Estrogen receptor-mediated pharmacogenomic eQTLs as predictors of endocrine therapy response in breast cancer

Background: Approximately 70% of breast cancers are estrogen receptor-positive (ER+), and endocrine therapies, including selective estrogen receptor modulators (SERMs) and aromatase inhibitors (AIs), are standard-of-care. However, interpatient variability in treatment response and relapse remains substantial, suggesting underlying germline pharmacogenomic factors that modify ER signaling. Here, we mapped ER pharmacogenomic eQTLs to identify germline variants that modulate transcriptional responses to estradiol (E2) and tamoxifen (Tam). Methods: We treated 30 genotyped lymphoblastoid cell lines (LCLs) with vehicle, E2, Tam, or E2+Tam and performed RNA-seq to quantify ligand-induced expression fold changes. Using MatrixEQTL, we identified SNP-gene PGx-eQTLs (cis, ±200 kb), requiring evidence of ER transcriptional specificity via (i) reversal by dual treatment, and (ii) overlap with ER ChIP-seq binding annotations. Clinical relevance was assessed by linkage to breast cancer GWAS datasets, including NSABP, MA.27, and M3. Chromatin regulatory states were annotated (ChromHMM), and transcription factor motif enrichment was performed from SNP-centered ±200 bp regions. Results: Distinct PGx-eQTL architectures were identified for E2 and Tam, with partial overlap in ligand-responsive loci. ER PGx-eQTL variants were predominantly enriched in enhancer chromatin and co-localized with canonical ER-binding motifs. Integrative analysis with GWAS of breast cancer outcomes highlighted multiple drug-response-associated loci, including rs311392-MRPL15 and rs7953325-SYCP3. High MRPL15 expression was linked to shorter relapse-free survival, whereas high SYCP3 expression correlated with improved outcomes. Additional loci derived from a GWAS catalog for cancer and hormone phenotypes included rs2850247-SIK2 and rs11673604-LSM4, where higher SIK2 expression was associated with improved relapse-free survival and higher LSM4 expression with poorer outcomes. Conclusions: We identified ligand-dependent ER PGx-eQTLs that mechanistically connect germline regulatory variants to transcriptional response heterogeneity and clinical endocrine therapy outcomes. These SNP-gene relationships represent potential biomarkers for precision endocrine therapy selection and may reveal endocrine-dependent therapeutic vulnerabilities.