Del Rio Maguy, Molina Franck, Bascoul-Mollevi Caroline, Copois Virginie, Bibeau Frédéric, Chalbos Patrick, Bareil Corinne, Kramar Andrew, Salvetat Nicolas, Fraslon Caroline, Conseiller Emmanuel, Granci Virginie, Leblanc Benjamin, Pau Bernard, Martineau Pierre, Ychou Marc
Centre National de la Recherche Scientifique Unité Mixte de Recherche 5160, Service d'Anatomie pathologique, Service d'Oncologie Digestive, Montpellier, France.
J Clin Oncol. 2007 Mar 1;25(7):773-80. doi: 10.1200/JCO.2006.07.4187.
In 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.
Tumor 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.
We 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%.
After 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.
在晚期结直肠癌患者中，亚叶酸、氟尿嘧啶和伊立替康（FOLFIRI）被视为参考一线治疗方案之一。然而，只有约一半的接受治疗的患者对该方案有反应，且尚无临床可用的预测反应的标志物。一项主要的临床挑战是识别能从这种化疗中获益的患者亚组。我们旨在确定原发性结肠癌组织中可预测化疗反应的基因表达谱。
使用人类基因组基因芯片U133对21例晚期结直肠癌患者的肿瘤结肠样本进行基因表达谱分析。在一线治疗结束时，根据世界卫生组织标准，将最佳观察反应用于定义反应者和无反应者。首先通过微阵列算法的显著性分析和受试者操作特征曲线下面积选择具有鉴别意义的基因。然后使用支持向量机构建预测分类器。最后，采用留一法交叉验证来估计输出类别预测规则的性能和准确性。
我们确定了一组14个对FOLFIRI反应的预测基因。9例反应者中的9例（特异性100%）和12例无反应者中的11例（敏感性92%）被正确分类，总体准确率为95%。
在独立患者队列中验证后，我们的基因特征可作为一种决策工具，协助肿瘤学家在辅助和一线转移情况下选择可从FOLFIRI化疗中获益的结直肠癌患者。
