DECIPHERING DRUG RESISTANCE MECHANISMS IN TRIPLE-NEGATIVE BREAST CANCER THROUGH CROSS-PLATFORM INTEGRATION OF SCRNA-SEQ,EPIGENOMICS, AND CHEMOINFORMATICSINTRODUCTION

Abstract

Triple-negative breast cancer (TNBC) is an aggressive and treatment-resistant subtype of breast cancer lacking targeted hormonal receptors and HER2 expression. This study presents a multi-omics and chemoinformatics-based investigation into the molecular mechanisms driving drug resistance in TNBC. Single-cell RNA sequencing (scRNA-seq) and ATAC-seq were performed on patient-derived TNBC samples to identify transcriptional and epigenomic alterations associated with chemotherapeutic response. Chemoinformatic modeling of IC50 profiles across diverse compounds, including paclitaxel and PARP inhibitors, revealed substantial heterogeneity in drug sensitivity. Nine comprehensive tables were constructed to catalog gene expression variability, methylation scores, and drug resistance indices, while twelve complex visualizations illustrated expression dynamics, resistance distribution, and biomarker patterns. The results highlighted critical resistance mechanisms, including epigenetic silencing, hypoxia-induced transcriptional rewiring, and immune-exclusion signatures from the tumor microenvironment. Notably, a subset of genes exhibited resistance-specific expression patterns linked to poor response outcomes. The integration of multi-omics datasets enabled the identification of high-confidence drug-gene associations, supporting the utility of predictive models in therapeutic stratification. These findings underscore the urgent need for personalized treatment strategies and emphasize the value of integrative systems biology approaches in overcoming therapeutic resistance. This study contributes a foundational framework for precision oncology in TNBC, offering robust biomarkers and novel targets for future clinical intervention.