Citations

Abstract Genome-wide association studies (GWAS) have identified SNPs in six genes that are associated with childhood acute lymphoblastic leukemia (ALL). A lead SNP was found to occur on chromosome 9p21.3, a region that is deleted in 30% of childhood ALLs, suggesting the presence of causal polymorphisms linked to ALL risk. We used SNP genotyping and imputation-based fine-mapping of a multiethnic ALL case–control population (Ncases = 1,464, Ncontrols = 3,279) to identify variants of large effect within 9p21.3. We identified a CDKN2A missense variant (rs3731249) with 2% allele frequency in controls that confers three-fold increased risk of ALL in children of European ancestry (OR, 2.99; P = 1.51 × 10−9) and Hispanic children (OR, 2.77; P = 3.78 × 10−4). Moreover, of 17 patients whose tumors displayed allelic imbalance at CDKN2A, 14 preferentially retained the risk allele and lost the protective allele (PBinomial = 0.006), suggesting that the risk allele provides a selective advantage during tumor growth. Notably, the CDKN2A variant was not significantly associated with melanoma, glioblastoma, or pancreatic cancer risk, implying that this polymorphism specifically confers ALL risk but not general cancer risk. Taken together, our findings demonstrate that coding polymorphisms of large effect can underlie GWAS “hits” and that inherited polymorphisms may undergo directional selection during clonal expansion of tumors. Cancer Res; 75(22); 4884–94. ©2015 AACR.

Abstract Biomarkers that select patients for therapeutics would benefit clinical trial design and patient care. The Akt pathway is a therapeutic target in Glioblastoma Multiforme (GBM) and an important determinant of patient outcome. However, it is not known whether activity of this pathway varies among GBM tumors. To investigate we used Akt pathway genes from published GBM expression datasets. We detected 5 patterns of Akt pathway gene expression and these Akt subgroups correlated with prognosis. We analyzed networks within subgroups using both gene set enrichment analysis and a novel method that scores relevance based on both expression and local network connectivity (Komurov et al., PLoS Comput Biol. 2010 6:8, 1-10). The results suggest therapeutic targets within the individual subgroups. Furthermore, preliminary analysis indicates that human GBM xenograft models and primary human GBM manifest similar Akt subgroups. We are investigating rodent xenograft models of Akt subgroups to evaluate subgroup-specific drug sensitivity, and will present a method and examples of analysis integrating gene expression data from human GBM xenografts and primary human GBM. We hypothesize that Akt subgroups will help personalize treatment for GBM therapeutics. Supported by Barrow Neurological Foundation, Halle Family Foundation, and NIH 1 K01 NS064952-01A1 (AMJ). Citation Format: {Authors}. {Abstract title} [abstract]. In: Proceedings of the 102nd Annual Meeting of the American Association for Cancer Research; 2011 Apr 2-6; Orlando, FL. Philadelphia (PA): AACR; Cancer Res 2011;71(8 Suppl):Abstract nr 4138. doi:10.1158/1538-7445.AM2011-4138

Genomewide association studies (GWAS) and candidate‐gene studies have implicated single‐nucleotide polymorphisms (SNPs) in at least 45 different genes as putative glioma risk factors. Attempts to validate these associations have yielded variable results and few genetic risk factors have been consistently replicated. We conducted a case‐control study of Caucasian glioma cases and controls from the University of California San Francisco (810 cases, 512 controls) and the Mayo Clinic (852 cases, 789 controls) in an attempt to replicate previously reported genetic risk factors for glioma. Sixty SNPs selected from the literature (eight from GWAS and 52 from candidate‐gene studies) were successfully genotyped on an Illumina custom genotyping panel. Eight SNPs in/near seven different genes (TERT, EGFR, CCDC26, CDKN2A, PHLDB1, RTEL1, TP53) were significantly associated with glioma risk in the combined dataset (P < 0.05), with all associations in the same direction as in previous reports. Several SNP associations showed considerable differences across histologic subtype. All eight successfully replicated associations were first identified by GWAS, although none of the putative risk SNPs from candidate‐gene studies was associated in the full case‐control sample (all P values > 0.05). Although several confirmed associations are located near genes long known to be involved in gliomagenesis (e.g., EGFR, CDKN2A, TP53), these associations were first discovered by the GWAS approach and are in noncoding regions. These results highlight that the deficiencies of the candidate‐gene approach lay in selecting both appropriate genes and relevant SNPs within these genes.

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 × 10−6). Expression of SSBP2 in tumors from three independent data sets also was significantly related to patient survival (P = 5.3 × 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 × 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. ©2012 AACR.