Browsing by Subject "Brain cancer"

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    TERT distal promoter GC islands are critical for telomerase and together with DNMT3B silencing may serve as a senescence-inducing agent in gliomas
    (Taylor & Francis Inc., 2022-08-23) Şerifoğlu, Naz; Adams, Michelle; Erbaba, Begün; Arslan-Ergül, Ayça
    Telomerase is reactivated in the majority of cancers. For instance, in gliomas, it is common that the TERT promoter is mutated. Research on telomere promoter GC islands have been focused primarily on proximal TERT promoter but little is known about the distal promoter. Therefore, in this study, we investigated the proximal and distal TERT promoter, in terms of DNA methylation. We did bisulfite sequencing in zebrafish tissue samples for the distal tert promoter. In the zebrafish brain tissues, we identified a hypomethylation site in the tert promoter, and found that this hypomethylation was associated with aging and shortened telomeres. Through site directed mutagenesis in glioma cell lines, we changed 10 GC spots individually, cloned into a reporter vector, and measured promoter activity. Finally, we silenced DNMT3B and measured telomerase activity along with vidaza and adriamycin treatments. Site directed mutagenesis of glioma cell lines revealed that each of the 10 GC spots are critical for telomerase activity. Changing GC to AT abolished promoter activity in all spots when transfected into glioma cell lines. Then, through silencing of DNMT3B, we observed a reduction in hTERT expression levels, while hTR remained the same, and a major increase in senescence-associated beta-galactosidase activity. Finally, we propose a model regarding the efficacy of two chemotherapeutic drugs, adriamycin and azacytidine, on gliomas. Here, we show that distal TERT promoter is critical; changing even one GC to AT abolishes TERT promoter activity. DNMT3B, a de novo methyltransferase, together with GC islands in distal TERT promoter plays an important role in regulation of telomerase expression and senescence.
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    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.