Evidence map›Paper›PMID 41145553›Full record

ArticleScientific reports2025

Identification of key biomarkers associated with necroptosis and immune infiltration in hepatitis B virus-related acute-on-chronic liver failure.

Chuangjie Cao, Dan Luo, Xia Xie, Chengyun Dou

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In one paragraph

Article in Scientific reports, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing 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

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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

2 citing papers in PubMed.

  1. Review
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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

4 authors.

Chuangjie CaoDepartment of Pathology, Hengyang Medical School, The First Affiliated Hospital of University of South China, University of South China, Hengyang, 421001, Hunan Province, China.
Dan LuoDepartment of Infectious Diseases, Hengyang Medical School, The First Affiliated Hospital of University of South China, University of South China, 69 Chuanshan Road, Hengyang, 421001, Hunan, China.
Xia XieDepartment of Infectious Diseases, Hengyang Medical School, The First Affiliated Hospital of University of South China, University of South China, 69 Chuanshan Road, Hengyang, 421001, Hunan, China.
Chengyun DouDepartment of Infectious Diseases, Hengyang Medical School, The First Affiliated Hospital of University of South China, University of South China, 69 Chuanshan Road, Hengyang, 421001, Hunan, China. ashleydou@163.com.

Funding

Provincial Natural Science Foundation of Hunan 2025JJ70165Provincial Natural Science Foundation of Hunan 2025JJ70166
6 · The paper itself

Abstract

Hepatitis B virus-related acute-on-chronic liver failure (ACHBLF) is a severe condition associated with short-term mortality without liver transplantation. Substantial evidence indicates that necroptosis and immune infiltration play critical roles in ACHBLF development. Therefore, the identification of necroptosis-related biomarkers may be beneficial for prognostic evaluations and may shed light on potential therapeutic targets for ACHBLF. In this study, we used integrated bioinformatics analysis and machine learning algorithms to investigate the correlation between necroptosis and immune infiltration using peripheral blood mononuclear cells from ACHBLF patients. First, after GSE168048 and GSE248217 were obtained from the Gene Expression Omnibus (GEO) database, differentially expressed genes (DEGs) between ACHBLF patients and normal controls were identified. With the help of the weighted gene coexpression network, 211 necroptosis-related DEGs were identified by intersecting the DEGs with necroptosis-related genes (NRGs). The functional characterization of these NRG-related DEGs was subsequently performed using GO, KEGG, and gene set enrichment analysis. Hub genes were identified through the integration of LASSO regression, support vector machines recursive feature elimination, and random forest. Immune-related functions were explored by analyzing the correlations between hub gene expression and immune cells infiltration. Furthermore, mRNA-miRNA-lncRNA interaction network, RNA-binding proteins (RBPs) and transcription factors were predicted using the miRDB, starBase and hTFtarget databases. Finally, target drugs were predicted using a connectivity map. A total of 7461 DEGs were identified between the ACHBLF and normal groups; 3123 genes were upregulated and 4338 genes were downregulated. A total of 211 NRG-related DEGs and 5 hub genes (FCRL3, CDC14A, KLHL22, RALY, and MAP4K1) were obtained. The hub genes were enriched in the T cell receptor signaling pathway, ubiquitin-mediated proteolysis, and the MAPK signaling pathway and were correlated with immune cell infiltration. A lncRNA XIST-miR-424-5p-CDC14A regulatory network was constructed, and 20RBPs and 2 transcription factors (GATA1 and CEBPB) were identified. In addition, 10 candidate drugs were predicted to target MAP4K1. The 5 hub genes could serve as biomarkers for predicting the prognosis of ACHBLF patients and provide clues for new potential therapeutic targets.

Indexed as

Acute-On-Chronic Liver FailureBiomarkersHepatitis BHepatitis B virusNecroptosisComputational BiologyGene Expression ProfilingGene Expression RegulationGene Regulatory NetworksHumansMicroRNAsBiomarkersMicroRNAsAcute-on-chronic hepatitis b liver failureBioinformaticsImmune infiltrationMachine learningNecroptosis

Identifiers

PMID41145553
PMCPMC12559277

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