Deep cell phenotyping and spatial analysis of multiplexed imaging with TRACERx-PHLEX.

Humans Deep Learning Image Processing, Computer-Assisted / methods Animals Software Spatial Analysis Single-Cell Analysis / methods Phenotype Mice Image Cytometry / methods

Journal

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

Informations de publication

Date de publication:
15 Jun 2024
Historique:
received: 11 10 2023
accepted: 16 05 2024
medline: 16 6 2024
pubmed: 16 6 2024
entrez: 15 6 2024
Statut: epublish

Résumé

The growing scale and dimensionality of multiplexed imaging require reproducible and comprehensive yet user-friendly computational pipelines. TRACERx-PHLEX performs deep learning-based cell segmentation (deep-imcyto), automated cell-type annotation (TYPEx) and interpretable spatial analysis (Spatial-PHLEX) as three independent but interoperable modules. PHLEX generates single-cell identities, cell densities within tissue compartments, marker positivity calls and spatial metrics such as cellular barrier scores, along with summary graphs and spatial visualisations. PHLEX was developed using imaging mass cytometry (IMC) in the TRACERx study, validated using published Co-detection by indexing (CODEX), IMC and orthogonal data and benchmarked against state-of-the-art approaches. We evaluated its use on different tissue types, tissue fixation conditions, image sizes and antibody panels. As PHLEX is an automated and containerised Nextflow pipeline, manual assessment, programming skills or pathology expertise are not essential. PHLEX offers an end-to-end solution in a growing field of highly multiplexed data and provides clinically relevant insights.

Identifiants

DOI: 10.1038/s41467-024-48870-5 PMID: 38879602
pubmed: 38879602
doi: 10.1038/s41467-024-48870-5
pii: 10.1038/s41467-024-48870-5
doi:

Types de publication

Journal Article

Langues

eng

Sous-ensembles de citation

IM

Pagination

5135

Subventions

Organisme : Wellcome Trust
ID : CC2041
Pays : United Kingdom
Organisme : Wellcome Trust
ID : CC2041
Pays : United Kingdom
Organisme : Cancer Research UK (CRUK)
ID : C416/A21999
Organisme : Royal Society
ID : RF\ERE\231118
Organisme : Royal Society
ID : RF\ERE\210216
Organisme : EC | Horizon 2020 Framework Programme (EU Framework Programme for Research and Innovation H2020)
ID : 838540
Organisme : EC | Horizon 2020 Framework Programme (EU Framework Programme for Research and Innovation H2020)
ID : 101079113

Informations de copyright

© 2024. The Author(s).

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Auteurs

Alastair Magness (A)

Cancer Evolution and Genome Instability Laboratory, The Francis Crick Institute, London, UK. alastair.magness@crick.ac.uk.

Emma Colliver (E)

Cancer Evolution and Genome Instability Laboratory, The Francis Crick Institute, London, UK.
ORCID: 0000-0002-1497-0740

Katey S S Enfield (KSS)

Cancer Evolution and Genome Instability Laboratory, The Francis Crick Institute, London, UK.
ORCID: 0000-0002-4551-6073

Claudia Lee (C)

Cancer Evolution and Genome Instability Laboratory, The Francis Crick Institute, London, UK.
ORCID: 0000-0003-1715-2265

Masako Shimato (M)

Cancer Evolution and Genome Instability Laboratory, The Francis Crick Institute, London, UK.
ORCID: 0000-0001-9776-0935

Emer Daly (E)

Cancer Evolution and Genome Instability Laboratory, The Francis Crick Institute, London, UK.

David A Moore (DA)

Cancer Evolution and Genome Instability Laboratory, The Francis Crick Institute, London, UK.
Cancer Research UK Lung Cancer Centre of Excellence, University College London Cancer Institute, London, UK.
Department of Cellular Pathology, University College London Hospitals, London, UK.
ORCID: 0000-0002-6296-1312

Monica Sivakumar (M)

Cancer Research UK Lung Cancer Centre of Excellence, University College London Cancer Institute, London, UK.

Karishma Valand (K)

Oncogene Biology Laboratory, The Francis Crick Institute, London, UK.
ORCID: 0000-0002-9158-5782

Dina Levi (D)

Flow Cytometry, The Francis Crick Institute, London, UK.

