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Enumeration and characterization of circulating tumor cells (CTC) hold the promise of a real time liquid biopsy. They are however present in a large background of hematopoietic cells making their isolation technically challenging. In 2004, the CellSearch system was introduced as the first and only FDA cleared method designed for the enumeration of circulating tumor cells in 7.5 mL of blood. Presence of CTC detected by CellSearch is associated with poor prognosis in metastatic carcinomas. CTC remaining in patients after the first cycles of therapy indicates a futile therapy. Here we review challenges faced during the development of the CellSearch system and the difficulties in assigning objects as CTC. The large heterogeneity of CTC and the different approaches introduced in recent years to isolate, enumerate and characterize CTC results in a large variation of the number of CTC reported urging the need for uniform definitions and at least a clear definition of what the criteria are for assigning an object as a CTC. •CTC enumeration and characterization hold the promise of a real time liquid biopsy.•Challenges for detection of rare tumor cells in blood are reviewed.•Frequent oversight is to accurately detect “rare cells” among all other events.•A uniform definition for assigning an object as a CTC is urgently needed.

EpCAM expressing circulating tumor cells, detected by CellSearch, are predictive of short survival in several cancers and may serve as a liquid biopsy to guide therapy. Here we investigate the presence of EpCAM + CTC detected by CellSearch and EpCAM – CTC discarded by CellSearch, after EpCAM based enrichment. EpCAM – CTC were identified by filtration and fluorescent labelling. This approach was validated using different cell lines spiked into blood and evaluated on blood samples of 27 metastatic lung cancer patients. The majority of spiked EpCAM + cells could be detected with CellSearch, whereas most spiked cells with EpCAM low or EpCAM – expression were detected using filtration. Five or more CTC were detected in 15% of the patient samples, this increased to 41% when adding the CTC detected in the discarded blood. The number of patients with CTC and the number of CTC detected were doubled by the presence of EpCAM – CTC. In this pilot study, the presence of EpCAM + CTC was associated with poor outcome, whereas the EpCAM – CTC were not. This observation will need to be confirmed in larger studies and molecular characterization needs to be conducted to elucidate differences between EpCAM – and EpCAM + CTC.

In the CellSearch® system, blood is immunomagnetically enriched for epithelial cell adhesion molecule (EpCAM) expression and cells are stained with the nucleic acid dye 4′6-diamidino-2-phenylindole (DAPI), Cytokeratin-PE (CK), and CD45-APC. Only DAPI+/CK+ objects are presented to the operator to identify circulating tumor cells (CTC) and the identity of all other cells and potential undetected CTC remains unrevealed. Here, we used the open source imaging program Automatic CTC Classification, Enumeration and PhenoTyping (ACCEPT) to analyze all DAPI+ nuclei in EpCAM-enriched blood samples obtained from 192 metastatic non-small cell lung cancer (NSCLC) patients and 162 controls. Significantly larger numbers of nuclei were detected in 300 patient samples with an average and standard deviation of 73,570 ± 74,948, as compared to 359 control samples with an average and standard deviation of 4191 ± 4463 (p < 0.001). In patients, only 18% ± 21% and in controls 23% ± 15% of the nuclei were identified as leukocytes or CTC. Adding CD16-PerCP for granulocyte staining, the use of an LED as the light source for CD45-APC excitation and plasma membrane staining obtained with wheat germ agglutinin significantly improved the classification of EpCAM-enriched cells, resulting in the identification of 94% ± 5% of the cells. However, especially in patients, the origin of the unidentified cells remains unknown. Further studies are needed to determine if undetected EpCAM+/DAPI+/CK-/CD45- CTC is present among these cells.

A variety of filters assays have been described to enrich circulating tumor cells (CTC) based on differences in physical characteristics of blood cells and CTC. In this study we evaluate different filter types to derive the properties of the ideal filter for CTC enrichment. Between 0.1 and 10 mL of whole blood spiked with cells from tumor cell lines were passed through silicon nitride microsieves, polymer track-etched filters and metal TEM grids with various pore sizes. The recovery and size of 9 different culture cell lines was determined and compared to the size of EpCAM+CK+CD45-DNA+ CTC from patients with metastatic breast, colorectal and prostate cancer. The 8 µm track-etched filter and the 5 µm microsieve had the best performance on MDA-231, PC3-9 and SKBR-3 cells, enriching >80% of cells from whole blood. TEM grids had poor recovery of ∼25%. Median diameter of cell lines ranged from 10.9-19.0 µm, compared to 13.1, 10.7, and 11.0 µm for breast, prostate and colorectal CTC, respectively. The 11.4 µm COLO-320 cell line had the lowest recovery of 17%. The ideal filter for CTC enrichment is constructed of a stiff, flat material, is inert to blood cells, has at least 100,000 regularly spaced 5 µm pores for 1 ml of blood with a ≤10% porosity. While cell size is an important factor in determining recovery, other factors must be involved as well. To evaluate a filtration procedure, cell lines with a median size of 11-13 µm should be used to challenge the system.

