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

ICBP90, an epigenetic regulator, induces DKK3 promoter methylation, promotes glioma progression, and reduces sensitivity to cis-platinum

Glioma is the most common brain malignancy, characterized by high morbidity, high mortality, and treatment-resistance. Inverted CCAAT box Binding Protein of 90 kDa (ICBP90) has been reported to be involved in tumor progression and the maintenance of DNA methylation. Herein, we constructed ICBP90 over-expression and knockdown glioma cell lines, and found that ICBP90 knockdown inhibited glioma cell proliferation, migration, and invasion. ICBP90 silencing potentially enhanced cellular sensitivity to cis-platinum (DDP) and exacerbated DDP-induced pyroptosis, manifested by the elevated levels of gasdermin D-N-terminal and cleaved caspase 1; whereas, ICBP90 over-expression exhibited the opposite effects. Consistently, ICBP90 knockdown inhibited tumor growth in an in vivo mouse xenograft study using U251 cells stably expressing sh-ICBP90 and oe-ICBP90. Further experiments found that ICBP90 reduced the expression of Dickkopf 3 homolog (DKK3), a negative regulator of β-catenin, by binding its promoter and inducing DNA methylation. ICBP90 knockdown prevented the nuclear translocation of β-catenin and suppressed the expression of c-Myc and cyclin D1. Besides, DKK3 over-expression restored the effects of ICBP90 over-expression on cell proliferation, migration, invasion, and DDP sensitivity. Our findings suggest that ICBP90 inhibits the expression of DKK3 in glioma by maintaining DKK3 promoter methylation, thereby conducing to ICBP90-mediated carcinogenesis and drug insensitivity.

MrGPS: an m6A-related gene pair signature to predict the prognosis and immunological impact of glioma patients

N6-methyladenosine (m6A) RNA methylation is the predominant epigenetic modification for mRNAs that regulates various cancer-related pathways. However, the prognostic significance of m6A modification regulators remains unclear in glioma. By integrating the TCGA lower-grade glioma (LGG) and glioblastoma multiforme (GBM) gene expression data, we demonstrated that both the m6A regulators and m6A-target genes were associated with glioma prognosis and activated various cancer-related pathways. Then, we paired m6A regulators and their target genes as m6A-related gene pairs (MGPs) using the iPAGE algorithm, among which 122 MGPs were significantly reversed in expression between LGG and GBM. Subsequently, we employed LASSO Cox regression analysis to construct an MGP signature (MrGPS) to evaluate glioma prognosis. MrGPS was independently validated in CGGA and GEO glioma cohorts with high accuracy in predicting overall survival. The average area under the receiver operating characteristic curve (AUC) at 1-, 3- and 5-year intervals were 0.752, 0.853 and 0.831, respectively. Combining clinical factors of age and radiotherapy, the AUC of MrGPS was much improved to around 0.90. Furthermore, CIBERSORT and TIDE algorithms revealed that MrGPS is indicative for the immune infiltration level and the response to immune checkpoint inhibitor therapy in glioma patients. In conclusion, our study demonstrated that m6A methylation is a prognostic factor for glioma and the developed prognostic model MrGPS holds potential as a valuable tool for enhancing patient management and facilitating accurate prognosis assessment in cases of glioma.

Xihuang pill facilitates glioma cell pyroptosis via the POU4F1/STAT3 axis

Glioma is the most common malignancy in the central nervous system. This study aims to disclose the impacts of Xihuang pill (XHP), a traditional Chinese formula, on glioma cell pyroptosis and relevant molecular mechanism. U251 and SHG-44 cells were treated with XHP alone or together with oe-POU4F1 and sh-STAT3. CCK8 assay detected the viability, flow cytometry evaluated pyroptosis, and microscopy observed cell morphology. LDH release was determined by the LDH kit and the levels of IL-1β and IL-18 were detected by ELISA. Immunofluorescence showed NLRP3 expression in glioma cells and western blotting measured the levels of POU4F1, STAT3, NLRP3, ASC, cleaved caspase-1, and IL-1β. The binding of POU4F1 to STAT3 was verified. Primary glioma model was established to observe tumor change by in vivo imaging, determine the levels of Ki67 and NLRP3 by immunochemistry, and detect relevant protein levels by western blotting. XHP treatment alone downregulated POU4F1 and STAT3 levels, aroused pyroptotic appearance in glioma cells such as ballooning swelling, reduced cell viability and number of pyroptotic cells, increased LDH release and IL-1β and IL-18 levels, formed NLRP3 sports in cells, and elevated the levels of pyroptosis-related proteins. However, POU4F1 overexpression or STAT3 silencing suppressed XHP-promoted pyroptosis. Mechanistically, POU4F1 acted as a transcription factor of STAT3 and regulated its transcription. In primary glioma models, XHP enhanced glioma cell pyroptosis and blocked glioma growth. XHP facilitates glioma cell pyroptosis via the POU4F1/STAT3 axis.

A pyroptosis gene-based prognostic model for predicting survival in low-grade glioma

Background

Pyroptosis, a lytic form of programmed cell death initiated by inflammasomes, has been reported to be closely associated with tumor proliferation, invasion and metastasis. However, the roles of pyroptosis genes (PGs) in low-grade glioma (LGG) remain unclear.

