Evidence map›Paper›PMID 35699863›Full record

ArticleHepatology international2022

A novel epithelial-mesenchymal transition gene signature for the immune status and prognosis of hepatocellular carcinoma.

Yanlong Shi, Jingyan Wang, Guo Huang, Jun Zhu, Haokun Jian, Guozhi Xia, Qian Wei, Yuanhai Li, Hongzhu Yu

Open access · hybridAbstract read
In one paragraph

Article in Hepatology international, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 23 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
23citing papers in PubMed, 1 pooled it
4.1field-weighted citation impact, top 5% of its field
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

23 citing papers in PubMed, 1 synthesis or guideline pooled it, 29 citations in OpenAlex.

  1. Contradictory Role of Gadd45β in Liver Diseases.Journal of cellular and molecular medicine · 2024
    Pooled it
  2. POSTNOncology reports · 2026
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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

9 authors at 4 institutions in 1 country.

Yanlong Shi *Department of General Surgery, Fuyang Hospital Affiliated to Anhui Medical University, Fuyang, 236000, Anhui, China.
Jingyan Wang *Department of Anesthesiology, Chaohu Hospital Affiliated to Anhui Medical University, Chaohu, 238000, Anhui, China.
Guo Huang *Hengyang Medical College, University of South China, Hengyang, 421001, Hunan, China.
Jun Zhu *Department of Oncology, Fuyang Hospital Affiliated to Anhui Medical University, Fuyang, 236000, Anhui, China.
Haokun JianSchool of Basic Medical Sciences, Xinxiang Medical University, Xinxiang, 453000, Henan, China.
Guozhi XiaDepartment of General Surgery, Fuyang Hospital Affiliated to Anhui Medical University, Fuyang, 236000, Anhui, China.
Qian WeiSchool of Nursing, Anhui Medical University, HeFei, 230000, Anhui, China.
Yuanhai LiDepartment of Anesthesiology, Chaohu Hospital Affiliated to Anhui Medical University, Chaohu, 238000, Anhui, China. liyuanhai-1@163.com.
Hongzhu YuDepartment of General Surgery, Fuyang Hospital Affiliated to Anhui Medical University, Fuyang, 236000, Anhui, China. hongzhuyu@ahmu.edu.cn.ORCID http://orcid.org/0000-0002-6378-1217
Anhui Medical University · CNChaohu Hospital of Anhui Medical University · CNUniversity of South China · CNXinxiang Medical University · CN

Funding

the Health Commission of Anhui Province AHWJ2021b138
6 · The paper itself

Abstract

backgroundThis study clarified whether EMT-related genes can predict immunotherapy efficacy and overall survival in patients with HCC.

methodsThe RNA-sequencing profiles and patient information of 370 samples were derived from the Cancer Genome Atlas (TCGA) dataset, and EMT-related genes were obtained from the Molecular Signatures database. The signature model was constructed using the least absolute shrinkage and selection operator Cox regression analysis in TCGA cohort. Validation data were obtained from the International Cancer Genome Consortium (ICGC) dataset of patients with HCC. Kaplan-Meier analysis and multivariate Cox analyses were employed to estimate the prognostic value. Immune status and tumor microenvironment were estimated using a single-sample gene set enrichment analysis (ssGSEA). The expression of prognostic genes was verified using qRT-PCR analysis of HCC cell lines.

resultsA signature model was constructed using EMT-related genes to determine HCC prognosis, based on which patients were divided into high-risk and low-risk groups. The risk score, as an independent factor, was related to tumor stage, grade, and immune cells infiltration. The results indicated that the most prognostic genes were highly expressed in the HCC cell lines, but GADD45B was down-regulated. Enrichment analysis suggested that immunoglobulin receptor binding and material metabolism were essential in the prognostic signature.

conclusionOur novel prognostic signature model has a vital impact on immune status and prognosis, significantly helping the decision-making related to the diagnosis and treatment of patients with HCC.

Indexed as

Carcinoma, HepatocellularLiver NeoplasmsBiomarkers, TumorEpithelial-Mesenchymal TransitionGene Expression Regulation, NeoplasticHumansPrognosisTumor MicroenvironmentBiomarkers, TumorBioinformaticsBiomarkerDecision-makingDrug sensitivityEpithelial–mesenchymal transitionHepatocellular carcinomaImmune microenvironmentModelOverall survivalPrognosis

Identifiers

PMID35699863
PMCPMC9349121
OpenAlexW4282830743

What OpenQuestion holds

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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 OpenQuestion graph.