Cancer Treatment by Tyrosine Kinase Inhibitors

**73**

**Chapter 4**

**Abstract**

**1. Introduction**

are not translated.

Noncoding RNAs as Predictive

Biomarkers of Therapeutic

*Julia Kovacova and Ondrej Slaby*

therapy in a wide range of metastatic cancers.

**Keywords:** biomarker, response, ncRNA, tyrosine kinase inhibitors

Response to Tyrosine Kinase

Inhibitors in Metastatic Cancer

Since their discovery, noncoding RNAs have acquired extensive attention due to their eminent role in the regulation of gene expression and thus also in the pathogenesis of many diseases. Currently, strong evidence is showing that noncoding RNAs are integral parts of key cancer-related cellular pathways, and the deregulation of their levels is pathogenetic on one hand but feasible as a biomarker of pathogenesis itself on the other hand. In cancer, diagnosis, prognosis, and prediction of therapy outcome can be derived from levels of various noncoding RNAs. This chapter is focused on potential application of noncoding RNAs in prediction of therapeutic response to tyrosine kinase inhibitors commonly used as targeted

Since the 1980s there was some spare evidence of low-molecular RNAs being

able to bind complementarily to bigger RNA molecules and having a role in chromatin organization. Small nuclear RNAs (snRNAs) and small nucleolar RNAs (snoRNAs) [1–4] were the early discoveries in noncoding RNA field besides tRNAs, and at first, it looked like an exotic exception in rather binary world of protein-coding sequences and the rest of the genome which considered to be "junk" DNA. At the time some mechanisms of regulation of gene expression were known, and overall picture seemed to be complete, give or take a few details. Although it was known that mRNA is a vital part of gene expression and central dogma of molecular biology, the only functional product arising from genetic information, as it was commonly believed, is protein. As the genomic era was just about to come, there was no reason to think that most RNA transcripts

Such remarks were first made in 1995 with H19. Expression of this lncRNA correlated with bladder carcinoma caused by loss of H19 imprinting pattern [5]. Further evidence was provided after discovery of other noncoding transcripts, for example, growth arrest-specific 5 (GAS5) [6] and, most importantly, prostate cancer antigen 3 (PCA3/DD3) highly overexpressed in prostate tumor tissue [7].

#### **Chapter 4**

## Noncoding RNAs as Predictive Biomarkers of Therapeutic Response to Tyrosine Kinase Inhibitors in Metastatic Cancer

*Julia Kovacova and Ondrej Slaby*

#### **Abstract**

Since their discovery, noncoding RNAs have acquired extensive attention due to their eminent role in the regulation of gene expression and thus also in the pathogenesis of many diseases. Currently, strong evidence is showing that noncoding RNAs are integral parts of key cancer-related cellular pathways, and the deregulation of their levels is pathogenetic on one hand but feasible as a biomarker of pathogenesis itself on the other hand. In cancer, diagnosis, prognosis, and prediction of therapy outcome can be derived from levels of various noncoding RNAs. This chapter is focused on potential application of noncoding RNAs in prediction of therapeutic response to tyrosine kinase inhibitors commonly used as targeted therapy in a wide range of metastatic cancers.

**Keywords:** biomarker, response, ncRNA, tyrosine kinase inhibitors

#### **1. Introduction**

Since the 1980s there was some spare evidence of low-molecular RNAs being able to bind complementarily to bigger RNA molecules and having a role in chromatin organization. Small nuclear RNAs (snRNAs) and small nucleolar RNAs (snoRNAs) [1–4] were the early discoveries in noncoding RNA field besides tRNAs, and at first, it looked like an exotic exception in rather binary world of protein-coding sequences and the rest of the genome which considered to be "junk" DNA. At the time some mechanisms of regulation of gene expression were known, and overall picture seemed to be complete, give or take a few details. Although it was known that mRNA is a vital part of gene expression and central dogma of molecular biology, the only functional product arising from genetic information, as it was commonly believed, is protein. As the genomic era was just about to come, there was no reason to think that most RNA transcripts are not translated.

Such remarks were first made in 1995 with H19. Expression of this lncRNA correlated with bladder carcinoma caused by loss of H19 imprinting pattern [5]. Further evidence was provided after discovery of other noncoding transcripts, for example, growth arrest-specific 5 (GAS5) [6] and, most importantly, prostate cancer antigen 3 (PCA3/DD3) highly overexpressed in prostate tumor tissue [7].

The beginning of the millennium was marked by the discovery of RNA interference and new short noncoding RNAs regulating gene expression and thus developmental timing in *Caenorhabditis elegans* [8–13]. MicroRNA (miRNA) was coined as the name for this new group of RNAs, and followed by diligent hunt for more, many other microRNAs were identified. Like miRNAs which were discovered first—lin-4 and let-7—many miRNAs were time- or site-specific, meaning they serve their function in some periods of life or only in some cell types [14, 15]. Targets of these RNAs were found in more than 60% of human protein-coding genes [16]. Together with their specific level necessary for fulfilling their job, it was inevitable to notice possible role of ncRNAs in the development of various diseases.

Of all ncRNAs known so far, miRNAs occupy exceptional position, considering the amount of knowledge on their role in pathogenesis of cancer; therefore, their biogenesis, function, and predictive potential will be discussed in the subsequent lines. Following will be lncRNAs, for their potential to be used as a biomarker has been studied extensively in recent years, even though their association with cancer has been outlined already in the very first publications on lncRNAs [5].

This chapter is therefore focused on the potential application of noncoding RNAs in prediction of therapeutic response to tyrosine kinase inhibitors commonly used as targeted therapy in a wide range of metastatic cancers.

#### **2. Noncoding RNAs and their role in cancer**

#### **2.1 Classification**

Noncoding RNAs (ncRNAs) are usually divided into two groups according to their length. The term small ncRNA (sncRNA) is reserved for diverse group of transcripts shorter than 200 nucleotides. Longer transcripts above 200 nucleotides of length are called long ncRNA (lncRNA). Both short and long ncRNAs usually do not possess any protein-coding capacity [17] which is the main difference from mRNA; there are, however, some cases of cryptic reading frames in longer ncRNAs [18] and even translation of short functional micropeptides from transcripts formerly annotated as noncoding [19].

In contrast to sncRNA, spectrum of lncRNAs is much broader in possible length and thus also in sequence, structure, and function; therefore, similarities with protein-coding mRNA are highly variable with many exceptions among numerous types of noncoding transcripts [20]. Classification of lncRNAs is now more than imperfect due to limited understanding of this group with many structural and functional families unknown yet [21].

For some types of ncRNA, known sequences and their annotations [22] are gathered in online databases. miRbase.org has been established in 2006 as a first noncoding RNA registry for microRNA [23] following the formation of a unified nomenclature for miRNA.

Catalog of lncRNAs has been created much later, in 2012, under the domain mitranscriptome.org and contains data acquired with high-throughput RNA sequencing [24], combining results from several published sources such as The Cancer Genome Atlas [25] or the GENCODE project [21, 24].

#### **2.2 Biogenesis**

#### *2.2.1 microRNA*

miRNAs are 19–24 nucleotides long endogenously produced regulatory RNAs. Canonical pathway starts with RNA polymerase II which typically transcribes

**75**

*Noncoding RNAs as Predictive Biomarkers of Therapeutic Response to Tyrosine Kinase Inhibitors…*

In the next step, pri-miRNA is spliced by a microprocessor complex to one or several hairpins each containing one future mature miRNA sequence—precursor miRNA (pre-miRNA) with its characteristic 5´phosphate and overhang of two nucleotides at 3´OH end. The microprocessor complex comprises mainly of RNase III enzyme Drosha [26] and dimer of protein DiGeorge critical region 8 (DGCR8 or known as Pasha in flies) able to bind double-stranded RNA (dsRNA)

Pre-miRNA is further processed in the cytoplasm, and to get there, it is bound by nuclear transporter protein Exportin 5 [29] and transferred out of the nucleus. In the cytoplasm, pre-miRNA is cleaved by another RNAse III-type enzyme Dicer in cooperation with other proteins depending on species; in humans, for example, it is *trans*-activation-responsive RNA-binding protein (TRBP) [30]. Pre-miRNA is cleaved at stem sequence close to the terminal loop, creating double-stranded RNA intermediate. Depending on several factors such as thermodynamic stability, one of the strands is then recruited into an RNA-induced silencing complex (RISC) by binding with protein Argonaute (AGO) [30], such strand is termed leading. The other, which is thermodynamically more stable, called passenger strand, is usually discarded but can also act in complex with Ago as functional

Canonical pathway, however, can be overcome, and miRNAs can be produced in alternative, noncanonical ways [32]. Alternative routes independent on various parts of the canonical biogenesis have been described before [33–35], and it is known that they give rise to some other types of sncRNA such as snoRNA or

Due to their highly variable structure and function, it is difficult to outline a general biogenesis pathway for lncRNA. At least part of the biogenesis is shared among lncRNAs and protein-coding mRNAs [21], including transcription by RNA polymerase II and chromatin modifications as those seen during transcription of protein-coding sequences, for example, methylation and acetylation of histones in active promoters [36]. The main differences lie in fewer but usually longer exons in lncRNAs [21], more tissue-specific expression [20], and abundance in the nucleus

Enormous variability of noncoding RNAs is achieved more on posttranscriptional level than by individual transcriptional mechanisms. Besides standard processes such as polyadenylation, capping, and splicing, nascent ncRNAs undergo modifications that are not typical for mRNAs. Cleaving of 3´end by RNAse P is a typical modification in the biogenesis of metastasis-associated lung adenocarcinoma transcript 1 (MALAT1) while creating short tRNA-like transcript (MATAL1-associated small cytoplasmic RNA—mascRNA) and mature lncRNA. Another variation of standard pre-mRNA splicing is the back-splicing of previously spliced transcript creating a circular lncRNA (circRNA). Spliced-out introns can also gain lncRNA status when they escape degradation and then function as lariat-shaped circular RNAs [38, 39]. After all, even miRNAs, as much as other sncRNAs, arise from primary long transcripts which are classifiable as lncRNA but are processed by following miRNA biogenesis pathway [39]. Evidence also suggests that transcriptional apparatus of miRNAs is somehow involved in expression of lncRNAs, too, as knockout of Dicer leads to

downregulation of not only miRNAs but also lncRNAs as a class [40].

miRNA sequences, creating capped and polyadenylated primary miRNAs (primiRNAs) several hundred nucleotides long. Future mature miRNA sequence resides

in the stem region of the secondary hairpin structure of pri-miRNA.

*DOI: http://dx.doi.org/10.5772/intechopen.86082*

endogenous short hairpin RNAs (shRNAs).

*2.2.2 Long noncoding RNA*

rather than the cytoplasm [36, 37].

[27, 28].

miRNA [31].

*Noncoding RNAs as Predictive Biomarkers of Therapeutic Response to Tyrosine Kinase Inhibitors… DOI: http://dx.doi.org/10.5772/intechopen.86082*

miRNA sequences, creating capped and polyadenylated primary miRNAs (primiRNAs) several hundred nucleotides long. Future mature miRNA sequence resides in the stem region of the secondary hairpin structure of pri-miRNA.

In the next step, pri-miRNA is spliced by a microprocessor complex to one or several hairpins each containing one future mature miRNA sequence—precursor miRNA (pre-miRNA) with its characteristic 5´phosphate and overhang of two nucleotides at 3´OH end. The microprocessor complex comprises mainly of RNase III enzyme Drosha [26] and dimer of protein DiGeorge critical region 8 (DGCR8 or known as Pasha in flies) able to bind double-stranded RNA (dsRNA) [27, 28].

Pre-miRNA is further processed in the cytoplasm, and to get there, it is bound by nuclear transporter protein Exportin 5 [29] and transferred out of the nucleus. In the cytoplasm, pre-miRNA is cleaved by another RNAse III-type enzyme Dicer in cooperation with other proteins depending on species; in humans, for example, it is *trans*-activation-responsive RNA-binding protein (TRBP) [30]. Pre-miRNA is cleaved at stem sequence close to the terminal loop, creating double-stranded RNA intermediate. Depending on several factors such as thermodynamic stability, one of the strands is then recruited into an RNA-induced silencing complex (RISC) by binding with protein Argonaute (AGO) [30], such strand is termed leading. The other, which is thermodynamically more stable, called passenger strand, is usually discarded but can also act in complex with Ago as functional miRNA [31].

Canonical pathway, however, can be overcome, and miRNAs can be produced in alternative, noncanonical ways [32]. Alternative routes independent on various parts of the canonical biogenesis have been described before [33–35], and it is known that they give rise to some other types of sncRNA such as snoRNA or endogenous short hairpin RNAs (shRNAs).

#### *2.2.2 Long noncoding RNA*

*Tyrosine Kinases as Druggable Targets in Cancer*

The beginning of the millennium was marked by the discovery of RNA interference and new short noncoding RNAs regulating gene expression and thus developmental timing in *Caenorhabditis elegans* [8–13]. MicroRNA (miRNA) was coined as the name for this new group of RNAs, and followed by diligent hunt for more, many other microRNAs were identified. Like miRNAs which were discovered first—lin-4 and let-7—many miRNAs were time- or site-specific, meaning they serve their function in some periods of life or only in some cell types [14, 15]. Targets of these RNAs were found in more than 60% of human protein-coding genes [16]. Together with their specific level necessary for fulfilling their job, it was inevitable to notice

Of all ncRNAs known so far, miRNAs occupy exceptional position, considering the amount of knowledge on their role in pathogenesis of cancer; therefore, their biogenesis, function, and predictive potential will be discussed in the subsequent lines. Following will be lncRNAs, for their potential to be used as a biomarker has been studied extensively in recent years, even though their association with cancer

This chapter is therefore focused on the potential application of noncoding RNAs in prediction of therapeutic response to tyrosine kinase inhibitors commonly

Noncoding RNAs (ncRNAs) are usually divided into two groups according to their length. The term small ncRNA (sncRNA) is reserved for diverse group of transcripts shorter than 200 nucleotides. Longer transcripts above 200 nucleotides of length are called long ncRNA (lncRNA). Both short and long ncRNAs usually do not possess any protein-coding capacity [17] which is the main difference from mRNA; there are, however, some cases of cryptic reading frames in longer ncRNAs [18] and even translation of short functional micropeptides from transcripts formerly annotated as noncoding [19]. In contrast to sncRNA, spectrum of lncRNAs is much broader in possible length

and thus also in sequence, structure, and function; therefore, similarities with protein-coding mRNA are highly variable with many exceptions among numerous types of noncoding transcripts [20]. Classification of lncRNAs is now more than imperfect due to limited understanding of this group with many structural and

For some types of ncRNA, known sequences and their annotations [22] are gathered in online databases. miRbase.org has been established in 2006 as a first noncoding RNA registry for microRNA [23] following the formation of a unified

Catalog of lncRNAs has been created much later, in 2012, under the domain mitranscriptome.org and contains data acquired with high-throughput RNA sequencing [24], combining results from several published sources such as The

miRNAs are 19–24 nucleotides long endogenously produced regulatory RNAs. Canonical pathway starts with RNA polymerase II which typically transcribes

Cancer Genome Atlas [25] or the GENCODE project [21, 24].

possible role of ncRNAs in the development of various diseases.

used as targeted therapy in a wide range of metastatic cancers.

**2. Noncoding RNAs and their role in cancer**

functional families unknown yet [21].

nomenclature for miRNA.

**2.2 Biogenesis**

*2.2.1 microRNA*

**2.1 Classification**

has been outlined already in the very first publications on lncRNAs [5].

**74**

Due to their highly variable structure and function, it is difficult to outline a general biogenesis pathway for lncRNA. At least part of the biogenesis is shared among lncRNAs and protein-coding mRNAs [21], including transcription by RNA polymerase II and chromatin modifications as those seen during transcription of protein-coding sequences, for example, methylation and acetylation of histones in active promoters [36]. The main differences lie in fewer but usually longer exons in lncRNAs [21], more tissue-specific expression [20], and abundance in the nucleus rather than the cytoplasm [36, 37].

Enormous variability of noncoding RNAs is achieved more on posttranscriptional level than by individual transcriptional mechanisms. Besides standard processes such as polyadenylation, capping, and splicing, nascent ncRNAs undergo modifications that are not typical for mRNAs. Cleaving of 3´end by RNAse P is a typical modification in the biogenesis of metastasis-associated lung adenocarcinoma transcript 1 (MALAT1) while creating short tRNA-like transcript (MATAL1-associated small cytoplasmic RNA—mascRNA) and mature lncRNA. Another variation of standard pre-mRNA splicing is the back-splicing of previously spliced transcript creating a circular lncRNA (circRNA). Spliced-out introns can also gain lncRNA status when they escape degradation and then function as lariat-shaped circular RNAs [38, 39]. After all, even miRNAs, as much as other sncRNAs, arise from primary long transcripts which are classifiable as lncRNA but are processed by following miRNA biogenesis pathway [39]. Evidence also suggests that transcriptional apparatus of miRNAs is somehow involved in expression of lncRNAs, too, as knockout of Dicer leads to downregulation of not only miRNAs but also lncRNAs as a class [40].

#### **2.3 Cellular functions and roles in cancer**

Distinct length of miRNA predestines them for a specific cellular function. The so-called seed region of miRNA sequence recognizes its target mRNA and binds complementary to its 3´untranslated region. miRNA-mRNA interaction leads to repression of the translation by destabilization of the target mRNA or by recruiting the mRNA degradation factors. As a result, expression of the target is decreased [41]. As the seed region of miRNA is only eight nucleotides long, recognized sequence will not be very specific—many different target mRNAs can contain identical eight-nucleotide combination. miRNAs are therefore pleiotropic in their effect, creating an intertwined posttranscriptional regulatory network. sncRNAs however expand their impact beyond posttranscriptional downregulation of expression. Other types of sncRNAs such as PiWi-interacting RNAs or siRNAs facilitate various cellular functions through pathway of RNA interference and its components. Transposon gene silencing, maturation of rRNA or histone pre-mRNA, and guiding of various complexes to a certain site are only some of very specific functions of short transcripts in cell [42].

In lncRNAs, the range of cellular roles is considerably wider, affecting processes spanning from transcription to epigenetic modification.

LncRNAs regulate transcription in *cis* (genes on the same chromosome) or *trans* (genes on another chromosome) manner acting through transcriptional interference, for example, by overlapping promoters or by binding to transcription factors [43, 44].

Of posttranscriptional modifications, lncRNAs are involved in pre-mRNA capping and polyadenylation, necessary for proper mRNA translation and mRNA splicing, the processes indispensable for diverse protein products from rather small choice of protein-coding sequences in higher eukaryotes [43]. lncRNAs are involved also in epigenetic regulation by loss of imprinting or changes in methylation patterns of cytosine residues in CpG dinucleotide islands. Chromatin remodeling is facilitated by lncRNA, too, as they can recruit chromatin-remodeling and histonemodifying enzymes [43, 45].

Like miRNA, lncRNA can affect mRNA half-life and its stability, consequently triggering mRNA decay or repression of translation by imperfect pairing; on the contrary, perfect pairing can protect the target mRNA from degradation. Moreover, lncRNAs can affect miRNA network by acting as miRNA decoys or cause forming of endogenous siRNAs [43, 46].

The processes stated above are just few of many cellular actions affected by ncRNAs. Mere expression of a gene, protein-coding or not, is only a first step in a working cellular environment which is achieved by fine tuning and multiple layers of control facilitated by ncRNAs on transcriptional and posttranscriptional level. Although different from their targets, ncRNAs suffer from the same errors and damages as protein-coding sequences. Deregulated levels of ncRNAs are mostly observed either because given ncRNA is a target of upstream mutated or epigenetically deregulated effector oncogene, as a result of mutation in ncRNA sequence or defects in transcription and posttranscriptional editing and splicing. Either way, disruption of this network can add to imbalances in critical nodes such as DNA damage repair, cell division, and response to mitogenic and proapoptotic signals, thus shifting cells to precancerous phenotypes.

The genome-wide studies to localize miRNA genes in human genome found that miRNAs are frequently localized at fragile sites, minimal regions of heterozygous loss or amplification, or common breakpoint regions in human cancer [45]. Besides the structural and genetic alterations, the epigenetic silencing of miRNAs genes by DNA promoter hypermethylation or histone hypoacetylation has been described in

**77**

*Noncoding RNAs as Predictive Biomarkers of Therapeutic Response to Tyrosine Kinase Inhibitors…*

some solid tumors and hematologic malignancies. Whole-genome miRNA expression analysis clearly showed that the aberrant miRNA expression patterns present a common feature in the various tumor types. Based on these studies, deregulation of miRNAs was declared to be an important event in the initiation and progression of many cancers. Considering the network of targeted mRNAs and miRNA expression changes, miRNA can be classified as oncogenic miRNA or tumor-suppressive miRNA; some miRNAs may exhibit both features dependently on the cellular

**3. Noncoding RNAs as predictive biomarkers of therapeutic response**

Drug resistance, either primary or developed secondary, is a crucial factor in tumor recurrence and poor outcome. Administration of the best of current therapies to a group of patients with similar symptoms and seemingly identical diagnosis has shown itself to be inefficient as there is almost always a subgroup of patients not benefiting from the treatment. With ever more precise options in molecular description of patients, it has become evident that cancer is not a single disease, but large family of heterogenous diseases asking for an individual approach. Even after onset of targeted therapy, incomparably more specific than conventional chemoand radiotherapy, the problem of non-responding subgroups of patients remained. Histological classification was insufficient in prediction of what would be the most

To be considered a feasible biomarker, a molecule needs to meet several criteria. Its expression must be cell-type- or tissue-specific and significantly altered during the disease or studied condition compared to normal state. Predictive biomarker then should provide an information on therapeutic outcome in a given patient before the treatment administration, and it could manifest itself in a form of up- and downregulations of RNA or protein expression level, gene copies, mutations, and signaling signatures either downstream or in parallel and can be derived retrospectively or prospectively [47]. For obvious reasons, before ncRNAs, various proteins in the blood and tissue, gene mutations, and later mRNA transcripts were prominent candidates as predictive biomarkers. Up to now, several genetic variants (e.g., SNPs in VEGF-A, VEGF-R1, VEGF-R3, and FGF-R2; [48]) were associated, for example, with response to sunitinib, pazopanib, sorafenib, or axitinib response. Histological and molecular features are also potential biomarkers, in addition to other such as protein expression and immune response activation (e.g., differential levels of some cytokines like IL-6 were observed in patients with progressive disease, although with insignificant results). Also, epigenetic factors such as methylation status were studied; for example, hypermethylation of cystatin-M gene (CST6) and leukocyte adhesion deficiency-1 (LAD1) were observed in patients with shorter PFS on TKI therapy (all reviewed in [48]). Although many molecules have been considered as biomarker candidates, only a few of them have really made it to clinical practice mostly due to lack of proper validation on significant cohorts and study design discrepancies. Also, in some cases, it is not clear whether given molecule has

With the discovery of miRNA and their regulatory impact, attention has been

turned to ncRNAs. Concerning miRNAs, the first attempts in finding cancerspecific ncRNA biomarkers were made in Carlo Croce's research group in 2002 [49]. A team of researchers discovered that miR-15 and miR-16 sequences lie in a region frequently deleted in chronic lymphocytic leukemia (CLL) and this deletion leads to downregulation of these miRNAs. Further investigation revealed that many microRNA genes are located at fragile genomic regions and that microRNA

*DOI: http://dx.doi.org/10.5772/intechopen.86082*

context in various cancers [45].

effective treatment for a given patient.

prognostic or rather predictive character.

