Single-Cell Transcriptome Atlas of Murine Endothelial Cells.

The heterogeneity of endothelial cells (ECs) across tissues remains incompletely inventoried. We constructed an atlas of >32,000 single-EC transcriptomes from 11 mouse tissues and identified 78 EC subclusters, including Aqp7+ intestinal capillaries and angiogenic ECs in healthy tissues. ECs from brain/testis, liver/spleen, small intestine/colon, and skeletal muscle/heart pairwise expressed partially overlapping marker genes. Arterial, venous, and lymphatic ECs shared more markers in more tissues than did heterogeneous capillary ECs. ECs from different vascular beds (arteries, capillaries, veins, lymphatics) exhibited transcriptome similarity across tissues, but the tissue (rather than the vessel) type contributed to the EC heterogeneity. Metabolic transcriptome analysis revealed a similar tissue-grouping phenomenon of ECs and heterogeneous metabolic gene signatures in ECs between tissues and between vascular beds within a single tissue in a tissue-type-dependent pattern. The EC atlas taxonomy enabled identification of EC subclusters in public scRNA-seq datasets and provides a powerful discovery tool and resource value.

Error modelled gene expression analysis (EMOGEA) provides a superior overview of time course RNA-seq measurements and low count gene expression.

Temporal RNA-sequencing (RNA-seq) studies of bulk samples provide an opportunity for improved understanding of gene regulation during dynamic phenomena such as development, tumor progression or response to an incremental dose of a pharmacotherapeutic. Moreover, single-cell RNA-seq (scRNA-seq) data implicitly exhibit temporal characteristics because gene expression values recapitulate dynamic processes such as cellular transitions. Unfortunately, temporal RNA-seq data continue to be analyzed by methods that ignore this ordinal structure and yield results that are often difficult to interpret. Here, we present Error Modelled Gene Expression Analysis (EMOGEA), a framework for analyzing RNA-seq data that incorporates measurement uncertainty, while introducing a special formulation for those acquired to monitor dynamic phenomena. This method is specifically suited for RNA-seq studies in which low-count transcripts with small-fold changes lead to significant biological effects. Such transcripts include genes involved in signaling and non-coding RNAs that inherently exhibit low levels of expression. Using simulation studies, we show that this framework down-weights samples that exhibit extreme responses such as batch effects allowing them to be modeled with the rest of the samples and maintain the degrees of freedom originally envisioned for a study. Using temporal experimental data, we demonstrate the framework by extracting a cascade of gene expression waves from a well-designed RNA-seq study of zebrafish embryogenesis and an scRNA-seq study of mouse pre-implantation and provide unique biological insights into the regulation of genes in each wave. For non-ordinal measurements, we show that EMOGEA has a much higher rate of true positive calls and a vanishingly small rate of false negative discoveries compared to common approaches. Finally, we provide two packages in Python and R that are self-contained and easy to use, including test data.

Identification of vascular cues contributing to cancer cell stemness and function.

Glioblastoma stem cells (GSCs) reside close to blood vessels (BVs) but vascular cues contributing to GSC stemness and the nature of GSC-BVs cross talk are not fully understood. Here, we dissected vascular cues influencing GSC gene expression and function to perfusion-based vascular cues, as well as to those requiring direct GSC-endothelial cell (EC) contacts. In light of our previous finding that perivascular tumor cells are metabolically different from tumor cells residing further downstream, cancer cells residing within a narrow, < 60 µm wide perivascular niche were isolated and confirmed to possess a superior tumor-initiation potential compared with those residing further downstream. To circumvent reliance on marker expression, perivascular GSCs were isolated from the respective locales based on their relative state of quiescence. Combined use of these procedures uncovered a large number of previously unrecognized differentially expressed GSC genes. We show that the unique metabolic milieu of the perivascular niche dominated by the highly restricted zone of mTOR activity is conducive for acquisition of GSC properties, primarily in the regulation of genes implicated in cell cycle control. A complementary role of vascular cues including those requiring direct glioma/EC contacts was revealed using glioma/EC co-cultures. Outstanding in the group of glioma cells impacted by nearby ECs were multiple genes responsible for maintaining GSCs in an undifferentiated state, a large fraction of which also relied on Notch-mediated signaling. Glioma-EC communication was found to be bidirectional, evidenced by extensive Notch-mediated EC reprogramming by contacting tumor cells, primarily metabolic EC reprogramming.

BIOMEX: an interactive workflow for (single cell) omics data interpretation and visualization.

