Lighting a Fire: Gasdermin-Mediated Pyroptosis Remodels the Glioma Microenvironment and Promotes Immune Checkpoint Blockade Response.

Pyroptosis is a proinflammatory programmed cell death pathway mediated by gasdermins. Exploring the role of pyroptosis can provide new insights into tumor malignancy. The most recent studies on pyroptosis have focused on tumor cells. However, the effects of pyroptosis on the tumor microenvironment (TME), immunotherapeutic responses, and efficacy have been neglected, especially in case of glioma. In this study, four independent glioma cohorts comprising 1,339 samples and a pan-cancer cohort comprising 10,535 tumor samples were analyzed. The relationships among pyroptosis status, prognosis, microenvironment cellular components, and clinical and biological phenotypes were investigated through the identification of pyroptosis subtypes, construction of a gasdermin-related prognostic index (GPI), and evaluation of immunological characteristics in glioma. The Genomics of Drug Sensitivity in Cancer database and "pRRophetic" package in R were used to estimate temozolomide (TMZ) sensitivity. The "Submap" package and external immunotherapy cohorts were used to investigate and confirm the role of GPI in response to and efficacy of immunotherapy in glioma. Finally, potential small-molecule compounds related to GPI were identified using the connectivity map database and mode-of-action analysis. We identified three different pyroptosis subtypes: cluster 1 (C1) characterized by a higher GPI, while cluster 2 (C2) and cluster 3 (C3) characterized by a lower GPI. The high GPI of C1 was associated with glioma progression and worse prognoses, whereas the low GPI of subtype C2 and C3 was associated with better prognoses. However, patients with high GPIs were found to be more sensitive to TMZ and immune checkpoint blockade than those with low GPIs. Furthermore, gasdermin D may be a principal potential biomarker and play key roles in pyroptosis-inducible therapy combined with immunotherapy in glioma. This study provides a clinical, biological, and molecular landscape of pyroptosis and suggests that pyroptosis of glioma cells may perform the dual function of promoting both tumorigenesis and antitumor immunity.

Optimization of cancer immunotherapy through pyroptosis: A pyroptosis-related signature predicts survival benefit and potential synergy for immunotherapy in glioma.

Background: Pyroptosis is a critical type of programmed cell death that is strongly associated with the regulation of tumor and immune cell functions. However, the role of pyroptosis in tumor progression and remodeling of the tumor microenvironment in gliomas has not been extensively studied. Thus, in this study, we aimed to establish a comprehensive pyroptosis-related signature and uncover its potential clinical application in gliomas. Methods: The TCGA glioma cohort was obtained and divided into training and internal validation cohorts, while the CGGA glioma cohort was used as an external validation cohort. Unsupervised consensus clustering was performed to identify pyroptosis-related expression patterns. A Cox regression analysis was performed to establish a pyroptosis-related risk signature. Real-time quantitative PCR was performed to analyze the expression of signature genes in glioma tissues. Immune infiltration was analyzed and validated by immunohistochemical staining. The expression patterns of signature genes in different cell types were analyzed using single-cell RNA sequencing data. Finally, therapeutic responses to chemotherapy, immunotherapy, and potential small-molecule inhibitors were investigated. Results: Patients with glioma were stratified into clusters 1 and 2 based on the expression patterns of pyroptosis-related genes. Cluster 2 showed a longer overall (P<0.001) and progression-free survival time (P<0.001) than Cluster 1. CD8+ T cell enrichment was observed in Cluster 1. A pyroptosis-related risk signature (PRRS) was then established. The high PRRS group showed a significantly poorer prognosis than the low PRRS group in the training cohort (P<0.001), with validation in the internal and external validation cohorts. Immunohistochemical staining demonstrated that CD8+ T cells were enriched in high PRRS glioma tissues. PRRS genes also showed cell-specific expression in tumor and immune cells. Moreover, the high PRRS risk group showed higher temozolomide sensitivity and increased response to anti-PD1 treatment in a glioblastoma immunotherapy cohort. Finally, Bcl-2 inhibitors were screened as candidates for adjunct immunotherapy of gliomas. Conclusion: The pyroptosis-related signature established in this study can be used to reliably predict clinical outcomes and immunotherapy responses in glioma patients. The correlation between the pyroptosis signature and the tumor immune microenvironment may be used to further guide the sensitization of glioma patients to immunotherapy.

A Ferroptosis-Related Gene Prognostic Index to Predict Temozolomide Sensitivity and Immune Checkpoint Inhibitor Response for Glioma.

Background: Gliomas are highly lethal brain tumors. Despite multimodality therapy with surgery, radiotherapy, chemotherapy, and immunotherapy, glioma prognosis remains poor. Ferroptosis is a crucial tumor suppressor mechanism that has been proven to be effective in anticancer therapy. However, the implications of ferroptosis on the clinical prognosis, chemotherapy, and immune checkpoint inhibitor (ICI) therapy for patients with glioma still need elucidation. Methods: Consensus clustering revealed two distinct ferroptosis-related subtypes based on the Cancer Genome Atlas (TCGA) glioma dataset (n = 663). Subsequently, the ferroptosis-related gene prognostic index (FRGPI) was constructed by weighted gene co-expression network analysis (WGCNA) and "stepAIC" algorithms and validated with the Chinese Glioma Genome Atlas (CGGA) dataset (n = 404). Subsequently, the correlation among clinical, molecular, and immune features and FRGPI was analyzed. Next, the temozolomide sensitivity and ICI response for glioma were predicted using the "pRRophetic" and "TIDE" algorithms, respectively. Finally, candidate small molecular drugs were defined using the connectivity map database based on FRGPI. Results: The FRGPI was established based on the HMOX1, TFRC, JUN, and SOCS1 genes. The distribution of FRGPI varied significantly among the different ferroptosis-related subtypes. Patients with high FRGPI had a worse overall prognosis than patients with low FRGPI, consistent with the results in the CGGA dataset. The final results showed that high FRGPI was characterized by more aggressive phenotypes, high PD-L1 expression, high tumor mutational burden score, and enhanced temozolomide sensitivity; low FRGPI was associated with less aggressive phenotypes, high microsatellite instability score, and stronger response to immune checkpoint blockade. In addition, the infiltration of memory resting CD4+ T cells, regulatory T cells, M1 macrophages, M2 macrophages, and neutrophils was positively correlated with FRGPI. In contrast, plasma B cells and naïve CD4+ T cells were negatively correlated. A total of 15 potential small molecule compounds (such as depactin, physostigmine, and phenacetin) were identified. Conclusion: FRGPI is a promising gene panel for predicting the prognosis, immune characteristics, temozolomide sensitivity, and ICI response in patients with glioma.