Evidence map›Paper›PMID 24810913›Full record

ArticlePloS one2014

Quantification of dynamic morphological drug responses in 3D organotypic cell cultures by automated image analysis.

Ville Härmä, Hannu-Pekka Schukov, Antti Happonen, Ilmari Ahonen, Johannes Virtanen, Harri Siitari, Malin Åkerfelt, Jyrki Lötjönen, Matthias Nees

Open access · goldAbstract read
In one paragraph

Article in PloS one, 2014. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 50 papers.

0numbers the graph read from it
0cells of the map it votes in
50citing papers in PubMed
12.0field-weighted citation impact, top 2% of its field
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

50 citing papers in PubMed, 83 citations in OpenAlex.

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  15. Optogenetic control of NOTCH1 signaling.Cell communication and signaling : CCS · 2022
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  19. High-Throughput Imaging Assay for Drug Screening of 3D Prostate Cancer Organoids.SLAS discovery : advancing life sciences R & D · 2021
    Article
  20. Review
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

9 authors at 5 institutions in 2 countries.

Ville HärmäMedical Biotechnology Knowledge Centre, VTT Technical Research Centre of Finland, Turku, Finland; Turku Centre for Biotechnology, University of Turku, Turku, Finland.
Hannu-Pekka SchukovMedical Biotechnology Knowledge Centre, VTT Technical Research Centre of Finland, Turku, Finland; Turku Centre for Biotechnology, University of Turku, Turku, Finland.
Antti HapponenDepartment of Signal Processing, Tampere University of Technology, Tampere, Finland.
Ilmari AhonenDepartment of Information Technology, University of Turku, Turku, Finland.
Johannes VirtanenMedical Biotechnology Knowledge Centre, VTT Technical Research Centre of Finland, Turku, Finland; Turku Centre for Biotechnology, University of Turku, Turku, Finland.
Harri SiitariMedical Biotechnology Knowledge Centre, VTT Technical Research Centre of Finland, Turku, Finland.
Malin ÅkerfeltMedical Biotechnology Knowledge Centre, VTT Technical Research Centre of Finland, Turku, Finland; Turku Centre for Biotechnology, University of Turku, Turku, Finland.
Jyrki LötjönenKnowledge Intensive Services, VTT Technical Research Centre of Finland, Tampere, Finland.
Matthias NeesMedical Biotechnology Knowledge Centre, VTT Technical Research Centre of Finland, Turku, Finland; Turku Centre for Biotechnology, University of Turku, Turku, Finland.
VTT Technical Research Centre of Finland · FITurku Centre for Biotechnology · FIInformation Technology University · PKTampere University · FIUniversity of Turku · FI

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Glandular epithelial cells differentiate into complex multicellular or acinar structures, when embedded in three-dimensional (3D) extracellular matrix. The spectrum of different multicellular morphologies formed in 3D is a sensitive indicator for the differentiation potential of normal, non-transformed cells compared to different stages of malignant progression. In addition, single cells or cell aggregates may actively invade the matrix, utilizing epithelial, mesenchymal or mixed modes of motility. Dynamic phenotypic changes involved in 3D tumor cell invasion are sensitive to specific small-molecule inhibitors that target the actin cytoskeleton. We have used a panel of inhibitors to demonstrate the power of automated image analysis as a phenotypic or morphometric readout in cell-based assays. We introduce a streamlined stand-alone software solution that supports large-scale high-content screens, based on complex and organotypic cultures. AMIDA (Automated Morphometric Image Data Analysis) allows quantitative measurements of large numbers of images and structures, with a multitude of different spheroid shapes, sizes, and textures. AMIDA supports an automated workflow, and can be combined with quality control and statistical tools for data interpretation and visualization. We have used a representative panel of 12 prostate and breast cancer lines that display a broad spectrum of different spheroid morphologies and modes of invasion, challenged by a library of 19 direct or indirect modulators of the actin cytoskeleton which induce systematic changes in spheroid morphology and differentiation versus invasion. These results were independently validated by 2D proliferation, apoptosis and cell motility assays. We identified three drugs that primarily attenuated the invasion and formation of invasive processes in 3D, without affecting proliferation or apoptosis. Two of these compounds block Rac signalling, one affects cellular cAMP/cGMP accumulation. Our approach supports the growing needs for user-friendly, straightforward solutions that facilitate large-scale, cell-based 3D assays in basic research, drug discovery, and target validation.

Indexed as

Cell DifferentiationCell Line, TumorCell MovementCell ProliferationCell ShapeEpithelial CellsExtracellular MatrixHumansImage Processing, Computer-Assisted

Identifiers

PMID24810913
PMCPMC4014501
OpenAlexW1985090392

What OpenQuestion holds

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LicenceCC BY
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Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.