Evidence map›Paper›PMID 42186138›Full record

ArticleJournal of cellular and molecular medicine2026

Single-Cell Characterization of Terminal States and State-Specific Transcriptional Regulatory Networks in Hepatocellular Carcinoma.

Biaolong Deng, Ke Xu, Yun Zhu, Wenhao Lin, Lang Lu, Tao Yang, Xiaoyan Zhou, Yuanyuan Chen

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

8 authors.

Biaolong DengThe First Affiliated Hospital of Guangzhou Medical University, Guangzhou, China.
Ke XuCollege of Science, Nanjing Agricultural University, Nanjing, China.
Yun ZhuCollege of Science, Nanjing Agricultural University, Nanjing, China.
Wenhao LinCollege of Science, Nanjing Agricultural University, Nanjing, China.
Lang LuCollege of Science, Nanjing Agricultural University, Nanjing, China.
Tao YangCollege of Science, Nanjing Agricultural University, Nanjing, China.
Xiaoyan ZhouCollege of Science, Nanjing Agricultural University, Nanjing, China.
Yuanyuan ChenCollege of Science, Nanjing Agricultural University, Nanjing, China.

Funding

Fundamental Research Funds for the Central Universities YDZX2025015
6 · The paper itself

Abstract

Hepatocellular carcinoma (HCC) exhibits pronounced cellular heterogeneity and dynamic state transitions during tumour progression, yet the emergence of tumour cell states along fate trajectories and their transcriptional regulation remain unclear. Here, we established an integrated framework linking cell fate dynamics with transcriptional regulatory networks using publicly available single-cell RNA sequencing data. Malignant cells were identified by inferred copy number variation, followed by CellRank-based fate inference and SCENIC-based regulatory network reconstruction. We identified three terminal HCC cell states-immune-activated, metabolic, and proliferative hepatocytes-forming a differentiation continuum from stem-like to more mature phenotypes. Each state was governed by a distinct regulatory network with specific core regulators, including IRF3, PPARA, and JUN. Integration with TCGA-LIHC bulk transcriptomic and clinical data revealed that a proliferative state-derived transcriptional signature was associated with poorer overall survival. Together, our study provides a mechanistic framework linking tumour cell fate trajectories, regulatory heterogeneity and clinical outcomes in HCC.

Indexed as

Carcinoma, HepatocellularGene Expression Regulation, NeoplasticGene Regulatory NetworksLiver NeoplasmsSingle-Cell AnalysisCell DifferentiationCell ProliferationGene Expression ProfilingHepatocytesHumansSingle-Cell Gene Expression AnalysisTranscriptomecell fatedifferentiationhepatocellular carcinomatranscriptional regulatory networks

Identifiers

PMID42186138
PMCPMC13240022

What Socratic 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 Socratic graph.