<> "The repository administrator has not yet configured an RDF license."^^ . <> . . "Computational multi-omics analysis of pediatric DADDR patients and synthetic lethality prediction in K27M mutated pediatric high-grade glioma"^^ . "Pediatric cancer is a conglomerate of complicated diseases remaining one of the leading causes\r\nof death worldwide in patients aged 1 – 19. In recent years, major sequencing and precision\r\noncology programs were launched and aggregated unprecedented amounts of data giving\r\ndetailed insights into pediatric cancer at multiple omics levels.\r\nOne possible avenue for improved treatment strategies, leverages synthetic lethality (SL)\r\ninteractions between genes, potentially resulting in clinically relevant combination treatments.\r\nDespite the great interest, discovery of gene pairs with synthetically lethal interaction is very\r\nchallenging and resource consuming because of the sheer size of the combinatorial space that\r\nneeds to be covered. Advancements in in-silico prediction methods, utilizing multi-omics data,\r\nfor SL interactions to narrow down the scope of investigation have gained popularity over the\r\nlast years. In the first part of this study, I present and extensively evaluate a computational\r\napproach for the prediction of interacting pairs of genes exhibiting synthetic lethality. I apply\r\nmy approach to two dedicated dataset I curated from multi-omics data of pediatric high-grade\r\nglioma (pedHGG) patients and compare the results. Finally, I describe a set of predicted SL\r\npairs specific for pedHGG K27M, a particularly challenging childhood brain tumor, which\r\nincludes multiple drug targets, targetable for example by HDAC inhibitors, that might serve as\r\na guide for future investigations.\r\nMutational signatures as a proxy for underlying mutational processes can be used as a\r\nbiomarker for example for the detection of homologous recombination (HR) deficiency in adult\r\ncancer patients. However, biomarkers identified for adult cancer cannot be used for pediatric\r\npatients without further investigation and validation because of the different disease types and\r\nbiological characteristics of pediatric cancer. In the second part of this study, I present an\r\ninvestigation into the active mutational processes in pediatric patients with disorders with\r\nabnormal DNA damage response. Using the latest set of mutational signatures and comparing\r\ntwo extraction algorithms, I thoroughly investigate associations of mutational signatures with\r\nclinically relevant characteristics and present a comprehensive overview of the mutational\r\nlandscape in pediatric patients with abnormal DNA damage response. I was able to confirm\r\nreported associations of mutational signatures and my results further refine previous results\r\nespecially with regard to differences between patients with germline TP53 mutation and\r\npatients with wildtype TP53. Further, I compare differences, reflected in mutational signatures,\r\nbetween patients with germline mutation in MSH6, MSH2, MLH1 or PMS2 that belong to the\r\nmismatch repair deficiency syndrome.\r\nNot just mutational signatures but also methylation can be used as a reliable biomarker e.g. to\r\nclassify pediatric tumors with high accuracy into subgroups beyond what is possible via\r\nmorphological differences. This classification method poises challenges for patients with\r\nhereditary abnormal DNA damage response and currently there is only limited knowledge about\r\nmethylation patterns in such patients. In the third part of this study, I present new insights\r\ninvestigating methylation patterns in patients with abnormal DNA damage response. Using a\r\nmolecularly characterized control cohort I assembled and accounting for immune cell\r\ninfiltration, I was able to identify methylation signatures specific for defective DNA damage\r\nresponse across different tumor types. After detailed characterization of the discriminatory\r\npower of the identified methylation signature, that indicated achieving 90% precision is\r\npossible, I further investigated the biological function of identified methylation sites. This\r\nrevealed association with biological functions including the RISC complex, RNAi and DNA\r\ndamage response pathways such as base excision repair and nucleotide excision repair. Finally,\r\nI validated the presented methylation signatures in an additional internal and one external\r\npatient cohort consisting of liquid biopsy samples, demonstrating the broader applicability and\r\nhighlighting a potential clinical application of the methylation signatures."^^ . "2024" . . . . . . . "Lukas"^^ . "Madenach"^^ . "Lukas Madenach"^^ . . . . . . "Computational multi-omics analysis of pediatric DADDR patients and synthetic lethality prediction in K27M mutated pediatric high-grade glioma (PDF)"^^ . . . "Thesis_LukasMadenach_final_for_printing.pdf"^^ . . . "Computational multi-omics analysis of pediatric DADDR patients and synthetic lethality prediction in K27M mutated pediatric high-grade glioma (Other)"^^ . . . . . . "indexcodes.txt"^^ . . . "Computational multi-omics analysis of pediatric DADDR patients and synthetic lethality prediction in K27M mutated pediatric high-grade glioma (Other)"^^ . . . . . . "lightbox.jpg"^^ . . . "Computational multi-omics analysis of pediatric DADDR patients and synthetic lethality prediction in K27M mutated pediatric high-grade glioma (Other)"^^ . . . . . . "preview.jpg"^^ . . . "Computational multi-omics analysis of pediatric DADDR patients and synthetic lethality prediction in K27M mutated pediatric high-grade glioma (Other)"^^ . . . . . . "medium.jpg"^^ . . . "Computational multi-omics analysis of pediatric DADDR patients and synthetic lethality prediction in K27M mutated pediatric high-grade glioma (Other)"^^ . . . . . . "small.jpg"^^ . . "HTML Summary of #35831 \n\nComputational multi-omics analysis of pediatric DADDR patients and synthetic lethality prediction in K27M mutated pediatric high-grade glioma\n\n" . "text/html" . . . "570 Biowissenschaften, Biologie"@de . "570 Life sciences"@en . .