BMC Cancer 2009, 9:397 http://www.biomedcentral.com/1471-2407/9/397 0.66-2.02; p = 0.622) on PCA risk among all subjects. Although the GSTM1-GSTP1 pairwise combination was selected as the best two factor LR and MDR models (p = 0.01), assessment of the hierarchical entropy graph suggested that the observed synergistic effect was primarily driven by the GSTP1 Val marker. Notably, the GSTM1-GSTP1 axis did not provide additional information gain when compared to either loci alone based on a hierarchical entropy algorithm and graph. Smoking status did not significantly modify the relationship between the GST SNPs and PCA. Conclusion: A moderately significant association was observed between PCA risk and men possessing at least one variant GSTP1 105 Val allele (p = 0.049) among men of African descent. We also observed a 2.1-fold increase in PCA risk associated with men possessing the GSTP1 (Val/Val) and GSTM1 (*1/*1 + *1/*0) alleles. MDR analysis validated these findings; detecting GSTP1 105 Val (p = 0.001) as the best single factor for predicting PCA risk. Our findings emphasize the importance of utilizing a combination of traditional and advanced statistical tools to identify and validate single gene and multi-locus interactions in relation to cancer susceptibility. Background Even though prostate cancer (PCA) ranks the highest in incidence and second mortality among all cancers affect- ing American men, its etiology and ethnic disparities are largely unknown[1]. For instance, age and family history are the strongest risk factors for PCA, but African-Ameri- can (AA) men are more than twice as likely to develop the disease compared to other racial or ethnic groups[1]. AA men are also more likely to be diagnosed with PCA at a younger age, with more aggressive disease and poorer prognosis [1-3]. Despite increases in five year survival rates for AA men over the last few decades; their rates still lag far behind other races[1]. While, the reasons for this disparity are largely speculative; risk, incidence, and mor- tality rates suggest that genetic factors play an important role in PCA initiation and progression[1]. However, life- style habits (e.g., cigarette smoking, diet) have also been implicated to increase risk; indicating that environmental factors may contribute to PCA[1,2,4]. Therefore, prostate carcinogenesis and its disparity most likely involve a com- plex interplay between genetic and environmental factors. More specifically, variations in carcinogen metabolism genes may play a critical role in PCA development due to their activation or detoxification functions. The glutathione S-transferase (GST) gene superfamily encodes enzymes that catalyze the conjugation of glutath- ione to electrophilic compounds[5,6]. These enzymes generally detoxify endogenous and exogenous agents, but also participate in the activation and inactivation of oxi- dative metabolites of carcinogenic compounds associated with prostate cancer[7,8]. Variant GST alleles have been identified within the general population. The most exten- sively studied variant GSTs include two GST deletion alle- les (i.e., GSTM1*0/*0 [GenBank: BC024005.2] and GSTT1*0/*0 [GenBank: BC007065.1]) and the GSTP1 Val allele which is characterized by an adenine to guanine substitution at position -313 (A-313G) in exon 5 [Gen- Bank: BC010915.1; dbSNP: rs1695][9]. The functional consequences of the GSTM1 and GSTT1 (*0/*0) geno- types are obvious in terms of enzyme activity; gene dele- tion results in loss of conjugation potential. The GSTP1 polymorphism, resulting from an isoleucine to valine substitution within the active site of the enzyme at codon 105 (I105V), is linked to altered substrate-specific ther- mostability and conjugation activity [10-12]. For instance, the GSTP1 105 Val variant has been associated with lower efficiency for diol epoxides of some polycyclic aromatic hydrocarbons, therefore resulting in decreased detoxifica- tion of these compounds compared to the Ile allele[10]. Genetic variations in polymorphic GST genes have been implicated in the etiology of numerous cancers [13-18]. Some studies indicate GST polymorphisms are associated with prostate cancer; however, this association is not accepted across all observational studies [18-25]. Discrep- ancies may be partially attributed to failure to consider gene combinations or interactions with tobacco smoking. Furthermore, few studies have involved a sufficient number of African-Americans in order to adequately investigate the role of GST polymorphisms and environ- mental factors in PCA development[12,26,27]. To clarify the role of GST genes in PCA risk within a high- risk sub-group, we evaluated the individual and joint modifying effects of three commonly studied sequence variants in a case-control study of 208 cases and 665 dis- ease-free controls among a population of men of African descent. In an exploratory analysis, we evaluated gene- gene interactions using an available non-parametric statis- tical model, namely Multifactor Dimensionality Reduc- tion (MDR). This advanced statistical tool readily overcomes sample size limitations often encountered by parametric statistical methods (e.g., logistic regression analysis). MDR has greater than 80% statistical power and rigor to evaluate gene-gene interactions even in the pres- ence of small sample sizes (i.e., 200 cases and 200 con- trols). This computationally sound statistical tool enabled Page 2 of 10 (page number not for citation purposes)