RUNX1-PDIA5 Axis Promotes Malignant Progression of Glioblastoma by Regulating CCAR1 Protein Expression.

PDIA5 is responsible for modification of disulfide bonds of proteins. However, its impact on the malignant progression of glioblastoma multiforme (GBM) remains unknown. We analyzed the expression and prognostic significance of PDIA5 in cohorts of GBM and clinical samples. The PDIA5 protein was significantly overexpressed in GBM tissues, and higher expression of PDIA5 was statistically associated with a worse prognosis in patients with GBM. Transcriptional data from PDIA5 knockdown GBM cells revealed that downstream regulatory genes of PDIA5 were enriched in malignant regulatory pathways and PDIA5 enhanced the proliferative and invasive abilities of GBM cells. By constructing a PDIA5 CXXC motif mutant plasmid, we found CCAR1 was the vital downstream factor of PDIA5 in regulating GBM malignancy in vitro and in vivo. Additionally, RUNX1 bound to the promoter region of PDIA5 and regulated gene transcription, leading to activation of the PDIA5/CCAR1 regulatory axis in GBM. The RUNX1/PDIA5/CCAR1 axis significantly influenced the malignant behavior of GBM cells. In conclusion, this study comprehensively elucidates the crucial role of PDIA5 in the malignant progression of GBM. Downregulating PDIA5 can mitigate the malignant biological behavior of GBM both in vitro and in vivo, potentially improving the efficacy of treatment for clinical patients with GBM.

S100A9, as a potential predictor of prognosis and immunotherapy response for GBM, promotes the malignant progression of GBM cells and migration of M2 macrophages.

In the past decades, the therapeutic effect of glioblastoma (GBM) has not been significantly improved. Generous evidence indicates that S100A9 has a wide range of functions in tumors, but its exploration in GBM is less. The purpose of this study is to conduct a comprehensive bioinformatics analysis and cytological experiment on S100A9 in GBM. The expression data and clinical data of GBM samples were downloaded from the public database, and comprehensive bioinformatics analysis was performed on S100A9 in GBM using R software. Wound healing assay and transwell assay were used to detect the migration activity of cells, and colony formation assay, EdU staining, and CCK-8 assay were used to detect the proliferation activity of cells. The effect of S100A9 on the migration activity of M2 macrophages was verified by the cell co-culture method. The protein expression was detected by western blotting and immunohistochemical staining. S100A9 is an independent prognostic factor in GBM patients and is related to poor prognosis. It can be used as an effective tool to predict the response of GBM patients to immune checkpoint inhibitors (ICIs). In addition, S100A9 can promote the malignant progression of GBM and the migration of M2 macrophages. On the whole, our study highlights the potential value of S100A9 in predicting prognosis and immunotherapeutic response in GBM patients. More importantly, S100A9 may promote the malignant progress of GBM by involving in some carcinogenic pathways and remodeling the tumor microenvironment (TME).

DNMT3A promotes glioma growth and malignancy via TNF-α/NF-κB signaling pathway.

