Evidence map›Paper›PMID 33505422›Full record

ArticleFrontiers in genetics2020

Identification of Hub Genes Associated With Immune Infiltration and Predict Prognosis in Hepatocellular Carcinoma via Bioinformatics Approaches.

Huaping Chen, Junrong Wu, Liuyi Lu, Zuojian Hu, Xi Li, Li Huang, Xiaolian Zhang, Mingxing Chen, Xue Qin, Li Xie

Open access · goldAbstract read
In one paragraph

Article in Frontiers in genetics, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 26 papers.

0numbers the graph read from it
0cells of the map it votes in
26citing papers in PubMed
4.8field-weighted citation impact, top 4% 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

26 citing papers in PubMed, 39 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

10 authors at 3 institutions in 1 country.

Huaping ChenDepartment of Clinical Laboratory, First Affiliated Hospital of Guangxi Medical University, Nanning, China.
Junrong WuDepartment of Clinical Laboratory, Affiliated Tumor Hospital of Guangxi Medical University, Nanning, China.
Liuyi LuDepartment of Clinical Laboratory, First Affiliated Hospital of Guangxi Medical University, Nanning, China.
Zuojian HuDepartment of Clinical Laboratory, First Affiliated Hospital of Guangxi Medical University, Nanning, China.
Xi LiDepartment of Clinical Laboratory, First Affiliated Hospital of Guangxi Medical University, Nanning, China.
Li HuangDepartment of Clinical Laboratory, First Affiliated Hospital of Guangxi Medical University, Nanning, China.
Xiaolian ZhangDepartment of Clinical Laboratory, First Affiliated Hospital of Guangxi Medical University, Nanning, China.
Mingxing ChenDepartment of Clinical Laboratory, First Affiliated Hospital of Guangxi Medical University, Nanning, China.
Xue QinDepartment of Clinical Laboratory, First Affiliated Hospital of Guangxi Medical University, Nanning, China.
Li XieDepartment of Clinical Laboratory, Second Affiliated Hospital of Guangxi Medical University, Nanning, China.
First Affiliated Hospital of GuangXi Medical University · CNGuangxi Medical University · CNTumor Hospital of Guangxi Medical University · CN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

aimsIn the cancer-related research field, there is currently a major need for a greater number of valuable biomarkers to predict the prognosis of hepatocellular carcinoma (HCC). In this study, we aimed to screen hub genes related to immune cell infiltration and explore their prognostic value for HCC.

methodsWe analyzed five datasets (GSE46408, GSE57957, GSE74656, GSE76427, and GSE87630) from the Gene Expression Omnibus database to screen the differentially expressed genes (DEGs). A protein-protein interaction network of the DEGs was constructed using the Search Tool for the Retrieval of Interacting Genes; then, the hub genes were identified. Functional enrichment of the genes was performed on the Metascape website. Next, the expression of these hub genes was validated in several databases, including Oncomine, Gene Expression Profiling Interactive Analysis 2 (GEPIA2), and Human Protein Atlas. We explored the correlations between the hub genes and infiltrated immune cells in the TIMER2.0 database. The survival curves were generated in GEPIA2, and the univariate and multivariate Cox regression analyses were performed using TIMER2.0.

resultsThe top ten hub genes [DNA topoisomerase II alpha (

conclusionIn sum, these hub genes (

Indexed as

biomarkerhepatocellular carcinomaimmune infiltrationprognosistumor-associated macrophage

Identifiers

PMID33505422
PMCPMC7831279
OpenAlexW3120983292

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.