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Comprehensive isolation, identification, and nucleic acid analysis of single breast cancer cells: CTC-isoTECH
Author(s) -
Lori Millner,
Lindsay N. Strotman,
Kevin Goudy,
Mark W. Linder,
Roland Valdes
Publication year - 2016
Publication title -
cancer research frontiers
Language(s) - English
Resource type - Journals
ISSN - 2328-5249
DOI - 10.17980/2016.286
Subject(s) - isolation (microbiology) , breast cancer , nucleic acid , identification (biology) , computational biology , cancer , biology , genetics , bioinformatics , botany
The ability to isolate, phenotypically characterize, and profile the gene signature of single circulating tumor cells (CTCs) will provide deeper insight into cancer metastasis and will lead to improved diagnosis and treatment of cancer patients. Using current methods based on positive selection of epithelial markers, up to 40% of patients with highly aggressive metastatic breast cancer have no CTCs detected. This may be due to CTCs undergoing the process of epithelial to mesenchymal transition (EMT). This process causes epithelial characteristics to be down regulated as more mesenchymal features develop allowing the cells to have higher motility and increased ability to evade immune detection. Methods to enable capture and characterization of heterogeneous CTCs including those with non-epithelial phenotypes are needed. Additionally, having the ability to isolate pure, single CTCs allows for individual cell analysis providing information that is masked by bulk analysis. Here we provide details on an integrated method for isolating and characterizing heterogeneous single breast cancer cells based on a multiantigen, negative depletion strategy followed by sorting with dielectrophoresis (DEPArray). This negative depletion method removes unwanted leukocytes and allows heterogeneous, epithelial and non-epithelial cells to be retained. We were able to visually verify the isolation of single tumor cells with 100% purity. Following sorting, next generation sequencing and real-time PCR of single cells is described. This method allows single, heterogeneous CTCs to be analyzed which will have implications for prognosis and treatment options.

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