Identifying a Hypoxia-Related Long Non-Coding RNAs Signature to Improve the Prediction of Prognosis and Immunotherapy Response in Hepatocellular Carcinoma

Abstract Background: Both hypoxia and long non-coding RNAs (lncRNAs) contribute to the tumor progression in hepatocellular carcinoma (HCC). We sought to establish a hypoxia-related lncRNA signature and explore its correlation with immunotherapy response in HCC.Materials and Methods: Hypoxia-related...

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Autores principales: Pingfei Tang, Weiming Qu, Taoli Wang, Minji Liu, Dajun Wu, Lin Tan, Hongbing Zhou
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Publicado: Frontiers Media S.A. 2021
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Acceso en línea:https://doaj.org/article/eb0c59614eef4323a33cd0a3ca0516f6
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spelling oai:doaj.org-article:eb0c59614eef4323a33cd0a3ca0516f62021-12-01T17:02:11ZIdentifying a Hypoxia-Related Long Non-Coding RNAs Signature to Improve the Prediction of Prognosis and Immunotherapy Response in Hepatocellular Carcinoma1664-802110.3389/fgene.2021.785185https://doaj.org/article/eb0c59614eef4323a33cd0a3ca0516f62021-11-01T00:00:00Zhttps://www.frontiersin.org/articles/10.3389/fgene.2021.785185/fullhttps://doaj.org/toc/1664-8021Abstract Background: Both hypoxia and long non-coding RNAs (lncRNAs) contribute to the tumor progression in hepatocellular carcinoma (HCC). We sought to establish a hypoxia-related lncRNA signature and explore its correlation with immunotherapy response in HCC.Materials and Methods: Hypoxia-related differentially expressed lncRNAs (HRDELs) were identified by conducting the differential gene expression analyses in GSE155505 and The Cancer Genome Atlas (TCGA)- liver hepatocellular carcinoma (LIHC) datasets. The HRDELs landscape in patients with HCC in TCGA-LIHC was dissected by an unsupervised clustering method. Patients in the TCGA-LIHC cohort were stochastically split into the training and testing dataset. The prognostic signature was developed using LASSO (least absolute shrinkage and selection operator) penalty Cox and multivariable Cox analyses. The tumor immune microenvironment was delineated by the single-sample gene set enrichment analysis (ssGSEA) algorithm. The Tumor Immune Dysfunction and Exclusion (TIDE) algorithm was applied to evaluate the predictive value of the constructed signature in immunotherapeutic responsiveness.Results: A total of 55 HRDELs were identified through integrated bioinformatical analyses in GSE155505 and TCGA-LIHC. Patients in the TCGA-LIHC cohort were categorized into three HRDELs-specific clusters associated with different clinical outcomes. The prognostic signature involving five hypoxia-related lncRNAs (LINC00869, CAHM, RHPN1-AS1, MKLN1-AS, and DUXAP8) was constructed in the training dataset and then validated in the testing dataset and entire TCGA-LIHC cohort. The 5-years AUC of the constructed signature for prognostic prediction reaches 0.705 and is superior to that of age, AJCC stage, and histopathological grade. Patients with high-risk scores consistently had poorer overall survival outcomes than those with low-risk scores irrespective of other clinical parameters status. The low-risk group had more abundance in activated CD8+ T cell and activated B cell and were predicted to be more responsive to immunotherapy and targeted therapy than the high-risk group.Conclusion: We established a reliable hypoxia-related lncRNAs signature that could accurately predict the clinical outcomes of HCC patients and correlate with immunotherapy response and targeted drug sensitivity, providing new insights for immunotherapy and targeted therapy in HCC.Pingfei TangWeiming QuTaoli WangMinji LiuDajun WuLin TanHongbing ZhouFrontiers Media S.A.articlehypoxialncRNA (long non-coding RNA)hepatocellular carcinomaprognostic signaturetumor immune microenvironmentimmunotherapy responseGeneticsQH426-470ENFrontiers in Genetics, Vol 12 (2021)
institution DOAJ
collection DOAJ
language EN
topic hypoxia
lncRNA (long non-coding RNA)
hepatocellular carcinoma
prognostic signature
tumor immune microenvironment
immunotherapy response
Genetics
