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Recurrent somatic mutations as predictors of immunotherapy response

Author

Listed:
  • Zoran Z. Gajic

    (New York Genome Center
    New York University
    New York University School of Medicine)

  • Aditya Deshpande

    (New York Genome Center
    Tri-institutional Ph.D. Program in Computational Biology and Medicine
    Englander Institute for Precision Medicine, Institute for Computational Biomedicine, and Meyer Cancer Center, Weill Cornell Medicine)

  • Mateusz Legut

    (New York Genome Center
    New York University
    New York University School of Medicine)

  • Marcin Imieliński

    (New York Genome Center
    Englander Institute for Precision Medicine, Institute for Computational Biomedicine, and Meyer Cancer Center, Weill Cornell Medicine)

  • Neville E. Sanjana

    (New York Genome Center
    New York University
    New York University School of Medicine)

Abstract

Immune checkpoint blockade (ICB) has transformed the treatment of metastatic cancer but is hindered by variable response rates. A key unmet need is the identification of biomarkers that predict treatment response. To address this, we analyzed six whole exome sequencing cohorts with matched disease outcomes to identify genes and pathways predictive of ICB response. To increase detection power, we focus on genes and pathways that are significantly mutated following correction for epigenetic, replication timing, and sequence-based covariates. Using this technique, we identify several genes (BCLAF1, KRAS, BRAF, and TP53) and pathways (MAPK signaling, p53 associated, and immunomodulatory) as predictors of ICB response and develop the Cancer Immunotherapy Response CLassifiEr (CIRCLE). Compared to tumor mutational burden alone, CIRCLE led to superior prediction of ICB response with a 10.5% increase in sensitivity and a 11% increase in specificity. We envision that CIRCLE and more broadly the analysis of recurrently mutated cancer genes will pave the way for better prognostic tools for cancer immunotherapy.

Suggested Citation

  • Zoran Z. Gajic & Aditya Deshpande & Mateusz Legut & Marcin Imieliński & Neville E. Sanjana, 2022. "Recurrent somatic mutations as predictors of immunotherapy response," Nature Communications, Nature, vol. 13(1), pages 1-11, December.
    • Handle: RePEc:nat:natcom:v:13:y:2022:i:1:d:10.1038_s41467-022-31055-3
    DOI: 10.1038/s41467-022-31055-3
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    References listed on IDEAS

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    1. Shashank J. Patel & Neville E. Sanjana & Rigel J. Kishton & Arash Eidizadeh & Suman K. Vodnala & Maggie Cam & Jared J. Gartner & Li Jia & Seth M. Steinberg & Tori N. Yamamoto & Anand S. Merchant & Gau, 2017. "Identification of essential genes for cancer immunotherapy," Nature, Nature, vol. 548(7669), pages 537-542, August.
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