Abstract PR11: Hyperspectral imaging tools capture the spatial organization of cell subsets within the tumor microenvironment

Immune cells are a major component of the tumor microenvironment (TME). The spatial organization of immune cell subpopulations within the TME is recognized to have biologic significance and clinical relevance. For example, spatial organization of immune cell subsets within the TME is critical for th...

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Veröffentlicht in:Clinical cancer research 2018-09, Vol.24 (17_Supplement), p.PR11-PR11
Hauptverfasser: Enfield, Katey S.S., Martin, Spencer D., Kung, Sonia H.Y., Gallagher, Paul, MacAulay, Calum E., Guillaud, Martial, Lam, Wan L.
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Sprache:eng
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Zusammenfassung:Immune cells are a major component of the tumor microenvironment (TME). The spatial organization of immune cell subpopulations within the TME is recognized to have biologic significance and clinical relevance. For example, spatial organization of immune cell subsets within the TME is critical for the inhibition of cytotoxic T-cell activity through direct interaction of ligand (PD-L1) with receptor (PD-1)). However, precise spatial deconvolution is limited by the lack of imaging algorithms for in situ multiplex single cell analyses as flow cytometry does not preserve data in the spatial dimension. To this end, we have developed a hyperspectral imaging platform designed for analyzing multichannel immunohistochemical-stained tissue sections for generating cell density data and reconstructing spatial architecture for tumor biology as well as clinical association studies. Whole-tissue sections from 20 lung adenocarcinomas with at least 5 years’ follow-up were stained for CD3 (pan-T cell), CD8 (cytotoxic T cell), and CD79a (B cell and plasma cell) and counterstained with hematoxylin. Multispectral images were acquired for five fields of view and analyzed to quantify cell types. Regions of Interest (ROIs) were then identified and analyzed in order to quantify cell-cell spatial relationships. Nonrandom patterns of immune cell distributions were identified using the Monte Carlo resampling method (500 iterations). Cell counts, densities, spatial relationships, and significant immune cell distributions were associated with clinical features (Kruskal-Wallis p
ISSN:1078-0432
1557-3265
DOI:10.1158/1557-3265.AACRIASLC18-PR11