant progression, and chemo/radioresistance of multiple human malignancies, including gliomas (Peruzzi et al, 2006; Carapancea et al, 2009; Hadjipanayis et al, 2009a, 2009b). Experimental studies using transient expression of anti-SF/HGF and anti-c-met U1snRNA/ribozymes suppress SF/HGF and c-met expression, c-met receptor activation, tumor cell migration, and anchorage-independent colony formation in vitro. The delivery of U1snRNA/ribozymes to established subcutaneous glioma xenografts via liposome-DNA complexes significantly inhibited tumor growth as well as tumor SF/HGF and c-met expression levels. Histological analysis of tumors treated showed a significant decrease in blood vessel density, increase in activation of the pro-apoptotic enzyme caspase-3, and increase in tumor cell apoptosis. Treatment of animals bearing intracranial glioma xenografts with anti-SF/HGF and anti-cmet U1snRNA/ribozymes substantially inhibited tumor growth and promoted animal

The use of monoclonal antibodies against the NK23 and NK422 domains of the HGF reduce tumor growth and mitotic rate (Bhargava et al., 1992; Boros et al., 1995; Kimura et al., 1995; Miwa et al., 1997; Neaud et al., 1997; Takeuchi et al 1997; Stella et al., 1999; Grierson et al., 2000; Cao et al, 2001; Brockmann et al, 2003; Burgess et al, 2006); Also, viral transgenes against HGF-RNA reduce invasion of white matter tracts, improving response to

The therapeutic efficacy of SGX523 has recently been proven in human brain tumors. It seems that SGX523 inhibits c-Met, AKT and MAPK phosphorylation, cell proliferation, cell

In recurrent GBM trials with temozolomide shown a poor therapeutic response where as VEGF inhibitors as bevacizumab, improve the response rate by 25% to 74%, and the periodfree of symptoms increases by 32% to 64%, which is superior to the rate reported for temozolomide alone (Pope et al., 2006; Guiu et al., 2008; Narayana et al., 2009; Nghiemphu et al., 2009; Poulsen et al., 2009; Zuniga et al., 2009). The main effect of VEGF inhibitors is centered on rapid reduction in peritumoral edema, improving corticosteroid use. These studies also indicated that bevacizumab treatment is well tolerated and the risk of intratumoral hemorrhage is low. Toxicity related to bevacizumab therapy in patients with malignant glioma includes hypertension, proteinuria, fatigue, thromboembolic events, and wound-healing delay.

#### **3.2.1 Epidermal growth factor**

Epidermal growth factor (EGF), is a prototype member of the EGF-family of peptides which have highly similar structural and functional characteristics. Other peptides include: Transforming Growth Factor- (TGF-), amphiregulin, epiregulin, and neuregulin 1-4, all of them related to tyrosine kinase activity which initiates a signal transduction cascade that result in several changes: rise in intracellular calcium contents, increased glycolysis, protein synthesis, DNA synthesis and cell proliferation (Fallon et al., 1984).

EGF is overexpressed in various cancers; malignant glioma, breast, pancreas and liver carcinoma, indicating its main role in malignant cell transformation, tumor occurrence and growth by promoting cell division (Xian et al., 2001). Recent reports show that +61G polymorphism of EGF gene increase the risk for glioma development in European subjects but are a protective factor in Chinese subjects (Tan et al., 2010).

The Epidermal growth factor receptor (EGFR) gene is amplified and overexpressed in approximately 40% of patients with primary GBMs. Increased EGFR signaling drives tumor cell proliferation, invasiveness, motility, angiogenesis, and inhibition of apoptosis. Attempts to identify biomarkers to help predict response to EGFR inhibitors have yielded conflicting results. Currently, there is no convincing evidence of a correlation between EGFR expression in tumoral tissue and prognosis (Van Meir et al., 2010).

#### **3.2.2 Hepatocyte growth factor**

Hepatocyte growth factor (HGF), also called scatter factor, is a multifunction protein with strong mitogenic effect on hepatocytes. It was initially isolated as a peptide related to hepatic regeneration. It is considered a reliable indicator of hepatic function alter hepatectomy. This protein is constituted by a heavy chain (60 kD) with four domains and a Light chain (32 kD); it binds through its tirosine-kinase receptor, a product of the protooncogene c-Met. Hepatocyte growth factor, secreted by mesenchymal cells, acts as a paracrine effector on different epithelial cells inducing mitogenesis and stimulating cellular motility. It is also a powerful angiogenic factor for endothelial cells in vitro and in vivo. In the liver and kidney, it may have a role as antiapoptotic (Xiao et al., 2001). It is also necessary for embriogenesis as regulator of cell migration and growth. Hepatocyte growth factor is also produced by other cells, such as osteoclasts, participating in the regulation of bone remodeling; its production by monocytes has a role in the regulation of hematopoyesis by stimulation of growth and differentiation of erythroid precursors (Arrieta et al., 2002).

Knockout mice for the HGF gene develop severe abnormalities in the liver, placenta, and nervous system causing fetal death. A direct genetic relation between HGF and cancer has

In recurrent GBM trials with temozolomide shown a poor therapeutic response where as VEGF inhibitors as bevacizumab, improve the response rate by 25% to 74%, and the periodfree of symptoms increases by 32% to 64%, which is superior to the rate reported for temozolomide alone (Pope et al., 2006; Guiu et al., 2008; Narayana et al., 2009; Nghiemphu et al., 2009; Poulsen et al., 2009; Zuniga et al., 2009). The main effect of VEGF inhibitors is centered on rapid reduction in peritumoral edema, improving corticosteroid use. These studies also indicated that bevacizumab treatment is well tolerated and the risk of intratumoral hemorrhage is low. Toxicity related to bevacizumab therapy in patients with malignant glioma includes hypertension, proteinuria, fatigue, thromboembolic events, and

Epidermal growth factor (EGF), is a prototype member of the EGF-family of peptides which have highly similar structural and functional characteristics. Other peptides include: Transforming Growth Factor- (TGF-), amphiregulin, epiregulin, and neuregulin 1-4, all of them related to tyrosine kinase activity which initiates a signal transduction cascade that result in several changes: rise in intracellular calcium contents, increased glycolysis, protein

EGF is overexpressed in various cancers; malignant glioma, breast, pancreas and liver carcinoma, indicating its main role in malignant cell transformation, tumor occurrence and growth by promoting cell division (Xian et al., 2001). Recent reports show that +61G polymorphism of EGF gene increase the risk for glioma development in European subjects

The Epidermal growth factor receptor (EGFR) gene is amplified and overexpressed in approximately 40% of patients with primary GBMs. Increased EGFR signaling drives tumor cell proliferation, invasiveness, motility, angiogenesis, and inhibition of apoptosis. Attempts to identify biomarkers to help predict response to EGFR inhibitors have yielded conflicting results. Currently, there is no convincing evidence of a correlation between EGFR expression

Hepatocyte growth factor (HGF), also called scatter factor, is a multifunction protein with strong mitogenic effect on hepatocytes. It was initially isolated as a peptide related to hepatic regeneration. It is considered a reliable indicator of hepatic function alter hepatectomy. This protein is constituted by a heavy chain (60 kD) with four domains and a Light chain (32 kD); it binds through its tirosine-kinase receptor, a product of the protooncogene c-Met. Hepatocyte growth factor, secreted by mesenchymal cells, acts as a paracrine effector on different epithelial cells inducing mitogenesis and stimulating cellular motility. It is also a powerful angiogenic factor for endothelial cells in vitro and in vivo. In the liver and kidney, it may have a role as antiapoptotic (Xiao et al., 2001). It is also necessary for embriogenesis as regulator of cell migration and growth. Hepatocyte growth factor is also produced by other cells, such as osteoclasts, participating in the regulation of bone remodeling; its production by monocytes has a role in the regulation of hematopoyesis by stimulation of growth and differentiation of erythroid precursors (Arrieta et al., 2002). Knockout mice for the HGF gene develop severe abnormalities in the liver, placenta, and nervous system causing fetal death. A direct genetic relation between HGF and cancer has

synthesis, DNA synthesis and cell proliferation (Fallon et al., 1984).

but are a protective factor in Chinese subjects (Tan et al., 2010).

in tumoral tissue and prognosis (Van Meir et al., 2010).

wound-healing delay.

**3.2.1 Epidermal growth factor** 

**3.2.2 Hepatocyte growth factor** 

also been recently proposed due to mutations in the catalytic domain of c-Met from patients with renal carcinoma. Overexpression of HGF is present in various cells lines of leukemia and lymphoma and in solid tumors of the breast, prostate, colon, liver, kidney, uterine cervix, endometrium, and bladder (Arrieta et al., 2002). Hepatocyte growth factor also promotes adhesion and migration of cancer cells, due to the high affinity of integrins to their ligands, a phenomenon related to the metastatic tendency of carcinomas (Trussolino et al., 2000; Arrieta et al., 2002).

Normal human astrocytes express HGF and its receptor c-Met (Yamada et al, 1994). Met is a proto-oncogene that when mutated can transform a variety of cell types; the Met receptor is a heterodimer consisting of an extracellular alpha chain and a trans-membrane beta chain, which is a tyrosine kinase, it is widely expressed by epithelial and endothelial cells as well as melanocytes, chondrocytes, skeletal muscle, hematopoietic, lymphoid, and neural cells. The activation of Met by HGF binding is linked to cell growth and survival, including the avoidance of anoikis which is apoptosis induced by insufficient association with cell-matrix, through activation of both the PI3-kinase/PDK/Akt and the Ras/Raf/MEK/ERK pathways and to cell mobility and cytoskeletal organization via activation of the Rho-GTPases, Rho, Rac and CDC (Arrieta et al., 2002).

Activation of Met tyrosine kinase also activates phospholipase C, resulting in the elevation of intracellular calcium and activation of conventional and novel protein kinase C pathways. HGF and Met have been associated with progression, invasiveness and metastasis in a number of neoplasms. Met is expressed in a wide variety of carcinomas, musculoskeletal tumors, soft tissue sarcomas, glioblastoma, astrosarcoma, and several hematopoietic malignancies. HGF Met signaling is a major potential target for the development of cancer therapeutics.

#### **3.2.2.1 Hepatocyte growth factor and malignant gliomas**

As HGF, its receptor c-met has been implicated in the genesis, malignant progression, and chemo/radioresistance of multiple human malignancies, including gliomas (Peruzzi et al, 2006; Carapancea et al, 2009; Hadjipanayis et al, 2009a, 2009b). Experimental studies using transient expression of anti-SF/HGF and anti-c-met U1snRNA/ribozymes suppress SF/HGF and c-met expression, c-met receptor activation, tumor cell migration, and anchorage-independent colony formation in vitro. The delivery of U1snRNA/ribozymes to established subcutaneous glioma xenografts via liposome-DNA complexes significantly inhibited tumor growth as well as tumor SF/HGF and c-met expression levels. Histological analysis of tumors treated showed a significant decrease in blood vessel density, increase in activation of the pro-apoptotic enzyme caspase-3, and increase in tumor cell apoptosis. Treatment of animals bearing intracranial glioma xenografts with anti-SF/HGF and anti-cmet U1snRNA/ribozymes substantially inhibited tumor growth and promoted animal survival (Abounander et al, 1999, 2002; Kim et al, 2006).

The use of monoclonal antibodies against the NK23 and NK422 domains of the HGF reduce tumor growth and mitotic rate (Bhargava et al., 1992; Boros et al., 1995; Kimura et al., 1995; Miwa et al., 1997; Neaud et al., 1997; Takeuchi et al 1997; Stella et al., 1999; Grierson et al., 2000; Cao et al, 2001; Brockmann et al, 2003; Burgess et al, 2006); Also, viral transgenes against HGF-RNA reduce invasion of white matter tracts, improving response to radiotherapy (Lal et al, 2005; Chu et al, 2006).

The therapeutic efficacy of SGX523 has recently been proven in human brain tumors. It seems that SGX523 inhibits c-Met, AKT and MAPK phosphorylation, cell proliferation, cell

Biological Markers of Recurrence and

et al., 1999).

specific gene for HGF.

**5.Conclusions** 

**6. References** 

with controls (Wen et al., 2011)

Survival of High-Grade Gliomas: The Role of Hepatocyte Growth Factor 43

peritumoral edema, independent of vascular density. Previous studies have shown that HGF increases the permeability of the hematoencephalic barrier, independently of VEGF expression, possibly by the induction of endothelial fenestrations and by the tumoral expression of proteases such as urokinase and extracellular matrix metalloproteinases (Book

A paracrine loop for HGF effects related with migration of tumor cells along white matter has been described. The increase of HGF in CSF observed may therefore reflect either the transport of HGF from brain parenchyma to the ventricular system or the diffusion of HGF

HGF concentration is closely related with malignancy of glioma; low-grade glioma shows a lower intratumoral concentration of HGF than high-grade glioma. CSF concentrations of HGF greater than 850 pg/ml prior to surgery was predictive of a shorter disease-free time among malignant glioma patients than was observed for patients with a lower concentration (6 ± 0.6 months (95% [CI], 5–7) vs. 9 ± 0.5 months (95% [CI], 8–10), respectively, p< 0.001), besides total-gross resection surgery (Garcia-Navarrete et al., 2010). CSF concentration of HGF shows a negative correlation with survival of patients with malignant glioma and explains with high certainty the variance for survival. This suggests that HGF could be a good target candidate for molecular therapy such as RNA interference, by silencing the

Although HGF seems a good target for therapeutic attempts, a phase II study reported the use of a monoclonal antibody against HGF (AMD 102). This study was conducted in patients with histopathologically confirmed diagnosis of GBM, gliosarcoma and history of more than 3 relapses; increases up to 10 times the basal levels of HGF in patients during treatment with AMD did not induce changes in survival time or clinical status as compared

To date, there is no biological marker that can accurately discern the activity of malignant gliomas. The scientific evidence obtained from experimental studies suggests that Hepatocyte Growth Factor plays a crucial role in the pathophysiology of high-grade gliomas. Findings from clinical studies suggest that HGF may be considered a distinguishing marker of biological activity of malignant gliomas, as it has been consistently demonstrated that the intratumoral, cerebrospinal fluid and serum concentrations are directly associated with prognosis and survival. The results of clinical trials aimed to evaluate the role of inhibitors of HGF or its receptor c-Met have shown disappointing therapeutic results. However, scientific advances in molecular biology could improve the response to treatment with specific inhibitors of HGF metabolism through ingenious

Abounader R, Lal B, Luddy C, Koe G, Davidson B, Rosen EM, Laterra J (2002) In vivo

targeting of SF/HGF and c-met expression via U1snRNA/ribozymes inhibits glioma growth and angiogenesis and promotes apoptosis. FASEB J. Vol. 16, No. 1,

along the subarachnoid space (Garcia-Navarrete et al., 2010).

genomic manipulations in patients with malignant gliomas.

pp. 108–10. PMID – 11729097

cycle progression, migration and invasion in different human glioblastoma cell lines, glioblastoma primary cells, glioblastoma stem cells and medulloblastoma cell lines. Importantly, oral administration of SGX523 to mice bearing intracranial human glioma xenografts led to inhibition of tumor growth in vivo. This experimental data suggests that c-Met kinase inhibition is a feasible and promising approach for brain tumor therapy (Guessous et al., 2010).

#### **4. HGF and gliomas on clinical setting**

Hepatocyte growth factor and its receptor (c-Met) have been detected in normal astrocytes as well as in human gliomas, and other malignant tumors (Koochekpour et al., 1995; Nabeshima et al., 1997; Hirose et al., 1998). In human cultured glioma cells, HGF and c-Met are simultaneously expressed, with an autocrinous effect inducing cell proliferation and migration.

Recent findings suggest that HGF contributes to glioma progression, inducing angiogenesis and expression of additional angiogenic autocrine factors such as VEGF (Laterra et al., 1997; Lamszus et al., 1999; Moriyama et al., 1999; Schmidt et al., 1999). The overexpression of HGF and its receptor c-Met increases cell motility and proliferation of human glioma cells in vitro (Koochekpour et al., 1995).

Intratumoral concentration of HGF in malignant gliomas is greatly increased in comparison with other intracranial tumors and nontumoral brain tissue (Arrieta et al., 2002); it is also related to cell proliferation and peritumoral edema, showing its participation in the pathogenesis of these tumors.

A common cause of failure of treatment of malignant gliomas is resistance to radiotherapy and chemotherapy; the mechanism by which the cell survives to therapeutic attempts involves the production of growth factors that regulate DNA repair and apoptosis. In vitro and in vivo, HGF inhibits drug-induced cytotoxicity and apoptosis in experimental neoplasms treated by radiation, cisplatin, and camptothencin (Bowers et al., 2000); this effect might decrease the therapeutic response of patients with high intratumoral contents of HGF. There is intense infiltration by microglia in gliomas, which may enhance malignancy by secretion of epidermal growth factor and by inhibition of cytotoxic lymphocytes (Wood et al., 1983); in vitro HGF stimulates the microglial infiltration of gliomas, favoring their growth (Badie et al., 1999).