Background: DNMT3A is the main molecule responsible for DNA methylation in cells. DNMT3A affects the progression of inflammation, degenerative diseases, and malignant tumors, and exhibits significant aberrantly expression in tumor tissues. Methods: Transcriptome data and relevant clinical information were downloaded from The Cancer Genome Atlas (TCGA), Chinese Glioma Genome Atlas (CGGA), and Gene Expression Omnibus (GEO) datasets. Differential expression analysis and prognostic analysis were conducted based on above statistics. We constructed a clinical prognostic model and identified DNMT3A as an independent prognostic factor to accurately predict patient prognosis. Differential gene enrichment analysis revealed that DNMT3A affects the progression of glioma through multiple pathways, among which the tumor necrosis factor-α (TNF-α)/nuclear factor-kappa B (NF-κB) pathway shows a strong correlation. Immunological analysis also revealed a certain correlation between DNMT3A and tumor immunity. We demonstrated through gene editing that DNMT3A can affect the release of TNF-α in cells, thereby affecting the progression of glioma. Functional experiments have also demonstrated that DNMT3A plays a crucial role in tumors. Results: RNA-sequencing and survival analyses of lower-grade glioma (LGG) patients in TCGA, CGGA, and GEO cohorts showed that high DNMT3A expression correlated with poor prognosis of LGG patients. Univariate and multivariate Cox regression analyses showed that DNMT3A expression was an independent prognostic indicator in LGG. The prognosis prediction nomogram with age, World Health Organization (WHO) grading, and DNMT3A expression showed reliable performance in predicting the 1-, 3-, and 5-year overall survival (OS) of LGG patients. Functional enrichment analysis, gene set enrichment analysis (GSEA), and ESTIMATE algorithm analyses showed that DNMT3A expression was associated with the tumor infiltration of immune cells and predicted response to immunotherapy in two immunotherapy cohorts of pan-cancer patients. Furthermore, short hairpin RNA (shRNA)-mediated knockdown of DNMT3A in the LGG cell lines suppressed proliferation, migration, and invasion of LGG cells by downregulating the TNF-α/NF-κB signaling pathway. Conclusions: Our data showed that DNMT3A was a potential prognostic biomarker in glioma. DNMT3A promoted proliferation and malignancy of LGG cells through the TNF-α/NF-κB signaling pathway. DNMT3A is a promising therapeutic target for treating patients with LGG.

WTAP regulates the production of reactive oxygen species, promotes malignant progression, and is closely related to the tumor microenvironment in glioblastoma.

RNA modifications have been substantiated to regulate the majority of physiological activities in the organism, including the metabolism of reactive oxygen species (ROS), which plays an important role in cells. As for the effect of RNA modification genes on ROS metabolism in glioblastoma (GBM), it has not been studied yet. Therefore, this study aims to screen the RNA modification genes that are most related to ROS metabolism and explore their effects on the biological behavior of GBM in vitro. Here, an association between WTAP and ROS metabolism was identified by bioinformatics analysis, and WTAP was highly expressed in GBM tissue compared with normal brain tissue, which was confirmed by western blotting and immunohistochemical staining. When using a ROS inducer to stimulate GBM cells in the WTAP overexpression group, the ROS level increased more significantly and the expression levels of superoxide dismutase 1 (SOD1) and catalase (CAT) also increased. Next, colony formation assay, wound healing assay, and transwell assay were performed to investigate the proliferation, migration, and invasion of GBM cells. The results showed that WTAP, as an oncogene, promoted the malignant progression of GBM cells. Functional enrichment analysis predicted that WTAP was involved in the regulation of tumor/immune-related functional pathways. Western blotting was used to identify that WTAP had a regulatory effect on the phosphorylation of PI3K/Akt signaling. Finally, based on functional enrichment analysis, we further performed immune-related analysis on WTAP. In conclusion, this study analyzed WTAP from three aspects, which provided new ideas for the treatment of GBM.

Pan-cancer analysis: predictive role of TAP1 in cancer prognosis and response to immunotherapy.

BACKGROUND: Transporter associated with antigen processing 1 (TAP1) is a molecule involved in processing and presentation of major histocompatibility complex class I restricted antigens, including tumor-associated antigens. TAP1 participates in tumor immunity, and is aberrantly expressed in multiple cancer types; METHODS: Transcriptome profiles were obtained from The Cancer Genome Atlas and Genotype-Tissue Expression databases. Genetic alterations, protein distribution, and interaction information for TAP1 were downloaded from cBioPortal, Human Protein Atlas and Compartmentalized Protein-Protein Interaction, respectively. Single-cell analyses of TAP1 across cancers were conducted via the Tumor Immune Single-cell Hub website. Gene set enrichment analysis was employed to investigate TAP1-associated functional mechanisms and processes. Immune cell infiltration was explored using Tumor Immune Estimation Resource 2.0. Pan-cancer correlations between TAP1 expression and immunotherapy biomarkers were explored using the Spearman's correlation test. Associations with immunotherapy responses were also investigated using clinicopathological and prognostic information from cohorts of patients with cancer receiving immune checkpoint inhibitors. RESULTS: TAP1 expression was elevated in most cancer types and exhibited distinct prognostic value. Immune cells expressed more TAP1 than malignant cells within most tumors. TAP1 expression was significantly correlated with immune-related pathways, T-lymphocyte infiltration, and immunotherapeutic biomarkers. Clinical cohort validation revealed a significant correlation with immune therapeutic effects and verified the prognostic role of TAP1 in immunotherapy. Western blot assay indicated that TAP1 is upregulated in glioblastoma compared with adjacent normal brain tissues. CONCLUSION: TAP1 is a robust tumor prognostic biomarker and a novel predictor of clinical prognosis and immunotherapeutic responses in various cancer types.

