Genetic variations in immune mediators and prostate cancer risk: A field synopsis with Bayesian calculations

Abstract

ObjectiveOur study aimed to revaluate the significant data from meta-analyses on genetic variations in immune mediators and the risk of prostate cancer (PCa) by Bayesian approaches. MethodsWe performed a search on the literature before September 5th, 2023, for meta-analytic studies on polymorphisms in immune mediator genes and the risk of PCa. Two Bayesian approaches were used to assess the level of noteworthiness in the meta-analytic data: the False-Positive Rate Probability (FPRP) and the Bayesian False Discovery Probability (BFDP) with a statistical power of 1.2 and 1.5 of Odds Ratio at a prior probability of 10−3 and 10−6. The quality evaluation of studies was performed with the Venice criteria. Gene-gene and protein–protein networks were designed for the genes and products enrolled in the results. ResultsAs results, 18 meta-analyses on 17 polymorphisms in several immune mediator genes were included (IL1B rs16944/rs1143627, IL4 rs2243250/rs2227284/rs2070874, IL6 1800795/rs1800796/rs1800797, IL8 rs4073, IL10 rs1800896/rs1800871/rs1800872, IL18 rs1946518, COX2 rs2745557, TNFA rs361525 and PTGS2 rs20417/689470). The Bayesian calculations showed the rs1143627 and the rs1946518 polymorphisms in IL1B and IL18 genes, respectively, were noteworthy. The Venice criteria showed that only four studies received the highest level of evidence. The gene-gene and protein–protein networks reinforced the findings on IL1B and IL18 genes. ConclusionIn conclusion, this current Bayesian revaluation showed that the rs1143627 and the rs1946518 polymorphisms in the IL1B and IL18 genes, respectively, were noteworthy biomarker candidates for PCa risk.