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Issue 10, 2014
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Microfluidic immunocapture of circulating pancreatic cells using parallel EpCAM and MUC1 capture: characterization, optimization and downstream analysis

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Abstract

We have developed and optimized a microfluidic device platform for the capture and analysis of circulating pancreatic cells (CPCs) and pancreatic circulating tumor cells (CTCs). Our platform uses parallel anti-EpCAM and cancer-specific mucin 1 (MUC1) immunocapture in a silicon microdevice. Using a combination of anti-EpCAM and anti-MUC1 capture in a single device, we are able to achieve efficient capture while extending immunocapture beyond single marker recognition. We also have detected a known oncogenic KRAS mutation in cells spiked in whole blood using immunocapture, RNA extraction, RT-PCR and Sanger sequencing. To allow for downstream single-cell genetic analysis, intact nuclei were released from captured cells by using targeted membrane lysis. We have developed a staining protocol for clinical samples, including standard CTC markers; DAPI, cytokeratin (CK) and CD45, and a novel marker of carcinogenesis in CPCs, mucin 4 (MUC4). We have also demonstrated a semi-automated approach to image analysis and CPC identification, suitable for clinical hypothesis generation. Initial results from immunocapture of a clinical pancreatic cancer patient sample show that parallel capture may capture more of the heterogeneity of the CPC population. With this platform, we aim to develop a diagnostic biomarker for early pancreatic carcinogenesis and patient risk stratification.

Graphical abstract: Microfluidic immunocapture of circulating pancreatic cells using parallel EpCAM and MUC1 capture: characterization, optimization and downstream analysis

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Article information


Submitted
11 Jan 2014
Accepted
21 Feb 2014
First published
21 Feb 2014

Lab Chip, 2014,14, 1775-1784
Article type
Paper
Author version available

Microfluidic immunocapture of circulating pancreatic cells using parallel EpCAM and MUC1 capture: characterization, optimization and downstream analysis

F. I. Thege, T. B. Lannin, T. N. Saha, S. Tsai, M. L. Kochman, M. A. Hollingsworth, A. D. Rhim and B. J. Kirby, Lab Chip, 2014, 14, 1775
DOI: 10.1039/C4LC00041B

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