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Deep topographic proteomics of a human brain tumour

Abstract:
The spatial organisation of cellular protein expression profiles within tissue determines cellular function and is key to understanding disease pathology. To define molecular phenotypes in the spatial context of tissue, there is a need for unbiased, quantitative technology capable of mapping proteomes within tissue structures. Here, we present a workflow for spatially-resolved, quantitative proteomics of tissue that generates maps of protein abundance across tissue slices derived from a human atypical teratoid-rhabdoid tumour at three spatial resolutions, the highest being 40 µm, to reveal distinct abundance patterns of thousands of proteins. We employ spatially-aware algorithms that do not require prior knowledge of the fine tissue structure to detect proteins and pathways with spatial abundance patterns and correlate proteins in the context of tissue heterogeneity and cellular features such as extracellular matrix or proximity to blood vessels. We identify PYGL, ASPH and CD45 as spatial markers for tumour boundary and reveal immune response-driven, spatially-organised protein networks of the extracellular tumour matrix. Overall, we demonstrate spatially-aware deep proteo-phenotyping of tissue heterogeneity, to re-define understanding tissue biology and pathology at the molecular level.
Publication status:
Published
Peer review status:
Peer reviewed

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Publisher copy:
10.1038/s41467-023-43520-8

Authors


More by this author
Institution:
University of Oxford
Division:
MSD
Department:
NDM
Sub department:
Target Discovery Institute
Role:
Author
More by this author
Institution:
University of Oxford
Division:
MSD
Department:
Clinical Neurosciences
Role:
Author
More by this author
Institution:
University of Oxford
Division:
MSD
Department:
NDM
Sub department:
Target Discovery Institute
Research group:
Big Data Institute
Role:
Author
More by this author
Institution:
University of Oxford
Division:
MSD
Department:
NDM
Sub department:
Target Discovery Institute
Role:
Author
ORCID:
0000-0002-8160-2446


Publisher:
Springer Nature
Journal:
Nature Communications More from this journal
Volume:
14
Issue:
1
Article number:
7710
Publication date:
2023-11-24
Acceptance date:
2023-11-13
DOI:
EISSN:
2041-1723


Language:
English
Keywords:
Pubs id:
1572930
Local pid:
pubs:1572930
Deposit date:
2023-11-28

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