Cuproptosis-related gene SLC31A1 expression correlates with the prognosis and tumor immune microenvironment in glioma.

Cuproptosis is a newly discovered form of cell death. It is regulated by a string of genes. The genes are identified to influence the tumor progression, but in glioma, the cuproptosis-related genes are little studied. The Cancer Genome Atlas (TCGA) and the Genotype-Tissue Expression (GTEx) were used to screen for SLC31A1 gene expression in glioma and healthy tissue samples. The results were validated using the Gene Expression Omnibus (GEO) and quantitative real-time polymerase chain reaction (qPCR). The Human Protein Atlas (HPA) and the National Cancer Institute's Clinical Proteomic Tumor Analysis Consortium (CPTAC) were used to validate our results at the protein level. Multivariable analysis and Kaplan-Meier survival curves were used to examine the relationship among SLC31A1 gene expression, clinical parameters, and survival rates. The online Search Tool for the Retrieval of Interacting Genes/Proteins (STRING) was used to find the genes and proteins that correlate to SLC31A1. The immune infiltration analysis was performed using the Tumor Immune Estimation Resource (TIMER) databases. Small interfering RNA was used to knock down the SLC31A1 expression, and the cell proliferation, apoptosis, and migration were analyzed using cell counting kit-8, flow cytometry, and transwell. The glioma patients have higher SLC31A1 expression levels, which increase as the World Health Organization (WHO) grade escalates. The survival analysis illustrates that the SLC31A1 gene expression negatively correlates with overall survival (OS), progression-free survival (PFS), and disease-specific survival (DSS). The immune infiltration analysis shows the SLC31A1 gene positively correlates with T helper 2 (Th2) cells, macrophages, and M2-type macrophages and negatively correlates with plasmacytoid dendritic cells (pDCs), natural killer (NK) CD56bright cells, and CD8 T cells. The in vitro KD experiment shows the SLC31A1 knockdown depressed the glioma cell proliferation and migration and promoted the apoptosis rate. The SLC31A1 gene expression can shorten the survival time of glioma patients. In vitro study shows that SLC31A1 can promote cell proliferation, and migration, and depress the cell apoptosis of glioma cells. It also can promote the formation of a tumor-suppressive microenvironment.

Oncolytic virus Ad-TD-nsIL-12 inhibits glioma growth and reprograms the tumor immune microenvironment.

AIMS: Gliomas are the most common central nervous system malignancies, with limited therapeutic options and poor prognosis, which are primarily attributed to the "immune desert" microenvironment. Previously, we constructed a three-gene-deleted oncolytic adenovirus (Ad-TD) loaded with non-secreting interleukin-12 (nsIL-12), which could be amplified in tumor cells and induce immunity to suppress tumors. However, the effects of this oncolytic virus on gliomas and their immune microenvironment remain unclear. There is an urgent need for further research. MATERIALS AND METHODS: We constructed a Syrian hamster brain tumor model and demonstrated the efficacy and mechanism of the novel oncolytic virus in treating brain tumors through a series of in vitro and in vivo experiments. We investigated the efficacy and safety (the number of hamsters in each group is either 5 or 10) of the oncolytic virus treatment in Syrian hamsters using a virus-treated group, a control virus-treated group, and a blank control group. KEY FINDINGS: In vitro assays showed that Ad-TD-nsIL-12 could specifically proliferate in brain tumor cells which induce tumor cell apoptosis and intracellular expression of interleukin (IL)-12. Moreover, in vivo experiments demonstrated that Ad-TD-nsIL-12 could effectively inhibit the progression of brain tumors and prolong survival. Ad-TD-nsIL-12 significantly enhanced T-cell infiltration in the brain tumor microenvironment. SIGNIFICANCE: Ad-TD-nsIL-12 can inhibit glioma progression and increase T-cell infiltration in the tumor tissue, particularly infiltration by cytotoxic T cells (CD8+). Ad-TD-nsIL-12 can amplify and produce IL-12, inducing anti-glioma immune responses to inhibit tumor progression.

