Identification and Validation of Pyroptosis-Related Gene Signature to Predict Prognosis and Reveal Immune Infiltration in Hepatocellular Carcinoma

被引:64
|
作者
Fu, Xiao-Wei [1 ,2 ,3 ,4 ]
Song, Chun-Qing [2 ,3 ,4 ]
机构
[1] Fudan Univ, Shanghai, Peoples R China
[2] Westlake Univ, Sch Life Sci, Key Lab Growth Regulat & Translat Res Zhejiang Pr, Hangzhou, Peoples R China
[3] Westlake Lab Life Sci & Biomed, Hangzhou, Peoples R China
[4] Westlake Inst Adv Study, Inst Basic Med Sci, Lab Gene Therapeut Biol, Hangzhou, Peoples R China
基金
中国国家自然科学基金;
关键词
pyroptosis; prognosis; biomarker; immune infiltration; drug sensitivity; hepatocellular carcinoma; CELL-DEATH; CANCER; MACROPHAGES; MECHANISMS; EXPRESSION;
D O I
10.3389/fcell.2021.748039
中图分类号
Q2 [细胞生物学];
学科分类号
071009 ; 090102 ;
摘要
Background: Hepatocellular carcinoma (HCC) is characterized by a poor prognosis and accounts for the fourth common cause of cancer-related deaths. Recently, pyroptosis has been revealed to be involved in the progression of multiple cancers. However, the role of pyroptosis in the HCC prognosis remains elusive.Methods: The clinical information and RNA-seq data of the HCC patients were collected from the TCGA-LIHC datasets, and the differential pyroptosis-related genes (PRG) were firstly explored. The univariate Cox regression and consensus clustering were applied to recognize the HCC subtypes. The prognostic PRGs were then submitted to the LASSO regression analysis to build a prognostic model in the TCGA training cohort. We further evaluated the predictive model in the TCGA test cohort and ICGC validation cohort (LIRI-JP). The accuracy of prediction was validated using the Kaplan-Meier (K-M) and receiver operating characteristic (ROC) analyses. The single-sample gene set enrichment analysis (ssGSEA) was used to determine the differential immune cell infiltrations and related pathways. Finally, the expression of the prognostic genes was validated by qRT-PCR in vivo and in vitro.Results: We identified a total of 26 differential PRGs, among which three PRGs comprising GSDME, GPX4, and SCAF11 were subsequently chosen for constructing a prognostic model. This model significantly distinguished the HCC patients with different survival years in the TCGA training, test, and ICGC validation cohorts. The risk score of this model was confirmed as an independent prognostic factor. A nomogram was generated indicating the survival years for each HCC patient. The ssGSEA demonstrated several tumor-infiltrating immune cells to be remarkably associated with the risk scores. The qRT-PCR results also showed the apparent dysregulation of PRGs in HCC. Finally, the drug sensitivity was analyzed, indicating that Lenvatinib might impact the progression of HCC via targeting GSDME, which was also validated in human Huh7 cells.Conclusion: The PRG signature comprised of GSDME, GPX4, and SCAF11 can serve as an independent prognostic factor for HCC patients, which would provide further evidence for more clinical and functional studies.
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页数:17
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