Prognosis Of Glioblastoma Multiforme Research Articles

H19- and hsa-miR-338-3p-mediated NRP1 expression is an independent predictor of poor prognosis in glioblastoma.

Glioblastoma multiforme (GBM) is the most common and also the most invasive brain cancer. GBM progression is rapid and its prognosis is poor. Therefore, finding molecular targets in GBM is a critical goal that could also play important roles in clinical diagnostics and treatments to improve patient prognosis. We jointly analyzed the GSE103227, GSE103229, and TCGA databases for differentially expressed RNA species, obtaining 52 long non-coding RNAs (lncRNAs), 31 microRNAs (miRNAs), and 186 mRNAs, which were used to build a competing endogenous RNA network. Kaplan–Meier and receiver operating characteristic (ROC) analyses revealed five survival-related lncRNAs: H19, LINC01574, LINC01614, RNF144A-AS1, and OSMR-AS1. With multiple optimization mRNAs, we found the H19-hsa-miR-338-3P-NRP1 regulatory pathway. Additionally, we noted high NRP1 expression in GBM patients, and Kaplan–Meier and ROC analyses showed that NRP1 expression was associated with GBM prognosis. Cox analysis indicated that NRP1 is an independent prognostic factor in GBM patients. In conclusion, H19 and hsa-miR-338-3P regulate NRP1 expression, and this pathway plays an important role in GBM.

CBIO-15. LOSS OF WILLIAMS SYNDROME TRANSCRIPTION FACTOR (WSTF) LEADS TO IMPROVED TEMOZOLOMIDE SENSITIVITY IN HUMAN GLIOBLASTOMA CELLS IRRESPECTIVE OF MGMT EXPRESSION

Abstract BACKGROUND The prognosis for glioblastoma multiforme (GBM) patients is poor with a median survival of approximately 15 months. The DNA repair protein O 6-methylguanine-DNA methyltransferase (MGMT) counteracts the effects of temozolomide (TMZ) chemotherapy and is thus associated with poor outcome in GBM patients. Williams Syndrome Transcription Factor (WSTF) has been suggested to regulate the DNA damage response pathway (DDR) in both an indirect (through chromatin remodeling) and direct manner (by phosphorylating H2AX at Tyr142). However, whether WSTF has any role in the development of resistance against chemotherapy through its functions in the DDR in GBMs, is so far unknown. In this study, we investigated whether a loss of WSTF sensitizes different MGMT-proficient and -deficient GBM cell lines to TMZ treatment. METHODS We generated WSTF knockout clones from both MGMT-proficient (LN18, T98G) and -deficient GBM cell lines (U-251) using CRISPR/Cas9 gene-editing technology with lentiviral vectors. The PCR-based screening results combined with the T7 endonuclease mismatch assay for bi-allelic monoclonal knockouts were verified via sequencing and immunoblotting to identify candidate knockout clones. Colony formation assays were performed to determine the survival ability in response to TMZ treatment. Statistical analysis was performed using two-way ANOVA. RESULTS WSTF knockout clones showed a significant decrease in colony formation after TMZ-treatment compared to the corresponding control groups (non-target single guide RNA) (LN18: Clone 59 vs control: p= 0.0456, T98G: All three studied clones vs control: p< 0.0001, U-251: Clone 7/35.1/70.2 vs control: p< 0.0001/p= 0.0107/p= 0.0119). CONCLUSION WSTF is an important factor in both MGMT de- and proficient GBM cell lines for response against TMZ chemotherapy. The loss of WSTF leads to a significantly increased TMZ sensitivity in clinically relevant concentrations for all the studied cell lines. Ongoing studies are investigating the underlying mechanisms and potential alterations in the DDR pathway caused by WSTF loss.

Development of a 3 RNA Binding Protein Signature for Predicting Prognosis and Treatment Response for Glioblastoma Multiforme.

