Gene expression signature in advanced colorectal cancer patients select drugs and response for the use of leucovorin, fluorouracil, and irinotecan
Gene expression signature in advanced colorectal cancer patients select drugs and response for the use of leucovorin, fluorouracil, and irinotecan
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DOI：
10.1200/jco.2006.07.4187
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发表时间：
2007-03-01
影响因子：
45.3
通讯作者：
Ychou, Marc
中科院分区：
文献类型：
--
作者：
Del Rio, Maguy;Molina, Franck;Ychou, Marc
目的对于晚期结直肠癌患者，亚叶酸、氟尿嘧啶和伊立替康（FOLFIRI）被认为是参考一线治疗方法之一。然而，只有大约一半的治疗患者对该方案有反应，并且没有临床上有用的标志物来预测反应。一个主要的临床挑战是确定可以从这种化疗中获益的患者子集。我们的目的是确定在原发性结肠癌组织中的基因表达谱，可以预测化疗responsibility.Patients和MethodsTumor结肠癌21例晚期结直肠癌患者的样本进行了分析，基因表达谱使用人类基因组基因芯片阵列U133。在一线治疗结束时，根据WHO标准，使用观察到的最佳缓解来定义缓解者和无缓解者。首先通过微阵列算法的显著性分析和受试者工作特征曲线下的面积筛选出具有鉴别力的基因。然后使用支持向量机构建预测分类器。最后，留一法交叉验证被用来估计的性能和准确性的输出类prediction rule.ResultsWe确定了一组14个预测基因的响应FOLFIRI。九个响应者中有九个（100%特异性）和12例无应答者中的11例（92%的敏感性）被正确分类，总体准确率为95%.ConclusionAfter validation in an independent cohort of patients，我们的基因签名可以被用作一个决策工具，以帮助肿瘤学家选择结直肠癌患者谁可以受益于FOLFIRI化疗，无论是在辅助治疗还是一线转移治疗中。
PurposeIn patients with advanced colorectal cancer, leucovorin, fluorouracil, and irinotecan (FOLFIRI) is considered as one of the reference first-line treatments. However, only about half of treated patients respond to this regimen, and there is no clinically useful marker that predicts response. A major clinical challenge is to identify the subset of patients who could benefit from this chemotherapy. We aimed to identify a gene expression profile in primary colon cancer tissue that could predict chemotherapy response.Patients and MethodsTumor colon samples from 21 patients with advanced colorectal cancer were analyzed for gene expression profiling using Human Genome GeneChip arrays U133. At the end of the first-line treatment, the best observed response, according to WHO criteria, was used to define the responders and nonresponders. Discriminatory genes were first selected by the significance analysis of microarrays algorithm and the area under the receiver operating characteristic curve. A predictor classifier was then constructed using support vector machines. Finally, leave-one-out cross validation was used to estimate the performance and the accuracy of the output class prediction rule.ResultsWe determined a set of 14 predictor genes of response to FOLFIRI. Nine of nine responders (100% specificity) and 11 of 12 nonresponders (92% sensitivity) were classified correctly, for an overall accuracy of 95%.ConclusionAfter validation in an independent cohort of patients, our gene signature could be used as a decision tool to assist oncologists in selecting colorectal cancer patients who could benefit from FOLFIRI chemotherapy, both in the adjuvant and the first-line metastatic setting.