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Deep topographic proteomics of a human brain tumour

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 proteom...

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Autores principales: Davis, Simon, Scott, Connor, Oetjen, Janina, Charles, Philip D., Kessler, Benedikt M., Ansorge, Olaf, Fischer, Roman
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Nature Publishing Group UK 2023
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10673928/
https://www.ncbi.nlm.nih.gov/pubmed/38001067
http://dx.doi.org/10.1038/s41467-023-43520-8
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author Davis, Simon
Scott, Connor
Oetjen, Janina
Charles, Philip D.
Kessler, Benedikt M.
Ansorge, Olaf
Fischer, Roman
author_facet Davis, Simon
Scott, Connor
Oetjen, Janina
Charles, Philip D.
Kessler, Benedikt M.
Ansorge, Olaf
Fischer, Roman
author_sort Davis, Simon
collection PubMed
description 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.
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spelling pubmed-106739282023-11-24 Deep topographic proteomics of a human brain tumour Davis, Simon Scott, Connor Oetjen, Janina Charles, Philip D. Kessler, Benedikt M. Ansorge, Olaf Fischer, Roman Nat Commun Article 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. Nature Publishing Group UK 2023-11-24 /pmc/articles/PMC10673928/ /pubmed/38001067 http://dx.doi.org/10.1038/s41467-023-43520-8 Text en © The Author(s) 2023 https://creativecommons.org/licenses/by/4.0/Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/ (https://creativecommons.org/licenses/by/4.0/) .
spellingShingle Article
Davis, Simon
Scott, Connor
Oetjen, Janina
Charles, Philip D.
Kessler, Benedikt M.
Ansorge, Olaf
Fischer, Roman
Deep topographic proteomics of a human brain tumour
title Deep topographic proteomics of a human brain tumour
title_full Deep topographic proteomics of a human brain tumour
title_fullStr Deep topographic proteomics of a human brain tumour
title_full_unstemmed Deep topographic proteomics of a human brain tumour
title_short Deep topographic proteomics of a human brain tumour
title_sort deep topographic proteomics of a human brain tumour
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10673928/
https://www.ncbi.nlm.nih.gov/pubmed/38001067
http://dx.doi.org/10.1038/s41467-023-43520-8
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