Identification and validation of biomarkers of IgVH mutation status in chronic lymphocytic leukemia using microfluiclics quantitative real-time polymerase chain reaction technology

被引:23
作者
Abruzzo, Lynne V.
Barron, Lynn L.
Anderson, Keith
Newman, Rachel J.
Wierda, William G.
O'Brien, Susan
Ferrajoli, Alessandra
Luthra, Madan
Talwalkar, Sameer
Luthra, Rajyalakshmi
Jones, Dan
Keating, Michael J.
Coombes, Kevin R.
机构
[1] Univ Texas, MD Anderson Canc Ctr, Dept Hematopathol, Houston, TX 77030 USA
[2] Univ Texas, MD Anderson Canc Ctr, Dept Bioinformat & Computat Biol, Houston, TX 77030 USA
[3] Univ Texas, MD Anderson Canc Ctr, Dept Computat Biol, Houston, TX 77030 USA
[4] Univ Texas, MD Anderson Canc Ctr, Dept Leukemia, Houston, TX 77030 USA
[5] Univ Texas, MD Anderson Canc Ctr, Dept Pathol, Houston, TX 77030 USA
关键词
D O I
10.2353/jmoldx.2007.070001
中图分类号
R36 [病理学];
学科分类号
100104 ;
摘要
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.
引用
收藏
页码:546 / 555
页数:10
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