The direct correlation of cell proliferation with the presence of HGF supports its participation in the promotion of tumoral growth of glioma, as has been shown for other tumors such as breast carcinoma (Lamszus et al., 1997).

The mechanism by which HGF stimulates cell proliferation seems to be related to the tirosine kinase activity of its receptor, which involves Ras and mitosis activation proteins (Arrieta et al., 2002). Such effects can be antagonized by tirosine kinase inhibitors. However, not all HGF effects require phosphorylation of its receptor; for instance, its antiapoptotic effect is independent, suggesting that it could also participate in the genesis of the tumor. The insertion of the HGF gene in human glioma cells increases proliferation of independent colonies in vitro and tumorigenesis in vivo (Laterra et al., 1997).

There are some histological features of malignant glioma associated with prognosis, such as the extent of necrosis or vascular density (Barker et al., 1996). Hepatocyte growth factor is a strong inductor of angiogenesis; its effects are synergistic with other growth factors such as VEGF and bFGF. Intratumoral concentration of HGF shows a direct relation with peritumoral edema, independent of vascular density. Previous studies have shown that HGF increases the permeability of the hematoencephalic barrier, independently of VEGF expression, possibly by the induction of endothelial fenestrations and by the tumoral expression of proteases such as urokinase and extracellular matrix metalloproteinases (Book et al., 1999).

A paracrine loop for HGF effects related with migration of tumor cells along white matter has been described. The increase of HGF in CSF observed may therefore reflect either the transport of HGF from brain parenchyma to the ventricular system or the diffusion of HGF along the subarachnoid space (Garcia-Navarrete et al., 2010).

HGF concentration is closely related with malignancy of glioma; low-grade glioma shows a lower intratumoral concentration of HGF than high-grade glioma. CSF concentrations of HGF greater than 850 pg/ml prior to surgery was predictive of a shorter disease-free time among malignant glioma patients than was observed for patients with a lower concentration (6 ± 0.6 months (95% [CI], 5–7) vs. 9 ± 0.5 months (95% [CI], 8–10), respectively, p< 0.001), besides total-gross resection surgery (Garcia-Navarrete et al., 2010). CSF concentration of HGF shows a negative correlation with survival of patients with malignant glioma and explains with high certainty the variance for survival. This suggests that HGF could be a good target candidate for molecular therapy such as RNA interference, by silencing the specific gene for HGF.

Although HGF seems a good target for therapeutic attempts, a phase II study reported the use of a monoclonal antibody against HGF (AMD 102). This study was conducted in patients with histopathologically confirmed diagnosis of GBM, gliosarcoma and history of more than 3 relapses; increases up to 10 times the basal levels of HGF in patients during treatment with AMD did not induce changes in survival time or clinical status as compared with controls (Wen et al., 2011)

### **5.Conclusions**

42 Glioma – Exploring Its Biology and Practical Relevance

cycle progression, migration and invasion in different human glioblastoma cell lines, glioblastoma primary cells, glioblastoma stem cells and medulloblastoma cell lines. Importantly, oral administration of SGX523 to mice bearing intracranial human glioma xenografts led to inhibition of tumor growth in vivo. This experimental data suggests that c-Met kinase inhibition is a feasible and promising approach for brain tumor therapy

Hepatocyte growth factor and its receptor (c-Met) have been detected in normal astrocytes as well as in human gliomas, and other malignant tumors (Koochekpour et al., 1995; Nabeshima et al., 1997; Hirose et al., 1998). In human cultured glioma cells, HGF and c-Met are simultaneously expressed, with an autocrinous effect inducing cell proliferation and

Recent findings suggest that HGF contributes to glioma progression, inducing angiogenesis and expression of additional angiogenic autocrine factors such as VEGF (Laterra et al., 1997; Lamszus et al., 1999; Moriyama et al., 1999; Schmidt et al., 1999). The overexpression of HGF and its receptor c-Met increases cell motility and proliferation of human glioma cells in vitro

Intratumoral concentration of HGF in malignant gliomas is greatly increased in comparison with other intracranial tumors and nontumoral brain tissue (Arrieta et al., 2002); it is also related to cell proliferation and peritumoral edema, showing its participation in the

A common cause of failure of treatment of malignant gliomas is resistance to radiotherapy and chemotherapy; the mechanism by which the cell survives to therapeutic attempts involves the production of growth factors that regulate DNA repair and apoptosis. In vitro and in vivo, HGF inhibits drug-induced cytotoxicity and apoptosis in experimental neoplasms treated by radiation, cisplatin, and camptothencin (Bowers et al., 2000); this effect might decrease the therapeutic response of patients with high intratumoral contents of HGF. There is intense infiltration by microglia in gliomas, which may enhance malignancy by secretion of epidermal growth factor and by inhibition of cytotoxic lymphocytes (Wood et al., 1983); in vitro HGF stimulates the microglial infiltration of gliomas, favoring their

The direct correlation of cell proliferation with the presence of HGF supports its participation in the promotion of tumoral growth of glioma, as has been shown for other

The mechanism by which HGF stimulates cell proliferation seems to be related to the tirosine kinase activity of its receptor, which involves Ras and mitosis activation proteins (Arrieta et al., 2002). Such effects can be antagonized by tirosine kinase inhibitors. However, not all HGF effects require phosphorylation of its receptor; for instance, its antiapoptotic effect is independent, suggesting that it could also participate in the genesis of the tumor. The insertion of the HGF gene in human glioma cells increases proliferation of independent

There are some histological features of malignant glioma associated with prognosis, such as the extent of necrosis or vascular density (Barker et al., 1996). Hepatocyte growth factor is a strong inductor of angiogenesis; its effects are synergistic with other growth factors such as VEGF and bFGF. Intratumoral concentration of HGF shows a direct relation with

(Guessous et al., 2010).

(Koochekpour et al., 1995).

pathogenesis of these tumors.

growth (Badie et al., 1999).

tumors such as breast carcinoma (Lamszus et al., 1997).

colonies in vitro and tumorigenesis in vivo (Laterra et al., 1997).

migration.

**4. HGF and gliomas on clinical setting** 

To date, there is no biological marker that can accurately discern the activity of malignant gliomas. The scientific evidence obtained from experimental studies suggests that Hepatocyte Growth Factor plays a crucial role in the pathophysiology of high-grade gliomas. Findings from clinical studies suggest that HGF may be considered a distinguishing marker of biological activity of malignant gliomas, as it has been consistently demonstrated that the intratumoral, cerebrospinal fluid and serum concentrations are directly associated with prognosis and survival. The results of clinical trials aimed to evaluate the role of inhibitors of HGF or its receptor c-Met have shown disappointing therapeutic results. However, scientific advances in molecular biology could improve the response to treatment with specific inhibitors of HGF metabolism through ingenious genomic manipulations in patients with malignant gliomas.

### **6. References**

Abounader R, Lal B, Luddy C, Koe G, Davidson B, Rosen EM, Laterra J (2002) In vivo targeting of SF/HGF and c-met expression via U1snRNA/ribozymes inhibits glioma growth and angiogenesis and promotes apoptosis. FASEB J. Vol. 16, No. 1, pp. 108–10. PMID – 11729097

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**4** 

Kerrie L. McDonald

*Australia* 

**Biomarker Discovery, Validation and Clinical** 

*Cure For Life Neuro-oncology Group, University of NSW* 

**Application for Patients Diagnosed with Glioma** 

Combined radiotherapy and chemotherapy with the alkylating agent, temozolomide plus an additional six cycles of temozolomide has been the mainstay of treatment for patients diagnosed with glioblastoma for the past 6 years. Clinically, high variability in the response to this treatment is typically observed, with some patients enjoying progression free survival for longer than others. However, tumour relapse is inevitable in the majority of patients. Local tumour recurrence, occurring within 2-3cm of the original resection cavity (the area exposed to radiation treatment) is most frequently observed. *Relapsed glioblastomas are typically unmanageable with median survival after recurrence of only a few months (Brandes et al. 2001)*. Numerous chemotherapeutic agents have been trialled in patients with recurrent glioblastomas and include enzastaurin (Wick et al. 2010), immunotherapeutic targeting of EGFRvIII (Sampson et al. 2011), cilengitide (trial ongoing) (Reardon et al. 2011), NovoTTF-100A (trial ongoing), gefitinib (Uhm et al. 2010), imatinib (Dresemann et al. 2010), bevacizumab plus irinotecan (Vredenburgh et al. 2007). Only bevacizumab has shown promise for the treatment of recurrent glioblastoma, although the benefits of such a drug are still debatable. The Food and Drug Administration (FDA) in the USA approved bevacizumab for GBM under its accelerated approval process. However in Europe, the Committee for Medicinal Products for Human Use (CHMP) adopted a negative opinion*.*  As new therapeutic regimes are developed, it is paramount that we develop a strategy for identifying the patients that will show a positive response to treatment. The recognition and validation of biomarkers of clinical response is important for several reasons: to avoid unnecessary toxicity in patients that fail to respond to the particular treatment; to reduce the colossal cost to healthcare which is typically associated with targeted therapy and most importantly, to better understand drug resistance. This improved knowledge could lead to new strategies to overcome the initial resistance and identify synergistic drug combinations.

Hopes for progressing curative treatment programs for cancer patients centre on the development and successful implementation of personalised medicine. Personalised medicine hinges on biomarkers which are highly sensitive and highly specific in revealling information that is relevant for diagnosis, prognosis and therapy. The most sought after biomarkers are the ones that can identify which patients are at high risk of tumour relapse

**1. Introduction** 

**1.1 Prognostic and predictive biomarkers** 

safety of AMG 102 (rilotumumab) in patients with recurrent glioblastoma. *Neuro Oncol.* Vol. 13, No. 4, pp. 437-46. PMID - 21297127


## **Biomarker Discovery, Validation and Clinical Application for Patients Diagnosed with Glioma**

Kerrie L. McDonald

*Cure For Life Neuro-oncology Group, University of NSW Australia* 

#### **1. Introduction**

48 Glioma – Exploring Its Biology and Practical Relevance

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(2009). Efficacy, safety and patterns of response and recurrence in patients with recurrent high-grade gliomas treated with bevacizumab plus irinotecan.*J*  Combined radiotherapy and chemotherapy with the alkylating agent, temozolomide plus an additional six cycles of temozolomide has been the mainstay of treatment for patients diagnosed with glioblastoma for the past 6 years. Clinically, high variability in the response to this treatment is typically observed, with some patients enjoying progression free survival for longer than others. However, tumour relapse is inevitable in the majority of patients. Local tumour recurrence, occurring within 2-3cm of the original resection cavity (the area exposed to radiation treatment) is most frequently observed. *Relapsed glioblastomas are typically unmanageable with median survival after recurrence of only a few months (Brandes et al. 2001)*. Numerous chemotherapeutic agents have been trialled in patients with recurrent glioblastomas and include enzastaurin (Wick et al. 2010), immunotherapeutic targeting of EGFRvIII (Sampson et al. 2011), cilengitide (trial ongoing) (Reardon et al. 2011), NovoTTF-100A (trial ongoing), gefitinib (Uhm et al. 2010), imatinib (Dresemann et al. 2010), bevacizumab plus irinotecan (Vredenburgh et al. 2007). Only bevacizumab has shown promise for the treatment of recurrent glioblastoma, although the benefits of such a drug are still debatable. The Food and Drug Administration (FDA) in the USA approved bevacizumab for GBM under its accelerated approval process. However in Europe, the Committee for Medicinal Products for Human Use (CHMP) adopted a negative opinion*.*  As new therapeutic regimes are developed, it is paramount that we develop a strategy for identifying the patients that will show a positive response to treatment. The recognition and validation of biomarkers of clinical response is important for several reasons: to avoid unnecessary toxicity in patients that fail to respond to the particular treatment; to reduce the colossal cost to healthcare which is typically associated with targeted therapy and most

importantly, to better understand drug resistance. This improved knowledge could lead to new strategies to overcome the initial resistance and identify synergistic drug combinations.

#### **1.1 Prognostic and predictive biomarkers**

Hopes for progressing curative treatment programs for cancer patients centre on the development and successful implementation of personalised medicine. Personalised medicine hinges on biomarkers which are highly sensitive and highly specific in revealling information that is relevant for diagnosis, prognosis and therapy. The most sought after biomarkers are the ones that can identify which patients are at high risk of tumour relapse

Biomarker Discovery, Validation and Clinical

2008; Paz-Ares et al. 2010).

**1.2 Molecular subtypes of glioblastoma** 

Application for Patients Diagnosed with Glioma 51

Fig. 2. Molecular diagnostics allows for the identification of GBM subgroups with similar

Much more difficult to identify are biomarkers with **predictive power** in the context of a specific therapy. Predictive biomarkers are markers which can be used to identify groups of patients who are most likely to respond to a given treatment. The key difference between a prognostic and a predictive biomarker is that the predictive biomarker should instigate a *change* in the treatment provided to the patient (Figure 1). Estrogen Receptor (ER) status in patients with breast cancer strongly predicts treatment response to tamoxifen (Kurokawa et al. 2000; Hu&Mokbel 2001). Additionally, patients with variant forms of the gene CYP2D6 (also called simply 2D6) may not receive full benefit from tamoxifen because of the slow metabolism of the tamoxifen prodrug into its active metabolite 4-hydroxytamoxifen (Goetz 2010; Stingl et al. 2010; de Souza&Olopade 2011). Approximately 60% of malignant melanomas harbour the BRAF mutation. Although patients with the damaged BRAF are non-responsive to the KRAS/BRAF inhibitor, sorafenib, response to the second-generation drug called PLX4720 is favourable (Whittaker et al. 2010). Improved outcomes have also been reported in patients with non-small cell lung cancer (NSCLC) harbouring EGFR mutations treated with the tyrosine kinase inhibitors (TKI) erlotinib and gefitinib (Kim et al.

*In a highly heterogeneous tumour such as glioblastoma, the search for predictive markers to treatment* 

Most centres around the world use the World Health Organisation (WHO) grading of tumours of the central nervous system (Fuller&Scheithauer 2007). Glioma grade is defined by the presence or absence of histopathological features, namely: nuclear pleomorphism, mitoses, proliferative index and necrosis and/or microvascular proliferation. A significant

*for use in clinical trials and in every day clinic has been disappointing.* 

genetic profile. This enrichment allows for a more uniform tumour response.

and developing cytotoxicity to specific chemotherapeutic agents. The use of biomarkers to identify patients who don't respond to treatment early could confer enormous benefits for patients diagnosed with glioblastoma, especially considering the short survival time. Many biomarkers have shown excellent utility in survival prognostication but not necessarily at the level of influencing an oncologist's decision to administer a specific drug or alter the treatment schedule (Figure 1). In addition, another challenge in oncology is the translation of prospective biomarkers from the lab into validated diagnostic tests.

Fig. 1. Schematic overview of the key difference between biomarkers with prognostic and predictive qualities. Prognostic markers are more common in glioblastoma.

Most biomarkers often have both prognostic and predictive value. There is no strict rule when it comes to what constitutes a biomarker. A marker can consist of genomic and proteomic patterns, single genes or proteins, chromosomal abnormalities, epigenetic signatures, aberrant microRNA as well as imaging changes observed on a MRI or PET scan. A **prognostic marker** has the capacity to **estimate survival** outcome in patients, independent of treatment. The genetic profiling of large tumour cohorts with comprehensive clinical and survival data have promoted the discovery of novel molecular biomarkers associated with survival, in addition to traditional clinical and morphological features. Examples of biomarkers with prognostic significance include amplification of Epithelial Growth Factor Receptor (EGFR) (Shinojima et al. 2003; Layfield et al. 2006; Kaloshi et al. 2007; Gan et al. 2009; Inda et al. 2010), over-expression of chitinase-3-like-1 (CH3L1 or YKL-40) (Hormigo et al. 2006; Pelloski et al. 2007), osteopontin (Sreekanthreddy et al. 2010), loss of phosphatase and tensin homolog (PTEN) (Hill et al. 2003; Parsa et al. 2007) and mutations in the tumour suppressor protein, p53 (Shiraishi et al. 2002; Ruano et al. 2009). Prognostic biomarkers have great utility in the clinic. Not only do these markers present as potential therapeutic targets but they can be used to pool groups of glioma with similar genetic profile. This enrichment of the test population leads to increased homogeneity and a much more uniform response to treatment (Figure 2).

and developing cytotoxicity to specific chemotherapeutic agents. The use of biomarkers to identify patients who don't respond to treatment early could confer enormous benefits for patients diagnosed with glioblastoma, especially considering the short survival time. Many biomarkers have shown excellent utility in survival prognostication but not necessarily at the level of influencing an oncologist's decision to administer a specific drug or alter the treatment schedule (Figure 1). In addition, another challenge in oncology is the translation

BIOMARKER

PROGNOSTIC PREDICTIVE

The key difference between a prognostic and a predictive biomarker is that the predictive biomarker should instigate a *change* in the treatment provided to the patient

Fig. 1. Schematic overview of the key difference between biomarkers with prognostic and

Most biomarkers often have both prognostic and predictive value. There is no strict rule when it comes to what constitutes a biomarker. A marker can consist of genomic and proteomic patterns, single genes or proteins, chromosomal abnormalities, epigenetic signatures, aberrant microRNA as well as imaging changes observed on a MRI or PET scan. A **prognostic marker** has the capacity to **estimate survival** outcome in patients, independent of treatment. The genetic profiling of large tumour cohorts with comprehensive clinical and survival data have promoted the discovery of novel molecular biomarkers associated with survival, in addition to traditional clinical and morphological features. Examples of biomarkers with prognostic significance include amplification of Epithelial Growth Factor Receptor (EGFR) (Shinojima et al. 2003; Layfield et al. 2006; Kaloshi et al. 2007; Gan et al. 2009; Inda et al. 2010), over-expression of chitinase-3-like-1 (CH3L1 or YKL-40) (Hormigo et al. 2006; Pelloski et al. 2007), osteopontin (Sreekanthreddy et al. 2010), loss of phosphatase and tensin homolog (PTEN) (Hill et al. 2003; Parsa et al. 2007) and mutations in the tumour suppressor protein, p53 (Shiraishi et al. 2002; Ruano et al. 2009). Prognostic biomarkers have great utility in the clinic. Not only do these markers present as potential therapeutic targets but they can be used to pool groups of glioma with similar genetic profile. This enrichment of the test population leads to increased homogeneity and a

predictive qualities. Prognostic markers are more common in glioblastoma.

identify groups of patients who are most likely to respond to a given treatment

of prospective biomarkers from the lab into validated diagnostic tests.

capacity to estimate survival outcome in patients, independent of treatment

much more uniform response to treatment (Figure 2).

