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Identification of a two-gene prognostic model associated with cytolytic activity for colon cancer
BACKGROUND: Increasing evidence has shown that cytolytic activity (CYT) is a new immunotherapy biomarker that characterises the antitumour immune activity of cytotoxic T cells and macrophages. In this study, we established a prognostic model associated with CYT. METHODS: A prognostic model based on...
Autores principales: | , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
BioMed Central
2021
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7869500/ https://www.ncbi.nlm.nih.gov/pubmed/33557848 http://dx.doi.org/10.1186/s12935-021-01782-6 |
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author | Jiang, Xiaoye Jiang, Zhongxiang Xiang, Lichun Chen, Xuenuo Wu, Jiao Jiang, Zheng |
author_facet | Jiang, Xiaoye Jiang, Zhongxiang Xiang, Lichun Chen, Xuenuo Wu, Jiao Jiang, Zheng |
author_sort | Jiang, Xiaoye |
collection | PubMed |
description | BACKGROUND: Increasing evidence has shown that cytolytic activity (CYT) is a new immunotherapy biomarker that characterises the antitumour immune activity of cytotoxic T cells and macrophages. In this study, we established a prognostic model associated with CYT. METHODS: A prognostic model based on CYT-related genes was developed. Furthermore, aberrant expression of genes of the model in colon cancer (CC) was identified by reverse transcription-quantitative polymerase chain reaction (RT-qPCR) and immunohistochemistry (IHC) assays. Next, the correlation between the model and T-cell infiltration in the CC microenvironment was analysed. The Tumour Immune Dysfunction and Exclusion (TIDE) algorithm and subclass mapping were used to predict clinical responses to immune checkpoint inhibitors. RESULTS: In total, 280 of the 1418 genes were differentially expressed based on CYT. A prognostic model (including HOXC8 and MS4A2) was developed based on CYT-related genes. The model was validated using the testing set, the whole set and a Gene Expression Omnibus (GEO) cohort (GSE41258). Gene set enrichment analysis (GSEA) and other analyses showed that the levels of immune infiltration and antitumour immune activation in low-risk-score tumours were greater than those in high-risk-score tumours. CC patients with a low-risk-score showed more promise in the response to anti-immune checkpoint therapy. CONCLUSIONS: Overall, our model may precisely predict the overall survival of CC and reflect the strength of antitumour immune activity in the CC microenvironment. Furthermore, the model may be a predictive factor for the response to immunotherapy. |
format | Online Article Text |
id | pubmed-7869500 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2021 |
publisher | BioMed Central |
record_format | MEDLINE/PubMed |
spelling | pubmed-78695002021-02-08 Identification of a two-gene prognostic model associated with cytolytic activity for colon cancer Jiang, Xiaoye Jiang, Zhongxiang Xiang, Lichun Chen, Xuenuo Wu, Jiao Jiang, Zheng Cancer Cell Int Primary Research BACKGROUND: Increasing evidence has shown that cytolytic activity (CYT) is a new immunotherapy biomarker that characterises the antitumour immune activity of cytotoxic T cells and macrophages. In this study, we established a prognostic model associated with CYT. METHODS: A prognostic model based on CYT-related genes was developed. Furthermore, aberrant expression of genes of the model in colon cancer (CC) was identified by reverse transcription-quantitative polymerase chain reaction (RT-qPCR) and immunohistochemistry (IHC) assays. Next, the correlation between the model and T-cell infiltration in the CC microenvironment was analysed. The Tumour Immune Dysfunction and Exclusion (TIDE) algorithm and subclass mapping were used to predict clinical responses to immune checkpoint inhibitors. RESULTS: In total, 280 of the 1418 genes were differentially expressed based on CYT. A prognostic model (including HOXC8 and MS4A2) was developed based on CYT-related genes. The model was validated using the testing set, the whole set and a Gene Expression Omnibus (GEO) cohort (GSE41258). Gene set enrichment analysis (GSEA) and other analyses showed that the levels of immune infiltration and antitumour immune activation in low-risk-score tumours were greater than those in high-risk-score tumours. CC patients with a low-risk-score showed more promise in the response to anti-immune checkpoint therapy. CONCLUSIONS: Overall, our model may precisely predict the overall survival of CC and reflect the strength of antitumour immune activity in the CC microenvironment. Furthermore, the model may be a predictive factor for the response to immunotherapy. BioMed Central 2021-02-08 /pmc/articles/PMC7869500/ /pubmed/33557848 http://dx.doi.org/10.1186/s12935-021-01782-6 Text en © The Author(s) 2021 Open AccessThis article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated in a credit line to the data. |
spellingShingle | Primary Research Jiang, Xiaoye Jiang, Zhongxiang Xiang, Lichun Chen, Xuenuo Wu, Jiao Jiang, Zheng Identification of a two-gene prognostic model associated with cytolytic activity for colon cancer |
title | Identification of a two-gene prognostic model associated with cytolytic activity for colon cancer |
title_full | Identification of a two-gene prognostic model associated with cytolytic activity for colon cancer |
title_fullStr | Identification of a two-gene prognostic model associated with cytolytic activity for colon cancer |
title_full_unstemmed | Identification of a two-gene prognostic model associated with cytolytic activity for colon cancer |
title_short | Identification of a two-gene prognostic model associated with cytolytic activity for colon cancer |
title_sort | identification of a two-gene prognostic model associated with cytolytic activity for colon cancer |
topic | Primary Research |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7869500/ https://www.ncbi.nlm.nih.gov/pubmed/33557848 http://dx.doi.org/10.1186/s12935-021-01782-6 |
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