Methods

We obtained information for 1,681 samples, including the mRNA expression profiles of LGGs and normal brain tissues and the relevant corresponding clinical information from two public datasets, TCGA and GTEx, and identified 45 differentially expressed pyroptosis genes (DEPGs). Among these DEPGs, nine hub pyroptosis genes (HPGs) were identified and used to construct a genetic risk scoring model. A total of 476 patients, selected as the training group, were divided into low-risk and high-risk groups according to the risk score. The area under the curve (AUC) values of the receiver operating characteristic (ROC) curves verified the accuracy of the model, and a nomogram combining the risk score and clinicopathological characteristics was used to predict the overall survival (OS) of LGG patients. In addition, a cohort from the Gene Expression Omnibus (GEO) database was selected as a validation group to verify the stability of the model. qRT-PCR was used to analyze the gene expression levels of nine HPGs in paracancerous and tumor tissues from 10 LGG patients.

Results

Survival analysis showed that, compared with patients in the low-risk group, patients in the high-risk group had a poorer prognosis. A risk score model combining PG expression levels with clinical features was considered an independent risk factor. Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) analyses indicated that immune-related genes were enriched among the DEPGs and that immune activity was increased in the high-risk group.

Conclusion

In summary, we successfully constructed a model to predict the prognosis of LGG patients, which will help to promote individualized treatment and provide potential new targets for immunotherapy.

The PANoptosis-related signature indicates the prognosis and tumor immune infiltration features of gliomas

Background

Gliomas are the most common primary tumors of the central nervous system, with high heterogeneity and highly variable survival rates. Accurate classification and prognostic assessment are key to the selection of treatment strategies. One hallmark of the tumor is resistance to cell death. PANoptosis, a novel mode of programmed cell death, has been frequently reported to be involved in the innate immunity associated with pathogen infection and played an important role in cancers. However, the intrinsic association of PANoptosis with glioma requires deeper investigation.

Methods

The genetics and expression of the 17 reported PANoptosome-related genes were analyzed in glioma. Based on these genes, patients were divided into two subtypes by consensus clustering analysis. After obtaining the differentially expressed genes between clusters, a prognostic model called PANopotic score was constructed after univariate Cox regression, LASSO regression, and multivariate Cox regression. The expression of the 5 genes included in the PANopotic score was also examined by qPCR in our cohort. The prognostic differences, clinical features, TME infiltration status, and immune characteristics between PANoptotic clusters and score groups were compared, some of which even extended to pan-cancer levels.

Results

Gene mutations, CNVs and altered gene expression of PANoptosome-related genes exist in gliomas. Two PANoptotic clusters were significantly different in prognosis, clinical features, immune characteristics, and mutation landscapes. The 5 genes included in the PANopotic score had significantly altered expression in glioma samples in our cohort. The high PANoptotic score group was inclined to show an unfavorable prognosis, lower tumor purity, worse molecular genetic signature, and distinct immune characteristics related to immunotherapy. The PANoptotic score was considered as an independent prognostic factor for glioma and showed superior prognostic assessment efficacy over several reported models. PANopotic score was included in the nomogram constructed for the potential clinical prognostic application. The associations of PANoptotic score with prognostic assessment and tumor immune characteristics were also reflected at the pan-cancer level.

Conclusion

Molecular subtypes of glioma based on PANoptosome-related genes were proposed and PANoptotic score was constructed with different clinical characteristics of anti-tumor immunity. The potential intrinsic association between PANoptosis and glioma subtypes, prognosis, and immunotherapy was revealed.

AKR1B1 Represses Glioma Cell Proliferation through p38 MAPK-Mediated Bcl-2/BAX/Caspase-3 Apoptotic Signaling Pathways

This study aimed to investigate the regulatory role of Aldo-keto reductase family 1 member B1 (AKR1B1) in glioma cell proliferation through p38 MAPK activation to control Bcl-2/BAX/caspase-3 apoptosis signaling. AKR1B1 expression was quantified in normal human astrocytes, glioblastoma multiforme (GBM) cell lines, and normal tissues by using quantitative real-time polymerase chain reaction. The effects of AKR1B1 overexpression or knockdown and those of AKR1B1-induced p38 MAPK phosphorylation and a p38 MAPK inhibitor (SB203580) on glioma cell proliferation were determined using an MTT assay and Western blot, respectively. Furthermore, the AKR1B1 effect on BAX and Bcl-2 expression was examined in real-time by Western blot. A luminescence detection reagent was also utilized to identify the effect of AKR1B1 on caspase-3/7 activity. The early and late stages of AKR1B1-induced apoptosis were assessed by performing Annexin V-FITC/PI double-staining assays. AKR1B1 expression was significantly downregulated in glioma tissues and GBM cell lines (T98G and 8401). Glioma cell proliferation was inhibited by AKR1B1 overexpression but was slightly increased by AKR1B1 knockdown. Additionally, AKR1B1-induced p38 MAPK phosphorylation and SB203580 reversed AKR1B1's inhibitory effect on glioma cell proliferation. AKR1B1 overexpression also inhibited Bcl-2 expression but increased BAX expression, whereas treatment with SB203580 reversed this phenomenon. Furthermore, AKR1B1 induced caspase-3/7 activity. The induction of early and late apoptosis by AKR1B1 was confirmed using an Annexin V-FITC/PI double-staining assay. In conclusion, AKR1B1 regulated glioma cell proliferation through the involvement of p38 MAPK-induced BAX/Bcl-2/caspase-3 apoptosis signaling. Therefore, AKR1B1 may serve as a new therapeutic target for glioma therapy development.