The l58Val/Met polymorphism of catechol-O-methyl transferase gene and prostate cancer risk: a meta-analysis

Abstract

The association between COMT Val158Met polymorphism and prostate cancer has been evaluated. However, the results of these studies on the association remain conflicting. To derive a more precise estimation of the relationship, a meta-analysis was performed. A comprehensive search was conducted to identify the eligible studies of COMT Val158Met polymorphism and prostate cancer risk. Summary odds ratios (OR) and 95 % confidence interval (CI) for COMT Val158Met polymorphism and prostate cancer were calculated. Statistical analysis was performed with the software program Review Manage (Version 5.0) and Stata (Version 12.0). Six case-control studies, totally 4,118 persons including 2,143 cases and 1,975 controls, met the included criteria and thus were selected. Our analysis suggested that Val158Met polymorphism was associated with prostate cancer risk in overall population. Collectively, the results of the present study suggest that significant associations of COMT Val158Met polymorphisms with prostate cancer were observed (for additive model: OR = 1.068, 95 % CI = 1.002-1.138, P (heterogeneity) = 0.363, P = 0.043; for dominant model: OR = 1.266, 95 % CI = 1.057-1.517, P (heterogeneity) = 0.000, P = 0.011; for recessive model: OR = 1.050, 95 % CI = 0.961-1.146, P (heterogeneity) = 0.558, P = 0.279; and Val allele versus Met allele OR = 0.932, 95 % CI = 0.894-0.971, P (heterogeneity) = 0.272, P = 0.001). In the subgroup analysis, we detected no significant association between the COMT 158 Val/Met genotype and prostate cancer risk in Caucasian and Asian populations, while the contrary result for additive model (OR = 2.43, 95 % CI = 1.08-5.43, P (heterogeneity) = 0.04, P = 0.03) in Asian populations. The result of this meta-analysis suggests that COMT l58Val/Met polymorphism might be contributed to the overall prostate cancer risk.

Genetic polymorphisms in CYP1A1, CYP1B1 and COMT genes in Greenlandic Inuit and Europeans

“…Thus, the prevalence of homozygous COMT Met/Met variant is hypothesized to be associated with increased risk of developing estrogen-related cancers. Epidemiological studies have investigated the association of COMT polymorphism with cancers in hormone-responsive tissues, but the results are inconsistent (32,33). …”

“…Individuals carrying the variant Met allele are hypothesized to have a decreased ability to form the anti-tumour 2-MeOE2, causing an increased accumulation of the reactive catechol estrogen intermediates and thus facilitating the development of estrogen-induced tumours such as breast cancer. Epidemiological study data on the influence of the COMT-L variant (Met/Met) with respect to human cancers such as breast (31,32), endometrial and prostate carcinoma (33) are controversial. In the European population, a near-equal frequency of the two alleles exists, while the wild type Val allele is much more common in the Asian population (34).…”

Polymorphisms of Estrogen Metabolism-Related Genes and Prostate Cancer Risk in Two Populations of African Ancestry

“…The association of the COMT (rs4680) polymorphism with the risk of prostate cancer has been investigated only in Caucasian and Asian populations, and three meta-analyses have reported no overall association [ 41 – 43 ]. However, one of these studies reported a significant inverse association in Asian carriers of the A allele [ 43 ]. We show here that the AA genotype or A allele was associated with a significantly lower risk of prostate cancer in Afro-Caribbean and native African populations.…”

Germline genetic variation in JAK2 as a prognostic marker in castration‐resistant prostate cancer

“…Lastly, because neuroendocrine differentiation plays an important role in the prognosis and treatment of patients with CRPC, we incorporated CHGA and SYP, two genes involved in neuroendocrine differentiation in our analysis. In summary, 15 candidate genes implicated in prostate cancer development and progression, including NKX3-1, JAK2, SLCO2B1, STAT3, CYP19A1, HSD17B4, TRMT11, PRMT3, HSD17B12, NCOA4, CHGA, FASN, COMT, SREBF2, and SYP 490 © 2016 The Authors BJU International © 2016 BJU International were selected [15][16][17][18][19][20][21][22][23][24][25][26][27]. For each gene, tagSNPs identified from HapMap using a pair-wise tagging approach with a minor allele frequency ≥5% and an r 2 of 0.9 were identified.…”