Evidence map›Paper›PMID 27412535›Full record

ArticleJournal of biomolecular screening2016

Development of a 3D Tissue Culture-Based High-Content Screening Platform That Uses Phenotypic Profiling to Discriminate Selective Inhibitors of Receptor Tyrosine Kinases.

Tijmen H Booij, Maarten J D Klop, Kuan Yan, Csaba Szántai-Kis, Balint Szokol, Laszlo Orfi, Bob van de Water, Gyorgy Keri, Leo S Price

Open access · hybridAbstract read
In one paragraph

Article in Journal of biomolecular screening, 2016. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 13 papers.

0numbers the graph read from it
0cells of the map it votes in
13citing papers in PubMed
2.4field-weighted citation impact, top 12% 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

13 citing papers in PubMed, 25 citations in OpenAlex.

  1. Review
  2. Article
  3. Article
  4. Article
  5. Article
  6. Article
  7. Article
  8. Machine learning and image-based profiling in drug discovery.Current opinion in systems biology · 2018
    Review
  9. High-content imaging assays on a miniaturized 3D cell culture platform.Toxicology in vitro : an international journal published in association with BIBRA · 2018
    Article
  10. Article
  11. Article
  12. Three-Dimensional Cell Cultures in Drug Discovery and Development.SLAS discovery : advancing life sciences R & D · 2017
    Review
  13. Organoids as a Model for Colorectal Cancer.Current colorectal cancer reports
    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 4 institutions in 2 countries.

Tijmen H BooijDivision of Toxicology, Leiden Academic Centre for Drug Research, Leiden University, Leiden, The Netherlands.
Maarten J D KlopOcellO B.V., Leiden, The Netherlands.
Kuan YanOcellO B.V., Leiden, The Netherlands.
Csaba Szántai-KisVichem Chemie Research Ltd., Budapest, Hungary.
Balint SzokolVichem Chemie Research Ltd., Budapest, Hungary.
Laszlo OrfiVichem Chemie Research Ltd., Budapest, Hungary Department of Pharmaceutical Chemistry, Semmelweis University, Budapest, Hungary.
Bob van de WaterDivision of Toxicology, Leiden Academic Centre for Drug Research, Leiden University, Leiden, The Netherlands.
Gyorgy KeriVichem Chemie Research Ltd., Budapest, Hungary MTA-SE Pathobiochemistry Research Group, Department of Medical Chemistry, Semmelweis University, Budapest, Hungary.
Leo S PriceDivision of Toxicology, Leiden Academic Centre for Drug Research, Leiden University, Leiden, The Netherlands OcellO B.V., Leiden, The Netherlands leo.price@ocello.nl.
Centre for Human Drug Research · NLSemmelweis University · HUVichem Chemie (Hungary) · HULeiden University · NL

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

3D tissue cultures provide a more physiologically relevant context for the screening of compounds, compared with 2D cell cultures. Cells cultured in 3D hydrogels also show complex phenotypes, increasing the scope for phenotypic profiling. Here we describe a high-content screening platform that uses invasive human prostate cancer cells cultured in 3D in standard 384-well assay plates to study the activity of potential therapeutic small molecules and antibody biologics. Image analysis tools were developed to process 3D image data to measure over 800 phenotypic parameters. Multiparametric analysis was used to evaluate the effect of compounds on tissue morphology. We applied this screening platform to measure the activity and selectivity of inhibitors of the c-Met and epidermal growth factor (EGF) receptor (EGFR) tyrosine kinases in 3D cultured prostate carcinoma cells. c-Met and EGFR activity was quantified based on the phenotypic profiles induced by their respective ligands, hepatocyte growth factor and EGF. The screening method was applied to a novel collection of 80 putative inhibitors of c-Met and EGFR. Compounds were identified that induced phenotypic profiles indicative of selective inhibition of c-Met, EGFR, or bispecific inhibition of both targets. In conclusion, we describe a fully scalable high-content screening platform that uses phenotypic profiling to discriminate selective and nonselective (off-target) inhibitors in a physiologically relevant 3D cell culture setting.

Indexed as

Cell ProliferationDrug Screening Assays, AntitumorErbB ReceptorsHigh-Throughput Screening AssaysHumansHydrogelsMaleProstatic NeoplasmsProtein Kinase InhibitorsProto-Oncogene Proteins c-metSmall Molecule LibrariesEGFR protein, humanErbB ReceptorsHydrogelsProtein Kinase InhibitorsProto-Oncogene Proteins c-metSmall Molecule Libraries3D tissue culturec-MetEGFRhigh-content screeningphenotypic profiling

Identifiers

PMID27412535
PMCPMC5030728
OpenAlexW2463835565

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC
Read underepoch 390

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.