Data Mining of Atherosclerotic Plaque Transcriptomes Predicts STAT1-Dependent Inflammatory Signal Integration in Vascular Disease
AbstractAtherosclerotic plaque development involves multiple extra- and intra-cellular signals engaging cells from the immune system and from the vasculature. Pro-inflammatory pathways activated by interferon gamma (IFNγ) and toll-like receptor 4 (TLR4) ligands are profoundly involved in plaque formation and have been shown to involve cross-talk in all atheroma-interacting cell types leading to increased activation of signal transducer and activator of transcription-1 (STAT1) and elevated expression of pro-inflammatory mediators. Here we demonstrate that in Gene Expression Omnibus repository (GEO) deposited microarray datasets, obtained from human coronary and carotid atherosclerotic plaques, a significant increase in expression of pro-inflammatory and immunomodulatory genes can be detected. Moreover, increased expression of multiple chemokines, adhesion molecules and matrix-remodeling molecules was commonly detected in both plaque types and correlated with the presence of putative STAT1 binding sites in their promoters, suggesting strong involvement of STAT1 in plaque development. We also provide evidence to suggest that STAT1-nuclear factor kappa-light-chain-enhancer of activated B cells (NFκB) or STAT1-interferon-regulated factor (IRF) regulatory modules are over-represented in the promoters of these inflammatory genes, which points to a possible contribution of IFNγ and TLR4 cross-talk in the process of atherogenesis. Finally, a subset of these genes encodes for secreted proteins that could serve as a basis of a non-invasive diagnostic assay. The results of our in silico analysis in vitro provide potential evidence that STAT1-dependent IFNγ-TLR4 cross-talk plays a crucial role in coronary and carotid artery plaque development and identifies a STAT1-dependent gene signature that could represent a novel diagnostic tool to monitor and diagnose plaque progression in human atherosclerosis. View Full-Text
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Sikorski, K.; Wesoly, J.; Bluyssen, H.A.R. Data Mining of Atherosclerotic Plaque Transcriptomes Predicts STAT1-Dependent Inflammatory Signal Integration in Vascular Disease. Int. J. Mol. Sci. 2014, 15, 14313-14331.
Sikorski K, Wesoly J, Bluyssen HAR. Data Mining of Atherosclerotic Plaque Transcriptomes Predicts STAT1-Dependent Inflammatory Signal Integration in Vascular Disease. International Journal of Molecular Sciences. 2014; 15(8):14313-14331.Chicago/Turabian Style
Sikorski, Krzysztof; Wesoly, Joanna; Bluyssen, Hans A.R. 2014. "Data Mining of Atherosclerotic Plaque Transcriptomes Predicts STAT1-Dependent Inflammatory Signal Integration in Vascular Disease." Int. J. Mol. Sci. 15, no. 8: 14313-14331.