Pos0091 use of High-Plex Data Reveals Novel Insights Into the Temporal Artery of Giant Cell Arteritis

Abstract

BackgroundGiant cell arteritis (GCA) is the most common systemic vasculitis that triggers acute arterial occlusion and can even lead to death over the age of 50 [1]. While mechanism underlying GCA are predominantly derived from inflammatory response, none of the anti-inflammatory drugs currently used limit efficiently patient’s disease course. It was previously shown that histopathological lesions involve the three layers of the artery wall called adventitia, media, and intima. Activation of adventitial dendritic cells is the initial trigger of the vascular remodeling in GCA leading to intimal hyperplasia but the early molecular mechanism that activates those cells remains unknown. Our hypothesis is that each layer of the artery, perivascular tissue included, shows a unique transcriptomic signature which could define and explain the different molecular events in the inflammatory and vascular remodeling processes in GCA. For that, whole tissue spatial transcriptomics analysis offers advanced opportunities in elucidating functional mechanisms of pathologic tissues with complex organization such as GCA especially in human temporal artery, the most frequently affected artery in GCA.ObjectivesUncover the key coding genes to define new biomarkers or pathways associated with GCA by performing the firstin situspatial profiling characterization of molecular actors involved in temporal arteries from GCA patients in comparison to normal arteries.MethodsFrom human formalin-fixed paraffin-embedded temporal artery biopsy samples (GCA n=9; controls n=7), we performed a whole transcriptome analysis by using NanoString GeoMx Digital Spatial Profiler (DSP) [2]. A total of 59 individual regions of interest (ROIs) were created within each of the 4 layers for each individual artery. After ROIs collection and library construction, samples were sequenced on the Illumina NovaSeq 6000 platform and reads were digitally quantified and normalized using GeoMx DSP Data Analysis software. Differential expressed genes (DEGs) (fold change >2 or <-2, p-adjusted <0.05) were compared for each layer, to build a spatial and pharmacogenomic network in disease course.ResultsOverall, we found that most of the transcriptome studied (12076 genes) was upregulated in GCA arteries. Precisely, 350, 340, 142 and 5 DEGs were found in intima, media, adventitia, and perivascular tissue respectively. Enrichment analysis highlighted that inflammation/immune-related functions and vascular remodeling were significantly limited to intima and media layers. Upregulated immune-related functions concerned macrophage differentiation & T cell, B cell, complement activations. Regarding vascular remodeling pathways, we found an upregulation of: (i) collagen metabolic process and fibroblast proliferation concerning the 3 artery layers, (ii) angiogenesis & epithelial cell migration in intima and media layers, (iii) smooth muscle cell proliferation & ossification in intima layer. Our pharmacogenomic network analysis identified genes that could potentially be targeted by immunosuppressive drugs currently approved or new immunotherapies.ConclusionOur findings provide the firstin situspatial profiling characterization of molecular actors involved in GCA which is essential for the discovery of potential new therapeutic targets to cure this disease. The differential spatial upregulation of genes involved in inflammatory process and vascular remodeling suggests a differential chronological involvement of each layer of the artery.References[1]Weyand CM, Goronzy JJ. Clinical practice. Giant-cell arteritis and polymyalgia rheumatica. N Engl J Med. 2014 371:50-7.[2]Merritt CR, Ong GT, Church SE, Barker K, Danaher P, Geiss G,et al. Multiplex digital spatial profiling of proteins and RNA in fixed tissue. Nat Biotechnol. 2020 38:586-599.Acknowledgements:NIL.Disclosure of InterestsNone Declared.