Fig. 2. Molecular diagnostics allows for the identification of GBM subgroups with similar genetic profile. This enrichment allows for a more uniform tumour response.

Much more difficult to identify are biomarkers with **predictive power** in the context of a specific therapy. Predictive biomarkers are markers which can be used to identify groups of patients who are most likely to respond to a given treatment. The key difference between a prognostic and a predictive biomarker is that the predictive biomarker should instigate a *change* in the treatment provided to the patient (Figure 1). Estrogen Receptor (ER) status in patients with breast cancer strongly predicts treatment response to tamoxifen (Kurokawa et al. 2000; Hu&Mokbel 2001). Additionally, patients with variant forms of the gene CYP2D6 (also called simply 2D6) may not receive full benefit from tamoxifen because of the slow metabolism of the tamoxifen prodrug into its active metabolite 4-hydroxytamoxifen (Goetz 2010; Stingl et al. 2010; de Souza&Olopade 2011). Approximately 60% of malignant melanomas harbour the BRAF mutation. Although patients with the damaged BRAF are non-responsive to the KRAS/BRAF inhibitor, sorafenib, response to the second-generation drug called PLX4720 is favourable (Whittaker et al. 2010). Improved outcomes have also been reported in patients with non-small cell lung cancer (NSCLC) harbouring EGFR mutations treated with the tyrosine kinase inhibitors (TKI) erlotinib and gefitinib (Kim et al. 2008; Paz-Ares et al. 2010).

*In a highly heterogeneous tumour such as glioblastoma, the search for predictive markers to treatment for use in clinical trials and in every day clinic has been disappointing.* 

#### **1.2 Molecular subtypes of glioblastoma**

Most centres around the world use the World Health Organisation (WHO) grading of tumours of the central nervous system (Fuller&Scheithauer 2007). Glioma grade is defined by the presence or absence of histopathological features, namely: nuclear pleomorphism, mitoses, proliferative index and necrosis and/or microvascular proliferation. A significant

Biomarker Discovery, Validation and Clinical

**2.1. Loss of heterozygosity 1p and 19q** 

(gCIMP).

Application for Patients Diagnosed with Glioma 53

EGFR, presence of the EGFR delta variant (EGFRvIII) and overexpression of chitinase 3-like 1 (YKL40). Gene profiling and cross validation in multiple independent datasets has resulted in the separation of glioblastoma into two major subgroupings: proneural and mesenchymal. The proneural tumours have a much better survival outlook and can be further characterised by the presence of a glioma CpG island methylation phenotype

Extensive reviews of EGFR, PTEN and TP53 are covered elsewhere. This discussion will

A hallmark of oligodendroglial tumours is the co-deletion of the chromosomal arms 1p and 19q corresponding to an unbalanced translocation t(1;19) (q10;p10). This can be readily detected using Fluorescence In situ hybridisation (FISH) (Figure 3). LOH at 1p19q is observed in up to 69% of grade II and grade III (anaplastic) oligodendrogliomas and is far more common in 'pure' oligodendroglioma than astrocytoma and mixed oligoastrocytoma (Barbashina et al. 2005). LOH of 1p19q confers a clear survival advantage in anaplastic oligodendroglioma and mixed oligoastrocytoma however the survival advantage conferred for grade II lesions is less clear (Laigle-Donadey et al. 2005; Jenkins et al. 2006; Walker et al. 2006) . Whether the co-deletion mediates a prognostic advantage or results in a heightened sensitivity to radiation and chemotherapy is unknown. In general, oligodendrogliomas with LOH at 1p19q represent a group of highly chemosensitive gliomas, especially to the

Fig. 3. Representative photomicrographs of loss of 1p (A) and loss of 19q (B) chromosomal arms detected using FISH. Arrow indicates only one chromosome copy instead of the expected two. Photomicrographs were kindly donated by Dr Michael Buckland, Department

The standard treatment for anaplastic oligodendrogliomas consists of complete surgical removal where possible followed by radiation therapy and chemotherapy, typically with temozolomide because it is well tolerated. It is generally accepted that chemotherapy is of value in the treatment of patients with anaplastic oligodendrogliomas (Mokhtari et al. 2011).

focus on LOH 1p/19q, MGMT promoter methylation and mutations in IDH.

combination of procarbazine, lomustine (CCNU), and vincristine (PCV).

A B

of Neuropathology, University of Sydney.

limitation to this histopathology-based analysis is its inability to detect functional differences occurring on the subcellular level. This is evidenced by the high variability observed in the clinical outcomes in patients with the same diagnosis and differences in response to therapy. To advance survival times and clinical treatment of these patients with an, on average, dismal prognosis molecular markers with capacity to take into consideration the high molecular heterogeneity are needed in the clinic.

The wide spectrum of molecular difference in glioblastoma is evident from global expression studies, in particular, the molecular cataloguing project: The Cancer Genome Atlas (TCGA) (2008). Surveying the mutational environment of glioblastoma revealed that aberrations occur most commonly in genes whose protein products regulate the core cell growth signalling pathways that are already known to be important such as EGFR, PTEN, p53 and CDKN2A. What this survey did reveal was the extent of genomic complexity. Each tumour harbours different mutations. In addition, we are beginning to appreciate that the core pathways of cancer are not linear, rather complex and interacting. Given this complexity, it is very unlikely that a single genetic change will predict treatment response.

Gene expression profiling has provided an opportunity to further define prognostic and predictive factors (Settle&Sulman 2011). Gene signatures have successfully categorised glioblastomas that histologically appear indistinguishable, into molecular subgroups which often have very different clinical outcomes (Colman et al. 2010; Verhaak et al. 2010). Based on survival associated genes, 76 high grade gliomas were classified into the broad genotology groups; proneural, mesenchymal and proliferative (Phillips et al. 2006). The use of larger and multiple datasets have refined these subtypes into two broad groups, proneural and mesenchymal angiogenic (Colman et al. 2010). Overexpression of a mesenchymal gene expression signature and loss of a proneural signature are associated with a poor prognosis group. By subtyping glioblastoma into mesenchymal and proneural subtypes, the sameness of patient populations is improved. In addition, the genes belonging to each group provides biologists hints for therapeutic targeting. For example, the mesenchymal subtype of glioblastoma is over-represented by genes involved in angiogenesis and invasion (Colman et al. 2010). This subgroup of patients is more responsive to bevacizumab. Mutation in the isocitrate dehydrogenase 1 (IDH1) gene is strongly associated with the proneural subtype of glioblastoma and a much better prognosis (Noushmehr et al. 2010). Increasing evidence suggests that proneural glioblastomas have a different histogenic origin which is further supported by the recent discovery of a glioma-CpG island methylator phenotype (G-CIMP) (Noushmehr et al. 2010). Both IDH1mt and the G-CIMP have a higher incidence in secondary GBMs which arise from a prior, lower grade lesion. MGMT promoter methylation, G-CIMP and mutations in IDH1 are all prognostic. Although a correlation between proneural GBM subtypes and specific treatment has not been determined, it has been suggested by a few studies that chemotherapy agents such as temozolomide and others targeted at cell growth may not be as effective for this group as previously thought (Verhaak&Valk 2010).

#### **2. Prognostic biomarkers in glioma**

Molecular markers identified to hold prognostic significance in glioma include loss of heterozygosity of the chromosomal arms 1p and 19q (LOH 1p/19q), methylguanine methyltransferase (MGMT) promoter methylation, mutations in the isocitrate dehydrogenase 1 (IDH1) gene, mutations in TP53, loss of PTEN activity, amplification of

limitation to this histopathology-based analysis is its inability to detect functional differences occurring on the subcellular level. This is evidenced by the high variability observed in the clinical outcomes in patients with the same diagnosis and differences in response to therapy. To advance survival times and clinical treatment of these patients with an, on average, dismal prognosis molecular markers with capacity to take into consideration

The wide spectrum of molecular difference in glioblastoma is evident from global expression studies, in particular, the molecular cataloguing project: The Cancer Genome Atlas (TCGA) (2008). Surveying the mutational environment of glioblastoma revealed that aberrations occur most commonly in genes whose protein products regulate the core cell growth signalling pathways that are already known to be important such as EGFR, PTEN, p53 and CDKN2A. What this survey did reveal was the extent of genomic complexity. Each tumour harbours different mutations. In addition, we are beginning to appreciate that the core pathways of cancer are not linear, rather complex and interacting. Given this complexity, it is very unlikely that a single genetic change will predict treatment response. Gene expression profiling has provided an opportunity to further define prognostic and predictive factors (Settle&Sulman 2011). Gene signatures have successfully categorised glioblastomas that histologically appear indistinguishable, into molecular subgroups which often have very different clinical outcomes (Colman et al. 2010; Verhaak et al. 2010). Based on survival associated genes, 76 high grade gliomas were classified into the broad genotology groups; proneural, mesenchymal and proliferative (Phillips et al. 2006). The use of larger and multiple datasets have refined these subtypes into two broad groups, proneural and mesenchymal angiogenic (Colman et al. 2010). Overexpression of a mesenchymal gene expression signature and loss of a proneural signature are associated with a poor prognosis group. By subtyping glioblastoma into mesenchymal and proneural subtypes, the sameness of patient populations is improved. In addition, the genes belonging to each group provides biologists hints for therapeutic targeting. For example, the mesenchymal subtype of glioblastoma is over-represented by genes involved in angiogenesis and invasion (Colman et al. 2010). This subgroup of patients is more responsive to bevacizumab. Mutation in the isocitrate dehydrogenase 1 (IDH1) gene is strongly associated with the proneural subtype of glioblastoma and a much better prognosis (Noushmehr et al. 2010). Increasing evidence suggests that proneural glioblastomas have a different histogenic origin which is further supported by the recent discovery of a glioma-CpG island methylator phenotype (G-CIMP) (Noushmehr et al. 2010). Both IDH1mt and the G-CIMP have a higher incidence in secondary GBMs which arise from a prior, lower grade lesion. MGMT promoter methylation, G-CIMP and mutations in IDH1 are all prognostic. Although a correlation between proneural GBM subtypes and specific treatment has not been determined, it has been suggested by a few studies that chemotherapy agents such as temozolomide and others targeted at cell growth may not be as effective for this group as

Molecular markers identified to hold prognostic significance in glioma include loss of heterozygosity of the chromosomal arms 1p and 19q (LOH 1p/19q), methylguanine methyltransferase (MGMT) promoter methylation, mutations in the isocitrate dehydrogenase 1 (IDH1) gene, mutations in TP53, loss of PTEN activity, amplification of

the high molecular heterogeneity are needed in the clinic.

previously thought (Verhaak&Valk 2010).

**2. Prognostic biomarkers in glioma** 

EGFR, presence of the EGFR delta variant (EGFRvIII) and overexpression of chitinase 3-like 1 (YKL40). Gene profiling and cross validation in multiple independent datasets has resulted in the separation of glioblastoma into two major subgroupings: proneural and mesenchymal. The proneural tumours have a much better survival outlook and can be further characterised by the presence of a glioma CpG island methylation phenotype (gCIMP).

Extensive reviews of EGFR, PTEN and TP53 are covered elsewhere. This discussion will focus on LOH 1p/19q, MGMT promoter methylation and mutations in IDH.

#### **2.1. Loss of heterozygosity 1p and 19q**

A hallmark of oligodendroglial tumours is the co-deletion of the chromosomal arms 1p and 19q corresponding to an unbalanced translocation t(1;19) (q10;p10). This can be readily detected using Fluorescence In situ hybridisation (FISH) (Figure 3). LOH at 1p19q is observed in up to 69% of grade II and grade III (anaplastic) oligodendrogliomas and is far more common in 'pure' oligodendroglioma than astrocytoma and mixed oligoastrocytoma (Barbashina et al. 2005). LOH of 1p19q confers a clear survival advantage in anaplastic oligodendroglioma and mixed oligoastrocytoma however the survival advantage conferred for grade II lesions is less clear (Laigle-Donadey et al. 2005; Jenkins et al. 2006; Walker et al. 2006) . Whether the co-deletion mediates a prognostic advantage or results in a heightened sensitivity to radiation and chemotherapy is unknown. In general, oligodendrogliomas with LOH at 1p19q represent a group of highly chemosensitive gliomas, especially to the combination of procarbazine, lomustine (CCNU), and vincristine (PCV).

Fig. 3. Representative photomicrographs of loss of 1p (A) and loss of 19q (B) chromosomal arms detected using FISH. Arrow indicates only one chromosome copy instead of the expected two. Photomicrographs were kindly donated by Dr Michael Buckland, Department of Neuropathology, University of Sydney.

The standard treatment for anaplastic oligodendrogliomas consists of complete surgical removal where possible followed by radiation therapy and chemotherapy, typically with temozolomide because it is well tolerated. It is generally accepted that chemotherapy is of value in the treatment of patients with anaplastic oligodendrogliomas (Mokhtari et al. 2011).

Biomarker Discovery, Validation and Clinical

**2.2 MGMT** 

2009; Mellai et al. 2009).

Application for Patients Diagnosed with Glioma 55

The O6-methylguanine-DNA methyltransferase gene, *MGMT*, located on chromosome 10q26.1 encodes a DNA repair protein that restores mutagenic O6-alkylguanine to normal guanine within genomic DNA. O6-alkylguanines can pair erroneously with thymine during DNA replication, resulting in G:C>A:T transitions, as well as causing cross-links between adjacent strands of DNA, both of which can lead to neoplastic transformation (Gerson 2004). MGMT thus protects cells from the toxic and carcinogenic effects of alkylating agents and is absent in many types of human malignancy. Loss of MGMT protein expression is frequently associated with transcriptional silencing of the MGMT gene by methylation of its CpG island promoter in various neoplasia, (Esteller et al. 1999) as exemplified by 35-55% of gliomas (Silber et al. 1998; Esteller et al. 2000; Nakamura et al. 2001; Kamiryo et al. 2004; Paz et al. 2004; Brell et al. 2005; Hegi et al. 2005). However, several large studies of glioma have shown the correlation between immunohistochemical loss of MGMT and promoter methylation is not always correlative (Preusser et al. 2008; Cao et al. 2009; Hawkins et al.

Alkylating drugs such as temozolomide are used in chemotherapy for the targeted cell death of rapidly-replicating neoplastic cells and MGMT expression is a key factor in conferring resistance to these agents. In 2005, a new treatment regime was developed and tested in a randomised, phase III clinical trial whereby the alkylating agent, temozolomide was combined with radiotherapy (RT) in concurrent treatment followed by an additional 6 cycles of Temozolomide for newly diagnosed glioblastoma (Stupp et al. 2005). This was the first trial to achieve a clinically meaningful and statistically significant overall median survival benefit of 2.5 months when compared to radiotherapy alone. More compelling were the two-year survival rates with 26% of patients treated with concurrent treatment still alive after two years compared with just 10.4% for patients treated with radiotherapy alone. These survival benefits were still apparent after 5 years of follow-up (Stupp et al. 2009). The molecular basis for the differential response of glioblastoma patients to temozolomide has been recognized. Temozolomide is an oral alkylating chemotherapy which is spontaneously converted into its active metabolite and readily crosses the blood-brain barrier. The primary mode of action of temozolomide is to damage the DNA by introducing alkyl adducts. These cause genetic mutations as well as cross-links between DNA strands that inhibit DNA replication and thereby trigger cell death. Thus alkylating agents target rapidly replicating neoplastic cells. However, while temozolomide introduces alkyl adducts into DNA, MGMT reverses them. Thus tumour cells expressing MGMT are chemoresistant to this class of drugs (Pegg 1990). In a companion laboratory study to the phase III trial combining radiotherapy with temozolomide, Hegi et al. demonstrated a pronounced positive survival response in patients whose tumours had lost MGMT by promoter methylation. Strikingly, patients whose tumours were MGMT-methylated demonstrated extended overall and progression-free survival compared to those whose tumours were unmethylated, and therefore MGMT methylation was postulated to be a positive predictor of patient response to alkylating agents (Esteller et al. 2000; Hegi et al. 2005). Since these seminal reports in 2005, the standard of care for patients diagnosed with glioblastoma has comprised surgery with maximal feasible resection and radiotherapy with concurrent and adjuvant temozolomide. Yet widespread adoption of MGMT methylation as a marker of

response to temozolomide in clinical practice has not transpired.

