Deep Phenotypic Characterisation of CTCs by Combination of Microfluidic Isolation (IsoFlux) and Imaging Flow Cytometry (ImageStream).

The isolation of circulating tumour cells (CTCs) in colorectal cancer (CRC) mostly relies on the expression of epithelial markers such as EpCAM, and phenotypic characterisation is usually performed under fluorescence microscopy with only one or two additional markers. This limits the ability to detect different CTC subpopulations based on multiple markers. The aim of this work was to develop a novel protocol combining two platforms (IsoFlux and ImageStream) to improve CTC evaluation. Cancer cell lines and peripheral blood from healthy donors were used to evaluate the efficiency of each platform independently and in combination. Peripheral blood was extracted from 16 early CRC patients (before loco-regional surgery) to demonstrate the suitability of the protocol for CTC assessment. Additionally, peripheral blood was extracted from nine patients one month after surgery to validate the utility of our protocol for identifying CTC subpopulation changes over time. Results: Our protocol had a mean recovery efficiency of 69.5% and a limit of detection of at least four cells per millilitre. We developed an analysis method to reduce noise from magnetic beads used for CTC isolation. CTCs were isolated from CRC patients with a median of 37 CTCs (IQ 13.0-85.5) at baseline. CTCs from CRC patients were significantly ( < 0.0001) larger than cytokeratin (CK)-negative cells, and patients were stratified into two groups based on BRAF and PD-L1 expression on CK-positive cells. The changes observed over time included not only the number of CTCs but also their distribution into four different subpopulations defined according to BRAF and PD-L1 positivity. We developed a novel protocol for semi-automatic CTC isolation and phenotypic characterisation by combining two platforms. Assessment of CTCs from early CRC patients using our protocol allowed the identification of two clusters of patients with changing phenotypes over time.