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目的用限制片段差异显示聚合酶链反应(restrictionfragmentdifferentialdisplaypolymerasechainreaction,RFDDPCR)技术建立基因表达谱,分析比较人类疾病表达谱差异的可行性。方法采集乳腺癌根治术患者的乳腺癌组织、乳腺癌转移淋巴结及正常乳腺组织,用RFDDPCR技术平行操作,获得3种组织全部转录物组片段。然后以7%尿素变性聚丙烯酰胺凝胶电泳进行表达差异基因片段的分离、显示,结合http://www.Qbiogene.com/display/数据库资料,进行生物信息学分析,初步筛选各组织间有表达差异的基因。结果建立了乳腺癌组织、乳腺癌转移淋巴结及正常乳腺组织的基因表达谱,获得基因片段5407个,其中在癌组织和正常组织间有表达差异的片段为1491个,癌组织与转移淋巴结间的差异片段有1176个,而转移淋巴结与正常组织间的差异片段为1462个,分别占表达数的40.9%,33.9%,39.6%。这些差异片段涉及细胞增殖分化,信号转导,炎性反应,肿瘤转移等多方面功能。结论RFDDPCR技术可以检测出大量表达基因,并同时比较3种或3种以上样本的表达差异,适用于人类疾病差异表达谱分析,筛选出疾病的候选基因。同时,还有可能找到新基因或新表达序列标签。
OBJECTIVE: To establish a gene expression profile by restriction fragment differential PCR (RFDDPCR) and to analyze and compare the differences of human disease expression profiles. Methods Breast cancer tissues, breast cancer metastatic lymph nodes and normal breast tissues were collected from patients with radical mastectomy. All the three transcriptome fragments were obtained by RFDDPCR. Then, 7% urea denatured polyacrylamide gel electrophoresis was used to separate the differentially expressed genes. The bioinformatics analysis was carried out based on the database of http://www.Qbiogene.com/display/, Genes that express differences. Results The gene expression profiles of breast cancer tissues, lymph node metastasis of breast cancer and normal breast tissues were established. A total of 5407 gene fragments were obtained, of which 1491 were differentially expressed between cancer tissues and normal tissues. There were 1491 fragments between cancer tissues and metastatic lymph nodes There were 1176 differential fragments and 1462 differential fragments between metastatic lymph nodes and normal tissues, accounting for 40.9%, 33.9% and 39.6% of the total. These differential fragments involved in various aspects of cell proliferation and differentiation, signal transduction, inflammatory response, tumor metastasis and other functions. Conclusion RFDDPCR can detect a large number of expressed genes, and at the same time compare the expression differences of three or more samples for differential expression profiling of human diseases and screen out candidate genes for disease. At the same time, it is also possible to find new genes or newly expressed sequence tags.