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Clin Cancer Res. 2016 Feb 1;22(3):734-45. doi: 10.1158/1078-0432.CCR-15-0143. Epub 2015 Oct 7.

A Composite Gene Expression Signature Optimizes Prediction of Colorectal Cancer Metastasis and Outcome.

Author information

1
Moffitt Cancer Center & Research Institute, Tampa, Florida. Yeatman@gibbscc.org Michael.schell@moffitt.org.
2
Gibbs Cancer Center & Research Institute, Spartanburg, South Carolina.
3
SIB Swiss Institute of Bioinformatics, Lausanne, Switzerland.
4
SIB Swiss Institute of Bioinformatics, Lausanne, Switzerland. Ludwig Center for Cancer Research, University of Lausanne (CH), Lausanne, Switzerland. Department of Oncology, University of Lausanne (CH), Lausanne, Switzerland.
5
Moffitt Cancer Center & Research Institute, Tampa, Florida.
6
Merck, Sharp and Dohme, West Point, Pennsylvania.
7
Gibbs Cancer Center & Research Institute, Spartanburg, South Carolina. Yeatman@gibbscc.org Michael.schell@moffitt.org.

Abstract

PURPOSE:

We previously found that an epithelial-to-mesenchymal transition (EMT)-based gene expression signature was highly correlated with the first principal component (PC1) of 326 colorectal cancer tumors and was prognostic. This study was designed to improve these signatures for better prediction of metastasis and outcome.

EXPERIMENTAL DESIGN:

A total of 468 colorectal cancer tumors including all stages (I-IV) and metastatic lesions were used to develop a new prognostic score (ΔPC1.EMT) by subtracting the EMT signature score from its correlated PC1 signature score. The score was validated on six other independent datasets with a total of 3,697 tumors.

RESULTS:

ΔPC1.EMT was found to be far more predictive of metastasis and outcome than its parent scores. It performed well in stages I to III, among microsatellite instability subtypes, and across multiple mutation-based subclasses, demonstrating a refined capacity to predict distant metastatic potential even in tumors with a "good" prognosis. For example, in the PETACC-3 clinical trial dataset, it predicted worse overall survival in an adjusted multivariable model for stage III patients (HR standardized by interquartile range [IQR] = 1.50; 95% confidence interval, 1.25-1.81; P = 0.000016, N = 644). The improved performance of ΔPC1.EMT was related to its propensity to identify epithelial-like subpopulations as well as mesenchymal-like subpopulations. Biologically, the signature was correlated positively with RAS signaling but negatively with mitochondrial metabolism. ΔPC1.EMT was a "best of assessed" prognostic score when compared with 10 other known prognostic signatures.

CONCLUSIONS:

The study developed a prognostic signature score with a propensity to detect non-EMT features, including epithelial cancer stem cell-related properties, thereby improving its potential to predict metastasis and poorer outcome in stage I-III patients.

PMID:
26446941
PMCID:
PMC4802496
DOI:
10.1158/1078-0432.CCR-15-0143
[Indexed for MEDLINE]
Free PMC Article

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