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High-Throughput Clonogenic Analysis of 3D-Cultured Patient-Derived Cells with a Micropillar and Microwell Chip

Title
High-Throughput Clonogenic Analysis of 3D-Cultured Patient-Derived Cells with a Micropillar and Microwell Chip
Authors
Lee D.W.Lee S.-Y.Park L.Kang M.-S.Kim M.-H.Doh I.Ryu G.H.Nam D.-H.
Ewha Authors
김명희
SCOPUS Author ID
김명희scopus
Issue Date
2017
Journal Title
SALAS Discovery
ISSN
2472-5552JCR Link
Citation
SALAS Discovery vol. 22, no. 5, pp. 645 - 651
Keywords
3D cell cultureassay miniaturizationcell encapsulation in alginateclonogenic assayhigh-throughput screening
Publisher
Oxford University Press
Indexed
SCIE; SCOPUS WOS scopus
Document Type
Article
Abstract
A high-throughput clonogenic assay with a micropillar–microwell chip platform is proposed by using the colony area of glioblastoma multiforme (GBM) patient-derived cells (PDCs) from colony images. Unlike conventional cell lines, PDCs from the tumor are composed of heterogeneous cell populations, and some clonogenic populations form colonies during culture while the rest die off or remain unchanged, thus causing the diverse distribution of colony size. Therefore, area-based analysis of the total colonies is not sufficient to estimate total cell viability or toxicity responses. In this work, the average and standard deviation of an individual colony’s area calculated from the colony images were used as indicators for cell clonogenicity and heterogeneity, respectively. Two parameters (the total and average area of colonies) were compared to draw the colony’s growth curve and measure a doubling time and dose–response curve (IC50). Based on both analyses of two PDCs, 464T PDCs show a higher heterogeneity and clonogenicity than 448T PDCs. The differences in the doubling time and the IC50 according to the analysis methods suggest that the average area of colonies, rather than their total area, is suitable for heterogeneous and clonogenic samples. © 2017, © 2017 Society for Laboratory Automation and Screening.
DOI
10.1177/2472555217692521
Appears in Collections:
인공지능대학 > 컴퓨터공학과 > Journal papers
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