Browsing by Subject "Glioma"

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Open Access
Alterations in the molecular properties of neural stem cells from aged brains and brain tumors
(2017-06) Burhan, Özge Pelin
It is known that new neuron formation in the brain continues throughout the life of an organism. In the adult human brain, it was proven that neurogenesis in the hippocampus is higher than expected, almost 700 new neurons are formed in a day. The formation of new neurons is supported by the stem cell subpopulation in the brain. With learning and the formation of new memories, the neuron production increases. However, changes in the cognitive abilities with advancing age are thought to be caused by the functional and molecular alterations in the stem cell populations. Molecular changes in neural stem cells throughout aging were found to be deterrents of the increased risk of cancer with age, such as tumor suppressor mechanisms. However, the activation and overlap of tumor suppressing mechanisms result in senescence in stem cells that have accumulated oncogenic mutations, which causes the stem cell pool exhaustion. It is thought that cancer cells acquire stem cell-like properties in order to have the unlimited proliferation and self-renewal properties, which are characteristics of both healthy and cancer stem cells. Neural cancer stem cells have the ability to produce glial and neural cells, like normal stem cells. The cancer stem cell subpopulations are implicated in the growth of tumor tissues. Hence, it is important to identify and characterize cancer stem cells and make a distinction between cancer and non-cancer stem cells. In this project, this issue was addressed by studying the marker expressions of brain tumor tissues obtained from humans, which confirmed that the cancer cells do express stem cell and progenitor cell markers, such as Sox2 and Vimentin. The presence of mature neurons was also established by the mature neuronal marker NeuN. In order to determine whether these stem cells may be different in young and old subjects, a study was also carried out in young and old zebrafish neural stem cells in order to identify the expression differences between the groups. The presence of proliferating stem cells and differentiated cells were identified in cell culture. This analysis of neural stem cells in old and young zebrafish revealed 18 differentially-expressed genes. The results indicated a higher differentiation rate in old zebrafish stem cells, which may be due to the increased loss of neural cells in the old zebrafish brain. The development of markers that could be widely used for the diagnosis of cancer and the identification of cell types is important. For reliable diagnosis and identification of cancer cells, multiple cellular markers are used. Hence the distinction of cell types based on light scattering differences would speed up the process of diagnosis, and the elimination of marker used for the distinction of cell types would be beneficial. The final project mentioned in this thesis involves the analysis of C6 (rat glioma) cell line for scattering properties and cell cycle arrest. A general method for definition of a scatter data interval for C6 cells in different stages was developed and can be applied to other cell types and diseases. These studies show that the proliferation and stem cell markers’ expressions differ between cancer and healthy stem cells, and the expression of neuroprotective genes is differentially upregulated in old zebrafish neural stem cells compared to the young. This data could contribute to the knowledge on normal and cancer stem cell expression differences, as well as how age affects the expression, and supply information required for the development of a cancer stem cell identification and targeting methods.
Open Access
Combination of Paclitaxel and R-flurbiprofen loaded PLGA nanoparticles suppresses glioblastoma growth on systemic administration
(Elsevier, 2020) Caban-Toktas, S.; Şahin, A.; Lule, S.; Esendagli, G.; Vural, İ.; Karlı-Oğuz, Kader K.; Söylemezoğlu, F.; Mut, M.; Dalkara, T.; Khan, M.; Capan, Y.
Malignant gliomas are highly lethal. Delivering chemotherapeutic drugs to the brain in sufficient concentration is the major limitation in their treatment due to the blood-brain barrier (BBB). Drug delivery systems may overcome this limitation and can improve the transportation through the BBB. Paclitaxel is an antimicrotubule agent with effective anticancer activity but limited BBB permeability. R-Flurbiprofen is a nonsteroidal antienflammatory drug and has potential anticancer activity. Accordingly, we designed an approach combining R-flurbiprofen and paclitaxel and positively-charged chitosan-modified poly-lactide-co-glycolic acid (PLGA) nanoparticles (NPs) and to transport them to glioma tissue. NPs were characterized and, cytotoxicity and cellular uptake studies were carried out in vitro. The in vivo efficacy of the combination and formulations were evaluated using a rat RG2 glioma tumor model. Polyethylene glycol (PEG) modified and chitosan-coated PLGA NPs demonstrated efficient cytotoxic activity and were internalized by the tumor cells in RG2 cell culture. In vivo studies showed that the chitosan-coated and PEGylated NPs loaded with paclitaxel and R-flurbiprofen exhibited significantly higher therapeutic activity against glioma. In conclusion, PLGA NPs can efficiently carry their payloads to glioma tissue and the combined use of anticancer and anti-inflammatory drugs may exert additional anti-tumor activity.
