Response Predictors of S-1, Cisplatin, and Docetaxel Combination Chemotherapy for Metastatic Gastric Cancer: Microarray Analysis of Whole Human Genes
Response Predictors of S-1, Cisplatin, and Docetaxel Combination Chemotherapy for Metastatic Gastric Cancer: Microarray Analysis of Whole Human Genes
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DOI：
10.1159/000464329
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发表时间：
2017-01-01
期刊：
影响因子：
3.5
通讯作者：
Takayama, Tetsuji
中科院分区：
文献类型：
--
作者：
Kitamura, Shinji;Tanahashi, Toshihito;Takayama, Tetsuji
目的：本研究的目的是使用化疗前活检标本的微阵列来确定预测多西他赛、顺铂和S-1（DCS）治疗晚期胃癌疗效的生物标志物。方法：从19例接受DCS作为一线治疗的不可切除转移性胃癌患者中采集19份样本。进行激光捕获显微切割，并从每个显微切割的样品中提取总细胞RNA。通过微阵列分析全基因表达，并通过定量实时PCR证实用微阵列观察到的mRNA表达差异。免疫组织化学染色使用临床组织切片获得内镜活检。结果：11例患者被确定为DCS治疗的早期应答者，8例患者为无应答者。29个基因在肿瘤组织和正常组织中的相对表达率有显著性差异。一个包含29个基因的分类器集对于区分11个早期应答者和8个非应答者之间的基因表达具有较高的准确性（94.7%）。将分类器集的大小减小到4个基因（PDGFB、PCGF 3、CISH和ANXA 5）将准确度提高到100%。通过实时PCR验证的表达水平与微阵列中的这4个基因具有良好的相关性。结论：筛选出的基因可作为个体化肿瘤靶向治疗的有效生物标志物。(C)2017 S. Karger AG，巴塞尔。
Objectives: The aim of this study was to identify biomarkers for predicting the efficacy of docetaxel, cisplatin, and S-1 (DCS) therapy for advanced gastric cancer using microarrays of biopsy specimens before chemotherapy. Methods: Nineteen samples were taken from 19 patients with unresectable metastatic gastric cancer who received DCS as a first-line therapy. Laser capture microdissection was performed, and total cellular RNA was extracted from each microdissected sample. Whole-gene expression was analyzed by microarray, and the difference in mRNA expression observed with the microarrays was confirmed by quantitative real-time PCR. Immunohistochemical staining was performed using clinical tissue sections obtained by endoscopic biopsy. Results: Eleven patients were identified as early responders and 8 patients as nonresponders to DCS therapy. Twentynine genes showed significant differences in relative expression ratios between tumor and normal tissues. A classifier set of 29 genes had high accuracy (94.7%) for distinguishing gene expression between 11 early responders and 8 nonre-sponders. Decreasing the size of the classifier set to 4 genes (PDGFB, PCGF3, CISH, and ANXA5) increased the accuracy to 100%. Expression levels by real-time PCR for validation were well correlated with those 4 genes in microarrays. Conclusion: The genes identified may serve as efficient biomarkers for personalized cancer-targeted therapy. (C) 2017 S. Karger AG, Basel.