A hypoxia-related signature for clinically predicting diagnosis, prognosis and immune microenvironment of hepatocellular carcinoma patients

Abstract Background Hypoxia plays an indispensable role in the development of hepatocellular carcinoma (HCC). However, there are few studies on the application of hypoxia molecules in the prognosis predicting of HCC. We aim to identify the hypoxia-related genes in HCC and construct reliable models f...

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Main Authors: Baohui Zhang, Bufu Tang, Jianyao Gao, Jiatong Li, Lingming Kong, Ling Qin
Format: Article
Language:English
Published: BMC 2020-09-01
Series:Journal of Translational Medicine
Subjects:
Online Access:http://link.springer.com/article/10.1186/s12967-020-02492-9
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spelling doaj-2dc595512a2c48978b7d55999dae43952020-11-25T03:25:46ZengBMCJournal of Translational Medicine1479-58762020-09-0118111710.1186/s12967-020-02492-9A hypoxia-related signature for clinically predicting diagnosis, prognosis and immune microenvironment of hepatocellular carcinoma patientsBaohui Zhang0Bufu Tang1Jianyao Gao2Jiatong Li3Lingming Kong4Ling Qin5Department of Physiology, School of Life Science, China Medical UniversityDepartment of Radiology, School of Medicine, Second Affiliated Hospital, Zhejiang UniversityDepartment of Radiation Oncology, the First Affiliated Hospital of China Medical UniversityDepartment of Orthopedics, The First Affiliated Hospital of China Medical UniversityDepartment of General Surgery, Shengjing Hospital of China Medical UniversityDepartment of Physiology, School of Life Science, China Medical UniversityAbstract Background Hypoxia plays an indispensable role in the development of hepatocellular carcinoma (HCC). However, there are few studies on the application of hypoxia molecules in the prognosis predicting of HCC. We aim to identify the hypoxia-related genes in HCC and construct reliable models for diagnosis, prognosis and recurrence of HCC patients as well as exploring the potential mechanism. Methods Differentially expressed genes (DEGs) analysis was performed using The Cancer Genome Atlas (TCGA) and Gene Expression Omnibus (GEO) database and four clusters were determined by a consistent clustering analysis. Three DEGs closely related to overall survival (OS) were identified using Cox regression and LASSO analysis. Then the hypoxia-related signature was developed and validated in TCGA and International Cancer Genome Consortium (ICGC) database. The Gene Set Enrichment Analysis (GSEA) was performed to explore signaling pathways regulated by the signature. CIBERSORT was used for estimating the fractions of immune cell types. Results A total of 397 hypoxia-related DEGs in HCC were detected and three genes (PDSS1, CDCA8 and SLC7A11) among them were selected to construct a prognosis, recurrence and diagnosis model. Then patients were divided into high- and low-risk groups. Our hypoxia-related signature was significantly associated with worse prognosis and higher recurrence rate. The diagnostic model also accurately distinguished HCC from normal samples and nodules. Furthermore, the hypoxia-related signature could positively regulate immune response. Meanwhile, the high-risk group had higher fractions of macrophages, B memory cells and follicle-helper T cells, and exhibited higher expression of immunocheckpoints such as PD1and PDL1. Conclusions Altogether, our study showed that hypoxia-related signature is a potential biomarker for diagnosis, prognosis and recurrence of HCC, and it provided an immunological perspective for developing personalized therapies.http://link.springer.com/article/10.1186/s12967-020-02492-9HypoxiaHepatocellular carcinomaPrognosticDiagnosticImmune microenvironment
collection DOAJ
language English
format Article
sources DOAJ
author Baohui Zhang
Bufu Tang
Jianyao Gao
Jiatong Li
Lingming Kong
Ling Qin
spellingShingle Baohui Zhang
Bufu Tang
Jianyao Gao
Jiatong Li
Lingming Kong
Ling Qin
A hypoxia-related signature for clinically predicting diagnosis, prognosis and immune microenvironment of hepatocellular carcinoma patients
Journal of Translational Medicine
Hypoxia
Hepatocellular carcinoma
Prognostic
Diagnostic
Immune microenvironment
author_facet Baohui Zhang
Bufu Tang
Jianyao Gao
Jiatong Li
Lingming Kong
Ling Qin
author_sort Baohui Zhang
title A hypoxia-related signature for clinically predicting diagnosis, prognosis and immune microenvironment of hepatocellular carcinoma patients
title_short A hypoxia-related signature for clinically predicting diagnosis, prognosis and immune microenvironment of hepatocellular carcinoma patients
title_full A hypoxia-related signature for clinically predicting diagnosis, prognosis and immune microenvironment of hepatocellular carcinoma patients
title_fullStr A hypoxia-related signature for clinically predicting diagnosis, prognosis and immune microenvironment of hepatocellular carcinoma patients
title_full_unstemmed A hypoxia-related signature for clinically predicting diagnosis, prognosis and immune microenvironment of hepatocellular carcinoma patients
title_sort hypoxia-related signature for clinically predicting diagnosis, prognosis and immune microenvironment of hepatocellular carcinoma patients
publisher BMC
series Journal of Translational Medicine
issn 1479-5876
publishDate 2020-09-01
description Abstract Background Hypoxia plays an indispensable role in the development of hepatocellular carcinoma (HCC). However, there are few studies on the application of hypoxia molecules in the prognosis predicting of HCC. We aim to identify the hypoxia-related genes in HCC and construct reliable models for diagnosis, prognosis and recurrence of HCC patients as well as exploring the potential mechanism. Methods Differentially expressed genes (DEGs) analysis was performed using The Cancer Genome Atlas (TCGA) and Gene Expression Omnibus (GEO) database and four clusters were determined by a consistent clustering analysis. Three DEGs closely related to overall survival (OS) were identified using Cox regression and LASSO analysis. Then the hypoxia-related signature was developed and validated in TCGA and International Cancer Genome Consortium (ICGC) database. The Gene Set Enrichment Analysis (GSEA) was performed to explore signaling pathways regulated by the signature. CIBERSORT was used for estimating the fractions of immune cell types. Results A total of 397 hypoxia-related DEGs in HCC were detected and three genes (PDSS1, CDCA8 and SLC7A11) among them were selected to construct a prognosis, recurrence and diagnosis model. Then patients were divided into high- and low-risk groups. Our hypoxia-related signature was significantly associated with worse prognosis and higher recurrence rate. The diagnostic model also accurately distinguished HCC from normal samples and nodules. Furthermore, the hypoxia-related signature could positively regulate immune response. Meanwhile, the high-risk group had higher fractions of macrophages, B memory cells and follicle-helper T cells, and exhibited higher expression of immunocheckpoints such as PD1and PDL1. Conclusions Altogether, our study showed that hypoxia-related signature is a potential biomarker for diagnosis, prognosis and recurrence of HCC, and it provided an immunological perspective for developing personalized therapies.
topic Hypoxia
Hepatocellular carcinoma
Prognostic
Diagnostic
Immune microenvironment
url http://link.springer.com/article/10.1186/s12967-020-02492-9
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