Multimodal genomic features predict outcome of immune checkpoint blockade in non-small-cell lung cancer

Valsamo Anagnostou, Noushin Niknafs, Kristen Marrone, Daniel C. Bruhm, James R. White, Jarushka Naidoo, Karlijn Hummelink, Kim Monkhorst, Ferry Lalezari, Mara Lanis, Samuel Rosner, Joshua E. Reuss, Kellie N. Smith, Vilmos Adleff, Kristen Rodgers, Zineb Belcaid, Lamia Rhymee, Benjamin Levy, Josephine Feliciano, Christine L. HannDavid S. Ettinger, Christos Georgiades, Franco Verde, Peter Illei, Qing Kay Li, Alexander S. Baras, Edward Gabrielson, Malcolm V. Brock, Rachel Karchin, Drew M. Pardoll, Stephen B. Baylin, Julie R. Brahmer, Robert B. Scharpf, Patrick M. Forde, Victor E. Velculescu

Research output: Contribution to journalArticlepeer-review


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.

Original languageEnglish (US)
Pages (from-to)99-111
Number of pages13
JournalNature Cancer
Issue number1
StatePublished - Jan 1 2020

ASJC Scopus subject areas

  • Oncology
  • Cancer Research


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