Accounting for intensity variation in image analysis of large-scale multiplexed clinical trial datasets.
digital pathology
fluorescence microscopy
image analysis
Journal
The journal of pathology. Clinical research
ISSN: 2056-4538
Titre abrégé: J Pathol Clin Res
Pays: England
ID NLM: 101658534
Informations de publication
Date de publication:
Nov 2023
Nov 2023
Historique:
revised:
14
08
2023
received:
30
05
2023
accepted:
20
08
2023
medline:
10
2
2024
pubmed:
12
9
2023
entrez:
12
9
2023
Statut:
ppublish
Résumé
Multiplex immunofluorescence (mIF) imaging can provide comprehensive quantitative and spatial information for multiple immune markers for tumour immunoprofiling. However, application at scale to clinical trial samples sourced from multiple institutions is challenging due to pre-analytical heterogeneity. This study reports an analytical approach to the largest multi-parameter immunoprofiling study of clinical trial samples to date. We analysed 12,592 tissue microarray (TMA) spots from 3,545 colorectal cancers sourced from more than 240 institutions in two clinical trials (QUASAR 2 and SCOT) stained for CD4, CD8, CD20, CD68, FoxP3, pan-cytokeratin, and DAPI by mIF. TMA slides were multi-spectrally imaged and analysed by cell-based and pixel-based marker analysis. We developed an adaptive thresholding method to account for inter- and intra-slide intensity variation in TMA analysis. Applying this method effectively ameliorated inter- and intra-slide intensity variation improving the image analysis results compared with methods using a single global threshold. Correlation of CD8 data derived by our mIF analysis approach with single-plex chromogenic immunohistochemistry CD8 data derived from subsequent sections indicates the validity of our method (Spearman's rank correlation coefficients ρ between 0.63 and 0.66, p ≪ 0.01) as compared with the current gold standard analysis approach. Evaluation of correlation between cell-based and pixel-based analysis results confirms equivalency (ρ > 0.8, p ≪ 0.01, except for CD20 in the epithelial region) of both analytical approaches. These data suggest that our adaptive thresholding approach can enable analysis of mIF-stained clinical trial TMA datasets by digital pathology at scale for precision immunoprofiling.
Identifiants
pubmed: 37697694
doi: 10.1002/cjp2.342
pmc: PMC10556275
doi:
Substances chimiques
Biomarkers, Tumor
0
Types de publication
Journal Article
Langues
eng
Sous-ensembles de citation
IM
Pagination
449-463Subventions
Organisme : Medical Research Council
ID : G0601705
Pays : United Kingdom
Organisme : Cancer Research UK
ID : C6716/A13941
Pays : United Kingdom
Organisme : Cancer Research UK
ID : C26642/A27963
Pays : United Kingdom
Organisme : Cancer Research UK
ID : C6716/A9894
Pays : United Kingdom
Organisme : Cancer Research UK
ID : 27963
Pays : United Kingdom
Organisme : Wellcome Trust
Pays : United Kingdom
Organisme : Cancer Research UK
ID : A25142
Pays : United Kingdom
Informations de copyright
© 2023 The Authors. The Journal of Pathology: Clinical Research published by The Pathological Society of Great Britain and Ireland and John Wiley & Sons Ltd.
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