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Gene expression profiling of gastric cancer by microarray combined with laser capture microdissection.

机译:芯片与激光捕获显微切割相结合的胃癌基因表达谱。

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AIM: To examine the gene expression profile of gastric cancer (GC) by combination of laser capture microdissection (LCM) and microarray and to correlate the profiling with histological subtypes. METHODS: Using LCM, pure cancer cells were procured from 45 cancerous tissues. After procurement of about 5000 cells, total RNA was extracted and the quality of RNA was determined before further amplification and hybridization. One microgram of amplified RNA was converted to cDNA and hybridized to cDNA microarray. RESULTS: Among 45 cases, only 21 were qualified for their RNAs. A total of 62 arrays were performed. These included 42 arrays for cancer (21 cases with dye-swab duplication) and 20 arrays for non-tumorous cells (10 cases with dye-swab duplication) with universal reference. Analyzed data showed 504 genes were differentially expressed and could distinguish cancerous and non-cancerous groups with more than 99% accuracy. Of the 504 genes, trefoil factors 1, 2, and 3 were in the list and their expression patterns were consistent with previous reports. Immunohistochemical staining of trefoil factor 1 was also consistent with the array data. Analyses of the tumor group with these 504 genes showed that there were 3 subgroups of GC that did not correspond to any current classification system, including Lauren's classification. CONCLUSION: By using LCM, linear amplification of RNA, and cDNA microarray, we have identified a panel of genes that have the power to discriminate between GC and non-cancer groups. The new molecular classification and the identified novel genes in gastric carcinogenesis deserve further investigations to elucidate their clinicopathological significance.
机译:目的:通过激光捕获显微切割术(LCM)和微阵列技术检测胃癌(GC)的基因表达谱,并将其与组织学亚型相关联。方法:使用LCM,从45个癌组织中获得纯癌细胞。购买约5000个细胞后,提取总RNA,并在进一步扩增和杂交之前确定RNA的质量。将一微克扩增的RNA转换为cDNA,并与cDNA微阵列杂交。结果:在45例中,只有21例符合其RNA的标准。总共进行了62个阵列。其中包括42个用于癌症的阵列(21个带有染色棒重复的病例)和20个用于非肿瘤细胞的阵列(10个带有染色棒重复的病例)。分析数据显示504个基因差异表达,可以区分癌和非癌组,准确率超过99%。在504个基因中,三叶因子1、2和3在列表中,它们的表达方式与以前的报道一致。三叶因子1的免疫组织化学染色也与阵列数据一致。用这504个基因对肿瘤进行的分析表明,有3个GC亚组与当前的分类系统(包括Lauren's分类)不符。结论:通过使用LCM,RNA线性扩增和cDNA微阵列,我们已经鉴定出一组能够区分GC和非癌基因的基因。胃癌发生中的新分子分类和已鉴定的新基因值得进一步研究,以阐明其临床病理意义。

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