Investigation of the heterogeneity of cancer cells using single cell calcium profiling.

Abstract

Calcium (Ca2+) is an essential second messenger that controls numerous cellular functions. Characteristics of intracellular Ca2+ oscillations define Ca2+ signatures representatives of the phenotype of a cell. Oncogenic functions such as migration, proliferation or resistance to chemotherapy have been associated with aberrant Ca2+ fluxes. However, the identification of Ca2+ signatures representatives of the oncogenic properties of cancer cells remains to be addressed. To characterize oncogenic Ca2+ signatures, we proposed an unbiased scalable method that combines single cell calcium imaging with unsupervised and supervised machine learning tools. Here, we applied this method to investigate the heterogeneity of Ca 2+ signatures in 16 cancer cell lines and the remodeling of oncogenic Ca2+ signatures induced by acquired docetaxel resistance and in the course of the interaction of cancer cells with fibroblasts. Finally, our method demonstrates the potential of Ca2+ profiling for discriminating cancer cells and predict their phenotypic characteristics at single cell level, and provides a framework for researchers to investigate the remodeling of the Ca2+ signature during cancer development.