Because of the potential toxicity to the CNS, many clinicians have suggested that radiotherapy treatment may be better reserved for progressive disease. Treatment with temozolomide is now favoured over PVC treatment because of its low toxicity. Studies treating anaplastic oligodendroglioma patients with temozolomide have also found that the presence of LOH at 1p/19q is a favourable predictive marker (Brandes et al. 2006; Mikkelsen et al. 2009; Ramirez et al. 2010). This could also be because the majority of oligodendrogliomas harbouring LOH at 1p/19q also show methylation in the promoter region of MGMT. Clinical studies have been designed to establish whether combining or adding chemotherapy to radiotherapy is of benefit to oligodendroglioma patients or whether these patients could benefit from upfront chemotherapy (without radiotherapy).

Two large prospective trials have shown little benefit for adding adjuvant PVC before radiotherapy (Cairncross et al. 2006) or after radiotherapy (van den Bent et al. 2006). To address whether treatment of oligodendrogliomas with chemotherapy alone is feasible and safe, the NOA-04 Phase III trial compared radiotherapy versus chemotherapy with either PCV or temozolomide as initial therapy in 318 patients with anaplastic gliomas (WHO grade 3) (randomly assigned 2:1:1 to receive radiotherapy (arm A) or chemotherapy with either PCV (arm B1) or temozolomide (arm B2)) (Wick et al. 2009). The clinical relevance of 1p/19q codeletion, O6-methylguanine DNA-methyltransferase (*MGMT*) promoter methylation, and *IDH1* mutations in codon 132 in these tumours were also measured and analysed. This important trial confirmed that there was no survival difference in administering initial radiotherapy or initial chemotherapy (Wick et al. 2009). One very important finding to emerge from the study was the presence of mutations in IDH1 provided the best prognostic model. An ongoing EORCT 26081 Phase III trial of radiotherapy, temozolomide and concomitant and adjuvant temozolomide in patients with anaplastic oligodendrogliomas with 1p/19q codeletions will further confirm what the optimal treatment for these tumours is (more information below).

The gene products that are affected as a result of LOH remain under investigation and may include mediators of cytotoxic resistance or may represent an early oncogenic lesion still retaining sensitivity to genotoxic agents or insults. Microarray technology has been used to profile gene expression in oligodendrogliomas to look for putative tumour suppressor gene candidates and genes which could mediate the observed chemosensitivity using a variety of microarray platforms (Mukasa et al. 2002; Nutt et al. 2003; Mukasa et al. 2004; Tews et al. 2006; Tews et al. 2007; Ducray et al. 2008). These studies have identified some interesting gene candidates located on the 1p and 19q chromosomal arms however none have gone on to be validated prospectively. Interestingly, these profiling experiments identified a proneural signature associated with 1p19q codeleted oligodendrogliomas and a better survival outcome (Phillips et al. 2006). In contrast, the mesenchymal signature is more commonly associated with glioblastoma (discussed in more detail below). Noteworthy is the absence of EGFR amplifications in the proneural group. Ducray and colleagues compared 1p19q codeleted gliomas to EGFR-amplified gliomas and found that the proneural gene internexin (INA) which encodes neurofilament-interacting protein was significantly differentially expressed (Ducray et al. 2009). The prognostic significance of INA was further assessed and confirmed in the prospective, randomized EORTC 26951 trial of adjuvant PVC (Mokhtari et al. 2011). INA strongly correlated with 1p19q codeletion, mutated IDH1 and MGMT promoter methylation.

#### **2.2 MGMT**

54 Glioma – Exploring Its Biology and Practical Relevance

Because of the potential toxicity to the CNS, many clinicians have suggested that radiotherapy treatment may be better reserved for progressive disease. Treatment with temozolomide is now favoured over PVC treatment because of its low toxicity. Studies treating anaplastic oligodendroglioma patients with temozolomide have also found that the presence of LOH at 1p/19q is a favourable predictive marker (Brandes et al. 2006; Mikkelsen et al. 2009; Ramirez et al. 2010). This could also be because the majority of oligodendrogliomas harbouring LOH at 1p/19q also show methylation in the promoter region of MGMT. Clinical studies have been designed to establish whether combining or adding chemotherapy to radiotherapy is of benefit to oligodendroglioma patients or whether these patients could benefit from upfront chemotherapy (without radiotherapy). Two large prospective trials have shown little benefit for adding adjuvant PVC before radiotherapy (Cairncross et al. 2006) or after radiotherapy (van den Bent et al. 2006). To address whether treatment of oligodendrogliomas with chemotherapy alone is feasible and safe, the NOA-04 Phase III trial compared radiotherapy versus chemotherapy with either PCV or temozolomide as initial therapy in 318 patients with anaplastic gliomas (WHO grade 3) (randomly assigned 2:1:1 to receive radiotherapy (arm A) or chemotherapy with either PCV (arm B1) or temozolomide (arm B2)) (Wick et al. 2009). The clinical relevance of 1p/19q codeletion, O6-methylguanine DNA-methyltransferase (*MGMT*) promoter methylation, and *IDH1* mutations in codon 132 in these tumours were also measured and analysed. This important trial confirmed that there was no survival difference in administering initial radiotherapy or initial chemotherapy (Wick et al. 2009). One very important finding to emerge from the study was the presence of mutations in IDH1 provided the best prognostic model. An ongoing EORCT 26081 Phase III trial of radiotherapy, temozolomide and concomitant and adjuvant temozolomide in patients with anaplastic oligodendrogliomas with 1p/19q codeletions will further confirm what the optimal treatment for these tumours

The gene products that are affected as a result of LOH remain under investigation and may include mediators of cytotoxic resistance or may represent an early oncogenic lesion still retaining sensitivity to genotoxic agents or insults. Microarray technology has been used to profile gene expression in oligodendrogliomas to look for putative tumour suppressor gene candidates and genes which could mediate the observed chemosensitivity using a variety of microarray platforms (Mukasa et al. 2002; Nutt et al. 2003; Mukasa et al. 2004; Tews et al. 2006; Tews et al. 2007; Ducray et al. 2008). These studies have identified some interesting gene candidates located on the 1p and 19q chromosomal arms however none have gone on to be validated prospectively. Interestingly, these profiling experiments identified a proneural signature associated with 1p19q codeleted oligodendrogliomas and a better survival outcome (Phillips et al. 2006). In contrast, the mesenchymal signature is more commonly associated with glioblastoma (discussed in more detail below). Noteworthy is the absence of EGFR amplifications in the proneural group. Ducray and colleagues compared 1p19q codeleted gliomas to EGFR-amplified gliomas and found that the proneural gene internexin (INA) which encodes neurofilament-interacting protein was significantly differentially expressed (Ducray et al. 2009). The prognostic significance of INA was further assessed and confirmed in the prospective, randomized EORTC 26951 trial of adjuvant PVC (Mokhtari et al. 2011). INA strongly correlated with 1p19q codeletion, mutated IDH1 and

is (more information below).

MGMT promoter methylation.

The O6-methylguanine-DNA methyltransferase gene, *MGMT*, located on chromosome 10q26.1 encodes a DNA repair protein that restores mutagenic O6-alkylguanine to normal guanine within genomic DNA. O6-alkylguanines can pair erroneously with thymine during DNA replication, resulting in G:C>A:T transitions, as well as causing cross-links between adjacent strands of DNA, both of which can lead to neoplastic transformation (Gerson 2004). MGMT thus protects cells from the toxic and carcinogenic effects of alkylating agents and is absent in many types of human malignancy. Loss of MGMT protein expression is frequently associated with transcriptional silencing of the MGMT gene by methylation of its CpG island promoter in various neoplasia, (Esteller et al. 1999) as exemplified by 35-55% of gliomas (Silber et al. 1998; Esteller et al. 2000; Nakamura et al. 2001; Kamiryo et al. 2004; Paz et al. 2004; Brell et al. 2005; Hegi et al. 2005). However, several large studies of glioma have shown the correlation between immunohistochemical loss of MGMT and promoter methylation is not always correlative (Preusser et al. 2008; Cao et al. 2009; Hawkins et al. 2009; Mellai et al. 2009).

Alkylating drugs such as temozolomide are used in chemotherapy for the targeted cell death of rapidly-replicating neoplastic cells and MGMT expression is a key factor in conferring resistance to these agents. In 2005, a new treatment regime was developed and tested in a randomised, phase III clinical trial whereby the alkylating agent, temozolomide was combined with radiotherapy (RT) in concurrent treatment followed by an additional 6 cycles of Temozolomide for newly diagnosed glioblastoma (Stupp et al. 2005). This was the first trial to achieve a clinically meaningful and statistically significant overall median survival benefit of 2.5 months when compared to radiotherapy alone. More compelling were the two-year survival rates with 26% of patients treated with concurrent treatment still alive after two years compared with just 10.4% for patients treated with radiotherapy alone. These survival benefits were still apparent after 5 years of follow-up (Stupp et al. 2009).

The molecular basis for the differential response of glioblastoma patients to temozolomide has been recognized. Temozolomide is an oral alkylating chemotherapy which is spontaneously converted into its active metabolite and readily crosses the blood-brain barrier. The primary mode of action of temozolomide is to damage the DNA by introducing alkyl adducts. These cause genetic mutations as well as cross-links between DNA strands that inhibit DNA replication and thereby trigger cell death. Thus alkylating agents target rapidly replicating neoplastic cells. However, while temozolomide introduces alkyl adducts into DNA, MGMT reverses them. Thus tumour cells expressing MGMT are chemoresistant to this class of drugs (Pegg 1990). In a companion laboratory study to the phase III trial combining radiotherapy with temozolomide, Hegi et al. demonstrated a pronounced positive survival response in patients whose tumours had lost MGMT by promoter methylation. Strikingly, patients whose tumours were MGMT-methylated demonstrated extended overall and progression-free survival compared to those whose tumours were unmethylated, and therefore MGMT methylation was postulated to be a positive predictor of patient response to alkylating agents (Esteller et al. 2000; Hegi et al. 2005). Since these seminal reports in 2005, the standard of care for patients diagnosed with glioblastoma has comprised surgery with maximal feasible resection and radiotherapy with concurrent and adjuvant temozolomide. Yet widespread adoption of MGMT methylation as a marker of response to temozolomide in clinical practice has not transpired.

Biomarker Discovery, Validation and Clinical

standard therapy (Perry et al. 2010).

**2.3 IDH mutations** 

Application for Patients Diagnosed with Glioma 57

lead to a progression free survival benefit, outcome with this treatment regimen was not

Treating patients with continuous 50mg/m2 at relapse after a standard temozolomide schedule of 150-200mg/m2 resulted in a PFS6 of 47-57% (Perry et al. 2008). The efficacy and safety of this continuous dose-intense temozolomide schedule for recurrent GBM was tested in a multicenter, phase II study, RESCUE. Overall, PFS6 in 116 patients with recurrent GBM was 24% (Perry et al. 2010). Not surprisingly, the best responding patients were those who were treated with conventional chemoradiotherapy. However, what was interesting was the similar benefit to treatment recorded in the patients who experienced early progression on

The Cancer Genome Atlas (TCGA) efforts made the initial breakthrough discovery that 11% of glioblastomas harbour point mutations in cytoplasmic and mitochondrial NADP+ dependent isocitrate dehydrogenases 1 and 2 (IDH1 and IDH2) (Balss et al. 2008; Parsons et al. 2008; Dang et al. 2009). The normal function of the IDH enzymes is to convert isocitrate into α-ketoglutarate. Mutations, specifically at the arginine 132 (R132) codon, are more frequently observed in low grade and anaplastic gliomas and secondary glioblastomas (50- 93%) than mutations found in IDH2 [arginine 172 (R172) codon] (3-5%). No gliomas have

Fig. 4. Representative photomicrographs of IDH1 mutations detected with the Anti-Human IDH1 R132H Mouse Monoclonal Antibody (DIA-H09M) at x20 magnification (A) and x40 (B) Photomicrographs were kindly donated by Dr Michael Buckland, Department of

Hartmann and colleagues used an antibody which specifically detected the R132 mutation in IDH1 allowing assessment with simple immunohistochemistry (Hartmann et al. 2010). (Figure 4). The mutation was detected in 72% low grade astrocytomas (AII; n=227); 64% anaplastic astrocytomas (AA; n=228); 82% low grade oligodendroglioma (OII; n=128); 70% anaplastic oligodendroglioma (AO; n=174); 82% low grade oligoastrocytomas (OAII; n=76); 66% anaplastic oligoastrocytoma (AOA; n=177) and 9% glioblastoma (GBM; n=521). What was most significant about this study was the progression free and overall survival curves.

significantly associated with MGMT promoter methylation (Wick et al. 2007).

been found to have point mutations in both IDH1 and IDH2 (Yan et al. 2009).

**A B**

Neuropathology, University of Sydney.

#### **2.2.1 Routine testing for MGMT methylation**

While MGMT methylation could be routinely used as a prognostic/predictive marker in glioblastoma, there is so far no consensus on the method to be applied. Assessment of MGMT promoter methylation is difficult due to the complex nature of the techniques involved. To detect methylation, bisulfite treatment of the DNA is required, a process that may result in degradation of DNA and subsequent low success rates in PCR. This is further compounded by the fact that the most commonly available tissue for assessment is formalin fixed paraffin embedded (FFPE), and the DNA subsequently extracted from this tissue is usually fragmented, again making PCR more difficult.

Promoter methylation analysis by qualitative methyl-specific polymerase chain reaction (MSP) or semi-quantitative methyl-specific polymerase chain reaction (SQ-MSP), especially from FPPE tissue is technically demanding. MSP is the more limited because the methylation status of only a few CpG sites (i.e., those interfering with the PCR primer binding) can be interrogated at once. The technique also has the drawback of providing only a qualitative indication of the methylation status of the sites. Karayan-Tapon (Karayan-Tapon et al. 2010) evaluated MGMT promoter methylation using MSP, SQ-MSP and pyrosequencing. The best predictive value for overall survival was obtained by *pyrosequencing*. Pyrosequencing technology is a technique that generates a quantitative measure of methylation and automatically calculates and reports percent methylation for each CpG site in the studied sequence, thus allowing detection of partially methylated CpG sites.

There are other methodologies for assessing the promoter methylation of MGMT. The testing needs to be resolved for MGMT to be used routinely in the clinic and perhaps a surrogate marker of MGMT such as another protein product readily visualised by immunohistochemistry or a polymorphism detected in blood may be the way forward.

#### **2.2.2 Strategies to overcome MGMT activity**

With the recognition that an unmethylated MGMT promoter is associated with a poorer response to temozolomide, strategies have evolved to circumvent the resistance that MGMT confers. Combination therapy with multiple chemotherapeutic drugs known to deplete MGMT (specifically procarbazine and temozolomide) has been successfully assessed in a Phase I trial (Newlands et al. 2003) but as yet has not been shown to confer a benefit in survival. O6 benzylguanine (O6BG), a substrate for MGMT, has also been used to decrease MGMT levels. However, systemic administration of O6BG has been associated with significant toxicity, thereby necessitating a reduction in chemotherapy dose (Quinn et al. 2002; Quinn et al. 2005). A recent case report of local administration of O6BG, allowing the systemic effects to be avoided, shows some promise (Koch et al. 2007).

Alteration of temozolomide dosing regimens from the usual method of 5 days of treatment every 28 days to more frequent, lower-dose treatment has been evaluated. Protracted temozolomide exposure may reduce MGMT activity. Brock and colleagues demonstrated safety of a low dose of temozolomide for up to 49 consecutive days, however the efficacy of this lower dose is unclear (Brock et al. 1998). Depletion of peripheral mononuclear MGMT has been demonstrated with more prolonged dosing regimens and unfortunately this has been associated with profound lymphocytopaenia and opportunistic infections (Tolcher et al. 2003; Wick et al. 2004; Wick&Weller 2005). More recent evidence suggest that daily dosing may be associated with improved outcome (Buttolo et al. 2006). Additionally, a dosing regimen of 14 days of treatment out of every 28 days has not only been shown to lead to a progression free survival benefit, outcome with this treatment regimen was not significantly associated with MGMT promoter methylation (Wick et al. 2007). Treating patients with continuous 50mg/m2 at relapse after a standard temozolomide schedule of 150-200mg/m2 resulted in a PFS6 of 47-57% (Perry et al. 2008). The efficacy and safety of this continuous dose-intense temozolomide schedule for recurrent GBM was tested in a multicenter, phase II study, RESCUE. Overall, PFS6 in 116 patients with recurrent GBM

was 24% (Perry et al. 2010). Not surprisingly, the best responding patients were those who were treated with conventional chemoradiotherapy. However, what was interesting was the similar benefit to treatment recorded in the patients who experienced early progression on standard therapy (Perry et al. 2010).

