Barrier Alain, Lemoine Antoinette, Boelle Pierre-Yves, Tse Chantal, Brault Didier, Chiappini Franck, Breittschneider Julia, Lacaine François, Houry Sidney, Huguier Michel, Van der Laan Mark J, Speed Terry, Debuire Brigitte, Flahault Antoine, Dudoit Sandrine
Service de Chirurgie Digestive, Hôpital Tenon, Université Pierre et Marie Curie, Assistance Publique, 75020 Paris, France.
Oncogene. 2005 Sep 8;24(40):6155-64. doi: 10.1038/sj.onc.1208984.
This study assessed the possibility to build a prognosis predictor, based on microarray gene expression measures, in stage II and III colon cancer patients. Tumour (T) and non-neoplastic mucosa (NM) mRNA samples from 18 patients (nine with a recurrence, nine with no recurrence) were profiled using the Affymetrix HGU133A GeneChip. The k-nearest neighbour method was used for prognosis prediction using T and NM gene expression measures. Six-fold cross-validation was applied to select the number of neighbours and the number of informative genes to include in the predictors. Based on this information, one T-based and one NM-based predictor were proposed and their accuracies were estimated by double cross-validation. In six-fold cross-validation, the lowest numbers of informative genes giving the lowest numbers of false predictions (two out of 18) were 30 and 70 with the T and NM gene expression measures, respectively. A 30-gene T-based predictor and a 70-gene NM-based predictor were then built, with estimated accuracies of 78 and 83%, respectively. This study suggests that one can build an accurate prognosis predictor for stage II and III colon cancer patients, based on gene expression measures, and one can use either tumour or non-neoplastic mucosa for this purpose.
本研究评估了基于微阵列基因表达测量结果为II期和III期结肠癌患者构建预后预测模型的可能性。使用Affymetrix HGU133A基因芯片对18例患者（9例复发，9例未复发）的肿瘤（T）和非肿瘤性黏膜（NM）mRNA样本进行分析。采用k近邻法，利用T和NM基因表达测量结果进行预后预测。应用六重交叉验证来选择预测模型中邻居的数量和信息基因的数量。基于这些信息，提出了一个基于T的预测模型和一个基于NM的预测模型，并通过双重交叉验证估计它们的准确性。在六重交叉验证中，使用T和NM基因表达测量结果时，给出错误预测数量最少（18例中有2例）的信息基因的最低数量分别为30个和70个。然后构建了一个基于30个基因的T预测模型和一个基于70个基因的NM预测模型，估计准确率分别为78%和83%。本研究表明，基于基因表达测量结果可以为II期和III期结肠癌患者构建准确的预后预测模型，并且可以为此目的使用肿瘤或非肿瘤性黏膜。
