Epidermal growth factor receptor in glioblastoma

Cancer Therapy-Associated Thrombosis

[Figure: see text].

BRAF paradox breakers PLX8394, PLX7904 are more effective against BRAFV600Ε CRC cells compared with the BRAF inhibitor PLX4720 and shown by detailed pathway analysis

PLX7904 and PLX8394 are novel BRAFV600E inhibitors-BRAFi that are designed to evade the paradoxical MAPK activation, a trait for the name "paradox breakers"-PB. Current FDA approved inhibitors (Vemurafenib, Dabrafenib, Encorafenib) although improved progression-free survival of mtBRAF melanoma patients suffer from this treatment related side effect. mtBRAF Colorectal Cancer (CRC) is resistant to the approved BRAF inhibitors, although combinatorial treatment co-targeting BRAF and EGFR/MEK is offering a promising prospect. In an effort to explore the potential of the novel BRAF inhibitors-PB to impede CRC cell proliferation, they were tested on RKO, HT29 and Colo-205 cells, bearing the BRAFV600E mutation. This study shows that the BRAF paradox breakers PLX7904 and PLX8394 cause a more prolonged MAPK pathway inhibition and achieve a stronger blockage of proliferation and reduced viability than PLX4720, the sister compound of Vemurafenib. In some treatment conditions, cells can undergo apoptosis. Genomic analysis on the more resistant RKO cells treated with PLX7904, PLX8394 and PLX4720 showed similar gene expression pattern, but the alterations imposed by the PB were more intense. Bioinformatic analysis resulted in a short list of genes representing potential master regulators of the cellular response to BRAF inhibitors' treatments. From our results, it is clear that the BRAF paradox breakers present a notable differential regulation of major pathways, like MAPK signalling, apoptosis, cell cycle, or developmental signalling pathways. Combinatorial treatments of BRAFi with Mcl-1 and Notch modulators show a better effect than mono-treatments. Additional pathways could be further exploited in novel efficient combinatorial treatment protocols with BRAFi.

Set-Wise Differential Interaction Between Copy Number Alterations and Gene Expressions of Lower-Grade Glioma Reveals Prognosis-Associated Pathways

The integrative analysis of copy number alteration (CNA) and gene expression (GE) is an essential part of cancer research considering the impact of CNAs on cancer progression and prognosis. In this research, an integrative analysis was performed with generalized differentially coexpressed gene sets (gdCoxS), which is a modification of dCoxS. In gdCoxS, set-wise interaction is measured using the correlation of sample-wise distances with Renyi’s relative entropy, which requires an estimation of sample density based on omics profiles. To capture correlations between the variables, multivariate density estimation with covariance was applied. In the simulation study, the power of gdCoxS outperformed dCoxS that did not use the correlations in the density estimation explicitly. In the analysis of the lower-grade glioma of the cancer genome atlas program (TCGA-LGG) data, the gdCoxS identified 577 pathway CNAs and GEs pairs that showed significant changes of interaction between the survival and non-survival group, while other benchmark methods detected lower numbers of such pathways. The biological implications of the significant pathways were well consistent with previous reports of the TCGA-LGG. Taken together, the gdCoxS is a useful method for an integrative analysis of CNAs and GEs.

Differential Network Analysis via Weighted Fused Conditional Gaussian Graphical Model

The development and prognosis of complex diseases usually involves changes in regulatory relationships among biomolecules. Understanding how the regulatory relationships change with genetic alterations can help to reveal the underlying biological mechanisms for complex diseases. Although several models have been proposed to estimate the differential network between two different states, they are not suitable to deal with situations where the molecules of interest are affected by other covariates. Nor can they make use of prior information that provides insights about the structures of biomolecular networks. In this study, we introduce a novel weighted fused conditional Gaussian graphical model to jointly estimate two state-specific biomolecular regulatory networks and their difference between two different states. Unlike previous differential network estimation methods, our model can take into account the related covariates and the prior network information when inferring differential networks. The effectiveness of our proposed model is first evaluated based on simulation studies. Experiment results demonstrate that our model outperforms other state-of-the-art differential networks estimation models in all cases. We then apply our model to identify the differential gene network between two subtypes of glioblastoma based on gene expression and miRNA expression data. Our model is able to discover known mechanisms of glioblastoma and provide interesting predictions.

Hsa-miR-27a-3p and epidermal growth factor receptor expression analysis in glioblastoma FFPE samples

AIM

Glioblastoma multiforme (GBM) is the most invasive type of glial tumors. MicroRNAs as the small, noncoding RNAs have been revealed that play an important role in tumorigenic processes. So, they may be used as potential biomarkers for detection and prognosis of cancers at the early stages. In addition, they can be applied as therapeutic targets. In the present study, the expression levels of hsa-miR-27a-3p and EGFR were investigated in GBM.

METHODS

Real-time RT-PCR was applied to evaluate hsa-miR-27a-3p and EGFR expressions in the formalin-fixed paraffin-embedded (FFPE) tissue samples obtained from 50 GBM and 50 normal people.

RESULTS

The expression level of hsa-miR-27a-3p and EGFR was significantly different between cases and controls. Positive association was found between gene expressions and immunohistochemistry markers, such as Ki67 and glial fibrillary acidic protein, except for IDH1 status.

