Link to bioRxiv paper:
http://biorxiv.org/cgi/content/short/2023.07.20.548170v1?rss=1
Authors: Masotti, M., Osher, N., Eliason, J., Rao, A., Baladandayuthapani, V.
Abstract:
The tumor microenvironment (TME) is a complex ecosystem containing tumor cells, other surrounding cells, blood vessels, and extracellular matrix. Recent advances in multiplexed imaging technologies allow researchers to map several cellular markers in the TME at the single cell level while preserving their spatial locations. Evidence is mounting that cellular interactions in the TME can promote or inhibit tumor development and contribute to drug resistance. Current statistical approaches to quantify cell-cell interactions do not readily scale to the outputs of new imaging technologies which can distinguish many unique cell phenotypes in one image. We propose a scalable analytical framework and accompanying R package, DIMPLE, to quantify, visualize, and model cell-cell interactions in the TME. In application of DIMPLE to publicly available MI data, we uncover statistically significant associations between image-level measures of cell-cell interactions and patient-level covariates.
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