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Microrna deregulation within optically altered oral cancer fields of non-smoker patients. Gorenchtein, Mike 2016

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		MICRORNA DEREGULATION WITHIN OPTICALLY ALTERED ORAL CANCER FIELDS OF NON-SMOKER PATIENTS     by   Mike Gorenchtein   B.M., B.S. University of Limerick Graduate Entry Medical School, 2016  B. Sc. The University of British Columbia, 2009        A THESIS SUBMITTED IN PARTIAL FULFILLMENT OF THE REQUIREMENTS FOR THE DEGREE OF MASTER OF SCIENCE   in   THE FACULTY OF GRADUATE AND POSTDOCTORAL STUDIES  (Interdisciplinary Oncology)      THE UNIVERSITY OF BRITISH COLUMBIA  (Vancouver)       October, 2016    © Mike Gorenchtein, 2016	ii		Abstract BACKGROUND: Oral cancer is a devastating disease with a five-year survival rate of 50%. While tobacco remains a key etiological factor for oral cancer, cases in non-smoker patients are also reported. An improved understanding of the molecular basis of oral cancer, including the alterations contributing to disease in non-smokers, is essential. To date, the role of microRNAs (miRNAs) in oral tumorigenesis – and oral premalignant lesions specifically, is largely unknown. The objectives of this study were (1) to identify miRNAs that are deregulated at the premalignant and malignant stages of oral cancer in non-smoker patients, and (2) to elucidate their expression patterns throughout disease progression.  METHODS: To remove variation due to timing differences in sampling, we analyzed global miRNA expression in varied stages of precancerous, cancerous and adjacent normal tissue biopsies obtained simultaneously from a single, contiguous field in a patient’s mouth. Total RNA was isolated from each microdissected specimen and profiled for the expression of 742 human miRNAs using Real-Time PCR. The expression of selected candidate miRNAs was further validated in an independent cohort of premalignant and malignant tissues via in situ hybridization (ISH).   RESULTS: Overall, the amount of miRNA alterations was associated with lesion severity, suggesting that miRNA changes are accumulated during premalignant progression. In addition, we have identified distinct lists of candidate miRNAs that were consistently deregulated at specific histopathological disease states. Examination of the individual expression profiles of 	iii		these candidates across sequential premalignant/malignant stages demonstrated that they follow distinct patterns of deregulation over time and may therefore function differently throughout oral tumorigenesis. ISH staining for one of the selected up-regulated candidates, miR-155, corresponded with its previous Real-Time PCR expression data and was further validated in independent dysplastic and malignant tissues.        CONCLUSIONS: Our unique sample set allowed us to investigate intralesional progression within a single surgical field and delineate miRNA aberrations that may be driving this process. Collectively, our results suggest that miR-155 may represent a key driver of oral tumorigenesis and that molecular heterogeneity across fields of diseased tissue has significant implications when selecting candidates for development of novel targeted therapies or prognostic screening protocols.        	iv		Preface The hypotheses and study designs in this study were researched and developed by Mike Gorenchtein following approval by Dr. Cathie Garnis. Other Garnis Lab members involved in this study were: Rebecca M. Towle, Angie Chu, Danielle Truong, Sara Maclellan and Christopher Dickman. In addition, this project was performed in collaboration with Dr. Catherine F. Poh’s Lab, with key contribution from Yuqi Zhu, Cindy Cui and Dr. Poh herself.  Mike Gorenchtein was responsible for formulating the original hypotheses and the overall design of this project (with the guidance of Dr. Garnis), and performed all the involved miRNA quantification and analysis, as well as the subsequent individual microRNA PCR experiments. With assistance from Yuqi Zhu and Danielle Truong, Mike carried out the entire optimization of the in situ hybridization (ISH) staining procedure, specific to the miRNA probes used. Mike performed all the tissue microarray (TMA) staining experiments for the verification and validation of candidate miRNA expression levels in diseased specimen. Interpretation of ISH staining results via light microscopy was conducted under the expertise of Yuqi Zhu and Dr. Poh. Finally, Mike wrote the entire thesis and part of the research manuscript arising from this work.   All tissue biopsies were evaluated, microdissected and kindly provided by Dr. Poh. Extractions of total RNA from microdissected tissue specimen were shared between Mike, Rebecca M. Towle and Angie Chu. Sara Maclellan and Christopher Dickman assisted in performing the proper statistical analysis on the miRNA expression data. Yuqi Zhu and Cindy Cui were responsible for construction of the TMAs used to verify and validate the expression of candidate miRNAs. 	v		A version of Chapter 2 has been published. Gorenchtein M, Poh CF, Saini R, Garnis C. (2012) MicroRNAs in an oral cancer context - from basic biology to clinical utility. J Dent Res. 91:440-446. Mike wrote the majority of the manuscript. A version of Chapter 3 and 4 has been submitted as a manuscript for peer review as: Dysregulation of microRNAs across oral cancer fields in non-smokers. Gorenchtein M, Towle RM, Dickman C, Zhu Y, Poh CF, Garnis C. Mike conducted the majority of all the experiments and wrote part of the manuscript. Additional manuscript editing was largely performed by Towle RM and Dickman C. For Figures 8 and 9, ISH staining experiments for miR-155 expression in biopsied tissue samples were conducted by Mike. The corresponding white light and fluorescence visualization clinical images, as well as the matched hematoxylin and eosin slides, were kindly provided by Dr. Poh. Additional editing to the figure was performed by Rebecca M. Towle. The work described in this thesis was approved by the Research Ethics Board of the University of British Columbia BC Cancer Agency. Human Ethics Certificate Number: H09-00018.      	vi		Table of Contents Abstract ........................................................................................................................................... ii Preface ............................................................................................................................................ iv Table of Contents ........................................................................................................................... vi List of Tables .................................................................................................................................. x List of Figures ................................................................................................................................ xi List of Abbreviations ................................................................................................................... xiv Acknowledgements ...................................................................................................................... xvi Dedication .................................................................................................................................. xviii 1. Oral Cancer ................................................................................................................................. 1 1.1 Oral Cancer (Definition & Epidemiology) ............................................................................ 1 1.2 Etiology and Risk Factors for Oral Cancer ........................................................................... 1 1.2.1 Tobacco Use and the Risk of Oral Cancer ..................................................................... 1 1.2.2 Alcohol and Oral Cancer ................................................................................................ 2 1.2.3 Microorganisms and Oral Cancer ................................................................................... 3 1.2.4 Diet and Nutrition in the Etiology of Oral Cancer ......................................................... 4 1.3 Oral Cavity Major Subsites and their Implication in the Clinical Pathology of Oral Cancer 5 1.3.1 Lips ................................................................................................................................. 5 1.3.2 Tongue ............................................................................................................................ 6 	vii		1.3.3 Floor of the Mouth .......................................................................................................... 7 1.3.4 Hard and Soft Palates ..................................................................................................... 7 1.3.5 Upper and Lower Alveolar Ridges ................................................................................. 8 1.3.6 Retromolar Trigone ........................................................................................................ 9 1.3.7 Buccal Mucosa ............................................................................................................... 9 1.4 Histology of the Oral Mucosa during Premalignant and Malignant States ......................... 10 1.5 The Molecular Biology of Oral Cancer ............................................................................... 11 1.5.1 Molecular and Genetic Aspects of Oral Carcinogenesis .............................................. 11 1.5.2 A Genetic Progression Model for Oral Cancer ............................................................ 12 1.5.3 Distinct Molecular Behavior of Oral Cancer in Non-Smoker Patients ........................ 13 1.6 Local Recurrence, Second Primary Tumors and Field Cancerization ................................ 14 2. MicroRNAs ............................................................................................................................... 17 2.1 MiRNA Discovery .............................................................................................................. 17 2.2 MiRNA Biogenesis and Function ....................................................................................... 18 2.3 Detection of MiRNAs in Human Specimens ...................................................................... 20 2.4 MiRNA Behaviors in Cancer .............................................................................................. 22 2.5 Mechanisms of MiRNA Dysregulation in Cancer .............................................................. 23 2.6 MiRNAs in Oral Tumorigenesis ......................................................................................... 26 2.7 Clinical Utility of Oral Cancer-Associated MiRNAs ......................................................... 32 2.8 MiRNAs and Treatment of Malignancy .............................................................................. 34 	viii		2.9 Thesis Theme and Rationale for Study ............................................................................... 35 2.10 Objectives and Hypotheses ............................................................................................... 36 2.11 Thesis Outline ................................................................................................................... 36 3. Methodology ............................................................................................................................. 37 3.1 Study Population ................................................................................................................. 37 3.2 Sample Accrual ................................................................................................................... 37 3.3 RNA Isolation and MiRNA Expression Quantification ...................................................... 38 3.4 Universal Real Time PCR ................................................................................................... 39 3.4.1 MiRNA Expression Profiling Analysis ........................................................................ 39 3.4.2 Verification of Deregulated miRNA Candidates through Individual PCR Assays ...... 39 3.5 In Situ Hybridization (ISH) ................................................................................................. 40 3.5.1 Use of ISH for the Detection of MiRNAs in Human FFPE Tissues ............................ 40 3.5.2 Development of Tissue Microarrays (TMAs) for Verification and Validation of Candidate MiRNA Deregulation ........................................................................................... 41 3.6 Statistical Analysis .............................................................................................................. 42 4. Results ....................................................................................................................................... 43 4.1 Differential MiRNA Expression in Oral Cancer Progression ............................................. 43 4.2 MicroRNA Dysregulation throughout Oral Cancer Progression ........................................ 47 4.3 Selection of Candidate MiRNAs associated with OPLs and OSCC ................................... 56 4.4 Confirmation of Candidate MiRNA Expression ................................................................. 75 	ix		4.5 ISH Analysis ....................................................................................................................... 79 5. Conclusions ............................................................................................................................... 82 5.1 Discussion and Future Perspectives .................................................................................... 82 5.2 Conclusion ........................................................................................................................... 86 Bibliography ................................................................................................................................. 87             	x		List of Tables Table 1. MiRNA Candidates in Oral Cancer with Potential Clinical Utility ................................ 29 Table 2. Patient Clinicopathological Information ......................................................................... 44 Table 3. Trends in MiRNA Expression Across Individual Patient Cases .................................... 55 Table 4A. Deregulated MiRNAs across the Dysplastic Tissue Cohort ........................................ 58 Table 4B. Deregulated MiRNAs across the CIS/OSCC Tissue Cohort ....................................... 59 Table 4C. Deregulated MiRNAs across both Dysplastic and CIS/OSCC Tissue Cohorts ........... 60 Table 5A. Comparison of 384-well Full Panel qRT-PCR Results with Individual Primer Assay Runs in Patient Case 2000 ............................................................................................................ 76 Table 5B. Comparison of 384-well Full Panel qRT-PCR Results with Individual Primer Assay Runs in Patient Case 2076 ............................................................................................................ 