Open Access
Mathematical modeling of the malignancy of cancer using graph evolution
(Elsevier Inc., 2007) Gunduz Demir, C.
We report a novel computational method based on graph evolution process to model the malignancy of brain cancer called glioma. In this work, we analyze the phases that a graph passes through during its evolution and demonstrate strong relation between the malignancy of cancer and the phase of its graph. From the photomicrographs of tissues, which are diagnosed as normal, low-grade cancerous and high-grade cancerous, we construct cell-graphs based on the locations of cells; we probabilistically generate an edge between every pair of cells depending on the Euclidean distance between them. For a cell-graph, we extract connectivity information including the properties of its connected components in order to analyze the phase of the cell-graph. Working with brain tissue samples surgically removed from 12 patients, we demonstrate that cell-graphs generated for different tissue types evolve differently and that they exhibit different phase properties, which distinguish a tissue type from another. © 2007 Elsevier Inc. All rights reserved.
Open Access
What does reduced FDG uptake mean in high-grade gliomas?
(NLM (Medline), 2019) Bund, C.; Lhermitte, B.; Çiçek, A. Ercüment; Ruhland, E.; Proust, F.; Namer, I. J.
Purpose: As well as in many others cancers, FDG uptake is correlated with the degree of malignancy in gliomas, that is, commonly high FDG uptake in high-grade gliomas. However, in clinical practice, it is not uncommon to observe high-grade gliomas with low FDG uptake. Our aim was to explore the tumor metabolism in 2 populations of high-grade gliomas presenting high or low FDG uptake. Methods: High-resolution magic-angle spinning nuclear magnetic resonance spectroscopy was realized on tissue samples from 7 high-grade glioma patients with high FDG uptake and 5 high-grade glioma patients with low FDG uptake. Tumor metabolomics was evaluated from 42 quantified metabolites and compared by network analysis. Results: Whether originating from astrocytes or oligodendrocytes, the highgrade gliomas with low FDG avidity represent a subgroup of high-grade gliomas presenting common characteristics: low aspartate, glutamate, and creatine levels, which are probably related to the impaired electron transport chain in mitochondria; high serine/glycine metabolism and so one-carbon metabolism; low glycerophosphocholine-phosphocholine ratio in membrane metabolism, which is associated with tumor aggressiveness; and finally negative MGMT methylation status. Conclusions: It seems imperative to identify this subgroup of high-grade gliomas with low FDG avidity, which is especially aggressive. Their identification could be important for early detection for a possible personalized treatment, such as antifolate treatment.
Open Access
Zebrafish glioma xenograft models: in vıvo investıgatıon of injection methods and development of a streamlit application
(2023-10-20) Tombuloğlu, Rüya
Glioblastoma (GBM) is one of the most aggressive and lethal forms of primary brain cancer, posing significant challenges to effective treatment and patient outcomes. Despite extensive research efforts, our understanding of GBM biology and the development of novel therapeutic strategies remains limited. Zebrafish xenograft models have emerged as a promising tool in cancer research, offering unique advantages in studying GBM. This thesis explores the utility of zebrafish xenograft models in advancing our understanding of GBM. Due to their genetic and physiological similarities to humans, zebrafish provide an excellent platform for studying GBM pathogenesis, tumor progression, and drug screening. Their transparency during early development allows for real-time visualization of tumor growth, invasion, and response to treatments. Moreover, zebrafish models enable rapid and cost-effective high-throughput drug screening, accelerating the identification of potential GBM therapeutics. In this thesis, I focused on creating an application named ZenofishDb Glioma, which is a more evolved and focused version of our previous database called ZenofishDb. ZenofishDb Glioma has been created using Python Streamlit, and comprises only the glioma studies and uses Natural Language Processing (NLP) to classify better, and effectively find and summarize information about zebrafish glioma xenograft models. In addition, after searching ZenofishDb Glioma, I decided to investigate an experimental protocol for injection of glioblastoma cells in the zebrafish model to test effects of injected cell numbers. Using MGG-119-GFP cells and Casper zebrafish, I injected different numbers of cells at different locations and stages, i.e., blastula and 2 days post fertilization, and observed there were significant differences between groups at 5 dpf using multiple quantification strategies. In conclusion, ZenofishDb Glioma can help design effective xenotransplantation strategies and make comparisons to understand how different experimental parameters affect the outcome of zebrafish glioma xenograft models.