Bulk and single cells transcriptomes with experimental validation identify USP18 as a novel glioma prognosis and proliferation indicator.

The mechanism by which ubiquitin-specific protease 18 (USP18) (enzyme commission: 3.4.19.12) inhibition in cancer promotes cell pyroptosis via the induction of interferon (IFN)-stimulated genes has been recently demonstrated. It is also known that USP18 influences the epithelial-mesenchymal transition of glioma cells. In the present study, the upregulation of USP18 in glioma was revealed through bulk transcriptome analysis, which was associated with poor prognosis in patients with glioma. Furthermore, USP18 levels affected the response to immunotherapy in patients with glioma. Single-cell transcriptome and enrichment analyses demonstrated that USP18 was associated with type 1 IFN responses in glioma T cells. To demonstrate the effect of USP18 expression levels on glioma cells, USP18 expression was knocked down in U251 and U87MG ATCC cell lines. A subsequent Cell Counting Kit-8 assay revealed that glioma cell viability was significantly decreased 4 days after USP18 knockdown. In addition, the knockdown of USP18 expression significantly inhibited the clonogenicity of U251 and U87MG ATCC cells. In conclusion, the present study demonstrated that knockdown of USP18 expression inhibited the proliferation of glioma cells, which may be mediated by the effect of USP18 on the IFN-I response.

DTX2 promotes glioma development via regulation of HLTF.

BACKGROUND: Human Deltex 2 (DTX2) is a ubiquitin E3 ligase that functions as an oncogene and has been shown to participate in many human cancers. However, the role of DTX2 in glioma progression has remained obscure. In this study, we explore the mechanism underlying the function of DTX2 in glioma progression. METHODS: The associations between DTX2 expression and clinical characteristics of glioma were determined by bioinformatic analysis of data from The Cancer Genome Atlas and Human Protein Atlas. The expression of DTX2 in glioma tissues was detected using immunohistochemistry and western blotting. Lentivirus-mediated gene knockdown and overexpression were used to determine the effects of DTX2 and helicase-like transcription element (HLTF) on glioma cell proliferation and migration with CCK-8, cell colony formation, transwell, and wound healing assays; flow cytometry in vitro; and animal models in vivo. The interaction of the DTX2 and HLTF proteins was verified by immunoprecipitation assay and confocal microscopy. RESULTS: DTX2 was highly expressed in glioma samples, and this was correlated with worse overall survival. Silencing of DTX2 suppressed glioma cell viability, colony formation, and migration and induced cell apoptosis. In vitro ubiquitination assays confirmed that DTX2 could downregulate HLTF protein levels by increasing ubiquitination of the HLTF protein. We also observed that HLTF inhibited proliferation and migration of glioma cells. Subcutaneous xenografts with DTX2-overexpressing U87 cells showed significantly increased tumor volumes and weights. CONCLUSIONS: We have identified DTX2/HLTF as a new axis in the development of glioma that could serve as a prognostic or therapeutic marker.

Integrated bioinformatics analysis and experimental validation identified CDCA families as prognostic biomarkers and sensitive indicators for rapamycin treatment of glioma.

The cell division cycle associated (CDCA) genes regulate the cell cycle; however, their relationship with prognosis in glioma has been poorly reported in the literature. The Cancer Genome Atlas (TCGA) was utilized to probe the CDCA family in relation to the adverse clinical features of glioma. Glioma single-cell atlas reveals specific expression of CDCA3, 4, 5, 8 in malignant cells and CDCA7 in neural progenitor cells (NPC)-like malignant cells. Glioma data from TCGA, the China Glioma Genome Atlas Project (CGGA) and the gene expression omnibus (GEO) database all demonstrated that CDCA2, 3, 4, 5, 7 and 8 are prognostic markers for glioma. Further analysis identified CDCA2, 5 and 8 as independent prognostic factors for glioma. Lasso regression-based risk models for CDCA families demonstrated that high-risk patients were characterized by high tumor mutational burden (TMB), low levels of microsatellite instability (MSI), and low tumor immune dysfunction and rejection (TIDE) scores. These pointed to immunotherapy for glioma as a potentially viable treatment option Further CDCA clustering suggested that the high CDCA subtype exhibited a high macrophage phenotype and was associated with a higher antigen presentation capacity and high levels of immune escape. In addition, hsa-mir-15b-5p was predicted to be common regulator of CDCA3 and CDCA4, which was validated in U87 and U251 cells. Importantly, we found that CDCAs may indicate response to drug treatment, especially rapamycin, in glioma. In summary, our results suggest that CDCAs have potential applications in clinical diagnosis and as drug sensitivity markers in glioma.

The value of basement membrane-associated genes in the prognosis and immune regulation of glioma.

