Transcriptome-based deep learning analysis identifies drug candidates targeting protein synthesis and autophagy for the treatment of muscle wasting disorder.
Min Hak LeeBada LeeSe Eun ParkGa Eul YangSeungwoo CheonDae Hoon LeeSukyeong KangYe Ji SunYongjin KimDong-Sub JungWonwoo KimJihoon KangYi Rang KimJin Woo ChoiPublished in: Experimental & molecular medicine (2024)
Sarcopenia, the progressive decline in skeletal muscle mass and function, is observed in various conditions, including cancer and aging. The complex molecular biology of sarcopenia has posed challenges for the development of FDA-approved medications, which have mainly focused on dietary supplementation. Targeting a single gene may not be sufficient to address the broad range of processes involved in muscle loss. This study analyzed the gene expression signatures associated with cancer formation and 5-FU chemotherapy-induced muscle wasting. Our findings suggest that dimenhydrinate, a combination of 8-chlorotheophylline and diphenhydramine, is a potential therapeutic for sarcopenia. In vitro experiments demonstrated that dimenhydrinate promotes muscle progenitor cell proliferation through the phosphorylation of Nrf2 by 8-chlorotheophylline and promotes myotube formation through diphenhydramine-induced autophagy. Furthermore, in various in vivo sarcopenia models, dimenhydrinate induced rapid muscle tissue regeneration. It improved muscle regeneration in animals with Duchenne muscular dystrophy (DMD) and facilitated muscle and fat recovery in animals with chemotherapy-induced sarcopenia. As an FDA-approved drug, dimenhydrinate could be applied for sarcopenia treatment after a relatively short development period, providing hope for individuals suffering from this debilitating condition.
Keyphrases
- skeletal muscle
- duchenne muscular dystrophy
- gene expression
- chemotherapy induced
- deep learning
- genome wide
- stem cells
- oxidative stress
- signaling pathway
- community dwelling
- emergency department
- multiple sclerosis
- endoplasmic reticulum stress
- squamous cell carcinoma
- high glucose
- single cell
- rna seq
- artificial intelligence
- sensitive detection
- protein kinase