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Immune-related gene-based model predicts the survival of colorectal carcinoma and reflected various biological statuses

Bakcground: Prognosis of colorectal cancer (CRC) varies due to complex genetic–microenviromental interactions, and multiple gene-based prognostic models have been highlighted. Material and Method: In this work, the immune-related genes’ expression-based model was developed and the scores of each sam...

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Autores principales: Kang, Zhengchun, Chen, Bingchen, Ma, Xiuzhu, Yan, Feihu, Wang, Zhen
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Frontiers Media S.A. 2023
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10619740/
https://www.ncbi.nlm.nih.gov/pubmed/37920710
http://dx.doi.org/10.3389/fmolb.2023.1277933
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author Kang, Zhengchun
Chen, Bingchen
Ma, Xiuzhu
Yan, Feihu
Wang, Zhen
author_facet Kang, Zhengchun
Chen, Bingchen
Ma, Xiuzhu
Yan, Feihu
Wang, Zhen
author_sort Kang, Zhengchun
collection PubMed
description Bakcground: Prognosis of colorectal cancer (CRC) varies due to complex genetic–microenviromental interactions, and multiple gene-based prognostic models have been highlighted. Material and Method: In this work, the immune-related genes’ expression-based model was developed and the scores of each sample were calculated. The correlation between the model and clinical information, immune infiltration, drug response and biological pathways were analyzed. Results: The high-score samples have a significantly longer survival (overall survival and progression-free survival) period than those with a low score, which was validated across seven datasets containing 1,325 samples (GSE17536 (N = 115), GSE17537 (N = 55), GSE33113 (N = 90), GSE37892 (N = 130), GSE38832 (N = 74), GSE39582 (N = 481), and TCGA (N = 380)). The score is significantly associated with clinical indicators, including age and stage, and further associated with PD-1/PD-L1 gene expression. Furthermore, high-score samples have significantly higher APC and a lower MUC5B mutation rate. The high-score samples show more immune infiltration (including CD4(+) and CD8(+) T cells, M1/M2 macrophages, and NK cells). Enriched pathway analyses showed that cancer-related pathways, including immune-related pathways, were significantly activated in high-score samples and that some drugs have significantly lower IC(50) values than those with low score. Conclusion: The model developed based on immune-related genes is robust and reflected various statuses of CRC and may be a potential clinical indicator.
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spelling pubmed-106197402023-11-02 Immune-related gene-based model predicts the survival of colorectal carcinoma and reflected various biological statuses Kang, Zhengchun Chen, Bingchen Ma, Xiuzhu Yan, Feihu Wang, Zhen Front Mol Biosci Molecular Biosciences Bakcground: Prognosis of colorectal cancer (CRC) varies due to complex genetic–microenviromental interactions, and multiple gene-based prognostic models have been highlighted. Material and Method: In this work, the immune-related genes’ expression-based model was developed and the scores of each sample were calculated. The correlation between the model and clinical information, immune infiltration, drug response and biological pathways were analyzed. Results: The high-score samples have a significantly longer survival (overall survival and progression-free survival) period than those with a low score, which was validated across seven datasets containing 1,325 samples (GSE17536 (N = 115), GSE17537 (N = 55), GSE33113 (N = 90), GSE37892 (N = 130), GSE38832 (N = 74), GSE39582 (N = 481), and TCGA (N = 380)). The score is significantly associated with clinical indicators, including age and stage, and further associated with PD-1/PD-L1 gene expression. Furthermore, high-score samples have significantly higher APC and a lower MUC5B mutation rate. The high-score samples show more immune infiltration (including CD4(+) and CD8(+) T cells, M1/M2 macrophages, and NK cells). Enriched pathway analyses showed that cancer-related pathways, including immune-related pathways, were significantly activated in high-score samples and that some drugs have significantly lower IC(50) values than those with low score. Conclusion: The model developed based on immune-related genes is robust and reflected various statuses of CRC and may be a potential clinical indicator. Frontiers Media S.A. 2023-10-18 /pmc/articles/PMC10619740/ /pubmed/37920710 http://dx.doi.org/10.3389/fmolb.2023.1277933 Text en Copyright © 2023 Kang, Chen, Ma, Yan and Wang. https://creativecommons.org/licenses/by/4.0/This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.
spellingShingle Molecular Biosciences
Kang, Zhengchun
Chen, Bingchen
Ma, Xiuzhu
Yan, Feihu
Wang, Zhen
Immune-related gene-based model predicts the survival of colorectal carcinoma and reflected various biological statuses
title Immune-related gene-based model predicts the survival of colorectal carcinoma and reflected various biological statuses
title_full Immune-related gene-based model predicts the survival of colorectal carcinoma and reflected various biological statuses
title_fullStr Immune-related gene-based model predicts the survival of colorectal carcinoma and reflected various biological statuses
title_full_unstemmed Immune-related gene-based model predicts the survival of colorectal carcinoma and reflected various biological statuses
title_short Immune-related gene-based model predicts the survival of colorectal carcinoma and reflected various biological statuses
title_sort immune-related gene-based model predicts the survival of colorectal carcinoma and reflected various biological statuses
topic Molecular Biosciences
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10619740/
https://www.ncbi.nlm.nih.gov/pubmed/37920710
http://dx.doi.org/10.3389/fmolb.2023.1277933
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