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Blood. 2012 Sep 27;120(13):2639-49. Epub 2012 Jul 26.

Subnetwork-based analysis of chronic lymphocytic leukemia identifies pathways that associate with disease progression.

Author information

1
Bioinformatics and Systems Biology Program, University of California, San Diego, La Jolla, CA 92093, USA.

Abstract

The clinical course of patients with chronic lymphocytic leukemia (CLL) is heterogeneous. Several prognostic factors have been identified that can stratify patients into groups that differ in their relative tendency for disease progression and/or survival. Here, we pursued a subnetwork-based analysis of gene expression profiles to discriminate between groups of patients with disparate risks for CLL progression. From an initial cohort of 130 patients, we identified 38 prognostic subnetworks that could predict the relative risk for disease progression requiring therapy from the time of sample collection, more accurately than established markers. The prognostic power of these subnetworks then was validated on 2 other cohorts of patients. We noted reduced divergence in gene expression between leukemia cells of CLL patients classified at diagnosis with aggressive versus indolent disease over time. The predictive subnetworks vary in levels of expression over time but exhibit increased similarity at later time points before therapy, suggesting that degenerate pathways apparently converge into common pathways that are associated with disease progression. As such, these results have implications for understanding cancer evolution and for the development of novel treatment strategies for patients with CLL.

PMID:
22837534
PMCID:
PMC3460686
DOI:
10.1182/blood-2012-03-416461
[Indexed for MEDLINE]
Free PMC Article

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