ReviewJournal of molecular medicine (Berlin, Germany)2024
Exploiting the therapeutic potential of contracting skeletal muscle-released extracellular vesicles in cancer: Current insights and future directions.
Review in Journal of molecular medicine (Berlin, Germany), 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 8 papers.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
8 citing papers in PubMed, 12 citations in OpenAlex.
- Review
- Exercise-Induced Extracellular Vesicles as Mediators of Mitochondrial Biogenesis and Insulin Sensitivity in Metabolic Adaptation.Endocrinology, diabetes & metabolism · 2026Review
- Role of irisin in physical activity, sarcopenia-associated type 2 diabetes, and cardiovascular complications.World journal of methodology · 2025Review
- Article
- Review
- From sweat to hope: The role of exercise-induced extracellular vesicles in cancer prevention and treatment.Journal of extracellular vesicles · 2024Review
- Myogenic microRNAs as Therapeutic Targets for Skeletal Muscle Mass Wasting in Breast Cancer Models.International journal of molecular sciences · 2024Review
- Exercise-induced extracellular vesicles in reprogramming energy metabolism in cancer.Frontiers in oncology · 2024Review
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
7 authors at 3 institutions in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
The health benefits of exercise training in a cancer setting are increasingly acknowledged; however, the underlying molecular mechanisms remain poorly understood. It has been suggested that extracellular vesicles (EVs) released from contracting skeletal muscles play a key role in mediating the systemic benefits of exercise by transporting bioactive molecules, including myokines. Nevertheless, skeletal muscle-derived vesicles account for only about 5% of plasma EVs, with the immune cells making the largest contribution. Moreover, it remains unclear whether the contribution of skeletal muscle-derived EVs increases after physical exercise or how muscle contraction modulates the secretory activity of other tissues and thus influences the content and profile of circulating EVs. Furthermore, the destination of EVs after exercise is unknown, and it depends on their molecular composition, particularly adhesion proteins. The cargo of EVs is influenced by the training program, with acute training sessions having a greater impact than chronic adaptations. Indeed, there are numerous questions regarding the role of EVs in mediating the effects of exercise, the clarification of which is critical for tailoring exercise training prescriptions and designing exercise mimetics for patients unable to engage in exercise programs. This review critically analyzes the current knowledge on the effects of exercise on the content and molecular composition of circulating EVs and their impact on cancer progression.
Indexed as
Identifiers
What OpenQuestion holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.