Epithelial-to-mesenchymal transition leads to loss of EpCAM and different physical properties in circulating tumor cells from metastatic breast cancer

• Published in: Oncotarget Vol. 7; no. 17; pp. 24677 - 24687
• Main Authors: Hyun, Kyung-A, Koo, Gi-Bang, Han, Hyunju, Sohn, Joohyuk, Choi, Wonshik, Kim, Seung-Il, Jung, Hyo-Il, Kim, You-Sun
• Format: Journal Article
• Language: English
• Published: United States Impact Journals LLC 26.04.2016
• Subjects: Breast Neoplasms - genetics; Breast Neoplasms - metabolism; Breast Neoplasms - pathology; Epithelial Cell Adhesion Molecule - genetics; Epithelial Cell Adhesion Molecule - metabolism; Epithelial-Mesenchymal Transition; Female; Humans; MCF-7 Cells; Neoplasm Metastasis; Neoplastic Cells, Circulating - metabolism; Neoplastic Cells, Circulating - pathology; Research Paper; EpCAM-negative; label-free separation; epithelial cell adhesion molecule (EpCAM); circulating tumor cells (CTCs); EMT-induced breast cancer cell
• ISSN: 1949-2553; 1949-2553
• DOI: 10.18632/oncotarget.8250

The dissemination of circulating tumor cells (CTCs) requires the Epithelial-to-Mesenchymal transition (EMT), in which cells lose their epithelial characteristics and acquire more mesenchymal-like phenotypes. Current isolation of CTCs relies on affinity-based approaches reliant on the expression of Epithelial Cell Adhesion Molecule (EpCAM). Here we show EMT-induced breast cancer cells maintained in prolonged mammosphere culture conditions possess increased EMT markers and cancer stem cell markers, as well as reduced cell mass and size by quantitative phase microscopy; however, EpCAM expression is dramatically decreased in these cells. Moreover, CTCs isolated from breast cancer patients using a label-free microfluidic flow fractionation device had differing expression patterns of EpCAM, indicating that affinity approaches reliant on EpCAM expression may underestimate CTC number and potentially miss critical subpopulations. Further characterization of CTCs, including low-EpCAM populations, using this technology may improve detection techniques and cancer diagnosis, ultimately improving cancer treatment.