Gene expression profiles accurately predict outcome following liver resection in patients with metastatic colorectal cancer.

Published online

Journal Article

PURPOSE: The aim of this study was to build a molecular prognostic model based on gene signatures for patients with completely resected hepatic metastases from colorectal cancer (MCRC). METHODS: Using the Illumina HumanHT-12 gene chip, RNA samples from the liver metastases of 96 patients who underwent R0 liver resection were analyzed. Patients were randomly assigned to a training (n = 60) and test (n = 36) set. The genes associated with disease-specific survival (DSS) and liver-recurrence-free survival (LRFS) were identified by Cox-regression and selected to construct a molecular risk score (MRS) using the supervised principle component method on the training set. The MRS was then evaluated in the independent test set. RESULTS: Nineteen and 115 genes were selected to construct the MRS for DSS and LRFS, respectively. Each MRS was validated in the test set; 3-year DSS/LRFS rates were 42/32% and 79/80% for patients with high and low MRS, respectively (p = 0.007 for DSS and p = 0.046 for LRFS). In a multivariate model controlling for a previously validated clinical risk score (CRS), the MRS remained a significant predictor of DSS (p = 0.001) and LRFS (p = 0.03). When CRS and MRS were combined, the patients were discriminated better with 3-year DSS/LRFS rates of 90/89% in the low risk group (both risk scores low) vs 42/26% in the high risk group (both risk scores high), respectively (p = 0.002/0.004 for DSS/LRFS). CONCLUSION: MRS based on gene expression profiling has high prognostic value and is independent of CRS. This finding provides a potential strategy for better risk-stratification of patients with liver MCRC.

Full Text

Duke Authors

Cited Authors

  • Ito, H; Mo, Q; Qin, L-X; Viale, A; Maithel, SK; Maker, AV; Shia, J; Kingham, P; Allen, P; DeMatteo, RP; Fong, Y; Jarnagin, WR; D'Angelica, M

Published Date

  • 2013

Published In

Volume / Issue

  • 8 / 12

Start / End Page

  • e81680 -

PubMed ID

  • 24339954

Pubmed Central ID

  • 24339954

Electronic International Standard Serial Number (EISSN)

  • 1932-6203

Digital Object Identifier (DOI)

  • 10.1371/journal.pone.0081680

Language

  • eng

Conference Location

  • United States