*Noncoding RNAs as Predictive Biomarkers of Therapeutic Response to Tyrosine Kinase Inhibitors… DOI: http://dx.doi.org/10.5772/intechopen.86082*

some solid tumors and hematologic malignancies. Whole-genome miRNA expression analysis clearly showed that the aberrant miRNA expression patterns present a common feature in the various tumor types. Based on these studies, deregulation of miRNAs was declared to be an important event in the initiation and progression of many cancers. Considering the network of targeted mRNAs and miRNA expression changes, miRNA can be classified as oncogenic miRNA or tumor-suppressive miRNA; some miRNAs may exhibit both features dependently on the cellular context in various cancers [45].

#### **3. Noncoding RNAs as predictive biomarkers of therapeutic response**

Drug resistance, either primary or developed secondary, is a crucial factor in tumor recurrence and poor outcome. Administration of the best of current therapies to a group of patients with similar symptoms and seemingly identical diagnosis has shown itself to be inefficient as there is almost always a subgroup of patients not benefiting from the treatment. With ever more precise options in molecular description of patients, it has become evident that cancer is not a single disease, but large family of heterogenous diseases asking for an individual approach. Even after onset of targeted therapy, incomparably more specific than conventional chemoand radiotherapy, the problem of non-responding subgroups of patients remained. Histological classification was insufficient in prediction of what would be the most effective treatment for a given patient.

To be considered a feasible biomarker, a molecule needs to meet several criteria. Its expression must be cell-type- or tissue-specific and significantly altered during the disease or studied condition compared to normal state. Predictive biomarker then should provide an information on therapeutic outcome in a given patient before the treatment administration, and it could manifest itself in a form of up- and downregulations of RNA or protein expression level, gene copies, mutations, and signaling signatures either downstream or in parallel and can be derived retrospectively or prospectively [47]. For obvious reasons, before ncRNAs, various proteins in the blood and tissue, gene mutations, and later mRNA transcripts were prominent candidates as predictive biomarkers. Up to now, several genetic variants (e.g., SNPs in VEGF-A, VEGF-R1, VEGF-R3, and FGF-R2; [48]) were associated, for example, with response to sunitinib, pazopanib, sorafenib, or axitinib response. Histological and molecular features are also potential biomarkers, in addition to other such as protein expression and immune response activation (e.g., differential levels of some cytokines like IL-6 were observed in patients with progressive disease, although with insignificant results). Also, epigenetic factors such as methylation status were studied; for example, hypermethylation of cystatin-M gene (CST6) and leukocyte adhesion deficiency-1 (LAD1) were observed in patients with shorter PFS on TKI therapy (all reviewed in [48]). Although many molecules have been considered as biomarker candidates, only a few of them have really made it to clinical practice mostly due to lack of proper validation on significant cohorts and study design discrepancies. Also, in some cases, it is not clear whether given molecule has prognostic or rather predictive character.

With the discovery of miRNA and their regulatory impact, attention has been turned to ncRNAs. Concerning miRNAs, the first attempts in finding cancerspecific ncRNA biomarkers were made in Carlo Croce's research group in 2002 [49]. A team of researchers discovered that miR-15 and miR-16 sequences lie in a region frequently deleted in chronic lymphocytic leukemia (CLL) and this deletion leads to downregulation of these miRNAs. Further investigation revealed that many microRNA genes are located at fragile genomic regions and that microRNA

*Tyrosine Kinases as Druggable Targets in Cancer*

**2.3 Cellular functions and roles in cancer**

short transcripts in cell [42].

modifying enzymes [43, 45].

endogenous siRNAs [43, 46].

thus shifting cells to precancerous phenotypes.

factors [43, 44].

spanning from transcription to epigenetic modification.

Distinct length of miRNA predestines them for a specific cellular function. The so-called seed region of miRNA sequence recognizes its target mRNA and binds complementary to its 3´untranslated region. miRNA-mRNA interaction leads to repression of the translation by destabilization of the target mRNA or by recruiting the mRNA degradation factors. As a result, expression of the target is decreased [41]. As the seed region of miRNA is only eight nucleotides long, recognized sequence will not be very specific—many different target mRNAs can contain identical eight-nucleotide combination. miRNAs are therefore pleiotropic in their effect, creating an intertwined posttranscriptional regulatory network. sncRNAs however expand their impact beyond posttranscriptional downregulation of expression. Other types of sncRNAs such as PiWi-interacting RNAs or siRNAs facilitate various cellular functions through pathway of RNA interference and its components. Transposon gene silencing, maturation of rRNA or histone pre-mRNA, and guiding of various complexes to a certain site are only some of very specific functions of

In lncRNAs, the range of cellular roles is considerably wider, affecting processes

LncRNAs regulate transcription in *cis* (genes on the same chromosome) or *trans* (genes on another chromosome) manner acting through transcriptional interference, for example, by overlapping promoters or by binding to transcription

Of posttranscriptional modifications, lncRNAs are involved in pre-mRNA capping and polyadenylation, necessary for proper mRNA translation and mRNA splicing, the processes indispensable for diverse protein products from rather small choice of protein-coding sequences in higher eukaryotes [43]. lncRNAs are involved also in epigenetic regulation by loss of imprinting or changes in methylation patterns of cytosine residues in CpG dinucleotide islands. Chromatin remodeling is facilitated by lncRNA, too, as they can recruit chromatin-remodeling and histone-

Like miRNA, lncRNA can affect mRNA half-life and its stability, consequently triggering mRNA decay or repression of translation by imperfect pairing; on the contrary, perfect pairing can protect the target mRNA from degradation. Moreover, lncRNAs can affect miRNA network by acting as miRNA decoys or cause forming of

The processes stated above are just few of many cellular actions affected by ncRNAs. Mere expression of a gene, protein-coding or not, is only a first step in a working cellular environment which is achieved by fine tuning and multiple layers of control facilitated by ncRNAs on transcriptional and posttranscriptional level. Although different from their targets, ncRNAs suffer from the same errors and damages as protein-coding sequences. Deregulated levels of ncRNAs are mostly observed either because given ncRNA is a target of upstream mutated or epigenetically deregulated effector oncogene, as a result of mutation in ncRNA sequence or defects in transcription and posttranscriptional editing and splicing. Either way, disruption of this network can add to imbalances in critical nodes such as DNA damage repair, cell division, and response to mitogenic and proapoptotic signals,

The genome-wide studies to localize miRNA genes in human genome found that miRNAs are frequently localized at fragile sites, minimal regions of heterozygous loss or amplification, or common breakpoint regions in human cancer [45]. Besides the structural and genetic alterations, the epigenetic silencing of miRNAs genes by DNA promoter hypermethylation or histone hypoacetylation has been described in

**76**

profiles show specific patterns correlating with distinct clinical subtypes of CLL [50, 51]. In this case, microRNAs were the first ncRNAs tested for biomarker potential, but many more different kinds of noncoding RNAs emerged throughout the years, mostly after next-generation sequencing was introduced. Advances in high-throughput profiling technologies led to discovery of over 1900 mature human miRNAs from more than 1500 miRNA gene loci [23] and were followed by numerous studies focused on application of ncRNAs as diagnostic, prognostic, and predictive markers or therapeutic targets. To name just a few of many examples of promising biomarkers [52, 53], long intergenic RNA named HOX transcript antisense RNA (HOTAIR) is known to be metastasis-associated in breast cancer and playing active role in modulating cancer epigenome [54]. Choosing from sncRNAs, one example out of many could be miR-126 which has been shown to be involved in VEGF/PI3K/Akt/MRP1 signaling pathway as a principal player directly binding to vascular endothelial growth factor A (VEGF-A) [55]. Another one is miR-31, a potent factor in the development of various tumors with many target genes [56] which has been shown in many studies to be a reliable biomarker of response to anti-EGFR therapy. Recent large randomized trials proved low expression of miR-31 is an indicator of longer response and overall survival of patients with advanced colorectal carcinoma and wild-type allele of KRAS [57–59]. As for therapeutical applications, phase I study of MRX34, a liposomal miR-34a mimic, has been finished in 2017 with promising results in treatment of various solid tumors [60].

Reasons for extensive biomarker research on ncRNAs are their unique attributes beating proteins and mRNAs as biomarkers. In comparison, ncRNAs often manifest higher tissue-specific expression patterns which are necessary for precise distinction between different molecular subtypes of the disease and avoiding false-positive or false-negative results. Among the important characteristics of promising biomarkers is their detection in samples obtained noninvasively. Overall trend is to get as many and as detailed information with minimal burden for patients. Although ncRNAs are easily detectable in tissue samples (either fresh frozen or formalin-fixed paraffin-embedded), they are released and circulating in body fluids such as the blood, plasma, saliva, or urine as well which is incomparably less painful and faster to obtain than tissue specimens. This would be of tremendous value, for example, for patients with lung cancer who are routinely recommended for molecular testing for mutational status of epidermal growth factor receptor (EGFR) and anaplastic lymphoma receptor tyrosine kinase (ALK) in order to identify patients with superior response to TKIs so that they can avoid conventional chemotherapy. However, to obtain accurate lung biopsies for such testing, patients experience severe discomfort during difficult invasive procedures. Liquid biopsies would be thus much convenient option [61].

Replicative nature of ncRNAs makes them easy to detect by polymerase chain reaction and various modifications of this method, also microarrays and sequencing. ncRNAs vary in stability according to their length, secondary structure, association with proteins, or protection by exosomes; however, there is a consensus that relative to DNA or mRNA, shorter ncRNAs are more stable and less likely to be cleaved by RNAses or to be degraded by environmental agents such as storing temperature [62]. There are however some limits and variability between different types of sample handling and storage [63].

Based on many functions and pleiotropic character of ncRNAs, their involvement in progression of cancer and in modulation of therapeutic response is not surprising. In the following lines, we provide an overview (**Table 1**) of ncRNAs currently known to play a role in the development of resistance to TKIs, and what is more, their level seems to be an indicator of such resistance.

**79**

*Noncoding RNAs as Predictive Biomarkers of Therapeutic Response to Tyrosine Kinase Inhibitors…*

**Diagnosis Technological platform**

Up RCC (all) NGS, qPCR García-Donas

Up qPCR Kovacova et al.

Down qPCR Puente et al.

MicroRNA Cards, qPcr, digital PCR

qPCR

qPCR

density array, qPCR

NanoString panel

FirePlex

NanoString panel

Up qPCR array Khella et al.

Up qPCR array Merhautova

miR-942 Up qPCR array Prior et al. [66]

miR-99-5p Down NGS, qPCR Lukamowicz-

miR-141 Down qPCR array Berkers et al.

miR-9-5p Up TaqMan-

miR-424c Down Microarray,

miR-425-3p Down HCC TaqMan low

EGFR-AS1 Up HNSC qPCR,

Up NSCLC,

EGFR-AS1 Up HNSC qPCR,

Up NSCLC,

Gefitinib miR-21 Up NSCLC Microarray qPCR Shen et al. [74]

miR-630 Down LUAD qPCR Wu et al.

miR-200c Down NSCLC qPCR Li et al. [75]

miR-200c Down NSCLC qPCR Li et al. [75]

BC

BC

Erlotinib miR-630 Down LUAD qPCR Wu et al. [77] miR-223 Up NSCLC Microarray,

Sorafenib SRLR Up RCC Microarray,

**Study**

et al. [64]

[65]

[67]

[70]

[72]

et al. [73]

Xu et al. [84]

Vaira et al. [83]

Tan et al. [85]

[88]

et al. [76]

Joerger et al. [78]

Tan et al. [85]

et al. [76]

qPCR Izumchenko

qPCR Izumchenko

Rajska et al. [68]

Ralla et al. [69]

Gámez-Pozo et al. [71]

**in drugresistant patients**

*DOI: http://dx.doi.org/10.5772/intechopen.86082*

Sunitinib miR-1307-3p

**Drug ncRNA Deregulation** 

+ miR-425-5p

miR-942 + miR-133 model

miR-628-5p miR-23b miR-27b

miR-1 + miR-597 model

miR-155 miR-484

MiG6 miR-200 ratio

MiG6 miR-200 ratio


*Noncoding RNAs as Predictive Biomarkers of Therapeutic Response to Tyrosine Kinase Inhibitors… DOI: http://dx.doi.org/10.5772/intechopen.86082*

*Tyrosine Kinases as Druggable Targets in Cancer*

various solid tumors [60].

convenient option [61].

types of sample handling and storage [63].

more, their level seems to be an indicator of such resistance.

profiles show specific patterns correlating with distinct clinical subtypes of CLL [50, 51]. In this case, microRNAs were the first ncRNAs tested for biomarker potential, but many more different kinds of noncoding RNAs emerged throughout the years, mostly after next-generation sequencing was introduced. Advances in high-throughput profiling technologies led to discovery of over 1900 mature human miRNAs from more than 1500 miRNA gene loci [23] and were followed by numerous studies focused on application of ncRNAs as diagnostic, prognostic, and predictive markers or therapeutic targets. To name just a few of many examples of promising biomarkers [52, 53], long intergenic RNA named HOX transcript antisense RNA (HOTAIR) is known to be metastasis-associated in breast cancer and playing active role in modulating cancer epigenome [54]. Choosing from sncRNAs, one example out of many could be miR-126 which has been shown to be involved in VEGF/PI3K/Akt/MRP1 signaling pathway as a principal player directly binding to vascular endothelial growth factor A (VEGF-A) [55]. Another one is miR-31, a potent factor in the development of various tumors with many target genes [56] which has been shown in many studies to be a reliable biomarker of response to anti-EGFR therapy. Recent large randomized trials proved low expression of miR-31 is an indicator of longer response and overall survival of patients with advanced colorectal carcinoma and wild-type allele of KRAS [57–59]. As for therapeutical applications, phase I study of MRX34, a liposomal miR-34a mimic, has been finished in 2017 with promising results in treatment of

Reasons for extensive biomarker research on ncRNAs are their unique attributes beating proteins and mRNAs as biomarkers. In comparison, ncRNAs often manifest higher tissue-specific expression patterns which are necessary for precise distinction between different molecular subtypes of the disease and avoiding false-positive or false-negative results. Among the important characteristics of promising biomarkers is their detection in samples obtained noninvasively. Overall trend is to get as many and as detailed information with minimal burden for patients. Although ncRNAs are easily detectable in tissue samples (either fresh frozen or formalin-fixed paraffin-embedded), they are released and circulating in body fluids such as the blood, plasma, saliva, or urine as well which is incomparably less painful and faster to obtain than tissue specimens. This would be of tremendous value, for example, for patients with lung cancer who are routinely recommended for molecular testing for mutational status of epidermal growth factor receptor (EGFR) and anaplastic lymphoma receptor tyrosine kinase (ALK) in order to identify patients with superior response to TKIs so that they can avoid conventional chemotherapy. However, to obtain accurate lung biopsies for such testing, patients experience severe discomfort during difficult invasive procedures. Liquid biopsies would be thus much

Replicative nature of ncRNAs makes them easy to detect by polymerase chain reaction and various modifications of this method, also microarrays and sequencing. ncRNAs vary in stability according to their length, secondary structure, association with proteins, or protection by exosomes; however, there is a consensus that relative to DNA or mRNA, shorter ncRNAs are more stable and less likely to be cleaved by RNAses or to be degraded by environmental agents such as storing temperature [62]. There are however some limits and variability between different

Based on many functions and pleiotropic character of ncRNAs, their involvement in progression of cancer and in modulation of therapeutic response is not surprising. In the following lines, we provide an overview (**Table 1**) of ncRNAs currently known to play a role in the development of resistance to TKIs, and what is

**78**


*mRCC, metastatic renal cell carcinoma; RCC, renal cell carcinoma; HCC, hepatocellular carcinoma; NSCLC, nonsmall cell lung carcinoma; HNSC, head and neck squamous carcinoma; LUAD, lung adenocarcinoma; BRCA, breast invasive carcinoma; BC, breast carcinoma; STAD, stomach adenocarcinoma.*

#### **Table 1.**

*Overview of potential ncRNA biomarkers of response to tyrosine kinase inhibitors.*

#### **3.1 Sunitinib**

Most studies on prediction of response by miRNA levels have been carried out on renal cell carcinoma and sunitinib as a prominent treatment choice in patients with clear cell renal cell carcinoma. Ten papers have been published so far on prediction of sunitinib response in metastatic renal cell carcinoma (mRCC). Though there are some discrepancies in experimental design, mainly in samples and technologies used in explorative phase, most of the studies are carried out on a rather small cohort; there is some overlap in results. miR-484, miR-221/222, miR-942, miR-133a, miR-628-5p, and miR-155-5p were successfully validated by more than one study; however, none of them turned out to be significantly deregulated in all the studies [64–73].

It is useful to have some information about mechanistic impact of predictive miRNAs, because usually their deregulation is somehow connected with the development of therapy resistance. For example, in the work of Puente et al., two of three significantly deregulated miRNAs, miR-23b and miR-27b, are known to inhibit Notch1 and c-Met pointing on potential involvement of Notch pathway in sunitinib response, serving as solid base for future research. In some cases, however, the targets of predictive miRNAs are waiting to be characterized and subjected to a further functional analysis of mechanistic connection of a given miRNA with response to sunitinib. In other work [77], miR-99b-5p has been discovered to be significantly lower in patients with shorter progression-free survival; unfortunately they did not manage to validate it in an independent cohort by RT-qPCR with sufficient statistical significance. However, miRNAs from miR-99 family are possibly tumor suppressors not only in RCC; there is evidence of their involvement in OSCC in regulation of IGF1R [81].

#### **3.2 Sorafenib**

Primarily used for treatment of RCC, sorafenib is ineffective in patients with initial resistance, which can be predicted by expression levels of sorafenib resistanceassociated lncRNA (SRLR) identified by Xu et al. [82]. lncRNA-SRLR level has been

**81**

*Noncoding RNAs as Predictive Biomarkers of Therapeutic Response to Tyrosine Kinase Inhibitors…*

correlated with sorafenib therapy response in RCC patients, and clear connection has been demonstrated. Manipulation with its expression leads to changes in response of RCC cell lines. According to recent findings, SRLR acts through IL-6/STAT3 pathway and by binding to NF-κB promotes IL-6 transcription and activation of STAT3, in the end causing the development of sorafenib resistance [82]. To prove that, researchers introduced STAT3 inhibitor and IL-6-receptor antagonist, which restored response

In another study on patients with hepatocellular carcinoma [83], six miRNAs have been significantly associated with progression-free survival (PFS); however, only miR-425-3p was successfully validated. Higher levels of this miRNA indicated longer PFS. In vitro tests have shown reduced cell motility and increased cell death in HCC cell lines when miR-425-3p was added which indicates that miR-425-3p

There are known some mutations in epidermal growth factor receptor (EGFR) which are reliable indicator of response to EGFR-targeting TKIs. However, these mutations are minor, and for patients with wild-type EGFR, there is no biomarker

Quite robust has been a study of non-small cellular lung carcinoma (NSCLC) patients treated with gefitinib [74], where miR-21 has been proven to be a potent biomarker of response. The study has been carried out on 128 radically resected patients in explorative phase compared to 32 healthy controls; results have been validated on 201 EGFR-mutated patients. In patients with better therapy outcome,

Tan et al. [85] showed interesting case report of two patients with exceptional response to gefitinib, diagnosed with head and neck squamous cell carcinoma. Silent mutation in lncRNA epidermal growth factor receptor—associated 1 (EGFR-AS1)—led to destabilization of this lncRNA which in turn shifted splicing of EGFR to isoform D and noncanonical EGFR addiction, thus affecting its sensitiv-

Gefitinib and erlotinib are frequently used in EGFR-mutated lung adenocarcinoma where they reach better results and longer progression-free survival than in wild-type-EGFR lung adenocarcinoma patients. However, in both cases the development of resistance to treatment is inevitable; still its mechanism remains uncovered. The first information on the development of resistance was shown by Wu et al*.* [77]. miR-630 and one of its target transcripts, YAP1, create a feedback loop with ERK and are suspected to be responsible for the resistance in EGFR-mutated adenocarcinoma cells. Further they showed that low level of miR-630 indicates future resistance to TKIs in EGFR-mutated patients with lung

Erlotinib alone has been studied in phase II clinical trial of Swiss Group for Clinical Cancer Research (SAKK) on blood samples of NSCLC patients treated with first-line combination of bevacizumab and erlotinib followed by chemotherapy. The study was focused on circulating miRNAs, and their main objective was to find prognostic miRNAs, but they identified also some predictive miRNAs both for targeted therapy and chemotherapy. miR-223 expression was shown to have the highest predictive value for disease stabilization and time to progression, with

Among other miRNAs, miR-200 family seems to have extensive impact on response to nintedanib, gefitinib, and erlotinib. Nintedanib is a multi-targeted angiokinase inhibitor prescribed for idiopathic pulmonary fibrosis and advanced

higher expression being associated with worse outcome [78].

*DOI: http://dx.doi.org/10.5772/intechopen.86082*

probably acts as tumor suppressor [83].

*3.2.1 Gefitinib, erlotinib, and nintedanib*

of response to the treatment [84].

miR-21 has been significantly reduced.

ity to tyrosine kinase inhibitors.

adenocarcinoma.

to the treatment.

#### *Noncoding RNAs as Predictive Biomarkers of Therapeutic Response to Tyrosine Kinase Inhibitors… DOI: http://dx.doi.org/10.5772/intechopen.86082*

correlated with sorafenib therapy response in RCC patients, and clear connection has been demonstrated. Manipulation with its expression leads to changes in response of RCC cell lines. According to recent findings, SRLR acts through IL-6/STAT3 pathway and by binding to NF-κB promotes IL-6 transcription and activation of STAT3, in the end causing the development of sorafenib resistance [82]. To prove that, researchers introduced STAT3 inhibitor and IL-6-receptor antagonist, which restored response to the treatment.

In another study on patients with hepatocellular carcinoma [83], six miRNAs have been significantly associated with progression-free survival (PFS); however, only miR-425-3p was successfully validated. Higher levels of this miRNA indicated longer PFS. In vitro tests have shown reduced cell motility and increased cell death in HCC cell lines when miR-425-3p was added which indicates that miR-425-3p probably acts as tumor suppressor [83].

#### *3.2.1 Gefitinib, erlotinib, and nintedanib*

*Tyrosine Kinases as Druggable Targets in Cancer*

Nintedanib miR-200

family

**Drug ncRNA Deregulation** 

Lapatinib miR-16 Down BRCA,

*invasive carcinoma; BC, breast carcinoma; STAD, stomach adenocarcinoma.*

*Overview of potential ncRNA biomarkers of response to tyrosine kinase inhibitors.*

**in drugresistant patients**

**Diagnosis Technological platform**

Down LUAD qPCR array Nishijima et al.

Microarray, qPCR

STAD

Neratinib miR-630 Down BRCA qPCRC Corcoran et al.

Afatinib miR-630 Down BRCA qPCRC Corcoran et al*.*

*mRCC, metastatic renal cell carcinoma; RCC, renal cell carcinoma; HCC, hepatocellular carcinoma; NSCLC, nonsmall cell lung carcinoma; HNSC, head and neck squamous carcinoma; LUAD, lung adenocarcinoma; BRCA, breast* 

miR-630 Down BRCA qPCRC Corcoran et al.

