Protein Counting in Single Cancer Cells

The cell is the basic unit of biology and protein expression drives cellular function. Tracking protein expression in single cells enables the study of cellular pathways and behavior but requires methodologies sensitive enough to detect low numbers of protein molecules with a wide dynamic range to distinguish unique cells and quantify population distributions. This study presents an ultrasensitive and automated approach for quantifying phenotypic responses with single cell resolution using single molecule array (SiMoA) technology. We demonstrate how prostate specific antigen (PSA) expression varies over several orders of magnitude between single prostate cancer cells and how PSA expression shifts with genetic drift. Single cell SiMoA introduces a straightforward process that is capable of detecting both high and low protein expression levels. This technique could be useful for understanding fundamental biology and may eventually enable both earlier disease detection and targeted therapy.