Oncometabolite D-2-hydroxyglutarate-dependent metabolic reprogramming induces skeletal muscle atrophy during cancer cachexia.
Xinting ZhuJuan HaoHong ZhangMengyi ChiYaxian WangJinlu HuangRong XuZhao XincaiBo XinXipeng SunJianping ZhangShumin ZhouDongdong ChengTing YuanJun DingShuier ZhengCheng GuoQuan-Jun YangPublished in: Communications biology (2023)
Cancer cachexia is characterized by weight loss and skeletal muscle wasting. Based on the up-regulation of catabolism and down-regulation of anabolism, here we showed genetic mutation-mediated metabolic reprogramming in the progression of cancer cachexia by screening for metabolites and investigating their direct effect on muscle atrophy. Treatment with 93 μM D-2-hydroxyglutarate (D2HG) resulted in reduced myotube width and increased expression of E3 ubiquitin ligases. Isocitrate Dehydrogenase 1 (IDH1) mutant patients had higher D2HG than non-mutant patients. In the in vivo murine cancer cachexia model, mutant IDH1 in CT26 cancer cells accelerated cachexia progression and worsened overall survival. Transcriptomics and metabolomics revealed a distinct D2HG-induced metabolic imbalance. Treatment with the IDH1 inhibitor ivosidenib delayed the progression of cancer cachexia in murine GL261 glioma model and CT26 colorectal carcinoma models. These data demonstrate the contribution of IDH1 mutation mediated D2HG accumulation to the progression of cancer cachexia and highlight the individualized treatment of IDH1 mutation associated cancer cachexia.
Keyphrases
- papillary thyroid
- skeletal muscle
- squamous cell
- end stage renal disease
- computed tomography
- magnetic resonance imaging
- squamous cell carcinoma
- mass spectrometry
- newly diagnosed
- insulin resistance
- type diabetes
- peritoneal dialysis
- prognostic factors
- dna methylation
- deep learning
- magnetic resonance
- fluorescent probe
- metabolic syndrome
- oxidative stress
- endothelial cells
- ms ms
- artificial intelligence
- smoking cessation
- drug induced
- living cells
- combination therapy
- binding protein
- data analysis