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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.

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.

BackgroundMedulloblastoma (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.MethodsGenomic 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.ResultsEccDNA 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.ConclusionsThis 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.

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.

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.

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. [ABSTRACT FROM AUTHOR]

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. [ABSTRACT FROM AUTHOR]

Cooling methods for multiple heat sources with high heat flux have rarely been reported, but such situations threaten the stable operation of electronic devices. Therefore, in this paper, the use of two microchannel heat sinks is proposed, with and without grooves, labeled Type A and Type B, respectively. Experimental investigations on the flow boiling of two microchannel heat sinks connected in parallel and in series are carried out under different mass fluxes. In addition, a high-speed camera is used to observe flow patterns in the microchannels. The cold plate wall temperature (Tw), heat transfer coefficient (HTC), and pressure drop (PD) are obtained with the use of two microchannel heat sinks. The flow patterns of the bubbly flow and elongated bubbles in the microchannels are observed. The results of the analysis indicated that the Tw, HTC, and PD of the two microchannel heat sinks connected in parallel were degraded, especially when using the Type A-B parallel connection. Compared to the use of a single heat sink, the maximum decrease in HTC was 9.44 kW/(m2K) for Type A heat sinks connected in parallel, which represents a decrease of 45.95%. The influence of the series connection on the Tw, HTC, and PD of the two heat sinks is obvious. The Type A-A series connection exerted the greatest positive effect on the performance of the two heat sinks, especially in the case of the postposition heat sink. The maximum increase in HTC was 12.77 kW/(m2K) for the postposition Type A heat sink, representing an increase of 72.88%. These results could provide a reference for a two-phase flow-cooling complex for multiple heat sources with high heat flux.