**5.2. Oral cavity, nasopharyngeal and laryngeal cancers**

In what concerns diagnostic of oral cancers, Raman spectroscopy has been widely used in biofluids like blood, urine and saliva and using fiber optic probes for *in vivo* diagnosis (**Table 1**). The advantage of using biofluids instead of tissue is that they can be collected using noninvasive and painless methods [26].

In 2010, Feng et al. described for the first time the use of a surface-enhanced Raman spectroscopy (SERS) method for plasma analysis for nasopharyngeal cancer detection using silver nanoparticles [27]. This type of spectroscopy produces strong signals and has a low associated cost. Besides, it is suitable for use with intact tissue, biofluids and during endoscopies [26]. A total of 76 samples were used in that study and using PCA and LDA multivariate analysis, the authors found a distinct biological signature between control and cancer samples mainly due to an increase in nucleic acids, collagen, phospholipids and phenylalanine and also a decrease in amino acids and saccharide in cancer samples compared to control samples [27]. These results gave new insights about the use of surface-enhanced Raman spectroscopy for noninvasive diagnostic methods. SERS using gold nanoparticles was also applied to blood serum to diagnose oral squamous cell carcinoma [28]. Analysis of 370 Raman spectra using PCA and LDA multivariate analysis allowed to discriminate serum samples of patients with and without neoplasia with high sensitivity and specificity [28].

The use of Raman spectroscopy in oral cancer diagnosis relies mainly on fiber optic probes, and data published so far present promising results. In 2010, a study showed the applicability of fiber optic Raman probed spectroscopy to target biopsies at endoscopy [29]. This type of approaches can be useful to avoid excision of normal tissue for biopsy. In this way, there is a reduction of the burden in histopathology departments and in the number of invasive procedures for the patient. Later, in 2012, Almond et al. also tested a fiber optic Raman probe to discriminate between benign, metaplastic and neoplastic esophageal *ex vivo* tissue [30]. Results showed high sensitivity and specificity, so it is suitable to think in this approach as a new technique for clinical diagnosis although *in vivo* clinical trials are needed to confirm the accuracy of this probe. In 2015, fiber optic Raman spectroscopy was successfully applied in 48 patients during endoscopy [31]. The authors were able to simultaneously acquire both fingerprint and high wavenumber Raman spectra to extract the maximum biological information and obtained sensitivity and specificity values about 97% for the diagnosis of esophageal squamous cell carcinoma [31]. Similar results were obtained with a probe designed to diagnose laryngeal cancer [32]. Analysis of 2124 Raman spectra of 60 patients during endoscopy showed sensitivity and specificity above 90% for the identification of laryngeal cancer when combined fingerprint and high-wavenumber spectra [32]. Recently, Ming et al. [33] performed a pilot study in 79 patients with and without nasopharyngeal cancer and in postirradiated patients. They detect a specific signature for each one of the three cohorts, which may indicate that Raman could not only be used for diagnostic purposes but also for surveillance in post-treated patients. Furthermore, the authors used a probe with only 1.8 mm, which is the smallest probe used in Raman diagnostics and is more suitable to be used in clinical endoscopies [33].

#### **5.3. Gastric cancers**

1300 cm−1, assigned to proteins and lipids, using PCA multivariate analysis, with high sensitivity and specificity [23]. Later, in 2012, the same author reported new results corroborating the previous study [24]. Using a Raman spectrometer attached to a fiber optic and PCA analysis, they analyzed 145 different samples of basocellular cell carcinoma, melanoma and without malignant lesions and were able to discriminate cancer and normal samples with sensitivity and specificity values over 90% [24]. In the same year, a different study was performed by Wang H et al. using HaCaT cells, melanocytes and their malignant derivatives [25]. They tested the ability of micro-Raman spectroscopy to separate different cell lines and found significant spectral differences between HaCaT cells and squamous cell carcinoma, melanocytes and melanoma cells as well as between all normal cells *versus* all tumor cells [25] (**Table 1**). The results of these *in vitro* studies are of extreme importance and can help the interpretation

