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Immune Determinants of the Association between Tumor Mutational Burden and Immunotherapy Response across Cancer Types.
Sinha, Neelam; Sinha, Sanju; Valero, Cristina; Schäffer, Alejandro A; Aldape, Kenneth; Litchfield, Kevin; Chan, Timothy A; Morris, Luc G T; Ruppin, Eytan.
Afiliación
  • Sinha N; Cancer Data Science Lab, Center for Cancer Research, National Cancer Institute, National Institute of Health, Bethesda, Maryland.
  • Sinha S; Cancer Data Science Lab, Center for Cancer Research, National Cancer Institute, National Institute of Health, Bethesda, Maryland.
  • Valero C; Department of Surgery, Memorial Sloan Kettering Cancer Center, New York, New York.
  • Schäffer AA; Immunogenomics and Precision Oncology Platform, Memorial Sloan Kettering Cancer Center, New York, New York.
  • Aldape K; Cancer Data Science Lab, Center for Cancer Research, National Cancer Institute, National Institute of Health, Bethesda, Maryland.
  • Litchfield K; Laboratory of Pathology, NCI, NIH, Bethesda, Maryland.
  • Chan TA; Cancer Evolution and Genome Instability Laboratory, The Francis Crick Institute, London, United Kingdom.
  • Morris LGT; Center for Immunotherapy and Precision Immuno-Oncology, Cleveland Clinic, Lerner Research Institute, Cleveland Clinic, Cleveland, National Center for Regenerative Medicine, Cleveland Clinic, Cleveland, Ohio.
  • Ruppin E; Department of Surgery, Memorial Sloan Kettering Cancer Center, New York, New York.
Cancer Res ; 82(11): 2076-2083, 2022 06 06.
Article en En | MEDLINE | ID: mdl-35385572
The FDA has recently approved a high tumor mutational burden (TMB-high) biomarker, defined by ≥10 mutations/Mb, for the treatment of solid tumors with pembrolizumab, an immune checkpoint inhibitor (ICI) that targets PD1. However, recent studies have shown that this TMB-high biomarker is only able to stratify ICI responders in a subset of cancer types, and the mechanisms underlying this observation have remained unknown. The tumor immune microenvironment (TME) may modulate the stratification power of TMB (termed TMB power), determining if it will be predictive of ICI response in a given cancer type. To systematically study this hypothesis, we inferred the levels of 31 immune-related factors characteristic of the TME of different cancer types in The Cancer Genome Atlas. Integration of this information with TMB and response data of 2,277 patients treated with anti-PD1 identified key immune factors that determine TMB power across 14 different cancer types. We find that high levels of M1 macrophages and low resting dendritic cells in the TME characterized cancer types with high TMB power. A model based on these two immune factors strongly predicted TMB power in a given cancer type during cross-validation and testing (Spearman Rho = 0.76 and 1, respectively). Using this model, we predicted the TMB power in nine additional cancer types, including rare cancers, for which TMB and ICI response data are not yet publicly available. Our analysis indicates that TMB-high may be highly predictive of ICI response in cervical squamous cell carcinoma, suggesting that such a study should be prioritized. SIGNIFICANCE: This study uncovers immune-related factors that may modulate the relationship between high tumor mutational burden and ICI response, which can help prioritize cancer types for clinical trials.
Asunto(s)

Texto completo: 1 Colección: 01-internacional Base de datos: MEDLINE Asunto principal: Inmunoterapia / Neoplasias Tipo de estudio: Prognostic_studies / Risk_factors_studies Límite: Humans Idioma: En Revista: Cancer Res Año: 2022 Tipo del documento: Article

Texto completo: 1 Colección: 01-internacional Base de datos: MEDLINE Asunto principal: Inmunoterapia / Neoplasias Tipo de estudio: Prognostic_studies / Risk_factors_studies Límite: Humans Idioma: En Revista: Cancer Res Año: 2022 Tipo del documento: Article
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