Evidence map›Paper›PMID 33777771›Full record

ArticleFrontiers in oncology2021

Identification of a Novel Four-Gene Signature Correlated With the Prognosis of Patients With Hepatocellular Carcinoma: A Comprehensive Analysis.

Weihua Zhu, Lixin Ru, Zhenchao Ma

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Article in Frontiers in oncology, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.

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5citing papers in PubMed
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5 citing papers in PubMed.

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5 · Who and what money

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3 authors.

Weihua ZhuDepartment of Gastroenterology, Affiliated Huzhou Hospital, Zhejiang University School of Medicine, Huzhou Central Hospital, Affiliated Central Hospital Huzhou University, Huzhou, China.
Lixin RuDepartment of Radiation Oncology, Affiliated Huzhou Hospital, Zhejiang University School of Medicine, Huzhou Central Hospital, Affiliated Central Hospital Huzhou University, Huzhou, China.
Zhenchao MaDepartment of Radiation Oncology, Affiliated Huzhou Hospital, Zhejiang University School of Medicine, Huzhou Central Hospital, Affiliated Central Hospital Huzhou University, Huzhou, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

purposeHepatocellular carcinoma (HCC) is a common solid-tumor malignancy with high heterogeneity, and accurate prognostic prediction in HCC remains difficult. This analysis was performed to find a novel prognostic multigene signature.

methodsThe TCGA-LIHC dataset was analyzed for differentially coexpressed genes through weighted gene coexpression network analysis (WGCNA) and differential gene expression analysis. A protein-protein interaction (PPI) network and univariate Cox regression analysis of overall survival (OS) were utilized to identify their prognostic value. Next, we used least absolute shrinkage and selection operator (LASSO) Cox regression to establish a prognostic module. Subsequently, the ICGC-LIRI-JP dataset was applied for further validation. Based on this module, HCC cases were stratified into high-risk and low-risk groups, and differentially expressed genes (DEGs) were identified. Functional enrichment analyses of these DEGs were conducted. Finally, single-sample gene set enrichment analysis (ssGSEA) was performed to explore the correlation between the prognostic signature and immune status.

resultsA total of 393 differentially coexpressed genes were obtained. Forty differentially coexpressed hub genes were identified using the CytoHubba plugin, and 38 of them were closely correlated with OS. Afterward, we established the four-gene prognostic signature with an acceptable accuracy (area under the curve [AUC] of 1-year survival: 0.739). The ICGC-LIRI-JP dataset also supported the acceptable accuracy (AUC of 1-year survival:0.752). Compared with low-risk cohort, HCC cases in the high-risk cohort had shorter OS, higher tumor grades, and higher T stages. The risk scores of this signature still act as independent predictors of OS (P<0.001). Functional enrichment analyses suggest that it was mainly organelle fission and nuclear division that were enriched. Finally, ssGSEA revealed that this signature is strongly associated with the immune status of HCC patients.

conclusionsThe proposed prognostic signature of four differentially coexpressed hub genes has satisfactory prognostic ability, providing important insight into the prediction of HCC prognosis.

Indexed as

hepatocellular carcinomaimmune statusleast absolute shrinkage and selection operator Cox regressionprognostic signaturesingle-sample gene set enrichment analysisweighted gene coexpression network analysis

Identifiers

PMID33777771
PMCPMC7994902

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