Evidence map›Paper›PMID 36353638›Full record

ArticleFrontiers in immunology2022

A novel risk score based on immune-related genes for hepatocellular carcinoma as a reliable prognostic biomarker and correlated with immune infiltration.

Meiying Long, Zihan Zhou, Xueyan Wei, Qiuling Lin, Moqin Qiu, Yunxiang Zhou, Peiqin Chen, Yanji Jiang, Qiuping Wen, Yingchun Liu and 3 more

Open access · goldAbstract read
In one paragraph

Article in Frontiers in immunology, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 15 papers.

0numbers the graph read from it
0cells of the map it votes in
15citing papers in PubMed
2.9field-weighted citation impact, top 8% 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

15 citing papers in PubMed, 20 citations in OpenAlex.

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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

13 authors at 2 institutions in 2 countries.

Meiying LongDepartment of Experimental Research, Guangxi Medical University Cancer Hospital, Nanning, Guangxi, China.
Zihan ZhouDepartment of Cancer Prevention and Control, Guangxi Medical University Cancer Hospital, Nanning, Guangxi, China.
Xueyan WeiDepartment of Epidemiology and Health Statistics, School of Public Health, Guangxi Medical University, Nanning, Guangxi, China.
Qiuling LinDepartment of Clinical Research, Guangxi Medical University Cancer Hospital, Nanning, Guangxi, China.
Moqin QiuDepartment of Respiratory Oncology, Guangxi Medical University Cancer Hospital, Nanning, Guangxi, China.
Yunxiang ZhouDepartment of Epidemiology and Health Statistics, School of Public Health, Guangxi Medical University, Nanning, Guangxi, China.
Peiqin ChenDepartment of Epidemiology and Health Statistics, School of Public Health, Guangxi Medical University, Nanning, Guangxi, China.
Yanji JiangScientific Research Department, Guangxi Medical University Cancer Hospital, Nanning, Guangxi, China.
Qiuping WenDepartment of Experimental Research, Guangxi Medical University Cancer Hospital, Nanning, Guangxi, China.
Yingchun LiuDepartment of Experimental Research, Guangxi Medical University Cancer Hospital, Nanning, Guangxi, China.
Runwei LiDepartment of Environmental and Occupational Health, School of Public Health, Indiana University, Bloomington, IN, United States.
Xianguo ZhouDepartment of Experimental Research, Guangxi Medical University Cancer Hospital, Nanning, Guangxi, China.
Hongping YuDepartment of Experimental Research, Guangxi Medical University Cancer Hospital, Nanning, Guangxi, China.
Guangxi Medical University · CNIndiana University Bloomington · US

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Background: Immunological-related genes (IRGs) play a critical role in the immune microenvironment of tumors. Our study aimed to develop an IRG-based survival prediction model for hepatocellular carcinoma (HCC) patients and to investigate the impact of IRGs on the immune microenvironment. Methods: Differentially expressed IRGs were obtained from The Genomic Data Commons Data Portal (TCGA) and the immunology database and analysis portal (ImmPort). The univariate Cox regression was used to identify the IRGs linked to overall survival (OS), and a Lasso-regularized Cox proportional hazard model was constructed. The International Cancer Genome Consortium (ICGC) database was used to verify the prediction model. ESTIMATE and CIBERSORT were used to estimate immune cell infiltration in the tumor immune microenvironment (TIME). RNA sequencing was performed on HCC tissue specimens to confirm mRNA expression. Results: A total of 401 differentially expressed IRGs were identified, and 63 IRGs were found related to OS on the 237 up-regulated IRGs by univariate Cox regression analyses. Finally, five IRGs were selected by the LASSO Cox model, including Conclusion: We established and verified a new prognosis model for HCC patients based on survival-related IRGs, and the signature could provide new insights into the prognosis of HCC.

Indexed as

Carcinoma, HepatocellularLiver NeoplasmsBiomarkers, TumorCarrier ProteinsGene Expression Regulation, NeoplasticHistocompatibility Antigens Class IHumansMembrane ProteinsPrognosisRisk FactorsTumor MicroenvironmentBiomarkers, TumorCarrier ProteinsHistocompatibility Antigens Class IMembrane ProteinsRAET1E protein, humanhepatocellular carcinomaimmune infiltrationimmune-related genesprognosis modelrisk score

Identifiers

PMID36353638
PMCPMC9637590
OpenAlexW4307270156

What OpenQuestion holds

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LicenceCC BY
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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.