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posted on 2025-02-01, 19:20 authored by Abigail Shea, Yaniv Eyal-Lubling, Daniel Guerrero-Romero, Raquel Manzano Garcia, Wendy Greenwood, Martin O’Reilly, Dimitra Georgopoulou, Maurizio Callari, Giulia Lerda, Sophia Wix, Agnese Giovannetti, Riccardo Masina, Elham Esmaeilishirazifard, Wei Cope, Alistair G. Martin, Ai Nagano, Lisa Young, Steven Kupczak, Yi Cheng, Helen Bardwell, Elena Provenzano, Justine Kane, Jonny Lay, Louise Grybowicz, Karen McAdam, Carlos Caldas, Jean Abraham, Oscar M. Rueda, Alejandra Bruna <p>PDTXs identify patient-specific drug responses and model patient- and treatment-specific regrowth dynamics. <b>A,</b> Experimental framework to test drug responses to alternative treatments and regrowth dynamics. <b>B</b> and <b>C,</b> Mean difference in daily growth rate between the treated and untreated groups during treatment (<b>B</b>) and after treatment has ceased (<b>C</b>). <b>D</b> and <b>E</b>, TV growth curves displaying linear mixed model fits of PDTX models 1040 (left) and 1141 (right) during treatment (<b>D</b>) and after treatment has ceased (<b>E</b>). T–UT, treated–untreated.</p>
Funding
Cancer Research UK (CRUK)
Cancer Research UK Cambridge Institute, University of Cambridge (CRUK CI)
HORIZON EUROPE European Research Council (ERC)
NIHR Cambridge Biomedical Research Centre (NIHR Cambridge BRC)
Medical Research Council (MRC)
HORIZON EUROPE Marie Sklodowska-Curie Actions (MSCA)
Institute of Cancer Research (ICR)
History
ARTICLE ABSTRACT
The intertumor and intratumor heterogeneity of triple-negative breast cancers, which is reflected in diverse drug responses, interplays with tumor evolution. In this study, we developed a preclinical experimental and analytical framework using patient-derived tumor xenografts (PDTX) from patients with treatment-naïve triple-negative breast cancers to test their predictive value in personalized cancer treatment approaches. Patients and their matched PDTXs exhibited concordant drug responses to neoadjuvant therapy using two trial designs and dosing schedules. This platform enabled analysis of nongenetic mechanisms involved in relapse dynamics. Treatment resulted in permanent phenotypic changes, with functional and therapeutic consequences. High-throughput drug screening methods in ex vivo PDTX cells revealed patient-specific drug response changes dependent on first-line therapy. This was validated in vivo, as exemplified by a change in olaparib sensitivity in tumors previously treated with clinically relevant cycles of standard-of-care chemotherapy. In summary, PDTXs provide a robust tool to test patient drug responses and therapeutic regimens and to model evolutionary trajectories. However, high intermodel variability and permanent nongenomic transcriptional changes constrain their use for personalized cancer therapy. This work highlights important considerations associated with preclinical drug response modeling and potential uses of the platform to identify efficacious and preferential sequential therapeutic regimens.Significance: Patient-derived tumor xenografts from treatment-naïve breast cancer samples can predict patient drug responses and model treatment-induced phenotypic and functional evolution, making them valuable preclinical tools.
