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Construction and validation of a pyroptosis-related gene signature in hepatocellular carcinoma based on RNA sequencing
BACKGROUND: To establish a pyroptosis-related gene (PRG) signature that could be utilized to predict hepatocellular carcinoma (HCC) survival and clinical features. METHODS: The Cancer Genome Atlas (TCGA) database was utilized to identify differentially expressed PRGs. Univariate Cox and least absolu...
Autores principales: | , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
AME Publishing Company
2022
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9273708/ https://www.ncbi.nlm.nih.gov/pubmed/35836524 http://dx.doi.org/10.21037/tcr-21-2898 |
Sumario: | BACKGROUND: To establish a pyroptosis-related gene (PRG) signature that could be utilized to predict hepatocellular carcinoma (HCC) survival and clinical features. METHODS: The Cancer Genome Atlas (TCGA) database was utilized to identify differentially expressed PRGs. Univariate Cox and least absolute shrinkage and selection operator (LASSO) Cox regression analyses were utilized to establish the prognostic signature. The signature was verified in the International Cancer Genome Consortium cohort (ID: LIHC-US). Based on the medium-risk score, HCC samples were classified into high- or low-risk subgroups. For signature accuracy prediction, we utilized receiver operating characteristic (ROC) analysis and the Kaplan-Meier estimate (K-M). Molecular and immunological aspects were also reviewed using single-sample gene set enrichment analysis (ssGSEA). Finally, quantitative real-time PCR (qRT-PCR) was utilized to verify the expression of hub genes in vitro. RESULTS: On basis of the 33 PRGs, five PRGs (CASP8, GSDMC, NLRP6, NOD2, and PLCG1) were identified that could predict HCC prognosis. Individuals with high-risk scores had significantly lower overall survival (OS) compared to those with low-risk scores. To assess and confirm this signature’s prediction performance, the area under the curve (AUC) of ROC curves was utilized. In multivariate analysis, the risk score was proven to be a significant independent prognostic factor. Immunological status and tumor cell infiltration in high-risk groups were both significantly greater than in low-risk groups, indicating that the immune system was more activated. qRT-PCR analysis demonstrated that the five PRGs in HCC cell lines were differently expressed in the prognostic signature. CONCLUSIONS: The signature could precisely predict survival outcomes and reveal immune microenvironment composition, as well as strengthen the argument for more credible clinical and functional research in HCC patients. |
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