Metastasis-Associated Gene Expression Changes Predict Poor Outcomes in Patients with Dukes Stage B and C Colorectal Cancer.
Metastasis-Associated Gene Expression Changes Predict Poor Outcomes in Patients with Dukes Stage B and C Colorectal Cancer.
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DOI：
10.1158/1078-0432.ccr-09-1431
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发表时间：
2009-12-15
期刊：
影响因子：
--
通讯作者：
Sieber OM
中科院分区：
文献类型：
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作者：
Jorissen RN;Gibbs P;Christie M;Prakash S;Lipton L;Desai J;Kerr D;Aaltonen LA;Arango D;Kruhøffer M;Orntoft TF;Andersen CL;Gruidl M;Kamath VP;Eschrich S;Yeatman TJ;Sieber OM
Colorectal cancer prognosis is currently predicted from pathological staging, providing limited discrimination for Dukes’ stage B and C disease. Additional markers for outcome are required to help guide therapy selection for individual patients. A multi-site single-platform microarray study was performed on 553 colorectal cancers. Gene expression changes were identified between stage A and D tumors (three training sets) and assessed as a prognosis signature in stage B and C tumors (independent test and external validation sets). 128 genes showed reproducible expression changes between three sets of stage A and D cancers. Using consistent genes, stage B and C cancers clustered into two groups resembling early-stage and metastatic tumors. A Prediction Analysis of Microarray (PAM) algorithm was developed to classify individual intermediate-stage cancers into stage A-like/good prognosis or stage D-like/poor prognosis types. For stage B patients, the treatment adjusted hazard ratio for six-year recurrence in individuals with stage D-like cancers was 10.3 (95% CI 1.3 to 80.0, P=0.011). For stage C patients, the adjusted hazard ratio was 2.9 (95% CI 1.1 to 7.6, P=0.016). Similar results were obtained for an external set of stage B and C patients. The prognosis signature was enriched for down-regulated immune response genes and up-regulated cell signaling and extracellular matrix genes. Accordingly, sparse tumor infiltration with mononuclear chronic inflammatory cells was associated with poor outcome in independent patients. Metastasis-associated gene expression changes can be used to refine traditional outcome prediction, providing a rational approach for tailoring treatments to subsets of patients.
