213 resultados para glioblastome multiforme (GBM)


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At St Thomas' Hospital, we have developed a computer program on a Titan graphics supercomputer to plan the stereotactic implantation of iodine-125 seeds for the palliative treatment of recurrent malignant gliomas. Use of the Gill-Thomas-Cosman relocatable frame allows planning and surgery to be carried out at different hospitals on different days. Stereotactic computed tomography (CT) and positron emission tomography (PET) scans are performed and the images transferred to the planning computer. The head, tumour and frame fiducials are outlined on the relevant images, and a three-dimensional model generated. Structures which could interfere with the surgery or radiotherapy, such as major vessels, shunt tubing etc., can also be outlined and included in the display. Catheter target and entry points are set using a three-dimensional cursor controlled by a set of dials attached to the computer. The program calculates and displays the radiation dose distribution within the target volume for various catheter and seed arrangements. The CT co-ordinates of the fiducial rods are used to convert catheter co-ordinates from CT space to frame space and to calculate the catheter insertion angles and depths. The surgically implanted catheters are after-loaded the next day and the seeds left in place for between 4 and 6 days, giving a nominal dose of 50 Gy to the edge of the target volume. 25 patients have been treated so far.

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Objectives Demonstrate the application of decision trees – classification and regression trees (CARTs), and their cousins, boosted regression trees (BRTs) – to understand structure in missing data. Setting Data taken from employees at three different industry sites in Australia. Participants 7915 observations were included. Materials and Methods The approach was evaluated using an occupational health dataset comprising results of questionnaires, medical tests, and environmental monitoring. Statistical methods included standard statistical tests and the ‘rpart’ and ‘gbm’ packages for CART and BRT analyses, respectively, from the statistical software ‘R’. A simulation study was conducted to explore the capability of decision tree models in describing data with missingness artificially introduced. Results CART and BRT models were effective in highlighting a missingness structure in the data, related to the Type of data (medical or environmental), the site in which it was collected, the number of visits and the presence of extreme values. The simulation study revealed that CART models were able to identify variables and values responsible for inducing missingness. There was greater variation in variable importance for unstructured compared to structured missingness. Discussion Both CART and BRT models were effective in describing structural missingness in data. CART models may be preferred over BRT models for exploratory analysis of missing data, and selecting variables important for predicting missingness. BRT models can show how values of other variables influence missingness, which may prove useful for researchers. Conclusion Researchers are encouraged to use CART and BRT models to explore and understand missing data.

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Cucurbit crops host a range of serious sap-sucking insect pests, including silverleaf whitefly (SLW) and aphids, which potentially represent considerable risk to the Australian horticulture industry. These pests are extremely polyphagous with a wide host range. Chemical control is made difficult due to resistance and pollution, and other side-effects are associated with insecticide use. Consequently, there is much interest in maximising the role of biological control in the management of these sap-sucking insect pests. This study aimed to evaluate companion cropping alongside cucurbit crops in a tropical setting as a means to increase the populations of beneficial insects and spiders so as to control the major sap-sucking insect pests. The Population of beneficial and harmful insects, with a focus on SLW and aphids, and other invertebrates were sampled weekly oil four different crops which could be used for habitat manipulation: Goodbug Mix (GBM; a proprietary seed Mixture including self-sowing annual and perennial herbaceous flower species); lablab (Lablab purpureus L. Sweet); lucerne (Medicago sativa L.); and niger (Guizotia abyssinica (L.f.) Cass.). Lablab hosted the highest numbers of beneficial insects (larvae and adults of lacewing (Mallada signata (Schneider)), ladybird beetles (Coccinella transversalis Fabricius) and spiders) while GBM hosted the highest numbers of European bees (Apis mellifera Linnaeus) and spiders. Lucerne and niger showed little promise in hosting beneficial insects, but lucerne hosted significantly more spiders (double the numbers) than niger. Lucerne hosted significantly more of the harmful insect species of aphids (Aphis gossypii (Glover)) and Myzus persicae (Sulzer)) and heliothis (Heliothis armigera Hubner). Niger hosted significantly more vegetable weevils (Listroderes difficillis (Germar)) than the other three species. Therefore, lablab and GBM appear to be viable options to grow within cucurbits or as field boundary crops to attract and increase beneficial insects and spiders for the control of sap-sucking insect pests. Use of these bio-control strategies affords the opportunity to minimise pesticide usage and the risks associated with pollution.

