Proteomic analysis of the influence of the adipocyte secretome on Glioma Gl261 cells

Glioma is the most frequent form of malignant brain tumor in the adults and childhood. There is a global tendency toward a higher incidence of gliomas in highly developed and industrialized countries. Simultaneously obesity is reaching epidemic proportions in such developed countries. It has been highly accepted that obesity may play an important role in the biology of several types of cancer. We have developed an in vitro method for the understanding of the influence of obesity on glioma mouse cells (Gl261). 3T3-L1 mouse pre-adipocytes were induced to the maturity. The conditioned medium was harvested and used into the Gl261 cultures. Using two-dimension electrophoresis it was analyzed the proteome content of Gl261 in the presence of conditioned medium (CGl) and in its absence (NCGl). The differently expressed spots were collected and analyzed by means of mass spectroscopy (MALDI-TOF-MS). Significantly expression pattern changes were observed in eleven proteins and enzymes. RFC1, KIF5C, ANXA2, N-RAP, RACK1 and citrate synthase were overexpressed or only present in the CGl. Contrariwise, STI1, hnRNPs and phosphoglycerate kinase 1 were significantly underexpressed in CGl. Aldose reductase and carbonic anhydrase were expressed only in NCGl. Our results show that obesity remodels the physiological and metabolic behavior of glioma cancer cells. Also, proteins found differently expressed are implicated in several signaling pathways that control matrix remodeling, proliferation, progression, migration and invasion. In general our results support the idea that obesity may increase glioma malignancy, however, some interesting paradox finding were also reported and discussed.

Marker-independent identification of glioma-initiating cells.

Tumor-initiating cells with stem cell properties are believed to sustain the growth of gliomas, but proposed markers such as CD133 cannot be used to identify these cells with sufficient specificity. We report an alternative isolation method purely based on phenotypic qualities of glioma-initiating cells (GICs), avoiding the use of molecular markers. We exploited intrinsic autofluorescence properties and a distinctive morphology to isolate a subpopulation of cells (FL1(+)) from human glioma or glioma cultures. FL1(+) cells are capable of self-renewal in vitro, tumorigenesis in vivo and preferentially express stem cell genes. The FL1(+) phenotype did not correlate with the expression of proposed GIC markers. Our data propose an alternative approach to investigate tumor-initiating potential in gliomas and to advance the development of new therapies and diagnostics.

Development of Techniques for the Automatic Extraction and Grade Detection of Glioma Tumors from Conventional Brain Magnetic Resonant Images

Cerebral glioma is the most prevalent primary brain tumor, which are classified broadly into low and high grades according to the degree of malignancy. High grade gliomas are highly malignant which possess a poor prognosis, and the patients survive less than eighteen months after diagnosis. Low grade gliomas are slow growing, least malignant and has better response to therapy. To date, histological grading is used as the standard technique for diagnosis, treatment planning and survival prediction. The main objective of this thesis is to propose novel methods for automatic extraction of low and high grade glioma and other brain tissues, grade detection techniques for glioma using conventional magnetic resonance imaging (MRI) modalities and 3D modelling of glioma from segmented tumor slices in order to assess the growth rate of tumors. Two new methods are developed for extracting tumor regions, of which the second method, named as Adaptive Gray level Algebraic set Segmentation Algorithm (AGASA) can also extract white matter and grey matter from T1 FLAIR an T2 weighted images. The methods were validated with manual Ground truth images, which showed promising results. The developed methods were compared with widely used Fuzzy c-means clustering technique and the robustness of the algorithm with respect to noise is also checked for different noise levels. Image texture can provide significant information on the (ab)normality of tissue, and this thesis expands this idea to tumour texture grading and detection. Based on the thresholds of discriminant first order and gray level cooccurrence matrix based second order statistical features three feature sets were formulated and a decision system was developed for grade detection of glioma from conventional T2 weighted MRI modality.The quantitative performance analysis using ROC curve showed 99.03% accuracy for distinguishing between advanced (aggressive) and early stage (non-aggressive) malignant glioma. The developed brain texture analysis techniques can improve the physician’s ability to detect and analyse pathologies leading to a more reliable diagnosis and treatment of disease. The segmented tumors were also used for volumetric modelling of tumors which can provide an idea of the growth rate of tumor; this can be used for assessing response to therapy and patient prognosis.

