Cargando…

Identification of lipid metabolism-associated genes as prognostic biomarkers based on the immune microenvironment in hepatocellular carcinoma

Lipid metabolism has been associated with progression of various cancers. However, the underlying mechanisms of the impact of lipid metabolism-associated genes (LMAGs) on the tumor immune microenvironment have not been well-elucidated. This study aimed to determine the effects of lipid metabolism on...

Descripción completa

Detalles Bibliográficos
Autores principales: Gu, Xiangqian, Jiang, Chenshan, Zhao, Jianguo, Qiao, Qian, Wu, Mingyu, Cai, Bing
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Frontiers Media S.A. 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9622944/
https://www.ncbi.nlm.nih.gov/pubmed/36330335
http://dx.doi.org/10.3389/fcell.2022.883059
_version_ 1784821885694902272
author Gu, Xiangqian
Jiang, Chenshan
Zhao, Jianguo
Qiao, Qian
Wu, Mingyu
Cai, Bing
author_facet Gu, Xiangqian
Jiang, Chenshan
Zhao, Jianguo
Qiao, Qian
Wu, Mingyu
Cai, Bing
author_sort Gu, Xiangqian
collection PubMed
description Lipid metabolism has been associated with progression of various cancers. However, the underlying mechanisms of the impact of lipid metabolism-associated genes (LMAGs) on the tumor immune microenvironment have not been well-elucidated. This study aimed to determine the effects of lipid metabolism on the progression and development of hepatocellular carcinoma (HCC). Expression profiles and clinical data of 371 and 231 patients with HCC were obtained from the TCGA and Internal Cancer Genome Consortium (ICGC) databases, respectively. Using Cox regression and LASSO regression analyses, a prognostic risk model was constructed based on the LMAG data. The tumor mutation burden (TMB), immune cell infiltration levels, and immune response checkpoints of the identified risk groups were determined and compared. A total of two clusters were identified based on the LMAG expression, showing significant differences in tumor stage and immune cell infiltration. A prognostic risk model based on four LMAGs was constructed and proven to have a significant prognostic value. The 1-, 3-, and 5-year survival rates in the high-risk group were 62.2%, 20.5%, and 8.1%, respectively, whereas those in the low-risk group were 78.9%, 28.1%, and 13.5%, respectively. The survival differences between the two risk groups were likely associated with TP53 mutation status, TMB score, degree of immunocyte infiltration, and immune checkpoint level. Likewise, the expression level of every LMAG included in the model had the same effect on the overall survival and immune cell infiltration levels. More importantly, the prognostic value of the signature was verified in an independent ICGC cohort. Thus, the expression levels of LMAGs are closely related to the tumor microenvironment in HCC and may serve as promising biological indicators for prognosis and immune therapy in patients with HCC.
format Online
Article
Text
id pubmed-9622944
institution National Center for Biotechnology Information
language English
publishDate 2022
publisher Frontiers Media S.A.
record_format MEDLINE/PubMed
spelling pubmed-96229442022-11-02 Identification of lipid metabolism-associated genes as prognostic biomarkers based on the immune microenvironment in hepatocellular carcinoma Gu, Xiangqian Jiang, Chenshan Zhao, Jianguo Qiao, Qian Wu, Mingyu Cai, Bing Front Cell Dev Biol Cell and Developmental Biology Lipid metabolism has been associated with progression of various cancers. However, the underlying mechanisms of the impact of lipid metabolism-associated genes (LMAGs) on the tumor immune microenvironment have not been well-elucidated. This study aimed to determine the effects of lipid metabolism on the progression and development of hepatocellular carcinoma (HCC). Expression profiles and clinical data of 371 and 231 patients with HCC were obtained from the TCGA and Internal Cancer Genome Consortium (ICGC) databases, respectively. Using Cox regression and LASSO regression analyses, a prognostic risk model was constructed based on the LMAG data. The tumor mutation burden (TMB), immune cell infiltration levels, and immune response checkpoints of the identified risk groups were determined and compared. A total of two clusters were identified based on the LMAG expression, showing significant differences in tumor stage and immune cell infiltration. A prognostic risk model based on four LMAGs was constructed and proven to have a significant prognostic value. The 1-, 3-, and 5-year survival rates in the high-risk group were 62.2%, 20.5%, and 8.1%, respectively, whereas those in the low-risk group were 78.9%, 28.1%, and 13.5%, respectively. The survival differences between the two risk groups were likely associated with TP53 mutation status, TMB score, degree of immunocyte infiltration, and immune checkpoint level. Likewise, the expression level of every LMAG included in the model had the same effect on the overall survival and immune cell infiltration levels. More importantly, the prognostic value of the signature was verified in an independent ICGC cohort. Thus, the expression levels of LMAGs are closely related to the tumor microenvironment in HCC and may serve as promising biological indicators for prognosis and immune therapy in patients with HCC. Frontiers Media S.A. 2022-10-18 /pmc/articles/PMC9622944/ /pubmed/36330335 http://dx.doi.org/10.3389/fcell.2022.883059 Text en Copyright © 2022 Gu, Jiang, Zhao, Qiao, Wu and Cai. https://creativecommons.org/licenses/by/4.0/This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.
spellingShingle Cell and Developmental Biology
Gu, Xiangqian
Jiang, Chenshan
Zhao, Jianguo
Qiao, Qian
Wu, Mingyu
Cai, Bing
Identification of lipid metabolism-associated genes as prognostic biomarkers based on the immune microenvironment in hepatocellular carcinoma
title Identification of lipid metabolism-associated genes as prognostic biomarkers based on the immune microenvironment in hepatocellular carcinoma
title_full Identification of lipid metabolism-associated genes as prognostic biomarkers based on the immune microenvironment in hepatocellular carcinoma
title_fullStr Identification of lipid metabolism-associated genes as prognostic biomarkers based on the immune microenvironment in hepatocellular carcinoma
title_full_unstemmed Identification of lipid metabolism-associated genes as prognostic biomarkers based on the immune microenvironment in hepatocellular carcinoma
title_short Identification of lipid metabolism-associated genes as prognostic biomarkers based on the immune microenvironment in hepatocellular carcinoma
title_sort identification of lipid metabolism-associated genes as prognostic biomarkers based on the immune microenvironment in hepatocellular carcinoma
topic Cell and Developmental Biology
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9622944/
https://www.ncbi.nlm.nih.gov/pubmed/36330335
http://dx.doi.org/10.3389/fcell.2022.883059
work_keys_str_mv AT guxiangqian identificationoflipidmetabolismassociatedgenesasprognosticbiomarkersbasedontheimmunemicroenvironmentinhepatocellularcarcinoma
AT jiangchenshan identificationoflipidmetabolismassociatedgenesasprognosticbiomarkersbasedontheimmunemicroenvironmentinhepatocellularcarcinoma
AT zhaojianguo identificationoflipidmetabolismassociatedgenesasprognosticbiomarkersbasedontheimmunemicroenvironmentinhepatocellularcarcinoma
AT qiaoqian identificationoflipidmetabolismassociatedgenesasprognosticbiomarkersbasedontheimmunemicroenvironmentinhepatocellularcarcinoma
AT wumingyu identificationoflipidmetabolismassociatedgenesasprognosticbiomarkersbasedontheimmunemicroenvironmentinhepatocellularcarcinoma
AT caibing identificationoflipidmetabolismassociatedgenesasprognosticbiomarkersbasedontheimmunemicroenvironmentinhepatocellularcarcinoma