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

Coronavirus 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. Relevant 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. The 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. This 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.

Authors

Institutions

Publication Details

Journal
BMC Infectious Diseases
Published
2025-12-17
DOI
https://doi.org/10.1186/s12879-025-11916-0
Primary Topic
Ferroptosis and cancer prognosis
Type
article
Field-Weighted Citation Impact
0.00

Funders

Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

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

Xue Zhou, Qing Ye, Ning Wang, Xue Wang et al.
BMC Infectious Diseases
Ferroptosis and cancer prognosis
article

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

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

Abstract

Coronavirus 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. Relevant 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. The 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. This 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.

BMC Infectious DiseasesVol. 25(1)
Tianjin University (CN), Tianjin Chengjian University (CN), Tianjin Third Central Hospital (CN), Tianjin Infectious Diseases Hospital (CN), Tianjin Vocational Institute (CN), Cell Technology (China) (HK), Tianjin Central Hospital of Gynecology Obstetrics (CN), Tianjin Fire Research Institute (CN), Tianjin haihe hospital (CN), Tianjin Medical University (CN)
Natural Science Foundation of Tianjin City
Openalex Percentile: Top 40%
Ferroptosis and cancer prognosis
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.