Document Type

Article

Publication Date

10-14-2021

Comments

This article is the author’s final published version in Scientific Reports, Volume 11, Issue 1, October 2021, Article number 20435.

The published version is available at https://doi.org/10.1038/s41598-021-99292-y. Copyright © Abignano et al.

Abstract

Myofibroblasts are the key effector cells responsible for the exaggerated tissue fibrosis in Systemic Sclerosis (SSc). Despite their importance to SSc pathogenesis, the specific transcriptome of SSc myofibroblasts has not been described. The purpose of this study was to identify transcriptome differences between SSc myofibroblasts and non-myofibroblastic cells. Alpha smooth muscle actin (α-SMA) expressing myofibroblasts and α-SMA negative cells were isolated employing laser capture microdissection from dermal cell cultures from four patients with diffuse SSc of recent onset. Total mRNA was extracted from both cell populations, amplified and analyzed employing microarrays. Results for specific genes were validated by Western blots and by immunohistochemistry. Transcriptome analysis revealed 97 differentially expressed transcripts in SSc myofibroblasts compared with non-myofibroblasts. Annotation clustering of the SSc myofibroblast-specific transcripts failed to show a TGF-β signature. The most represented transcripts corresponded to several different genes from the Neuroblastoma Breakpoint Family (NBPF) of genes. NBPF genes are highly expanded in humans but are not present in murine or rat genomes. In vitro studies employing cultured SSc dermal fibroblasts and immunohistochemistry of affected SSc skin confirmed increased NBPF expression in SSc. These results indicate that SSc myofibroblasts represent a unique cell lineage expressing a specific transcriptome that includes very high levels of transcripts corresponding to numerous NBPF genes. Elevated expression of NBPF genes in SSc myofibroblasts suggests that NBPF gene products may play a role in SSc pathogenesis and may represent a novel therapeutic target.

Creative Commons License

Creative Commons License
This work is licensed under a Creative Commons Attribution 4.0 License.

PubMed ID

34650102

Language

English

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