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

Blood. 2012 Sep 27;120(13):2639-49. doi: 10.1182/blood-2012-03-416461. Epub 2012 Jul 26.

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.

Publication types

  • Research Support, N.I.H., Extramural
  • Research Support, Non-U.S. Gov't
  • Research Support, U.S. Gov't, Non-P.H.S.

MeSH terms

  • Biomarkers, Tumor / genetics*
  • Biomarkers, Tumor / metabolism
  • Disease Progression
  • Gene Expression Profiling*
  • Gene Regulatory Networks
  • Humans
  • Leukemia, Lymphocytic, Chronic, B-Cell / genetics*
  • Leukemia, Lymphocytic, Chronic, B-Cell / mortality
  • Leukemia, Lymphocytic, Chronic, B-Cell / pathology*
  • Oligonucleotide Array Sequence Analysis
  • Prognosis
  • RNA, Messenger / genetics
  • Real-Time Polymerase Chain Reaction
  • Reverse Transcriptase Polymerase Chain Reaction
  • Signal Transduction*
  • Survival Rate
  • Tumor Cells, Cultured

Substances

  • Biomarkers, Tumor
  • RNA, Messenger