Abstract:

Formalin-fixed and paraffin-embedded (FFPE) tissues represent an invaluable resource for studying molecular mechanisms underlying diseases. The long archival times of FFPE tissue and the fact that proteins are largely stable therein make them ideal analytes for mass spectrometry driven discovery proteomics. Classical approaches have provided “averaged” descriptions of the disease related proteome and fail to characterize the critical disease promoting cell populations within the complex tissue environment. To address this, we have recently co-developed Deep Visual Proteomics (DVP) for image-guided tissue proteomics. DVP leverages high resolution microscopy and machine learning based image analysis to identify phenotypically distinct cell populations. Cells for proteomic profiling, discovered by supervised or unsupervised machine learning, are isolated in situ by automated laser microdissection and analyzed by ultra-sensitive mass spectrometry. In my presentation, I will provide an overview of our spatial tissue proteomics pipeline, discuss our DVP workflow, as well as future applications of tissue proteomics down to a few or even single cells.

Bio:

Fabian Coscia is a Principal investigator in Spatial Proteomics at Max Delbrück Center for Molecular Medicine, Berlin, Germany since June 2021. Fabian Obtained his PhD in Prof. Matthias Mann lab at Max Plank Institute of Biochemistry, Munich, Germany (2012-2016) and subsequently continued his Postdoctoral studies in Mann lab as a Marie Skłodowska-Curie Postdoctoral Fellow (2019). Fabian played an instrumental role in developing cutting edge mass spectrometry-based proteomic techniques on FFPE tissue specimens as well as development of Deep Visual Proteomics for image-guided tissue proteomics. He recently secured 1.5€ million ERC starting grant in developing high-resolution spatial proteomics.

Selected Publications:

Deep Visual Proteomics defines single-cell identity and heterogeneity. Andreas Mund # 1, Fabian Coscia #, András Kriston , Réka Hollandi , Ferenc Kovács , Andreas-David Brunner, Ede Migh , Lisa Schweizer , Alberto Santos, Michael Bzorek , Soraya Naimy , Lise Mette Rahbek-Gjerdrum , Beatrice Dyring-Andersen, Jutta Bulkescher, Claudia Lukas, Mark Adam Eckert, Ernst Lengyel, Christian Gnann, Emma Lundberg., Peter Horvath and Matthias Mann. Nature Biotechnology. 2022. PMID: 35590073

A streamlined mass spectrometry-based proteomics workflow for large-scale FFPE tissue analysis. F. Coscia. S. Doll., J.M., Bech., L Schweizer., A. Mund., E. Lengyel., J. Lindebjerg., G.I. Madsen., J.M. Moreira. and M. Mann. The Journal of Pathology. 2020. PMID: 32154592

Multi-level Proteomics Identifies CT45 as a Chemosensitivity Mediator and Immunotherapy Target in Ovarian Cancer. F. Coscia., E. Lengyel., J. Duraiswamy., B. Ashcroft., M. Bassani-Sternberg., M. Wierer., A. Johnson., K. Wroblewski., A. Montag., S.D. Yamada., B. López-Méndez., J. Nilsson., A. Mund., M. Mann and M. Curtis. Cell. 2018. PMID: 30241606