Evidence map›Paper›PMID 40465781›Full record

ArticlePloS one2025

Identification of key genes and signaling pathways of liver cancer and model construction for prognosis and diagnosis based on bioinformatics analysis.

Benzun Wei, Yao Zheng, Shuaijun Yu, Aiyun Wang, Xiao Lyu

Abstract read
In one paragraph

Article in PloS one, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing 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

1 citing paper in PubMed.

  1. Article
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.

Benzun WeiDepartment of Hepatobiliary Surgery, Zibo Central Hospital, Zibo, Shandong, China.
Yao ZhengDepartment of Pathology, Zibo Central Hospital, Zibo, Shandong, China.
Shuaijun YuDepartment of Critical Care Medicine, Huantai County Hospital of Traditional Chinese Medicine, Zibo, Shandong, China.
Aiyun WangDepartment of Pathology, Zibo Municipal Hospital, Zibo, Shandong, China.ORCID https://orcid.org/0009-0005-5525-5945
Xiao LyuDepartment of Medical Oncology, Zibo Central Hospital, Zibo, Shandong, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

objectiveThis study aims to identify key genes, biomarkers, and associated signaling pathways involved in liver cancer progression by analyzing differentially expressed genes (DEGs) between normal and cancerous liver tissues, with the goal of establishing diagnostic and prognostic models for liver cancer.

methodsTwo datasets, GSE39791 and GSE84402 from GEO, and clinical data from TCGA were selected. Differentially expressed genes (DEGs) were identified using the "limma" package in R, and volcano plots were generated. Functional enrichment of DEGs was performed with Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) analysis. Logistic regression and multivariate Cox regression models were established for diagnostic and prognostic prediction. The immortalized liver cell line THLE-3 and HepG2 cells were used to verify key gene expression via RT-qPCR and Western blot. HepG2 cells were transfected to up- and down-regulate SNAPC2 expression, and cell proliferation, migration, and apoptosis were assessed using CCK-8, colony formation, scratch, transwell migration assays, and flow cytometry with Annexin V-PE/7-AAD staining. Additionally, Gene Set Enrichment Analysis (GSEA) of SNAPC2 revealed its involvement in cancer-related pathways.

resultsBioinformatics analysis identified 10,961 down-regulated and 3,321 up-regulated genes in the GSE39791 and GSE84402 datasets, and 272 down-regulated and 4,855 up-regulated genes in TCGA data. GO and KEGG analysis revealed 3,820 co-DEGs associated with processes like cell differentiation and morphogenesis. CDCA8, GRPEL2, HAVCR1, MT3, MYCN, NDRG1, PHOSPHO2, SNAPC2, SOCS2, and TXNRD1 were selected to construct prognostic models, and MYCN, NDRG1, TXNRD1, SNAPC2, PHOSPHO2, and CDCA8 for diagnostic models. Western blot validation showed upregulation of CDCA8, GRPEL2, HAVCR1, MYCN, NDRG1, PHOSPHO2, SNAPC2, and TXNRD1 in liver cancer tissues, correlating with poor prognosis. Moreover, reduced SNAPC2 expression in HepG2 cells led to decreased proliferation and migration, and increased apoptosis, suggesting SNAPC2 plays a role in liver cancer progression by promoting cell proliferation and migration.

conclusionCDCA8, GRPEL2, HAVCR1, MT3, MYCN, NDRG1, PHOSPHO2, SNAPC2, SOCS2, TXNRD1 were key genes for liver cancer prognosis and diagnosis. Moreover, lowering SNAPC2 expression could improve the prognosis of liver cancer through decreasing proliferation and migration s and increasing apoptosis of cancer cell.

Indexed as

Carcinoma, HepatocellularComputational BiologyLiver NeoplasmsSignal TransductionApoptosisBiomarkers, TumorCell MovementCell ProliferationDatabases, GeneticGene Expression ProfilingGene Expression Regulation, NeoplasticGene OntologyHep G2 CellsHumansPrognosisBiomarkers, Tumor

Identifiers

PMID40465781
PMCPMC12136465

What OpenQuestion holds

Textmetadata
LicenceCC BY
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.