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Diet-induced fatty liver is a considerable threaten to fish aquaculture due to the popularity of the high-fat diet (HFD) feeding. Our study aims to investigate the effects of flavanones from Sedum sarmentosum Bunge (FSSB) on the liver function to identify a potential treatment for HFD-induced fatty liver disease. Physiological and pathological indicators were tested in the liver of Nile tilapia (Oreochromis niloticus) and results showed parameters including lipid metabolites, redox parameters, and inflammatory factors could be adequately restored to normal level by addition of 150 mg/kg FSSB to HFD. Proteomics analysis was performed in liver tissues from tilapia with normal diet (ND), HFD, and HFD+FSSB. Totally, 51 upregulated proteins and 77 downregulated proteins were identified in HFD groups and 67 proteins of them were restored after treated with FSSB. Bioinformatics analysis showed that differentially expressed proteins (DEPs) in HFD+FSSB150 group compared with HFD group are mainly enriched in acety-CoA metabolic process, adenosine-triphosphate (ATP) biosynthetic process, lipid metabolic process, and phospholipid metabolic process. The dysregulated proteins were involved in peroxidosome proliferators-activated receptor (PPAR) signaling pathway, fat digestion and absorption, and immune system. The quantitative real-time PCR (qRT-PCR) assay further revealed that the expression of GST, PPARα, PPARγ, and multiple-inflammatory cytokines could be also reversed in HFD group under the treatment of 150 mg/kg FSSB. Our findings demonstrated FSSB is efficient for the treatment of fatty liver disease through regulation of lipid metabolism and antioxidation in Nile tilapia, providing a new treatment of non-alcoholic fatty liver disease (NAFLD) in fish aquaculture.

Homeostasis of membrane phospholipids plays an important role in cell oncogenesis and cancer progression. The flippase ATPase class I type 8b member 1 (ATP8B1), one of the P4-ATPases, translocates specific phospholipids from the exoplasmic to the cytoplasmic leaflet of membranes. ATP8B1 is critical for maintaining the epithelium membrane stability and polarity. However, the prognostic values of ATP8B1 in colorectal cancer (CRC) patients remain unclear. We analyzed transcriptomics, genomics, and clinical data of CRC samples from The Cancer Genome Atlas (TCGA). ATP8B1 was the only potential biomarker of phospholipid transporters in CRC. Its prognostic value was also validated with the data from the Gene Expression Omnibus (GEO). Compared to the normal group, the expression of ATP8B1 was downregulated in the tumor group and the CRC cell lines, which declined with disease progression. The lower expression level of ATP8B1 was also significantly associated with worse survival outcomes in both the discovery samples (359 patients) and the validation samples (566 patients). In multivariate analyses, low ATP8B1 levels predicted unfavorable OS (adjusted HR 1.512, 95% CI: 1.069-2.137; P = 0.019 ) and were associated with poor progress-free interval (PFI) (adjusted HR: 1.62, 95% CI: 1.207-2.174; P = 0.001 ). The pathway analysis results showed that the underexpression of ATP8B1 was negatively associated with phospholipid transport, phospholipid metabolic process, and cell-cell adherent junction and positively associated with the epithelial-mesenchymal transition in CRC. Our analysis suggests that ATP8B1 is a potential cancer suppressor in CRC patients and may offer new strategies for CRC therapy.

Primary aldosteronism is the most common form of secondary hypertension, and aldosteronoma makes up a significant proportion of primary aldosteronism cases. Aldosteronoma is also called aldosterone-producing adenoma (APA). Although there have been many studies about APA, the pathogenesis of this disease is not yet fully understood. In this study, we aimed to find out the difference of gene expression patterns between APA and nonfunctional adrenocortical adenoma (NFAA) using a weighted gene coexpression network (WGCNA) and differentially expressed gene (DEG) analysis; only the genes that meet the corresponding standards of both methods were defined as real hub genes and then used for further analysis. Twenty-nine real hub genes were found out, most of which were enriched in the phospholipid metabolic process. WISP2, S100A10, SSTR5-AS1, SLC29A1, APOC1, and SLITRK4 are six real hub genes with the same gene expression pattern between the combined and validation datasets, three of which indirectly or directly participate in lipid metabolism including WISP2, S100A10, and APOC1. According to the gene expression pattern of DEGs, we speculated five candidate drugs with potential therapeutic value for APA, one of which is cycloheximide, an inhibitor for phospholipid biosynthesis. All the evidence suggests that phospholipid metabolism may be an important pathophysiological mechanism for APA. Our study provides a new perspective regarding the pathophysiological mechanism of APA and offers some small molecules that may possibly be effective drugs against APA.

