Digital Pathology Analysis Quantifies Spatial Heterogeneity of CD3, CD4, CD8, CD20, and FoxP3 Immune Markers in Triple-Negative Breast Cancer

Frontiers in Physiology
Haoyang MiAleksander S Popel

Abstract

Overwhelming evidence has shown the significant role of the tumor microenvironment (TME) in governing the triple-negative breast cancer (TNBC) progression. Digital pathology can provide key information about the spatial heterogeneity within the TME using image analysis and spatial statistics. These analyses have been applied to CD8+ T cells, but quantitative analyses of other important markers and their correlations are limited. In this study, a digital pathology computational workflow is formulated for characterizing the spatial distributions of five immune markers (CD3, CD4, CD8, CD20, and FoxP3) and then the functionality is tested on whole slide images from patients with TNBC. The workflow is initiated by digital image processing to extract and colocalize immune marker-labeled cells and then convert this information to point patterns. Afterward invasive front (IF), central tumor (CT), and normal tissue (N) are characterized. For each region, we examine the intra-tumoral heterogeneity. The workflow is then repeated for all specimens to capture inter-tumoral heterogeneity. In this study, both intra- and inter-tumoral heterogeneities are observed for all five markers across all specimens. Among all regions, IF tends to have hi...Continue Reading

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Software Mentioned

R package ‘ concavemann
R package “ spatstat
R package ‘ rgeos
R package ‘ SDraw ’
Icy
R package concaveman
R package ‘ spatstat ’
Matlab Registration Estimator
R
Ord

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