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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.

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.

The clinical utility of circulating tumor cells (CTCs) is hampered by the low number of cells detected. Diagnostic leukapheresis (DLA) offers a solution but, due to the observed non‐specific binding and clumping, processing of DLA samples using the CellSearch system only allows for the processing of aliquots consisting of ~ 2% of the total DLA sample per test. Here, we introduce a flow enrichment target capture Halbach‐array (FETCH)‐based separation method in combination with a DNase preprocessing step to capture CTCs from larger fractions of DLA products without clumping. To evaluate the FETCH method, we processed peripheral blood samples from 19 metastatic castration‐naïve prostate cancer (mCNPC) patients with CellSearch, and processed 2% aliquots of leukapheresis samples from the same patients with CellSearch as well as FETCH with or without DNase preprocessing. Using 2% aliquots from six patients, the use of FETCH with fewer immunomagnetic epithelial cellular adhesion molecule (EpCAM) conjugated ferrofluids was tested, whereas 20% aliquots from four patients were used to evaluate the processing of 10‐fold larger DLA samples using FETCH. Results show that the cell clumping normally seen after immunomagnetic enrichment of DLA material was greatly reduced with the use of DNase pretreatment, while the number of CTCs detected was not affected. The number of CTCs detected in 2% aliquots of DLA using FETCH was unchanged compared to CellSearch and did not decrease when using down to 10% of the volume of immunomagnetic anti‐EpCAM ferrofluids normally used in a CellSearch test, whereas the number of co‐enriched white blood cells reduced a median 3.2‐fold. Processing of a 20% aliquot of DLA with FETCH resulted in a 14‐fold increase in CTCs compared to the processing of 2% aliquots of DLA using CellSearch and a total 42‐fold median increase in CTCs compared to peripheral‐blood CellSearch. The number of circulating tumor cells obtained from prostate cancer patients was increased approximately 5‐fold compared to regular CellSearch when processing 2 mL diagnostic leukapheresis material aliquots and increased by 44‐fold when processing 20 mL DLA aliquots using the flow enrichment target capture Halbach‐array. Clumping of cells during the procedure could be prevented by pre‐incubation with DNase.

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.

The clinical implementation of circulating tumor cells (CTCs) as a predictive tool for therapy efficacy in the growing field of precision oncology likely requires advanced CTC phenotyping. While their predictive value for disease progression and therapy response has extensively been shown, the low number of CTCs that are obtained from whole blood tubes limits their clinical application. The magnetic enrichment of CTCs using the FDA-cleared CellSearch system is limited by the expression of the epithelial cell adhesion molecule (EpCAM) on CTC, and an increase in CTC yield may be obtained through enhanced capture of low EpCAM expressing cells. In this study, we compared the Flow Enabled Target Capture Halbach (FETCH) magnetic enrichment technology with the FDA-cleared CellSearch system for CTC capture using paired blood samples from 34 patients with non-small-cell lung, breast, and prostate cancer. Results show a statistically significant median 1.5-fold increase in CTCs captured with the FETCH system compared with CellSearch, accompanied by a median twofold reduction in non-specifically captured leukocytes. This increase in CTC capture can aid the comprehensive analysis of CTCs in a larger number of patients, further supporting clinical implementation of CTC-based diagnostics.

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.

Circulating tumor cells (CTCs) are important biomarkers for cancer diagnosis and treatment monitoring. However, their scarcity limits their utility as current enrichment techniques are hampered by low volume throughput and/or the inability to capture CTCs with low target antigen densities. Our group previously reported a device capable of processing samples in a flow manner using an optimized Halbach array to enhance the capture of low EpCAM-expressing cells (Flow-through Immunomagnetic CTC Enrichment system). In this study, we tested the capture efficiency of eight commercially available streptavidin magnetic beads using this device to identify the most suitable bead. Results indicate that using this system, the best-performing magnetic beads are in the ~ 100 to ~ 150 nm size range. Considering the combination of binding efficiency and final sample purity, we found that among the beads tested in combination with biotinylated anti-EpCAM, MojoSort Streptavidin Nanobeads performed the best, with high capture efficiencies for both the high EpCAM expressing LNCaP and low EpCAM expressing PC3-9 cell lines. For CTC enrichment from the blood of cancer patients, reducing the number of WBCs co-enriched with these beads will be essential, especially when processing large-volume samples acquired, for instance, through diagnostic leukapheresis to overcome the limitations caused by the scarcity of CTCs.