CONCLUSION

We showed the association of hsa-miR-27a-3p and EGFR with GBM and it can be concluded that they have a promising potential to use as primary cancer biomarkers.

Inferring tumor progression in large datasets

Identification of mutations of the genes that give cancer a selective advantage is an important step towards research and clinical objectives. As such, there has been a growing interest in developing methods for identification of driver genes and their temporal order within a single patient (intra-tumor) as well as across a cohort of patients (inter-tumor). In this paper, we develop a probabilistic model for tumor progression, in which the driver genes are clustered into several ordered driver pathways. We develop an efficient inference algorithm that exhibits favorable scalability to the number of genes and samples compared to a previously introduced ILP-based method. Adopting a probabilistic approach also allows principled approaches to model selection and uncertainty quantification. Using a large set of experiments on synthetic datasets, we demonstrate our superior performance compared to the ILP-based method. We also analyze two biological datasets of colorectal and glioblastoma cancers. We emphasize that while the ILP-based method puts many seemingly passenger genes in the driver pathways, our algorithm keeps focused on truly driver genes and outputs more accurate models for cancer progression.

Cancer is a disease caused by the accumulation of somatic mutations in the genome. This process is mainly driven by mutations in certain genes that give the harboring cells some selective advantage. The rather few driver genes are usually masked amongst an abundance of so-called passenger mutations. Identification of the driver genes and the temporal order in which the mutations occur is of great importance towards research and clinical objectives. In this paper, we introduce a probabilistic model for cancer progression and devise an efficient inference algorithm to train the model. We show that our method scales favorably to large datasets and provides superior performance compared to an ILP-based counterpart on a wide set of synthetic data simulations. Our Bayesian approach also allows for systematic model selection and confidence quantification procedures in contrast to the previous non-probabilistic progression models. We also study two large datasets on colorectal and glioblastoma cancers and validate our inferred model in comparison to the ILP-based method.

A compendium of mutational cancer driver genes

A fundamental goal in cancer research is to understand the mechanisms of cell transformation. This is key to developing more efficient cancer detection methods and therapeutic approaches. One milestone towards this objective is the identification of all the genes with mutations capable of driving tumours. Since the 1970s, the list of cancer genes has been growing steadily. Because cancer driver genes are under positive selection in tumorigenesis, their observed patterns of somatic mutations across tumours in a cohort deviate from those expected from neutral mutagenesis. These deviations, which constitute signals of positive selection, may be detected by carefully designed bioinformatics methods, which have become the state of the art in the identification of driver genes. A systematic approach combining several of these signals could lead to a compendium of mutational cancer genes. In this Review, we present the Integrative OncoGenomics (IntOGen) pipeline, an implementation of such an approach to obtain the compendium of mutational cancer drivers. Its application to somatic mutations of more than 28,000 tumours of 66 cancer types reveals 568 cancer genes and points towards their mechanisms of tumorigenesis. The application of this approach to the ever-growing datasets of somatic tumour mutations will support the continuous refinement of our knowledge of the genetic basis of cancer.

Impact of blood-brain barrier permeabilization induced by ultrasound associated to microbubbles on the brain delivery and kinetics of cetuximab: An immunoPET study using 89Zr-cetuximab

Epidermal growth factor receptor (EGFR), involved in cell proliferation and migration, is overexpressed in ~50% of glioblastomas. Anti-EGFR based strategies using monoclonal antibodies (mAb) such as cetuximab (CTX) have been proposed for central nervous system (CNS) cancer therapy. However, the blood-brain barrier (BBB) drastically restricts their brain penetration which limits their efficacy for the treatment of glioblastomas. Herein, a longitudinal PET imaging study was performed to assess the relevance and the impact of focused ultrasound (FUS)-mediated BBB permeabilization on the brain exposure to the anti-EGFR mAb CTX over time. For this purpose, FUS permeabilization process with microbubbles was applied on intact BBB mouse brain before the injection of ⁸⁹Zr-labeled CTX for longitudinal imaging monitoring. FUS induced a dramatic increase in mAb penetration to the brain, 2 times higher compared to the intact BBB. The transfer of ⁸⁹Zr-CTX from blood to the brain was rendered significant by FUS (k_uptake = 1.3 ± 0.23 min^-1 with FUS versus k_uptake = 0 ± 0.006 min^-1 without FUS). FUS allowed significant and prolonged exposure to mAb in the brain parenchyma. This study confirms the potential of FUS as a target delivery method for mAb in CNS.

Excellent response to erlotinib in breast carcinoma with rare EGFR mutation-a case report

Triple negative breast carcinoma is a problematic subtype with poor outcomes. Many clinical trials are underway to find possible target to increase treatment options. Epidermal growth factor receptor (EGFR) has emerged as one such molecule which is over expressed in some of these patients and can be targeted by tyrosine kinase inhibitors. We describe a diagnostically challenging case of metastatic breast carcinoma, with extensive lung disease and poor Eastern Cooperative Oncology Group (ECOG) performance status, which expressed an uncommon EGFR mutation (Exon 21L861Q) and which benefitted from erlotinib following failure of all primary treatment modalities. The case uncovers the presence of these unusual mutations in breast carcinoma and highlights the importance of performing molecular analysis and the appropriate targeted therapy. This approach can be an important problem-solving tool, especially in cases where the patient is not fit for the other standard treatment options.

