Forschung / Research

MICROENVIRONMENTAL SIGNALS IN HEALTH AND DISEASE
IN THE CENTRAL AND PERIPHERAL NERVOUS SYSTEM

Our institute focuses on advancing research at the interface of neuropathology, (neuro)-oncology, neurology, and bioinformatics, with a comprehensive approach spanning three interconnected focus areas: Experimental Neuro-Oncology, Computational Neuropathology, and Translational Neuromuscular Research. Together, these domains aim to bridge the gap between fundamental discoveries and clinical applications, using advanced experimental models, computational tools, and translational approaches to address critical challenges in neuro-oncology and neuromuscular diseases.

Our Focus:

Our goal is to deepen the understanding of tumor biology and neuromuscular diseases while developing practical strategies to improve diagnostics and therapies. Through collaboration between neuropathologists, (neuro)oncologists, neurologists and (bio)medical informaticians we create a multidisciplinary environment where classical and AI-assisted approaches are integrated to address complex research questions, connecting biological insights with meaningful clinical applications. By leveraging patient-derived data and combining experimental, computational, and translational research, we aim to bridge the gap between basic science and clinical practice. This approach supports a continuous exchange between benchside discoveries and bedside applications, contributing to advancements in personalized medicine and improved patient care in neuro-oncology, neuromuscular diseases, and related fields.

Our Offer

We offer an open, supportive, internationally competitive academic environment with excellent training opportunities within the PhD graduate programs of the International Giessen Graduate school for Life Sciences (GGL) and the International Max Planck Research School for Molecular Organ Biology (IMPRS-MOB). We have won a number of external research grants and are involved in several national and international collaborative projects.

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Experimental Neuro-Oncology

This area investigates the mechanisms by which tumor cells adapt to their microenvironment, with a focus on primary tumor growth and metastasis, particularly in the brain and lung. By studying stress responses such as hypoxia and metabolic reprogramming, we aim to understand how these factors drive cancer progression and therapy resistance. Utilizing a range of experimental methods, including in vitro, ex vivo, and in vivo models, we explore the metabolic and epigenetic adaptations of cancer cells, identify therapeutic targets, and work toward translating these findings into strategies with clinical relevance....

Translational Neuromuscular Research

This focus area investigates the underlying mechanisms of neuromuscular disorders, including immune-mediated muscle diseases (myositis), genetic myopathies, and neuropathies in childhood and adulthood as well as rare neuromuscular conditions. By combining advanced diagnostic techniques, such as histological and ultrastructural analyses, with molecular and genetic studies, we aim to uncover key pathways driving age-related disease progression. Research efforts also address metabolic dysfunction, sarcomeric dynamics, autophagy and proteostasis in neuromuscular disorders. This area emphasizes integrating experimental and clinical data to refine diagnostics, identify novel therapeutic targets, and improve patient outcomes, creating a direct pathway from research to clinical application....

3-D Tour of the Experimental Neuro-Oncology lab

Visit the research laboratory on a Virtual Tour created in 2023 by the initiative “Hessen schafft Wissen” Science Spaces 3D series....

Computational Neuropathology

This area integrates bioinformatics, AI, and federated learning approaches to enhance neuropathological research. By combining structured patient data with high-dimensional omics datasets, we aim to uncover patterns that can inform diagnostics and therapeutic strategies. Key efforts include developing methods to obtain and standardize structured patient data, normalizing morphomolecular data across different sites for data sharing and applying AI-driven computational approaches to advance morphomolecular neuropathology. This interdisciplinary approach combines traditional neuropathology with computational sciences to enhance diagnostic accuracy and identify innovative therapeutic targets....