Stefansson, Steingrimur

Abstract Background: Tumor endothelial cells (ECs) are a population of stromal cells required for tumor growth that cooperate with tumors to form angiogenic structures. In blood, circulating ECs (CECs) are normal constituents of healthy individuals, although a Cancer Associated Vascular Endothelial cell (CAVE) subtype has been observed in cancer patients. The CAVE population has been isolated and identified using their large size or multicellular clustering and a pooled mixture of classical EC markers (i.e. CD31 and CD146). However, there has been no attempt to differentiate CAVEs from the many EC subtypes. This is not surprising as in-depth phenotyping of ECs requires an array of biomarkers that until recently has not been feasible. A multi-phenotypic screening of EC markers was tested on CAVEs from 116 blood samples in 3 types of solid tumors. This data suggests that CAVEs exist as a common and diverse subtype of tumor derived CECs that may express cytokeratin (CK) and various EC biomarkers, correlating to disease stage. Methods: Peripheral blood samples from 116 cancer patients (stage I-IV) were drawn from 2012-2014 including breast (n=42), lung (n=39) and prostate (n=35), as well as blood from 34 healthy controls. Blood was processed by an established filtration approach, i.e. the CellSieveTM microfiltration technique (Creatv MicroTech), filtering blood by size exclusion and staining cells for CK 8, 18 & 19, EpCAM and CD45. After identification and imaging, the QUAS-R (Quench, Underivatize, Amine-Strip and Restain) technique was used to remove fluorescence signal and restain all cells with CD31, CD146, CD144, & DAPI. After reimaging, QUAS-R was again used to remove fluorescence and restain the cells for CD14, CD105, CD34, & DAPI. Results: Out of 116 patient samples, we identified CAVEs in 63 patients (54%) based on positivity of CD31, CD144 or CD146, but none were found in healthy controls. CAVEs per 7.5mL sample in patients averaged 5.1 (breast), 5.6 (prostate) and 7.9 (lung). Presence of CAVEs appeared related to stage with 26% in stage 1, 61% in stage 2, 68% in stage 3, and 74% in stage 4 patients. No CAVEs were positive for CD14 or CD45. CD31 was the most present marker, found on 93% of CAVEs, followed by CD144 (85%), CD34 (64%), CD146 (45%), & CD105 (4%). In contrast with the previous study on this topic, CK was found in 67% of CAVEs, but was not a universal marker. Conclusions: It has been reported that CK+ and CD45- CECs are isolated from the blood of cancer patients in colon and lung cancers, prompting some to classify them as circulating tumor cells. However, subtyping these CECs is incomplete when characterized with only 3-4 biomarkers. A multi-phenotypic subtyping technique was used to properly identify and subtype these CECs in cancer patients. This data suggest that a subset of CECs, e.g. CAVEs, are found in circulation as CK+/CD45-, but exist as a heterogeneous population of cancer specific circulating cells that require further study. Citation Format: Daniel L. Adams, R. Katherine Alpaugh, Steven H. Lin, Jeffrey R. Marks, Raymond Bergan, Stuart S. Martin, Sarany Chumsri, Massimo Cristofanilli, Cha-Mei Tang, Steingrimur Stefansson. Identifying, subtyping and classifying tumor associated circulating endothelial cells in patients with solid tumors [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2017; 2017 Apr 1-5; Washington, DC. Philadelphia (PA): AACR; Cancer Res 2017;77(13 Suppl):Abstract nr 778. doi:10.1158/1538-7445.AM2017-778

An all-in-one Circulating Tumor Cell (CTC) isolation platform with streamlined multiplex integration of proteomic and genomic clinical testing.

AbstractRecent studies reporting hundreds, to thousands, of circulating tumor cells (CTCs) in the blood of cancer patients have raised questions regarding the prevalence of CTCs, as enumerated by the CellSearch® CTC Test. Although CellSearch has been shown to consistently detect clinically relevant CTCs; the ability to only capture EpCAM positive cells has led to speculation that it captures limited subsets of CTCs. In contrast, alternative approaches to CTC isolation are often cited as capturing large numbers of CTCs from patient blood. Not surprisingly the number of cells isolated by alternative approaches show poor correlations when compared to CellSearch, even when accounting for EpCAM presence or absence. In an effort to address this discrepancy, we ran an exploratory method comparison study to characterize and compare the CTC subgroups captured from duplicate blood samples from 30 breast and prostate cancer patients using a microfiltration system (CellSieve™) and CellSearch. We then categorized the CellSieve Cytokeratin(CK)+/CD45−/DAPI+ cells into five morphologically distinct subpopulations for correlative analysis. Like other filtration techniques, CellSieve isolated greater numbers of CK+/CD45− cells than CellSearch. Furthermore, analysis showed low correlation between the total CK+/CD45− cells captured by these two assays, regardless of EpCAM presence. However, subgrouping of CK+/CD45−/DAPI+ cells based on distinct cytokeratin staining patterns and nuclear morphologies elucidated a subpopulation correlative to CellSearch. Using method comparison analyses, we identified a specific CTC morphology which is highly correlative between two distinct capture methods. These data suggests that although various morphologic CTCs with similar phenotypic expressions are present in the blood of cancer patients, the clinically relevant cells isolated by CellSearch can potentially be identified using non‐EpCAM dependent isolation. © 2014 The Authors. Published by Wiley Periodicals, Inc.