Flavagline synthetic derivative induces senescence in glioblastoma cancer cells without being toxic to healthy astrocytes

Glioblastoma (GBM) is one of the most aggressive types of cancer, which begins within the brain. It is the most invasive type of glioma developed from astrocytes. Until today, Temozolomide (TMZ) is the only standard chemotherapy for patients with GBM. Even though chemotherapy extends the survival of patients, there are many undesirable side effects, and most cases show resistance to TMZ. FL3 is a synthetic flavagline which displays potent anticancer activities, and is known to inhibit cell proliferation, by provoking cell cycle arrest, and leads to apoptosis in a lot of cancer cell lines. However, the effect of FL3 in glioblastoma cancer cells has not yet been examined. Hypoxia is a major problem for patients with GBM, resulting in tumor resistance and aggressiveness. In this study, we explore the effect of FL3 in glioblastoma cells under normoxia and hypoxia conditions. Our results clearly indicate that this synthetic flavagline inhibits cell proliferation and induced senescence in glioblastoma cells cultured under both conditions. In addition, FL3 treatment had no effect on human brain astrocytes. These findings support the notion that the FL3 molecule could be used in combination with other chemotherapeutic agents or other therapies in glioblastoma treatments.

mTOR Inhibition Leads to Src-Mediated EGFR Internalisation and Degradation in Glioma Cells

Epidermal Growth Factor receptor (EGFR) is a tyrosine kinase receptor widely expressed on the surface of numerous cell types, which activates several downstream signalling pathways involved in cell proliferation, migration and survival. EGFR alterations, such as overexpression or mutations, have been frequently observed in several cancers, including glioblastoma (GBM), and are associated to uncontrolled cell proliferation. Here we show that the inhibition of mammalian target of Rapamycin (mTOR) mediates EGFR delivery to lysosomes for degradation in GBM cells, independently of autophagy activation. Coherently with EGFR internalisation and degradation, mTOR blockade negatively affects the mitogen activated protein/extracellular signal-regulated kinase (MAPK)/ERK pathway. Furthermore, we provide evidence that Src kinase activation is required for EGFR internaliation upon mTOR inhibition. Our results further support the hypothesis that mTOR targeting may represent an effective therapeutic strategy in GBM management, as its inhibition results in EGFR degradation and in proliferative signal alteration.

Unsupervised machine learning reveals risk stratifying glioblastoma tumor cells

A goal of cancer research is to reveal cell subsets linked to continuous clinical outcomes to generate new therapeutic and biomarker hypotheses. We introduce a machine learning algorithm, Risk Assessment Population IDentification (RAPID), that is unsupervised and automated, identifies phenotypically distinct cell populations, and determines whether these populations stratify patient survival. With a pilot mass cytometry dataset of 2 million cells from 28 glioblastomas, RAPID identified tumor cells whose abundance independently and continuously stratified patient survival. Statistical validation within the workflow included repeated runs of stochastic steps and cell subsampling. Biological validation used an orthogonal platform, immunohistochemistry, and a larger cohort of 73 glioblastoma patients to confirm the findings from the pilot cohort. RAPID was also validated to find known risk stratifying cells and features using published data from blood cancer. Thus, RAPID provides an automated, unsupervised approach for finding statistically and biologically significant cells using cytometry data from patient samples.

The limitations of targeting MEK signalling in Glioblastoma therapy

Glioblastoma (GB) is a highly aggressive, difficult to treat brain tumour. Successful treatment, consisting of maximal safe tumour de-bulking, followed by radiotherapy and treatment with the alkylating agent Temozolomide (TMZ), can extend patient survival to approximately 15 months. Combination treatments based on the inhibition of the PI3K pathway, which is the most frequently activated signalling cascade in GB, have so far only shown limited therapeutic success. Here, we use the clinically approved MEK inhibitor Trametinib to investigate its potential use in managing GB. Trametinib has a strong anti-proliferative effect on established GB cell lines, stem cell-like cells and their differentiated progeny and while it does not enhance anti-proliferative and cell death-inducing properties of the standard treatment, i.e. exposure to radiation or TMZ, neither does MEK inhibition block their effectiveness. However, upon MEK inhibition some cell populations appear to favour cell-substrate interactions in a sprouting assay and become more invasive in the Chorioallantoic Membrane assay, which assesses cell penetration into an organic membrane. While this increased invasion can be modulated by additional inhibition of the PI3K signalling cascade, there is no apparent benefit of blocking MEK compared to targeting PI3K.

The effects of altered neurogenic microRNA levels and their involvement in the aggressiveness of periventricular glioblastoma

INTRODUCTION

Glioblastoma multiforme is the most common primary brain tumour, with the least favourable prognosis. Despite numerous studies and medical advances, it continues to be lethal, with an average life expectancy of 15 months after chemo-radiotherapy.

