Use of the gamma method for self-contained gene-set analysis of SNP data

Gene-set analysis (GSA) evaluates the overall evidence of association between a phenotype and all genotyped single nucleotide polymorphisms (SNPs) in a set of genes, as opposed to testing for association between a phenotype and each SNP individually. We propose using the Gamma Method (GM) to combine gene-level P-values for assessing the significance of GS association. We performed simulations to compare the GM with several other self-contained GSA strategies, including both one-step and two-step GSA approaches, in a variety of scenarios. We denote a ‘one-step' GSA approach to be one in which all SNPs in a GS are used to derive a test of GS association without consideration of gene-level effects, and a ‘two-step' approach to be one in which all genotyped SNPs in a gene are first used to evaluate association of the phenotype with all measured variation in the gene and then the gene-level tests of association are aggregated to assess the GS association with the phenotype. The simulations suggest that, overall, two-step methods provide higher power than one-step approaches and that combining gene-level P-values using the GM with a soft truncation threshold between 0.05 and 0.20 is a powerful approach for conducting GSA, relative to the competing approaches assessed. We also applied all of the considered GSA methods to data from a pharmacogenomic study of cisplatin, and obtained evidence suggesting that the glutathione metabolism GS is associated with cisplatin drug response

ABCB1 (MDR1) polymorphisms and ovarian cancer progression and survival: A comprehensive analysis from the Ovarian Cancer Association Consortium and The Cancer Genome Atlas

<b>Objective</b> <i>ABCB1</i> encodes the multi-drug efflux pump P-glycoprotein (P-gp) and has been implicated in multi-drug resistance. We comprehensively evaluated this gene and flanking regions for an association with clinical outcome in epithelial ovarian cancer (EOC).<p></p> <b>Methods</b> The best candidates from fine-mapping analysis of 21 <i>ABCB1</i> SNPs tagging C1236T (rs1128503), G2677T/A (rs2032582), and C3435T (rs1045642) were analysed in 4616 European invasive EOC patients from thirteen Ovarian Cancer Association Consortium (OCAC) studies and The Cancer Genome Atlas (TCGA). Additionally we analysed 1,562 imputed SNPs around ABCB1 in patients receiving cytoreductive surgery and either ‘standard’ first-line paclitaxel–carboplatin chemotherapy (n = 1158) or any first-line chemotherapy regimen (n = 2867). We also evaluated ABCB1 expression in primary tumours from 143 EOC patients.<p></p> <b>Result</b> Fine-mapping revealed that rs1128503, rs2032582, and rs1045642 were the best candidates in optimally debulked patients. However, we observed no significant association between any SNP and either progression-free survival or overall survival in analysis of data from 14 studies. There was a marginal association between rs1128503 and overall survival in patients with nil residual disease (HR 0.88, 95% CI 0.77–1.01; p = 0.07). In contrast, <i>ABCB1</i> expression in the primary tumour may confer worse prognosis in patients with sub-optimally debulked tumours.<p></p> <b>Conclusion</b> Our study represents the largest analysis of <i>ABCB1</i> SNPs and EOC progression and survival to date, but has not identified additional signals, or validated reported associations with progression-free survival for rs1128503, rs2032582, and rs1045642. However, we cannot rule out the possibility of a subtle effect of rs1128503, or other SNPs linked to it, on overall survival.<p></p&gt

Meta-analysis of 8q24 for seven cancers reveals a locus between NOV and ENPP2 associated with cancer development.

