Tirier, Stephan M.Park, JeongbinPreußer, FriedrichAmrhein, LisaGu, ZuguangSteiger, SimonMallm, Jan-PhilippKrieger, TeresaWaschow, MarcelEismann, BjörnGut, MartaGut, Ivo GlynneRippe, KarstenSchlesner, MatthiasTheis, FabianFuchs, ChristianeBall, Claudia R.Glimm, HannoEils, RolandConrad, Christian2019-10-282019-10-282019Tirier SM, Park J, Preußer F, Amrhein L, Gu Z, Steiger S et al. Pheno-seq - linking visual features and gene expression in 3D cell culture systems. Sci Rep. 2019;9(1):12367. DOI: 10.1038/s41598-019-48771-42045-2322http://hdl.handle.net/10230/42533Patient-derived 3D cell culture systems are currently advancing cancer research since they potentiate the molecular analysis of tissue-like properties and drug response under well-defined conditions. However, our understanding of the relationship between the heterogeneity of morphological phenotypes and the underlying transcriptome is still limited. To address this issue, we here introduce "pheno-seq" to directly link visual features of 3D cell culture systems with profiling their transcriptome. As prototypic applications breast and colorectal cancer (CRC) spheroids were analyzed by pheno-seq. We identified characteristic gene expression signatures of epithelial-to-mesenchymal transition that are associated with invasive growth behavior of clonal breast cancer spheroids. Furthermore, we linked long-term proliferative capacity in a patient-derived model of CRC to a lowly abundant PROX1-positive cancer stem cell subtype. We anticipate that the ability to integrate transcriptome analysis and morphological patho-phenotypes of cancer cells will provide novel insight on the molecular origins of intratumor heterogeneity.application/pdfeng© The Author(s) 2019. Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons license, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons license and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this license, visit http://creativecommons.org/licenses/by/4.0/.info:eu-repo/semantics/articlehttp://dx.doi.org/10.1038/s41598-019-48771-4Cancer modelsFluorescence imagingTranscriptomicsinfo:eu-repo/semantics/openAccess