Biomarkers for Early Diagnostics on Oral Cancer: Comparison
View Latest Version
Please note this is a comparison between Version 2 by Dean Liu and Version 3 by Dean Liu.

One of the most frequent head and neck cancers is oral cancer, with less than half of those diagnosed surviving five years. Despite breakthroughs in the treatment of many other cancers, the prognosis for people with OSCC remains dismal. The conventional methods of detection include a thorough clinical examination, biochemical investigations, and invasive biopsies. Early identification and treatment are important for a better chance of extending a patient’s life. Early diagnosis may be possible by identifying biomarkers in biological fluids.

  • oral cancer
  • OPMD
  • OSCC
  • early diagnosis

1. Diagnostic Methods for Detection of OC

1.1. Visual Oral Examination

Doctors need to know as soon as possible if an OPMD has a chance of becoming cancerous so that they can keep an eye on it, treat it, and improve survival rates. Currently, the usual screening approach for detecting oral mucosal lesions is a visual oral examination (VOE). Because white or red lesions and long-term ulcers can be hard to tell apart at first glance, VOE is very dependent on the physician’s knowledge [1][2]. It is very important to distinguish lesions with a greater risk of malignant transformation because this will have a big impact on the treatment success. Though histological evaluation acts as the gold standard for clinical diagnosis and therapy, it may be insufficient to distinguish lesions that require active treatment, particularly if they are subtle or in a non-dysplasia stage.
A quick diagnosis is very important for preventing oral premalignant disorders from becoming cancerous and increasing the chances that the patients will live long lives. For the right diagnosis, many different procedures need to be performed, such as swabbing the exterior of the abscess and looking at the biological data of oral precancerous lesions. It is hard to tell, but specialists need to be capable of distinguishing between the features of ulcerations just by looking at them, without changing the cells in the area [3][4][5][6][7][8][9][10][11][12][13][14]. While incisional biopsy with histopathology is the gold standard for identifying dental pathology, it is hurtful for patients and results in a late diagnosis, due to the completion of histology. The autofluorescence approach is a new noninvasive tool for analyzing a soft-tissue injury. It can be utilized to locate oral precursor malignant lesions, as well as the proper place for biopsies within the changed mucosa. The procedure’s biggest drawback is the risk of false-positive outcomes [3][4][15]. Identifying the potential biomarkers will improve the ability to exactly analyze and forecast the likelihood and danger of OPMDs evolving into an OC lesion, which requires active treatment if found.

1.2. Physical Examination

The physical examination is the first and most important stage in diagnosing oral cancer. Typically, it is processed in two stages: a comprehensive visual evaluation, followed by palpation. External body components such as lymph nodes, salivary glands, and lips were inspected initially, followed by an inspection of the buccal cavity’s interior. In the superficial anatomy, abnormalities, irregularities, edema, and fluctuation are observed. Soft-tissue thickening, lumps, discomfort, difficulty moving the jaw, chewing and swallowing, earache, and other symptoms are typical. The parotid gland (biggest salivary gland) is palpated both within and outside the mouth, as well as the submandibular and sublingual glands [16]. Physical observations are compared to the patient’s clinical picture by the examiner. Additionally, morphological changes, as well as texture and color aberrations, are described [17].

1.3. Histopathological Examination

OC can range from benign tumors to extremely aggressive tumors with a high proclivity for invasion. Histological examinations demonstrate how oral carcinogenesis progresses from benign dysplasia to highly invasive malignancies. Histological investigation is essential to identify cell proliferation and development difficulties, cellular and cytoplasmic atypia, and abnormalities in the surface epithelium or deep tissue cytoarchitecture [18]. The crucial stage in a histological examination is identifying the correct region and proper sampling of the oral lesion, as the histopathological alterations can also develop in places where there is no indication of oral lesions upon physical examination. Thus, for the diagnosis of benign or malignant tumors, a method that recognizes both histopathological and molecular changes is desirable, as genomic changes can occur in normal tissues prior to the emergence of microscopic and clinical morphological changes [19].