77 Table 5C. Comparison of 384-well Full Panel qRT-PCR Results with Individual Primer Assay Runs in Patient Case 7071 ............................................................................................................ 78      	xi		List of Figures Figure 1. Key Features of MiRNA Biogenesis and Function ....................................................... 19 Figure 2. Mechanisms of MiRNA Deregulation in Cancer .......................................................... 25 Figure 3. MiRNA Expression through Progressive Oral Cancer Stages ...................................... 45 Figure 4. General Trends in MiRNA Detection Across Oral Cancer Progression ....................... 46 Figure 5A. MiRNA Deregulation (Up-Regulation and Down-Regulation) ................................. 49 Figure 5B. MiRNA Up-Regulation ............................................................................................... 50 Figure 5C. MiRNA Down-Regulation .......................................................................................... 51 Figure 6A. Case-by-Case Trends in MiRNA Overall Deregulation (Up-Regulation and Down-Regulation) .................................................................................................................................... 52 Figure 6B. Case-by-Case Trends in MiRNA Up-Regulation ....................................................... 53 Figure 6C. Case-by-Case Trends in MiRNA Down-Regulation .................................................. 54 Figure 7A. Up-Regulation Profile of MiR-223 Across Successive Case-Matched Histopathological Tissues ............................................................................................................. 61 Figure 7B. Down-Regulation Profile of MiR-375 Across Successive Case-Matched Histopathological Tissues ............................................................................................................. 62 Figure 7C. Expression Profile of MiR-142-3p Across Successive Case-Matched Histopathological Tissues ............................................................................................................. 63 Figure 7D. Expression Profile of MiR-146a Across Successive Case-Matched Histopathological Tissues ........................................................................................................................................... 64 	xii		Figure 7E. Expression Profile of MiR-21 Across Successive Case-Matched Histopathological Tissues ........................................................................................................................................... 65 Figure 7F. Expression Profile of MiR-424 Across Successive Case-Matched Histopathological Tissues ........................................................................................................................................... 66 Figure 7G. Expression Profile of MiR-155 Across Successive Case-Matched Histopathological Tissues ........................................................................................................................................... 67 Figure 7H. Expression Profile of MiR-150 Across Successive Case-Matched Histopathological Tissues ........................................................................................................................................... 68 Figure 7I. Expression Profile of MiR-886-5p Across Successive Case-Matched Histopathological Tissues ........................................................................................................................................... 69 Figure 7J. Expression Profile of MiR-135a Across Successive Case-Matched Histopathological Tissues ........................................................................................................................................... 70 Figure 7K. Expression Profile of MiR-204 Across Successive Case-Matched Histopathological Tissues ........................................................................................................................................... 71 Figure 7L. Expression Profile of MiR-605 Across Successive Case-Matched Histopathological Tissues ........................................................................................................................................... 72 Figure 7M. Expression Profile of MiR-720 Across Successive Case-Matched Histopathological Tissues ........................................................................................................................................... 73 Figure 7N. Expression Profile of MiR-1260 Across Successive Case-Matched Histopathological Tissues ........................................................................................................................................... 74 	xiii		Figure 8. Clinical Characterization and Corresponding Histology within an Oral Cancer Field of Patient Case 7071 .......................................................................................................................... 80 Figure 9. Validation of MiR-155 Expression via ISH TMA Staining .......................................... 81                	xiv		List of Abbreviations 3'UTR 3' Untranslated Region AGO2 Argonaute 2 cDNA Complementary DNA CIS Carcinoma in situ DNA Deoxyribonucleic Acid FFPE Formalin-Fixed Paraffin Embedded HNSCC Head and Neck Squamous Cell Carcinoma HPV Human Papillomavirus LNA Locked Nucleic Acid LOH Loss of Heterozygosity miRNA microRNA              mm Millimeters  NGS Next Generation Sequencing OPL Oral Premalignant Lesion OSCC Oral Squamous Cell Carcinoma PCR Polymerase Chain Reaction Pol II RNA Polymerase II qRT-PCR Quantitative Real-Time PCR RISC RNA-Induced Silencing Complex RNA Ribonucleic Acid SCC Squamous Cell Carcinoma 	xv		SPT Second Primary Tumor TSCC Tongue Squamous Cell Carcinoma 	          					xvi		Acknowledgements I would like to express my deepest thanks to my supervisor, Dr. Cathie Garnis, for believing in me and taking the chance allowing me to pursue my project. I thank her for the excellent mentoring, guidance, help and for equipping herself with lots of patience when it was most needed. I am thankful to other members of my committee, Dr. Catherine F. Poh and Dr. Torsten O. Nielsen. I thank them for finding the time in their busy schedules to meet with me and guide me through my project.  My thanks also go to members of the Garnis Lab and the closely collaborating Poh Lab. First and foremost, my gratitude goes to Danielle Truong and Rebecca M. Towle. This project would not have been possible without them. I particularly thank them for helping me with the extensive laboratory work required in my studies. I also wish to express my sincere gratitude and appreciation to Yuqi Zhu and Cindy Cui, who unconditionally provided me with processed patient specimen and invaluable guidance on many of the techniques used in this project. I am immensely thankful to Dr. Rajan Saini for teaching me a great deal about project design, translational research, and for being a good friend. Thank you also goes to all the other members of the Garnis Lab who believed in me and were willing to discuss the project at any time during their busy schedule: Sara Maclellan, Marina Laissus, Angie Chu, Shevaun Hughes, James Lawson, and Jamil Manji. I am grateful to Dr. Timon P. Buys for his continuous support and assistance on many of the works completed throughout my graduate studies. I would like to thank the Interdisciplinary Oncology Program (IOP) and the College for Interdisciplinary Studies (CFIS) for their financial support of my research endeavors.  	xvii		Finally, I would like to express loving thanks to my family and all of my dear friends, without whose support I would have never gone this far.                 	xviii		Dedication          To all my family.       	1		1. Oral Cancer 1.1 Oral Cancer (Definition & Epidemiology) Oral cancer is one of the most common malignancies worldwide and is the most prevalent subtype of head and neck cancer1,2.  It originates from multiple sites of the oral cavity and oropharynx, with tongue cancer being the primary dominant form. In Canada last year, there have been 4,400 estimated new cases of oral cancer and 1,200 deaths, representing 24.4% of all new cases and 1.5% of all cancer deaths3. The five-year survival rate for this malignancy has remained at a dismal 50% – largely due to frequent late stages of diagnosis and high rates of tumor recurrence3,4. Globally, a much higher prevalence of oral cancer is reported in South East Asia countries (e.g. Sri Lanka and Taiwan) and certain Pacific countries (e.g. Papua New Guinea). These geographical variations are mainly due to the type and pattern of tobacco use and areca nut chewing. In industrialized countries, men are two or three times more likely to develop oral cancer in comparison to women, primarily due to their greater indulgence in key risk factors, such as tobacco and alcohol consumption2. However, these trends equalize between the sexes in high-incidence areas worldwide, where tobacco chewing and smoking habits are just as common amongst women as in men.  1.2 Etiology and Risk Factors for Oral Cancer 1.2.1 Tobacco Use and the Risk of Oral Cancer The use of tobacco in its various forms remains the leading etiological factor for oral cancer1,2,5,6. Aside from cigarette smoke, large quantities of tobacco are consumed by being 	2		placed into contact with mucous membranes, allowing the absorption of nicotine2,6. The predominant form of smokeless tobacco in North America is prepared in blocks or flakes for chewing. In developing countries, mixtures of tobacco and additional ingredients are preferred, with betel quid being the most common preparation. Betel quid is composed of betel leaf, areca nut, slaked lime and tobacco (preparations without tobacco also exist), and is deeply embedded in the social structure of multiple South Asian countries (e.g. India, Sri Lanka, and Bangladesh), as well as emigrant communities from these countries2,6. A plethora of carcinogens has been identified in tobacco smoke and chewable tobacco, including polycyclic aromatic hydrocarbons and tobacco-specific nitrosamines [e.g. N-nitrosonornicotine (NNN) and 4-(methylnitrosamino)-1-(3-pyridyl)-1-butanone (NNK)]2,5,6. The metabolism of these products within oral mucosa cells is believed to result in DNA adducts that interfere with DNA replication and lead to mutations associated with malignant transformation. It is also important to note that areca nut alone is classified as an independent risk factor for oral carcinogenesis2,6. Primarily, this is due to the content of nitrosamine products and polyphenols in areca nut, the latter of which generate reactive oxygen species following auto-oxidation in the oral cavity.   1.2.2 Alcohol and Oral Cancer Alcohol consumption, including binge drinking, has been on the rise in much of the western world and is a major public concern2,6. A substantial amount of evidence now exists to confirm alcohol consumption as a separate chief risk factor for oral cancer despite removal of the effects from tobacco7-10. Alcoholic beverages are mainly composed of ethanol and water, with varied amounts of impurities depending on the type of beverage2,6. Acetaldehyde is the immediate 	3		metabolite of ethanol via oxidation by alcohol dehydrogenase that is present in oral epithelia and bacteria residing in the oral cavity. The action of acetaldehyde is responsible for most of the mutagenic effects of alcohol while further damage can incur from impurities such as polycyclic aromatic hydrocarbons and nitrosamines. Moreover, ethanol in its raw form damages the phospholipid bilayer of cell membranes, thereby increasing the permeability of oral mucosa to tobacco-specific carcinogens in individuals that smoke or chew tobacco. Alcohol also acts as a water-soluble solvent that allows more efficient distribution of harmful tobacco substances throughout the oral tissue. Because alcohol is high in calories, it suppresses appetite in heavy drinkers and consequently the consumption of nutritional foods such as fruits and vegetables. Lastly, as a hepatotoxic substance, alcohol reduces the effectiveness of crucial enzyme systems required for the detoxification of drugs and carcinogens (e.g. the cytochrome P450 system). An interesting area of research is centralized around the potential linkage between alcohol-containing mouthwashes and the risk of oral cancer2,6,11. The plausible underlying mechanisms of carcinogenesis are hypothesized to follow the same route as in drinkable alcohol, with ethanol and acetaldehyde being the primary drivers. Despite inconsistent epidemiological findings regarding this topic, it seems reasonable to keep mouthwash formulations with alcohol content that is as low as possible2.  1.2.3 Microorganisms and Oral Cancer It is obvious that other factors are responsible for the development of oral neoplasms in lifelong abstainers from tobacco and alcohol. Numerous viruses have been shown to play a role in oral carcinogenesis, with association between the human papillomavirus (HPV) being one of 	4		the most well-described2,6. HPV-16 is the prevalent HPV strain linked to oral malignancies2,6,11. HPV-positive oral tumors exhibit different clinical and molecular characteristics in comparison to their HPV-negative counterparts. For instance, patients with HPV-positive lesions respond better to surgery, radiation and chemotherapy12,13. Likewise, HPV-positive tumors rarely harbor mutations in the p53 tumor-suppressor gene and instead express its wild-type version14,15. HPV-positive tumors may therefore represent a distinct disease entity for which tailored treatment is required. The fungus Candida albicans is a common commensal of the oral cavity2,6. It becomes an opportunistic pathogen primarily during immunosuppression (caused by either the usage of pharmacological agents or underlying disease), reduction of other commensal flora or poor dental hygiene. Indeed, C. albicans has been detected in histological sections of leukoplakia, a common oral pre-cancerous state. Whether this microorganism invades potentially malignant oral lesions as a secondary event or whether it has a direct mutagenic role remains enigmatic.  1.2.4 Diet and Nutrition in the Etiology of Oral Cancer Poor diet is a well-established risk factor for numerous types of neoplasms, including oral cancer6,16. The most significant negative correlation lies between consumption of fruits and vegetables, specifically those that are rich in β-carotene and vitamins A, C, and E. These micronutrients display important antioxidant activities in reducing the accumulation of free radicals responsible for DNA mutations and lipid peroxidation of cellular membranes6. In addition, these essential elements help maintain normal cellular differentiation, proper functioning of the immune system, appropriate metabolism of exogenous carcinogens and 	5		attenuation of oncogene expression. The other potentially positive effects from healthy diet are regression of oral premalignant conditions, prevention of tumor recurrence and protection from disease initiation and progression17-20. Hence, a healthy diet or appropriate nutrient supplementation may prove especially beneficial to heavy smokers and alcohol drinkers who are already at an elevated risk of oral cancer development.  