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

Tirier, Stephan M.; Park, Jeongbin; Preußer, Friedrich; Amrhein, Lisa; Gu, Zuguang; Steiger, Simon; Mallm, Jan-Philipp; Krieger, Teresa; Waschow, Marcel; Eismann, Björn; Gut, Marta; Gut, Ivo Glynne; Rippe, Karsten; Schlesner, Matthias; Theis, Fabian; Fuchs, Christiane; Ball, Claudia R.; Glimm, Hanno; Eils, Roland; Conrad, Christian

doi:http://dx.doi.org/10.1038/s41598-019-48771-4

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

Citation

Tirier 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/s41598-019-48771-4

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.