Evidence map›Paper›PMID 34596136›Full record

ArticleMedicine2021

Comprehensive analysis of prognostic immune-related genes in the tumor microenvironment of hepatocellular carcinoma (HCC).

Mengting Li, Hongliang Li, Canxin Zhou, Xianpeng Li, Jiande Gong, Changxi Chen, Yi Zhang

Abstract read
In one paragraph

Article in Medicine, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

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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

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3 · Its place in the literature

Who cites it

2 citing papers in PubMed.

  1. Frontiers in oncology · 2025
    Article
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4 · The record

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5 · Who and what money

Authors and funding

7 authors.

Mengting LiDepartment of Gastroenterology, The Affiliated People's Hospital of Ningbo University, Zhejiang Province, China.ORCID 0000-0001-5894-757
Hongliang Li
Canxin Zhou
Xianpeng Li
Jiande Gong
Changxi Chen
Yi Zhang

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

abstractGrowing evidence supports that the tumor microenvironment plays a key role in the development and progression of tumors. But immune microenvironment of hepatocellular carcinoma (HCC) has not yet been fully explored. In the present investigation, the clinical value and prognostic significance of immune-related genes in HCC were investigated.The immune and stromal scores of HCC were calculated through the application of Estimation of Stromal and Immune cells in Malignant Tumor tissues using Expression data Algorithm based on the Cancer Genome Atlas database. Differentially expressed genes were identified using the "edgeR" package of the R software. Functional annotation and pathway enrichment were performed using "ggplots2" and "clusterProfiler" packages in R software. Protein-protein interaction network was constructed using STRING, and the hub genes were identified through the Cytoscape. Survival analysis was performed using Kaplan-Meier methods. Tumor Immune Estimation Resource algorithm was used to view the immune landscape of the microenvironment in HCC.Firstly, the immune and stromal scores of HCC were calculated and we found that the immune and stromal scores of HCC were closely related to the patients' prognosis. Then the differentially expressed genes were identified respectively stratified by the median value of the immune and stromal scores, and the immune-related genes that related to the prognosis in HCC patients were further identified. Functional enrichment analysis and protein-protein interaction networks further showed that these genes mainly participated in immune-related biological process. In addition, dendritic cells were found to be the most abundant in the microenvironment of HCC through Tumor Immune Estimation Resource algorithm and were significantly associated with the patients' prognosis. To robust the results, the immune-related genes were validated in an independent dataset from the Gene Expression Omnibus database.We arrived at a more comprehensive understanding of the microenvironment of HCC and extracted 7 immune-related genes that were significantly associated with the recurrence survival of HCC.

Indexed as

Carcinoma, HepatocellularGene Expression ProfilingHumansKaplan-Meier EstimateLiver NeoplasmsPrognosisProtein Interaction MapsStromal CellsTumor Microenvironment

Identifiers

PMID34596136
PMCPMC8483847

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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.