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Www.polyomx.org Identification of Single Nucleotide Polymorphisms Predictive of Sporadic Prostate Cancer Susceptibility Using a Case-Control Association.

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Presentation on theme: "Www.polyomx.org Identification of Single Nucleotide Polymorphisms Predictive of Sporadic Prostate Cancer Susceptibility Using a Case-Control Association."— Presentation transcript:

1 www.polyomx.org Identification of Single Nucleotide Polymorphisms Predictive of Sporadic Prostate Cancer Susceptibility Using a Case-Control Association Study Design Sambasivarao Damaraju* 1,#, Badan S. Sehrawat 1,#, Sunita Ghosh 2, Kathryn Calder 1,#, Diana Carandang 1,#, Jennifer Dufour 1,#, Russ Greiner 3,# Carol E. Cass 2,#, and Matthew Parliament 2,# 1 Departments of Laboratory Medicine and Pathology, 2 Oncology and 3 Computing Science, University of Alberta and the # PolyomX Program, Cross Cancer Institute, Edmonton, Alberta; * Corresponding and presenting author Background: Prostate cancer is the most common cancer among men. Sporadic prostate cancer comprises up to 80% of all cases diagnosed and is recognized as a heterogeneous disorder, with multiple genetic and environmental factors involved in its etiology. We adopted a two-stage approach in this case-control association study design to identify single nucleotide polymorphisms (SNPs) that predict predisposition (or protection from disease) of individuals to prostate cancer. Methods: We selected 84 cases of confirmed prostate cancer patients who underwent therapy at the Cross Cancer Institute, Edmonton, Canada and 93 unrelated controls who were age and sex matched (excess unused blood samples collected from non-cancer patients at local hospital) from the Edmonton region for this initial phase of the study. Blood samples from prostate cancer patients’ were collected after obtaining consent and the study was approved by the institutional ethics board. DNA was isolated from buffy coat cells for genotyping assays. We selected 280 SNPs from 75 candidate genes from DNA repair, tissue repair, xenobiotic metabolism and immune regulation using criteria based on reported literature findings on the role of genes and their reported associations with cancer disease phenotypes, inclusion of SNPs in the HapMap project data set and predictions for deleterious changes in amino acid substitutions from SIFT (Sorting Intolerant From Tolerant) analysis. We designed and performed genotyping assays for 185 SNPs on the Pyrosequencing platform. The data was subjected to Hardy Weinberg Equilibrium (HWE) analysis after removal of non- polymorphic and rare loci (86 SNPs). The 97 SNPs that met the HWE criteria were analyzed by using SNPStats software (web tool for SNP analysis), logistic regression, multifactor dimensionality reduction (MDR), pair wise linkage disequilibrium analysis, tests of associations using single locus and inferred haplotypes. Measures were implemented to correct for statistical significance of the identified loci (Bonferroni correction in a multiple marker setting), and for population stratification using the program ‘Structure’. Results: We identified seven haplotype blocks across various chromosomes with sizes that ranged from 0.2 to 49 kb. Two haplotype blocks were observed to differ significantly between cases and controls (P<0.02). Statistically significant differences were observed between cases and controls from BRCA2, XRC, MMP9, BCL2, XRCC1, XRCC3, XRCC4, NTHL1, HSD3B2, IL10, ADPRT, POLD1, TGF B1, ERCC2, MSH3, ATM, CYP1A1, ESRa and LIG 1 gene SNPs with P values ranging