Back to Search
Start Over
Multimodel preclinical platform predicts clinical response of melanoma to immunotherapy.
- Source :
-
Nature medicine [Nat Med] 2020 May; Vol. 26 (5), pp. 781-791. Date of Electronic Publication: 2020 Apr 13. - Publication Year :
- 2020
-
Abstract
- Although immunotherapy has revolutionized cancer treatment, only a subset of patients demonstrate durable clinical benefit. Definitive predictive biomarkers and targets to overcome resistance remain unidentified, underscoring the urgency to develop reliable immunocompetent models for mechanistic assessment. Here we characterize a panel of syngeneic mouse models, representing a variety of molecular and phenotypic subtypes of human melanomas and exhibiting their diverse range of responses to immune checkpoint blockade (ICB). Comparative analysis of genomic, transcriptomic and tumor-infiltrating immune cell profiles demonstrated alignment with clinical observations and validated the correlation of T cell dysfunction and exclusion programs with resistance. Notably, genome-wide expression analysis uncovered a melanocytic plasticity signature predictive of patient outcome in response to ICB, suggesting that the multipotency and differentiation status of melanoma can determine ICB benefit. Our comparative preclinical platform recapitulates melanoma clinical behavior and can be employed to identify mechanisms and treatment strategies to improve patient care.
- Subjects :
- Animals
Antineoplastic Agents, Immunological therapeutic use
CTLA-4 Antigen immunology
Cells, Cultured
Disease Models, Animal
Female
Gene Expression Regulation, Neoplastic drug effects
Genetic Heterogeneity
Humans
Ipilimumab therapeutic use
Melanoma diagnosis
Melanoma genetics
Mice
Mice, Inbred C57BL
Mice, Transgenic
Prognosis
Programmed Cell Death 1 Receptor immunology
RNA-Seq
Treatment Outcome
Whole Genome Sequencing
Drug Screening Assays, Antitumor methods
Immunotherapy adverse effects
Immunotherapy methods
Melanoma pathology
Melanoma therapy
Subjects
Details
- Language :
- English
- ISSN :
- 1546-170X
- Volume :
- 26
- Issue :
- 5
- Database :
- MEDLINE
- Journal :
- Nature medicine
- Publication Type :
- Academic Journal
- Accession number :
- 32284588
- Full Text :
- https://doi.org/10.1038/s41591-020-0818-3