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Molecular subtypes and a prognostic model for hepatocellular carcinoma based on immune- and immunogenic cell death-related lncRNAs

BACKGROUND: Accumulating evidence shows that immunogenic cell death (ICD) enhances immunotherapy effectiveness. In this study, we aimed to develop a prognostic model combining ICD, immunity, and long non-coding RNA biomarkers for predicting hepatocellular carcinoma (HCC) outcomes. METHODS: Immune- a...

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Autores principales: He, Mingang, Gu, Wenchao, Gao, Yang, Liu, Ying, Liu, Jie, Li, Zengjun
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Frontiers Media S.A. 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9720162/
https://www.ncbi.nlm.nih.gov/pubmed/36479122
http://dx.doi.org/10.3389/fimmu.2022.1043827
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author He, Mingang
Gu, Wenchao
Gao, Yang
Liu, Ying
Liu, Jie
Li, Zengjun
author_facet He, Mingang
Gu, Wenchao
Gao, Yang
Liu, Ying
Liu, Jie
Li, Zengjun
author_sort He, Mingang
collection PubMed
description BACKGROUND: Accumulating evidence shows that immunogenic cell death (ICD) enhances immunotherapy effectiveness. In this study, we aimed to develop a prognostic model combining ICD, immunity, and long non-coding RNA biomarkers for predicting hepatocellular carcinoma (HCC) outcomes. METHODS: Immune- and immunogenic cell death-related lncRNAs (IICDLs) were identified from The Cancer Genome Atlas and Ensembl databases. IICDLs were extracted based on the results of differential expression and univariate Cox analyses and used to generate molecular subtypes using ConsensusClusterPlus. We created a prognostic signature based on IICDLs and a nomogram based on risk scores. Clinical characteristics, immune landscapes, immune checkpoint blocking (ICB) responses, stemness, and chemotherapy responses were also analyzed for different molecular subtypes and risk groups. RESULT: A total of 81 IICDLs were identified, 20 of which were significantly associated with overall survival (OS) in patients with HCC. Cluster analysis divided patients with HCC into two distinct molecular subtypes (C1 and C2), with patients in C1 having a shorter survival time than those in C2. Four IICDLs (TMEM220-AS1, LINC02362, LINC01554, and LINC02499) were selected to develop a prognostic model that was an independent prognostic factor of HCC outcomes. C1 and the high-risk group had worse OS (hazard ratio > 1.5, p < 0.01), higher T stage (p < 0.05), higher clinical stage (p < 0.05), higher pathological grade (p < 0.05), low immune cell infiltration (CD4(+) T cells, B cells, macrophages, neutrophils, and myeloid dendritic cells), low immune checkpoint gene expression, poor response to ICB therapy, and high stemness. Different molecular subtypes and risk groups showed significantly different responses to several chemotherapy drugs, such as doxorubicin (p < 0.001), 5-fluorouracil (p < 0.001), gemcitabine (p < 0.001), and sorafenib (p < 0.01). CONCLUSION: Our study identified molecular subtypes and a prognostic signature based on IICDLs that could help predict the clinical prognosis and treatment response in patients with HCC.
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spelling pubmed-97201622022-12-06 Molecular subtypes and a prognostic model for hepatocellular carcinoma based on immune- and immunogenic cell death-related lncRNAs He, Mingang Gu, Wenchao Gao, Yang Liu, Ying Liu, Jie Li, Zengjun Front Immunol Immunology BACKGROUND: Accumulating evidence shows that immunogenic cell death (ICD) enhances immunotherapy effectiveness. In this study, we aimed to develop a prognostic model combining ICD, immunity, and long non-coding RNA biomarkers for predicting hepatocellular carcinoma (HCC) outcomes. METHODS: Immune- and immunogenic cell death-related lncRNAs (IICDLs) were identified from The Cancer Genome Atlas and Ensembl databases. IICDLs were extracted based on the results of differential expression and univariate Cox analyses and used to generate molecular subtypes using ConsensusClusterPlus. We created a prognostic signature based on IICDLs and a nomogram based on risk scores. Clinical characteristics, immune landscapes, immune checkpoint blocking (ICB) responses, stemness, and chemotherapy responses were also analyzed for different molecular subtypes and risk groups. RESULT: A total of 81 IICDLs were identified, 20 of which were significantly associated with overall survival (OS) in patients with HCC. Cluster analysis divided patients with HCC into two distinct molecular subtypes (C1 and C2), with patients in C1 having a shorter survival time than those in C2. Four IICDLs (TMEM220-AS1, LINC02362, LINC01554, and LINC02499) were selected to develop a prognostic model that was an independent prognostic factor of HCC outcomes. C1 and the high-risk group had worse OS (hazard ratio > 1.5, p < 0.01), higher T stage (p < 0.05), higher clinical stage (p < 0.05), higher pathological grade (p < 0.05), low immune cell infiltration (CD4(+) T cells, B cells, macrophages, neutrophils, and myeloid dendritic cells), low immune checkpoint gene expression, poor response to ICB therapy, and high stemness. Different molecular subtypes and risk groups showed significantly different responses to several chemotherapy drugs, such as doxorubicin (p < 0.001), 5-fluorouracil (p < 0.001), gemcitabine (p < 0.001), and sorafenib (p < 0.01). CONCLUSION: Our study identified molecular subtypes and a prognostic signature based on IICDLs that could help predict the clinical prognosis and treatment response in patients with HCC. Frontiers Media S.A. 2022-11-21 /pmc/articles/PMC9720162/ /pubmed/36479122 http://dx.doi.org/10.3389/fimmu.2022.1043827 Text en Copyright © 2022 He, Gu, Gao, Liu, Liu and Li 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 Immunology
He, Mingang
Gu, Wenchao
Gao, Yang
Liu, Ying
Liu, Jie
Li, Zengjun
Molecular subtypes and a prognostic model for hepatocellular carcinoma based on immune- and immunogenic cell death-related lncRNAs
title Molecular subtypes and a prognostic model for hepatocellular carcinoma based on immune- and immunogenic cell death-related lncRNAs
title_full Molecular subtypes and a prognostic model for hepatocellular carcinoma based on immune- and immunogenic cell death-related lncRNAs
title_fullStr Molecular subtypes and a prognostic model for hepatocellular carcinoma based on immune- and immunogenic cell death-related lncRNAs
title_full_unstemmed Molecular subtypes and a prognostic model for hepatocellular carcinoma based on immune- and immunogenic cell death-related lncRNAs
title_short Molecular subtypes and a prognostic model for hepatocellular carcinoma based on immune- and immunogenic cell death-related lncRNAs
title_sort molecular subtypes and a prognostic model for hepatocellular carcinoma based on immune- and immunogenic cell death-related lncrnas
topic Immunology
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9720162/
https://www.ncbi.nlm.nih.gov/pubmed/36479122
http://dx.doi.org/10.3389/fimmu.2022.1043827
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