A risk signature with four autophagy-related genes for predicting survival of glioblastoma multiforme

Glioblastoma multiforme (GBM) is a devastating brain tumour without effective treatment. Recent studies have shown that autophagy is a promising therapeutic strategy for GBM. Therefore, it is necessary to identify novel biomarkers associated with autophagy in GBM. In this study, we downloaded autophagy-related genes from Human Autophagy Database (HADb) and Gene Set Enrichment Analysis (GSEA) website. Least absolute shrinkage and selection operator (LASSO) regression and multivariate Cox regression analysis were performed to identify genes for constructing a risk signature. A nomogram was developed by integrating the risk signature with clinicopathological factors. Time-dependent receiver operating characteristic (ROC) curve and calibration plot were used to evaluate the efficiency of the prognostic model. Finally, four autophagy-related genes (DIRAS3, LGALS8, MAPK8 and STAM) were identified and were used for constructing a risk signature, which proved to be an independent risk factor for GBM patients. Furthermore, a nomogram was developed based on the risk signature and clinicopathological factors (IDH1 status, age and history of radiotherapy or chemotherapy). ROC curve and calibration plot suggested the nomogram could accurately predict 1-, 3- and 5-year survival rate of GBM patients. For function analysis, the risk signature was associated with apoptosis, necrosis, immunity, inflammation response and MAPK signalling pathway. In conclusion, the risk signature with 4 autophagy-related genes could serve as an independent prognostic factor for GBM patients. Moreover, we developed a nomogram based on the risk signature and clinical traits which was validated to perform better for predicting 1-, 3- and 5-year survival rate of GBM.     

A robust two-gene signature for glioblastoma survival prediction

Glioblastoma multiforme (GBM) is a highly malignant brain tumor. We explored the prognostic gene signature in 443 GBM samples by systematic bioinformatics analysis, using GSE16011 with microarray expression and corresponding clinical data from Gene Expression Omnibus as the training set. Meanwhile, patients from The Chinese Glioma Genome Atlas database (CGGA) were used as the test set and The Cancer Genome Atlas database (TCGA) as the validation set. Through Cox regression analysis, Kaplan-Meier analysis, t-distributed Stochastic Neighbor Embedding algorithm, clustering, and receiver operating characteristic analysis, a two-gene signature (GRIA2 and RYR3) associated with survival was selected in the GSE16011 dataset. The GRIA2-RYR3 signature divided patients into two risk groups with significantly different survival in the GSE16011 dataset (median: 0.72, 95% confidence interval [CI]: 0.64-0.98, vs median: 0.98, 95% CI: 0.65-1.61 years, logrank test P < .001), the CGGA dataset (median: 0.84, 95% CI: 0.70-1.18, vs median: 1.21, 95% CI: 0.95-2.94 years, logrank test P = .0017), and the TCGA dataset (median: 1.03, 95% CI: 0.86-1.24, vs median: 1.23, 95% CI: 1.04-1.85 years, logrank test P = .0064), validating the predictive value of the signature. And the survival predictive potency of the signature was independent from clinicopathological prognostic features in multivariable Cox analysis. We found that after transfection of U87 cells with small interfering RNA, GRIA2 and RYR3 influenced the biological behaviors of proliferation, migration, and invasion of glioblastoma cells. In conclusion, the two-gene signature was a robust prognostic model to predict GBM survival.     

Scaffold-based spheroid models of glioblastoma multiforme and its use in drug screening

Among several types of brain cancers, glioblastoma multiforme (GBM) is a terminal and aggressive disease with a median survival of 15 months despite the most intensive surgery and chemotherapy. Preclinical models that accurately reproduce the tumor microenvironment are vital for developing new therapeutic alternatives. Understanding the complicated interactions between cells and their surroundings is essential to comprehend the tumor's microenvironment, however the monolayer cell culture approach falls short. Numerous approaches are used to develop GBM cells into tumor spheroids, while scaffold-based spheroids provides the opportunity to investigate the synergies between cells as well as cells and the matrix. This review summarizes the development of various scaffold-based GBM spheroid models and the prospective for their use as drug testing systems.     

