Functional Deconstruction of AC-T Chemotherapy Reveals Interindividual Heterogeneity and Independent Drug Action in Breast Cancer

Background/Objectives: Combination chemotherapy remains a cornerstone of breast cancer (BC) treatment, yet the relative contribution of individual drugs within standard regimens remains poorly understood. We investigated whether the activity of the widely used anthracycline-cyclophosphamide-taxane (AC-T) regimen reflects uniform benefit from all constituent drugs or heterogeneous drug-specific vulnerabilities across tumors. Methods: We combined in silico drug-response analyses, functional validation in BC cell lines, and ex vivo profiling in patient-derived organoids (PDOs). Drug responses were integrated into the Probability of Chemotherapeutic Efficacy (PCE), a multidimensional response metric combining relative drug potency, maximal efficacy, and clinically achievable free-drug exposure. To explore the broader applicability of PCE, we additionally applied it to an independent publicly available GR-based pharmacological dataset generated by the HMS LINCS Center. Results: Across BC models, anthracyclines and taxanes displayed only partially overlapping sensitivity profiles, indicating distinct drug-specific vulnerabilities. Functional validation in 2D cell lines and PDOs confirmed highly context-dependent responses to AC-T components. Among 21 PDOs with complete drug-response datasets, extensive interpatient heterogeneity was observed, with non-overlapping patterns of sensitivity to A, C, and T. Responses were better represented as a continuum of functional vulnerability states than as binary sensitive-versus-resistant categories. AC generated the highest proportion of favorable response profiles, with 62% of PDOs classified as partial response-like or complete response-like, compared with 48% for A, 38% for C, and 14% for T. AC activity was positively associated with the most active constituent drug within each PDO. Application of this framework to an independent public dataset produced biologically plausible response patterns consistent with the molecular characteristics of the evaluated breast cancer cell lines, supporting its computational transferability. Conclusions: These findings reveal substantial heterogeneity in the contribution of individual drugs to AC-T activity and are compatible with a model in which different tumors derive benefit from different regimen components. Together, these findings establish a hypothesis-generating functional framework for dissecting the contribution of individual drugs within combination chemotherapy regimens. Prospective studies correlating PDO-derived functional responses with clinical outcomes will be required to determine the predictive value and potential clinical utility of this approach before informing therapeutic decision-making.