Screening And Identification Of Genes Associated With Oral Submucous Fibrosis

Oral submucous Fibrosis(OSF) is a kind of chronic insidious disease and it predisposes to cancer, the main aetiological factor of which is betel nut chewing. As a precancerous condition regarded by WHO, the malignant transformation rate of OSF was 7.6%. The pathogenesis of OSF is still unknown. The development of gene chip technology and bioinformatics boosts greatly our ability of studying biology medicine and exploring the molecular mechanism of diseases. Gene chip technology has become more and more important because of its virtue of high throughput, parallel detection, micromation etc, and it is now widely used in many fields including medical and biological researches.In this study, we studied the gene expression profiles of human OSF and normal buccal mucosa tissues by using the Affymetrix U133A 2.0 chips, and analyzed the differentially expressed genes of OSF tissues screened by microarray by using several bioinformatics tools. Candidate genes were further validated using semi- quantitative RT-PCR. The results obtained from the present study, therefore, determine the molecular pathways potentially involved in OSF pathogenesis and lay the groundwork for future analysis of these potential markers/targets for clinical utility in the diagnosis, prognosis and treatment of OSF.Chapter I : Identification of differentially expressed genes associated with oral submucous fibrosisObjective: To establish the gene expression profiling of OSF and screen differentially expressed genes of OSF.Material and Methods: Total RNA was isolated from buccal mucosa tissue samples of 4 OSF patients and 4 normal persons. Five ug of total RNA were used to prepare biotinylated cRNAs for hybridization using the standard Affymetrix protocol. After sample quality evaluation using a control microarray (Test 3), the hybridization cocktails were hybridized to the human genome U133A 2.0 GeneChips. After hybridization, washing and scanning, the hybridization data were exported using GeneChip Operating software (GCOS 1.4). The raw signal of individual probes for the 8 arrays were normalized against the chip with median raw signal intensity using the dchip software (dChip2006). Differentially expressed genes were identified by supervised analysis with the Significance Analysis of Microarrays (SAM) software. Normalized expression values from dChip analysis were used for a two class paired SAM analysis. The SAM software estimated the false discovery rate and generated a q value for each gene.Results: The results of hybridization of GeneChips accorded with the standard of quality control for affymetrix genechip. Using a q value of < 5%, a total of 865 significant probe sets were identified to have more than 2-fold changes between the OSF and normal buccal mucosa tissues. There were 716 up-regulated and 149 down-regulated probe sets in OSF.Conclusion: The gene expression profiles of OSF were established in whole genome. Differentially expressed genes associated with OSF were identified to provide theoretical foundation for the further studies in the molecular pathogenesis involved in OSF and searching potential biomarkers.Chapter II: The second Screen of the Differential Expression Genes of OSF using bioinformatics toolsObjective: To apply the bioinformatics tools for analyzing the differentially expressed genes in OSF to obtain the implied biological significance.Material and Methods: Several bioinformatic analysises were used in the second screening of 865 differentially expressed genes in OSF, which included cluster analysis, gene ontology(GO) analysis, pathway analysis, chromosome location, analysis of genetic-association diseases and MILANO analysis..Results: Cluster analysis showed the differential expression genes could distinguish OSF from normal tissues perfectly, the most striking subclusters were the immunity-related genes. GO classification of the differentially expressed genes identified the biological process subgroups, including genes involved in immune response, cell adhesion, inflammatory response, regulation of transcription, DNA-dependent et al. Cellular component subgroups consisted of genes mainly located in extracellular region, extracellular matrix and plasma membrane, membrane, integral to membrane. The function of 119 genes remains unkown. The others were mostly related to ion bingding, extracellular matrix structural constituent, receptor activity et el. Pathway analysis suggested the differently expressed genes mainly involved in pathways including antigen processing and presentation, ECM-receptor interaction, focal adhesion, cell adhesion molecules, cytokine-cytokine receptor interaction, TGF-beta signaling pathway et al. A majority of the differentially expressed genes were located on chromosome 1, 2, 5, 6, 7, 11, 12 (P<0.01).The diseases genetic associated with OSF included infection, immune and cardiovascular diseases. MILANO analysis revealed many genes wildly studied in fibrosis and cancer showed occurrences of low frequency in studies of OSF.Conclusion: Bioinformatic tools can provide the quick and parallel analysis of massive data derived from genechips and enable the function classification of the differentially expressed genes, which provides new clues on the research of pathogenesis and epidemiology of OSF.Chapter III: Verification of partial differently expressed genes of OSF by semi quantitative RT-PCRObjective: To valid candidate genes and explore their significance in the pathogenesis of OSF.Material and Methods: Candidate genes were chosen according to the result of bioinformatics analysis and literature review. The total RNA of 11 specimens of OSF buccal mucosa and 10 specimens of normal mucosa was extracted respectively. The reverse transcription polymerase chain reaction (RT-PCR) was used to examine the levels of mRNA of candidate genes in the buccal mucosa of OSF and normal buccal mucosa. Results: Six EMT-related genes were chosen to be valid by RT-PCR, which included SFRP4, THBS1, MMP2, CDH11, ZO-1, and CK18. Except for CDH11, the results of RT-PCR showed the consistent trend of change with the results of genechip (P<0.05).Conclusion: The results of genechip were demonstrated credible. EMT might play an important role in the pathogenesis of OSF.