The amount of biological data, generated with (single cell) omics technologies, is rapidly increasing, thereby exacerbating bottlenecks in the data analysis and interpretation of omics experiments. Data mining platforms that facilitate non-bioinformatician experimental scientists to analyze a wide range of experimental designs and data types can alleviate such bottlenecks, aiding in the exploration of (newly generated or publicly available) omics datasets. Here, we present BIOMEX, a browser-based software, designed to facilitate the Biological Interpretation Of Multi-omics EXperiments by bench scientists. BIOMEX integrates state-of-the-art statistical tools and field-tested algorithms into a flexible but well-defined workflow that accommodates metabolomics, transcriptomics, proteomics, mass cytometry and single cell data from different platforms and organisms. The BIOMEX workflow is accompanied by a manual and video tutorials that provide the necessary background to navigate the interface and get acquainted with the employed methods. BIOMEX guides the user through omics-tailored analyses, such as data pretreatment and normalization, dimensionality reduction, differential and enrichment analysis, pathway mapping, clustering, marker analysis, trajectory inference, meta-analysis and others. BIOMEX is fully interactive, allowing users to easily change parameters and generate customized plots exportable as high-quality publication-ready figures. BIOMEX is open source and freely available at https://www.vibcancer.be/software-tools/biomex.

EndoDB: a database of endothelial cell transcriptomics data.

Endothelial cells (ECs) line blood vessels, regulate homeostatic processes (blood flow, immune cell trafficking), but are also involved in many prevalent diseases. The increasing use of high-throughput technologies such as gene expression microarrays and (single cell) RNA sequencing generated a wealth of data on the molecular basis of EC (dys-)function. Extracting biological insight from these datasets is challenging for scientists who are not proficient in bioinformatics. To facilitate the re-use of publicly available EC transcriptomics data, we developed the endothelial database EndoDB, a web-accessible collection of expert curated, quality assured and pre-analyzed data collected from 360 datasets comprising a total of 4741 bulk and 5847 single cell endothelial transcriptomes from six different organisms. Unlike other added-value databases, EndoDB allows to easily retrieve and explore data of specific studies, determine under which conditions genes and pathways of interest are deregulated and assess reprogramming of metabolism via principal component analysis, differential gene expression analysis, gene set enrichment analysis, heatmaps and metabolic and transcription factor analysis, while single cell data are visualized as gene expression color-coded t-SNE plots. Plots and tables in EndoDB are customizable, downloadable and interactive. EndoDB is freely available at https://vibcancer.be/software-tools/endodb, and will be updated to include new studies.

Single-Cell RNA Sequencing Reveals Renal Endothelium Heterogeneity and Metabolic Adaptation to Water Deprivation.

BACKGROUND: Renal endothelial cells from glomerular, cortical, and medullary kidney compartments are exposed to different microenvironmental conditions and support specific kidney processes. However, the heterogeneous phenotypes of these cells remain incompletely inventoried. Osmotic homeostasis is vitally important for regulating cell volume and function, and in mammals, osmotic equilibrium is regulated through the countercurrent system in the renal medulla, where water exchange through endothelium occurs against an osmotic pressure gradient. Dehydration exposes medullary renal endothelial cells to extreme hyperosmolarity, and how these cells adapt to and survive in this hypertonic milieu is unknown. METHODS: We inventoried renal endothelial cell heterogeneity by single-cell RNA sequencing >40,000 mouse renal endothelial cells, and studied transcriptome changes during osmotic adaptation upon water deprivation. We validated our findings by immunostaining and functionally by targeting oxidative phosphorylation in a hyperosmolarity model in vitro and in dehydrated mice in vivo. RESULTS: We identified 24 renal endothelial cell phenotypes (of which eight were novel), highlighting extensive heterogeneity of these cells between and within the cortex, glomeruli, and medulla. In response to dehydration and hypertonicity, medullary renal endothelial cells upregulated the expression of genes involved in the hypoxia response, glycolysis, and-surprisingly-oxidative phosphorylation. Endothelial cells increased oxygen consumption when exposed to hyperosmolarity, whereas blocking oxidative phosphorylation compromised endothelial cell viability during hyperosmotic stress and impaired urine concentration during dehydration. CONCLUSIONS: This study provides a high-resolution atlas of the renal endothelium and highlights extensive renal endothelial cell phenotypic heterogeneity, as well as a previously unrecognized role of oxidative phosphorylation in the metabolic adaptation of medullary renal endothelial cells to water deprivation.

The gluconeogenesis enzyme PCK2 has a non-enzymatic role in proteostasis in endothelial cells.