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This thesis presents novel modelling applications for environmental geospatial data using remote sensing, GIS and statistical modelling techniques. The studied themes can be classified into four main themes: (i) to develop advanced geospatial databases. Paper (I) demonstrates the creation of a geospatial database for the Glanville fritillary butterfly (Melitaea cinxia) in the Åland Islands, south-western Finland; (ii) to analyse species diversity and distribution using GIS techniques. Paper (II) presents a diversity and geographical distribution analysis for Scopulini moths at a world-wide scale; (iii) to study spatiotemporal forest cover change. Paper (III) presents a study of exotic and indigenous tree cover change detection in Taita Hills Kenya using airborne imagery and GIS analysis techniques; (iv) to explore predictive modelling techniques using geospatial data. In Paper (IV) human population occurrence and abundance in the Taita Hills highlands was predicted using the generalized additive modelling (GAM) technique. Paper (V) presents techniques to enhance fire prediction and burned area estimation at a regional scale in East Caprivi Namibia. Paper (VI) compares eight state-of-the-art predictive modelling methods to improve fire prediction, burned area estimation and fire risk mapping in East Caprivi Namibia. The results in Paper (I) showed that geospatial data can be managed effectively using advanced relational database management systems. Metapopulation data for Melitaea cinxia butterfly was successfully combined with GPS-delimited habitat patch information and climatic data. Using the geospatial database, spatial analyses were successfully conducted at habitat patch level or at more coarse analysis scales. Moreover, this study showed it appears evident that at a large-scale spatially correlated weather conditions are one of the primary causes of spatially correlated changes in Melitaea cinxia population sizes. In Paper (II) spatiotemporal characteristics of Socupulini moths description, diversity and distribution were analysed at a world-wide scale and for the first time GIS techniques were used for Scopulini moth geographical distribution analysis. This study revealed that Scopulini moths have a cosmopolitan distribution. The majority of the species have been described from the low latitudes, sub-Saharan Africa being the hot spot of species diversity. However, the taxonomical effort has been uneven among biogeographical regions. Paper III showed that forest cover change can be analysed in great detail using modern airborne imagery techniques and historical aerial photographs. However, when spatiotemporal forest cover change is studied care has to be taken in co-registration and image interpretation when historical black and white aerial photography is used. In Paper (IV) human population distribution and abundance could be modelled with fairly good results using geospatial predictors and non-Gaussian predictive modelling techniques. Moreover, land cover layer is not necessary needed as a predictor because first and second-order image texture measurements derived from satellite imagery had more power to explain the variation in dwelling unit occurrence and abundance. Paper V showed that generalized linear model (GLM) is a suitable technique for fire occurrence prediction and for burned area estimation. GLM based burned area estimations were found to be more superior than the existing MODIS burned area product (MCD45A1). However, spatial autocorrelation of fires has to be taken into account when using the GLM technique for fire occurrence prediction. Paper VI showed that novel statistical predictive modelling techniques can be used to improve fire prediction, burned area estimation and fire risk mapping at a regional scale. However, some noticeable variation between different predictive modelling techniques for fire occurrence prediction and burned area estimation existed.

