Zeng H.,Yale University |
Zeng H.,Peking University |
Yu H.,Yale University |
Lu L.,Yale University |
And 5 more authors.
Pancreas | Year: 2011
Objectives: Germ-line genetic variation may affect clinical outcomes of cancer patients. We applied a candidate-gene approach to evaluate the effect of putative markers on survival of patients with pancreatic cancer. We also examined gene-radiotherapy and gene-chemotherapy interactions, aiming to explain interindividual differences in treatment outcomes. Methods: In total, 211 patients with pancreatic cancer were recruited in a population-based study. Sixty-four candidate genes associated with cancer survival or treatment response were selected from existing publications. Genotype information was obtained from a previous genome-wide association study data set. The main effects of genetic variation and gene-specific treatment interactions on overall survival were examined by proportional hazards regression models. Results: Fourteen genes showed evidence of association with pancreatic cancer survival. Among these, rs1760217, located at the DPYD gene; rs17091162 at SERPINA3; and rs2231164 at ABCG2 had the lowest P of 10, 0.0013, and 0.0023, respectively. We also observed that 2 genes, RRM1 and IQGAP2, had significant interactions with radiotherapy in association with survival, and 2 others, TYMS and MET, showed evidence of interaction with 5-fluorouracil and erlotinib, respectively. Conclusions: Our study suggested significant associations between germ-line genetic polymorphisms and overall survival in pancreatic cancer, as well as survival interactions between various genes and radiotherapy and chemotherapy. Copyright © 2011 by Lippincott Williams & Wilkins.
Tang W.,Laboratory of Translational Genomics |
Fu Y.,Laboratory of Translational Genomics |
Figueroa J.D.,U.S. National Cancer Institute |
Malats N.,Spanish National Cancer Research Center |
And 36 more authors.
Human Molecular Genetics | Year: 2012
A recent genome-wide association study of bladder cancer identified the UGT1A gene cluster on chromosome 2q37.1 as a novel susceptibility locus. The UGT1A cluster encodes a family of UDP-glucuronosyltransferases (UGTs), which facilitate cellular detoxification and removal of aromatic amines. Bioactivated forms of aromatic amines found in tobacco smoke and industrial chemicals are the main risk factors for bladder cancer. The association within the UGT1A locus was detected by a single nucleotide polymorphism (SNP) rs11892031. Now, we performed detailed resequencing, imputation and genotyping in this region. We clarified the original genetic association detected by rs11892031 and identified an uncommon SNP rs17863783 that explained and strengthened the association in this region (allele frequency 0.014 in 4035 cases and 0.025 in 5284 controls, OR = 0.55, 95%CI = 0.44-0.69, P = 3.3 × 10 -7). Rs17863783 is a synonymous coding variant Val209Val within the functional UGT1A6.1 splicing form, strongly expressed in the liver, kidney and bladder. We found the protective T allele of rs17863783 to be associated with increased mRNA expression of UGT1A6.1 in in-vitro exontrap assays and in human liver tissue samples. We suggest that rs17863783 may protect from bladder cancer by increasing the removal of carcinogens from bladder epithelium by the UGT1A6.1 protein. Our study shows an example of genetic and functional role of an uncommon protective genetic variant in a complex human disease, such as bladder cancer. Published by Oxford University Press 2012.
Chung C.C.,Laboratory of Translational Genomics |
Chung C.C.,U.S. National Institutes of Health |
Ciampa J.,U.S. National Institutes of Health |
Yeager M.,U.S. National Institutes of Health |
And 53 more authors.
Human Molecular Genetics | Year: 2011
Genome-wide association studies have identified prostate cancer susceptibility alleles on chromosome 11q13. As part of the Cancer Genetic Markers of Susceptibility (CGEMS) Initiative, the region flanking the most significant marker, rs10896449, was fine mapped in 10 272 cases and 9123 controls of European origin (10 studies) using 120 common single nucleotide polymorphisms (SNPs) selected by a two-staged tagging strategy using HapMap SNPs. Single-locus analysis identified 18 SNPs below genome-wide significance (P < 10-8) with rs10896449 the most significant (P = 7.94 × 10-19). Multi-locus models that included significant SNPs sequentially identified a second association at rs12793759 [odds ratio (OR) = 1.14, P = 4.76 × 10-5, adjusted P = 0.004] that is independent of rs10896449 and remained significant after adjustment for multiple testing within the region. rs10896438, a proxy of previously reported rs12418451 (r2= 0.96), independent of both rs10896449 and rs12793759 was detected (OR = 1.07, P = 5.92 × 10-3, adjusted P = 0.054). Our observation of a recombination hotspot that separates rs10896438 from rs10896449 and rs12793759, and low linkage disequilibrium (rs10896449-rs12793759, r2= 0.17; r2=10896449-rs10896438, r2= 0.10; rs12793759- rs10896438, r2= 0.12) corroborate our finding of three independent signals. By analysis of tagged SNPs across ~123 kb using next generation sequencing of 63 controls of European origin, 1000 Genome and HapMap data, we observed multiple surrogates for the three independent signals marked by rs10896449 (n = 31), rs10896438 (n = 24) and rs12793759 (n = 8). Our results indicate that a complex architec- ture underlying the common variants contributing to prostate cancer risk at 11q13. We estimate that at least 63 common variants should be considered in future studies designed to investigate the biological basis of the multiple association signals. © The Author 2011. Published by Oxford University Press. All rights reserved.