Construction of a predictive model for the prognosis of patients with hepatocellular carcinoma based on lipid metabolism-related metastasis risk genes

Abstract

Objective To identify the lipid metabolism-related metastasis risk genes for hepatocellular carcinoma (HCC) based on related databases, and to construct a predictive model for the prognosis of HCC patients in combination with other clinical risk factors. Methods R software was used to obtain the differentially expressed genes (DEGs) between the patients with primary HCC and those with metastatic HCC from the GEO database, and the DEGs associated with the prognosis of patients were identified. The HCC patients in TCGA database were divided into two groups based on hierarchical clustering, and the two groups were assessed in terms of epithelial-mesenchymal transition (EMT), lipid metabolism, and prognosis. The data in the ICGC database were used for validation of the above analysis. The LASSO regression model was used to obtain the lipid metabolism-related metastasis risk genes and determine their risk scores, and according to the median of risk scores, HCC patients in both TCGA and ICGC databases were divided into high and low risk groups to analyze the prognosis of patients. Univariate and multivariate Cox regression analyses were used to obtain independent risk factors for the prognosis of HCC patients, and a nomogram prognostic model was constructed. Western blot and oil red O staining were used to detect the lipid metabolism of Huh7 cells after treatment with the lipid metabolism inhibitor Fatostatin, and qPCR was used to measure the expression levels of lipid metabolism-related metastasis risk genes in Huh7 cells. Results A total of 159 DEGs were obtained from the patients with primary HCC and those with metastatic HCC in the GEO database, among which 65 DEGs were significantly associated with the overall survival (OS) of HCC patients. Based on the EMT score, the two groups of HCC patients obtained by clustering from the TCGA database were defined as high and low metastasis risk groups, respectively, and the patients in the high metastasis risk group tended to have a higher lipid metabolism score and a shorter OS. The validation results in the ICGC database were consistent with the results based on the TCGA database. The LASSO regression model was used to identify the lipid metabolism-related metastasis risk genes, and the high-risk group had a shorter OS. The lipid metabolism-related metastasis risk genes were combined with the independent risk factors for the prognosis of patients with HCC to construct a nomogram prognostic model. Cell experiments confirmed that after the treatment with Fatostatin, there were reductions in the expression of fatty acid synthase and the content of lipid droplets in Huh7 cells, as well as changes in the expression of a variety of lipid metabolism-related metastasis risk genes. Conclusion A total of 13 lipid metabolism-related metastasis risk genes are obtained based on related databases, which are combined with the clinical risk factors to construct a prognostic predictive model for HCC patients, and cell experiments are conducted to confirm that the lipid metabolism-related metastasis risk genes are closely associated with lipid metabolism.

Keywords

• carcinoma, hepatocellular|neoplasm metastasis|lipid metabolism|gene expression|databases, genetic|prognosis