Integrative molecular and clinical modeling of clinical outcomes to PD1 blockade in patients with metastatic melanoma.
Authors | |
Abstract | Immune-checkpoint blockade (ICB) has demonstrated efficacy in many tumor types, but predictors of responsiveness to anti-PD1 ICB are incompletely characterized. In this study, we analyzed a clinically annotated cohort of patients with melanoma (n = 144) treated with anti-PD1 ICB, with whole-exome and whole-transcriptome sequencing of pre-treatment tumors. We found that tumor mutational burden as a predictor of response was confounded by melanoma subtype, whereas multiple novel genomic and transcriptomic features predicted selective response, including features associated with MHC-I and MHC-II antigen presentation. Furthermore, previous anti-CTLA4 ICB exposure was associated with different predictors of response compared to tumors that were naive to ICB, suggesting selective immune effects of previous exposure to anti-CTLA4 ICB. Finally, we developed parsimonious models integrating clinical, genomic and transcriptomic features to predict intrinsic resistance to anti-PD1 ICB in individual tumors, with validation in smaller independent cohorts limited by the availability of comprehensive data. Broadly, we present a framework to discover predictive features and build models of ICB therapeutic response. |
Year of Publication | 2019
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Journal | Nat Med
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Volume | 25
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Issue | 12
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Pages | 1916-1927
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Date Published | 2019 Dec
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ISSN | 1546-170X
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DOI | 10.1038/s41591-019-0654-5
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PubMed ID | 31792460
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Links | |
Grant list | R01 CA227388 / CA / NCI NIH HHS / United States
U01 CA233100 / CA / NCI NIH HHS / United States
SCHA 422/17-1; PA 2376/1-1; HO 6389/2-1 (KFO 337) / Deutsche Forschungsgemeinschaft (German Research Foundation)
T32 GM008313 / GM / NIGMS NIH HHS / United States
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