Research Paper Volume 15, Issue 8 pp 3094—3106

Identification of the pyroptosis-related gene signature and risk score model for esophageal squamous cell carcinoma

Minghong Pan1, *, , Yuanyong Wang1, *, , Zhaoyang Wang1, *, , Changjian Shao1, *, , Yingtong Feng2, , Peng Ding1, , Hongtao Duan1, , Xiaoya Ren1, , Weixun Duan3, , Zhiqiang Ma4, , Xiaolong Yan1, ,

  • 1 Department of Thoracic Surgery, Tangdu Hospital, The Air Force Military Medical University, Xi’an 710038, China
  • 2 Department of Cardiothoracic Surgery, The Affiliated Huaihai Hospital of Xuzhou Medical University/The 71st Group Army Hospital of PLA, Xuzhou 221004, China
  • 3 Department of Cardiovascular Surgery, Xijing Hospital, The Air Force Military Medical University, Xi’an 710038, China
  • 4 Department of Medical Oncology, Senior Department of Oncology, Chinese PLA General Hospital, The Fifth Medical Center, Beijing 100853, China
* Equal contribution

Received: November 22, 2022       Accepted: April 3, 2023       Published: April 17, 2023
How to Cite

Copyright: © 2023 Pan et al. This is an open access article distributed under the terms of the Creative Commons Attribution License (CC BY 3.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.


Advanced esophageal squamous cell carcinoma (ESCC) still has a dismal prognostic outcome. However, the current approaches are unable to evaluate patient survival. Pyroptosis represents a novel programmed cell death type which widely investigated in various disorders and can influence tumor growth, migration, and invasion. Furthermore, few existing studies have used pyroptosis-related genes (PRGs) to construct a model for predicting ESCC survival. Therefore, the present study utilized bioinformatics approaches for analyzing ESCC patient data obtained from the TCGA database to construct the prognostic risk model and applied it to the GSE53625 dataset for validation. There were 12 differentially expressed PRGs in healthy and ESCC tissue samples, among which eight were selected through univariate and LASSO cox regression for constructing the prognostic risk model. According to K-M and ROC curve analyses, our eight-gene model might be useful in predicting ESCC prognostic outcomes. Based on the cell validation analysis, C2, CD14, RTP4, FCER3A, and SLC7A7 were expressed higher in KYSE410 and KYSE510 than in normal cells (HET-1A). Hence, ESCC patient prognostic outcomes can be assessed by our PRGs-based risk model. Further, these PRGs may also serve as therapeutic targets.


EC: Esophageal cancer; ESCC: esophageal squamous cell carcinoma; PRGs: pyroptosis-related genes; GSDME: Gasdermin E; TIME: tumor immune microenvironment; TIICs: tumor-infiltrating immune cells; GSDMC: Gasdermin C; PYCARD: PYD and CARD Domain Containing; TP63: Tumor Protein P63; NOD2: Nucleotide Binding Oligomerization Domain Containing 2; IL1A: Interleukin 1 Alpha; AIM2: Absent in Melanoma 2; CASP1: Caspase 1; GZMB: Granzyme B; TNF: Tumor Necrosis Factor; NLRP1: NLR Family Pyrin Domain Containing 1; ELANE: Elastase, Neutrophil Expressed; B2M: β2-microglobulin; C1QB: Complement Component 1, Q Subcomponent, Beta Polypeptide; C2: Complement Component 2; CD14: Monocyte Differentiation Antigen CD14; FCER1G: Fc Fragment of IgE, High Affinity I, Receptor for Gamma; FCGR3A: Fc Fragment of IgG, Low Affinity IIIa, Receptor; RTP4: Receptor Transporter Protein 4; SLC7A7: Solute Carrier Family 7 Member 7.