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Article

Improved prediction of immune checkpoint blockade efficacy across multiple cancer types.

Nature biotechnology - 1 Apr 2022

Chowell Diego, Yoo Seong-Keun, Valero Cristina, Pastore Alessandro, Krishna Chirag, Lee Mark, Hoen Douglas, Shi Hongyu, Kelly Daniel W, Patel Neal, Makarov Vladimir, Ma Xiaoxiao, Vuong Lynda, Sabio Erich Y, Weiss Kate, Kuo Fengshen, Lenz Tobias L, Samstein Robert M, Riaz Nadeem, Adusumilli Prasad S, Balachandran Vinod P, Plitas George, Ari Hakimi A, Abdel-Wahab Omar, Shoushtari Alexander N, Postow Michael A, Motzer Robert J, Ladanyi Marc, Zehir Ahmet, Berger Michael F, Gönen Mithat, Morris Luc G T, Weinhold Nils, Chan Timothy A

Abstract excerpt

Only a fraction of patients with cancer respond to immune checkpoint blockade (ICB) treatment, but current decision-making procedures have limited accuracy. In this study, we developed a machine learning model to predict ICB response by integrating genomic, molecular, demographic and clinical data from a comprehensively curated cohort (MSK-IMPACT) with 1,479 patients treated with ICB across 16 different cancer...

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Identifiers

PMID: 34725502
DOI: 10.1038/s41587-021-01070-8
PMCID: PMC9363980

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