The biological mechanism and emerging therapeutic interventions of liver aging.

Research on liver aging has become prominent and has attracted considerable interest in uncovering the mechanism and therapeutic targets of aging to expand lifespan. In addition, multi-omics studies are widely used to perform further mechanistic investigations on liver aging. In this review, we illustrate the changes that occur with aging in the liver, present the current models of liver aging, and emphasize existing multi-omics studies on liver aging. We integrated the multi-omics data of enrolled studies and reanalyzed them to identify key pathways and targets of liver aging. The results indicated that C-X-C motif chemokine ligand 9 (Cxcl9) was a regulator of liver aging. In addition, we provide a flowchart for liver aging research using multi-omics analysis and molecular experiments to help researchers conduct further research. Finally, we present emerging therapeutic treatments that prolong lifespan. In summary, using cells and animal models of liver aging, we can apply a multi-omics approach to find key metabolic pathways and target genes to mitigate the adverse effects of liver aging.

SMYD2 Promotes Hepatocellular Carcinoma Progression by Reprogramming Glutamine Metabolism via c-Myc/GLS1 Axis.

Metabolic reprogramming, such as alterations in glutamine metabolism or glycolysis, is the hallmark of hepatocellular carcinoma (HCC). However, the underlying mechanisms are still incompletely elucidated. Previous studies have identified that methyltransferase SET and MYND domain-containing protein 2(SMYD2) is responsible for the pathogenesis of numerous types of cancer. Here, we innovatively uncover how SMYD2 regulates glutamine metabolism in HCC cells and promotes HCC progression. We identified that SMYD2 expression is upregulated in HCC tissues, which correlates with unfavorable clinical outcomes. Our in vitro and in vivo results showed that the depletion of SMYD2 inhibits HCC cell growth. Mechanistically, c-Myc methylation by SMYD2 increases its protein stability through the ubiquitin-proteasome system. We showed SMYD2 depletion destabilized c-Myc protein by increasing the conjugated K48-linked polyubiquitin chain. SMYD2 increased c-Myc expression and further upregulated glutaminase1 (GLS1), a crucial enzyme that catalyzes the conversion of glutamine to glutamic acid, in HCC cells. GLS1 plays an important role in SMYD2-mediated HCC progression and glutamine metabolism regulation. The knockdown of SMYD2 inhibited glutamine metabolism in HCC cells and overcame their chemoresistance to sorafenib. Collectively, our findings demonstrated a novel mechanism of how SMYD2 promotes HCC progression by regulating glutamine metabolism through the c-Myc/GLS1signaling, implicating the therapeutic potential of targeting SMYD2 in HCC patients.

Identification of hub genes and regulators associated with pancreatic ductal adenocarcinoma based on integrated gene expression profile analysis.

Pancreatic ductal adenocarcinoma (PDAC) is one of the most lethal malignancies without effective screening strategy during the early stage. Therefore, a novel screening panel was identified based on potential biomarkers associated with PDAC using the gene expression profile. The dataset GSE15471, which was downloaded from the Gene Expression Omnibus (GEO) database, included matching pairs of normal and tumor tissue samples from the resected pancreas of 39 pancreatic cancer patients. We used the online tool GEO2R to screen and pick out the differentially expressed genes (DEGs). Then we performed functional and pathway enrichment and constructed a DEG-associated protein-protein interaction (PPI) network by searching interacting genes in STRING. By using the visualization software Cytoscape, we sorted the modules in the PPI network and hub genes of DEGs through the MCODE and CytoHubba plugins. In total, 326 DEGs, including 306 upregulated genes and 20 downregulated genes, were targeted in PDAC. Kyoto Encyclopedia of Gene and Genome (KEGG) pathway and gene ontology (GO), based on the Database for Annotation, Visualization, and Integrated Discovery (DAVID), revealed that the DEGs are mainly involved in 'PI3K-Akt signaling pathway,' 'Focal adhesion,' and 'ECM-receptor interaction.' In addition, top 50 core genes were identified from the PPI network by CytoHubba. Gene Expression Profiling Interactive Analysis (GEPIA) survival analysis showed that high expressions of KRT7, KRT19, SEMA3C, ITGA2, MYOF, and ANXA1 may predict poor survival outcome in PDAC. Finally, Oncomine confirmed that the high expressions of these genes were strongly related to cancer grade. These hub genes and regulators straightened out the molecular pathways and recurrence mechanisms in PDAC and could be used as targets for PDAC's diagnosis, treatment, and prognostic prediction.