**Study**

Venturutti et al. [86]

[79]

[80]

[79]

[79]

Most studies on prediction of response by miRNA levels have been carried out on renal cell carcinoma and sunitinib as a prominent treatment choice in patients with clear cell renal cell carcinoma. Ten papers have been published so far on prediction of sunitinib response in metastatic renal cell carcinoma (mRCC). Though there are some discrepancies in experimental design, mainly in samples and technologies used in explorative phase, most of the studies are carried out on a rather small cohort; there is some overlap in results. miR-484, miR-221/222, miR-942, miR-133a, miR-628-5p, and miR-155-5p were successfully validated by more than one study; however, none of them turned out to be significantly deregulated in all

It is useful to have some information about mechanistic impact of predictive miRNAs, because usually their deregulation is somehow connected with the development of therapy resistance. For example, in the work of Puente et al., two of three significantly deregulated miRNAs, miR-23b and miR-27b, are known to inhibit Notch1 and c-Met pointing on potential involvement of Notch pathway in sunitinib response, serving as solid base for future research. In some cases, however, the targets of predictive miRNAs are waiting to be characterized and subjected to a further functional analysis of mechanistic connection of a given miRNA with response to sunitinib. In other work [77], miR-99b-5p has been discovered to be significantly lower in patients with shorter progression-free survival; unfortunately they did not manage to validate it in an independent cohort by RT-qPCR with sufficient statistical significance. However, miRNAs from miR-99 family are possibly tumor suppressors not only in RCC; there is evidence of their involvement in OSCC

Primarily used for treatment of RCC, sorafenib is ineffective in patients with initial resistance, which can be predicted by expression levels of sorafenib resistanceassociated lncRNA (SRLR) identified by Xu et al. [82]. lncRNA-SRLR level has been

**80**

**3.1 Sunitinib**

**Table 1.**

the studies [64–73].

in regulation of IGF1R [81].

**3.2 Sorafenib**

There are known some mutations in epidermal growth factor receptor (EGFR) which are reliable indicator of response to EGFR-targeting TKIs. However, these mutations are minor, and for patients with wild-type EGFR, there is no biomarker of response to the treatment [84].

Quite robust has been a study of non-small cellular lung carcinoma (NSCLC) patients treated with gefitinib [74], where miR-21 has been proven to be a potent biomarker of response. The study has been carried out on 128 radically resected patients in explorative phase compared to 32 healthy controls; results have been validated on 201 EGFR-mutated patients. In patients with better therapy outcome, miR-21 has been significantly reduced.

Tan et al. [85] showed interesting case report of two patients with exceptional response to gefitinib, diagnosed with head and neck squamous cell carcinoma. Silent mutation in lncRNA epidermal growth factor receptor—associated 1 (EGFR-AS1)—led to destabilization of this lncRNA which in turn shifted splicing of EGFR to isoform D and noncanonical EGFR addiction, thus affecting its sensitivity to tyrosine kinase inhibitors.

Gefitinib and erlotinib are frequently used in EGFR-mutated lung adenocarcinoma where they reach better results and longer progression-free survival than in wild-type-EGFR lung adenocarcinoma patients. However, in both cases the development of resistance to treatment is inevitable; still its mechanism remains uncovered. The first information on the development of resistance was shown by Wu et al*.* [77]. miR-630 and one of its target transcripts, YAP1, create a feedback loop with ERK and are suspected to be responsible for the resistance in EGFR-mutated adenocarcinoma cells. Further they showed that low level of miR-630 indicates future resistance to TKIs in EGFR-mutated patients with lung adenocarcinoma.

Erlotinib alone has been studied in phase II clinical trial of Swiss Group for Clinical Cancer Research (SAKK) on blood samples of NSCLC patients treated with first-line combination of bevacizumab and erlotinib followed by chemotherapy. The study was focused on circulating miRNAs, and their main objective was to find prognostic miRNAs, but they identified also some predictive miRNAs both for targeted therapy and chemotherapy. miR-223 expression was shown to have the highest predictive value for disease stabilization and time to progression, with higher expression being associated with worse outcome [78].

Among other miRNAs, miR-200 family seems to have extensive impact on response to nintedanib, gefitinib, and erlotinib. Nintedanib is a multi-targeted angiokinase inhibitor prescribed for idiopathic pulmonary fibrosis and advanced NSCLC [80]. It has been shown in work on lung cancer cell lines (5 nintedanibresistant/5 nintedanib-sensitive) that some miRNAs belonging to miR-200 family (miR-200, miR-200a, and miR-141) are significantly lower in nintedanib-resistant cells. Induction of miR-200 and miR-141 has led to restored treatment sensitivity in resistant cells. miR-200/ZEB axis might play a role in resistance to treatment and serves as a potential biomarker of response to nintedanib. The work also proved some role of this family in EMT transition which has been outlined before in Izumchenko et al*.* [76] where miR-200 has been suggested to play a role in TGFβ-miR200-MIG6 axis. According to their findings, authors concluded that this pathway creates an EMT-associated switch-inducing resistance to EGFR-targeting drugs. Further, they observed that the ratio of MIG6 versus miR-200 expression indicates response to erlotinib.

Yet another work connected miR-200c with response to erlotinib and gefitinib in patients with NSCLC. When upregulated, miR-200c correlates with sensitivity to gefitinib in EGFR wild-type cell lines. Besides other pathways leading to EMT, in this work it has been shown that miR-200c regulates EMT also through PI3K/ AKT pathway and MEK/WRK. One hundred fifty patients treated with gefitinib or erlotinib as a second- or third-line treatment were tested in this study, and in 66 NSCLC patients with wild-type EGFR, high levels of miR-200c expression were associated with higher disease control rate (DCR), longer progression-free survival (PFS), and longer overall survival (OS) than low miR-200c expression subgroup [75].

#### *3.2.2 Lapatinib*

MiR-16 mediates trastuzumab and lapatinib response, as shown on trastuzumab- and lapatinib-resistant breast and gastric cancer cell cultures [86]. Artificial increase of miR-16 expression had an inhibitory effect on cell growth in vitro, and it is speculated that expression of miR-16 is regulated by phosphatidylinositol 3 kinase (PI3K)/AKT pathway starting at extracellular signal regulated kinases 1/2 (ERK1/2) which are blocked by trastuzumab and lapatinib. Probably due to inhibition of c-Myc which is downregulated by PI3K/AKT, the level of miR-16 is then upregulated to normal level and inhibits proliferation of both breast cancer and gastric cancer cells. The same effect was achieved by artificial increase of miR-16, as stated above, indicating that miR-16 is not only a biomarker but possible therapeutic target, too.

#### *3.2.3 HER-targeting drugs*

miR-630, as mentioned above, has been linked also to response to HER-targeting drugs, namely, lapatinib, neratinib, and afatinib, used in breast and lung cancer. The same problem as elsewhere repeats itself also in these diagnosis—targeting of HER in HER2 overexpressing patients is mostly effective, except in patients with primary or secondary resistance. Response to these drugs is mediated by IGF1R which is targeted by miR-630. Work of Corcoran et al*.* [79] shows that an artificial increase of miR-630 in cells with primary or secondary resistance to anti-HER therapy leads to restored efficacy of such drugs. Blocking of miR-630 leads to the development of resistance. Results were validated also on set of tumor and non-tumor tissue. According to current knowledge, miR-630 plays a dual role in apoptosis and drug resistance, because depending on cell type, it serves as a tumor suppressor in breast carcinoma [87] and hepatocellular carcinoma [88] or as an oncogene in renal cell carcinoma [89].

**83**

*Noncoding RNAs as Predictive Biomarkers of Therapeutic Response to Tyrosine Kinase Inhibitors…*

Noncoding RNAs gained extensive attention in recent years for their unique features as endogenous regulators of gene expression, potential biomarkers, and therapeutic targets. Tissue specificity, stability, and detectability in all types of tissues and body fluids predestine them to become very promising biomarkers applicable in personalized medicine. Major attention has been devoted to miRNAs; less is known about involvement of lncRNAs. Although studies on profiling and feasibility of various ncRNAs as diagnostic, prognostic, and predictive biomarkers are accumulating, none have made it to real clinical practice so far. Here we provide an overview of current knowledge on possible biomarkers of response to tyrosine kinase inhibitors, a breakthrough targeted therapy of several solid tumors. Currently, besides studies focused on sunitinib, there are rather solitary results acquired on small cohorts of less than 100 patients; therefore, it is difficult to come up with any conclusions. Even if there are more studies on response prediction of one therapeutic agent, inter-study discrepancies in validated biomarkers are significant, and results overlap sparsely. This can be ascribed to differences in study design such as type of samples, technology, normalization, statistical analysis, thresholds, and cutoff values set as criteria for stratification of patients and many more. Out of all TKI, sunitinib is much more ahead in terms of number of biomarker studies,

In spite all of that, miR-200 family, miR-221/222, miR-484, miR-221/222, miR-942, miR-133a, miR-628-5p, miR-155-5p, and miR-630 seem to have significant biomarker potential indicated by several studies. However, independent prospective validation on larger cohorts taking utmost account of study design in previous relevant studies is necessary for future clinical application of miRNA-based biomarker

This publication was supported by the Ministry of Health of the Czech Republic,

The authors whose names are listed immediately below certify that they have no affiliations with or involvement in any organization or entity with any financial interest (such as honoraria; educational grants; participation in speakers' bureaus; membership, employment, consultancies, stock ownership, or other equity interest; and expert testimony or patent-licensing arrangements) or nonfinancial interest (such as personal or professional relationships, affiliations, knowledge, or beliefs)

in the subject matter or materials discussed in this manuscript.

*DOI: http://dx.doi.org/10.5772/intechopen.86082*

study design similarity, and partial overlap of the results.

technology to TKIs' therapeutic response prediction.

**Acknowledgements**

grant no. 15-34678A.

**Conflict of interest**

**4. Conclusions**

*Noncoding RNAs as Predictive Biomarkers of Therapeutic Response to Tyrosine Kinase Inhibitors… DOI: http://dx.doi.org/10.5772/intechopen.86082*

#### **4. Conclusions**

*Tyrosine Kinases as Druggable Targets in Cancer*

indicates response to erlotinib.

subgroup [75].

*3.2.2 Lapatinib*

sible therapeutic target, too.

oncogene in renal cell carcinoma [89].

*3.2.3 HER-targeting drugs*

NSCLC [80]. It has been shown in work on lung cancer cell lines (5 nintedanibresistant/5 nintedanib-sensitive) that some miRNAs belonging to miR-200 family (miR-200, miR-200a, and miR-141) are significantly lower in nintedanib-resistant cells. Induction of miR-200 and miR-141 has led to restored treatment sensitivity in resistant cells. miR-200/ZEB axis might play a role in resistance to treatment and serves as a potential biomarker of response to nintedanib. The work also proved some role of this family in EMT transition which has been outlined before in Izumchenko et al*.* [76] where miR-200 has been suggested to play a role in TGFβ-miR200-MIG6 axis. According to their findings, authors concluded that this pathway creates an EMT-associated switch-inducing resistance to EGFR-targeting drugs. Further, they observed that the ratio of MIG6 versus miR-200 expression

Yet another work connected miR-200c with response to erlotinib and gefitinib in patients with NSCLC. When upregulated, miR-200c correlates with sensitivity to gefitinib in EGFR wild-type cell lines. Besides other pathways leading to EMT, in this work it has been shown that miR-200c regulates EMT also through PI3K/ AKT pathway and MEK/WRK. One hundred fifty patients treated with gefitinib or erlotinib as a second- or third-line treatment were tested in this study, and in 66 NSCLC patients with wild-type EGFR, high levels of miR-200c expression were associated with higher disease control rate (DCR), longer progression-free survival (PFS), and longer overall survival (OS) than low miR-200c expression

MiR-16 mediates trastuzumab and lapatinib response, as shown on trastuzumab- and lapatinib-resistant breast and gastric cancer cell cultures [86]. Artificial increase of miR-16 expression had an inhibitory effect on cell growth in vitro, and it is speculated that expression of miR-16 is regulated by phosphatidylinositol 3 kinase (PI3K)/AKT pathway starting at extracellular signal regulated kinases 1/2 (ERK1/2) which are blocked by trastuzumab and lapatinib. Probably due to inhibition of c-Myc which is downregulated by PI3K/AKT, the level of miR-16 is then upregulated to normal level and inhibits proliferation of both breast cancer and gastric cancer cells. The same effect was achieved by artificial increase of miR-16, as stated above, indicating that miR-16 is not only a biomarker but pos-

miR-630, as mentioned above, has been linked also to response to HER-targeting drugs, namely, lapatinib, neratinib, and afatinib, used in breast and lung cancer. The same problem as elsewhere repeats itself also in these diagnosis—targeting of HER in HER2 overexpressing patients is mostly effective, except in patients with primary or secondary resistance. Response to these drugs is mediated by IGF1R which is targeted by miR-630. Work of Corcoran et al*.* [79] shows that an artificial increase of miR-630 in cells with primary or secondary resistance to anti-HER therapy leads to restored efficacy of such drugs. Blocking of miR-630 leads to the development of resistance. Results were validated also on set of tumor and non-tumor tissue. According to current knowledge, miR-630 plays a dual role in apoptosis and drug resistance, because depending on cell type, it serves as a tumor suppressor in breast carcinoma [87] and hepatocellular carcinoma [88] or as an

**82**

Noncoding RNAs gained extensive attention in recent years for their unique features as endogenous regulators of gene expression, potential biomarkers, and therapeutic targets. Tissue specificity, stability, and detectability in all types of tissues and body fluids predestine them to become very promising biomarkers applicable in personalized medicine. Major attention has been devoted to miRNAs; less is known about involvement of lncRNAs. Although studies on profiling and feasibility of various ncRNAs as diagnostic, prognostic, and predictive biomarkers are accumulating, none have made it to real clinical practice so far. Here we provide an overview of current knowledge on possible biomarkers of response to tyrosine kinase inhibitors, a breakthrough targeted therapy of several solid tumors. Currently, besides studies focused on sunitinib, there are rather solitary results acquired on small cohorts of less than 100 patients; therefore, it is difficult to come up with any conclusions. Even if there are more studies on response prediction of one therapeutic agent, inter-study discrepancies in validated biomarkers are significant, and results overlap sparsely. This can be ascribed to differences in study design such as type of samples, technology, normalization, statistical analysis, thresholds, and cutoff values set as criteria for stratification of patients and many more. Out of all TKI, sunitinib is much more ahead in terms of number of biomarker studies, study design similarity, and partial overlap of the results.

In spite all of that, miR-200 family, miR-221/222, miR-484, miR-221/222, miR-942, miR-133a, miR-628-5p, miR-155-5p, and miR-630 seem to have significant biomarker potential indicated by several studies. However, independent prospective validation on larger cohorts taking utmost account of study design in previous relevant studies is necessary for future clinical application of miRNA-based biomarker technology to TKIs' therapeutic response prediction.

#### **Acknowledgements**

This publication was supported by the Ministry of Health of the Czech Republic, grant no. 15-34678A.

#### **Conflict of interest**

The authors whose names are listed immediately below certify that they have no affiliations with or involvement in any organization or entity with any financial interest (such as honoraria; educational grants; participation in speakers' bureaus; membership, employment, consultancies, stock ownership, or other equity interest; and expert testimony or patent-licensing arrangements) or nonfinancial interest (such as personal or professional relationships, affiliations, knowledge, or beliefs) in the subject matter or materials discussed in this manuscript.

*Tyrosine Kinases as Druggable Targets in Cancer*

#### **Author details**

Julia Kovacova and Ondrej Slaby\* Central European Institute of Technology, Masaryk University, Brno, Czech Republic

\*Address all correspondence to: on.slaby@gmail.com

© 2019 The Author(s). Licensee IntechOpen. This chapter is distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/ by/3.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

**85**

*Noncoding RNAs as Predictive Biomarkers of Therapeutic Response to Tyrosine Kinase Inhibitors…*

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*DOI: http://dx.doi.org/10.5772/intechopen.86082*

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**Author details**

Czech Republic

Julia Kovacova and Ondrej Slaby\*

provided the original work is properly cited.

\*Address all correspondence to: on.slaby@gmail.com

© 2019 The Author(s). Licensee IntechOpen. This chapter is distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/ by/3.0), which permits unrestricted use, distribution, and reproduction in any medium,

Central European Institute of Technology, Masaryk University, Brno,

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[63] Glinge C, Clauss S, Boddum K, Jabbari R, Jabbari J, Risgaard B, et al. Stability of circulating bloodbased microRNAs - pre-analytic

2016;**34**(15\_suppl):3516

0432.CCR-18-1324

2017;**35**(2):180-188

2017;**13**(4):221-227

[51] Calin GA, Liu CG, Sevignani C, Ferracin M, Felli N, Dumitru CD, et al. MicroRNA profiling reveals distinct signatures in B cell chronic lymphocytic leukemias. Proceedings of the National Academy of Sciences of the United States of America. 2004;**101**(32):11755-11760

[52] Gutschner T, Richtig G, Haemmerle M, Pichler M. From biomarkers to therapeutic targets—the promises and perils of long non-coding RNAs in cancer. Cancer Metastasis Reviews.

[53] Di Leva G, Garofalo M, Croce CM. MicroRNAs in cancer. Annual Review of Pathology. 2014;**9**:287-314

[54] Gupta RA, Shah N, Wang KC, Kim J, Horlings HM, Wong DJ, et al. Long non-coding RNA HOTAIR reprograms chromatin state to promote cancer metastasis. Nature.

[55] Zhu X, Li H, Long L, Hui L, Chen H, Wang X, et al. miR-126 enhances the sensitivity of non-small cell lung cancer cells to anticancer agents by targeting vascular endothelial growth factor A. Acta Biochimica et Biophysica Sinica.

[56] Gao W, Liu L, Xu J, Shao Q, Liu Y, Zeng H, et al. A systematic analysis of predicted MiR-31-targets identifies a diagnostic and prognostic signature for lung cancer. Biomedicine and Pharmacotherapy. 2014;**68**(4):419-427

[57] Laurent-Puig P, Paget-Bailly S, Vernerey D, Vazart C, Decaulne

2010;**464**(7291):1071-1076

2012;**44**(6):519-526

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[64] García-Donas J, Beuselinck B, Inglada-Pérez L, Graña O, Schöffski P, Wozniak A, et al. Deep sequencing reveals microRNAs predictive of antiangiogenic drug response. JCI Insight. 2016;**1**(10):e86051

[65] Kovacova J, Juracek J, Poprach A, Buchler T, Kopecky J, Fiala O, et al. Candidate microRNA biomarkers of therapeutic response to sunitinib in metastatic renal cell carcinoma: A validation study in patients with extremely good and poor response. Anticancer Research. 2018;**38**(5):2961-2965

[66] Prior C, Perez-Gracia JL, Garcia-Donas J, Rodriguez-Antona C, Guruceaga E, Esteban E, et al. Identification of tissue microRNAs predictive of sunitinib activity in patients with metastatic renal cell carcinoma. PLoS One. 2014;**9**(1):e86263

[67] Puente J, Laínez N, Dueñas M, Méndez-Vidal MJ, Esteban E, Castellano D, et al. Novel potential predictive markers of sunitinib outcomes in long-term responders versus primary refractory patients with metastatic clear-cell renal cell carcinoma. Oncotarget. 2017;**8**(18):30410-30421

[68] Lukamowicz-Rajska M, Mittmann C, Prummer M, Zhong Q, Bedke J, Hennenlotter J, et al. MiR-99b-5p expression and response to tyrosine kinase inhibitor treatment in clear cell renal cell carcinoma patients. Oncotarget. 2016;**7**(48):78433-78447

[69] Ralla B, Busch J, Flörcken A, Westermann J, Zhao Z, Kilic E, et al. miR-9-5p in nephrectomy specimens is a potential predictor of primary resistance to first-line treatment with tyrosine kinase inhibitors in patients with metastatic renal cell carcinoma. Cancers (Basel). 2018;**10**(9):pii: E321. DOI: 10.3390/cancers10090321

[70] Berkers J, Govaere O, Wolter P, Beuselinck B, Schöffski P, van Kempen LC, et al. A possible role for microRNA-141 down-regulation in sunitinib resistant metastatic clear cell renal cell carcinoma through induction of epithelial-to-mesenchymal transition and hypoxia resistance. Journal of Urology. 2013;**189**(5):1930-1938

[71] Gámez-Pozo A, Antón-Aparicio LM, Bayona C, Borrega P, Gallegos Sancho MI, García-Domínguez R, et al. MicroRNA expression profiling of peripheral blood samples predicts resistance to first-line sunitinib in advanced renal cell carcinoma patients. Neoplasia. 2012;**14**(12):1144-1152

[72] Khella HWZ, Butz H, Ding Q, Rotondo F, Evans KR, Kupchak P, et al. miR-221/222 are involved in response to sunitinib treatment in metastatic renal cell carcinoma. Molecular Therapy. 2015;**23**(11):1748-1758

[73] Merhautova J, Hezova R, Poprach A, Kovarikova A, Radova L, Svoboda M, et al. miR-155 and miR-484 are associated with time to progression in metastatic renal cell carcinoma treated with sunitinib. BioMed Research International. 2015;**2015**:941980

[74] Shen Y, Tang D, Yao R, Wang M, Wang Y, Yao Y, et al. microRNA expression profiles associated with survival, disease progression, and response to gefitinib in completely resected non-small-cell lung cancer with EGFR mutation. Medical Oncology. 2013;**30**(4):750

[75] Li J, Li X, Ren S, Chen X, Zhang Y, Zhou F, et al. miR-200c overexpression is associated with better efficacy of EGFR-TKIs in non-small cell lung cancer patients with EGFR wild-type. Oncotarget. 2014;**5**(17):7902-7916

[76] Izumchenko E, Chang X, Michailidi C, Kagohara L, Ravi R, Paz K, et al. The TGFβ-miR200-MIG6 pathway

orchestrates the EMT-associated kinase switch that induces resistance to EGFR inhibitors. Cancer Research. 2014;**74**(14):3995-4005

[77] Wu DW, Wang YC, Wang L, Chen CY, Lee H. A low microRNA-630 expression confers resistance to tyrosine kinase inhibitors in EGFR-mutated lung adenocarcinomas via miR-630/ YAP1/ERK feedback loop. Theranostics. 2018;**8**(5):1256-1269

[78] Joerger M, Baty F, Früh M, Droege C, Stahel RA, Betticher DC, et al. Circulating microRNA profiling in patients with advanced non-squamous NSCLC receiving bevacizumab/ erlotinib followed by platinumbased chemotherapy at progression (SAKK 19/05). Lung Cancer. 2014;**85**(2):306-313

[79] Corcoran C, Rani S, Breslin S, Gogarty M, Ghobrial IM, Crown J, et al. miR-630 targets IGF1R to regulate response to HER-targeting drugs and overall cancer cell progression in HER2 over-expressing breast cancer. Molecular Cancer. 2014;**13**:71

[80] Nishijima N, Seike M, Soeno C, Chiba M, Miyanaga A, Noro R, et al. miR-200/ZEB axis regulates sensitivity to nintedanib in non-small cell lung cancer cells. International Journal of Oncology. 2016;**48**(3):937-944

[81] Yen YC, Shiah SG, Chu HC, Hsu YM, Hsiao JR, Chang JY, et al. Reciprocal regulation of microRNA-99a and insulin-like growth factor I receptor signaling in oral squamous cell carcinoma cells. Molecular Cancer. 2014;**13**:6

[82] Xu Z, Yang F, Wei D, Liu B, Chen C, Bao Y, et al. Long noncoding RNA-SRLR elicits intrinsic sorafenib resistance via evoking IL-6/STAT3 axis in renal cell carcinoma. Oncogene. 2017;**36**(14):1965-1977

[83] Vaira V, Roncalli M, Carnaghi C, Faversani A, Maggioni M, Augello C, et al. MicroRNA-425-3p predicts response to sorafenib therapy in patients with hepatocellular carcinoma. Liver International. 2015;**35**(3):1077-1086

[84] Li X, Cai W, Yang G, Su C, Ren S, Zhao C, et al. Comprehensive analysis of EGFR-mutant abundance and its effect on efficacy of EGFR TKIs in advanced NSCLC with EGFR mutations. Journal of Thoracic Oncology. 2017;**12**(9):1388-1397

[85] Tan DSW, Chong FT, Leong HS, Toh SY, Lau DP, Kwang XL, et al. Long noncoding RNA EGFR-AS1 mediates epidermal growth factor receptor addiction and modulates treatment response in squamous cell carcinoma. Nature Medicine. 2017;**23**(10):1167-1175

[86] Venturutti L, Cordo Russo RI, Rivas MA, Mercogliano MF, Izzo F, Oakley RH, et al. MiR-16 mediates trastuzumab and lapatinib response in ErbB-2 positive breast and gastric cancer via its novel targets CCNJ and FUBP1. Oncogene. 2016;**35**(48):6189-6202

[87] Zhou CX, Wang CL, Yu AL, Wang QY, Zhan MN, Tang J, et al. MiR-630 suppresses breast cancer progression by targeting metadherin. Oncotarget. 2016;**7**(2):1288-1299

[88] Chen WX, Zhang ZG, Ding ZY, Liang HF, Song J, Tan XL, et al. MicroRNA-630 suppresses tumor metastasis through the TGF-βmiR-630-Slug signaling pathway and correlates inversely with poor prognosis in hepatocellular carcinoma. Oncotarget. 2016;**7**(16):22674-22686

[89] Zhao JJ, Chen PJ, Duan RQ, Li KJ, Wang YZ, Li Y. miR-630 functions as a tumor oncogene in renal cell carcinoma. Archives of Medical Science. 2016;**12**(3):473-478

**91**

**Chapter 5**

*Yibin Feng*

**Abstract**

are discussed below.