Purpose: Glioblastoma multiforme (GBM) is the most widely occurring brain malignancy. It is modulated by a variety of genes, and patients with GBM have a low survival ratio and an unsatisfactory treatment effect. The irregular regulation of RNA binding proteins (RBPs) is implicated in several malignant neoplasms and reported to exhibit an association with the occurrence and development of carcinoma. Thus, it is necessary to build a stable, multi-RBPs signature-originated model for GBM prognosis and treatment response prediction. Methods: Differentially expressed RBPs (DERBPs) were screened out based on the RBPs data of GBM and normal brain tissues from The Cancer Genome Atlas (TCGA) and Genotype-Tissue Expression Program (GTEx) datasets. Gene Ontology and Kyoto Encyclopedia of Genes and Genomes analyses on DERBPs were performed, followed by an analysis of the Protein-Protein Interaction network. Survival analysis of the DERBPs was conducted by univariate and multivariate Cox regression. Then, a risk score model was created on the basis of the gene signatures in various survival-associated RBPs, and its prognostic and predictive values were evaluated through Kaplan-Meier analysis and log-rank test. A nomogram on the basis of the hub RBPs signature was applied to estimate GBM patients’ survival rates. Moreover, western blot was for the detection of the proteins. Results: BICC1, GNL3L, and KHDRBS2 were considered as prognosis-associated hub RBPs and then were applied in the construction of a prognostic model. Poor survival results appeared in GBM patients with a high-risk score. The area under the time-dependent ROC curve of the prognostic model was 0.723 in TCGA and 0.707 in Chinese Glioma Genome Atlas (CGGA) cohorts, indicating a good prognostic model. What was more, the survival duration of the high-risk group receiving radiotherapy or temozolomide chemotherapy was shorter than that of the low-risk group. The nomogram showed a great discriminating capacity for GBM, and western blot experiments demonstrated that the proteins of these 3 RBPs had different expressions in GBM cells. Conclusion: The identified 3 hub RBPs-derived risk score is effective in the prediction of GBM prognosis and treatment response, and benefits to the treatment of GBM patients.

Master Regulators Associated with Poor Prognosis in Glioblastoma Multiforme

Master Regulators Associated with Poor Prognosis in Glioblastoma Multiforme

Identification of HOXD10 as a Marker of Poor Prognosis in Glioblastoma Multiforme.

PurposeHOXD10 is a tumor modulator that can either be a tumor-suppressor or a tumor-promoting gene. However, the role of HOXD10 in glioblastoma multiforme (GBM) remains unclear.MethodsImmunohistochemistry (IHC) was applied to detect protein expression of HOXD10 in GBM and normal brain tissue patients. Clinicopathological characteristics with GBM were recorded, and a Kaplan–Meier curve was plotted. Additionally, the mRNA expression of HOXD10 and its effect on prognosis were analyzed using the online tool GEPIA and the Cancer Genome Atlas (TCGA), Chinese Glioma Genome Atlas (CGGA), and the Gene Expression Omnibus (GEO) databases. Based on the mRNA expression of HOXD10, GBM patients from TCGA database were divided into low- and high-HOXD10 expression groups to analyze the Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathways, and construct a lncRNA-miRNA-mRNA network and a protein–protein interaction (PPI) network.ResultsThe mRNA expression of HOXD10 was up-regulated in GBM according to GEPIA, while the protein expression of HOXD10 in GBM was down-regulated according to IHC analysis of samples from patients collected from our hospital. Correlation analysis showed that HOXD10 expression was significantly related to IDH1 status. Univariate analysis revealed that low HOXD10 expression, complete surgical resection, postoperative radiotherapy, postoperative temozolomide chemotherapy and IDH1 mutation were all beneficial prognostic factors. Further multivariate analysis revealed that only complete surgical resection and postoperative radiotherapy were independent prognostic factors. GO and KEGG enrichment analyses indicated that HOXD10 expression is mainly involved in cytokine-cytokine receptor interactions. In the ceRNA network, 89 nodes, containing 45 mRNAs, 39 miRNAs and five lncRNAs associated with prognosis were involved. The PPI network revealed a tight interaction between HOXD10 and HOXD8, HOXD9, HOXD11, HOXD13 and HOXB3.ConclusionBased on our experimental data, although HOXD10 expression is low in GBM compared with normal brain tissue, GBM patients with high HOXD10 expression have a worse prognosis. HOXD10 may play different or even opposite roles in different stages of GBM occurrence and development. For patients with GBM, HOXD10 may be a valid predictor of prognosis.

