$$\rightleftharpoonup{xx}$$
$$\longleftharp{xx}$$,
$$\longrightharp{xx}$$,
In 2013 it is estimated that 580,350 individuals will die from cancer and that 1,660,290 new cases of this disease will be diagnosed in the United States alone1. The majority of these deaths occur subsequent to the development of metastatic disease2. The current lack of effective therapies in treating metastases and a limited understanding of the metastatic cascade makes this stage of disease highly lethal. The presence of circulating tumor cells (CTCs) within the bloodstream have been demonstrated to correlate with metastatic disease3. These cells are extremely rare and their detection is indicative of overall survival in metastatic breast4, prostate5, and colorectal6 cancer. In these patients, the presence of ≥5 (breast and prostate) or ≥3 (colorectal) CTCs in 7.5 ml of blood is indicative of poorer prognosis when compared to those patients with fewer or no detectable CTCs in the same blood volume. In addition, the change in CTC number during or after therapeutic intervention has been demonstrated to be useful as a predictor of treatment response, often sooner than currently utilized techniques7-10.
It has been estimated that, in metastatic cancer patients, CTCs occur at a frequency of approximately 1 CTC per 105-107 blood mononuclear cells and in patients with localized disease, this frequency may be even lower (~1 in 108). The rare nature of these cells can make it difficult to accurately and reliably detect and analyze CTCs11. Several methods (reviewed previously12-14) have been utilized to enrich and detect these cells by exploiting properties that differentiate them from surrounding blood components. In general, CTC enumeration is a two-part process that requires both an enrichment step and a detection step. Traditionally, enrichment steps rely on differences in physical properties of CTCs (cell size, density, deformability) or on protein marker expression (i.e. epithelial cell adhesion molecule [EpCAM], cytokeratin [CK]). Following enrichment, CTC detection can be performed in a number of different ways, the most common of which are nucleic acid-based assays and/or cytometric approaches. Each of these strategies are unique, having distinct advantages and disadvantages, however they all lack standardization; a necessity for entrance into the clinical setting. The CellSearch system (CSS) was therefore developed to provide a standardized method for the detection and enumeration of rare CTCs in human blood using fluorescence microscopy and antibody-based techniques4-6. This platform is currently considered the gold standard in CTC enumeration and is the only technique approved by the U.S. Food and Drug Administration (FDA) for use in the clinic15.
The CSS is a two component platform consisting of, (1) the CellTracks AutoPrep system (hereafter referred to as the preparation instrument), which automates the preparation of human blood samples, and (2) the CellTracks Analyzer II (hereafter referred to as the analysis instrument), which scans these samples following preparation. To distinguish CTCs from contaminating leukocytes the preparation instrument employs an antibody mediated, ferrofluid-based magnetic separation approach and differential fluorescence staining. Initially, the system labels CTCs using anti-EpCAM antibodies conjugated to iron nanoparticles. The sample is then incubated in a magnetic field, and all unlabeled cells are aspirated. Selected tumor cells are resuspended, and incubated in a differential fluorescence stain, consisting of fluorescently-labeled antibodies and a nuclear staining reagent. Finally, the sample is transferred to a magnetic cartridge, called a MagNest (hereafter referred to as the magnetic device), and scanned using the analysis instrument.
The analysis instrument is used to scan prepared samples using different fluorescence filters, each optimized to the appropriate fluorescent particle, using a 10X objective lens. CTCs are identified as cells that are bound by anti-EpCAM, anti-pan-CK-phycoerythrin (PE) (CK8, 18, and 19), and the nuclear stain 4',6-diamidino-2-phenylindole (DAPI). Conversely, contaminating leukocytes are identified as cells that are bound by anti-CD45-allophycocyanin (APC) and DAPI. Following scanning, computer-defined potential tumor cells are presented to the user. From these images, the user must employ qualitative analysis using the defined parameters and differential staining discussed above to determine which events are CTCs.
