Profiling the heterogeneous phenotypes of rare circulating tumour cells (CTCs) in whole blood is critical to unravelling the complex and dynamic properties of these potential clinical markers. This task is challenging because these cells are present at parts per billion levels among normal blood cells. Here we report a new nanoparticle-enabled method for CTC characterization, called magnetic ranking cytometry, which profiles CTCs on the basis of their surface expression phenotype. We achieve this using a microfluidic chip that successfully processes whole blood samples. The approach classifies CTCs with single-cell resolution in accordance with their expression of phenotypic surface markers, which is read out using magnetic nanoparticles. We deploy this new technique to reveal the dynamic phenotypes of CTCs in unprocessed blood from mice as a function of tumour growth and aggressiveness. We also test magnetic ranking cytometry using blood samples collected from cancer patients.
The analysis of circulating tumor cells (CTCs) is an important capability that may lead to new approaches for cancer management. CTC capture devices developed to date isolate a bulk population of CTCs and do not differentiate subpopulations that may have varying phenotypes with different levels of clinical relevance. Here, we present a new device for CTC spatial sorting and profiling that sequesters blood-borne tumor cells with different phenotypes into discrete spatial bins. Validation data are presented showing that cancer cell lines with varying surface expression generate different binning profiles within the device. Working with patient blood samples, we obtain profiles that elucidate the heterogeneity of CTC populations present in cancer patients and also report on the status of CTCs within the epithelial-to-mesenchymal transition (EMT).
Over the last decade, significant progress has been made towards the development of approaches that enable the capture of rare circulating tumor cells (CTCs) from the blood of cancer patients, a critical capability for noninvasive tumor profiling. These advances have leveraged new insights in materials chemistry and microfluidics and allowed the capture and enumeration of CTCs with unprecedented sensitivity. However, it has become increasingly clear that simply capturing and counting tumor cells launched into the bloodstream may not provide the information needed to advance our understanding of the biology of these rare cells, or to allow us to better exploit them in medicine. A variety of advances have now emerged demonstrating that more information can be extracted from CTCs with next-generation devices and materials featuring tailored physical and chemical properties. In this Minireview, the last ten years of work in this area will be discussed, with an emphasis on the groundbreaking work of the last five years, during which the focus has moved beyond the simple capture of CTCs and gravitated towards approaches that enable in-depth analysis.
Cancer cells, and in particular those found circulating in blood, can have widely varying phenotypes and molecular profiles despite a common origin. New methods are needed that can deconvolute the heterogeneity of cancer cells and sort small numbers of cells to aid in the characterization of cancer cell subpopulations. Here, we describe a new molecular approach to capturing cancer cells that isolates subpopulations using two-dimensional sorting. Using aptamer-mediated capture and antisense-triggered release, the new strategy sorts cells according to levels of two different markers and thereby separates them into their corresponding subpopulations. Using a phenotypic assay, we demonstrate that the subpopulations isolated have markedly different properties. This system provides an important new tool for identifying circulating tumor cell subtypes.
A chip-based approach for electrochemical characterization and detection of microsomes and exosomes based on direct electro-oxidation of metal nanoparticles (MNPs) that specifically recognize surface markers of these vesicles is reported. It is found that exosomes and microsomes derived from prostate cancer cells can be identified by their surface proteins EpCAM and PSMA, suggesting the potential of exosomes and microsomes for use as diagnostic biomarkers.
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