Browsing by Subject "stem-cells"

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Antibody-Independent Isolation of Circulating Tumor Cells by Continuous-Flow Dielectrophoresis
(2013-01) Shim, Sangjo; Stemke-Hale, Katherine; Tsimberidou, Apostolia M.; Noshari, Jamileh; Anderson, Thomas E.; Gascoyne, Peter R. C.; Shim, Sangjo; Noshari, Jamileh; Anderson, Thomas E.; Gascoyne, Peter R. C.
Circulating tumor cells (CTCs) are prognostic markers for the recurrence of cancer and may carry molecular information relevant to cancer diagnosis. Dielectrophoresis (DEP) has been proposed as a molecular marker-independent approach for isolating CTCs from blood and has been shown to be broadly applicable to different types of cancers. However, existing batch-mode microfluidic DEP methods have been unable to process 10 ml clinical blood specimens rapidly enough. To achieve the required processing rates of 106 nucleated cells/min, we describe a continuous flow microfluidic processing chamber into which the peripheral blood mononuclear cell fraction of a clinical specimen is slowly injected, deionized by diffusion, and then subjected to a balance of DEP, sedimentation and hydrodynamic lift forces. These forces cause tumor cells to be transported close to the floor of the chamber, while blood cells are carried about three cell diameters above them. The tumor cells are isolated by skimming them from the bottom of the chamber while the blood cells flow to waste. The principles, design, and modeling of the continuous-flow system are presented. To illustrate operation of the technology, we demonstrate the isolation of circulating colon tumor cells from clinical specimens and verify the tumor origin of these cells by molecular analysis. (C) 2013 American Institute of Physics. [http://dx.doi.org/10.1063/1.4774304]
Dielectrophoresis has Broad Applicability to Marker-Free Isolation of Tumor Cells from Blood by Microfluidic Systems
(2013-01) Shim, Sangjo; Stemke-Hale, Katherine; Noshari, Jamileh; Becker, Frederick F.; Gascoyne, Peter R. C.; Shim, Sangjo
The number of circulating tumor cells (CTCs) found in blood is known to be a prognostic marker for recurrence of primary tumors, however, most current methods for isolating CTCs rely on cell surface markers that are not universally expressed by CTCs. Dielectrophoresis (DEP) can discriminate and manipulate cancer cells in microfluidic systems and has been proposed as a molecular marker-independent approach for isolating CTCs from blood. To investigate the potential applicability of DEP to different cancer types, the dielectric and density properties of the NCI-60 panel of tumor cell types have been measured by dielectrophoretic field-flow fractionation (DEP-FFF) and compared with like properties of the subpopulations of normal peripheral blood cells. We show that all of the NCI-60 cell types, regardless of tissue of origin, exhibit dielectric properties that facilitate their isolation from blood by DEP. Cell types derived from solid tumors that grew in adherent cultures exhibited dielectric properties that were strikingly different from those of peripheral blood cell subpopulations while leukemia-derived lines that grew in non-adherent cultures exhibited dielectric properties that were closer to those of peripheral blood cell types. Our results suggest that DEP methods have wide applicability for the surface-marker independent isolation of viable CTCs from blood as well as for the concentration of leukemia cells from blood. (C) 2013 American Institute of Physics. [http://dx.doi.org/10.1063/1.4774307]
Nonparametric Bayesian Bi-Clustering for Next Generation Sequencing Count Data
(2013) Xu, Yanxun; Lee, Juhee; Yuan, Yuan; Mitra, Riten; Liang, Shoudan; Muller, Peter; Ji, Yi; Mitra, Riten; Muller, Peter
Histone modifications (HMs) play important roles in transcription through post-translational modifications. Combinations of HMs, known as chromatin signatures, encode specific messages for gene regulation. We therefore expect that inference on possible clustering of HMs and an annotation of genomic locations on the basis of such clustering can contribute new insights about the functions of regulatory elements and their relationships to combinations of HMs. We propose a nonparametric Bayesian local clustering Poisson model (NoB-LCP) to facilitate posterior inference on two-dimensional clustering of HMs and genomic locations. The NoB-LCP clusters HMs into HM sets and lets each HM set define its own clustering of genomic locations. Furthermore, it probabilistically excludes HMs and genomic locations that are irrelevant to clustering. By doing so, the proposed model effectively identifies important sets of HMs and groups regulatory elements with similar functionality based on HM patterns.