Effects of human placenta-derived mesenchymal stem cells with NK4 gene expression on glioblastoma multiforme cell lines

Poor prognosis and low survival are commonly seen in patients with glioblastoma multiforme (GBM). Due to the specific nature of solid tumors such as GBM, delivery of therapeutic agents to the tumor sites is difficult. So, one of the major challenges in the treatment of these tumors is a selection of appropriate method for drug delivery. Mesenchymal stem cells (MSCs) have a unique characteristic in migration toward the tumor tissue. In this regard, the present study examined the antitumor effects of manipulating human placenta-derived mesenchymal stem cells (PDMSCs) with NK4 expression (PDMSC-NK4) on GBM cells. After separation and characterization of PDMSCs, these cells were transduced with NK4 which was known as the antagonist of hepatocyte growth factor (HGF). The results indicated that engineered PDMSCs preferably migrate into GBM cells by transwell coculture system. In addition, the proliferation of the GBM cells significantly reduced after coculture with these cells. In fact, manipulated PDMSCs inhibited growth of tumor cells by induction of apoptosis. Our findings suggested that besides having antitumor effects, PDMSCs can also be applied as an ideal cellular vehicle to target the glioblastoma multiforme.     

Quercetin-loaded platelets as a potential targeted therapy for glioblastoma multiforme cell line U373-MG

Over the globe, the incidence of glioblastoma multiforme (GM) is very low, that is, 1–4 cases per 100,000, but it is fatal and cancer grows very fast inside the brain tissues, namely astrocytes and oligodendrocytes. Because of the rapid growth, it is difficult to halt the dissemination of tumor in adjacent tissues. Although temozolomide (TMZ) is a currently approved standard of care, it develops resistance over the period. Therefore, there is a need to develop a novel drug delivery system. In this work, authors have developed platelets as drug delivery carriers-loaded with quercetin (QCT) for targeting GM. The effect of QCT and QCT-platelet was assessed on the U373-MG cell line. Natural human platelets were used as carriers for drug loading and drug delivery. Platelets possess an open canalicular system that allows the uptake of drug molecules in the platelet cytoplasm. The study showed that the maximum encapsulation efficiency of QCT-platelet was 93.96 ± 0.12% and the maximum drug release in 24 h was 76.26 ± 0.13% in-vitro at pH 5.5 that mimics the tumor microenvironment. In this work, there is a three-fold enhancement of solubility of QCT. The cytotoxic activity of QCT-platelets was studied in the U373-MG human astrocytoma glioblastoma cell line and the cell viability was 14.52 ± 1.53% after 48 h. Thus, platelets were proved as good carriers for therapeutic moieties and can be effectively used to target the glioblastoma tumor in the near future.     

IDH1 mutations is prognostic marker for primary glioblastoma multiforme but MGMT hypermethylation is not prognostic for primary glioblastoma multiforme

Purpose

To establish the frequency of IDH1 mutations and MGMT methylation in primary glioblastomas.

Experimental design

We screened primary glioblastoma multiforme (GBM) in a population-based study for IDH1 mutations and MGMT methylation and correlated them with clinical data.

Results

IDH1 mutations were detected in 5 of 40 primary glioblastomas (12,5%). Primary GBM patients carrying IDH1 mutations were significantly younger, mean age of 41 ± 5.06 years, than patients with wild-type IDH1, mean age of 57 ± 2,29 years, p = 0.011. The mean survival time of all GBM patients with and without IDH1 mutations was 19 months (5 cases) and 16 months (35 cases), respectively (p > 0,05). MGMT methylation was detected in 13 of the 40 patients (32,5%). MGMT-promoter methylation did not correlate with overall survival (OS; p > 0,05).

Conclusion

In summary, our study is the first study to investigate the IDH1 mutation status and MGMT methylation in primary GBMs in Turkish population and confirmed IDH1 mutation as a genetic marker for also primary GBMs. Our data are still insufficient for definite ascertainment; and our preliminary results suggest: IDH1 status shows an association with younger age and there is a lack of association between IDH1 mutation and survival time. Furthermore MGMT promoter methylation had no prognostic value and lower frequency in primary glioblastomas.     

