Chemogenomic Screening in a Patient-Derived 3D Fatty Liver Disease Model Reveals the CHRM1-TRPM8 Axis as a Novel Module for Targeted Intervention

患者来源的 3D 脂肪肝疾病模型中的化学基因组学筛选揭示了 CHRM1-TRPM8 轴作为靶向干预的新模块

阅读:6
作者:Sonia Youhanna, Aurino M Kemas, Shane C Wright, Yi Zhong, Britta Klumpp, Kathrin Klein, Aikaterini Motso, Maurice Michel, Nicole Ziegler, Mingmei Shang, Pierre Sabatier, Aimo Kannt, Hongda Sheng, Nuria Oliva-Vilarnau, Florian A Büttner, Brinton Seashore-Ludlow, Jonas Schreiner, Maike Windbergs, Mart

Abstract

Metabolic dysfunction-associated steatohepatitis (MASH) is a leading cause of chronic liver disease with few therapeutic options. To narrow the translational gap in the development of pharmacological MASH treatments, a 3D liver model from primary human hepatocytes and non-parenchymal cells derived from patients with histologically confirmed MASH was established. The model closely mirrors disease-relevant endpoints, such as steatosis, inflammation and fibrosis, and multi-omics analyses show excellent alignment with biopsy data from 306 MASH patients and 77 controls. By combining high-content imaging with scalable biochemical assays and chemogenomic screening, multiple novel targets with anti-steatotic, anti-inflammatory, and anti-fibrotic effects are identified. Among these, activation of the muscarinic M1 receptor (CHRM1) and inhibition of the TRPM8 cation channel result in strong anti-fibrotic effects, which are confirmed using orthogonal genetic assays. Strikingly, using biosensors based on bioluminescence resonance energy transfer, a functional interaction along a novel MASH signaling axis in which CHRM1 inhibits TRPM8 via Gq/11 and phospholipase C-mediated depletion of phosphatidylinositol 4,5-bisphosphate can be demonstrated. Combined, this study presents the first patient-derived 3D MASH model, identifies a novel signaling module with anti-fibrotic effects, and highlights the potential of organotypic culture systems for phenotype-based chemogenomic drug target identification at scale.

特别声明

1、本页面内容包含部分的内容是基于公开信息的合理引用;引用内容仅为补充信息,不代表本站立场。

2、若认为本页面引用内容涉及侵权,请及时与本站联系,我们将第一时间处理。

3、其他媒体/个人如需使用本页面原创内容,需注明“来源:[生知库]”并获得授权;使用引用内容的,需自行联系原作者获得许可。

4、投稿及合作请联系:info@biocloudy.com。