#### **2.3 IDH mutations**

56 Glioma – Exploring Its Biology and Practical Relevance

While MGMT methylation could be routinely used as a prognostic/predictive marker in glioblastoma, there is so far no consensus on the method to be applied. Assessment of MGMT promoter methylation is difficult due to the complex nature of the techniques involved. To detect methylation, bisulfite treatment of the DNA is required, a process that may result in degradation of DNA and subsequent low success rates in PCR. This is further compounded by the fact that the most commonly available tissue for assessment is formalin fixed paraffin embedded (FFPE), and the DNA subsequently extracted from this tissue is

Promoter methylation analysis by qualitative methyl-specific polymerase chain reaction (MSP) or semi-quantitative methyl-specific polymerase chain reaction (SQ-MSP), especially from FPPE tissue is technically demanding. MSP is the more limited because the methylation status of only a few CpG sites (i.e., those interfering with the PCR primer binding) can be interrogated at once. The technique also has the drawback of providing only a qualitative indication of the methylation status of the sites. Karayan-Tapon (Karayan-Tapon et al. 2010) evaluated MGMT promoter methylation using MSP, SQ-MSP and pyrosequencing. The best predictive value for overall survival was obtained by *pyrosequencing*. Pyrosequencing technology is a technique that generates a quantitative measure of methylation and automatically calculates and reports percent methylation for each CpG site in the studied sequence, thus allowing detection of partially methylated CpG

There are other methodologies for assessing the promoter methylation of MGMT. The testing needs to be resolved for MGMT to be used routinely in the clinic and perhaps a surrogate marker of MGMT such as another protein product readily visualised by immunohistochemistry or a polymorphism detected in blood may be the way forward.

With the recognition that an unmethylated MGMT promoter is associated with a poorer response to temozolomide, strategies have evolved to circumvent the resistance that MGMT confers. Combination therapy with multiple chemotherapeutic drugs known to deplete MGMT (specifically procarbazine and temozolomide) has been successfully assessed in a Phase I trial (Newlands et al. 2003) but as yet has not been shown to confer a benefit in survival. O6 benzylguanine (O6BG), a substrate for MGMT, has also been used to decrease MGMT levels. However, systemic administration of O6BG has been associated with significant toxicity, thereby necessitating a reduction in chemotherapy dose (Quinn et al. 2002; Quinn et al. 2005). A recent case report of local administration of O6BG, allowing the

Alteration of temozolomide dosing regimens from the usual method of 5 days of treatment every 28 days to more frequent, lower-dose treatment has been evaluated. Protracted temozolomide exposure may reduce MGMT activity. Brock and colleagues demonstrated safety of a low dose of temozolomide for up to 49 consecutive days, however the efficacy of this lower dose is unclear (Brock et al. 1998). Depletion of peripheral mononuclear MGMT has been demonstrated with more prolonged dosing regimens and unfortunately this has been associated with profound lymphocytopaenia and opportunistic infections (Tolcher et al. 2003; Wick et al. 2004; Wick&Weller 2005). More recent evidence suggest that daily dosing may be associated with improved outcome (Buttolo et al. 2006). Additionally, a dosing regimen of 14 days of treatment out of every 28 days has not only been shown to

systemic effects to be avoided, shows some promise (Koch et al. 2007).

**2.2.1 Routine testing for MGMT methylation** 

usually fragmented, again making PCR more difficult.

**2.2.2 Strategies to overcome MGMT activity** 

sites.

The Cancer Genome Atlas (TCGA) efforts made the initial breakthrough discovery that 11% of glioblastomas harbour point mutations in cytoplasmic and mitochondrial NADP+ dependent isocitrate dehydrogenases 1 and 2 (IDH1 and IDH2) (Balss et al. 2008; Parsons et al. 2008; Dang et al. 2009). The normal function of the IDH enzymes is to convert isocitrate into α-ketoglutarate. Mutations, specifically at the arginine 132 (R132) codon, are more frequently observed in low grade and anaplastic gliomas and secondary glioblastomas (50- 93%) than mutations found in IDH2 [arginine 172 (R172) codon] (3-5%). No gliomas have been found to have point mutations in both IDH1 and IDH2 (Yan et al. 2009).

Fig. 4. Representative photomicrographs of IDH1 mutations detected with the Anti-Human IDH1 R132H Mouse Monoclonal Antibody (DIA-H09M) at x20 magnification (A) and x40 (B) Photomicrographs were kindly donated by Dr Michael Buckland, Department of Neuropathology, University of Sydney.

Hartmann and colleagues used an antibody which specifically detected the R132 mutation in IDH1 allowing assessment with simple immunohistochemistry (Hartmann et al. 2010). (Figure 4). The mutation was detected in 72% low grade astrocytomas (AII; n=227); 64% anaplastic astrocytomas (AA; n=228); 82% low grade oligodendroglioma (OII; n=128); 70% anaplastic oligodendroglioma (AO; n=174); 82% low grade oligoastrocytomas (OAII; n=76); 66% anaplastic oligoastrocytoma (AOA; n=177) and 9% glioblastoma (GBM; n=521). What was most significant about this study was the progression free and overall survival curves.

Biomarker Discovery, Validation and Clinical

IDH1 in GBMs that don't possess the mutation.

analysed than what we previously assumed.

promoter methylation as a predictive test.

**4. Use of biomarkers in clinical trials** 

to radiotherapy itself.

promoter methylation.

**3. Use as predictive biomarkers** 

Application for Patients Diagnosed with Glioma 59

IDH1 mutations conferred a significantly longer time to treatment failure (TTF) which was independent of histology, treatment, codeletion of 1p and 19q and MGMT promoter methylation status (Wick et al. 2009). IDH1 mutations as well as the gCIMP represent a significant breakthrough in how we diagnose patients. Testing for IDH1 mutations has quickly translated into routine diagnostic use. No doubt, IDH1 mutations and perhaps the gCIMP will be used to stratify patients for future clinical trials. Attention has shifted to examining therapeutic targets for IDH1 as well as the possibility of inducing mutations in

Biomarkers which can foretell whether patients are resistant to a certain treatment and predict drug sensitivity are urgently needed. The success rate of matching biomarkers with treatments has been less than satisfactory. Fewer than 100 biomarkers have been validated for routine clinical practice, despite the publication of more than 150,000 claimed biomarkers. Impeding the successful translation of biomarkers into the clinical setting is non-standardised biological specimen and clinical data collection, particularly clinical information pertaining to drug sensitivity and progression free survival. In addition, far greater numbers of tumour specimens from patients treated uniformly may be needed to be

The only biomarker with reported predictive value is MGMT promoter methylation. As discussed earlier in the MGMT section, the role of MGMT is to protect cells from alkylating damage specifically by removing the alkyl adducts from the O6 position of guanine and the O4 position of thymine and effectively restoring the DNA bases and prevent TMZ-induced cell death. However, the present NOA-04 trial does not support the suggestion that *MGMT* promoter methylation is simply predictive for response to alkylating chemotherapy (Wick et al. 2009). NOA-04 showed a striking difference in PFS between patients with versus without *MGMT* promoter methylation who were treated with radiotherapy alone. Thus *MGMT* promoter hypermethylation in anaplastic gliomas may be regarded as (1) a prognostic marker for good outcome in patients treated with radiotherapy or (2) predictive for response

The most significant issue with implementing MGMT promoter methylation as a predictive test for TMZ therapy is that there is currently no alternative treatment strategy available for those patients with unmethylated MGMT tumours. Until alternative treatments are available and the MGMT test is more reliable and robust, will clinicians consider MGMT

Co-deletion of the chromosomal arms 1p and 19q is a requirement for entry of anaplastic gliomas into the CODEL study which is assessing the role of concomitant and adjuvant temozolomide added to standard radiotherapy and has temozolomide monotherapy in an observation arm. A phase III randomized sister study to CODEL, CATNON, examines radiotherapy with or without concurrent and/or adjuvant temozolomide in patients with non-1p/19q deleted anaplastic gliomas (Figure 5). This type of dual study design allows for the patient populations to be enriched in a specific marker, yet it doesn't exclude either tumour types (codeleted and nondeleted 1p/19q). All specimens will also be tested for MGMT

In order of most favourable to poor survival: (1) AA with IDH1 mutation, (2) GBM with IDH1 mutation, (3) AA with IDH1 wild type and (4) GBM with IDH1 wild type. Routine testing for IDH1 mutations will have clinical ramifications regarding histological diagnosis and treatment schemes. The IDH1 mutation is of greater prognostic relevance than histopathological diagnosis according to the World Health Organisation (WHO) classification system (Hartmann et al. 2010). Subsidised treatment schemes approved for glioblastoma such as concomitant radiotherapy and temozolomide and bevacizumab (USA only) may need to be revised to allow anaplastic gliomas with IDH1 wild type status to be treated.

Mutations of the codons in IDH1 and 2 lead to a loss in the production of α-ketoglutarate and a gain of the catalytic activity to produce 2-hydroxyglutarate (2-HG) (Xu et al. 2011). 2- HG levels are highly elevated in IDH-mutated cancers and lead to genome wide histone and DNA methylation alterations (Xu et al., 2011; Dang et al., 2009). Hypermethylation at a large number of loci have been associated with IDH-mutated glioma suggesting that IDH mutation is associated with a distinct DNA methylation phenotype (Noushmehr et al. 2010; Christensen et al. 2011). GoldenGate array methylation data was obtained from 131 glioma patients (all types and histological grades) to interrogate methylation patterns associated with IDH mutation and survival. IDH1 mutations were present in 60% of tumours. Distinct differences between the numbers of significantly differentially hypermethylated loci were noted in IDH mutant tumours compared to IDH wild type tumours. Specific to IDH mutant tumours, cellular signalling pathways were hypermethylated whilst metabolism and biosynthesis pathways were hypermethylated (Christensen et al. 2011). This might be compensatory for the metabolic stress related to the mutation.

In a series of elegant *in vitro*-based experiments, Yan's group transformed human oligodendroglial (HOG) cells with IDH1-R132 or treated cells with 2-HG (Yan et al. 2009). They noted changes in gene expression common to both IDH1-R132 cells and 2-HG-treated cells when compared to IDH1-wildtype and untreated cells, implying that these changes were the result of increased 2HG (Reitman et al. 2010; Reitman&Yan 2010). However, reductions in glutamate and several glutamate-related metabolites were observed exclusively in the IDH1-R132 cells. Particular attention was paid to reduced levels of a common dipeptide in the brain, N-acetyl-aspartyl-glutamate (NAAG), however its contribution to pathogenesis remains unclear (Reitman et al. 2011).

Recently, IDH mutations have been shown to be tightly associated with the presence of a glioma CpG island methylator phenotype (gCIMP) (Noushmehr et al. 2010). CIMPs are characterised by highly concordant DNA methylation of a subset of loci. Improved survival was observed in gliomas with IDH1 mutation and positive for gCIMP suggesting that there are molecular features within gCIMP gliomas that encourage a less aggressive phenotype. CIMP positive colon cancers also have a better prognosis. It is not known whether glioma cells acquire the mutation in IDH1 which then leads to genome histone and DNA methylation patterns, reflected by the presence of a gCIMP or that transcriptional silencing of gCIMP targets may provide the optimal environment for gliomas to acquire the mutation (genomic instability) (Noushmehr et al. 2010).

Gliomas with IDH1 mutations as well as the presence of gCIMP displayed significantly better overall survival (median survival: 2.9 years) compared to all other patients (median survival: 1.04 years). The favourable survival observed in IDH1 mutation-gCIMP positive gliomas may be because these tumours are highly represented in the proneural subset of gliomas. Clinically, the prognostic utility of IDH1 mutations emerged in the NOA-04 trial.

In order of most favourable to poor survival: (1) AA with IDH1 mutation, (2) GBM with IDH1 mutation, (3) AA with IDH1 wild type and (4) GBM with IDH1 wild type. Routine testing for IDH1 mutations will have clinical ramifications regarding histological diagnosis and treatment schemes. The IDH1 mutation is of greater prognostic relevance than histopathological diagnosis according to the World Health Organisation (WHO) classification system (Hartmann et al. 2010). Subsidised treatment schemes approved for glioblastoma such as concomitant radiotherapy and temozolomide and bevacizumab (USA only) may need to be revised to allow anaplastic gliomas with IDH1 wild type status to be

Mutations of the codons in IDH1 and 2 lead to a loss in the production of α-ketoglutarate and a gain of the catalytic activity to produce 2-hydroxyglutarate (2-HG) (Xu et al. 2011). 2- HG levels are highly elevated in IDH-mutated cancers and lead to genome wide histone and DNA methylation alterations (Xu et al., 2011; Dang et al., 2009). Hypermethylation at a large number of loci have been associated with IDH-mutated glioma suggesting that IDH mutation is associated with a distinct DNA methylation phenotype (Noushmehr et al. 2010; Christensen et al. 2011). GoldenGate array methylation data was obtained from 131 glioma patients (all types and histological grades) to interrogate methylation patterns associated with IDH mutation and survival. IDH1 mutations were present in 60% of tumours. Distinct differences between the numbers of significantly differentially hypermethylated loci were noted in IDH mutant tumours compared to IDH wild type tumours. Specific to IDH mutant tumours, cellular signalling pathways were hypermethylated whilst metabolism and biosynthesis pathways were hypermethylated (Christensen et al. 2011). This might be

In a series of elegant *in vitro*-based experiments, Yan's group transformed human oligodendroglial (HOG) cells with IDH1-R132 or treated cells with 2-HG (Yan et al. 2009). They noted changes in gene expression common to both IDH1-R132 cells and 2-HG-treated cells when compared to IDH1-wildtype and untreated cells, implying that these changes were the result of increased 2HG (Reitman et al. 2010; Reitman&Yan 2010). However, reductions in glutamate and several glutamate-related metabolites were observed exclusively in the IDH1-R132 cells. Particular attention was paid to reduced levels of a common dipeptide in the brain, N-acetyl-aspartyl-glutamate (NAAG), however its

Recently, IDH mutations have been shown to be tightly associated with the presence of a glioma CpG island methylator phenotype (gCIMP) (Noushmehr et al. 2010). CIMPs are characterised by highly concordant DNA methylation of a subset of loci. Improved survival was observed in gliomas with IDH1 mutation and positive for gCIMP suggesting that there are molecular features within gCIMP gliomas that encourage a less aggressive phenotype. CIMP positive colon cancers also have a better prognosis. It is not known whether glioma cells acquire the mutation in IDH1 which then leads to genome histone and DNA methylation patterns, reflected by the presence of a gCIMP or that transcriptional silencing of gCIMP targets may provide the optimal environment for gliomas to acquire the mutation

Gliomas with IDH1 mutations as well as the presence of gCIMP displayed significantly better overall survival (median survival: 2.9 years) compared to all other patients (median survival: 1.04 years). The favourable survival observed in IDH1 mutation-gCIMP positive gliomas may be because these tumours are highly represented in the proneural subset of gliomas. Clinically, the prognostic utility of IDH1 mutations emerged in the NOA-04 trial.

compensatory for the metabolic stress related to the mutation.

contribution to pathogenesis remains unclear (Reitman et al. 2011).

(genomic instability) (Noushmehr et al. 2010).

treated.

IDH1 mutations conferred a significantly longer time to treatment failure (TTF) which was independent of histology, treatment, codeletion of 1p and 19q and MGMT promoter methylation status (Wick et al. 2009). IDH1 mutations as well as the gCIMP represent a significant breakthrough in how we diagnose patients. Testing for IDH1 mutations has quickly translated into routine diagnostic use. No doubt, IDH1 mutations and perhaps the gCIMP will be used to stratify patients for future clinical trials. Attention has shifted to examining therapeutic targets for IDH1 as well as the possibility of inducing mutations in IDH1 in GBMs that don't possess the mutation.

### **3. Use as predictive biomarkers**

Biomarkers which can foretell whether patients are resistant to a certain treatment and predict drug sensitivity are urgently needed. The success rate of matching biomarkers with treatments has been less than satisfactory. Fewer than 100 biomarkers have been validated for routine clinical practice, despite the publication of more than 150,000 claimed biomarkers. Impeding the successful translation of biomarkers into the clinical setting is non-standardised biological specimen and clinical data collection, particularly clinical information pertaining to drug sensitivity and progression free survival. In addition, far greater numbers of tumour specimens from patients treated uniformly may be needed to be analysed than what we previously assumed.

