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Identification of crucial genes of pyrimidine metabolism as biomarkers for gastric cancer prognosis
BACKGROUND: Metabolic reprogramming has been reported in various kinds of cancers and is related to clinical prognosis, but the prognostic role of pyrimidine metabolism in gastric cancer (GC) remains unclear. METHODS: Here, we employed DEG analysis to detect the differentially expressed genes (DEGs)...
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/PMC8670209/ https://www.ncbi.nlm.nih.gov/pubmed/34906153 http://dx.doi.org/10.1186/s12935-021-02385-x |
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author | Wu, Zhengxin Tan, Jinshui Zhuang, Yifan Zhong, Mengya Xiong, Yubo Ma, Jingsong Yang, Yan Gao, Zhi Zhao, Jiabao Ye, Zhijian Zhou, Huiwen Zhu, Yuekun Lu, Haijie Hong, Xuehui |
author_facet | Wu, Zhengxin Tan, Jinshui Zhuang, Yifan Zhong, Mengya Xiong, Yubo Ma, Jingsong Yang, Yan Gao, Zhi Zhao, Jiabao Ye, Zhijian Zhou, Huiwen Zhu, Yuekun Lu, Haijie Hong, Xuehui |
author_sort | Wu, Zhengxin |
collection | PubMed |
description | BACKGROUND: Metabolic reprogramming has been reported in various kinds of cancers and is related to clinical prognosis, but the prognostic role of pyrimidine metabolism in gastric cancer (GC) remains unclear. METHODS: Here, we employed DEG analysis to detect the differentially expressed genes (DEGs) in pyrimidine metabolic signaling pathway and used univariate Cox analysis, Lasso-penalizes Cox regression analysis, Kaplan–Meier survival analysis, univariate and multivariate Cox regression analysis to explore their prognostic roles in GC. The DEGs were experimentally validated in GC cells and clinical samples by quantitative real-time PCR. RESULTS: Through DEG analysis, we found NT5E, DPYS and UPP1 these three genes are highly expressed in GC. This conclusion has also been verified in GC cells and clinical samples. A prognostic risk model was established according to these three DEGs by Univariate Cox analysis and Lasso-penalizes Cox regression analysis. Kaplan–Meier survival analysis suggested that patient cohorts with high risk score undertook a lower overall survival rate than those with low risk score. Stratified survival analysis, Univariate and multivariate Cox regression analysis of this model confirmed that it is a reliable and independent clinical factor. Therefore, we made nomograms to visually depict the survival rate of GC patients according to some important clinical factors including our risk model. CONCLUSION: In a word, our research found that pyrimidine metabolism is dysregulated in GC and established a prognostic model of GC based on genes differentially expressed in pyrimidine metabolism. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1186/s12935-021-02385-x. |
format | Online Article Text |
id | pubmed-8670209 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2021 |
publisher | BioMed Central |
record_format | MEDLINE/PubMed |
spelling | pubmed-86702092021-12-15 Identification of crucial genes of pyrimidine metabolism as biomarkers for gastric cancer prognosis Wu, Zhengxin Tan, Jinshui Zhuang, Yifan Zhong, Mengya Xiong, Yubo Ma, Jingsong Yang, Yan Gao, Zhi Zhao, Jiabao Ye, Zhijian Zhou, Huiwen Zhu, Yuekun Lu, Haijie Hong, Xuehui Cancer Cell Int Primary Research BACKGROUND: Metabolic reprogramming has been reported in various kinds of cancers and is related to clinical prognosis, but the prognostic role of pyrimidine metabolism in gastric cancer (GC) remains unclear. METHODS: Here, we employed DEG analysis to detect the differentially expressed genes (DEGs) in pyrimidine metabolic signaling pathway and used univariate Cox analysis, Lasso-penalizes Cox regression analysis, Kaplan–Meier survival analysis, univariate and multivariate Cox regression analysis to explore their prognostic roles in GC. The DEGs were experimentally validated in GC cells and clinical samples by quantitative real-time PCR. RESULTS: Through DEG analysis, we found NT5E, DPYS and UPP1 these three genes are highly expressed in GC. This conclusion has also been verified in GC cells and clinical samples. A prognostic risk model was established according to these three DEGs by Univariate Cox analysis and Lasso-penalizes Cox regression analysis. Kaplan–Meier survival analysis suggested that patient cohorts with high risk score undertook a lower overall survival rate than those with low risk score. Stratified survival analysis, Univariate and multivariate Cox regression analysis of this model confirmed that it is a reliable and independent clinical factor. Therefore, we made nomograms to visually depict the survival rate of GC patients according to some important clinical factors including our risk model. CONCLUSION: In a word, our research found that pyrimidine metabolism is dysregulated in GC and established a prognostic model of GC based on genes differentially expressed in pyrimidine metabolism. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1186/s12935-021-02385-x. BioMed Central 2021-12-14 /pmc/articles/PMC8670209/ /pubmed/34906153 http://dx.doi.org/10.1186/s12935-021-02385-x 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 | Primary Research Wu, Zhengxin Tan, Jinshui Zhuang, Yifan Zhong, Mengya Xiong, Yubo Ma, Jingsong Yang, Yan Gao, Zhi Zhao, Jiabao Ye, Zhijian Zhou, Huiwen Zhu, Yuekun Lu, Haijie Hong, Xuehui Identification of crucial genes of pyrimidine metabolism as biomarkers for gastric cancer prognosis |
title | Identification of crucial genes of pyrimidine metabolism as biomarkers for gastric cancer prognosis |
title_full | Identification of crucial genes of pyrimidine metabolism as biomarkers for gastric cancer prognosis |
title_fullStr | Identification of crucial genes of pyrimidine metabolism as biomarkers for gastric cancer prognosis |
title_full_unstemmed | Identification of crucial genes of pyrimidine metabolism as biomarkers for gastric cancer prognosis |
title_short | Identification of crucial genes of pyrimidine metabolism as biomarkers for gastric cancer prognosis |
title_sort | identification of crucial genes of pyrimidine metabolism as biomarkers for gastric cancer prognosis |
topic | Primary Research |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8670209/ https://www.ncbi.nlm.nih.gov/pubmed/34906153 http://dx.doi.org/10.1186/s12935-021-02385-x |
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