Cellular Systems Genomics

Coordinator:    Prof. Dr. Stefan Wiemann
Institution: Deutsches Krebsforschungszentrum
The IG Cellular Systems Genomics builds on expertise, research tools, technologies, capacities and collaborations mostly established in NGFN-2 (e.g. within SMP-Cell), and generates knowledge on fundamental molecular, cellular, and disease-relevant processes.

Our main objectives are:

• to apply qualitative and quantitative functional genomic, proteomic, and cell biological strategies, in order to analyze and understand the dynamics and cross-talk as well as feedback mechanisms in signaling pathways and networks in vitro and in vivo. To this end, we study genes, proteins and micro RNAs and their impact on biological systems. Discoveries made in cell culture systems are then tested by applying patient samples (biopsies, tumor material, blood samples) in order to validate and translate in vitro findings into the in vivo system.
• to generate systems genomics models that predict and validate novel markers for diagnosis and prognosis as well as target molecules with potential for therapeutic intervention. To this end, we first analyze and integrate functional data and information, construct mathematical models describing the biological networks that are comprised of genes, proteins, miRNAs and other factors. Then, we test these models experimentally in order to validate (or falsify) assumptions in order to refine the model, and to lastly make predictions for the behavior of the system upon applied stress.
• to validate the gained knowledge in breast cancer, where drug resistance mechanisms shall be elucidated. Here we define routes that shall prevent or overcome acquired drug resistance and lead to tumor remission. Focusing on the EGF-family of growth factor receptors as well as connected signaling networks, we study mechanisms of resistance against therapeutics used in the clinics, for example, trastuzumab and tamoxifen. There, we aim to devise novel strategies for therapeutic intervention that should overcome de novo and acquired resistance.

Latest results can be found in detail in the descriptions of the subprojects

Additional relevant Internet links:
IG Cellular Systems Genomics
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