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Development and validation of a coagulation-related genes prognostic model for hepatocellular carcinoma
BACKGROUND: Hepatocellular carcinoma (HCC) has a high incidence and mortality worldwide, which seriously threatens people's physical and mental health. Coagulation is closely related to the occurrence and development of HCC. Whether coagulation-related genes (CRGs) can be used as prognostic mar...
Autores principales: | , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
BioMed Central
2023
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9996845/ https://www.ncbi.nlm.nih.gov/pubmed/36894886 http://dx.doi.org/10.1186/s12859-023-05220-4 |
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author | Yang, Wan-Xia Gao, Hong-Wei Cui, Jia-Bo Zhang, An-An Wang, Fang-Fang Xie, Jian-Qin Lu, Ming-Hua You, Chong-Ge |
author_facet | Yang, Wan-Xia Gao, Hong-Wei Cui, Jia-Bo Zhang, An-An Wang, Fang-Fang Xie, Jian-Qin Lu, Ming-Hua You, Chong-Ge |
author_sort | Yang, Wan-Xia |
collection | PubMed |
description | BACKGROUND: Hepatocellular carcinoma (HCC) has a high incidence and mortality worldwide, which seriously threatens people's physical and mental health. Coagulation is closely related to the occurrence and development of HCC. Whether coagulation-related genes (CRGs) can be used as prognostic markers for HCC remains to be investigated. METHODS: Firstly, we identified differentially expressed coagulation-related genes of HCC and control samples in the datasets GSE54236, GSE102079, TCGA-LIHC, and Genecards database. Then, univariate Cox regression analysis, LASSO regression analysis, and multivariate Cox regression analysis were used to determine the key CRGs and establish the coagulation-related risk score (CRRS) prognostic model in the TCGA-LIHC dataset. The predictive capability of the CRRS model was evaluated by Kaplan–Meier survival analysis and ROC analysis. External validation was performed in the ICGC-LIRI-JP dataset. Besides, combining risk score and age, gender, grade, and stage, a nomogram was constructed to quantify the survival probability. We further analyzed the correlation between risk score and functional enrichment, pathway, and tumor immune microenvironment. RESULTS: We identified 5 key CRGs (FLVCR1, CENPE, LCAT, CYP2C9, and NQO1) and constructed the CRRS prognostic model. The overall survival (OS) of the high-risk group was shorter than that of the low-risk group. The AUC values for 1 -, 3 -, and 5-year OS in the TCGA dataset were 0.769, 0.691, and 0.674, respectively. The Cox analysis showed that CRRS was an independent prognostic factor for HCC. A nomogram established with risk score, age, gender, grade, and stage, has a better prognostic value for HCC patients. In the high-risk group, CD4(+)T cells memory resting, NK cells activated, and B cells naive were significantly lower. The expression levels of immune checkpoint genes in the high-risk group were generally higher than that in the low-risk group. CONCLUSIONS: The CRRS model has reliable predictive value for the prognosis of HCC patients. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1186/s12859-023-05220-4. |
format | Online Article Text |
id | pubmed-9996845 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2023 |
publisher | BioMed Central |
record_format | MEDLINE/PubMed |
spelling | pubmed-99968452023-03-10 Development and validation of a coagulation-related genes prognostic model for hepatocellular carcinoma Yang, Wan-Xia Gao, Hong-Wei Cui, Jia-Bo Zhang, An-An Wang, Fang-Fang Xie, Jian-Qin Lu, Ming-Hua You, Chong-Ge BMC Bioinformatics Research BACKGROUND: Hepatocellular carcinoma (HCC) has a high incidence and mortality worldwide, which seriously threatens people's physical and mental health. Coagulation is closely related to the occurrence and development of HCC. Whether coagulation-related genes (CRGs) can be used as prognostic markers for HCC remains to be investigated. METHODS: Firstly, we identified differentially expressed coagulation-related genes of HCC and control samples in the datasets GSE54236, GSE102079, TCGA-LIHC, and Genecards database. Then, univariate Cox regression analysis, LASSO regression analysis, and multivariate Cox regression analysis were used to determine the key CRGs and establish the coagulation-related risk score (CRRS) prognostic model in the TCGA-LIHC dataset. The predictive capability of the CRRS model was evaluated by Kaplan–Meier survival analysis and ROC analysis. External validation was performed in the ICGC-LIRI-JP dataset. Besides, combining risk score and age, gender, grade, and stage, a nomogram was constructed to quantify the survival probability. We further analyzed the correlation between risk score and functional enrichment, pathway, and tumor immune microenvironment. RESULTS: We identified 5 key CRGs (FLVCR1, CENPE, LCAT, CYP2C9, and NQO1) and constructed the CRRS prognostic model. The overall survival (OS) of the high-risk group was shorter than that of the low-risk group. The AUC values for 1 -, 3 -, and 5-year OS in the TCGA dataset were 0.769, 0.691, and 0.674, respectively. The Cox analysis showed that CRRS was an independent prognostic factor for HCC. A nomogram established with risk score, age, gender, grade, and stage, has a better prognostic value for HCC patients. In the high-risk group, CD4(+)T cells memory resting, NK cells activated, and B cells naive were significantly lower. The expression levels of immune checkpoint genes in the high-risk group were generally higher than that in the low-risk group. CONCLUSIONS: The CRRS model has reliable predictive value for the prognosis of HCC patients. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1186/s12859-023-05220-4. BioMed Central 2023-03-09 /pmc/articles/PMC9996845/ /pubmed/36894886 http://dx.doi.org/10.1186/s12859-023-05220-4 Text en © The Author(s) 2023 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 Yang, Wan-Xia Gao, Hong-Wei Cui, Jia-Bo Zhang, An-An Wang, Fang-Fang Xie, Jian-Qin Lu, Ming-Hua You, Chong-Ge Development and validation of a coagulation-related genes prognostic model for hepatocellular carcinoma |
title | Development and validation of a coagulation-related genes prognostic model for hepatocellular carcinoma |
title_full | Development and validation of a coagulation-related genes prognostic model for hepatocellular carcinoma |
title_fullStr | Development and validation of a coagulation-related genes prognostic model for hepatocellular carcinoma |
title_full_unstemmed | Development and validation of a coagulation-related genes prognostic model for hepatocellular carcinoma |
title_short | Development and validation of a coagulation-related genes prognostic model for hepatocellular carcinoma |
title_sort | development and validation of a coagulation-related genes prognostic model for hepatocellular carcinoma |
topic | Research |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9996845/ https://www.ncbi.nlm.nih.gov/pubmed/36894886 http://dx.doi.org/10.1186/s12859-023-05220-4 |
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