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An effective prognostic model in colon adenocarcinoma composed of cuproptosis-related epigenetic regulators

Background: Colorectal adenocarcinoma (COAD) is a common malignant tumor with little effective prognostic markers. Cuproptosis is a newly discovered mode of cell death that may be related to epigenetic regulators. This study aimed to explore the association between epigenetic regulators and cupropto...

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Autores principales: Liu, Yang, Wang, Yizhao, Li, Chang, Feng, Huijin, Liu, Yanqing, Ma, Lianjun
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Frontiers Media S.A. 2023
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10494936/
https://www.ncbi.nlm.nih.gov/pubmed/37701039
http://dx.doi.org/10.3389/fphar.2023.1254918
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author Liu, Yang
Wang, Yizhao
Li, Chang
Feng, Huijin
Liu, Yanqing
Ma, Lianjun
author_facet Liu, Yang
Wang, Yizhao
Li, Chang
Feng, Huijin
Liu, Yanqing
Ma, Lianjun
author_sort Liu, Yang
collection PubMed
description Background: Colorectal adenocarcinoma (COAD) is a common malignant tumor with little effective prognostic markers. Cuproptosis is a newly discovered mode of cell death that may be related to epigenetic regulators. This study aimed to explore the association between epigenetic regulators and cuproptosis, and to establish a prognostic prediction model for COAD based on epigenetic regulators associated with cuproptosis (EACs). Methods: RNA sequencing data and clinical data of 524 COAD patients were obtained from the TCGA-COAD database, cuproptosis-related genes were from the FerrDb database, and epigenetic-related genes were from databases such as GO and EpiFactors. LASSO regression analysis and other methods were used to screen out epigenetic regulators associated with cuproptosis and prognosis. The risk score of each patient was calculated and the patients were divided into high-risk group and low-risk group. Next, the survival difference, functional enrichment analyses, tumor mutation burden, chemotherapy drug sensitivity and other indicators between the two groups were compared and analyzed. Results: We found 716 epigenetic regulators closely related to cuproptosis, among which 35 genes were related to prognosis of COAD. We further screened out 7 EACs from the 35 EACs to construct a prognostic prediction model. We calculated the risk score of each patient based on these 7 genes, and divided the patients into high-risk group and low-risk group. We found that the overall survival rate and progression-free survival rate of the high-risk group were significantly lower than those of the low-risk group. This model showed good predictive ability in the training set, test set and overall data set. We also constructed a prognostic prediction model based on risk score and other clinical features, and drew the corresponding Nomogram. In addition, we found significant differences between the high-risk group and the low-risk group in tumor mutation burden, chemotherapy drug sensitivity and other clinical aspects. Conclusion: We established an effective predictive prediction model for COAD based on EACs, revealing the association between epigenetic regulators and cuproptosis in COAD. We hope that this model can not only facilitate the treatment decision of COAD patients, but also promote the research progress in the field of cuproptosis.
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spelling pubmed-104949362023-09-12 An effective prognostic model in colon adenocarcinoma composed of cuproptosis-related epigenetic regulators Liu, Yang Wang, Yizhao Li, Chang Feng, Huijin Liu, Yanqing Ma, Lianjun Front Pharmacol Pharmacology Background: Colorectal adenocarcinoma (COAD) is a common malignant tumor with little effective prognostic markers. Cuproptosis is a newly discovered mode of cell death that may be related to epigenetic regulators. This study aimed to explore the association between epigenetic regulators and cuproptosis, and to establish a prognostic prediction model for COAD based on epigenetic regulators associated with cuproptosis (EACs). Methods: RNA sequencing data and clinical data of 524 COAD patients were obtained from the TCGA-COAD database, cuproptosis-related genes were from the FerrDb database, and epigenetic-related genes were from databases such as GO and EpiFactors. LASSO regression analysis and other methods were used to screen out epigenetic regulators associated with cuproptosis and prognosis. The risk score of each patient was calculated and the patients were divided into high-risk group and low-risk group. Next, the survival difference, functional enrichment analyses, tumor mutation burden, chemotherapy drug sensitivity and other indicators between the two groups were compared and analyzed. Results: We found 716 epigenetic regulators closely related to cuproptosis, among which 35 genes were related to prognosis of COAD. We further screened out 7 EACs from the 35 EACs to construct a prognostic prediction model. We calculated the risk score of each patient based on these 7 genes, and divided the patients into high-risk group and low-risk group. We found that the overall survival rate and progression-free survival rate of the high-risk group were significantly lower than those of the low-risk group. This model showed good predictive ability in the training set, test set and overall data set. We also constructed a prognostic prediction model based on risk score and other clinical features, and drew the corresponding Nomogram. In addition, we found significant differences between the high-risk group and the low-risk group in tumor mutation burden, chemotherapy drug sensitivity and other clinical aspects. Conclusion: We established an effective predictive prediction model for COAD based on EACs, revealing the association between epigenetic regulators and cuproptosis in COAD. We hope that this model can not only facilitate the treatment decision of COAD patients, but also promote the research progress in the field of cuproptosis. Frontiers Media S.A. 2023-08-24 /pmc/articles/PMC10494936/ /pubmed/37701039 http://dx.doi.org/10.3389/fphar.2023.1254918 Text en Copyright © 2023 Liu, Wang, Li, Feng, Liu and Ma. 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 Pharmacology
Liu, Yang
Wang, Yizhao
Li, Chang
Feng, Huijin
Liu, Yanqing
Ma, Lianjun
An effective prognostic model in colon adenocarcinoma composed of cuproptosis-related epigenetic regulators
title An effective prognostic model in colon adenocarcinoma composed of cuproptosis-related epigenetic regulators
title_full An effective prognostic model in colon adenocarcinoma composed of cuproptosis-related epigenetic regulators
title_fullStr An effective prognostic model in colon adenocarcinoma composed of cuproptosis-related epigenetic regulators
title_full_unstemmed An effective prognostic model in colon adenocarcinoma composed of cuproptosis-related epigenetic regulators
title_short An effective prognostic model in colon adenocarcinoma composed of cuproptosis-related epigenetic regulators
title_sort effective prognostic model in colon adenocarcinoma composed of cuproptosis-related epigenetic regulators
topic Pharmacology
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10494936/
https://www.ncbi.nlm.nih.gov/pubmed/37701039
http://dx.doi.org/10.3389/fphar.2023.1254918
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