1.4. Vital Staining Techniques

The vital staining technique includes labeling cells or tissues in their living state. This method of optical tissue staining for cancer detection provides an alternative to physical examination [20]. Toluidine blue staining is used to detect oral mucosal abnormalities. Toluidine blue is an acidophilic metachromatic dye that has a good attachment for acidic tissue components, coloring the nuclear material of DNA and RNA-rich tissues. This approach, when used in conjunction with Lugol’s iodine, aids in the differentiating between inflammatory lesions. Such a combination accurately predicts the stage of tumors, ranging from benign to malignant lesions, making it an advantageous visual staining technique for evaluating OC before treatment [21].

1.5. Biopsy

Biopsy is a process where part of tissue or sample of cells is surgically extracted from the suspicious area from the body and submitted to a pathology facility for microscopic analysis. This is the sole approach to determine if an oral cavity or oropharyngeal carcinoma is present [22]. For a reliable histological diagnosis after a biopsy, proper treatment of the tissue is essential. Improper sample handling might lead to a faulty biopsy, which necessitates repeating the process. Exfoliative cytology and incisional biopsy are two types of biopsies that are performed depending on the individual need. Brush biopsy involves scraping the surface mucosa from the oral lesion to extract the cells from transepithelial region. This technique is a straightforward, safe, painless, cost-effective, and highly sensitive method. Small white and red lesions in the mouth can be checked to make sure that they are not dysplastic. Compared to other biopsy procedures, brush biopsy holds 90% of sensitivity and specificity [23].
Oral exfoliative cytology (OEC) is a simple, non-aggressive method which is comfortable for the patient and can be used to detect OC early. OEC concentrates on the individual cell’s morphological and staining features, thus necessitating the involvement of expert cytopathologists [24]. Despite its benefits, OEC is neither specific nor sensitive, and as a result, it is mostly utilized for screening from a large population, regular monitoring of precancerous lesions, and identification of appropriate biopsy sites in large lesions [25]. Once the cancer is detected by OEC, incisional biopsy is performed, in which a small portion tissue sample is carefully chosen for diagnosis. Though it does not cover the whole lesion, the incisional biopsy is reasonably accurate [26]. In circumstances when it is impossible to remove the entire lesion, e.g., a broad white patch or lichen planus, an incisional biopsy is employed. In addition, this approach is favored when the clinical diagnosis is unknown [27].

1.6. Imaging Techniques

OC is diagnosed by using a variety of technological imaging methods, such as computed tomography (CT), magnetic resonance imaging (MRI), and positron emission tomography (PET) [28].

2. Biomarker Detection

2.1. Next-Generation-Sequencing-Based Biomarkers

Squamous cell carcinoma progresses because of changes at the genomic level. Next-generation sequencing (NGS) technology is a good way to find the mutations and copy number changes that cause these changes [29]. Stransky et al. performed whole-exome investigations on head and neck SCC from 74 patients and observed matched DNA pairs between tumors and peripheral whole blood [30]. This team had identified 130 coding mutations per tumor. Given that 14 percent of all cancers were HPV-positive, results from sequencing research show how these would have a genetic variation that was half that of HPV-negative tumors. This supports the idea that there are molecular differences among the two types of SCC. With the help of NGS which possess high sensitivity, the molecular characterization among the two SCCs may go even further, subdividing HPV-negative tumors not only by their precise location, but also by the frequency of specific nucleotide alterations. Aside from these findings, the presence of mutant NOTCH1 in 11% of all tumors examined was noteworthy, since it would be the first study linking genetic alterations in this gene to the genesis and progression of SCC. It shows that the changes that happen at different stages of squamous differentiation have a big impact on the many genetic processes that drive SCC development [29][31]. Another interesting finding is that a mutation at TP53 had a key influence in the development of this disease for the younger patients who are preferably non-smokers [32]. Pickering and his colleagues did a very detailed genomic study of OSCC in order to find out what causes the disease to become malignant and what biomarkers can be used to classify, predict, and treat it [33]. Pickering and his team used fresh-frozen malignant cells and nonmalignant cells from 38 patients with OSCC to study genome-wide copy number changes. They found strong correlations between gene expression and comparative copy numbers for 1721 genes.
The NOTCH1 gene had many missense and truncating mutations in around one-tenth of the tumor samples, and this was confirmed by using a panel of HNSCC cell lines. With the previously described study group, they found comparable results. The absence of protein expression, along with other tests, such as in vivo experiments using mouse models, supports the hypothesis that the Notch signaling system had a major role in tumor-suppressive mechanisms in SCC [34]. This new but widely used method can help researchers understand not only the main molecular devices that play a role in SCC emergence and development, but also other possible participants that play a role in the tumor transformation process.
Pushalkar and his study team sought to investigate how bacteria might play a role in tumorigenesis, especially with SCC [35]. They collected saliva samples from three people who had OSCC and two people who were healthy (control). Then the bacterial gDNA was extracted, processed, and pyro-sequenced. After analyzing the data, the researchers discovered several bacterial species related to eight distinct taxonomic phyla, with the Firmicutes phylum being the best defined in samples compared to controls. At the species level, NGS analyses revealed how microorganisms are expressed variably in the dental environments of SCC individuals versus healthy participants, suggesting that these microbes might contribute to the course of the disease. The same research group then looked at matched pairs of cancerous and non-cancerous tissue from SCC patients. This shows how important it is to use unique techniques such as this to understand the many and complex aspects of OSCC transition [36].

