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

Improving the CellSearch® system

Introduction: The CellSearch® CTC test enumerates tumor cells present in 7.5 ml blood of cancer patients. improvements, extensions and different utilities of the cellsearch system are discussed in this paper. Areas covered: This paper describes work performed with the CellSearch system, which go beyond the normal scope of the test. All results from searches with the search term ‘CellSearch’ from Web of Science and PubMed were categorized and discussed. Expert commentary: The CellSearch Circulating Tumor Cell test captures and identifies tumor cells in blood that are associated with poor clinical outcome. How to best use CTC in clinical practice is being explored in many clinical trials. The ability to extract information from the CTC to guide therapy will expand the potential clinical utility of CTC

HER2 expression on tumor-derived extracellular vesicles and circulating tumor cells in metastatic breast cancer

International audienceBACKGROUND: Tumor-derived extracellular vesicles (tdEVs) and circulating tumor cells (CTCs) in the blood of metastatic cancer patients associate with poor outcomes. In this study, we explored the human epidermal growth factor receptor 2 (HER2) expression on CTCs and tdEVs of metastatic breast cancer patients. METHODS: Blood samples from 98 patients (CLCC-IC-2006-04 study) were originally processed with the CellSearch® system using the CTC kit and anti-HER2 as an additional marker in the staining cocktail. CTCs and tdEVs were automatically enumerated from the generated CellSearch images using the open-source ACCEPT software. RESULTS: CTCs and tdEVs were subdivided based on their cytokeratin (CK) and HER2 phenotype into CK+HER2-, CK-HER2+, and CK+HER2+. The inclusion of anti-HER2 increased the percentage of informative samples with ≥ 1 detectable CTC from 89 to 95%. CK- CTCs and tdEVs correlated equally well with the clinical outcome as CK+ CTCs and tdEVs. Inter- and intra-patient heterogeneity was found for the CTC/tdEV phenotypes, and the presence of 2 or 3 classes of CTCs/tdEVs was associated with worse prognosis compared to a uniform CTC/tdEV phenotype present (1 class). The use of ≥ 7% HER2+CK+ tdEVs can predict HER2 expression of the tissue with 74% sensitivity and specificity using the HER2 amplification status of the primary tumor as a classification variable. CONCLUSIONS: HER2 can be detected on CTCs and tdEVs not expressing CK, and these CK- CTCs/tdEVs have similar clinical relevance to CTCs and tdEVs expressing CK. tdEVs perform better than CTCs in predicting the HER2 status of the primary tissue. CTC and tdEV heterogeneity in the blood of patients is inversely associated with overall surviv

A microwell array platform to print and measure biomolecules produced by single cells

Here we describe a combined method to monitor the secretion of molecules produced by single cells, followed by a method to isolate the individual cells that produced these molecules. The method is based on a self-sorting microwell chip that is connected to an activated membrane that collects the produced molecules. The produced molecules are printed by diffusion in small spots onto the membrane. The location of the printed spots can be correlated to the microwell number and the cell that produced these molecules. To demonstrate the method, we used the EpCAM antibody producing hybridoma cell line VU1D9 and a genetically engineered CHO cell-line producing Her2. VU1D9 cells produced 4.6 ± 5.6 pg (mean ± SD) of EpCAM antibody per 24 h and CHO cells 6.5 ± 8.2 pg per 24 h of Herceptin antibody

Kurzprotokoll ueber eine Sitzung der DGLR-Fachgruppe 12 'Geschichte der Luft- und Raumfahrt'

Copy held by FIZ Karlsruhe; available from UB/TIB Hannover / FIZ - Fachinformationszzentrum Karlsruhe / TIB - Technische InformationsbibliothekSIGLEDEGerman