Frontiers in Immunology (Nov 2024)
Integrated single-cell and bulk RNA sequencing reveals immune-related SPP1+ macrophages as a potential strategy for predicting the prognosis and treatment of liver fibrosis and hepatocellular carcinoma
Abstract
BackgroundLiver fibrosis is a pathological response to liver damage induced by multiple etiologies including NASH and CCl4, which may further lead to cirrhosis and hepatocellular carcinoma (HCC). Despite the increasing understanding of liver fibrosis and HCC, clinical prognosis and targeted therapy remain challenging.MethodsThis study integrated single-cell sequencing analysis, bulk sequencing analysis, and mouse models to identify highly expressed genes, cell subsets, and signaling pathways associated with liver fibrosis and HCC. Clinical prediction models and prognostic genes were established and verified through machine learning, survival analysis, as well as the utilization of clinical data and tissue samples from HCC patients. The expression heterogeneity of the core prognostic gene, along with its correlation with the tumor microenvironment and prognostic outcomes, was analyzed through single-cell analysis and immune infiltration analysis. In addition, the cAMP database and molecular docking techniques were employed to screen potential small molecule drugs for the treatment of liver fibrosis and HCC.ResultWe identified 40 pathogenic genes, 15 critical cell subsets (especially Macrophages), and regulatory signaling pathways related to cell adhesion and the actin cytoskeleton that promote the development of liver fibrosis and HCC. In addition, 7 specific prognostic genes (CCR7, COL3A1, FMNL2, HP, PFN1, SPP1 and TENM4) were identified and evaluated, and expression heterogeneity of core gene SPP1 and its positive correlation with immune infiltration and prognostic development were interpreted. Moreover, 6 potential small molecule drugs for the treatment of liver fibrosis and HCC were provided.ConclusionThe comprehensive investigation, based on a bioinformatics and mouse model strategy, may identify pathogenic genes, cell subsets, regulatory mechanisms, prognostic genes, and potential small molecule drugs, thereby providing valuable insights into the clinical prognosis and targeted treatment of liver fibrosis and HCC.
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