Patient-derived Xenograft models: An emerging platform for translational cancer research

Manuel Hidalgo, Frederic Amant, Andrew V. Biankin, Eva Budinská, Annette T. Byrne, Carlos Caldas, Robert B. Clarke, Steven de Jong, Jos Jonkers, Gunhild Mari Mælandsmo, Sergio Roman-Roman, Joan Seoane, Livio Trusolino, Alberto Villanueva

Research output: Contribution to journalArticlepeer-review


Recently, there has been an increasing interest in the development and characterization of patient-derived tumor xenograft (PDX) models for cancer research. PDX models mostly retain the principal histologic and genetic characteristics of their donor tumor and remain stable across passages. These models have been shown to be predictive of clinical outcomes and are being used for preclinical drug evaluation, biomarker identification, biologic studies, and personalized medicine strategies. This article summarizes the current state of the art in this field, including methodologic issues, available collections, practical applications, challenges and shortcomings, and future directions, and introduces a European consortium of PDX models. Significance: PDX models are increasingly used in translational cancer research. These models are useful for drug screening, biomarker development, and the preclinical evaluation of personalized medicine strategies. This review provides a timely overview of the key characteristics of PDX models and a detailed discussion of future directions in the field.

Original languageEnglish
Pages (from-to)998-1013
Number of pages16
JournalCancer Discovery
Issue number9
Publication statusPublished - 2014

ASJC Scopus subject areas

  • Oncology


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