TRAIL/DR5 pathway promotes AKT phosphorylation, skeletal muscle differentiation, and glucose uptake.
Barbara ToffoliFederica TononVeronica TisatoGiorgio ZauliPaola SecchieroBruno FabrisStella BernardiPublished in: Cell death & disease (2021)
TNF-related apoptosis-inducing ligand (TRAIL) is a protein that induces apoptosis in cancer cells but not in normal ones, where its effects remain to be fully understood. Previous studies have shown that in high-fat diet (HFD)-fed mice, TRAIL treatment reduced body weight gain, insulin resistance, and inflammation. TRAIL was also able to increase skeletal muscle free fatty acid oxidation. The aim of the present work was to evaluate TRAIL actions on skeletal muscle. Our in vitro data on C2C12 cells showed that TRAIL treatment significantly increased myogenin and MyHC and other hallmarks of myogenic differentiation, which were reduced by Dr5 (TRAIL receptor) silencing. In addition, TRAIL treatment significantly increased AKT phosphorylation, which was reduced by Dr5 silencing, as well as glucose uptake (alone and in combination with insulin). Our in vivo data showed that TRAIL increased myofiber size in HFD-fed mice as well as in db/db mice. This was associated with increased myogenin and PCG1α expression. In conclusion, TRAIL/DR5 pathway promotes AKT phosphorylation, skeletal muscle differentiation, and glucose uptake. These data shed light onto a pathway that might hold therapeutic potential not only for the metabolic disturbances but also for the muscle mass loss that are associated with diabetes.
Keyphrases
- skeletal muscle
- insulin resistance
- high fat diet
- high fat diet induced
- type diabetes
- adipose tissue
- weight gain
- cell proliferation
- oxidative stress
- metabolic syndrome
- polycystic ovary syndrome
- blood glucose
- electronic health record
- fatty acid
- body mass index
- rheumatoid arthritis
- combination therapy
- cell cycle arrest
- cardiovascular disease
- big data
- glycemic control
- editorial comment
- induced apoptosis
- machine learning
- weight loss
- nitric oxide
- data analysis
- protein kinase
- endoplasmic reticulum stress
- long non coding rna
- cell death
- deep learning
- drug induced