A self-seeding microwell chip is introduced for the isolation and interrogation of single cells. A cell suspension is transferred to a microwell chip containing 6400 microwells, each microwell with a single 5 μm pore in the bottom. The fluid enters the microwell and drags a cell onto the pore. After a cell has landed onto the pore, it will stop the fluid flow through this microwell. The remaining fluid and cells will be diverted to the next available microwell. This results in a fast and efficient distribution of single cells in individual microwells. After identification by fluorescence microscopy, the cells of interest are isolated from the microwell by punching the bottom together with the cell. The overall single cell recovery of seeding followed by isolation of the single cell, is >70% with a specificity of 100% as confirmed by the genetic make-up of the isolated cells.

Here we present the Puncher technology for the isolation of single cells. This technology combines a silicon chip with microwells, fluorescence imaging, and a punching method to isolate and transfer the single cells to standard reaction tubes. The technology is compatible with commercially available downstream workflows and instrumentation. Here we focus on the isolation of CTC but the Puncher technology can be applied to isolate single cells from liquid biopsies and more general from cell suspensions. It is especially suited for cell suspensions that contain: • Cells of interest at a frequency of 1 per 10,000 or less • A low total number of cells ranging from 1 to 100,000, that are present in a volume of 0.01 to 50 mL.The frequency of appearance of CTC in blood is in the order of the 1 per 10 6 leukocytes.To be able to isolate the single CTC with the Puncher technology, enrichment of the CTC by a 3 logs reduction of the leukocytes is required. Here we describe the use of Rosettesep and Parsortix as examples of pre-enrichment methods that are compatible with the Puncher technology and further downstream applications.

Self-seeding microwell chips can sort single cells into 6400 wells based on cell size and their identity verified by immunofluorescence staining. Here, we developed a microfluidic device in which these single cells can be placed, lysed and their DNA amplified for further interrogation. Whole blood spiked with MCF7 tumor cells was passed through the microwell chips after leukocyte depletion and 37% of the MCF7 cells were identified by epithelial cell adhesion molecule (EpCAM) staining in the microwells. Identified single cells were punched into the reaction chamber of the microfluidic device and reagents for cell lysis and DNA amplification introduced sequentially by peristaltic pumping of micro-valves. On-chip lysis and amplification was performed in 8 parallel chambers yielding a 10,000 fold amplification of DNA. Accessibility of the sample through the reaction chamber allowed for easy retrieval and interrogation of target-specific genes to characterize the tumor cells.

After a CellSearch-processed circulating tumor cell (CTC) sample is imaged, a segmentation algorithm selects nucleic acid positive (DAPI+), cytokeratin-phycoerythrin expressing (CK-PE+) events for further review by an operator. Failures in this segmentation can result in missed CTCs. The CellSearch segmentation algorithm was not designed to handle samples with high cell density, such as diagnostic leukapheresis (DLA) samples. Here, we evaluate deep-learning-based segmentation method StarDist as an alternative to the CellSearch segmentation. CellSearch image archives from 533 whole blood samples and 601 DLA samples were segmented using CellSearch and StarDist and inspected visually. In 442 blood samples from cancer patients, StarDist segmented 99.95% of CTC segmented by CellSearch, produced good outlines for 98.3% of these CTC, and segmented 10% more CTC than CellSearch. Visual inspection of the segmentations of DLA images showed that StarDist continues to perform well when the cell density is very high, whereas CellSearch failed and generated extremely large segmentations (up to 52% of the sample surface). Moreover, in a detailed examination of seven DLA samples, StarDist segmented 20% more CTC than CellSearch. Segmentation is a critical first step for CTC enumeration in dense samples and StarDist segmentation convincingly outperformed CellSearch segmentation.

Here the feasibility is demonstrated that by combining Surface Plasmon Resonance Imaging (SPRi) and self-sorting microwell technology product secretion of individual cells can be monitored. Additionally isolation of the selected cells can be performed by punching the cells from the microwells using coordinates of the positions of microwells obtained with SPRi. Cells of interest can be retrieved sterile from the microwell array for further cultivation.

Here, we review the characteristics and synthesis of magnetic nanoparticles (MNPs) and place these in the context of their usage in the immunomagnetic enrichment of Circulating Tumor Cells (CTCs). The importance of the different characteristics is explained, the need for a very specific enrichment is emphasized and different (commercial) magnetic separation techniques are shown. As the specificity of an MNP is in a large part dependent on the antibody coated onto the particle, different strategies in the coupling of specific antibodies as well as an overview of the available antibodies is given.

Due to the low frequency of circulating tumor cells (CTC), the standard CellSearch method of enumeration and isolation using a single tube of blood is insufficient to measure treatment effects consistently, or to steer personalized therapy. Using diagnostic leukapheresis this sample size can be increased; however, this also calls for a suitable new method to process larger sample inputs. In order to achieve this, we have optimized the immunomagnetic enrichment process using a flow-through magnetophoretic system. An overview of the major forces involved in magnetophoretic separation is provided and the model used for optimizing the magnetic configuration in flow through immunomagnetic enrichment is presented. The optimal Halbach array element size was calculated and both optimal and non-optimal arrays were built and tested using anti-EpCAM ferrofluid in combination with cell lines of varying EpCAM antigen expression. Experimentally measured distributions of the magnetic moment of the cell lines used for comparison were combined with predicted recoveries and fit to the experimental data. Resulting predictions agree with measured data within measurement uncertainty. The presented method can be used not only to optimize magnetophoretic separation using a variety of flow configurations but could also be adapted to optimize other (static) magnetic separation techniques.

When evaluating EpCAM-based enrichment technologies for circulating tumour cells (CTCs), the cell lines used should closely resemble real CTCs, meaning the EpCAM expression of CTCs needs to be known, but also the EpCAM expression of cell lines at different institutions and times is important. As the number of CTCs in the blood is low, we enriched CTCs through the depletion of leukocytes from diagnostic leukapheresis products of 13 prostate cancer patients and measured EpCAM expression using quantitative flow cytometry. Antigen expression was compared between multiple institutions by measuring cultures from each institution. Capture efficiency was also measured for one of the used cell lines. Results show CTCs derived from castration-sensitive prostate cancer patients have varying but relatively low EpCAM expression, with median expression per patient ranging from 35 to 89,534 (mean 24,993) molecules per cell. A large variation in the antigen expression of identical cell lines cultured at different institutions was found, resulting in recoveries when using the CellSearch system ranging from 12 up to 83% for the same cell line. We conclude that large differences in capture efficiency can occur while using the same cell line. To closely resemble real CTCs from castration-sensitive prostate cancer patients, a cell line with a relatively low EpCAM expression should be used, and its expression should be monitored frequently.