Mass spectrometry-based proteomic analysis reveals the interacting partners of lipin1

Biosynthesis and Significance of Fatty Acids, Glycerophospholipids, and Triacylglycerol in the Processes of Glioblastoma Tumorigenesis

One area of glioblastoma research is the metabolism of tumor cells and detecting differences between tumor and healthy brain tissue metabolism. Here, we review differences in fatty acid metabolism, with a particular focus on the biosynthesis of saturated fatty acids (SFA), monounsaturated fatty acids (MUFA), and polyunsaturated fatty acids (PUFA) by fatty acid synthase (FASN), elongases, and desaturases. We also describe the significance of individual fatty acids in glioblastoma tumorigenesis, as well as the importance of glycerophospholipid and triacylglycerol synthesis in this process. Specifically, we show the significance and function of various isoforms of glycerol-3-phosphate acyltransferases (GPAT), 1-acylglycerol-3-phosphate O-acyltransferases (AGPAT), lipins, as well as enzymes involved in the synthesis of phosphatidylcholine (PC), phosphatidylethanolamine (PE), phosphatidylserine (PS), phosphatidylinositol (PI), and cardiolipin (CL). This review also highlights the involvement of diacylglycerol O-acyltransferase (DGAT) in triacylglycerol biosynthesis. Due to significant gaps in knowledge, the GEPIA database was utilized to demonstrate the significance of individual enzymes in glioblastoma tumorigenesis. Finally, we also describe the significance of lipid droplets in glioblastoma and the impact of fatty acid synthesis, particularly docosahexaenoic acid (DHA), on cell membrane fluidity and signal transduction from the epidermal growth factor receptor (EGFR).

High Levels of HIST1H2BK in Low-Grade Glioma Predicts Poor Prognosis: A Study Using CGGA and TCGA Data

A number of biomarkers have been identified for various cancers. However, biomarkers associated with glioma remain largely to be explored. In the current study, we investigated the relationship between the expression and prognostic value of the HIST1H2BK gene in glioma. Sequential data filtering (survival analysis, independent prognostic analysis, ROC curve analysis, and clinical correlation analysis) was performed, which resulted in identification of the association between the HIST1H2BK gene and glioma. Then, the HIST1H2BK gene was analyzed using bioinformatics (Kaplan–Meier survival analysis, univariate Cox analysis, multivariate Cox analysis, and ROC curve analysis). The results showed that low expression of HIST1H2BK was associated with better prognosis, and high expression of HIST1H2BK was associated with poor prognosis. In addition, HIST1H2BK was an independent prognostic indicator for patients with glioma. We also evaluated the association between HIST1H2BK and clinical characteristics. Furthermore, gene set enrichment analysis (GSEA) and analysis of immune infiltration were performed. The results showed that HIST1H2BK was associated with intensity of immune infiltration in glioma. Finally, co-expression analysis was performed. The results showed that HIST1H2BK was positively correlated with HIST1H2AG, HIST2H2AA4, HIST1H2BJ, HIST2H2BE, and HIST1H2AC, and negatively correlated with PDZD4, CRY2, GABBR1, rp5-1119a7.17, and KCNJ11. This study showed that upregulation of HIST1H2BK in low-grade glioma (LGG) tissue was an indicator of poor prognosis. Moreover, this study demonstrated that HIST1H2BK may be a promising biomarker for the treatment of LGG.