Large parallel genetic screens have been used to identify targets and regulators that enhance T-cell antitumor capability and persistence in the tumor microenvironment. We hypothesized that by combining the pooled screen data from multiple independent genetic screens, we could provide a systematic, comprehensive, and robust analysis of the effect of gene perturbation on T cell-based immunotherapies. After collecting data from previously published T-cell screens, including CRISPR-based and open reading frame-based screens, through the Gene Expression Omnibus, we reprocessed the gene hits summary and conducted a pathway enrichment analysis. A T-cell screen perturbation score metric was employed to quantify the impact of a gene perturbation on T-cell function. Additionally, gene expression data (both bulk RNA level and single-cell RNA level) from autoimmune disease cohorts and patients with T cell-derived cancer were incorporated to gain further insight into gene perturbations that potentially augment T-cell proliferation. We integrated all data and analysis on 35 T-cell screens into our state-of-the-art T-cell perturbation genomics database (TCPGdb), which is accessible through our web server (http://tcpgdb.sidichenlab.org/) and allows users to interactively explore the impact of query genes on T-cell function.
©2025 American Association for Cancer Research.