Analysis of prostate cancer risk and aggressiveness via selected SNPs and testing potential for AKR1C3 selective inhibitors as treatment options for prostate cancer

Abstract

Prostate cancer (PCa) is the most commonly diagnosed cancer and the second most common cause of cancer-related death among men in Australia and New Zealand. Current strategies for managing PCa involve screening and early detection of PCa, calculating the risk of developing aggressive forms of PCa, and responding with appropriate therapies. As advanced PCa is incurable and has high mortality, identification and treatment of PCa at a non-advanced stage is desired. The most commonly used biomarker for screening prostate cancer is prostate specific antigen (PSA). However PSA is a biomarker for the prostate rather than PCa, therefore, the use of PSA can often lead to unnecessary prostate biopsies and possibly missing some cases of PCa. PCa arises as a result of a combination of genetic and environmental influences. Several genetic polymorphisms and lifestyle factors have been found to be associated with increased risk of PCa and aggressive PCa. Identification of these factors can help with predicting the risk of developing PCa and PCa progression into aggressive forms. This study included 684 participants, including 336 healthy controls and 348 men with prostate abnormalities. The lifestyles and physical characteristics of the participants were acquired from self-reported questionnaires. We have found current smoking and those with high BMI to be significantly at risk for PCa. In addition, we have no significant association between serum selenium level and PCa risk. We selected 37 SNPs from published studies which found associations between the SNPs and PCa. The selected SNP alleles of the study participants were genotyped using Sequenom iPLEX MassARRAY. We found statistically significant associations between the A allele of rs3774315 and the C allele of rs5945619 with increased risk of PCa. We have also found the C allele of rs17160911 to be significantly associated with Gleason score. The three SNPs found to be associated with PCa pathology are related to TNFSF10, NUDT11, and KLRG2 genes respectively. Aldo-keto reductase (AKR) 1C3 is involved in PCa pathology via promoting androgen synthesis, synthesis of pro-proliferation signal protein Prostaglandin F (PGF), and regulation of oncogenes and tumour suppressor genes. AKR1C3 may be a potential target for the treatment of PCa. The growth inhibitory effects of four AKR1C3-specific inhibitors in LNCaP and PC3 cell lines were tested. These cell lines represent hormone-dependent and hormone-independent PCa cell lines respectively. SN33941 and SN34037 were found to show stronger growth inhibitory effects than SN33607 and SN34379. Changes in expression levels of prostate cancer antigen 3 (PCA3) and PSA genes in LNCaP cells following treatment with AKR1C3 inhibitors were also investigated. SN34037 which is morpholino(4-phenylpiperazin-1-yl)methanone (MPPM) significantly reduced the expression of PCA3 and PSA in LNCaP cells at sub-lethal dosages. Therefore, the MPPM class of AKR1C3 inhibitor is a potential candidate for the treatment of PCa.