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目的:研究胃癌多药耐药相关microRNA并对其进行鉴定、靶基因预测和预测靶基因的生物信息学分析。方法:运用microRNA芯片对胃癌多药耐药细胞SGC7901/ADR和其亲本细胞SGC7901进行microRNA表达谱分析;采用实时定量PCR的方法对差异表达的miRNA进行验证;再运用生物信息学方法对差异表达的miRNA进行靶基因预测;再对预测的靶基因进行GO和KEGG通路分析。结果:与SGC7901相比SGC7901/ADR表达上调超过2倍的miRNA有6个,表达下调超过2倍的有11个。实时定量PCR对共同差异表达的microRNA进行验证显示与芯片结果的一致性。对这17个差异表达的miRNA进行靶基因预测,再对预测得到的靶基因进行GO和KEGG通路分析显示预测的靶基因参与了肿瘤相关通路、MAPK通路、Focal Adhesion通路等。结论:我们初步筛选得到了胃癌多药耐药相关miRNA并对其进行了生物信息学分析,为进一步地探索miRNA在胃癌多药耐药中的作用及其分子机制奠定了基础。
OBJECTIVE: To study and identify multidrug resistance related microRNAs in gastric cancer and to predict their target genes and bioinformatics analysis of target genes. Methods: The microRNA expression profiles of SGC7901 / ADR cells and their parental SGC7901 cells were analyzed by microRNA microarray. The miRNAs were differentially expressed by real-time PCR. Bioinformatics methods were used to analyze the differentially expressed miRNA target gene prediction; and then predict the target gene GO and KEGG pathway analysis. RESULTS: Six of the miRNAs up-regulated more than 2-fold in SGC7901 / ADR compared with SGC7901 and 11 in more than 2-fold down-regulated expression. Real-time quantitative PCR validation of differentially expressed microRNAs showed agreement with the chip results. Targeted gene prediction of the 17 differentially expressed miRNAs, and GO and KEGG pathway analysis of the predicted target genes revealed that the predicted target genes are involved in tumor-associated pathways, MAPK pathway, Focal Adhesion pathway, and the like. CONCLUSION: Our preliminary screening of multi-drug resistant miRNAs in gastric cancer and their bioinformatics analysis provide a basis for further exploration of miRNAs in multidrug resistance of gastric cancer and their molecular mechanisms.