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Identification and Validation of a Novel Inflammatory Response-Related Gene Signature for the Prognosis of Colon Cancer

PURPOSE: The inflammatory response plays a crucial role in the occurrence and development of colon cancer. In this study, we aimed to explore a novel prognostic model for patients with colon cancer (COAD) based on inflammatory response-related genes. METHODS: Inflammatory response-related genes were...

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Autores principales: Liang, Yichao, Wu, Xin, Su, Qi, Liu, Yujie, Xiao, Hong
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Dove 2021
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8364916/
https://www.ncbi.nlm.nih.gov/pubmed/34408464
http://dx.doi.org/10.2147/JIR.S321852
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author Liang, Yichao
Wu, Xin
Su, Qi
Liu, Yujie
Xiao, Hong
author_facet Liang, Yichao
Wu, Xin
Su, Qi
Liu, Yujie
Xiao, Hong
author_sort Liang, Yichao
collection PubMed
description PURPOSE: The inflammatory response plays a crucial role in the occurrence and development of colon cancer. In this study, we aimed to explore a novel prognostic model for patients with colon cancer (COAD) based on inflammatory response-related genes. METHODS: Inflammatory response-related genes were obtained from Molecular Signatures database. Univariate and multivariate Cox regression analyses were used for model construction based on TCGA dataset. GSE39582 dataset and qRT-PCR dataset were used for validation. Gene set variation analysis and gene set enrichment analysis were performed to explore the potential regulatory pathways. The immune cell infiltration level was analyzed via CIBERSORT. Immunohistochemistry analysis and experiments were used to explore the function of genes in model. RESULTS: In this study, a novel prognostic signature was identified using stepwise Cox proportional hazards regression analysis based on TCGA dataset. The results were subsequently validated in 562 patients from GSE39582 and a qRT-PCR data set from 70 tumor samples. Functional analysis indicated that the tumor microenvironment and immune cell infiltrate were different between high- and low-risk groups. Additionally, IHC results showed that the protein levels of prognostic genes were significantly different between COAD tissues and adjacent non-tumorous tissues, and prognostic genes could regulate the malignant phenotype of COAD cells. CONCLUSION: Overall, the inflammation-related gene signature can be used for prognostic prediction in patients with COAD.
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spelling pubmed-83649162021-08-17 Identification and Validation of a Novel Inflammatory Response-Related Gene Signature for the Prognosis of Colon Cancer Liang, Yichao Wu, Xin Su, Qi Liu, Yujie Xiao, Hong J Inflamm Res Original Research PURPOSE: The inflammatory response plays a crucial role in the occurrence and development of colon cancer. In this study, we aimed to explore a novel prognostic model for patients with colon cancer (COAD) based on inflammatory response-related genes. METHODS: Inflammatory response-related genes were obtained from Molecular Signatures database. Univariate and multivariate Cox regression analyses were used for model construction based on TCGA dataset. GSE39582 dataset and qRT-PCR dataset were used for validation. Gene set variation analysis and gene set enrichment analysis were performed to explore the potential regulatory pathways. The immune cell infiltration level was analyzed via CIBERSORT. Immunohistochemistry analysis and experiments were used to explore the function of genes in model. RESULTS: In this study, a novel prognostic signature was identified using stepwise Cox proportional hazards regression analysis based on TCGA dataset. The results were subsequently validated in 562 patients from GSE39582 and a qRT-PCR data set from 70 tumor samples. Functional analysis indicated that the tumor microenvironment and immune cell infiltrate were different between high- and low-risk groups. Additionally, IHC results showed that the protein levels of prognostic genes were significantly different between COAD tissues and adjacent non-tumorous tissues, and prognostic genes could regulate the malignant phenotype of COAD cells. CONCLUSION: Overall, the inflammation-related gene signature can be used for prognostic prediction in patients with COAD. Dove 2021-08-11 /pmc/articles/PMC8364916/ /pubmed/34408464 http://dx.doi.org/10.2147/JIR.S321852 Text en © 2021 Liang 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
Liang, Yichao
Wu, Xin
Su, Qi
Liu, Yujie
Xiao, Hong
Identification and Validation of a Novel Inflammatory Response-Related Gene Signature for the Prognosis of Colon Cancer
title Identification and Validation of a Novel Inflammatory Response-Related Gene Signature for the Prognosis of Colon Cancer
title_full Identification and Validation of a Novel Inflammatory Response-Related Gene Signature for the Prognosis of Colon Cancer
title_fullStr Identification and Validation of a Novel Inflammatory Response-Related Gene Signature for the Prognosis of Colon Cancer
title_full_unstemmed Identification and Validation of a Novel Inflammatory Response-Related Gene Signature for the Prognosis of Colon Cancer
title_short Identification and Validation of a Novel Inflammatory Response-Related Gene Signature for the Prognosis of Colon Cancer
title_sort identification and validation of a novel inflammatory response-related gene signature for the prognosis of colon cancer
topic Original Research
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8364916/
https://www.ncbi.nlm.nih.gov/pubmed/34408464
http://dx.doi.org/10.2147/JIR.S321852
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