Overexpression of c-Met is Associated with Poor Prognosis in Glioblastoma Multiforme: A Systematic Review and Meta-Analyses.

Objective:The aim of this study is to evaluate the association of c-Met overexpression with survival of glioblastoma multiforme (GBM) patients. Methods:A systematic review with meta-analyses was conducted on related articles from PubMed, EBSCOhost, Scopus, and Cochrane databases with last updated search on October 31, 2020. A total of 7 studies regarding c-Met overexpression and overall survival (OS) and/or progression free survival (PFS) are included in this study. Results:All studies used immunohistochemistry to examine the expression of c-Met protein. The results showed that the positive rate of c-Met overexpression was detected in approximately 33,9% - 60,5% of GBM patients. c-Met overexpression was related to worse OS (HR: 1,74; 95% CI: 1,482-2,043; Z=6,756; p<0,001) and PFS (HR: 1,66; 95% CI: 1,327-2,066; Z=4,464; p<0,001) in GBM patients. Low heterogeneity of subjects was found in both OS and PFS analyses, I2 values were 7,8% and 0,0%, respectively. Conclusion:In conclusion, c-Met overexpression is significantly related to shorter OS and PFS in GBM patients, so c-Met can be considered as a potential prognostic indicator in GBM.

Regulatory Network of PD1 Signaling Is Associated with Prognosis in Glioblastoma Multiforme.

Glioblastoma is an aggressive cancer of the brain and spine. While analysis of glioblastoma 'omics data has somewhat improved our understanding of the disease, it has not led to direct improvement in patient survival. Cancer survival is often characterized by differences in gene expression, but the mechanisms that drive these differences are generally unknown. We therefore set out to model the regulatory mechanisms associated with glioblastoma survival. We inferred individual patient gene regulatory networks using data from two different expression platforms from The Cancer Genome Atlas. We performed comparative network analysis between patients with long- and short-term survival. Seven pathways were identified as associated with survival, all of them involved in immune signaling; differential regulation of PD1 signaling was validated to correspond with outcome in an independent dataset from the German Glioma Network. In this pathway, transcriptional repression of genes for which treatment options are available was lost in short-term survivors; this was independent of mutational burden and only weakly associated with T-cell infiltration. Collectively, these results provide a new way to stratify patients with glioblastoma that uses network features as biomarkers to predict survival. They also identify new potential therapeutic interventions, underscoring the value of analyzing gene regulatory networks in individual patients with cancer. SIGNIFICANCE: Genome-wide network modeling of individual glioblastomas identifies dysregulation of PD1 signaling in patients with poor prognosis, indicating this approach can be used to understand how gene regulation influences cancer progression.

PPFIBP1 induces glioma cell migration and invasion through FAK/Src/JNK signaling pathway

Glioblastoma multiforme (GBM) is the most aggressive brain tumor, with a 5-year survival ratio <5%. Invasive growth is a major determinant of the poor prognosis in GBM. In this study, we demonstrate that high expression of PPFIA binding protein 1 (PPFIBP1) correlates with remarkable invasion and poor prognosis of GBM patients. Using scratch and transwell assay, we find that the invasion and migration of GBM cells are promoted by overexpression of PPFIBP1, while inhibited by knockdown of PPFIBP1. Then, we illustrate that overexpression of PPFIBP1 facilitates glioma cell infiltration and reduces survival in xenograft models. Next, RNA-Seq and GO enrichment analysis reveal that PPFIBP1 regulates differentially expressed gene clusters involved in the Wnt and adhesion-related signaling pathways. Furthermore, we demonstrate that PPFIBP1 activates focal adhesion kinase (FAK), Src, c-Jun N-terminal kinase (JNK), and c-Jun, thereby enhancing Matrix metalloproteinase (MMP)-2 expression probably through interacting with SRCIN1 (p140Cap). Finally, inhibition of phosphorylation of Src and FAK significantly reversed the augmentation of invasion and migration caused by PPFIBP1 overexpression in GBM cells. In conclusion, these findings uncover a novel mechanism of glioma invasion and identify PPFIBP1 as a potential therapeutic target of glioma.