DEVELOPMENT

Recent research has addressed several factors associated with the diagnosis and prognosis of glioblastoma; one significant factor is tumour localisation, particularly the subventricular zone, which represents one of the most active neurogenic niches of the adult human brain. Glioblastomas in this area are generally more aggressive, resulting in unfavourable prognosis and a shorter life expectancy. Currently, the research into microRNAs (miRNA) has intensified, revealing different expression patterns under physiological and pathophysiological conditions. It has been reported that the expression levels of certain miRNAs, mainly those related to neurogenic processes, are dysregulated in oncogenic events, thus favouring gliomagenesis and greater tumour aggressiveness. This review discusses some of the most important miRNAs involved in subventricular neurogenic processes and their association with glioblastoma aggressiveness.

CONCLUSIONS

MiRNA regulation and function play an important role in the development and progression of glioblastoma; understanding the alterations of certain miRNAs involved in both differentiation and neural and glial maturation could help us to better understand the malignant characteristics of glioblastoma.

Targeted Polymer-Based Probes for Fluorescence Guided Visualization and Potential Surgery of EGFR-Positive Head-and-Neck Tumors

This report describes the design, synthesis and evaluation of tumor-targeted polymer probes to visualize epidermal growth factor receptor (EGFR)-positive malignant tumors for successful resection via fluorescence guided endoscopic surgery. Fluorescent polymer probes of various molecular weights enabling passive accumulation in tumors via enhanced permeability and retention were prepared and evaluated, showing an optimal molecular weight of 200,000 g/mol for passive tumor targeting. Moreover, poly(N-(2-hydroxypropyl)methacrylamide)-based copolymers labeled with fluorescent dyes were targeted with the EGFR-binding oligopeptide GE-11 (YHWYGYTPQNVI), human EGF or anti-EGFR monoclonal antibody cetuximab were all able to actively target the surface of EGFR-positive tumor cells. Nanoprobes targeted with GE-11 and cetuximab showed the best targeting profile but differed in their tumor accumulation kinetics. Cetuximab increased tumor accumulation after 15 min, whereas GE 11 needed at least 4 h. Interestingly, after 4 h, there were no significant differences in tumor targeting, indicating the potential of oligopeptide targeting for fluorescence-navigated surgery. In conclusion, fluorescent polymer probes targeted by oligopeptide GE-11 or whole antibody are excellent tools for surgical navigation during oncological surgery of head and neck squamous cell carcinoma, due to their relatively simple design, synthesis and cost, as well as optimal pharmacokinetics and accumulation in tumors.

A review of predictive, prognostic and diagnostic biomarkers for brain tumours: towards personalised and targeted cancer therapy

Background:

Brain tumours are relatively rare disease but present a large medical challenge as there is currently no method for early detection of the tumour and are typically not diagnosed until patients have progressed to symptomatic stage which significantly decreases chances of survival and also minimises treatment efficacy. However, if brain cancers can be diagnosed at early stages and also if clinicians have the potential to prospectively identify patients likely to respond to specific treatments, then there is a very high potential to increase patients’ treatment efficacy and survival. In recent years, there have been several investigations to identify biomarkers for brain cancer risk assessment, early detection and diagnosis, the likelihood of identifying which group of patients will benefit from a particular treatment and monitoring patient response to treatment.

Materials and methods:

This paper reports on a review of 21 current clinical and emerging biomarkers used in risk assessment, screening for early detection and diagnosis, and monitoring the response of treatment of brain cancers.

Conclusion:

Understanding biomarkers, molecular mechanisms and signalling pathways can potentially lead to personalised and targeted treatment via therapeutic targeting of specific genetic aberrant pathways which play key roles in malignant brain tumour formation. The future holds promising for the use of biomarker analysis as a major factor for personalised and targeted brain cancer treatment, since biomarkers have the potential to measure early disease detection and diagnosis, the risk of disease development and progression, improved patient stratification for various treatment paradigms, provide accurate information of patient response to a specific treatment and inform clinicians about the likely outcome of a brain cancer diagnosis independent of the treatment received.

Identification of Dysregulated Competitive Endogenous RNA Networks Driven by Copy Number Variations in Malignant Gliomas

Gliomas represent 80% of malignant brain tumors. Because of the high heterogeneity, the oncogenic mechanisms in gliomas are still unclear. In this study, we developed a new approach to identify dysregulated competitive endogenous RNA (ceRNA) interactions driven by copy number variation (CNV) in both lower-grade glioma (LGG) and glioblastoma multiforme (GBM). By analyzing genome and transcriptome data from The Cancer Genome Atlas (TCGA), we first found out the protein coding genes and long non-coding RNAs (lncRNAs) significantly affected by CNVs and further determined CNV-driven dysregulated ceRNA interactions by a customized pipeline. We obtained 13,776 CNV-driven dysregulated ceRNA pairs (including 3,954 mRNAs and 306 lncRNAs) in LGG and 262 pairs (including 221 mRNAs and 11 lncRNAs) in GBM, respectively. Our results showed that most of the ceRNA interactions were weakened by CNVs in both LGG and GBM, and many CNV-driven genes shared the same ceRNAs in the dysregulated ceRNA networks. Functional analysis indicated that the CNV-driven ceRNA network involved in some important mechanisms of tumorigenesis, such as cell cycle, p53 signaling pathway and TGF-beta signaling pathway. Further investigation of the ceRNA pairs in the communities from the dysregulated ceRNA network revealed more detailed biological functions related to the oncogenesis of malignant gliomas. Moreover, by exploring the association of CNV-driven ceRNAs with prognosis and histological subtype, we found that the copy number status of MTAP, KLHL9, and ELAVL2 related to the overall survival in LGG and showed high correlation with histological subtype. In conclusion, this study provided new insight into the molecular mechanisms and clinical biomarkers in gliomas.

