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Positional influence on cellular transcriptional identity revealed through spatially segmented single-cell transcriptomics

ABSTRACT: Single-cell RNA-sequencing (scRNA-seq) is a powerful technique for describing cell states. Unfortunately, identifying the spatial arrangement of these states in tissues remains challenging. Here, we describe SEgmentation by Exogenous Perfusion (SEEP), a rapid and integrated method to link positional location to transcriptional identity within three-dimensional (3D) disease models. The method utilizes the steady-state diffusion kinetics of a fluorescent dye to establish a gradient along the radial axis of 3D disease models. Classification of sample layers based on dye accessibility permits dissociated and sorted cells to be retrospectively characterized by transcriptomic and regional identity. Using SEEP, we analyze spheroid, organoid, and in vivo tumor models of high grade serous ovarian cancer (HGSOC). The results validate long-standing beliefs regarding the relationship between cell state and position while also revealing new concepts on how the spatially unique microenvironment of individual cells within tumors influences cell identity.

ORGANISM(S): Mus musculus Homo sapiens

PROVIDER: GSE157299 | GEO | 2020/10/11

REPOSITORIES: GEO

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Project description:The traditional method for studying cancer in vitro is to grow immortalized cancer cells in two-dimensional (2D) monolayers on plastic. However, many cellular features are impaired in these unnatural conditions and big alterations in gene expression in comparison to tumors have been reported. Three-dimensional (3D) cell culture models have become increasingly popular and are suggested to be better models than 2D monolayers due to improved cell-to-cell contacts and structures that resemble in vivo architecture. The aim of this study was to develop a simple high-throughput 3D drug screening method and to compare drug responses in JIMT1 breast cancer cells when grown in 2D, in polyHEMA coated anchorage independent 3D models and in Matrigel on-top 3D cell culture models. We screened 102 compounds with multiple concentrations and biological replicates for their effects on cell proliferation. The cells were either treated immediately upon plating or they were allowed to grow in 3D for four days prior to the drug treatment. Big variations in drug responses were observed between the models indicating that comparisons of culture model influenced drug sensitivities cannot be made based on effects of a single drug. However, we show with the 63 most prominent drugs that, in general, JIMT1 cells grown on Matrigel were significantly more sensitive to drugs than cells grown in 2D cultures, while responses of cells grown in polyHEMA resembled those of 2D. Furthermore, comparison of gene expression profiles of the cell culture models to xenograft tumors indicated that cells cultured in Matrigel and as xenografts most closely resembled each other. In this study we also suggest that 3D cultures can provide a platform for systematic experimentation of larger compound collections in a high-throughput mode and be used as alternatives for traditional 2D screens towards better comparability to in vivo state. Gene expression analysis of JIMT1 breast cancer cells cultured as xenografts for 43 days, in two dimensional cultures for seven days (2D7d), in polyHEMA three dimensional cell culture models for four and seven days (PH7d and PH7d), and in Matrigel three dimensional cultures for four and seven days (MG4d and MG7d). Two biological replicates was included for each sample.

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Positional influence on cellular transcriptional identity revealed through spatially segmented single-cell transcriptomics

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