Gene expression in oligodendroglial tumors
CELLULAR ONCOLOGY
Authors: Shaw, Elisabeth J.; Haylock, Brian; Husband, David; du Plessis, Daniel; Sibson, D. Ross; Warnke, Peter C.; Walker, Carol
Abstract
Oligodendroglial tumors with 1p/19q loss are more likely to be chemosensitive and have longer survival than those with intact 1p/19q, but not all respond to chemotherapy, warranting investigation of the biological basis of chemosensitivity. Gene expression profiling was performed using amplified antisense RNA from 28 oligodendroglial tumors treated with chemotherapy [26 serial stereotactic biopsy, 2 resection]. Expression of differentially expressed genes was validated by real-time PCR. Unsupervised hierarchical clustering showed clustering of multiple samples from the same case in 14/17 cases and identified subgroups associated with tumor grade and 1p/19q status. 176 genes were differentially expressed, 164 being associated with 1p/19q loss (86% not on 1p or 19q). 94 genes differed between responders and non-responders to chemotherapy; 12 were not associated with 1p/19q loss. Significant differential expression was confirmed in 11/13 selected genes. Novel genes associated with response to therapy included SSBP2, GFRA1, FAP and RASD1. IQGAP1, INA, TGIF1, NR2F2 and MYCBP were differentially expressed in oligodendroglial tumors with 1p/19q loss. Gene expression profiling using serial stereotactic biopsies indicated greater homogeneity within tumors than between tumors. Genes associated with 1p/19q status or response were identified warranting further elucidation of their role in oligodendroglial tumors.
SSBP2 Variants Are Associated with Survival in Glioblastoma Patients
CLINICAL CANCER RESEARCH
Authors: Xiao, Yuanyuan; Decker, Paul A.; Rice, Terri; McCoy, Lucie S.; Smirnov, Ivan; Patoka, Joseph S.; Hansen, Helen M.; Wiemels, Joe L.; Tihan, Tarik; Prados, Michael D.; Chang, Susan M.; Berger, Mitchel S.; Kosel, Matthew L.; Fridley, Brooke L.; Lachance, Daniel H.; O'Neill, Brian Patrick; Buckner, Jan C.; Thompson, Reid C.; Nabors, Louis Burt; Olson, Jeffrey J.; Brem, Steve; Madden, Melissa H.; Browning, James E.; Wiencke, John K.; Egan, Kathleen M.; Jenkins, Robert B.; Wrensch, Margaret R.
Abstract
Purpose: Glioblastoma is a devastating, incurable disease with few known prognostic factors. Here, we present the first genome-wide survival and validation study for glioblastoma. Experimental Design: Cox regressions for survival with 314,635 inherited autosomal single-nucleotide polymorphisms (SNP) among 315 San Francisco Adult Glioma Study patients for discovery and three independent validation data sets [87 Mayo Clinic, 232 glioma patients recruited from several medical centers in Southeastern United States (GliomaSE), and 115 The Cancer Genome Atlas patients] were used to identify SNPs associated with overall survival for Caucasian glioblastoma patients treated with the current standard of care, resection, radiation, and temozolomide (total n = 749). Tumor expression of the gene that contained the identified prognostic SNP was examined in three separate data sets (total n 619). Genotype imputation was used to estimate hazard ratios (HR) for SNPs that had not been directly genotyped. Results: From the discovery and validation analyses, we identified a variant in single-stranded DNA-binding protein 2 (SSBP2) on 5q14.1 associated with overall survival in combined analyses (HR, 1.64; P = 1.3 x 10(-6)). Expression of SSBP2 in tumors from three independent data sets also was significantly related to patient survival (P = 5.3 x 10(-4)). Using genotype imputation, the SSBP2 SNP rs17296479 had the strongest statistically significant genome-wide association with poorer overall patient survival (HR, 1.79; 95% CI, 1.45-2.22; P = 1.0 x 10(-7)). Conclusion: The minor allele of SSBP2 SNP rs17296479 and the increased tumor expression of SSBP2 were statistically significantly associated with poorer overall survival among glioblastoma patients. With further confirmation, previously unrecognized inherited variations influencing survival may warrant inclusion in clinical trials to improve randomization. Unaccounted for genetic influence on survival could produce unwanted bias in such studies. Clin Cancer Res; 18(11); 3154-62. (C) 2012 AACR.