1.3 Oral Cavity Major Subsites and their Implication in the Clinical Pathology of Oral Cancer The oral cavity is divided into seven anatomic subsites: the lips, tongue, floor of the mouth, hard and soft palates, upper and lower alveolar ridges, retromolar trigone, and buccal mucosa1. The entire mucosa of the oral cavity is lined by stratified squamous epithelium, bounded inferiorly by the basal lamina and layers of connective tissue2.  Diagnosis of oral cavity neoplasms is typically established through histopathologic inspection of a biopsy1. The histology of these lesions [primarily squamous cell carcinoma (SCC)] is characterized by malignant cells that penetrate through the basement membrane of the epithelium. In addition, malignant cells exhibit morphological and cellular features that indicate aberrations in their maturation process.  1.3.1 Lips Carcinoma of the lip accounts for ~21.5% of oral cavity malignancies and is generally a slow-growing, locally advanced disease with a substantially higher incidence in males21. Previous results from a screen of 1047 lip cancer patients have demonstrated that over 90% of lesions are located in the lower lip, with the rest arising in the upper lip (~4%) and the commissures 	6		(~1%)22. Normally, the tumor appears as a papule or a plate that tends to progress into a vegetative or ulcerative form2. About three quarters of lip carcinomas are less than 2 cm in diameter, extending to adjacent skin, lip mucosa and bone. Upon diagnosis, ~10-15% of patients have metastases to the cervical lymph nodes. However, this figure increases considerably during the advanced disease stages23. While distant metastasis is fairly rare, reports of spread to the lungs, liver, skin, spleen and at times, to skeletal structures have been published21. Low survival is associated with lesions greater than 2 cm in diameter, occurrence on the upper lip and commissures, poor histological differentiation, perineural invasion, spread to the mandible, and distant and regional metastasis2. Furthermore, subjects who are less than 40 years of age are predisposed to the more lethal disease phenotypes.  1.3.2 Tongue A vast majority of oral tumors arise from the tongue epithelium. Up to 75% of these lesions occur in the anterior two-thirds, but are equivalent in severity as those arising from the posterior region24. Carcinoma of the anterior tongue generally presents as a painless, dense ulcer, appearing most frequently on the lateral border2. Since there are no real anatomical barriers in the tongue, infiltration to the floor of the mouth, gingiva, posterior region and the mandible occurs in about one-quarter of cases2. Importantly, expansion to the floor of the mouth corresponds with increased frequency of nodal metastasis. Base-of-tongue carcinoma is clinically characterized as an ulcerative-infiltrative neoplasm with the ability to spread into the anterior tongue, pre-epiglottic space, pharyngeal wall and the mandible. Moreover, base-of-tongue tumors can damage the hypoglossal nerve due to its close proximity to the extrinsic 	7		muscles of the tongue25. This in turn can lead to hemiatrophy of the tongue, as well as limitation of lateral movement and deviation of the tongue toward the side of nerve impairment upon extrusion1. To establish prognosis for tongue carcinoma cases, assessment of tumour thickness (aside from delineating disease stage) is largely recommended26.  1.3.3 Floor of the Mouth Neoplasms that originate from the floor of the mouth are only second in frequency to tongue carcinoma and are among the most aggressive types27. This behaviour is mainly due to the lack of a strong mechanical barrier and the presence of a rich lymphatic drainage system. Hence, the tumors can obstruct the submandibular duct, invade the adjacent mandible, tongue and sublingual gland, and perforate into the oropharynx2,28. According to Hicks et al., cervical nodal involvement is found in a large number of cases upon initial diagnosis and is more prominent in late disease stages27.  1.3.4 Hard and Soft Palates Carcinomas of the palate are relatively less common than those arising from the tongue or floor of the mouth29. Approximately 75% of these tumors occur in the soft palate and 25% in the hard palate2. The lesions are often evenly distributed over the palatal surface and present as lateral ulcers. At the time of diagnosis, about half of carcinomas are localized to the palate alone, while up to 30% of lesions protrude into the underlying bone, floor of the nasal cavity, maxillary sinus and gingiva. In addition, due to the extensive abundance of minor salivary glands in both the hard and soft palates, there is a high likelihood of invasion of these structures as well1. In 	8		fact, multiple sources describe the palate as the most common site of intraoral minor salivary gland tumours30-33. The probability of lymph node metastasis appears to be largely associated with primary tumour size34. For instance, the more extensive T3-T4 tumors are believed to mostly impact the retropharyngeal lymph nodes while T1-T2 tumors are proposed to favor the cervical lymph nodes34.  1.3.5 Upper and Lower Alveolar Ridges Overall, both ridge carcinomas display similar clinical behaviour2. Typical symptoms include abnormal outgrowths on the gingival margins, ulcerations with rolled borders, sockets that fail to heal after extractions, and mobility of the involved teeth35. At times, these carcinomas can be mistaken for persistent gingivitis, periodontal disease or abscess, resulting in false teeth extractions2. This misdiagnosis, as well as the small thickness of the gingiva (2-3mm) covering the ridges, often leads to invasion of the underlying bone35. Based on multiple histopathological studies, two basic patterns of bone involvement seem to exist35,36. In the infiltrative pattern, tumor cells progress irregularly through the cancellous bone, periosteum and the inferior alveolar nerve. In the less aggressive expansive pattern, the tumor advances on a broad front and a sharp tumor/bone interface. These features therefore assist clinicians to determine the extent of surgical resection. Additional major regions affected by the tumors include the hard palate, maxillary sinus, buccal mucosa (upper ridge carcinoma), floor of the mouth, tongue, and retromolar trigone (lower ridge carcinoma)2,36.  	9		1.3.6 Retromolar Trigone Carcinomas of the retromolar trigone are relatively rare, principally affecting men 50-70 years of age2,37. Due to limited surface area, lesions often present with extensions into adjacent structures at the time of discovery2. This includes the gingiva, anterior tonsillar pillars, floor of the mouth, tongue, buccogingival sulcus, buccal mucosa, and pterygoid space. Erosions through the jaw bones can also occur, with studies showing a larger predisposition towards the maxilla38. In the advanced stages, tumors permeate to the buccal, lingual, and inferior alveolar branches of the mandibular nerve and the muscles of mastication (primarily the pterygoid and masseter muscles)37,39-41. This leads to pain and trismus (inability to open the mouth). According to results from one retrospective study, the submandibular triangle and upper jugular regions often represent the most common sites of metastasis2,40. These locations are also predominantly affected by carcinomas of the lower alveolar ridge2.  1.3.7 Buccal Mucosa In India, buccal SCC is the most common subtype of oral cancer, mainly due to the prevalent habits of chewing tobacco and betel quid2,42. In these cases, sites of primary tumor development correspond to areas where the tobacco or quid is placed. Globally, tumors have a predilection for the posterior buccal mucosa, followed by the middle third and rarely, the anterior third2. Buccal SCCs generally present as slow growing, diffuse, exophytic lesions, and are often found at the level of the buccal commissures. When neoplasms become ulceroinfiltrative, they extend to the buccinator muscle and present as a deep, excavating ulcer with diffuse extensions. If left untreated, these carcinomas erode through the skin, adjacent bone and the pharyngomaxillary 	10		fossa. Regional metastasis occurs primarily in the cervical nodes, while distant metastasis can advance to the lungs, bone/rib/spine, extrafacial skin, liver, mediastinum and thyroid43,44. In addition, Pichi and colleagues have described a case of buccal SCC where ipsilateral metastasis was detected in the talus 10 months after initial intervention45.  1.4 Histology of the Oral Mucosa during Premalignant and Malignant States Of all the different types of oral cancer, oral squamous cell carcinoma (OSCC) is by far the most dominant form2. As with other epithelial tumors, malignancy develops through successive histological stages: from hyperplasia, through mild, moderate and severe dysplasia, then carcinoma in situ (CIS), and ultimately ending with invasive SCC. Hyperplasia is defined as a highly proliferative state that usually occurs in response to tissue injury2. It is characterized by thickening of the mucosal epithelial layer with full retention of the underlying basal layer. Cytological abnormalities are present at relatively low levels or are completely absent. Unlike the subsequent histological stages, hyperplasia is reversible and is not considered premalignant. Dysplasia differs from hyperplasia by multiple architectural and cytological changes in the epithelium, including loss of cell polarity, abnormal variation in cell size (anisocytosis) decreased nuclear/cytoplasmic ratio, drop-shaped rete ridges, increased number of mitotic figures, abnormal expression of keratin in single cells (dyskeratosis), irregular mitotic figures, and abnormal variation in nuclear size and shape (anisonucleosis and nuclear pleomorphism, respectively)2,46,47. The extent of these histologic atypia determines grading of the dysplasia as 	11		mild, moderate (categorized as low-grade) or severe (categorized as high-grade). Atypia is confined to the lower third of epithelial thickness in mild dysplasia, two thirds of epithelial thickness in moderate dysplasia, and between two thirds and the entire epithelial thickness in severe dysplasia47. Lesions in which atypia extends throughout the entire epithelial layer but does not penetrate through the basement membrane are diagnosed as CIS, while SCC is reserved for defining the point at which dysplastic cells invade beyond the basement membrane and spread through the underlying connective tissue. An overlap between these histologic stages often exists and the expertise of an experienced pathologist is required for accurate diagnosis. Due to the much higher tendency of high-grade dysplasias to progress into invasive disease in comparison to low-grade dysplasias, they are routinely excised in British Columbia47. Nevertheless, differentiating between high-risk and low-risk low-grade dysplasias remains a clinical challenge.  1.5 The Molecular Biology of Oral Cancer 1.5.1 Molecular and Genetic Aspects of Oral Carcinogenesis As in all solid tumors, oral cancer cells harbor a spectrum of genetic abnormalities, acquired through either specific gene mutations, chromosomal imbalances, or epigenetic aberations48,49. The p53 tumor-suppressor gene is the most frequently mutated gene in oral neoplasms, leading to disruption of normal cell cycle control and inefficient DNA repair5.  In addition, findings from studies show an association between p53 mutations and resistance of oral neoplasms to radiotherapy and reduced sensitivity of OPLs towards chemopreventative treatment strategies50,51. Gene over-expression is also common in oral cancer and is similarly tied with differences in tumor behavior clinically49. For instance, elevated levels of the Bcl-2 protein 	12		product have been associated with poor treatment outcomes and shorter survival52. Up-regulation of the epidermal growth factor receptor (EGFR) proto-oncogene is commonly observed in oral malignant lesions and is associated with altered cell renewal, cellular metabolism, cell differentiation and angiogenesis2,53,54. Because of its numerous important functions, EGFR has become an attractive target for development of novel treatment strategies. Deletions of the 3p14 and 9p21 loci represent two of the most frequent chromosomal alterations detected in oral tumors49. Due to the presence of crucial tumor-suppressor genes in these regions (e.g. FHIT at 3p14 and p16 at 9p21), such deletions are postulated to play a key role in malignant transformation and disease progression. Gene silencing via hypermethylation at CpG-rich promoter regions represents another important mode of carcinogenesis49. Essential tumor-suppressors inactivated by this mechanism in oral neoplasms include p16, DAP-kinase and E-cadherin.  1.5.2 A Genetic Progression Model for Oral Cancer According to Califano et al., oral cancer is believed to arise through accumulation of genetic and epigenetic events, with each successive histologic stage holding a greater amount of alterations55. Deletions of chromosomes 3p, 9p and 17p correspond with transition from normal tissue to dysplasia, while progression from dysplasia to SCC is mainly associated with further loss at the 4q, 6p, 8p, 11q, 13q and 14q loci. All of these chromosomal loci contain fragile sites which are extremely vulnerable to carcinogenic effects. These events do not always occur in sequential order, and it is generally accepted that the amount of genetic instability is the principal determinant of oral tumorigenesis rather than the sequence itself56. 	13		1.5.3 Distinct Molecular Behavior of Oral Cancer in Non-Smoker Patients The causal link between tobacco smoke and oral carcinogenesis is well established and has been previously described in Section 1.2.1. However, non-smoking patients appear to have distinct disease characteristics in comparison to those that do smoke. Oral cancer patients without history of tobacco (and alcohol) use exhibit a female predominance, higher average age, and preponderance of tumor presentation at the mandibular alveolar ridge and maxilla57-61. In terms of cellular alterations, a lower proliferation index (determined via Ki-67 protein expression status) has been noted in tumor-adjacent epithelia of non-smoking head and neck SCC patients relative to that of smoker patients (the majority of samples originating from the oral cavity)62. Results from p53 immunohistochemical staining experiments have demonstrated that non-smoking and non-drinking patients contain reduced p53 expression in tumor-adjacent mucosa in comparison to patients that smoke and drink60,63. In addition, P53 gene mutations are less prevalent in non-smoker patients and when present, are specifically confined to cytidine phosphate guanosine (CpG) dinucleotide “hot spots”5,64,65. Koch et al. also found that abstainers harbor fewer tumors with a loss of heterozygosity (LOH) at the 3p, 4q, and 11q13 chromosomal loci65. In addition, non-smoker subjects have shown a higher frequency of 3q26-27 amplification and a gain of 1p when compared to the smoking patient population66. While the exact causes for the different clinicopathological behavior of oral malignancies in non-smokers remain enigmatic, these collective findings suggest a unique mechanism of pathogenesis.    	