High-content phenotyping with Imaging Mass Cytometry

TissueGnostics contextual image analysis software, StrataQuest, is able to process high-content images (multiple channels/markers) of virtual tissue sections acquired via Imaging Mass Cytometry (IMC). This innovative technology enables the staining and imaging of high numbers of biomarkers within one slide using a mass-tagging technique for distinguishing signals reflecting subtle differences in mass. The following example was performed as a comprehensive analysis of 30 markers within one tissue section. The image below shows several representative markers in pseudocolors: DNA (nuclei), CD4 (helper T cells), CD31 (marker for vascular differentiation), CD14 (monocytes and macrophages), Ki67 (proliferation marker), Tryptase (mast cells), CD8 (cytotoxic T cells), CD45 (lymphocyte common antigen) and aSMA (myofibroblasts).

The goal was to detect nuclei, identify and quantify marker-positive cells and perform distance assessment of marker-positive nuclei to the blood vessels.

Images: Dr. Akhila Balachander, Spatial ImmunoPhenomics Platform, Singapore Immunology Network, courtesy, SIGNAL grant.

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Step 1: the nuclei are automatically detected based on DNA channel, as it is represented in the right image where the nuclei are outlined in turquoise.

 

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Step 2: Identification of marker-positive cells (in this example, Ki67, shown in orange) are detected. To gain quantitative numbers, scattergrams are used with cut-offs separating Ki67-positive (1.36%) from Ki67-negative cells.

 

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The same workflow can be applied to any marker of interest: for example, CD31.

 

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Scattergrams can be generated for any marker, offering a wide panel of data to choose from. The panel below represents scattergrams for 16 different markers at once, where individual marker mean intensity is plotted against corresponding nuclei size. This way, StrataQuest offers the researcher a good overview of the whole data set with adjustable parameters.

 

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Step 3: The distance between marker-positive nuclei and the blood vessels is calculated and defined by ranges (0-20µm, 20-40µm etc). These ranges can be modified easily if needed. First, a proximity map is established based on the distance range from the nearest blood vessel, where the ranges are represented heap map-like: the blue color marks the vessels, the further from the vessels, the warmer the color is. Then the distance map and nuclei detection are combined, and now it is possible to define marker-positive cells within a particular range: white arrows indicate some Ki67+ cells in 0-20µm range from the nearest vessel, and red arrow indicates some Ki67+ cells in 20-40µm range.

 

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Empowered by the StrataQuest streamlined workflow, Imaging Mass Cytometry combined with distance evaluation can be a useful tool for solving a variety of biological questions. If you would like to know more about how TissueGnostics solutions can help your research, please reach out to a member of the TissueGnostics team.

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