Optical biopsy identification and grading of gliomas using label-free visible resonance Raman spectroscopy.

Glioma is one of the most refractory types of brain tumor. Accurate tumor boundary identification and complete resection of the tumor are essential for glioma removal during brain surgery. We present a method based on visible resonance Raman (VRR) spectroscopy to identify glioma margins and grades. A set of diagnostic spectral biomarkers features are presented based on tissue composition changes revealed by VRR. The Raman spectra include molecular vibrational fingerprints of carotenoids, tryptophan, amide I/II/III, proteins, and lipids. These basic in situ spectral biomarkers are used to identify the tissue from the interface between brain cancer and normal tissue and to evaluate glioma grades. The VRR spectra are also analyzed using principal component analysis for dimension reduction and feature detection and support vector machine for classification. The cross-validated sensitivity, specificity, and accuracy are found to be 100%, 96.3%, and 99.6% to distinguish glioma tissues from normal brain tissues, respectively. The area under the receiver operating characteristic curve for the classification is about 1.0. The accuracies to distinguish normal, low grade (grades I and II), and high grade (grades III and IV) gliomas are found to be 96.3%, 53.7%, and 84.1% for the three groups, respectively, along with a total accuracy of 75.1%. A set of criteria for differentiating normal human brain tissues from normal control tissues is proposed and used to identify brain cancer margins, yielding a diagnostic sensitivity of 100% and specificity of 71%. Our study demonstrates the potential of VRR as a label-free optical molecular histopathology method used for in situ boundary line judgment for brain surgery in the margins

Oncometabolites: tailoring our genes

Increased glucose metabolism in cancer cells is a phenomenon that has been known for over 90 years, allowing maximal cell growth through faster ATP production and redistribution of carbons towards nucleotide, protein and fatty acid synthesis. Recently, metabolites that can promote tumorigeneis by altering the epigenome have been identified. These ‘oncometabolites’ include the tricarboxylic acid cycle metabolites succinate and fumarate, whose levels are elevated in rare tumours with succinate dehydrogenase and fumarate hydratase mutations, respectively. 2-Hydroxyglutarate is another oncometabolite; it is produced de novo as a result of the mutation of isocitrate dehydrogenase, and is commonly found in gliomas and acute myeloid leukaemia. Interestingly, the structural similarity of these oncometabolites to their precursor metabolite, α-ketoglutarate, explains the tumorigenic potential of these metabolites, by competitive inhibition of a superfamily of enzymes called the α-ketoglutarate-dependent dioxygenases. These enzymes utilize α-ketoglutarate as a cosubstrate, and are involved in fatty acid metabolism, oxygen sensing, collagen biosynthesis, and modulation of the epigenome. They include enzymes that are involved in regulating gene expression via DNA and histone tail demethylation. In this review, we will focus on the link between metabolism and epigenetics, and how we may target oncometabolite-induced tumorigenesis in the future

Transdural Spread of Glioblastoma with Endonasal Growth in a Long-Term Survivor Patient: Case Report and Literature Review.

Glioblastoma (GBM) is the most aggressive primary tumor of the central nervous system (CNS) in adults. Its growth has been always described as locally invasive. This tumor rarely penetrates dura mater and invades extracranial structures. We present a case of GBM, which occurred in a 39-year-old man, with final involvement of the nasal cavity. The patient was operated four times in three years, and a personalized adjuvant chemotherapy regimen was administered in a neo-adjuvant fashion. Histopathological features of the tumor are described. To our knowledge, there are only 9 cases reported in the literature showing this growth pattern and the last case was reported in 1998

Towards a Radio-guided Surgery with β−\beta^{-} Decays: Uptake of a somatostatin analogue (DOTATOC) in Meningioma and High Grade Glioma

A novel radio guided surgery (RGS) technique for cerebral tumors using $\beta^{-}$ radiation is being developed. Checking the availability of a radio-tracer that can deliver a $\beta^{-}$ emitter to the tumor is a fundamental step in the deployment of such technique. This paper reports a study of the uptake of 90Y labeled (DOTATOC) in the meningioma and the high grade glioma (HGG) and a feasibility study of the RGS technique in these cases.Comment: 21 pages, 5 figure

Full Issue: Volume 13, Issue 1 - Winter 2018

Full Issue: Volume 13, Issue 1 - Winter 201

Axitinib induces senescence-associated cell death and necrosis in glioma cell lines: The proteasome inhibitor, bortezomib, potentiates axitinib-induced cytotoxicity in a p21(Waf/Cip1) dependent manner.