**1. Introduction**

then be discussed.

clinical efficacy, limitations, future strategies

Cancer Management by Tyrosine

Limitation, and Future Strategies

Tyrosine kinase inhibitors are taking up an increasingly significant role in treating cancers. There are different types of TKIs currently used in clinical settings. However, TKI-associated limitations such as resistance and adverse effects are frequently reported. In this chapter, we would comprehensively review the clinical efficacy of current TKIs using the currently available clinical trial data. Significant limitations of TKIs on cancer treatment will be further summarized and discussed. The strategies on overcoming the limitations of TKIs to maximize their clinical effectiveness and efficiency, such as complementary use of Chinese medicine or development of novel TKIs, will be proposed. In conclusion, an overall picture of the clinical use and limitation of the current TKIs will be drawn and the prospective development in overcoming the limitations will be discussed. Evaluation of clinical efficacy of TKIs, evaluation of limitations of TKIs, strategies in overcoming the limitations of TKIs, and conclusion (including prospective development of TKIs)

**Keywords:** tyrosine kinase inhibitors, targeted therapy, cancer management,

The development of tyrosine kinase inhibitors (TKIs) is revolutionary in treating cancers, as they act much more specifically toward malignant cells when compared to conventional cytotoxic chemotherapy [1]. In the past two decades, a plenty of novel compounds under this category have been discovered and are taking up an increasingly significant role in cancer treatment, especially for metastatic carcinomas. Many are proven with great efficacy. They showed significantly better results in progress-free survival rate with fewer side effects [1]. Looking back at the short but eventful history of this drug class, this book chapter intends to do an evaluation on clinical efficacy and effectiveness of TKIs, basing on the currently available clinical trial data. Significant limitations of TKIs on cancer treatment will be further summarized and discussed. Finally, strategies in overcoming the limitations will be proposed. With an overall picture of clinical use and limitations of current TKIs, prospective developmental directions will

Kinase Inhibitors: Efficacy,

*Venice Wing Tung Ho, Hor Yue Tan, Ning Wang and* 

#### **Chapter 5**

*Tyrosine Kinases as Druggable Targets in Cancer*

[83] Vaira V, Roncalli M, Carnaghi C, Faversani A, Maggioni M, Augello C, et al. MicroRNA-425-3p predicts response to sorafenib therapy in patients with hepatocellular carcinoma. Liver International. 2015;**35**(3):1077-1086

[84] Li X, Cai W, Yang G, Su C, Ren S, Zhao C, et al. Comprehensive analysis of EGFR-mutant abundance and its effect on efficacy of EGFR TKIs in advanced NSCLC with EGFR mutations.

Journal of Thoracic Oncology.

[85] Tan DSW, Chong FT, Leong HS, Toh SY, Lau DP, Kwang XL, et al. Long noncoding RNA EGFR-AS1 mediates epidermal growth factor receptor addiction and modulates treatment response in squamous cell carcinoma. Nature Medicine. 2017;**23**(10):1167-1175

[86] Venturutti L, Cordo Russo RI, Rivas MA, Mercogliano MF, Izzo F, Oakley RH, et al. MiR-16 mediates trastuzumab and lapatinib response in ErbB-2 positive breast and gastric cancer via its novel targets CCNJ and FUBP1. Oncogene. 2016;**35**(48):6189-6202

[87] Zhou CX, Wang CL, Yu AL, Wang QY, Zhan MN, Tang J, et al. MiR-630 suppresses breast cancer progression by targeting metadherin. Oncotarget.

[88] Chen WX, Zhang ZG, Ding ZY, Liang HF, Song J, Tan XL, et al. MicroRNA-630 suppresses tumor metastasis through the TGF-βmiR-630-Slug signaling pathway and correlates inversely with poor prognosis in hepatocellular carcinoma. Oncotarget. 2016;**7**(16):22674-22686

[89] Zhao JJ, Chen PJ, Duan RQ, Li KJ, Wang YZ, Li Y. miR-630 functions as a tumor oncogene in renal cell

carcinoma. Archives of Medical Science.

2016;**7**(2):1288-1299

2016;**12**(3):473-478

2017;**12**(9):1388-1397

[77] Wu DW, Wang YC, Wang L, Chen CY, Lee H. A low microRNA-630 expression confers resistance to tyrosine kinase inhibitors in EGFR-mutated lung adenocarcinomas via miR-630/ YAP1/ERK feedback loop. Theranostics.

[78] Joerger M, Baty F, Früh M, Droege C, Stahel RA, Betticher DC, et al. Circulating microRNA profiling in patients with advanced non-squamous NSCLC receiving bevacizumab/ erlotinib followed by platinumbased chemotherapy at progression (SAKK 19/05). Lung Cancer.

[79] Corcoran C, Rani S, Breslin S, Gogarty M, Ghobrial IM, Crown J, et al. miR-630 targets IGF1R to regulate response to HER-targeting drugs and overall cancer cell progression in HER2 over-expressing breast cancer.

Molecular Cancer. 2014;**13**:71

[80] Nishijima N, Seike M, Soeno C, Chiba M, Miyanaga A, Noro R, et al. miR-200/ZEB axis regulates sensitivity to nintedanib in non-small cell lung cancer cells. International Journal of Oncology. 2016;**48**(3):937-944

[81] Yen YC, Shiah SG, Chu HC, Hsu YM, Hsiao JR, Chang JY, et al. Reciprocal regulation of microRNA-99a and insulin-like growth factor I receptor signaling in oral squamous cell carcinoma cells. Molecular Cancer.

[82] Xu Z, Yang F, Wei D, Liu B, Chen C, Bao Y, et al. Long noncoding RNA-SRLR elicits intrinsic sorafenib

resistance via evoking IL-6/STAT3 axis in renal cell carcinoma. Oncogene.

2017;**36**(14):1965-1977

orchestrates the EMT-associated kinase switch that induces resistance to EGFR inhibitors. Cancer Research.

2014;**74**(14):3995-4005

2018;**8**(5):1256-1269

2014;**85**(2):306-313

**90**

2014;**13**:6

## Cancer Management by Tyrosine Kinase Inhibitors: Efficacy, Limitation, and Future Strategies

*Venice Wing Tung Ho, Hor Yue Tan, Ning Wang and Yibin Feng*

#### **Abstract**

Tyrosine kinase inhibitors are taking up an increasingly significant role in treating cancers. There are different types of TKIs currently used in clinical settings. However, TKI-associated limitations such as resistance and adverse effects are frequently reported. In this chapter, we would comprehensively review the clinical efficacy of current TKIs using the currently available clinical trial data. Significant limitations of TKIs on cancer treatment will be further summarized and discussed. The strategies on overcoming the limitations of TKIs to maximize their clinical effectiveness and efficiency, such as complementary use of Chinese medicine or development of novel TKIs, will be proposed. In conclusion, an overall picture of the clinical use and limitation of the current TKIs will be drawn and the prospective development in overcoming the limitations will be discussed. Evaluation of clinical efficacy of TKIs, evaluation of limitations of TKIs, strategies in overcoming the limitations of TKIs, and conclusion (including prospective development of TKIs) are discussed below.

**Keywords:** tyrosine kinase inhibitors, targeted therapy, cancer management, clinical efficacy, limitations, future strategies

#### **1. Introduction**

The development of tyrosine kinase inhibitors (TKIs) is revolutionary in treating cancers, as they act much more specifically toward malignant cells when compared to conventional cytotoxic chemotherapy [1]. In the past two decades, a plenty of novel compounds under this category have been discovered and are taking up an increasingly significant role in cancer treatment, especially for metastatic carcinomas. Many are proven with great efficacy. They showed significantly better results in progress-free survival rate with fewer side effects [1]. Looking back at the short but eventful history of this drug class, this book chapter intends to do an evaluation on clinical efficacy and effectiveness of TKIs, basing on the currently available clinical trial data. Significant limitations of TKIs on cancer treatment will be further summarized and discussed. Finally, strategies in overcoming the limitations will be proposed. With an overall picture of clinical use and limitations of current TKIs, prospective developmental directions will then be discussed.

Tyrosine kinases are a subclass of protein kinases, which are enzymes that catalyze the transfer of gamma phosphate group from a nucleoside triphosphate donor (e.g., ATP) to targeted proteins, hence resulting in a conformational change of the protein, which alters its function [2]. Tyrosine kinases are frequently involved in the cellular response to various growth factors, cytokines, and hormones (e.g., EGF, PDGF, VEGF, ABL, and JAK) [3, 4]. These molecules are, in many cases, responsible for the various mechanisms of tumor growth such as cell growth, cell proliferation, stromal growth, angiogenesis, and tissue invasion [4, 5]. In neoplasms, there are often gene mutations resulting in activation of the above pathways [6, 7]. It could be an excessive expression of growth factors/hormones, an excessive expression of their receptors (i.e., increased sensitivity to receptor tyrosine kinases), or intrinsic activation of tyrosine kinases receptors, etc. [7]. Thus, by inhibiting them, we may be able to control or even regress tumor growth.

Tyrosine kinases inhibitors (TKIs) inhibit these growth factor signaling pathways by various mechanisms. They compete with ATP, substrate or for sites for dimerization, and could also act allosterically [8]. By targeting these mutated pathways, TKIs are able to act specifically to cells with malignant changes and disrupt their malignant growth without causing much disturbance to other physiological functioning.

Imatinib was the first tyrosine kinase inhibitor developed, and also the first to be approved by the U.S. Food and Drug administration (FDA) in May 2001. It was approved initially for the use on patients with chronic myeloid leukemia. Shortly after, other tyrosine kinase inhibitors are discovered. There are currently at least 26 FDA-approved tyrosine kinase inhibitors [9] and more going down the pipeline. TKIs were initially only used as second-/third-line therapies, but nowadays, it is increasingly used as primary therapy, especially in selected patients with known mutations.

Tyrosine kinase inhibitors can be classified according to their acting target [10]. Major target classes include BCR-ABLTKIs (e.g., imatinib, dasatinib, and nilotinib), EGFR TKIs (e.g., gefitinib and erlotinib), and VEGFR TKIs (e.g., sunitinib and sorafenib) [10]. Another way to classify them would however be according to their generations. There are up to three, and even four, generations of TKIs. They differ not only by the period they are discovered, but also by their working mechanisms. The first-generation TKIs (e.g., imatinib and gefitinib) are reversible/competitive inhibitors (mostly ATP-competitive inhibitors) and are mostly single-targeted, whereas the second-generation TKIs (e.g., afatinib and dasatinib) and other newer generations of TKIs (e.g., osimertinib) are mostly irreversible/covalent binding and multitargeted [11]. Comparison of approaches used in first and newer generations will be made in later sections.

When compared to traditional chemotherapy and radiation therapy, which simply targets fast-growing cells, TKIs, along with many other targeted drugs, have a much higher specificity toward tumor cells. Thus, they provide a broader therapeutic window with less general toxicity. They are taking up a large role in treating cancers by showing significant improvements in progression-free survival rate and tolerability in patients.

#### **2. Evaluation of clinical efficacy/effectiveness of TKIs**

Numerous studies have been conducted to evaluate the clinical efficacy and effectiveness of TKIs. Different TKIs are found to have different clinical performances on different cancers. Most of them showed significant efficacy, especially in improving progression-free survival (PFS), when used as first-line or non–first-line therapies. Therefore, a lot of studies are trying to expand the use of these TKIs to other

**93**

*Cancer Management by Tyrosine Kinase Inhibitors: Efficacy, Limitation, and Future Strategies*

cancers, yet results are not always promising. However, overall survival was not improved in many cases. A lot of the studies discovered a high percentage of users progressing to drug resistance eventually. In the following, the clinical efficacy and effectiveness of a number of TKIs will be discussed individually. And in the end of

Imatinib is an orally administered small molecule tyrosine kinase inhibitor, which inhibits tyrosine kinases, specifically BCR-ABL, c-KIT, and PDGFRA [12]. Its marketing name is Gleevec (USA) or Glivec (Europe/Australia), also referred to as CGP57148B or STI571 in some literature [13]. It was invented in 1990s and first approved by FDA in 2001. It has been a huge success and was a revolutionary discovery in combating cancer. Up till today, Imatinib is well known for its efficacy with CML and GIST, and other tumors. A summary on its clinical efficacies will be

Imatinib is first developed against chronic myeloid leukemia (CML). CML is characterized by the presence of a Philadelphia chromosome [14], which is a product of reciprocal translocation between chromosome 9 and 22. BCL-ABL tyrosine kinase is overexpressed in these CML patients and is a driving force for leukemogenesis [15]. By inhibiting the BCL-ABL tyrosine kinase, Imatinib is found to be able to control the disease effectively. Imatinib has proven significant clinical efficacy and effectiveness, both as a single agent or in combination therapy in

Imatinib, as a single agent, outperformed combined chemotherapy and interferon therapy with major cytogenic response induced in 87.1% (vs. 34.7%) at 18 months [16]. Imatinib also showed significant superiority, when combined with chemotherapy, against the combination of interferon therapy and chemotherapy. In a well-known International Randomized Study (IRIS) on 1106 newly diagnosed CML patients, complete hematological response was induced in 95.3% patients and complete cytogenic response in 73.8% patients [17]. The patients have an overall low risk of progressing to accelerated phase/blast crisis, and overall survival rate at 8 years remained as high as 85% [18] exceeding the reported survival rates in all previous CML therapies. Other studies trying to combine imatinib with other therapies, including chemotherapy and IFN, showed that MCR/CCR did tend to occur earlier, for example, rate of MCR at 3 months was 70% compared to 60% when combining imatinib with cytarabine. Yet the gap seemed to close after 12 months, with 84 and 83%, respectively. Combinations have however also resulted in more severe side effects, and are thus in general not preferred [19]. Other studies echo their results and have shown that imatinib in combination with chemotherapy does not display superiority against imatinib as a monotherapy in CML-chronic phase,

Imatinib is proved effective in accelerated phase/blast crisis as well [19, 22]. However, there are also studies reporting that its effects are only transient, and can only produce palliative function to those patients at this stage [23]. Acquired resistance developed in a large portion of the cases treated with imatinib. Acquired resistance was defined as a progression of disease or loss of response with a 5- to 10-fold increase in BCL-ABL transcripts. These patients are subsequently treated

*DOI: http://dx.doi.org/10.5772/intechopen.82513*

this section, a brief comparison is drawn.

*2.1.1.1 Chronic myeloid leukemia (CML)*

but instead yielded more toxicity [20, 21].

*2.1.1 Imatinib (BCR-ABL TKIs)*

provided as follows:

**2.1 Clinical efficacy/effectiveness of first-generation TKIs**

chronic phase as well as accelerated phase/blast crisis in CML.

*Cancer Management by Tyrosine Kinase Inhibitors: Efficacy, Limitation, and Future Strategies DOI: http://dx.doi.org/10.5772/intechopen.82513*

cancers, yet results are not always promising. However, overall survival was not improved in many cases. A lot of the studies discovered a high percentage of users progressing to drug resistance eventually. In the following, the clinical efficacy and effectiveness of a number of TKIs will be discussed individually. And in the end of this section, a brief comparison is drawn.

#### **2.1 Clinical efficacy/effectiveness of first-generation TKIs**

#### *2.1.1 Imatinib (BCR-ABL TKIs)*

*Tyrosine Kinases as Druggable Targets in Cancer*

we may be able to control or even regress tumor growth.

Tyrosine kinases are a subclass of protein kinases, which are enzymes that catalyze the transfer of gamma phosphate group from a nucleoside triphosphate donor (e.g., ATP) to targeted proteins, hence resulting in a conformational change of the protein, which alters its function [2]. Tyrosine kinases are frequently involved in the cellular response to various growth factors, cytokines, and hormones (e.g., EGF, PDGF, VEGF, ABL, and JAK) [3, 4]. These molecules are, in many cases, responsible for the various mechanisms of tumor growth such as cell growth, cell proliferation, stromal growth, angiogenesis, and tissue invasion [4, 5]. In neoplasms, there are often gene mutations resulting in activation of the above pathways [6, 7]. It could be an excessive expression of growth factors/hormones, an excessive expression of their receptors (i.e., increased sensitivity to receptor tyrosine kinases), or intrinsic activation of tyrosine kinases receptors, etc. [7]. Thus, by inhibiting them,

Tyrosine kinases inhibitors (TKIs) inhibit these growth factor signaling pathways by various mechanisms. They compete with ATP, substrate or for sites for dimerization, and could also act allosterically [8]. By targeting these mutated pathways, TKIs are able to act specifically to cells with malignant changes and disrupt their malignant growth without causing much disturbance to other physiological functioning. Imatinib was the first tyrosine kinase inhibitor developed, and also the first to be approved by the U.S. Food and Drug administration (FDA) in May 2001. It was approved initially for the use on patients with chronic myeloid leukemia. Shortly after, other tyrosine kinase inhibitors are discovered. There are currently at least 26 FDA-approved tyrosine kinase inhibitors [9] and more going down the pipeline. TKIs were initially only used as second-/third-line therapies, but nowadays, it is increasingly used as primary therapy, especially in selected patients with

Tyrosine kinase inhibitors can be classified according to their acting target [10]. Major target classes include BCR-ABLTKIs (e.g., imatinib, dasatinib, and nilotinib), EGFR TKIs (e.g., gefitinib and erlotinib), and VEGFR TKIs (e.g., sunitinib and sorafenib) [10]. Another way to classify them would however be according to their generations. There are up to three, and even four, generations of TKIs. They differ not only by the period they are discovered, but also by their working mechanisms. The first-generation TKIs (e.g., imatinib and gefitinib) are reversible/competitive inhibitors (mostly ATP-competitive inhibitors) and are mostly single-targeted, whereas the second-generation TKIs (e.g., afatinib and dasatinib) and other newer generations of TKIs (e.g., osimertinib) are mostly irreversible/covalent binding and multitargeted [11]. Comparison of approaches used in first and newer generations

When compared to traditional chemotherapy and radiation therapy, which simply targets fast-growing cells, TKIs, along with many other targeted drugs, have a much higher specificity toward tumor cells. Thus, they provide a broader therapeutic window with less general toxicity. They are taking up a large role in treating cancers by showing significant improvements in progression-free survival rate and

Numerous studies have been conducted to evaluate the clinical efficacy and effectiveness of TKIs. Different TKIs are found to have different clinical performances on different cancers. Most of them showed significant efficacy, especially in improving progression-free survival (PFS), when used as first-line or non–first-line therapies. Therefore, a lot of studies are trying to expand the use of these TKIs to other

**2. Evaluation of clinical efficacy/effectiveness of TKIs**

**92**

known mutations.

will be made in later sections.

tolerability in patients.

Imatinib is an orally administered small molecule tyrosine kinase inhibitor, which inhibits tyrosine kinases, specifically BCR-ABL, c-KIT, and PDGFRA [12]. Its marketing name is Gleevec (USA) or Glivec (Europe/Australia), also referred to as CGP57148B or STI571 in some literature [13]. It was invented in 1990s and first approved by FDA in 2001. It has been a huge success and was a revolutionary discovery in combating cancer. Up till today, Imatinib is well known for its efficacy with CML and GIST, and other tumors. A summary on its clinical efficacies will be provided as follows:

#### *2.1.1.1 Chronic myeloid leukemia (CML)*

Imatinib is first developed against chronic myeloid leukemia (CML). CML is characterized by the presence of a Philadelphia chromosome [14], which is a product of reciprocal translocation between chromosome 9 and 22. BCL-ABL tyrosine kinase is overexpressed in these CML patients and is a driving force for leukemogenesis [15]. By inhibiting the BCL-ABL tyrosine kinase, Imatinib is found to be able to control the disease effectively. Imatinib has proven significant clinical efficacy and effectiveness, both as a single agent or in combination therapy in chronic phase as well as accelerated phase/blast crisis in CML.

Imatinib, as a single agent, outperformed combined chemotherapy and interferon therapy with major cytogenic response induced in 87.1% (vs. 34.7%) at 18 months [16]. Imatinib also showed significant superiority, when combined with chemotherapy, against the combination of interferon therapy and chemotherapy. In a well-known International Randomized Study (IRIS) on 1106 newly diagnosed CML patients, complete hematological response was induced in 95.3% patients and complete cytogenic response in 73.8% patients [17]. The patients have an overall low risk of progressing to accelerated phase/blast crisis, and overall survival rate at 8 years remained as high as 85% [18] exceeding the reported survival rates in all previous CML therapies. Other studies trying to combine imatinib with other therapies, including chemotherapy and IFN, showed that MCR/CCR did tend to occur earlier, for example, rate of MCR at 3 months was 70% compared to 60% when combining imatinib with cytarabine. Yet the gap seemed to close after 12 months, with 84 and 83%, respectively. Combinations have however also resulted in more severe side effects, and are thus in general not preferred [19]. Other studies echo their results and have shown that imatinib in combination with chemotherapy does not display superiority against imatinib as a monotherapy in CML-chronic phase, but instead yielded more toxicity [20, 21].

Imatinib is proved effective in accelerated phase/blast crisis as well [19, 22]. However, there are also studies reporting that its effects are only transient, and can only produce palliative function to those patients at this stage [23]. Acquired resistance developed in a large portion of the cases treated with imatinib. Acquired resistance was defined as a progression of disease or loss of response with a 5- to 10-fold increase in BCL-ABL transcripts. These patients are subsequently treated

with higher dosage of imatinib, or a second-generation BCR-ABL TKI. Yet, allogenic hematopoietic cell transplantation remains the ultimate solution.

Response rate of imatinib in unselected CML patients is high only due to the high occurrence (91%) of the presence of Philadelphia chromosome [24, 25]. Its clinical efficacy in Philadelphia chromosome negative patients is however very low.

#### *2.1.1.2 Gastrointestinal stromal tumors (GIST)*

Gastrointestinal stromal tumor is the most common neoplasm of the mesenchymal cells of the digestive system and is thought to arise from the interstitial cells of Cajal [26]. C-KIT and PDGFRA tyrosine kinase mutations are present in a vast majority (85%) of these tumors [27–29]. Imatinib is able to inhibit the mutant C-KIT and PDGFRA tyrosine kinases. Imatinib has high efficacy against GIST in patients with these two mutations, both as an adjuvant therapy after surgery in non-metastatic GISTs, and as a palliative treatment for advanced non-resectable GISTs. For primary resectable GISTs, recurrence rate after surgery is extremely high. Studies have found that adjuvant therapy of imatinib can prolong relapse free survival (RFS), especially in those patients with great risks of relapse [30, 31]. Absolute relapse rate was 19 vs. 47% in imatinib treated patients and non-treated patients, respectively [30, 32]. Other studies have shown that imatinib displays similar promising results in GISTs in advanced stages as well. Approximately 80% of GIST patients with advanced disease receive some benefit from imatinib therapy [33], with median overall survival of 57 months, compared to 18 in chemotherapy. Yet, a significant proportion eventually became resistant with a median time to progression of 2 years [33]. Primary resistance was found in around 12% of the patients [34]. It was also found that, higher dosage of Imatinib showed no superiority over lower dosage [35, 36]. In GIST patients, side effects arose in 99% of the case [37]. The most common adverse events were diarrhea (29% of patients), nausea (27%), eyelid edema (23%), peripheral edema (22%), muscle cramps (15%), and fatigue (13%) [38]. Luckily, most patients found the side effects tolerable [37].

