Dataset Information

An integrated approach to profile lung tumor endothelial cell heterogeneity across species and models and to identify angiogenic candidates

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

INSTRUMENT(S): Q Exactive HF

ORGANISM(S): Homo Sapiens (human)

TISSUE(S): Lung, Colon, Endothelial Cell, Kidney

DISEASE(S): Lung Cancer,Colorectal Cancer,Kidney Cancer

SUBMITTER: Delphi Van Haver

LAB HEAD: Peter Carmeliet

PROVIDER: PXD014123 | Pride | 2021-07-07

REPOSITORIES: Pride

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Publications

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

Goveia Jermaine J Rohlenova Katerina K Taverna Federico F Treps Lucas L Conradi Lena-Christin LC Pircher Andreas A Geldhof Vincent V de Rooij Laura P M H LPMH Kalucka Joanna J Sokol Liliana L García-Caballero Melissa M Zheng Yingfeng Y Qian Junbin J Teuwen Laure-Anne LA Khan Shawez S Boeckx Bram B Wauters Els E Decaluwé Herbert H De Leyn Paul P Vansteenkiste Johan J Weynand Birgit B Sagaert Xavier X Verbeken Erik E Wolthuis Albert A Topal Baki B Everaerts Wouter W Bohnenberger Hanibal H Emmert Alexander A Panovska Dena D De Smet Frederik F Staal Frank J T FJT Mclaughlin Rene J RJ Impens Francis F Lagani Vincenzo V Vinckier Stefan S Mazzone Massimiliano M Schoonjans Luc L Dewerchin Mieke M Eelen Guy G Karakach Tobias K TK Yang Huanming H Wang Jian J Bolund Lars L Lin Lin L Thienpont Bernard B Li Xuri X Lambrechts Diether D Luo Yonglun Y Carmeliet Peter P

Cancer cell 20200101 1

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 a ...[more]

PMID: 31935371

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Project description:Purpose: In all vertebrates, the thymus is necessary and sufficient for production of classic adaptive T cells. The key components of the thymus are cortical and medullary thymic epithelial cells (cTECs and mTECs). Despite the capital role of TECs, our understanding of TEC biology is quite rudimentary. For instance, we ignore what might be the extent of divergence in the functional program of these two TECs populations. It also remains unclear why the number of TECs decreases rapidly with age, thereby leading to progressive thymic insufficiency. Methods: Systems level understanding of cell function begins with gene expression profiling, and the transcriptome is currently the only '-ome' that can be reliably tackled in its entirety in freshly harvested primary cells. In order to gain novel insights into TEC biology, we therefore decided to analyse the whole transcriptome of cTECs, mTECs and skin epithelial cells. We elected to analyse gene expression using RNA-seq rather microarrays because RNA-seq has higher sensitivity and dynamic range coupled to lower technical variations. Results: Our deep sequencing approach provides a unique perspective into the transcriptome of TECs. Consistent with their ability to express ectopic genes, we found that mTECs expressed more genes than other cell populations. Out of a total of 15,069 genes expressed in TECs, 25% were differentially expressed by at least 5-fold in cTECs vs. mTECs. Genes expressed at higher levels in cTECs than mTECs regulate numerous cell functions including cell differentiation, cell movement and microtubule dynamics. Almost all positive regulators of the cell cycle were overexpressed in skin ECs relative to TECs. Conclusions: Our RNA-seq data provide novel insights into the transcriptional landscape of TECs, highlight substantial divergences in the transcriptome of TEC subsets and suggest that cell cycle progression is differentially regulated in TECS and skinECs. We believe that our work will therefore represent a valuable resource and will be of great interest to readers working in biological sciences, particularly in the areas of immunology and systems biology. The mRNA profiles of cTEC, mTEC (from 14 thymi of 7-days old C57BL/6 mice) and skinEC (from the trunk and dorsum of seven newborn mice) were generated by RNA-sequencing using Illumina HiSeq2000.

Dataset Information

An integrated approach to profile lung tumor endothelial cell heterogeneity across species and models and to identify angiogenic candidates

Publications

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

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