Endothelial cells (ECs) are highly glycolytic, but whether they generate glycolytic intermediates via gluconeogenesis (GNG) in glucose-deprived conditions remains unknown. Here, we report that glucose-deprived ECs upregulate the GNG enzyme PCK2 and rely on a PCK2-dependent truncated GNG, whereby lactate and glutamine are used for the synthesis of lower glycolytic intermediates that enter the serine and glycerophospholipid biosynthesis pathways, which can play key roles in redox homeostasis and phospholipid synthesis, respectively. Unexpectedly, however, even in normal glucose conditions, and independent of its enzymatic activity, PCK2 silencing perturbs proteostasis, beyond its traditional GNG role. Indeed, PCK2-silenced ECs have an impaired unfolded protein response, leading to accumulation of misfolded proteins, which due to defective proteasomes and impaired autophagy, results in the accumulation of protein aggregates in lysosomes and EC demise. Ultimately, loss of PCK2 in ECs impaired vessel sprouting. This study identifies a role for PCK2 in proteostasis beyond GNG.

Single cell atlas identifies lipid-processing and immunomodulatory endothelial cells in healthy and malignant breast.

Since a detailed inventory of endothelial cell (EC) heterogeneity in breast cancer (BC) is lacking, here we perform single cell RNA-sequencing of 26,515 cells (including 8433 ECs) from 9 BC patients and compare them to published EC taxonomies from lung tumors. Angiogenic ECs are phenotypically similar, while other EC subtypes are different. Predictive interactome analysis reveals known but also previously unreported receptor-ligand interactions between ECs and immune cells, suggesting an involvement of breast EC subtypes in immune responses. We also identify a capillary EC subtype (LIPEC (Lipid Processing EC)), which expresses genes involved in lipid processing that are regulated by PPAR-γ and is more abundant in peri-tumoral breast tissue. Retrospective analysis of 4648 BC patients reveals that treatment with metformin (an indirect PPAR-γ signaling activator) provides long-lasting clinical benefit and is positively associated with LIPEC abundance. Our findings warrant further exploration of this LIPEC/PPAR-γ link for BC treatment.

Tumor vessel co-option probed by single-cell analysis.

Tumor vessel co-option is poorly understood, yet it is a resistance mechanism against anti-angiogenic therapy (AAT). The heterogeneity of co-opted endothelial cells (ECs) and pericytes, co-opting cancer and myeloid cells in tumors growing via vessel co-option, has not been investigated at the single-cell level. Here, we use a murine AAT-resistant lung tumor model, in which VEGF-targeting induces vessel co-option for continued growth. Single-cell RNA sequencing (scRNA-seq) of 31,964 cells reveals, unexpectedly, a largely similar transcriptome of co-opted tumor ECs (TECs) and pericytes as their healthy counterparts. Notably, we identify cell types that might contribute to vessel co-option, i.e., an invasive cancer-cell subtype, possibly assisted by a matrix-remodeling macrophage population, and another M1-like macrophage subtype, possibly involved in keeping or rendering vascular cells quiescent.

Single-Cell RNA Sequencing Maps Endothelial Metabolic Plasticity in Pathological Angiogenesis.

Endothelial cell (EC) metabolism is an emerging target for anti-angiogenic therapy in tumor angiogenesis and choroidal neovascularization (CNV), but little is known about individual EC metabolic transcriptomes. By single-cell RNA sequencing 28,337 murine choroidal ECs (CECs) and sprouting CNV-ECs, we constructed a taxonomy to characterize their heterogeneity. Comparison with murine lung tumor ECs (TECs) revealed congruent marker gene expression by distinct EC phenotypes across tissues and diseases, suggesting similar angiogenic mechanisms. Trajectory inference predicted that differentiation of venous to angiogenic ECs was accompanied by metabolic transcriptome plasticity. ECs displayed metabolic transcriptome heterogeneity during cell-cycle progression and in quiescence. Hypothesizing that conserved genes are important, we used an integrated analysis, based on congruent transcriptome analysis, CEC-tailored genome-scale metabolic modeling, and gene expression meta-analysis in cross-species datasets, followed by in vitro and in vivo validation, to identify SQLE and ALDH18A1 as previously unknown metabolic angiogenic targets.

An Integrated Gene Expression Landscape Profiling Approach to Identify Lung Tumor Endothelial Cell Heterogeneity and Angiogenic Candidates.

