细胞生物学
纤维化
细胞外基质
癌症研究
病理
医学
生物
作者
Xiaojuan Dai,Ying Sun,Lingying Ma,Jun Hou,Li Wang,Yu Gong,Xiaoning Sun,Sifan Wu,Sheng Wang,Zongfei Ji,Huiyong Chen,Lili Ma,Lindi Jiang,Xiufang Kong
标识
DOI:10.1016/j.trsl.2022.12.004
摘要
Abstract
Takayasu arteritis (TAK) is a chronic large vessel disease characterized by aortic fibrotic thickening, which was mainly mediated by activation of aorta adventitial fibroblasts (AAFs). Our previous genetic study demonstrated that TAK-associated locus IL6 rs2069837 regulated glycoprotein non-metastatic melanoma protein B (GPNMB) expression. Thus, this study aimed to investigate the pathogenic role of GPNMB in TAK. Through pathological staining, we find that GPNMB was mainly expressed in vascular adventitia and positively correlated with adventitial extracellular matrix (ECM) expression in TAK vascular lesion. Specifically, GPNMB was increased in adventitial CD68+ macrophages, which were closely located with CD90+ adventitial fibroblasts. In in-vitro cell culture, THP-1-derived macrophages with GPNMB overexpression promoted ECM expression in AAFs. This effect was also confirmed in aortic tissue or AAFs culture with GPNMB overexpression or active GPNMB protein stimulation. Mechanistically, Co-IP assay and siRNA or inhibitor intervention demonstrated that integrin αVβ1 receptor mediated GPNMB effect on AAFs, which also activated downstream Akt and Erk pathway in AAFs. Furthermore, we showed that leflunomide treatment inhibited GPNMB-mediated fibrosis in AAFs, as well as GPNMB expression in macrophages, which were also partially validated in leflunomide-treated patients. Taken together, these data indicated that macrophage-derived GPNMB promotes AAFs ECM expression via the integrin αVβ1 receptor and Akt/Erk signaling pathway and leflunomide might play an anti-fibrotic role in TAK by interfering with the macrophage-derived GPNMB/AAFs axis. This study provides evidence that targeting GPNMB is a potential therapeutic strategy for treating vascular fibrosis in TAK.
科研通智能强力驱动
Strongly Powered by AbleSci AI