RESUMO
Studies on the association of cytochrome p450 A1 (m1, m2), catechol-O-methyltransferase (COMT) H108L, glutathione S-transferase (GST) T1 and M1 polymorphisms with breast cancer risk were inconclusive. The current study was aimed to clarify the ambiguity in genetic associations of these enzymes with breast cancer risk on a global perspective. A systematic literature search was carried out in PubMed, Google Scholar and Medline, covering all the case-control studies published until September 2017. A meta-analysis was performed based on the random-effect and fixed-effect models to calculate the overall association of each genetic variant with breast cancer risk. Of the five polymorphisms studied, GSTT1 (OR: 1.07, 95% CI: 1.02-1.12 and OR: 1.08, 95% CI: 1.01-1.15 for fixed-effect and random-effect models, respectively) and GSTM1 (OR: 1.22, 95% CI: 1.17-1.26 and OR: 1.25, 95% CI: 1.12-1.35 for fixed-effect and random-effect models, respectively) null polymorphisms exhibited an increased risk for breast cancer in both the models. Cochrane Q-test and I² statistics revealed heterogeneity in association with these polymorphisms (P< 0.0001) with no evidence of publication bias. Thus, GSTT1 and GSTM1 null polymorphisms are risk factors for breast cancer.
Assuntos
Neoplasias da Mama/genética , Glutationa Transferase/genética , Polimorfismo Genético , Neoplasias da Mama/metabolismo , Estudos de Casos e Controles , Catecol O-Metiltransferase/genética , Catecol O-Metiltransferase/metabolismo , Citocromo P-450 CYP1A1/genética , Citocromo P-450 CYP1A1/metabolismo , Feminino , Predisposição Genética para Doença , Glutationa Transferase/metabolismo , Humanos , Fatores de Risco , Xenobióticos/metabolismoRESUMO
In the current study, an artificial neural network (ANN)-based breast cancer prediction model was developed from the data of folate and xenobiotic pathway genetic polymorphisms along with the nutritional and demographic variables to investigate how micronutrients modulate susceptibility to breast cancer. The developed ANN model explained 94.2% variability in breast cancer prediction. Fixed effect models of folate (400 µg/day) and B12 (6 µg/day) showed 33.3% and 11.3% risk reduction, respectively. Multifactor dimensionality reduction analysis showed the following interactions in responders to folate: RFC1 G80A × MTHFR C677T (primary), COMT H108L × CYP1A1 m2 (secondary), MTR A2756G (tertiary). The interactions among responders to B12 were RFC1G80A × cSHMT C1420T and CYP1A1 m2 × CYP1A1 m4. ANN simulations revealed that increased folate might restore ER and PR expression and reduce the promoter CpG island methylation of extra cellular superoxide dismutase and BRCA1. Dietary intake of folate appears to confer protection against breast cancer through its modulating effects on ER and PR expression and methylation of EC-SOD and BRCA1.