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Glioblastoma (GBM; grade IV astrocytoma) is a very aggressive form of brain cancer with a poor survival and few qualified predictive markers. This study integrates experimentally validated genes that showed specific upregulation in GBM along with their protein-protein interaction information. A system level analysis was used to construct GBM-specific network. Computation of topological parameters of networks showed scale-free pattern and hierarchical organization. From the large network involving 1,447 proteins, we synthesized subnetworks and annotated them with highly enriched biological processes. A careful dissection of the functional modules, important nodes, and their connections identified two novel intermediary molecules CSK21 and protein phosphatase 1 alpha (PP1A) connecting the two subnetworks CDC2-PTEN-TOP2A-CAV1-P53 and CDC2-CAV1-RB-P53-PTEN, respectively. Real-time quantitative reverse transcription-PCR analysis revealed CSK21 to be moderately upregulated and PP1A to be overexpressed by 20-fold in GBM tumor samples. Immunohistochemical staining revealed nuclear expression of PP1A only in GBM samples. Thus, CSK21 and PP1A, whose functions are intimately associated with cell cycle regulation, might play key role in gliomagenesis. Cancer Res; 70(16); 6437-47. (C)2010 AACR.

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Glioblastoma (GBM; grade IV astrocytoma) is the most malignant and common primary brain tumor in adults. Using combination of 2-DE and MALDI-TOF MS, we analyzed 14 GBM and 6 normal control sera and identified haptoglobin alpha 2 chain as an up-regulated serum protein in GBM patients. GBM-specific up-regulation was confirmed by ELISA based quantitation of haptoglobin (Hp) in the serum of 99 GBM patients as against lower grades (49 grade III/AA; 26 grade II/DA) and 26 normal individuals (p = 0.0001). Further validation using RT-qPCR on an independent set (n = 78) of tumor and normal brain (n = 4) samples and immunohistochemcial staining on a subset (n = 42) of above samples showed increasing levels of transcript and protein with tumor grade and were highest in GBM (p = < 0.0001 and < 0.0001, respectively). Overexpression of Hp either by stable integration of Hp cDNA or exogenous addition of purified Hp to immortalized astrocytes resulted in increased cell migration. RNAi-mediated silencing of Hp in glioma cells decreased cell migration. Further, we demonstrate that both human glioma and mouse melanoma cells overexpressing Hp showed increased tumor growth. Thus, we have identified haptoglobin as a GBM-specific serum marker with a role on glioma tumor growth and migration.

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Glioblastoma (GBM) is the most common and aggressive primary brain tumor with very poor patient median survival. To identify a microRNA (miRNA) expression signature that can predict GBM patient survival, we analyzed the miRNA expression data of GBM patients (n = 222) derived from The Cancer Genome Atlas (TCGA) dataset. We divided the patients randomly into training and testing sets with equal number in each group. We identified 10 significant miRNAs using Cox regression analysis on the training set and formulated a risk score based on the expression signature of these miRNAs that segregated the patients into high and low risk groups with significantly different survival times (hazard ratio HR] = 2.4; 95% CI = 1.4-3.8; p < 0.0001). Of these 10 miRNAs, 7 were found to be risky miRNAs and 3 were found to be protective. This signature was independently validated in the testing set (HR = 1.7; 95% CI = 1.1-2.8; p = 0.002). GBM patients with high risk scores had overall poor survival compared to the patients with low risk scores. Overall survival among the entire patient set was 35.0% at 2 years, 21.5% at 3 years, 18.5% at 4 years and 11.8% at 5 years in the low risk group, versus 11.0%, 5.5%, 0.0 and 0.0% respectively in the high risk group (HR = 2.0; 95% CI = 1.4-2.8; p < 0.0001). Cox multivariate analysis with patient age as a covariate on the entire patient set identified risk score based on the 10 miRNA expression signature to be an independent predictor of patient survival (HR = 1.120; 95% CI = 1.04-1.20; p = 0.003). Thus we have identified a miRNA expression signature that can predict GBM patient survival. These findings may have implications in the understanding of gliomagenesis, development of targeted therapy and selection of high risk cancer patients for adjuvant therapy.

