Characterization of Lipid and Lipid Droplet Metabolism in Human HCC

Abstract

Human hepatocellular carcinoma (HCC) is the most common type of primary liver cancer in adults and the most common cause of death in people with cirrhosis. While previous metabolic studies of HCC have mainly focused on the glucose metabolism (Warburg effect), less attention has been paid to tumor-specific features of the lipid metabolism. Here, we applied a computational approach to analyze major pathways of fatty acid utilization in individual HCC. To this end, we used protein intensity profiles of eleven human HCCs to parameterize tumor-specific kinetic models of cellular lipid metabolism including formation, enlargement, and degradation of lipid droplets (LDs). Our analysis reveals significant inter-tumor differences in the lipid metabolism. The majority of HCCs show a reduced uptake of fatty acids and decreased rate of β-oxidation, however, some HCCs display a completely different metabolic phenotype characterized by high rates of β-oxidation. Despite reduced fatty acid uptake in the majority of HCCs, the content of triacylglycerol is significantly enlarged compared to the tumor-adjacent tissue. This is due to tumor-specific expression profiles of regulatory proteins decorating the surface of LDs and controlling their turnover. Our simulations suggest that HCCs characterized by a very high content of triglycerides comprise regulatory peculiarities that render them susceptible to selective drug targeting without affecting healthy tissue.

Aberrant lipid metabolism in hepatocellular carcinoma cells as well as immune microenvironment: A review

“…6 A recent study has analysed the global gene expression profile of HCC, which reveals that genes involved in the biosynthesis of fatty acids (FAs) are universally up-regulated in most HCC tissues compared with the noncancerous liver tissues. 7,8 Typically, FAs function as the signalling molecules, energy sources, and the structural components of cell membrane, all of which are essential for cancer cell proliferation. 9 Normal cells preferentially utilize the circulating exogenous lipids, whereas cancer cells, including HCC cells, show a high de novo lipid synthesis rate, 10 suggesting FA accumulation in tumour cells.…”

“…8 Enhanced FAO, reduced glycolysis accompanied by the up-regulated expression of PPARα and CPT2 are observed in the β-catenin-activated HCCs derived from mice and humans ( Figure 2), suggesting that such tumours rely mainly on FAO to provide energy. 8,9,14 Typically, the β-catenin-activated HCCs carry an activating mutation in the CTNNB1, a gene that encodes β-catenin in the Wnt pathway, whose mutation is not uncommon (19.5%) in human HCC. [15][16][17] Inhibiting FAO by genetic and pharmacological approaches blocks the HCC development, which suggests that inhibiting FAO is a suitable therapeutic approach for the β-catenin-mutated HCC.…”

Peer Review #3 of "Identification of a prognostic signature of nine metabolism-related genes for hepatocellular carcinoma (v0.1)"

“…It is thus necessary to build a metabolism-related prognostic model for HCC (De Matteis et al 2018;Nakagawa et al 2018;Pope et al 2019). Changes in metabolic pathways, which are driven by oncogenes, are recognised as cancer markers, and such changes provide cancers with a selective advantage for tumour growth, proliferation, and metastasis (Berndt et al 2019;De Matteis et al 2018;Huang et al 2014;Kim et al 2019). TP53 and CTNNB1 are two genes that are most prone to mutations in HCC, and have received continuous research attention because of their involvement in events that dominate tumour development and progression.…”

Metabolic modelling of kidney diseases: Lessons learned from the liver

“…A "fatty liver" increases the risk for developing an inflammation of the liver, the so-called non-alcoholic steatohepatitis, which may further progress to cirrhosis and eventually hepatocellular carcinoma (HCC). Thanks to hundreds of enzymatic studies on liver enzymes performed by experimental biochemists since the middle of the last century, physiologically reliable kinetic models were first established for small metabolic subsystems [11][12][13] and recently even for the complete central metabolism of liver cells. 9 Metabolic models of the liver range from genome-wide network models 10 to small-scale metabolic models of single pathways.…”

“…The real challenge in kinetic modelling consists in the establishment of realistic enzymatic rate laws describing the relationship between reaction rates and metabolite concentrations. Thanks to hundreds of enzymatic studies on liver enzymes performed by experimental biochemists since the middle of the last century, physiologically reliable kinetic models were first established for small metabolic subsystems [11][12][13] and recently even for the complete central metabolism of liver cells. 14 The latter model allows simulating diurnal variations of the metabolic state of the liver at various perturbations caused by nutritional challenges (alcohol), drugs (valproate) and inherited enzyme disorders (galactosaemia).…”