Cancers (Jan 2024)

Patient-Derived Models of Cancer in the NCI PDMC Consortium: Selection, Pitfalls, and Practical Recommendations

  • Amber N. Habowski,
  • Deepthi P. Budagavi,
  • Sandra D. Scherer,
  • Arin B. Aurora,
  • Giuseppina Caligiuri,
  • William F. Flynn,
  • Ellen M. Langer,
  • Jonathan R. Brody,
  • Rosalie C. Sears,
  • Giorgia Foggetti,
  • Anna Arnal Estape,
  • Don X. Nguyen,
  • Katerina A. Politi,
  • Xiling Shen,
  • David S. Hsu,
  • Donna M. Peehl,
  • John Kurhanewicz,
  • Renuka Sriram,
  • Milagros Suarez,
  • Sophie Xiao,
  • Yuchen Du,
  • Xiao-Nan Li,
  • Nora M. Navone,
  • Estefania Labanca,
  • Christopher D. Willey

DOI
https://doi.org/10.3390/cancers16030565
Journal volume & issue
Vol. 16, no. 3
p. 565

Abstract

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For over a century, early researchers sought to study biological organisms in a laboratory setting, leading to the generation of both in vitro and in vivo model systems. Patient-derived models of cancer (PDMCs) have more recently come to the forefront of preclinical cancer models and are even finding their way into clinical practice as part of functional precision medicine programs. The PDMC Consortium, supported by the Division of Cancer Biology in the National Cancer Institute of the National Institutes of Health, seeks to understand the biological principles that govern the various PDMC behaviors, particularly in response to perturbagens, such as cancer therapeutics. Based on collective experience from the consortium groups, we provide insight regarding PDMCs established both in vitro and in vivo, with a focus on practical matters related to developing and maintaining key cancer models through a series of vignettes. Although every model has the potential to offer valuable insights, the choice of the right model should be guided by the research question. However, recognizing the inherent constraints in each model is crucial. Our objective here is to delineate the strengths and limitations of each model as established by individual vignettes. Further advances in PDMCs and the development of novel model systems will enable us to better understand human biology and improve the study of human pathology in the lab.

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