학술논문
An analysis of growth, differentiation and apoptosis genes with risk of renal cancer.
Document Type
article
Author
Linda M Dong; Paul Brennan; Sara Karami; Rayjean J Hung; Idan Menashe; Sonja I Berndt; Meredith Yeager; Stephen Chanock; David Zaridze; Vsevolod Matveev; Vladimir Janout; Hellena Kollarova; Vladimir Bencko; Kendra Schwartz; Faith Davis; Marie Navratilova; Neonila Szeszenia-Dabrowska; Dana Mates; Joanne S Colt; Ivana Holcatova; Paolo Boffetta; Nathaniel Rothman; Wong-Ho Chow; Philip S Rosenberg; Lee E Moore
Source
PLoS ONE, Vol 4, Iss 3, p e4895 (2009)
Subject
Language
English
ISSN
1932-6203
Abstract
We conducted a case-control study of renal cancer (987 cases and 1298 controls) in Central and Eastern Europe and analyzed genomic DNA for 319 tagging single-nucleotide polymorphisms (SNPs) in 21 genes involved in cellular growth, differentiation and apoptosis using an Illumina Oligo Pool All (OPA). A haplotype-based method (sliding window analysis of consecutive SNPs) was used to identify chromosome regions of interest that remained significant at a false discovery rate of 10%. Subsequently, risk estimates were generated for regions with a high level of signal and individual SNPs by unconditional logistic regression adjusting for age, gender and study center. Three regions containing genes associated with renal cancer were identified: caspase 1/5/4/12(CASP 1/5/4/12), epidermal growth factor receptor (EGFR), and insulin-like growth factor binding protein-3 (IGFBP3). We observed that individuals with CASP1/5/4/12 haplotype (spanning area upstream of CASP1 through exon 2 of CASP5) GGGCTCAGT were at higher risk of renal cancer compared to individuals with the most common haplotype (OR:1.40, 95% CI:1.10-1.78, p-value = 0.007). Analysis of EGFR revealed three strong signals within intron 1, particularly a region centered around rs759158 with a global p = 0.006 (GGG: OR:1.26, 95% CI:1.04-1.53 and ATG: OR:1.55, 95% CI:1.14-2.11). A region in IGFBP3 was also associated with increased risk (global p = 0.04). In addition, the number of statistically significant (p-value