Identification of breast cancer genes and establishment of a prediction model after menopausal hormone therapy

Abstract

Menopausal hormone therapy (MHT) is a widely employed approach for managing menopausal syndrome, entailing the administration of exogenous estrogen to alleviate diverse symptoms and mitigate associated diseases in perimenopausal women. However, recent studies have reported an increased risk of breast cancer associated with estrogen and progestin therapy, although there are notable variations among these studies. Therefore, it is imperative to identify individuals at high risk for breast cancer following MHT. This study conducted a comparative analysis of genes between breast cancer patients who received MHT and those who did not, identifying SNP loci closely associated with the risk of developing breast cancer in postmenopausal women undergoing MHT. A predictive model for assessing the risk of breast cancer in postmenopausal women undergoing MHT was established to facilitate personalized treatment recommendations and alleviate menopausal symptoms. Based on the sequencing data of perimenopausal patients with breast cancer (treated MHT) and unaffected breast cancer (treated MHT), effective SNP sites were obtained in the whole genome, and differential SNP sites associated with breast cancer and hormone therapy were initially screened based on association analysis. Finally, a group of 128 SNP sites for risk prediction of breast cancer in perimenopausal women after hormone therapy was determined. The score of Breast cancer (treated MHT) Cohort was significantly different from the other two groups (Breast cancer (untreated MHT) Cohort, and Unaffected breast cancer (treated MHT) Cohort) (P=0.0032 and P=1.8E-06), which showed that patients with a high risk of breast cancer undergoing MHT could be distinguished based on the above 128 MHT-SNPs. In addition, the efficient of four algorithms was evaluated and the RF method had the highest AUC value 0.813, indicating its superior predictive capability in assessing MHT-related breast cancer risk. The 128 MHT-SNPs presented in this study can be utilized for precise determination of the suitability of MHT for women during perimenopause. And the validated model risk prediction tool effectively forecasts the risk of breast cancer following MHT, thereby offering personalized diagnostic and therapeutic recommendations to clinical practitioners.