Identification of a robust scoring system based on metabolic genes followed by in-depth validation of ATP1A3 in glioma.

AIMS: In the past few decades, the prognosis of glioma patients has not significantly improved. Therefore, to provide more precise medical services for glioma patients, it is urgent to identify more clinically meaningful subtypes, establish more robust clinical prediction models, and find more effective therapeutic targets. MATERIALS AND METHODS: Four distinct metabolic-associated subtypes were identified by the NMF algorithm based on metabolic genes (MEGs). A robust scoring system was constructed based on the differentially expressed genes (DEGs) screened from the four metabolic-associated subtypes with the LASSO regression algorithm and multivariate Cox regression analysis. Further analysis of scoring systems was done by different R packages. In addition, the ATP1A3 gene was screened and bioinformatics analysis of it was conducted on several public websites. GSEA software was utilized to search hallmark signaling pathways closely related to ATP1A3. Cytological experiments were used to investigate the role of ATP1A3 in the malignant progression of glioblastoma (GBM) cells. KEY FINDINGS: Four metabolic-associated subtypes with significantly different clinicopathological characteristics were identified, and a robust scoring system with outstanding clinical application value was established. In addition, a tumor suppressor gene ATP1A3 was found, which is expected to be a potential therapeutic target for glioma. SIGNIFICANCE: This study is of great significance in the diagnosis, prognosis, and prediction of the response to immune checkpoint blockers (ICBs) for glioma patients. More importantly, this study found a potential therapeutic target for glioma.

Ferroptosis in tumor immunity and therapy.

Ferroptosis is a type of regulated cell death (RCD), and it plays an important role in the occurrence of diseases, especially the development of tumors. Ferroptosis of tumor cells affects the antitumor immunity and the immune response to treatment to varying degrees. Ferroptosis also plays a key role in immune cells. This review outlines the mechanism of the immune-related effects of ferroptosis pathways in tumor progression and treatment, and it discusses potential methods for improving antitumor immunity and enhancing the efficacy of current cancer treatments by targeting ferroptosis.

Intrinsic immune evasion patterns predict temozolomide sensitivity and immunotherapy response in lower-grade gliomas.

BACKGROUND: Although intrinsic immune-evasion is important in cancer proliferation, metastasis and response to treatment, it is unclear whether intrinsic immune-evasion patterns of gliomas can aid in predicting clinical prognosis and determining treatment. METHODS: A total of 182 immune-evasion genes intrinsic to cancer were subjected to consensus clustering to identify immune-evasion patterns in 1421 patients with lower-grade glioma (LGG). The levels of each cancer hallmark were determined by the Gene Set Variant Analysis (GSVA) method, and immune cell infiltrations were quantified using two algorithms, the single-sample Gene Set Enrichment Analysis (ssGSEA) and the Cell-type Identification By Estimating Relative Subsets Of RNA Transcripts (CIBERSORT) methods. IEVscore was determined by a method that combined univariate Cox regression analysis, least absolute shrinkage and selection operator (LASSO) regression and principal component analysis (PCA). RESULTS: Transcriptional and genomic analysis showed that most immune evasion genes (IEVGs) were upregulated in LGGs, with aberrant expression driven by alterations in copy number variants (CNV). Based on the mRNA expression profiles of cancer-intrinsic IEVGs could be divided into three LGG subgroups with distinct prognosis, clinicopathological features and immune infiltrations. A combined scoring scheme designed to assess the immune-evasion levels of LGGs divided these 1421 patients into two subgroups that differed in IEVscores. LGG patients with low-IEVscore had a better prognosis, would be more likely to benefit from immune check-point inhibitors and would be more susceptible to temozolomide (TMZ) chemotherapy. CONCLUSION: Intrinsic immune evasion in the tumor microenvironment (TME) has a crucial effect on glioma formation. Quantitatively assessing the IEV scores of individual LGG patients could enhance knowledge about the intra-glioma microenvironment and lead to the development of individualized therapeutic strategies for patients with LGG.

