Pheno-seq – linking visual features and gene expression in 3D cell culture systems

Tirier SM, Park J, Preusser F, Amrhein L, Gu Z, Steiger S, Mallm JP, Krieger T, Waschow M, Eismann B, Gut M, Gut IG, Rippe K, Schlesner M, Theis F, Fuchs C, Ball CR, Glimm H, Eils R, Conrad C (2019)

Publication Type: Journal article

Publication year: 2019

Journal

Scientific Reports Nature Publishing Group: Open Access Journals - Option B

Book Volume: 9

Article Number: 12367

Journal Issue: 1

DOI: 10.1038/s41598-019-48771-4

Abstract

Patient-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.

Involved external institutions

Ruprecht-Karls-Universität Heidelberg DE Germany (DE) Charité - Universitätsmedizin Berlin DE Germany (DE) Helmholtz Zentrum München - Deutsches Forschungszentrum für Gesundheit und Umwelt (HMGU) / Helmholtz Munich DE Germany (DE) Deutsches Krebsforschungszentrum (DKFZ) DE Germany (DE) Autonomous University of Barcelona (UAB) / Universitat Autònoma de Barcelona ES Spain (ES) Technische Universität Dresden DE Germany (DE)

How to cite

APA:

Tirier, S.M., Park, J., Preusser, F., Amrhein, L., Gu, Z., Steiger, S.,... Conrad, C. (2019). Pheno-seq – linking visual features and gene expression in 3D cell culture systems. Scientific Reports, 9(1). https://doi.org/10.1038/s41598-019-48771-4

MLA:

Tirier, Stephan M., et al. "Pheno-seq – linking visual features and gene expression in 3D cell culture systems." Scientific Reports 9.1 (2019).

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