2.2. Transcriptomics-Based Biomarkers

MicroRNA is a group of functional non-coding RNA molecules that have about 22 nucleotides each. They contribute to gene control after transcription, and they have about 22 nucleotides in each. Many diseases start and get worse when there are problems with the way microRNAs are made. This is because microRNAs control so many important biological processes, such as advancement, divergence, and cell cycles [29][37]. Tus miRNAs might be used as biomarkers for a variety of illnesses, including neurodevelopmental disorders (Ohnishi et al. 2014), cancer, and cardiovascular disease [38][39]. A microarray analysis of 20 human whole-blood specimens on 1200 miRNAs revealed OSCC-specific signature biomarkers. Then qRT-PCR was used to validate the most important miRNAs, which showed a two-fold upregulation for miR-494 and miR-3651 and a two-fold downregulation for miR-186. Another study with microarray data using Affymetrix U133A platform revealed that 51 genes were upregulated and found that most of genes were related to OSCC [40]. Their findings also showed a new set of OSCC-related genes (RHEB, SOD2, SKP2, IFI16, IFI44, STAT1, and GREM1) and three genes (MMP1, SOCS3, and ACOX1) that differentiate the normal tissue from the cancer [41]. Microarray and qPCR were used to examine a group of 23 CXC-chemokine ligands and receptors that were then connected to therapeutic response by using a logistic regression technique. CXCL10 expression was found to be substantially associated with radiotherapy response, with the group with CXCL10 overexpression having a poor outcome [42]. Similar study was also observed where miRNAs showed different levels of expression between normal tissue and OSCC tissue. miR-375 showed the greatest inhibition, whereas miR-31 recorded overexpression. Moreover, 61 miRNAs were found to establish a 93 percent accurate molecular categorization of OSCC [39]. Lajer and his group found that HPV causes changes to 21 miRNAs, the most important of which are miR-127-3p and miR-363 [43]. The influence of HPV might explain why HPV-infected malignancies have variable clinical outcomes on miRNA profile.
MiR-375 downregulation, miR-127 overexpression, and miR-137 hypermethylation were discovered in another study of OSCC. Another interesting biomarker which is epigenetically activated in tumor tissue was observed with miR-200 and miR-205. Observing changes in miR-375 and miR-200a methylation, and also changes in miR-200c methylation, is a useful non-invasive biomarker, as shown by a study that compared the saliva of OSCC patients and healthy people. It has been suggested that salivary miRNA profiles could be used as a biomarker for initial evaluation of patients in OSCC [44]. The first lncRNA heat map for usual oral cavity vs. a pre-malignant abscess was made and publicly disclosed [45]. Many recent research studies have shown that new lncRNA can be used as non-invasive saliva biological markers for prediction and diagnosis. HOTAIR identified in saliva was shown to have considerable predictive relevance in a recent research study, with the expression level associated with lymph node metastases.

