Signalling Network Analysis of Blood Mononuclear Cells From Clinical Samples by Bivariate Correlation

Abstract

Signalling networks have been assessed in blood cells by assessing individual phosphoantigens. We considered the possibility that bivariate correlations involving a series of signalling molecules could be used to delineate functional signalling networks in cells from clinical samples. Here, we describe a novel approach to signalling network analysis using enhanced flow cytometry to provide increased resolving power and restricted-dimensional cytometry which simplifies the analysis so that the precision of the analysis is optimised. This approach has been validated in short-term cultures by recapitulating known tenets of two distinct pathways. Additionally, new findings from our unique approach provide both expanded and nuanced views of signalling circuits. Applying our technology platform to blood mononuclear cells from patients with plasma cell disorders, we identified cell-type specific features of signalling pathways by distinct patterns of bivariate correlations. The intermolecular relationships between signalling analytes provide a description of the signalling network in blood cells from clinical samples. Consequently, our approach has the potential to assess how the blood mononuclear cell-type specific signalling network affects pathophysiology and pathogenesis.