Digital Pathology Analysis Quantifies Spatial Heterogeneity of CD3, CD4, CD8, CD20, and FoxP3 Immune Markers in...

Area of Science:

• Computational pathology
• Cancer immunology
• Triple-negative breast cancer (TNBC) research

Background:

• The tumor microenvironment (TME) significantly influences triple-negative breast cancer (TNBC) progression.
• Digital pathology offers spatial insights into TME heterogeneity, but quantitative analysis of multiple immune markers is limited.

Purpose of the Study:

• To develop and test a digital pathology computational workflow for characterizing spatial distributions of five immune markers (CD3, CD4, CD8, CD20, FoxP3) in TNBC.
• To investigate intra- and inter-tumoral heterogeneity of these immune markers across different tissue regions.

Main Methods:

• Digital image processing to extract and colocalize immune marker-labeled cells, converting them into point patterns.
• Characterization of invasive front (IF), central tumor (CT), and normal tissue (N) regions.
• Analysis of intra- and inter-tumoral heterogeneity for five immune markers using the developed workflow on whole slide images.

Main Results:

• Both intra- and inter-tumoral heterogeneities were observed for all five immune markers.
• The invasive front (IF) exhibited higher immune cell densities, greater spatial model parameter variations, and more cell clusters/hotspots compared to CT and N.
• These findings suggest a distinct role for the IF in tumor immuno-architecture.

Conclusions:

• The developed computational workflow effectively characterizes immune marker spatial distributions and heterogeneity in TNBC.
• The invasive front plays a unique role in the tumor's immune landscape.
• The workflow is reproducible, scalable, and has potential for biomarker discovery and computational immuno-oncology model validation.