Evidence map›Paper›PMID 40386252›Full record

ArticleTranslational cancer research2025

Potential diagnostic marker gene set for non-alcoholic steatohepatitis associated hepatocellular carcinoma with lymphocyte infiltration.

Xueyun Wang, Mengzhou Gao, Zexi Zhang, Xiang Ao, An Luo, Zhenguo Wen, Xingquan Pan, Mengge Sun, Teng Wang, Zhaojun Jia

Abstract read
PubMed Full text at PMC Publisher
In one paragraph

Article in Translational cancer research, 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

10 authors.

Xueyun WangBeijing Key Laboratory of Enze Biomass Fine Chemicals, College of New Materials and Chemical Engineering, Beijing Institute of Petrochemical Technology, Beijing, China.
Mengzhou GaoBeijing Key Laboratory of Enze Biomass Fine Chemicals, College of New Materials and Chemical Engineering, Beijing Institute of Petrochemical Technology, Beijing, China.
Zexi ZhangBeijing Key Laboratory of Enze Biomass Fine Chemicals, College of New Materials and Chemical Engineering, Beijing Institute of Petrochemical Technology, Beijing, China.
Xiang AoSchool of Basic Medicine, Qingdao University, Qingdao, China.
An LuoBeijing Key Laboratory of Enze Biomass Fine Chemicals, College of New Materials and Chemical Engineering, Beijing Institute of Petrochemical Technology, Beijing, China.
Zhenguo WenBeijing Key Laboratory of Enze Biomass Fine Chemicals, College of New Materials and Chemical Engineering, Beijing Institute of Petrochemical Technology, Beijing, China.
Xingquan PanBeijing Key Laboratory of Enze Biomass Fine Chemicals, College of New Materials and Chemical Engineering, Beijing Institute of Petrochemical Technology, Beijing, China.
Mengge SunBeijing Key Laboratory of Enze Biomass Fine Chemicals, College of New Materials and Chemical Engineering, Beijing Institute of Petrochemical Technology, Beijing, China.
Teng WangBeijing Key Laboratory of Enze Biomass Fine Chemicals, College of New Materials and Chemical Engineering, Beijing Institute of Petrochemical Technology, Beijing, China.
Zhaojun JiaBeijing Key Laboratory of Enze Biomass Fine Chemicals, College of New Materials and Chemical Engineering, Beijing Institute of Petrochemical Technology, Beijing, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Background: Non-alcoholic steatohepatitis (NASH), a prominent driver of hepatocellular carcinoma (HCC) besides virus and alcohol, induces a series of complex liver structural and immune microenvironment changes, which make the early diagnosis and treatment of NASH-associated HCC (NASH-HCC) more challenging. This study aims to identify signature genes and explore the role of immune cell infiltration in NASH-HCC to improve early detection and prognosis assessment. Methods: Differential gene and immune cell infiltration are important indicators for predicting the progress of oncology and responsiveness of tumor patients to immunotherapy, usually confirmed through biopsy tests with poor patient compliance. To obtain a highly correlated signature gene set and validate immune cell infiltration status, the GSE164760 and GSE102079 datasets from the Gene Expression Omnibus (GEO) database were analyzed using machine learning algorithms. Feature genes were identified based on differentially expressed genes and key modular genes identified by weighted gene co-expression network analysis (WGCNA). The signature genes were screened using the least absolute shrinkage and selection operator (LASSO), random forest, and support vector machine recursive feature elimination (SVM-RFE) machine learning algorithms. Subsequently, the signature genes were subjected to diagnostic efficacy tests, gene set enrichment analysis, immune cell infiltration assessment and real-time reverse transcription polymerase chain reaction (RT-qPCR) validation. Results: Six signature genes were identified, including C-C motif chemokine ligand 14 ( Conclusions:

Indexed as

hepatocellular carcinoma (HCC)immune cell infiltrationNon-alcoholic steatohepatitis (NASH)signature genesweighted gene co-expression network analysis (WGCNA)

Identifiers

PMID40386252
PMCPMC12079610

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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.