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

TLDR

The Cancer Genome Atlas mapped the genomic landscapes of human cancers, while immunotherapy is transforming advanced cancer treatment, yet most patients fail to respond, underscoring the need for predictive markers and understanding resistance mechanisms. The study aimed to elucidate tumor‑immune interactions by profiling intratumoral immune landscapes and cancer antigenomes across 20 solid cancers and establishing The Cancer Immunome Atlas. Using machine learning, the authors identified determinants of tumor immunogenicity and developed the immunophenoscore to quantify it. The analysis revealed that tumor genotypes dictate immunophenotypes and escape mechanisms, and the immunophenoscore accurately predicted response to anti‑CTLA‑4 and anti‑PD‑1 therapies in two validation cohorts, offering a resource to guide precision immuno‑oncology.

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.