Evidence map›Paper›PMID 40599775›Full record

ArticleFrontiers in immunology2025

Identification of anoikis-related subtypes and a risk score prognosis model, the association with TME landscapes and therapeutic responses in hepatocellular carcinoma.

Xiangyu Zhai, Kecheng Li, Hailing Ding, Yanmei Wu, Xinlu Zhang, Hao Zhang, Huaxin Zhou, Chongzhong Liu, Zili Zhang, Bin Jin

Abstract read
In one paragraph

Article in Frontiers in immunology, 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.

Xiangyu ZhaiDepartment of Hepatobiliary Surgery, The Second Hospital of Shandong University, Jinan, China.
Kecheng LiMedical Research & Laboratory Diagnostic Center, Jinan Central Hospital Affiliated to Shandong First Medical University, Jinan, China.
Hailing DingSchool of Medicine, Qilu Institute of Technology, Jinan, China.
Yanmei WuInstitute of Basic Medical Sciences, Shandong Maternal and Child Health Hospital, Jinan, China.
Xinlu ZhangBasic Medical Research Center, Jinan Central Hospital Affiliated to Shandong First Medical University, Jinan, China.
Hao ZhangShandong Province Engineering Research Center for Multidisciplinary Research on Hepatobiliary and Pancreatic Malignant Tumors, Jinan, China.
Huaxin ZhouDepartment of Hepatobiliary Surgery, The Second Hospital of Shandong University, Jinan, China.
Chongzhong LiuDepartment of Hepatobiliary Surgery, The Second Hospital of Shandong University, Jinan, China.
Zili ZhangDepartment of General Surgery, The Fourth People's Hospital of Jinan, Jinan, China.
Bin JinDepartment of Hepatobiliary Surgery, The Second Hospital of Shandong University, Jinan, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Introduction: Anoikis is a distinct form of programmed cell death, differing from classical apoptosis, and its role in malignant tumor progression, particularly in hepatocellular carcinoma (HCC), remains insufficiently understood. This study aims to elucidate the prognostic significance and therapeutic relevance of anoikis-related genes (ARGs) in HCC. Methods: We systematically analyzed the expression, mutation, and copy number variation profiles of 27 known ARGs in HCC using public datasets. Unsupervised consensus clustering was performed to classify patients into anoikis subtypes. Weighted Gene Co-expression Network Analysis (WGCNA) identified hub gene modules, and LASSO Cox regression was applied to construct a prognostic risk score model. Correlations between the risk model and clinical outcomes, tumor microenvironment (TME) characteristics, and immunotherapy responses were evaluated. Single-cell RNA-seq and pan-cancer analyses were conducted to explore gene expression across cell types and cancer types. Finally, in vitro experiments were performed to validate the biological function of model genes. Results: Two distinct anoikis subtypes with differing prognoses and TME features were identified in HCC. A two-gene prognostic model (TTC26 and TPX2) was developed, demonstrating robust performance in predicting patient outcomes. High-risk patients exhibited lower overall survival and distinct immune infiltration profiles. Pan-cancer analysis showed widespread dysregulation of TTC26 and TPX2. In vitro experiments confirmed that TTC26 promotes HCC cell proliferation, migration, and invasion. Discussion: Our findings reveal that anoikis-related molecular classification is closely linked to HCC prognosis and immune landscape. The established prognostic model has potential clinical utility for risk stratification and treatment guidance. TTC26 may serve as a novel biomarker and therapeutic target in HCC.

Indexed as

AnoikisCarcinoma, HepatocellularLiver NeoplasmsTumor MicroenvironmentBiomarkers, TumorGene Expression ProfilingGene Expression Regulation, NeoplasticGene Regulatory NetworksHumansMutationPrognosisBiomarkers, Tumoranoikishepatocellular carcinomaimmunotherapy responseprognostic signaturetumor microenvironment

Identifiers

PMID40599775
PMCPMC12209314

What Socratic holds

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LicenceCC BY
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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 Socratic graph.