#### *2.1.1.3 Others*

Imatinib was also approved by the FDA and has now become the first-line treatment for patients with Philadelphia chromosome positive acute lymphoblastic leukemia (Ph + ALL), which accounts for approximately 30% of all ALL cases [39]. Patients treated with imatinib early are found to have higher overall survival, event-free survival, and relapse-free survival [40]. Studies have also justified the efficacy of imatinib in dermatofibrosarcoma protuberans [41, 42], chronic eosinophilic leukemia [43], systemic mastocytosis [44, 45], aggressive fibromatosis [46], malignant melanoma [47], AIDS-related Kaposi's sarcoma [48], chordoma [49, 50], recurrent epithelial ovarian cancer [51], and anaplastic thyroid cancer [52]. The use of imatinib in these cancers is not yet approved, but lots of clinical trials have already been conducted and their use in the future is expected.

#### *2.1.1.4 Tolerability of side effects*

Clinical trials have shown that the side effects of imatinib are generally welltolerated by the patients. Common side effects include edema, rash, nausea, diarrhea, muscle cramps, and more severely, myelosuppression [53]. Luckily, most side effects were mild to moderate, and in more than 95% of the patients, side effects could be managed with standard concomitant treatments [38].

**95**

results.

similar [67, 68].

*2.1.2.2 Other*

*Cancer Management by Tyrosine Kinase Inhibitors: Efficacy, Limitation, and Future Strategies*

Gefitinib (Iressa, ZD1839) and erlotinib (Tarceva, OSI774) are the two firstgeneration EGFR-TKIs and are used mostly against non-small cell lung cancer (NSCLC), which accounts for 85% of all lung cancers [54]. As competitive antagonists of the ATP-binding site of EGFR, gefitinib and erlotinib were approved by the FDA in May 2003 and November 2004, respectively. As many cancers involve the hyperactivity of EGFRs, numerous studies have been conducted on drug repurpos-

Gefitinib and Erlotinib are most established in treating non-small cell lung cancer (NSCLC) and are currently the first-line treatment for EGFR-mutated NSCLC patients [55]. EGFR mutations are commonly found in NSCLC patients, particularly in Asian populations, female gender, and nonsmokers [56, 57]. EGFR mutations are associated with the activation of antiapoptotic pathways as well as proliferation induction, thus leading to uncontrolled growth of cells. Among all the types of NSCLC, adenocarcinoma takes up the largest proportion, and is also the most commonly associated with EGFR mutations. Gefitinib was initially approved against NSCLC, but was then withdrawn from the market due to various studies showing its lack of benefit in overall survival in unselected patients. However, it was later found that EGFR mutation is a huge positive predicting factor for drug response to gefitinib, and was thus approved again. Gefitinib has well established clinical efficacy against advanced NSCLC when compared to chemotherapy [58, 59]. Progression-free survival was 10.8 vs. 5.4 months and mean overall survival was 30.5 vs. 23.6 months [59]. Combination of gefitinib with chemotherapy showed no superiority over gefitinib monotherapy [60]. Similarly, Erlotinib showed significant superiority over chemotherapy in EGFR mutation positive advanced NSCLC (PFS 13.1 vs. 4.6 months) [61]. However, its overall survival was reported to be lower than that of chemotherapy (24.68 vs. 26.16 months) [62]. Erlotinib plus chemotherapy is superior to chemotherapy alone with an improved PFS but not OS [63]. A meta-analysis revealed that the efficacy between gefitinib and erlotinib are

comparable with erlotinib reported of more adverse drug effects [64].

Clinical effectiveness in unselected NSCLC patients were low as the frequency

There are currently some researches conducted on the use of gefitinib and erlotinib on other cancers, yet most are currently not approved yet. Gefitinib is reported to show effect on pancreatic cancer [69] and is approved to treat metastatic pancreatic cancer in combination with chemotherapy in 2005. The effects of gefitinib and erlotinib on other cancers are also being investigated, such as nasopharyngeal cancer [70], gastric cancer [71], esophageal cancer [72], cervical cancer [73], renal cell carcinoma [74], and hepatocellular carcinoma [75]. Yet most studies are still in preclinical stages, and those limited clinical trials were often with disappointing

of EGFR gene mutation is 47.9% in Asians but only 19.2% in Western patients [65]. About only 10–35% of the NSCLC patients have EGFR mutations which are sensitive to the EGFR TKIs [66]. Progression-free survival in rare EGFR mutations was also lower than that of common EGFR mutations, yet the overall survival was

*DOI: http://dx.doi.org/10.5772/intechopen.82513*

*2.1.2 Gefitinib and erlotinib (EGFR TKIs)*

ing of these two TKIs.

*2.1.2.1 Non-small cell lung cancer*

*Cancer Management by Tyrosine Kinase Inhibitors: Efficacy, Limitation, and Future Strategies DOI: http://dx.doi.org/10.5772/intechopen.82513*

#### *2.1.2 Gefitinib and erlotinib (EGFR TKIs)*

*Tyrosine Kinases as Druggable Targets in Cancer*

*2.1.1.2 Gastrointestinal stromal tumors (GIST)*

with higher dosage of imatinib, or a second-generation BCR-ABL TKI. Yet, allogenic

Gastrointestinal stromal tumor is the most common neoplasm of the mesenchymal cells of the digestive system and is thought to arise from the interstitial cells of Cajal [26]. C-KIT and PDGFRA tyrosine kinase mutations are present in a vast majority (85%) of these tumors [27–29]. Imatinib is able to inhibit the mutant C-KIT and PDGFRA tyrosine kinases. Imatinib has high efficacy against GIST in patients with these two mutations, both as an adjuvant therapy after surgery in non-metastatic GISTs, and as a palliative treatment for advanced non-resectable GISTs. For primary resectable GISTs, recurrence rate after surgery is extremely high. Studies have found that adjuvant therapy of imatinib can prolong relapse free survival (RFS), especially in those patients with great risks of relapse [30, 31]. Absolute relapse rate was 19 vs. 47% in imatinib treated patients and non-treated patients, respectively [30, 32]. Other studies have shown that imatinib displays similar promising results in GISTs in advanced stages as well. Approximately 80% of GIST patients with advanced disease receive some benefit from imatinib therapy [33], with median overall survival of 57 months, compared to 18 in chemotherapy. Yet, a significant proportion eventually became resistant with a median time to progression of 2 years [33]. Primary resistance was found in around 12% of the patients [34]. It was also found that, higher dosage of Imatinib showed no superiority over lower dosage [35, 36]. In GIST patients, side effects arose in 99% of the case [37]. The most common adverse events were diarrhea (29% of patients), nausea (27%), eyelid edema (23%), peripheral edema (22%), muscle cramps (15%), and fatigue

Response rate of imatinib in unselected CML patients is high only due to the high occurrence (91%) of the presence of Philadelphia chromosome [24, 25]. Its clinical

hematopoietic cell transplantation remains the ultimate solution.

efficacy in Philadelphia chromosome negative patients is however very low.

(13%) [38]. Luckily, most patients found the side effects tolerable [37].

already been conducted and their use in the future is expected.

could be managed with standard concomitant treatments [38].

Imatinib was also approved by the FDA and has now become the first-line treatment for patients with Philadelphia chromosome positive acute lymphoblastic leukemia (Ph + ALL), which accounts for approximately 30% of all ALL cases [39]. Patients treated with imatinib early are found to have higher overall survival, event-free survival, and relapse-free survival [40]. Studies have also justified the efficacy of imatinib in dermatofibrosarcoma protuberans [41, 42], chronic eosinophilic leukemia [43], systemic mastocytosis [44, 45], aggressive fibromatosis [46], malignant melanoma [47], AIDS-related Kaposi's sarcoma [48], chordoma [49, 50], recurrent epithelial ovarian cancer [51], and anaplastic thyroid cancer [52]. The use of imatinib in these cancers is not yet approved, but lots of clinical trials have

Clinical trials have shown that the side effects of imatinib are generally welltolerated by the patients. Common side effects include edema, rash, nausea, diarrhea, muscle cramps, and more severely, myelosuppression [53]. Luckily, most side effects were mild to moderate, and in more than 95% of the patients, side effects

**94**

*2.1.1.3 Others*

*2.1.1.4 Tolerability of side effects*

Gefitinib (Iressa, ZD1839) and erlotinib (Tarceva, OSI774) are the two firstgeneration EGFR-TKIs and are used mostly against non-small cell lung cancer (NSCLC), which accounts for 85% of all lung cancers [54]. As competitive antagonists of the ATP-binding site of EGFR, gefitinib and erlotinib were approved by the FDA in May 2003 and November 2004, respectively. As many cancers involve the hyperactivity of EGFRs, numerous studies have been conducted on drug repurposing of these two TKIs.

#### *2.1.2.1 Non-small cell lung cancer*

Gefitinib and Erlotinib are most established in treating non-small cell lung cancer (NSCLC) and are currently the first-line treatment for EGFR-mutated NSCLC patients [55]. EGFR mutations are commonly found in NSCLC patients, particularly in Asian populations, female gender, and nonsmokers [56, 57]. EGFR mutations are associated with the activation of antiapoptotic pathways as well as proliferation induction, thus leading to uncontrolled growth of cells. Among all the types of NSCLC, adenocarcinoma takes up the largest proportion, and is also the most commonly associated with EGFR mutations. Gefitinib was initially approved against NSCLC, but was then withdrawn from the market due to various studies showing its lack of benefit in overall survival in unselected patients. However, it was later found that EGFR mutation is a huge positive predicting factor for drug response to gefitinib, and was thus approved again. Gefitinib has well established clinical efficacy against advanced NSCLC when compared to chemotherapy [58, 59]. Progression-free survival was 10.8 vs. 5.4 months and mean overall survival was 30.5 vs. 23.6 months [59]. Combination of gefitinib with chemotherapy showed no superiority over gefitinib monotherapy [60]. Similarly, Erlotinib showed significant superiority over chemotherapy in EGFR mutation positive advanced NSCLC (PFS 13.1 vs. 4.6 months) [61]. However, its overall survival was reported to be lower than that of chemotherapy (24.68 vs. 26.16 months) [62]. Erlotinib plus chemotherapy is superior to chemotherapy alone with an improved PFS but not OS [63]. A meta-analysis revealed that the efficacy between gefitinib and erlotinib are comparable with erlotinib reported of more adverse drug effects [64].

Clinical effectiveness in unselected NSCLC patients were low as the frequency of EGFR gene mutation is 47.9% in Asians but only 19.2% in Western patients [65]. About only 10–35% of the NSCLC patients have EGFR mutations which are sensitive to the EGFR TKIs [66]. Progression-free survival in rare EGFR mutations was also lower than that of common EGFR mutations, yet the overall survival was similar [67, 68].

#### *2.1.2.2 Other*

There are currently some researches conducted on the use of gefitinib and erlotinib on other cancers, yet most are currently not approved yet. Gefitinib is reported to show effect on pancreatic cancer [69] and is approved to treat metastatic pancreatic cancer in combination with chemotherapy in 2005. The effects of gefitinib and erlotinib on other cancers are also being investigated, such as nasopharyngeal cancer [70], gastric cancer [71], esophageal cancer [72], cervical cancer [73], renal cell carcinoma [74], and hepatocellular carcinoma [75]. Yet most studies are still in preclinical stages, and those limited clinical trials were often with disappointing results.

#### *2.1.2.3 Tolerability of side effects*

Gefitinib has better tolerability than many cytotoxic drugs [76]. Acne-like rash was reported as the most common side effect, others include nausea, diarrhea, anorexia, stomatitis, dehydration, etc. Side effects were in general well-tolerated and few withdraw from gefitinib due to intolerability [76]. Erlotinib is in general well tolerated as well. Yet it was reported to have more severe side effects than that of gefitinib and was more frequently involved with dosage reduction due to side effect intolerance [77]. Significantly higher rates and severity of skin rash, nausea, vomiting, fatigue, and stomatitis were also reported.

#### *2.1.3 Sunitinib and sorafenib (VEGFR TKIs)*

Sunitinib (Sutent, SU11248) and sorafenib (Nexavar) are first-generation VEGFR-TKIs and are well established in the use against renal cell carcinoma (RCC) and hepatocellular carcinoma (HCC), respectively. The VEGF family are frequently overexpressed in various solid tumors and bind to vascular endothelium and induce angiogenesis. Sunitinib and sorafenib are both multitarget ATPcompetitive TKIs. Sunitinib inhibits tyrosine kinases such as VEGFR2, PDGFRβ, KIT, RET, CSF1R, and FLT3. Sorafenib inhibits tyrosine kinases including VEGFRs, PDGFRs, B-RAF, MEK, and ERK. They are both FDA approved for RCC, GIST and RCC, HCC, respectively. Their clinical efficacies are discussed below.

#### *2.1.3.1 RCC*

VEGF overexpression and high vascularization is a common feature of RCC. Both sunitinib and sorafenib were approved for renal cell carcinoma as first- and secondline therapies. Sunitinib was approved for metastatic RCC (mRCC) in 2006 after a phase III trial showing its superiority over IFN therapy [78]. Sunitinib displayed well clinical efficacy and effectiveness with median OS 26.4 months and PFS 11.0 months, especially in clear cell RCC, compared to OS 21.8 months in IFN therapy [78]. However, study also showed that median PFS and OS are not significantly different in poor-risk group [79]. Finally, a large scaled clinical trials conducted on unselected heterogeneous RCC patients confirmed the effectiveness of sunitinib [80]. Combination of sunitinib with chemotherapy was not explored after phase I trials showing its poor safety profile [81]. Trials combining sunitinib with other therapies have also shown no improved efficacy, yet increased toxicity [82]. On the other hand, Sorafenib was also proven to have high clinical efficacy against mRCC, both as firstand second-line therapy [83]. It was found to prolong PFS when compared to placebo after the failure of immunotherapy [84]. Yet there is no statistically significant difference in OS. Studies comparing efficacy of sunitinib and sorafenib showed no significant difference, with sorafenib slightly superior in elderly patients [85]. Sequence of use of sunitinib and sorafenib also has no significant difference [86].

#### *2.1.3.2 HCC*

Preclinical studies have demonstrated that MEK and ERK pathways play a role in hepatocellular carcinoma [87]. VEGF pathway also plays a significant role in angiogenesis in HCC [88]. This provides a window of opportunity of prolonging survival through TKIs targeting these pathways, including sorafenib. For unresectable HCC, especially in cases where potential curative methods or transarterial chemoembolization (TACE) are not available, Sorafenib is highly recommended as it demonstrates high clinical efficacy [89]. Sorafenib was reported with 3 months

**97**

*Cancer Management by Tyrosine Kinase Inhibitors: Efficacy, Limitation, and Future Strategies*

longer in median overall survival (10.7 vs. 7.9) when compared to placebo [90]. Yet there was no significant difference in the median progression time to symptomatic progression [91]. Sorafenib, when combined with chemotherapy, also showed superiority over chemotherapy alone, with PFS 6.0 vs. 2.7 months and OS 13.7 vs. 6.5 months [92]. Yet it has poor effectiveness in generalized HCC patients and many

Sunitinib is used against GIST as well and has been approved for usage following failure/intolerance of imatinib in 2006 [94]. The median time to progression was 27.3 weeks compared to 6.4 weeks in placebo [95]. There was no overall survival benefit of sunitinib over placebo, but the results were not reliable due to crossing over of placebo patients to sorafenib group. Studies have been conducted to modify the patient selection procedure in attempt to further raise its effectiveness, but are all in vain [96]. On the other hand, sorafenib also showed certain efficacy toward GIST. Yet its efficacy was lower than that of imatinib, and was thus only used as

Sorafenib is also approved for use against advanced thyroid cancer which are resistant to radioactive iodine. Prior to the discovery of sorafenib, there was no effective treatment for this group of patients and overall survival was poor [98]. With sorafenib, a phase III trial showed that their PFS is greatly improved when compared to placebo (10.8 vs. 5.8 months) and thus provides a new treatment

Compared to other TKIs, the tolerability of sunitinib is lower. Adverse events of any grade are reported in up to 95% of patients with one-third drug interruption due to intolerability in metastatic RCC [100]. Most common grade 3/4 adverse events include thrombocytopenia (10%), fatigue (9%), and asthenia, neutropenia and hand foot mouth syndrome (each 7%) [80]. It is commonly associated with various side effects including hypertension, hypothyroidism, diarrhea, fatigue, and nausea. Therefore, studies have recommended a special schedule for the administration for this reason, with 2-week drug use followed by a 1-week drug holiday alternatively, which offers a similar efficacy but with higher tolerability [101–103]. Sorafenib has a slightly better safety profile [104]. Safety profile agrees with what is previously reported, with hand–foot skin reaction (58.0%), lipase elevation (57.3%), and diarrhea (42.7%) as the most frequent drug-related adverse events. Neither unknown adverse event nor cumulative toxicity was observed over the long-term use of sorafenib [105]. Yet intolerability

option for radioactive iodine resistant advanced DTC patients [99].

**2.2 Clinical efficacy/effectiveness of second-generation TKIs**

*2.2.1 Dasatinib, nilotinib, bosutinib, and radotinib (BCR-ABL TKIs)*

Following the success of Imatinib, many second-generation TKIs targeting BCR-ABL have also been developed. These include dasatinib, nilotinib, bosutinib, and radotinib, and also a few more that will not be included in this discussion, including

*DOI: http://dx.doi.org/10.5772/intechopen.82513*

argue that its efficacy is questionable [93].

third/fourth line, after failure of initial therapy [97].

*2.1.3.4 Differentiated thyroid cancer (DTC)*

*2.1.3.5 Tolerability of side effects*

remains one of its greatest limitations.

*2.1.3.3 GIST*

#### *Cancer Management by Tyrosine Kinase Inhibitors: Efficacy, Limitation, and Future Strategies DOI: http://dx.doi.org/10.5772/intechopen.82513*

longer in median overall survival (10.7 vs. 7.9) when compared to placebo [90]. Yet there was no significant difference in the median progression time to symptomatic progression [91]. Sorafenib, when combined with chemotherapy, also showed superiority over chemotherapy alone, with PFS 6.0 vs. 2.7 months and OS 13.7 vs. 6.5 months [92]. Yet it has poor effectiveness in generalized HCC patients and many argue that its efficacy is questionable [93].

#### *2.1.3.3 GIST*

*Tyrosine Kinases as Druggable Targets in Cancer*

vomiting, fatigue, and stomatitis were also reported.

*2.1.3 Sunitinib and sorafenib (VEGFR TKIs)*

Gefitinib has better tolerability than many cytotoxic drugs [76]. Acne-like rash was reported as the most common side effect, others include nausea, diarrhea, anorexia, stomatitis, dehydration, etc. Side effects were in general well-tolerated and few withdraw from gefitinib due to intolerability [76]. Erlotinib is in general well tolerated as well. Yet it was reported to have more severe side effects than that of gefitinib and was more frequently involved with dosage reduction due to side effect intolerance [77]. Significantly higher rates and severity of skin rash, nausea,

Sunitinib (Sutent, SU11248) and sorafenib (Nexavar) are first-generation VEGFR-TKIs and are well established in the use against renal cell carcinoma (RCC) and hepatocellular carcinoma (HCC), respectively. The VEGF family are frequently overexpressed in various solid tumors and bind to vascular endothelium and induce angiogenesis. Sunitinib and sorafenib are both multitarget ATPcompetitive TKIs. Sunitinib inhibits tyrosine kinases such as VEGFR2, PDGFRβ, KIT, RET, CSF1R, and FLT3. Sorafenib inhibits tyrosine kinases including

VEGFRs, PDGFRs, B-RAF, MEK, and ERK. They are both FDA approved for RCC, GIST and RCC, HCC, respectively. Their clinical efficacies are discussed below.

VEGF overexpression and high vascularization is a common feature of RCC. Both sunitinib and sorafenib were approved for renal cell carcinoma as first- and secondline therapies. Sunitinib was approved for metastatic RCC (mRCC) in 2006 after a phase III trial showing its superiority over IFN therapy [78]. Sunitinib displayed well clinical efficacy and effectiveness with median OS 26.4 months and PFS

11.0 months, especially in clear cell RCC, compared to OS 21.8 months in IFN therapy [78]. However, study also showed that median PFS and OS are not significantly different in poor-risk group [79]. Finally, a large scaled clinical trials conducted on unselected heterogeneous RCC patients confirmed the effectiveness of sunitinib [80]. Combination of sunitinib with chemotherapy was not explored after phase I trials showing its poor safety profile [81]. Trials combining sunitinib with other therapies have also shown no improved efficacy, yet increased toxicity [82]. On the other hand, Sorafenib was also proven to have high clinical efficacy against mRCC, both as firstand second-line therapy [83]. It was found to prolong PFS when compared to placebo after the failure of immunotherapy [84]. Yet there is no statistically significant difference in OS. Studies comparing efficacy of sunitinib and sorafenib showed no significant difference, with sorafenib slightly superior in elderly patients [85]. Sequence of

Preclinical studies have demonstrated that MEK and ERK pathways play a role in hepatocellular carcinoma [87]. VEGF pathway also plays a significant role in angiogenesis in HCC [88]. This provides a window of opportunity of prolonging survival through TKIs targeting these pathways, including sorafenib. For unresectable HCC, especially in cases where potential curative methods or transarterial chemoembolization (TACE) are not available, Sorafenib is highly recommended as it demonstrates high clinical efficacy [89]. Sorafenib was reported with 3 months

use of sunitinib and sorafenib also has no significant difference [86].

*2.1.2.3 Tolerability of side effects*

**96**

*2.1.3.2 HCC*

*2.1.3.1 RCC*

Sunitinib is used against GIST as well and has been approved for usage following failure/intolerance of imatinib in 2006 [94]. The median time to progression was 27.3 weeks compared to 6.4 weeks in placebo [95]. There was no overall survival benefit of sunitinib over placebo, but the results were not reliable due to crossing over of placebo patients to sorafenib group. Studies have been conducted to modify the patient selection procedure in attempt to further raise its effectiveness, but are all in vain [96]. On the other hand, sorafenib also showed certain efficacy toward GIST. Yet its efficacy was lower than that of imatinib, and was thus only used as third/fourth line, after failure of initial therapy [97].

#### *2.1.3.4 Differentiated thyroid cancer (DTC)*

Sorafenib is also approved for use against advanced thyroid cancer which are resistant to radioactive iodine. Prior to the discovery of sorafenib, there was no effective treatment for this group of patients and overall survival was poor [98]. With sorafenib, a phase III trial showed that their PFS is greatly improved when compared to placebo (10.8 vs. 5.8 months) and thus provides a new treatment option for radioactive iodine resistant advanced DTC patients [99].

#### *2.1.3.5 Tolerability of side effects*

Compared to other TKIs, the tolerability of sunitinib is lower. Adverse events of any grade are reported in up to 95% of patients with one-third drug interruption due to intolerability in metastatic RCC [100]. Most common grade 3/4 adverse events include thrombocytopenia (10%), fatigue (9%), and asthenia, neutropenia and hand foot mouth syndrome (each 7%) [80]. It is commonly associated with various side effects including hypertension, hypothyroidism, diarrhea, fatigue, and nausea. Therefore, studies have recommended a special schedule for the administration for this reason, with 2-week drug use followed by a 1-week drug holiday alternatively, which offers a similar efficacy but with higher tolerability [101–103]. Sorafenib has a slightly better safety profile [104]. Safety profile agrees with what is previously reported, with hand–foot skin reaction (58.0%), lipase elevation (57.3%), and diarrhea (42.7%) as the most frequent drug-related adverse events. Neither unknown adverse event nor cumulative toxicity was observed over the long-term use of sorafenib [105]. Yet intolerability remains one of its greatest limitations.

