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The Tumor Microenvironment02:17

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Every normal cell or tissue is embedded in a complex local environment called stroma, consisting of different cell types, a basal membrane, and blood vessels. As normal cells mutate and develop into cancer cells, their local environment also changes to allow cancer progression. The tumor microenvironment (TME) consists of a complex cellular matrix of stromal cells and the developing tumor. The cross-talk between cancer cells and surrounding stromal cells is critical to disrupt normal tissue...
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Visualization, Quantification, and Mapping of Immune Cell Populations in the Tumor Microenvironment
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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.

Nucleic Acids Research
|November 12, 2020
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Summary
This summary is machine-generated.

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.

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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.