from <0.04 to 10-8 in single locus and multilocus haplotype association analysis respectively. Population Stratification Analysis “Structure” (Pritchard et al., 1998). Simulation was done using arbitrary population number assuming 1 to 5 populations present in the sample set. Total 13 markers (on chromosome 1, 2, 3, 4, 8, 9,10, 11, 12) unlinked with disease status on single locus analysis were selected and analysis was carried out for 100 independent runs. There was no population stratification present in controls whereas in cases a non significant indication of subpopulations was present Chromosome 1Chromosome 17 Multi Dimensionality Reduction (MDR) Analysis Chromosome 1 Haplotypes Susceptibility haplotypes: 2 Protective haplotypes: 2 p-value significant at 0.005 after Bonferroni Correctionrs1361530C/GHSD3B2Exon-rs1878672C/GIL10Intron- rs3024492A/TIL10Intron- rs1518111A/GIL10Intron- rs2222202C/TIL10Intron- rs1800871C/TIL10Promoter- rs1800896A/GIL10Promoter- rs3219145A/GPARP1 Coding Ex K/R rs1136410C/TPARP1 V/A rs3219062A/CPARP1 S/Y Chromosome 19 Haplotypes Susceptibility haplotypes: 3 (2 in cases and 1 shared) Protective haplotype: 1 p-value significant at 0.013 after Bonferroni Correctionrs25677A/C/TCD22 Coding Ex C/?rs1800471C/GMGC4093 3' UTR - rs1800469C/TMGC4093 - rs25487A/GXRCC1 Coding Ex - rs25489A/GXRCC1 - rs1799782C/TXRCC1 R/W rs13181G/TKLC2L 3' UTR - rs1052555C/TKLC2L - rs3730933A/GLIG1 Coding Ex N/S rs20580A/CLIG1 A/A rs3218772C/TPOLD1 R/W MDR Analysis: Four SNP Interaction rs 2228001 XPC Chr1 rs 1801406 BRCA2 Chr13 rs 861539 XRCC3 Chr14 rs 1801018 BCL2 Chr18 1 protective haplotype with p<4.5 x 10 -4 1 protective haplotype with p<8.7 x 10 -7 2 susceptibility haplotypes with p < 6 x 10 -8 p value significant after Bonferroni correction (97 markers) Three SNP interaction Haplotype Frequency rs 2228001XPCChr1 rs 861539XRCC3Chr14 rs 1801018BCL2Chr18 p value significant after Bonferroni correction (97 markers) 1.91.71TGC 8.677.4GAC 0.330.3646GGC 0.30.33GAT 0.280.31TAC Odds Ratio Risk Ratio Haplotype Haplotype Blocks: Association Analysis Average Density per Chromosome: 4.62 Range: 1-11 97 markers total Marker Density/Chromosome * * * * 10 -6 9 x 10 -6 2 x 10 -3 2 x 10 -5 * * 10 -6 4.5 x 10 -3 ** 3.5 x10 -6 5 x 10 -8 ** 6 x 10 -8 * 4.5 x 10 -4 * 8.7 x 10 -7 0.01 * 0.01 * AG/TC/GT/AA (3.0) AA/TC/GT/GG (3.0) AG/TT/TT/GA (4.0) AG/CC/GT/GA (5.0) TT/GG/GG (3.0) AG/TC/GT/GA (7.0) TC/TT/GA (4.33) TC/GG (1.86) AA/TC/TT/GG (8.0) CC/GT/GA (4.5) CC/GA (2.0) CC (3.0) 49.35%46.90%46.90%50.20% Mean Prediction Error 40%30%20%60% Cross Validation Consistency rs2228001/rs1801406rs861539/rs1801018Rs2228001rs861539/1801018rs1811018rs1800071rrs2250889SNPs XPC/BRCA2/XRCC3/BCL2XPC/XRCC3/BCL2BCL2/CYP2D6MMP9Genes Four Locus Three Locus Two Locus One Locus Risk Genotypes (Odds Ratio) Single Locus Analysis: Genotype Distribution - log p value 0 0.5 1 1.5 2 2.5 rs1800935rs1870134rs1799977 rs184967 rs1805329rs1801516rs1048943rs1800067rs1801018rs25487rs2250889 0.05 0.01 11 markers out of 97 showed evidence of association Single Locus Analysis: Allelic Association Associated Allele 11 markers out of 97 showed evidence of association Chr3 5 6 11Chr15Chr16Chr19Chr20 -log p value 0 0.5 1 1.5 2 2.5 3 3.5 TCTGCATGGTC rs3731062rs1870134rs184967rs6195rs1801132rs1801516rs1048943rs1799814rs1800067rs25487rs2250889 0.05 0.01 0.001 value significant at 0.025 after Bonferroni correction Chromosome 5Chromosome 16 0.270.297GAAT 0.24690.2988GGAT 0.06410.0759GGGC 0.20260.2278TAAC 1.971.8TGGC Odds Ratio Risk Ratio Haplotype --TGAT 2.62.39GAAC --GGAC Supported by ACF and ACB


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