The only biomarker with reported predictive value is MGMT promoter methylation. As discussed earlier in the MGMT section, the role of MGMT is to protect cells from alkylating damage specifically by removing the alkyl adducts from the O6 position of guanine and the O4 position of thymine and effectively restoring the DNA bases and prevent TMZ-induced cell death. However, the present NOA-04 trial does not support the suggestion that *MGMT* promoter methylation is simply predictive for response to alkylating chemotherapy (Wick et al. 2009). NOA-04 showed a striking difference in PFS between patients with versus without *MGMT* promoter methylation who were treated with radiotherapy alone. Thus *MGMT* promoter hypermethylation in anaplastic gliomas may be regarded as (1) a prognostic marker for good outcome in patients treated with radiotherapy or (2) predictive for response to radiotherapy itself.

The most significant issue with implementing MGMT promoter methylation as a predictive test for TMZ therapy is that there is currently no alternative treatment strategy available for those patients with unmethylated MGMT tumours. Until alternative treatments are available and the MGMT test is more reliable and robust, will clinicians consider MGMT promoter methylation as a predictive test.

#### **4. Use of biomarkers in clinical trials**

Co-deletion of the chromosomal arms 1p and 19q is a requirement for entry of anaplastic gliomas into the CODEL study which is assessing the role of concomitant and adjuvant temozolomide added to standard radiotherapy and has temozolomide monotherapy in an observation arm. A phase III randomized sister study to CODEL, CATNON, examines radiotherapy with or without concurrent and/or adjuvant temozolomide in patients with non-1p/19q deleted anaplastic gliomas (Figure 5). This type of dual study design allows for the patient populations to be enriched in a specific marker, yet it doesn't exclude either tumour types (codeleted and nondeleted 1p/19q). All specimens will also be tested for MGMT promoter methylation.

Biomarker Discovery, Validation and Clinical

**5. Targeted therapies for glioblastoma** 

Application for Patients Diagnosed with Glioma 61

Molecular targeted therapies specifically inhibit amplified or aberrant proteins that drive tumour cell growth. The key to targeted therapy is identifying a target whose *inhibition will stop the growth of the tumour cell*. Whilst this field has rapidly developed, our understanding at the molecular level of the precise role that potential targets have in tumorigenesis and the survival dependence that tumours have on these components has not progressed at the same rate. Unlike melanoma, lung and breast cancer, glioblastoma lacks significant driver mutations which are present in ample abundance and in all tumours. The TCGA analysis revealed a wide spectrum of molecular variation in glioblastoma. TCGA used global gene expression analysis to show aberrations occurred more commonly in genes whose protein products regulated the core cell growth signalling pathways that were already known to be important such as EGFR, PTEN, p53 and CDKN2A. One pathway which is frequently dysregulated is the receptor tyrosine kinase (RTK)/phosphatidylinositol 3-kinase (PI3K)/Akt/mammalian target of rapamycin (mTOR) cascade. Approximately 86% of clinical samples analysed by the TCGA with both copy number and sequencing data had a genetic alteration in the RTK/PI3K pathway (Parsons et al. 2008). In addition, genetic alterations in two other core pathways; RB (87%) and TP53 (78%) were documented. At the time (3 years ago now) it was reasonable to suggest that all tumours be sequenced and the genetic aberrations be documented before selecting the targeted therapy. For example, for tumours with alterations in CDKN2A or CDKN2C or amplifications in CDK4 or CDK6, a CDK inhibitor should be recommended. Unfortunately, we underestimated the extent of genomic complexity and it is very doubtful that therapies targeted to a single genetic change will ever be effective. A range of molecular targeted drugs applied in combination or in addition to each other is needed (Jansen et al. 2010). In clinical practice, the multi-drug approach is currently limited by intellectual property. Most likely the efficacy of two drugs

may require two competing pharmaceutical companies to work together.

**5.1 Targeting the RTK/PI3K pathway** 

with response.

much more prominent such as KRAS or BRAF, valuable lessons can still be learnt.

To understand why our current single targeted therapies are ineffective, it is useful to examine the earlier clinical studies with EGFR- and VEGF-targeted drugs. We can also glean value from trials using targeted therapy in other cancers. Even when the target of interest is

In a study of 49 patients with recurrent glioblastoma, tumour shrinkage was evident in 9 patients (25%) (Mellinghoff et al. 2005). Logically, it was of great interest to better understand the underlying molecular biology of these 9 responders. Pre-treatment tissue was only available for 7 of the responding patients and 19 patients who did not respond. The authors found coexpression of EGFRvIII and PTEN sensitised glioblastoma to erlotinib and correctly validated this finding in tissue samples from different institutions undergoing similar treatment (n=33) (Mellinghoff et al. 2005). Unfortunately, the relationship between EGFRvIII and intact PTEN co-expression did not translate to the subsequent prospective phase I/II trials (Brown et al. 2008; van den Bent et al. 2009). No relationship between aberrations in the RTK core and the EGFR inhibitor, lapatinib (Thiessen et al. 2010) or addition of erlotinib with the mTOR inhibitor, sirolimus (Reardon et al. 2010) were linked

Fig. 5. Overview of the CATNON and CODEL trials

A phase I/IIa trial examined the effectiveness of adding cilengitide to concurrent chemoradiotherapy (Stupp et al. 2010). This study demonstrated the effectiveness of cilengitide but also showed that there was a clear survival benefit in the patients with MGMT promoter methylation (Stupp et al. 2010). The phase III CENTRIC trial (recruitment closed in Feb, 2011) restricted recruitment to newly diagnosed GBM patients with confirmed MGMT methylation. An additional two phase II trials sponsored by the pharmaceutical company, EMD Serono, are designed to treat patients with unmethylated MGMT: CORE (Cilengitide, Temozolomide, and Radiation Therapy in Treating Patients with Newly Diagnosed Glioblastoma and Unmethylated Gene Promoter Status) and ExCentric. CORE (trial still open; May 2011) examines the efficacy of increasing the dose schedule of cilengitide (2000mg twice weekly and 2000mg five times per week) versus standard concurrent chemoradiotherapy (without cilengitide). The ExCentric trial (recruitment open, May 2011) has taken a much different approach. In this trial, procarbazine is added to the concurrent schedule of radiotherapy, TMZ, cilengitide and patients will be treated adjuvantly for an additional 6 cycles with the triple cocktail of cilengitide, TMZ and procarbazine. The patients have so far shown excellent toleration of this combination.

The RTOG-0825 examines the effect of bevacizumab administered with radiotherapy compared to conventional concurrent chemoradiotherapy (TMZ) in primary GBM. All patients enrolled in this study will be tested for MGMT promoter methylation. Unique to this study, however, all samples will be prospectively tested with the nine-gene profile which separates the proneural GBM from the mesenchymal-angiogenic GBM (Colman et al. 2010). It is becoming mandatory for future trial design to incorporate molecular inclusion criteria to identify the poorly responding patients from the patients who benefit.

CODELETED

A phase I/IIa trial examined the effectiveness of adding cilengitide to concurrent chemoradiotherapy (Stupp et al. 2010). This study demonstrated the effectiveness of cilengitide but also showed that there was a clear survival benefit in the patients with MGMT promoter methylation (Stupp et al. 2010). The phase III CENTRIC trial (recruitment closed in Feb, 2011) restricted recruitment to newly diagnosed GBM patients with confirmed MGMT methylation. An additional two phase II trials sponsored by the pharmaceutical company, EMD Serono, are designed to treat patients with unmethylated MGMT: CORE (Cilengitide, Temozolomide, and Radiation Therapy in Treating Patients with Newly Diagnosed Glioblastoma and Unmethylated Gene Promoter Status) and ExCentric. CORE (trial still open; May 2011) examines the efficacy of increasing the dose schedule of cilengitide (2000mg twice weekly and 2000mg five times per week) versus standard concurrent chemoradiotherapy (without cilengitide). The ExCentric trial (recruitment open, May 2011) has taken a much different approach. In this trial, procarbazine is added to the concurrent schedule of radiotherapy, TMZ, cilengitide and patients will be treated adjuvantly for an additional 6 cycles with the triple cocktail of cilengitide, TMZ and procarbazine. The patients have so far shown excellent toleration of

The RTOG-0825 examines the effect of bevacizumab administered with radiotherapy compared to conventional concurrent chemoradiotherapy (TMZ) in primary GBM. All patients enrolled in this study will be tested for MGMT promoter methylation. Unique to this study, however, all samples will be prospectively tested with the nine-gene profile which separates the proneural GBM from the mesenchymal-angiogenic GBM (Colman et al. 2010). It is becoming mandatory for future trial design to incorporate molecular inclusion

criteria to identify the poorly responding patients from the patients who benefit.

CATNON CODEL

CENTRAL PATH: ANAPLASTIC O/OA LOH 1p19q

RANDOMISATION

CONCURRENT RT/TMZ + ADJ TMZ RT ONLY TMZ

200mg/m2 (12 cy)

*3 ARMS UP TO PATIENT 150 2 ARMS UP TO PATIENT 488*

SURGERY

NON-DELETED LOH

MGMT

RANDOMISATION

II I

CONCURRENT RT/TMZ RT ONLY

IV

this combination.

ADJUVANT CHEMOTHERAPY NO ADJUVANT TREATMENT

III

FOLLOW-UP

Fig. 5. Overview of the CATNON and CODEL trials

#### **5. Targeted therapies for glioblastoma**

Molecular targeted therapies specifically inhibit amplified or aberrant proteins that drive tumour cell growth. The key to targeted therapy is identifying a target whose *inhibition will stop the growth of the tumour cell*. Whilst this field has rapidly developed, our understanding at the molecular level of the precise role that potential targets have in tumorigenesis and the survival dependence that tumours have on these components has not progressed at the same rate. Unlike melanoma, lung and breast cancer, glioblastoma lacks significant driver mutations which are present in ample abundance and in all tumours. The TCGA analysis revealed a wide spectrum of molecular variation in glioblastoma. TCGA used global gene expression analysis to show aberrations occurred more commonly in genes whose protein products regulated the core cell growth signalling pathways that were already known to be important such as EGFR, PTEN, p53 and CDKN2A. One pathway which is frequently dysregulated is the receptor tyrosine kinase (RTK)/phosphatidylinositol 3-kinase (PI3K)/Akt/mammalian target of rapamycin (mTOR) cascade. Approximately 86% of clinical samples analysed by the TCGA with both copy number and sequencing data had a genetic alteration in the RTK/PI3K pathway (Parsons et al. 2008). In addition, genetic alterations in two other core pathways; RB (87%) and TP53 (78%) were documented. At the time (3 years ago now) it was reasonable to suggest that all tumours be sequenced and the genetic aberrations be documented before selecting the targeted therapy. For example, for tumours with alterations in CDKN2A or CDKN2C or amplifications in CDK4 or CDK6, a CDK inhibitor should be recommended. Unfortunately, we underestimated the extent of genomic complexity and it is very doubtful that therapies targeted to a single genetic change will ever be effective. A range of molecular targeted drugs applied in combination or in addition to each other is needed (Jansen et al. 2010). In clinical practice, the multi-drug approach is currently limited by intellectual property. Most likely the efficacy of two drugs may require two competing pharmaceutical companies to work together.

To understand why our current single targeted therapies are ineffective, it is useful to examine the earlier clinical studies with EGFR- and VEGF-targeted drugs. We can also glean value from trials using targeted therapy in other cancers. Even when the target of interest is much more prominent such as KRAS or BRAF, valuable lessons can still be learnt.

#### **5.1 Targeting the RTK/PI3K pathway**

In a study of 49 patients with recurrent glioblastoma, tumour shrinkage was evident in 9 patients (25%) (Mellinghoff et al. 2005). Logically, it was of great interest to better understand the underlying molecular biology of these 9 responders. Pre-treatment tissue was only available for 7 of the responding patients and 19 patients who did not respond. The authors found coexpression of EGFRvIII and PTEN sensitised glioblastoma to erlotinib and correctly validated this finding in tissue samples from different institutions undergoing similar treatment (n=33) (Mellinghoff et al. 2005). Unfortunately, the relationship between EGFRvIII and intact PTEN co-expression did not translate to the subsequent prospective phase I/II trials (Brown et al. 2008; van den Bent et al. 2009). No relationship between aberrations in the RTK core and the EGFR inhibitor, lapatinib (Thiessen et al. 2010) or addition of erlotinib with the mTOR inhibitor, sirolimus (Reardon et al. 2010) were linked with response.

Biomarker Discovery, Validation and Clinical

Application for Patients Diagnosed with Glioma 63

clear-cut evidence of a response or tumour progression had sufficient tissue for molecular analysis. Hence, just over half of the originally small cohort was analysed for molecular biomarkers. The validation study used a different tissue type entirely as only paraffinembedded slides were available. Again, this material was untreated tumour tissue, not the recurrent lesion. The validation set was extremely underpowered (n=33) with only 8 responders identified in this dataset. It is imperative that collaborations between different institutes and countries work together to increase the power of these biomarker studies.

Assays for biomarkers need to be reliable. The assay needs to give identical results if repeated in the same or in another laboratory. The result needs to be the same, even when different methodologies are used. And finally, we need to ask whether the test provides added value to clinical practice. This has often been a strong criticism of studies incorporating MGMT promoter methylation (as discussed previously) and unfortunately the same issues surround biomarkers for targeted therapies. The original study by Mellinghoff and colleagues used immunohistochemistry (IHC) to assess PTEN expression (Mellinghoff et al. 2005). The problem with this approach is the antibody used does not detect the full length PTEN protein. Should mutations arise in the C-terminal end of the protein, these would go undiscovered using IHC assay. IHC for EGFR is also contentious. EGFR overexpression in GBM is generally driven by EGFR amplification. The scoring of EGFR IHC can be variable and different antibodies have different specificities to the EGFR protein. Amplification of EGFR or more specifically gain of copy number is most commonly detected by fluorescence *in situ* hybridization (FISH) and can be routinely performed in most histopathological laboratories. What is puzzling is the lack of sequencing of both EGFR and PTEN genes in the subsequent phase I/II clinical trials assessing TKIs. The most frequent mutant form of EGFR is EGFR Variant III (EGFRvIII or EGFR delta) which is missing the ligand –binding domain resulting in the constitutive activation of the EGFRphosphoinositide 3-kinase pathway. IHC specific to the EGFRvIII mutant form is highly specific as too is the commonly used RT-PCR method. However, there are additional missense mutations encoding extracellular EGFR that have been shown to drive oncogenesis

**5.3.1 A lack of standardisation in the methods used for marker measurement** 

*in vitro* and can be inhibited by small-molecular tyrosine kinase inhibitors.

The original pre-clinical/clinical study sequenced all exons and flanking intronic sequences for EGFR (kinase domain), the HER2/neu (kinase domain) and all exons of PTEN. FISH was also performed to detect EGFR amplification and RT-PCR was used to amplify EGFR (1044 bp product) and EGFRvIII (243-bp product). In addition, EGFR and PTEN were examined with IHC (Mellinghoff et al. 2005). 26 of the 49 patients underwent sequencing, which included 6 patients who showed a response to erlotinib. No mutations were found. Van den Bent and colleagues assessed the benefits of erlotinib compared to temozolomide or cumustine in recurrent GBM in a randomized phase II study (van den Bent et al. 2009). Obtaining full data for all patients in this study was problematic. From 100 patients, PTEN expression could be determined in 82 patient cases and pAKT in 64 patients. Like the Mellinghoff study, no mutations in EGFR were detected, however only exons 19 to 21 were assessed. Although an association between EGFRvIII and EGFR amplification with poor overall survival was shown, no correlation between response and the co-expression of PTEN and EGFR was measured (van den Bent et al. 2009). In fact, no significant activity of erlotinib was observed. In another study of 65 patients, erlotinib efficacy was assessed in

#### **5.2 Targeting angiogenesis**

The development of anti-angiogenic agents for glioblastoma have been promising and include bevacizumab (Vascular endothelial growth factor [VEGF] antibody), cediranib (VEGF receptor antagonist), cilengitide (mentioned previously; integrin antagonist) and Enzastaurin (Protein Kinase-C-β-antagonist).

The preclinical and clinical data for cediranib treatment in glioblastoma looked very promising (Dietrich et al. 2009; Gerstner et al. 2011). Unfortunately, the International Multicentre Phase III trial, REGAL was negative. The REGAL study compared the use of cediranib alone, cediranib in combination with lomustine and lomustine plus placebo. In the 325 patients with recurrent GBM studied, only 16% treated with cediranib monotherapy were alive and progression free at 6 months (APF6) compared to 34.5% in the combination group and 24.5% in the lomustine plus placebo group (results reported by T. Batchelor at the Society of Neuro-oncology Annual Meeting, 2010; (Ahluwalia 2011)). Akin to cediranib, preclinical and studies of enzastaurin showed good anti-glioma activity but failed to show any significant benefits when trialled in a phase III study comparing enzastaurin to lomustine. Although less toxicity was observed with enzastaurin, no significant differences in median progression free survival and overall survival were observed (Wick et al. 2011). The humanized antibody, Bevacizumab (Avastin), has received the most attention, with Food and Drug Administration (FDA) approval for use in recurrent GBM in the USA. No such approvals have been obtained in Europe and Australia. This is predominantly because there is only a modest overall survival benefit of 7.8-9.2 months suggesting a further improvement of efficacy is needed. Numerous phase II studies have shown modest survival benefits with bevacizumab either as a monotherapy or in combination with irinotecan (Chinot et al. 2011; Jakobsen et al. 2011; Lai et al. 2011; Prados et al. 2011; Reardon et al. 2011). Consistent to all trials examining bevacizumab efficacy is the reduction of steroids for patients and valuable palliation with preservation of key performance status (KPS), supporting a role for bevacizumab as a therapy in late stage disease (Hofer et al. 2011). Whether bevacizumab results in true glioma cell destruction or is it merely its ability to control the perivascular leak, resulting in better symptom control (associated with improvement of gadolinium MRI) needs to be elucidated.

