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Pan-cancer Immunogenomic Analyses Reveal Genotype-Immunophenotype Relationships and Predictors of Response to Checkpoint Blockade

Cell Reports · 2017 · Vol. 18(1) · pp. 248–262
Pornpimol CharoentongFrancesca FinotelloMihaela AngelovaClemens MayerMirjana EfremovaDietmar RiederHubert HacklZlatko Trajanoski

Abstract

The Cancer Genome Atlas revealed the genomic landscapes of human cancers. In parallel, immunotherapy is transforming the treatment of advanced cancers. Unfortunately, the majority of patients do not respond to immunotherapy, making the identification of predictive markers and the mechanisms of resistance an area of intense research. To increase our understanding of tumor-immune cell interactions, we characterized the intratumoral immune landscapes and the cancer antigenomes from 20 solid cancers and created The Cancer Immunome Atlas (https://tcia.at/). Cellular characterization of the immune infiltrates showed that tumor genotypes determine immunophenotypes and tumor escape mechanisms. Using machine learning, we identified determinants of tumor immunogenicity and developed a scoring scheme for the quantification termed immunophenoscore. The immunophenoscore was a superior predictor of response to anti-cytotoxic T lymphocyte antigen-4 (CTLA-4) and anti-programmed cell death protein 1 (anti-PD-1) antibodies in two independent validation cohorts. Our findings and this resource may help inform cancer immunotherapy and facilitate the development of precision immuno-oncology.

Cancer Genomics and DiagnosticsCancer Immunotherapy and BiomarkersLung Cancer Treatments and MutationsBlockadeImmunophenotypingGenotypeCancerBiologyMedicineInternal medicineCancer researchOncologyImmunology

MeSH terms

Machine LearningAntigens, NeoplasmGenotypeHumansImmunotherapyMutationNeoplasmsPrognosisCD4-Positive T-LymphocytesImmunophenotypingCD8-Positive T-LymphocytesGenomicsCell Cycle CheckpointsCTLA-4 AntigenProgrammed Cell Death 1 Receptor

Funding

  • Austrian Science Fund
  • Oesterreichische Nationalbank
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