학술논문
Integrative molecular and clinical modeling of clinical outcomes to PD1 blockade in patients with metastatic melanoma
Document Type
Article
Author
Liu, David; Schilling, Bastian; Liu, Derek; Sucker, Antje; Livingstone, Elisabeth; Jerby-Arnon, Livnat; Zimmer, Lisa; Gutzmer, Ralf; Satzger, Imke; Loquai, Carmen; Grabbe, Stephan; Vokes, Natalie; Margolis, Claire A.; Conway, Jake; He, Meng Xiao; Elmarakeby, Haitham; Dietlein, Felix; Miao, Diana; Tracy, Adam; Gogas, Helen; Goldinger, Simone M.; Utikal, Jochen; Blank, Christian U.; Rauschenberg, Ricarda; von Bubnoff, Dagmar; Krackhardt, Angela; Weide, Benjamin; Haferkamp, Sebastian; Kiecker, Felix; Izar, Ben; Garraway, Levi; Regev, Aviv; Flaherty, Keith; Paschen, Annette; Van Allen, Eliezer M.; Schadendorf, Dirk
Source
Nature Medicine; December 2019, Vol. 25 Issue: 12 p1916-1927, 12p
Subject
Language
ISSN
10788956; 1546170X
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.