Integrating single-cell and bulk RNA-seq to reveal cholesterol homeostasis-related genes via machine learning to predict prognosis and therapeutic response in hepatocellular carcinoma
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Background: Liver cancer, particularly hepatocellular carcinoma (HCC), has emerged as a significant global health challenge. Recent studies have highlighted cholesterol homeostasis (CH) as a new research frontier, providing insights into its involvement in diverse biological functions and diseases. This study seeks to investigate the significance of CH in the context of HCC. Methods: This study explores CH's role in HCC using single-cell RNA sequencing data (GSE140228) from the TISCH database, analyzed via the "Seurat" R package. Genes associated with cholesterol homeostasis (CH) were sourced from the MsigDB database. Utilizing these CH-related genes, we performed unsupervised hierarchical clustering analysis to stratify hepatocellular carcinoma (HCC) into molecular subtypes. A comprehensive analysis was conducted on the differences among the identified clusters, focusing on clinical characteristics, pathways, and the infiltration of immune cells. By leveraging the CH-related genes, a CH score was computed using various machine learning techniques to predict the overall survival of patients with HCC. Results: We began by investigating the CH-related genes, subsequently identifying three distinct subtypes. A risk score model was developed to classify HCC patients into high-score and low-score groups. Evaluation of the tumor immune microenvironment (TIME) demonstrated that individuals categorized in the high-risk subgroup showed significantly reduced overall survival rates and demonstrated diminished therapeutic efficacy in response to immune checkpoint inhibitor treatment regimens. ANXA5, ADH4, ATXN2, ACTG1, MVD, and S100A11 were identified essential CH-related genes in HCC. Conclusion: We developed a new signature derived from CH-related genes that offers a strong prediction of survival outcomes and responses to immunotherapy in patients with HCC.
