POS0382 RNA-SEQUENCING ANALYSIS TO IDENTIFY POTENTIAL FUNCTIONAL PATHWAYS INVOLVED IN SYSTEMIC SCLEROSIS PATHOGENESIS: OUR PRELIMINARY EXPERIENCE

Abstract

BackgroundSystemic Sclerosis (SSc) is a connective tissue disease, characterized by endothelial dysfunction, autoimmunity abnormalities and fibrosis of the skin and internal organs. The exact pathogenetic mechanisms that propagate SSc vasculopathy are still not completely understood. A complex network of interactions between endothelial cells, pericytes, myofibroblasts, and the extracellular matrix (ECM) has been implicated but it is currently unclear what drives the activation of fibroblasts and the increased ECM deposition responsible for the fibrotic changes well known in SSc.ObjectivesUsing RNA sequencing (RNA-seq), our goal was to identify potential functional pathways possibly involved in SSc pathogenesis and markers that could potentially be used to better understand endothelial dysfunction and fibrosis mechanisms in SSc patients.MethodsRNA-seq analysis was performed on RNA obtained from biopsies from 3 SSc patients and 3 age- and sex-matched healthy controls (HC) enrolled in our University Hospital between January 2019 and December 2020. The samples were transferred to a labelled cryovial and immediately stored in liquid nitrogen. RNA extraction followed standard methodologies. RNA from each sample was used to generate sequencing libraries that were sequenced according to proper transcriptomic analyses. To identify potential functional pathways that could be involved in SSc pathogenesis, we performed gene set enrichment analysis (GSEA) of differentially expressed genes (DEGs). GSEA was applied on the entire list of genes that compose the RNA-seq expression matrix. Genes were ranked based on their fold change calculated between groups of each pairwise comparison and analyzed by GSEA in pre-ranked mode. We adopted the “classic” enrichment statistic, the recommended approach for RNA-sequencing data.ResultsAccording to GSEA analysis of DEGs applied to SSc and HC, we identified 305 DEGs that were upregulated or downregulated at least 2-fold. In particular, 175 genes were upregulated and 130 genes were downregulated. A marked upregulation of genes involved in Wnt signaling, including Wnt family members, was present in HC if compared with SSc. The upregulation of collagen type VI, extracellular matrix protein 2, vascular endothelial growth factor D, among others, was also observed. Conversely, a marked downregulation of late cornified envelope and of genes encoding for keratins, was present in HC versus SSc samples. GSEA revealed that HC were characterized, among others, by gene signatures related to stromal stem cells proliferation, cytokine-cytokine receptor interaction, macrophage-enriched metabolic network, whereas SSc tissues were enriched in signatures related to keratinization, cornification, retinoblastoma (RB) 1 and tumour suppressor (TP) 53 signaling. Figure 1 displays GSEA in HC vs SSc tissues.Figure 1.GSEA in HC vs SSc tissues.Enrichment of gene signature was analyzed in transcriptomic data from HC and SSc samples.ES=enrichment score. NES=normalized enrichment score. FDR=false discovery rate.ConclusionAccording to our preliminary data, RNA-seq, differential gene expression and pathway analysis revealed that SSc patients show a discrete pattern of gene expression associated with keratinization, extracellular matrix generation, and negative regulation of angiogenesis and stromal stem cells proliferation. Further analysis on larger numbers of patients are needed; however, our results provide an interesting framework for the development of biomarkers representing vascular injury and fibrotic changes in SSc in order to explore potential future therapeutic targets.Disclosure of InterestsNone declared