| Literature DB >> 32984843 |
Valsamo Anagnostou1,2, Noushin Niknafs3, Kristen Marrone3,4, Daniel C Bruhm3, James R White3, Jarushka Naidoo3,4, Karlijn Hummelink5, Kim Monkhorst5, Ferry Lalezari5, Mara Lanis3, Samuel Rosner3, Joshua E Reuss3, Kellie N Smith3,4, Vilmos Adleff3, Kristen Rodgers6, Zineb Belcaid3, Lamia Rhymee3, Benjamin Levy3,4, Josephine Feliciano3,4, Christine L Hann3,4, David S Ettinger3,4, Christos Georgiades7, Franco Verde8, Peter Illei3,9, Qing Kay Li9, Alexander S Baras9, Edward Gabrielson9, Malcolm V Brock6, Rachel Karchin3,10, Drew M Pardoll3,4, Stephen B Baylin3, Julie R Brahmer3,4, Robert B Scharpf3, Patrick M Forde3,4, Victor E Velculescu11,12,13,14.
Abstract
Despite progress in immunotherapy, identifying patients that respond has remained a challenge. Through analysis of whole-exome and targeted sequence data from 5,449 tumors, we found a significant correlation between tumor mutation burden (TMB) and tumor purity, suggesting that low tumor purity tumors are likely to have inaccurate TMB estimates. We developed a new method to estimate a corrected TMB (cTMB) that was adjusted for tumor purity and more accurately predicted outcome to immune checkpoint blockade (ICB). To identify improved predictive markers together with cTMB, we performed whole-exome sequencing for 104 lung tumors treated with ICB. Through comprehensive analyses of sequence and structural alterations, we discovered a significant enrichment in activating mutations in receptor tyrosine kinase (RTK) genes in nonresponding tumors in three immunotherapy treated cohorts. An integrated multivariable model incorporating cTMB, RTK mutations, smoking-related mutational signature and human leukocyte antigen status provided an improved predictor of response to immunotherapy that was independently validated.Entities:
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Year: 2020 PMID： 32984843 PMCID： PMC7514475 DOI： 10.1038/s43018-019-0008-8
Source DB: PubMed Journal: Nat Cancer ISSN： 2662-1347