3D extracellular matrix microenvironment in bioengineered tissue models of primary pediatric and adult brain tumors

Dynamic alterations in the unique brain extracellular matrix (ECM) are involved in malignant brain tumors. Yet studies of brain ECM roles in tumor cell behavior have been difficult due to lack of access to the human brain. We present a tunable 3D bioengineered brain tissue platform by integrating microenvironmental cues of native brain-derived ECMs and live imaging to systematically evaluate patient-derived brain tumor responses. Using pediatric ependymoma and adult glioblastoma as examples, the 3D brain ECM-containing microenvironment with a balance of cell-cell and cell-matrix interactions supports distinctive phenotypes associated with tumor type-specific and ECM-dependent patterns in the tumor cells' transcriptomic and release profiles. Label-free metabolic imaging of the composite model structure identifies metabolically distinct sub-populations within a tumor type and captures extracellular lipid-containing droplets with potential implications in drug response. The versatile bioengineered 3D tumor tissue system sets the stage for mechanistic studies deciphering microenvironmental role in brain tumor progression.

Imaging signatures of glioblastoma molecular characteristics: A radiogenomics review

Over the past few decades, the advent and development of genomic assessment methods and computational approaches have raised the hopes for identifying therapeutic targets that may aid in the treatment of glioblastoma. However, the targeted therapies have barely been successful in their effort to cure glioblastoma patients, leaving them with a grim prognosis. Glioblastoma exhibits high heterogeneity, both spatially and temporally. The existence of different genetic subpopulations in glioblastoma allows this tumor to adapt itself to environmental forces. Therefore, patients with glioblastoma respond poorly to the prescribed therapies, as treatments are directed towards the whole tumor and not to the specific genetic subregions. Genomic alterations within the tumor develop distinct radiographic phenotypes. In this regard, MRI plays a key role in characterizing molecular signatures of glioblastoma, based on regional variations and phenotypic presentation of the tumor. Radiogenomics has emerged as a (relatively) new field of research to explore the connections between genetic alterations and imaging features. Radiogenomics offers numerous advantages, including noninvasive and global assessment of the tumor and its response to therapies. In this review, we summarize the potential role of radiogenomic techniques to stratify patients according to their specific tumor characteristics with the goal of designing patient-specific therapies. Level of Evidence: 5 Technical Efficacy: Stage 2 J. Magn. Reson. Imaging 2020;52:54-69.

Pharmacokinetics and safety of erlotinib and its metabolite OSI-420 in infants and children with primary brain tumors

PURPOSE

Erlotinib (Tarceva^®), a potent small molecule inhibitor of the epidermal growth factor receptor tyrosine kinase, has been evaluated to treat infants and children with primary brain tumors. The pharmacokinetics of erlotinib and its primary metabolite OSI-420 were characterized and exposure-safety associations were investigated.

METHODS

This analysis involved patients enrolled in two clinical studies and receiving oral erlotinib once daily as part of treatment. Single-dose and steady-state erlotinib and OSI-420 plasma concentrations were assayed using HPLC-MS/MS methods. Population pharmacokinetic modeling and univariate covariate analysis evaluating demographic, clinical and selected CYP3A5, CYP3A4, ABCB1, and ABCG2 genotypes were performed. Associations between erlotinib and OSI-420 pharmacokinetics, and with toxicities (diarrhea and skin rash) occurring post-dose were explored.

RESULTS

Data from 47 patients (0.7-19 years old) were collected and best fitted by one-compartment linear models. Erlotinib and OSI-420 apparent clearances (CL/F and CL_m/F_m) were higher in patients < 5 years compared to older patients (mean CL/F: 6.8 vs 3.6 L/h/m², and mean CL_m/F_m: 79 vs 38 L/h/m², p < 0.001), and were 1.62-fold and 1.73-fold higher in males compared to females (p < 0.01). Moreover, CL/F was 1.53-fold higher in wild-type patients than in patients heterozygous or homozygous mutant for ABCG2 rs55930652 (p < 0.05). Most of the toxicities reported were grade 1. No associations were found between drug pharmacokinetics and drug-induced toxicities.

CONCLUSIONS

Erlotinib therapy was well tolerated by pediatric patients with primary brain tumors. No dosing adjustments based on age or patient characteristics are recommended for this patient population.