Comprehensive Analysis of CD163 as a Prognostic Biomarker and Associated with Immune Infiltration in Glioblastoma Multiforme

Background Glioblastoma multiforme (GBM) is the most common and aggressive primary malignancy in adults with high aggression. The prognosis of GBM patients is poor. There is a critical need for novel biomarkers for the prognosis and therapy of GBM. Methods Differentially expressed genes (DEGs) in GBM were screened using TCGA cohort. Univariate and multivariate Cox regression analyses were performed on DEGs to identify the optimal prognosis-related genes. qRT-PCR was performed to verify the result. Results A total of 5216 DEGs, including 2785 upregulated and 2458 downregulated genes, were obtained. Enrichment analysis revealed that these DEGs were mainly involved in the p53 signaling pathway and cell cycle, immune response, and MAPK signaling pathways. Moreover, the top 50 DEGs were associated with drug resistance or drug sensitivity. Prognosis analysis revealed that GBM patients with a high expression of CD163 and CHI3L2 had a poor overall survival, prognosis-free survival, and disease-specific survival. The univariate and multivariate analyses revealed that CD163 and age were independent factors affecting the prognosis of GBM patients. A validation study revealed that CD163 was upregulated in GBM tissues and associated with poor overall survival. Moreover, further analysis revealed that CD163 showed significant correlation with immune cells, immune biomarkers, chemokines, and chemokine receptors. We also identified several CD163-associated kinase, miRNA, and transcription factor targets in GBM, including LCK, miR-483, and ELF1. Conclusions In conclusion, our study suggested CD163 as a prognostic biomarker and associated it with immune infiltration in GBM.

Dissecting Prognosis Modules and Biomarkers in Glioblastoma Based on Weighted Gene Co-Expression Network Analysis.

IntroductionAs one of the most prevalent and malignant brain cancers, glioblastoma multiforme (GBM) presents a poor prognosis and the molecular mechanisms remain poorly understood. Consequently, molecular research, including various biomarkers, is essential to exploit the occurrence and development of glioma.MethodsWeighted gene co-expression network analysis (WGCNA) was used to construct gene co-expression modules and networks based on the Chinese Glioma Genome Atlas (CGGA) glioblastoma specimens. Then, protein–protein interaction (PPI) and gene ontology (GO) analyses were performed to mine hub genes. RT-PCR and immunohistochemistry were employed to examine the expression level of GRPR, CXCL5, and CXCL11 in glioma patients.ResultsWe confirmed two gene modules by protein–protein interaction networks. Functional enrichment analysis was performed to identify the significance of gene modules. Prognostic biomarkers GRPR, CXCL5, and CXCL11 related to the survival time of GBM samples were mined in The Cancer Genome Atlas (TCGA) dataset. qRT-PCR revealed that GRPR, CXCL5, and CXCL11 led to a significant increase in GBM sample compared to control.ConclusionIn this study, we developed and confirmed three mRNA signatures (GRPR, CXCL5, and CXCL11) for evaluating overall survival in GBM patients. Our research assists in existing understanding of GBM diagnosis and prognosis.

IGFBP2 Is a Potential Master Regulator Driving the Dysregulated Gene Network Responsible for Short Survival in Glioblastoma Multiforme.

