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Expression data from untreated CLL patients

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 two 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 timepoints prior to 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.

ORGANISM(S): Homo sapiens

PROVIDER: GSE39671 | GEO | 2012/07/26

SECONDARY ACCESSION(S): PRJNA171376

REPOSITORIES: GEO

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Expression data from untreated CLL patients

Project description: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 two 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 timepoints prior to 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. Leukemia cells were isolated from blood samples of CLL patients enrolled in the MILE study who had not received prior therapy for CLL, as per the MILE protocol22. Expression data were gathered from samples found to have a CLL cell population with greater than 90% CD5+CD19+, as accessed via flow cytometry. Total RNA was isolated and hybridized to Affymetrix HG-U133+2 GeneChips. This study is about the time to treatment, ie., prognosis instead of diagnosis.

2012-07-25 | E-GEOD-39671 | biostudies-arrayexpress

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