EGF receptor (EGFR) inhibition promotes a slow-twitch oxidative, over a fast-twitch, muscle phenotype.
Margherita CianoGiada MantellatoMartin ConnollyMark Paul-ClarkSaffron Willis-OwenMiriam F MoffattWilliam O C M CooksonJane A MitchellMichael I PolkeySimon M HughesPaul R KempS Amanda NatanekPublished in: Scientific reports (2019)
A low quadriceps slow-twitch (ST), oxidative (relative to fast-twitch) fiber proportion is prevalent in chronic diseases such Chronic Obstructive Pulmonary Disease (COPD) and is associated with exercise limitation and poor outcomes. Benefits of an increased ST fiber proportion are demonstrated in genetically modified animals. Pathway analysis of published data of differentially expressed genes in mouse ST and FT fibers, mining of our microarray data and a qPCR analysis of quadriceps specimens from COPD patients and controls were performed. ST markers were quantified in C2C12 myotubes with EGF-neutralizing antibody, EGFR inhibitor or an EGFR-silencing RNA added. A zebrafish egfra mutant was generated by genome editing and ST fibers counted. EGF signaling was (negatively) associated with the ST muscle phenotype in mice and humans, and muscle EGF transcript levels were raised in COPD. In C2C12 myotubes, EGFR inhibition/silencing increased ST, including mitochondrial, markers. In zebrafish, egfra depletion increased ST fibers and mitochondrial content. EGF is negatively associated with ST muscle phenotype in mice, healthy humans and COPD patients. EGFR blockade promotes the ST phenotype in myotubes and zebrafish embryos. EGF signaling suppresses the ST phenotype, therefore EGFR inhibitors may be potential treatments for COPD-related muscle ST fiber loss.
Keyphrases
- chronic obstructive pulmonary disease
- small cell lung cancer
- epidermal growth factor receptor
- tyrosine kinase
- lung function
- end stage renal disease
- growth factor
- skeletal muscle
- randomized controlled trial
- ejection fraction
- oxidative stress
- chronic kidney disease
- machine learning
- electronic health record
- genome editing
- systematic review
- signaling pathway
- type diabetes
- physical activity
- adipose tissue
- big data
- dna methylation
- climate change
- peritoneal dialysis
- transcription factor
- single cell
- air pollution
- deep learning
- patient reported