Melanoma models for the next generation of therapies. Review uri icon

Overview

abstract

  • There is a lack of appropriate melanoma models that can be used to evaluate the efficacy of novel therapeutic modalities. Here, we discuss the current state of the art of melanoma models including genetically engineered mouse, patient-derived xenograft, zebrafish, and ex vivo and in vitro models. We also identify five major challenges that can be addressed using such models, including metastasis and tumor dormancy, drug resistance, the melanoma immune response, and the impact of aging and environmental exposures on melanoma progression and drug resistance. Additionally, we discuss the opportunity for building models for rare subtypes of melanomas, which represent an unmet critical need. Finally, we identify key recommendations for melanoma models that may improve accuracy of preclinical testing and predict efficacy in clinical trials, to help usher in the next generation of melanoma therapies.

authors

  • Patton, E Elizabeth
  • Mueller, Kristen L
  • Adams, David J
  • Anandasabapathy, Niroshana
  • Aplin, Andrew E
  • Bertolotto, Corine
  • Bosenberg, Marcus
  • Ceol, Craig J
  • Burd, Christin E
  • Chi, Ping
  • Herlyn, Meenhard
  • Holmen, Sheri L
  • Karreth, Florian A
  • Kaufman, Charles K
  • Khan, Shaheen
  • Kobold, Sebastian
  • Leucci, Eleonora
  • Levy, Carmit
  • Lombard, David B
  • Lund, Amanda W
  • Marie, Kerrie L
  • Marine, Jean-Christophe
  • Marais, Richard
  • McMahon, Martin
  • Robles-Espinoza, Carla Daniela
  • Ronai, Ze'ev A
  • Samuels, Yardena
  • Soengas, Maria S
  • Villanueva, Jessie
  • Weeraratna, Ashani T
  • White, Richard M
  • Yeh, Iwei
  • Zhu, Jiyue
  • Zon, Leonard I
  • Hurlbert, Marc S
  • Merlino, Glenn

publication date

  • February 4, 2021

Research

keywords

  • Disease Models, Animal
  • Melanoma
  • Skin Neoplasms
  • Tumor Microenvironment

Identity

PubMed Central ID

  • PMC8378471

Scopus Document Identifier

  • 85100410854

Digital Object Identifier (DOI)

  • 10.1016/j.ccell.2021.01.011

PubMed ID

  • 33545064

Additional Document Info

volume

  • 39

issue

  • 5