TCPGdb: A Comprehensive T-cell Perturbation Genomics Database for the Identification of Critical T-cell Regulators

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.

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Publication Details

Journal
Cancer Immunology Research
Published
2025-11-21
DOI
https://doi.org/10.1158/2326-6066.cir-25-0168
Primary Topic
Single-cell and spatial transcriptomics
Type
article
Field-Weighted Citation Impact
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article

TCPGdb: A Comprehensive T-cell Perturbation Genomics Database for the Identification of Critical T-cell Regulators

Chuanpeng Dong, Nipun Verma, Feifei Zhang, Hongyu Zhao et al.
Cancer Immunology Research
Single-cell and spatial transcriptomics
article

TCPGdb: A Comprehensive T-cell Perturbation Genomics Database for the Identification of Critical T-cell Regulators

Chuanpeng Dong, Nipun Verma, Feifei Zhang, Hongyu Zhao, Sidi Chen, Di Feng, Xinxin Zhu, J. Cai, Kaiyuan Tang
article en

Abstract

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.

Cancer Immunology ResearchVol. 14(2)
Yale Cancer Center (US), Yale University (US), Boehringer Ingelheim (Brazil) (BR), Yale New Haven Health System (US), Boehringer Ingelheim (Egypt) (EG), Boehringer Ingelheim (France) (FR), Boehringer Ingelheim (United States) (US), Boehringer Ingelheim (Spain) (ES), Texas A&M University (US)
Openalex Percentile: Top 68%
Single-cell and spatial transcriptomics
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