Association of folate metabolism-related enzymes (MTHFR, MYD88, and TP53) and their single nucleotide polymorphisms with breast cancer susceptibility in women from Southwest China: a Bayesian network approach - Li, Xingxu; Gong, Yunyu; Zhao, Yuxin; Kong, Xianshu; Liu, Yingbo; Liu, Qunshan; Zhang, Yunjiao; Li, Zhen (Frontiers in Oncology, 2025)
BackgroundBreast cancer remains one of the most prevalent malignant tumors affecting women globally. Genetic factors are significant contributors to its pathogenesis. Single nucleotide polymorphisms (SNPs), as a common form of genetic variation, have garnered considerable attention in recent years. However, most studies have predominantly focused on associations between individual loci and breast cancer susceptibility, while the complex interactions among multiple loci across different genes remain insufficiently explored.MethodsTo analyze high-dimensional multi-locus variables, chi-square test and random forests were employed. Bayesian networks, a sophisticated statistical model, were used to investigate SNP interactions across multiple genes and to construct a comprehensive genetic susceptibility model for female breast cancer.ResultsThe study analyzed 980 samples, comprising 490 breast cancer patients and 490 controls. Key intergenic genotypes were identified involving SNPs in TP53 (rs1042522), MTHFR (rs1801133), MTHFR (rs56221660), MTRR (rs1801394), MTR-A2756G (rs1805087), MYD88 (rs7744), and rs7851696. These interactions were associated with a significant increase in breast cancer prevalence, rising from 48.2% in the original data to 99% under the largest posterior probability combination. External validation further demonstrated a breast cancer prevalence of 70%, underscoring the robustness of the model.ConclusionsInteractions among the TP53, MYD88, and folate metabolism-related genes (MTHFR, MTR, and MTRR) may play a critical role in breast cancer susceptibility.