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Glioblastoma is the most common and malignant form of primary astrocytoma. Upon investigation of the insulin-like growth factor (IGF) pathway, we found the IGF2BP3/IMP3 transcript and protein to be up-regulated in GBMs but not in lower grade astrocytomas (p<0.0001). IMP3 is an RNA binding protein known to bind to the 5'-untranslated region of IGF-2 mRNA, thereby activating its translation. Overexpression-and knockdown-based studies establish a role for IMP3 in promoting proliferation, anchorage-independent growth, invasion, and chemoresistance. IMP3 overexpressing B16F10 cells also showed increased tumor growth, angiogenesis, and metastasis, resulting in poor survival in a mouse model. Additionally, the infiltrating front, perivascular, and subpial regions in a majority of the GBMs stained positive for IMP3. Furthermore, two different murine glioma models were used to substantiate the above findings. In agreement with the translation activation functions of IMP3, we also found increased IGF-2 protein in the GBM tumor samples without a corresponding increase in its transcript levels. Also, in vitro IMP3 overexpression/knockdown modulated the IGF-2 protein levels without altering its transcript levels. Additionally, IGF-2 neutralization and supplementation studies established that the proproliferative effects of IMP3 were indeed mediated through IGF-2. Concordantly, PI3K and MAPK, the downstream effectors of IGF-2, are activated by IMP3 and are found to be essential for IMP3-induced cell proliferation. Thus, we have identified IMP3 as a GBM-specific proproliferative and proinvasive marker acting through IGF-2 resulting in the activation of oncogenic PI3K and MAPK pathways.

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IDH1 mutations are frequent genetic alterations in low-grade diffuse gliomas and secondary glioblastoma (GBM). To validate mutation frequency, IDH1 gene at codon 132 was sequenced in 74 diffusely infiltrating astrocytomas: diffuse astrocytoma (DA; World Health Organization WHO] grade II), anaplastic astrocytoma (AA; WHO grade III), and GBM (WHO grade IV). All cases were immunostained with IDH1-R132H monoclonal antibody. Mutational status was correlated with mutant protein expression, patient age, duration of symptoms, and prognosis of patients with GBM. We detected 31 (41.9%) heterozygous IDH1 mutations resulting in arginine-to-histidine substitution (R132H;CGT-CAT). All 12 DAs (100%), 13 of 14 AAs (92.9%), and 6 of 48 GBMs (12.5%) (5/6 83.3%] secondary, and 1/42 2.4%] primary) harbored IDH1 mutations. The correlation between mutational status and protein expression was significant (P < .001). IDH1 mutation status, though not associated with prognosis of patients with GBM, showed significant association with younger age and longer duration of symptoms in the whole cohort (P < .001). Our study validates IDH1 mutant protein expression across various grades of astrocytoma, and demonstrates a high incidence of IDH1 mutations in DA, AA, and secondary GBM.

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Glioblastoma is one of the common types of primary brain tumors with a median survival of 12-15 months. The receptor tyrosine kinase (RTK) pathway is known to be deregulated in 88% of the patients with glioblastoma. 45% of GBM patients show amplifications and activating mutations in EGFR gene leading to the upregulation of the pathway. In the present study, we demonstrate that a brain specific miRNA, miR-219-5p, repressed EGFR by directly binding to its 3'-UTR. The expression of miR-219-5p was downregulated in glioblastoma and the overexpression of miR-219-5p in glioma cell lines inhibited the proliferation, anchorage independent growth and migration. In addition, miR-219-5p inhibited MAPK and PI3K pathways in glioma cell lines in concordance with its ability to target EGFR. The inhibitory effect of miR-219-5p on MAPK and PI3K pathways and glioma cell migration could be rescued by the overexpression of wild type EGFR and vIII mutant of EGFR (both lacking 3'-UTR and thus being insensitive to miR-219-5p) suggesting that the inhibitory effects of miR-219-5p were indeed because of its ability to target EGFR. We also found significant negative correlation between miR-219-5p levels and total as well as phosphorylated forms of EGFR in glioblastoma patient samples. This indicated that the downregulation of miR-219-5p in glioblastoma patients contribute to the increased activity of the RTK pathway by the upregulation of EGFR. Thus, we have identified and characterized miR-219-5p as the RTK regulating novel tumor suppressor miRNA in glioblastoma.

