Tumour-derived extracellular vesicles in blood of metastatic cancer patients associate with overall survival

Background: Circulating tumour cells (CTCs) in blood associate with overall survival (OS) of cancer patients, but they are detected in extremely low numbers. Large tumour-derived extracellular vesicles (tdEVs) in castration-resistant prostate cancer (CRPC) patients are present at around 20 times higher frequencies than CTCs and have equivalent prognostic power. In this study, we explored the presence of tdEVs in other cancers and their association with OS. Methods: The open-source ACCEPT software was used to automatically enumerate tdEVs in digitally stored CellSearch® images obtained from previously reported CTC studies evaluating OS in 190 CRPC, 450 metastatic colorectal cancer (mCRC), 179 metastatic breast cancer (MBC) and 137 non-small cell lung cancer (NSCLC) patients before the initiation of a new treatment. Results: Presence of unfavourable CTCs and tdEVs is predictive of OS, with respective hazard ratios (HRs) of 2.4 and 2.2 in CRPC, 2.7 and 2.2 in MBC, 2.3 and 1.9 in mCRC and 2.0 and 2.4 in NSCLC, respectively. Conclusions: tdEVs have equivalent prognostic value as CTCs in the investigated metastatic cancers. CRPC, mCRC, and MBC (but not NSCLC) patients with favourable CTC counts can be further prognostically stratified using tdEVs. Our data suggest that tdEVs could be used in clinical decision-making.</p

Classification of Cells in CTC-Enriched Samples by Advanced Image Analysis

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

Quantifying HER-2 expression on circulating tumor cells by ACCEPT

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 (R) 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 HER2 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

Single tube liquid biopsy for advanced non-small cell lung cancer

The need for a liquid biopsy in non-small cell lung cancer (NSCLC) patients is rapidly increasing. We studied the relation between overall survival (OS) and the presence of four cancer biomarkers from a single blood draw in advanced NSCLC patients: EpCAM(high) circulating tumor cells (CTC), EpCAM(low) CTC, tumor-derived extracellular vesicles (tdEV) and cell-free circulating tumor DNA (ctDNA). EpCAM(high) CTC were detected with CellSearch, tdEV in the CellSearch images and EpCAM(low) CTC with filtration after CellSearch. ctDNA was isolated from plasma and mutations present in the primary tumor were tracked with deep sequencing methods. In 97 patients, 21% had >= 2 EpCAM(high) CTC, 15% had >= 2 EpCAM(low) CTC, 27% had >= 18 tdEV and 19% had ctDNA with >= 10% mutant allele frequency. Either one of these four biomarkers could be detected in 45% of the patients and all biomarkers were present in 2%. In 11 out of 16 patients (69%) mutations were detected in the ctDNA. Two or more unfavorable biomarkers were associated with poor OS. The presence of EpCAM(high) CTC and elevated levels of tdEV and ctDNA was associated with a poor OS; however, the presence of EpCAM(low) CTC was not. This single tube approach enables simultaneous analysis of multiple biomarkers to explore their potential as a liquid biopsy

Automated Identification of Circulating Tumor Cells by Image Analysis

In the field of Circulating Tumor Cell (CTC) research many new technologies are emerging to isolate CTCs. Some of them provide accompanying automated image analysis tools that present possible CTCs to the user. Others need fully manual image analysis. For all CTC isolation technologies the definition of a CTC based on the immuno-morphologic criteria is either customized to the specific platform or subjective to the user causing high interreader differences – a problem which may condemn many CTC-based clinical studies to failure. Thus, an important issue that the field is confronted with is the lack of a unified and standardized definition to classify a cellular object as a CTC. This problem is addressed within the European FP7 consortium CTCTrap and the Innovative Medicines Initiative (IMI) consortium CANCER-ID by the development of an open-source image analysis toolbox for CTC identification and enumeration. This toolbox is baptized ACCEPT (Automated CTC Classification, Enumeration and Phenotyping) and can process images generated by various CTC isolation technologies. The main software components are the Marker Characterization, the Full Detection and the Automatic Classification. The Marker Characterization tool aims at quantifying the antigens expressed by previously selected CTCs. The Full Detection tool is based on advanced mathematical methods to reliably detect all objects in the images, visualize the objects in scatter plots and enable the user to classify the cell types by the use of gates or selection of specific objects in the scatter plots or on the actual images. The Automatic Classification tool first detects all objects in the images followed by an automated classification approach that – as a result – presents found CTCs to the user. We demonstrate the effectiveness of these tools on two different datasets. The Marker Characterization tool was tested for Her2 expression on archived CTC images isolated and classified by the CellSearch system from patients with metastatic breast cancer. Investigators from three different institutes were asked to score these cells for Her2 positivity first on the images generated by the CellTracks Analyzer and afterwards using ACCEPT. We show that the improved CTC visualization provided in ACCEPT, combined with several measurements which we extract for each cell, can reduce the inter-user variability. The Full Detection and Automatic Classification tools of ACCEPT were tested on archived samples of patients with castration resistant prostate cancer processed with the CellSearch system as well as on microsieves obtained after filtration of the blood discarded by the CellSearch system. Results were compared with manually scored CTCs and showed the improvement of CTC classification by the availability of quantitative image analysis tools

Leukocyte-Derived Extracellular Vesicles in Blood with and without EpCAM Enrichment

Large tumor-derived Extracellular Vesicles (tdEVs) detected in blood of metastatic prostate, breast, colorectal, and non-small cell lung cancer patients after enrichment for Epithelial Cell Adhesion Molecule (EpCAM) expression and labeling with 4′,6-diamidino-2-phenylindole (DAPI), phycoerythrin-conjugated antibodies against Cytokeratins (CK-PE), and allophycocyanin-conjugated antibody against the cluster of differentiation 45 (CD45-APC), are negatively associated with the overall survival of patients. Here, we investigated whether, similarly to tdEVs, leukocyte-derived EVs (ldEVs) could also be detected in EpCAM-enriched blood. Presence of ldEVs and leukocytes in image data sets of EpCAM-enriched samples of 25 healthy individuals and 75 metastatic cancer patients was evaluated using the ACCEPT software. Large ldEVs could indeed be detected, but in contrast to the 20-fold higher frequency of tdEVs as compared to Circulating Tumor Cells (CTCs), ldEVs were present in a 5-fold lower frequency as compared to leukocytes. To evaluate whether these ldEVs pre-exist in the blood or are formed during the CellSearch procedure, the blood of healthy individuals without EpCAM enrichment was labelled with the nuclear dye Hoechst and fluorescently tagged monoclonal antibodies recognizing the leukocyte-specific CD45, platelet-specific CD61, and red blood cell-specific CD235a. Fluorescence microscopy imaging using a similar setup as the CellSearch was performed and demonstrated the presence of a similar population of ldEVs present at a 3-fold lower frequency as compared to leukocytes