2.3. Proteomic-Based Biomarkers

Proteomics is a promising technique for identifying new biomarkers with prognostic and diagnostic potential [46][47]. The identification of new biomarkers in OSCC may be aided by analyzing cellular entire protein complements or biofluids. A key feature of various research studies [48] is a saliva proteome profiling study based on patient categorization. Tests have been performed to see how much protein is found in samples of OSCC and healthy tissue, as well as in other in vitro systems for this disease [49]. A lot of proteins that affect cellular functions and structure, cellular adhesion, or cell migration, and proteins that make cancer more likely were found to be changed in studies [50][51]. When researchers looked at the plasma proteome of mice with OSCC, they found that haptoglobin and the precursor of apolipoprotein A1 have both been upregulated. The expression of haptoglobin plasma in humans showed that there was a strong connection between increasing levels of haptoglobin and the clinical stages of OSCC. This suggests that haptoglobin could be used as a plasma diagnostic marker for identification of OSCC patients [52].
A SELDI-TOF Protein Chip technology was used to screen saliva proteins from pre- and post-treatment OSCC tests to find 26 candidates with different patterns in their saliva that could be linked to the disease. The investigation found a shortened cystatin SA-I of 14 kDa in pre-treatment saliva samples, with a deletion of three amino acids at the N-terminal end [53]. Protein Chip analysis could be a good way to screen for OSCC at an early stage, and truncated cystatin SA-I could be a good tumor prognostic marker for OSCC. Transglutaminase 3 (TGM3) downregulation was linked to OSCC histological differentiation loss in another study [54]. There were 52 proteins that had statistical significance, so a comparative proteomics study found a group of eight proteins that were more or less common in different people. Annexin A8, Peroxiredoxin-2, and Tyrosine Kinase have been observed in both diabetes and OSCC, and they were thought to be possible biomarkers for OSCC diagnosis because they were found in both [55]. A mass spectrometer study of saliva from people with cancer and healthy people found 213 new proteins. The salivary biomarkers Profilin, Cofilin, S100A9, and MMP9 have all been found to be linked to head and neck cancer. Vimentin has been linked to the epithelial–mesenchymal transition and metastasis of head and neck cancer [56].
Exosomes are endocytic membrane bound vesicles with nucleic acids (DNA and RNA) inside their lumen that originate from the cell’s cytoplasm. They are secreted in large amounts and are found abundantly in bodily fluids. Exosome surface proteins can function as antigens for certain antibodies, which can then be utilized to isolate desired exosomes via affinity-based approaches. Exosomes generated from cancer are said to reflect the tumor microenvironment and can thus be employed as a biomarker for tumor identification [57][58]. The lipid bilayer of exosomes is made up of cholesterol, phosphatidylserine, and ceramide, as well as trans-membrane receptors, proteolytic enzymes, tetraspanins, and adhesion molecules. Some proteins that are linked to cancer are also very common on the exterior of exosomes, thus making them useful as markers for differentiating between different types of cancer. Proteins such as HER2, LMP1, and MUC18 can be used to make biosensors that can detect total exosomes.

2.4. Advantage of Use of Biomarker over the Traditional Technique

The diagnostic and predictive biological markers of cancer are the future of clinical cancer management. These biomarkers are critical because they will be utilized to make therapeutic decisions that will save lives. Biomarkers will help doctors make decisions about cancer treatment in the future. It is necessary to discover biomarkers that accurately predict the prognosis of a particular disease and allow clinicians and patients to make correct treatment decisions. In the absence of viable treatments, the consensus about cancer diagnostics has been that early detection, followed by surgical surgery before the tumor had progressed, was the best approach to cancer. Few novel diagnostic biomarkers have evolved, despite the success of traditional approaches, such as biopsy, vital staining, and imaging techniques, in the early identification of cancer. A noninvasive saliva or serum biomarkers that properly predicts cancer prognosis is still needed. Patients’ cancer is still being detected too late and treated without knowing if their tumor has progressed beyond its initial stage. Biomarkers will not only assist screen, detect, diagnose, aid in prognostic assessment, monitor therapy, and forecast recurrence over the next few decades, but they will also play an important role in medical decision making. Markers that indicate responsiveness to a specific therapy are, in fact, required.

