Strategy for drug repurposing in fibroadipogenic replacement during muscle wasting: application to duchenne muscular...

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 in vitro 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.