Project Details
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Processing, management, and integrated analysis of ALL OMICS data

Applicants Dr. Michael Forster, since 1/2024; Dr. Alina Hartmann
Subject Area Hematology, Oncology
Term since 2022
Project identifier Deutsche Forschungsgemeinschaft (DFG) - Project number 444949889
 
Acute lymphoblastic leukemia (ALL) has a complex molecular genetic makeup comprising multiple subtypes commonly defined by structural chromosomal alterations, mostly identified by recurrent driver gene fusions or specific aneuploidy patterns. The identification of gene fusions in particular is essential, not only for diagnosis but also for choosing a treatment regime and predicting clinical outcome. Thus, analysis of bulk expression data is a common choice for studying ALL patients, individually or across cohorts. However, while comparatively cheap, the diagnostic “resolution” of this approach is still limited due to challenges associated with extracting cell-population specific expression signals from mixed tissues. Moreover, the resulting data only represent one aspect of the complex molecular underpinnings of ALL. Ultimately, delineating the mechanistic basis of the disease and its various manifestations will require the use of a wider range of molecular high-throughput next generation sequencing- and chip array techniques - bringing together information from genetics and molecular phenotypes. Such data open the door for complex integration and computational modelling as a basis to develop novel, cost effective and more targeted analytical strategies and in turn improve diagnosis and decision making. This proposal is part of the planned clinical research group “CATCH ALL” and will take on the task of coordinating, processing, and managing the wide range of next-generation sequencing data generated across experimental projects. In addition to offering a unified data base for scientific analysis, the INF project will support the clinical interpretation of molecular data and conduct data integration and modelling to improve the diagnostic precision of high-throughput sequencing of e.g., transcriptomes.
DFG Programme Clinical Research Units
Ehemaliger Antragsteller Marc Höppner, Ph.D., until 12/2023
 
 

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