#### **2.2 Clinical efficacy/effectiveness of second-generation TKIs**

#### *2.2.1 Dasatinib, nilotinib, bosutinib, and radotinib (BCR-ABL TKIs)*

Following the success of Imatinib, many second-generation TKIs targeting BCR-ABL have also been developed. These include dasatinib, nilotinib, bosutinib, and radotinib, and also a few more that will not be included in this discussion, including ON012380, MK0457, PHA739358, etc. They are much more potent than imatinib and showed promising efficacy in treating patients who have failed imatinib treatment [106].

Dasatinib (Sprycel, DB01254) was the first FDA approved among them and is a dual Src and ABL kinase inhibitor. Besides binding to these two kinases, it also has inhibitory effect on PDGFRβ, c-KIT, and EPHA2 [107]. By targeting more kinases than those of imatinib, dasatinib is able to tackle multiple types of resistant mechanisms against imatinib, including secondary BCR-ABL mutation, alternative Src signaling pathway activation, and multidrug resistance gene overexpression. Study showed durable results of treatment with dasatinib following imatinib. Imatinib resistant/ intolerant patients showed early (3–6 months) complete cytogenic response and major molecular response, and were associated with better PFS and OS rates [108, 109]. When compared to imatinib as first-line treatment to newly diagnosed CML, dasatinib showed even better response. It was able to achieve higher percentage of complete cytogenic response and major molecular response with a higher rate [110].

Nilotinib (Tasigna, AMN107), on the other hand, is more structurally similar to imatinib, but is 20–50 folds more potent. Nilotinib was another huge success. It was able to induce complete hematological response in 92% of the patients who were resistant/intolerant to imatinib [111]. Similarly, it was also found to be superior as first-line treatment than imatinib for newly diagnosed Ph + CML [112]. Both Dasatinib and Nilotinib are found to give similar results in large community settings as well. When compared to first-generation TKI imatinib, dasatinib and nilotinib performed significantly better as first-line treatment to newly diagnosed CML patients. They achieve higher Complete Cytogenic Response (CCyR) or Major Molecular Response (MMR) at 6, 12, and 18 months, respectively. By 12 months, 61% patients achieved CCyR or MMR compared to only 38% treated with imatinib. Time to MMR is also significantly higher in dasatinib and nilotinib than imatinib [113].

Bosutinib (Bosulif, SKI606) was initially approved in CML-AP/BC, and is later expanded to CML-CP. Trials prove improved rates of MMR at 12 months when compared to imatinib (47.2 vs. 36.9%) [114]. Soon it was also used as first-line therapy against CML.

Radotinib (Supect, IY5511) also showed significant superiority over imatinib. With minimum 12 months follow-up, radotinib demonstrated significantly higher and faster rates of CCyR and MMR than imatinib in patients with newly diagnosed CML-CP [115].

#### *2.2.1.1 Tolerability of side effects*

The second-generation BCR-ABL TKIs seem to have significantly higher efficacy than imatinib. Yet, their side effects are also more severe than that of imatinib. This is likely due to the increased potency as well as multi-targeting of the drugs. For example, when comparing bosutinib to imatinib, patients taking bosutinib have higher rates of increased liver enzyme values (24 vs. 4%), thrombocytopenia (13.8 vs. 5.7%), neutropenia (6.7 vs. 12.1%), and diarrhea (7.8 vs. <1%). 77.9% patients experienced severe Grade 3/4 adverse events and 24% patients had to discontinue bosutinib therapy due to emergence of adverse events in a study [116]. Radotinib's side effects are also more severe than that of imatinib. Grade 3/4 ALT/AST elevations caused 68% dosage reduction/interruption in radotinib patients, but only 19% in imatinib patients.

#### *2.2.2 Afatinib and dacomitinib (EGFR TKIs)*

Second-generation EGFR TKIs are irreversible inhibitors and are designed to target other ErbB family members, including HER2, to have more potent inhibition.

**99**

progression.

sorafenib [125].

*Cancer Management by Tyrosine Kinase Inhibitors: Efficacy, Limitation, and Future Strategies*

They target not only the T790M mutation of EGFR, but also other EGFR-activating

Afatinib (Gilotrif, BIBW2992) is an irreversible inhibitor for the ERBB family, including HER1(EGFR), HER2, and HER4. Studies have proven that afatinib was effective in prolonging PFS when compared to chemotherapy (median PFS 11.1 vs. 6.9 months) [118]. When compared to erlotinib, afatinib can also significantly increase PFS by 18%, improve OS by 19% and improve disease control rate (51 vs. 40%) in NSCLC patients after failure of chemotherapy. It was eventually

Dacomitinib (PF299804) is also an irreversible inhibitor of the ERBB family, including HER1(EGFR), HER2 and 4. It is currently still in the preregistration stage and is not approved yet in any country. Findings have shown superiority over gefitinib: PFS 14.7 months with dacomitinib vs. 9.2 months with gefitinib as first-

Second-generation EGFR-TKIs exhibit many dose-limiting toxicities, mainly

Pazopanib (Votrient, GW786034B) was compared to sunitinib and showed superiority. It was shown to significantly improve PFS when compared to placebo in both treatment naïve and cytokine-pretreated patients of RCC [121]. Similar to the first-generation VEGFR-TKIs, Pazopanib inhibits a large number of pathways, including VEGFR, c-KIT, FGFR, PDGFRβ. The lack of specificity accounts for its multiple side effects. Yet, its tolerability is higher than that of sorafenib and

Tivozanib and axitinib on the contrary, are well-known for their higher selectivity. Tivozanib (Fotivda, AV-951) is highly selective for VEGFR. In a study conducted on metastatic RCC, Tivozanib outperformed sorafenib as first-line treatment in prolonging PFS [124]. The study revealed that Tivozanib improved PFS in RCC by 3 months (30%) when compared to sorafenib, yet has an inferior overall survival [124, 125]. For this reason, it is unable to obtain approval from FDA. It was however approved by the European Medicines Agency (EMA). Axitinib (Inlyta, AG13736) is also highly selective for VEGFR. Axitinib was proved to be better than sorafenib in treating RCCs by giving longer PFS (6.8 vs. 4.7 months) in pretreated patients and

Regorafenib (STIVARGA) is approved by the FDA in 2012 for its use in metastatic colorectal cancer (mCRC) and GIST. Regorafenib monotherapy was found to significantly improve OS (6.4 vs. 5.0 months) in mCRC when compared to placebo following failure of standard therapy [126]. Soon after, its efficacy in GIST was also found. A clinical trial compared patients treated with regorafenib monotherapy vs. placebo after acquiring resistance against imatinib and sunitinib [127]. PFS was way higher in regorafenib group (4.8 vs. 0.9 months) and is thus approved by the FDA. OS was however not determined as the patients in the placebo group were crossed over to the regorafenib group after disease

Their tolerability is significantly better than sorafenib, especially with tivozanib.

Drug dosage reduction due to intolerance was 11.6% in tivozanib, but 42.8% in

*DOI: http://dx.doi.org/10.5772/intechopen.82513*

mutations as well as wild-type EGFR [117].

line therapy [119, 120].

sunitinib [122, 123].

are thus approved as second-line use.

*2.2.3.1 Tolerability of side effects*

approved by FDA as another first-line therapy for NSCLC.

skin and GI toxicities, as they inhibit WT-EGFRs as well [117].

*2.2.3 Pazopanib, tivozanib, axitinib, and regorafenib (VEGFR TKIs)*

*Cancer Management by Tyrosine Kinase Inhibitors: Efficacy, Limitation, and Future Strategies DOI: http://dx.doi.org/10.5772/intechopen.82513*

They target not only the T790M mutation of EGFR, but also other EGFR-activating mutations as well as wild-type EGFR [117].

Afatinib (Gilotrif, BIBW2992) is an irreversible inhibitor for the ERBB family, including HER1(EGFR), HER2, and HER4. Studies have proven that afatinib was effective in prolonging PFS when compared to chemotherapy (median PFS 11.1 vs. 6.9 months) [118]. When compared to erlotinib, afatinib can also significantly increase PFS by 18%, improve OS by 19% and improve disease control rate (51 vs. 40%) in NSCLC patients after failure of chemotherapy. It was eventually approved by FDA as another first-line therapy for NSCLC.

Dacomitinib (PF299804) is also an irreversible inhibitor of the ERBB family, including HER1(EGFR), HER2 and 4. It is currently still in the preregistration stage and is not approved yet in any country. Findings have shown superiority over gefitinib: PFS 14.7 months with dacomitinib vs. 9.2 months with gefitinib as firstline therapy [119, 120].

Second-generation EGFR-TKIs exhibit many dose-limiting toxicities, mainly skin and GI toxicities, as they inhibit WT-EGFRs as well [117].

#### *2.2.3 Pazopanib, tivozanib, axitinib, and regorafenib (VEGFR TKIs)*

Pazopanib (Votrient, GW786034B) was compared to sunitinib and showed superiority. It was shown to significantly improve PFS when compared to placebo in both treatment naïve and cytokine-pretreated patients of RCC [121]. Similar to the first-generation VEGFR-TKIs, Pazopanib inhibits a large number of pathways, including VEGFR, c-KIT, FGFR, PDGFRβ. The lack of specificity accounts for its multiple side effects. Yet, its tolerability is higher than that of sorafenib and sunitinib [122, 123].

Tivozanib and axitinib on the contrary, are well-known for their higher selectivity. Tivozanib (Fotivda, AV-951) is highly selective for VEGFR. In a study conducted on metastatic RCC, Tivozanib outperformed sorafenib as first-line treatment in prolonging PFS [124]. The study revealed that Tivozanib improved PFS in RCC by 3 months (30%) when compared to sorafenib, yet has an inferior overall survival [124, 125]. For this reason, it is unable to obtain approval from FDA. It was however approved by the European Medicines Agency (EMA). Axitinib (Inlyta, AG13736) is also highly selective for VEGFR. Axitinib was proved to be better than sorafenib in treating RCCs by giving longer PFS (6.8 vs. 4.7 months) in pretreated patients and are thus approved as second-line use.

Regorafenib (STIVARGA) is approved by the FDA in 2012 for its use in metastatic colorectal cancer (mCRC) and GIST. Regorafenib monotherapy was found to significantly improve OS (6.4 vs. 5.0 months) in mCRC when compared to placebo following failure of standard therapy [126]. Soon after, its efficacy in GIST was also found. A clinical trial compared patients treated with regorafenib monotherapy vs. placebo after acquiring resistance against imatinib and sunitinib [127]. PFS was way higher in regorafenib group (4.8 vs. 0.9 months) and is thus approved by the FDA. OS was however not determined as the patients in the placebo group were crossed over to the regorafenib group after disease progression.

#### *2.2.3.1 Tolerability of side effects*

Their tolerability is significantly better than sorafenib, especially with tivozanib. Drug dosage reduction due to intolerance was 11.6% in tivozanib, but 42.8% in sorafenib [125].

*Tyrosine Kinases as Druggable Targets in Cancer*

treatment [106].

CML-CP [115].

*2.2.1.1 Tolerability of side effects*

*2.2.2 Afatinib and dacomitinib (EGFR TKIs)*

ON012380, MK0457, PHA739358, etc. They are much more potent than imatinib and showed promising efficacy in treating patients who have failed imatinib

Dasatinib (Sprycel, DB01254) was the first FDA approved among them and is a dual Src and ABL kinase inhibitor. Besides binding to these two kinases, it also has inhibitory effect on PDGFRβ, c-KIT, and EPHA2 [107]. By targeting more kinases than those of imatinib, dasatinib is able to tackle multiple types of resistant mechanisms against imatinib, including secondary BCR-ABL mutation, alternative Src signaling pathway activation, and multidrug resistance gene overexpression. Study showed durable results of treatment with dasatinib following imatinib. Imatinib resistant/ intolerant patients showed early (3–6 months) complete cytogenic response and major molecular response, and were associated with better PFS and OS rates [108, 109]. When compared to imatinib as first-line treatment to newly diagnosed CML, dasatinib showed even better response. It was able to achieve higher percentage of complete

cytogenic response and major molecular response with a higher rate [110].

higher in dasatinib and nilotinib than imatinib [113].

Nilotinib (Tasigna, AMN107), on the other hand, is more structurally similar to imatinib, but is 20–50 folds more potent. Nilotinib was another huge success. It was able to induce complete hematological response in 92% of the patients who were resistant/intolerant to imatinib [111]. Similarly, it was also found to be superior as first-line treatment than imatinib for newly diagnosed Ph + CML [112]. Both Dasatinib and Nilotinib are found to give similar results in large community settings as well. When compared to first-generation TKI imatinib, dasatinib and nilotinib performed significantly better as first-line treatment to newly diagnosed CML patients. They achieve higher Complete Cytogenic Response (CCyR) or Major Molecular Response (MMR) at 6, 12, and 18 months, respectively. By 12 months, 61% patients achieved CCyR or MMR compared to only 38% treated with imatinib. Time to MMR is also significantly

Bosutinib (Bosulif, SKI606) was initially approved in CML-AP/BC, and is later expanded to CML-CP. Trials prove improved rates of MMR at 12 months when compared to imatinib (47.2 vs. 36.9%) [114]. Soon it was also used as first-line therapy against CML. Radotinib (Supect, IY5511) also showed significant superiority over imatinib. With minimum 12 months follow-up, radotinib demonstrated significantly higher and faster rates of CCyR and MMR than imatinib in patients with newly diagnosed

The second-generation BCR-ABL TKIs seem to have significantly higher efficacy than imatinib. Yet, their side effects are also more severe than that of imatinib. This is likely due to the increased potency as well as multi-targeting of the drugs. For example, when comparing bosutinib to imatinib, patients taking bosutinib have higher rates of increased liver enzyme values (24 vs. 4%), thrombocytopenia (13.8 vs. 5.7%), neutropenia (6.7 vs. 12.1%), and diarrhea (7.8 vs. <1%). 77.9% patients experienced severe Grade 3/4 adverse events and 24% patients had to discontinue bosutinib therapy due to emergence of adverse events in a study [116]. Radotinib's side effects are also more severe than that of imatinib. Grade 3/4 ALT/AST elevations caused 68% dosage reduc-

Second-generation EGFR TKIs are irreversible inhibitors and are designed to target other ErbB family members, including HER2, to have more potent inhibition.

tion/interruption in radotinib patients, but only 19% in imatinib patients.

**98**

#### **2.3 Clinical efficacy/effectiveness of third-generation TKIs**

#### *2.3.1 Ponatinib (BCR-ABL TKIs)*

Ponatinib (Iclusig, IY5511) is a multitargeted TKI including BCR-ABL. It was specifically designed for T315I mutation-caused imatinib resistance. Studies have proven its high clinical efficacy of inducing cytogenic response in 66% CML-CP patients, which include all of the T315I mutation positive patients. Yet, in generalized CML-CP patients, ponatinib did not show significantly superior efficacy than the previous second- and first-generation TKIs [128]. Thus, it is suggested for first-line use only in the setting of detected T315I mutation, otherwise, merely as a second-line treatment following first- and second-generation TKIs.

#### *2.3.1.1 Tolerability of side effects*

Treatment-related side effects are moderately significant with ponatinib. Common adverse events include rash (47%), abdominal pain (46%), thrombocytopenia (46%), headache (43%), dry skin (42%), and constipation (41%). It is however associated with a severe adverse event, which is arterial occlusive events (AOE), which occurred in a cumulative of 31% patients.

#### *2.3.2 Osimertinib (EGFR)*

Due to the limited efficacy in tackling T790M resistance of EGFR of the secondgeneration TKIs, the third generation of EGFR-TKIs has been discovered. Third generation works significantly better against the T790M-mutated EGFR while sparing the wild-type EGFRs, making them very mutant selective. Various thirdgeneration EGFR-TKIs are currently under clinical trials, including osimertinib, PF06747775, YH5448, avitinib, rociletinib, etc. Of them all, osimertinib is the only currently approved drug.

Osimertinib (Tagrisso, AZD9291) is a very promising third-generation EGFR-TKI. It is able to tackle gefitinib/erlotinib acquired resistance through T790M, exon 19 and 21, which accounts for a large portion of acquired resistant cases. In a FLAURA study, Osimertinib was compared to first-line EGFR-TKIs (erlotinib and gefitinib) as first line therapy [129]. It showed significantly higher efficacy against EGFR-mutated patients, with PFS 18.9 vs. 10.2 months. An extra feature of osimertinib is its ability to penetrate the blood-brain barrier and tackle patients with brain metastasis as well. CNS progression was lower in patients treated with osimertinib (6 vs. 15%). There is not yet data available on comparing overall survival between the two, yet osimertinib showed a trend of superiority. At 18 months of the FLAURA study, 83% of the patients in the osimertinib group were still alive vs. 71% in the first-generation EGFR-TKI group. Most third-generation EGFR-TKIs combat the T790M EGFR resistance mechanism selectively. Yet, the other 50% resistant mechanisms remain a challenge.

#### *2.3.2.1 Tolerability of side effects*

Side effects of third-generation EGFR-TKIs are rather mild and tolerable. Side effects of Osimertinib commonly include rash, nausea, and diarrhea. Grade 3 or 4 adverse events occurred in 24% of the patients, but only 2% of the patients required a dosage reduction, and only 4% discontinuation. However, there are also studies which disagree. In the FLAURA study, rate of permanent discontinuation due to adverse events of osimertinib was 13%. Yet it is still lower than that of those receiving first-generation EGFR-TKIs, which was 18% [129].

**101**

*Cancer Management by Tyrosine Kinase Inhibitors: Efficacy, Limitation, and Future Strategies*

Viewed as a whole, TKIs of the later generations tend to outperform the first generation in terms of efficacy. This is mainly because the newer generations tend to target multiple pathways and also provide a more potent irreversible inhibition. This allows them to be effective in both first-line setting, as well as combatting heterogeneous resistant mechanisms arisen. Yet, their downside is the occurrence of more severe side effects. The third-generation TKIs thus aim at targeting multiple pathways while sparing physiological functions, e.g., third-generation EGFR-TKIs. VEGFR-TKIs are the exceptions. Their first-generation TKIs are multitargeted, and their newer generation TKIs are more specific, and thus offer a higher tolerability. Studies on newer generations of TKIs delineate promising results on both their efficacy as a potential first-line treatment and as a second-line treatment after acquired

Many TKIs seem to show merely improvement in progression-free survival, but not in overall survival rate. These include gefitinib in NSCLC [130], sunitinib, nilotinib and regorafenib in GIST [131], lenvatinib in differentiated thyroid cancer [132], and many other TKIs, regardless of whether they are of newer generations or not. Erlotinib even showed poorer overall survival rate than chemotherapy (24.68 vs. 26.16 months), despite a significantly higher progression-free survival [62].

Response rate of TKIs are low in unselected patients. Various studies have shown that, in the absence of targeted mutation, targeted therapy performed worse than traditional chemotherapy. Presence of targeted mutation is a huge positive predicting factor for good tumor response [133, 134]. Response rate in unselected population is however high in a few cases, for example, in unselected CML patients. This is likely because the vast majority of them carry the same single mutation of BCR-ABL. It is also high in RCC for first-generation TKIs, since the first-generation VEGFR-TKIs are

The development of resistance has always been and will probably always be the greatest problem limiting the use of TKIs. The rate of developing acquired resistance (AR) is extremely high, and appears even to be inevitable in certain diseases. In EGFR-TKI therapy, a study showed the median time for patients developing AR is 8–10 months, and all responding patients developed AR eventually, with the inevitable consequence of disease progression [135, 136]. The case with imatinib is slightly better; around 7–15% is found to have secondary resistance, i.e., disease progression following initial achievement of cytogenic response [137, 138]. And this is the reason why the PFS, despite longer than chemotherapy, is still not very long, with most ranging from a few months to at most a few years, despite their high disease response rate and promptness in controlling the disease. Acquiring resistance and disease progression seem almost inevitable in many cancer lines using TKIs. This phenomenon

relatively nonspecific, and are able to target multiple mutation mechanisms.

occurs indiscriminately in all generations of TKIs and is a huge challenge.

*DOI: http://dx.doi.org/10.5772/intechopen.82513*

resistance of the initial therapy.

*2.4.1.1 High efficacy but low effectiveness*

The potential reasons shall be further discussed.

**3. Evaluation of limitations of TKIs**

**3.1 Development of resistance**

*2.4.1 Newer generations perform better than first generation*

**2.4 Comparison**

#### **2.4 Comparison**

*Tyrosine Kinases as Druggable Targets in Cancer*

*2.3.1 Ponatinib (BCR-ABL TKIs)*

*2.3.1.1 Tolerability of side effects*

*2.3.2 Osimertinib (EGFR)*

currently approved drug.

*2.3.2.1 Tolerability of side effects*

ing first-generation EGFR-TKIs, which was 18% [129].

**2.3 Clinical efficacy/effectiveness of third-generation TKIs**

second-line treatment following first- and second-generation TKIs.

(AOE), which occurred in a cumulative of 31% patients.

Ponatinib (Iclusig, IY5511) is a multitargeted TKI including BCR-ABL. It was specifically designed for T315I mutation-caused imatinib resistance. Studies have proven its high clinical efficacy of inducing cytogenic response in 66% CML-CP patients, which include all of the T315I mutation positive patients. Yet, in generalized CML-CP patients, ponatinib did not show significantly superior efficacy than the previous second- and first-generation TKIs [128]. Thus, it is suggested for first-line use only in the setting of detected T315I mutation, otherwise, merely as a

Treatment-related side effects are moderately significant with ponatinib. Common adverse events include rash (47%), abdominal pain (46%), thrombocytopenia (46%), headache (43%), dry skin (42%), and constipation (41%). It is however associated with a severe adverse event, which is arterial occlusive events

Due to the limited efficacy in tackling T790M resistance of EGFR of the secondgeneration TKIs, the third generation of EGFR-TKIs has been discovered. Third generation works significantly better against the T790M-mutated EGFR while sparing the wild-type EGFRs, making them very mutant selective. Various thirdgeneration EGFR-TKIs are currently under clinical trials, including osimertinib, PF06747775, YH5448, avitinib, rociletinib, etc. Of them all, osimertinib is the only

Osimertinib (Tagrisso, AZD9291) is a very promising third-generation EGFR-TKI. It is able to tackle gefitinib/erlotinib acquired resistance through T790M, exon 19 and 21, which accounts for a large portion of acquired resistant cases. In a FLAURA study, Osimertinib was compared to first-line EGFR-TKIs (erlotinib and gefitinib) as first line therapy [129]. It showed significantly higher efficacy against EGFR-mutated patients, with PFS 18.9 vs. 10.2 months. An extra feature of osimertinib is its ability to penetrate the blood-brain barrier and tackle patients with brain metastasis as well. CNS progression was lower in patients treated with osimertinib (6 vs. 15%). There is not yet data available on comparing overall survival between the two, yet osimertinib showed a trend of superiority. At 18 months of the FLAURA study, 83% of the patients in the osimertinib group were still alive vs. 71% in the first-generation EGFR-TKI group. Most third-generation EGFR-TKIs combat the T790M EGFR resistance mechanism selectively. Yet, the other 50% resistant mechanisms remain a challenge.