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Glioblastoma (GBM) is the most common, malignant adult primary tumor with dismal patient survival, yet the molecular determinants of patient survival are poorly characterized. Global methylation profile of GBM samples (our cohort; n = 44) using high-resolution methylation microarrays was carried out. Cox regression analysis identified a 9-gene methylation signature that predicted survival in GBM patients. A risk-score derived from methylation signature predicted survival in univariate analysis in our and The Cancer Genome Atlas (TCGA) cohort. Multivariate analysis identified methylation risk score as an independent survival predictor in TCGA cohort. Methylation risk score stratified the patients into low-risk and high-risk groups with significant survival difference. Network analysis revealed an activated NF-kappa B pathway association with high-risk group. NF-kappa B inhibition reversed glioma chemoresistance, and RNA interference studies identified interleukin-6 and intercellular adhesion molecule-1 as key NF-kappa B targets in imparting chemoresistance. Promoter hypermethylation of neuronal pentraxin II (NPTX2), a risky methylated gene, was confirmed by bisulfite sequencing in GBMs. GBMs and glioma cell lines had low levels of NPTX2 transcripts, which could be reversed upon methylation inhibitor treatment. NPTX2 overexpression induced apoptosis, inhibited proliferation and anchorage-independent growth, and rendered glioma cells chemosensitive. Furthermore, NPTX2 repressed NF-kappa B activity by inhibiting AKT through a p53-PTEN-dependent pathway, thus explaining the hypermethylation and downregulation of NPTX2 in NF-kappa B-activated high-risk GBMs. Taken together, a 9-gene methylation signature was identified as an independent GBM prognosticator and could be used for GBM risk stratification. Prosurvival NF-kappa B pathway activation characterized high-risk patients with poor prognosis, indicating it to be a therapeutic target. (C) 2013 AACR.

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Anaplastic astrocytoma (AA; Grade III) and glioblastoma (GBM; Grade IV) are diffusely infiltrating tumors and are called malignant astrocytomas. The treatment regimen and prognosis are distinctly different between anaplastic astrocytoma and glioblastoma patients. Although histopathology based current grading system is well accepted and largely reproducible, intratumoral histologic variations often lead to difficulties in classification of malignant astrocytoma samples. In order to obtain a more robust molecular classifier, we analysed RT-qPCR expression data of 175 differentially regulated genes across astrocytoma using Prediction Analysis of Microarrays (PAM) and found the most discriminatory 16-gene expression signature for the classification of anaplastic astrocytoma and glioblastoma. The 16-gene signature obtained in the training set was validated in the test set with diagnostic accuracy of 89%. Additionally, validation of the 16-gene signature in multiple independent cohorts revealed that the signature predicted anaplastic astrocytoma and glioblastoma samples with accuracy rates of 99%, 88%, and 92% in TCGA, GSE1993 and GSE4422 datasets, respectively. The protein-protein interaction network and pathway analysis suggested that the 16-genes of the signature identified epithelial-mesenchymal transition (EMT) pathway as the most differentially regulated pathway in glioblastoma compared to anaplastic astrocytoma. In addition to identifying 16 gene classification signature, we also demonstrated that genes involved in epithelial-mesenchymal transition may play an important role in distinguishing glioblastoma from anaplastic astrocytoma.