14		1.6 Local Recurrence, Second Primary Tumors and Field Cancerization The mainstay treatment for solid oral neoplasms is resection of the primary tumor, usually with substantially large surgical margins to remove clinically occult disease2. Routine dissection of positive lymph nodes is generally accepted during advanced disease stages, as it corresponds with improved outcomes1. Often, chemotherapy and radiation therapy (utilized alone or in combination) are added to treatment1,2. Different combinations of these modalities are selected based on various considerations such as enhanced loco-regional control for cases with aggressive disease, anticipated functional and cosmetic outcomes, tumor resectability, and overall patient health status. Despite these current treatment strategies, a relatively high rate of local recurrence, the development of second primary tumors (SPTs), and lymph node metastasis remain a problem and hinder progress in oral cancer management67. Local recurrence, defined according to clinical criteria, occurs at a distance <2 cm from the initial tumor within a three-year time period67. Following removal of the primary tumor, it is a standard practice to thoroughly examine the resection margins to identify any residual disease. It is believed, however, that a relatively small number of cancer cells can remain in the patient at the margins and is the main source of local recurrence. Another type of recurrence, defined as a “second field tumor” (SFTs), is suggested to arise from remains of a contiguous field of preneoplastic cells from which the index tumor developed48,67. The transformation of these precancerous cells into invasive carcinoma proceeds through the accumulation of molecular alterations induced by additional carcinogenic hits67. Residual premalignant lesions (histopathologically diagnosed as dysplasia or carcinoma in situ) pose additional threat67. Severe 	15		dysplasia and carcinoma in situ specifically have a high probability of progressing into invasive disease and call for further intervention. To exclude the possibility of local recurrence, SPTs are typically defined as lesions occurring >2 cm away from the primary and at least 3 years after diagnosis of the primary67. The incidence of multiple SPTs following discovery of the initial tumor varies from 10 to 20%2. Although most SPTs are found in the oral cavity, pharynx and esophagus, lesions in the lung and larynx can also occur. Further, a follow-up of 727 OSCC patients has shown that the site of the primary tumor (floor of mouth, retromolar area, and lower alveolar process in particular) correlates with a higher risk of second malignancies68. This theory is substantiated by additional studies69,70. As with local recurrence, the concept of “field cancerization” is often used to explain two types of SPTs. “True” SPTs have an independent origin, whereas SFTs share a common clonal progenitor or a progenitor cell population with the first primary tumor. In the case of both local recurrence and SPTs, the presence of a “cancer field” has crucial clinical implications, as it often requires more aggressive intervention. The presence of oral tumors that indeed evolve from genetically related precursor fields offers an opportunity to study the natural process of oral carcinogenesis, with particular focus on the key genetic drivers of premalignant progression. Deciphering such molecular alterations within a single “oral cancer field” can be beneficial in the development of more accurate risk-assessment and treatment protocols. For instance, molecular analysis of histopathologically heterogenous field areas can help identify novel markers suitable for delineating disease progression risk. Similarly, newly discovered disease-related molecular aberrations that occur across an oral cancer field can assist with selection of targeted therapies based on tissue histology.  	16		Detection of oral cancer fields in known cancer patients is equally important to provide the means for sampling and studying the key tissue changes occurring on the molecular level. Since contiguous genetically altered fields are often difficult to fully outline under regular intraoperative illumination (white light), visual aids relying on optical methods have been developed to better demarcate the extent of clinically occult diseased areas. One promising approach involves employment of fluorescence visualization (FV) onto the oral mucosa to identify pre-neoplastic and neoplastic lesions that are undetectable by the naked eye71. The association between the loss of autofluorescence and tumorigenesis is now well accepted and has been demonstrated in a number of cancerous tissues, including oral cancer71-73. Overall, optically guided surgical resection of suspicious neoplastic lesions offers the potential for significant reduction in disease recurrence71. In addition, it offers a new opportunity to study molecular alterations within histopathologically different yet adjacent tissues without the effect of timing variability and extrinsic factors.               	17		2. MicroRNAs MicroRNAs (miRNAs) represent a large family of ~22-nucleotide-long, non-coding, single-stranded RNA molecules that are endogenous to all mammalian cells74,75. Since their initial discovery in the early 1990’s they have become an extensive area of research and have been well-described as crucial post-transcriptional regulators of gene expression. Hence, miRNAs have now been recognized to play crucial roles in almost every cellular developmental process and their deregulation has been implicated in numerous types of pathologies, including cancer.  2.1 MiRNA Discovery The first miRNA was discovered in 1993 by Lee et al. while studying the gene lin-14 in Caernorhabditis elegans development. Interestingly, they found that the levels of the lin-14 protein product were controlled by expression of the lin-4 gene during specific time points76. Cloning of the lin-4 locus and analysis of its genomic sequence revealed that lin-4 does not encode for a protein product but instead codes for a short RNA that is complementary to multiple sites in the 3’UTR of the lin-14 mRNA. Based on these findings and results from earlier experiments exploring the relationship between lin-4, lin-14 and the C. elegans maturation cycle, a model for RNA-RNA antisense interaction was proposed, suggesting lin-4 acts by negatively regulating the level of LIN-14 protein77-79. The identification of a second miRNA, let-7, as well as its target genes lin-14, lin-28, lin-41, lin-42 and daf-12, confirmed the importance of small regulatory RNAs in C. elegans development80. Furthermore, genome sequence comparisons and gene expression analyses in a separate study revealed exact matches to the mature let-7 miRNA sequence in Drosophila 	18		melanogaster and humans, indicating its conservation across animal species81-83. Following these discoveries, cloning and characterization of small RNAs that share similar characteristics and are expressed in different organisms and cellular systems have led to the identification of ~1000 miRNAs84.  2.2 MiRNA Biogenesis and Function MicroRNAs (miRNAs) represent a large family of ~22-nucleotide-long, non-coding, single-stranded RNA molecules that are endogenous to mammalian cells. They are believed to serve as crucial post-transcriptional regulators of gene expression. Given this pivotal function, miRNAs are significant players in almost every cellular process and – significantly – have been implicated in numerous disease types, including cancer. MiRNAs are coded throughout the human genome. They can be found as individual transcriptional units, clusters of distinct miRNAs, and within the introns of protein-coding genes85,86. Other miRNA genes can be polycistronic, residing for example in Hox clusters (groups of related genes that regulate morphogenesis). MiRNA processing has been reviewed extensively75. It is described in detail in Figure 1.     	19			Figure 1. Key Features of MiRNA Biogenesis and Function MiRNA genes reside in multiple genomic regions, ranging from individual transcriptional units to members of arranged miRNA clusters. They are transcribed by RNA polymerase (Pol II) into primary miRNA (pri-miRNA) molecules that harbor a ~33-bp stem, a terminal loop, and flanking single stranded segments. These are then converted into second precursors (pre-miRNA) by the Microprocessor Complex (composed primarily of the Drosha enzyme and DGCR8 protein) and are exported into the cytoplasm by the RAN-GTP dependent transporter Exportin-5. Additional processing by the Dicer enzyme produces a miRNA/miRNA* duplex, from which one strand is preferentially added to the RNA-induced silencing complex (RISC). As part of RISC, mature miRNAs bind to complementary 3′ untranslated regions (UTRs) of target mRNAs and down-regulate protein expression through either mRNA degradation (largely mediated by the AGO2 and GW182 proteins) or translational repression.  	20		2.3 Detection of MiRNAs in Human Specimens During the time of their discovery, miRNA expression in tissue specimens was generally quantified using Northern blotting76,80,81,83. This procedure is based on the separation of total RNA from samples according to size using gel (usually agarose) electrophoresis87. The RNA is then transferred onto a nylon membrane by capillary forces and hybridized to labeled probes that are specific to target miRNAs. Following the washing of unbound probes, results are visualized through autoradiography. Northern analysis is still a standard method for measuring gene expression due to its relatively high specificity and the ability to detect transcript size. Its major drawbacks with respect to miRNA screening are low sensitivity in comparison to other techniques and the inability to visualize entire miRNA profiles in tissue samples. In addition, the dependency on large amounts of total RNA (at least 20 ug for each Northern blot) makes it a less favorable approach when analyzing patient specimens87,88.     To account for the extensive abundance of miRNAs in the human genome and for measuring the global miRNA expression profiles in individual cells or tissue samples, various microarray platforms have been developed89-91. Microarrays are robust multiplex systems in which series of DNA oligonucleotides (called probes) with complementary sequences to specific miRNAs are spotted onto a solid surface (glass slide or silicon chip). Processed RNA segments from individual samples, or reverse transcribed complementary DNA (cDNA) products, are coupled to detector molecules and then hybridized to the array88,91-93. Upon successful binding between probes and their target miRNAs, signals with intensities relative to the amount of bound structures are generated. The resulting miRNA microarray data sets are extremely large and thus, are interpreted through statistical methods such as clustering analysis, leading to a graphical representation of miRNA expression values94.   	21		Since less abundant miRNAs may routinely escape detection during microarray experiments, the advent of next generation sequencing (NGS) has provided an alternative tool for determining total miRNA expression patterns. Although variable NGS systems have been developed, they generally follow the same basic principle. Essentially, after extraction and purification of total RNA, small RNA transcripts are extended through ligation of adapter sequences on each side, amplified through polymerase chain reaction (PCR) and isolated with gel fractionation. These elongated segments are then reverse transcribed into cDNA, sequenced and compared to a reference genome, allowing detection of specific miRNAs and determination of their frequency95-97. Accordingly, this technology has been used successfully in several biological settings for surveying miRNA expression levels, identifying variability in mature miRNA sequences and discovering sequences belonging to previously unidentified miRNA genes95,98,99. Nevertheless, whether NGS is superior to existing microarray techniques in analyzing human samples is debatable96,100. To accommodate for the need of high sensitivity and specificity during absolute or relative miRNA expression quantification, separate studies have employed the quantitative real-time PCR (qRT-PCR) method101-104. This procedure follows a similar protocol as standard PCR, but is unique in its ability to detect cDNA amplification throughout the progress of the reaction instead of detecting the product after completion of the reaction. Non-specific fluorescent dyes (SYBR Green) and sequence-specific fluorescent reporter probes (TaqMan probes) can be used alternatively to correlate fluorescence signals to the amount of amplified product105-108. As a result, signal generation at an earlier cycle indicates greater abundance of a target miRNA within a studied sample.  Due to the difficulty of assaying for short sequences, as is the case in miRNA detection, qRT-PCR requires modification of primers to increase their binding efficiency and 	22		minimize the formation of undesired by-products. This is achieved though construction of stem-loop primers or integration of locked nucleic acid (LNA) into the primer sequences107-109.  While additional strategies for profiling for miRNA expression exist, Northern blotting, microarray analysis, NGS and qRT-PCR remain the most widely used at the present time110-112. Analysis can be performed on fresh frozen or formalin-fixed paraffin embedded (FFPE) tissue, serum, plasma and saliva samples. Furthermore, in most cases, a combination of these techniques is adopted for proper validation113-120.  2.4 MiRNA Behaviors in Cancer Alterations in miRNA expression are now known to be a common feature across human malignancies. Both tumor suppressive and oncogenic miRNAs have been uncovered, with the former down-regulated with disease and the latter up-regulated. The first cancer-associated miRNAs uncovered were miR-15a and miR-16-1, which map to a chromosomal region frequently deleted in chronic lymphoblastic leukemia (CLL)121. These miRNAs down-regulate anti-apoptotic BCL2, their deletion suggesting a mechanism for pro-survival signaling in CLL121. Another well-characterized tumor suppressive miRNA was identified in the let-7 miRNA family123. RAS, HMGA2, and MYC oncogenes have been identified as let-7 targets, suggesting significant tumor suppressive importance for this miRNA family84. Additionally, reduced expression of let-7 species has been correlated with post-operative survival in lung cancer patients and introduction of let-7 miRNAs in lung cancer models can result in significantly decreased cell and tumor growth124,125. To date, many other tumor suppressive miRNAs have been identified, including miR-29, miR-145, miR-221/miR-222, miR-205, and the miR-34 family84,126.   	