Circulating tumor cells (CTCs) are important biomarkers for cancer diagnosis and treatment monitoring. However, their scarcity limits their utility as current enrichment techniques are hampered by low volume throughput and/or the inability to capture CTCs with low target antigen densities. Our group previously reported a device capable of processing samples in a flow manner using an optimized Halbach array to enhance the capture of low EpCAM-expressing cells (Flow-through Immunomagnetic CTC Enrichment system). In this study, we tested the capture efficiency of eight commercially available streptavidin magnetic beads using this device to identify the most suitable bead. Results indicate that using this system, the best-performing magnetic beads are in the ~ 100 to ~ 150 nm size range. Considering the combination of binding efficiency and final sample purity, we found that among the beads tested in combination with biotinylated anti-EpCAM, MojoSort Streptavidin Nanobeads performed the best, with high capture efficiencies for both the high EpCAM expressing LNCaP and low EpCAM expressing PC3–9 cell lines. For CTC enrichment from the blood of cancer patients, reducing the number of WBCs co-enriched with these beads will be essential, especially when processing large-volume samples acquired, for instance, through diagnostic leukapheresis to overcome the limitations caused by the scarcity of CTCs.

Circulating tumor cells (CTCs) are detected in approximately 30% of metastatic non-small-cell lung cancer (NSCLC) cases using the CellSearch system, which relies on EpCAM immunomagnetic enrichment and Cytokeratin detection. This study evaluated the effectiveness of immunomagnetic enrichment targeting oncofetal chondroitin sulfate (ofCS) using recombinant VAR2CSA proteins (rVAR2) to improve the recovery of different NSCLC cell lines spiked into lysed blood samples. Four NSCLC cell lines—NCI-H1563, A549, NCI-H1792, and NCI-H661—were used to assess capture efficiency. The results demonstrated that the combined use of anti-EpCAM antibody and rVAR2 significantly enhanced the capture efficiency to an average of 88.2% compared with 40.6% when using only anti-EpCAM and 56.6% when using only rVAR2. These findings suggest that a dual-marker approach using anti-EpCAM and rVAR2 can provide a more robust and sensitive method for CTC enrichment in NSCLC, potentially leading to better diagnostic and prognostic outcomes.

As surface melt is increasing on the Greenland Ice Sheet (GrIS), quantifying the retention capacity of the firn layer is critical to linking meltwater production to meltwater runoff. Firn-densification models have so far relied on empirical approaches to account for the percolation–refreezing process, and more physically based representations of liquid water flow might bring improvements to model performance. Here we implement three types of water percolation schemes into the Community Firn Model: the bucket approach, the Richards equation in a single domain and the Richards equation in a dual domain, which accounts for partitioning between matrix and fast preferential flow. We investigate their impact on firn densification at four locations on the GrIS and compare model results with observations. We find that for all of the flow schemes, significant discrepancies remain with respect to observed firn density, particularly the density variability in depth, and that inter-model differences are large (porosity of the upper 15 m firn varies by up to 47 %). The simple bucket scheme is as efficient in replicating observed density profiles as the single-domain Richards equation, and the most physically detailed dual-domain scheme does not necessarily reach best agreement with observed data. However, we find that the implementation of preferential flow simulates ice-layer formation more reliably and allows for deeper percolation. We also find that the firn model is more sensitive to the choice of densification scheme than to the choice of water percolation scheme. The disagreements with observations and the spread in model results demonstrate that progress towards an accurate description of water flow in firn is necessary. The numerous uncertainties about firn structure (e.g. grain size and shape, presence of ice layers) and about its hydraulic properties, as well as the one-dimensionality of firn models, render the implementation of physically based percolation schemes difficult. Additionally, the performance of firn models is still affected by the various effects affecting the densification process such as microstructural effects, wet snow metamorphism and temperature sensitivity when meltwater is present.