Wenzhao Wang

Metabonomics study of liver cancer based on ultra performance liquid chromatography coupled to mass spectrometry with HILIC and RPLC separations

In this study, urinary metabolites from liver cancer patients and healthy volunteers were studied by a metabonomic method based on ultra performance liquid chromatography coupled to mass spectrometry. Both hydrophilic interaction chromatography (HILIC) and reversed-phase liquid chromatography (RPLC) were used to separate the urinary metabolites. Principle component analysis (PCA) and partial least squares to latent structure-discriminant analysis (PLS-DA) models were built to separate the healthy volunteers from the liver cancer patients and to find compounds that are expressed in significantly different amounts between the two populations. 21 metabolite ions were considered as potential biomarkers according to the Variable importance in the Project (VIP) value and S-plot. Compared with RPLC, a more sensitive and stable response can be recorded in HILIC mode due to the high content of organic solvent used. Moreover, the liver cancer group and the healthy volunteers can be better separated based on the data from the HILIC separation, which indicates that HILIC is suitable for urinary metabonomic analysis. In HILIC mode, several polar compounds related to arginine and proline metabolism, alanine and aspartate metabolism, lysine degradation, nicotinate and nicotinamide metabolism were found to be significantly changed in the concentrations of the two different populations: healthy and cancer. In contrast, in RPLC mode, these changed compounds are related to fatty acids oxidation.

Practical approach for the identification and isomer elucidation of biomarkers detected in a metabonomic study for the discovery of individuals at risk for diabetes by integrating the chromatographic and mass spectrometric information

Sensitive and high-resolution chromatographic-driven metabonomomics studies experienced major growth with the aid of new analytical technologies and bioinformatics software packages. Hence, data collections by LC-MS and data analyses by multivariate statistical methods are by far the most straightforward steps, and the detection of biomarker candidates can easily be achieved. However, the unequivocal identification of the detected metabolite candidates, including isomer elucidation, is still a crux of current metabonomics studies. Here we present a comprehensive analytical strategy for the elucidation of the molecular structure of metabolite biomarkers detected in a metabonomics study, exemplified analyzing spot urine of a cohort of healthy, insulin sensitive subjects and clinically well characterized prediabetic, insulin resistant individuals. An integrated approach of LC-MS fingerprinting, multivariate statistic analysis, LC-MSn experiments, micro preparation, FTICR-MS, GC retention index, database search, and generation of an isotope labeled standard was applied. Overall, we could demonstrate the efficiency of our analytical approach by the unambiguous elucidation of the molecular structure of an isomeric biomarker candidate detected in a complex human biofluid. The proposed strategy is a powerful new analytical tool, which will allow the definite identification of physiologically important molecules in metabonomics studies from basic biochemistry to clinical biomarker discovery.

Metabolomics study of stepwise hepatocarcinogenesis from the model rats to patients: potential biomarkers effective for small hepatocellular carcinoma diagnosis

The aim of this study is to find the potential biomarkers from the rat hepatocellular carcinoma (HCC) disease model by using a non-target metabolomics method, and test their usefulness in early human HCC diagnosis. The serum metabolic profiling of the diethylnitrosamine-induced rat HCC model, which presents a stepwise histopathological progression that is similar to human HCC, was performed using liquid chromatography-mass spectrometry. Multivariate data analysis methods were utilized to identify the potential biomarkers. Three metabolites, taurocholic acid, lysophosphoethanolamine 16:0, and lysophosphatidylcholine 22:5, were defined as “marker metabolites,” which can be used to distinguish the different stages of chemical hepatocarcinogenesis. These metabolites represented the abnormal metabolism during the progress of hepatocarcinogenesis, which could also be found in patients. To test their diagnosis potential 412 sera from 262 patients with HCC, 76 patients with cirrhosis and 74 patients with chronic hepatitis B were collected and studied, it was found that 3 marker metabolites were effective for the discrimination of small liver tumor (solitary nodules of less than 2 cm in diameter) patients, achieved a sensitivity of 80.5% and a specificity of 80.1%,which is better than those of α-fetoprotein (53 and 64%, respectively). Moreover, they were also effective for the discrimination of all HCCs and chronic liver disease patients, which could achieve a sensitivity of 87.5% and a specificity of 72.3%, better than those of α-fetoprotein (61.2 and 64%). These results indicate metabolomics method has the potential of finding biomarkers for the early diagnosis of HCC.

Urinary metabonomic study of lung cancer by a fully automatic hyphenated hydrophilic interaction/RPLC-MS system

Lung cancer is one of the most common and lethal cancers in the world. In this study, a home-devised hydrophilic interaction chromatography/RPLC-MS (HILIC/RPLC-MS) system was developed to study the urinary metabonomics of lung cancer patients. This system combined the orthogonal selectivity of HILIC and RPLC and could chromatographically reveal more comprehensive information of the urinary metabolites. Within a total analysis time of 50 min, we detected 577 polar metabolite ions on the first HILIC column and 261 apolar ones on the second RPLC column. In addition, an orthogonal signal correction partial least-squares discriminant analysis model was constructed to characterize differences between health and lung cancer cases. Eleven potential biomarkers, ten from HILIC column and one from the second RP column, were identified and all of these biomarkers were found upregulated in lung cancer patients. Overall, the results indicated that the developed HILIC/RPLC-MS system is a promising tool for metabonomic studies in revealing more information of highly complex samples.

Urinary metabolic profiling of colorectal carcinoma based on online affinity solid phase extraction-high performance liquid chromatography and ultra performance liquid chromatography-mass spectrometry

Colorectal carcinoma (CRC) is the third most commonly encountered cancer and fourth cause of cancer-associated death worldwide. Abundant studies have demonstrated that one of the best effective therapies for enhancing the 5-year survival rate of patients is to diagnose the disease at an early stage. Urine metabonomics is widely being utilized as an efficient platform to investigate the metabolic changes and discover the potential biomarkers of malignant diseases. In this study both ultra-performance liquid chromatography-mass spectrometry (UPLC-MS) and online affinity solid phase extraction-high performance liquid chromatography (SPE-HPLC) were used to analyze the urinary metabolites from 34 healthy volunteers, 34 benign colorectal tumor and 50 colorectal carcinoma patients to produce comprehensive metabolic profiling data. A reliable separation between the control and disease groups as well as significantly changed metabolites were obtained from orthogonal signal correction partial least squares models which were built based on the two separate data sets from UPLC-MS and affinity SPE-HPLC, respectively. 15 metabolites, showing the metabolic disorders of CRC, were identified finally. These metabolites were found to be related to glutamine metabolism, fatty acid oxidation, nucleotide biosynthesis and protein metabolism.