Quantitative analysis of γ-glutamylisoleucine, γ-glutamylthreonine, and γ-glutamylvaline in HeLa cells using UHPLC-MS/MS

UPLC-Q-TOF/MS-based urine metabolomics for the diagnosis and staging of bladder cancer

BACKGROUND

Bladder cancer (BC) is a common malignant tumour of the urinary system. Currently, the gold standard for diagnosing BC is cystoscopy, but it is an invasive examination that can lead to a certain psychological burden on the patient. In this study, we aimed to identify non-invasive potential metabolic biomarkers that could improve the diagnostic accuracy of bladder cancer.

METHODS

Urine from 30 healthy people and 50 BC patients, including 40 non-muscle-invasive bladder cancer (NMIBC) patients and 10 muscle-invasive bladder cancer (MIBC) patients, were analyzed by liquid chromatography coupled with mass spectrometry to identify potential diagnostic metabolites. Binary Logistic regression was used to construct biomarker panels. Correlation analysis and construction of compound-reaction-enzyme-gene network were also performed to explore the possible mechanisms of BC development.

RESULTS

Twenty-six metabolites were identified for differentiating BC patients from healthy controls, and eight metabolites were identified for differentiating NMIBC patients form MIBC patients. The biomarker panel consisting of urate, 4-Androstene-3α, 17β-diol and 3-Indoxyl sulfate can distinguish well between BC patients and healthy controls, with an area under the ROC curve (AUC) value of 0.983. And the biomarker panel consisting of L-Octanoylcarnitine, γ-Glutamylleucine, and heptanoylcarnitine for distinguishing NMIBC patients from MIBC patients had an AUC value of 0.941.

CONCLUSIONS

The diagnostic capability of the biomarker panels are superior to that of any single potential biomarker. This panel significantly benefits bladder cancer diagnostics and reveals insight into bladder cancer pathogenesis.

Metabolomics Reveals Molecular Signatures for Psoriasis Biomarkers and Drug Targets Discovery

Purpose

Psoriasis is a chronic, multi-system skin disease that can be influenced by immunological, environmental, and genetic factors. Plasma metabolomic analysis can provide a great deal of information on potential diagnostic biomarkers, pathogenesis and personalized treatment. However, the role of metabolites in psoriasis is unknown.

Patients and Methods

We performed an untargeted metabolomic analysis of plasma based on high-resolution liquid chromatography mass spectrometry from 10 plaque psoriasis patients and 10 healthy controls.

Results

A total of 301 differential metabolites were detected, of which 10 metabolites were possible potential biomarkers, including vitamins, amino acids, and lipids. At the same time, KEGG pathway enrichment analysis was performed for all detected differential metabolites, and it was found that protein digestion and absorption, amino acid metabolism and lipid metabolism may be jointly involved in regulating the pathogenesis of psoriasis. In addition, the proteins ESR1, OPRM1 and HSD11B1 were identified as possible potential topical therapeutic targets for psoriasis through analysis of the metabolite-protein interaction network.

Conclusion

In this study, we identified 10 differential metabolites as possible potential combinatorial biomarkers for the diagnosis of psoriasis. 12 metabolic pathways were significantly enriched that may be closely related to the occurrence and development of psoriasis. Three proteins, ESR1, OPRM1, and HSD11B1, were identified as possible potential therapeutic targets for psoriasis.

Isolation, optimized extraction, and ultra-high performance liquid chromatography with photodiode array method for quantitative analysis of chiratol in Swertia paniculata

The global natural product-based industry is growing fast with the introduction of new phytochemicals and herbal extract products from different geographical regions. Swertia paniculata is a well-known plant with medicinal properties; however, the quality control for its major phytochemical constituents from the Himalayan geographical region is nevertheless reported. Therefore, the first objective of this investigation was to characterize and optimize the extraction process while the second objective was to validate a quantitative analytical method for chiratol from S. paniculata herbal extract. The chiratol was characterized with spectral analysis. The optimum extraction condition for the highest yield of metabolite was realized in chloroform as a solvent system under ultrasonication. The ultra-high performance liquid chromatography coupled with photodiode array detection method for analytical quantification was validated for specificity, linearity, limits of detection, limits of quantification, precision, repeatability, recovery, and robustness using Eclipse Plus C18 column (100 mm × 4.6 mm × 3.5 μm id). The gradient elution of water/acetonitrile as mobile phase was used at a flow rate of 0.5 ml/min. The recovery percentage was very satisfactory with values within specification. The robustness parameters showed no substantial influence of evaluated parameters by the Youden test. The developed method was ascertained to be appropriate for the proposed purpose.