An Update on Novel Therapeutic Warfronts of Extracellular Vesicles (EVs) in Cancer Treatment: Where We Are Standing Right Now and Where to Go in the Future

Extracellular vesicles (EVs) are a heterogeneous group of membrane-bounded vesicles that are believed to be produced and secreted by presumably all cell types under physiological and pathological conditions, including tumors. EVs are very important vehicles in intercellular communications for both shorter and longer distances and are able to deliver a wide range of cargos including proteins, lipids, and various species of nucleic acids effectively. EVs have been emerging as a novel biotherapeutic platform to efficiently deliver therapeutic cargos to treat a broad range of diseases including cancer. This vast potential of drug delivery lies in their abilities to carry a variety of cargos and their ease in crossing the biological membranes. Similarly, their presence in a variety of body fluids makes them a potential biomarker for early diagnosis, prognostication, and surveillance of cancer. Here, we discuss the relatively least and understudied aspects of EV biology and tried to highlight the obstacles and limitations in their clinical applications and also described most of the new warfronts to beat cancer at multiple stages. However, much more challenges still remain to evaluate EV-based therapeutics, and we are very much hopeful that the current work prompts further discovery.

Seizures in glioma patients: An overview of incidence, etiology, and therapies

Gliomas are fatal brain tumors, and even low-grade gliomas (LGGs) have an average survival of less than a decade. Seizures are a common presentation of gliomas, particularly LGGs, and substantially impact quality of life. Glioma-related seizures differ from other focal epilepsies in their pathogenesis and in the likelihood of refractory epilepsy. We review factors that predict seizure activity and response to treatment, optimal pharmacologic and surgical management of glioma-related epilepsy, and the benefit of using newer anti-seizure medications in patients with gliomas. As surgery is so often beneficial with seizure reduction, we discuss oncologic and epilepsy surgery perspectives. Treatment of gliomas has the potential to ameliorate seizures and increase rates of seizure freedom. Prospective, well-powered studies are needed to provide more definitive answers for practitioners taking care of glioma patients with seizures.

NFBTA: A Potent Cytotoxic Agent against Glioblastoma

Piplartine (PPL), also known as piperlongumine, is a biologically active alkaloid extracted from the Piper genus which has been found to have highly effective anticancer activity against several tumor cell lines. This study investigates in detail the antitumoral potential of a PPL analogue; (E)-N-(4-fluorobenzyl)-3-(3,4,5-trimethoxyphenyl) acrylamide (NFBTA). The anticancer potential of NFBTA on the glioblastoma multiforme (GBM) cell line (U87MG) was determined by 3-(4,5-dimethyl-2-thia-zolyl)-2, 5-diphenyl-2H-tetrazolium bromide (MTT), and lactate dehydrogenase (LDH) release analysis, and the selectivity index (SI) was calculated. To detect cell apoptosis, fluorescent staining via flow cytometry and Hoechst 33258 staining were performed. Oxidative alterations were assessed via colorimetric measurement methods. Alterations in expressions of key genes related to carcinogenesis were determined. Additionally, in terms of NFBTA cytotoxic, oxidative, and genotoxic damage potential, the biosafety of this novel agent was evaluated in cultured human whole blood cells. Cell viability analyses revealed that NFBTA exhibited strong cytotoxic activity in cultured U87MG cells, with high selectivity and inhibitory activity in apoptotic processes, as well as potential for altering the principal molecular genetic responses in U87MG cell growth. Molecular docking studies strongly suggested a plausible anti-proliferative mechanism for NBFTA. The results of the experimental in vitro human glioblastoma model and computational approach revealed promising cytotoxic activity for NFBTA, helping to orient further studies evaluating its antitumor profile for safe and effective therapeutic applications.

Pathway-based deep clustering for molecular subtyping of cancer

Cancer is a genetic disease comprising multiple subtypes that have distinct molecular characteristics and clinical features. Cancer subtyping helps in improving personalized treatment and making decision, as different cancer subtypes respond differently to the treatment. The increasing availability of cancer related genomic data provides the opportunity to identify molecular subtypes. Several unsupervised machine learning techniques have been applied on molecular data of the tumor samples to identify cancer subtypes that are genetically and clinically distinct. However, most clustering methods often fail to efficiently cluster patients due to the challenges imposed by high-throughput genomic data and its non-linearity. In this paper, we propose a pathway-based deep clustering method (PACL) for molecular subtyping of cancer, which incorporates gene expression and biological pathway database to group patients into cancer subtypes. The main contribution of our model is to discover high-level representations of biological data by learning complex hierarchical and nonlinear effects of pathways. We compared the performance of our model with a number of benchmark clustering methods that recently have been proposed in cancer subtypes. We assessed the hypothesis that clusters (subtypes) may be associated to different survivals by logrank tests. PACL showed the lowest p-value of the logrank test against the benchmark methods. It demonstrates the patient groups clustered by PACL may correspond to subtypes which are significantly associated with distinct survival distributions. Moreover, PACL provides a solution to comprehensively identify subtypes and interpret the model in the biological pathway level. The open-source software of PACL in PyTorch is publicly available at https://github.com/tmallava/PACL.

