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pmid:37051536

A pyroptosis-related gene signature for prognosis prediction in hepatocellular carcinoma.

Yongwei Chen · Yanyun Zhu · Yuanmei Dong · Huizi Li · Chumeng Gao · Guoqiang Zhu · Xiao Mi · Chengcheng Li · Yu Xu · Guoqiang Wang · Shangli Cai · Yusheng Han · Chunwei Xu · Wenxian Wang · Shizhong Yang · Wenbin Ji

Frontiers in oncology · 2023 doi:10.3389/fonc.2023.1085188

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Experiment

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Data

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Analysis

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title
A pyroptosis-related gene signature for prognosis prediction in hepatocellular carcinoma.
doi
10.3389/fonc.2023.1085188
pmid
37051536
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[0]
Yongwei Chen
[1]
Yanyun Zhu
[2]
Yuanmei Dong
[3]
Huizi Li
[4]
Chumeng Gao
[5]
Guoqiang Zhu
[6]
Xiao Mi
[7]
Chengcheng Li
[8]
Yu Xu
[9]
Guoqiang Wang
[10]
Shangli Cai
[11]
Yusheng Han
[12]
Chunwei Xu
[13]
Wenxian Wang
[14]
Shizhong Yang
[15]
Wenbin Ji
journal
Frontiers in oncology
year
2023
abstract
Introduction: Hepatocellular carcinoma (HCC) is one of the most invasive cancers with a low 5-year survival rate. Pyroptosis, a specialized form of cell death, has shown its association with cancer progression. However, its role in the prognosis of HCC has not been fully understood. Methods: In our study, clinical information and mRNA expression for 1076 patients with HCC were obtained from the five public cohorts. Pyroptotic clusters were generated by unsupervised clustering based on 40 pyroptosis-related genes (PRGs) in the TCGA and ICGC cohort. A pyroptosis-related signature was constructed using least absolute shrinkage and selection operator (LASSO) regression according to differentially expressed genes (DEGs) of pyroptotic clusters. The signature was then tested in the validation cohorts (GES10142 and GSE14520) and subsequently validated in the CPTAC cohort (n=159) at both mRNA and protein levels. Response to sorafenib was explored in GSE109211. Results: Three clusters were identified based on the 40 PRGs in the TCGA cohort. A total of 24 genes were selected based on DEGs of the above three pyroptotic clusters to construct the pyroptotic risk score. Patients with the high-risk score showed shorter overall survival (OS) compared to those with the low-risk score in the training set (P<0.001; HR, 3.06; 95% CI, 2.22-4.24) and the test set (P=0.008; HR, 1.61; 95% CI, 1.13-2.28). The predictive ability of the risk score was further confirmed in the CPTAC cohort at both mRNAs (P<0.001; HR, 2.99; 95% CI, 1.67-5.36) and protein levels (P<0.001; HR, 2.97; 95% CI 1.66-5.31). The expression of the model genes was correlated with immune cell infiltration, angiogenesis-related genes, and sensitivity to antiangiogenic therapy (P<0.05). Discussion: In conclusion, we established a prognostic signature of 24 genes based on pyroptosis clusters for HCC patients, providing insight into the risk stratification of HCC.
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Patients with the high-risk score showed shorter overall survival (OS) compared to those with the low-risk score in the training set (P<0.001; HR, 3.06; 95% CI, 2.22-4.24) and the test set (P=0.008; HR, 1.61; 95% CI, 1.13-2.28).
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Patients with the high-risk score showed shorter overall survival (OS) compared to those with the low-risk score in the training set (P<0.001; HR, 3.06; 95% CI, 2.22-4.24) and the test set (P=0.008; HR, 1.61; 95% CI, 1.13-2.28).
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Pyroptosis, a specialized form of cell death, has shown its association with cancer progression. However, its role in the prognosis of HCC has not been fully understood.\nMethods: In our study, clinical information and mRNA expression for 1076 patients with HCC were obtained from the five public cohorts. Pyroptotic clusters were generated by unsupervised clustering based on 40 pyroptosis-related genes (PRGs) in the TCGA and ICGC cohort. A pyroptosis-related signature was constructed using least absolute shrinkage and selection operator (LASSO) regression according to differentially expressed genes (DEGs) of pyroptotic clusters. The signature was then tested in the validation cohorts (GES10142 and GSE14520) and subsequently validated in the CPTAC cohort (n=159) at both mRNA and protein levels. Response to sorafenib was explored in GSE109211.\nResults: Three clusters were identified based on the 40 PRGs in the TCGA cohort. A total of 24 genes were selected based on DEGs of the above three pyroptotic clusters to construct the pyroptotic risk score. Patients with the high-risk score showed shorter overall survival (OS) compared to those with the low-risk score in the training set (P<0.001; HR, 3.06; 95% CI, 2.22-4.24) and the test set (P=0.008; HR, 1.61; 95% CI, 1.13-2.28). The predictive ability of the risk score was further confirmed in the CPTAC cohort at both mRNAs (P<0.001; HR, 2.99; 95% CI, 1.67-5.36) and protein levels (P<0.001; HR, 2.97; 95% CI 1.66-5.31). The expression of the model genes was correlated with immune cell infiltration, angiogenesis-related genes, and sensitivity to antiangiogenic therapy (P<0.05).\nDiscussion: In conclusion, we established a prognostic signature of 24 genes based on pyroptosis clusters for HCC patients, providing insight into the risk stratification of HCC.", "claims": [{"id": "claim-method", "statement": "The R package glmnet was used to construct the risk model (21).", "kind": "methodological", "target": null, "evidence": [{"asset": "source:pmid:37051536", "locator": "sections[4] \"Generation of PRGs-related risk model\" paragraph 3", "quote": "The R package glmnet was used to construct the risk model (21)."}], "state": "complete"}, {"id": "claim-data-access", "statement": "The datasets presented in this study can be found in online repositories. 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