In addition to providing a standardized method for CTC enumeration, the CSS allows for molecular characterization of CTCs based on protein markers of interest. This interrogation can be performed at the single-cell level, using a fluorescein isothiocyanate (FITC) fluorescence channel not required for CTC identification16. Although this platform provides the capacity for molecular characterization, the detailed process of protocol development and optimization is not well-defined. Three commercially available markers have been developed by the manufacturer for use with the CSS, including epidermal growth factor receptor (EGFR), human epidermal growth factor receptor 2 (HER2), and insulin-like growth factor 1 receptor (IGF-1R). HER2 analysis, in combination with the CSS, has been utilized by several groups to illustrate the potential for CTC characterization to inform clinical decision-making and to potentially change existing treatment guidelines. For example, Fehm et al.17 demonstrated that approximately one third of breast cancer patients with HER2-primary tumors had HER2+ CTCs. In addition, Liu et al.18 recently reported that up to 50% of patients with HER+ metastatic breast cancer did not have HER2+ CTCs. Herceptin, a HER2 receptor interfering monoclonal antibody demonstrated to greatly benefit patients whose tumors express sufficient levels of HER2, is a commonly utilized treatment for patients with HER2+ primary tumors19-21. However, these studies suggest that Herceptin may be being sub-optimally utilized and that CTC characterization may aid in predicting treatment response. Ultimately, CTC characterization may have the potential to improve personalized care.
CTC research is unique in that it has largely utilized a bedside-to-benchtop approach. This method, unlike benchtop-to-bedside research, which can often take years to impact patient care, has allowed CTCs quick entry into the clinical setting. However, physicians are hesitant to use results from CTC analysis in patient treatment decision-making due to a lack of understanding of their underlying biology. Therefore appropriate preclinical mouse models of metastasis and complementary CTC analysis techniques must be utilized in order to investigate these outstanding questions. In general, there are two types of preclinical models used to study the metastatic cascade, (1) spontaneous metastasis models, which allow for the study of all the steps in the metastatic cascade, and (2) experimental metastasis models, which only allow for the study of later steps in the metastatic process such as extravasation and secondary tumor formation22. Spontaneous metastasis models, involve tumor cell injections into appropriate orthotopic locations (e.g. injection of prostate cancer cells into the prostate gland for the study of prostate cancer). Cells are then given time to form primary tumors and spontaneously metastasize to secondary sites such as the bone, lung, and lymph nodes. In contrast, experimental metastasis models involve direct injection of tumor cells into the bloodstream (e.g. via tail vein or intracardiac injection to target cells to specific locations) and therefore skip the initial steps of intravasation and dissemination to secondary organs22. Thus far the majority of CTC analysis in in vivo model systems has been performed using either cytometry-based23 or adapted human-based CTC techniques (e.g. AdnaTest)24. Although useful, none of these techniques adequately reflect CTC enumeration using the gold standard CSS. Based on the clinical approval, standardized nature, and widespread usage of the CSS, the development of a CTC capture and detection technique for in vivo modeling that utilizes equivalent sample preparation, processing, and identification criteria would be advantageous as results would be comparable to those obtained from patient samples. However, due to the volume requirements of the preparation instrument it is not possible to process small volumes of blood using this automated platform. In addition, previous work by Eliane et al.25 has demonstrated that contamination of samples with mouse epithelial cells (which also meet the standard CTC definition [EpCAM+CK+DAPI+CD45-]) can lead to misclassification of mouse squamous epithelial cells as CTCs. To address these issues an adapted technique that allows the utilization of the CSS CTC kit reagents combined with a manual isolation procedure was developed. The addition of a FITC labeled human leukocyte antigen (HLA) antibody to the assay allows human tumor cells to be distinguished from mouse squamous epithelial cells.
This manuscript describes the standard, commercially developed and optimized CSS protocol for processing patient blood samples and common pitfalls that may be encountered, including discrepant items that can lead to CTC misclassification errors. In addition, customization of the CSS assay to examine user-defined protein characteristics of captured CTCs and a comparable adapted CSS technique that allows for the enrichment and detection of CTCs from small volumes of blood in preclinical mouse models of metastasis are described.