References

  1. Mehrotra, R.; Gupta, D.K. Exciting new advances in oral cancer diagnosis: Avenues to early detection. Head Neck Oncol. 2011, 3, 33.
  2. Speight, P.M.; Epstein, J.; Kujan, O.; Lingen, M.W.; Nagao, T.; Ranganathan, K.; Vargas, P. Screening for oral cancer—A perspective from the Global Oral Cancer Forum. Oral Surg. Oral Med. Oral Pathol. Oral Radiol. 2017, 123, 680–687.
  3. Mascolo, M.; Siano, M.; Ilardi, G.; Russo, D.; Merolla, F.; De Rosa, G.; Staibano, S. Epigenetic disregulation in oral cancer. Int. J. Mol. Sci. 2012, 13, 2331–2353.
  4. Galeano, M.; Altavilla, D.; Cucinotta, D.; Russo, G.T.; Calò, M.; Bitto, A.; Marini, H.; Marini, R.; Adamo, E.B.; Seminara, P.; et al. Recombinant human erythropoietin stimulates angiogenesis and wound healing in the genetically diabetic mouse. Diabetes 2004, 53, 2509–2517.
  5. Siriwardena, S.B.S.M.; Tsunematsu, T.; Qi, G.; Ishimaru, N.; Kudo, Y. Invasion-related factors as potential diagnostic and therapeutic targets in oral squamous cell carcinoma—A review. Int. J. Mol. Sci. 2018, 19, 1462.
  6. Sahibzada, H.A.; Khurshid, Z.; Khan, R.S.; Naseem, M.; Siddique, K.M.; Mali, M.; Zafar, M.S. Salivary IL-8, IL-6 and TNF-α as potential diagnostic biomarkers for oral cancer. Diagnostics 2017, 7, 21.
  7. Chuang, J.-Y.; Huang, Y.-L.; Yen, W.-L.; Chiang, I.-P.; Tsai, M.-H.; Tang, C.-H. Syk/JNK/AP-1 signaling pathway mediates interleukin-6-promoted cell migration in oral squamous cell carcinoma. Int. J. Mol. Sci. 2014, 15, 545–559.
  8. Ho, M.T.; Kang, H.S.; Huh, J.S.; Kim, Y.M.; Lim, Y.; Cho, M. Effects of the novel compound DK223 (hydrazine) on migration and proliferation of human keratinocytes and primary dermal fibroblasts. Int. J. Mol. Sci. 2014, 15, 13091–13110.
  9. Hameedaldeen, A.; Liu, J.; Batres, A.; Graves, G.S.; Graves, D.T. FOXO1, TGF-β regulation and wound healing. Int. J. Mol. Sci. 2014, 15, 16257–16269.
  10. Cervino, G.; Fiorillo, L.; Laino, L.; Herford, A.S.; Lauritano, F.; Giudice, G.L.; Famà, F.; Santoro, R.; Troiano, G.; Iannello, G.; et al. Oral health impact profile in celiac patients: Analysis of recent findings in a literature review. Gastroenterol. Res. Pract. 2018, 2018, 7848735.
  11. Majtan, J.; Jesenak, M. β-Glucans: Multi-functional modulator of wound healing. Molecules 2018, 23, 806.
  12. Seo, G.Y.; Hyun, C.; Koh, D.; Park, S.; Lim, Y.; Kim, Y.M.; Cho, M. A novel synthetic material, BMM, accelerates wound repair by stimulating re-epithelialization and fibroblast activation. Int. J. Mol. Sci. 2018, 19, 1164.
  13. Ligi, L.; Croce, G.; Mosti, J.; Raffetto, D.; Mannello, F. Chronic venous insufficiency: Transforming growth factor-β isoforms and soluble endoglin concentration in different states of wound healing. Int. J. Mol. Sci. 2017, 18, 2206.
  14. Horng, H.-C.; Chang, W.-H.; Yeh, C.-C.; Huang, B.-S.; Chang, C.-P.; Chen, Y.-J.; Tsui, K.-H.; Wang, P.-H. Estrogen effects on wound healing. Int. J. Mol. Sci. 2017, 18, 2325.
  15. Cicciù, M.; Herford, A.S.; Cervino, G.; Troiano, G.; Lauritano, F.; Laino, L. Tissue fluorescence imaging (VELscope) for quick non-invasive diagnosis in oral pathology. J. Craniofacial Surg. 2017, 28, e112–e115.
