Abstract
BackgroundGlioma is the most common intracranial malignancy with a poor prognosis. Although remarkable advances have been made in the study of diagnostic and prognostic biomarkers, the efficacy of current treatment strategies is still unsatisfactory. Therefore, developing novel and reliable targets is desperately needed for glioma patients. Pyroptosis reshapes tumor immune microenvironment (TME) and promotes the destruction of the tumor by the immune system. Moreover, pyroptosis levels correlate with prognosis and immunotherapy response in many cancer patients. This study performed a comprehensive analysis of pyroptosis in the glioma, unveiling its potential value in glioma prognosis prediction and therapy efficacy.MethodsFirstly, the pyroptosis regulation patterns were comprehensively evaluated on 33 pyroptosis-related genes in 1716 glioma samples. The correlations were analyzed between pyroptosis regulation patterns and TME immune cell infiltration properties. Next, pyroptosis regulation patterns were measured by the PSscore model based on principal component analysis algorithms. The correlations were analyzed between PSscore and tumor mutational burden (TMB), immune checkpoint blockade (ICB) therapeutic advantages. Last, the findings were validated in an independently collected external clinical cohort.ResultsWe determined two distinct pyroptosis regulation patterns. The cluster-A was high immune cell infiltration with a poor prognosis (p < 0.001), whereas the cluster-B was low immune cell infiltration with a better prognosis (p < 0.001). We developed the PSscore as a measure for pyroptosis regulation patterns. The high PSscore with an inflamed TME phenotype, a high TMB (p < 0.0001), increased innate immune response, and a poor prognosis (p < 0.001). It was in stark contrast to the low PSscore (p < 0.001). Analysis of PSscore with checkpoint therapy indicated high PSscore were correlated with enhanced response to anti-PD-1 immunotherapy (p = 0.0046). For validation, we utilized in vitro experiments on an external clinical cohort. The results demonstrated that GSDMD expression level in the high PSscore group was significantly upregulated compared to the low PSscore group (p < 0.001); the CD3+ T cells and the CD3+PD-1+ cells significantly increased in the high PSscore group compared to the low PSscore group (p < 0.01).ConclusionsThe PSscore of pyroptosis regulation pattern is a reliable biomarker, and it is valuable to predict prognosis, TME, and ICB therapeutic efficiency in glioma patients.
Highlights
Glioma is the most common intracranial malignancy [1]
It was found that the NLRP2, NLRP3, NLRP7, PLCG1, SCAF11, NLRP1, NOD1, CASP1, and NOD2 exhibited relatively high mutation frequency (1%), while CASP3, gasdermin E (GSDME), IL1B, PJVK, TIRAP did not show any mutations in glioma samples (Fig. S1b)
The analysis demonstrated that in comparison with normal brain tissues, 20 pyroptosis-related genes were upregulated in the tumor (e.g. CASP1 and CASP3), and 11 pyroptosis-related genes were significantly downregulated in the tumor (e.g. gasdermin B (GSDMB) and NLRP1) (Fig. 1d)
Summary
Glioma is the most common intracranial malignancy [1]. Over the past four decades, various therapies for glioma have been developed. Significant progress has been made to identify molecular markers that could predict the glioma’s progression and clinical prognosis, such as IDH1, 1p19q, and MGMT methylation [2–4]. These parameters are not ideal due to their limited accuracy, sensitivity, and specificity. This study performed a comprehensive analysis of pyroptosis in the glioma, unveiling its potential value in glioma prognosis prediction and therapy efficacy. The correlations were analyzed between pyroptosis regulation patterns and TME immune cell infiltration properties. The high PSscore with an inflamed TME phenotype, a high TMB (p < 0.0001), increased innate immune response, and a poor prognosis (p < 0.001). The results demonstrated that GSDMD expression level in the high PSscore group was significantly upregulated compared to the low PSscore group (p < 0.001); the CD3+ T cells and the CD3+PD-1+ cells significantly increased in the high PSscore group compared to the low PSscore group (p < 0.01)
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