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Genetic perturbation of IFN-α transcriptional modulators in human endothelial cells uncovers pivotal regulators of angiogenesis

Authors :
Francesco Ciccarese
Angela Grassi
Lorenza Pasqualini
Stefania Rosano
Alessio Noghero
Francesca Montenegro
Federico Bussolino
Barbara Di Camillo
Lorenzo Finesso
Gianna Maria Toffolo
Stefania Mitola
Stefano Indraccolo
Source :
Computational and Structural Biotechnology Journal, Vol 18, Iss , Pp 3977-3986 (2020)
Publication Year :
2020
Publisher :
Elsevier, 2020.

Abstract

Interferon-α (IFN-α) comprises a family of 13 cytokines involved in the modulation of antiviral, immune, and anticancer responses by orchestrating a complex transcriptional network. The activation of IFN-α signaling pathway in endothelial cells results in decreased proliferation and migration, ultimately leading to suppression of angiogenesis. In this study, we knocked-down the expression of seven established or candidate modulators of IFN-α response in endothelial cells to reconstruct a gene regulatory network and to investigate the antiangiogenic activity of IFN-α. This genetic perturbation approach, along with the analysis of interferon-induced gene expression dynamics, highlighted a complex and highly interconnected network, in which the angiostatic chemokine C-X-C Motif Chemokine Ligand 10 (CXCL10) was a central node targeted by multiple modulators. IFN-α-induced secretion of CXCL10 protein by endothelial cells was blunted by the silencing of Signal Transducer and Activator of Transcription 1 (STAT1) and of Interferon Regulatory Factor 1 (IRF1) and it was exacerbated by the silencing of Ubiquitin Specific Peptidase 18 (USP18). In vitro sprouting assay, which mimics in vivo angiogenesis, confirmed STAT1 as a positive modulator and USP18 as a negative modulator of IFN-α-mediated sprouting suppression. Our data reveal an unprecedented physiological regulation of angiogenesis in endothelial cells through a tonic IFN-α signaling, whose enhancement could represent a viable strategy to suppress tumor neoangiogenesis.

Details

Language :
English
ISSN :
20010370
Volume :
18
Issue :
3977-3986
Database :
Directory of Open Access Journals
Journal :
Computational and Structural Biotechnology Journal
Publication Type :
Academic Journal
Accession number :
edsdoj.0e760e3a921c49da8c90407d15d0df2a
Document Type :
article
Full Text :
https://doi.org/10.1016/j.csbj.2020.11.048