Heterogeneity of lung tumor endothelial cell (TEC) phenotypes across patients, species (human/mouse), and models (in vivo/in vitro) remains poorly inventoried at the single-cell level. We single-cell RNA (scRNA)-sequenced 56,771 endothelial cells from human/mouse (peri)-tumoral lung and cultured human lung TECs, and detected 17 known and 16 previously unrecognized phenotypes, including TECs putatively regulating immune surveillance. We resolved the canonical tip TECs into a known migratory tip and a putative basement-membrane remodeling breach phenotype. Tip TEC signatures correlated with patient survival, and tip/breach TECs were most sensitive to vascular endothelial growth factor blockade. Only tip TECs were congruent across species/models and shared conserved markers. Integrated analysis of the scRNA-sequenced data with orthogonal multi-omics and meta-analysis data across different human tumors, validated by functional analysis, identified collagen modification as a candidate angiogenic pathway.

Blockade of Myeloid-Derived Suppressor Cell Expansion with All-Trans Retinoic Acid Increases the Efficacy of Antiangiogenic Therapy.

Intrinsic and adaptive resistance hampers the success of antiangiogenic therapies (AAT), especially in breast cancer where this treatment modality has proven largely ineffective. Therefore, novel strategies to improve the efficacy of AAT are warranted. Solid tumors such as breast cancer are characterized by a high infiltration of myeloid-derived suppressor cells (MDSC), which are key drivers of resistance to AAT. Therefore, we hypothesized that all-trans retinoic acid (ATRA), which induces differentiation of MDSC into mature cells, could improve the therapeutic effect of AAT. ATRA increased the efficacy of anti-VEGFR2 antibodies alone and in combination with chemotherapy in preclinical breast cancer models. ATRA reverted the anti-VEGFR2-induced accumulation of intratumoral MDSC, alleviated hypoxia, and counteracted the disorganization of tumor microvessels. Mechanistic studies indicate that ATRA treatment blocked the AAT-induced expansion of MDSC secreting high levels of vessel-destabilizing S100A8. Thus, concomitant treatment with ATRA holds the potential to improve AAT in breast cancer and possibly other tumor types.Significance: Increasing the therapeutic efficiency of antiangiogenic drugs by reducing resistance-conferring myeloid-derived suppressor cells might improve breast cancer treatment.Graphical Abstract: http://cancerres.aacrjournals.org/content/canres/78/12/3220/F1.large.jpg Cancer Res; 78(12); 3220-32. ©2018 AACR.

Impairment of Angiogenesis by Fatty Acid Synthase Inhibition Involves mTOR Malonylation.

The role of fatty acid synthesis in endothelial cells (ECs) remains incompletely characterized. We report that fatty acid synthase knockdown (FASNKD) in ECs impedes vessel sprouting by reducing proliferation. Endothelial loss of FASN impaired angiogenesis in vivo, while FASN blockade reduced pathological ocular neovascularization, at >10-fold lower doses than used for anti-cancer treatment. Impaired angiogenesis was not due to energy stress, redox imbalance, or palmitate depletion. Rather, FASNKD elevated malonyl-CoA levels, causing malonylation (a post-translational modification) of mTOR at lysine 1218 (K1218). mTOR K-1218 malonylation impaired mTOR complex 1 (mTORC1) kinase activity, thereby reducing phosphorylation of downstream targets (p70S6K/4EBP1). Silencing acetyl-CoA carboxylase 1 (an enzyme producing malonyl-CoA) normalized malonyl-CoA levels and reactivated mTOR in FASNKD ECs. Mutagenesis unveiled the importance of mTOR K1218 malonylation for angiogenesis. This study unveils a novel role of FASN in metabolite signaling that contributes to explaining the anti-angiogenic effect of FASN blockade.

Quiescent Endothelial Cells Upregulate Fatty Acid ß-Oxidation for Vasculoprotection via Redox Homeostasis.

Little is known about the metabolism of quiescent endothelial cells (QECs). Nonetheless, when dysfunctional, QECs contribute to multiple diseases. Previously, we demonstrated that proliferating endothelial cells (PECs) use fatty acid ß-oxidation (FAO) for de novo dNTP synthesis. We report now that QECs are not hypometabolic, but upregulate FAO >3-fold higher than PECs, not to support biomass or energy production but to sustain the tricarboxylic acid cycle for redox homeostasis through NADPH regeneration. Hence, endothelial loss of FAO-controlling CPT1A in CPT1AΔEC mice promotes EC dysfunction (leukocyte infiltration, barrier disruption) by increasing endothelial oxidative stress, rendering CPT1AΔEC mice more susceptible to LPS and inflammatory bowel disease. Mechanistically, Notch1 orchestrates the use of FAO for redox balance in QECs. Supplementation of acetate (metabolized to acetyl-coenzyme A) restores endothelial quiescence and counters oxidative stress-mediated EC dysfunction in CPT1AΔEC mice, offering therapeutic opportunities. Thus, QECs use FAO for vasculoprotection against oxidative stress-prone exposure.