Document Detail

Subnetwork-based analysis of chronic lymphocytic leukemia identifies pathways that associate with disease progression.
MedLine Citation:
PMID:  22837534     Owner:  NLM     Status:  MEDLINE    
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.
Han-Yu Chuang; Laura Rassenti; Michelle Salcedo; Kate Licon; Alexander Kohlmann; Torsten Haferlach; Robin Foà; Trey Ideker; Thomas J Kipps
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Publication Detail:
Type:  Journal Article; Research Support, N.I.H., Extramural; Research Support, Non-U.S. Gov't; Research Support, U.S. Gov't, Non-P.H.S.     Date:  2012-07-26
Journal Detail:
Title:  Blood     Volume:  120     ISSN:  1528-0020     ISO Abbreviation:  Blood     Publication Date:  2012 Sep 
Date Detail:
Created Date:  2012-09-28     Completed Date:  2013-01-10     Revised Date:  2013-10-10    
Medline Journal Info:
Nlm Unique ID:  7603509     Medline TA:  Blood     Country:  United States    
Other Details:
Languages:  eng     Pagination:  2639-49     Citation Subset:  AIM; IM    
Bioinformatics and Systems Biology Program, University of California, San Diego, La Jolla, CA 92093, USA.
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MeSH Terms
Disease Progression
Gene Expression Profiling*
Gene Regulatory Networks
Leukemia, Lymphocytic, Chronic, B-Cell / genetics*,  mortality,  pathology*
Oligonucleotide Array Sequence Analysis
RNA, Messenger / genetics
Real-Time Polymerase Chain Reaction
Reverse Transcriptase Polymerase Chain Reaction
Signal Transduction*
Survival Rate
Tumor Cells, Cultured
Tumor Markers, Biological / genetics*,  metabolism
Grant Support
Reg. No./Substance:
0/RNA, Messenger; 0/Tumor Markers, Biological

From MEDLINE®/PubMed®, a database of the U.S. National Library of Medicine

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