A high-throughput targeted metabolomics method for the quantification of 104 non-polar metabolites in cholesterol, eicosanoid, and phospholipid metabolism: application in the study of a CCl4-induced liver injury mouse model

Effect of Short-Chain Fatty Acids and Polyunsaturated Fatty Acids on Metabolites in H460 Lung Cancer Cells

Lung cancer is the most common primary malignant lung tumor. However, the etiology of lung cancer is still unclear. Fatty acids include short-chain fatty acids (SCFAs) and polyunsaturated fatty acids (PUFAs) as essential components of lipids. SCFAs can enter the nucleus of cancer cells, inhibit histone deacetylase activity, and upregulate histone acetylation and crotonylation. Meanwhile, PUFAs can inhibit lung cancer cells. Moreover, they also play an essential role in inhibiting migration and invasion. However, the mechanisms and different effects of SCFAs and PUFAs on lung cancer remain unclear. Sodium acetate, butyrate, linoleic acid, and linolenic acid were selected to treat H460 lung cancer cells. Through untargeted metabonomics, it was observed that the differential metabolites were concentrated in energy metabolites, phospholipids, and bile acids. Then, targeted metabonomics was conducted for these three target types. Three LC-MS/MS methods were established for 71 compounds, including energy metabolites, phospholipids, and bile acids. The subsequent methodology validation results were used to verify the validity of the method. The targeted metabonomics results show that, in H460 lung cancer cells incubated with linolenic acid and linoleic acid, while the content of PCs increased significantly, the content of Lyso PCs decreased significantly. This demonstrates that there are significant changes in LCAT content before and after administration. Through subsequent WB and RT-PCR experiments, the result was verified. We demonstrated a substantial metabolic disparity between the dosing and control groups, further verifying the reliability of the method.

LPCAT1 overexpression promotes the progression of hepatocellular carcinoma

BACKGROUND

Hepatocellular carcinoma (HCC) remains one of the most common malignant neoplasms. Lysophosphatidylcholine acyltransferase 1 (LPCAT1) plays a key role in the lipid remodelling and is correlated with various neoplasms. Nonetheless, the biological functions and molecular mechanisms of LPCAT1 underlying HCC remain obscure.

METHODS

In the present study, we investigated the role of LPCAT1 in the progression of HCC. In-house RT-qPCR, tissue microarrays, and immunohistochemistry were performed to detect the expression levels and the clinical value of LPCAT1 in HCC. External datasets were downloaded to confirm the results. Proliferation, migration, invasiveness, cell cycle, and apoptosis assays were conducted to reveal the biological effects LPCAT1 has on SMMC-7721 and Huh7 cells. HCC differentially expressed genes and LPCAT1 co-expressed genes were identified to explore the molecular mechanisms underlying HCC progression.

RESULTS

LPCAT1 showed upregulated expression in 3715 HCC specimens as opposed to 3105 non-tumour specimens. Additionally, LPCAT1 might be an independent prognostic factor for HCC. LPCAT1-knockout hampered cellular proliferation, migration, and metastasis in SMMC-7721 and Huh7 cells. More importantly, the cell cycle and chemical carcinogenesis were the two most enriched signalling pathways.

CONCLUSIONS

The present study demonstrated that increased LPCAT1 correlated with poor prognosis in HCC patients and fuelled HCC progression by promoting cellular growth, migration, and metastasis.

Simultaneous quantitative determination of arachidonic acid and cascade metabolites in rat serum by UPLC-MS/MS: application for longitudinal metabolomics of anlotinib

Arachidonic acid (AA) and cascade metabolites have been shown to be involved in cancer pathologic states. Anlotinib, a novel oral small molecule inhibitor of multiple receptor tyrosine kinases, has brought significant improvement to the survival of patients with advanced lung cancer. Here, a robust and reproducible ultrahigh performance liquid chromatography-tandem mass spectrometry (UPLC-MS/MS) method was developed, optimized and validated for quantitating AA and cascade metabolites for the first time. Through careful optimization of the analytical conditions, a total of 69 analytes can be efficiently separated and quantitated in a single run of 17 min. A simple and labor-saving protein precipitation procedure was utilized for serum sample pretreatment. The validation parameters and quality control chart of all analytes satisfy the acceptance criteria of bioanalytical method guidelines. The limit of detection (LOD) ranged from 0.005 ng mL^-1 to 1 ng mL^-1, and the volume of serum was only 20 μL. This rapid and sensitive UPLC-MS/MS method was successfully applied to a longitudinal metabolomics study in rat serum after a single administration of anlotinib (6 mg kg^-1). Finally, a total of 41 metabolites can be calculated under the present conditions. Serum samples from the same rat were segregated into a tight cluster in both unsupervised principal component analysis (PCA) and supervised orthogonal partial least-squares discriminant analysis (OPLS-DA) at different sampling time points after anlotinib treatment. Moreover, the number of analytes whose variable importance (VIP) values were larger than 1.0 was 17. The present study not only offers a UPLC-MS/MS analytical reference for AA but also brings out insights for future mechanistic studies or biomarkers to predict the efficacy, toxicity and clinical outcomes in patients with cancer.