Evidence map›Paper›PMID 42178613›Full record

ArticleJournal of cellular and molecular medicine2026

Deciphering Angiogenic Drivers in Hepatocellular Carcinoma: From Prognostic Signature Construction to Genistein-Mediated Inhibition.

Hao Zheng, Shengwei Tang, Ruida Shi, Zichuan Yu, Ruiyu Zhang, Xiaoyu Qu, Hao Wan, Chenshuo Fang, Xin Wang, Ye Zhu and 2 more

Abstract read
In one paragraph

Article in Journal of cellular and molecular medicine, 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

12 authors.

Hao ZhengDepartment of Hepatobiliary Surgery III, Guizhou Provincial People's Hospital, Guiyang, China.
Shengwei TangSecond College of Clinical Medicine, Nanchang University, Nanchang, China.
Ruida ShiSecond College of Clinical Medicine, Nanchang University, Nanchang, China.
Zichuan YuSecond College of Clinical Medicine, Nanchang University, Nanchang, China.
Ruiyu ZhangSecond College of Clinical Medicine, Nanchang University, Nanchang, China.
Xiaoyu QuSecond College of Clinical Medicine, Nanchang University, Nanchang, China.
Hao WanSecond College of Clinical Medicine, Nanchang University, Nanchang, China.
Chenshuo FangSecond College of Clinical Medicine, Nanchang University, Nanchang, China.
Xin WangSecond College of Clinical Medicine, Nanchang University, Nanchang, China.
Ye ZhuSecond College of Clinical Medicine, Nanchang University, Nanchang, China.
Da HuangDepartment of Thyroid Surgery, Second Affiliated Hospital of Nanchang University, Nanchang, Jiangxi Province, China.ORCID 0000-0002-1435-0373
Gen ChenDepartment of Hepatobiliary Surgery III, Guizhou Provincial People's Hospital, Guiyang, China.ORCID 0009-0007-5558-2959

Funding

Doctoral Foundation of Guizhou Provincial People's Hospital GZSYBS[2022]05the Science and Technology Foundation of Guizhou Provincial Health Commission gzwkj2023-039the Science and Technology Foundation of Guizhou Provincial Health Commission YKLPGEX202401
6 · The paper itself

Abstract

Hepatocellular carcinoma (HCC) is an aggressive malignancy with poor prognosis and a lack of reliable biomarkers. In this study, we integrated weighted gene co-expression network analysis, machine-learning-based prognosticmodelling, single-cell RNA sequencing, spatial transcriptomics, and molecular docking to identify angiogenesis-related drivers in HCC. SCAF1 was identified as a hub gene and was significantly upregulated in HCC tissues compared with normal liver tissues. High SCAF1 expression was closely associated with advanced clinicopathological features and unfavourable survival outcomes. The prognostic model constructed by machine learning showed robust predictive performance in both training and validation cohorts, and decision curve analysis supported its clinical utility. Single-cell and spatial transcriptomic analyses further suggested that SCAF1 was mainly associated with endothelial and immune-related features of the tumour microenvironment. Functional assays showed that SCAF1 knockdown suppressed HCC cell migration, invasion, VEGFA expression, and angiogenic capacity in vitro. Mechanistically, SCAF1 was negatively correlated with anti-angiogenic chemokines, including CCL19, CCL14, and CCL11, indicating a role in shaping a pro-angiogenic microenvironment. In addition, molecular docking identified genistein as a promising compound with stable binding to SCAF1. Experimental validation showed that genistein reduced SCAF1 and VEGFA expression and inhibited HCC cell proliferation, migration, invasion, and tube formation. Collectively, these findings suggest that SCAF1 is a novel prognostic and angiogenesis-related biomarker in HCC and a potential therapeutic target for genistein-based intervention.

Indexed as

Carcinoma, HepatocellularGenisteinLiver NeoplasmsNeovascularization, PathologicBiomarkers, TumorCell Line, TumorCell MovementCell ProliferationFemaleGene Expression Regulation, NeoplasticHumansMaleMolecular Docking SimulationPrognosisTumor MicroenvironmentBiomarkers, TumorGenisteinangiogenesisbiomarkerchemokinehepatocellular carcinomapharmacology

Identifiers

PMID42178613
PMCPMC13238579

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Registered trials

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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.