Evidence map›Paper›PMID 42884036›Full record

ArticleInternational journal of molecular sciences2026

Cell Painting Identifies Phenotypic Clusters Associated with Anticancer Drug Responses in OVCAR-3 Ovarian Cancer Cells.

Vladimir E Popov, Velemir S Lavrinenko, Ekaterina V Litau, Alena A Shurova, Mikhail A Trofimov, Daria M Danilenko, Dmitry A Lioznov, Ramziya G Kiyamova, Stanislav F Tyazhelnikov

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Article in International journal of molecular sciences, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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1 · What the graph read from it

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2 · The registry

The trial behind it

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3 · Its place in the literature

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4 · The record

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5 · Who and what money

Authors and funding

9 authors.

Vladimir E PopovJSC BIOCAD, 191186 Saint Petersburg, Russia.ORCID 0000-0001-7354-7283
Velemir S LavrinenkoJSC BIOCAD, 191186 Saint Petersburg, Russia.ORCID 0009-0007-8681-4484
Ekaterina V LitauJSC BIOCAD, 191186 Saint Petersburg, Russia.ORCID 0009-0001-4093-1403
Alena A ShurovaJSC BIOCAD, 191186 Saint Petersburg, Russia.
Mikhail A TrofimovNanotechnology Research and Education Centre, Saint Petersburg Academic University, 194021 Saint Petersburg, Russia.ORCID 0000-0002-7749-0541
Daria M DanilenkoSmorodintsev Research Institute of Influenza, 197376 Saint Petersburg, Russia.ORCID 0000-0001-6174-0836
Dmitry A LioznovSmorodintsev Research Institute of Influenza, 197376 Saint Petersburg, Russia.ORCID 0000-0003-3643-7354
Ramziya G KiyamovaBiomarker Research Laboratory, Institute of Fundamental Medicine and Biology, Kazan Federal University, 420008 Kazan, Russia.
Stanislav F TyazhelnikovJSC BIOCAD, 191186 Saint Petersburg, Russia.

Funding

BIOCAD (Russia)
6 · The paper itself

Abstract

Cell Painting is a high-content imaging approach that enables systematic characterization of cellular responses to chemical perturbations through quantitative morphological profiling. Although this methodology has been widely applied in drug discovery and functional genomics, ovarian cancer models remain comparatively underrepresented in Cell Painting studies. In the present work, we established a Cell Painting workflow for OVCAR-3 ovarian cancer cells and applied it to the phenotypic profiling of 54 anticancer compounds representing diverse mechanisms of action. Cells were exposed to compounds under short- and prolonged-treatment conditions, followed by multiplex fluorescent staining, high-content imaging, feature extraction using CellProfiler, and computational analysis of the resulting morphological profiles. Profiles obtained at the two treatment durations were analyzed separately. For each compound, the treatment condition showing greater within-compound consistency in PCA space was additionally retained to construct a combined dataset. Morphological relationships were explored using Pearson correlation analysis, dimensionality reduction, and unsupervised clustering. Morphological profiles showed reproducible relationships among compounds. Compounds with related mechanisms showed greater morphological similarity than expected by chance, although substantial within-class heterogeneity remained. Statistically significant cluster enrichment was observed for microtubule-targeting agents and topoisomerase inhibitors, whereas other mechanism-related patterns were incomplete. Among the evaluated clustering approaches, Leiden and agglomerative clustering produced similar separation of the Combined dataset, with silhouette scores of 0.486 and 0.482, respectively. Cell Painting identified mechanism-associated but heterogeneous morphological responses in OVCAR-3 cells. The results support the use of this model for exploratory phenotypic profiling while highlighting the influence of exposure conditions and the limited ability of morphology alone to recover annotated molecular mechanisms.

Indexed as

Antineoplastic AgentsOvarian NeoplasmsCell Line, TumorCluster AnalysisClustering AlgorithmsDrug Screening Assays, AntitumorFemaleHumansPhenotypeAntineoplastic Agentscell paintingmechanism of actionmorphological profilingovarian cancerOVCAR-3phenotypic screeningunsupervised clustering

Identifiers

PMID42884036
PMCPMC13664869

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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.