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Image-Based Detection of Patient-Specific Drug-Induced Cell-Cycle Effects in Glioblastoma

Matuszewski, Damian J. (author)
Uppsala universitet,Avdelningen för visuell information och interaktion,Bildanalys och människa-datorinteraktion,Science for Life Laboratory, SciLifeLab
Wählby, Carolina, professor, 1974- (author)
Uppsala universitet,Bildanalys och människa-datorinteraktion,Science for Life Laboratory, SciLifeLab,Avdelningen för visuell information och interaktion
Krona, Cecilia, 1976- (author)
Uppsala universitet,Institutionen för immunologi, genetik och patologi
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Nelander, Sven (author)
Uppsala universitet,Science for Life Laboratory, SciLifeLab,Neuroonkologi
Sintorn, Ida-Maria, 1976- (author)
Uppsala universitet,Bildanalys och människa-datorinteraktion,Avdelningen för visuell information och interaktion
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 (creator_code:org_t)
Elsevier BV, 2018
2018
English.
In: SLAS Discovery. - : Elsevier BV. - 2472-5560 .- 2472-5552. ; 23:10, s. 1030-1039
  • Journal article (peer-reviewed)
Abstract Subject headings
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  • Image-based analysis is an increasingly important tool to characterize the effect of drugs in large-scale chemical screens. Herein, we present image and data analysis methods to investigate population cell-cycle dynamics in patient-derived brain tumor cells. Images of glioblastoma cells grown in multiwell plates were used to extract per-cell descriptors, including nuclear DNA content. We reduced the DNA content data from per-cell descriptors to per-well frequency distributions, which were used to identify compounds affecting cell-cycle phase distribution. We analyzed cells from 15 patient cases representing multiple subtypes of glioblastoma and searched for clusters of cell-cycle phase distributions characterizing similarities in response to 249 compounds at 11 doses. We show that this approach applied in a blind analysis with unlabeled substances identified drugs that are commonly used for treating solid tumors as well as other compounds that are well known for inducing cell-cycle arrest. Redistribution of nuclear DNA content signals is thus a robust metric of cell-cycle arrest in patient-derived glioblastoma cells.

Subject headings

NATURVETENSKAP  -- Data- och informationsvetenskap -- Datorseende och robotik (hsv//swe)
NATURAL SCIENCES  -- Computer and Information Sciences -- Computer Vision and Robotics (hsv//eng)

Keyword

Computerized Image Processing
Datoriserad bildbehandling

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