Browsing by Author "Kandemir, Basak"

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ETS-Domain Transcription Factor Elk-1 Regulates Stemness Genes in Brain Tumors and CD133+ BrainTumor-Initiating Cells
(2021) Sogut, Melis Savasan; Venugopal, Chitra; Kandemir, Basak; Dag, Ugur; Mahendram, Sujeivan; Singh, Sheila; Gulfidan, Gizem; Arga, Kazim Yalcin; Yilmaz, Bayram; Kurnaz, Isil Aksan; 0000-0003-1909-5778; 33672811
Elk-1, a member of the ternary complex factors (TCFs) within the ETS (E26 transformation-specific) domain superfamily, is a transcription factor implicated in neuroprotection, neurodegeneration, and brain tumor proliferation. Except for known targets, c-fos and egr-1, few targets of Elk-1 have been identified. Interestingly, SMN, SOD1, and PSEN1 promoters were shown to be regulated by Elk-1. On the other hand, Elk-1 was shown to regulate the CD133 gene, which is highly expressed in brain-tumor-initiating cells (BTICs) and used as a marker for separating this cancer stem cell population. In this study, we have carried out microarray analysis in SH-SY5Y cells overexpressing Elk-1-VP16, which has revealed a large number of genes significantly regulated by Elk-1 that function in nervous system development, embryonic development, pluripotency, apoptosis, survival, and proliferation. Among these, we have shown that genes related to pluripotency, such as Sox2, Nanog, and Oct4, were indeed regulated by Elk-1, and in the context of brain tumors, we further showed that Elk-1 overexpression in CD133+ BTIC population results in the upregulation of these genes. When Elk-1 expression is silenced, the expression of these stemness genes is decreased. We propose that Elk-1 is a transcription factor upstream of these genes, regulating the self-renewal of CD133+ BTICs.
Gene Regulatory Network of ETS Domain Transcription Factors in Different Stages of Glioma
(2021) Babal, Yigit Koray; Kandemir, Basak; Kurnaz, Isil Aksan; 0000-0003-1909-5778; 33671331
The ETS domain family of transcription factors is involved in a number of biological processes, and is commonly misregulated in various forms of cancer. Using microarray datasets from patients with different grades of glioma, we have analyzed the expression profiles of various ETS genes, and have identified ETV1, ELK3, ETV4, ELF4, and ETV6 as novel biomarkers for the identification of different glioma grades. We have further analyzed the gene regulatory networks of ETS transcription factors and compared them to previous microarray studies, where Elk-1-VP16 or PEA3-VP16 were overexpressed in neuroblastoma cell lines, and we identify unique and common regulatory networks for these ETS proteins.
Transcriptomic profile of Pea3 family members reveal regulatory codes for axon outgrowth and neuronal connection specificity
(2020) Kandemir, Basak; Gulfidan, Gizem; Arga, Kazim Yalcin; Yilmaz, Bayram; Kurnaz, Isil Aksan; 0000-0003-1909-5778; 33097800
PEA3 transcription factor subfamily is present in a variety of tissues with branching morphogenesis, and play a particularly significant role in neural circuit formation and specificity. Many target genes in axon guidance and cell-cell adhesion pathways have been identified for Pea3 transcription factor (but not for Erm or Er81); however it was not so far clear whether all Pea3 subfamily members regulate same target genes, or whether there are unique targets for each subfamily member that help explain the exclusivity and specificity of these proteins in neuronal circuit formation. In this study, using transcriptomics and qPCR analyses in SH-SY5Y neuroblastoma cells, hypothalamic and hippocampal cell line, we have identified cell type-specific and subfamily member-specific targets for PEA3 transcription factor subfamily. While Pea3 upregulates transcription of Sema3D and represses Sema5B, for example, Erm and Er81 upregulate Sema5A and Er81 regulates Unc5C and Sema4G while repressing EFNB3 in SH-SY5Y neuroblastoma cells. We furthermore present a molecular model of how unique sites within the ETS domain of each family member can help recognize specific target motifs. Such cell-context and member-specific combinatorial expression profiles help identify cell-cell and cell-extracellular matrix communication networks and how they establish specific connections.