Modeling Drug Responses and Evolutionary Dynamics Using Patient-Derived Xenografts Reveals Precision Medicine

Abigail Shea1,2, Yaniv Eyal-Lubling1, Daniel Guerrero-Romero1

  • 1Department of Oncology, Cancer Research UK Cambridge Institute, Li Ka Shing Centre, University of Cambridge, Cambridge, United Kingdom.

Cancer Research
|November 8, 2024
PubMed

Insights

Patient-derived tumor xenografts (PDTX) accurately predict triple-negative breast cancer drug responses. This preclinical model reveals how therapies drive tumor evolution and phenotypic changes, aiding personalized treatment strategies.

Area of Science:

  • Oncology
  • Translational Research
  • Cancer Heterogeneity

Background:

  • Triple-negative breast cancer (TNBC) exhibits significant intertumor and intratumor heterogeneity, leading to variable drug responses and complex tumor evolution.
  • Understanding these dynamics is crucial for developing effective personalized cancer treatment strategies.

Purpose of the Study:

  • To develop and validate a preclinical experimental and analytical framework using patient-derived tumor xenografts (PDTX) from treatment-naïve TNBC.
  • To assess the predictive value of PDTXs for personalized cancer therapy and investigate treatment-induced tumor evolution.

Main Methods:

  • Established PDTX models from treatment-naïve TNBC patients.
  • Conducted preclinical studies using two trial designs and dosing schedules to compare patient and PDTX drug responses.
  • Utilized high-throughput drug screening in ex vivo PDTX cells and in vivo validation.
  • Analyzed nongenetic mechanisms driving relapse dynamics and phenotypic changes.

Main Results:

  • PDTX models demonstrated concordant drug responses with matched patients to neoadjuvant therapy.
  • Treatment induced permanent phenotypic changes with functional and therapeutic consequences.
  • Ex vivo drug screening identified patient-specific drug response alterations post-first-line therapy, validated in vivo (e.g., olaparib sensitivity changes after chemotherapy).

Conclusions:

  • PDTXs are robust preclinical tools for predicting patient drug responses and modeling therapeutic regimens and evolutionary trajectories in TNBC.
  • High intermodel variability and permanent nongenomic transcriptional changes are important considerations for personalized therapy.
  • The PDTX platform can guide the identification of efficacious sequential therapeutic regimens.

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