Accession Number : ADA593732


Title :   Systematic Search for Gene-Gene Interaction Effect on Prostate Cancer Risk


Descriptive Note : Final rept. 1 Jul 2009-30 Jun 2013


Corporate Author : WAKE FOREST UNIV WINSTON-SALEM NC


Personal Author(s) : Sun, Jielin ; Xu, Jianfeng ; Zheng, Siqun L


Full Text : https://apps.dtic.mil/dtic/tr/fulltext/u2/a593732.pdf


Report Date : Jul 2013


Pagination or Media Count : 33


Abstract : Prostate cancer (PCa) is the most common cancer and the second leading cause of cancer death among men in the United States. Considering that PCa development requires the coordination of many genes, it is expected that a simultaneous evaluation of multiple genetic variants can improve the statistical power to detect additional PCa risk variants. Recent improvements in analytical methods and computation make it feasible to search for gene-gene interaction of SNPs in the genome. We hypothesized that multiple sequence variants in the genome may interact to increase PCa risk. These variants may or may not have known main effect on PCa risk and can be better detected by systematically evaluating gene-gene interactions for SNPs in the genome. We utilized data from an existing GWAS of a large NCI Cancer Genetic Markers of Susceptibility (CGEMS) study to systematically discover genes that interacted with known PCa risk variants in the genome. We also evaluated the genes that interacted with known PCa risk variants in another two independent populations, including a population based PCa case-control study from Sweden (CAPS) and a PCa patient population from Johns Hopkins Hospital (JHH). In addition, we performed an exhaustive search for pair-wide SNP-SNP interactions without main effect in the JHH and CGEMS populations using a novel statistical approach of Boolean Operation-based Screening and Testing (BOOST). We identified thirty-five pairs of SNPs that significantly interacted with the thirty-two known risk variants on PCa risk at a P-value of 1E-05 in the combined analysis of three populations. The most significant interaction detected was between rs12418451 in MYEOV and rs784411 in CEP152, with a Pinteraction of 1.15E-07 in the meta-analysis.


Descriptors :   *GENES , *PROSTATE CANCER , *RISK , CASE STUDIES , COMPUTATIONS , DEATH , GENETICS , PATIENTS , SEQUENCES , STATISTICAL PROCESSES , SYNCHRONISM , TEST AND EVALUATION


Subject Categories : Medicine and Medical Research


Distribution Statement : APPROVED FOR PUBLIC RELEASE