In what concerns diagnostic of oral cancers, Raman spectroscopy has been widely used in biofluids like blood, urine and saliva and using fiber optic probes for *in vivo* diagnosis (**Table 1**). The advantage of using biofluids instead of tissue is that they can be collected using noninva-

In 2010, Feng et al. described for the first time the use of a surface-enhanced Raman spectroscopy (SERS) method for plasma analysis for nasopharyngeal cancer detection using silver nanoparticles [27]. This type of spectroscopy produces strong signals and has a low associated cost. Besides, it is suitable for use with intact tissue, biofluids and during endoscopies [26]. A total of 76 samples were used in that study and using PCA and LDA multivariate analysis, the authors found a distinct biological signature between control and cancer samples mainly due to an increase in nucleic acids, collagen, phospholipids and phenylalanine and also a decrease in amino acids and saccharide in cancer samples compared to control samples [27]. These results gave new insights about the use of surface-enhanced Raman spectroscopy for noninvasive diagnostic methods. SERS using gold nanoparticles was also applied to blood serum to diagnose oral squamous cell carcinoma [28]. Analysis of 370 Raman spectra using PCA and LDA multivariate analysis allowed to discriminate serum samples of patients with

The use of Raman spectroscopy in oral cancer diagnosis relies mainly on fiber optic probes, and data published so far present promising results. In 2010, a study showed the applicability of fiber optic Raman probed spectroscopy to target biopsies at endoscopy [29]. This type of approaches can be useful to avoid excision of normal tissue for biopsy. In this way, there is a reduction of the burden in histopathology departments and in the number of invasive procedures for the patient. Later, in 2012, Almond et al. also tested a fiber optic Raman probe to discriminate between benign, metaplastic and neoplastic esophageal *ex vivo* tissue [30]. Results showed high sensitivity and specificity, so it is suitable to think in this approach as a new technique for clinical diagnosis although *in vivo* clinical trials are needed to confirm the accuracy of this probe. In 2015, fiber optic Raman spectroscopy was successfully applied in 48 patients during endoscopy [31]. The authors were able to simultaneously acquire both

spectra of *in vivo* samples for cancer skin diagnosis.

sive and painless methods [26].

282 Raman Spectroscopy

**5.2. Oral cavity, nasopharyngeal and laryngeal cancers**

and without neoplasia with high sensitivity and specificity [28].

Diagnosis of gastric cancer using Raman technologies relies either on the use of fiber optic probes or on SERS (**Table 1**). In fact, SERS was applied to plasma samples to detect gastric cancer in a noninvasive way [34], similar to what was done to diagnose nasopharyngeal cancer [27]. The authors use two cohorts, with a total of 65 samples (32 patients with confirmed gastric cancer and 33 control patients). Using PCA and LDA multivariate analysis, it was observed discrimination between cancer and normal samples with sensitivity and specificity of 100 and 97%, respectively. In 2012, the same methodology was applied to discriminate gastric cancer from normal controls based on serum RNAs, also achieving high sensitivity and specificity (100 and 94.1%, respectively) [35]. SERS seems to be a useful technique to apply in routine clinical diagnosis coupled, for instance, with endoscopy. Fiber optic probes can be used for *in vivo* identification of gastric metaplasia. Lin et al. [36] coupled fingerprinting and high-wavenumber Raman spectroscopy with a fiber optic Raman probe and were able to detect, in real-time, pre-cancerous gastric lesions. They acquired 4520 spectra in real time, during gastroscopy, and by using PCA and LDA analysis, they were able to identify precancerous lesions with high sensitivity and specificity [36]. This can improve early diagnosis of neoplasia and significantly improve the efficacy of treatments.

