Deep topographic proteomics of a human brain tumour
Simon Davis,
Connor Scott,
Janina Oetjen,
Philip D. Charles,
Benedikt M. Kessler,
Olaf Ansorge and
Roman Fischer ()
Additional contact information
Simon Davis: University of Oxford
Connor Scott: University of Oxford
Janina Oetjen: Bruker Daltonics GmbH & Co. KG
Philip D. Charles: University of Oxford
Benedikt M. Kessler: University of Oxford
Olaf Ansorge: University of Oxford
Roman Fischer: University of Oxford
Nature Communications, 2023, vol. 14, issue 1, 1-15
Abstract:
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.
Date: 2023
References: View references in EconPapers View complete reference list from CitEc
Citations:
Downloads: (external link)
https://www.nature.com/articles/s41467-023-43520-8 Abstract (text/html)
Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.
Export reference: BibTeX
RIS (EndNote, ProCite, RefMan)
HTML/Text
Persistent link: https://EconPapers.repec.org/RePEc:nat:natcom:v:14:y:2023:i:1:d:10.1038_s41467-023-43520-8
Ordering information: This journal article can be ordered from
https://www.nature.com/ncomms/
DOI: 10.1038/s41467-023-43520-8
Access Statistics for this article
Nature Communications is currently edited by Nathalie Le Bot, Enda Bergin and Fiona Gillespie
More articles in Nature Communications from Nature
Bibliographic data for series maintained by Sonal Shukla () and Springer Nature Abstracting and Indexing ().