SOX2 in focus: association of SOX2 copy number variation with TP53 mutation in TCGA pancancer cohorts and codon optimized design for de novo SOX2 synthesis using novel shiny application
buir.advisor | Karakayalı, Özlen Konu | |
dc.contributor.author | Çelik, Siber Güneş | |
dc.date.accessioned | 2024-02-05T06:12:21Z | |
dc.date.available | 2024-02-05T06:12:21Z | |
dc.date.copyright | 2024-01 | |
dc.date.issued | 2024-01 | |
dc.date.submitted | 2024-02-02 | |
dc.description | Cataloged from PDF version of article. | |
dc.description | Thesis (Master's): Bilkent University, Graduate Program in Neuroscience, İhsan Doğramacı Bilkent University, 2024. | |
dc.description | Includes bibliographical references (leaves 76-85). | |
dc.description.abstract | Recombinant proteins are crucial for diverse research applications such as biosensors and cancer studies. Proteins are engineered through de novo gene synthesis methods. Numerous tools and databases have emerged to facilitate the design of recombinant proteins, starting from the design of the gene sequence. De novo DNA synthesis enables the synthesis of custom-designed sequences, allowing codon optimization to enhance expression yield in heterologous systems. In cancer research, recombinant expression of proteins involved in tumorigenesis-related signaling pathways is employed for functional studies, potentially revealing new therapeutic targets. A notable example is the pivotal role of SOX2 expression in the formation of cancer stem cells (CSCs) across various cancer types. Previous studies highlight SOX2 expression functionally overlaps with TP53 expression on the PI3K/AKT signaling pathway. This association may stem from the p53-MDM2 interaction. This thesis investigates the association between SOX2 copy number gain and TP53 mutations within TCGA PanCancer cohorts. Fisher’s exact test results reveal varying association, dependent on tissue type and specific driver mutations within each cancer type. The findings suggest the potential therapeutic relevance of SOX2 in cancer research. Furthermore, the thesis employs an in-silico approach to design de novo SOX2 synthesis, utilizing a novel shiny app that integrates codon optimization and primer design functionalities. The app enables simultaneous codon optimization for multiple expression systems and offers distance analysis through hierarchical clustering. Codon optimization feature provides control over the rate of replacement value for codon substitution which validated through a case study involving human insulin. Finally, app design set of overlapping primers with synchronized melting temperature to be used in PCR assembly for de novo SOX2 gene synthesis. | |
dc.description.provenance | Made available in DSpace on 2024-02-05T06:12:21Z (GMT). No. of bitstreams: 1 B151275.pdf: 3494244 bytes, checksum: b519017587cba5d21cbc8861c1886cd0 (MD5) Previous issue date: 2024-01 | en |
dc.description.statementofresponsibility | by Siber Güneş Çelik | |
dc.format.extent | xvii, 89 leaves : color illustrations, charts ; 30 cm. | |
dc.identifier.itemid | B151275 | |
dc.identifier.uri | https://hdl.handle.net/11693/114251 | |
dc.language.iso | English | |
dc.rights | info:eu-repo/semantics/openAccess | |
dc.subject | Recombinant protein | |
dc.subject | Cancer | |
dc.subject | TCGA-PANCAN | |
dc.subject | SOX2 | |
dc.subject | TP53 | |
dc.subject | Association analysis | |
dc.subject | Codon optimization | |
dc.subject | PCR assembly | |
dc.subject | Primer design | |
dc.title | SOX2 in focus: association of SOX2 copy number variation with TP53 mutation in TCGA pancancer cohorts and codon optimized design for de novo SOX2 synthesis using novel shiny application | |
dc.title.alternative | SOX2 odak noktasında: SOX2 gen kopya sayısı varyosyonunun TCGA pancancer kümelerinde TP53 mutasyonu ile ilişkisi ve shıny uygulaması kullanılarak de novo SOX2 sentezi için kodon optimize tasarım | |
dc.type | Thesis | |
thesis.degree.discipline | Neuroscience | |
thesis.degree.grantor | Bilkent University | |
thesis.degree.level | Master's | |
thesis.degree.name | MS (Master of Science) |