In Silico Characterization of Pathogenic ESR2 Coding and UTR Variants as Oncogenic Potential Biomarkers in Hormone-Dependent Cancers

Background: The ESR2 gene encodes Estrogen Receptor-β1 (ERβ1), a putative tumor suppressor in hormone-dependent malignancies. Although ERβ biology has been studied extensively at the expression level, the functional impact of nonsynonymous SNPs (nsSNPs) and untranslated-region (UTR) variants in ESR2 remains underexplored. Methods: We retrieved variants from Ensembl and performed an integrative in silico assessment using PredictSNP, I-Mutant, MUpro, HOPE, MutPred2, and CScape for pathogenicity, oncogenicity and structural stability; STRING/KEGG/GO for pathway context; RegulomeDB and polymiRTS for regulatory effects; and cBioPortal for pan-cancer clinical outcomes (breast (BRCA), endometrial (UCEC), and ovarian (OV)). We evaluated effects of nsSNPs on ERβ1 stability, ligand-binding/DNA-binding domains, co-factor recruitment, and post-transcriptional regulation. Results: Across tools, 93 missense nsSNPs were consistently predicted to be deleterious. Notably, several variants were found to destabilize ERβ1, particularly within the ligand-binding domains (LBD) and DNA-binding domains (DBD). Putative oncogenic drivers R198P and D154N showed high CScape scores and very low population frequencies, consistent with pathogenicity. Several substitutions were predicted to impair coactivator binding and disrupt interactions with key transcriptional partners, including JUN, NCOA1, and SP1. At the post-transcriptional level, rs139004885 was predicted to disrupt miRNA binding, while 3′UTR rs4986938 showed strong regulatory potential and comparatively high population frequency; by contrast, most other identified SNPs were rare. Clinically, pan-cancer survival analyses indicated worse overall survival (OS) in BRCA for ESR2-Altered cases (HR ≈ 2.25; q < 0.001), but better OS in UCEC (HR ≈ 0.24; q ≈ 0.014) and OV (HR ≈ 0.29; q < 0.001), highlighting a tumor-type-specific association. Conclusions: This integrative analysis prioritizes high-impact ESR2 variants that likely impair ERβ1 structure and shows context-dependent clinical effects. Despite their generally low frequency (except for rs4986938), prospective validation linking variant class to ERβ expression and survival outcomes is needed to support biomarker development and therapeutic applications.