23		Expression profiling of different tumor types has also revealed myriad oncogenic miRNAs. The first reported oncogenic miRNAs were miR-155 and the miR-17-92 cluster84. Accumulation of these miRNAs has been associated with lymphomas and different solid tumor types84,127. MiR-224 is also up-regulated in various cancer types, including hepatocellular, thyroid, prostate, and pancreatic tumors114,128. MiR-224 was found to abrogate endogenous expression of anti-apoptotic API-5 by directly degrading its mRNA transcript114. Although the downstream effects of this interaction are not fully understood, this miRNA-level disruption may drive tumorigenesis by activation of anti-apoptotic signaling114.     Importantly, the tumor suppressive/oncogenic function of any miRNA can vary depending on cell or tissue type. Conflicting behaviors have been observed for miR-221/miR-222 and the above-mentioned miR-17-92 cluster84,129,130. Ultimately, the same miRNA can have numerous gene targets, be involved in distinct pathways, and contribute to different biological downstream effects in differing cell types. Moreover, the expression pattern of a miRNA target can vary between tissue types, influencing whether miRNA regulation is possible.  2.5 Mechanisms of MiRNA Dysregulation in Cancer The mechanisms that underlie miRNA expression changes in cancer are similar to those controlling the expression of protein-coding genes (Figure 2). Altered behavior of transcription factors represent one mechanism for miRNA dysregulation, MYC-driven over-expression of the miR-17-92 oncogenic cluster is a well-characterized event84.  P53-induced expression of miR-34 via binding to the miRNA promoter offers another example84. Chromosomal alterations also govern miRNA dysregulation in cancer; many commonly altered miRNAs map to genome loci that frequently undergo rearrangements in human malignancies. For instance, members of the 	24		let-7 family, as well as miR-125b and miR-100 (both down-regulated in oral squamous cell carcinoma [OSCC] and implicated in tumorigenesis and radioresistance) map to chromosomal loci commonly deleted in solid tumors84,131. Epigenetic changes can also alter miRNA behaviors; hypermethylation of CpG islands in promoters of tumor suppressor miRNAs can result in miRNA silencing and the emergence of cancer phenotypes131. Promoter methylation silencing of miR-137 (believed to induce senescence in normal human keratinocytes) was first observed in oral tumors and cell lines – and this silencing was found to be associated with cell growth rates133-136. Polymorphisms (especially SNPs) can also govern dysregulation of pri-, pre- and mature miRNAs, affecting miRNA processing or transcript targeting. A recently reported SNP within miR-196a2 (rs11614913) was detected in multiple solid neoplasms (including OSCC) and while not all downstream effects of this variation are known, patients homozygous for this variant were reported to have a higher risk of developing multiple cancer types137,138. Similarly, a SNP within miR-26a-1 (rs7372209) has been reported to alter expression of this miRNA and may have utility for predicting the risk of developing oral premalignant lesions (OPLs)139.   Finally, defects in miRNA processing machinery can also contribute to miRNA-mediated oncogenic processes. Several factors control miRNA biogenesis (including the Microprocessor Complex, Dicer, AGO2, and GW182) and disruption of any one of these components could potentially cause changes to miRNAs capable of contributing to cancer phenotypes. Elevated expression of Drosha, a key member of the Microprocessor Complex, provides an example of this, having been reported as over-expressed in tissues taken from patients with cervical squamous cell carcinoma140. Concurrent expression increases of multiple oncogenic miRNAs were observed, with additional results indicating that Drosha mediated the observed activation of miRNAs. 	25			Figure 2. Mechanisms of MiRNA Deregulation in Cancer The transcription of miRNA genes is regulated in a fashion similar to that of protein-coding genes. Alterations in certain transcription factors, such as MYC and p53, can disrupt the normal expression of miRNAs that act as tumor suppressors or oncogenes. In addition, miRNA-coding loci can be subjected to genetic and epigenetic aberrations. Chromosomal abnormalities (deletions, translocations, and copy-number changes) in regions that harbor important miRNA genes and miRNA polymorphisms have been reported in various types of neoplasms. Likewise, the number of putative anti-cancer miRNAs undergoing promoter CpG island methylation is vastly expanding, and associations with growth-promoting phenotypes have been reported. Last, flaws in any key components of the miRNA biosynthesis machinery can lead to deregulation of functional miRNAs and their target genes. The overall outcome of these events may ultimately cause increased proliferation, invasion, cell migration, angiogenesis or chemoresistance, or reduced apoptosis, thereby promoting tumorigenesis. 	26		2.6 MiRNAs in Oral Tumorigenesis Many recent molecular studies of head and neck cancer – and OSCC specifically – have focused on miRNA dysregulation. Increased expression of miR-21 and miR-221 and decreased expression of the let-7 family of miRNAs have been frequently observed in OSCC, as well as in other malignancies of the head and neck103,116,117,141-149. Additionally, miRNAs such as miR-184 have been identified as deregulated in OSCCs specifically (but not other head and neck squamous cell carcinoma [HNSCC] types)150,151. With the recent explosion of new literature pertaining to miRNAs and OSCC, discussion in this section is limited to those miRNAs that have been examined in multiple studies or validated by independent means within a single report. A listing of miRNA candidates that have been investigated for their role in oral tumorigenesis and as potential biomarkers for OSCC detection, risk assessment and management is provided in Table 1.  The oncogenic activity of miR-21 has been reported in many different types of malignancies (including glioblastomas, acute myeloid leukemia, aggressive chronic lymphocytic leukemia, as well as breast, colon, pancreatic, lung, prostate, liver, and stomach cancers)84. In OSCC, increased miR-21 expression has been negatively associated with low levels of TPM1 and PTEN – two well-described tumor suppressors that mediate apoptotic and cell cycle events, respectively145. Closer investigation of this interaction has revealed that miR-21 facilitates anchorage-independent growth of OSCC cells partly through down-regulating TPM1145. This finding has been validated in additional disease reports describing elevated miR-21 expression and contribution to neoplastic phenotypes117,148.   The tumor suppressive role of let-7 family miRNAs in OSCC progression has been similarly well studied. Assessment of let-7b miRNA and Dicer levels in HNSCC cell lines (including 	27		some OSCC-derived lines) showed an inverse relationship between the two144. Compared to normal primary gingival epithelial cells, Dicer protein levels were elevated in cancerous cell lines while let-7b levels were significantly reduced. Both Dicer suppression and transfection of chemically synthesized let-7b independently led to attenuation of cell proliferation in OSCC cell lines. These findings align with previous studies, where Dicer has been shown to be important in cell cycle regulation and cell growth – and a target of let-7 miRNAs. Hence, Dicer up-regulation combined with let-7b down-regulation may both contribute to OSCC progression. The function of miR-222 and miR-138 in metastatic processes of OSCC has been determined through studies on tongue SCC lines. In one study, cells with aggressive metastatic potential exhibited relative down-regulation of miR-222 and, following transfection of miR-222 mimics, displayed decreased invasive abilities152. This same analysis identified pro-metastatic genes MMP1 and SOD2 as miR-222 targets. Both miR-222 expression and SOD2 knockdown led to suppression of MMP1, suggesting that miR-222 interacts with MMP1 through direct and indirect (SOD2-targeting) mechanisms. Additionally, highly invasive cells were found to have significantly reduced miR-138 expression, which was shown to antagonize cell migration and invasion by targeting two components of the Rho GTPase pathway (RhoC and ROCK2)153. An independent study showed reduced miR-138 in OSCC cells and an anti-apoptotic role for miR-138, further indicating that this is a critical tumor suppressor miRNA154.    Additional data suggest that miR-1 and miR-133a may be critical in oral tumorigenesis. These miRNAs have been detected at reduced levels in OSCC and map to the same chromosomal locus, suggesting that a common mechanism may govern their behavior143,155-158. MiR-1 is proposed to suppress metastasis by targeting TAGLN2, a gene coding for an actin-binding protein that is believed to mediate cell migration and invasion158. The tumor suppressive action of miR-	28		133a is understood to be a result of this miRNA targeting CAV1 and GSTP1, which are both frequently over-expressed in many cancer types and known to promote multiple oncogenic processes156,157.    Recently, differential miRNA expression patterns were observed in two docetaxel-resistant OSCC cell lines when compared to parental cells159. MiR-101 over-expression, detected in the resistant OSCC lines, has also been reported in HNSCC tissues and implicated in the oncogenic EZH2-Rap1GAP pathway160. A comparison of miRNA expression between a cisplatin-sensitive tongue SCC line (Tca8113) and its cisplatin-resistant sub-line (Tca/cisplatin) revealed differential miRNA expression: Tca/cisplatin cells exhibited higher miR-23a and miR-214 and lower miR-21 levels161. Administration of anti-miR-23a, anti-miR-214, or pre-miR-21 plasmid in the Tca/cisplatin line decreased cell viability during cisplatin treatment, suggesting a role for miR-21 in chemosensitivity and a role for miR-23a and miR-214 in chemoresistance. Examination of the miR-23a sequence revealed TOP2B – a key player in transcription and a frequent drug target – as a potential target, suggesting a further miRNA-driven mechanism for chemoresistance in these cells. Additional evidence suggests miR-21-mediated cell signaling is tied to cisplatin resistance in OSCC cells162. Further evaluation of the relationship between these miRNAs and drug resistance in OSCC is needed.	29		 MiRNA Detection Validated/ Putative Targets Significance in Oral Cancer References miR-21 OSCC tissue, cell lines TPM1, PTEN, P12 (CDK2AP1) Facilitates anchorage-independent growth; promotes cell proliferation; promotes chemosensitivity/ chemoresistance**; up-regulation associated with decreased survival and disease progression (Avissar et al., 2009b; Bourguignon et al., 2011; Cervigne et al., 2009; Chang et al., 2008b; Li et al., 2009; Yu et al., 2010; Zheng et al., 2011) let-7b OSCC cell lines DICER, MYC, RAS, HMGA2 Suppresses cell proliferation (Croce, 2009; Jakymiw et al., 2010) let-7d OSCC tissue MYC, RAS, HMGA2 Down-regulation associated with shorter time of death, disease recurrence, distant metastasis (Childs et al., 2009; Croce, 2009) let-7i OSCC tissue MYC, RAS, HMGA2 Down-regulations associated with progression to lymph node metastasis (Croce, 2009; Scapoli et al., 2010) miR-222 OSCC cell lines MMP1, SOD2 Inhibits cell invasion (Liu et al., 2009b) miR-138 OSCC cell lines  RhoC, ROCK2 Suppresses cell migration and invasion; promotes cell cycle arrest and apoptosis (Jian g et al., 2010; Liu et al., 2009a) Table 1. MiRNA Candidates in Oral Cancer with Potential Clinical Utility  	30		 MiRNA Detection Validated/ Putative Targets Significance in Oral Cancer References miR-1 OSCC tissue, cell lines TAGLN2 Suppresses cell proliferation migration, and invasion; mediates apoptosis and cell cycle arrest (Nohata et al., 2011b) miR-133a OSCC tissue, cell lines CAV1, GSTP1 Inhibits cell proliferation, migration and invasion; induces apoptosis (Mutallip et al., 2011; Nohata et al., 2011a; Wong et al., 2008a) miR-221 OSCC tissue PTEN, TIMP3 Up-regulation delineates cancerous tissue (Avissar et al., 2009a; Avissar et al., 2009b; Garofalo et al., 2009) miR-375 OSCC tissue PDK1 Reduces cell proliferation and clonogenicity and mediates cell cycle arrest; down-regulation delineates cancerous tissue and corresponds with alcohol use (Avissar et al., 2009a; Avissar et al., 2009b; Hui et al., 2010; Lajer et al., 2011; Scapoli et al., 2010) miR-184  Plasma of OSCC patients None Promotes cell proliferation and inhibits apoptosis; up-regulation associated with tumor load (Wong et al., 2008b; Wong et al., 2009) miR-31 OSCC tissue; Plasma and saliva of OSCC patients FIH Promotes cell proliferation, migration, and anchorage-independent growth; up-regulation associated with tumor load (Lajer et al., 2011; Liu et al., 2010a; Liu et al., 2010b) Table 1. MiRNA Candidates in Oral Cancer with Potential Clinical Utility  	31		*Regular Font = Up-regulated miRNAs; Italicized Font = Down-regulated miRNAs **Denotes the differential findings with regards to drug resistance in OSCC and miR-21 up-regulation or down-regulation. 	32		2.7 Clinical Utility of Oral Cancer-Associated MiRNAs Numerous groups have worked to identify miRNA alterations associated with specific OSCC clinical phenotypes. Some groups have worked to uncover miRNAs associated with disease progression. While examining miRNA expression patterns in sequential oral lesions, Cervigne et al. reported over-expression of miR-21, miR-181b, and miR-345 in progressive leukoplakias and OSCC, but not in associated non-progressive leukoplakias or normal oral mucosa142. Over-expression of these miRNAs increased gradually throughout the progressive stages of OSCC, suggesting that a subset of miRNAs may constitute a signature for disease progression.   The prognostic capacity of miRNAs in OSCC has also been evaluated. Elevated miR-211 expression in primary OSCCs has been reported as being associated with development of nodal metastases, vascular invasion, and poor survival rates163. Another group reported an association between under-expression of miR-155, let-7i, and miR-146a and OSCC with lymph node metastases146. MiRNA expression analysis of 103 tongue SCC patients showed that miR-21 up-regulation was positively correlated with advanced clinical stages, poorer differentiation, lymph node metastasis, and reduced post-operative survival145. In this same study, miR-21 expression was confirmed as an independent prognostic factor for tongue SCC. This aberration was also concordant with a significantly decreased 5-year survival in a separate investigation141. Reduced expression of let-7d was also reported for a set of 104 HNSCC patient samples, the majority of which were derived from the oral cavity and oropharynx143. In combination with low levels of miR-205, let-7d expression was associated with shorter time to death, disease recurrence, and distant metastases. Analysis of another let-7 family member, let-7a, in a separate cohort of HNSCC patients showed a similar correlation between decreased expression and severe clinicopathological features164. 	