GSE115487
CXCL4 links inflammation and fibrosis through transcriptional and epigenetic reprogramming of inflammatory monocyte-derived cells [RNA-seq]
Fibrosis is a condition shared by numerous inflammatory diseases. The molecular mechanisms underlying fibrosis have remained incompletely understood severely hampering drug development. CXCL4 is associated with the onset and extent of fibrosis development in systemic sclerosis (SSc), a prototypic inflammatory and fibrotic disease. Here, we integrated 65 paired sequential whole genome transcriptional and methylation profiles from monocyte-derived cells as they respond to CXCL4 exposure. Using data-driven gene regulatory network analyses, we demonstrate that CXCL4 dramatically alters monocyte differentiation trajectory inducing a novel pro-inflammatory and pro-fibrotic phenotype mediated via key regulators such as CIITA and IRF8. Importantly, these CXCL4 exposed pro-inflammatory cells trigger a fibrosis cascade by directly producing ECM molecules and by inducing myofibroblast differentiation. Underscoring the computationally identified gene regulatory network, inhibition of CIITA mimicked CXCL4 inducing pro-inflammatory and pro-fibrotic phenotype. Our study uncovers CXCL4 as the endogenous ligand driving innate immune training and forming the long-sought link between inflammation and fibrosis. Correspondence to: Prof. Timothy RDJ Radstake (T.R.D.J.Radstake@umcutrecht.nl) and Dr. Aridaman Pandit (A.Pandit@umcutrecht.nl) Overall design: Monocytes were collected from 5 healthy donors. To systematically study the effects of CXCL4 on cell differentiation, we obtained sequential RNA-seq profiles at day 0 (monocytes), day 2, 4, and 6, for monocyte differentiation into both moDCs and CXCL4-moDCs. To further study the effects of CXCL4 on cell maturation, at day 7 moDCs were stimulated with the toll-like receptor 3 ligand polyI:C. The transcriptional profiles at day 7 (before stimulation), 4 hours and 24 hours (day 8) after stimulation were studied(Fig. 1A).  In total, we obtained 65 samples for RNA-seq.