009 | Metabolic adaptation to hypoxia via lipid droplet accumulation in a 3D hepatocellular carcinoma model

Giorgia Cannatà¹, Caterina Faggio^1|2, Maria Giovanna Rizzo¹ | ¹Department of Chemical, Biological, Pharmaceutical and Environmental Sciences, University of Messina, Italy; ²Department of Eco-sustainable Marine Biotechnology, Stazione Zoologica Anton Dohrn, Naples, Italy.

Hepatocellular carcinoma (HCC), the most prevalent primary liver malignancy, is characterized by metabolic reprogramming. Within the hypoxic tumor microenvironment, elevated intracellular levels of reactive oxygen species (ROS) drive adaptive metabolic responses that promote tumor survival [1]. In particular, ROS induce lipid metabolic remodeling, resulting in lipid droplet (LD) accumulation through the regulation of LD-associated proteins. LD accumulation represents a critical adaptive mechanism supporting tumor cell survival, progression, and aggressiveness. In this study, lipid metabolic reorganization was investigated in a three-dimensional (3D) HCC model that faithfully recapitulated the metabolic and microenvironmental features of solid tumors [2]. Specifically, i) lipid droplets were visualized and quantified by Nile Red staining; ii) oxidative stress was assessed using ROS-based assays, together with gene expression analyses of lipid metabolism markers, hypoxia-associated metabolic pathways, and extracellular matrix (ECM) remodeling markers. The results demonstrated a significant accumulation of lipid droplets associated with sustained oxidative stress and activation of hypoxia-related metabolic pathways. These metabolic adaptations were accompanied by increased expression of ECM remodeling markers, suggesting a functional link between lipid handling and tumor microenvironment modulation. Overall, these findings identify lipid droplets as key regulators of metabolic adaptation in HCC, highlighting their potential as therapeutic targets and improve responsiveness to conventional anticancer therapies.
This work was carried out within the framework of the MUR–PNRR Project SAMOTHRACE (ECS00000022), supported by the European Union – Next Generation EU.