Evidence map›Paper›PMID 32887635›Full record

ArticleJournal of translational medicine2020

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

Baohui Zhang, Bufu Tang, Jianyao Gao, Jiatong Li, Lingming Kong, Ling Qin

Open access · goldAbstract read
In one paragraph

Article in Journal of translational medicine, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 106 papers.

0numbers the graph read from it
0cells of the map it votes in
106citing papers in PubMed
13.4field-weighted citation impact, top 1% of its field
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

106 citing papers in PubMed, 142 citations in OpenAlex.

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46 more citing papers are in PubMed but not listed here.

4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

6 authors at 4 institutions in 1 country.

Baohui ZhangDepartment of Physiology, School of Life Science, China Medical University, No. 77 Puhe Road, Shenyang North New AreaLiaoning Province, Shenyang, 110122, People's Republic of China.
Bufu TangDepartment of Radiology, School of Medicine, Second Affiliated Hospital, Zhejiang University, Hangzhou, 310058, China.
Jianyao GaoDepartment of Radiation Oncology, the First Affiliated Hospital of China Medical University, Shenyang, China.
Jiatong LiDepartment of Orthopedics, The First Affiliated Hospital of China Medical University, Shenyang, 110001, Liaoning, People's Republic of China.
Lingming KongDepartment of General Surgery, Shengjing Hospital of China Medical University, Shenyang, 110004, China.
Ling QinDepartment of Physiology, School of Life Science, China Medical University, No. 77 Puhe Road, Shenyang North New AreaLiaoning Province, Shenyang, 110122, People's Republic of China. qinlingling@yahoo.com.ORCID 0000-0001-8717-3833
China Medical University · CNFirst Hospital of China Medical University · CNSecond Affiliated Hospital of Zhejiang University · CNShenyang Medical College · CN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

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.

Indexed as

Carcinoma, HepatocellularLiver NeoplasmsBiomarkers, TumorGene Expression ProfilingGene Expression Regulation, NeoplasticHumansHypoxiaKaplan-Meier EstimateNeoplasm Recurrence, LocalPrognosisTumor MicroenvironmentBiomarkers, TumorDiagnosticHepatocellular carcinomaHypoxiaImmune microenvironmentPrognostic

Identifiers

PMID32887635
PMCPMC7487492
OpenAlexW3083391098

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Registered trials

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.