Only 2% of glioblastoma multiforme (GBM) patients respond to standard therapy and survive beyond 36 months (long-term survivors, LTS), while the majority survive less than 12 months (short-term survivors, STS). To understand the mechanism leading to poor survival, we analyzed publicly available datasets of 113 STS and 58 LTS. This analysis revealed 198 differentially expressed genes (DEGs) that characterize aggressive tumor growth and may be responsible for the poor prognosis. These genes belong largely to the Gene Ontology (GO) categories “epithelial-to-mesenchymal transition” and “response to hypoxia.” In this article, we applied an upstream analysis approach that involves state-of-the-art promoter analysis and network analysis of the dysregulated genes potentially responsible for short survival in GBM. Binding sites for transcription factors (TFs) associated with GBM pathology like NANOG, NF-κB, REST, FRA-1, PPARG, and seven others were found enriched in the promoters of the dysregulated genes. We reconstructed the gene regulatory network with several positive feedback loops controlled by five master regulators [insulin-like growth factor binding protein 2 (IGFBP2), vascular endothelial growth factor A (VEGFA), VEGF165, platelet-derived growth factor A (PDGFA), adipocyte enhancer-binding protein (AEBP1), and oncostatin M (OSMR)], which can be proposed as biomarkers and as therapeutic targets for enhancing GBM prognosis. A critical analysis of this gene regulatory network gives insights into the mechanism of gene regulation by IGFBP2 via several TFs including the key molecule of GBM tumor invasiveness and progression, FRA-1. All the observations were validated in independent cohorts, and their impact on overall survival has been investigated.

New Protocol-Guided Exploitation of a Lysosomal Sulfatase Inhibitor to Suppress Cell Growth in Glioblastoma Multiforme

Glioblastoma multiforme (GBM) is a highly invasive and aggressive malignant glioma. Current treatment modalities are unable to significantly prolong survival in patients diagnosed with glioblastoma, so more effective strategies of antitumor treatments are in urgent demand. Here, we found that lysosomal sulfatase expression was significantly correlated with poor prognosis of GBM. Hence, a new probe, MNG, was developed with a new protocol utilizing glucose groups to detect lysosomal sulfatase. It also exhibits potential for monitoring GBM cells, depending on the hyperactive lysosomal sulfatase expression of tumor cells. Meantime, we identified that sulbactam as the first reported lysosomal sulfatase inhibitor inhibits the tumor growth of GBM. Collectively, our work highlights that lysosomal sulfatase was detected using a new protocol and its potential as a therapeutic target in GBM and reveals a distinct mechanism that sulbactam inhibits cell proliferation related to lysosomal sulfatase, indicating that sulbactam could be a promising therapeutic agent against GBM.

Identification of an IFN-β-associated gene signature for the prediction of overall survival among glioblastoma patients.

BackgroundBrain glioblastoma multiforme (GBM) is the most common primary malignant intracranial tumor. The prognosis of this disease is extremely poor. While the introduction of β-interferon (IFN-β) regimen in the treatment of gliomas has significantly improved the outcome of patients; The mechanism by which IFN-β induces increased TMZ sensitivity has not been described. Therefore, the main objective of the study was to elucidate the molecular mechanisms responsible for the beneficial effect of IFNβ in GBM.MethodsMessenger RNA expression profiles and clinicopathological data were downloaded from The Cancer Genome Atlas (TCGA) GBM and GSE83300 dataset from the Gene Expression Omnibus. Univariate Cox regression analysis and lasso Cox regression model established a novel 4-gene IFN-β signature (peroxiredoxin 1, Sec61 subunit beta, X-ray repair cross-complementing 5, and Bcl-2-like protein 2) for GBM prognosis prediction. Further, GBM samples (n=50) and normal brain tissues (n=50) were then used for real-time polymerase chain reaction experiments. Gene set enrichment analysis (GSEA) was performed to further understand the underlying molecular mechanisms. Pearson correlation was applied to calculate the correlation between the long non-coding RNAs (lncRNAs) and IFN-β-associated genes. An lncRNA with a correlation coefficient |R2|>0.3 and P<0.05 was considered to be an IFN-β-associated lncRNA.ResultsPatients in the high-risk group had significantly poorer survival than patients in the low-risk group. The signature was found to be an independent prognostic factor for GBM survival. Furthermore, GSEA revealed several significantly enriched pathways, which might help explain the underlying mechanisms. Our study identified a novel robust 4-gene IFN-β signature for GBM prognosis prediction. The signature might contain potential biomarkers for metabolic therapy and treatment response prediction for GBM patients.ConclusionsIn the present study, we established a novel IFN-β-associated gene signature to predict the overall survival of GBM patients, which may help in clinical decision making for individual treatment.

