Conclusions
Our study conducted a systematical investigation on inflammasome signaling in various tumor types. These findings highlight the importance of inflammasome evaluation in tumor classification and provide a foundation for improving relevant therapeutic regimens.
Methods
A total of 9881 patients across 33 tumor types from The Cancer Genome Atlas database were included in this study. Five gene sets were identified to step-wisely profile inflammasome signaling. Unsupervised clustering was used for sample classification based on gene set enrichment. Machine learning and in vitro and in vivo experiments were used to confirm the implications of inflammasome classification.
Results
A hundred and forty-one inflammasome-signaling-related genes were identified to construct five gene sets representing the sensing, activation, and termination steps of the inflammasome signaling. Six inflammasome clusters were robustly established with distinct molecular, biological, clinical, and therapeutic features. Importantly, clusters with inflammasome signaling activation were found to be immunosuppressive and resistant to ICB treatment. Inflammasome inhibition reverted the therapeutic failure of ICB in inflammasome-activated tumors. Moreover, based on the proposed classification and therapeutic implications, an open website was established to provide tumor patients with comprehensive information on inflammasome signaling. Conclusions: Our study conducted a systematical investigation on inflammasome signaling in various tumor types. These findings highlight the importance of inflammasome evaluation in tumor classification and provide a foundation for improving relevant therapeutic regimens.