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Next generation pan-cancer blood proteome profiling using proximity extension assay

A comprehensive characterization of blood proteome profiles in cancer patients can contribute to a better understanding of the disease etiology, resulting in earlier diagnosis, risk stratification and better monitoring of the different cancer subtypes. Here, we describe the use of next generation pr...

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Autores principales: Álvez, María Bueno, Edfors, Fredrik, von Feilitzen, Kalle, Zwahlen, Martin, Mardinoglu, Adil, Edqvist, Per-Henrik, Sjöblom, Tobias, Lundin, Emma, Rameika, Natallia, Enblad, Gunilla, Lindman, Henrik, Höglund, Martin, Hesselager, Göran, Stålberg, Karin, Enblad, Malin, Simonson, Oscar E., Häggman, Michael, Axelsson, Tomas, Åberg, Mikael, Nordlund, Jessica, Zhong, Wen, Karlsson, Max, Gyllensten, Ulf, Ponten, Fredrik, Fagerberg, Linn, Uhlén, Mathias
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Nature Publishing Group UK 2023
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10354027/
https://www.ncbi.nlm.nih.gov/pubmed/37463882
http://dx.doi.org/10.1038/s41467-023-39765-y
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author Álvez, María Bueno
Edfors, Fredrik
von Feilitzen, Kalle
Zwahlen, Martin
Mardinoglu, Adil
Edqvist, Per-Henrik
Sjöblom, Tobias
Lundin, Emma
Rameika, Natallia
Enblad, Gunilla
Lindman, Henrik
Höglund, Martin
Hesselager, Göran
Stålberg, Karin
Enblad, Malin
Simonson, Oscar E.
Häggman, Michael
Axelsson, Tomas
Åberg, Mikael
Nordlund, Jessica
Zhong, Wen
Karlsson, Max
Gyllensten, Ulf
Ponten, Fredrik
Fagerberg, Linn
Uhlén, Mathias
author_facet Álvez, María Bueno
Edfors, Fredrik
von Feilitzen, Kalle
Zwahlen, Martin
Mardinoglu, Adil
Edqvist, Per-Henrik
Sjöblom, Tobias
Lundin, Emma
Rameika, Natallia
Enblad, Gunilla
Lindman, Henrik
Höglund, Martin
Hesselager, Göran
Stålberg, Karin
Enblad, Malin
Simonson, Oscar E.
Häggman, Michael
Axelsson, Tomas
Åberg, Mikael
Nordlund, Jessica
Zhong, Wen
Karlsson, Max
Gyllensten, Ulf
Ponten, Fredrik
Fagerberg, Linn
Uhlén, Mathias
author_sort Álvez, María Bueno
collection PubMed
description A comprehensive characterization of blood proteome profiles in cancer patients can contribute to a better understanding of the disease etiology, resulting in earlier diagnosis, risk stratification and better monitoring of the different cancer subtypes. Here, we describe the use of next generation protein profiling to explore the proteome signature in blood across patients representing many of the major cancer types. Plasma profiles of 1463 proteins from more than 1400 cancer patients are measured in minute amounts of blood collected at the time of diagnosis and before treatment. An open access Disease Blood Atlas resource allows the exploration of the individual protein profiles in blood collected from the individual cancer patients. We also present studies in which classification models based on machine learning have been used for the identification of a set of proteins associated with each of the analyzed cancers. The implication for cancer precision medicine of next generation plasma profiling is discussed.
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spelling pubmed-103540272023-07-20 Next generation pan-cancer blood proteome profiling using proximity extension assay Álvez, María Bueno Edfors, Fredrik von Feilitzen, Kalle Zwahlen, Martin Mardinoglu, Adil Edqvist, Per-Henrik Sjöblom, Tobias Lundin, Emma Rameika, Natallia Enblad, Gunilla Lindman, Henrik Höglund, Martin Hesselager, Göran Stålberg, Karin Enblad, Malin Simonson, Oscar E. Häggman, Michael Axelsson, Tomas Åberg, Mikael Nordlund, Jessica Zhong, Wen Karlsson, Max Gyllensten, Ulf Ponten, Fredrik Fagerberg, Linn Uhlén, Mathias Nat Commun Article A comprehensive characterization of blood proteome profiles in cancer patients can contribute to a better understanding of the disease etiology, resulting in earlier diagnosis, risk stratification and better monitoring of the different cancer subtypes. Here, we describe the use of next generation protein profiling to explore the proteome signature in blood across patients representing many of the major cancer types. Plasma profiles of 1463 proteins from more than 1400 cancer patients are measured in minute amounts of blood collected at the time of diagnosis and before treatment. An open access Disease Blood Atlas resource allows the exploration of the individual protein profiles in blood collected from the individual cancer patients. We also present studies in which classification models based on machine learning have been used for the identification of a set of proteins associated with each of the analyzed cancers. The implication for cancer precision medicine of next generation plasma profiling is discussed. Nature Publishing Group UK 2023-07-18 /pmc/articles/PMC10354027/ /pubmed/37463882 http://dx.doi.org/10.1038/s41467-023-39765-y 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
Álvez, María Bueno
Edfors, Fredrik
von Feilitzen, Kalle
Zwahlen, Martin
Mardinoglu, Adil
Edqvist, Per-Henrik
Sjöblom, Tobias
Lundin, Emma
Rameika, Natallia
Enblad, Gunilla
Lindman, Henrik
Höglund, Martin
Hesselager, Göran
Stålberg, Karin
Enblad, Malin
Simonson, Oscar E.
Häggman, Michael
Axelsson, Tomas
Åberg, Mikael
Nordlund, Jessica
Zhong, Wen
Karlsson, Max
Gyllensten, Ulf
Ponten, Fredrik
Fagerberg, Linn
Uhlén, Mathias
Next generation pan-cancer blood proteome profiling using proximity extension assay
title Next generation pan-cancer blood proteome profiling using proximity extension assay
title_full Next generation pan-cancer blood proteome profiling using proximity extension assay
title_fullStr Next generation pan-cancer blood proteome profiling using proximity extension assay
title_full_unstemmed Next generation pan-cancer blood proteome profiling using proximity extension assay
title_short Next generation pan-cancer blood proteome profiling using proximity extension assay
title_sort next generation pan-cancer blood proteome profiling using proximity extension assay
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10354027/
https://www.ncbi.nlm.nih.gov/pubmed/37463882
http://dx.doi.org/10.1038/s41467-023-39765-y
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