Glioblastoma is associated with a poor overall survival despite new treatment advances. Antiangiogenic strategies targeting VEGF based on tyrosine kinase inhibitors (TKIs) are currently undergoing extensive research for the treatment of glioma. Herein we demonstrated that the TKI axitinib induces DNA damage response (DDR) characterized by γ-H2AX phosphorylation and Chk1 kinase activation leading to G2/M cell cycle arrest and mitotic catastrophe in U87, T98 and U251 glioma cell lines. Moreover, we found that p21(Waf1/Cip1) increased levels correlates with induction of ROS and senescence-associated cell death in U87 and T98 cell lines, which are reverted by N-acetyl cysteine pretreatment. Conversely, U251 cell line showed a resistant phenotype in response to axitinib treatment, as evidenced by cell cycle arrest but no sign of cell death. The combinatorial use of axitinib with other therapies, with the aim of inhibiting multiple signaling pathways involved in tumor growth, can increase the efficiency of this TKI. Thus, we addressed the combined effects of axitinib with no toxic doses of the proteasome inhibitor bortezomib on the growth of U87 and T98 axitinib- sensitive and axitinib-resistant U251 cell lines. Compared to single treatments, combined exposure was more effective in inhibiting cell viability of all glioma cell lines, although with different cell death modalities. The regulation of key DDR and cell cycle proteins, including Chk1, γ-H2AX and p21(Waf1/Cip1) was also studied in glioma cell lines. Collectively, these findings provide new perspectives for the use of axitinib in combination with Bortezomib to overcome the therapy resistance in gliomas

Modeling brain dynamics in brain tumor patients using the virtual brain

Presurgical planning for brain tumor resection aims at delineating eloquent tissue in the vicinity of the lesion to spare during surgery. To this end, noninvasive neuroimaging techniques such as functional MRI and diffusion-weighted imaging fiber tracking are currently employed. However, taking into account this information is often still insufficient, as the complex nonlinear dynamics of the brain impede straightforward prediction of functional outcome after surgical intervention. Large-scale brain network modeling carries the potential to bridge this gap by integrating neuroimaging data with biophysically based models to predict collective brain dynamics. As a first step in this direction, an appropriate computational model has to be selected, after which suitable model parameter values have to be determined. To this end, we simulated large-scale brain dynamics in 25 human brain tumor patients and 11 human control participants using The Virtual Brain, an open-source neuroinformatics platform. Local and global model parameters of the Reduced Wong-Wang model were individually optimized and compared between brain tumor patients and control subjects. In addition, the relationship between model parameters and structural network topology and cognitive performance was assessed. Results showed (1) significantly improved prediction accuracy of individual functional connectivity when using individually optimized model parameters; (2) local model parameters that can differentiate between regions directly affected by a tumor, regions distant from a tumor, and regions in a healthy brain; and (3) interesting associations between individually optimized model parameters and structural network topology and cognitive performance

Breaking through the glioblastoma micro-environment via extracellular vesicles

Glioblastoma (GBM) is the most common and most aggressive brain tumour. Prognosis remains poor, despite the combined treatment of radio- and chemotherapy following surgical removal. GBM cells coexist with normal non-neoplastic cells, including endothelial cells, astrocytes and immune cells, constituting a complex and dynamic tumour micro-environment (TME). Extracellular vesicles (EVs) provide a critical means of bidirectional inter-cellular communication in the TME. Through delivery of a diverse range of genomic, lipidomic and proteomic cargo to neighbouring and distant cells, EVs can alter the phenotype and function of the recipient cell. As such, EVs have demonstrated their role in promoting angiogenesis, immune suppression, invasion, migration, drug resistance and GBM recurrence. Moreover, EVs can reflect the phenotype of the cells within the TME. Thus, in conjunction with their accessibility in biofluids, they can potentially serve as a biomarker reservoir for patient prognosis, diagnosis and predictive therapeutic response as well as treatment follow-up. Furthermore, together with the ability of EVs to cross the blood–brain barrier undeterred and through the exploitation of their cargo, EVs may provide an effective mean of drug delivery to the target site. Unveiling the mechanisms by which EVs within the GBM TME are secreted and target recipient cells may offer an indispensable understanding of GBM that holds the potential to provide a better prognosis and overall quality of life for GBM patients

