Immune Cell and Cell Cluster Phenotyping, Quantitation, and Visualization Using In Silico Multiplexed Images and...

Area of Science:

• Immunology
• Biotechnology
• Computational Pathology

Background:

• In situ immune cell phenotyping is crucial for understanding tissue microenvironments.
• Conventional microscopy is limited to imaging only four biomarkers simultaneously.
• Advanced methods are needed to analyze multiple immune cell markers.

Purpose of the Study:

• To describe and demonstrate a workflow for phenotyping, quantifying, and visualizing more than four biomarkers in silico.
• To overcome the limitations of conventional microscopy for multiplexed biomarker analysis.
• To enable detailed characterization of immune cell phenotypes and spatial relationships.

Main Methods:

• Utilized multiplexed fluorescence histology with sequential dye inactivation on formalin-fixed paraffin-embedded tissue sections.
• Employed the TissueFAXS quantitative imaging system with a conventional microscopy setup.
• Developed in silico phenotype profiles by combining biomarker data and used algorithms for image alignment, cell isolation, and biomarker identification.

Main Results:

• Successfully phenotyped, quantitated, and visualized greater than four biomarkers in silico.
• Generated flow cytometry-like histograms and dot scatterplots for quantitative analysis.
• Provided visual verification of cell isolation and identification, highlighting cell and cluster characteristics.

Conclusions:

• The described workflow enables comprehensive in situ immune cell phenotyping beyond the limits of conventional imaging.
• This approach facilitates detailed analysis of immune cell populations and their spatial context within tissues.
• The method offers visual validation, enhancing the reliability of complex immune cell profiling.