Evidence map›Paper›PMID 41408605›Full record

ArticleBMC infectious diseases2025

Gene signatures and networks: linking COVID-19 to liver cirrhosis and hepatocellular carcinoma.

Ning Wang, Xue Wang, Xue Zhou, Guoyue Yang, Qing Ye

Abstract read
In one paragraph

Article in BMC infectious diseases, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing papers in PubMed
–field-weighted citation impact
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

0 citing papers in PubMed.

No citing paper in PubMed yet.

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.

Ning Wang *Department of Gastroenterology and Hepatology, Central Hospital, Tianjin University, 83 Jintang Road, Hedong District, Tianjin, 300170, China. wxxwjy@yeah.net.ORCID http://orcid.org/0000-0003-3103-4636
Xue Wang *Tianjin Key Laboratory of Extracorporeal Life Support for Critical Diseases, Tianjin, 300170, China.
Xue ZhouDepartment of Nephrology, Haihe Hospital, Tianjin University, Tianjin, 300350, China.ORCID http://orcid.org/0000-0002-3675-9479
Guoyue YangTianjin Key Laboratory of Extracorporeal Life Support for Critical Diseases, Tianjin, 300170, China. 24592453@qq.com.ORCID http://orcid.org/0000-0001-7877-6747
Qing YeDepartment of Gastroenterology and Hepatology, Central Hospital, Tianjin University, 83 Jintang Road, Hedong District, Tianjin, 300170, China. yeqing022@163.com.

Funding

Natural Science Foundation of Tianjin City 22JCQNJC00800Tianjin Health Commission of Integrated traditional Chinese and western medicine Research Project 2023180Tianjin Health Research Project TJWJ2022QN076
6 · The paper itself

Abstract

backgroundCoronavirus disease 2019 (COVID-19) outbreak has widespread impacts on the patients with pre-existing conditions. It is well-established that liver cirrhosis (LC) is a significant risk factor in the etiopathogenesis of hepatocellular carcinoma (HCC). This study was undertaken to investigate the potential gene signatures and the gene regulatory networks between COVID-19 and LC-HCC.

methodsRelevant gene signatures were identified through the shared differentially expressed genes (DEGs) based on COVID-19 and LC-HCC utilizing the bioinformatics analysis. Subsequently, the gene functional enrichment analysis (including Kyoto encyclopedia of genes and genomes (KEGG) and Gene Ontology (GO)) and protein-protein interaction (PPI) network were performed to identify the hub gene as the key biomarker. Finally, receiver operating characteristic (ROC) analysis, along with biological function and gene expression regulatory network analyses were systematically performed.

resultsThe study successfully identified 78 common candidate gene signatures distinguishing COVID-19 from liver cirrhosis-hepatocellular carcinoma (LC-HCC). Subsequent KEGG and GO enrichment analyses revealed that these gene signatures were predominantly associated with the cell cycle. In constructing the PPI network, the core gene CDK1 was successfully identified based on the ten scoring methods. Furthermore, ROC analysis demonstrated that CDK1 possesses excellent predictive efficacy for both COVID-19 (AUC = 0.955) and LC-HCC (AUC = 0.946) cohorts. Moreover, it was observed that HCC patients with elevated CDK1 expression had poorer prognoses. Finally, the comprehensive gene regulatory networks were established.

conclusionThis study successfully identified the key biomarker and gene regulatory networks between COVID-19 and LC-HCC, thereby contributing to the prediction of clinical outcomes and the identification of novel therapeutic targets.

Indexed as

Carcinoma, HepatocellularCOVID-19Gene Regulatory NetworksLiver CirrhosisLiver NeoplasmsCDC2 Protein KinaseComputational BiologyGene Expression ProfilingHumansProtein Interaction MapsROC CurveSARS-CoV-2TranscriptomeCDC2 Protein KinaseCDK1 protein, humanBiomarkerCOVID-19Differentially expressed genesHepatocellular carcinomaLiver cirrhosis

Identifiers

PMID41408605
PMCPMC12709797

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC-ND
Read underepoch 390

Registered trials

None linked

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.