Identification and validation of biomarkers of IgV(H) mutation status in chronic lymphocytic leukemia using microfluidics quantitative real-time polymerase chain reaction technology.

Abstract

To develop a model incorporating relevant prognostic biomarkers for untreated chronic lymphocytic leukemia patients, we re-analyzed the raw data from four published gene expression profiling studies. We selected 88 candidate biomarkers linked to immunoglobulin heavy-chain variable region gene (IgV(H)) mutation status and produced a reliable and reproducible microfluidics quantitative real-time polymerase chain reaction array. We applied this array to a training set of 29 purified samples from previously untreated patients. In an unsupervised analysis, the samples clustered into two groups. Using a cutoff point of 2% homology to the germline IgV(H) sequence, one group contained all 14 IgV(H)-unmutated samples; the other contained all 15 mutated samples. We confirmed the differential expression of 37 of the candidate biomarkers using two-sample t-tests. Next, we constructed 16 different models to predict IgV(H) mutation status and evaluated their performance on an independent test set of 20 new samples. Nine models correctly classified 11 of 11 IgV(H)-mutated cases and eight of nine IgV(H)-unmutated cases, with some models using three to seven genes. Thus, we can classify cases with 95% accuracy based on the expression of as few as three genes.

• Authors: Lynne V Abruzzo, Lynn L Barron, Keith Anderson, Rachel J Newman, William G Wierda, Susan O'brien, Alessandra Ferrajoli, Madan Luthra, Sameer Talwalkar, Rajyalakshmi Luthra, Dan Jones, Michael J Keating, Kevin R Coombes
• Journal: The Journal of molecular diagnostics : JMD (J Mol Diagn) Vol. 9 Issue 4 Pg. 546-55 (Sep 2007) ISSN: 1525-1578 [Print] United States
• PMID: 17690214 (Publication Type: Journal Article, Research Support, Non-U.S. Gov't)

Chemical References

• Biomarkers, Tumor
• Genetic Markers
• Immunoglobulin Heavy Chains
• Immunoglobulin Variable Region

Topics

• Biomarkers, Tumor (genetics)
• Cluster Analysis
• Gene Expression Profiling
• Genetic Markers
• Humans
• Immunoglobulin Heavy Chains (genetics)
• Immunoglobulin Variable Region (genetics)
• Leukemia, Lymphocytic, Chronic, B-Cell (genetics)
• Microfluidics (methods)
• Models, Genetic
• Mutation (genetics)
• Polymerase Chain Reaction (methods)
• Reproducibility of Results