Screening for lipid metabolism-related genes and identifying the therapeutic potential of ACACA for ER stress-related progression in hepatocellular carcinoma

Abstract

Aim: The reprogramming of lipid metabolism can markedly enhance the nutritional adaptability of tumor cells to the glucose-deficient and hypoxic tumor microenvironment, which holds profound significance for the development and metastasis of liver cancer. Nevertheless, the alterations of lipid metabolism under stress conditions and the specific mechanisms remain ambiguous. The current study aimed to explore the molecular interaction between endoplasmic reticulum (ER) stress and lipid metabolism in hepatocellular carcinoma (HCC) using bioinformatics analysis, and further verify the role of core hub genes and offer potential targets for diagnosing and treating HCC.

Methods: Differentially expressed lipid-related genes (DLRGs) were identified via cross-crossing differentially expressed genes (DEGs) in the TCGA-LIHC program and lipid metabolism-related genes in the Genecards database. Identification of hub genes was achieved by constructing a protein-protein interaction (PPI) network, gene ontology (GO), and Kyoto Encyclopedia of Genes and Genomes (KEGG). Disease correlation analysis was performed in the Comparison of Toxicology Database, receiver operating characteristic (ROC) curve and Kaplan-Meier curve analyses were performed for the hub genes, and the CIBERSORT algorithm was employed to assess immune infiltration. The role of acetyl-CoA carboxylase 1 (ACACA) in HCC was evaluated by Western blotting, polymerase chain reaction, immunohistochemistry, and CCK-8 assay.

Results: In total, 131 DLRGs were identified, comprising 70 upregulated and 61 downregulated. PPI analysis identified 20 hub DLRGs, while ROC curve analysis and Kaplan-Meier analysis further revealed that ACACA, LCAT, APOC3, LPA and PON1 may hold diagnostic and prognostic value for HCC patients. More importantly, ACACA overexpression was related to unfavorable overall survival (OS) and adverse pathological characteristics in HCC patients. In addition, both free fatty acid (FFA) and tunicamycin (TM) could activate ER stress and enhance the expression of ACACA in HCC. Interestingly, inhibition of ER stress or fatty acid synthesis using 4-phenylbutyric acid (4-PBA) or fenofibrate significantly reduced the expression of ACACA, and fenofibrate inhibits HCC cell proliferation.

Conclusion: The study identifies a novel core lipid metabolism-related gene called ACACA, which has prognostic and therapeutic potential for HCC. We also provide a deep understanding of lipid metabolism correlated with ER stress in the progression of HCC, offering new opportunities for the identification of biological targets and the development of drugs and treatments for HCC patients.

Keywords

Hepatocellular carcinoma / lipid metabolism / ACACA / endoplasmic reticulum stress / bioinformatics analysis

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