Abstract
Vascular Endothelial Growth Factor-A (VEGFA) signaling is crucial to the cellular processes involved in angiogenesis. Previously, we assembled a network of molecular reactions induced by VEGFA in human umbilical vein endothelial cell populations. Considering transcriptome as a read-out of the transcriptional and epigenomic regulatory network, we now present an analysis of VEGFA-induced temporal transcriptome datasets from 6 non-synchronized studies. From these datasets, applying a confidence criterion, a set of early VEGFA-responsive signature genes were derived and evaluated for their co-expression potential with respect to multiple cancer gene expression datasets. Further, inclusive of a set of ligand-receptor pairs, a list of ligand and receptor signaling systems that potentially fine-tune the endothelial cell functions subsequent to VEGFA signaling were also derived. We believe that a number of these signaling systems would concurrently and/or hierarchically fine-tune the signaling network of endothelial cell populations towards the processes associated with angiogenesis through autocrine, paracrine, juxtacrine, and matricrine modes. By further analysis of published literature on VEGFA signaling, we also present an improved update-version of our previous VEGFA signaling network model in endothelial cells as a platform for analysis of cross-talk with these signaling systems.
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Abbreviations
- DEGs:
-
Differentially Expressed Genes
- EC:
-
Endothelial cell
- EGF:
-
Epidermal Growth Factor
- ENA:
-
European Nucleotide Archive
- FC:
-
Fold Change
- FGF:
-
Fibroblast Growth Factor
- GEO:
-
Gene Expression Omnibus
- GO:
-
Gene Ontology
- HUVECs:
-
Human Umbilical Vein Endothelial Cells
- MMP:
-
Matrix MetalloProteinase
- PTMs:
-
Post Translational Modifications
- TF:
-
Transcription Factor
- TGF-beta:
-
Transforming Growth Factor-beta
- VCAM:
-
Vascular Cell Adhesion Molecule
- VEGFA:
-
Vascular Endothelial Growth Factor-A
- VEGFR:
-
Vascular Endothelial Growth Factor Receptor
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Acknowledgements
The authors acknowledge the Campus Computing Facility (CCF) at the Central Laboratory for Instrumentation and Facilitation, University of Kerala for providing the HPC cluster facility to carry out this research work. The authors also acknowledge the AICADD, SIUCEB and DBT-BIF support at the Department of Computational Biology & Bioinformatics, University of Kerala, India for extending the necessary facilities to carry out this research work. PRS is a receipient of Asutosh Mookerjee Fellowship of ISCA. RR is a recipient of the SERB Young Scientist award (YSS/2014/000607) from Department of Science and Technology (DST), India.
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Supplementary Figure 1
Representation of the overlap of the genes across the 6 temporal studies. Total number of DEGs obtained from each of the 6 temporal studies and the overlapping DEGs across the 6 non-synchronized studies is represented as a Venn diagram using the jvenn tool (http://jvenn.toulouse.inra.fr/). (PDF 137 kb)
Supplementary Figure 2
DEGs upregulated in 3 or more temporal datasets from distinct studies. Alluvial diagram (https://app.rawgraphs.io/) represents individual DEGs that are up-regulated in 3 or more temporal datasets across 6 temporal studies along with the information on the timepoints of stimulation with VEGFA, number of distinct temporal datasets with the overlap and the study datasets. (PDF 109 kb)
Supplementary Figure 3
Network of ligands, receptors, and kinases induced by VEGFA in ECs. An interaction network based on the interaction data from the STRING database comprising of 124 receptors, 31 ligands of the 48 ligand-receptor pairs and the 65 kinases (including the receptor-kinases among 124 receptors) transcriptionally modulated by VEGFA together from all the temporal datasets is represented using the Cytoscape v3.7.1 tool (https://cytoscape.org/). The purple color nodes represent kinases, pink nodes are the receptors with kinase activity, orange nodes are receptors and green nodes represent 31 ligands within the 48 ligand-receptor pairs. (PDF 520 kb)
Supplementary Table 1
Supplementary Table 1A: Information on the datasets chosen and analyzed in this study. Supplementary Table 1B: Comparison of the VEGFA responsive DEGs with the genes prior associated to angiogenesis by GO annotation. Supplementary Table 1C: DEGs common to the Human Angiogenesis RT2 Profiler™ PCR Array profile by Qiagen. (PDF 128 kb)
Supplementary Table 2
DEGs across multiple temporal datasets categorized into early, intermediate and late time frames. (XLSX 3019 kb)
Supplementary Table 3
GO biological process and KEGG-pathway enrichment analysis of the categorized DEGs within the early, intermediate and late time frames. (XLSX 50 kb)
Supplementary Table 4
List of ligands and receptors in the VEGFA-induced DEGs across temporal datasets. (PDF 229 kb)
Supplementary Table 4A
List of ligand-receptor pairs in the VEGFA-induced DEGs across temporal datasets. (XLSX 15 kb)
Supplementary Table 5
List of all proteins in the update version of the VEGFA/VEGFR2 pathway map along with there experimentally characterized reactions such as molecular associations, catalysis, transport, phosphosite regulations and direct/indirect activation/inhibition reactions. Though, all the DEGs analyzed in this study are transcriptionally regulated genes of VEGFA in endothelial cells, the DEGs experimentally identified to be regulated by any of the transcription factors or specific signaling modules in this network model are currently represented. (XLS 172 kb)
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Sunitha, P., Raju, R., Sajil, C.K. et al. Temporal VEGFA responsive genes in HUVECs: Gene signatures and potential ligands/receptors fine-tuning angiogenesis. J. Cell Commun. Signal. 13, 561–571 (2019). https://doi.org/10.1007/s12079-019-00541-7
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DOI: https://doi.org/10.1007/s12079-019-00541-7