Abstract

Due to low numbers of circulating tumor cells (CTCs) in liquid biopsies, there is much interest in enrichment of alternative circulating-like mesenchymal cancer cell subpopulations from in vitro tumor cultures for utilization within molecular profiling and drug screening. Viable cancer cells that are released into the media of drug-treated adherent cancer cell cultures exhibit anoikis resistance or anchorage-independent survival away from their extracellular matrix with nutrient sources and waste sinks, which serves as a pre-requisite for metastasis. The enrichment of these cell subpopulations from tumor cultures can potentially serve as an in vitro source of circulating-like cancer cells with greater potential for scale-up in comparison with CTCs. However, these live circulating-like cancer cell subpopulations exhibit size overlaps with necrotic and apoptotic cells in the culture media, which makes it challenging to selectively enrich them, while maintaining them in their suspended state. We present optimization of a flowthrough high frequency (1 MHz) positive dielectrophoresis (pDEP) device with sequential 3D field non-uniformities that enables enrichment of the live chemo-resistant circulating cancer cell subpopulation from an in vitro culture of metastatic patient-derived pancreatic tumor cells. Central to this strategy is the utilization of single-cell impedance cytometry with gates set by supervised machine learning, to optimize the frequency for pDEP, so that live circulating cells are selected based on multiple biophysical metrics, including membrane physiology, cytoplasmic conductivity and cell size, which is not possible using deterministic lateral displacement that is solely based on cell size. Using typical drug-treated samples with low levels of live circulating cells (<3%), we present pDEP enrichment of the target subpopulation to ∼44% levels within 20 minutes, while rejecting >90% of dead cells. This strategy of utilizing single-cell impedance cytometry to guide the optimization of dielectrophoresis has implications for other complex biological samples.

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