Subgrouping breast cancer patients based on immune evasion mechanisms unravels a high involvement of transforming growth factor-beta and decoy receptor 3.

摘要: In the era of immunotherapy and personalized medicine, there is an urgent need for advancing knowledge immune evasion in different cancer types identifying reliable biomarkers that guide both therapy selection patient inclusion clinical trials. Given differential responses mechanisms breast cancer, we expect to identify groups based on their expression immune-related genes. For that, used sequential biclustering method The Cancer Genome Atlas RNA-seq data identified 7 clusters. We found 77.4% clustered tumor specimens evade through transforming growth factor-beta (TGF-β) immunosuppression, 57.7% decoy receptor 3 (DcR3) counterattack, 48.0% cytotoxic T-lymphocyte-associated protein 4 (CTLA4), 34.3% programmed cell death-1 (PD-1). TGF-β DcR3 are potential novel drug targets immunotherapy. Targeting may provide a powerful approach treating because patients overexpressed these two molecules. Furthermore, triple-negative (TNBC) equally into subgroups: one with impaired antigen presentation another high leukocyte recruitment but four mechanisms. Thus, TNBC be treated approaches. cluster subgroups choice These findings better understanding patients’ response immunotherapies shed light rational design combination therapies.