Abstract 2740: Decision tree-based modeling of androgen pathway genes and prostate cancer risk

Abstract

Abstract Background: Inherited variability in genes that influence androgen metabolism has been implicated in the etiology of prostate cancer. However, joint effects of these genes have not been fully defined in terms of risk. Objective: The objective of this analysis was to evaluate gene-gene and gene-environment interactions for prostate cancer risk using classification and regression tree (CART) models (i.e. decision trees), and to evaluate whether these interactive effects add information about prostate cancer risk prediction beyond that of “traditional” risk factors. Methods: We compared CART models to traditional logistic regression models for associations of factors with prostate cancer risk using 1084 prostate cancer cases and 941 controls. All analyses were stratified by race. We used unconditional logistic regression (LR) to complement and compare to the race-stratified CART results using the area under curve (AUC) for the receiver operating characteristic (ROC) curves. Results: In European Americans, single SNP or haplotype associations were found with CYP3A5 (OR=2.11 (1.13, 3.97)); increasing number of CAG repeats in the AR gene (OR=0.90 (0.83, 0.98)); and the CYP3A4/CYP3A5 AG haplotype (OR=2.86 (1.15, 7.12)). No significant single SNP or haplotype associations were found in African Americans. The CART modeling of prostate cancer risk showed different interaction profiles by race. For European Americans, interactions among CYP3A43 genotype, history of BPH, family history of prostate cancer and age at consent revealed a distinct hierarchy of gene-environment and gene-gene interactions. While for African Americans, interactions among family history of prostate cancer, individual proportion of European ancestry, number of GGC AR repeats and CYP3A4/CYP3A5 haplotype revealed distinct interaction effects from those found in European Americans. For European Americans the CART model had the highest AUC while for African Americans, the LR model with the CART discovered factors had the largest AUC. Conclusion: These results show novel gene-gene and gene-environment interactions specific for European Americans and African Americans discovered using CART as compared to standard LR techniques. Citation Format: {Authors}. {Abstract title} [abstract]. In: Proceedings of the 102nd Annual Meeting of the American Association for Cancer Research; 2011 Apr 2-6; Orlando, FL. Philadelphia (PA): AACR; Cancer Res 2011;71(8 Suppl):Abstract nr 2740. doi:10.1158/1538-7445.AM2011-2740