ArticleBMC systems biology2012
Computational gene network analysis reveals TNF-induced angiogenesis.
Article in BMC systems biology, 2012. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers.
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Who cites it
7 citing papers in PubMed, 27 citations in OpenAlex.
- Esaxerenone Inhibits Renal Angiogenesis and Endothelial-Mesenchymal Transition via the VEGFA and TGF-β1 Pathways in Aldosterone-Infused Mice.International journal of molecular sciences · 2023Article
- The anti-angiogenesis mechanism of Geniposide on rheumatoid arthritis is related to the regulation of PTEN.Inflammopharmacology · 2022Article
- Intracellular and Intercellular Gene Regulatory Network Inference From Time-Course Individual RNA-Seq.Frontiers in bioinformatics · 2021Article
- The pathogenic role of angiogenesis in rheumatoid arthritis.Angiogenesis · 2015Review
- Identification of molecular sub-networks associated with cell survival in a chronically SIVmac-infected human CD4+ T cell line.Virology journal · 2014Article
- Expression of interleukine-8 as an independent prognostic factor for sporadic colon cancer dissemination.Journal of medicine and life · 2014Article
- Angiogenesis-related biomarkers in patients with alcoholic liver disease: their association with liver disease complications and outcome.Mediators of inflammation · 2014Article
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Authors and funding
7 authors at 2 institutions in 2 countries.
Funding
No grant is acknowledged in the PubMed record.
Abstract
backgroundTNF (Tumor Necrosis Factor-α) induces HUVEC (Human Umbilical Vein Endothelial Cells) to proliferate and form new blood vessels. This TNF-induced angiogenesis plays a key role in cancer and rheumatic disease. However, the molecular system that underlies TNF-induced angiogenesis is largely unknown.
methodsWe analyzed the gene expression changes stimulated by TNF in HUVEC over a time course using microarrays to reveal the molecular system underlying TNF-induced angiogenesis. Traditional k-means clustering analysis was performed to identify informative temporal gene expression patterns buried in the time course data. Functional enrichment analysis using DAVID was then performed for each cluster. The genes that belonged to informative clusters were then used as the input for gene network analysis using a Bayesian network and nonparametric regression method. Based on this TNF-induced gene network, we searched for sub-networks related to angiogenesis by integrating existing biological knowledge.
resultsk-means clustering of the TNF stimulated time course microarray gene expression data, followed by functional enrichment analysis identified three biologically informative clusters related to apoptosis, cellular proliferation and angiogenesis. These three clusters included 648 genes in total, which were used to estimate dynamic Bayesian networks. Based on the estimated TNF-induced gene networks, we hypothesized that a sub-network including IL6 and IL8 inhibits apoptosis and promotes TNF-induced angiogenesis. More particularly, IL6 promotes TNF-induced angiogenesis by inducing NF-κB and IL8, which are strong cell growth factors.
conclusionsComputational gene network analysis revealed a novel molecular system that may play an important role in the TNF-induced angiogenesis seen in cancer and rheumatic disease. This analysis suggests that Bayesian network analysis linked to functional annotation may be a powerful tool to provide insight into disease.
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