Prognostic gene expression signature associated with two molecularly distinct subtypes of colorectal cancer

Department of Systems Biology, Division of Cancer Medicine, The University of Texas MD Anderson Cancer Center, Houston, TX 77030, USA.
Gut (Impact Factor: 13.32). 10/2011; 61(9):1291-8. DOI: 10.1136/gutjnl-2011-300812
Source: PubMed

ABSTRACT Despite continual efforts to develop prognostic and predictive models of colorectal cancer by using clinicopathological and genetic parameters, a clinical test that can discriminate between patients with good or poor outcome after treatment has not been established. Thus, the authors aim to uncover subtypes of colorectal cancer that have distinct biological characteristics associated with prognosis and identify potential biomarkers that best reflect the biological and clinical characteristics of subtypes.
Unsupervised hierarchical clustering analysis was applied to gene expression data from 177 patients with colorectal cancer to determine a prognostic gene expression signature. Validation of the signature was sought in two independent patient groups. The association between the signature and prognosis of patients was assessed by Kaplan-Meier plots, log-rank tests and the Cox model.
The authors identified a gene signature that was associated with overall survival and disease-free survival in 177 patients and validated in two independent cohorts of 213 patients. In multivariate analysis, the signature was an independent risk factor (HR 3.08; 95% CI 1.33 to 7.14; p=0.008 for overall survival). Subset analysis of patients with AJCC (American Joint Committee on Cancer) stage III cancer revealed that the signature can also identify the patients who have better outcome with adjuvant chemotherapy (CTX). Adjuvant chemotherapy significantly affected disease-free survival in patients in subtype B (3-year rate, 71.2% (CTX) vs 41.9% (no CTX); p=0.004). However, such benefit of adjuvant chemotherapy was not significant for patients in subtype A.
The gene signature is an independent predictor of response to chemotherapy and clinical outcome in patients with colorectal cancer.

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Available from: Ju-Seog Lee, Jun 27, 2015
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