Post-hepatectomy liver dysfunction is a life-threatening morbidity that lacks efficient therapy. Bioactive lipids involved in macrophage polarization crucially regulate tissue injury and regeneration. Herein, we investigate the key bioactive lipids that mediate the cytotherapeutic potential of polarized-macrophage for post-hepatectomy liver dysfunction. Untargeted lipidomics identified elevation of ceramide (CER) metabolites as signature lipid species relevant to M1/M2 polarization in mouse bone-marrow-derived-macrophages (BMDMs). M1 BMDMs expressed a CER-generation-metabolic pattern, leading to elevation of CER; M2 BMDMs expressed a CER-breakdown-metabolic pattern, resulting in upregulation of sphingosine-1-phosphate (S1P). After infusing M1- or M2-polarized BMDMs into the mouse liver after hepatectomy, we found that M1-BMDM infusion increased M1 polarization and CER accumulation, resulting in exaggeration of hepatocyte apoptosis and liver dysfunction. Conversely, M2-BMDM infusion enhanced M2 polarization and S1P generation, leading to alleviation of liver dysfunction with improved hepatocyte proliferation. Treatment of exogenous CER and S1P or inhibition CER and S1P synthesis by siRNA targeting relevant enzymes further revealed that CER induced apoptosis while S1P promoted proliferation in post-hepatectomy primary hepatocytes. In conclusion, CER and S1P are uncovered as critical lipid mediators for M1- and M2-polarized BMDMs to promote injury and regeneration in the liver after hepatectomy, respectively. Notably, the upregulation of hepatic S1P induced by M2-BMDM infusion may have therapeutic potential for post-hepatectomy liver dysfunction.
The aim of the present study was to identify the differentially expressed genes (DEGs) between primary tumor tissue and adjacent non-tumor tissue of hepatocellular carcinoma (HCC) samples in order to investigate the mechanisms of HCC. The microarray data of the datasets GSE76427, GSE84005 and GSE57957 were downloaded from the Gene Expression Omnibus database. DEGs were identified using the limma package in the R programming language. Following the intersection of the DEGs screened from the three datasets, 218 genes were selected for further study. A protein-protein interaction (PPI) network was constructed using the Search Tool for the Retrieval of Interacting Genes database. The construction and analysis of modules were performed using Cytoscape and the module with the highest score was selected for further analysis. Gene Ontology enrichment analysis and Kyoto Encyclopedia of Genes and Genomes pathway enrichment analysis were conducted for genes involved in the PPI network and the selected subnetwork. The network of the enriched pathways and their associated genes was constructed using Cytoscape. For the genes in the global PPI network, metabolism-associated pathways were significantly enriched; whereas, for the genes in the subnetwork, ‘cell cycle’, ‘oocyte meiosis’ and ‘DNA replication’ pathways were significantly enriched. To demonstrate the portability and repeatability of the prognostic value of the weighted genes, a validation cohort was obtained from datasets of The Cancer Genome Atlas and Kaplan-Meier survival analysis was conducted. Evidence is presented that the expression levels of aldehyde dehydrogenase 2 family member, cytochrome P450 family 2 subfamily C member 8, alcohol dehydrogenase 4 (class II), pi polypeptide, alcohol dehydrogenase 1B (class I), β polypeptide and cytochrome P450 family 2 subfamily C member 9 were associated with the overall survival of patients with HCC and that the expression levels of pituitary tumor-transforming 1, cell division cycle 20, DNA topoisomerase II α and cyclin B2 were negatively associated with the overall survival of patients with HCC. In conclusion, 9 weighted genes, involved in the development and progression of HCC, were identified using bioinformatics and survival analyses.
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