Evidence map›Paper›PMID 41847220›Full record

ArticleJournal of hepatocellular carcinoma2026

ScRNA-Seq Deciphers an Autocrine EFNA1-EPHA1 Loop That Reprograms the Microenvironment in Hepatocellular Carcinoma.

Yuanhong Chen, Yulian Tang, Yufan Ning, Yang Yang, Rensheng Tian, Yongjiao Mao, Zhiquan Feng, Wenxian Lin, Decai Wang, Xueping Feng

Abstract read
In one paragraph

Article in Journal of hepatocellular carcinoma, 2026. 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

10 authors.

Yuanhong Chen *Department of Pathogenic Biology and Immunology, Youjiang Medical University for Nationalities, Baise, Guangxi Zhuang Autonomous Region, 533000, People's Republic of China.
Yulian Tang *School of Medical Technology and Artificial Intelligence, Youjiang Medical University for Nationalities, Baise, Guangxi Zhuang Autonomous Region, 533000, People's Republic of China.
Yufan NingSchool of Basic Medical Sciences, Youjiang Medical University for Nationalities, Baise, Guangxi Zhuang Autonomous Region, 533000, People's Republic of China.
Yang YangSchool of Basic Medical Sciences, Youjiang Medical University for Nationalities, Baise, Guangxi Zhuang Autonomous Region, 533000, People's Republic of China.
Rensheng TianSchool of Basic Medical Sciences, Youjiang Medical University for Nationalities, Baise, Guangxi Zhuang Autonomous Region, 533000, People's Republic of China.
Yongjiao MaoSchool of Basic Medical Sciences, Youjiang Medical University for Nationalities, Baise, Guangxi Zhuang Autonomous Region, 533000, People's Republic of China.
Zhiquan FengSchool of Basic Medical Sciences, Youjiang Medical University for Nationalities, Baise, Guangxi Zhuang Autonomous Region, 533000, People's Republic of China.ORCID 0009-0003-4051-2369
Wenxian LinInstitute of Cardiovascular Sciences, Guangxi Academy of Medical Sciences & the People's Hospital of Guangxi Zhuang Autonomous Region, Nanning, Guangxi Zhuang Autonomous Region, 533000, People's Republic of China.ORCID 0009-0007-5224-4436
Decai WangLibrary, Youjiang Medical University for Nationalities, Baise, Guangxi Zhuang Autonomous Region, 533000, People's Republic of China.
Xueping FengDepartment of Pathogenic Biology and Immunology, Youjiang Medical University for Nationalities, Baise, Guangxi Zhuang Autonomous Region, 533000, People's Republic of China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Background: Hepatocytes demonstrate significant heterogeneity between normal liver tissue and hepatocellular carcinoma (HCC), with malignant hepatocytes playing a crucial role in remodeling the tumor microenvironment through specific ligand-receptor interactions. However, the mechanisms by which hepatocytes drive HCC progression at the single-cell level remain poorly understood. Methods: We analyzed single-cell RNA sequencing datasets (GSE174748 and GSE166635) from the GEO database using CellChat to decode intercellular communication networks, which specifically revealed enhanced EPHA signaling in HCC hepatocytes and identified EFNA1-EPHA1 as the most prominent ligand-receptor pair. This key finding was validated through immunofluorescence analysis in both clinical HCC tissues and HepG2/LO2 cell lines, and its clinical relevance was assessed using the TCGA-LIHC dataset via UALCAN. Results: Single-cell analysis revealed that HCC hepatocytes act as both senders and receivers of pro-tumorigenic signals, with upregulated expression of malignancy-related genes (AFP, ACSL4, and SERPINA1). CellChat inference demonstrated significantly strengthened outgoing interaction signals from hepatocytes in the HCC microenvironment. The EFNA1-EPHA1 axis was identified as a key mediator of hepatocyte-microenvironment crosstalk, showing marked activation in HCC tissues and high co-expression in HepG2 cells. TCGA analysis confirmed EFNA1 upregulation in HCC, correlating with advanced clinical stage, higher tumor grade, and metastatic events. Conclusion: Our study provides single-cell resolution evidence that malignant hepatocytes promote HCC progression through autocrine and paracrine signaling via the EFNA1-EPHA1 axis, reshaping the tumor microenvironment. These findings delineate a key autocrine-paracrine mechanism in HCC progression and nominate the EFNA1-EPHA1 axis as a promising candidate for therapeutic development.

Indexed as

EFNA1EPHA1HCChepatocyteheterogeneityscRNA-seqTME

Identifiers

PMID41847220
PMCPMC12989684

What Socratic holds

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LicenceCC BY-NC
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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 Socratic graph.