Evidence map›Paper›PMID 40708676›Full record

ArticleJournal of translational internal medicine2024

A Notch signaling pathway-related gene signature: Characterizing the immune microenvironment and predicting prognosis in hepatocellular carcinoma.

Qingmiao Shi, Shuwen Jiang, Yifan Zeng, Xin Yuan, Yaqi Zhang, Qingfei Chu, Chen Xue, Lanjuan Li

Abstract read
In one paragraph

Article in Journal of translational internal medicine, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 14 papers.

0numbers the graph read from it
0cells of the map it votes in
14citing 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

14 citing papers in PubMed.

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  8. Expression ofInternational journal of molecular sciences · 2026
    Article
  9. Review
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  11. Article
  12. Review
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  14. Notch signaling in cancers: mechanism and potential therapy.Frontiers in cell and developmental biology · 2025
    Review
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.

Qingmiao ShiState Key Laboratory for Diagnosis and Treatment of Infectious Diseases, National Clinical Research Center for Infectious Diseases, National Medical Center for Infectious Diseases, Collaborative Innovation Center for Diagnosis and Treatment of Infectious Diseases, The First Affiliated Hospital, Zhejiang University School of Medicine, Hangzhou 310003, Zhejiang Province, China.
Shuwen JiangState Key Laboratory for Diagnosis and Treatment of Infectious Diseases, National Clinical Research Center for Infectious Diseases, National Medical Center for Infectious Diseases, Collaborative Innovation Center for Diagnosis and Treatment of Infectious Diseases, The First Affiliated Hospital, Zhejiang University School of Medicine, Hangzhou 310003, Zhejiang Province, China.
Yifan ZengState Key Laboratory for Diagnosis and Treatment of Infectious Diseases, National Clinical Research Center for Infectious Diseases, National Medical Center for Infectious Diseases, Collaborative Innovation Center for Diagnosis and Treatment of Infectious Diseases, The First Affiliated Hospital, Zhejiang University School of Medicine, Hangzhou 310003, Zhejiang Province, China.
Xin YuanState Key Laboratory for Diagnosis and Treatment of Infectious Diseases, National Clinical Research Center for Infectious Diseases, National Medical Center for Infectious Diseases, Collaborative Innovation Center for Diagnosis and Treatment of Infectious Diseases, The First Affiliated Hospital, Zhejiang University School of Medicine, Hangzhou 310003, Zhejiang Province, China.
Yaqi ZhangState Key Laboratory for Diagnosis and Treatment of Infectious Diseases, National Clinical Research Center for Infectious Diseases, National Medical Center for Infectious Diseases, Collaborative Innovation Center for Diagnosis and Treatment of Infectious Diseases, The First Affiliated Hospital, Zhejiang University School of Medicine, Hangzhou 310003, Zhejiang Province, China.
Qingfei ChuState Key Laboratory for Diagnosis and Treatment of Infectious Diseases, National Clinical Research Center for Infectious Diseases, National Medical Center for Infectious Diseases, Collaborative Innovation Center for Diagnosis and Treatment of Infectious Diseases, The First Affiliated Hospital, Zhejiang University School of Medicine, Hangzhou 310003, Zhejiang Province, China.
Chen XueState Key Laboratory for Diagnosis and Treatment of Infectious Diseases, National Clinical Research Center for Infectious Diseases, National Medical Center for Infectious Diseases, Collaborative Innovation Center for Diagnosis and Treatment of Infectious Diseases, The First Affiliated Hospital, Zhejiang University School of Medicine, Hangzhou 310003, Zhejiang Province, China.
Lanjuan LiState Key Laboratory for Diagnosis and Treatment of Infectious Diseases, National Clinical Research Center for Infectious Diseases, National Medical Center for Infectious Diseases, Collaborative Innovation Center for Diagnosis and Treatment of Infectious Diseases, The First Affiliated Hospital, Zhejiang University School of Medicine, Hangzhou 310003, Zhejiang Province, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Background and Objectives: Prior studies have highlighted an escalating global burden of hepatocellular carcinoma (HCC). The Notch signaling pathway regulates the initiation and development of HCC and determines the HCC prognosis. Methods: The expression data of genes related to the Notch signaling pathway were acquired from public databases. To filter prognostic gene signatures and establish the risk model, the analyses of consensus clustering, least absolute shrinkage and selection operator (LASSO), and multivariate Cox were conducted. Subsequently, the risk stratification was optimized using a decision tree and nomogram. The immune landscapes were revealed utilizing the single-sample gene set enrichment analysis, and tumor immune dysfunction and exclusion score. Results: According to the mRNA expression profile of Notch signaling pathway-related genes, HCC patients were stratified to three clusters, which have different survival probability and immune infiltration characteristic. Subsequently, we developed a risk model based on five prognostic Notch signaling-related gene signatures (SPP1, SMG5, HMMR, PLOD2, and CFHR4). The model demonstrated an accurate estimation of overall survival, revealing alterations in immune status and immunotherapy sensitivity among HCC patients with different risk scores. Conclusions: This study constructed a Notch signaling pathway-related prognostic model, offering valuable insights for the assessment of immune characteristics and immunotherapy responses in HCC patients.

Indexed as

hepatocellular carcinomaimmune microenvironmentNotch signaling pathwayprognosisrisk model

Identifiers

PMID40708676
PMCPMC12288947

What OpenQuestion holds

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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.