4.7 Article

A negative selection methodology using a microfluidic platform for the isolation and enumeration of circulating tumor cells

期刊

METHODS
卷 64, 期 2, 页码 137-143

出版社

ACADEMIC PRESS INC ELSEVIER SCIENCE
DOI: 10.1016/j.ymeth.2013.05.027

关键词

Circulating tumor cells; Negative selection; Microfluidics; ELISPOT

资金

  1. Department of Defense Prostate Cancer Research Program [W81XWH-09-1-0192]
  2. NIH-National Cancer Institute [R33 CA 137673, R33 CA 160344]
  3. NIH [T32 CA157322]

向作者/读者索取更多资源

Circulating tumor cells (CTCs) exist in the peripheral blood stream of metastatic cancer patients at rates of approximately 1 CTC per billion background cells. In order to capture and analyze this rare cell population, various techniques exist that range from antibody-based surface marker positive selection to methods that use physical properties of CTCs to negatively exclude background cells from a CTC population. However, methods to capture cells for functional downstream analyses are limited due to inaccessibility of the captured sample or labeling techniques that may be prohibitive to cell function. Here, we present a negative selection method that leverages a Microfluidic Cell Concentrator (MCC) to allow collection and analysis of this rare cell population without needing cell adhesion or other labeling techniques to keep the cells within the chamber. Because the MCC is designed to allow collection and analysis of non-adherent cell populations, multiple staining steps can be applied in parallel to a given CTC population without losing any of the population. The ability of the MCC for patient sample processing of CTCs for enumeration was demonstrated with five patient samples, revealing an average of 0.31 CTCs / mL. The technique was compared to a previously published method - the ELISPOT - that showed similar CTC levels among the five patient samples tested. Because the MCC method does not use positive selection, the method can be applied across a variety of tumor types with no changes to the process. (C) 2013 Elsevier Inc. All rights reserved.

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