Hypoxia-induced phenotypic transition from highly invasive to less invasive tumors in glioma stem-like cells: Significance of CD44 and osteopontin as therapeutic targets in glioblastoma

The poor prognosis of glioblastoma multiforme (GBM) is primarily due to highly invasive glioma stem-like cells (GSCs) in tumors. Upon GBM recurrence, GSCs with highly invasive and highly migratory activities must assume a less-motile state and proliferate to regenerate tumor mass. Elucidating the molecular mechanism underlying this transition from a highly invasive phenotype to a less-invasive, proliferative tumor could facilitate the identification of effective molecular targets for treating GBM. Here, we demonstrate that severe hypoxia (1% O2) upregulates CD44 expression via activation of hypoxia-inducible factor (HIF-1α), inducing GSCs to assume a highly invasive tumor. In contrast, moderate hypoxia (5% O2) upregulates osteopontin expression via activation of HIF-2α. The upregulated osteopontin inhibits CD44-promoted GSC migration and invasion and stimulates GSC proliferation, inducing GSCs to assume a less-invasive, highly proliferative tumor. These data indicate that the GSC phenotype is determined by interaction between CD44 and osteopontin. The expression of both CD44 and osteopontin is regulated by differential hypoxia levels. We found that CD44 knockdown significantly inhibited GSC migration and invasion both in vitro and in vivo. Mouse brain tumors generated from CD44-knockdown GSCs exhibited diminished invasiveness, and the mice survived significantly longer than control mice. In contrast, siRNA-mediated silencing of the osteopontin gene decreased GSC proliferation. These results suggest that interaction between CD44 and osteopontin plays a key role in tumor progression in GBM; inhibition of both CD44 and osteopontin may represent an effective therapeutic approach for suppressing tumor progression, thus resulting in a better prognosis for patients with GBM.

Prognostic role of ALK-1 and h-TERT expression in glioblastoma multiforme: correlation with ALK gene alterations.

BackgroundAnaplastic lymphoma kinase (ALK) is a receptor tyrosine kinase that is expressed in the developing central and peripheral nervous systems during embryogenesis. Human telomerase reverse transcriptase (h-TERT) protein resumption is the main process of preservation of telomeres that maintains DNA integrity. The present study aims to evaluate the prognostic role of ALK-1 and h-TERT protein expression and their correlation with ALK gene alterations in glioblastoma multiforme (GBM). MethodsThe current study is a retrospective study on a cohort of patients with GBM (n = 53) that attempted to detect ALK gene alterations using fluorescence in situ hybridization. ALK-1 and h-TERT proteins were evaluated using immunohistochemistry. ResultsScore 3 ALK-1 expression was significantly associated with male sex, tumor multiplicity, Ki labeling index (Ki LI), and type of therapeutic modality. Score 3 h-TERT expression exhibited a significant association with Ki LI. ALK gene amplifications (ALK-A) were significantly associated with increased Ki LI and therapeutic modalities. Score 3 ALK-1 protein expression, score 3 h-TERT protein expression, and ALK-A were associated with poor overall survival (OS) and progression-free survival (PFS). Multivariate analysis for OS revealed that ALK gene alterations were an independent prognostic factor for OS and PFS.ConclusionsHigh protein expression of both ALK-1 and h-TERT, as well as ALK-A had a poor impact on the prognosis of GBM. Further studies are needed to establish the underlying mechanisms.

Glioblastoma multiforme prognosis: MRI missing modality generation, segmentation and radiogenomic survival prediction.

