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


Journal

Nature communications
ISSN: 2041-1723
Titre abrégé: Nat Commun
Pays: England
ID NLM: 101528555

Informations de publication

Date de publication:
18 07 2023
Historique:
received: 26 10 2022
accepted: 27 06 2023
medline: 21 7 2023
pubmed: 19 7 2023
entrez: 18 7 2023
Statut: epublish

Résumé

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.

Identifiants

pubmed: 37463882
doi: 10.1038/s41467-023-39765-y
pii: 10.1038/s41467-023-39765-y
pmc: PMC10354027
doi:

Substances chimiques

Proteome 0

Types de publication

Journal Article Research Support, Non-U.S. Gov't

Langues

eng

Sous-ensembles de citation

IM

Pagination

4308

Informations de copyright

© 2023. The Author(s).

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Auteurs

María Bueno Álvez (MB)

Science for Life Laboratory, Department of Protein Science, KTH Royal Institute of Technology, Stockholm, Sweden.

Fredrik Edfors (F)

Science for Life Laboratory, Department of Protein Science, KTH Royal Institute of Technology, Stockholm, Sweden.

Kalle von Feilitzen (K)

Science for Life Laboratory, Department of Protein Science, KTH Royal Institute of Technology, Stockholm, Sweden.

Martin Zwahlen (M)

Science for Life Laboratory, Department of Protein Science, KTH Royal Institute of Technology, Stockholm, Sweden.

Adil Mardinoglu (A)

Science for Life Laboratory, Department of Protein Science, KTH Royal Institute of Technology, Stockholm, Sweden.
Centre for Host-Microbiome Interactions, Faculty of Dentistry, Oral & Craniofacial Sciences, King's College London, London, SE1 9RT, UK.

Per-Henrik Edqvist (PH)

Department of Immunology, Genetics and Pathology, Uppsala University, Uppsala, Sweden.

Tobias Sjöblom (T)

Department of Immunology, Genetics and Pathology, Uppsala University, Uppsala, Sweden.

Emma Lundin (E)

Department of Immunology, Genetics and Pathology, Uppsala University, Uppsala, Sweden.

Natallia Rameika (N)

Department of Immunology, Genetics and Pathology, Uppsala University, Uppsala, Sweden.

Gunilla Enblad (G)

Department of Immunology, Genetics and Pathology, Uppsala University, Uppsala, Sweden.

Henrik Lindman (H)

Department of Immunology, Genetics and Pathology, Uppsala University, Uppsala, Sweden.

Martin Höglund (M)

Department of Medical Sciences, Uppsala University, Uppsala, Sweden.

Göran Hesselager (G)

Department of Medical Sciences, Uppsala University, Uppsala, Sweden.

Karin Stålberg (K)

Department of Women's and Children's Health, Uppsala University, Uppsala, Sweden.

Malin Enblad (M)

Department of Surgical Sciences, Uppsala University, Uppsala, Sweden.

Oscar E Simonson (OE)

Department of Surgical Sciences, Uppsala University, Uppsala, Sweden.

Michael Häggman (M)

Department of Surgical Sciences, Uppsala University, Uppsala, Sweden.

Tomas Axelsson (T)

Department of Medical Sciences, Uppsala University, Uppsala, Sweden.

Mikael Åberg (M)

Department of Medical Sciences, Clinical Chemistry and SciLifeLab Affinity Proteomics, Uppsala University, Uppsala, Sweden.

Jessica Nordlund (J)

Department of Medical Sciences, Uppsala University, Uppsala, Sweden.

Wen Zhong (W)

Science for Life Laboratory, Department of Biomedical and Clinical Sciences (BKV), Linköping University, Linköping, Sweden.

Max Karlsson (M)

Science for Life Laboratory, Department of Protein Science, KTH Royal Institute of Technology, Stockholm, Sweden.

Ulf Gyllensten (U)

Department of Immunology, Genetics and Pathology, Uppsala University, Uppsala, Sweden.

Fredrik Ponten (F)

Department of Immunology, Genetics and Pathology, Uppsala University, Uppsala, Sweden.

Linn Fagerberg (L)

Science for Life Laboratory, Department of Protein Science, KTH Royal Institute of Technology, Stockholm, Sweden.

Mathias Uhlén (M)

Science for Life Laboratory, Department of Protein Science, KTH Royal Institute of Technology, Stockholm, Sweden. mathias.uhlen@scilifelab.se.
Department of Neuroscience, Karolinska Institutet, Stockholm, Sweden. mathias.uhlen@scilifelab.se.

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Classifications MeSH