Comprehensive Pan-Cancer Analyses of Pyroptosis-Related Genes to Predict Survival and Immunotherapeutic Outcome

Simple Summary Pyroptosis is a type of programmed cell death accompanied by inflammation. Although the dysregulation of pyroptosis has been reported to be involved in carcinogenesis, its function in cancer progression and therapy remains largely unknown and controversial because of the inconsistency across different cancer types. This study provides the most complete gene set of pyroptosis-related genes (PRGs), depicts their expression changes across 31 cancer types for the first time, and constructs a novel prognostic risk model to predict cancer patient survival. In addition, the effects of pyroptosis on immune cell infiltration and immunotherapy were dissected at the pan-cancer level. Small-molecule compounds, which may be beneficial to immunotherapy, were screened on the basis of differentially expressed PRGs. These results lay the foundation for the study of pyroptosis in cancer. Abstract Pyroptosis is a newly characterized type of programmed cell death. However, its function in cancer progression and its response to treatments remain controversial. Here, we extensively and systematically compiled genes associated with pyroptosis, integrated multiomics data and clinical data across 31 cancer types from The Cancer Genome Atlas, and delineated the global alterations in PRGs at the transcriptional level. The underlying transcriptional regulations by copy number variation, miRNAs, and enhancers were elucidated by integrating data from the Genotype-Tissue Expression and International Cancer Genome Consortium. A prognostic risk model, based on the expression of PRGs across 31 cancer types, was constructed. To investigate the role of pyroptosis in immunotherapy, we found five PRGs associated with effectiveness by exploring the RNA-Seq data of patients with immunotherapy, and further identified two small-molecule compounds that are potentially beneficial for immunotherapy. For the first time, from a pyroptosis standpoint, this study establishes a novel strategy to predict cancer patient survival and immunotherapeutic outcomes.