Tetrandrine inhibits human brain glioblastoma multiforme GBM 8401 cancer cell migration and invasion in vitro

Tetrandrine (TET) has been reported to induce anti-cancer activity in many human cancer cells and also to inhibit cancer cell migration and invasion. However, there are no reports to show TET inhibits cell migration and invasion in human brain glioblastoma multiforme GBM 8401 cells. In this study, we investigated the anti-metastasis effects of TET on GBM 8401 cells in vitro. Under sub-lethal concentrations (from 1, 5 up to 10 μM), TET significantly inhibited cell mobility, migration and invasion of GBM 8401 cells that were assayed by wound healing and Transwell assays. Gelatin zymography assay showed that TET inhibited MMP-2 activity in GBM 8401 cells. Western blotting results indicated that TET inhibited several key metastasis-related proteins, such as p-EGFR_(Tyr1068) , SOS-1, GRB2, Ras, p-AKT_(Ser473) and p-AKT_(Thr308) , NF-κB-p65, Snail, E-cadherin, N-cadherin, NF-κB, MMP-2 and MMP-9 that were significant reduction at 24 and 48 hours treatment by TET. TET reduced MAPK signaling associated proteins such as p-JNK1/2 and p-c-Jun in GBM 8401 cells. The electrophoretic mobility shift (EMSA) assay was used to investigate NF-κB and DNA binding was reduced by TET in a dose-dependently. Based on these findings, we suggested that TET could be used in anti-metastasis of human brain glioblastoma multiforme GBM 8401 cells in the future.

Identification of a Novel Splice Variant of Neural Cell Adhesion Molecule in Glioblastoma Through Proteogenomics Analysis

Splice variants are known to be important in the pathophysiology of tumors, including the brain cancers. We applied a proteogenomics pipeline to identify splice variants in glioblastoma (GBM, grade IV glioma), a highly malignant brain tumor, using in-house generated mass spectrometric proteomic data and public domain RNASeq dataset. Our analysis led to the identification of a novel exon that maps to the long isoform of Neural cell adhesion molecule 1 (NCAM1), expressed on the surface of glial cells and neurons, important for cell adhesion and cell signaling. The presence of the novel exon is supported with the identification of five peptides spanning it. Additional peptides were also detected in sodium dodecyl sulfate-polyacrylamide gel electrophoresis (SDS-PAGE) gel separated proteins from GBM patient tissue, underscoring the presence of the novel peptides in the intact brain protein. The novel exon was detected in the RNASeq dataset in 18 of 25 GBM samples and separately validated in additional 10 GBM tumor tissues using quantitative real-time-polymerase chain reaction (qRT-PCR). Both transcriptomic and proteomic data indicate downregulation of NCAM1, including the novel variant, in GBM. Domain analysis of the novel NCAM1 sequence indicates that the insertion of the novel exon contributes extra low-complexity region in the protein that may be important for protein-protein interactions and hence for cell signaling associated with tumor development. Taken together, the novel NCAM1 variant reported in this study exemplifies the importance of future multiomics research and systems biology applications in GBM.

Genetics of Glioblastoma in Moroccan population: Review of literature

Glioblastoma is the most aggressive malignant type of central nervous system tumors. The literature review revealed that the most common genetic abnormalities in primary and secondary glioblastomas are IDH1 / 2 mutations, p53 mutations, and overexpression of EGFR. To our knowledge, this is the first Moroccan study to provide a global picture of genetic studies performed on Moroccan patients to describe genetic markers and their frequency in our population. An in-depth research in ScienceDirect and Pubmed on glioblastoma articles treated in Morocco, this research is based on the following keywords: glioblastoma in Morocco, primary glioblastoma in Morocco, secondary glioblastoma in Morocco. We found only three research articles on genomic alteration of IDH1 / 2, p53 and EGFR expression. The frequency of these gene mutations in our population was similar to those reported from other populations. Additional molecular studies need to be performed on other genes to describe other genetic markers in the Moroccan population.

Comprehensive analysis of Reverse Phase Protein Array data reveals characteristic unique proteomic signatures for glioblastoma subtypes

The most common and lethal type of intracranial tumors include the astrocytomas. Grade IV astrocytoma or Glioblastoma (GBM) is highly aggressive and treatment-refractory with a median survival of only 14 to 16 months. Molecular profiling of GBMs reveals a high degree of intra- and inter-tumoral heterogeneity, and hence it is important to understand the important signalling axes that get deregulated in different GBM subtypes to provide effective tailor-made therapies. In this study, we have carried out extensive analysis of Reverse Phase Protein Array (RPPA) data from TCGA cohort to develop protein signatures that define glioma grades or subtypes. The protein signatures that distinguished Grade II or III from GBM had largely overlapped, and pathway analysis revealed the positive enrichment of extracellular matrix proteins (ECM), MYC pathway, uPAR pathway and G2/M checkpoint genes in GBM. We also identified protein signatures for GBMs with genetic alterations (IDH mutation, p53 mutation, EGFR amplification or mutation, CDKN2A/CDKN2B deletion, and PTEN mutation) that occur at high frequency. G-CIMP positive GBM-specific protein signature showed a large similarity with IDH1-mutant protein signature, thus signifying the importance of IDH1 mutation driving the G-CIMP. Gene expression subtype analysis revealed an association of specific proteins to classical (EGFR and phosphor variants), mesenchymal (SERPINE1, TAZ, and Myosin-IIa_pS1943), neural (TUBA1B), and proneural (GSK3_pS9) types. Univariate Cox regression analysis identified several proteins showing significant correlation with GBM survival. Multivariate analysis revealed that IGFBP2 and RICTOR_pT1135 are independent predictors of survival. Overall, our analyses reveal that specific proteins are regulated in different glioma subtypes underscoring the importance of diverse signalling axes playing important role in the pathogenesis of glioma tumors.