Immune Characteristics and Prognosis Analysis of the Proteasome 20S Subunit Beta 9 in Lower-Grade Gliomas.

Glioma is a common intracranial malignancy in adults and has a high mortality due to its poor prognosis and high recurrence rate. Dysregulation of protein degradation is one of the main promoting factors in glioma development. As an indispensable unit of the proteasome, Proteasome 20S Subunit Beta 9 (PSMB9) is one of the major enzymes in ubiquitin-dependent protein degradation in cells. In addition, proteasomes also participate in a series of cellular processing, like immune regulation, nerve signal transduction, material transport through channels, cell adhesion, and various signaling pathways. However, the relationship between the PSMB9 expression and the occurrence of lower-grade glioma (LGG) is still unknown. First, we collected the RNA-seq and clinical information about LGG clinical samples from The Cancer Genome Atlas (TCGA) cohort, Chinese Glioma Genome Atlas (CGGA; including CGGAseq1 and CGGAseq2) cohort, and Gene Expression Omnibus (GEO; GSE16011, GSE61374, and Rembrandt) cohort. Then, these data were used for differential analysis, survival analysis, enrichment analysis, clinical model construction, etc. In addition, we combine immune-related data for immune-related analysis, including immune infiltration and immunotherapy. Through the above research, we have provided a new biomarker for LGG prognosis prediction and more comprehensively explained the role of PSMB9 in the development of LGG. This study determined that PSMB9 can be used as an immunotherapy target through the analysis of immune data, providing new ideas for the clinical treatment of LGG.

CLCF1 Is a Novel Potential Immune-Related Target With Predictive Value for Prognosis and Immunotherapy Response in Glioma.

Background: Cardiotrophin-like cytokine factor 1 (CLCF1) has been described as an oncogene and a potential therapeutic target in a variety of cancers, but its role in glioma remains unknown. Methods: Based on The Cancer Genome Atlas (TCGA), we conducted a bioinformatics analysis to investigate the clinical significance and biological functions of CLCF1 in glioma at the transcriptional level and predicted the response to immunotherapy of glioma patients with different CLCF1 expression levels. All the results were further verified in Chinese Glioma Genome Altas(CGGA) Data processing and figure generating were performed with R language. Results: Elevated CLCF1 expression was common in cancers and usually predicted poor prognosis, which was also consistent with gliomas. In Univariate Cox Regression analysis and Kaplan-Meier survival analysis, tumor patients with higher CLCF1 expression tended to experience a worse prognosis. In the multivariate Cox proportional hazard model, the expression of CLCF1 was an independent prognostic factor in gliomas. The biological function analysis of CLCF1 in glioma showed that CLCF1 was closely associated with immune signatures, including immune-related pathways, immune cell infiltration, and immune checkpoints. Moreover, glioma patients with low CLCF1 expression showed a greater tendency to respond to anti-PD1/PD-L1 immunotherapy, indicating CLCF1 also had potential clinical significance in guiding immunotherapy. And CLCF1 as a member of the IL6 family had a better predictive value for prognosis and immunotherapy response in glioma than that of IL6 and other IL6 family members. Conclusion: CLCF1 expression is an independent prognosticator and a promising therapeutic target correlated with immunotherapy in glioma.