A human skeletal muscle stem/myotube model reveals multiple signaling targets of cancer secretome in skeletal muscle
Skeletal muscle dysfunction or reprogramming due to the effects of the cancer secretome is observed in multiple malignancies. Although mouse models are routinely used to study skeletal muscle defects in cancer, because of species specificity of certain cytokines/chemokines in the secretome, a human...
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Veröffentlicht in: | iScience 2023-04, Vol.26 (4), p.106541-106541, Article 106541 |
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Sprache: | eng |
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Zusammenfassung: | Skeletal muscle dysfunction or reprogramming due to the effects of the cancer secretome is observed in multiple malignancies. Although mouse models are routinely used to study skeletal muscle defects in cancer, because of species specificity of certain cytokines/chemokines in the secretome, a human model system is required. Here, we establish simplified multiple skeletal muscle stem cell lines (hMuSCs), which can be differentiated into myotubes. Using single nuclei ATAC-seq (snATAC-seq) and RNA-seq (snRNA-seq), we document chromatin accessibility and transcriptomic changes associated with the transition of hMuSCs to myotubes. Cancer secretome accelerated stem to myotube differentiation, altered the alternative splicing machinery and increased inflammatory, glucocorticoid receptor, and wound healing pathways in hMuSCs. Additionally, cancer secretome reduced metabolic and survival pathway associated miR-486, AKT, and p53 signaling in hMuSCs. hMuSCs underwent myotube differentiation when engrafted into NSG mice and thus providing a humanized in vivo skeletal muscle model system to study cancer cachexia.
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•Four immortalized skeletal muscle stem cell lines (hMuSCs) from male and female donors were created•hMuSCs differentiate into myotubes with accompanying transcriptome changes•hMuSCs engraft and differentiate in tibialis anterior muscle of NSG mice•Cancer secretome impacted alternative splicing, AKT, and p53 signaling in hMuSCs
Cancer systems biology; Cell biology; Molecular biology |
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ISSN: | 2589-0042 2589-0042 |
DOI: | 10.1016/j.isci.2023.106541 |