Drug resistance and adverse reactions to oxaliplatin remain a considerable issue in clinical practice. Emerging evidence has suggested that alterations in the lipid metabolism during drug therapy affect cancer cells. To gain insight into the important process of lipid metabolism, we investigated the lipid and gene expression profile changes in HT29 cells treated with oxaliplatin. A total of 1403 lipid species from 16 lipid classes were identified by UHPLC-MS. Interestingly, phospholipids, including phosphatidylglycerol (PG), phosphatidic acid (PA), phosphatidylcholine (PC), and most of phosphatidylethanolamine (PE) with polyunsaturated fatty acid (PUFA) chains, were significantly higher due to oxaliplatin treatment, while triacylglycerols (TAGs) with a saturated fatty acid chain or monounsaturated fatty acid were significantly downregulated. Gene Set Enrichment Analysis (GSEA) based on RNA sequencing data suggested that neutral lipid metabolism was enriched in the control group, whereas the phospholipid metabolic process was enriched in the oxaliplatin-treated group. We observed that altered lipid metabolism enzyme genes were involved in the synthesis and lipolysis of TAGs and the Lands cycle pathway based on the network between the core lipid-related gene and lipid species, which was further verified by qRT-PCR. In summary, our findings revealed that oxaliplatin impressed a specific lipid profile signature and lipid transcriptional reprogramming in HT29 cells, which provides new insights into biomarker discovery and pathways for overcoming drug resistance and adverse reactions.

Background This study explored the prognostic significance of Glypican (GPC) family genes in patients with pancreatic ductal adenocarcinoma (PDAC) after pancreaticoduodenectomy using data from The Cancer Genome Atlas (TCGA) and Gene Expression Omnibus (GEO). Methods A total of 112 PDAC patients from TCGA and 48 patients from GEO were included in the analysis. The relationship between overall survival and the expression of GPC family genes as well as basic clinical characteristics was analyzed using the Kaplan-Meier method with the log-rank test. Joint effects survival analysis was performed to further examine the relationship between GPC genes and prognosis. A prognosis nomogram was established based on clinical characteristics and prognosis-related genes. Prognosis-related genes were investigated by genome-wide co-expression analysis and gene set enrichment analysis (GSEA) was carried out to identify potential mechanisms of these genes affecting prognosis. Results In TCGA database, high expression of GPC2, GPC3, and GPC5 was significantly associated with favorable survival (log-rank P = 0.031, 0.021, and 0.028, respectively; adjusted P value = 0.005, 0.022, and 0.020, respectively), and joint effects analysis of these genes was effective for prognosis prediction. The prognosis nomogram was applied to predict the survival probability using the total scores calculated. Genome-wide co-expression and GSEA analysis suggested that the GPC2 may affect prognosis through sequence-specific DNA binding, protein transport, cell differentiation and oncogenic signatures (KRAS, RAF, STK33, and VEGFA). GPC3 may be related to cell adhesion, angiogenesis, inflammatory response, signaling pathways like Ras, Rap1, PI3K-Akt, chemokine, GPCR, and signatures like cyclin D1, p53, PTEN. GPC5 may be involved in transcription factor complex, TFRC1, oncogenic signatures (HOXA9 and BMI1), gene methylation, phospholipid metabolic process, glycerophospholipid metabolism, cell cycle, and EGFR pathway. Conclusion GPC2, GPC3, and GPC5 expression may serve as prognostic indicators in PDAC, and combination of these genes showed a higher efficiency for prognosis prediction.

Study ObjectiveIdentify small molecule biomarkers of insufficient sleep using untargeted plasma metabolomics in humans undergoing experimental insufficient sleep.MethodsWe conducted a crossover laboratory study where 16 normal-weight participants (eight men; age 22 ± 5 years; body mass index < 25 kg/m2) completed three baseline days (9 hours sleep opportunity per night) followed by 5-day insufficient (5 hours sleep opportunity per night) and adequate (9 hours sleep opportunity per night) sleep conditions. Energy balanced diets were provided during baseline, with ad libitum energy intake provided during the insufficient and adequate sleep conditions. Untargeted plasma metabolomics analyses were performed using blood samples collected every 4 hours across the final 24 hours of each condition. Biomarker models were developed using logistic regression and linear support vector machine (SVM) algorithms.ResultsThe top-performing biomarker model was developed by linear SVM modeling, consisted of 65 compounds, and discriminated insufficient versus adequate sleep with 74% overall accuracy and a Matthew’s Correlation Coefficient of 0.39. The compounds in the top-performing biomarker model were associated with ATP Binding Cassette Transporters in Lipid Homeostasis, Phospholipid Metabolic Process, Plasma Lipoprotein Remodeling, and sphingolipid metabolism.ConclusionWe identified potential metabolomics-based biomarkers of insufficient sleep in humans. Although our current biomarkers require further development and validation using independent cohorts, they have potential to advance our understanding of the negative consequences of insufficient sleep, improve diagnosis of poor sleep health, and could eventually help identify targets for countermeasures designed to mitigate the negative health consequences of insufficient sleep.