An issue consistent with all trials of cediranib, enzastaurin and bevacizumab is their testing on recurrent glioblastoma as opposed to primary glioblastoma. Recurrent glioblastoma are already highly refractory to treatment and the potential benefits of these drugs may be missed. New studies are investigating bevacizumab up front with standard radiation therapy and temozolomide. This has shown to be well tolerated (Vredenburgh et al. 2011) and it is a strategy that the RTOG-0825 trial has incorporated (discussed previously).

With all of these targeted therapies, it would seem obvious that the more target present, the more efficacious the drug. Unfortunately, this has not been the case. For example, why patients with high expression of VEGF have not shown strong response to bevacizumab? These issues pertaining to biomarkers in targeted therapy trials will be discussed in turn below:

#### **5.3 Many retrospective analyses of single arm investigations are performed in small and often heterogeneous cohorts of patients**

The co-expression of EGFRvIII and PTEN was first discovered in an initial test set consisting of 49 recurrent GBM treated with either gefitinib (n=37) or erlotinib (n=12). 26 patients with

The development of anti-angiogenic agents for glioblastoma have been promising and include bevacizumab (Vascular endothelial growth factor [VEGF] antibody), cediranib (VEGF receptor antagonist), cilengitide (mentioned previously; integrin antagonist) and

The preclinical and clinical data for cediranib treatment in glioblastoma looked very promising (Dietrich et al. 2009; Gerstner et al. 2011). Unfortunately, the International Multicentre Phase III trial, REGAL was negative. The REGAL study compared the use of cediranib alone, cediranib in combination with lomustine and lomustine plus placebo. In the 325 patients with recurrent GBM studied, only 16% treated with cediranib monotherapy were alive and progression free at 6 months (APF6) compared to 34.5% in the combination group and 24.5% in the lomustine plus placebo group (results reported by T. Batchelor at the Society of Neuro-oncology Annual Meeting, 2010; (Ahluwalia 2011)). Akin to cediranib, preclinical and studies of enzastaurin showed good anti-glioma activity but failed to show any significant benefits when trialled in a phase III study comparing enzastaurin to lomustine. Although less toxicity was observed with enzastaurin, no significant differences in median progression free survival and overall survival were observed (Wick et al. 2011). The humanized antibody, Bevacizumab (Avastin), has received the most attention, with Food and Drug Administration (FDA) approval for use in recurrent GBM in the USA. No such approvals have been obtained in Europe and Australia. This is predominantly because there is only a modest overall survival benefit of 7.8-9.2 months suggesting a further improvement of efficacy is needed. Numerous phase II studies have shown modest survival benefits with bevacizumab either as a monotherapy or in combination with irinotecan (Chinot et al. 2011; Jakobsen et al. 2011; Lai et al. 2011; Prados et al. 2011; Reardon et al. 2011). Consistent to all trials examining bevacizumab efficacy is the reduction of steroids for patients and valuable palliation with preservation of key performance status (KPS), supporting a role for bevacizumab as a therapy in late stage disease (Hofer et al. 2011). Whether bevacizumab results in true glioma cell destruction or is it merely its ability to control the perivascular leak, resulting in better symptom control (associated with

An issue consistent with all trials of cediranib, enzastaurin and bevacizumab is their testing on recurrent glioblastoma as opposed to primary glioblastoma. Recurrent glioblastoma are already highly refractory to treatment and the potential benefits of these drugs may be missed. New studies are investigating bevacizumab up front with standard radiation therapy and temozolomide. This has shown to be well tolerated (Vredenburgh et al. 2011)

With all of these targeted therapies, it would seem obvious that the more target present, the more efficacious the drug. Unfortunately, this has not been the case. For example, why patients with high expression of VEGF have not shown strong response to bevacizumab? These issues pertaining to biomarkers in targeted therapy trials will be discussed in turn

**5.3 Many retrospective analyses of single arm investigations are performed in small** 

The co-expression of EGFRvIII and PTEN was first discovered in an initial test set consisting of 49 recurrent GBM treated with either gefitinib (n=37) or erlotinib (n=12). 26 patients with

and it is a strategy that the RTOG-0825 trial has incorporated (discussed previously).

**5.2 Targeting angiogenesis** 

Enzastaurin (Protein Kinase-C-β-antagonist).

improvement of gadolinium MRI) needs to be elucidated.

**and often heterogeneous cohorts of patients** 

below:

clear-cut evidence of a response or tumour progression had sufficient tissue for molecular analysis. Hence, just over half of the originally small cohort was analysed for molecular biomarkers. The validation study used a different tissue type entirely as only paraffinembedded slides were available. Again, this material was untreated tumour tissue, not the recurrent lesion. The validation set was extremely underpowered (n=33) with only 8 responders identified in this dataset. It is imperative that collaborations between different institutes and countries work together to increase the power of these biomarker studies.

#### **5.3.1 A lack of standardisation in the methods used for marker measurement**

Assays for biomarkers need to be reliable. The assay needs to give identical results if repeated in the same or in another laboratory. The result needs to be the same, even when different methodologies are used. And finally, we need to ask whether the test provides added value to clinical practice. This has often been a strong criticism of studies incorporating MGMT promoter methylation (as discussed previously) and unfortunately the same issues surround biomarkers for targeted therapies. The original study by Mellinghoff and colleagues used immunohistochemistry (IHC) to assess PTEN expression (Mellinghoff et al. 2005). The problem with this approach is the antibody used does not detect the full length PTEN protein. Should mutations arise in the C-terminal end of the protein, these would go undiscovered using IHC assay. IHC for EGFR is also contentious. EGFR overexpression in GBM is generally driven by EGFR amplification. The scoring of EGFR IHC can be variable and different antibodies have different specificities to the EGFR protein. Amplification of EGFR or more specifically gain of copy number is most commonly detected by fluorescence *in situ* hybridization (FISH) and can be routinely performed in most histopathological laboratories. What is puzzling is the lack of sequencing of both EGFR and PTEN genes in the subsequent phase I/II clinical trials assessing TKIs. The most frequent mutant form of EGFR is EGFR Variant III (EGFRvIII or EGFR delta) which is missing the ligand –binding domain resulting in the constitutive activation of the EGFRphosphoinositide 3-kinase pathway. IHC specific to the EGFRvIII mutant form is highly specific as too is the commonly used RT-PCR method. However, there are additional missense mutations encoding extracellular EGFR that have been shown to drive oncogenesis *in vitro* and can be inhibited by small-molecular tyrosine kinase inhibitors.

The original pre-clinical/clinical study sequenced all exons and flanking intronic sequences for EGFR (kinase domain), the HER2/neu (kinase domain) and all exons of PTEN. FISH was also performed to detect EGFR amplification and RT-PCR was used to amplify EGFR (1044 bp product) and EGFRvIII (243-bp product). In addition, EGFR and PTEN were examined with IHC (Mellinghoff et al. 2005). 26 of the 49 patients underwent sequencing, which included 6 patients who showed a response to erlotinib. No mutations were found. Van den Bent and colleagues assessed the benefits of erlotinib compared to temozolomide or cumustine in recurrent GBM in a randomized phase II study (van den Bent et al. 2009). Obtaining full data for all patients in this study was problematic. From 100 patients, PTEN expression could be determined in 82 patient cases and pAKT in 64 patients. Like the Mellinghoff study, no mutations in EGFR were detected, however only exons 19 to 21 were assessed. Although an association between EGFRvIII and EGFR amplification with poor overall survival was shown, no correlation between response and the co-expression of PTEN and EGFR was measured (van den Bent et al. 2009). In fact, no significant activity of erlotinib was observed. In another study of 65 patients, erlotinib efficacy was assessed in

Biomarker Discovery, Validation and Clinical

**5.3.3 Not all mutations within a given gene are screened** 

implicated in cancer (Dienstmann&Tabernero 2011; Puzanov et al. 2011).

(Humphreys et al. 2005; Pillai et al. 2005; Esquela-Kerscher&Slack 2006).

**5.3.4 A pathway-centric approach is needed** 

VEGF.

Application for Patients Diagnosed with Glioma 65

or vessel co-option. A commonly held theory is that recurrent glioblastomas switch their growth pattern after anti-VEGF treatment (di Tomaso et al. 2011). The tumour cells are exposed to an increased hypoxic environment leading to increased migration, invasion, heightened glycolysis and increased PI3K pathway activation. Combining bevacizumab with anti-glycolytic agents or PI3K inhibitors might be more effective. Tumour-initiating CD133+ve cells are radio-resistant and can self renew to reform tumours, suggesting that these cells are responsible for tumour relapse (Liu et al. 2009). More significantly, exposure to bevacizumab inhibited the maturation of tumour endothelial progenitors into the endothelium but not the differentiation of CD133+ cells into progenitor cells (Wang et al. 2011). This fundamental study showed that there is a dynamic balance between the CD133+ cell population and tumour cells and we need to target the endothelial transition as well as

In simplistic terms, the plethora of TKIs are designed to be effective on patients harbouring EGFR mutations. However, in the majority of studies exploring gefitinib and erlotinib, the EGFR gene is not fully sequenced to identify variants and mutations. TCGA analyses have identified a high diversity of genes mutated within glioblastoma. As prices drop with Next Generation sequencing, capabilities to better define precise genetic aberrations associated with response to a specific treatment will improve. Copy number aberrations (amplifications and deletions) and structural aberrations (intra-chromosomal rearrangements- inversions, inverted/tandem duplications) are not detected using traditional Sanger sequencing in the lab. Our ability to assess these aberrations must improve at the rate that new targeted therapies are flooding the market. BRAF is a commonly deleted gene in approximately 8% of solid tumours, however over 30 different mutations in the BRAF gene have been

As eluded to in our discussion of multiple pathways and feedback loops in any given target, we need to develop ways to target multiple points of a pathway akin to attacking the Achilles heel of the tumour. Recent data suggest that miRNA expression is tightly coordinated, and that each miRNA may target numerous messages. Thus, a specific miRNA has the potential to regulate several members of an entire signalling pathway. miRNAs negatively regulate their targets by one of two mechanisms: either by near perfect binding to the mRNA target and induction of miRNA-associated, multiprotein RNA-induced-silencing complex (miRISC), which results in accelerated mRNA decay (Yekta 2004; Wu 2006) or by less perfect binding to the target mRNA 3'-UTR and inhibition of translation through a RISC complex similar to, or identical with, the complex recruited in RNA interference (RNAi)

miR-7 directly regulates the expression of EGFR in glioblastoma and has also been shown to directly attenuate the activation of AKT and ERK1/2 (extracellular signal-regulated kinase) indicating its ability to co-ordinately regulate EGFR signalling (Webster et al. 2009). We also showed that miR-124a attenuated glioblastoma migration and invasion at multiple points of the pathway (Fowler et al. 2011). New technologies are currently being developed to facilitate the use of miRNAs as a realistic therapeutic option. Until then, combination treatments and developing inhibitors which can affect a multiplicity of targets are critical.

combination with temozolomide (Prados et al. 2009). Again no association with EGFRvIII and PTEN and response was measured, however in this study, MGMT promoter methylation was associated with better response. EGFR was measured with FISH and IHC, PTEN and EGFRvIII were analysed by IHC. No mutational analysis of EGFR was undertaken. Reardon and colleagues assessed the combination of erlotinib with a mTOR inhibitor, sirolimus in recurrent GBM (Reardon et al. 2010). Again, EGFR, EGFRvIII, PTEN, PI3K and pS6 were assessed by IHC and no association for these markers with clinical response was found. Mutational analysis was not conducted. Moreover, the general methodologies did not differ in the studies addressing erlotinib and response and the Phase II studies could not validate the findings of Mellinghoff et al.

Elegant biomarker studies have been associated with the anti-angiogenic drugs. Attention has focused predominantly on secreted factors and imaging modalities. Interleukin 6 (IL-6) is over-expressed in the majority of gliomas and functions as an immune regulator and an autocrine growth factor (Saidi et al. 2009). High starting levels of IL-6 may influence the efficacy of bevacizumab as it provides redundancy for the VEGF/VEGFR pathway and promotes an immune response that stimulates angiogenesis by non-VEGF mechanisms. Sorenson et al. reported the combination of MRI imaging (measured changes in vascular permeability/flow [Ktrans] and changes in microvessel volume) and circulating collagen IV levels in plasma to be predictive of outcome in glioblastoma patients treated with cediranib (Sorensen et al. 2009). The level of circulating endothelial progenitor cells (cEPCs) and viable circulating endothelial cells (cECs) has also been shown to correlate with response (Sorensen et al. 2009). The ability to identify changes in a tumour's perfusion offers the potential to predict growth or regression. Dynamic susceptibility-weighted contrast-enhanced (DSC) MR imaging can be used to measure relative cerebral blood volume (rCBV) as a surrogate marker of perfusion. A pilot study of 16 patients with recurrent glioblastoma and treatment with bevacizumab found that MR perfusion imaging showed a significantly improved correlation with time to progression (Sawlani et al. 2011). Studies from Tsien (Tsien et al. 2011) and Server (Server et al. 2011)- both show positive results for this scan in patients with PsPD. Only changes in the hypoxia inducing factor (HIF) 2 alpha [HIF2] have been shown to be promising surrogates of response to anti-angiogenic therapies (Mao et al. 2011).

#### **5.3.2 Methodologies chosen in the study may not represent a comprehensive analysis of multiple components of a specific pathway**

None of the studies examining erlotinib have comprehensively analysed the downstream components involved in EGFR signalling. Additional testing of PI3K and PS6 were added in some studies. It is very common for glioblastomas to have dysregulated signalling cascades downstream of EGFR, particular the negative feedback loops. Several growth factor pathways are also triggered. It's not economically feasible in most instances to assess all aspects of the RTK/PI3K/AKT/mTOR signalling cascade. However, a new system of testing drugs and identifying which subtypes of glioblastoma are susceptible to the drug could be to use human glioblastoma xenograft panels serially passaged in nude mice. This model allows tumour burden to be monitored non-invasively and rapid assessment of biological pathways (Prasad et al. 2011).

Feedback mechanisms also pose an issue with targeted therapies blocking angiogenesis. Tumours frequently recur after treatment with cediranib and bevacizumab and are refractory to further treatments. There have been different theories postulated as to why this "rebound" effect occurs. Tumours may switch to VEGF-independent angiogenic pathways

combination with temozolomide (Prados et al. 2009). Again no association with EGFRvIII and PTEN and response was measured, however in this study, MGMT promoter methylation was associated with better response. EGFR was measured with FISH and IHC, PTEN and EGFRvIII were analysed by IHC. No mutational analysis of EGFR was undertaken. Reardon and colleagues assessed the combination of erlotinib with a mTOR inhibitor, sirolimus in recurrent GBM (Reardon et al. 2010). Again, EGFR, EGFRvIII, PTEN, PI3K and pS6 were assessed by IHC and no association for these markers with clinical response was found. Mutational analysis was not conducted. Moreover, the general methodologies did not differ in the studies addressing erlotinib and response and the Phase

Elegant biomarker studies have been associated with the anti-angiogenic drugs. Attention has focused predominantly on secreted factors and imaging modalities. Interleukin 6 (IL-6) is over-expressed in the majority of gliomas and functions as an immune regulator and an autocrine growth factor (Saidi et al. 2009). High starting levels of IL-6 may influence the efficacy of bevacizumab as it provides redundancy for the VEGF/VEGFR pathway and promotes an immune response that stimulates angiogenesis by non-VEGF mechanisms. Sorenson et al. reported the combination of MRI imaging (measured changes in vascular permeability/flow [Ktrans] and changes in microvessel volume) and circulating collagen IV levels in plasma to be predictive of outcome in glioblastoma patients treated with cediranib (Sorensen et al. 2009). The level of circulating endothelial progenitor cells (cEPCs) and viable circulating endothelial cells (cECs) has also been shown to correlate with response (Sorensen et al. 2009). The ability to identify changes in a tumour's perfusion offers the potential to predict growth or regression. Dynamic susceptibility-weighted contrast-enhanced (DSC) MR imaging can be used to measure relative cerebral blood volume (rCBV) as a surrogate marker of perfusion. A pilot study of 16 patients with recurrent glioblastoma and treatment with bevacizumab found that MR perfusion imaging showed a significantly improved correlation with time to progression (Sawlani et al. 2011). Studies from Tsien (Tsien et al. 2011) and Server (Server et al. 2011)- both show positive results for this scan in patients with PsPD. Only changes in the hypoxia inducing factor (HIF) 2 alpha [HIF2] have been shown

to be promising surrogates of response to anti-angiogenic therapies (Mao et al. 2011).

