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Identification of a ferroptosis-related gene signature predictive model in colon cancer
BACKGROUND: The prognosis of colon cancer (CC) is challenging to predict due to its highly heterogeneous nature. Ferroptosis, an iron-dependent form of cell death, has roles in various cancers; however, the correlation between ferroptosis-related genes (FRGs) and prognosis in CC remains unclear. MET...
Autores principales: | , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
BioMed Central
2021
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8086290/ https://www.ncbi.nlm.nih.gov/pubmed/33926457 http://dx.doi.org/10.1186/s12957-021-02244-z |
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author | Wang, Ye Xia, Heng-bo Chen, Zhang-ming Meng, Lei Xu, A-man |
author_facet | Wang, Ye Xia, Heng-bo Chen, Zhang-ming Meng, Lei Xu, A-man |
author_sort | Wang, Ye |
collection | PubMed |
description | BACKGROUND: The prognosis of colon cancer (CC) is challenging to predict due to its highly heterogeneous nature. Ferroptosis, an iron-dependent form of cell death, has roles in various cancers; however, the correlation between ferroptosis-related genes (FRGs) and prognosis in CC remains unclear. METHODS: The expression profiles of FRGs and relevant clinical information were retrieved from the Cancer Genome Atlas (TCGA) database. Cox regression analysis and the least absolute shrinkage and selection operator (LASSO) regression model were performed to build a prognostic model in TCGA cohort. RESULTS: Ten FRGs, five of which had mutation rates ≥ 3%, were found to be related to the overall survival (OS) of patients with CC. Patients were divided into high- and low-risk groups based on the results of Cox regression and LASSO analysis. Patients in the low-risk group had a significantly longer survival time than patients in the high-risk group (P < 0.001). Enrichment analyses in different risk groups showed that the altered genes were associated with the extracellular matrix, fatty acid metabolism, and peroxisome. Age, risk score, T stage, N stage, and M stage were independent predictors of patient OS based on the results of Cox analysis. Finally, a nomogram was constructed to predict 1-, 3-, and 5-year OS of patients with CC based on the above five independent factors. CONCLUSION: A novel FRG model can be used for prognostic prediction in CC and may be helpful for individualized treatment. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1186/s12957-021-02244-z. |
format | Online Article Text |
id | pubmed-8086290 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2021 |
publisher | BioMed Central |
record_format | MEDLINE/PubMed |
spelling | pubmed-80862902021-04-30 Identification of a ferroptosis-related gene signature predictive model in colon cancer Wang, Ye Xia, Heng-bo Chen, Zhang-ming Meng, Lei Xu, A-man World J Surg Oncol Research BACKGROUND: The prognosis of colon cancer (CC) is challenging to predict due to its highly heterogeneous nature. Ferroptosis, an iron-dependent form of cell death, has roles in various cancers; however, the correlation between ferroptosis-related genes (FRGs) and prognosis in CC remains unclear. METHODS: The expression profiles of FRGs and relevant clinical information were retrieved from the Cancer Genome Atlas (TCGA) database. Cox regression analysis and the least absolute shrinkage and selection operator (LASSO) regression model were performed to build a prognostic model in TCGA cohort. RESULTS: Ten FRGs, five of which had mutation rates ≥ 3%, were found to be related to the overall survival (OS) of patients with CC. Patients were divided into high- and low-risk groups based on the results of Cox regression and LASSO analysis. Patients in the low-risk group had a significantly longer survival time than patients in the high-risk group (P < 0.001). Enrichment analyses in different risk groups showed that the altered genes were associated with the extracellular matrix, fatty acid metabolism, and peroxisome. Age, risk score, T stage, N stage, and M stage were independent predictors of patient OS based on the results of Cox analysis. Finally, a nomogram was constructed to predict 1-, 3-, and 5-year OS of patients with CC based on the above five independent factors. CONCLUSION: A novel FRG model can be used for prognostic prediction in CC and may be helpful for individualized treatment. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1186/s12957-021-02244-z. BioMed Central 2021-04-29 /pmc/articles/PMC8086290/ /pubmed/33926457 http://dx.doi.org/10.1186/s12957-021-02244-z Text en © The Author(s) 2021 https://creativecommons.org/licenses/by/4.0/Open AccessThis article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/ (https://creativecommons.org/licenses/by/4.0/) . The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/ (https://creativecommons.org/publicdomain/zero/1.0/) ) applies to the data made available in this article, unless otherwise stated in a credit line to the data. |
spellingShingle | Research Wang, Ye Xia, Heng-bo Chen, Zhang-ming Meng, Lei Xu, A-man Identification of a ferroptosis-related gene signature predictive model in colon cancer |
title | Identification of a ferroptosis-related gene signature predictive model in colon cancer |
title_full | Identification of a ferroptosis-related gene signature predictive model in colon cancer |
title_fullStr | Identification of a ferroptosis-related gene signature predictive model in colon cancer |
title_full_unstemmed | Identification of a ferroptosis-related gene signature predictive model in colon cancer |
title_short | Identification of a ferroptosis-related gene signature predictive model in colon cancer |
title_sort | identification of a ferroptosis-related gene signature predictive model in colon cancer |
topic | Research |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8086290/ https://www.ncbi.nlm.nih.gov/pubmed/33926457 http://dx.doi.org/10.1186/s12957-021-02244-z |
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