<> "The repository administrator has not yet configured an RDF license."^^ . <> . . "A new approach to analyze cancer-specific DNA \r\nmethylation data by considering the cellular origin"^^ . "Current approaches in the cancer field mainly focus on the identification of genetic alterations driving \r\ntumors. However, in many tumor types, including chronic lymphocytic leukemia (CLL), no underlying \r\ngenetic mechanism has been identified in about 30% of the affected patients. Consequently, the focus of \r\nresearch has shifted towards epigenetic modifications, including aberrant DNA methylation as a potential \r\ndriver contributing to tumorigenesis. Unlike genetic modifications, epigenetic alterations are potentially \r\nreversible, making them attractive targets for therapeutic interventions. \r\nChronic lymphocytic leukemia (CLL) is the most frequent leukemia in adults and originates from rapidly differentiating B cells, which undergo extensive epigenetic reprogramming during normal B cell differentiation. Every differentiation stage of a normal B cell is represented by unique patterns present at \r\nthe DNA methylation level (methylation footprint), which is maintained and stably propagated in CLL. \r\nConsequently, this stable epigenetic patterning can serve as an indicator for the identification of the cell-of-\r\norigin for each individual CLL case. For the purpose of this thesis, I define the cancer cell-of-origin as the cell \r\nthat acquires sufficient oncogenic hits (genetic and/or epigenetic) to initiate its tumorigenic growth defined \r\nas a measurable deviation from the normal B cell differentiation trajectory. This means that at least two \r\nfactors contribute to the epigenetic patterns seen in CLL: first, epigenetic patterns which were present in \r\nthe tumor-initiating B cell at the time of transformation, and second, CLL-specific epigenetic alterations that \r\noccur during leukemogenesis and, which may relate to genetic alterations or to aberrant signaling events \r\nthat the leukemic cells acquire in response to extrinsic or intrinsic stimuli. \r\nDefining CLL-specific epigenetic events, which are distinct from normal epigenetic B cell programming, is of \r\nutmost importance to understand the molecular alterations contributing to CLL. Previous studies in CLL have already proposed aberrant methylation events and attempted to describe their impact on the \r\nexpression of both, protein-coding genes (e.g. DAPK1, ZAP70, ID4) and microRNAs (e.g. miR-9, miR-181a/b, \r\nmiR-34a, miR-708). However, all these studies defined aberrant methylation events based on the \r\ncomparison of CLL methylomes with those of peripheral blood CD19+ B cells as a control. As a result, these \r\nstudies completely neglected the massive epigenetic programming that occurs during normal B cell \r\ndifferentiation. Therefore, novel approaches aiming at identifying truly CLL-specific methylation changes \r\nconsidering the highly dynamic methylome during normal B cell differentiation were urgently needed. \r\nIn this thesis, I used linear modeling to describe the continuum of epigenetic alterations occurring during \r\nnormal B cell differentiation. DNA methylomes of CLL cells were subsequently precisely positioned into the \r\nnormal B cell differentiation trajectory to define the DNA methylomes of the cell-of-origin for every CLL patient. Considering this cellular origin, I identified CLL-specific methylation events as well as epigenetic alterations reflecting on normal B cell differentiation. The relevance of this approach was demonstrated by contrasting the number of epigenetically deregulated miRNAs and protein-coding genes to those determined using bulk CD19+ cells from peripheral blood as controls. This analysis highlighted the extent of overcalling of leukemia-specific methylation changes in previous studies and highlights the importance of the use of proper control cells for the identification of disease-specific DNA methylation events. The analytical approach described in this thesis provides a general framework for the identification of the cancer cell-of-origin that could be applied in the future to other cancer entities."^^ . "2018" . . . . . . . "Justyna Anna"^^ . "Wierzbinska"^^ . "Justyna Anna Wierzbinska"^^ . . . . . . "A new approach to analyze cancer-specific DNA \r\nmethylation data by considering the cellular origin (PDF)"^^ . . . "Thesis_Wierzbinska_JW_final_en.pdf"^^ . . . "A new approach to analyze cancer-specific DNA \r\nmethylation data by considering the cellular origin (Other)"^^ . . . . . . "indexcodes.txt"^^ . . . "A new approach to analyze cancer-specific DNA \r\nmethylation data by considering the cellular origin (Other)"^^ . . . . . . "lightbox.jpg"^^ . . . "A new approach to analyze cancer-specific DNA \r\nmethylation data by considering the cellular origin (Other)"^^ . . . . . . "preview.jpg"^^ . . . "A new approach to analyze cancer-specific DNA \r\nmethylation data by considering the cellular origin (Other)"^^ . . . . . . "medium.jpg"^^ . . . "A new approach to analyze cancer-specific DNA \r\nmethylation data by considering the cellular origin (Other)"^^ . . . . . . "small.jpg"^^ . . "HTML Summary of #25748 \n\nA new approach to analyze cancer-specific DNA \nmethylation data by considering the cellular origin\n\n" . "text/html" . . . "570 Biowissenschaften, Biologie"@de . "570 Life sciences"@en . .