Identification of prognostic genes for hepatocellular carcinoma based on hepatocyte and ketone body metabolism using integrated bulk and single cell RNA sequencing

Abstract

<title>Abstract</title> Background The precise role of ketone body (KB) metabolism and the underlying cellular mechanisms in hepatocellular carcinoma (HCC) remain unclear. This study aimed to identify and mechanistically explore KB metabolism-related prognostic genes in HCC. Methods All data were obtained from public databases. Single-cell RNA sequencing (scRNA-seq) analysis and high-dimensional weighted gene co-expression network analysis (hdWGCNA) were integrated to identify key module genes related to key cell type with high KB metabolism-related gene (KMRG) activity. After intersecting with differentially expressed genes (DEGs) in HCC and KMRGs, candidate genes were acquired. Subsequently, prognostic genes were recognized by univariate Cox and least absolute shrinkage and selection operator (LASSO) regression. A risk model for risk stratification was established and validated. Further risk group-based analyses mainly examined the impact of risk scores on function, tumor microenvironment (TME), immunotherapy response, and drug sensitivity. Prognostic gene expression dynamics during key cell type differentiation were analyzed by cell trajectory analysis. Eventually, prognostic gene expression was validated via reverse transcription-quantitative PCR (RT-qPCR) Results Hepatocytes were identified as the key cell type with high KMRG activity. Remarkably, PPARGC1A, PDK4, HSD17B6, APOC3, and OXCT1 were identified as prognostic genes. RT-qPCR demonstrated that OXCT1 was upregulated in HCC, while the other prognostic genes were downregulated. The constructed risk model exhibited robust predictive capacity, showing that high-risk patients had lower survival probabilities. Activities of pathways like "MYC targets V1", infiltration of immune cell types like activated CD4 T cells, response to immunotherapy, and sensitivities to drugs like camptothecin were altered by risk scores. Dynamic expression changes of PPARGC1A, PDK4, HSD17B6, and APOC3 were observed during hepatocyte differentiation. Conclusion Five prognostic genes related to hepatocytes and KB metabolism were identified in HCC, and a risk model with strong predictive utility was developed, offering novel insights into clinical prognostic prediction for HCC.