Evidence map›Paper›PMID 35633444›Full record

ArticleBiochemical genetics2022

Identification of Immune-Related Markers in Hepatocellular Carcinoma Based on Gene Co-expression Network.

Guogang Li, Yang Tian, Zhenzhen Gao, Xi Ma, Chaojie Ren

Abstract read
PubMed Publisher
In one paragraph

Article in Biochemical genetics, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing papers in PubMed
0.5field-weighted citation impact, top 37% 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

1 citing paper in PubMed, 3 citations in OpenAlex.

  1. Article
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

5 authors at 1 institution in 1 country.

Guogang LiDepartment of Hepatobiliary and Pancreatic Surgery, The Second Affiliated Hospital Zhejiang University School of Medicine, No.88 Jiefang Road, Hangzhou, 310009, Zhejiang Province, China. liguogangnag@163.com.ORCID http://orcid.org/0000-0002-3629-6697
Yang TianDepartment of Hepatobiliary and Pancreatic Surgery, The Second Affiliated Hospital Zhejiang University School of Medicine, No.88 Jiefang Road, Hangzhou, 310009, Zhejiang Province, China.
Zhenzhen GaoDepartment of Hepatobiliary and Pancreatic Surgery, The Second Affiliated Hospital Zhejiang University School of Medicine, No.88 Jiefang Road, Hangzhou, 310009, Zhejiang Province, China.
Xi MaDepartment of Hepatobiliary and Pancreatic Surgery, The Second Affiliated Hospital Zhejiang University School of Medicine, No.88 Jiefang Road, Hangzhou, 310009, Zhejiang Province, China.
Chaojie RenDepartment of Hepatobiliary and Pancreatic Surgery, The Second Affiliated Hospital Zhejiang University School of Medicine, No.88 Jiefang Road, Hangzhou, 310009, Zhejiang Province, China.
Second Affiliated Hospital of Zhejiang University · CN

Funding

National Natural Science Foundation 882000619
6 · The paper itself

Abstract

Hepatocellular carcinoma (HCC) is a major cause of cancer-related death throughout the world, with constant increasing morbidity and mortality. Existing studies suggest that immunotherapy is beneficial to the treatment of advanced HCC. At present, it is imperative to identify biomarkers suitable for HCC immunotherapy. In this paper, the mRNA expression data of HCC were downloaded from The Cancer Genome Atlas, and Stromal Score, Immune Score and ESTIMATE Score of each sample were calculated. Weighted gene co-expression network analysis clustered the pretreated genes into eight modules. The brown module that was remarkably associated with Immune Score was identified by module eigengene-immune trait analysis, in which genes were mainly enriched in immune-related pathways. Four hub genes (CCR5, CD53, ITGB2, and TYROBP) related to tumor immunity, were screened out by intramodular gene connectivity combined with protein-protein interaction network topology analysis. Kaplan-Meier survival analysis presented a correlation between high expression of CCR5 and CD53, and better prognoses of HCC patients. TIMER analysis revealed a positive correlation between expression of each hub gene and immune cell infiltration level, and a positive correlation between the expression of each hub gene and the expression of immunosuppressive factors CTLA4 and PDCD1. Gene set enrichment analysis displayed that there was an evident difference in the activation of cytokines and the activation of immune signal transduction-related pathways between high- and low-expression groups of each hub gene. In conclusion, this study identified four potential genetic markers associated with HCC immunity and assessed their association with HCC patient's prognosis and immune microenvironment. The study results are expected to provide theoretical guidance for immunotherapy of HCC patients.

Indexed as

Carcinoma, HepatocellularLiver NeoplasmsBiomarkersBiomarkers, TumorComputational BiologyGene Expression ProfilingGene Expression Regulation, NeoplasticHumansTumor MicroenvironmentBiomarkersBiomarkers, TumorHepatocellular carcinomaImmune traitsImmunosuppressive moleculesPPI networkWGCNA

Identifiers

PMID35633444
OpenAlexW4281631277

What OpenQuestion holds

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Read underepoch 390

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.