#### **5.4. Breast cancers**

Breast cancer is the second most prevalent cancer in the world and, it is the most common cancer in women, causing more than 500,000 deaths every year [37]. According to these statistics, it is not surprising that Raman spectroscopy has been used as a diagnostic tool for this disease. Kong et al. used Raman microspectrometry to detect ductal carcinoma in tissue excised during breast-conserving surgery [38]. They developed a model that allowed to discriminate normal and cancerous tissue in approximately 17 min, with sensitivity and specificity above 95% [38]. A different approach was used by Feng et al. in 2015 [39]. Similar to what this group did for other types of cancer (see **Table 1** for detailed information), they applied SERS to saliva proteins of 97 patients and were able to discriminate between control, benign tumors and malignant tumors with sensitivities and specificities between 72.7–75.8% and 81.2– 93.4%, respectively, using PLS-DA analysis [39]. These results give good perspectives for new noninvasive diagnostic tools. Depciuch et al. acquired Raman spectra of breast biopsies and did direct spectral analysis without performing multivariate analysis [40]. They reported differences in spectral regions assigned to the principal biomolecules: lipids, sugars and proteins between normal and cancerous samples [40]. All these reports give new light in understanding the molecular mechanisms involved in breast cancer.

to bacterial identification and typing and producing fast and accurate results. Raman spectra of bacteria are like a fingerprint, since it represents the molecular composition and it is specific for each sample. The following studies are examples of the use of Raman in the field of

Raman Spectroscopy Applied to Health Sciences http://dx.doi.org/10.5772/intechopen.73087 285

In 2009, Willemse et al. used Raman spectroscopy to type methicillin-resistant and methicillinsensible *Staphylococcus aureus* and compare it with traditional DNA typing methods, which are time- and labor-consuming [49]. After spectra collection and cluster analysis, results showed that Raman spectroscopy has reproducibility and discrimination ability, and all Raman clusters were in accordance with epidemiologic data of the isolates [49]. Similar results were obtained by the same group using *Escherichia coli* and *Klebsiella pneumoniae* isolates [50]. Using SpectraCell analyzer (River Diagnostics), they obtained high reproducible spectra and a discriminatory power similar to traditional DNA typing methods [50]. However, Raman spectroscopy was not able to detect ESBL-producing *E. coli* transmission events even when coupled to High-throughput MultiLocus Sequence Typing [51]. SERS is also used in the field of microbiology to identify pathogens. For instance, malaria parasite can be detected using a SERS nanoplatform [52]. Besides, it is also possible to discriminate wild-type malaria DNA from mutant malaria DNA using this technique [52]. SERS was also used in milk samples to identify *Salmonella enterica* serotype Enteritidis [53]. In this study, SERS was used with Au nanoprobes, and the results were almost 100x more sensitive than those obtained by PCR [53]. In clinical microbiology, it would be of particular interest to apply bacterial identification approaches directly to biological samples. One of the possible drawbacks of using spectroscopy in this field is that biological fluids can have complex matrixes that may mask the specific spectral signature of a given pathogen. To verify the applicability of Raman to bacterial identification in biofluids, Harz et al. used micro-Raman to directly analyze cerebrospinal fluid (CFS) of patients with bacterial meningitis [54]. Since lethality of the disease depends on the pathogen involved, time is crucial and it is necessary to properly identify the bacteria and initiate the adequate antibiotic therapy in a short period of time. In this study, the authors showed that CFS did not affect Raman spectra of bacteria, and it was possible to identify it with accuracy [54]. This corroborates the idea that Raman can be used as a diagnostic assay. In hospitals, it is important not only to identify the pathogen but also to understand the antimicrobial susceptibility profile of the microorganism in order to choose the right antibiotic to mitigate and treat the infection. Raman spectroscopy has been recently successfully used with this purpose [55]. The authors were able to discriminate Raman spectra of 67 antibioticsusceptible strains isolated from positive blood cultures in the presence of different concentrations of antibiotic in only 5 h [55]. Further development of this technology could produce results with robustness similar to current methods used in hospitals, and therefore in the

Raman-based approaches can also be used in the field of virology. It is possible to identify rotavirus with an accuracy above 96% using SERS fingerprinting, and the detection of the virus was possible even using a complex cellular matrix, although the results were not as sensitive as those obtained with purified samples [56]. A similar procedure was used to detect respiratory syncytial virus [57]. In this study, the authors applied SERS enzyme-catalyzed immunoassay of respiratory syncytial virus in cell lysates, and the results showed a linear

clinical microbiology.

future, it can be applied to clinical diagnosis.
