Cargando…

Construction and validation of 3-genes hypoxia-related prognostic signature to predict the prognosis and therapeutic response of hepatocellular carcinoma patients

BACKGROUND: Previous studies have shown that the hypoxia microenvironment significantly impacted tumor progression. However, the clinical prognostic value of hypoxia-related risk signatures and their effects on the tumor microenvironment (TME) in hepatocellular carcinoma (HCC) remains hazy. This stu...

Descripción completa

Detalles Bibliográficos
Autores principales: Liu, Yunxun, Shen, Bingbing, Huang, Ting, Wang, Jianguo, Jiang, Jianxin
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Public Library of Science 2023
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10321610/
https://www.ncbi.nlm.nih.gov/pubmed/37406019
http://dx.doi.org/10.1371/journal.pone.0288013
_version_ 1785068648541454336
author Liu, Yunxun
Shen, Bingbing
Huang, Ting
Wang, Jianguo
Jiang, Jianxin
author_facet Liu, Yunxun
Shen, Bingbing
Huang, Ting
Wang, Jianguo
Jiang, Jianxin
author_sort Liu, Yunxun
collection PubMed
description BACKGROUND: Previous studies have shown that the hypoxia microenvironment significantly impacted tumor progression. However, the clinical prognostic value of hypoxia-related risk signatures and their effects on the tumor microenvironment (TME) in hepatocellular carcinoma (HCC) remains hazy. This study aimed to conduct novel hypoxia-related prognostic signatures and improve HCC prognosis and treatment. METHODS: Differentially expressed hypoxia-related genes (HGs) were identified with the gene set enrichment analysis (GSEA). Univariate Cox regression was utilized to generate the tumor hypoxia-related prognostic signature, which consists of 3 HGs, based on the least absolute shrinkage and selection operator (LASSO) algorithm. Then the risk score for each patient was performed. The prognostic signature’s independent prognostic usefulness was confirmed, and systematic analyses were done on the relationships between the prognostic signature and immune cell infiltration, somatic cell mutation, medication sensitivity, and putative immunological checkpoints. RESULTS: A prognostic risk model of four HGs (FDPS, SRM, and NDRG1) was constructed and validated in the training, testing, and validation datasets. To determine the model’s performance in patients with HCC, Kaplan–Meier curves and time-dependent receiver operating characteristic (ROC) curves analysis was implemented. According to immune infiltration analysis, the high-risk group had a significant infiltration of CD4+ T cells, M0 macrophages, and dendritic cells (DCs) than those of the low-risk subtype. In addition, the presence of TP53 mutations in the high-risk group was higher, in which LY317615, PF−562271, Pyrimethamine, and Sunitinib were more sensitive. The CD86, LAIR1, and LGALS9 expression were upregulated in the high-risk subtype. CONCLUSIONS: The hypoxia-related risk signature is a reliable predictive model for better clinical management of HCC patients and offers clinicians a holistic viewpoint when determining the diagnosis and course of HCC treatment.
format Online
Article
Text
id pubmed-10321610
institution National Center for Biotechnology Information
language English
publishDate 2023
publisher Public Library of Science
record_format MEDLINE/PubMed
spelling pubmed-103216102023-07-06 Construction and validation of 3-genes hypoxia-related prognostic signature to predict the prognosis and therapeutic response of hepatocellular carcinoma patients Liu, Yunxun Shen, Bingbing Huang, Ting Wang, Jianguo Jiang, Jianxin PLoS One Research Article BACKGROUND: Previous studies have shown that the hypoxia microenvironment significantly impacted tumor progression. However, the clinical prognostic value of hypoxia-related risk signatures and their effects on the tumor microenvironment (TME) in hepatocellular carcinoma (HCC) remains hazy. This study aimed to conduct novel hypoxia-related prognostic signatures and improve HCC prognosis and treatment. METHODS: Differentially expressed hypoxia-related genes (HGs) were identified with the