**5.3.2 Methodologies chosen in the study may not represent a comprehensive analysis** 

None of the studies examining erlotinib have comprehensively analysed the downstream components involved in EGFR signalling. Additional testing of PI3K and PS6 were added in some studies. It is very common for glioblastomas to have dysregulated signalling cascades downstream of EGFR, particular the negative feedback loops. Several growth factor pathways are also triggered. It's not economically feasible in most instances to assess all aspects of the RTK/PI3K/AKT/mTOR signalling cascade. However, a new system of testing drugs and identifying which subtypes of glioblastoma are susceptible to the drug could be to use human glioblastoma xenograft panels serially passaged in nude mice. This model allows tumour burden to be monitored non-invasively and rapid assessment of

Feedback mechanisms also pose an issue with targeted therapies blocking angiogenesis. Tumours frequently recur after treatment with cediranib and bevacizumab and are refractory to further treatments. There have been different theories postulated as to why this "rebound" effect occurs. Tumours may switch to VEGF-independent angiogenic pathways

II studies could not validate the findings of Mellinghoff et al.

**of multiple components of a specific pathway** 

biological pathways (Prasad et al. 2011).

or vessel co-option. A commonly held theory is that recurrent glioblastomas switch their growth pattern after anti-VEGF treatment (di Tomaso et al. 2011). The tumour cells are exposed to an increased hypoxic environment leading to increased migration, invasion, heightened glycolysis and increased PI3K pathway activation. Combining bevacizumab with anti-glycolytic agents or PI3K inhibitors might be more effective. Tumour-initiating CD133+ve cells are radio-resistant and can self renew to reform tumours, suggesting that these cells are responsible for tumour relapse (Liu et al. 2009). More significantly, exposure to bevacizumab inhibited the maturation of tumour endothelial progenitors into the endothelium but not the differentiation of CD133+ cells into progenitor cells (Wang et al. 2011). This fundamental study showed that there is a dynamic balance between the CD133+ cell population and tumour cells and we need to target the endothelial transition as well as VEGF.

#### **5.3.3 Not all mutations within a given gene are screened**

In simplistic terms, the plethora of TKIs are designed to be effective on patients harbouring EGFR mutations. However, in the majority of studies exploring gefitinib and erlotinib, the EGFR gene is not fully sequenced to identify variants and mutations. TCGA analyses have identified a high diversity of genes mutated within glioblastoma. As prices drop with Next Generation sequencing, capabilities to better define precise genetic aberrations associated with response to a specific treatment will improve. Copy number aberrations (amplifications and deletions) and structural aberrations (intra-chromosomal rearrangements- inversions, inverted/tandem duplications) are not detected using traditional Sanger sequencing in the lab. Our ability to assess these aberrations must improve at the rate that new targeted therapies are flooding the market. BRAF is a commonly deleted gene in approximately 8% of solid tumours, however over 30 different mutations in the BRAF gene have been implicated in cancer (Dienstmann&Tabernero 2011; Puzanov et al. 2011).

#### **5.3.4 A pathway-centric approach is needed**

As eluded to in our discussion of multiple pathways and feedback loops in any given target, we need to develop ways to target multiple points of a pathway akin to attacking the Achilles heel of the tumour. Recent data suggest that miRNA expression is tightly coordinated, and that each miRNA may target numerous messages. Thus, a specific miRNA has the potential to regulate several members of an entire signalling pathway. miRNAs negatively regulate their targets by one of two mechanisms: either by near perfect binding to the mRNA target and induction of miRNA-associated, multiprotein RNA-induced-silencing complex (miRISC), which results in accelerated mRNA decay (Yekta 2004; Wu 2006) or by less perfect binding to the target mRNA 3'-UTR and inhibition of translation through a RISC complex similar to, or identical with, the complex recruited in RNA interference (RNAi) (Humphreys et al. 2005; Pillai et al. 2005; Esquela-Kerscher&Slack 2006).

miR-7 directly regulates the expression of EGFR in glioblastoma and has also been shown to directly attenuate the activation of AKT and ERK1/2 (extracellular signal-regulated kinase) indicating its ability to co-ordinately regulate EGFR signalling (Webster et al. 2009). We also showed that miR-124a attenuated glioblastoma migration and invasion at multiple points of the pathway (Fowler et al. 2011). New technologies are currently being developed to facilitate the use of miRNAs as a realistic therapeutic option. Until then, combination treatments and developing inhibitors which can affect a multiplicity of targets are critical.

Biomarker Discovery, Validation and Clinical

the clinical circumstance of the patient is required.

**6. Future directions for biomarker development** 

after 24 hours).

Application for Patients Diagnosed with Glioma 67

Collection and storage of frozen tissue is critical for biomarker development. Many of our current biomarker assays are performed on Formalin Fixed Paraffin Embedded (FFPE) tissue. This type of tissue, whilst preserving morphology for diagnosis, induces problems for downstream molecular applications. High quality RNA is difficult to obtain from FFPE tissue and PCR amplification from FFPE DNA is limited to products of less than 200 base pairs. It is also difficult to control the processes leading up to tissue fixation. In a first class Neuro-oncology centre in Australia, FFPE blocks were being sent to Central Headquarters for MGMT methylation detection. Unfortunately, a sizeable batch of tissues were nondeterminative (could not be amplified). Tissue from surgeries performed on a Friday were fixed in formalin, however the laboratory was unattended over the weekend, resulting in the tissue submerged in formalin for up to 72 hours (routinely, formalin should be removed

Another issue that we are not taking into careful consideration are the molecular changes acquired in the tumour *after* treatment. Many biomarker studies are performed on tumour obtained at initial surgery event. This tissue has not been exposed to treatment. However, the majority of novel treatments are tested at the time of recurrence. Changes in chromosome aberrations and mismatch repair proteins have been detected in paired tumour specimens (primary and relapsed). Careful consideration of the tissue and its relevance to

To advance personalised medicine, a co-operative effort between cancer researchers and clinicians is urgently needed. There is very little collaboration between scientists working on targeted therapies such as the TKIs and anti-angiogenics...what worked, what didn't? Specific consideration needs to be paid to increasing sample sizes, sequencing entire genes, implementing robust methodologies and taking a holistic approach to understanding pathways. Cancer is multifaceted and we urgently need to unravel these complexities. Two prospective biomarker trials have been encouraging: the I-SPY 2 (investigation of serial studies to predict your therapeutic response with imaging and molecular analysis 2) for women with locally advanced breast cancer (Barker et al. 2009) and BATTLE (Biomarker Integrated Approaches of Targeted Therapy for Lung Cancer Elimination) for pre-treated patients with non-small cell lung cancer (NSLC) (Kim 2011). Both trials employ an adaptive phase II/III clinical trial design. The I-SPY 2 is performed as a neo-adjuvant trial. A core biopsy is provided and tested for Estrogen Receptor (ER), Progesterone Receptor (PR), Human Epidermal Growth Factor Receptor 2 (HER2) and MammaPrint status (a gene signature known to be predictive of outcome). Based upon the marker outcomes, the patients will be stratified into two arms of a standard neoadjuvant regime: paclitaxel (plus trastuzumab [Herceptin] for HER2+ patients followed by doxorubicin (Adriamycin) and cyclophosphamide (Cytoxan). Five new drugs will be trialled in the other arms (each being added to the standard therapy). Patients are currently being recruited. The BATTLE trial takes on a very similar adaptive design but differs in its examination of samples from posttreated NSLC. Key drugs and associated biomarkers (Erlotinib/EGFR; Vandetanib/VEGFR; Erlotinib + bexarotene/ Retinoid + EGFR and Sorafenib/ KRAS/BRAF) were tested both as an equal randomisation design and an adaptive randomisation design. This trial confirmed that tumours harbouring mutations in KRAS/BRAF showed a disease control of 79% when treated with sorafenib but only 14% of the patients responded to erlotinib. Conversely,

#### **5.3.5 Differing response criterion**

The inability to accurately define endpoints from clinical trials makes the evaluation of new therapies subjective and significantly delays treatment development. At present overall survival (OS) and 6 month progression free survival (PFS6) are two defined end points accepted in most clinical trials testing for new GBM therapies. PFS6 relies on a combination of gadolinium enhanced MRI imaging and potentially subjective clinical evaluation. Seizures, depression and steroid induced myopathy can all influence clinical signs and symptoms. Since 1990, the MacDonald criterion has been used as an objective radiologic assessment of response in GBM. This two dimensional measurement has been mainstay for evaluating tumour response and is based upon measurements of the enhancing tumour area (the product of the maximal cross-sectional enhancing diameters) (Macdonald et al. 1990). With the advance of treatments administered to patients with GBM, the MacDonald Criteria has a number of important limitations. The MacDonald criteria does not discriminate measurable disease from non-measureable disease, cannot identify non-tumour related increases in enhancement and provides no use for the evaluation of anti-angiogenic drugs. Bevacizumab can cause accelerated regression of VEGF driven angiogenesis and rapid resolution of gadolinium MRI changes in responding patients. There is concern however as to whether anti-VEGF therapy results in true glioma cell destruction or their ability to control the perivascular leak, resulting in better symptom control (associated with improvement of gadolinium MRI).

An international working group was formed to review and improve the response assessment criteria for high grade gliomas, coined Response Assessment in Neuro-Oncology (RANO) (Wen et al. 2010). The guidelines have devised a better standardisation of how clinicians measure response, which will ultimately result in a more uniform assessment of disease status across different centres. Unfortunately, the new RANO guidelines do not address the persistent problem of the irregularity of gliomas and the difficulty of measuring tumours treated with anti-angiogenic drugs, suggesting that volumetric measurements that count all enhancing and non-enhancing voxels may prove more accurate in the future.The RANO working party acknowledges that an important area of future research is the need to *develop advanced novel MRI techniques.* 

#### **5.3.6 Inadequate tissue**

Biobanks or biorepositories play a critical role in the evolution of biomarkers, targets and targeted therapies. Five years ago, the NCI announced their plans to enlist dozens of biorepositories in the USA to provide large tumour numbers and use high-throughput DNA sequencing and computational biology to produce with new methods of detecting and treating cancers. Unfortunately sub-standard tissue and data collection provided a significant road block to the Cancer Genome Atlas effort. Biorepositories remain underfunded and unappreciated. Despite billions of dollars poured into cancer research, innovation in the field of biobanking is sadly lacking. Standard operating procedures (SOPs) are not consistent between sites, and sometimes differ within single institutes. Methodologies for preserving tissue vary and times between tumour removal and time of processing fluctuate. Significant genetic changes can occur between the time of tissue removal from the body and time of processing. The collection of tissue has to be taken seriously and investments need to be urgently made to promote basic, translational and clinical research as well as social gain in terms of improved cancer care and economic development.

The inability to accurately define endpoints from clinical trials makes the evaluation of new therapies subjective and significantly delays treatment development. At present overall survival (OS) and 6 month progression free survival (PFS6) are two defined end points accepted in most clinical trials testing for new GBM therapies. PFS6 relies on a combination of gadolinium enhanced MRI imaging and potentially subjective clinical evaluation. Seizures, depression and steroid induced myopathy can all influence clinical signs and symptoms. Since 1990, the MacDonald criterion has been used as an objective radiologic assessment of response in GBM. This two dimensional measurement has been mainstay for evaluating tumour response and is based upon measurements of the enhancing tumour area (the product of the maximal cross-sectional enhancing diameters) (Macdonald et al. 1990). With the advance of treatments administered to patients with GBM, the MacDonald Criteria has a number of important limitations. The MacDonald criteria does not discriminate measurable disease from non-measureable disease, cannot identify non-tumour related increases in enhancement and provides no use for the evaluation of anti-angiogenic drugs. Bevacizumab can cause accelerated regression of VEGF driven angiogenesis and rapid resolution of gadolinium MRI changes in responding patients. There is concern however as to whether anti-VEGF therapy results in true glioma cell destruction or their ability to control the perivascular leak, resulting in better symptom control (associated with

An international working group was formed to review and improve the response assessment criteria for high grade gliomas, coined Response Assessment in Neuro-Oncology (RANO) (Wen et al. 2010). The guidelines have devised a better standardisation of how clinicians measure response, which will ultimately result in a more uniform assessment of disease status across different centres. Unfortunately, the new RANO guidelines do not address the persistent problem of the irregularity of gliomas and the difficulty of measuring tumours treated with anti-angiogenic drugs, suggesting that volumetric measurements that count all enhancing and non-enhancing voxels may prove more accurate in the future.The RANO working party acknowledges that an important area of future research is the need to

Biobanks or biorepositories play a critical role in the evolution of biomarkers, targets and targeted therapies. Five years ago, the NCI announced their plans to enlist dozens of biorepositories in the USA to provide large tumour numbers and use high-throughput DNA sequencing and computational biology to produce with new methods of detecting and treating cancers. Unfortunately sub-standard tissue and data collection provided a significant road block to the Cancer Genome Atlas effort. Biorepositories remain underfunded and unappreciated. Despite billions of dollars poured into cancer research, innovation in the field of biobanking is sadly lacking. Standard operating procedures (SOPs) are not consistent between sites, and sometimes differ within single institutes. Methodologies for preserving tissue vary and times between tumour removal and time of processing fluctuate. Significant genetic changes can occur between the time of tissue removal from the body and time of processing. The collection of tissue has to be taken seriously and investments need to be urgently made to promote basic, translational and clinical research as well as social gain in terms of improved cancer care and economic

**5.3.5 Differing response criterion** 

improvement of gadolinium MRI).

*develop advanced novel MRI techniques.* 

**5.3.6 Inadequate tissue** 

development.

Collection and storage of frozen tissue is critical for biomarker development. Many of our current biomarker assays are performed on Formalin Fixed Paraffin Embedded (FFPE) tissue. This type of tissue, whilst preserving morphology for diagnosis, induces problems for downstream molecular applications. High quality RNA is difficult to obtain from FFPE tissue and PCR amplification from FFPE DNA is limited to products of less than 200 base pairs. It is also difficult to control the processes leading up to tissue fixation. In a first class Neuro-oncology centre in Australia, FFPE blocks were being sent to Central Headquarters for MGMT methylation detection. Unfortunately, a sizeable batch of tissues were nondeterminative (could not be amplified). Tissue from surgeries performed on a Friday were fixed in formalin, however the laboratory was unattended over the weekend, resulting in the tissue submerged in formalin for up to 72 hours (routinely, formalin should be removed after 24 hours).

Another issue that we are not taking into careful consideration are the molecular changes acquired in the tumour *after* treatment. Many biomarker studies are performed on tumour obtained at initial surgery event. This tissue has not been exposed to treatment. However, the majority of novel treatments are tested at the time of recurrence. Changes in chromosome aberrations and mismatch repair proteins have been detected in paired tumour specimens (primary and relapsed). Careful consideration of the tissue and its relevance to the clinical circumstance of the patient is required.

#### **6. Future directions for biomarker development**

To advance personalised medicine, a co-operative effort between cancer researchers and clinicians is urgently needed. There is very little collaboration between scientists working on targeted therapies such as the TKIs and anti-angiogenics...what worked, what didn't? Specific consideration needs to be paid to increasing sample sizes, sequencing entire genes, implementing robust methodologies and taking a holistic approach to understanding pathways. Cancer is multifaceted and we urgently need to unravel these complexities. Two prospective biomarker trials have been encouraging: the I-SPY 2 (investigation of serial studies to predict your therapeutic response with imaging and molecular analysis 2) for women with locally advanced breast cancer (Barker et al. 2009) and BATTLE (Biomarker Integrated Approaches of Targeted Therapy for Lung Cancer Elimination) for pre-treated patients with non-small cell lung cancer (NSLC) (Kim 2011). Both trials employ an adaptive phase II/III clinical trial design. The I-SPY 2 is performed as a neo-adjuvant trial. A core biopsy is provided and tested for Estrogen Receptor (ER), Progesterone Receptor (PR), Human Epidermal Growth Factor Receptor 2 (HER2) and MammaPrint status (a gene signature known to be predictive of outcome). Based upon the marker outcomes, the patients will be stratified into two arms of a standard neoadjuvant regime: paclitaxel (plus trastuzumab [Herceptin] for HER2+ patients followed by doxorubicin (Adriamycin) and cyclophosphamide (Cytoxan). Five new drugs will be trialled in the other arms (each being added to the standard therapy). Patients are currently being recruited. The BATTLE trial takes on a very similar adaptive design but differs in its examination of samples from posttreated NSLC. Key drugs and associated biomarkers (Erlotinib/EGFR; Vandetanib/VEGFR; Erlotinib + bexarotene/ Retinoid + EGFR and Sorafenib/ KRAS/BRAF) were tested both as an equal randomisation design and an adaptive randomisation design. This trial confirmed that tumours harbouring mutations in KRAS/BRAF showed a disease control of 79% when treated with sorafenib but only 14% of the patients responded to erlotinib. Conversely,

Biomarker Discovery, Validation and Clinical

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#### **7. Acknowledgements**

I would like to acknowledge the support and financial assistance from the Cure For Life Foundation and the Cancer Institute NSW.

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**Part 2** 

**Gliomagenesis** 