Gliomas have a high incidence rate in central nervous tumors. Although many breakthroughs have been made in the pathogenesis and treatment of glioma, the recurrence and metastasis rates of patients have not been improved based on the uniqueness of glioma. Glioma destroys the surrounding basement membrane (BM), leading to local infiltration, resulting in the corresponding clinical and neurological symptoms. Therefore, exploring the biological roles played by BM associated genes in glioma is particularly necessary for a comprehensive understanding of the biological processes of glioma and its treatment. Differential expression and univariate COX regression analyses were used to identify the basement membrane genes (BMGs) to be included in the model. LASSO regression was used to construct the BMG model. The Kaplan-Meier (KM) survival analysis model was used to assess the prognosis discrimination between training sets, validation sets, and clinical subgroups. Receiver-operating characteristic (ROC) analysis was used to test the prognostic efficacy of the model. Use calibration curves to verify the accuracy of nomograms. Gene ontology (GO), Kyoto encyclopedia of genes and genomes (KEGG), and gene set enrichment analysis (GSEA) were used to analyze the function and pathway enrichment among the model groups. ESTIMATE and other 7 algorithms including CIBERSORT were used to evaluate the immune microenvironment. "pRRophetic" was used to evaluate drug sensitivity. This study demonstrated that high-risk genes (LAMB4, MMP1, MMP7) promote glioma progression and negatively correlate with patient prognosis. In the tumor microenvironment (TME), high-risk genes have increased scores of macrophages, neutrophils, immune checkpoints, chemokines, and chemokine receptors. This study suggests that BMGs, especially high-risk-related genes, are potential sites for glioma therapy, a new prospect for comprehensively understanding the molecular mechanism of glioma.

GBP2 as a potential prognostic predictor with immune-related characteristics in glioma.

Guanylate binding protein 2 (GBP2) is a member of the guanine binding protein family, and its relationship with prognostic outcomes and tumor immune microenvironments in glioma remains elusive. We found GBP2 were increased in glioma tissues at both mRNA and protein levels. Kaplan-Meier curves revealed that high GBP2 expression was linked with worse survival of glioma patients, and multivariate Cox regression analysis indicated that high GBP2 expression was an independent prognostic factor for glioma. Combined analysis in immune database revealed that the expression of GBP2 was significantly related to the level of immune infiltration and immunomodulators. Single-cell analysis illustrated the high expression of GBP2 in malignant glioma cells showed the high antigen presentation capability, which were confirmed by real-time polymerase chain reaction (qRT-PCR) data. Additionally, the hsa-mir-26b-5p and hsa-mir-335-5p were predicted as GBP2 regulators and were validated in U87 and U251 cells. Our results first decipher immune-related characteristics and noncoding regulators of GBP2 in glioma, which may provide insights into associated immunotherapies and prognostic predictor.

GBP2 facilitates the progression of glioma via regulation of KIF22/EGFR signaling.

Identifying the mechanism of glioma progression is critical for diagnosis and treatment. Although studies have shown that guanylate-binding protein 2(GBP2) has critical roles in various cancers, its function in glioma is unclear. In this work, we demonstrate that GBP2 has high expression levels in glioma tissues. In glioma cells, depletion of GBP2 impairs proliferation and migration, whereas overexpression of GBP2 enhances proliferation and migration. Regarding the mechanism, we clarify that epidermal growth factor receptor (EGFR) signaling is regulated by GBP2, and also demonstrate that GBP2 interacts directly with kinesin family member 22(KIF22) and regulates glioma progression through KIF22/EGFR signaling in vitro and in vivo. Therefore, our study provides new insight into glioma progression and paves the way for advances in glioma treatment.

Pleural fluid carcinoembryonic antigen as a biomarker for the discrimination of tumor-related pleural effusion.

OBJECTIVES: To assess the value of tumor biomarkers in the determination of tumor-related pleural effusion (PE). Cytological examination of the pleural fluid has a limited sensitivity in diagnosing tumor PE. METHODS: Pleural fluid and serum samples were obtained from 1137 patients and PE etiology was determined by multiple diagnostic techniques. Carcinoembryonic antigen (CEA) levels were measured in both pleural fluid and serum samples. Levels of cancer antigen (CA) 125, glucose, and lactate dehydrogenase (LDH) were assessed in pleural fluid specimens. RESULTS: 601 PE patients were diagnosed with tumors, while 595 tested individuals were tumor-free. Among the measured biomarkers, pleural fluid CA 125, glucose, and LDH levels, and serum CEA amounts were comparable between tumor and tumor-free PE patients (P > 0.05). Only pleural fluid CEA levels were significantly different between the two groups (P < 0.05). A CEA cutoff of 2.645 ng/mL yielded sensitivity and specificity of 69.4% and 82.2%, respectively, for tumor-related PE detection. The area under the curve for CEA was 0.740 (95%CI: 0.710-0.770). CONCLUSION: CEA levels in pleural fluid were a potential biomarker for the detection of tumor-related PE. These findings provide an easy and simple method for clinical screening and detection of PE.