Immune Microenvironment and Immunotherapies for Diffuse Intrinsic Pontine Glioma.

Diffuse intrinsic pontine glioma (DIPG) is a primary glial glioma that occurs in all age groups but predominates in children and is the main cause of solid tumor-related childhood mortality. Due to its rapid progression, the inability to operate and insensitivity to most chemotherapies, there is a lack of effective treatment methods in clinical practice for DIPG patients. The prognosis of DIPG patients is extremely poor, with a median survival time of no more than 12 months. In recent years, there have been continuous breakthroughs for immunotherapies in various hematological tumors and malignant solid tumors with extremely poor prognoses, which provides new insights into tumors without effective treatment strategies. Meanwhile, with the gradual development of stereotactic biopsy techniques, it is gradually becoming easier and safer to obtain live DIPG tissue, and the understanding of the immune properties of DIPG has also increased. On this basis, a series of immunotherapy studies of DIPG are under way, some of which have shown encouraging results. Herein, we review the current understanding of the immune characteristics of DIPG and critically reveal the limitations of current immune research, as well as the opportunities and challenges for immunological therapies in DIPG, hoping to clarify the development of novel immunotherapies for DIPG treatment.

Remdesivir inhibits the progression of glioblastoma by enhancing endoplasmic reticulum stress.

Glioblastoma (GBM) is one of the most aggressive primary malignant brain tumors. The major challenge is the lack of effective therapeutic drugs due to the blood-brain barrier (BBB) and tumor heterogeneity. Remdesivir (RDV), a new member of the nucleotide analog family, has previously been shown to have excellent antiviral effects and BBB penetration, and was predicted here to have anti-GBM effects. In vitro experiments, RDV significantly inhibited the growth of GBM cells, with IC50 values markedly lower than those of normal cell lines or the same cell lines treated with temozolomide. Moreover, in multiple mouse models, RDV not only distinctly inhibited the progression and improved the prognosis of GBM but also exhibited a promising biosafety profile, as manifested by the lack of significant body weight loss, liver or kidney dysfunction or organ structural damage after administration. Furthermore, we investigated the anti-GBM mechanism by RNA-seq and identified that RDV might induce apoptosis of GBM cells by enhancing endoplasmic reticulum (ER) stress and activating the PERK-mediated unfolded protein response. In conclusion, our results indicated that RDV might serve as a novel agent for GBM treatment by increasing ER stress and inducing apoptosis in GBM cells.

Mutation-derived, genomic instability-associated lncRNAs are prognostic markers in gliomas.

Background: Gliomas are the most commonly-detected malignant tumors of the brain. They contain abundant long non-coding RNAs (lncRNAs), which are valuable cancer biomarkers. LncRNAs may be involved in genomic instability; however, their specific role and mechanism in gliomas remains unclear. LncRNAs that are related to genomic instability have not been reported in gliomas. Methods: The transcriptome data from The Cancer Genome Atlas (TCGA) database were analyzed. The co-expression network of genomic instability-related lncRNAs and mRNA was established, and the model of genomic instability-related lncRNA was identified by univariate Cox regression and LASSO analyses. Based on the median risk score obtained in the training set, we divided the samples into high-risk and low-risk groups and proved the survival prediction ability of genomic instability-related lncRNA signatures. The results were verified in the external data set. Finally, a real-time quantitative polymerase chain reaction assay was performed to validate the signature. Results: The signatures of 17 lncRNAs (LINC01579, AL022344.1, AC025171.5, LINC01116, MIR155HG, AC131097.3, LINC00906, CYTOR, AC015540.1, SLC25A21.AS1, H19, AL133415.1, SNHG18, FOXD3.AS1, LINC02593, AL354919.2 and CRNDE) related to genomic instability were identified. In the internal data set and Gene Expression Omnibus (GEO) external data set, the low-risk group showed better survival than the high-risk group (P < 0.001). In addition, this feature was identified as an independent risk factor, showing its independent prognostic value with different clinical stratifications. The majority of patients in the low-risk group had isocitrate dehydrogenase 1 (IDH1) mutations. The expression levels of these lncRNAs were significantly higher in glioblastoma cell lines than in normal cells. Conclusions: Our study shows that the signature of 17 lncRNAs related to genomic instability has prognostic value for gliomas and could provide a potential therapeutic method for glioblastoma.