Crispin T Hiley (CT)

Cancer Evolution and Genome Instability Laboratory, The Francis Crick Institute, London, UK.
Cancer Research UK Lung Cancer Centre of Excellence, University College London Cancer Institute, London, UK.

Philip S Hobson (PS)

Flow Cytometry, The Francis Crick Institute, London, UK.

Febe van Maldegem (F)

Oncogene Biology Laboratory, The Francis Crick Institute, London, UK.
Department of Molecular Cell Biology and Immunology, Amsterdam UMC, Location VUMC, Amsterdam, The Netherlands.
Cancer Center Amsterdam, Cancer Biology and Immunology, Amsterdam, The Netherlands.
Amsterdam Institute for Infection and Immunity, Cancer Immunology, Amsterdam, The Netherlands.
ORCID: 0000-0002-2544-544X

James L Reading (JL)

Cancer Research UK Lung Cancer Centre of Excellence, University College London Cancer Institute, London, UK.
Pre-cancer Immunology Laboratory, University College London Cancer Institute, London, UK.
Immune Regulation and Tumour Immunotherapy Group, Cancer Immunology Unit, Research, Department of Haematology, University College London Cancer Institute, London, UK.
ORCID: 0000-0001-5381-978X

Sergio A Quezada (SA)

Cancer Research UK Lung Cancer Centre of Excellence, University College London Cancer Institute, London, UK.
Immune Regulation and Tumour Immunotherapy Group, Cancer Immunology Unit, Research, Department of Haematology, University College London Cancer Institute, London, UK.
ORCID: 0000-0002-9763-1700

Julian Downward (J)

Oncogene Biology Laboratory, The Francis Crick Institute, London, UK.
ORCID: 0000-0002-2331-4729

Erik Sahai (E)

Tumour Cell Biology Laboratory, The Francis Crick Institute, London, UK.
ORCID: 0000-0002-3932-5086

Charles Swanton (C)

Cancer Evolution and Genome Instability Laboratory, The Francis Crick Institute, London, UK. charles.swanton@crick.ac.uk.
Cancer Research UK Lung Cancer Centre of Excellence, University College London Cancer Institute, London, UK. charles.swanton@crick.ac.uk.
Department of Oncology, University College London Hospitals, London, UK. charles.swanton@crick.ac.uk.
ORCID: 0000-0002-4299-3018

Mihaela Angelova (M)

Cancer Evolution and Genome Instability Laboratory, The Francis Crick Institute, London, UK. mihaela.angelova@crick.ac.uk.
ORCID: 0000-0002-0495-9695

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Classifications MeSH

questionsmedicales.fr › Eucaryotes › Animaux › Chordés › Vertébrés › Mammifères › Eutheria › Primates › Haplorhini › Catarrhini › Hominidae › Humains › Deep cell phenotyping and spatial analysis of...
questionsmedicales.fr › Sciences de l'information › Méthodologies informatiques › Algorithmes › Intelligence artificielle › Réseaux neuronaux (ordinateur) › Apprentissage profond › Deep cell phenotyping and spatial analysis of...
questionsmedicales.fr › Sciences de l'information › Méthodologies informatiques › Traitement d'image par ordinateur › Deep cell phenotyping and spatial analysis of...
questionsmedicales.fr › Eucaryotes › Animaux › Deep cell phenotyping and spatial analysis of...
questionsmedicales.fr › Sciences de l'information › Méthodologies informatiques › Logiciel › Deep cell phenotyping and spatial analysis of...
questionsmedicales.fr › Environnement et santé publique › Santé publique › Méthodes épidémiologiques › Statistiques comme sujet › Analyse spatiale › Deep cell phenotyping and spatial analysis of...
questionsmedicales.fr › Techniques d'investigation › Techniques cytologiques › Analyse sur cellule unique › Deep cell phenotyping and spatial analysis of...
questionsmedicales.fr › Phénomènes génétiques › Phénotype › Deep cell phenotyping and spatial analysis of...
questionsmedicales.fr › Eucaryotes › Animaux › Chordés › Vertébrés › Mammifères › Eutheria › Rodentia › Muridae › Murinae › Souris › Deep cell phenotyping and spatial analysis of...
questionsmedicales.fr › Techniques d'investigation › Techniques cytologiques › Cytophotométrie › Cytométrie en images › Deep cell phenotyping and spatial analysis of...