The general control of nucleotide synthesis 5 (GCN5), which is one kind of lysine acetyltransferases, regulates a number of cellular processes, such as cell proliferation, differentiation, cell cycle and DNA damage repair. However, its biological role in human glioma development remains elusive. In the present study, we firstly reported that GCN5 was frequently overexpressed in human glioma tissues and GCN5 was positively correlated with proliferation of cell nuclear antigen PCNA and matrix metallopeptidase MMP9. Meanwhile, down-regulation of GCN5 by siRNA interfering inhibited glioma cell proliferation and invasion. In addition, GCN5 knockdown reduced expression of p-STAT3, p-AKT, PCNA and MMP9 and increased the expression of p21 in glioma cells. In conclusion, GCN5 exhibited critical roles in glioma development by regulating cell proliferation and invasion, which suggested that GCN5 might be a potential molecular target for glioma treatment.

Ferroptosis is an iron-dependent programmed cell death related to the biological process of many kinds of tumors. Long noncoding RNAs (LncRNA) have been found to play essential roles in the tumor, and their functions in the ferroptosis of tumor cells have been partially discovered. However, there is no summary of ferroptosis-related LncRNA and its functions in melanoma. In the present study, we aim to explore the expression profile of ferroptosis-related LncRNA genes and their value in melanoma prognosis by bioinformatics analysis. The expression of ferroptosis-related gene (FRG) from melanoma clinical data was extracted based on the Cancer Genome Atlas (TCGA) database. By screening the RNA expression data of 472 cases of melanoma and 810 cases of normal skin, eighteen ferroptosis-related differential genes were found to be related to the overall survival rate. Furthermore, 384 ferroptosis-related LncRNAs were discovered through constructing the mRNA-LncRNA co-expression network, and ten of them were found with prognostic significance in melanoma by multivariate Cox analysis. Risk assessment showed that the high expression of LncRNA00520 is associated with poor prognosis, while the increased expression of the other LncRNA is beneficial to the prognosis of patients with melanoma. From univariate and multivariate Cox regression analysis, there were ten ferroptosis-related LncRNA risk models towards to be significant independent prognostic factors for patients with melanoma and valuable predictive factors for overall survival (OS)(P<0.05). The ROC curve further suggested that the risk score has relatively reliable predictive ability (AUC=0.718). The protein level of ferroptosis-related genes was verified by the HPA database and IHC test, leading to the discovery that the expressions of ALOX5, PEBP1, ACSL4, and ZEB1 proteins up-regulated in tumor tissues, and existed differences between tumor tissues and normal tissues. In conclusion, we identified ten ferroptosis-related LncRNA and constructed a prognosis model base.

Background Glioma, a common primary brain tumor arising from glial cells, presents significant therapeutic challenges due to its diverse and complex biological behavior. While disulfidptosis has recently emerged as a novel form of cell death, the role of disulfidptosis-related genes (DRGs) in glioma and their relationship with the tumor immune microenvironment remains poorly understood. Methods We analyzed DRGs expression patterns in glioma samples and their correlation with patient survival using data from TCGA, GEO, and CGGA databases. We employed ROC curve analysis to evaluate the diagnostic potential of individual DRGs and identify hub genes. We investigated the relationship between hub gene expression and immune cell infiltration through immune infiltration analysis. Additionally, we conducted drug sensitivity analysis and molecular docking to explore associations between hub gene expression and drug responsiveness. Finally, we validated DRGs expression in glioma samples using RT-PCR and tissue microarrays. Results Among the ten DRGs examined, six genes (OXSM, SLC3A2, RPN1, NDUFS1, GYS1, and LRPPRC) showed significant differential expression in glioma tissues, while four (NCKAP1, NDUFA11, NUBPL, and SLC7A11) did not. Survival analysis revealed that elevated expression of OXSM, RPN1, GYS1, SLC3A2, and NDUFA11 correlated with poor patient outcomes. ROC analysis of both TCGA test and GEO validation sets identified OXSM as a hub gene, with AUC values exceeding 0.88. CGGA database analysis demonstrated higher OXSM expression in GBM compared to LGG, with peak expression in WHO grade IV tumors, significantly correlating with reduced overall survival (p < 0.01). Immune infiltration analysis showed that OXSM expression correlated with various immune cell populations, particularly significantly positively correlated with macrophages M0, M2, and T cells gamma delta, and significantly negatively correlated with monocytes. Drug sensitivity analysis indicated that high OXSM expression enhanced sensitivity to several therapeutic agents. RT-PCR and tissue microarray analyses confirmed elevated OXSM expression in high-grade gliomas. Conclusion Our study identifies OXSM as a key DRG hub gene in glioma, with elevated expression strongly correlating with poor patient prognosis. The observed relationship between OXSM expression and immune cell infiltration suggests its potential role in modulating the glioma microenvironment. These findings advance our understanding of glioma’s molecular mechanisms and may inform the development of novel therapeutic strategies.

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Introduction: Super-enhancers play crucial roles in tumor development as key transcriptional regulatory elements, yet their prognostic value in bladder cancer (BLCA) remains to be systematically elucidated. Objective: This study aimed to comprehensively analyze the regulatory mechanisms of super-enhancer-related genes (SERGs) in predicting BLCA prognosis and immune therapy response. Methods: This study integrated BLCA RNA sequencing data from the cancer genome atlas (training set) and gene expression omnibus (validation set) databases and obtained SERG sets from the SEdb database. Using 101 machine learning ensemble frameworks, we screened and validated SERG sets with significant prognostic value and constructed a risk score model was constructed based on based on CoxBoost and plsRcox. Model performance was evaluated through nomograms. We conducted an in-depth analysis of the association between the risk model and tumor immune microenvironment, identified key hub genes through differential expression analysis, survival analysis, and receiver operating characteristic curve analysis, and performed multi-dimensional validation using immunohistochemistry and single-cell sequencing data. Results: Through machine learning algorithm optimization, we identified eight core genes (AHNAK, NT5DC3, NFIC, MTHFD1L, C1QTNF6, SLC45A3, QRICH2, KRT8). High-risk group patients exhibited poor prognosis and elevated immune and tumor immune dysfunction and exclusion scores, suggesting potential immune therapy resistance. The single-sample gene set enrichment analysis analysis revealed significant positive correlations between risk scores and multiple key signaling pathways, including extracellular matrix-receptor interaction, regulation of actin cytoskeleton, and pathogenic Escherichia coli infection, focal adhesion, melanoma, and gap junction pathways. Further analysis indicated that C1QTNF6 and MTHFD1L displayed significant potential as biomarkers based on expression profiles across cell types. Conclusion: This study pioneered the construction of a prognostic prediction model for BLCA based on SERGs, revealing the crucial role of super-enhancers in regulating the tumor immune microenvironment and identifying potential therapeutic targets and prognostic markers. This research provides a new molecular typing strategy for the precision treatment of BLCA while establishing a theoretical foundation for personalized immunotherapy.