Chinese Academy of Sciences
A research group led by Prof. PIAO Hailong from the Dalian Institute of Chemical Physics (DICP) of the Chinese Academy of Sciences (CAS) identified hepatocellular carcinoma (HCC) subtypes with distinctive metabolic phenotypes through bioinformatics and machine learning methods, and elucidated the potential mechanisms based on a metabolite-protein interaction network and multi-omics data.
The study, published in Advanced Science on July 11, provides insights guiding precise personalized HCC medicine.
Metabolic reprogramming, which can promote rapid cell proliferation by regulating energy and nutrient metabolism, is considered to be one hallmark of cancer. It can impact other biological processes through complex metabolite-protein interactions.