Abstract 700: CellSig: A data-driven model of cytokine activity identifies therapeutic targets for severe COVID-19 and cancer immunotherapy-induced colitis

Studies of cytokine activity are foundational to immunology research. However, the complexity and redundancy of cytokine functions have prevented systematic profiling of signaling activities in biological samples. To address these issues, we developed Cell Signaling Analyzer (CellSig, https://cellsig.ccr.cancer.gov), a data-driven infrastructure to model how cytokines cooperate with and antagonize each other in inflammation processes. We manually curated 20,591 transcriptomic profiles related to human cytokine, chemokine, and growth-factor response. CellSig revealed two main cytokine groups typified by NFKB and interferon-associated signals, respectively. The primary pro-inflammatory members of each group induce a distinct set of secondary signals and are repressed by different anti-inflammatory cytokines. CellSig can reliably predict target activities of 43 cytokines using the transcriptomic data from severe COVID-19 cases, cancer immunotherapy-induced colitis, and immune checkpoint blockade response. Among these clinical applications, the differential activities of the NFKB and interferon cytokine groups revealed potential therapeutic targets for alleviating adverse inflammation without compromising viral clearance or cancer treatment. Citation Format: Peng Jiang, Yu Zhang, Beibei Ru, Eytan Ruppin, Kai Wucherpfennig. CellSig: A data-driven model of cytokine activity identifies therapeutic targets for severe COVID-19 and cancer immunotherapy-induced colitis [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2021; 2021 Apr 10-15 and May 17-21. Philadelphia (PA): AACR; Cancer Res 2021;81(13_Suppl):Abstract nr 700.