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Updated: Nov 30, 2025
Visualization, Quantification, and Mapping of Immune Cell Populations in the Tumor Microenvironment
Published on: March 25, 2020
TISCH: a comprehensive web resource enabling interactive single-cell transcriptome visualization of tumor
Dongqing Sun1, Jin Wang1, Ya Han1
1Shanghai Putuo District People's Hospital, School of Life Science and Technology, Tongji University, Shanghai 200060, China.
Abstract:
Cancer immunotherapy targeting co-inhibitory pathways by checkpoint blockade shows remarkable efficacy in a variety of cancer types. However, only a minority of patients respond to treatment due to the stochastic heterogeneity of tumor microenvironment (TME). Recent advances in single-cell RNA-seq technologies enabled comprehensive characterization of the immune system heterogeneity in tumors but posed computational challenges on integrating and utilizing the massive published datasets to inform immunotherapy. Here, we present Tumor Immune Single Cell Hub (TISCH, http://tisch.comp-genomics.org), a large-scale curated database that integrates single-cell transcriptomic profiles of nearly 2 million cells from 76 high-quality tumor datasets across 27 cancer types. All the data were uniformly processed with a standardized workflow, including quality control, batch effect removal, clustering, cell-type annotation, malignant cell classification, differential expression analysis and functional enrichment analysis. TISCH provides interactive gene expression visualization across multiple datasets at the single-cell level or cluster level, allowing systematic comparison between different cell-types, patients, tissue origins, treatment and response groups, and even different cancer-types. In summary, TISCH provides a user-friendly interface for systematically visualizing, searching and downloading gene expression atlas in the TME from multiple cancer types, enabling fast, flexible and comprehensive exploration of the TME.
Insights
The Tumor Immune Single Cell Hub (TISCH) database integrates single-cell data from nearly 2 million cells across 27 cancer types. This resource aids researchers in exploring tumor microenvironment heterogeneity to improve cancer immunotherapy strategies.
Area of Science:
- Immunology
- Bioinformatics
- Genomics
Background:
- Cancer immunotherapy, particularly checkpoint blockade, shows promise but limited patient response due to tumor microenvironment (TME) heterogeneity.
- Single-cell RNA sequencing (scRNA-seq) offers deep insights into immune cell diversity within tumors, yet integrating large datasets presents computational hurdles.
Purpose of the Study:
- To develop and present the Tumor Immune Single Cell Hub (TISCH), a comprehensive database for exploring TME immune cell transcriptomics.
- To facilitate the integration and analysis of massive scRNA-seq datasets to inform cancer immunotherapy development.
Main Methods:
- Integrated single-cell transcriptomic profiles from 76 high-quality tumor datasets, comprising nearly 2 million cells across 27 cancer types.
- Applied a standardized bioinformatics workflow for uniform data processing, including quality control, batch effect removal, cell clustering, and annotation.
- Performed malignant cell classification, differential gene expression analysis, and functional enrichment analysis.
Main Results:
- The TISCH database provides a user-friendly platform for interactive gene expression visualization at single-cell and cluster levels.
- Enables systematic comparisons across different cell types, patients, cancer types, and treatment/response groups.
- Offers downloadable gene expression atlases for flexible and comprehensive TME exploration.
Conclusions:
- TISCH serves as a valuable resource for systematically visualizing, searching, and downloading TME gene expression data.
- The database empowers researchers to conduct fast and flexible exploration of tumor immune cell heterogeneity.
- Facilitates deeper understanding of TME dynamics to advance the efficacy of cancer immunotherapy.
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