Patient-derived xenografts effectively capture responses to oncology therapy in a heterogeneous cohort of patients with solid tumors.


While patient-derived xenografts (PDXs) offer a powerful modality for translational cancer research, a precise evaluation of how accurately patient responses correlate with matching PDXs in a large, heterogeneous population is needed for assessing the utility of this platform for preclinical drug-testing and personalized patient cancer treatment.

Tumors obtained from surgical or biopsy procedures from 237 cancer patients with a variety of solid tumors were implanted into immunodeficient mice and whole-exome sequencing was carried out. For 92 patients, responses to anticancer therapies were compared with that of their corresponding PDX models.

We compared whole-exome sequencing of 237 PDX models with equivalent information in The Cancer Genome Atlas database, demonstrating that tumorgrafts faithfully conserve genetic patterns of the primary tumors. We next screened PDXs established for 92 patients with various solid cancers against the same 129 treatments that were administered clinically and correlated patient outcomes with the responses in corresponding models. Our analysis demonstrates that PDXs accurately replicate patients' clinical outcomes, even as patients undergo several additional cycles of therapy over time, indicating the capacity of these models to correctly guide an oncologist to treatments that are most likely to be of clinical benefit.

Integration of PDX models as a preclinical platform for assessment of drug efficacy may allow a higher success-rate in critical end points of clinical benefit.

  • Bedi A
  • Ben-Zvi I
  • Ciznadija D
  • Davies A
  • Gaya A
  • Harris W
  • Hidalgo M
  • Hoque MO
  • Izumchenko E
  • Katz A
  • Maki R
  • McGuire W
  • Morris R
  • Pass H
  • Paz K
  • Peled N
  • Ravi R
  • Rodriguez-Galindo C
  • Sidransky D
  • Sloma I
  • Stebbing J
  • Vasquez-Dunddel D
  • Wexler LH
  • Zacharoulis S
PubMed ID
Appears In
Ann Oncol, 2017, 28 (10)