QH426-470
spellingShingle hypoxia
lncRNA (long non-coding RNA)
hepatocellular carcinoma
prognostic signature
tumor immune microenvironment
immunotherapy response
Genetics
QH426-470
Pingfei Tang
Weiming Qu
Taoli Wang
Minji Liu
Dajun Wu
Lin Tan
Hongbing Zhou
Identifying a Hypoxia-Related Long Non-Coding RNAs Signature to Improve the Prediction of Prognosis and Immunotherapy Response in Hepatocellular Carcinoma
description Abstract Background: Both hypoxia and long non-coding RNAs (lncRNAs) contribute to the tumor progression in hepatocellular carcinoma (HCC). We sought to establish a hypoxia-related lncRNA signature and explore its correlation with immunotherapy response in HCC.Materials and Methods: Hypoxia-related differentially expressed lncRNAs (HRDELs) were identified by conducting the differential gene expression analyses in GSE155505 and The Cancer Genome Atlas (TCGA)- liver hepatocellular carcinoma (LIHC) datasets. The HRDELs landscape in patients with HCC in TCGA-LIHC was dissected by an unsupervised clustering method. Patients in the TCGA-LIHC cohort were stochastically split into the training and testing dataset. The prognostic signature was developed using LASSO (least absolute shrinkage and selection operator) penalty Cox and multivariable Cox analyses. The tumor immune microenvironment was delineated by the single-sample gene set enrichment analysis (ssGSEA) algorithm. The Tumor Immune Dysfunction and Exclusion (TIDE) algorithm was applied to evaluate the predictive value of the constructed signature in immunotherapeutic responsiveness.Results: A total of 55 HRDELs were identified through integrated bioinformatical analyses in GSE155505 and TCGA-LIHC. Patients in the TCGA-LIHC cohort were categorized into three HRDELs-specific clusters associated with different clinical outcomes. The prognostic signature involving five hypoxia-related lncRNAs (LINC00869, CAHM, RHPN1-AS1, MKLN1-AS, and DUXAP8) was constructed in the training dataset and then validated in the testing dataset and entire TCGA-LIHC cohort. The 5-years AUC of the constructed signature for prognostic prediction reaches 0.705 and is superior to that of age, AJCC stage, and histopathological grade. Patients with high-risk scores consistently had poorer overall survival outcomes than those with low-risk scores irrespective of other clinical parameters status. The low-risk group had more abundance in activated CD8+ T cell and activated B cell and were predicted to be more responsive to immunotherapy and targeted therapy than the high-risk group.Conclusion: We established a reliable hypoxia-related lncRNAs signature that could accurately predict the clinical outcomes of HCC patients and correlate with immunotherapy response and targeted drug sensitivity, providing new insights for immunotherapy and targeted therapy in HCC.
format article
author Pingfei Tang
Weiming Qu
Taoli Wang
Minji Liu
Dajun Wu
Lin Tan
Hongbing Zhou
author_facet Pingfei Tang
Weiming Qu
Taoli Wang
Minji Liu
Dajun Wu
Lin Tan
Hongbing Zhou
author_sort Pingfei Tang
title Identifying a Hypoxia-Related Long Non-Coding RNAs Signature to Improve the Prediction of Prognosis and Immunotherapy Response in Hepatocellular Carcinoma
title_short Identifying a Hypoxia-Related Long Non-Coding RNAs Signature to Improve the Prediction of Prognosis and Immunotherapy Response in Hepatocellular Carcinoma
title_full Identifying a Hypoxia-Related Long Non-Coding RNAs Signature to Improve the Prediction of Prognosis and Immunotherapy Response in Hepatocellular Carcinoma
title_fullStr Identifying a Hypoxia-Related Long Non-Coding RNAs Signature to Improve the Prediction of Prognosis and Immunotherapy Response in Hepatocellular Carcinoma
title_full_unstemmed Identifying a Hypoxia-Related Long Non-Coding RNAs Signature to Improve the Prediction of Prognosis and Immunotherapy Response in Hepatocellular Carcinoma
title_sort identifying a hypoxia-related long non-coding rnas signature to improve the prediction of prognosis and immunotherapy response in hepatocellular carcinoma
publisher Frontiers Media S.A.
publishDate 2021
url https://doaj.org/article/eb0c59614eef4323a33cd0a3ca0516f6
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