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Glioblastoma (GBM) is the most aggressive type of brain tumor and shows very poor prognosis. Here, using genome-wide methylation analysis, we show that G-CIMP+ and G-CIMP-subtypes enrich distinct classes of biological processes. One of the hypermethylated genes in GBM, ULK2, an upstream autophagy inducer, was found to be down-regulated in GBM. Promoter hypermethylation of ULK2 was confirmed by bisulfite sequencing. GBM and glioma cell lines had low levels of ULK2 transcripts, which could be reversed upon methylation inhibitor treatment. ULK2 promoter methylation and transcript levels showed significant negative correlation. Ectopic overexpression of ULK2-induced autophagy, which further enhanced upon nutrient starvation or temozolomide chemotherapy. ULK2 also inhibited the growth of glioma cells, which required autophagy induction as kinase mutant of ULK2 failed to induce autophagy and inhibit growth. Furthermore, ULK2 induced autophagy and inhibited growth in Ras-transformed immortalized Baby Mouse Kidney (iBMK) ATG5(+/+) but not in autophagy-deficient ATG5(-/-) cells. Growth inhibition due to ULK2 induced high levels of autophagy under starvation or chemotherapy utilized apoptotic cell death but not at low levels of autophagy. Growth inhibition by ULK2 also appears to involve catalase degradation and reactive oxygen species generation. ULK2 overexpression inhibited anchorage independent growth, inhibited astrocyte transformation in vitro and tumor growth in vivo. Of all autophagy genes, we found ULK2 and its homologue ULK1 were only down-regulated in all grades of glioma. Thus these results altogether suggest that inhibition of autophagy by ULK1/2 down-regulation is essential for glioma development.

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Insulin like growth factor binding protein 2 (IGFBP2) is highly up regulated in glioblastoma (GBM) tissues and has been one of the prognostic indicators. There are compelling evidences suggesting important roles for IGFBP2 in glioma cell proliferation, migration and invasion. Extracellular IGFBP2 through its carboxy terminal arginine glycine aspartate (RGD) motif can bind to cell surface alpha 5 beta 1 integrins and activate pathways downstream to integrin signaling. This IGFBP2 activated integrin signaling is known to play a crucial role in IGFBP2 mediated invasion of glioma cells. Hence a molecular inhibitor of carboxy terminal domain of IGFBP2 which can inhibit IGFBP2-cell surface interaction is of great therapeutic importance. In an attempt to develop molecular inhibitors of IGFBP2, we screened single chain variable fragment (scFv) phage display libraries, Tomlinson I (Library size 1.47 x 10(8)) and Tomlinson J (Library size 1.37 x 10(8)) using human recombinant IGFBP2. After screening we obtained three IGFBP2 specific binders out of which one scFv B7J showed better binding to IGFBP2 at its carboxy terminal domain, blocked IGFBP2-cell surface association, reduced activity of matrix metalloprotease 2 in the conditioned medium of glioma cells and inhibited IGFBP2 induced migration and invasion of glioma cells. We demonstrate for the first time that in vitro inhibition of extracellular IGFBP2 activity by using human scFv results in significant reduction of glioma cell migration and invasion. Therefore, the inhibition of IGFBP2 can serve as a potential therapeutic strategy in the management of GBM.

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Glioblastomas (GBM) are largely incurable as they diffusely infiltrate adjacent brain tissues and are difficult to diagnose at early stages. Biomarkers derived from serum, which can be obtained by minimally invasive procedures, may help in early diagnosis, prognosis and treatment monitoring. To develop a serum cytokine signature, we profiled 48 cytokines in sera derived from normal healthy individuals (n = 26) and different grades of glioma patients (n = 194). We divided the normal and grade IV glioma/GBM serum samples randomly into equal sized training and test sets. In the training set, the Prediction Analysis for Microarrays (PAM) identified a panel of 18 cytokines that could discriminate GBM sera fromnormal sera with maximum accuracy (95.40%) and minimum error (4.60%). The 18-cytokine signature obtained in the training set discriminated GBM sera from normal sera in the test set as well (accuracy 96.55%; error 3.45%). Interestingly, the 18-cytokine signature also differentiated grade II/Diffuse Astrocytoma (DA) and grade III/Anaplastic Astrocytoma (AA) sera from normal sera very efficiently (DA vs. normal-accuracy 96.00%, error 4.00%; AA vs. normal-accuracy 95.83%, error 4.17%). Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analysis using 18 cytokines resulted in the enrichment of two pathways, cytokine-cytokine receptor interaction and JAK-STAT pathways with high significance. Thus our study identified an 18-cytokine signature for distinguishing glioma sera fromnormal healthy individual sera and also demonstrated the importance of their differential abundance in glioma biology.