33		Some OSCC cases are characterized by miR-221 over-expression and/or miR-375 under-expression103,106,141. One study demonstrated that the ratio of miR-221 to miR-375 could delineate cancerous and non-cancerous tissues at a high sensitivity (92%) and specificity (93%)106. The same group also observed that miR-375 activation is associated with alcohol use111. Further, miR-375 deficiency was the most significant aberration in a separate subset of OSCC biopsies, while miR-221 up-regulation has been confirmed and implicated in numerous cancer types116,62,166. These results indicate that miRNA markers may be able to not only delineate disease states, but also etiology for a given case. MiRNA markers may also have utility for identifying the primary anatomical site of metastatic lymph nodes with unknown primary tumor location. Analysis of miRNA expression in cancers from the tonsil, base of tongue, and post-nasal space found that, for each of the cases studied, miRNA expression was consistent between matched primary lesions and local metastatic disease167. More importantly, miRNA profiles were found to be distinct among various anatomical subsites, suggesting an effective means for tissue of origin determination.   Epigenetic aberrations in miRNA genes have also been tested as markers for OSCC detection. Examination of oral rinse samples from 99 HNSCC patients and 99 cancer-free controls – as well as in formalin-fixed paraffin embedded tumor tissues of 64 patients – showed that, relative to control subjects, odds ratios for miR-137 promoter methylation were ~12 for the cancer group (evaluated cases were primarily obtained from the oral cavity)135. Hypermethylation of miR-137 was also associated with female sex and inversely associated with body mass index. Further, miR-137 promoter methylation was significantly associated with poorer overall survival, suggesting downstream utility for this alteration as a prognostic tool116. 	34		Some studies have also evaluated the OSCC biomarker potential for miRNAs obtained through biological fluids, including serum, plasma, and saliva. The goal with these works has been to develop markers that are evaluable through non-invasive means. Two miRNAs have been examined in the plasma of OSCC patients to date: miR-184 and miR-31. In patients with invasive disease, plasma levels of miR-184 were significantly higher compared to normal healthy individuals. Further, when compared to pre-surgical levels, miR-184 levels were considerably lower following tumor resection (an important result given removal of the disease miRNA source, the tumor)150,151. Moreover, subjecting tongue SCC cell lines to miR-184 inhibitors hindered proliferative potential and induced cell death. These findings strongly argue that 1) miR-184 plays a role in tongue SCC pathogenesis and 2) miR-184 levels in plasma may have utility for defining tumor load, especially when residual disease is undetectable by other methods. Analogous to miR-184, miR-31 has also been reported at elevated levels in the plasma and saliva of OSCC patients (and shown to decrease following tumor removal)168. Other reports describe miR-31 as the most up-regulated miRNA in OSCC tissues and report an oncogenic role for miR-31 in tumor formation, providing further evidence that this miRNA is critical to malignant processes in oral sites149,166.   2.8 MiRNAs and Treatment of Malignancy Given the established role of miRNAs in many oncogenic processes, some groups have begun to explore the feasibility of miRNA-based therapies. Depending on whether they function as oncogenes or tumor suppressors, miRNAs may be either silenced with miRNA inhibitors or therapeutically administered into tumor cells, respectively84. The introduction of these constructs can be achieved via vectors or through direct delivery into tissues that can readily uptake 	35		miRNAs84. Studies of oncogenic miR-21 have demonstrated that intravenous injection of antisense miR-21 oligonucleotides into laryngeal and tongue squamous cell carcinoma murine models dramatically reduced tumor growth145,169. In addition, in vivo administration of an adeno-associated virus vector expressing miR-26a – a down-regulated miRNA in hepatocellular carcinoma – impeded disease progression without the presence of any side effects170. The role of miRNAs in chemosensitivity and drug resistance for OSCC has been discussed above. These findings suggest that, if validated, drug response-associated miRNA signatures could be used to stratify patients and select those treatment options most likely to prove efficacious for a particular individual. Ultimately, given the contribution of specific miRNAs to drug response phenotypes, future treatment regimens for OSCC could see novel miRNA-targeting drugs used in concert with conventional chemotherapy in order to improve patient responses.   2.9 Thesis Theme and Rationale for Study The theme of this thesis is to understand miRNA deregulations in oral cancer development, with a specific focus on non-smoker patients.  The identification of alterations in miRNA expression in different types of premalignant and advanced disease tissue biopsies will yield signature miRNAs that may aid in the development of a novel genomic platform for risk assessment, diagnosis and even as new therapeutic targets in a clinical setting.  	36		2.10 Objectives and Hypotheses The primary objectives of this thesis are (1) to identify miRNAs that are aberrantly expressed at the various stages of oral cancer and oral premalignancy in a cohort of non-smoker patients, and (2) to determine how miRNA expression differentiates across an oral cancer field.  This is based on the following hypotheses: Hypothesis 1: MiRNAs are deregulated in the earliest stages of oral cancer development. Hypothesis 2: Like DNA alterations, miRNA changes are accumulated during progression from premalignant to invasive disease stages.    2.11 Thesis Outline We have investigated objective (1) by analyzing miRNA expression levels in histopathologically distinct oral tissues relative to matched normal specimen from 9 non-smoker patients.  We have investigated objective (2) by examining the trends, frequencies and magnitudes of miRNA deregulation throughout the different stages of oral tumorigenesis arising within histopathologically heterogeneous oral cancer fields.  We also implemented multiple modes of laboratory techniques to verify the aberrant expression levels of selected candidate miRNAs and survey their expression profiles across the progression of oral carcinogenesis.       	37		3. Methodology 3.1 Study Population A total of 27 fresh frozen tissue samples were obtained from 9 patient cases.  These cases were drawn from an ongoing Pan-Canadian surgical trial (the COOLS trial), which has been previously described171. Specifically, all individuals included in our study were those who presented with histologically distinct oral premalignant lesions (OPLs) located within a single region of the oral cavity, allowing 3 samples to be collected from each patient. All the patient clinicopathological information is available in the Results section in Table 4.1.     3.2 Sample Accrual In many cases, OSCC arises within a genetically altered tissue field in the oral cavity. This oral cancer field is often histopathologically heterogeneous, allowing various stages of disease to be observed simultaneously during patient examination. Thus, diseased regions in the oral cavity were detected by a hand-held Fluorescence Visualization (FV) device capable of delineating occult disease proximate to oral tumors in real-time. This device uses a blue/violet light (400-460 nm) to scan the oral mucosa.  While normal tissues re-emit this light as pale green, abnormal tissues show loss of such autofluorescence and appear as dark patches. For each patient case, histologically different oral premalignant lesion (OPL) biopsies, including adjacent normal tissue, were collected at the same time from a single, contiguous field in a patient’s mouth. Complete protocols for surgical field assessment in the operating room, biopsy acquisition, and histopathological evaluation are further described by Poh et al.171,172. Briefly, FV assessment was performed with an autofluorescence imaging device, marketed as VELscope®, (LED Dental 	38		Inc., White Rock, British Columbia, Canada). In the operating room, two boundaries around a single lesion where demarcated – the clinically visible lesion under white light outlined by the surgeon, and the tissue showing decreased autofluoroscence under reduced room lighting outlined by a FV Specialist with a green Sharpie pen. A 10 mm surgical boundary was taken either around the clinically visible tumor or the FV-guided boundary, whichever wider. Overall, our FV-guided surgical approach minimizes the differences in miRNA expression that may arise due to tissue and timing variability, as well as extrinsic factors such as smoking and diet. This in turn facilitates more stringent analysis conditions.  3.3 RNA Isolation and MiRNA Expression Quantification Following histopathological evaluation and microdissection of each specimen by an oral pathologist, total RNA was extracted using a standard Trizol protocol. During global miRNA expression profiling, 40ng total RNA from each tissue sample was reverse transcribed using the miRCURY LNA Universal RT miRNA PCR, Polyadenylation and cDNA synthesis kit (Exiqon Inc.). cDNA was then quantified by quantitative real-time PCR (qRT-PCR) on the miRNA Ready-to-Use PCR, Human panel I and panel II with the miRCURY LNA Universal RT miRNA PCR, SYBR Green master mix according to the manufacturer’s protocol (Exiqon Inc.). Briefly, a 10µL mix comprised of 4.98µL cDNA, 5µL SYBR Green (Exiqon Inc.) and 0.02µL ROX dye (Invitrogen Inc.) was distributed into individual wells across two separate 384-well panels. Collectively, these panels covered 742 human miRNAs and contained dried down individual primer sets specific to these miRNAs. For greater duplex stability and higher specificity, locked nucleic acids (LNAs) were incorporated into the sequence of each primer set. All assays were quantified on the ViiA™ 7 Real-Time PCR System (Applied Biosystems Inc.). The 	39		amplification profile was denatured at 95°C for 10 min, followed by 40 cycles of 95°C for 10 s and 60°C for 60 s. At the end of the PCR cycles, melting curve analyses were performed.  3.4 Universal Real Time PCR 3.4.1 MiRNA Expression Profiling Analysis Only assays with distinct melting curves and CT < 35 were included in the analysis. All real-time PCR data was analyzed using the comparative CT method, normalizing against the global mean173,174. It was then filtered based on a minimum of 2-fold expression change relative to matched normal. Candidate miRNAs were selected according to their frequency of deregulation and average fold change value across the 9 separate patient cases.  3.4.2 Verification of Deregulated miRNA Candidates through Individual PCR Assays The expression of selected miRNA candidates (miR-224, miR-135a, miR-143, miR-223, miR-155, miR-720 and miR-605) was re-examined in all the 27 tissue samples, using individual miRNA PCR primer sets (Exiqon Inc.) and following the same protocol as the one used for the 384-well panels. Due to their stable expression across the sample set during the previous global miRNA expression analysis, miR-103 and miR-23b were chosen as reference genes. All assays were run in triplicate on the MicroAmp® Fast Optical 96-Well Reaction Plates (Applied Biosystems Inc.). A no enzyme control was included to detect if contamination of the template 	40		RNA was present. Tissue levels of miRNA candidates whose expression profiles matched the full panel real-time PCR results were further investigated via in situ hybridization experiments.    3.5 In Situ Hybridization (ISH) 3.5.1 Use of ISH for the Detection of MiRNAs in Human FFPE Tissues Digoxigenin (DIG) labeled locked nucleic acid (LNA) modified probes targeting selected miRNA candidates, positive control (U6 snRNA) and negative control (scrambled-miRNA) were purchased from Exiqon Inc. The entire procedure was performed according to manufacturer’s instructions, with minor adjustments.   Briefly, 6µm-thick formalin-fixed paraffin embedded (FFPE) tissue sections were deparaffinized with xylene, rehydrated in graded ethanol and treated with 300µL Proteinase-K (15 min for slides stained with U6 probe; 20 min for slides stained with miRNA and scrambled probes) at 37°C. Tissue sections were then dehydrated through successive ethanol washes, and hybridized with miRNA-specific (100nM), U6 (1nM) and scrambled (40nM) probes for 1 hour. Hybridization temperatures were 48°C for the miRNA-specific probes, and 54°C for the U6 and scrambled probes. Following stringent washes in SSC buffers, the sections were incubated with alkaline phosphatase-conjugated anti-DIG (diluted 1:500 for miRNA probes; 1:800 for U6 and scrambled probes, Roche) at room temperature for 60 min. ISH signal was then detected by incubation with 4-nitro-blue tetrazolium (NBT) and 5-bromo-4-chloro-3′-Indolylphosphate (BCIP) substrate (Roche) at 30°C for 2 hours. Nuclear fast red (Vector Laboratories) was used as a counterstain and Eukitt mounting medium (VWR) for cover glass mounting. Results were 	41		analyzed the next day with an Olympus MVX10 microscope equipped with a charge-coupled device camera and Olympus CellP software.  3.5.2 Development of Tissue Microarrays (TMAs) for Verification and Validation of Candidate MiRNA Deregulation FFPE specimen corresponding to each of the 27 fresh frozen patient tissue samples were collected via the previously mentioned COOLS trial and used for assembly of TMAs to verify the expression of candidate miRNAs. Cores of 2 mm were obtained in duplicate from each paraffin biopsy and distributed amongst 2 recipient TMA blocks using a specific arraying device.  To validate the expression of miRNA candidates in these TMAs, 2 separate TMAs were constructed using premalignant and malignant archival patient tissues from the British Columbia Oral Biopsy Service (BC OBS). Individual 0.5-3 mm tissue cylinders from 26 primary dysplasias were deposited into a single TMA block. A second TMA block was built from 31 independent OSCC tumors, each sampled in 2 replicates (0.6 mm deep).  Multiple 6 µm sections were cut from each TMA block with a microtome and used for in situ hybridization (ISH) analysis. Representative and viable tissue sections were examined manually and semi-quantitatively for cytoplasmic staining on a computer screen by 1 experienced pathologist and 1 technician (C.F.P. and S.Z.). The dominant staining intensity was scored as: 0 = negative; 1 = weak; 2 = intermediate; 3 = strong. The ‘ISH-score’ was then binned into a 2-tier classification of ‘negative’ (score 0), and ‘positive’ (score ≥1).  	42		3.6 Statistical Analysis Significant differences in miRNA expression were detected using the one-way ANOVA test, by comparing miRNA expression values in dysplastic and CIS/OSCC samples versus normal. The level of significance was set at P < 0.05.                 	