肿瘤细胞特别是恶性肿瘤细胞最显著的能量代谢特点是即便在氧供应充分的条件下也主要由糖酵解获取能量，即Warburg效应，这也是科学家们一直渴望能够利用的一个癌细胞代谢特征。天然小分子化合物脱氧鬼臼毒素(Deoxypodophyllotoxin,DPT)具有抗肿瘤、抗病毒、抑制炎症等生物活性，本项目前期成果表明DPT可通过诱导大量活性氧(ROS)的产生导致胶质瘤细胞发生PARP-1依赖的死亡方式即Parthanatos,前期预实验又发现DPT可抑制胶质瘤细胞糖酵解但其分子机制尚不清楚。本项目中，我们通过体外胶质瘤细胞培养及构建BALB/C裸鼠皮下胶质瘤模型，运用细胞生物学及分子生物学实验手段，阐明了DPT抑制胶质瘤细胞糖酵解的分子机制。我们主要发现:(1)DPT可抑制胶质瘤细胞的糖酵解并能抑制胶质瘤细胞的侵袭迁移。PARP-1抑制剂和抗氧化剂可逆转DPT诱导的胶质瘤细胞糖酵解障碍。(2)DPT作用于胶质瘤细胞后诱导大量活性氧产生激活PARP-1生成PAR聚合物,PAR与糖酵解关键酶HK2、PKM2结合抑制其功能进而抑制糖酵解。同时还发现HK2与PKM2被PAR结合抑制后促使胶质瘤细胞活性氧积聚增多进一步促进糖酵解障碍。(3)通过构建BALB/C裸鼠荷胶质瘤模型，证实DPT在体内也可下调糖酵解关键酶HK2和PKM2的表达，抑制糖酵解产物的产生。通过本项目，我们明确了DPT作用于胶质瘤细胞通过诱导大量活性氧的产生激活PARP-1产生毒性PAR聚合物,PAR与糖酵解关键酶HK2、PKM2结合抑制糖酵解的分子机制。这有助于我们探索以PARP-1、HK2、PKM2为靶点的胶质瘤治疗新方案，还为脱氧鬼臼毒素尽早设计成为新型小分子抗肿瘤药物提供了理论依据。

Background: Due to high heterogeneity and mortality of low-grade gliomas (LGGs), it is of great significance to find biomarkers for prognosis and immunotherapy. Pyroptosis is emerging as an attractive target in cancer research for its effect on tumor immune microenvironment (TIME). However, the investigation of pyroptosis in LGGs is insufficient.Methods: LGG samples from TCGA and CGGA database were classified into two pyroptosis patterns based on the expression profiles of 52 PRGs using consensus clustering. A prognostic model was constructed by using the LASSO-COX method. ESTIMATE algorithm and single sample gene set enrichment analysis (ssGSEA) were used to characterize the TIME. Based on the differentially expressed genes between two pyroptosis patterns, favorable and unfavorable pyroptosis gene signatures were determined. Pyroptosis score scheme was constructed to quantify the pyroptosis patterns through gene set variation analysis (GSVA) method. Two external datasets and immunotherapy cohort from CGGA and GEO database were used to validate the predictive value of the pyroptosis score. The Human Protein Atlas website and Western blotting were utilized to confirm the expression of the selected genes in the prognostic model in LGGs.Results: Distinct overall survival and immune checkpoint blockage therapeutic responses were identified between two pyroptosis patterns. A low pyroptosis score in LGG patients implies higher overall survival, poor immune cell infiltration, and better response to immunotherapy of immune checkpoint blockage.Conclusion: Our findings provided a foundation for future research targeting pyroptosis and opened a new sight to explore the prognosis and immunotherapy from the angle of pyroptosis in LGGs.

Background:Due to the highly variable prognosis of low-grade gliomas(LGGs),it is important to find robust biomarkers for predicting clinical outcomes.Aging cancer-associated fibroblasts(CAFs)within the senescent stroma of a tumor microenvironment(TME)have been recently reported to play a key role in tumor development.However,there are few studies focusing on this topic in gliomas.Methods and Results:Based on the transcriptome data from TCGA and CGGA databases,we identified aging CAF-related genes(ACAFRGs)in LGGs by the weighted gene co-expression network analysis(WGCNA)method,followed by which LGG samples were classified into two aging CAF-related gene clusters with distinct prognosis and characteristics of the TME.Machine learning algorithms were used to screen out eight featured ACAFRGs to characterize two aging CAF-related gene clusters,and a nomogram model was constructed to predict the probability of gene cluster A for each LGG sample.Then,a powerful aging CAF scoring system was developed to predict the prognosis and response to immune checkpoint blockage therapy.Finally,the ACAFRGs were verified in two glioma-related external datasets.The performance of the aging CAF score in predicting the immunotherapy response was further validated in two independent cohorts.We also confirmed the expression of ACAFRGs at the protein level in glioma tissues through the Human Protein Atlas website and Western blotting analysis.Conclusion:We developed a robust aging CAF scoring system to predict the prognosis and immunotherapy response in LGGs.Our findings may provide new targets for therapeutics and contribute to the exploration focusing on aging CAFs.