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背景:基因芯片等高通量的研究手段已在肿瘤研究中得到广泛的应用,胃癌方面的研究主要集中在手术切除标本,对胃镜下取得的疑似胃癌组织的基因表达比较研究则较少报道。目的:比较胃镜下取得的病理诊断为胃癌和非癌样品的基因表达谱特征,为识别胃癌早期诊断的指标和疾病的分子分型奠定基础。方法:内镜下取47例胃癌疑似病变组织和对应非病变组织,经病理学诊断为胃癌28例,非癌病变19例。提取RNA,采用含14592个点的人cDNA芯片,经RNA放大技术进行基因表达谱的检测,检测结果采用GeneSpring软件分析,数据标准化用局部加权回归分析(LOWESS)处理,胃癌和非癌两组样品的组内和组间差异的显著性分析应用差异显著性分析(SAM)方法。结果:以30%样品中的表达调节水平大于1.5倍作为差异基因筛选标准,胃癌组表达上调的基因有133个,下调的有143个。非胃癌样品中有51个基因表达上调,22个表达下调,其中分别有18个上调基因和13个下调基因与胃癌组相同。组间差异分析筛选出40个基因,其表达调节可以由之进行胃癌和非癌组样品的区分。结论:基因表达谱芯片技术可以有效地应用于识别胃癌和非癌样品中的差异表达基因,并可用于肿瘤发病机制和分子分型的研究。
BACKGROUND: High-throughput methods such as gene chip have been widely used in cancer research. The studies on gastric cancer mainly focus on the resected specimens, and the comparative studies on the gene expression of suspected gastric cancer tissues obtained under endoscopy are rarely reported. OBJECTIVE: To compare the gene expression profiles of gastric and non-cancerous samples obtained by gastroscopy, and to lay a foundation for identifying the indicators of early diagnosis of gastric cancer and the molecular typing of the disease. Methods: Twenty-seven cases of suspected gastric lesion and corresponding non-diseased tissue were taken under endoscopy. 28 cases were diagnosed as gastric cancer by pathology and 19 cases were non-cancerous lesions. RNA was extracted and human cDNA chips containing 14592 spots were used to detect the gene expression profile by RNA amplification. The detection results were analyzed by GeneSpring software. The data were standardized by LOWESS, gastric and non-cancer samples Significant analysis of intra- and inter-group differences was performed using the difference significance analysis (SAM) method. Results: Thirty-three of the up-regulated genes were up-regulated in 143 of the gastric cancer patients, with the level of expression being greater than 1.5-fold in 30% of the samples as the differential gene screening criteria. 51 genes were up-regulated and 22 down-regulated in non-gastric cancer samples, of which 18 up-regulated genes and 13 down-regulated genes were the same in gastric cancer group. Forty genes were screened by the difference analysis between groups. The expression of these genes could be differentiated between gastric and noncancerous samples. Conclusion: Gene expression microarray technology can be effectively applied to identify differentially expressed genes in gastric and non-cancerous samples, and can be used in the study of tumor pathogenesis and molecular typing.