AGAP2-AS1 serves as an oncogenic lncRNA and prognostic biomarker in glioblastoma multiforme

Long noncoding RNA (lncRNA) AGAP2 antisense RNA 1 (AGAP2-AS1) has been suggested to function as an oncogenic lncRNA in lung cancer, breast cancer, and anaplastic glioma. However, the expression pattern and molecular mechanism of AGAP2-AS1 in glioblastoma multiforme (GBM) remains unknown. The purpose of this study is to present more evidence about the clinical and biological function of AGAP2-AS1 in GBM. In our results, we found AGAP2-AS1 expression was increased in GBM compared with adjacent normal brain tissues or low-grade glioma tissues, and there was no significantly different between low-grade glioma tissues and normal tissues. Kaplan-Meier survival analysis indicated patients with GBM having high-expression of AGAP2-AS1 had shorter overall survival time than those with low expression of AGAP2-AS1. The loss-of-function studies showed that downregulation of AGAP2-AS1 depressed cell proliferation, migration, and invasion, and promoted cell apoptosis in GBM. In summary, AGAP2-AS1 is a prognostic biomarker for patients with GBM, and functions as an oncogenic lncRNA to modulate GBM cell proliferation, apoptosis, migration, and invasion, which suggests that AGAP2-AS1 is potential therapeutic target for GBM.     

Invasion as target for therapy of glioblastoma multiforme

The survival of cancer patients suffering from glioblastoma multiforme is limited to just a few months even after treatment with the most advanced techniques. The indefinable borders of glioblastoma cell infiltration into the surrounding healthy tissue prevent complete surgical removal. In addition, genetic mutations, epigenetic modifications and microenvironmental heterogeneity cause resistance to radio- and chemotherapy altogether resulting in a hardly to overcome therapeutic scenario. Therefore, the development of efficient therapeutic strategies to combat these tumors requires a better knowledge of genetic and proteomic alterations as well as the infiltrative behavior of glioblastoma cells and how this can be targeted. Among many cell surface receptors, members of the integrin family are known to regulate glioblastoma cell invasion in concert with extracellular matrix degrading proteases. While preclinical and early clinical trials suggested specific integrin targeting as a promising therapeutic approach, clinical trials failed to deliver improved cure rates up to now. Little is known about glioblastoma cell motility, but switches in invasion modes and adaption to specific microenvironmental cues as a consequence of treatment may maintain tumor cell resistance to therapy. Thus, understanding the molecular basis of integrin and protease function for glioblastoma cell invasion in the context of radiochemotherapy is a pressing issue and may be beneficial for the design of efficient therapeutic approaches. This review article summarizes the latest findings on integrins and extracellular matrix in glioblastoma and adds some perspective thoughts on how this knowledge might be exploited for optimized multimodal therapy approaches.     

Investigation of serum proteome alterations in human glioblastoma multiforme

Glioblastoma multiforme (GBM) or grade IV astrocytoma is the most common and lethal adult malignant brain tumor. The present study was conducted to investigate the alterations in the serum proteome in GBM patients compared to healthy controls. Comparative proteomic analysis was performed employing classical 2DE and 2D‐DIGE combined with MALDI TOF/TOF MS and results were further validated through Western blotting and immunoturbidimetric assay. Comparison of the serum proteome of GBM and healthy subjects revealed 55 differentially expressed and statistically significant (p <0.05) protein spots. Among the identified proteins, haptoglobin, plasminogen precursor, apolipoprotein A‐1 and M, and transthyretin are very significant due to their functional consequences in glioma tumor growth and migration, and could further be studied as glioma biomarkers and grade‐specific protein signatures. Analysis of the lipoprotein pattern indicated elevated serum levels of cholesterol, triacylglycerol, and low‐density lipoproteins in GBM patients. Functional pathway analysis was performed using multiple software including ingenuity pathway analysis (IPA), protein analysis through evolutionary relationships (PANTHER), database for annotation, visualization and integrated discovery (DAVID), and GeneSpring to investigate the biological context of the identified proteins, which revealed the association of candidate proteins in a few essential physiological pathways such as intrinsic prothrombin activation pathway, plasminogen activating cascade, coagulation system, glioma invasiveness signaling, and PI3K signaling in B lymphocytes. A subset of the differentially expressed proteins was applied to build statistical sample class prediction models for discrimination of GBM patients and healthy controls employing partial least squares discriminant analysis (PLS‐DA) and other machine learning methods such as support vector machine (SVM), Decision Tree and Naïve Bayes, and excellent discrimination between GBM and control groups was accomplished.     