The accurate prognosis of glioblastoma multiforme (GBM) plays an essential role in planning correlated surgeries and treatments. The conventional models of survival prediction rely on radiomic features using magnetic resonance imaging (MRI). In this paper, we propose a radiogenomic overall survival (OS) prediction approach by incorporating gene expression data with radiomic features such as shape, geometry, and clinical information. We exploit TCGA (The Cancer Genomic Atlas) dataset and synthesize the missing MRI modalities using a fully convolutional network (FCN) in a conditional generative adversarial network (cGAN). Meanwhile, the same FCN architecture enables the tumor segmentation from the available and the synthesized MRI modalities. The proposed FCN architecture comprises octave convolution (OctConv) and a novel decoder, with skip connections in spatial and channel squeeze & excitation (skip-scSE) block. The OctConv can process low and high-frequency features individually and improve model efficiency by reducing channel-wise redundancy. Skip-scSE applies spatial and channel-wise excitation to signify the essential features and reduces the sparsity in deeper layers learning parameters using skip connections. The proposed approaches are evaluated by comparative experiments with state-of-the-art models in synthesis, segmentation, and overall survival (OS) prediction. We observe that adding missing MRI modality improves the segmentation prediction, and expression levels of gene markers have a high contribution in the GBM prognosis prediction, and fused radiogenomic features boost the OS estimation.

Elevated XRCC5 expression level can promote temozolomide resistance and predict poor prognosis in glioblastoma.

Drug resistance and disease recurrence are important contributors for the poor prognosis of glioblastoma multiforme (GBM). Temozolomide (TMZ), the standard chemotherapy for GBM treatment, can methylate DNA and cause the formation of double-strand breaks (DSBs). X-ray repair cross complementing 5 (XRCC5), also known as Ku80 or Ku86, is required for the repair of DSBs. The present study identified novel determinants that sensitize cells to TMZ, using an array-based short hairpin (sh)RNA library. Then, cBioportal, Oncomine, and R2 databases were used to analyze the association between gene expression levels and clinical characteristics. Subsequently, lentiviral shRNA or pCMV was used to knockdown or overexpress the gene of interest, and the effects on TMZ sensitivity were determined using a MTT assay and western blot analysis. TMZ-resistant cells were also established and were used in in vitro and in vivo experiments to analyze the role of the gene of interest in TMZ resistance. The results indicated that XRCC5 was effective in enhancing TMZ cytotoxicity. The results from the bioinformatics analysis revealed that XRCC5 mRNA expression levels were associated with clinical deterioration and lower overall survival rates. In addition, XRCC5 knockdown could significantly increase TMZ sensitivity in GBM cells, while XRCC5 overexpression caused the cancer cells to be resistant to TMZ. Both the in vivo and in vitro experiments showed that TMZ treatment could induce expression of XRCC5 in TMZ-resistant cells. Taken together these findings suggested that XRCC5 could be a promising target for GBM treatment and could also be used as a diagnostic marker for refractory GBM.

A Novel Six-mRNA Signature Predicts Survival of Patients With Glioblastoma Multiforme.

Glioblastoma multiforme (GBM) is a devastating brain tumor and displays divergent clinical outcomes due to its high degree of heterogeneity. Reliable prognostic biomarkers are urgently needed for improving risk stratification and survival prediction. In this study, we analyzed genome-wide mRNA profiles in GBM patients derived from The Cancer Genome Atlas (TCGA) and Gene Expression Omnibus (GEO) databases to identify mRNA-based signatures for GBM prognosis with survival analysis. Univariate Cox regression model was used to evaluate the relationship between the expression of mRNA and the prognosis of patients with GBM. We established a risk score model that consisted of six mRNA (AACS, STEAP1, STEAP2, G6PC3, FKBP9, and LOXL1) by the LASSO regression method. The six-mRNA signature could divide patients into a high-risk and a low-risk group with significantly different survival rates in training and test sets. Multivariate Cox regression analysis confirmed that it was an independent prognostic factor in GBM patients, and it has a superior predictive power as compared with age, IDH mutation status, MGMT, and G-CIMP methylation status. By combining this signature and clinical risk factors, a nomogram can be established to predict 1-, 2-, and 3-year OS in GBM patients with relatively high accuracy.

Primary and metastatic glioblastoma of the spine in the pediatric population: a systematic review.

