Department of Systems Biology, Division of Cancer Medicine, The University of Texas M. D. Anderson Cancer Center, Houston, Texas 77054, USA.
Clin Cancer Res. 2011 Apr 1;17(7):1850-7. doi: 10.1158/1078-0432.CCR-10-2180. Epub 2011 Mar 29.
Despite continual efforts to develop a prognostic model of gastric cancer by using clinical and pathologic parameters, a clinical test that can discriminate patients with good outcomes from those with poor outcomes after gastric cancer surgery has not been established. We aim to develop practical biomarker-based risk score that can predict relapse of gastric cancer after surgical treatment.
Microarray technologies were used to generate and analyze gene expression profiling data from 65 gastric cancer patients to identify biomarker genes associated with relapse. The association of expression patterns of identified genes with relapse and overall survival was validated in independent gastric cancer patients.
We uncovered two subgroups of gastric cancer that were strongly associated with the prognosis. For the easy translation of our findings into practice, we developed a scoring system based on the expression of six genes that predicted the likelihood of relapse after curative resection. In multivariate analysis, the risk score was an independent predictor of relapse in a cohort of 96 patients. We were able to validate the robustness of the six-gene signature in an additional independent cohort.
The risk score derived from the six-gene set successfully prognosticated the relapse of gastric cancer patients after gastrectomy.
尽管一直在努力通过临床和病理参数来开发胃癌的预后模型，但尚未建立一种能够区分胃癌手术后预后良好和预后不良患者的临床检测方法。我们旨在开发实用的基于生物标志物的风险评分，以预测胃癌手术后的复发。
使用微阵列技术从 65 名胃癌患者中生成和分析基因表达谱数据，以鉴定与复发相关的生物标志物基因。在独立的胃癌患者中验证了鉴定基因的表达模式与复发和总生存的相关性。
我们发现了两种与预后密切相关的胃癌亚组。为了方便将我们的发现转化为实践，我们开发了一种基于六种基因表达的评分系统，该系统预测了根治性切除术后复发的可能性。在多变量分析中，风险评分是 96 名患者队列中复发的独立预测因子。我们能够在另一个独立的队列中验证六个基因特征的稳健性。
从六个基因集得出的风险评分成功地预测了胃癌患者胃切除术后的复发。
