Microarray Analyses In A Case-Control Cohort Of T-ALL Samples Identifies Gene Signature Of Potential Prognostic Significance

 

Stuart S. Winter, MD1, Hadya Khawaja2, Zeyu Jiang, PhD3, Charles Kooperberg, PhD4, Adolfo Ferrando, MD5, Thomas Look, MD6 and Richard S. Larson, MD, PhD2.

 

 1Pediatric Hematology/Oncology, University of New Mexico Health Sciences Center (HSC), Albuquerque, NM; 2Pathology, University of New Mexico HSC, Albuquerque, NM; 3Biostatistics, University of New Mexico HSC, Albuquerque, NM; 4Division of Public Health Sciences, Fred Hutchinson Cancer Center, Seattle, WA; 5Institute for Cancer Genetics, Columbia University, New York, NY and 6Pediatric Oncology, Dana Farber Cancer Institute, Boston, MA.

 

Risk stratification remains limited for patients being treated for T-ALL due to a lack of biologic predictors of outcome. As a consequence, treatment assignment on modern protocols has been largely achieved through random assignment. Recent observations have suggested that overexpression of specific gene(s) may provide a reliable means to risk stratify patients. We hypothesized that microarray analysis may identify gene sets that distinguish both therapeutic response and patient outcome in T-ALL. We analyzed the gene expression profiles of 45 primary T-ALL samples (24 CCR, 21 relapse) from a matched, case control study with sufficient cRNA for microarray analysis (COG #8704). We performed oligonucleotide microarray analysis using Affymetrix U133Av.2 genechips which have approximately 23,000 target genes and ESTs. Following heirarchical clustering in dChip and R Language analyses (Chiaretti et al. Blood, 2004), but using RMA normalization, we identified 37 genes that serve as reliable predictors of CCR or relapse. Leave-one-out least discriminant analysis cross-over validation further constrained our prognostic gene identifiers to 21 genes of robust significance. These 21 genes predict 87 % of CCR and 82% of relapse accurately (p<0.0001, two-tailed Fishers exact test). These results were verified by qRT-PCR. Transcriptional factors previously described as having prognostic significance were not identified in our study. Twenty-six of the 45 cases received high dose L-asparaginase (16 CCR, 10 relapse) on the companion study. As a result, we examined whether a distinct signature could be also identified that distinguishes response to dose-intensified asparaginase treatment for patients with T-ALL. Using the same approach, a 27-member gene signature was identified that accurately predicted response in 24 of the 26 cases (92 %; 2 cases of relapse were misclassified). These results have identified two sets of genes that may be further pursued as prognostic indicators in T-ALL or as predictors of response to therapy.