High accordance in prognosis prediction of colorectal cancer across independent datasets by multi-gene module expression profiles.

ABSTRACT: A considerable portion of patients with colorectal cancer have a high risk of disease recurrence after surgery. These patients can be identified by analyzing the expression profiles of signature genes in tumors. But there is no consensus on which genes should be used and the performance of specific set of signature genes varies greatly with different datasets, impeding their implementation in the routine clinical application. Instead of using individual genes, here we identified functional multi-gene modules with significant expression changes between recurrent and recurrence-free tumors, used them as the signatures for predicting colorectal cancer recurrence in multiple datasets that were collected independently and profiled on different microarray platforms. The multi-gene modules we ide

SUBMITTER: Li W 

PROVIDER: S-EPMC3306280 | biostudies-literature | 2012

REPOSITORIES: biostudies-literature