Genomic Analysis Uncovers the Prognostic and Immunogenetic Feature of Pyroptosis in Gastric Carcinoma: Indication for Immunotherapy - Zhou, Jie; Nie, Run-cong; Yin, Yi-xin; Wang, Yun; Yuan, Shu-qiang; Zhao, Zi-han; Zhang, Xin-ke; Duan, Jin-ling; Chen, Ying-bo; Zhou, Zhi-wei; Xie, Dan; Li, Yuan-fang; et al. (Frontiers in Cell and Developmental Biology, 2022)
Crosstalk between pyroptosis and tumor immune microenvironment (TIME) in cancer has yet to be elucidated. Herein, we aimed to explore the role of pyroptosis, and its association with TIME in gastric cancer. Unsupervised clustering was performed to identify the pyroptosis-related clusters. Pyroptosis risk score was constructed using LASSO Cox regression. Clinicopathological and genetic data of pyroptosis clusters and pyroptosis risk score were explored. Reproducibility of pyroptosis risk score in predicting response to immunotherapy and screening potential antitumor drugs was also investigated. Three pyroptosis clusters with distinct prognosis, immune cell fractions and signatures, were constructed. Low-pyroptosis risk score was characterized by increased activated T-cell subtype and M1 macrophage, decreased M2 macrophage, higher MSI status and TMB. Meanwhile, low-score significantly correlated with PD-L1 expression, antigen presentation markers and IFN-γ signature. The 5-year AUCs of PRS were 0.67, 0.62, 0.65, 0.67 and 0.67 in the TCGA, three external public and one real-world validation (SYSUCC) cohorts. Multivariable analyses further validated the prognostic performance of the pyroptosis risk scoring system, with HRs of 2.43, 1.83, 1.78, 2.35 and 2.67 (all P <0.05) in the 5 cohorts. GSEA indicated significant enrichment of DNA damage repair pathways in the low-score group. Finally, pyroptosis risk scoring system was demonstrated to be useful in predicting response to immunotherapy, and in screening potential antitumor drugs. Our study highlights the crucial role of interaction between pyroptosis and TIME in gastric cancer. The pyroptosis risk scoring system can be used independently to predict the survival of individuals and their response to immunotherapy.