Matthews Izzy, Mehra Priyanka, Suárez-Calvet Xavier, Piñol-Jurado Patricia, Cox Dan, Justian Vellia, Carrasco-Rozas Ana, Laidler Zoe, Bowey Andrew, Rushton Paul, López-Fernández Susana, Díaz-Manera Jordi, Fernández-Simón Esther
John Walton Muscular Dystrophy Research Centre, Institute of Translational and Clinical Research, Newcastle University, Newcastle upon Tyne, United Kingdom.
Department of Comparative Biomedical Sciences, The Royal Veterinary College, London, United Kingdom.
Front Cell Dev Biol. 2025 Mar 26;13:1505697. doi: 10.3389/fcell.2025.1505697. eCollection 2025.
Understanding the cell functionality during disease progression or drugs' mechanism are major challenges for precision medicine. Predictive models describing biological phenotypes can be challenging to obtain, particularly in scenarios where sample availability is limited, such as in the case of rare diseases. Here we propose a new method that reproduces the fibroadipogenic expansion that occurs in muscle wasting.
We used immortalized fibroadipogenic progenitor cells (FAPs) and differentiated them into fibroblasts or adipocytes. The method successfully identified FAPs cell differentiation fate using accurate measurements of changes in specific proteins, which ultimately constitute a valid cellular platform for drug screening. Results were confirmed using primary FAPs differentiation as well as comparison with omics data from proteomics and genomic studies.
Our method allowed us to screen 508 different drugs from 2 compounds libraries. Out of these 508, we identified 4 compounds that reduced fibrogenesis and adipogenesis of ≥30% of fibrogenesis and adipogenesis using immortalized cells. After selecting the optimal dose of each compound, the inhibitory effect on FAP differentiation was confirmed by using primary FAPs from healthy subjects (n = 3) and DMD patients (n = 3). The final 4 selected hits reduced fibrogenic differentiation in healthy and DMD samples. The inhibition of adipogenesis was more evident in DMD samples than healthy samples. After creating an inhibitory map of the tested drugs, we validated the signalling pathways more involved in FAPs differentiation analysing data from proteomic and genomic studies.
We present a map of molecular targets of approved drugs that helps in predicting which therapeutic option may affect FAP differentiation. This method allows to study the potential effect of signalling circuits on FAP differentiation after drug treatment providing insights into molecular mechanism of action of muscle degeneration. The accuracy of the method is demonstrated by comparing the signal pathway activity obtained after drug treatment with proteomic and genomic data from patient-derived cells.
了解疾病进展过程中的细胞功能或药物作用机制是精准医学面临的主要挑战。描述生物学表型的预测模型难以获得，尤其是在样本可用性有限的情况下，例如罕见疾病。在此，我们提出一种新方法，该方法可重现肌肉萎缩中发生的纤维脂肪生成扩张。
我们使用永生化的纤维脂肪生成祖细胞（FAPs）并将其分化为成纤维细胞或脂肪细胞。该方法通过准确测量特定蛋白质的变化成功鉴定了FAPs细胞的分化命运，最终构成了一个有效的药物筛选细胞平台。使用原代FAPs分化以及与蛋白质组学和基因组研究的组学数据进行比较来确认结果。
我们的方法使我们能够从2个化合物库中筛选508种不同的药物。在这508种药物中，我们使用永生化细胞鉴定出4种化合物，它们可使纤维生成和脂肪生成减少≥30%。在选择每种化合物的最佳剂量后，通过使用来自健康受试者（n = 3）和杜氏肌营养不良症（DMD）患者（n = 3）的原代FAPs证实了对FAP分化的抑制作用。最终选择的4种药物在健康和DMD样本中均减少了纤维生成分化。脂肪生成的抑制在DMD样本中比健康样本中更明显。在创建测试药物的抑制图谱后，我们通过分析蛋白质组学和基因组研究的数据验证了更多参与FAPs分化的信号通路。
我们展示了已批准药物的分子靶点图谱，有助于预测哪种治疗选择可能影响FAP分化。该方法允许研究药物治疗后信号通路对FAP分化的潜在影响，从而深入了解肌肉退化的分子作用机制。通过将药物治疗后获得的信号通路活性与来自患者来源细胞的蛋白质组学和基因组数据进行比较，证明了该方法的准确性。