43		4. Results 4.1 Differential MiRNA Expression in Oral Cancer Progression Our initial objective was to obtain an overview of the distinctions and similarities of miRNA expression among adjacent, yet histopathologically different, oral premalignant tissues. We therefore measured miRNA expression levels in 27 fresh frozen tissue biopsies from 9 patient cases, examining a histologically confirmed dysplastic, a CIS or OSCC, and a normal specimen in each patient (Table 2).   Of the 742 human miRNAs analyzed by qRT-PCR, a total of 602 were successfully detected (CT < 35 in at least one profiled sample) across our entire cohort of 27 samples. As with gene activation, only a subset of miRNAs are expressed in any given tissue type or disease state127. Similarly, we detected a different number of miRNAs in each of the histopathological groups (normal, dysplasia, and CIS/OSCC) within our sample pool (Figure 3). A repeated measures ANOVA with a post hoc Tukey test was performed to determine statistical differences between the three tissue groups. The total number of detected miRNAs was not statistically different between the normal and the dysplastic specimens, yet statistically significant differences were present between the normal versus the CIS/OSCC group and between the dysplasia versus the CIS/OSCC group (p-value = 0.0009, for both comparisons). Examining the general trends in miRNA expression across each histological group, we observed a greater number of miRNAs in the CIS/OSCC tissue subset compared to the dysplastic group (Figure 4).     	44		Patient ID Gender Smoking Status* HPV Status Lesion Site Age Diagnosis** 1878 Male NS Negative Left Tongue 48 OSCC 1953 Female NS Negative Left Tongue 53 CIS 2000 Female NS Negative Right Tongue 58 OSCC 2076 Female NS Negative Left Tongue 82 OSCC 3002 Female NS Negative Lateral Tongue 41 OSCC 5266 Male NS Negative Right Tongue 55 OSCC 7057 Female NS Negative Right Lateral Tongue 53 OSCC 7071 Male NS Negative Right tongue 71 OSCC 7058 Female NS Negative Left Ventral Tongue 43 OSCC Table 2. Patient Clinicopathological Information *NS = Non-smoker **OSCC = Oral Squamous Cell Carcinoma; CIS = Carcinoma in situ     	45			Figure 3. MiRNA Expression through Progressive Oral Cancer Stages A Venn diagram showing patterns of miRNA detection across each histopathological stage. Each number represents the miRNAs detected in at least one case in adjacent normal, dysplasia and/or CIS/OSCC.          	46			Figure 4. General Trends in MiRNA Detection Across Oral Cancer Progression Mean number of miRNA detected in normal, dysplasia, and CIS/OSCC biopsies. Error bars generated from the standard error in each histopathological tissue group are included.         0 50 100 150 200 250 300 350 400 450 Number of miRNAs Detected Normal Dysplasia CIS/OSCC 	47		4.2 MicroRNA Dysregulation throughout Oral Cancer Progression To identify miRNAs potentially playing a role in oral tumorigenesis, we undertook paired analyses of miRNA expression data from each of the dysplasia and CIS/OSCC cases versus miRNA expression results obtained from associated normal biopsies. When applying a 2-fold threshold, we observed a larger amount of deregulation in the more advanced stages, with 54 miRNA changes unique to dysplasias, 87 to CIS/OSCC tissues, and 260 common to both (Figure 5A). After analyzing only the over-expression miRNA profiles across all 9 cases, we found 96 aberrations confined to dysplastic samples and 71 that were CIS/OSCC-specific (Figure 5B). Down-regulation, however, was considerably more pronounced in CIS/OSCC, with 101 exclusive miRNA deficiencies compared to 48 in the dysplastic group (Figure 5C). When examining case-by-case trends in miRNA expression in the 9 set of matched dysplastic and CIS/OSCC tissues, we did not observe an obvious pattern in the overall deregulation (up-regulation or down-regulation) or up-regulation exclusively (Figures 6A-B). However, we did find a greater number down-regulated miRNAs in 8/9 CIS/OSCC specimens compared to their matched dysplastic biopsies (Figure 6C). Altogether, these results may suggest that relative to miRNA over-expression, reduction in miRNA cellular levels may be more prominent and may have a significant impact in the latter stages of oral tumorigenesis. It is also important to note that some of these miRNAs were deregulated in an opposite fashion between the two types of histopathological tissue cohorts as well as the separate patient cases (i.e. up-regulated in one tissue type while down-regulated in another). The number of miRNA alterations exclusive to these histopathological tissue groups was therefore greater when examining up- or down-	48		regulation alone than when combining these alterations in the analysis summarized by Figure 5A.                	49			Figure 5A. MiRNA Deregulation (Up-Regulation and Down-Regulation)         	50			Figure 5B. MiRNA Up-Regulation            	51			Figure 5C. MiRNA Down-Regulation  	52			Figure 6A. Case-by-Case Trends in MiRNA Overall Deregulation (Up-Regulation and Down-Regulation)     	53			Figure 6B. Case-by-Case Trends in MiRNA Up-Regulation      	54			Figure 6C. Case-by-Case Trends in MiRNA Down-Regulation                 	55		In the last portion of this analysis, we reviewed the general trends of global miRNA expression through OSCC progression in each of the 9 patient cases. Focusing solely on those miRNAs whose levels were initially altered (either elevated or reduced by ≥2-fold compared to matched normal) in the dysplastic tissues, we did not find a particular trend of deregulation over time. More specifically, 4 of the cases displayed a minor shift towards higher expression throughout tumor progression while the other 5 showed the opposite pattern (Table 3).    Patient ID Total Number of MiRNA Deregulations in Dys  MiRNAs* at Progressively Higher Levels in CIS/OSCC Compared to Dys MiRNAs at Progressively Lower Levels in CIS/OSCC Compared to Dys MiRNA Deregulations Common to Both CIS/OSCC and Dys 1878 51 32 (63%)** 19 (37%) 25 1953 31 15 (48%) 16 (52%) 11 2000 83 29 (35%) 54 (65%) 21 2076 81 29 (36%) 52 (64%) 19 3002 46 25 (54%) 21 (46%) 35 5266 126 46 (37%) 80 (63%) 31 7057 61 36 (59%) 25 (41%) 32 7071 63 33 (52%) 30 (48%) 22 7058 89 32 (36%) 57 (64%) 28 Table 3. Trends in MiRNA Expression Across Individual Patient Cases *Number and precentage provided. **The more prevalent progressive shift in miRNA deregulation is highlighted in bold for each case.    	56		4.3 Selection of Candidate MiRNAs associated with OPLs and OSCC We next sought to identify the most frequent miRNA aberrations occurring during either oral premalignancy or invasive disease. In the dysplastic tissue subset, the most prevalent events amongst the 9 biopsies were down-regulation of miR-886-5p, miR-375 and miR-143 relative to paired normal tissues [observed in 5/9 (56%) of cases]. The most dominant up-regulations were noted for miR-142-3p, miR-146a, miR-150, miR-182*, miR-187, miR-224 miR-26b*, miR-577, miR-1201 and miR-501-5p (detected in 4/9 (44%) of cases). All of these deregulations are summarized in Table 4A. As demonstrated by Table 4B, up-regulation of miR-21, miR-424, miR-142-3p, miR-146a, miR-155, miR-223, and miR-31*, as well as down-regulation of miR-375, miR-605, miR-720 and miR-1260 were the most consistent alterations [minimum frequency of 7/9 (78%)] in the CIS/OSCC tissue cohort.   Across both, the dysplastic and CIS/OSCC sample cohorts (n = 18), elevated levels of miR-142-3p, miR-146a, miR-150, miR-21, miR-424, miR-155, and miR-223 were detected [minimum frequency of 9/18 (50%)]. According to the same criteria, the most widespread miRNA deficiencies were for miR-375, miR-886-5p, miR-135a, miR-204, miR-605, miR-720 and miR-1260. This is summarized in Table 4C. The above-mentioned top deregulated miRNAs displayed dynamic expression profiles throughout OSCC progression. For instance, a spike in miR-223 levels occurred specifically during the more advanced disease stages (Figure 7A). Down-regulation of miR-375, on the other hand, was first detected in dysplastic tissues and then generally to a much greater extent in the 	57		case-matched CIS/OSCC specimen (Figure 7B). These results suggest that certain miRNA deregulations may be of functional significance at specific histopathological stages while other miRNA disruptions are continuously important throughout disease progression. While we did not observe the same deregulation patterns in the other top deregulated miRNAs, their expression across successive case-matched histopathological tissues is illustrated in Figures 7C-N.   For each miRNA (except miR-150 since it was not consistently altered in either the dysplastic or CIS/OSCC stages exclusively), we calculated its average fold change expression solely across cases in which it was deregulated (Tables 4A and 4B). Based on this parameter, the frequency of deregulation across the 9 patient cases, and on the abundance of literature linking each miRNA candidate with oral carcinogenesis, we selected miR-224 (dysplastic tissues), miR-223 and miR-155 (CIS/OSCC tissues) as the top up-regulated miRNAs to be further investigated in downstream experiments. According to the same criteria, we chose miR-143 (dysplastic tissues), miR-720, and miR-605 (CIS/OSCC tissues) as the chief down-regulated miRNAs.   It is important to note that aside from these 6 selected miRNA candidates, we uncovered miRNA expression changes that have already been cited by other groups. MiR-21, a highly oncogenic miRNA, has been frequently reported at increased levels in OSCC, as well as other malignancies of the head and neck103,116,117,141,142,145-147,149,175,176. In our subjects, miR-21 over-expression was similarly detected in 89% of CIS/OSCC samples by a 9.4 average fold-change compared to matched normal (Table 4B). Additional notable miRNA aberrations concordant with previous literature findings were up-regulation of miR-424 (89% of CIS/OSCC samples; 6.7 mean fold-change), up-regulation of miR-142-3p (78% of CIS/OSCC samples; 4.5 mean fold-change), and down-regulation of miR-375 (89% of CIS/OSCC samples; 0.05 mean fold-change) (Table 4B)103,116,149,151,168,177-181.  	58		MiRNA Name Frequency (n = 9) Mean Fold Change* miR-142-3p (up-regulated) 44% 2.7 miR-146a (up-regulated) 44% 2.7 miR-150 (up-regulated) 44% 5.5 miR-501-5p (up-regulated) 44% 3.1 miR-1201 (up-regulated) 44% 4.4 miR-182* (up-regulated) 44% 3.5 miR-187 (up-regulated) 44% 2.8 miR-224 (up-regulated) 44% 2.3 miR-577 (up-regulated) 44% 6.7 miR-26b* (up-regulated) 44% 2.6 miR-886-5p (down-regulated) 56% 0.26 miR-375 (down-regulated) 56% 0.33 miR-143 (down-regulated) 56% 0.33 Table 4A. Deregulated MiRNAs across the Dysplastic Tissue Cohort *Mean fold change was calculated exclusively from diseased specimens showing ≥2-fold expression change relative to normal tissue.          	59		MiRNA Name Frequency (n = 9) Mean Fold Change* miR-21 (up-regulated) 89% 9.4 miR-424 (up-regulated) 89% 6.7 miR-142-3p (up-regulated) 78% 4.5 miR-146 (up-regulated) 78% 4.1 miR-155 (up-regulated) 78% 5.1 miR-223 (up-regulated) 78% 7.1 miR-31* (up-regulated) 78% 16.3 miR-375 (down-regulated) 89% 0.05 miR-605 (down-regulated) 89% 0.23 miR-720 (down-regulated) 89% 0.20 miR-1260 (down-regulated) 78% 0.18 Table 4B. Deregulated MiRNAs across the CIS/OSCC Tissue Cohort *Mean fold change was calculated exclusively from diseased specimens showing ≥2-fold expression change relative to normal tissue.            	60		MiRNA Name Frequency (n = 18) Mean Fold Change* miR-142-3p (up-regulated) 61% 3.9 miR-146a (up-regulated) 61% 3.6 miR-21 (up-regulated) 56% 8.0 miR-424 (up-regulated) 56% 6.0 miR-155 (up-regulated) 56% 4.8 miR-150 (up-regulated) 56% 4.2 miR-223 (up-regulated) 50% 6.1 miR-375 (down-regulated) 72% 0.13 miR-886-5p (down-regulated) 56% 0.31 miR-135a (down-regulated) 56% 0.13 miR-204 (down-regulated) 50% 0.26 miR-605 (down-regulated) 50% 0.22 miR-720 (down-regulated) 50% 0.21 miR-1260 (down-regulated) 50% 0.21 Table 4C. Deregulated MiRNAs across both Dysplastic and CIS/OSCC Tissue Cohorts *Mean fold change was calculated exclusively from diseased specimens showing ≥2-fold expression change relative to normal tissue.      	61			Figure 7A. Up-Regulation Profile of MiR-223 Across Successive Case-Matched Histopathological Tissues The dashed lined represents the 2-fold threshold cutoff value for either over-expression or under-expression.    	62			Figure 7B. Down-Regulation Profile of MiR-375 Across Successive Case-Matched Histopathological Tissues The dashed lined represents the 2-fold threshold cutoff value for either over-expression or under-expression.    	63			Figure 7C. Expression Profile of MiR-142-3p Across Successive Case-Matched Histopathological Tissues The dashed lined represents the 2-fold threshold cutoff value for either over-expression or under-expression.      	64			Figure 7D. Expression Profile of MiR-146a Across Successive Case-Matched Histopathological Tissues The dashed lined represents the 2-fold threshold cutoff value for either over-expression or under-expression.     	65			Figure 7E. Expression Profile of MiR-21 Across Successive Case-Matched Histopathological Tissues The dashed lined represents the 2-fold threshold cutoff value for either over-expression or under-expression.    	66			Figure 7F. Expression Profile of MiR-424 Across Successive Case-Matched Histopathological Tissues The dashed lined represents the 2-fold threshold cutoff value for either over-expression or under-expression.     	67			Figure 7G. Expression Profile of MiR-155 Across Successive Case-Matched Histopathological Tissues The dashed lined represents the 2-fold threshold cutoff value for either over-expression or under-expression.    	68			Figure 7H. Expression Profile of MiR-150 Across Successive Case-Matched Histopathological Tissues The dashed lined represents the 2-fold threshold cutoff value for either over-expression or under-expression.    	69			Figure 7I. Expression Profile of MiR-886-5p Across Successive Case-Matched Histopathological Tissues The dashed lined represents the 2-fold threshold cutoff value for either over-expression or under-expression.      	70			Figure 7J. Expression Profile of MiR-135a Across Successive Case-Matched Histopathological Tissues The dashed lined represents the 2-fold threshold cutoff value for either over-expression or under-expression.      	71			Figure 7K. Expression Profile of MiR-204 Across Successive Case-Matched Histopathological Tissues The dashed lined represents the 2-fold threshold cutoff value for either over-expression or under-expression.    	72			Figure 7L. Expression Profile of MiR-605 Across Successive Case-Matched Histopathological Tissues The dashed lined represents the 2-fold threshold cutoff value for either over-expression or under-expression.    	73			Figure 7M. Expression Profile of MiR-720 Across Successive Case-Matched Histopathological Tissues The dashed lined represents the 2-fold threshold cutoff value for either over-expression or under-expression.     	74			Figure 7N. Expression Profile of MiR-1260 Across Successive Case-Matched Histopathological Tissues The dashed lined represents the 2-fold threshold cutoff value for either over-expression or under-expression.            	