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Identification and verification of an exosome-related gene risk model to predict prognosis and evaluate immune infiltration for colorectal cancer

Colorectal cancer (CRC) is a common malignant tumor that severely endangers human health. Exosomes show great potential in tumor immunotherapy. Increasingly studies have shown that exosome-related genes are effective prognostic biomarkers. Clinical information and gene expression data of CRC patient...

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Autores principales: Shao, Huan, Yao, Li, Tao, Ye, Huang, Xuan
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Lippincott Williams & Wilkins 2023
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10553194/
https://www.ncbi.nlm.nih.gov/pubmed/37800824
http://dx.doi.org/10.1097/MD.0000000000035365
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author Shao, Huan
Yao, Li
Tao, Ye
Huang, Xuan
author_facet Shao, Huan
Yao, Li
Tao, Ye
Huang, Xuan
author_sort Shao, Huan
collection PubMed
description Colorectal cancer (CRC) is a common malignant tumor that severely endangers human health. Exosomes show great potential in tumor immunotherapy. Increasingly studies have shown that exosome-related genes are effective prognostic biomarkers. Clinical information and gene expression data of CRC patients were obtained from gene expression omnibus and the cancer genome atlas. The data were then classified into training and independent validation sets. In the training set, exosome-related genes with a prognostic value were selected by univariate Cox analysis, least absolute shrinkage and selection operator Cox regression model, and stepwise Cox regression analysis. Risk scores were calculated based on the selected genes to stratify patients. The selected exosome-related genes were applied to establish a risk model. Based on 11 exosome-related genes, a prognostic risk model, which could stratify the risk both in the training and validation sets, was established. According to the survival curves, the prognoses of the high- and low-risk groups were significantly different. The AUCs of the risk model for prognostic prediction were 0.735 and 0.784 in the training and validation sets, respectively. A nomogram was constructed to predict the survival of CRC patients. Single-sample gene set enrichment analysis and ESTIMATE algorithms revealed that the risk model was related to immune cell infiltration. The value of the risk model in predicting immunotherapeutic outcomes was also confirmed. An exosome-related gene risk model was constructed to predict prognosis, evaluate microenvironment immune cell infiltration levels and bring a new perspective to CRC patient treatment.
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spelling pubmed-105531942023-10-06 Identification and verification of an exosome-related gene risk model to predict prognosis and evaluate immune infiltration for colorectal cancer Shao, Huan Yao, Li Tao, Ye Huang, Xuan Medicine (Baltimore) 5700 Colorectal cancer (CRC) is a common malignant tumor that severely endangers human health. Exosomes show great potential in tumor immunotherapy. Increasingly studies have shown that exosome-related genes are effective prognostic biomarkers. Clinical information and gene expression data of CRC patients were obtained from gene expression omnibus and the cancer genome atlas. The data were then classified into training and independent validation sets. In the training set, exosome-related genes with a prognostic value were selected by univariate Cox analysis, least absolute shrinkage and selection operator Cox regression model, and stepwise Cox regression analysis. Risk scores were calculated based on the selected genes to stratify patients. The selected exosome-related genes were applied to establish a risk model. Based on 11 exosome-related genes, a prognostic risk model, which could stratify the risk both in the training and validation sets, was established. According to the survival curves, the prognoses of the high- and low-risk groups were significantly different. The AUCs of the risk model for prognostic prediction were 0.735 and 0.784 in the training and validation sets, respectively. A nomogram was constructed to predict the survival of CRC patients. Single-sample gene set enrichment analysis and ESTIMATE algorithms revealed that the risk model was related to immune cell infiltration. The value of the risk model in predicting immunotherapeutic outcomes was also confirmed. An exosome-related gene risk model was constructed to predict prognosis, evaluate microenvironment immune cell infiltration levels and bring a new perspective to CRC patient treatment. Lippincott Williams & Wilkins 2023-10-06 /pmc/articles/PMC10553194/ /pubmed/37800824 http://dx.doi.org/10.1097/MD.0000000000035365 Text en Copyright © 2023 the Author(s). Published by Wolters Kluwer Health, Inc. https://creativecommons.org/licenses/by-nc/4.0/This is an open-access article distributed under the terms of the Creative Commons Attribution-Non Commercial License 4.0 (CCBY-NC) (https://creativecommons.org/licenses/by-nc/4.0/) , where it is permissible to download, share, remix, transform, and buildup the work provided it is properly cited. The work cannot be used commercially without permission from the journal.
spellingShingle 5700
Shao, Huan
Yao, Li
Tao, Ye
Huang, Xuan
Identification and verification of an exosome-related gene risk model to predict prognosis and evaluate immune infiltration for colorectal cancer
title Identification and verification of an exosome-related gene risk model to predict prognosis and evaluate immune infiltration for colorectal cancer
title_full Identification and verification of an exosome-related gene risk model to predict prognosis and evaluate immune infiltration for colorectal cancer
title_fullStr Identification and verification of an exosome-related gene risk model to predict prognosis and evaluate immune infiltration for colorectal cancer
title_full_unstemmed Identification and verification of an exosome-related gene risk model to predict prognosis and evaluate immune infiltration for colorectal cancer
title_short Identification and verification of an exosome-related gene risk model to predict prognosis and evaluate immune infiltration for colorectal cancer
title_sort identification and verification of an exosome-related gene risk model to predict prognosis and evaluate immune infiltration for colorectal cancer
topic 5700
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10553194/
https://www.ncbi.nlm.nih.gov/pubmed/37800824
http://dx.doi.org/10.1097/MD.0000000000035365
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