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An integrated gene expression landscape profiling approach to identify lung tumor endothelial cell heterogeneity and angiogenic candidates

(2020) CANCER CELL. 37(1). p.21-36.e13
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Abstract
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.
Keywords
R-PACKAGE, VESSEL NORMALIZATION, BIOCONDUCTOR PACKAGE, INHIBITION, CANCER, IDENTIFICATION, METASTASIS, MECHANISMS, COLLAGEN, REVEAL

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MLA
Goveia, Jermaine, et al. “An Integrated Gene Expression Landscape Profiling Approach to Identify Lung Tumor Endothelial Cell Heterogeneity and Angiogenic Candidates.” CANCER CELL, vol. 37, no. 1, 2020, pp. 21-36.e13, doi:10.1016/j.ccell.2019.12.001.
APA
Goveia, J., Rohlenova, K., Taverna, F., Treps, L., Conradi, L.-C., Pircher, A., … Carmeliet, P. (2020). An integrated gene expression landscape profiling approach to identify lung tumor endothelial cell heterogeneity and angiogenic candidates. CANCER CELL, 37(1), 21-36.e13. https://doi.org/10.1016/j.ccell.2019.12.001
Chicago author-date
Goveia, Jermaine, Katerina Rohlenova, Federico Taverna, Lucas Treps, Lena-Christin Conradi, Andreas Pircher, Vincent Geldhof, et al. 2020. “An Integrated Gene Expression Landscape Profiling Approach to Identify Lung Tumor Endothelial Cell Heterogeneity and Angiogenic Candidates.” CANCER CELL 37 (1): 21-36.e13. https://doi.org/10.1016/j.ccell.2019.12.001.
Chicago author-date (all authors)
Goveia, Jermaine, Katerina Rohlenova, Federico Taverna, Lucas Treps, Lena-Christin Conradi, Andreas Pircher, Vincent Geldhof, Laura P. M. H. de Rooij, Joanna Kalucka, Liliana Sokol, Melissa Garcia-Caballero, Yingfeng Zheng, Junbin Qian, Laure-Anne Teuwen, Shawez Khan, Bram Boeckx, Els Wauters, Herbert Decaluwe, Paul De Leyn, Johan Vansteenkiste, Birgit Weynand, Xavier Sagaert, Erik Verbeken, Albert Wolthuis, Baki Topal, Wouter Everaerts, Hanibal Bohnenberger, Alexander Emmert, Dena Panovska, Frederik De Smet, Frank J. T. Staal, Rene J. Mclaughlin, Francis Impens, Vincenzo Lagani, Stefan Vinckier, Massimiliano Mazzone, Luc Schoonjans, Mieke Dewerchin, Guy Eelen, Tobias K. Karakach, Huanming Yang, Jian Wang, Lars Bolund, Lin Lin, Bernard Thienpont, Xuri Li, Diether Lambrechts, Yonglun Luo, and Peter Carmeliet. 2020. “An Integrated Gene Expression Landscape Profiling Approach to Identify Lung Tumor Endothelial Cell Heterogeneity and Angiogenic Candidates.” CANCER CELL 37 (1): 21-36.e13. doi:10.1016/j.ccell.2019.12.001.
Vancouver
1.
Goveia J, Rohlenova K, Taverna F, Treps L, Conradi L-C, Pircher A, et al. An integrated gene expression landscape profiling approach to identify lung tumor endothelial cell heterogeneity and angiogenic candidates. CANCER CELL. 2020;37(1):21-36.e13.
IEEE
[1]
J. Goveia et al., “An integrated gene expression landscape profiling approach to identify lung tumor endothelial cell heterogeneity and angiogenic candidates,” CANCER CELL, vol. 37, no. 1, pp. 21-36.e13, 2020.
@article{8685015,
  abstract     = {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.},
  author       = {Goveia, Jermaine and Rohlenova, Katerina and Taverna, Federico and Treps, Lucas and Conradi, Lena-Christin and Pircher, Andreas and Geldhof, Vincent and de Rooij, Laura P. M. H. and Kalucka, Joanna and Sokol, Liliana and Garcia-Caballero, Melissa and Zheng, Yingfeng and Qian, Junbin and Teuwen, Laure-Anne and Khan, Shawez and Boeckx, Bram and Wauters, Els and Decaluwe, Herbert and De Leyn, Paul and Vansteenkiste, Johan and Weynand, Birgit and Sagaert, Xavier and Verbeken, Erik and Wolthuis, Albert and Topal, Baki and Everaerts, Wouter and Bohnenberger, Hanibal and Emmert, Alexander and Panovska, Dena and De Smet, Frederik and Staal, Frank J. T. and Mclaughlin, Rene J. and Impens, Francis and Lagani, Vincenzo and Vinckier, Stefan and Mazzone, Massimiliano and Schoonjans, Luc and Dewerchin, Mieke and Eelen, Guy and Karakach, Tobias K. and Yang, Huanming and Wang, Jian and Bolund, Lars and Lin, Lin and Thienpont, Bernard and Li, Xuri and Lambrechts, Diether and Luo, Yonglun and Carmeliet, Peter},
  issn         = {1535-6108},
  journal      = {CANCER CELL},
  keywords     = {R-PACKAGE,VESSEL NORMALIZATION,BIOCONDUCTOR PACKAGE,INHIBITION,CANCER,IDENTIFICATION,METASTASIS,MECHANISMS,COLLAGEN,REVEAL},
  language     = {eng},
  number       = {1},
  pages        = {21--36.e13},
  title        = {An integrated gene expression landscape profiling approach to identify lung tumor endothelial cell heterogeneity and angiogenic candidates},
  url          = {http://dx.doi.org/10.1016/j.ccell.2019.12.001},
  volume       = {37},
  year         = {2020},
}

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