A specific miRNA signature in the peripheral blood of glioblastoma patients

The prognosis of patients afflicted by glioblastoma remains poor. Biomarkers for the disease would be desirable in order to allow for an early detection of tumor progression or to indicate rapidly growing tumor subtypes requiring more intensive therapy. In this study, we investigated whether a blood-derived specific miRNA fingerprint can be defined in patients with glioblastoma. To this end, miRNA profiles from the blood of 20 patients with glioblastoma and 20 age- and sex-matched healthy controls were compared. Of 1158 tested miRNAs, 52 were significantly deregulated, as assessed by unadjusted Student's t-test at an alpha level of 0.05. Of these, two candidates, miR-128 (up-regulated) and miR-342-3p (down-regulated), remained significant after correcting for multiple testing by Benjamini-Hochberg adjustment with a p-value of 0.025. The altered expression of these two biomarkers was confirmed in a second cohort of glioblastoma patients and healthy controls by real-time PCR and validated for patients who had received neither radio- nor chemotherapy and for patients who had their glioblastomas resected more than 6 months ago. Moreover, using machine learning, a comprehensive miRNA signature was obtained that allowed for the discrimination between blood samples of glioblastoma patients and healthy controls with an accuracy of 81% [95% confidence interval (CI) 78-84%], specificity of 79% (95% CI 75-83%) and sensitivity of 83% (95% CI 71-85%). In summary, our proof-of-concept study demonstrates that blood-derived glioblastoma-associated characteristic miRNA fingerprints may be suitable biomarkers and warrant further exploration.     

Distinctive effects of the cellular inhibitor of apoptosis protein c-IAP2 through stabilization by XIAP in glioblastoma multiforme cells

Inhibitor of apoptosis proteins (IAPs) are extensively involved in NFκB signaling pathways. Regulation of c-IAP2 turnover by other proteins was investigated in glioblastoma multiforme (GBM) cells in the present study. When overexpressed, X-linked IAP (XIAP) enhanced expression of ectopic c-IAP2, but not c-IAP1, and endogenous c-IAP2 levels were reduced once XIAP expression was silenced. TNFα stimulation substantially increased c-IAP2 expression, and this upregulation was impaired by suppression of XIAP. Similarly, when XIAP was limiting due to severe hypoxic conditions, c-IAP2 levels were downregulated. These data together indicate that XIAP is an important regulator responsible for stabilization of c-IAP2 levels under different conditions. Protein interactions occur through binding of BIR2 and BIR3 domains of c-IAP2 with the RING finger of XIAP. XIAP inhibition of c-IAP2 auto-degradation was dependent on this physical interaction, and it was independent of XIAP E3 ligase activity. Global c-IAP2 ubiquitination was not affected by XIAP, although c-IAP2 levels were significantly increased. A CARD-RING-containing fragment of c-IAP2 was found to target XIAP for proteasome-independent degradation, but it was unable to sensitize GBM cells to chemo-reagents. The XIAP-stabilized c-IAP2 was found to enhance IκB-α phosphorylation on serines 32 and 36, and to antagonize XIAP-induced increase in mature Smac and Bcl10. Taken together, our data identify a distinctive role of c-IAP2 as stabilizer of XIAP, which is likely involved in regulation of NFκB activation and apoptosis in GBM cells.     

Pyroptosis in glioblastoma: A crucial regulator of the tumour immune microenvironment and a predictor of prognosis

Recent studies have shown that pyroptosis, an inflammatory form of cell death, has a dual role in tumorigenesis and tumour progression and affects the prognosis of patients; however, the role of pyroptosis in glioblastoma (GBM) is still unclear. In this study, based on GBM patients'' data from two independent cohorts, we performed a comprehensive analysis of the expression and prognostic value of 33 pyroptosis‐associated genes (PAGs) in GBM, as well as their role in the tumour immune microenvironment (TIME) of GBM. We identified 29 PAGs that were differentially expressed between GBM and normal brain tissue, 18 of which were upregulated in GBM tissue. Most of the 33 PAGs were strongly correlated with the levels of immune cell infiltration. Based on the 33 PAGs, the GBM samples can be divided into two clusters (C1‐C2), with C1 having a ‘hot’ but immunosuppressive TIME and C2 having a ‘cold’ TIME, suggesting different immunotherapeutic responses in the two clusters. In addition, we identified four PAGs that were strongly associated with GBM prognosis and constructed a risk model based on these four PAGs. This risk model is an independent prognostic factor for GBM patients, and there is a different immune status between high‐ and low‐risk groups. In conclusion, this study demonstrates that pyroptosis is closely associated with the prognosis and TIME of GBM and provides an important basis for further studies on the relationship between pyroptosis and GBM.     

