Persistent fibrosis in multiple organs is the hallmark of systemic sclerosis (SSc). Recent genetic and genomic studies implicate TLRs and their damage-associated molecular pattern (DAMP) endogenous ligands in fibrosis. To test the hypothesis that TLR4 and its coreceptor myeloid differentiation 2 (MD2) drive fibrosis persistence, we measured MD2/TLR4 signaling in tissues from patients with fibrotic SSc, and we examined the impact of MD2 targeting using a potentially novel small molecule. Levels of MD2 and TLR4, and a TLR4-responsive gene signature, were enhanced in SSc skin biopsies. We developed a small molecule that selectively blocks MD2, which is uniquely required for TLR4 signaling. Targeting MD2/TLR4 abrogated inducible and constitutive myofibroblast transformation and matrix remodeling in fibroblast monolayers, as well as in 3-D scleroderma skin equivalents and human skin explants. Moreover, the selective TLR4 inhibitor prevented organ fibrosis in several preclinical disease models and mouse strains, and it reversed preexisting fibrosis. Fibroblast-specific deletion of TLR4 in mice afforded substantial protection from skin and lung fibrosis. By comparing experimentally generated fibroblast TLR4 gene signatures with SSc skin biopsy gene expression datasets, we identified a subset of SSc patients displaying an activated TLR4 signature. Together, results from these human and mouse studies implicate MD2/TLR4-dependent fibroblast activation as a key driver of persistent organ fibrosis. The results suggest that SSc patients with high TLR4 activity might show optimal therapeutic response to selective inhibitors of MD2/TLR4 complex formation.
Swati Bhattacharyya, Wenxia Wang, Wenyi Qin, Kui Cheng, Sara Coulup, Sherry Chavez, Shuangshang Jiang, Kirtee Raparia, Lucia Maria V. De Almeida, Christian Stehlik, Zenshiro Tamaki, Hang Yin, John Varga
Usage data is cumulative from May 2019 through May 2020.
Usage information is collected from two different sources: this site (JCI) and Pubmed Central (PMC). JCI information (compiled daily) shows human readership based on methods we employ to screen out robotic usage. PMC information (aggregated monthly) is also similarly screened of robotic usage.
Various methods are used to distinguish robotic usage. For example, Google automatically scans articles to add to its search index and identifies itself as robotic; other services might not clearly identify themselves as robotic, or they are new or unknown as robotic. Because this activity can be misinterpreted as human readership, data may be re-processed periodically to reflect an improved understanding of robotic activity. Because of these factors, readers should consider usage information illustrative but subject to change.