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

Authors
  • Zhang, Baohui1
  • Tang, Bufu2
  • Gao, Jianyao3
  • Li, Jiatong4
  • Kong, Lingming5
  • Qin, Ling1
  • 1 China Medical University, No. 77 Puhe Road, Shenyang North New AreaLiaoning Province, Shenyang, 110122, People’s Republic of China , Shenyang (China)
  • 2 Second Affiliated Hospital, Zhejiang University, Hangzhou, 310058, China , Hangzhou (China)
  • 3 the First Affiliated Hospital of China Medical University, Shenyang, China , Shenyang (China)
  • 4 The First Affiliated Hospital of China Medical University, Shenyang, Liaoning, 110001, People’s Republic of China , Shenyang (China)
  • 5 Shengjing Hospital of China Medical University, Shenyang, 110004, China , Shenyang (China)
Type
Published Article
Journal
Journal of Translational Medicine
Publisher
Springer (Biomed Central Ltd.)
Publication Date
Sep 04, 2020
Volume
18
Issue
1
Identifiers
DOI: 10.1186/s12967-020-02492-9
Source
Springer Nature
Keywords
License
Green

Abstract

BackgroundHypoxia 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.MethodsDifferentially 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.ResultsA 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.ConclusionsAltogether, 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.

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