Evidence map›Paper›PMID 32046766›Full record

ArticleJournal of translational medicine2020

Development and validation of a novel immune-related prognostic model in hepatocellular carcinoma.

Zheng Wang, Jie Zhu, Yongjuan Liu, Changhong Liu, Wenqi Wang, Fengzhe Chen, Lixian Ma

Abstract read
In one paragraph

Article in Journal of translational medicine, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 67 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
67citing papers in PubMed, 1 pooled it
–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

67 citing papers in PubMed, 1 synthesis or guideline pooled it.

  1. Pooled it
  2. Translational cancer research · 2026
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  12. ANXA5: A Key Regulator of Immune Cell Infiltration in Hepatocellular Carcinoma.Medical science monitor : international medical journal of experimental and clinical research · 2024
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7 more citing papers are in PubMed but not listed here.

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

7 authors.

Zheng WangDepartment of Infectious Diseases, Qilu Hospital, Shandong University, Wenhua Xi Road 107, Jinan, 250012, Shandong, China.
Jie ZhuDepartment of Infectious Diseases, Qilu Hospital, Shandong University, Wenhua Xi Road 107, Jinan, 250012, Shandong, China.
Yongjuan LiuShandong Center for Disease Control and Prevention, Health Education Institute, Jinan, 250000, Shandong, China.
Changhong LiuDepartment of Gastroenterology, Shandong Provincial Qianfoshan Hospital, The First Hospital Affiliated With Shandong First Medical University, Jingshi Road 16766, Jinan, 250014, Shandong, China.
Wenqi WangDepartment of Gastroenterology, Shandong Provincial Qianfoshan Hospital, The First Hospital Affiliated With Shandong First Medical University, Jingshi Road 16766, Jinan, 250014, Shandong, China.
Fengzhe ChenDepartment of Infectious Diseases, Qilu Hospital, Shandong University, Wenhua Xi Road 107, Jinan, 250012, Shandong, China. cfzj2019@sdu.edu.cn.
Lixian MaDepartment of Infectious Diseases, Qilu Hospital, Shandong University, Wenhua Xi Road 107, Jinan, 250012, Shandong, China. mlx_sdu@163.com.ORCID 0000-0002-7904-3841

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundGrowing evidence has suggested that immune-related genes play crucial roles in the development and progression of hepatocellular carcinoma (HCC). Nevertheless, the utility of immune-related genes for evaluating the prognosis of HCC patients are still lacking. The study aimed to explore gene signatures and prognostic values of immune-related genes in HCC.

methodsWe comprehensively integrated gene expression data acquired from 374 HCC and 50 normal tissues in The Cancer Genome Atlas (TCGA). Differentially expressed genes (DEGs) analysis and univariate Cox regression analysis were performed to identify DEGs that related to overall survival. An immune prognostic model was constructed using the Lasso and multivariate Cox regression analyses. Furthermore, Cox regression analysis was applied to identify independent prognostic factors in HCC. The correlation analysis between immune-related signature and immune cells infiltration were also investigated. Finally, the signature was validated in an external independent dataset.

resultsA total of 329 differentially expressed immune-related genes were detected. 64 immune-related genes were identified to be markedly related to overall survival in HCC patients using univariate Cox regression analysis. Then we established a TF-mediated network for exploring the regulatory mechanisms of these genes. Lasso and multivariate Cox regression analyses were applied to construct the immune-based prognostic model, which consisted of nine immune-related genes. Further analysis indicated that this immune-related prognostic model could be an independent prognostic indicator after adjusting to other clinical factors. The relationships between the risk score model and immune cell infiltration suggested that the nine-gene signature could reflect the status of tumor immune microenvironment. The prognostic value of this nine-gene prognostic model was further successfully validated in an independent database.

conclusionsTogether, our study screened potential prognostic immune-related genes and established a novel immune-based prognostic model of HCC, which not only provides new potential prognostic biomarkers and therapeutic targets, but also deepens our understanding of tumor immune microenvironment status and lays a theoretical foundation for immunotherapy.

Indexed as

Carcinoma, HepatocellularLiver NeoplasmsBiomarkers, TumorGene Expression ProfilingGene Expression Regulation, NeoplasticHumansPrognosisTumor MicroenvironmentBiomarkers, TumorBioinformaticsHepatocellular carcinomaImmune related genePrognosisPrognostic signature

Identifiers

PMID32046766
PMCPMC7011553

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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.