75		4.4 Confirmation of Candidate MiRNA Expression We assayed for the expression of miR-224, miR-143, miR-223, miR-155, miR-720 and miR-605 using individual qRT-PCR primer sets, the sequences of which were identical to primers included in the 384-well panels. The levels of each miRNA were re-evaluated in two corresponding cases that previously showed its deregulation. The 2-fold cutoff was implemented once again, while raw data were normalized according to the stably expressed miRNAs, miR-103 and miR-23b. Because the individual assay results for miR-224 failed to match the full panel data, we removed miR-224 from subsequent investigation (Tables 5A and 5B). As for the other 5 miRNA candidates, we detected similar deregulation patterns across both cases (Tables 5A-C). The expression of miR-605 during the individual qRT-PCR runs deviated slightly from the panel results in one of the cases (Table 5C). However, we decided to retain this miRNA in our downstream experiments since it missed the 2-fold cutoff by a negligible margin. In addition, because its association with OSCC has not yet been delineated we viewed it as a potentially interesting miRNA worth exploring.          	76		  Case 2000: Dys vs Norm Case 2000: OSCC vs Norm MiRNA Name Full Panel Fold Change Individual Assay Fold Change Full Panel Fold Change Individual Assay Fold Change miR-224 2.3251 1.8846   miR-143 0.3268 0.2639   miR-223   4.0465 6.7491 miR-155   10.6123 12.0069 miR-720   0.1802 0.2345 miR-605   0.2602 0.2521 Table 5A. Comparison of 384-well Full Panel qRT-PCR Results with Individual Primer Assay Runs in Patient Case 2000 Individual miRNA assay results that deviated from its full panel expression levels are highlighted in red.                5A. 	77		   Case 2076: Dys vs Hyp Caas 2076: OSCC vs Hyp MiRNA Name Full Panel Fold Change Individual Assay Fold Change Full Panel Fold Change Individual Assay Fold Change miR-224 2.4281 0.4511   miR-143 0.3765 0.1726   miR-223   4.1724 7.0273 Table 5B. Comparison of 384-well Full Panel qRT-PCR Results with Individual Primer Assay Runs in Patient Case 2076 Individual miRNA assay results that deviated from its full panel expression levels are highlighted in red.                   5B. 	78		  Case 7071: Dys vs Hyp Case 7071: OSCC vs Hyp MiRNA Name Full Panel Fold Change Individual Assay Fold Change Full Panel Fold Change Individual Assay Fold Change miR-155   6.6449 12.9842 miR-720   0.1456 0.2990 miR-605   0.0638 0.5094 Table 5C. Comparison of 384-well Full Panel qRT-PCR Results with Individual Primer Assay Runs in Patient Case 7071 Individual miRNA assay results that deviated from its full panel expression levels are highlighted in red.                 5C. 	79		4.5 ISH Analysis MiR-155 was identified to be frequently up-regulated in both dysplasia and CIS/OSCC tissues. It also exhibited the highest average fold-changes in expression among candidate miRNAs in both dysplasia (4.14-fold change) and CIS/OSCC (5.1-fold change) groups relative to normal tissues (Tables 4A and 4B). With several recent reports presenting miR-155 as an oncogene candidate in multiple cancer types (including oral cancer), we selected this candidate for further evaluation in a larger sample set. Two tissue microarrays (TMAs) were constructed for verification and validation purposes. The first TMA consisted of biopsies from the 9 patients used for the above qRT-PCR analysis. This TMA was used to confirm a correlation between miR-155 ISH staining and qRT-PCR expression data. ISH staining for miR-155 corresponded with the RT-PCR data for all samples represented on the TMA (Figure 8F-H). The next TMA consisted of an independent panel of 29 tissue cores representing both dysplasia (n = 18) and OSCC (n = 12) cases. Staining of this TMA revealed high miR-155 expression, with elevated levels (assessed through the scoring system previously described in methodology) in 58% (7/12) of OSCC cores and 94% (17/18) of CIS and dysplastic cores. A sample of the positive and negative staining results for miR-155 expression during the TMA tissue validation series is provided in Figure 9. MiR-155 expression did not corresond with HPV infection (present in 28% of the cores). It was observed to be highly expressed in tissues from non-smokers [14/19 (74%)], as well as in all the tissues of smoker patients [10/10 (100%)].    	80			                  Figure 8. Clinical Characterization and Corresponding Histology within an Oral Cancer Field of Patient Case 7071 A) White light visualization. B) Fluorescent visualization of lesions, with biopsied regions encircled.  C-E) Photomicrographs of hematoxylin and eosin stained slides of varying histology: C) adjacent normal, D) dysplasia and  E) CIS.  F-H: Staining results for miR-155 in F) adjacent normal, G) dysplasia and H) CIS. The bottom bar graph displays levels of miR-155 expression obtained via qRT-PCR in the 3 matched histologically distinct tissue samples, which corresponds with the difference in staining intensity.    	81			Figure 9. Validation of MiR-155 Expression via ISH TMA Staining A) High levels of miR-155 expression in a selected OSCC core. B) Absence of miR-155 expression in a separate OSCC core. C) High levels of miR-155 expression in a selected dysplastic core. D) Absence of miR-155 expression in a separate dysplastic core. *All cores were obtained from individual patient cases independent from the initially examined cohort of 27 tissue biopsies.     A D C B 	82		5. Conclusions  5.1 Discussion and Future Perspectives The term “field cancerization” was initially coined by Slaughter et al., with specific reference to oral cancer182. It describes the presence of a contiguous field of preneoplastic cells that surrounds the original tumor and extends beyond the margins visible under standard white light. It is believed that retention of these clinically occult regions predisposes patients to disease recurrence following tumor removal. The formation of genetically altered patches arises when oral mucosa sites are exposed to a carcinogen (e.g. tobacco), introducing genotoxic events into tissue without altering its clinical and histological appearance48.67. The exact molecular process driving “field cancerization” is still up to debate and essentially involves 2 plausible theories: (1) carcinogenic hits at multiple epithelial sites produce independent genetically unrelated lesions; or (2) molecular alterations are acquired by a single progenitor cell which develops into a field of genetically identical daughter cells, ultimately giving rise to clonally-related tumors183,184. “Field cancerization” has been reported and explored in neoplasms of the lung, esophagus, vulva, cervix, anus, colon, breast, bladder, skin, pharynx, larynx, and oral cavity48. Utilization of both conventional screening approaches and novel imaging technologies such as the FV device used in our study, allows a more accurate means to detect the extent of field change172. This allowed us to obtain biopsies of distinct histopathological stages within a single definable oral cancer field and examine molecular alterations that may have functional importance in the initiation or progression of tumorigenesis. Secondly, this approach provided us with an opportunity to study molecular patterns using intra-individual controls and remove further variation that may arise due to timing differences in sampling. 	83		Molecular-targeted therapies are becoming an increasing area of research in relation to oral cancer management, with certain markers being currently investigated in clinical trials67,185. The identification of molecular patterns that specifically occur in histologically distinct regions within altered oral cancer fields may have valuable therapeutic implications. Through our work, we found such alterations when examining miRNA deregulation events (Figures 5-7 and Tables 4A-B). The existence of different disease-related molecular alterations across a cancer field based on histological stage suggests that a given targeted therapy may not prove effective for an entire field – thus setting the stage for post-treatment recurrence. A more suitable method may therefore be to select an agent according to its capacity to suppress the greatest number of abnormal cells that harbor a specific molecular irregularity within a cancerous lesion. MiRNAs offer attractive new options for customized therapies that are either geared towards silencing oncogenic miRNA or re-introducing miRNA that function as tumor-suppressors (miRNA mimics)186. The current challenges that remain to be overcome in miRNA-targeted therapeutics include hybridization-associated off-target effects (largely due to similar seed regions), hybridization-independent off-target effects (such as immunostimulatory effects), and delivery-related concerns.     Aberrant expression of specific biological molecules (including miRNAs) within histopathologically distinct tissues can also have important prognostic applications. With respect to oral cancer, the discovery of novel markers can potentially aid conventional assessment techniques in distinguishing between early premalignant lesions with a high likelihood to transform into invasive disease and those with low progression risk. This would provide an opportunity for earlier intervention and a chance to salvage larger areas of the oral cavity before the need for extensive surgical intervention during advanced disease.  	84		Based on our analyses, the most attractive miRNA candidates for downstream analysis as novel prognostic or therapeutic targets would be those that exhibited altered expression in both dysplasia and CIS/OSCC groups relative to paired normal tissues. MiR-155 may represent such a candidate. Apart from miRNAs encoded by the miR-17-92 cluster, miR-155 was the first miRNA to be over-expressed in multiple types of malignancies84,117,187-194. With respect to oral cancer, elevated levels of miR-155 have been similarly reported117,195. MiR-155 is postulated to down-regulate the tumor-suppressor CDC73, resulting in enhanced cell viability and reduced apoptosis195. Furthermore, expression of miR-155 has been documented to be induced by the TGFβ/Smad pathway, which is understood to be activated in epithelial tumors including OSCC196,197. Through our patient-paired real-time PCR analysis, we observed miR-155 up-regulation in both dysplastic and CIS/OSCC tissues. These results corresponded with miR-155 ISH staining levels in TMAs constructed from the same patient biopsies, as well as TMAs constructed from an independent sample set.    Oral cancer comprises a heterogeneous group of malignancies, with tumors of non-smokers representing a potentially distinct subgroup. Hence, we restricted our analysis to tissues from non-smokers to minimize sample variation. When we evaluated the expression of our miR-155 candidate in a TMA composed of tissues from smoker and non-smoker patients, we found its levels to be enhanced in both groups, without pronounced association between miR-155 expression and smoking status. Neither was an association noted between miR-155 expression and HPV status (a different etiological factor that could play a critical role in development of OSCC in non-smokers). However, differential expression of miR-155 between HPV-positive and HPV-negative HNSCC cell lines (most of which are of oral cavity origin) has already been noted195. Hence, a larger sample set is required to assess whether distinct miR-155 expression 	85		profiles truly exist between tumor subgroups based on etiological factors (smoking, HPV). In addition, it is possible that other key miRNA candidates follow different expression trends across these subgroups.  While the latter portion of this project deals with miR-155, our results support the findings of other studies that demonstrate additional miRNA deregulations in oral and non-oral solid neoplasms. Our detection of miR-143 down-regulation in 5/9 dysplastic samples corresponds with reports claiming it to have tumor-suppressive properties. First, reduced miR-143 levels have been observed in colorectal, gastric, cervical and bladder tumors, as well as esophageal SCC which arises from tissue that is of close proximity and character to the oral mucosa199-204. Secondly, functional cell investigations have shown that miR-143 negatively impacts tumor growth and directly targets known oncogenes204. To the best of our knowledge, our work was the first to depict a decrease in miR-143 expression within oral precancerous tissue specifically. In combination with the aforementioned findings, this suggests miR-143 down-regulation may represent an important early event in oral tumorigenesis requiring further exploration. Among our other miRNA candidates was miR-223, which we found to be up-regulated in 7/9 CIS/OSCC patient specimen. This miRNA has been similarly reported at elevated levels within tongue SCC tissues compared to normal tissues205. Outside the scope of oral cancer, miR-223 has been demonstrated to enhance gastric cancer invasion and metastasis through direct attenuation of the tumor-suppressor EPB41L3206. Elevation of miR-223 levels has also been identified in the serum of hepatocellular carcinoma patients, proposing a biomarker potential207. A recent report of miR-223 up-regulation in esophageal SCC with a causative oncogenic role and a linkage with poorer prognosis validates miR-223 as a good candidate for further studies208. Lastly, we found little literature pertaining to some of our other chief deregulated 	86		candidates, such as miR-720 and miR-605 (both down-regulated in 8/9 CIS/OSCC biopsies). These miRNAs may therefore present an opportunity to be potentially investigated as novel players in oral tumorigenesis via larger scale cohort studies, as well as in vitro models.       5.2 Conclusion In conclusion, our work shows that novel imaging technologies capable of clearly delineating fields of cancerous tissue can be implemented to facilitate stringent investigations into the molecular basis of cancer progression. Second, we report that molecular heterogeneity exists across these altered tissue fields and thus, must be accounted for during selection of biomarker targets for novel anticancer therapies. Third, we propose that miR-155 may represent an early and sustained driver of oral tumorigenesis in non-smokers – and perhaps in smokers as well. The exploration of miRNA-based therapeutics for the management of different pathologies is currently a booming area of research145,169,170,209,210. It is therefore only a matter of time before such agents are introduced into the field of oncology. Likewise, many miRNAs are currently investigated for their potential role as prognostic indicators211,212. Once validated in larger trials, such miRNA biomarkers may have the potential to improve risk assessment during early premalignant disease stages and facilitate treatment decisions. Additional examination of the pathways through which miR-155 and other miRNAs contribute to oral tumorigenesis, as well as the underlying mechanisms through which these miRNAs are deregulated, may shed further light into how these miRNAs can be best manipulated for clinical purposes. 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