Multiscale, multimodal analysis of tumor heterogeneity in IDH1 mutant vs wild-type diffuse gliomas.

Glioma is recognized to be a highly heterogeneous CNS malignancy, whose diverse cellular composition and cellular interactions have not been well characterized. To gain new clinical- and biological-insights into the genetically-bifurcated IDH1 mutant (mt) vs wildtype (wt) forms of glioma, we integrated data from protein, genomic and MR imaging from 20 treatment-naïve glioma cases and 16 recurrent GBM cases. Multiplexed immunofluorescence (MxIF) was used to generate single cell data for 43 protein markers representing all cancer hallmarks, Genomic sequencing (exome and RNA (normal and tumor) and magnetic resonance imaging (MRI) quantitative features (protocols were T1-post, FLAIR and ADC) from whole tumor, peritumoral edema and enhancing core vs equivalent normal region were also collected from patients. Based on MxIF analysis, 85,767 cells (glioma cases) and 56,304 cells (GBM cases) were used to generate cell-level data for 24 biomarkers. K-means clustering was used to generate 7 distinct groups of cells with divergent biomarker profiles and deconvolution was used to assign RNA data into three classes. Spatial and molecular heterogeneity metrics were generated for the cell data. All features were compared between IDH mt and IDHwt patients and were finally combined to provide a holistic/integrated comparison. Protein expression by hallmark was generally lower in the IDHmt vs wt patients. Molecular and spatial heterogeneity scores for angiogenesis and cell invasion also differed between IDHmt and wt gliomas irrespective of prior treatment and tumor grade; these differences also persisted in the MR imaging features of peritumoral edema and contrast enhancement volumes. A coherent picture of enhanced angiogenesis in IDHwt tumors was derived from multiple platforms (genomic, proteomic and imaging) and scales from individual proteins to cell clusters and heterogeneity, as well as bulk tumor RNA and imaging features. Longer overall survival for IDH1mt glioma patients may reflect mutation-driven alterations in cellular, molecular, and spatial heterogeneity which manifest in discernable radiological manifestations

Efficacy of Combined 5-Fluorouracil and Photodynamic Therapy in Glioma Spheroids

Standard treatment regimens consisting of surgery, radiation and chemotherapy have proven ineffective for the treatment of high-grade gliomas such as glioblastoma multiforme (GBM). An effective cure requires elimination of nests of tumor cells that have migrated from the resection margin and infiltrated normal brain. A number of localized therapies, including light-based approaches such as photodynamic therapy (PDT) and photochemical internalization (PCI) are currently under investigation for the management of GBM patients. Several studies have demonstrated a high degree of synergy between PDT and bleomycin, via the PCI mechanism, in a variety of in vitro and in vivo models, including glioma cell lines. The purpose of this study was to examine the efficacy of combined treatments consisting of PDT and the chemotherapeutic agent, 5-fluorouracil (5-FU) in a 3-dimensional spheroid model consisting of F98 rat glioma cells. Spheroids were incubated with a photosensitizer (aluminum phthalocyanine disulfonate; AlPcS2a) and irradiated with 670 nm laser light. Three different wash protocols (0, 4 and 24 h) were employed to determine whether any observed interactions between PDT and 5-FU could be attributed to the PCI mechanism, or were simply due to different cytotoxic pathways of the two treatment modalities. Although the combined PDT + 5-FU treatments resulted in greater suppression of spheroid growth compared to either treatment alone, no statistically significant differences in growth effects were observed between 0 and 4 h wash protocols suggesting that the combined treatment effects were due to different mechanisms of cytotoxicity, rather than a PCI effect