The ‘immune contexture’ of tumors is defined as the type, functional orientation, density and location of immune cells within distinct tumor regions. Differentially staining specific cell types allows the quantification of the distance between individual cells and their nearest neighbour within tumor tissue. This approach can help confirm the mechanism of action of therapies that are designed to enhance or reduce the interaction between specific cell types within tumor tissue.
Left: Original Image. Right: Classifier Overlay
Once we receive your slides or images for evaluation, we develop a customised algorithm to address the specific question of interest. For example, the question may be to evaluate the therapeutic effect on the spatial relationship (distance) between 2 specific immune cell types involved in the mechanism of action of the therapy. IHC stained immune cell populations are initially detected within the tumor microenvironment. Secondly, a criteria is set within a customised algorithm for the two different cell populations to identify each cell’s nearest neighbour. Example analysis and data is shown in the images to the right. We analyse each section in a consistent, detailed way to generate data which is fully representative of the staining and cellular distribution present in your tissue samples.
Left: Classifier Overlay. Right: Proximity analysis. In the spatial plot above, the number of CD8 positive cells within or greater than 30 microns of a pan cytokeratin (PCK) positive cell (blue) are labelled pink and purple, respectively.
Area of specific tissue regions of interest (ROI) including Tumor, Stroma & Necrotic content across whole section.
Number of cells within a certain distance to another cell type (for example number of FoxP3 cells within 30µm of a CD8 cell).
Average nearest neighbour distance between two cell populations across a whole tissue section or within a specific ROI.
Immune Cell Spatial Analysis Data
Receive highly detailed data quantifying immune / inflammatory cell population spatial distribution and spatial interactions within the tumor microenvironment.
Our automated batch analysis service objectively analyses each section using the same algorithm to reduce variability and improve data quality and interpretation.