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Transcriptome analysis reveals a reprogramming energy metabolism-related signature to improve prognosis in colon cancer
Although much progress has been made to improve treatment, colon cancer remains a leading cause of cancer death worldwide. Metabolic reprogramming is a significant ability of cancer cells to ensure the necessary energy supply in uncontrolled proliferation. Since reprogramming energy metabolism has e...
Autores principales: | , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
PeerJ Inc.
2020
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7350917/ https://www.ncbi.nlm.nih.gov/pubmed/32704448 http://dx.doi.org/10.7717/peerj.9458 |
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author | Zhang, Xinxin Xu, Jinyuan Lan, Yujia Guo, Fenghua Xiao, Yun Li, Yixue Li, Xia |
author_facet | Zhang, Xinxin Xu, Jinyuan Lan, Yujia Guo, Fenghua Xiao, Yun Li, Yixue Li, Xia |
author_sort | Zhang, Xinxin |
collection | PubMed |
description | Although much progress has been made to improve treatment, colon cancer remains a leading cause of cancer death worldwide. Metabolic reprogramming is a significant ability of cancer cells to ensure the necessary energy supply in uncontrolled proliferation. Since reprogramming energy metabolism has emerged as a new hallmark of cancer cells, accumulating evidences have suggested that metabolism-related genes may serve as key regulators of tumorigenesis and potential biomarkers. In this study, we analyzed a set of reprogramming energy metabolism-related genes by transcriptome analysis in colon cancer and revealed a five-gene signature that could significantly predict the overall survival. The reprogramming energy metabolism-related signature could distinguish patients into high-risk and low-risk groups with significantly different survival times (P = 0.0011; HR = 1.92; 95% CI [1.29–2.87]). Its prognostic value was confirmed in another two independent colon cancer cohorts (P = 5.2e–04; HR = 2.09, 95%; CI [1.37–3.2] for GSE17538 and P = 3.8e−04; HR = 2.08, 95% CI [1.37–3.16] for GSE41258). By multivariable analysis, we found that the signature was independent of clinicopathological features. Its power in promoting risk stratification of the current clinical stage was then evaluated by stratified analysis. Moreover, the signature could improve the power of the TNM stage for the prediction of overall survival and could be used in patients who received adjuvant chemotherapy. Overall, our results demonstrated the important role of the reprogramming energy metabolism-related signature in promoting stratification of high-risk patients, which could be diagnostic of adjuvant therapy benefit. |
format | Online Article Text |
id | pubmed-7350917 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2020 |
publisher | PeerJ Inc. |
record_format | MEDLINE/PubMed |
spelling | pubmed-73509172020-07-22 Transcriptome analysis reveals a reprogramming energy metabolism-related signature to improve prognosis in colon cancer Zhang, Xinxin Xu, Jinyuan Lan, Yujia Guo, Fenghua Xiao, Yun Li, Yixue Li, Xia PeerJ Bioinformatics Although much progress has been made to improve treatment, colon cancer remains a leading cause of cancer death worldwide. Metabolic reprogramming is a significant ability of cancer cells to ensure the necessary energy supply in uncontrolled proliferation. Since reprogramming energy metabolism has emerged as a new hallmark of cancer cells, accumulating evidences have suggested that metabolism-related genes may serve as key regulators of tumorigenesis and potential biomarkers. In this study, we analyzed a set of reprogramming energy metabolism-related genes by transcriptome analysis in colon cancer and revealed a five-gene signature that could significantly predict the overall survival. The reprogramming energy metabolism-related signature could distinguish patients into high-risk and low-risk groups with significantly different survival times (P = 0.0011; HR = 1.92; 95% CI [1.29–2.87]). Its prognostic value was confirmed in another two independent colon cancer cohorts (P = 5.2e–04; HR = 2.09, 95%; CI [1.37–3.2] for GSE17538 and P = 3.8e−04; HR = 2.08, 95% CI [1.37–3.16] for GSE41258). By multivariable analysis, we found that the signature was independent of clinicopathological features. Its power in promoting risk stratification of the current clinical stage was then evaluated by stratified analysis. Moreover, the signature could improve the power of the TNM stage for the prediction of overall survival and could be used in patients who received adjuvant chemotherapy. Overall, our results demonstrated the important role of the reprogramming energy metabolism-related signature in promoting stratification of high-risk patients, which could be diagnostic of adjuvant therapy benefit. PeerJ Inc. 2020-07-07 /pmc/articles/PMC7350917/ /pubmed/32704448 http://dx.doi.org/10.7717/peerj.9458 Text en ©2020 Zhang et al. https://creativecommons.org/licenses/by/4.0/ This is an open access article distributed under the terms of the Creative Commons Attribution License (https://creativecommons.org/licenses/by/4.0/) , which permits unrestricted use, distribution, reproduction and adaptation in any medium and for any purpose provided that it is properly attributed. For attribution, the original author(s), title, publication source (PeerJ) and either DOI or URL of the article must be cited. |
spellingShingle | Bioinformatics Zhang, Xinxin Xu, Jinyuan Lan, Yujia Guo, Fenghua Xiao, Yun Li, Yixue Li, Xia Transcriptome analysis reveals a reprogramming energy metabolism-related signature to improve prognosis in colon cancer |
title | Transcriptome analysis reveals a reprogramming energy metabolism-related signature to improve prognosis in colon cancer |
title_full | Transcriptome analysis reveals a reprogramming energy metabolism-related signature to improve prognosis in colon cancer |
title_fullStr | Transcriptome analysis reveals a reprogramming energy metabolism-related signature to improve prognosis in colon cancer |
title_full_unstemmed | Transcriptome analysis reveals a reprogramming energy metabolism-related signature to improve prognosis in colon cancer |
title_short | Transcriptome analysis reveals a reprogramming energy metabolism-related signature to improve prognosis in colon cancer |
title_sort | transcriptome analysis reveals a reprogramming energy metabolism-related signature to improve prognosis in colon cancer |
topic | Bioinformatics |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7350917/ https://www.ncbi.nlm.nih.gov/pubmed/32704448 http://dx.doi.org/10.7717/peerj.9458 |
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