Literature DB >> 32505900

Comprehensive analysis of CTLA-4 in the tumor immune microenvironment of 33 cancer types.

Chufan Zhang1, Jianing Chen2, Qian Song3, Xiaoyan Sun4, Meijuan Xue5, Zuyi Yang6, Jun Shang7.   

Abstract

Immunotherapy has recently become a powerful weapon against cancer. Cytotoxic T lymphocyte-associated antigen-4 (CTLA-4) was the first immune checkpoint used for immunotherapy. However, CTLA-4-related mechanisms in various cancers have not been comprehensively investigated. This aim of this study was an in-depth investigation of CTLA-4 in the tumor microenvironment and its relationship with other immunomodulators, immune-related pathways and survival outcomes of 33 cancer types. Overall 9,743 tumor samples and 710 normal samples of 33 cancer types from The Cancer Genome Atlas (TCGA) database were included. CTLA-4 expression level was compared between tumor and normal tissues in 22 cancer types. The microenvironment cell populations (MCP)-counter method was used to analyze the correlation between CTLA-4 and immune cell infiltration. Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) analyses were employed to investigate its relationship with immune pathways. Survival analysis was conducted using the Kaplan-Meier method with log-rank test. CTLA-4 expression was found to be increased in some types of cancer and decreased in other cancer types (P < 0.05). When comparing between different tumor tissues, CTLA-4 was lowest in uveal melanoma (UVM). MCP analysis demonstrated that CTLA-4 had a strong correlation with T cells in almost all cancer types and that CTLA-4 showed a positive correlation with most immune cells in UVM. Immune pathway analysis found that CTLA-4 is involved in a variety of immune pathways. Survival analysis revealed that CTLA-4 can predict patients' survival outcomes. This comprehensive analysis of CTLA-4 will promote anti-CTLA-4 therapy and personalized combined immunotherapy.
Copyright © 2020 Elsevier B.V. All rights reserved.

Entities:  

Keywords:  CTLA-4; Cancer; Immunomodulator; Immunotherapy; Tumor microenvironment

Mesh:

Substances:

Year:  2020        PMID: 32505900     DOI: 10.1016/j.intimp.2020.106633

Source DB:  PubMed          Journal:  Int Immunopharmacol        ISSN: 1567-5769            Impact factor:   4.932


  5 in total

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Journal:  Front Genet       Date:  2021-11-11       Impact factor: 4.599

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Review 5.  The Application of Artificial Intelligence in the Analysis of Biomarkers for Diagnosis and Management of Uveitis and Uveal Melanoma: A Systematic Review.

Authors:  Arshpreet Bassi; Saffire H Krance; Aidan Pucchio; Daiana R Pur; Rafael N Miranda; Tina Felfeli
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  5 in total

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