Leveraging Genome-wide Association Studies to Identify Pathogenic Variants for Breast Cancer Among Multiple...

Breast cancer (BCa) remains one of the most prevalent malignancies and a leading cause of cancer-related deaths globally. Understanding the genetic underpinnings of BCa is critical for advancing precision medicine, including the development of predictive biomarkers and repurposed therapies. This study aimed to identify and functionally annotate BCa-associated single nucleotide polymorphisms (SNPs) to identify biological risk genes and assess drug repositioning opportunities.

We extracted BCa-related SNPs from the GWAS Catalog, applying a genome-wide significance threshold (p-value <10^-8) to identify 1,219 SNPs. From these, 14 missense variants were prioritized and evaluated using six complementary tools: missense annotation, cis-expression quantitative trait loci (eQTL) mapping, combined annotation dependent depletion (CADD), sorting intolerant from tolerant (SIFT), polymorphism phenotyping v2 (PolyPhen-2) and AlphaMissense. Genes were scored across these criteria, with those scoring ≥2 considered biologically relevant. GTEx data was used to assess tissue-specific gene expression. Allele frequencies across populations were obtained from the Ensembl database, and druggability was evaluated using DrugBank.

We identified nine genes achieving the maximum score of 4 as the highest-priority candidates SLCO1B1 (rs4149056), ARHGEF38 (rs61751053), EXO1 (rs4149909), KDELC2 (rs74911261), MAPT (rs63750417), PHLDA3 (rs35383942), AKAP9 (rs6964587), ATXN7 (rs1053338) and DCLRE1B (rs11552449). SLCO1B1 (rs4149056) and ARHGEF38 (rs61751053), supported by functional and regulatory evidence. SLCO1B1, predominantly expressed in the liver, may influence BCa metastasis and drug metabolism; its variant shows population-specific allele distribution, being particularly higher in Europeans (16%). ARHGEF38, though variably expressed across tissues, may play regulatory roles relevant to tumorigenesis. Among the prioritized genes, MAPT was identified as the only druggable target, with existing therapeutics such as paclitaxel and docetaxel indirectly linked to its function, suggesting potential for drug repurposing. These findings provide a foundation for further studies on SNP-guided biomarkers and repositioned therapies targeting key BCa-related genes.

This integrative bioinformatics approach prioritized functionally significant BCa-associated SNPs and identified promising candidates for biomarker development and drug repositioning. The nine high-scoring variants, including SLCO1B1 and ARHGEF38 emerge as biologically impactful genes, while MAPT's known drug interactions highlight its translational potential in repurposing existing anticancer agents.