A study led by Adil Mardinoglu (KTH/SciLifeLab) uncovers three distinct tumor subtypes of hepatocellular carcinoma. Due to tumor heterogeneity, effective treatment methods for this form of liver cancer, which is one of the most frequent ones, are limited.
By integrating genomics and proteomics data with a metabolic network-driven analysis, the researchers could successfully characterize three tumor subtypes with differences in metabolic and signaling pathways, as well as patient survival. This systematic way of defining subtypes of hepatocellular carcinoma may have implications for health care in that it can drive the development of precision medicine approaches for treatment. It also opens up new possibilities for subtyping other cancer variants.
Read the full paper in PNAS
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