Identification of N6-Methyladenosine-Related lncRNAs as a Prognostic Signature in Glioma.

N6-methyladenosine (m6A) modification is the most abundant modification in long noncoding RNAs (lncRNAs). Current studies have shown that the abnormal expression of m6A-related genes is closely associated with the tumorigenesis and progression of glioma. However, the role of m6A-related lncRNAs in glioma development is still unclear. Herein, we screened 566 m6A-related lncRNAs in glioma from The Cancer Genome Atlas (TCGA) database. The expression pattern of these lncRNAs could cluster samples into two groups, in which various classical tumor-related functions and the tumor immune microenvironment were significantly different. Subsequently, a nine-factor m6A-related lncRNA prognostic signature (MLPS) was constructed by using a LASSO regression analysis in the training set and was validated in the test set and independent datasets. The AUC values of the MLPS were 0.881, 0.918 and 0.887 for 1-, 3- and 5-year survival in the training set, respectively, and 0.856, 0.916 and 0.909 for 1-, 3-, and 5-year survival in the test set, respectively. Stratification analyses of the MLPS illustrated its prognostic performance in gliomas with different characteristics. Correlation analyses showed that the infiltrations of monocytes and tumor-associated macrophages (TAMs) were significantly relevant to the risk score in the MLPS. Moreover, we detected the expression of four MLPS factors with defined sequences in glioma and normal cells by using RT-PCR. Afterwards, we investigated the functions of LNCTAM34A (one of the MLPS factors) in glioma cells, which have rarely been reported. Via in vitro experiments, LNCTAM34A was demonstrated to promote the proliferation, migration and epithelial-mesenchymal transition (EMT) of glioma cells. Overall, our study revealed the critical role of m6A-related lncRNAs in glioma and elucidated that LNCTAM34A could promote glioma proliferation, migration and EMT.

Whole-genome sequencing of extrachromosomal circular DNA of cerebrospinal fluid of medulloblastoma.

Background: Medulloblastoma (MB) is a malignant tumor associated with a poor prognosis in part due to a lack of effective detection methods. Extrachromosomal circular DNA (eccDNA) has been associated with multiple tumors. Nonetheless, little is currently known on eccDNA in MB. Methods: Genomic features of eccDNAs were identified in MB tissues and matched cerebrospinal fluid (CSF) and compared with corresponding normal samples using Circle map. The nucleotides on both sides of the eccDNAs' breakpoint were analyzed to understand the mechanisms of eccDNA formation. Bioinformatics analysis combined with the Gene Expression Omnibus (GEO) database identified features of eccDNA-related genes in MB. Lasso Cox regression model, univariate and multivariate Cox regression analysis, time-dependent ROC, and Kaplan-Meier curve were used to assess the potential diagnostic and prognostic value of the hub genes. Results: EccDNA was profiled in matched tumor and CSF samples from MB patients, and control, eccDNA-related genes enriched in MB were identified. The distribution of eccDNAs in the genome was closely related to gene density and the mechanism of eccDNA formation was evaluated. EccDNAs in CSF exhibited similar distribution with matched MB tissues but were differentially expressed between tumor and normal. Ten hub genes prominent in both the eccDNA dataset and the GEO database were selected to classify MB patients to either high- or low-risk groups, and a prognostic nomogram was thus established. Conclusions: This study provides preliminary evidence of the characteristics and formation mechanism of eccDNAs in MB and CSF. Importantly, eccDNA-associated hub genes in CSF could be used as diagnostic and prognostic biomarkers for MB.

Development of a prognostic model based on an immunogenomic landscape analysis of medulloblastoma.