  16. Weinberg, M.A.; Estefan, D.J. Assessing oral malignancies. Am. Fam. Physician 2002, 65, 1–5.
  17. Mangalath, U.; Mikacha, M.K.; Abdul Khadar, A.H.; Aslam, S.; Francis, P.; Kalathingal, J. Recent trends in prevention of oral cancer. J. Int. Soc. Prev. Community Dent. 2014, 4, 131.
  18. Dascalu, I.T. Histopathological aspects in oral squamous cell carcinoma. J. Dent. Sci. 2018, 3, 000173.
  19. Hasan, S.; Elongovan, S. Conventional and advanced diagnostic aids in oral cancer screening—The journey so far. Int. J. Pharm. Pharmaceut. Sci. 2015, 7, 29–33.
  20. Sreeshyla, H.; Sudheendra, U.; Shashidara, R. Vital tissue staining in the diagnosis of oral precancer and cancer: Stains, technique, utility, and reliability. Clin. Cancer Investig. J. 2014, 3, 141.
  21. Nagaraju, K.; Prasad, S.; Ashok, L. Diagnostic efficiency of toluidine blue with Lugol’s iodine in oral premalignant and malignant lesions. Indian J. Dent. Res. 2010, 21, 223.
  22. Chaudhari, A.; Hegde-Shetiya, S.; Shirahatti, R.; Agrawal, D. Comparison of different screening methods in estimating the prevalence of precancer and cancer amongst male inmates of a jail in Maharashtra, India. Asian Pac. J. Cancer Prev. 2013, 14, 859–864.
  23. Mehrotra, R.; Mishra, S.; Singh, M.; Singh, M. The efficacy of oral brush biopsy with computer-assisted analysis in identifying precancerous and cancerous lesions. Head Neck Oncol. 2011, 3, 39.
  24. Jaitley, S.; Agarwal, P.; Upadhyay, R. Role of oral exfoliative cytology in predicting premalignant potential of oral submucous fibrosis: A short study. J. Cancer Res. Ther. 2015, 11, 471–474.
  25. Shaila, M.; Shetty, P.; Pai, P. A new approach to exfoliative cytology: A comparative cytomorphometric study. Indian J. Cancer 2016, 53, 193.
  26. Sylvie, A.L.; Hagen, K.B.E. Oral soft tissue biopsy:an overview. J. Can. Dent. Assoc. 2012, 78, c75.
  27. Zargaran, M. A review of biopsy in dentistry: Principles, techniques, and considerations. J. Dent. Mater. Tech. 2014, 3, 47–54.
  28. Pałasz, P.; Adamski, Ł.; Gorska-Chrząstek, M.; Starzynska, A.; Studniarek, M. Contemporary diagnostic imaging of oral squamous cell carcinoma – a review of literature. Pol. J. Radiol. 2017, 82, 193–202.
  29. Koontongkaew, S. The tumor microenvironment contribution to development, growth, invasion and metastasis of head and necksquamous cell carcinomas. J. Cancer 2013, 4, 66–83.
  30. Stransky, N.; Egloff, A.M.; Tward, A.D.; Kostic, A.D.; Cibulskis, K.; Sivachenko, A.; Kryukov, G.V.; Lawrence, M.S.; Sougnez, C.; McKenna, A.; et al. The mutational landscape of head and neck squamous cell carcinoma. Science 2011, 333, 1157–1160.
  31. Soon, W.W.; Hariharan, M.; Snyder, M.P. High-throughput sequencing for biology and medicine. Mol. Syst. Biol. 2013, 9, 640.
  32. Li, R.; Faden, D.L.; Fakhry, C.; Langelier, C.; Jiao, Y.; Wang, Y.; Wilkerson, M.D.; Pedamallu, C.S.; Old, M.; Lang, J.; et al. Clinical, genomic and metagenomic characterization of oral tongue squamous cell carcinoma in patients who do not smoke. Head Neck 2014, 37, 1642–1649.
