Metabolic heterogeneity of human hepatocellular carcinoma: implications for personalized pharmacological treatment.

Abstract:

Metabolic reprogramming is a characteristic feature of cancer cells, but there is no unique metabolic program for all tumors. Genetic and gene expression studies have revealed heterogeneous inter- and intratumor patterns of metabolic enzymes and membrane transporters. The functional implications of this heterogeneity remain often elusive. Here, we applied a systems biology approach to gain a comprehensive and quantitative picture of metabolic changes in individual hepatocellular carcinoma (HCC). We used protein intensity profiles determined by mass spectrometry in samples of 10 human HCCs and the adjacent noncancerous tissue to calibrate Hepatokin1, a complex mathematical model of liver metabolism. We computed the 24-h profile of 18 metabolic functions related to carbohydrate, lipid, and nitrogen metabolism. There was a general tendency among the tumors toward downregulated glucose uptake and glucose release albeit with large intertumor variability. This finding calls into question that the Warburg effect dictates the metabolic phenotype of HCC. All tumors comprised elevated beta-oxidation rates. Urea synthesis was found to be consistently downregulated but without compromising the tumor's capacity for ammonia detoxification owing to increased glutamine synthesis. The largest intertumor heterogeneity was found for the uptake and release of lactate and the size of the cellular glycogen content. In line with the observed metabolic heterogeneity, the individual HCCs differed largely in their vulnerability against pharmacological treatment with metformin. Taken together, our approach provided a comprehensive and quantitative characterization of HCC metabolism that may pave the way for a computational a priori assessment of pharmacological therapies targeting metabolic processes of HCC.

SEEK ID: https://seek.lisym.org/publications/284

PubMed ID: 33030799

Projects: LiSyM Pillar IV: Liver Function Diagnostics (LiSyM-LiFuDi)

Publication type: Journal

Journal: FEBS J

Citation: FEBS J. 2020 Oct 8. doi: 10.1111/febs.15587.

Date Published: 8th Oct 2020

Registered Mode: by PubMed ID

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Created: 11th Dec 2020 at 11:34

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