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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 G; Rippe, Karsten; Schlesner, Matthias; Theis, Fabian; Fuchs, Christiane; Ball, Claudia R; Glimm, Hanno; Eils, Roland; Conrad, Christian.
Afiliación
  • Tirier SM; Center for Quantitative Analysis of Molecular and Cellular Biosystems (BioQuant), University of Heidelberg, Heidelberg, Germany.
  • Park J; Division of Theoretical Bioinformatics, German Cancer Research Center (DKFZ), Heidelberg, Germany.
  • Preußer F; Division of Chromatin Networks, German Cancer Research Center (DKFZ), Heidelberg, Germany.
  • Amrhein L; Digital Health Center, Berlin Institute of Health (BIH)/Charité-Universitätsmedizin Berlin, Berlin, Germany.
  • Gu Z; Division of Theoretical Bioinformatics, German Cancer Research Center (DKFZ), Heidelberg, Germany.
  • Steiger S; Center for Quantitative Analysis of Molecular and Cellular Biosystems (BioQuant), University of Heidelberg, Heidelberg, Germany.
  • Mallm JP; Division of Theoretical Bioinformatics, German Cancer Research Center (DKFZ), Heidelberg, Germany.
  • Krieger T; Max Delbrück Center for Molecular Medicine, Berlin Institute for Medical Systems Biology, Berlin, Germany.
  • Waschow M; Helmholtz Zentrum München - German Research Center for Environmental Health, Institute of Computational Biology, Munich, Neuherberg, Germany.
  • Eismann B; Department of Mathematics, Technische Universität München, Munich, Germany.
  • Gut M; Division of Theoretical Bioinformatics, German Cancer Research Center (DKFZ), Heidelberg, Germany.
  • Gut IG; Heidelberg Center for Personalized Oncology, DKFZ-HIPO, DKFZ, Heidelberg, Germany.
  • Rippe K; Center for Quantitative Analysis of Molecular and Cellular Biosystems (BioQuant), University of Heidelberg, Heidelberg, Germany.
  • Schlesner M; Division of Theoretical Bioinformatics, German Cancer Research Center (DKFZ), Heidelberg, Germany.
  • Theis F; Center for Quantitative Analysis of Molecular and Cellular Biosystems (BioQuant), University of Heidelberg, Heidelberg, Germany.
  • Fuchs C; Division of Chromatin Networks, German Cancer Research Center (DKFZ), Heidelberg, Germany.
  • Ball CR; Heidelberg Center for Personalized Oncology, DKFZ-HIPO, DKFZ, Heidelberg, Germany.
  • Glimm H; Digital Health Center, Berlin Institute of Health (BIH)/Charité-Universitätsmedizin Berlin, Berlin, Germany.
  • Eils R; Center for Quantitative Analysis of Molecular and Cellular Biosystems (BioQuant), University of Heidelberg, Heidelberg, Germany.
  • Conrad C; Division of Theoretical Bioinformatics, German Cancer Research Center (DKFZ), Heidelberg, Germany.
Sci Rep ; 9(1): 12367, 2019 08 26.
Article en En | MEDLINE | ID: mdl-31451731
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.
Asunto(s)

Texto completo: 1 Base de datos: MEDLINE Asunto principal: Regulación Neoplásica de la Expresión Génica / Técnicas de Cultivo de Célula Tipo de estudio: Prognostic_studies Idioma: En Revista: Sci Rep Año: 2019 Tipo del documento: Article

Texto completo: 1 Base de datos: MEDLINE Asunto principal: Regulación Neoplásica de la Expresión Génica / Técnicas de Cultivo de Célula Tipo de estudio: Prognostic_studies Idioma: En Revista: Sci Rep Año: 2019 Tipo del documento: Article