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Prognostic Model and Tumor Immune Microenvironment Analysis of Complement-Related Genes in Gastric Cancer
INTRODUCTION: The complement system is integral to the innate and adaptive immune response, helping antibodies eliminate pathogens. However, the potential role of complement and its modulators in the tumor microenvironment (TME) of gastric cancer (GC) remains unclear. METHODS: This study assessed th...
Autores principales: | , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Dove
2023
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Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10590588/ https://www.ncbi.nlm.nih.gov/pubmed/37872955 http://dx.doi.org/10.2147/JIR.S422903 |
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author | Gu, Xianhua Shen, Honghong Zhu, Guangzheng Li, Xinwei Zhang, Yue Zhang, Rong Su, Fang Wang, Zishu |
author_facet | Gu, Xianhua Shen, Honghong Zhu, Guangzheng Li, Xinwei Zhang, Yue Zhang, Rong Su, Fang Wang, Zishu |
author_sort | Gu, Xianhua |
collection | PubMed |
description | INTRODUCTION: The complement system is integral to the innate and adaptive immune response, helping antibodies eliminate pathogens. However, the potential role of complement and its modulators in the tumor microenvironment (TME) of gastric cancer (GC) remains unclear. METHODS: This study assessed the expression, frequency of somatic mutations, and copy number variations of complement family genes in GC derived from The Cancer Genome Atlas (TCGA). Lasso and Cox regression analyses were conducted to develop a prognostic model based on the complement genes family, with the training and validation sets taken from the TCGA-GC cohort (n=371) and the International Gene Expression Omnibus (GEO) cohort (n=433), correspondingly. The nomogram assessment model was used to predict patient outcomes. Additionally, the link between immune checkpoints, immune cells, and the prognostic model was investigated. RESULTS: In contrast to patients at low risk, those at high risk had a less favorable outcome. The prognostic model-derived risk score was shown to serve as a prognostic marker of GC independently, as per the multivariate Cox analysis. Nomogram assessment showed that the model had high reliability for predicting the survival of patients with GC in the 1, 3, 5 years. Additionally, the risk score was positively linked to the expression of immune checkpoints, notably CTLA4, LAG3, PDCD1, and CD274, according to an analysis of immune processes. The core gene C5aR1 in the prognostic model was found to be upregulated in GC tissues in contrast to adjoining normal tissues, and patients with elevated expressed levels of C5aR1 had lower 10-year overall survival (OS) rates. CONCLUSION: Our work reveals that complement genes are associated with the diversity and complexity of TME. The complement prognosis model help improves our understanding of TME infiltration characteristics and makes immunotherapeutic strategies more effective. |
format | Online Article Text |
id | pubmed-10590588 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2023 |
publisher | Dove |
record_format | MEDLINE/PubMed |
spelling | pubmed-105905882023-10-23 Prognostic Model and Tumor Immune Microenvironment Analysis of Complement-Related Genes in Gastric Cancer Gu, Xianhua Shen, Honghong Zhu, Guangzheng Li, Xinwei Zhang, Yue Zhang, Rong Su, Fang Wang, Zishu J Inflamm Res Original Research INTRODUCTION: The complement system is integral to the innate and adaptive immune response, helping antibodies eliminate pathogens. However, the potential role of complement and its modulators in the tumor microenvironment (TME) of gastric cancer (GC) remains unclear. METHODS: This study assessed the expression, frequency of somatic mutations, and copy number variations of complement family genes in GC derived from The Cancer Genome Atlas (TCGA). Lasso and Cox regression analyses were conducted to develop a prognostic model based on the complement genes family, with the training and validation sets taken from the TCGA-GC cohort (n=371) and the International Gene Expression Omnibus (GEO) cohort (n=433), correspondingly. The nomogram assessment model was used to predict patient outcomes. Additionally, the link between immune checkpoints, immune cells, and the prognostic model was investigated. RESULTS: In contrast to patients at low risk, those at high risk had a less favorable outcome. The prognostic model-derived risk score was shown to serve as a prognostic marker of GC independently, as per the multivariate Cox analysis. Nomogram assessment showed that the model had high reliability for predicting the survival of patients with GC in the 1, 3, 5 years. Additionally, the risk score was positively linked to the expression of immune checkpoints, notably CTLA4, LAG3, PDCD1, and CD274, according to an analysis of immune processes. The core gene C5aR1 in the prognostic model was found to be upregulated in GC tissues in contrast to adjoining normal tissues, and patients with elevated expressed levels of C5aR1 had lower 10-year overall survival (OS) rates. CONCLUSION: Our work reveals that complement genes are associated with the diversity and complexity of TME. The complement prognosis model help improves our understanding of TME infiltration characteristics and makes immunotherapeutic strategies more effective. Dove 2023-10-18 /pmc/articles/PMC10590588/ /pubmed/37872955 http://dx.doi.org/10.2147/JIR.S422903 Text en © 2023 Gu et al. https://creativecommons.org/licenses/by-nc/3.0/This work is published and licensed by Dove Medical Press Limited. The full terms of this license are available at https://www.dovepress.com/terms.php and incorporate the Creative Commons Attribution – Non Commercial (unported, v3.0) License (http://creativecommons.org/licenses/by-nc/3.0/ (https://creativecommons.org/licenses/by-nc/3.0/) ). By accessing the work you hereby accept the Terms. Non-commercial uses of the work are permitted without any further permission from Dove Medical Press Limited, provided the work is properly attributed. For permission for commercial use of this work, please see paragraphs 4.2 and 5 of our Terms (https://www.dovepress.com/terms.php). |
spellingShingle | Original Research Gu, Xianhua Shen, Honghong Zhu, Guangzheng Li, Xinwei Zhang, Yue Zhang, Rong Su, Fang Wang, Zishu Prognostic Model and Tumor Immune Microenvironment Analysis of Complement-Related Genes in Gastric Cancer |
title | Prognostic Model and Tumor Immune Microenvironment Analysis of Complement-Related Genes in Gastric Cancer |
title_full | Prognostic Model and Tumor Immune Microenvironment Analysis of Complement-Related Genes in Gastric Cancer |
title_fullStr | Prognostic Model and Tumor Immune Microenvironment Analysis of Complement-Related Genes in Gastric Cancer |
title_full_unstemmed | Prognostic Model and Tumor Immune Microenvironment Analysis of Complement-Related Genes in Gastric Cancer |
title_short | Prognostic Model and Tumor Immune Microenvironment Analysis of Complement-Related Genes in Gastric Cancer |
title_sort | prognostic model and tumor immune microenvironment analysis of complement-related genes in gastric cancer |
topic | Original Research |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10590588/ https://www.ncbi.nlm.nih.gov/pubmed/37872955 http://dx.doi.org/10.2147/JIR.S422903 |
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