Evidence map›Paper›PMID 35562678›Full record

ArticleBMC bioinformatics2022

Diagnostic and prognostic values of pyroptosis-related genes for the hepatocellular carcinoma.

Mindan Xing, Jia Li

Abstract read
In one paragraph

Article in BMC bioinformatics, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 14 papers.

0numbers the graph read from it
0cells of the map it votes in
14citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

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2 · The registry

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3 · Its place in the literature

Who cites it

14 citing papers in PubMed.

  1. Article
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  5. The mTranslational cancer research · 2024
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  8. Review
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4 · The record

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5 · Who and what money

Authors and funding

2 authors.

Mindan XingNankai University School of Medicine, Nankai University, Tianjin, China.
Jia LiNankai University School of Medicine, Nankai University, Tianjin, China. 18622663700@163.com.

Funding

Tianjin Health Science and Technology Project NoTJWJ2021ZD010
6 · The paper itself

Abstract

backgroundDue to the high heterogeneity, the early diagnosis and prognostic prediction of hepatic cellular cancer (HCC) is challenging. In this study, we explored the diagnostic and prognostic value of pyroptosis-related genes (PRGs) in HCC. We downloaded the mRNA expression profiles of HCC and the corresponding clinical data from the TCGA and ICGC databases. Fifty-one PRGs were extracted from Genecards, MsigDB, and relevant literature. The area under the receiver operating characteristic (AUC) was used to explore the diagnostic value of the PRGs.

resultsThe results revealed that BAK1, BAX, CHMP2A, CHMP4C, CHMP6, GSDMC, and GSDMD had higher diagnostic values for HCC (AUCs > 0.8, P < 0.05). Then, univariate and multivariate analyses of 51 PRGs were performed for HCC samples, and 4 PRGs (TP53, GPX4, GSDMC, BAK1) associated with HCC prognosis were obtained and used to construct a pyroptosis-related risk model. HCC samples were divided into high-risk and low-risk groups based on the risk score's cut-off. Kaplan-Meier curve and Log-rank test were used to compare the overall survival (OS) of two risk groups. The OS was lower in the high-risk group than in the low-risk group. In addition, the time-dependent receiver operating characteristics revealed that the risk model could be used to predict the prognosis of HCC more accurately. The risk score also resulted as an independent risk factor for HCC prognosis (TCGA: HR = 2.45, 95% CI 1.53-3.92; ICGC: HR = 2.19, 95% CI 1.39-3.46). Moreover, the AUC of the risk score for diagnosing HCC was relatively higher (TCGA: AUC = 0.840, P < 0.05; ICGC: AUC = 0.795, P < 0.05).

conclusionsIn a word, BAK1, BAX, CHMP2A, CHMP4C, CHMP6, GSDMC, GSDMD, and the pyroptosis-related risk model could be used to diagnose the HCC, and the risk score also resulted as an independent risk factor for the HCC prognosis.

Indexed as

Carcinoma, HepatocellularLiver Neoplasmsbcl-2-Associated X ProteinBiomarkers, TumorDNA-Binding ProteinsGasderminsGene Expression ProfilingHumansPore Forming Cytotoxic ProteinsPrognosisPyroptosisbcl-2-Associated X ProteinBiomarkers, TumorDNA-Binding ProteinsGasderminsGSDMC protein, humanPore Forming Cytotoxic ProteinsDiagnosis markersHepatocellular carcinomaPrognostic markersPyroptosisRisk model

Identifiers

PMID35562678
PMCPMC9101834

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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.