title: Ultra high content image analysis and phenotype profiling of 3D cultured micro-tissues.
abstract: In many situations, 3D cell cultures mimic the natural organization of tissues more closely than 2D cultures. Conventional methods for phenotyping such 3D cultures use either single or multiple simple parameters based on morphology and fluorescence staining intensity. However, due to their simplicity many details are not taken into account which limits system-level study of phenotype characteristics. Here, we have developed a new image analysis platform to automatically profile 3D cell phenotypes with 598 parameters including morphology, topology, and texture parameters such as wavelet and image moments. As proof of concept, we analyzed mouse breast cancer cells (4T1 cells) in a 384-well plate format following exposure to a diverse set of compounds at different concentrations. The result showed concentration dependent phenotypic trajectories for different biologically active compounds that could be used to classify compounds based on their biological target. To demonstrate the wider applicability of our method, we analyzed the phenotypes of a collection of 44 human breast cancer cell lines cultured in 3D and showed that our method correctly distinguished basal-A, basal-B, luminal and ERBB2+ cell lines in a supervised nearest neighbor classification method.
authors.affiliation: Division of Toxicology, Leiden Academic Center for Drug Research, Leiden University, Leiden, The Netherlands.
authors.forename: Zi
authors.initials: Z
authors.lastname: Di
authors.affiliation: OcellO B.V., Bio Partner Center Leiden, Leiden, The Netherlands.
authors.forename: Maarten J D
authors.initials: MJ
authors.lastname: Klop
authors.affiliation: Division of Toxicology, Leiden Academic Center for Drug Research, Leiden University, Leiden, The Netherlands.
authors.forename: Vasiliki-Maria
authors.initials: VM
authors.lastname: Rogkoti
authors.affiliation: Division of Toxicology, Leiden Academic Center for Drug Research, Leiden University, Leiden, The Netherlands.
authors.forename: Sylvia E
authors.initials: SE
authors.lastname: Le Dévédec
authors.affiliation: Division of Toxicology, Leiden Academic Center for Drug Research, Leiden University, Leiden, The Netherlands.
authors.forename: Bob
authors.initials: B
authors.lastname: van de Water
authors.affiliation: Imaging and BioInformatics, Leiden Institute of Advanced Computer Science, Leiden University, Leiden, The Netherlands.
authors.forename: Fons J
authors.initials: FJ
authors.lastname: Verbeek
authors.affiliation: Division of Toxicology, Leiden Academic Center for Drug Research, Leiden University, Leiden, The Netherlands; OcellO B.V., Bio Partner Center Leiden, Leiden, The Netherlands.
authors.forename: Leo S
authors.initials: LS
authors.lastname: Price
authors.affiliation: Division of Toxicology, Leiden Academic Center for Drug Research, Leiden University, Leiden, The Netherlands.
authors.forename: John H N
authors.initials: JH
authors.lastname: Meerman
mesh_terms: D000818:Animals; D000970:Antineoplastic Agents / Q000494:pharmacology*; D018929:Cell Culture Techniques; D045744:Cell Line, Tumor; D016503:Drug Delivery Systems; D004847:Epithelial Cells / Q000187:drug effects* / Q000378:metabolism / Q000473:pathology; D005260:Female; D006801:Humans; D007091:Image Processing, Computer-Assisted / Q000379:methods / Q000706:statistics & numerical data*; D021621:Imaging, Three-Dimensional; D008321:Mammary Glands, Animal / Q000187:drug effects / Q000378:metabolism / Q000473:pathology; D042361:Mammary Glands, Human / Q000187:drug effects / Q000378:metabolism / Q000473:pathology; D051379:Mice; D010641:Phenotype
chemical_list: D000970:Antineoplastic Agents