Single cell phenotyping using molecular or protein multiplexing techniques is gaining momentum, especially in the characterization of cancer and the tumor microenvironment. It has proven to be particularly useful in studying the extent of heterogeneity in cancer, and in the profiling of the immune environment to assess whether certain cell subsets could be predictive of treatment response. Using a sequential protein marker labelling system called Multiplex Immunofluorescence (MxIF, GE Research), we have developed quantitative image analysis and computational tools for phenotyping individual immune and cancer cells for various cancer types. The expressions of T cell markers CD3, CD8, macrophage markers CD68, immune checkpoint proteins PD-1 and PD-L1, together with proliferative marker (Ki67) and cancer-specific marker PCK (pan-Cytokeratin) were studied on single 4um sections of formalin-fixed, paraffinembedded (FFPE) ovarian cancer tissue sections. We explored the composition of immune phenotype using t-SNE and quantified cell densities and marker co-expression patterns using binary cell counting. In addition to phenotyping immune cell types, their spatial localizations were analyzed. Neighborhood analysis was conducted using co-occurrence matrices to determine the number of times that a particular cell type is proximal to one another. Cell-to-cell spatial relationship was assessed by quantifying the Euclidean distances between individual cell types. These tools are being applied to specimens from an immunotherapy clinical trial to evaluate the dynamic changes in immune phenotype during the course of immune blockade therapy.
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