| Title: |
Modeling Drug Responses and Evolutionary Dynamics Using Patient-Derived Xenografts Reveals Precision Medicine Strategies for Triple-Negative Breast Cancer. |
| Authors: |
Shea, A; Eyal-Lubling, Y; Guerrero-Romero, D; Manzano Garcia, R; Greenwood, W; O'Reilly, M; Georgopoulou, D; Callari, M; Lerda, G; Wix, S; Giovannetti, A; Masina, R; Esmaeilishirazifard, E; Cope, W; Martin, AG; Nagano, A; Young, L; Kupczak, S; Cheng, Y; Bardwell, H; Provenzano, E; Kane, J; Lay, J; Grybowicz, L; McAdam, K; Caldas, C; Abraham, J; Rueda, OM; Bruna, A |
| Contributors: |
Bruna Cabot, Alejandra |
| Publisher Information: |
AMER ASSOC CANCER RESEARCH |
| Publication Year: |
2024 |
| Collection: |
The Institute of Cancer Research (ICR): Publications Repository |
| Description: |
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. |
| Document Type: |
article in journal/newspaper |
| File Description: |
application/pdf |
| Language: |
English |
| ISSN: |
1538-7445; 0008-5472 |
| Relation: |
Cancer Research, 2024; https://repository.icr.ac.uk/handle/internal/6480 |
| Availability: |
https://repository.icr.ac.uk/handle/internal/6480 |
| Rights: |
https://creativecommons.org/licenses/by/4.0/ |
| Accession Number: |
edsbas.A2A35A8A |
| Database: |
BASE |