  33. Pickering, C.R.; Zhang, J.; Yoo, S.Y.; Bengtsson, L.; Moorthy, S.; Neskey, D.M.; Zhao, M.; Alves, M.V.O.; Chang, K.; Drummond, J.; et al. Integrative genomic characterization of oral squamous cell carcinoma identifies frequent somatic drivers. Cancer Discov. 2013, 3, 770–781.
  34. Ohnishi, Y.; Watanabe, M.; Wato, M.; Tanaka, A.; Kakudo, K.; Nozaki, M. Cyclin D1 expression is correlated with cell differentiation and cell proliferation in oral squamous cell carcinomas. Oncol. Lett. 2014, 7, 1123–1127.
  35. Pushalkar, S.; Mane, S.P.; Ji, X.; Li, Y.; Evans, C.; Crasta, O.R.; Morse, D.; Meagher, R.; Singh, A.; Saxena, D. Microbial diversity in saliva of oral squamous cell carcinoma. FEMS Immunol. Med. Microbiol. 2011, 61, 269–277.
  36. Pushalkar, S.; Ji, X.; Li, Y.; Estilo, C.; Yegnanarayana, R.; Singh, B.; Li, X.; Saxena, D. Comparison of oral microbiota in tumor and non-tumor tissues of patients with oral squamous cell carcinoma. BMC Microbiol. 2012, 12, 144.
  37. Rivera, C.; Venegas, B. Histological and molecular aspects of oral squamous cell carcinoma (Review). Oncol. Lett. 2014, 8, 7–11.
  38. Brinkman, B.M.; Wong, D.T. Disease mechanism and biomarkers of oral squamous cell carcinoma. Curr. Opin. Oncol. 2006, 18, 228–233.
  39. Shamaa, A.A.; Zyada, M.M.; Wagner, M.; Awad, S.S.; Osman, M.M.; Abdel Azeem, A.A. The significance of Epstein Barr virus (EBV) & DNA topoisomerase II alpha (DNA-Topo II alpha) immunoreactivity in normal oral mucosa, oral epithelial dysplasia (OED) and oral squamous cell carcinoma (OSCC). Diagn. Pathol. 2008, 3, 45.
  40. Kim, K.Y.; Cha, I.H. Possibility of the use of public microarray database for identifying significant genes associated with oral squamous cell carcinoma. Genom. Inform. 2012, 10, 23–32.
  41. Neville, B.W.; Day, T.A. Oral cancer and precancerous lesions. CA Cancer J. Clin. 2002, 52, 195–215.
  42. Rentoft, M.; Coates, P.J.; Loljung, L.; Wilms, T.; Laurell, G.; Nylander, K. Expression of CXCL10 is associated with response to radiotherapy and overall survival in squamous cell carcinoma of the tongue. Tumor Biol. 2014, 35, 4191–4198.
  43. Lajer, C.B.; Nielsen, F.C.; Friis-Hansen, L.; Norrild, B.; Borup, R.; Garnaes, E.; Rossing, M.A.; Specht, L.; Therkildsen, M.H.; Nauntofte, B.; et al. Different miRNA signatures of oral and pharyngeal squamous cell carcinomas: A prospective translational study. Br. J. Cancer 2011, 104, 830–840.
  44. Wiklund, E.D.; Gao, S.; Hulf, T.; Sibbritt, T.; Nair, S.; Costea, D.E.; Villadsen, S.B.; Bakholdt, V.; Bramsen, J.B.; Sørensen, J.A.; et al. MicroRNA alterations and associated aberrant DNA methylation patterns across multiple sample types in oral squamous cell carcinoma. PLoS ONE 2011, 6, e27840.
  45. Gibb, E.A.; Enfield, K.S.; Stewart, G.L.; Lonergan, K.M.; Chari, R.; Ng, R.T.; Zhang, L.; MacAulay, C.E.; Rosin, M.P.; Lam, W.L. Long non-coding RNAs are expressed in oral mucosa and altered in oral premalignant lesions. Oral Oncol. 2011, 47, 1055–1061.
  46. Herrmann, P.C.; Liotta, L.A.; Petricoin, E.F. Cancer proteomics: The state of the art. Dis. Markers 2001, 17, 49–57.
