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.

Keywords

BlockadeImmunophenotypingGenotypeCancerBiologyMedicineInternal medicineCancer researchOncologyImmunologyGeneticsGeneReceptorFlow cytometry

MeSH Terms

AntigensNeoplasmCD4-Positive T-LymphocytesCD8-Positive T-LymphocytesCTLA-4 AntigenCell Cycle CheckpointsGenomicsGenotypeHumansImmunophenotypingImmunotherapyMachine LearningMutationNeoplasmsPrognosisProgrammed Cell Death 1 Receptor

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Publication Info

Year
2017
Type
article
Volume
18
Issue
1
Pages
248-262
Citations
5056
Access
Closed

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5056
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Cite This

Pornpimol Charoentong, Francesca Finotello, Mihaela Angelova et al. (2017). Pan-cancer Immunogenomic Analyses Reveal Genotype-Immunophenotype Relationships and Predictors of Response to Checkpoint Blockade. Cell Reports , 18 (1) , 248-262. https://doi.org/10.1016/j.celrep.2016.12.019

Identifiers

DOI
10.1016/j.celrep.2016.12.019
PMID
28052254

Data Quality

Data completeness: 90%