Meta-analysis of genetic polymorphisms in xenobiotic metabolizing enzymes and their association with breast cancer risk.

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.

Artificial neural network-based exploration of gene-nutrient interactions in folate and xenobiotic metabolic pathways that modulate susceptibility to breast cancer.

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.