PD23-11 UNCOVERING THE GENETIC PATHWAYS OF PEYRONIE'S FIBROSIS: SINGLE CELL TRANSCRIPTOMIC ANALYSIS OF PEYRONIE'S PLAQUE

Field: Biochemistry, Genetics and Molecular Biology (Life Sciences)

You have accessJournal of UrologyCME1 May 2022PD23-11 UNCOVERING THE GENETIC PATHWAYS OF PEYRONIE'S FIBROSIS: SINGLE CELL TRANSCRIPTOMIC ANALYSIS OF PEYRONIE'S PLAQUE Luke Witherspoon, Reza Soltani, Meghan Robinson, Faraz Hach, and Ryan Flannigan Luke WitherspoonLuke Witherspoon More articles by this author , Reza SoltaniReza Soltani More articles by this author , Meghan RobinsonMeghan Robinson More articles by this author , Faraz HachFaraz Hach More articles by this author , and Ryan FlanniganRyan Flannigan More articles by this author View All Author Informationhttps://doi.org/10.1097/JU.0000000000002565.11AboutPDF ToolsAdd to favoritesDownload CitationsTrack CitationsPermissionsReprints ShareFacebookLinked InTwitterEmail Abstract INTRODUCTION AND OBJECTIVE: The mechanisms behind the pathogenesis of Peyronie’s disease largely remain a mystery. Single-cell transcriptomics provides a new means to assess the genetic expression profiles occurring on a cell-by-cell basis within a Peyronie’s plaque. This study set out to use single-cell RNA sequencing to investigate the transcriptional pathways involved in Peyronie’s disease. METHODS: Tunica albuginea biopsy was performed in a patient undergoing penile incision and grafting surgery. Cells were explanted from biopsy tissue and propagated. Peyronie’s plaque derived cells were then exposed to transforming growth factor beta(TGF-beta). RNA-seq single cell sequencing was then completed at 0 and 24 hours. We used principle component analysis (PCA) to reduce the dimension of data and built the nearest-neighbors graph using PCA weights. We performed clustering over the nearest-neighbor graphs and visualized the clusters using UMAP. Differential gene expression analyses were performed using the top 50 genes with increased expression between time points. RESULTS: Assessment of cell clustering identified several potential cell populations that became more clearly defined following administration of TGF-beta (Figure 1). Known gene expression profiles of fibroblasts, myofibroblasts, and smooth muscle were applied to our cluster analysis and did not localize to specific cell cluster populations suggesting myofibroblasts were largely present at both time points. Differential gene expression showed that genes involved in cellular binding and catalytic activity were most commonly upregulated (Figure 2). CONCLUSIONS: This analysis provides insight into the expression profiles of Peyronie’s plaque cell populations stimulated via TGF-beta to activate myofibroblasts akin to the active phase of Peyronie’s disease. Source of Funding: None © 2022 by American Urological Association Education and Research, Inc.FiguresReferencesRelatedDetails Volume 207Issue Supplement 5May 2022Page: e413 Advertisement Copyright & Permissions© 2022 by American Urological Association Education and Research, Inc.MetricsAuthor Information Luke Witherspoon More articles by this author Reza Soltani More articles by this author Meghan Robinson More articles by this author Faraz Hach More articles by this author Ryan Flannigan More articles by this author Expand All Advertisement PDF downloadLoading ...