Identification of pyroptosis-related subtypes, development of a prognostic model, and characterization of tumour microenvironment infiltration in gastric cancer - Cao, Feng; Hu, Jingtao; Yuan, Hongtao; Cao, Pengwei; Cheng, Yunsheng; Wang, Yong (Frontiers in Genetics, 2022)
Background As a new programmed death mode, pyroptosis plays an indispensable role in gastric cancer (GC) and has strong immunotherapy potential, but the specific pathogenic mechanism and antitumor function remain unclear. Methods We comprehensively analysed the overall changes of pyroptosis-related genes (PRGs) at the genomic and epigenetic levels in 886 GC patients. The molecular subtypes were determined by consensus unsupervised clustering analysis. Then, univariate Cox regression analysis identified pyroptosis-associated differential genes (DEGs) linked to GC prognosis. LASSO and multivariate Cox regression analyses were used to calculate the risk score (RS) and to construct the prognostic model in the training cohorts and were verified in the test cohorts. Finally, the characteristics of the tumour microenvironment (TME), microsatellite instability (MSI), cancer stem cells (CSCs) and tumour mutational burden (TMB) between the high and low RS groups were further explored. Results PRGs had high mutation frequencies and copy number variations in the GC cohort. Patients can be divided into two subtypes, A and B. The prognosis and immune infiltration of subtype A was significantly better than that of subtype B. Then, we constructed the prognostic model and plotted a highly accurate nomogram to predict the prognosis of GC patients. In addition, The low-risk group was mainly characterized by microsatellite hyperinstability and increased abundance of immune infiltration. Moreover, the risk score was also significantly associated with TME, MSI, CSCs and drug sensitivity. Conclusion This study revealed the genomic, transcriptional and TME multiomics features of PRGs and deeply explored the potential role of pyroptosis in the TME, clinicopathological features and prognosis in GC. This study provides a new immune strategy and prediction model for clinical treatment and prognosis evaluation.