• Etiologie

  • Facteurs endogènes

  • Prostate

Interactions of PVT1 and CASC11 on Prostate Cancer Risk in African Americans

Menée auprès de 2 253 patients afro-américains atteints d'un cancer de la prostate et auprès de 2 423 témoins, cette étude évalue l'association entre les interactions des polymorphismes à simple nucléotide des gènes CASC11, MYC et PVT1 et le risque de développer la maladie

Background : African American (AA) men have a higher risk of developing prostate cancer (PCa) than White men. Single nucleotide polymorphisms (SNPs) are known to play an important role in developing PCa. The impact of PVT1 and its neighborhood genes (CASC11 and MYC) on PCa risk are getting more attention recently. The interactions among these three genes associated with PCa risk are understudied, especially for AA men. The objective of this study is to investigate SNP-SNP interactions in the CASC11-MYC-PVT1 region associated with PCa risk in AA men. Methods : We evaluated 205 SNPs using the 2,253 PCa patients and 2,423 controls and applied multi-phase (discovery-validation) design. In addition to SNP individual effects, SNP-SNP interactions were evaluated using the SNP Interaction Pattern Identifier (SIPI), which assesses 45 patterns. Results : Three SNPs (rs9642880, rs16902359, and rs12680047) and 79 SNP-SNP pairs were significantly associated with PCa risk. These two SNPs (rs16902359 and rs9642880) in CASC11 interacted frequently with other SNPs with 56 and 9 pairs, respectively. We identified the novel interaction of CASC11-PVT1, which is the most common gene interactions (70%) in the top 79 pairs. Several top SNP interactions have a moderate to large effect size (odds ratio=0.27-0.68) and have a higher prediction power to PCa risk than SNP individual effects. Conclusions : Novel SNP-SNP interactions in the CASC11-MYC-PVT1 region have a larger impact than SNP individual effects on PCa risk in AA men. Impact : This gene-gene interaction between CASC11 and PVT1 can provide valuable information to reveal potential biological mechanisms of PCa development.

Cancer Epidemiology Biomarkers & Prevention

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