Identification of a metabolism-related gene signature predicting overall survival for bladder cancer

Reprogramming of metabolism is becoming a novel hallmark of cancer. This study aims to perform bioinformatics analysis of metabolism-related genes in bladder cancer, and to construct a signature of metabolism-related genes for predicting the prognosis. A total of 373 differentially expressed metabolism-related genes were identified from TCGA database. Taking survival time and clinical information into consideration, we constructed a risk score to predict clinical prognosis. Low-risk patients had a better prognosis than high-risk patients. Multivariate analysis showed that risk score was an independent prognostic indicator in bladder cancer. ROC curve also proved that risk score had better ability to predict prognosis than other individual indicators. Nomogram also showed a clinical net benefit to evaluate the prognosis of bladder cancer patients. GSEA revealed several metabolism-related pathways that were differentially enriched in the high-risk and low-risk groups, which might help to explain the underlying mechanisms. This signature was confirmed to be an effective prognostic biomarker in bladder cancer.     

Expression and significance of SOX B1 genes in glioblastoma multiforme patients

The overall survival of glioblastoma multiforme (GBM) patients remains poor. To improve patient outcomes, effective diagnostic and prognostic biomarkers for GBM are needed. In this study, we first applied bioinformatic analyses to identify biomarkers for GBM, focusing on SOX (sex‐determining region on the Y chromosome (SRY)‐related high mobility group (HMG) box) B1 family members. The ONCOMINE, GEPIA, LinkedOmics and CCLE databases were used to assess mRNA expression levels of the SOX B1 family members in different cancers and normal tissue. Further bioinformatic analysis was performed using the ONCOMINE database in combination with the LinkedOmics data set to identify the prognostic value of SOX B1 family members for GBM. We found mRNA expression levels of all tested SOX B1 genes were significantly increased in GBM. In the LinkedOmics database, increased expression of SOX3 indicated a better overall survival. In GEPIA databases, increased expression of all SOX B1 family members suggested an improved overall survival, but none of them were statistically different. Then, Transwell assays and wound healing were employed to evaluate the motility and invasive captivity of U251 cells when silencing SOX2 and SOX3. We found exogenous inhibition of SOX2 appeared to reduce the migration and invasion of U251 cells in vitro. Collectively, our research suggested that SOX2 might serve as a cancer‐promoting gene to identify high‐risk GBM patients, and SOX3 had the potential to be a prognostic biomarker for GBM patients.     

Maintenance of EGFR and EGFRvIII expressions in an in vivo and in vitro model of human glioblastoma multiforme

Glioblastoma multiforme (GBM) is the most common, and most aggressive primary brain tumor among adults. A vast majority of the tumors express high levels of the epidermal growth factor receptor (EGFR) as a consequence of gene amplification. Furthermore, gene amplification is often associated with mutation of EGFR, and the constitutive activated deletion variant EGFRvIII is the most common EGFR mutation found in GBM. Activated EGFR signaling, through overexpression and/or mutation, is involved in increased tumorigenic potential. As such, EGFR is an attractive target for GBM therapy. However, clinical studies with EGFR inhibitors have shown inconsistent results, and as such, further knowledge regarding the role of EGFR and EGFRvIII in GBM is needed. For this, an appropriate in vivo/in vitro tumor model is required. Here, we report the establishment of an experimental GBM model in which the expressions of EGFR and EGFRvIII are maintained both in xenograft tumors growing subcutaneously on mice and in cell cultures established in stem cell conditions. With this model it will be possible to further study the role of EGFR and EGFRvIII, and response to targeted therapy, in GBM.