Side effects of third-generation EGFR-TKIs are rather mild and tolerable. Side effects of Osimertinib commonly include rash, nausea, and diarrhea. Grade 3 or 4 adverse events occurred in 24% of the patients, but only 2% of the patients required a dosage reduction, and only 4% discontinuation. However, there are also studies which disagree. In the FLAURA study, rate of permanent discontinuation due to adverse events of osimertinib was 13%. Yet it is still lower than that of those receiv-

**100**

#### *2.4.1 Newer generations perform better than first generation*

Viewed as a whole, TKIs of the later generations tend to outperform the first generation in terms of efficacy. This is mainly because the newer generations tend to target multiple pathways and also provide a more potent irreversible inhibition. This allows them to be effective in both first-line setting, as well as combatting heterogeneous resistant mechanisms arisen. Yet, their downside is the occurrence of more severe side effects. The third-generation TKIs thus aim at targeting multiple pathways while sparing physiological functions, e.g., third-generation EGFR-TKIs. VEGFR-TKIs are the exceptions. Their first-generation TKIs are multitargeted, and their newer generation TKIs are more specific, and thus offer a higher tolerability. Studies on newer generations of TKIs delineate promising results on both their efficacy as a potential first-line treatment and as a second-line treatment after acquired resistance of the initial therapy.

#### *2.4.1.1 High efficacy but low effectiveness*

Many TKIs seem to show merely improvement in progression-free survival, but not in overall survival rate. These include gefitinib in NSCLC [130], sunitinib, nilotinib and regorafenib in GIST [131], lenvatinib in differentiated thyroid cancer [132], and many other TKIs, regardless of whether they are of newer generations or not. Erlotinib even showed poorer overall survival rate than chemotherapy (24.68 vs. 26.16 months), despite a significantly higher progression-free survival [62]. The potential reasons shall be further discussed.

Response rate of TKIs are low in unselected patients. Various studies have shown that, in the absence of targeted mutation, targeted therapy performed worse than traditional chemotherapy. Presence of targeted mutation is a huge positive predicting factor for good tumor response [133, 134]. Response rate in unselected population is however high in a few cases, for example, in unselected CML patients. This is likely because the vast majority of them carry the same single mutation of BCR-ABL. It is also high in RCC for first-generation TKIs, since the first-generation VEGFR-TKIs are relatively nonspecific, and are able to target multiple mutation mechanisms.

#### **3. Evaluation of limitations of TKIs**

#### **3.1 Development of resistance**

The development of resistance has always been and will probably always be the greatest problem limiting the use of TKIs. The rate of developing acquired resistance (AR) is extremely high, and appears even to be inevitable in certain diseases. In EGFR-TKI therapy, a study showed the median time for patients developing AR is 8–10 months, and all responding patients developed AR eventually, with the inevitable consequence of disease progression [135, 136]. The case with imatinib is slightly better; around 7–15% is found to have secondary resistance, i.e., disease progression following initial achievement of cytogenic response [137, 138]. And this is the reason why the PFS, despite longer than chemotherapy, is still not very long, with most ranging from a few months to at most a few years, despite their high disease response rate and promptness in controlling the disease. Acquiring resistance and disease progression seem almost inevitable in many cancer lines using TKIs. This phenomenon occurs indiscriminately in all generations of TKIs and is a huge challenge.

The development of resistance comes in many ways, and many researches have been dedicated to finding out the mechanisms of resistance to TKIs. Studies have shown that cancer cells adapt to chronic therapy by through common mechanisms found include secondary mutations of target, activation of alternative signaling pathway, evading immune system and adaptive or cell fate changes, etc. Point mutation at site coding for TK resulting in decreased affinity for the TKI remains the most prevalent mechanism of acquired resistance [139]. Point mutations (esp. T315I mutation) in CML patients are a major cause in AR toward imatinib. Occurrence of these mutations reduces the life expectancy of chronic phase CML patients from 10 years to just 22 months [140]. Exon 20-T790M mutation is found in approximately half of the patients with progressed disease following initial EGFR-TKI use [141]. Any of the ways allow the tumor cells to regain its ability to grow and divide. The heterogeneity of resistance mechanisms poses huge difficulty for a single TKI to produce high response rate following AR to the initial TKI.

Newer generations of TKIs aimed at resolving acquired resistance toward the older generation TKIs. Yet, there are too many different types of resistance mechanisms that could arise between different patients, as discussed. Taking NSCLC AR to erlotinib and gefitinib as an example, AR mechanism could be T790M missense mutation, other secondary mutations of EGFR, MET amplification, HER2 amplification, small cell histological transformation, etc. And up to 30% of the NSCLC patients with AR to first gen TKIs have unknown resistance mechanism [135]. Its heterogeneity makes the development of new generation TKIs, especially one with high tumor response, very hard.

The management of post-TKI disease progression is a new therapeutic challenge. The ways to overcome include using multitargeted approach, in which the TKI is effective against a broad spectrum of resistance mechanisms, or perform genetic tests and learning the specific resistance mechanism of the individual patient and selecting the next TKI. Details are discussed in the next session.

#### **3.2 Complexity and redundancy in tumor pathways and between tumor subclones**

Multiple regulatory factors and multiple signaling pathways exist within a tumor, and they each share a role in supporting tumor growth [142]. Many elements of these pathways are redundant, and contribute toward the same function. With all these redundancy, inhibiting one factor or one pathway will often not be sufficient in inhibiting tumor growth [143]. This is part of the reason for the robustness of cancer cells, allowing them to survive through a diversity of treatments. Take angiogenesis as an example. Although VEGF is the most potent stimulatory regulator of angiogenesis, and human cancers often have an overexpression of VEGF, there are also many other stimulatory and inhibitory factors involved, which some are produced by tumor cells and some by the host cells. Therefore, simply administrating a singletarget VEGFR-TKIs may not result in significant antiangiogenic effect. Besides, some of the factors, including VEGF, can exist in multiple isoforms, making it even harder to inhibit the angiogenic process [1, 144]. Moreover, many tumors have more than one mutated pathways, for instance, both VEGFR and PDGFR mutation [145]. It is only through multitargeting and combination therapy, or targeting more upstream pathways, could a more significant response be brought about [143]. Simply inhibiting one target is in many cases not effective enough to hinder cell growth.

With technology of next-generation sequencing of patient biopsies, it has been revealed that tumors contain vastly heterogeneous genetic alterations in multiple subclones. This is also called intratumor heterogeneity. This also includes geographical heterogeneity, in which the genetic makeup of metastatic tumors differs

**103**

*Cancer Management by Tyrosine Kinase Inhibitors: Efficacy, Limitation, and Future Strategies*

from each other as well. As the neoplastic cells divide and undergo DNA replication, the clones are highly prone to genetic mutations, and the mutated cells continue to grow and give rise to their colony of cells. Thus within the same tumor, there could be multiple subclones each with their own variant of DNA makeup. This plays a huge role in the development of resistance toward TKIs. Heterogenic tumor subclones may exhibit different sensitivity toward the TKIs. Some tumors may have primary resistance, and with the TKI acting as the selecting pressure, the resistant subclones are selected and are able to continue growing. This accounts for the high rate of resistance toward TKIs. And research has also proven that high intratumoral heterogeneity predicts poorer prognosis and poorer response to treatment [146].

Low effectiveness of TKIs in studies may be due to poor patient selection. By knowing the mechanism of action of the TKIs, we know well that they could only work in a selected population of tumor cells, which contains the pharmacological target. They do not always work well in unselected populations. There are a certain portion of cancer cell lines which are innately resistant to the TKI therapy administered. In unselected NSCLC patients, only 15 in 58 in Japan and 1 in 61 in USA responded to the gefitinib treatment [147]. This is due to the heterogeneity of mutations of the same cancer in different individuals. This occurs not only with initial therapy option, but also newer generations of TKIs as well as non–first-line TKIs. Response rates of many newly developed EGFR-TKIs, targeting at patients with AR to first-line TKIs, were lower than 10%. These include neratinib, whose response rate is 3% [148] and IPI-504, whose response rate is 4% [148]. Therefore, poor patient selection will greatly limit the effectiveness of TKIs. Mechanisms for patient selection must be developed in order to increase TKI effectiveness in community settings.

Many studies found that combining TKI with traditional chemotherapy showed no significant benefit, but rather an additive effect of toxicity, resulting in disappointment. Concurrent administration may not be effective due to TKI induced G1 phase cell cycle arrest [149]. Although combination approach is believed to provide better outcome in many cases, practitioners must pay attention to antagonistic drug interactions in order to prevent this from limiting the effectiveness of TKI. Alternating administration schedule is proposed for many combination

Although TKIs are deemed to be relatively well tolerated, especially when compared to systemic cytotoxic chemotherapy, there are still many cases of side effects limiting the use of this drug. With variations from drug to drug, up to 50% report cases of skin toxicity and folliculitis with TKI use. EGFR TKIs display a broad spectrum of skin and hair adverse effects, including folliculitis, facial hair growth, facial erythema, paronychia, and varying forms of frontal alopecia, whereas VEGFR TKIs are more commonly associated with subungual splinter hemorrhages. Imatinib frequently causes periorbital edema. TKIs produce various hematological side effects (anemia, thrombocytopenia, neutropenia) and extra-hematological side effects, most commonly being edema, nausea, hypothyroidism, vomiting, and diarrhea. Regarding long-term effects, cardiac toxicity with congestive heart failure is discussed in patients receiving imatinib and sunitinib [150]. Adverse events have been reported in the use

*DOI: http://dx.doi.org/10.5772/intechopen.82513*

**3.3 Poor patient selection**

**3.4 Antagonistic drug interaction**

therapies in order to avoid this problem.

**3.5 Side effects**

*Cancer Management by Tyrosine Kinase Inhibitors: Efficacy, Limitation, and Future Strategies DOI: http://dx.doi.org/10.5772/intechopen.82513*

from each other as well. As the neoplastic cells divide and undergo DNA replication, the clones are highly prone to genetic mutations, and the mutated cells continue to grow and give rise to their colony of cells. Thus within the same tumor, there could be multiple subclones each with their own variant of DNA makeup. This plays a huge role in the development of resistance toward TKIs. Heterogenic tumor subclones may exhibit different sensitivity toward the TKIs. Some tumors may have primary resistance, and with the TKI acting as the selecting pressure, the resistant subclones are selected and are able to continue growing. This accounts for the high rate of resistance toward TKIs. And research has also proven that high intratumoral heterogeneity predicts poorer prognosis and poorer response to treatment [146].

#### **3.3 Poor patient selection**

*Tyrosine Kinases as Druggable Targets in Cancer*

high tumor response, very hard.

**subclones**

produce high response rate following AR to the initial TKI.

selecting the next TKI. Details are discussed in the next session.

**3.2 Complexity and redundancy in tumor pathways and between tumor** 

and they each share a role in supporting tumor growth [142]. Many elements of these pathways are redundant, and contribute toward the same function. With all these redundancy, inhibiting one factor or one pathway will often not be sufficient in inhibiting tumor growth [143]. This is part of the reason for the robustness of cancer cells, allowing them to survive through a diversity of treatments. Take angiogenesis as an example. Although VEGF is the most potent stimulatory regulator of angiogenesis, and human cancers often have an overexpression of VEGF, there are also many other stimulatory and inhibitory factors involved, which some are produced by tumor cells and some by the host cells. Therefore, simply administrating a singletarget VEGFR-TKIs may not result in significant antiangiogenic effect. Besides, some of the factors, including VEGF, can exist in multiple isoforms, making it even harder to inhibit the angiogenic process [1, 144]. Moreover, many tumors have more than one mutated pathways, for instance, both VEGFR and PDGFR mutation [145]. It is only through multitargeting and combination therapy, or targeting more upstream pathways, could a more significant response be brought about [143]. Simply inhibit-

ing one target is in many cases not effective enough to hinder cell growth.

With technology of next-generation sequencing of patient biopsies, it has been revealed that tumors contain vastly heterogeneous genetic alterations in multiple subclones. This is also called intratumor heterogeneity. This also includes geographical heterogeneity, in which the genetic makeup of metastatic tumors differs

The development of resistance comes in many ways, and many researches have been dedicated to finding out the mechanisms of resistance to TKIs. Studies have shown that cancer cells adapt to chronic therapy by through common mechanisms found include secondary mutations of target, activation of alternative signaling pathway, evading immune system and adaptive or cell fate changes, etc. Point mutation at site coding for TK resulting in decreased affinity for the TKI remains the most prevalent mechanism of acquired resistance [139]. Point mutations (esp. T315I mutation) in CML patients are a major cause in AR toward imatinib. Occurrence of these mutations reduces the life expectancy of chronic phase CML patients from 10 years to just 22 months [140]. Exon 20-T790M mutation is found in approximately half of the patients with progressed disease following initial EGFR-TKI use [141]. Any of the ways allow the tumor cells to regain its ability to grow and divide. The heterogeneity of resistance mechanisms poses huge difficulty for a single TKI to

Newer generations of TKIs aimed at resolving acquired resistance toward the older generation TKIs. Yet, there are too many different types of resistance mechanisms that could arise between different patients, as discussed. Taking NSCLC AR to erlotinib and gefitinib as an example, AR mechanism could be T790M missense mutation, other secondary mutations of EGFR, MET amplification, HER2 amplification, small cell histological transformation, etc. And up to 30% of the NSCLC patients with AR to first gen TKIs have unknown resistance mechanism [135]. Its heterogeneity makes the development of new generation TKIs, especially one with

The management of post-TKI disease progression is a new therapeutic challenge. The ways to overcome include using multitargeted approach, in which the TKI is effective against a broad spectrum of resistance mechanisms, or perform genetic tests and learning the specific resistance mechanism of the individual patient and

Multiple regulatory factors and multiple signaling pathways exist within a tumor,

**102**

Low effectiveness of TKIs in studies may be due to poor patient selection. By knowing the mechanism of action of the TKIs, we know well that they could only work in a selected population of tumor cells, which contains the pharmacological target. They do not always work well in unselected populations. There are a certain portion of cancer cell lines which are innately resistant to the TKI therapy administered. In unselected NSCLC patients, only 15 in 58 in Japan and 1 in 61 in USA responded to the gefitinib treatment [147]. This is due to the heterogeneity of mutations of the same cancer in different individuals. This occurs not only with initial therapy option, but also newer generations of TKIs as well as non–first-line TKIs. Response rates of many newly developed EGFR-TKIs, targeting at patients with AR to first-line TKIs, were lower than 10%. These include neratinib, whose response rate is 3% [148] and IPI-504, whose response rate is 4% [148]. Therefore, poor patient selection will greatly limit the effectiveness of TKIs. Mechanisms for patient selection must be developed in order to increase TKI effectiveness in community settings.

#### **3.4 Antagonistic drug interaction**

Many studies found that combining TKI with traditional chemotherapy showed no significant benefit, but rather an additive effect of toxicity, resulting in disappointment. Concurrent administration may not be effective due to TKI induced G1 phase cell cycle arrest [149]. Although combination approach is believed to provide better outcome in many cases, practitioners must pay attention to antagonistic drug interactions in order to prevent this from limiting the effectiveness of TKI. Alternating administration schedule is proposed for many combination therapies in order to avoid this problem.

#### **3.5 Side effects**

Although TKIs are deemed to be relatively well tolerated, especially when compared to systemic cytotoxic chemotherapy, there are still many cases of side effects limiting the use of this drug. With variations from drug to drug, up to 50% report cases of skin toxicity and folliculitis with TKI use. EGFR TKIs display a broad spectrum of skin and hair adverse effects, including folliculitis, facial hair growth, facial erythema, paronychia, and varying forms of frontal alopecia, whereas VEGFR TKIs are more commonly associated with subungual splinter hemorrhages. Imatinib frequently causes periorbital edema. TKIs produce various hematological side effects (anemia, thrombocytopenia, neutropenia) and extra-hematological side effects, most commonly being edema, nausea, hypothyroidism, vomiting, and diarrhea. Regarding long-term effects, cardiac toxicity with congestive heart failure is discussed in patients receiving imatinib and sunitinib [150]. Adverse events have been reported in the use

of sorafenib against HCC, including Hand Foot Skin Reactions (HFSR), hyperbilirubinemia associated with heightened ALT. Adverse effects occurred in up to 40% of differentiated thyroid cancer patients, which are mainly hypertension, diarrhea, asthenia, or fatigue, nausea, decreased weight and appetite. This had resulted in dosage reduction despite good tumor response [151]. About 14% of the patients had to discontinue therapy due to intolerance of adverse events. Severity of side effects was found correlated with specificity of the TKIs. The newer generations are usually multitargeted, and thus yield more severe side effects. Luckily, third generations are more mutant selective, and thus showed improvement in this aspect.

#### **3.6 Lack of follow-up and nonadherence**

As TKI is a drug class that has to be administrated over a long period of time, the lack of follow-up during the course of treatment is a problem that could limit the effectiveness. In a study reporting effectiveness of TKIs in CML patients in a community setting, it is found that cytogenetic and molecular response monitoring assessments were conducted less frequently than recommended [113]. Poor monitoring may result in delay in adjustments in treatment plan. On the other hand, TKIs are mostly administrated orally, which may pose a challenge in patient adherence. Poor patient compliance plays a role in increasing rates of acquired resistance to TKIs. It is found that, as the treatment progresses, those with higher adherence did achieve better results in achieving CCyR and MMR [113]. While adherence to TKIs is critical in achieving durable responses, it is surprising that merely 56% patients in a study of 229 CML patients adhere to their dosage (which is defined as ³90% adherence) [113].

#### **3.7 Financial burden on patients**

There have been numerous studies conducted on cost-effectiveness of TKIs. But most work on merely the comparison between different TKIs or compare TKIs with other treatment. As TKIs are in many occasions not covered by the public health system, they are usually self-funded, unless the patient is covered by insurance, has successfully applied for external funding or is enrolled in a clinical trial. The average per person total cost of treatment with branded imatinib is (79,000 USD/ year) and even higher for dasatinib and nilotinib (87,000–92,000 USD/year) [152]. The humongous financial burden complicates the patients' decision in drug choice. It may also affect their choice of continuation of treatment. Studies have shown that high costs of TKIs even lead to a delay in treatment for many patients with leukemia [153]. Some patients may resort to generic TKIs, which quality may not be always consistently good. For example, a study showed that generic Imatinib show suboptimal efficacy when compared to branded imatinib as first-line therapy in CML [154].

#### **4. Strategies in overcoming the limitations of TKIs**

Plenty studies have been coming up with all sorts of strategies in overcoming the limitations of TKIs. The big direction is to develop new inhibitors, use a combination approach, and improve patient selection.

#### **4.1 Development of new inhibitors: specific approach and multitargeted approach**

Following post-TKI disease progression, continuing the use of the initial TKI therapy does not improve PFS [155]. There is thus a desperate need for new

**105**

**4.2 Combination therapy**

*Cancer Management by Tyrosine Kinase Inhibitors: Efficacy, Limitation, and Future Strategies*

treatment options, or new TKIs. Various studies are working on drugs available for use after acquired resistance. A large number of new TKIs are working their way down the pipeline, in preclinical studies and clinical studies, a lot of which are very promising. The new inhibitors are either very specific toward a certain type of acquired mutation, or multitargeted to inhibit a broader spectrum of pathways, in

With next-generation sequencing, we are able to identify the specific mutations and design molecules that specifically target them. The mutation mechanisms are however vast in diversity. Taking acquired resistance to imatinib in GIST as an example, in a study, among the 15 patients who acquired resistance to imatinib, 7 were found with secondary mutation at the KIT target, 6 of which occurred at the exon 17 (three were N822K, two were D820Y and one was Y823D) [156]. Luckily we were also able to identify some more common ones, e.g., T790M mutation in EGFR-TKI AR. One of the strategies is thus to develop drugs that target these mutations specifically. To facilitate this, however, there should be more research on mechanisms of acquired resistance against TKIs in different cancers. However, this

Another approach of new inhibitors, also a more practical approach, would be the multi-targeted approach, as well as the inhibiting of upstream pathways. As stated previously, the vast heterogeneity within tumor subclones and the redundancy of cancer cell signaling pathways poses a huge challenge for targeted therapies. One of the strategies regarding is to have multiple targets. Network model suggests that partial inhibition of multiple targets may exhibit better effect than complete inhibition of a single target [157]. This has been the trend in many newly developed drugs. Many studies agree that multi-targeted TKIs should perform bet-

ter than single-targeted ones in terms of efficacy and tumor response rate

allow us to combat acquired resistance more effortlessly.

[145, 158–160]. When targeting a single molecule, the cancer cells can easily adapt and bend around the hindered pathway by activation of alternative pathways. By interacting with multiple targets simultaneously, it leaves less chance for cancer cells to do so [159, 161]. Multitargeted approach also eliminates the malignant cells faster as they inhibit multiple pathways, inhibiting the cancer cells at multiple levels.

Identifying convergent resistance mechanisms or targeting upstream pathways enables us to achieve something similar. Despite the large number of resistance mechanisms, a lot of them converge on reactivation of the driving pathway. For example, in BRAF-mutant melanomas, 89% of resistance mechanisms lie within the MAPK pathway [162]. Identifying these convergent resistance mechanisms could

However, the multi-targeted approach is also with more severe adverse effects than the single-targeted [158]. It is thus important to be able to identify the suitable set of targets, which allows us to be specific enough to act selectively at the tumor cells only, not the normal body cells, yet not specific enough to prevent cancer cells from acquiring resistance too easily. Luckily, we are equipped with newer tools, including the network pharmacology approach, to aid us in the design of these new drugs [157].

Combination approach with a similar mindset when that of developing multitargeted TKIs, it is believed that a combination of therapies would leave less chance for selection of resistant subclones, which allows the tumor to acquire resistance. TKIs treatment could potentially combine with many different treatments. Many studies have already been conducted on the combination of TKIs with conventional therapies, including chemotherapy, radiation therapy, interferon therapy, etc. A study showed that combination of standard-dose imatinib and IF-therapy

*DOI: http://dx.doi.org/10.5772/intechopen.82513*

order to overcome resistance.

would also be a very costly method.

#### *Cancer Management by Tyrosine Kinase Inhibitors: Efficacy, Limitation, and Future Strategies DOI: http://dx.doi.org/10.5772/intechopen.82513*

treatment options, or new TKIs. Various studies are working on drugs available for use after acquired resistance. A large number of new TKIs are working their way down the pipeline, in preclinical studies and clinical studies, a lot of which are very promising. The new inhibitors are either very specific toward a certain type of acquired mutation, or multitargeted to inhibit a broader spectrum of pathways, in order to overcome resistance.

With next-generation sequencing, we are able to identify the specific mutations and design molecules that specifically target them. The mutation mechanisms are however vast in diversity. Taking acquired resistance to imatinib in GIST as an example, in a study, among the 15 patients who acquired resistance to imatinib, 7 were found with secondary mutation at the KIT target, 6 of which occurred at the exon 17 (three were N822K, two were D820Y and one was Y823D) [156]. Luckily we were also able to identify some more common ones, e.g., T790M mutation in EGFR-TKI AR. One of the strategies is thus to develop drugs that target these mutations specifically. To facilitate this, however, there should be more research on mechanisms of acquired resistance against TKIs in different cancers. However, this would also be a very costly method.

Another approach of new inhibitors, also a more practical approach, would be the multi-targeted approach, as well as the inhibiting of upstream pathways. As stated previously, the vast heterogeneity within tumor subclones and the redundancy of cancer cell signaling pathways poses a huge challenge for targeted therapies. One of the strategies regarding is to have multiple targets. Network model suggests that partial inhibition of multiple targets may exhibit better effect than complete inhibition of a single target [157]. This has been the trend in many newly developed drugs. Many studies agree that multi-targeted TKIs should perform better than single-targeted ones in terms of efficacy and tumor response rate [145, 158–160]. When targeting a single molecule, the cancer cells can easily adapt and bend around the hindered pathway by activation of alternative pathways. By interacting with multiple targets simultaneously, it leaves less chance for cancer cells to do so [159, 161]. Multitargeted approach also eliminates the malignant cells faster as they inhibit multiple pathways, inhibiting the cancer cells at multiple levels.

