Spatial Quantification of Biomarkers within Target tissues with Image analysis platform

Tissue based biomarker investigation is a key step in pre clinical / clinical drug development as it can serve either identification of novel therapeutic target, assessment of a surrogate marker of drug efficacy as well as prediction of a candidate compound benefit. The application of quantitative image analysis has thus become an indispensable tool for in depth tissue biomarker questions in this context. In this perspective, we highlight the use of ImaLink digital pathology analysis platform to unravel cell interplays during complex biological events.


In this Application Note, we have described the analysis workflow that allows the automation of cell segmentation and their classification to resolve the molecular architecture of the tissue. The workflow that reports morphological and multiplexed expression data on a cell by cell basis across the tissue section, first includes the import of the TIFF images into QuPath to detect the cells and retrieve the information including the intensities for a simultaneous analysis of an unlimited number of fluorescent markers in any cellular compartment nucleus, cytoplasm, and/or membrane. With the option to define specific cells phenotypes according to markers positivity the cell targeting module is ideally suited for the characterization of distinct cell populations where multiple markers are required to characterize distinct immune and tumor cell populations within the tissue. Spatial relationship of these population can be further interrogate to understand the mechanism of tissue heterogeneity. Unsupervised machine learning analysis in the cell clustering module allows for the detection of clusters of cells with similar information without providing input parameters a priori. The method allows for the discovery of interesting patterns in data in the context of known biological knowledge.


What role do cellular interactions play in promoting or suppressing disease? How do the same cell types behave differently based on their cellular microenvironments in areas such as oncology, immunology, and neurology? These conceptual phenotypes based on adjacencies between cell types are providing new insights into inflammatory process and tumour progression to reveal
•Novel drug targets
•Novel efficacy biomarkers/predictive biomarkers
•Novel Impact of drug on tissue

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