Identification of potential therapeutic targets for breast cancer using Mendelian randomization analysis and drug target prediction.

Abstract

Breast cancer stands as the foremost cause of cancer-related mortality among women, presenting a substantial economic impact on society. The limitations in current therapeutic options, coupled with poor patient tolerance, underscore the urgent need for novel treatments. Our study embarked on a genomic association exploration of breast cancer, leveraging whole-genome sequencing data from the Finngen database, complemented by expression quantitative trait loci (eQTL) insights from the eQTLGen and GTEx Consortiums. An initial investigation was conducted through summary-based Mendelian randomization (MR) to pinpoint primary eQTLs. Analysis of blood specimens revealed 103 eQTLs significantly correlated with breast cancer. Focusing our efforts, we identified 19 candidates with potential therapeutic significance. Further scrutiny via two-sample MR pinpointed UROD, LMO4, HORMAD1, and ZSWIM5 as promising targets for breast cancer therapy. Our research sheds light on new avenues for the treatment of breast cancer, highlighting the potential of genomic association studies in uncovering viable therapeutic targets.