Investigation of niclosamide as a repurposing agent for skeletal muscle atrophy

Advancements in Drug Delivery Systems for the Treatment of Sarcopenia: An Updated Overview

Since sarcopenia is a progressive condition that leads to decreased muscle mass and function, especially in elderly people, it is a public health problem that requires attention from researchers. This review aims to highlight drug delivery systems that have a high and efficient therapeutic potential for sarcopenia. Current as well as future research needs to consider the barriers encountered in the realization of delivery systems, such as the route of administration, the interaction of the systems with the aggressive environment of the human body, the efficient delivery and loading of the systems with therapeutic agents, and the targeted delivery of therapeutic agents into the muscle tissue without creating undesirable adverse effects. Thus, this paper sets the framework of existing drug delivery possibilities for the treatment of sarcopenia, serving as an inception point for future interdisciplinary studies.

Bioinformatics and systems biology approaches to identify potential common pathogeneses for sarcopenia and osteoarthritis

Sarcopenia, a geriatric syndrome characterized by progressive loss of muscle mass and strength, and osteoarthritis, a common degenerative joint disease, are both prevalent in elderly individuals. However, the relationship and molecular mechanisms underlying these two diseases have not been fully elucidated. In this study, we screened microarray data from the Gene Expression Omnibus to identify associations between sarcopenia and osteoarthritis. We employed multiple statistical methods and bioinformatics tools to analyze the shared DEGs (differentially expressed genes). Additionally, we identified 8 hub genes through functional enrichment analysis, protein-protein interaction analysis, transcription factor-gene interaction network analysis, and TF-miRNA coregulatory network analysis. We also discovered potential shared pathways between the two diseases, such as transcriptional misregulation in cancer, the FOXO signalling pathway, and endometrial cancer. Furthermore, based on common DEGs, we found that strophanthidin may be an optimal drug for treating sarcopenia and osteoarthritis, as indicated by the Drug Signatures database. Immune infiltration analysis was also performed on the sarcopenia and osteoarthritis datasets. Finally, receiver operating characteristic (ROC) curves were plotted to verify the reliability of our results. Our findings provide a theoretical foundation for future research on the potential common pathogenesis and molecular mechanisms of sarcopenia and osteoarthritis.

Inhibiting 5-lipoxygenase prevents skeletal muscle atrophy by targeting organogenesis signalling and insulin-like growth factor-1

BACKGROUND

Skeletal muscle atrophy can occur in response to numerous factors, such as ageing and certain medications, and produces a major socio-economic burden. At present, there are no approved drugs for treating skeletal muscle atrophy. Arachidonate 5-lipoxygenase (Alox5) is a drug target for a number of diseases. However, pharmacological targeting of Alox5, and its role in skeletal muscle atrophy, is unclear.

METHODS

The potential effects of gene knockdown and pharmacological targeting of Alox5 on skeletal muscle atrophy were investigated using cell-based models, animal models and human skeletal muscle primary cells. Malotilate, a clinically safe drug developed for enhancing liver regeneration and Alox5 inhibitor, was investigated as a repurposing candidate. Mechanism(s) of action in skeletal muscle atrophy was assessed by measuring the expression level or activation status of key regulatory pathways and validated using gene knockdown and RNA sequencing.

RESULTS

Myotubes treated with the atrophy-inducing glucocorticoid, dexamethasone, were protected from catabolic responses by treatment with malotilate (+41.29%, P < 0.01). Similar anti-atrophy effects were achieved by gene knockdown of Alox5 (+30.4%, P < 0.05). Malotilate produced anti-atrophy effects without affecting the myogenic differentiation programme. In an in vivo model of skeletal muscle atrophy, malotilate treatment preserved muscle force/strength (grip strength: +35.72%, latency to fall: +553.1%, P < 0.05), increased mass and fibre cross-sectional area (quadriceps: +23.72%, soleus: +33.3%, P < 0.01) and down-regulated atrogene expression (Atrogin-1: -61.58%, Murf-1: -66.06%, P < 0.01). Similar, beneficial effects of malotilate treatment were observed in an ageing muscle model, which also showed the preservation of fast-twitch fibres (Type 2a: +56.48%, Type 2b: +37.32%, P < 0.01). Leukotriene B4, a product of Alox5 activity with inflammatory and catabolic functions, was found to be elevated in skeletal muscle undergoing atrophy (quadriceps: +224.4%, P < 0.001). Cellular transcriptome analysis showed that targeting Alox5 up-regulated biological processes regulating organogenesis and increased the expression of insulin-like growth factor-1, a key anti-atrophy hormone (+226.5%, P < 0.05). Interestingly, these effects were restricted to the atrophy condition and not observed in normal skeletal muscle cultures with Alox5 inhibition. Human myotubes were also protected from atrophy by pharmacological targeting of Alox5 (+23.68%, P < 0.05).

CONCLUSIONS

These results shed new light on novel drug targets and mechanisms underpinning skeletal muscle atrophy. Alox5 is a regulator and drug target for muscle atrophy, and malotilate is an attractive compound for repurposing studies to treat this disease.

Muscle and Bone Defects in Metastatic Disease

PURPOSE OF REVIEW

The present review addresses most recently identified mechanisms implicated in metastasis-induced bone resorption and muscle-wasting syndrome, known as cachexia.

RECENT FINDINGS

Metastatic disease in bone and soft tissues is often associated with skeletal muscle defects. Recent studies have identified a number of secreted molecules and extracellular vesicles that contribute to cancer cell growth and metastasis leading to bone destruction and muscle atrophy. In addition, alterations in muscle microenvironment including dysfunctions in hepatic and mitochondrial metabolism have been implicated in cancer-induced regeneration defect and muscle loss. Moreover, we review novel in vitro and animal models including promising new drug candidates for bone metastases and cancer cachexia. Preservation of bone health could be highly beneficial for maintaining muscle mass and function. Therefore, a better understanding of molecular pathways implicated in bone and muscle crosstalk in metastatic disease may provide new insights and identify new strategies to improve current anticancer therapeutics.

Detection of Target Genes for Drug Repurposing to Treat Skeletal Muscle Atrophy in Mice Flown in Spaceflight

Skeletal muscle atrophy is a common condition in aging, diabetes, and in long duration spaceflights due to microgravity. This article investigates multi-modal gene disease and disease drug networks via link prediction algorithms to select drugs for repurposing to treat skeletal muscle atrophy. Key target genes that cause muscle atrophy in the left and right extensor digitorum longus muscle tissue, gastrocnemius, quadriceps, and the left and right soleus muscles are detected using graph theoretic network analysis, by mining the transcriptomic datasets collected from mice flown in spaceflight made available by GeneLab. We identified the top muscle atrophy gene regulators by the Pearson correlation and Bayesian Markov blanket method. The gene disease knowledge graph was constructed using the scalable precision medicine knowledge engine. We computed node embeddings, random walk measures from the networks. Graph convolutional networks, graph neural networks, random forest, and gradient boosting methods were trained using the embeddings, network features for predicting links and ranking top gene-disease associations for skeletal muscle atrophy. Drugs were selected and a disease drug knowledge graph was constructed. Link prediction methods were applied to the disease drug networks to identify top ranked drugs for therapeutic treatment of skeletal muscle atrophy. The graph convolution network performs best in link prediction based on receiver operating characteristic curves and prediction accuracies. The key genes involved in skeletal muscle atrophy are associated with metabolic and neurodegenerative diseases. The drugs selected for repurposing using the graph convolution network method were nutrients, corticosteroids, anti-inflammatory medications, and others related to insulin.