Research Paper Volume 15, Issue 16 pp 8113—8136

Comprehensive characterization of pyroptosis phenotypes with distinct tumor immune profiles in gastric cancer to aid immunotherapy

Kaida Huang1, *, , Yubiao Lin1, *, , Guoqin Qiu2, *, , Shengyu Wang3, *, , Lihua Feng1, , Zhigao Zheng1, , Yingqin Gao1, , Xin Fan1, , Wenhui Zheng1, &, , Jianmin Zhuang4, , Fanghong Luo3, , Shuitu Feng1,5, ,

  • 1 Department of Oncology, Xiamen Haicang Hospital, Xiamen 361026, Fujian, China
  • 2 Chenggong Hospital Affiliated to Xiamen University, Xiamen 361003, Fujian, China
  • 3 Cancer Research Center, Medical College, Xiamen University, Xiamen 361102, China
  • 4 Department of General Surgery, Xiamen Haicang Hospital, Xiamen 361026, Fujian, China
  • 5 Fudan University Shanghai Cancer Center Xiamen Hospital, Xiamen 361000, Fujian, China
* Equal contribution

Received: March 14, 2023       Accepted: July 19, 2023       Published: August 17, 2023
How to Cite

Copyright: © 2023 Huang 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.


Objective: Pyroptosis is a form of programmed cell death that is essential for immunity. Herein, this study was conducted to uncover the implication of pyroptosis in immunomodulation and tumor microenvironment (TME) in gastric cancer.

Methods: Prognostic pyroptosis-related genes were extracted to identify different pyroptosis phenotypes and pyroptosis genomic phenotypes via unsupervised clustering analysis in the gastric cancer meta-cohort cohort (GSE15459, GSE62254, GSE84437, GSE26253 and TCGA-STAD). The activation of hallmark gene sets was quantified by GSVA and immune cell infiltration was estimated via ssGSEA and CIBERSORT. Through PCA algorithm, pyroptosis score was conducted. The predictors of immune response (TMB and IPS) and genetic mutations were evaluated. The efficacy of pyroptosis score in predicting immune response was verified in two anti-PD-1 therapy cohorts.

Results: Three different pyroptosis phenotypes with different prognosis, biological pathways and tumor immune microenvironment were established among 1275 gastric cancer patients, corresponding to three immune phenotypes: immune-inflamed, immune-desert, and immune-excluded. According to the pyroptosis score, patients were separated into high and low pyroptosis score groups. Low pyroptosis score indicated favorable survival outcomes, enhanced immune responses, and increased mutation frequency. Moreover, low pyroptosis score patients displayed more clinical benefits from anti-PD-1 and prolonged survival time.

Conclusion: Our findings uncovered a nonnegligible role of pyroptosis in immunomodulation and TME multiformity and complicacy in gastric cancer. Quantifying the pyroptosis score in individual tumors may tailor more effective immunotherapeutic strategies.


STAD: stomach adenocarcinoma; TME: tumor microenvironment; TCGA: the Cancer Genome Atlas; GEO: Gene Expression Omnibus; CNV: copy number variation; PPI: protein-protein interaction; STRING: Search Tool for the Retrieval of Interacting Genes; t-SNE: t-distributed stochastic neighbor embedding; GSVA: Gene set variation analysis; MSigDB: Molecular Signatures Database; ssGSEA: single sample gene set enrichment analysis; ESTIMATE: Estimation of Stromal and Immune Cells in Malignant Tumors using Expression Data; TMB: tumor mutation burden; IPS: Immunophenoscore; DEGs: differentially expressed genes; PCA: principal component analysis; PC: principal component; GO: Gene Ontology; KEGG: Kyoto Encyclopedia of Genes and Genomes; GSEA: Gene set enrichment analysis; pan-F-TBRS: pan-fibroblast TGF-β response signature; EMT: epithelial-mesenchymal transition; IC50: half-maximal inhibitory concentration; ROC: receiver operating characteristic; AUC: area under the curve.