Evidence map›Paper›PMID 40424306›Full record

ArticlePloS one2025

Exploring the level of metabolic reprogramming and the role of prognostic factor SF3A3 in hepatocellular carcinoma through integrated single-cell landscape analysis.

Wanshuo Wei, Yuan Gan, Xindan Zhang, Yumo Chen, Zengfeng Huang, Shuhan Wang, Xiaomei Xie, Yongle Li, Pengtao Qin, Lihe Jiang

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

10 authors.

Wanshuo WeiScool of Clinical Medicine, School of Basic Medical Sciences, Youjiang Medical University for Nationalities, Baise, Guangxi Province, P.R. China.
Yuan GanScool of Clinical Medicine, School of Basic Medical Sciences, Youjiang Medical University for Nationalities, Baise, Guangxi Province, P.R. China.
Xindan ZhangScool of Clinical Medicine, School of Basic Medical Sciences, Youjiang Medical University for Nationalities, Baise, Guangxi Province, P.R. China.
Yumo ChenThe First Affiliated Hospital, School of Basic Medical Sciences, Guangxi Medical University, Nanning, Guangxi Province, P.R. China.
Zengfeng HuangThe First Affiliated Hospital, School of Basic Medical Sciences, Guangxi Medical University, Nanning, Guangxi Province, P.R. China.
Shuhan WangScool of Clinical Medicine, School of Basic Medical Sciences, Youjiang Medical University for Nationalities, Baise, Guangxi Province, P.R. China.
Xiaomei XieScool of Clinical Medicine, School of Basic Medical Sciences, Youjiang Medical University for Nationalities, Baise, Guangxi Province, P.R. China.
Yongle LiScool of Clinical Medicine, School of Basic Medical Sciences, Youjiang Medical University for Nationalities, Baise, Guangxi Province, P.R. China.
Pengtao QinScool of Clinical Medicine, School of Basic Medical Sciences, Youjiang Medical University for Nationalities, Baise, Guangxi Province, P.R. China.
Lihe JiangScool of Clinical Medicine, School of Basic Medical Sciences, Youjiang Medical University for Nationalities, Baise, Guangxi Province, P.R. China.ORCID https://orcid.org/0000-0002-9043-3162

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

This study aims to investigate metabolic reprogramming heterogeneity in hepatocellular carcinoma (HCC) cells and identify novel therapeutic targets for HCC treatment. Single-cell RNA sequencing data from public databases were used to analyze the TME of HCC and reveal the characteristics of different cell subsets, including mononuclear phagocytes, epithelial cells, endothelial cells, NK/T cells, B cells, and unknown cells. The analysis revealed that these cell subsets play their own unique roles in tumor progression and immune escape. Analysis of copy number variations (CNVs) was performed on tumor-derived epithelial cells, with the epithelial cells in Cluster 3 subgroup showing the highest CNV levels. Gene Ontology (GO) enrichment analysis revealed that these cell subsets were involved in a variety of biological processes such as immune response, cell communication, and metabolic pathways, which were consistent with their functional roles. Pseudotemporal analysis further delineated the malignant trajectory of HCC cells, with Cluster 3 exhibiting enhanced phosphatidylinositol metabolism, suggesting a critical role for metabolic reprogramming in tumor invasion and proliferation. Furthermore, a diagnostic model incorporating metabolic reprogramming-associated gene signatures was established, which effectively distinguished HCC from normal tissues. Among these signatures, splicing factor 3a subunit 3 (SF3A3) was identified as both diagnostic and independent prognostic biomarker. Mechanistically, SF3A3 knockdown in HCC cell lines significantly suppressed proliferation, migration, PI3K/AKT signaling, and EMT marker expression, thereby demonstrating its role in driving HCC aggressiveness. In conclusion, these findings elucidate novel molecular characteristics of HCC based on metabolic reprogramming, while establishing SF3A3 as a promising multi-faceted target for HCC diagnosis, prognostic assessment, and therapeutic intervention.

Indexed as

Carcinoma, HepatocellularLiver NeoplasmsRNA Splicing FactorsBiomarkers, TumorCell Line, TumorCell ProliferationDNA Copy Number VariationsGene Expression Regulation, NeoplasticHumansMaleMetabolic ReprogrammingPrognosisSingle-Cell AnalysisBiomarkers, TumorRNA Splicing Factors

Identifiers

PMID40424306
PMCPMC12111341

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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.