gene set enrichment analysis (GSEA). Univariate Cox regression was utilized to generate the tumor hypoxia-related prognostic signature, which consists of 3 HGs, based on the least absolute shrinkage and selection operator (LASSO) algorithm. Then the risk score for each patient was performed. The prognostic signature’s independent prognostic usefulness was confirmed, and systematic analyses were done on the relationships between the prognostic signature and immune cell infiltration, somatic cell mutation, medication sensitivity, and putative immunological checkpoints. RESULTS: A prognostic risk model of four HGs (FDPS, SRM, and NDRG1) was constructed and validated in the training, testing, and validation datasets. To determine the model’s performance in patients with HCC, Kaplan–Meier curves and time-dependent receiver operating characteristic (ROC) curves analysis was implemented. According to immune infiltration analysis, the high-risk group had a significant infiltration of CD4+ T cells, M0 macrophages, and dendritic cells (DCs) than those of the low-risk subtype. In addition, the presence of TP53 mutations in the high-risk group was higher, in which LY317615, PF−562271, Pyrimethamine, and Sunitinib were more sensitive. The CD86, LAIR1, and LGALS9 expression were upregulated in the high-risk subtype. CONCLUSIONS: The hypoxia-related risk signature is a reliable predictive model for better clinical management of HCC patients and offers clinicians a holistic viewpoint when determining the diagnosis and course of HCC treatment. Public Library of Science 2023-07-05 /pmc/articles/PMC10321610/ /pubmed/37406019 http://dx.doi.org/10.1371/journal.pone.0288013 Text en © 2023 Liu 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, and reproduction in any medium, provided the original author and source are credited.
spellingShingle Research Article
Liu, Yunxun
Shen, Bingbing
Huang, Ting
Wang, Jianguo
Jiang, Jianxin
Construction and validation of 3-genes hypoxia-related prognostic signature to predict the prognosis and therapeutic response of hepatocellular carcinoma patients
title Construction and validation of 3-genes hypoxia-related prognostic signature to predict the prognosis and therapeutic response of hepatocellular carcinoma patients
title_full Construction and validation of 3-genes hypoxia-related prognostic signature to predict the prognosis and therapeutic response of hepatocellular carcinoma patients
title_fullStr Construction and validation of 3-genes hypoxia-related prognostic signature to predict the prognosis and therapeutic response of hepatocellular carcinoma patients
title_full_unstemmed Construction and validation of 3-genes hypoxia-related prognostic signature to predict the prognosis and therapeutic response of hepatocellular carcinoma patients
title_short Construction and validation of 3-genes hypoxia-related prognostic signature to predict the prognosis and therapeutic response of hepatocellular carcinoma patients
title_sort construction and validation of 3-genes hypoxia-related prognostic signature to predict the prognosis and therapeutic response of hepatocellular carcinoma patients
topic Research Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10321610/
https://www.ncbi.nlm.nih.gov/pubmed/37406019
http://dx.doi.org/10.1371/journal.pone.0288013
work_keys_str_mv AT liuyunxun constructionandvalidationof3geneshypoxiarelatedprognosticsignaturetopredicttheprognosisandtherapeuticresponseofhepatocellularcarcinomapatients
AT shenbingbing constructionandvalidationof3geneshypoxiarelatedprognosticsignaturetopredicttheprognosisandtherapeuticresponseofhepatocellularcarcinomapatients
AT huangting constructionandvalidationof3geneshypoxiarelatedprognosticsignaturetopredicttheprognosisandtherapeuticresponseofhepatocellularcarcinomapatients
AT wangjianguo constructionandvalidationof3geneshypoxiarelatedprognosticsignaturetopredicttheprognosisandtherapeuticresponseofhepatocellularcarcinomapatients
AT jiangjianxin constructionandvalidationof3geneshypoxiarelatedprognosticsignaturetopredicttheprognosisandtherapeuticresponseofhepatocellularcarcinomapatients