In Silico Analysis And Verification Of S100 Gene Expression In Gastric Cancer

Gastric cancer is the second most common cause of cancer death worldwide. Environmental and genetic factors are both important in gastric carcinogenesis. In the past two decades, much progress has been made in identifying genes involved in the development of gastric cancer. These identified genes are useful in understanding the pathogenesis of gastric cancer and defining its molecular signature. They can also serve as biomarkers for early diagnosis and targets for drug development.Recently, large-scale gene expression analyses have emerged as important tools for screening genes related to cance. The two experimental technologies available for large-scale gene expression analysis are: 1) DNA sequencing-based serial analysis of gene expression (SAGE) and expressed sequence tag (EST) approaches and 2) dot-blot based microarray analysis. Multiple bioinformatics infrastructures have been established to compile data derived from these techniques. Among them, the Cancer Genome Anatomy Project (CGAP) and Gene Expression Omnibus (GEO) are two important networks. Previous applications of data mining using CGAP and GEO resource have led to the identification of several novel or known cancer-related genes.The S100 protein family comprises 22 members whose protein sequences encompass at least one EF-hand Ca2+ binding motif. S100 proteins are localized in the cytoplasm and/or nucleus of a wide range of cells, and involved in the regulation of a number of cellular processes such as cell cycle progression and differentiation. Seventeen S100 family members are located as a cluster on chromosome 1q21-22, a region frequently rearranged in several tumors. In addition, molecular analysis has revealed that several S100s, including S100A2, S100A4, S100A7 and S100A10, exhibit altered expression levels in gastric cancer. So it is interesting to systematically investigate the expression of other members of S100 family in normal and gastric cancer tissues.In this study, we utilized the databases and analytical approaches available from the Gene Expression Omnibus and Cancer Genome Anatomy Project to systematically analyze the expression of 22 S100 genes in normal and cancerous stomach tissues.Further,we utilized biological experimental technologies to verify altered-S100 genes in gastric cancer.Part one: In silico analysis of S100 gene expression in gastric cancerObjective: This study was to explore the feasibility and strategy of incor- porating in silico methods to identify human gastric cancer-related S100 genes.Methods: Combined with analysis of series analysis of gene expression, virtual Northern blot and microarray data, the expression levels of S100 family members in normal and malignant stomach tissues were systematically investigated through CGAP and GEO. Results: At least 5 S100 genes were found to be upregulated in gastric cancer by in silico analysis. Among them, four genes, including S100A2,S100A4,S100A7 and S100A10, were reported to overexpressed in gastric cancer previously. This is the first report that S100A3 is overexpressed in gastric cancer.Conclusion: To our knowledge this is the first report of systematic evaluation of S100 gene expressions in gastric cancer by multiple in silico analysis. The results indicated that overexpression of S100 gene family members were characteristics of gastric cancer. Reasonable use of public databases by the internet-available tools is a simple, effective approach to identify cancer-related genes ,and might provide useful clues for further investigation although the results require experimental validation.Part two: In vitro analysis of S100A3 gene expression in gastric cancerObjective: This study was to explore the corelations of S100A3 and gastric cancer in vitro analysis and further to verify the reliability of in silico analysis results. Methods: Combined with analysis of RT-PCR and Western blot, the mRNA and protein expression levels of S100A3 in normal and malignant stomach tissues and cell lines were systematically investigated. Tissue microarray(TMA) was futher used to verify S100A3 expression. Results: The mean expression levels of S100A3 in gastric cancer tissues were 2.5 times as high as in adjacent non-tumorous tissues. S100A3 expression was correlated with tumor differentiation and TNM (Tumor-Node-Metastasis) stage of gastric cancer.S100A3 was overexpression in gastric cancer cell lines .The rate of detection of the S100A3 mRNA was lower than the S100A3 protein.Conclusion: This is the first report that S100A3 is gastric cancer associated gene and overexpressed S100A3 may be associated with the differentiation and progression of gastric cancer. Part three: Effects of S100A3 gene on biological characteristics of gastri cancer cell linesObjective: This study was to inhibit the S100A3 gene expression by RNA interference to investigate the changes in cell cycle progression and growth. Methods: S100A3-specific siRNA was designed according to software of Ambion. S100A3-specific shRNA expression vector was constructed by using recombinant DNA technology and transfected into gastric cancer cell line BGC823 cell.The expression of S100A3 gene was analyzed by RT-PCR;Cell cycle and apoptosis were detected by flowcytometry;Cell proliferation was detected by MTT. Results: 1.The influence of RNAi on expression of S100A3 gene in gastric cancer cell BGC823 cell:After transfection of S100A3-shRNA into BGC823 cell,the expression of S100A3 gene was significantly inhibited as detected by RT-PCR.2.The influence of RNAi on gastric cancer cell apoptosis and proliferation :The inhibition of expression of S100A3 gene promotes apoptosis,induces the arrest of cell cycle in Gl Phase,and decreases proliferation ability of gastric cancer cell BGC823. Conclusion: S100A3-specific shRNA expression vector may efficiently inhibit the expression after transfected into gastric cancer. S100A3-specific shRNA increases apoptosis,decrease proliferation ability,and induces the arrest of cell cycle in Gl Phase.