Hypoxia Molecular Characterization in Hepatocellular Carcinoma Identifies One Risk Signature and Two Nomograms for Clinical Management

Hypoxia is a universal feature in the tumor microenvironment (TME). Nonetheless, the heterogeneous hypoxia patterns of TME have still not been elucidated in hepatocellular carcinoma (HCC). Using consensus clustering algorithm and public datasets, we identified heterogeneous hypoxia subtypes. We also...

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Main Authors: Zaoqu Liu, Long Liu, Taoyuan Lu, Libo Wang, Zhaonan Li, Dechao Jiao, Xinwei Han
Format: Article
Language:English
Published: Hindawi Limited 2021-01-01
Series:Journal of Oncology
Online Access:http://dx.doi.org/10.1155/2021/6664386
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spelling doaj-3e8088aa46744b2db2d2345f30eb214c2021-02-15T12:53:05ZengHindawi LimitedJournal of Oncology1687-84501687-84692021-01-01202110.1155/2021/66643866664386Hypoxia Molecular Characterization in Hepatocellular Carcinoma Identifies One Risk Signature and Two Nomograms for Clinical ManagementZaoqu Liu0Long Liu1Taoyuan Lu2Libo Wang3Zhaonan Li4Dechao Jiao5Xinwei Han6Department of Interventional Radiology, The First Affiliated Hospital of Zhengzhou University, Zhengzhou 450052, ChinaDepartment of Hepatobiliary and Pancreatic Surgery, The First Affiliated Hospital of Zhengzhou University, Zhengzhou 450052, ChinaDepartment of Cerebrovascular Disease, Zhengzhou University People’s Hospital, Zhengzhou 450003, ChinaDepartment of Hepatobiliary and Pancreatic Surgery, The First Affiliated Hospital of Zhengzhou University, Zhengzhou 450052, ChinaDepartment of Interventional Radiology, The First Affiliated Hospital of Zhengzhou University, Zhengzhou 450052, ChinaDepartment of Interventional Radiology, The First Affiliated Hospital of Zhengzhou University, Zhengzhou 450052, ChinaDepartment of Interventional Radiology, The First Affiliated Hospital of Zhengzhou University, Zhengzhou 450052, ChinaHypoxia is a universal feature in the tumor microenvironment (TME). Nonetheless, the heterogeneous hypoxia patterns of TME have still not been elucidated in hepatocellular carcinoma (HCC). Using consensus clustering algorithm and public datasets, we identified heterogeneous hypoxia subtypes. We also revealed the specific biological and clinical characteristics via bioinformatic methods. The principal component analysis algorithm was employed to develop a hypoxia-associated risk score (HARS). We identified the two hypoxia subtypes: low hypoxia pattern (C1) and high hypoxia pattern (C2). C1 was less sensitive to immunotherapy compared to C2, consistent with the lack of immune cells and immune checkpoints (ICPs) in C1, whereas C2 was the opposite. C2 displayed worse prognosis and higher sensitivity to obatoclax relative to C1, while C1 was more sensitive to sorafenib. The two subtypes also demonstrated subtype-specific genomic variations including mutation, copy number alteration, and methylation. Moreover, we developed and validated a risk signature: HARS, which had excellent performance for predicting prognosis and immunotherapy. We revealed two hypoxia subtypes with distinct biological and clinical characteristics in HCC, which enhanced the understanding of hypoxia pattern. The risk signature was a promising biomarker for predicting prognosis and immunotherapy.http://dx.doi.org/10.1155/2021/6664386
collection DOAJ
language English
format Article
sources DOAJ
author Zaoqu Liu
Long Liu
Taoyuan Lu
Libo Wang
Zhaonan Li
Dechao Jiao
Xinwei Han
spellingShingle Zaoqu Liu
Long Liu
Taoyuan Lu
Libo Wang
Zhaonan Li
Dechao Jiao
Xinwei Han
Hypoxia Molecular Characterization in Hepatocellular Carcinoma Identifies One Risk Signature and Two Nomograms for Clinical Management
Journal of Oncology
author_facet Zaoqu Liu
Long Liu
Taoyuan Lu
Libo Wang
Zhaonan Li
Dechao Jiao
Xinwei Han
author_sort Zaoqu Liu
title Hypoxia Molecular Characterization in Hepatocellular Carcinoma Identifies One Risk Signature and Two Nomograms for Clinical Management
title_short Hypoxia Molecular Characterization in Hepatocellular Carcinoma Identifies One Risk Signature and Two Nomograms for Clinical Management
title_full Hypoxia Molecular Characterization in Hepatocellular Carcinoma Identifies One Risk Signature and Two Nomograms for Clinical Management
title_fullStr Hypoxia Molecular Characterization in Hepatocellular Carcinoma Identifies One Risk Signature and Two Nomograms for Clinical Management
title_full_unstemmed Hypoxia Molecular Characterization in Hepatocellular Carcinoma Identifies One Risk Signature and Two Nomograms for Clinical Management
title_sort hypoxia molecular characterization in hepatocellular carcinoma identifies one risk signature and two nomograms for clinical management
publisher Hindawi Limited
series Journal of Oncology
issn 1687-8450
1687-8469
publishDate 2021-01-01
description Hypoxia is a universal feature in the tumor microenvironment (TME). Nonetheless, the heterogeneous hypoxia patterns of TME have still not been elucidated in hepatocellular carcinoma (HCC). Using consensus clustering algorithm and public datasets, we identified heterogeneous hypoxia subtypes. We also revealed the specific biological and clinical characteristics via bioinformatic methods. The principal component analysis algorithm was employed to develop a hypoxia-associated risk score (HARS). We identified the two hypoxia subtypes: low hypoxia pattern (C1) and high hypoxia pattern (C2). C1 was less sensitive to immunotherapy compared to C2, consistent with the lack of immune cells and immune checkpoints (ICPs) in C1, whereas C2 was the opposite. C2 displayed worse prognosis and higher sensitivity to obatoclax relative to C1, while C1 was more sensitive to sorafenib. The two subtypes also demonstrated subtype-specific genomic variations including mutation, copy number alteration, and methylation. Moreover, we developed and validated a risk signature: HARS, which had excellent performance for predicting prognosis and immunotherapy. We revealed two hypoxia subtypes with distinct biological and clinical characteristics in HCC, which enhanced the understanding of hypoxia pattern. The risk signature was a promising biomarker for predicting prognosis and immunotherapy.
url http://dx.doi.org/10.1155/2021/6664386
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