title: The interaction of CYP3A5 polymorphisms along the androgen metabolism pathway in prostate cancer.
abstract: Prostate cancer is a leading solid tumor among men in the Western world. Androgens play an important role in the carcinogenesis and treatment of prostate cancer. CYP3A5 is a cytochrome P450 superfamily member which also has activity in testosterone metabolism. In this study, we looked for two-gene interactions associated with clinical characteristics of prostate cancer in the Finnish population. We used multifactor-dimensionality reduction for the identification of the two-gene interactions in androgen metabolism pathway genes together with clinical characteristics of prostate cancer among 754 genotyped prostate cancer patients. The CYP3A5*3/*3 and SRD5A2 A49T GG genotype interaction was associated with the clinical tumor stage T2-T4 (T-stage, TNM classification) with odds ratio (OR) 2.14, 95% confidence interval (CI) 1.35-3.40. Patients with CYP3A5*3/*3 and KLK3 I179T CC/TC genotypes had increased OR 2.30, 95% CI 1.16-4.58 for metastatic disease. Further, two-gene interaction CYP3A5*3/*3 and KLK3 -252A > G AA was associated with Gleason scores >or=7 with OR 1.52, 95% CI 1.11-2.09. Prostate cancer patients with CYP3A5*3/*3 and KLK -252A > G GG/AG genotypes had decreased OR of 0.70 with 95% CI 0.50-0.98 for high prostate-specific antigen levels at diagnosis. For prostate cancer patients aged below 65 years, the OR for interaction of CYP3A5*1/*3 or *1/*1 and AKR1C3 Q5H CC genotypes was 1.84 with 95% CI 1.03-3.28. For prostate cancer, the best two-gene interaction included genotypes SRD5A2 V89L GG and AKR1C3 Q5H CC with OR 1.30, 95% CI 1.01-1.66. It remains to be clarified whether these polymorphism associations identified here are also present in other populations.
authors.affiliation: Department of Pathology, University of Oulu, Oulu, Finland. markku.vaarala@oulu.fi
authors.forename: Markku H
authors.initials: MH
authors.lastname: Vaarala
authors.forename: Henna
authors.initials: H
authors.lastname: Mattila
authors.forename: Pasi
authors.initials: P
authors.lastname: Ohtonen
authors.forename: Teuvo L J
authors.initials: TL
authors.lastname: Tammela
authors.forename: Timo K
authors.initials: TK
authors.lastname: Paavonen
authors.forename: Johanna
authors.initials: J
authors.lastname: Schleutker
mesh_terms: D000368:Aged; D000369:Aged, 80 and over; D000728:Androgens / Q000378:metabolism*; D016022:Case-Control Studies; D016001:Confidence Intervals; D051544:Cytochrome P-450 CYP3A / Q000235:genetics*; D005387:Finland; D020022:Genetic Predisposition to Disease; D005838:Genotype; D006801:Humans; D016015:Logistic Models; D008297:Male; D008875:Middle Aged; D009367:Neoplasm Staging; D009376:Neoplasms, Hormone-Dependent / Q000201:enzymology / Q000378:metabolism*; D016017:Odds Ratio; D011110:Polymorphism, Genetic; D020641:Polymorphism, Single Nucleotide; D017430:Prostate-Specific Antigen / Q000097:blood; D011471:Prostatic Neoplasms / Q000201:enzymology / Q000276:immunology / Q000378:metabolism* / Q000473:pathology; D015398:Signal Transduction / Q000235:genetics; D044465:White People / Q000235:genetics
chemical_list: D000728:Androgens; C510164:CYP3A5 protein, human; D051544:Cytochrome P-450 CYP3A; D017430:Prostate-Specific Antigen