Prioritization and functional validation of target genes from single-cell transcriptomics studies.

Translation of academic results into clinical practice is a formidable unmet medical need. Single-cell RNA-sequencing (scRNA-seq) studies generate long descriptive ranks of markers with predicted biological function, but without functional validation, it remains challenging to know which markers truly exert the putative function. Given the lengthy/costly nature of validation studies, gene prioritization is required to select candidates. We address these issues by studying tip endothelial cell (EC) marker genes because of their importance for angiogenesis. Here, by tailoring Guidelines On Target Assessment for Innovative Therapeutics, we in silico prioritize previously unreported/poorly described, high-ranking tip EC markers. Notably, functional validation reveals that four of six candidates behave as tip EC genes. We even discover a tip EC function for a gene lacking in-depth functional annotation. Thus, validating prioritized genes from scRNA-seq studies offers opportunities for identifying targets to be considered for possible translation, but not all top-ranked scRNA-seq markers exert the predicted function.

The pulmonary vasculature in lethal COVID-19 and idiopathic pulmonary fibrosis at single-cell resolution.

AIMS: Severe acute respiratory syndrome coronavirus-2 infection causes COVID-19, which in severe cases evokes life-threatening acute respiratory distress syndrome (ARDS). Transcriptome signatures and the functional relevance of non-vascular cell types (e.g. immune and epithelial cells) in COVID-19 are becoming increasingly evident. However, despite its known contribution to vascular inflammation, recruitment/invasion of immune cells, vascular leakage, and perturbed haemostasis in the lungs of severe COVID-19 patients, an in-depth interrogation of the endothelial cell (EC) compartment in lethal COVID-19 is lacking. Moreover, progressive fibrotic lung disease represents one of the complications of COVID-19 pneumonia and ARDS. Analogous features between idiopathic pulmonary fibrosis (IPF) and COVID-19 suggest partial similarities in their pathophysiology, yet, a head-to-head comparison of pulmonary cell transcriptomes between both conditions has not been implemented to date. METHODS AND RESULTS: We performed single-nucleus RNA-sequencing on frozen lungs from 7 deceased COVID-19 patients, 6 IPF explant lungs, and 12 controls. The vascular fraction, comprising 38 794 nuclei, could be subclustered into 14 distinct EC subtypes. Non-vascular cell types, comprising 137 746 nuclei, were subclustered and used for EC-interactome analyses. Pulmonary ECs of deceased COVID-19 patients showed an enrichment of genes involved in cellular stress, as well as signatures suggestive of dampened immunomodulation and impaired vessel wall integrity. In addition, increased abundance of a population of systemic capillary and venous ECs was identified in COVID-19 and IPF. COVID-19 systemic ECs closely resembled their IPF counterparts, and a set of 30 genes was found congruently enriched in systemic ECs across studies. Receptor-ligand interaction analysis of ECs with non-vascular cell types in the pulmonary micro-environment revealed numerous previously unknown interactions specifically enriched/depleted in COVID-19 and/or IPF. CONCLUSIONS: This study uncovered novel insights into the abundance, expression patterns, and interactomes of EC subtypes in COVID-19 and IPF, relevant for future investigations into the progression and treatment of both lethal conditions.

Metabolic Reprogramming in Tumor Endothelial Cells.

The dynamic crosstalk between the different components of the tumor microenvironment is critical to determine cancer progression, metastatic dissemination, tumor immunity, and therapeutic responses. Angiogenesis is critical for tumor growth, and abnormal blood vessels contribute to hypoxia and acidosis in the tumor microenvironment. In this hostile environment, cancer and stromal cells have the ability to alter their metabolism in order to support the high energetic demands and favor rapid tumor proliferation. Recent advances have shown that tumor endothelial cell metabolism is reprogrammed, and that targeting endothelial metabolic pathways impacts developmental and pathological vessel sprouting. Therefore, the use of metabolic antiangiogenic therapies to normalize the blood vasculature, in combination with immunotherapies, offers a clinical niche to treat cancer.

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.

Protocols for endothelial cell isolation from mouse tissues: brain, choroid, lung, and muscle.

Endothelial cells (ECs) harbor distinct phenotypical and functional characteristics depending on their tissue localization and contribute to brain, eye, lung, and muscle diseases such as dementia, macular degeneration, pulmonary hypertension, and sarcopenia. To study their function, isolation of pure ECs in high quantities is crucial. Here, we describe protocols for rapid and reproducible blood vessel EC purification established for scRNA sequencing from murine tissues using mechanical and enzymatic digestion followed by magnetic and fluorescence-activated cell sorting. For complete details on the use and execution of these protocol, please refer to Kalucka et al. (2020), Rohlenova et al. (2020), and Goveia et al. (2020).

Protocols for endothelial cell isolation from mouse tissues: kidney, spleen, and testis.

Endothelial cells (ECs) exhibit phenotypic and functional tissue specificities, critical for studies in the vascular field and beyond. Thus, tissue-specific methods for isolation of highly purified ECs are necessary. Kidney, spleen, and testis ECs are relevant players in health and diseases such as chronic kidney disease, acute kidney injury, myelofibrosis, and cancer. Here, we provide tailored protocols for rapid and reproducible EC purification established for scRNA sequencing from these adult murine tissues using the combination of magnetic- and fluorescence-activated cell sorting. For complete details on the use and execution of these protocols, please refer to Kalucka et al. (2020) and Dumas et al. (2020).

Protocols for endothelial cell isolation from mouse tissues: small intestine, colon, heart, and liver.

Endothelial cells (ECs) from the small intestine, colon, liver, and heart have distinct phenotypes and functional adaptations that are dependent on their physiological environment. Gut ECs adapt to low oxygen, heart ECs to contractile forces, and liver ECs to low flow rates. Isolating high-purity ECs in sufficient quantities is crucial to study their functions. Here, we describe protocols combining magnetic and fluorescent activated cell sorting for rapid and reproducible EC purification from four adult murine tissues. For complete details on the use and execution of these protocols, please refer to Kalucka et al. (2020).

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.

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.

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.

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.