CARMA3 Is a Critical Mediator of G Protein-Coupled Receptor and Receptor Tyrosine Kinase-Driven Solid Tumor Pathogenesis

The CARMA–Bcl10–MALT1 (CBM) signalosome is an intracellular protein complex composed of a CARMA scaffolding protein, the Bcl10 linker protein, and the MALT1 protease. This complex was first recognized because the genes encoding its components are targeted by mutation and chromosomal translocation in lymphoid malignancy. We now know that the CBM signalosome plays a critical role in normal lymphocyte function by mediating antigen receptor-dependent activation of the pro-inflammatory, pro-survival NF-κB transcription factor, and that deregulation of this signaling complex promotes B-cell lymphomagenesis. More recently, we and others have demonstrated that a CBM signalosome also operates in cells outside of the immune system, including in several solid tumors. While CARMA1 (also referred to as CARD11) is expressed primarily within lymphoid tissues, the related scaffolding protein, CARMA3 (CARD10), is more widely expressed and participates in a CARMA3-containing CBM complex in a variety of cell types. The CARMA3-containing CBM complex operates downstream of specific G protein-coupled receptors (GPCRs) and/or growth factor receptor tyrosine kinases (RTKs). Since inappropriate expression and activation of GPCRs and/or RTKs underlies the pathogenesis of several solid tumors, there is now great interest in elucidating the contribution of CARMA3-mediated cellular signaling in these malignancies. Here, we summarize the key discoveries leading to our current understanding of the role of CARMA3 in solid tumor biology and highlight the current gaps in our knowledge.

Salivary exosomes as potential biomarkers in cancer

Over the past decade, there has been emerging research in the field of extracellular vesicles, especially those originating from endosomes, referred to as 'exosomes. Exosomes are membrane-bound nanovesicles secreted by most cell types upon fusion of multivesicular bodies (MVBs) to the cell plasma membrane. These vesicles are present in almost all body fluids such as blood, urine, saliva, breast milk, cerebrospinal and peritoneal fluids. Exosomes participate in intercellular communication by transferring the biologically active molecules like proteins, nucleic acids, and lipids to neighboring cells. Exosomes are enriched in the tumour microenvironment and growing evidence demonstrates that exosomes mediate cancer progression and metastasis. Given the important biological role played by these nanovesicles in cancer pathogenesis, these can be used as ideal non-invasive biomarkers in detecting and monitoring tumours as well as therapeutic targets. The scope of the current review is to provide an overview of exosomes with a special focus on salivary exosomes as potential biomarkers in head and neck cancers.

Epstein-Barr Virus in Gliomas: Cause, Association, or Artifact?

Gliomas are the most common malignant brain tumors and account for around 60% of all primary central nervous system cancers. Glioblastoma multiforme (GBM) is a grade IV glioma associated with a poor outcome despite recent advances in chemotherapy. The etiology of gliomas is unknown, but neurotropic viruses including the Epstein–Barr virus (EBV) that is transmitted via salivary and genital fluids have been implicated recently. EBV is a member of the gamma herpes simplex family of DNA viruses that is known to cause infectious mononucleosis (glandular fever) and is strongly linked with the oncogenesis of several cancers, including B-cell lymphomas, nasopharyngeal, and gastric carcinomas. The fact that EBV is thought to be the causative agent for primary central nervous system (CNS) lymphomas in immune-deficient patients has led to its investigations in other brain tumors including gliomas. Here, we provide a review of the clinical literature pertaining to EBV in gliomas and discuss the possibilities of this virus being simply associative, causative, or even an experimental artifact. We searched the PubMed/MEDLINE databases using the following key words such as: glioma(s), glioblastoma multiforme, brain tumors/cancers, EBV, and neurotropic viruses. Our literature analysis indicates conflicting results on the presence and role of EBV in gliomas. Further comprehensive studies are needed to fully implicate EBV in gliomagenesis and oncomodulation. Understanding the role of EBV and other oncoviruses in the etiology of gliomas, would likely open up new avenues for the treatment and management of these, often fatal, CNS tumors.

Aptamers and Glioblastoma: Their Potential Use for Imaging and Therapeutic Applications

Glioblastoma is a highly aggressive primary brain tumour, renowned for its infiltrative growth and varied genetic profiles. The current treatment options are insufficient, and their off-target effects greatly reduce patient quality of life. The major challenge in improving glioblastoma diagnosis and treatment involves the development of a targeted imaging and drug delivery platform, capable of circumventing the blood brain barrier and specifically targeting glioblastoma tumours. The unique properties of aptamers demonstrate their capability of bridging the gap to the development of successful diagnosis and treatment options, where antibodies have previously failed. Aptamers possess many characteristics that make them an ideal novel imaging and therapeutic agent for the treatment of glioblastoma and other brain malignancies, and are likely to provide patients with a better standard of care and improved quality of life. Their target sensitivity, selective nature, ease of modification and low immunogenicity make them an ideal drug-delivery platform. This review article summarises the aptamers previously generated against glioblastoma cells or its identified biomarkers, and their potential application in diagnosis and therapeutic targeting of glioblastoma tumours.