Identifying convergent resistance mechanisms or targeting upstream pathways enables us to achieve something similar. Despite the large number of resistance mechanisms, a lot of them converge on reactivation of the driving pathway. For example, in BRAF-mutant melanomas, 89% of resistance mechanisms lie within the MAPK pathway [162]. Identifying these convergent resistance mechanisms could allow us to combat acquired resistance more effortlessly.

However, the multi-targeted approach is also with more severe adverse effects than the single-targeted [158]. It is thus important to be able to identify the suitable set of targets, which allows us to be specific enough to act selectively at the tumor cells only, not the normal body cells, yet not specific enough to prevent cancer cells from acquiring resistance too easily. Luckily, we are equipped with newer tools, including the network pharmacology approach, to aid us in the design of these new drugs [157].

#### **4.2 Combination therapy**

Combination approach with a similar mindset when that of developing multitargeted TKIs, it is believed that a combination of therapies would leave less chance for selection of resistant subclones, which allows the tumor to acquire resistance.

TKIs treatment could potentially combine with many different treatments. Many studies have already been conducted on the combination of TKIs with conventional therapies, including chemotherapy, radiation therapy, interferon therapy, etc. A study showed that combination of standard-dose imatinib and IF-therapy

*Tyrosine Kinases as Druggable Targets in Cancer*

**3.6 Lack of follow-up and nonadherence**

**3.7 Financial burden on patients**

**4. Strategies in overcoming the limitations of TKIs**

tion approach, and improve patient selection.

of sorafenib against HCC, including Hand Foot Skin Reactions (HFSR), hyperbilirubinemia associated with heightened ALT. Adverse effects occurred in up to 40% of differentiated thyroid cancer patients, which are mainly hypertension, diarrhea, asthenia, or fatigue, nausea, decreased weight and appetite. This had resulted in dosage reduction despite good tumor response [151]. About 14% of the patients had to discontinue therapy due to intolerance of adverse events. Severity of side effects was found correlated with specificity of the TKIs. The newer generations are usually multitargeted, and thus yield more severe side effects. Luckily, third generations are

As TKI is a drug class that has to be administrated over a long period of time, the lack of follow-up during the course of treatment is a problem that could limit the effectiveness. In a study reporting effectiveness of TKIs in CML patients in a community setting, it is found that cytogenetic and molecular response monitoring assessments were conducted less frequently than recommended [113]. Poor monitoring may result in delay in adjustments in treatment plan. On the other hand, TKIs are mostly administrated orally, which may pose a challenge in patient adherence. Poor patient compliance plays a role in increasing rates of acquired resistance to TKIs. It is found that, as the treatment progresses, those with higher adherence did achieve better results in achieving CCyR and MMR [113]. While adherence to TKIs is critical in achieving durable responses, it is surprising that merely 56% patients in a study of 229 CML patients adhere to their dosage (which is defined as ³90% adherence) [113].

There have been numerous studies conducted on cost-effectiveness of TKIs. But most work on merely the comparison between different TKIs or compare TKIs with other treatment. As TKIs are in many occasions not covered by the public health system, they are usually self-funded, unless the patient is covered by insurance, has successfully applied for external funding or is enrolled in a clinical trial. The average per person total cost of treatment with branded imatinib is (79,000 USD/ year) and even higher for dasatinib and nilotinib (87,000–92,000 USD/year) [152]. The humongous financial burden complicates the patients' decision in drug choice. It may also affect their choice of continuation of treatment. Studies have shown that high costs of TKIs even lead to a delay in treatment for many patients with leukemia [153]. Some patients may resort to generic TKIs, which quality may not be always consistently good. For example, a study showed that generic Imatinib show suboptimal efficacy when compared to branded imatinib as first-line therapy in CML [154].

Plenty studies have been coming up with all sorts of strategies in overcoming the limitations of TKIs. The big direction is to develop new inhibitors, use a combina-

**4.1 Development of new inhibitors: specific approach and multitargeted** 

Following post-TKI disease progression, continuing the use of the initial TKI therapy does not improve PFS [155]. There is thus a desperate need for new

more mutant selective, and thus showed improvement in this aspect.

**104**

**approach**

yielded better results than standard-dose or high-dose imatinib alone, as well as standard-dose imatinib combined with chemotherapy [21, 163]. Icotinib, an EGFR-TKI is proved to improve radiosensitivity in lung cancer in vitro and in vivo, thus possibly allowing better radiotherapy effects [164]. They are extensively studied and are in many cases already put to clinical practice.

A TKI could also be combined with another TKI. For example, dual EGFR blockade by first and third-generation EGFR TKI combinations [165]. Or dual ALK and EGFR target inhibition in ALK translocated NSCLC with additional EGFR mutation [166]. Other ongoing clinical trials study the potential benefits of combining anti-angiogenic TKIs (e.g., apatinib, endostatin, and anlotinib) with EGFR-TKIs [167].

There are also studies proposing TKI combination with other target inhibitors including monoclonal antibodies. Researches are exploring possibilities of combinations of brigatinib and anti-EGFR antibodies, third-generation TKIs with MEK inhibitors, and osimertinib with oxidative phosphorylation inhibitors etc. [165]. For acute lymphocytic lymphoma, a WEE1 inhibitor AZD-1775 is proven to significantly enhance the efficacy of several tyrosine kinase inhibitors, such as imatinib, bosutinib, and ponatinib [168], or similarly, vitamin K1 with sorafenib in treating HCC [151] and antiestrogen fulvestrant with vandetanib in NSCLC.

Combination approach is promising, yet limited by potential toxicity. Combination of drug effects is true for both positive and side effects. Many studies echoed that concurrent chemotherapy and TKI therapy yielded no added benefits. Therefore, it is important to understand the mechanism of action of the two therapies and understand their interaction, thus design the best administration schedule. Taking TKIs and chemotherapy in an intercalated manner may reduce inhibitory drug interaction. A study compared synchronized administration and intercalated administration of the two therapies [101], and found that intercalated administration schedule improved PFS and OS [169]. More and more studies are thus conducted on the administration schedule and yielded similar results [63].

#### **4.3 Wisdom from traditional Chinese medicine (TCM)**

TCM has long been used to treat different cancers and are often shown with clinical efficacy. TCM herbs are able to stabilize tumor growth, control patient symptoms and alleviate side effects, and ultimately improve quality of life of patients [161]. Many researches are thus dedicated to discovering novel drugs by uncovering therapeutic potentials of various natural compounds.

Accumulating studies have been discovering tyrosine kinase inhibiting effects from natural compounds. Many TCM herbs contain natural compounds that are capable of interacting with multiple cellular targets [161]. Various molecules from traditional Chinese medicine are being discovered with tyrosine kinase inhibiting effects and these include 2-O-caffeoyl tartaric acid, emetine, rosmaricine, and 2-O-feruloyl tartaric acid, which are potential EGFR inhibitors [170]. Another meta-analysis identified another 24 kinase inhibitors from TCM [171]. Network pharmacology enables us to discover more of such molecules and their targets [161]. Using natural compounds as drugs is relatively safe and exhibit less side effects [161].

On the other hand, complementary use of TCM has been actively discussed in recent years. Many recent studies have been conducted. They appear to be able to increase efficacy as well as reduce toxicity when combined with TKI therapy [161, 172]. Some studies showed that TCM work synergistically with EGFR-TKI

**107**

*Cancer Management by Tyrosine Kinase Inhibitors: Efficacy, Limitation, and Future Strategies*

and has additional effect of alleviating TKI induced toxicity [173]. They are able to significantly raise overall response rates, disease control rate, 1-year survival rate, 2-year survival rate, and improvement/stable Karnofsky Performance scores of tumors. Severe toxicity for rash was decreased, so were nausea, vomiting, and diarrhea [174, 175]. The strategy of minimizing or alleviating side effects of TKIs may be potential. This could help increase tolerability of patients and also reduce drugrelated adverse events and subsequent possible drug reduction and discontinuation,

The drug effects of TKIs can be drastically different in two patients. It can work miracles in one, but have no effect at all in another. The genetic makeup of a patient's tumor is a huge predicting value of the efficacy of the TKI. Various studies have shown the correspondence between genetic profiling and therapy response [176, 177]. Thus, it is vital to perform procedures to select the population of patients responsive toward the TKI. In the new era of personalized medicine, the most effective way of using TKIs to treat cancer is to consider each patient/tumor individually and to determine the strategy that specifically targets the consequences of altered genetics of the tumor. Not simply which TKI to use, but also which combination of

**4.5 Repeated monitoring, including repeated biopsy/ liquid biopsy**

It was proposed that in order to overcome the limitation of AR in TKIs, repeated tumor biopsies should be done during the course of treatment. This is to give us the ability to spot mutations early and learn its resistance mechanism, thus allowing intervention prior to standard detection of radiographic signs of progression. The specific agent/combination against that particular resistance mechanism can thus be selected. Yet multiple resistance mechanisms within a single patient, especially between multiple lesions in a patient, pose challenges for biopsy. Besides, biopsies are not accessible for all tumors and are also invasive to the patient. Studies have proposed repeated liquid biopsies as a solution [178]. Liquid biopsy checks for tumor DNA circulating in the blood, which is shed into the bloodstream by tumors all around the body, thus allowing us to peer into the tumor genome in distinct subclones in different metastatic lesions within the patient. It is more effective in learning the heterogeneity and multiple resistance mechanisms than performing a single lesion biopsy. It being less invasive (a simple blood draw will suffice), also allows a more frequent sampling.

Patient compliance does make a big difference in treatment outcome. Studies have proven that those with higher adherence did achieve better results in achieving CCyR and MMR [113]. Since many TKIs are orally administered, of long-term usage, and in some cases, self-administered in an out-patient setting, patient compliance could pose a serious challenge, especially with irregular drug schedule, such as one with drug holidays. Patient education is one of the ways we could improve patient compliance. Perhaps systems for patient monitoring could also be developed, including system like DOTs therapy for TB patients, where out-patients are required to come to the clinic and take the medicine in front of the healthcare workers and official record is made. Other suggestions include designing phone

*DOI: http://dx.doi.org/10.5772/intechopen.82513*

which will have a toll on TKI therapy effectiveness.

TKIs and which combination of therapies.

**4.6 Improve patient compliance**

apps for patients to keep track of their drug schedule.

**4.4 Improve patient selection**

*Cancer Management by Tyrosine Kinase Inhibitors: Efficacy, Limitation, and Future Strategies DOI: http://dx.doi.org/10.5772/intechopen.82513*

and has additional effect of alleviating TKI induced toxicity [173]. They are able to significantly raise overall response rates, disease control rate, 1-year survival rate, 2-year survival rate, and improvement/stable Karnofsky Performance scores of tumors. Severe toxicity for rash was decreased, so were nausea, vomiting, and diarrhea [174, 175]. The strategy of minimizing or alleviating side effects of TKIs may be potential. This could help increase tolerability of patients and also reduce drugrelated adverse events and subsequent possible drug reduction and discontinuation, which will have a toll on TKI therapy effectiveness.

#### **4.4 Improve patient selection**

*Tyrosine Kinases as Druggable Targets in Cancer*

EGFR-TKIs [167].

results [63].

and are in many cases already put to clinical practice.

yielded better results than standard-dose or high-dose imatinib alone, as well as standard-dose imatinib combined with chemotherapy [21, 163]. Icotinib, an EGFR-TKI is proved to improve radiosensitivity in lung cancer in vitro and in vivo, thus possibly allowing better radiotherapy effects [164]. They are extensively studied

A TKI could also be combined with another TKI. For example, dual EGFR blockade by first and third-generation EGFR TKI combinations [165]. Or dual ALK and EGFR target inhibition in ALK translocated NSCLC with additional EGFR mutation [166]. Other ongoing clinical trials study the potential benefits of combining anti-angiogenic TKIs (e.g., apatinib, endostatin, and anlotinib) with

There are also studies proposing TKI combination with other target inhibitors including monoclonal antibodies. Researches are exploring possibilities of combinations of brigatinib and anti-EGFR antibodies, third-generation TKIs with MEK inhibitors, and osimertinib with oxidative phosphorylation inhibitors etc. [165]. For acute lymphocytic lymphoma, a WEE1 inhibitor AZD-1775 is proven to significantly enhance the efficacy of several tyrosine kinase inhibitors, such as imatinib, bosutinib, and ponatinib [168], or similarly, vitamin K1 with sorafenib in treating

HCC [151] and antiestrogen fulvestrant with vandetanib in NSCLC.

**4.3 Wisdom from traditional Chinese medicine (TCM)**

uncovering therapeutic potentials of various natural compounds.

Combination approach is promising, yet limited by potential toxicity. Combination of drug effects is true for both positive and side effects. Many studies echoed that concurrent chemotherapy and TKI therapy yielded no added benefits. Therefore, it is important to understand the mechanism of action of the two therapies and understand their interaction, thus design the best administration schedule. Taking TKIs and chemotherapy in an intercalated manner may reduce inhibitory drug interaction. A study compared synchronized administration and intercalated administration of the two therapies [101], and found that intercalated administration schedule improved PFS and OS [169]. More and more studies are thus conducted on the administration schedule and yielded similar

TCM has long been used to treat different cancers and are often shown with clinical efficacy. TCM herbs are able to stabilize tumor growth, control patient symptoms and alleviate side effects, and ultimately improve quality of life of patients [161]. Many researches are thus dedicated to discovering novel drugs by

Accumulating studies have been discovering tyrosine kinase inhibiting effects from natural compounds. Many TCM herbs contain natural compounds that are capable of interacting with multiple cellular targets [161]. Various molecules from traditional Chinese medicine are being discovered with tyrosine kinase inhibiting effects and these include 2-O-caffeoyl tartaric acid, emetine, rosmaricine, and 2-O-feruloyl tartaric acid, which are potential EGFR inhibitors [170]. Another meta-analysis identified another 24 kinase inhibitors from TCM [171]. Network pharmacology enables us to discover more of such molecules and their targets [161]. Using natural compounds as drugs is relatively safe and exhibit less side

On the other hand, complementary use of TCM has been actively discussed in recent years. Many recent studies have been conducted. They appear to be able to increase efficacy as well as reduce toxicity when combined with TKI therapy [161, 172]. Some studies showed that TCM work synergistically with EGFR-TKI

**106**

effects [161].

The drug effects of TKIs can be drastically different in two patients. It can work miracles in one, but have no effect at all in another. The genetic makeup of a patient's tumor is a huge predicting value of the efficacy of the TKI. Various studies have shown the correspondence between genetic profiling and therapy response [176, 177]. Thus, it is vital to perform procedures to select the population of patients responsive toward the TKI. In the new era of personalized medicine, the most effective way of using TKIs to treat cancer is to consider each patient/tumor individually and to determine the strategy that specifically targets the consequences of altered genetics of the tumor. Not simply which TKI to use, but also which combination of TKIs and which combination of therapies.

#### **4.5 Repeated monitoring, including repeated biopsy/ liquid biopsy**

It was proposed that in order to overcome the limitation of AR in TKIs, repeated tumor biopsies should be done during the course of treatment. This is to give us the ability to spot mutations early and learn its resistance mechanism, thus allowing intervention prior to standard detection of radiographic signs of progression. The specific agent/combination against that particular resistance mechanism can thus be selected.

Yet multiple resistance mechanisms within a single patient, especially between multiple lesions in a patient, pose challenges for biopsy. Besides, biopsies are not accessible for all tumors and are also invasive to the patient. Studies have proposed repeated liquid biopsies as a solution [178]. Liquid biopsy checks for tumor DNA circulating in the blood, which is shed into the bloodstream by tumors all around the body, thus allowing us to peer into the tumor genome in distinct subclones in different metastatic lesions within the patient. It is more effective in learning the heterogeneity and multiple resistance mechanisms than performing a single lesion biopsy. It being less invasive (a simple blood draw will suffice), also allows a more frequent sampling.

#### **4.6 Improve patient compliance**

Patient compliance does make a big difference in treatment outcome. Studies have proven that those with higher adherence did achieve better results in achieving CCyR and MMR [113]. Since many TKIs are orally administered, of long-term usage, and in some cases, self-administered in an out-patient setting, patient compliance could pose a serious challenge, especially with irregular drug schedule, such as one with drug holidays. Patient education is one of the ways we could improve patient compliance. Perhaps systems for patient monitoring could also be developed, including system like DOTs therapy for TB patients, where out-patients are required to come to the clinic and take the medicine in front of the healthcare workers and official record is made. Other suggestions include designing phone apps for patients to keep track of their drug schedule.

#### **4.7 Generic drug use**

Generic drug use could be a possible solution to high cost of TKIs [179]. Researches on generic versions of various drugs have been conducted [180]. Studies have shown that generic imatinib and Brand named imatinib (Gleevec) showed no difference in efficacy [181]. Aside from imatinib, many TKIs are currently available in generic form, including dasatinib and sorafenib. Yet the quality of generic drugs is not always certified and has to be judged case by case.

#### **4.8 Exploring the potential of TKI therapy termination**

Many TKIs are believed to be required to be administered a lifetime. This has posed certain difficulties, including inconvenience to the patients, accumulative side effects, financial burden to the hospital and patient etc. Many studies are thus working on the possibility of discontinuing TKI therapy after a certain response is achieved. Some researches have identified specific subsets of patient populations which could consider discontinuation of TKIs [182].

### **5. Conclusion**

Although TKIs have a very high clinical efficacy upon initial administration, the frequency of acquired resistance is too high, making it not as effective in improving overall survival. There are however many ways we can resort to, in order to prolong the period of stable disease, before progression. These include using multi-targeted approaches, or combination approaches, although it is also accompanied with more severe side effects. Resorting to natural compounds, for example, those from TCM, could be a potential way. They are often multitargeted and not as potent, thus allowing multitarget inhibition without bringing about severe toxicities. Adequate monitoring of disease status and patient adherence is another simple yet effective way to improve the performance of TKIs. Being able to make timely adaptations to treatment plan can play a vital role in prolonging survival. Another direction would be to place more emphasis on patient selection. There are many factors that could help us predict the patient's sensitivity and response toward that TKI. TKI should not be used as an empirical treatment, which would be too cost-ineffective. Even for the same cancer same stage, the specific genetic constitution of each tumor differ from each other, and choice of TKI may vary dependently. Hence, personalized treatment is the key.

### **Acknowledgements**

The study was financially supported by grants from the research council of the University of Hong Kong (Project Codes: 104004092, 104004460, and 104004746), the Research Grants Committee (RGC) of Hong Kong, HKSAR (Project Codes: 764708, 766211, and 17152116), Wong's Donation on Modern Oncology of Chinese Medicine (Project code: 200006276), and Gala Family Trust (Project Code: 200007008).

**109**

**Author details**

provided the original work is properly cited.

\*Address all correspondence to: yfeng@hku.hk

© 2019 The Author(s). Licensee IntechOpen. This chapter is distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/ by/3.0), which permits unrestricted use, distribution, and reproduction in any medium,

School of Chinese Medicine, Li Ka Shing Faculty of Medicine, The University of

Venice Wing Tung Ho, Hor Yue Tan, Ning Wang and Yibin Feng\*

Hong Kong, Pokfulam, Hong Kong, People's Republic of China

*Cancer Management by Tyrosine Kinase Inhibitors: Efficacy, Limitation, and Future Strategies*

*DOI: http://dx.doi.org/10.5772/intechopen.82513*

*Cancer Management by Tyrosine Kinase Inhibitors: Efficacy, Limitation, and Future Strategies DOI: http://dx.doi.org/10.5772/intechopen.82513*

### **Author details**

*Tyrosine Kinases as Druggable Targets in Cancer*

is not always certified and has to be judged case by case.

**4.8 Exploring the potential of TKI therapy termination**

which could consider discontinuation of TKIs [182].

Generic drug use could be a possible solution to high cost of TKIs [179]. Researches on generic versions of various drugs have been conducted [180]. Studies have shown that generic imatinib and Brand named imatinib (Gleevec) showed no difference in efficacy [181]. Aside from imatinib, many TKIs are currently available in generic form, including dasatinib and sorafenib. Yet the quality of generic drugs

Many TKIs are believed to be required to be administered a lifetime. This has posed certain difficulties, including inconvenience to the patients, accumulative side effects, financial burden to the hospital and patient etc. Many studies are thus working on the possibility of discontinuing TKI therapy after a certain response is achieved. Some researches have identified specific subsets of patient populations

Although TKIs have a very high clinical efficacy upon initial administration, the frequency of acquired resistance is too high, making it not as effective in improving overall survival. There are however many ways we can resort to, in order to prolong the period of stable disease, before progression. These include using multi-targeted approaches, or combination approaches, although it is also accompanied with more severe side effects. Resorting to natural compounds, for example, those from TCM, could be a potential way. They are often multitargeted and not as potent, thus allowing multitarget inhibition without bringing about severe toxicities. Adequate monitoring of disease status and patient adherence is another simple yet effective way to improve the performance of TKIs. Being able to make timely adaptations to treatment plan can play a vital role in prolonging survival. Another direction would be to place more emphasis on patient selection. There are many factors that could help us predict the patient's sensitivity and response toward that TKI. TKI should not be used as an empirical treatment, which would be too cost-ineffective. Even for the same cancer same stage, the specific genetic constitution of each tumor differ from each other, and choice of TKI may vary dependently. Hence, personalized

The study was financially supported by grants from the research council of the University of Hong Kong (Project Codes: 104004092, 104004460, and 104004746), the Research Grants Committee (RGC) of Hong Kong, HKSAR (Project Codes: 764708, 766211, and 17152116), Wong's Donation on Modern Oncology of Chinese Medicine (Project code: 200006276), and Gala Family Trust (Project Code:

**4.7 Generic drug use**

**5. Conclusion**

treatment is the key.

**Acknowledgements**

200007008).

**108**

Venice Wing Tung Ho, Hor Yue Tan, Ning Wang and Yibin Feng\* School of Chinese Medicine, Li Ka Shing Faculty of Medicine, The University of Hong Kong, Pokfulam, Hong Kong, People's Republic of China

\*Address all correspondence to: yfeng@hku.hk

© 2019 The Author(s). Licensee IntechOpen. This chapter is distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/ by/3.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

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[2] Cammack R, et al. Tyrosine Kinase. Oxford, England, UK: Oxford

[3] Maruyama IN. Mechanisms of activation of receptor tyrosine kinases: Monomers or dimers. Cell.

[4] Perona R. Cell signalling: Growth factors and tyrosine kinase receptors. Clinical & Translational Oncology.

[5] Witsch E, Sela M, Yarden Y. Roles for growth factors in cancer progression. Physiology (Bethesda). 2010;**25**(2):85-101

[7] Goustin AS et al. Growth factors and

[8] Posner I et al. Kinetics of inhibition by tyrphostins of the tyrosine kinase activity of the epidermal growth factor receptor and analysis by a new computer program. Molecular Pharmacology.

2005;**315**(3):971-979

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1994;**45**(4):673-683

Elsevier; 2007. pp. 1-4

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### *Edited by Huan Ren*

Protein tyrosine kinase (PTK) deregulation contributes to growth of cancer and many other diseases. The development of small-molecule tyrosine kinase inhibitors (TKIs) that target the deregulated PTKs, such as epidermal growth factor receptor (EGFR) in nonsmall-cell lung cancer (NSCLC) and Bcr-ABL in chronic myeloid leukemia (CML), has revolutionized disease management. In this book, we examine a few aspects of PTKs and cancer, considering efficacy, predictive markers to therapeutic response, limitations, and future directions in TKI treatment. In this rapidly evolving field, overcoming therapeutic resistance is most challenging, and multi-targeting directs the next-generation TKIs and combination therapy as ongoing strategies in cancer treatment.

Published in London, UK © 2019 IntechOpen © Arina\_Bogachyova / iStock

Tyrosine Kinases as Druggable Targets in Cancer

Tyrosine Kinases as

Druggable Targets in Cancer

*Edited by Huan Ren*