A semi-automatic method for segmentation and 3D modeling of glioma tumors from brain MRI

This work presents an efficient method for volume rendering of glioma tumors from segmented 2D MRI Datasets with user interactive control, by replacing manual segmentation required in the state of art methods. The most common primary brain tumors are gliomas, evolving from the cerebral supportive cells. For clinical follow-up, the evaluation of the pre- operative tumor volume is essential. Tumor portions were automatically segmented from 2D MR images using morphological filtering techniques. These seg- mented tumor slices were propagated and modeled with the software package. The 3D modeled tumor consists of gray level values of the original image with exact tumor boundary. Axial slices of FLAIR and T2 weighted images were used for extracting tumors. Volumetric assessment of tumor volume with manual segmentation of its outlines is a time-consuming proc- ess and is prone to error. These defects are overcome in this method. Authors verified the performance of our method on several sets of MRI scans. The 3D modeling was also done using segmented 2D slices with the help of a medical software package called 3D DOCTOR for verification purposes. The results were validated with the ground truth models by the Radi- ologist.

Texture Description of low grade and high grade Glioma using Statistical features in Brain MRIs

Low grade and High grade Gliomas are tumors that originate in the glial cells. The main challenge in brain tumor diagnosis is whether a tumor is benign or malignant, primary or metastatic and low or high grade. Based on the patient's MRI, a radiologist could not differentiate whether it is a low grade Glioma or a high grade Glioma. Because both of these are almost visually similar, autopsy confirms the diagnosis of low grade with high-grade and infiltrative features. In this paper, textural description of Grade I and grade III Glioma are extracted using First order statistics and Gray Level Co-occurance Matrix Method (GLCM). Textural features are extracted from 16X16 sub image of the segmented Region of Interest(ROI) .In the proposed method, first order statistical features such as contrast, Intensity , Entropy, Kurtosis and spectral energy and GLCM features extracted were showed promising results. The ranges of these first order statistics and GLCM based features extracted are highly discriminant between grade I and Grade III. In this study which gives statistical textural information of grade I and grade III Glioma which is very useful for further classification and analysis and thus assisting Radiologist in greater extent.

Automatic Detection and Classification of Glioma Tumors using Statistical Features

The characterization and grading of glioma tumors, via image derived features, for diagnosis, prognosis, and treatment response has been an active research area in medical image computing. This paper presents a novel method for automatic detection and classification of glioma from conventional T2 weighted MR images. Automatic detection of the tumor was established using newly developed method called Adaptive Gray level Algebraic set Segmentation Algorithm (AGASA).Statistical Features were extracted from the detected tumor texture using first order statistics and gray level co-occurrence matrix (GLCM) based second order statistical methods. Statistical significance of the features was determined by t-test and its corresponding p-value. A decision system was developed for the grade detection of glioma using these selected features and its p-value. The detection performance of the decision system was validated using the receiver operating characteristic (ROC) curve. The diagnosis and grading of glioma using this non-invasive method can contribute promising results in medical image computing

Subcutaneous study on the controlled release of Etanidazole and Taxol for the treatment of Glioma

BALB/c nude mice 6 weeks old were inoculated with glioma C6 cell-line and the efficacy of the different amount of Etanidazole-discs and Taxol-microspheres was investigated. Poly (D,L-lactic-co-glycolic acid) (PLGA) was used as the main encapsulating polymer and polyethylene glycol was added to increase the porosity. The 1% drug loading microspheres of each drug were produced by spray drying and the discs were obtained by compressing the Etanidazole-microspheres. Intra-tumoral injection followed by irradiation resulted in high systemic dosage and thus systemic toxicity. Tumors grown for 6 days, 9 days and 16 days were implanted with 0.5 mg or 1.0 mg or 1.5 mg of the drug. A radiation dosage of 2 Gy each time for a number of times was given for animals implanted with Etanidazole and no irradiation was given for animals implanted with Taxol. Increasing the number of doses clearly decreased the rate of tumor growth. The increase in the amount of drug on smaller sized tumors controlled the tumor better and there was agglomeration of the microspheres resulting in deviation of release profile of the drug as compared to the in vitro studies. It was observed that 1.0 mg of Taxol given to a tumor grown for 6 days was able to suppress the tumor for a total period of approximately two months and no tumor resurrection was observed during the second month.

La investigación educativa en el aula hospitalaria : estudio de un caso de intervención escolar, de glioma óptico infantil mediante videoconferencia.