The GILUPI CellCollector (CC) is a novel in vivo circulating tumor cell (CTC) detection device reported to overcome the limitations of small blood sample volumes. The aim of this prospective, blinded study was to evaluate the clinical application of the CC and to compare its performance to the CellSearch (CS) system in M0 and M1 colorectal cancer (CRC) patients. A total of 80 patients (31 M0, 49 M1) with CRC were enrolled. CTCs were simultaneously measured in the peripheral blood using CS and the CC, and the results of both assays were correlated to clinicopathological variables and overall survival. The total number of detected CTCs and CTC‐positive patients did not significantly differ between both assays. In the M0 patients, the CC detected CTCs more frequently than CS. There was no significant difference in total CTC numbers detected with the CC between M0 and M1 patients. In addition, no significant correlation with clinicopathological parameters or overall survival was observed with CC CTCs. In contrast, detection of CTCs with CS was significantly correlated with Union for International Cancer Control stage and reduced overall survival. There was no correlation between CTCs detected by the CC and the CS system. Using in silico analysis, we estimate that CC screens a volume of 0.33–18 mL during in vivo application, in contrast to much higher volumes reported elsewhere. In conclusion, while being safe and easy to use, the CC did not outperform CS in terms of CTC yield or sensitivity. While CTC detection in M0 CRC patients was significantly increased with the CC, the clinical relevance of these CTCs appears inferior to the cells identified by the CS system. The GILUPI CellCollector (CC) is a novel in vivo circulating tumor cell detection device reported to overcome the limitations of small blood sample volumes. In our prospective, blinded study, we simultaneously compared its clinical application and prognostic performance with the CellSearch system in colorectal cancer patients. Using in silico analysis, we estimate the blood volume screened by the CC.

The limited sensitivity of circulating tumor cell (CTC) detection in pancreatic adenocarcinoma (PDAC) stems from their extremely low concentration in the whole circulating blood, necessitating enhanced detection methodologies. This study sought to amplify assay-sensitivity by employing diagnostic leukapheresis (DLA) to screen large blood volumes. Sixty patients were subjected to DLA, with a median processed blood volume of ~ 2.8 L and approximately 5% of the resulting DLA-product analyzed using CellSearch (CS). Notably, DLA significantly increased CS-CTC detection to 44% in M0-patients and 74% in M1-patients, yielding a 60-fold increase in CS-CTC enumeration. DLA also provided sufficient CS-CTCs for genomic profiling, thereby delivering additional genomic information compared to tissue biopsy samples. DLA CS-CTCs exhibited a pronounced negative prognostic impact on overall survival (OS), evidenced by a reduction in OS from 28.6 to 8.5 months (univariate: p = 0.002; multivariable: p = 0.043). Additionally, a marked enhancement in sensitivity was achieved (by around 3-4-times) compared to peripheral blood (PB) samples, with positive predictive values for OS being preserved at around 90%. Prognostic relevance of CS-CTCs in PDAC was further validated in PB-samples from 228 PDAC patients, consolidating the established association between CTC-presence and reduced OS (8.5 vs. 19.0 months, p < 0.001). In conclusion, DLA-derived CS-CTCs may serve as a viable tool for identifying high-risk PDAC-patients and aiding the optimization of multimodal treatment strategies. Moreover, DLA enables comprehensive diagnostic profiling by providing ample CTC material, reinforcing its utility as a reliable liquid-biopsy approach. This high-volume liquid-biopsy strategy presents a potential pathway for enhancing clinical management in this malignancy.

