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Abstract
Background The ability to probe the tumor microenvironment (TME) at the single cell level is important for understanding of interactions between tumors and immune cells, particularly whether immune cells have infiltrated into tumor nests, and immune checkpoint marker presence. This requires assessing multiple biomarkers simultaneously for cell phenotyping in their spatial context. Here we demonstrate rapid design and optimization of a panel of antibodies for multiplexed immunohistochemical staining of a series of oral cancer tumor samples.
Methods A panel of biomarkers were selected to cover a range of immune cell biomarkers. Immunostaining was performed in a sequential immunofluorescence platform, the Lunaphore COMET (Lunaphore, Lausanne, Switzerland). Simultaneous imaging of serial dilutions of antibodies in the same staining run permitted the fine tuning of the panel to provide appropriate signal coverage more rapidly than with previous multiplex panel methods. Once the images were acquired, tumor nests were manually annotated, followed by application of the deep learning based StarDist segmentation to the tissue. Cellular phenotypes were identified based on marker thresholding, validated by visual inspection.
Results Validation and optimization of thirteen unique immune markers was completed in less than two weeks. The staining and imaging of twenty-five oral cancer tissue samples was completed in five weeks and whole-slide image data was exported for analysis. Tissue and cell segmentation permitted the quantification of biomarkers in a spatially resolved manner. Quantitative analysis revealed the presence of immune cells both surrounding and infiltrating tumor nests within oral cancer tissue sections. Breaking down the immune cell types into subcategories, the phenotypes assessed included tumor cell count (PanCK+), tumor cell proliferation (CK+PCNA+), functional Th (CD3+CD4+FoxP3-PD1-), Treg; immune suppression (CD3+FoxP3+), Activated Tc (CD3+CD8a+Granzyme B+), Memory Th cells (CD3+CD4+CD45RO+), Memory Tc cells (CD3+CD8+CD45RO+). The full table for marker phenotyping is shown in table 1, representative markers in figure 1A/B.
Conclusions Here, we present an end-to-end workflow for the rapid development of multiplexed immunostaining on clinical tissue samples. Sequential immunofluorescence staining permitted us to optimize antibody concentrations rapidly, enabling quick imaging turnaround. Quantitative image analysis was applied to identify discrete cells, define their localization relative to tumor nests, revealing areas of tumor cell proliferation and immune cell exclusion from the tumor center (figure 1A/B). The ability to provide quantitative readouts of spatial interactions allowed for a more refined understanding of tumor-immune cell interactions, permitting a more complete interrogation of the TME in a spatially resolved manner.
Complete marker phenotyping panel
Analysis of tumor nests
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