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DOI 10.1038/s12276-024-01189-z

Медицинская библиотека · Experimental & molecular medicine · 2024

Transcriptome-based deep learning analysis identifies drug candidates targeting protein synthesis and autophagy for the treatment of muscle wasting disorder.

Lee Min Hak, Lee Bada, Park Se Eun, Yang Ga Eul, Cheon Seungwoo, Lee Dae Hoon, Kang Sukyeong, Sun Ye Ji, Kim Yongjin, Jung Dong-Sub, Kim Wonwoo, Kang Jihoon, Kim Yi Rang, Choi Jin Woo

СтатьяПоддержка исследования: вне правительства СШАПеревод в очереди

Аннотация

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.

Для цитирования: Lee Min Hak, Lee Bada, Park Se Eun, Yang Ga Eul, Cheon Seungwoo, Lee Dae Hoon, Kang Sukyeong, Sun Ye Ji, Kim Yongjin, Jung Dong-Sub, Kim Wonwoo, Kang Jihoon, Kim Yi Rang, Choi Jin Woo. Transcriptome-based deep learning analysis identifies drug candidates targeting protein synthesis and autophagy for the treatment of muscle wasting disorder.. Experimental & molecular medicine. 2024. DOI: 10.1038/s12276-024-01189-z.

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