Dr. Vidhya Madapusi Ravi

CV

Dr. Vidhya M. Ravi obtained her Ph.D. in Biophysics and Biochemistry from University Autonoma of Barcelona, Spain in 2016, where her thesis research was funded by European Union (FI-DGR AGAUR). Her long-term passion in the field of Neuroscience motivated her to University of Freiburg to conduct her postdoctoral research. She joined the lab of Prof. Dr. Ulrich G. Hofmann, where she established a 3D culturing method for the long-term preservation of adult human cortical brain tissue, considered to be a real challenge. She then moved to the Department of Neurosurgery, mentored by Prof. Dr. Jürgen Beck and Prof. Oliver Schnell, where she established a novel (3D human brain tumor) model to determine the distinct role of specific cell types in brain and their role in tumor progression. She further went on to define the mechanism of immune deactivation in GBM. Her latest work involves deep profiling of human GBM using spatially resolved RNA sequencing, proteomics and metabolomics. Dr. Ravi also has received several awards in her career including National scholarship in India, like DBT and ICMR junior research fellowship. Dr. Ravi’s long-term goals involve the generation of models of human disease as a platform to minimize the usage of animals in neuroscience research.

Publikationen (Auswahl)

• Heiland D.H*, Ravi V.M. *, et al. “Tumor Associated Astrocytes aid the evolution of immunosuppressive environment in Glioblastoma”. https://www.nature.com/articles/s41467-019-10493-6   (2019)
• Ravi. V.M *, Joseph K * et al., “Human Organotypic Brain Slice Culture: A novel framework for environmental research in NeuroOncology” https://www.life-science-alliance.org/content/2/4/e201900305 (2019)
• Ravi. V.M, Neidert.N. et al.,” Lineage and Spatial Mapping of Glioblastoma associated Immunity” (under revision in Nature Communication) https://www.biorxiv.org/content/10.1101/2020.06.01.121467v1  (2020)

•  Ravi. V.M, Will P et al., Spatiotemporal heterogeneity of glioblastoma is dictated by microenvironmental interference. https://www.biorxiv.org/content/biorxiv/early/2021/02/17/2021.02.16.431475.full.pdf (Under review in Cell) (2021)

• M.Schneider, L.Vollmer, A-L.Pothoff, V.M.Ravi et al., Meclofenamate causes loss of cellular tethering and     decoupling of functional networks in glioblastoma https://academic.oup.com/neuro-oncology/advance-article-abstract/doi/10.1093/neuonc/noab092/6231712?redirectedFrom=fulltext (2021)

FRIAS Projekt

AutograFt  Immune CompeteNt HumAn GLioblastoma ModEl  (FINALE)

Glioblastoma (GBM) is the most aggressive form of brain tumor with a median patient survival time of less than 14 months. The tumor microenvironent (TME) within GBM is a key regulator of tumor proliferation and drug-resistance and thus has entered the spotlight as a potential therapeutic target. Progress towards the development of treatments targeting the TME is currently limited due to a lack of reliable preclinical model that can accurately recreate the distinct features of the human brain. To this end, I recently established a human cortical tissue based GBM model which is identical to the human brain with respect to composition and function. My long term goal is to understand the molecular details of GBM’s distinctive physiology, and to apply this knowledge in the development of novel therapeutic strategies. The central hypothesis based on previously published data is that there exists unwanted immune responses and interactions within the TME in the existing patient-mismatched model, with respect to tumor growth and interactions. Hence, the objective of the proposed project “FINALE” is to establish personalized GBM models which can address this paucity in a comprehensive and physiologically relevant fashion. We will pursue this project using an innovative combination of tissue engineering and transcriptomic characterization using state of the art techniques, as we have demonstrated previously. This work would be a stepping stone towards engineering human brain models that can precisely dissect mechanisms of GBM progression, accelerate clinical testing and, most importantly, provide a platform for personalized medicine.