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

Sci Rep. 2019 Aug 26;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.

Publication types

  • Research Support, Non-U.S. Gov't

MeSH terms

  • Breast Neoplasms / pathology
  • Cell Culture Techniques / methods*
  • Cell Line, Tumor
  • Cell Lineage / genetics
  • Cell Proliferation
  • Colorectal Neoplasms / genetics
  • Colorectal Neoplasms / pathology
  • Female
  • Gene Expression Regulation, Neoplastic*
  • Genes, Neoplasm
  • Humans
  • Neoplastic Stem Cells / pathology
  • Phenotype
  • Single-Cell Analysis