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Transcriptomic Analysis of Complex Tissue Microenvironments

Abstract

Single cell RNA-Sequencing is a powerful technique to analyze the transcriptomic landscape of cells. Here we present two distinct in vitro systems (3D in vitro vascular networks in fibrin hydrogels; ex vivo organoid model of colorectal liver metastasis) and apply single cell RNA-Sequencing in order to better understand the extent of cellular heterogeneity in these 2 systems. For the 3D in vitro vascular network work, we are motivated by the fact that endothelial cells line all major blood vessels and serve as integral regulators of many functions including vessel diameter, cellular trafficking, and transport of soluble mediators. Despite similar functions, the phenotype of endothelial cells is highly organ-specific, yet our understanding of the mechanisms leading to organ-level differentiation is incomplete. We generated 3D vascular networks by combining a common naïve endothelial cell with six different stromal cells derived from the lung, skin, heart, bone marrow, pancreas, and pancreatic cancer. Single cell RNA-Seq analysis of the vascular networks reveals five distinct endothelial cell populations, for which the relative proportion depends on the stromal cell population. Morphologic features of the organotypic vessel networks inversely correlate with a cluster of endothelial cells associated with protein synthesis. The organotypic stromal cells were each characterized by a unique subpopulation of cells dedicated to extracellular matrix organization and assembly. Finally, compared to cells in 2D monolayer, the endothelial cell transcriptome from the 3D in vitro skin and lung vascular networks shows a closer match to the in vivo endothelial cells from the respective organs. We conclude that stromal cells contribute to endothelial cell and vascular network organ tropism, and create an endothelial cell phenotype that more closely resembles that present in vivo. For the colorectal liver metastasis work, we are motivated by the fact that colorectal cancer is a leading cause of cancer-related death in the United States. A significant proportion of colorectal cancer cases present liver metastases at some point during the course of disease, with limited treatment options for these liver metastases. In order to better understand the liver metastases and their response to treatment, it is necessary to develop a robust model of these liver metastases. We generated a patient-matched ex vivo organoid model of colorectal cancer liver metastases and compared this organoid model to parental tumor samples using single cell RNA-Seq. Parental tumor samples have a rich diversity of cell types, whereas the organoid sample contains only epithelial cells. Additionally, we identify 3 sub-populations of epithelial cells with distinct transcriptomic profiles that are present in different amounts between the parental and organoid samples. We conclude that there is transcriptomic drift from the in vivo parental sample to the ex vivo organoid sample, which manifest in phenotypic drift between these samples. In both in vitro systems outlined above, single cell RNA-Seq is a powerful technique to understand both emergent cellular heterogeneity within the in vitro samples and transcriptomic differences between in vitro and in vivo tissues.

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