  47. Turhani, D.; Krapfenbauer, K.; Thurnher, D.; Langen, H.; Fountoulakis, M. Identification of differentially expressed, tumor-associated proteins in oral squamous cell carcinoma by proteomic analysis. Electrophoresis 2006, 27, 1417–1423.
  48. Wu, J.Y.; Yi, C.; Chung, H.R.; Wang, D.J.; Chang, W.C.; Lee, S.-Y.; Lin, C.-T.; Yang, Y.-C.; Yang, W.-C.V. Potential biomarkers in saliva for oral squamous cell carcinoma. Oral Oncol. 2010, 46, 226–231.
  49. Mlynarek, A.M.; Balys, R.L.; Su, J.; Hier, M.P.; Black, M.J.; Alaoui-Jamali, M.A. A cell proteomic approach for the detection of secretable biomarkers of invasiveness in oral squamous cell carcinoma. Arch. Otolaryngol. Head Neck Surg. 2007, 133, 910–918.
  50. Lo, W.Y.; Tsai, M.H.; Tsai, Y.; Hua, C.H.; Tsai, F.J.; Huang, S.Y.; Tsai, C.-H.; Lai, C.-C. Identification of over-expressed proteins in oral squamous cell carcinoma (OSCC) patients by clinical proteomic analysis. Clin. Chim. Acta 2007, 376, 101–107.
  51. Lo, W.Y.; Lai, C.C.; Hua, C.H.; Tsai, M.H.; Huang, S.Y.; Tsai, C.H.; Tsai, F.-J. S100A8 is identified as a biomarker of HPV18-infected oral squamous cell carcinomas by suppression subtraction hybridization, clinical proteomics analysis, and immunohistochemistry staining. J. Proteome Res. 2007, 6, 2143–2151.
  52. Lai, C.H.; Chang, N.W.; Lin, C.F.; Lin, C.D.; Lin, Y.J.; Wan, L.; Lin, C.W. Proteomics-based identification of haptoglobin as a novel plasma biomarker in oral squamous cell carcinoma. Clin. Chim. Acta 2010, 411, 984–991.
  53. Shintani, S.; Hamakawa, H.; Ueyama, Y.; Hatori, M.; Toyoshima, T. Identification of a truncated cystatin SA-I as a saliva biomarker for oral squamous cell carcinoma using the SELDI ProteinChip platform. Int. J. Oral Maxillofac. Surg. 2010, 39, 68–74.
  54. Negishi, A.; Masuda, M.; Ono, M.; Honda, K.; Shitashige, M.; Satow, R.; Sakuma, T.; Kuwabara, H.; Nakanishi, Y.; Kanai, Y.; et al. Quantitative proteomics using formalin-fixed paraffin-embedded tissues of oral squamous cell carcinoma. Cancer Sci. 2009, 100, 1605–1611.
  55. Jancsik, V.A.; Gelencser, G.; Maasz, G.; Schmidt, J.; Molnar, G.A.; Wittmann, I.; Olasz, L.; Mark, L. Salivary proteomic analysis of diabetic patients for possible oral squamous cell carcinoma biomarkers. Pathol. Oncol. Res. 2014, 20, 591–595.
  56. Sivadasan, P.; Palit, P.; Pinto, S.; Sekhar, N.; Harsha, H.C.; Pandey, A.; Suresh, A.; Hicks, W., Jr.; Gupta, V.; Sirdeshmukh, R.; et al. Salivary proteome for diagnosis and prognosis of oral cancer. Oral Oncol. 2013, 49, S27.
  57. Sharma, S.; Zuniga, F.; Rice, G.E.; Perrin, L.C.; Hooper, J.D.; Salomon, C. Tumor-derived exosomes in ovarian cancer - liquid biopsies for early detection and realtime monitoring of cancer progression. Oncotarget 2017, 8, 104687–104703.
  58. Cheng, N.; Du, D.; Wang, X.; Liu, D.; Xu, W.; Luo, Y.; Lin, Y. Recent advances in biosensors for detecting cancer-derived exosomes. Trends Biotechnol. 2019, 37, 1236–1254.
More
© Text is available under the terms and conditions of the Creative Commons Attribution (CC BY) license (http://creativecommons.org/licenses/by/4.0/)
Video Production Service
Feedback