Breast cancer is the second most common cancer type worldwide and breast cancer metastasis accounts for the majority of breast cancer-related deaths. Tumour cells produce increased levels of sialic acid (SA) that terminates the monosaccharide on glycan chains of the glycosylated proteins. SA can contribute to cellular recognition, cancer invasiveness and increase the metastatic potential of cancer cells. SA-templated molecularly imprinted polymers (MIPs) have been proposed as promising reporters for specific targeting of cancer cells when deployed in nanoparticle format. The sialic acid-molecularly imprinted polymers (SA-MIPs), which use SA for the generation of binding sites through which the nanoparticles can target and stain breast cancer cells, opens new strategies for efficient diagnostic tools. This study aims at monitoring the effects of SA-MIPs on morphology and motility of the epithelial type MCF-7 and the highly metastatic MDAMB231 breast cancer cell lines, using digital holographic cytometry (DHC). DHC is a label-free technique that is used in cell morphology studies of e.g., cell volume, area and thickness as well as in motility studies. Here, we show that MCF-7 cells move slower than MDAMB231 cells. We also show that SA-MIPs have an effect on cell morphology, motility and viability of both cell lines. In conclusion, by using DH microscopy, we could detect SA-MIPs impact on different breast cancer cells regarding morphology and motility.

Breast cancer is the second most common cancer worldwide. Metastasis is the main reason for death in breast cancer, and today, there is a lack of methods to detect and isolate circulating tumor cells (CTCs), mainly due to their heterogeneity and rarity. There are some systems that are designed to detect rare epithelial cancer cells in whole blood based on the most common marker used today, the epithelial cell adhesion molecule (EpCAM). It has been shown that aggressive breast cancer metastases are of non-epithelial origin and are therefore not always detected using EpCAM as a marker. In the present study, we used an in vitro-based circulating tumor cell model comprising a collection of six breast cancer cell lines and white blood cell lines. We used digital holographic cytometry (DHC) to characterize and distinguish between the different cell types by area, volume and thickness. Here, we present significant differences in cell size-related parameters observed when comparing white blood cells and breast cancer cells by using DHC. In conclusion, DHC can be a powerful diagnostic tool for the characterization of CTCs in the blood.

Cells in complex organisms can transition between epithelial and mesenchymal phenotypes during both normal and malignant physiological events. These two phenotypes are not binary, but rather describe a spectrum of cell states along an axis. Mammalian cells can undergo dynamic and heterogenous bidirectional interconversions along the epithelial–mesenchymal phenotypic (EMP) spectrum, and such transitions are marked by morphological change. Here, we exploit digital holographic cytometry (DHC) to develop a tractable method for monitoring the degree, kinetics, and heterogeneity of epithelial and mesenchymal phenotypes in adherent mammalian cell populations. First, we demonstrate that the epithelial and mesenchymal states of the same cell line present distinct DHC-derived morphological features. Second, we identify quantitative changes in these features that occur hours after induction of the epithelial to mesenchymal transition (EMT). We apply this approach to achieve label-free tracking of the degree and the rate of EMP transitions. We conclude that DHC is an efficient method to investigate morphological changes during transitions between epithelial and mesenchymal states.

A cell line derived from a tumor is a heterogeneous mixture of phenotypically different cells. Such cancer cell lines are used extensively in the search for new anticancer drugs and for investigating their mechanisms of action. Most studies today are population-based, implying that small subpopulations of cells, reacting differently to the potential drug go undetected. This is a problem specifically related to the most aggressive single cancer cells in a tumor as they appear to be insensitive to the drugs used today. These cells are not detected in population-based studies when developing new anticancer drugs. Thus, to get a deeper understanding of how all individual cancer cells react to chemotherapeutic drugs, longitudinal tracking of individual cells is needed. Here we have used digital holography for long time imaging and longitudinal tracking of individual JIMT-1 breast cancer cells. To gain further knowledge about the tracked cells, we combined digital holography with fluorescence microscopy. We grouped the JIMT-1 cells into different subpopulations based on expression of CD24 and E-cadherin and analyzed cell proliferation and cell migration for 72 h. We investigated how the cancer stem cell (CSC) targeting drug salinomycin affected the different subpopulations. By uniquely combining digital holography with fluorescence microscopy we show that salinomycin specifically targeted the CD24⁻ subpopulation, i.e., the CSCs, by inhibiting cell proliferation, which was evident already after 24 h of drug treatment. We further found that after salinomycin treatment, the surviving cells were more epithelial-like due to the selection of the CD24⁺ cells.