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Wang, Xue

Mayo Clinic

Mayo Clinic

Citations 1

Study of Estrogen Receptor-Mediated PGx-eQTLs Identifies Genetic Determinants of Breast Cancer Endocrine Therapy Response
Meng, Martin, Ghosh, Arnab , Gao, Huanyao , August, John, Indulkar, Shreya, Wang, Meijie , Wang, Xue, Wang, Zhuyao, Namagerdi, Asadoor Amirkhani, Weinshilboum, Richard M., Ingle, James N. , Wang, Liewei, Ingle, J , Meng, Martin, Wang, Xue, Weinshilboum, Richard M., Wang, Liewei

International Journal of Molecular Sciences | September 15, 2026 | Volume: 27 | Issue: 18 | Pages: 8217

10.3390/ijms27188217 Get It

Endocrine therapy remains the cornerstone of treatment for estrogen receptor alpha (ERα)-positive breast cancer, yet the relationship between individual genetic background and molecular response to ERα-targeted therapy remains incompletely understood. Using a well-characterized panel of lymphoblastoid cell lines (LCLs), we performed genome-wide pharmacogenomic expression quantitative trait locus (PGx-eQTL) analysis to identify estradiol (E2)- and tamoxifen (TAM)-induced SNP-gene pairs. PGx-eQTL signals were integrated with previously published breast cancer genome-wide association study datasets to examine their association with clinically relevant breast cancer phenotypes. We identified two ER-mediated PGx-eQTL SNP-gene pairs associated with breast cancer prognosis post-treatment with E2 or TAM. Notable loci included E2-regulated MRPL15 and TAM-regulated SYCP3, which have effects in a genotype-dependent manner, with genotype-dependent survival outcomes, from worse to better relapse-free survival. Similar endocrine-therapy effects on patient survival and breast cancer risk were observed in SIK2, post TAM-treatment, and in LSM4 with E2-treatment. Moreover, qRT-PCR validation in an independent LCL panel confirmed the genotype-specificity of these signals. Overall, we identified ER-mediated PGx-eQTL SNP-gene pairs which represent potential pharmacogenomic tools for identifying patients likely to benefit from ERα-targeted endocrine therapy, offering a foundation for more genotype-informed individualized treatment decisions in breast cancer.