BACKGROUND: Human chromosomal region 8q24 contains several genes which could be functionally related to cancer, including the proto-oncogene c-MYC. However, the abundance of associations around 128 Mb on chromosome 8 could mask the appearance of a weaker, but important, association elsewhere on 8q24. METHODS: In this study, we completed a meta-analysis of results from nine genome-wide association studies for seven types of solid-tumor cancers (breast, prostate, pancreatic, lung, ovarian, colon, and glioma) to identify additional associations that were not apparent in any individual study. RESULTS: Fifteen SNPs in the 8q24 region had meta-analysis p-values < 1E-04. In particular, the region consisting of 120,576,000-120,627,000 bp contained 7 SNPs with p-values < 1.0E-4, including rs6993464 (p = 1.25E-07). This association lies in the region between two genes, NOV and ENPP2, which have been shown to play a role in tumor development and motility. An additional region consisting of 5 markers from 128,478,000 bp - 128,524,000 (around gene POU5F1B) had p-values < 1E-04, including rs6983267, which had the smallest p-value (p = 6.34E-08). This result replicates previous reports of association between rs6983267 and prostate and colon cancer. CONCLUSIONS: Further research in this area is warranted as these results demonstrate that the chromosomal region 8q24 may contain a locus that influences general cancer susceptibility between 120,576 and 120,630 kb.RIGHTS : This article is licensed under the BioMed Central licence at http://www.biomedcentral.com/about/license which is similar to the 'Creative Commons Attribution Licence'. In brief you may : copy, distribute, and display the work; make derivative works; or make commercial use of the work - under the following conditions: the original author must be given credit; for any reuse or distribution, it must be made clear to others what the license terms of this work are

Cell cycle genes and ovarian cancer susceptibility: a tagSNP analysis

BACKGROUND: Dysregulation of the cell cycle is a hallmark of many cancers including ovarian cancer, a leading cause of gynaecologic cancer mortality worldwide.METHODS: We examined single nucleotide polymorphisms (SNPs) (n = 288) from 39 cell cycle regulation genes, including cyclins, cyclin-dependent kinases (CDKs) and CDK inhibitors, in a two-stage study. White, non-Hispanic cases (n = 829) and ovarian cancer-free controls (n = 941) were genotyped using an Illumina assay.RESULTS: Eleven variants in nine genes (ABL1, CCNB2, CDKN1A, CCND3, E2F2, CDK2, E2F3, CDC2, and CDK7) were associated with risk of ovarian cancer in at least one genetic model. Seven SNPs were then assessed in four additional studies with 1689 cases and 3398 controls. Association between risk of ovarian cancer and ABL1 rs2855192 found in the original population [odds ratio, ORBB vs AA 2.81 (1.29-6.09), P = 0.01] was also observed in a replication population, and the association remained suggestive in the combined analysis [ORBB vs AA 1.59 (1.08-2.34), P = 0.02]. No other SNP associations remained suggestive in the replication populations.CONCLUSION: ABL1 has been implicated in multiple processes including cell division, cell adhesion and cellular stress response. These results suggest that characterization of the function of genetic variation in this gene in other ovarian cancer populations is warranted. British Journal of Cancer (2009) 101, 1461-1468. doi: 10.1038/sj.bjc.6605284 www.bjcancer.com Published online 8 September 2009 (C) 2009 Cancer Research U

No association between a candidate TCF7L2 variant and risk of breast or ovarian cancer

<p>Abstract</p> <p>Background</p> <p>TCF7L2 is a transcription factor involved in Wnt/β-catenin signaling which has a variant known to be associated with risk of Type 2 diabetes and, in some studies, with risk of certain cancers, including familial breast cancer. No studies of ovarian cancer have been reported to date.</p> <p>Methods</p> <p>Two clinic-based case-control studies at the Mayo Clinic were assessed including 798 breast cancer cases, 843 breast cancer controls, 391 ovarian cancer cases, and 458 ovarian cancer controls. Genotyping at <it>TCF7L2 </it>rs12255372 used a 5' endonuclease assay, and statistical analysis used logistic regression among participants as a whole and among <it>a priori</it>-defined subsets.</p> <p>Results</p> <p>No associations with risk of breast or ovarian cancer were observed (ordinal model, p = 0.62 and p = 0.75, respectively). In addition, no associations were observed among sub-groups defined by age, BMI, family history, stage, grade, histology, or tumor behavior.</p> <p>Conclusion</p> <p>Although the biology of the Wnt/β-catenin signaling pathway and prior association between rs12255372 and numerous phenotypes warranted examination of this <it>TCF7L2 </it>SNP, no compelling evidence for association with breast or ovarian cancer was observed.</p