Systematic Analysis of the Transcriptome Profiles and Co-Expression Networks of Tumour Endothelial Cells Identifies Several Tumour-Associated Modules and Potential Therapeutic Targets in Hepatocellular Carcinoma

Hepatocellular carcinoma (HCC) is the sixth most common cancer and the third most common cause of cancer-related death, with tumour associated liver endothelial cells being thought to be major drivers in HCC progression. This study aims to compare the gene expression profiles of tumour endothelial cells from the liver with endothelial cells from non-tumour liver tissue, to identify perturbed biologic functions, co-expression modules, and potentially drugable hub genes that could give rise to novel therapeutic targets and strategies. Gene Set Variation Analysis (GSVA) showed that cell growth-related pathways were upregulated, whereas apoptosis induction, immune and inflammatory-related pathways were downregulated in tumour endothelial cells. Weighted Gene Co-expression Network Analysis (WGCNA) identified several modules strongly associated to tumour endothelial cells or angiogenic activated endothelial cells with high endoglin (ENG) expression. In tumour cells, upregulated modules were associated with cell growth, cell proliferation, and DNA-replication, whereas downregulated modules were involved in immune functions, particularly complement activation. In ENG+ cells, upregulated modules were associated with cell adhesion and endothelial functions. One downregulated module was associated with immune system-related functions. Querying the STRING database revealed known functional-interaction networks underlying the modules. Several possible hub genes were identified, of which some (for example FEN1, BIRC5, NEK2, CDKN3, and TTK) are potentially druggable as determined by querying the Drug Gene Interaction database. In summary, our study provides a detailed picture of the transcriptomic differences between tumour and non-tumour endothelium in the liver on a co-expression network level, indicates several potential therapeutic targets and presents an analysis workflow that can be easily adapted to other projects

Systematic Identification of Cell-Cell Communication Networks in the Developing Brain

Since the generation of cell-type specific knockout models, the importance of inter-cellular communication between neural, vascular, and microglial cells during neural development has been increasingly appreciated. However, the extent of communication between these major cell populations remains to be systematically mapped. Here, we describe EMBRACE (embryonic brain cell extraction using FACS), a method to simultaneously isolate neural, mural, endothelial, and microglial cells to more than 94% purity in ∼4 h. Utilizing EMBRACE we isolate, transcriptionally analyze, and build a cell-cell communication map of the developing mouse brain. We identify 1,710 unique ligand-receptor interactions between neural, endothelial, mural, and microglial cells in silico and experimentally confirm the APOE-LDLR, APOE-LRP1, VTN-KDR, and LAMA4-ITGB1 interactions in the E14.5 brain. We provide our data via the searchable “Brain interactome explorer”, available at https://mpi-ie.shinyapps.io/braininteractomeexplorer/. Together, this study provides a comprehensive map that reveals the richness of communication within the developing brain

Functionally heterogeneous human satellite cells identified by single cell RNA sequencing.

Although heterogeneity is recognized within the murine satellite cell pool, a comprehensive understanding of distinct subpopulations and their functional relevance in human satellite cells is lacking. We used a combination of single cell RNA sequencing and flow cytometry to identify, distinguish, and physically separate novel subpopulations of human PAX7+ satellite cells (Hu-MuSCs) from normal muscles. We found that, although relatively homogeneous compared to activated satellite cells and committed progenitors, the Hu-MuSC pool contains clusters of transcriptionally distinct cells with consistency across human individuals. New surface marker combinations were enriched in transcriptional subclusters, including a subpopulation of Hu-MuSCs marked by CXCR4/CD29/CD56/CAV1 (CAV1+). In vitro, CAV1+ Hu-MuSCs are morphologically distinct, and characterized by resistance to activation compared to CAV1- Hu-MuSCs. In vivo, CAV1+ Hu-MuSCs demonstrated increased engraftment after transplantation. Our findings provide a comprehensive transcriptional view of normal Hu-MuSCs and describe new heterogeneity, enabling separation of functionally distinct human satellite cell subpopulations

Hepatic macrophage responses in inflammation, a function of plasticity, heterogeneity or both?

peer-reviewedWith the increasing availability and accessibility of single cell technologies, much attention has been given to delineating the specific populations of cells present in any given tissue. In recent years, hepatic macrophage heterogeneity has also begun to be examined using these strategies. While previously any macrophage in the liver was considered to be a Kupffer cell (KC), several studies have recently revealed the presence of distinct subsets ofhepatic macrophages, including those distinct from KCs both under homeostatic and non-homeostatic conditions. This heterogeneity has brought the concept of macrophage plasticity into question. Are KCs really as plastic as once thought, being capable of responding efficiently and specifically to any given stimuli? Or are the differential responses observed from hepatic macrophages in distinct settings due to the presence of multiple subsets of these cells? With these questions in mind, here we examine what is currently understood regarding hepatic macrophage heterogeneity in mouse and human and examine the role of heterogeneity vs plasticity in regards to hepatic macrophage responses in settings of both pathogen-induced and sterile inflammation

A human liver cell atlas reveals heterogeneity and epithelial progenitors

Antonio Saviano and Sagar contributed equally.International audienceThe human liver is an essential multifunctional organ. The incidence of liver diseases is rising and there are limited treatment options. However, the cellular composition of the liver remains poorly understood. Here we performed single-cell RNA sequencing of about 10,000 cells from normal liver tissue from nine human donors to construct a human liver cell atlas. Our analysis identified previously unknown subtypes of endothelial cells, Kupffer cells, and hepatocytes, with transcriptome-wide zonation of some of these populations. We show that the EPCAM+ population is heterogeneous, comprising hepatocyte-biased and cholangiocyte populations as well as a TROP2int progenitor population with strong potential to form bipotent liver organoids. As a proof-of-principle, we used our atlas to unravel the phenotypic changes that occur in hepatocellular carcinoma cells and in human hepatocytes and liver endothelial cells engrafted into a mouse liver. Our human liver cell atlas provides a powerful resource to enable the discovery of previously unknown cell types in normal and diseased livers