Pediatric glioblastoma multiforme (GBM) involving the spine is an aggressive tumor with a poor quality of life for patients. Despite this, there is only a limited number of reports describing the outcomes of pediatric spinal GBMs, both as primary spinal GBMs and metastases from an intracranial tumor. Here, we performed an individual patient meta-analysis to characterize factors affecting prognosis of pediatric spinal GBM. MEDLINE, Embase, and the Cochrane databases were searched for published studies on GBMs involving the spine in pediatric patients (age ≤ 21 years old). Factors associated with the survival were assessed with multi-factor ANOVAs, Cox hazard regression, and Kaplan-Meier analyses. We extracted data on 61 patients with spinal GBM from 40 studies that met inclusion criteria. Median survival was significantly longer in the primary spinal GBM compared that those with metastatic GBM (11 vs 3 months, p < 0.001). However, median survival of metastatic GBM patients was 10 months following diagnosis of their primary brain tumor, which was not different from that of primary spinal GBM patients (p = 0.457). Among primary spinal GBM patients, chemotherapy (hazard ratio (HR) = 0.255 [0.106-0.615], p = 0.013) and extent of resection (HR = 0.582 [0.374-0.905], p = 0.016) conferred a significant survival benefit. Younger age (less than 14 years) was associated with longer survival in patients treated with chemotherapy than those who did not undergo chemotherapy (β = - 1.12, 95% CI [- 2.20, - 0.03], p < 0.05). In conclusion, survival after presentation of metastases from intracranial GBM is poor in the pediatric population. In patients with metastatic GBM, chemotherapy may have provided the most benefit in young patients, and its efficacy might have an association with extent of surgical resection.

Adenosinergic Pathway: A Hope in the Immunotherapy of Glioblastoma.

Simple SummaryGlioblastoma multiforme (GBM) is the most aggressive type of brain tumor with dismal survival and poor response to conventional therapies. Therefore, the development of immunotherapy for GBM treatment is necessary. However, the rigorous immunosuppression in the GBM-microenvironment (GME) is a crucial impediment for GBM immunotherapy. The adenosinergic pathway (AP) is a major player in suppressing antitumor immune responses in the GME. We reviewed the current GBM immunotherapies and elaborated on the role of AP in the immunopathogenesis, treatment, and even prognosis of GBM. Tumor cells metabolize pro-inflammatory ATP to anti-inflammatory adenosine using CD39 and CD73 enzymes. Adenosine suppresses immune responses through the signaling of adenosine receptors on immune cells. The preclinical results targeting AP in the GBM showed promising results in reinvigorating antitumor responses and overriding chemoresistance. We suggest that future clinical studies should consider this pathway in combination therapies along with other immunotherapeutic approaches.Brain tumors comprise different types of malignancies, most of which are originated from glial cells. Glioblastoma multiforme (GBM) is the most aggressive type of brain tumor with a poor response to conventional therapies and dismal survival rates (15 months) despite multimodal therapies. The development of immunotherapeutic strategies seems to be necessary to enhance the overall survival of GBM patients. So far, the immunotherapies applied in GBM had promising results in the primary phases of clinical trials but failed to continue their beneficial effects in later phases. GBM-microenvironment (GME) is a heterogenic and rigorously immunosuppressive milieu wrapping by an impenetrable blood-brain barrier. Hence, in-depth knowledge about the dominant immunosuppressive mechanisms in the GME could foster GBM immunotherapy. Recently, the adenosinergic pathway (AP) is found to be a major player in the suppression of antitumor immune responses in the GME. Tumor cells evolve to metabolize pro-inflammatory ATP to anti-inflammatory adenosine. Adenosine can suppress immune responses through the signaling of adenosine receptors on immune cells. The preclinical results targeting AP in GBM showed promising results in reinvigorating antitumor responses, overriding chemoresistance, and increasing survival. We reviewed the current GBM immunotherapies and elaborated on the role of AP in the immunopathogenesis, treatment, and even prognosis of GBM. We suggest that future clinical studies should consider this pathway in their combination therapies along with other immunotherapeutic approaches.