Citations 1
Patient-Derived Xenograft-Guided Prediction of Chemotherapy Response in Triple-Negative Breast Cancer
Huang, Chen , Srinivasan, Ramakrishnan Rajaram , Lewis, Alaina , Sallas, Christina , Zhao, Na , Cao, Jin , Pilcher, Jacob B., Moon, Chang In, Liao, Yuxing , Rimawi, Mothaffar F. , Malovannaya, Anna , Li, Shunqiang , Kraushaar, Daniel C. , Goetz, Matthew P., Boughey, JC , Wang, Liewei, Kalari, Krishna R., Suman, Vera J., Damodaran, Senthil, Zheng, Xiaofeng, Meric-Bernstam, F, Welm, Bryan E. , Welm, Alana L. , Zhang, Bing , Lei, Jonathan T , Zhao, Na , Wen, Bo , Rimawi, Mothaffar , Lei, Jonathan T. , Dobrolecki, Lacey E. , Vasaikar, Suhas , Landua, John David , Pilcher, Jacob B. , Hilsenbeck, Susan Galloway , Ellis, Matthew J. , Petrosyan, Varduhi, Li, Kai shang , Saltzman, Alexander B. , Jain, Antrix , Wulf, Gerburg M. , Marangoni, Elisabetta , Wang, Tao , Goetz, Matthew P. , Damodaran, Senthil , Zheng, Xiaofeng , Meric‐Bernstam, Funda , Echeverria, Gloria Vittone , Anurag, Meenakshi , Chen, Xi , Lewis, Michael T.
No container title available | December 12, 2024 | Volume: No volume available | Issue: No issue available | Pages: No page available
Abstract Chemotherapy regimens for triple-negative breast cancer (TNBC) combine agents without knowing which agents drive response. Consequently, predictors derived from multi-agent regimens cannot be assumed to generalize to individual drugs or other regimens, motivating development of treatment-matched predictors. Here, we used TNBC patient-derived xenografts (PDXs) treated with carboplatin, docetaxel, or the combination to deconvolute drug-specific responses and identify associated molecular features. Combination treatment rarely improved upon the best single agent, with enhanced responses in only 13% of PDXs and antagonism in a comparable fraction. Proteogenomic analyses identified high cytokeratin-5 (KRT5) as a general marker of chemotherapy responsiveness and KRT5 immunohistochemistry discriminated responsive PDXs (AUROC, 0.83). To train treatment-specific predictors, we integrated these data with independent PDX and clinical cohorts with responses assessed after anthracycline-free platinum, taxane, or platinum-taxane therapy, ensuring response corresponded to the modeled treatment. Four feature selection strategies yielded largely nonoverlapping biomarker panels converging on treatment-relevant pathways. On independent test data, RNA-based predictors of complete response (CR) to platinum-based (carboplatin or cisplatin) and taxane-based (docetaxel or paclitaxel) chemotherapy achieved AUROCs of 0.80 and 0.86, respectively. For platinum-taxane regimens (carboplatin plus docetaxel or paclitaxel), proteomic-guided feature selection generated a 10-biomarker, protein- informed RNA predictor of pathologic complete response (pCR) that outperformed RNA-only feature selection and achieved an AUROC of 0.85 in an independent clinical cohort, while retaining practicality as an RNA-based assay. Treatment-matched integration of multi-omic PDX and clinical datasets provides a framework for chemotherapy-specific predictors with clinically relevant performance, supporting biomarker-guided precision selection and treatment optimization for patients with TNBC. Statement of significance Integration of multi-omic data from patient-derived xenografts with treatment-matched clinical cohorts yielded three retrospectively validated predictors of platinum, taxane, and platinum+taxane response, enabling biomarker-guided chemotherapy selection for patients with triple-negative breast cancer.