Abstract 491: Molecular correlates of drug response to identify novel therapeutic combinations in triple-negative breast cancer
Authors: Nathan M. Merrill, Hamadi Madhi, Nathalie Vandecan, Athena Apfel, Habib Serhan, Peter J. Ulintz, Liwei Bao, Xu Cheng, Aki Morikawa, Matthew B. Soellner, Sofia D. Merajver
Journal: Cancer Research (2025)

Abstract TNBC accounts for 10-20% of total breast cancer cases in the US and is more aggressive, higher grade, and has a poorer prognosis than other forms of breast cancer. TNBC is more likely to metastasize within 3-5 years than other forms of breast cancer and there is an urgent need to effectively implement precision medicine to improve outcomes for patients with TNBC, beyond unranked lists of drugs that may affect pathways related to genomic alterations. To this end, we have developed a precision-medicine-platform (PMP) to identify robust predictors of drug response in TNBC. We assembled a panel of 35 TNBC models that were screened with a curated library of 359 compounds comprising a broad array of approved and experimental small-molecule inhibitors. Additionally, we completed multiomic characterization (DNA sequencing, RNA sequencing, RNA targeted panels, and Reverse Phase Protein Array, RPPA) of passage-matched material. Integrating drug response readouts with molecular characterization allowed us to identify statistically significant molecular correlates of response to therapy. Further, co-targeting correlating pathways has proven to be a reliable method to identify robust synergistic combinations. Following screening, we prioritized 35 drugs on the basis of their activity and variance of response, identifying significant molecular correlates of drug response for 27 prioritized compounds. Grouping together chemotherapeutic agents, we were able to identify a signature of response generalized to chemotherapeutics. From our molecular correlate signatures, we identified a robust and novel correlation between combretastatin A4 (CA4) response and expression of EGFR at both the RNA and protein levels. Combining CA4 and EGFR inhibitors resulted in robust synergy in cell lines, ex vivo patient-derived xenograft models, and patient-derived organoid models. We finally validated this synergy using in vivo models of TNBC. Moving forward, we are working to evaluate the CA4 and EGFR inhibitor combination using additional in vivo models of TNBC. In conclusion, our PMP has allowed us to identify molecular correlates of response to therapy. Leveraging these molecular correlations, we identified robust novel combinations. This strategy will be critical in helping to translate precision-medicine to the clinic for patients with TNBC. Moreover, our strategy could allow us to revive repurposing strategies that previously failed clinical trials by pairing the right patients with the right drug and combination. Citation Format: Nathan M. Merrill, Hamadi Madhi, Nathalie Vandecan, Athena Apfel, Habib Serhan, Peter J. Ulintz, Liwei Bao, Xu Cheng, Aki Morikawa, Matthew B. Soellner, Sofia D. Merajver. Molecular correlates of drug response to identify novel therapeutic combinations in triple-negative breast cancer [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2025; Part 1 (Regular Abstracts); 2025 Apr 25-30; Chicago, IL. Philadelphia (PA): AACR; Cancer Res 2025;85(8_Suppl_1):Abstract nr 491.