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Deep topographic proteomics of a human brain tumour

View ORCID ProfileSimon Davis, Connor Scott, Janina Oetjen, View ORCID ProfilePhilip D Charles, View ORCID ProfileBenedikt M Kessler, Olaf Ansorge, View ORCID ProfileRoman Fischer
doi: https://doi.org/10.1101/2022.03.21.485119
Simon Davis
1Target Discovery Institute, Centre for Medicines Discovery, Nuffield Department of Medicine, University of Oxford, Roosevelt Drive, Oxford, OX3 7FZ, UK
2Chinese Academy for Medical Sciences Oxford Institute, Nuffield Department of Medicine, University of Oxford, Roosevelt Drive, Oxford, OX3 7FZ, UK
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Connor Scott
3Academic Unit of Neuropathology, Nuffield Department of Clinical Neurosciences, University of Oxford, John Radcliffe Hospital, Oxford, OX3 9DU, UK
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Janina Oetjen
4Bruker Daltonics GmbH & Co. KG, Fahrenheitstraße 4, 28359 Bremen, Germany
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Philip D Charles
1Target Discovery Institute, Centre for Medicines Discovery, Nuffield Department of Medicine, University of Oxford, Roosevelt Drive, Oxford, OX3 7FZ, UK
5Big Data Institute, Nuffield Department of Medicine, University of Oxford, Roosevelt Drive, Oxford, OX3 7FZ, UK
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Benedikt M Kessler
1Target Discovery Institute, Centre for Medicines Discovery, Nuffield Department of Medicine, University of Oxford, Roosevelt Drive, Oxford, OX3 7FZ, UK
2Chinese Academy for Medical Sciences Oxford Institute, Nuffield Department of Medicine, University of Oxford, Roosevelt Drive, Oxford, OX3 7FZ, UK
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Olaf Ansorge
3Academic Unit of Neuropathology, Nuffield Department of Clinical Neurosciences, University of Oxford, John Radcliffe Hospital, Oxford, OX3 9DU, UK
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Roman Fischer
1Target Discovery Institute, Centre for Medicines Discovery, Nuffield Department of Medicine, University of Oxford, Roosevelt Drive, Oxford, OX3 7FZ, UK
2Chinese Academy for Medical Sciences Oxford Institute, Nuffield Department of Medicine, University of Oxford, Roosevelt Drive, Oxford, OX3 7FZ, UK
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  • For correspondence: roman.fischer@ndm.ox.ac.uk
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Abstract

Cellular protein expression profiles within tissues are key to understanding disease pathology, and their spatial organisation determines cellular function. To precisely define molecular phenotypes in the spatial context of tissue, there is a need for unbiased, quantitative technology capable of mapping the expression of many hundreds to thousands of proteins within tissue structures. Here, we present a workflow for spatially resolved, quantitative proteomics of tissue that generates maps of protein expression across a tissue slice derived from a human atypical teratoid-rhabdoid tumour (AT/RT). We employ spatially-aware statistical methods that do not require prior knowledge of tissue structure to highlight proteins and pathways with varying spatial abundance patterns. We identify novel aspects of AT/RT biology that map onto the brain-tumour interface. Overall, this work informs on methods for spatially resolved deep proteo-phenotyping of tissue heterogeneity. Advanced spatially resolved tissue proteomics will push the boundaries of understanding tissue biology and pathology at the molecular level.

Competing Interest Statement

J.O is an employee of Bruker Daltonics GmbH & Co. KG. All other authors have no competing interests.

Copyright 
The copyright holder for this preprint is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made available under a CC-BY-NC 4.0 International license.
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Posted March 21, 2022.
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Deep topographic proteomics of a human brain tumour
Simon Davis, Connor Scott, Janina Oetjen, Philip D Charles, Benedikt M Kessler, Olaf Ansorge, Roman Fischer
bioRxiv 2022.03.21.485119; doi: https://doi.org/10.1101/2022.03.21.485119
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Deep topographic proteomics of a human brain tumour
Simon Davis, Connor Scott, Janina Oetjen, Philip D Charles, Benedikt M Kessler, Olaf Ansorge, Roman Fischer
bioRxiv 2022.03.21.485119; doi: https://doi.org/10.1101/2022.03.21.485119

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