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p53 Mutant Human Glioma Cells Are Sensitive to UV-C-Induced Apoptosis Due to Impaired Cyclobutane Pyrimidine Dimer Removal

The p53 protein is a key regulator of cell responses to DNA damage, and it has been shown that It sensitizes glioma cells to the alkylating agent temozolomide by up-regulating the extrinsic apoptotic pathway, whereas it increases the resistance to chloroethylating agents, such as ACNU and BCNU, probably by enhancing the efficiency of DNA repair. However, because these agents induce a wide variety of distinct DNA lesions, the direct Importance of DNA repair is hard to access. Here, it is shown that the Induction of photoproducts by UV light (UV-C) significantly Induces apoptosis In a p53-mutated glioma background. This Is caused by a reduced level of photoproduct repair, resulting In the persistence of DNA lesions in p53-mutated glioma cells. UV-C-Induced apoptosis in p53 mutant glioma cells Is preceded by strong transcription and replication inhibition due to blockage by unrepaired photolesions. Moreover, the results Indicate that UV-C-induced apoptosis of p53 mutant glioma cells Is executed through the intrinsic apoptotic pathway, with Bcl-2 degradation and sustained Bax and Bak up-regulation. Collectively, the data Indicate that unrepaired DNA lesions Induce apoptosis In p53 mutant gliomas despite the resistance of these gliomas to temozolomide, suggesting that efficiency of treatment of p53 mutant gliomas might be higher with agents that Induce the formation of DNA lesions whose global genomic repair is dependent on p53. (Mol Cancer Res 2009;7(2):237-46)

Inhibition of C6 rat glioma proliferation by [Ru(2)Cl(Ibp)(4)] depends on changes in p21, p27, Bax/Bcl2 ratio and mitochondrial membrane potential

The ruthenium compound [Ru(2)Cl(Ibp)(4)] (or RuIbp) has been reported to cause significantly greater inhibition of C6 glioma cell proliferation than the parent HIbp. The present study determined the effects of 0-72 h exposure to RuIbp upon C6 cell cycle distribution, mitochondrial membrane potential, reactive species generation and mRNA and protein expression of E2F1, cyclin D1, c-myc, pRb, p21, p27, p53, Ku70, Ku80, Bax, Bcl2, cyclooxygenase 1 and 2 (COX1 and COX2). The most significant changes in mRNA and protein expression were seen for the cyclin-dependent kinase inhibitors p21 and p27 which were both increased (p<0.05). The marked decrease in mitochondrial membrane potential (p<0.01) and modest increase in apoptosis was accompanied by a decrease in anti-apoptotic Bcl2 expression and an increase in pro-apoptotic Bax expression (p<0.05). Interestingly, COX1 expression was increased in response to a significant loss of prostaglandin E(2) production (p<0.001), most likely due to the intracellular action of Ibp. Future studies will investigate the efficacy of this novel ruthenium-ibuprofen complex in human glioma cell lines in vitro and both rat and human glioma cells growing under orthotopic conditions in vivo. (C) 2010 Elsevier Inc. All rights reserved.

The novel ruthenium-gamma-linolenic complex [Ru(2)(aGLA)(4)Cl] inhibits C6 rat glioma cell proliferation and induces changes in mitochondrial membrane potential, increased reactive oxygen species generation and apoptosis in vitro

The present study reports the synthesis of a novel compound with the formula [Ru(2)(aGLA)(4)Cl] according to elemental analyses data, referred to as Ru(2)GLA. The electronic spectra of Ru(2)GLA is typical of a mixed valent diruthenium(II,III) carboxylate. Ru(2)GLA was synthesized with the aim of combining and possibly improving the anti-tumour properties of the two active components ruthenium and gamma-linolenic acid (GLA). The properties of Ru(2)GLA were tested in C6 rat glioma cells by analysing cell number, viability, lipid droplet formation, apoptosis, cell cycle distribution, mitochondrial membrane potential and reactive oxygen species. Ru(2)GLA inhibited cell proliferation in a time and concentration dependent manner. Nile Red staining suggested that Ru(2)GLA enters the cells and ICP-AES elemental analysis found all increase in ruthenium from <0.02 to 425 mg/Kg in treated cells. The sub-G1 apoptotic cell population was increased by Ru(2)GLA (22 +/- 5.2%) when analysed by FACS and this was confirmed by Hoechst staining of nuclei. Mitochondrial membrane potential was decreased in the presence of Ru(2)GLA (44 +/- 2.3%). In contrast, the cells which maintained a high mitochondrial membrane potential had an increase (18 +/- 1.5%) in reactive oxygen species generation. Both decreased mitochondrial membrane potential and increased reactive oxygen species generation may be involved in triggering apoptosis in Ru(2)GLA exposed cells. The EC(50) for Ru(2)GLA decreased with increasing time of exposure from 285 mu M at 24h, 211 mu M at 48 h to 81 mu M at 72 h. In conclusion, Ru(2)GLA is a novel drug with anti proliferative properties in C6 glioma cells and is a potential candidate for novel therapies in gliomas. Copyright (C) 2009 John Wiley & Sons, Ltd.