Circulating tumour cells (CTCs) found in the blood of cancer patients are a promising biomarker in precision medicine. However, their use is currently hindered by their low frequency, tedious manual scoring and extensive cell heterogeneities. Those challenges limit the effectiveness of classical machine-learning methods for automated CTC analysis. Here, we combine autoencoding convolutional neural networks with advanced visualization techniques. This provides a very informative view on the data that opens the way for new biomedical research questions. We unravel hidden information in the raw image data of fluorescent images of blood samples enriched for CTCs. Our network classifies fluorescent images of single cells in five different classes with an accuracy, sensitivity and specificity of over 96%, and the obtained CTC counts predict the overall survival of cancer patients as well as state-of-the-art manual counts. Moreover, our network excelled in identifying different important subclasses of objects. Deep learning was faster and superior to classical image analysis approaches and enabled the identification of new biological phenomena. Counting different types of circulating tumour cells can give valuable information on the severity of the disease and on whether treatments are effective for a specific patient. In this work, the authors show that their method based on autoencoders can identify and count cells more accurately and faster than human experts.

Circulating tumor cells (CTCs) isolated from blood can be probed for the expression of treatment targets. Immunofluorescence is often used for both the enumeration of CTC and the determination of protein expression levels related to treatment targets. Accurate and reproducible assessment of such treatment target expression levels is essential for their use in the clinic. To enable this, an open source image analysis program named ACCEPT was developed in the EU-FP7 CTCTrap and CANCER-ID programs. Here its application is shown on a retrospective cohort of 132 metastatic breast cancer patients from which blood samples were processed by CellSearch® and stained for HER-2 expression as additional marker. Images were digitally stored and reviewers identified a total of 4084 CTCs. CTC's HER-2 expression was determined in the thumbnail images by ACCEPT. 150 of these images were selected and sent to six independent investigators to score the HER-2 expression with and without ACCEPT. Concordance rate of the operators' scoring results for HER-2 on CTCs was 30% and could be increased using the ACCEPT tool to 51%. Automated assessment of HER-2 expression by ACCEPT on 4084 CTCs of 132 patients showed 8 (6.1%) patients with all CTCs expressing HER-2, 14 (10.6%) patients with no CTC expressing HER-2 and 110 (83.3%) patients with CTCs showing a varying HER-2 expression level. In total 1576 CTCs were determined HER-2 positive. We conclude that the use of image analysis enables a more reproducible quantification of treatment targets on CTCs and leads the way to fully automated and reproducible approaches.

Filtration can achieve circulating tumor cell (CTC) enrichment from blood. Key parameters such as flow-rate, applied pressure, and fixation, vary largely between assays and their influence is not well understood. Here, we used a filtration system, to monitor these parameters and determine their relationships. Whole blood, or its components, with and without spiked tumor cells were filtered through track-etched filters. We characterize cells passing through filter pores by their apparent viscosity; the viscosity of a fluid that would pass with the same flow. We measured a ratio of 5·10(4)∶10(2)∶1 for the apparent viscosities of 15 µm diameter MDA-231 cells, 10 µm white cells and 90 fl red cells passing through a 5 µm pore. Fixation increases the pressure needed to pass cells through 8 µm pores 25-fold and halves the recovery of spiked tumor cells. Filtration should be performed on unfixed samples at a pressure of ∼10 mbar for a 1 cm(2) track-etched filter with 5 µm pores. At this pressure MDA-231 cells move through the filter in 1 hour. If fixation is needed for sample preservation, a gentle fixative should be selected. The difference in apparent viscosity between CTC and blood cells is key in optimizing recovery of CTC.

Here, we tested two magnetic-bead based systems for the enrichment and detection of rare tumor cells in concentrated blood products. For that, the defined numbers of cells from three pancreatic cancer cell lines were spiked in 108 peripheral blood mononuclear cells (PBMNCs) concentrated in 1 mL, mimicking diagnostic leukapheresis (DLA) samples, and samples were processed for circulating tumor cells (CTC) enrichment with the IsoFlux or the KingFisher systems, using different types of magnetic beads from the respective technology providers. Beads were conjugated with different anti-EpCAM and MUC-1 antibodies. Recovered cells were enumerated and documented by fluorescent microscopy. For the IsoFlux system, best performance was obtained with IsoFlux CTC enrichment kit, but these beads compromised the subsequent immunofluorescence staining. For the KingFisher system, best recoveries were obtained using Dynabeads Biotin Binder beads. These beads also allowed one to capture CTCs with different antibodies and the subsequent immunofluorescence staining. KingFisher instrument allowed a single and streamlined protocol for the enrichment and staining of CTCs that further prevented cell loss at the enrichment/staining interface. Both IsoFlux and KingFisher systems allowed the enrichment of cell line cells from the mimicked-DLA samples. However, in this particular experimental setting, the recovery rates obtained with the KingFisher system were globally higher, the system was more cost-effective, and it allowed higher throughput.