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利用丝氨酸蛋白酶及其抑制剂开发胃癌生存预测模型。

Development of a survival prediction model for gastric cancer using serine proteases and their inhibitors.

作者信息

Lei Ke-Feng, Liu Bing-Ya, Zhang Xiao-Qing, Jin Xiao-Long, Guo Yan, Ye Min, Zhu Zheng-Gang

机构信息

Department of Surgery, Shanghai Institute of Digestive Surgery;

出版信息

Exp Ther Med. 2012 Jan;3(1):109-116. doi: 10.3892/etm.2011.353. Epub 2011 Sep 21.

Abstract

Proteolytic enzymes play a key role in the metastatic stage of gastric cancer (GC). In this study, we aimed to identify the serine proteases (SPs) and their inhibitors (serpins) as related to GC. The gene expression profiles of 40 cases of GC were initially detected by cDNA microarray. The results of the differentially expressed SPs and their inhibitor genes from the microarrays were confirmed by real-time PCR. The status of the immunohistochemical staining of the confirmed genes in patients with complete data was used to develop a survival prediction model. Finally, the prediction model was tested in different groups of GC patients. As a result, seven genes, SERPINB5, KLK10, KLK11, HPN, SPINK1, SERPINA5 and PRSS8, were considered as GC progression-related genes. A survival prediction model including the immunohistochemical scores of three genes and the tumor node metastasis (TNM) score was developed: Survival time (months) = 88.8607 + 2.6395 SERPINB5 - 12.0772 KLK10 + 13.7562 KLK11 - 7.0318 TNM. In conclusion, SERPINB5, KLK10, KLK11, HPN, SPINK1, SERPINA5 and PRSS8 were GC progression-related SPs or serpin genes. The model consisting of the expression profiles of three genes extracted from the microarray study accompanied by the TNM score accurately predicts surgery-related survival of GC patients.

摘要

蛋白水解酶在胃癌(GC)的转移阶段起着关键作用。在本研究中,我们旨在鉴定与GC相关的丝氨酸蛋白酶(SPs)及其抑制剂(丝氨酸蛋白酶抑制剂)。首先通过cDNA微阵列检测40例GC的基因表达谱。通过实时PCR确认微阵列中差异表达的SPs及其抑制基因的结果。利用具有完整数据的患者中经确认基因的免疫组织化学染色状态建立生存预测模型。最后,在不同组的GC患者中对该预测模型进行测试。结果,七个基因,即丝氨酸蛋白酶抑制剂B5(SERPINB5)、激肽释放酶10(KLK10)、激肽释放酶11(KLK11)、肝细胞生成素(HPN)、丝氨酸蛋白酶抑制剂Kazal型1(SPINK1)、丝氨酸蛋白酶抑制剂A5(SERPINA5)和蛋白酶3型丝氨酸蛋白酶8(PRSS8),被认为是与GC进展相关的基因。建立了一个包括三个基因的免疫组织化学评分和肿瘤淋巴结转移(TNM)评分的生存预测模型:生存时间(月)= 88.8607 + 2.6395×SERPINB5 - 12.0772×KLK10 + 13.7562×KLK11 - 7.0318×TNM。总之,SERPINB5、KLK10、KLK11、HPN、SPINK1、SERPINA5和PRSS8是与GC进展相关的丝氨酸蛋白酶或丝氨酸蛋白酶抑制剂基因。由微阵列研究中提取的三个基因的表达谱以及TNM评分组成的模型能够准确预测GC患者的手术相关生存率。

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