Screening of genes related to programmed cell death in esophageal squamous cell carcinoma and construction of prognostic model based on transcriptome analysis

被引:1
|
作者
Chen, Min [1 ,2 ,3 ,4 ,5 ,6 ,7 ]
Qi, Yijun [2 ,3 ,4 ,5 ,6 ,7 ]
Zhang, Shenghua [2 ,3 ,4 ,5 ,6 ,7 ]
Du, Yubo [2 ,3 ,4 ,5 ,6 ,7 ]
Cheng, Haodong [2 ,3 ,4 ,5 ,6 ,7 ]
Gao, Shegan [1 ,2 ,3 ,4 ,5 ,6 ,7 ]
机构
[1] Henan Univ Sci & Technol, Sch Informat Engn, Luoyang 471023, Henan, Peoples R China
[2] Henan Univ Sci & Technol, Affiliated Hosp 1, State Key Lab Esophageal Canc Prevent & Treatment, Luoyang, Peoples R China
[3] Henan Univ Sci & Technol, Affiliated Hosp 1, Henan Key Lab Microbiome & Esophageal Canc Prevent, Luoyang, Peoples R China
[4] Henan Univ Sci & Technol, Affiliated Hosp 1, Henan Key Lab Canc Epigenet, Luoyang, Peoples R China
[5] Henan Univ Sci & Technol, Canc Hosp, Affiliated Hosp 1, Luoyang, Peoples R China
[6] Henan Univ Sci & Technol, Coll Clin Med, Luoyang, Peoples R China
[7] Henan Univ Sci & Technol, Med Coll, Luoyang, Peoples R China
基金
中国国家自然科学基金;
关键词
Programmed cell death; esophageal cancer; prognosis; immunotherapy; immune cell infiltration; BLOCKADE;
D O I
10.1080/14737140.2024.2377184
中图分类号
R73 [肿瘤学];
学科分类号
100214 ;
摘要
ObjectivesTo screen programmed cell death (PCD)-related genes in esophageal squamous cell carcinoma (ESCC) based on transcriptomic data and to explore its clinical value.MethodsDifferentially expressed PCD genes (DEPCDGs) were screened from ESCC transcriptome and clinical data in TCGA database. Univariate COX and LASSO COX were performed on prognostically DEPCDGs in ESCC to develop prognostic model. Differences in immune cell infiltration in different RiskScore groups were determined by ssGSEA and CIBERSORT. The role of RiskScore in immunotherapy response was explored using Tumor Immune Dysfunction and Exclusion (TIDE) and IMvigor210 cohorts.ResultsFourteen DEPCDGs associated with prognosis were tapped in ESCC. These DEPCDGs form a RiskScore with good predictive performance for prognosis. RiskScore demonstrated excellent prediction accuracy in three data sets. The abundance of M2 macrophages and Tregs was higher in the high RiskScore group, and the abundance of M1 macrophages was higher in the low RiskScore group. The RiskScore also showed good immunotherapy sensitivity. RT-qPCR analysis showed that AUP1, BCAP31, DYRK2, TAF9 and UBQLN2 were higher expression in KYSE-150 cells. Knockdown BCAP31 inhibited migration and invasion.ConclusionA prognostic risk model can predict prognosis of ESCC and may be a useful biomarker for risk stratification and immunotherapy assessment.
引用
收藏
页码:905 / 915
页数:11
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