Medulloblastoma (MB) is one of the most common central nervous system tumors in children. At present, the vital role of immune abnormalities has been proved in tumorigenesis and progression. However, the immune mechanism in MB is still poorly understood. In the present study, 51 differentially expressed immune-related genes (DE-IRGs) and 226 survival associated immune-related genes (Sur-IRGs) were screened by an integrated analysis of multi-array. Moreover, the potential pathways were enriched by functional analysis, such as 'cytokine-cytokine receptor interaction', 'Ras signaling pathway', 'PI3K-Akt signaling pathway' and 'pathways in cancer'. Furthermore, 10 core IRGs were identified from DE-IRGs and Sur-IRGs. And the potential regulatory mechanisms of core IRGs were also explored. Additionally, a new prognostic model, including 7 genes (HDGF, CSK, PNOC, S100A13, RORB, FPR1, and ICAM2) based on IRGs, was established by multivariable COX analysis. In summary, our study revealed the underlying immune mechanism of MB. Moreover, we developed a prognostic model associated with clinical characteristics and could reflect the infiltration of immune cells.

Comprehensive Analyses of Glucose Metabolism in Glioma Reveal the Glioma-Promoting Effect of GALM.

Glioma is the most common tumor with the worst prognosis in the central nervous system. Current studies showed that glucose metabolism could affect the malignant progression of tumors. However, the study on the dysregulation of glucose metabolism in glioma is still limited. Herein, we firstly screened 48 differentially expressed glucose metabolism-related genes (DE-GMGs) by comparing glioblastomas to low-grade gliomas. Then a glucose metabolism-related gene (GMG)-based model (PC, lactate dehydrogenase A (LDHA), glucuronidase beta (GUSB), galactosidase beta 1 (GLB1), galactose mutarotase (GALM), or fructose-bisphosphatase 1 (FBP1)) was constructed by a protein-protein interaction (PPI) network and Lasso regression. Thereinto, the high-risk group encountered a worse prognosis than the low-risk group, and the M2 macrophage was positively relevant to the risk score. Various classical tumor-related functions were enriched by Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) analyses. Since protein GALM was rarely studied in glioma, we detected high expression of GALM by western blot and immunohistochemistry in glioma tissues. And experiments in vitro showed that GALM could promote the epithelial-to-mesenchymal transition (EMT) process of glioma cells and could be regulated by TNFAIP3 in glioma cells. Overall, our study revealed the critical role of glucose metabolism in the prognosis of patients with glioma. Furthermore, we demonstrated that GALM was significantly related to the malignancy of glioma and could promote glioma cells' EMT process.

Tumor-associated macrophages based signaling pathway analysis and hub genes identification in glioma.

ABSTRACT: Tumor-associated macrophages (TAMs) play a crucial role in the immune response to many malignancies, but the signaling pathways by which the glioma microenvironment cross-talk with TAMs are poorly understood. The aim of this study was to uncover the potential signaling pathways of the regulation of TAMs and identify candidate targets for therapeutic intervention of glioma through bioinformatics analysis.Chinese Glioma Genome Atlas (CGGA) and The Cancer Genome Atlas (TCGA) datasets were used to download RNA-Seq data and microarray data of human glioma specimen. Differentially expressed genes (DEGs) between CD68-high samples and CD68-low samples were sorted. Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analysis of the DEGs was conducted. Protein-protein interaction (PPI) network were formed to identify the hub genes.The prognostic value of TAMs in glioma patients was confirmed. A total of 477 specific DEGs were sorted. The signaling pathway was identified in pathway enrichment and the DEGs showed prominent representations of immune response networks in glioma. The hub genes including C3, IL6, ITGB2, PTAFR, TIMP1 and VAMP8 were identified form the PPI network and they were all correlated positively with the expression of CD68 and showed the excellent prognostic value in glioma patients.TAMs can be used as a good prognostic indicator in glioma patients. By analyzing comprehensive bioinformatics data, we uncovered the underlying signaling pathway of the DEGs between glioma patients with high and low expression level of CD68. Furthermore, the 6 hub genes identified were closely associated with TAMs in glioma microenvironment and need further investigation.