A PANoptosis‐Based Signature for Survival and Immune Predication in Glioblastoma Multiforme

ABSTRACT Objective PANoptosis is a concept of total cell death characterized by pyroptosis, apoptosis, and necroptosis. We aimed to explore the clinical significance of PANoptosis‐related genes (PARGs) in glioblastoma multiforme (GBM). Methods Expression profiles of GBM were downloaded from the XENA database as a training dataset to construct a differentially expressed PARGs (DE‐PARGs)‐based risk score (RS) model, and the prognostic prediction role was validated in the CGGA database and GSE108474 using Kaplan–Meier (KM) curve and receiver operating characteristic (ROC) curve. Meanwhile, independent prognostic clinical factors were screened, and their prognosis predictive activity was evaluated by a nomogram model. Furthermore, the relationships between key DE‐PARGs and immune cell infiltration, as well as chemotherapy drug sensitivity were analyzed. Results The RS model consisting of five DE‐PARGs was constructed, including NOD2 , NLRP2 , NLRP7 , GATA3 , and TERT . ROC and KM curves confirmed the good potency of the RS prognostic model both in XENA database and GSE108474. Three clinical prognostic factors, including chemotherapy, pharmaceutical therapy, and RS model, were selected as individual prognostic factors. The nomogram model showed RS contributed most to survival probability, followed by chemotherapy and pharmaceutical therapy. In high‐ and low‐risk groups, B cell memory, NK cell resting, and macrophage M1 had significant differences. As compared with the immune checkpoint therapy non‐responder group, the responder involved a higher ratio of patients sub‐grouped into the low‐risk group. Three drugs between high‐ and low‐risk groups had significant differences, including Cisplatin, Gefitinib, and Vorinostat. Interpretation Our data exhibit the prognostic value of PARGs in GBM and offer new insights for GBM pathogenesis and immune treatment.