The role of multiple metabolic genes in predicting the overall survival of colorectal cancer: A study based on TCGA and GEO databases.

The recent advances in gene chip technology have led to the identification of multiple metabolism-related genes that are closely associated with colorectal cancer (CRC). Nevertheless, none of these genes could accurately diagnose or predict CRC. The prognosis of CRC has been made by previous prognos...

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Autores principales:	Weijun Shi, Xincan Li, Xu Su, Hexin Wen, Tianwen Chen, Huazhang Wu, Mulin Liu
Formato:	article
Lenguaje:	EN
Publicado:	Public Library of Science (PLoS) 2021
Materias:	Medicine R Science Q
Acceso en línea:	https://doaj.org/article/0c21b5c628eb4dfbb0905e5e599949de
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spelling	oai:doaj.org-article:0c21b5c628eb4dfbb0905e5e599949de2021-12-02T20:18:05ZThe role of multiple metabolic genes in predicting the overall survival of colorectal cancer: A study based on TCGA and GEO databases.1932-620310.1371/journal.pone.0251323https://doaj.org/article/0c21b5c628eb4dfbb0905e5e599949de2021-01-01T00:00:00Zhttps://doi.org/10.1371/journal.pone.0251323https://doaj.org/toc/1932-6203The recent advances in gene chip technology have led to the identification of multiple metabolism-related genes that are closely associated with colorectal cancer (CRC). Nevertheless, none of these genes could accurately diagnose or predict CRC. The prognosis of CRC has been made by previous prognostic models constructed by using multiple genes, however, the predictive function of multi-gene prognostic models using metabolic genes for the CRC prognosis remains unexplored. In this study, we used the TCGA-CRC cohort as the test dataset and the GSE39582 cohort as the experimental dataset. Firstly, we constructed a prognostic model using metabolic genes from the TCGA-CRC cohort, which were also associated with CRC prognosis. We analyzed the advantages of the prognostic model in the prognosis of CRC and its regulatory mechanism of the genes associated with the model. Secondly, the outcome of the TCGA-CRC cohort analysis was validated using the GSE39582 cohort. We found that the prognostic model can be employed as an independent prognostic risk factor for estimating the CRC survival rate. Besides, compared with traditional clinical pathology, it can precisely predict CRC prognosis as well. The high-risk group of the prognostic model showed a substantially lower survival rate as compared to the low-risk group. In addition, gene enrichment analysis of metabolic genes showed that genes in the prognostic model are enriched in metabolism and cancer-related pathways, which may explain its underlying mechanism. Our study identified a novel metabolic profile containing 11 genes for prognostic prediction of CRC. The prognostic model may unravel the imbalanced metabolic microenvironment, and it might promote the development of biomarkers for predicting treatment response and streamlining metabolic therapy in CRC.Weijun ShiXincan LiXu SuHexin WenTianwen ChenHuazhang WuMulin LiuPublic Library of Science (PLoS)articleMedicineRScienceQENPLoS ONE, Vol 16, Iss 8, p e0251323 (2021)
institution	DOAJ
collection	DOAJ
language	EN
topic	Medicine R Science Q
spellingShingle	Medicine R Science Q Weijun Shi Xincan Li Xu Su Hexin Wen Tianwen Chen Huazhang Wu Mulin Liu The role of multiple metabolic genes in predicting the overall survival of colorectal cancer: A study based on TCGA and GEO databases.
description	The recent advances in gene chip technology have led to the identification of multiple metabolism-related genes that are closely associated with colorectal cancer (CRC). Nevertheless, none of these genes could accurately diagnose or predict CRC. The prognosis of CRC has been made by previous prognostic models constructed by using multiple genes, however, the predictive function of multi-gene prognostic models using metabolic genes for the CRC prognosis remains unexplored. In this study, we used the TCGA-CRC cohort as the test dataset and the GSE39582 cohort as the experimental dataset. Firstly, we constructed a prognostic model using metabolic genes from the TCGA-CRC cohort, which were also associated with CRC prognosis. We analyzed the advantages of the prognostic model in the prognosis of CRC and its regulatory mechanism of the genes associated with the model. Secondly, the outcome of the TCGA-CRC cohort analysis was validated using the GSE39582 cohort. We found that the prognostic model can be employed as an independent prognostic risk factor for estimating the CRC survival rate. Besides, compared with traditional clinical pathology, it can precisely predict CRC prognosis as well. The high-risk group of the prognostic model showed a substantially lower survival rate as compared to the low-risk group. In addition, gene enrichment analysis of metabolic genes showed that genes in the prognostic model are enriched in metabolism and cancer-related pathways, which may explain its underlying mechanism. Our study identified a novel metabolic profile containing 11 genes for prognostic prediction of CRC. The prognostic model may unravel the imbalanced metabolic microenvironment, and it might promote the development of biomarkers for predicting treatment response and streamlining metabolic therapy in CRC.
format	article
author	Weijun Shi Xincan Li Xu Su Hexin Wen Tianwen Chen Huazhang Wu Mulin Liu
author_facet	Weijun Shi Xincan Li Xu Su Hexin Wen Tianwen Chen Huazhang Wu Mulin Liu
author_sort	Weijun Shi
title	The role of multiple metabolic genes in predicting the overall survival of colorectal cancer: A study based on TCGA and GEO databases.
title_short	The role of multiple metabolic genes in predicting the overall survival of colorectal cancer: A study based on TCGA and GEO databases.
title_full	The role of multiple metabolic genes in predicting the overall survival of colorectal cancer: A study based on TCGA and GEO databases.
title_fullStr	The role of multiple metabolic genes in predicting the overall survival of colorectal cancer: A study based on TCGA and GEO databases.
title_full_unstemmed	The role of multiple metabolic genes in predicting the overall survival of colorectal cancer: A study based on TCGA and GEO databases.
title_sort	role of multiple metabolic genes in predicting the overall survival of colorectal cancer: a study based on tcga and geo databases.
publisher	Public Library of Science (PLoS)
publishDate	2021
url	https://doaj.org/article/0c21b5c628eb4dfbb0905e5e599949de
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The role of multiple metabolic genes in predicting the overall survival of colorectal cancer: A study based on TCGA and GEO databases.

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