Histone lactylation-derived LINC01127 promotes the self-renewal of glioblastoma stem cells via the cis-regulating the MAP4K4 to activate JNK pathway.

Gliomas are the most prevalent and aggressive brain tumors, exhibiting high proliferation, abnormal glycolysis, and poor prognosis. LncRNAs act as regulatory molecules and play crucial roles in the malignant behaviors of GBM cells, including cell self-renewal. However, the regulatory mechanisms involved are largely unknown. In this study, we performed bioinformatics analysis to explore NF-κB pathway-related lncRNAs. ECAR and qRT-PCR were used to measure the relationship between glycolytic activity and lncRNA expression. Assays such as RIP-PCR and ChIP-PCR were employed to reveal the regulatory mechanisms of the lncRNA. Neurosphere formation and limiting dilution assays were performed to evaluate the self-renewal capacity of GBM cells. In our study, we identified an NF-κB pathway-related lncRNA named LINC01127 in GBM, which was found to be associated with poor progression of GBM. Functionally, the NF-κB pathway promoted warburg effect, which, in turn, induced the lactylation of H3 histone and increased the expression of LINC01127. Consequently, this enhancement of LINC01127 expression led to the promotion of self-renewal in GBM cells. Furthermore, LINC01127 regulated MAP4K4 expression in cis by directly guiding POLR2A to the MAP4K4 promoter regions, thereby leading to JNK pathway activation, and ultimately modulating the self-renewal of GBM cells. Moreover, the activated JNK pathway promoted the phosphorylation of IκBα. Overall, targeting LINC01127-mediated axis impeded orthotopic tumor growth in GBM xenografts. Taken together these results revealed that warburg effect-induced histone lactylation drives NF-κB-related LINC01127 expression, thereby promoting the self-renewal of GBM cells through the MAP4K4/JNK/NF-κB axis, and providing substantial evidence that LINC01127 might provide a novel therapeutic strategy for GBM patients.

HK3 stimulates immune cell infiltration to promote glioma deterioration.

BACKGROUND: Glioma is the most common and lethal type of brain tumor, and it is characterized by unfavorable prognosis and high recurrence rates. The reprogramming of energy metabolism and an immunosuppressive tumor microenvironment (TME) are two hallmarks of tumors. Complex and dynamic interactions between neoplastic cells and the surrounding microenvironment can generate an immunosuppressive TME, which can accelerate the malignant progression of glioma. Therefore, it is crucial to explore associations between energy metabolism and the immunosuppressive TME and to identify new biomarkers for glioma prognosis. METHODS: In our work, we analyzed the co-expression relationship between glycolytic genes and immune checkpoints based on the transcriptomic data from The Cancer Genome Atlas (TCGA) and Chinese Glioma Genome Atlas (CGGA) and found the correlation between HK3 expression and glioma tumor immune status. To investigate the biological role of HK3 in glioma, we performed bioinformatics analysis and established a mouse glioblastoma (GBM) xenograft model. RESULTS: Our study showed that HK3 significantly stimulated immune cell infiltration into the glioma TME. Tissue samples with higher HK3 expressive level showed increasing levels of immune cells infiltration, including M2 macrophages, neutrophils, and various subtypes of activated memory CD4+ T cells. Furthermore, HK3 expression was significantly increasing along with the elevated tumor grade, had a higher level in the mesenchymal subtype compared with those in other subtypes of GBM and could independently predict poor outcomes of GBM patients. CONCLUSION: The present work mainly concentrated on the biological role of HK3 in glioma and offered a novel insight of HK3 regulating the activation of immune cells in the glioma microenvironment. These findings could provide a new theoretical evidence for understanding the metabolic molecular within the glioma microenvironment and identifying new therapeutic targets.

Using integrated analysis from multicentre studies to identify RNA methylation-related lncRNA risk stratification systems for glioma.

BACKGROUND: N6-methyladenosine (m6A), 5-methylcytosine (m5C) and N1-methyladenosine (m1A) are the main RNA methylation modifications involved in the progression of cancer. However, it is still unclear whether RNA methylation-related long noncoding RNAs (lncRNAs) affect the prognosis of glioma. METHODS: We summarized 32 m6A/m5C/m1A-related genes and downloaded RNA-seq data and clinical information from The Cancer Genome Atlas (TCGA) database. Differential expression analysis and weighted gene co-expression network analysis (WGCNA) were used to identify differentially expressed (DE-) RNA methylation-related lncRNAs in order to construct a prognostic signature of glioma and in order to determine their correlation with immune function, immune therapy and drug sensitivity. In vitro and in vivo assays were performed to elucidate the effects of RNA methylation-related lncRNAs on glioma. RESULTS: A total of ten RNA methylation-related lncRNAs were used to construct a survival and prognosis signature, which had good independent prediction ability for patients. It was found that the high-risk group had worse overall survival (OS) than the low-risk group in all cohorts. In addition, the risk group informed the immune function, immunotherapy response and drug sensitivity of patients with glioma in different subgroups. Knockdown of RP11-98I9.4 and RP11-752G15.8 induced a more invasive phenotype, accelerated cell growth and apparent resistance to temozolomide (TMZ) both in vitro and in vivo. We observed significantly elevated global RNA m5C and m6A levels in glioma cells. CONCLUSION: Our study determined the prognostic implication of RNA methylation-related lncRNAs in gliomas, established an RNA methylation-related lncRNA prognostic model, and elucidated that RP11-98I9.4 and RP11-752G15.8 could suppress glioma proliferation, migration and TMZ resistance. In the future, these RNA methylation-related lncRNAs may become a new choice for immunotherapy of glioma.

Development and validation of a pyroptosis-related genes signature for risk stratification in gliomas.

Background: Glioma is a highly heterogeneous disease, causing the prognostic prediction a challenge. Pyroptosis, a programmed cell death mediated by gasdermin (GSDM), is characterized by cell swelling and the release of inflammatory factors. Pyroptosis occurs in several types of tumor cells, including gliomas. However, the value of pyroptosis-related genes (PRGs) in the prognosis of glioma remains to be further clarified. Methods: In this study, mRNA expression profiles and clinical data of glioma patients were acquired from TCGA and CGGA databases, and one hundred and eighteen PRGs were obtained from the Molecular Signatures Database and GeneCards. Then, consensus clustering analysis was performed to cluster glioma patients. The least absolute shrinkage and selection operator (LASSO) Cox regression model was used to establish a polygenic signature. Functional verification of the pyroptosis-related gene GSDMD was achieved by gene knockdown and western blotting. Moreover, the immune infiltration status between two different risk groups were analyzed through the "gsva" R package. Results: Our results demonstrated that the majority of PRGs (82.2%) were differentially expressed between lower-grade gliomas (LGG) and glioblastoma (GBM) in the TCGA cohort. In univariate Cox regression analysis, eighty-three PRGs were shown to be associated with overall survival (OS). A five-gene signature was constructed to divide patients into two risk groups. Compared with patients in the low-risk group, patients in the high-risk group had obviously shorter OS (p < 0.001). Also, we found that the high-risk group showed a higher infiltrating score of immune cells and immune-related functions. Risk score was an independent predictor of OS (HR > 1, p < 0.001). Furthermore, knockdown of GSDMD decreased the expression of IL-1ß and cleaved caspase-1. Conclusion: Our study constructed a new PRGs signature, which can be used to predict the prognosis of glioma patients. Targeting pyroptosis might serve as a potential therapeutic strategy for glioma.