Metabonomic Study On Bladder Cancer By RPLC And Hilic-LC Mass Spectrometry | 12962
ISSN: 2161-1165

Epidemiology: Open Access
Open Access

Like us on:

Our Group organises 3000+ Global Conferenceseries Events every year across USA, Europe & Asia with support from 1000 more scientific Societies and Publishes 700+ Open Access Journals which contains over 50000 eminent personalities, reputed scientists as editorial board members.

Open Access Journals gaining more Readers and Citations
700 Journals and 15,000,000 Readers Each Journal is getting 25,000+ Readers

This Readership is 10 times more when compared to other Subscription Journals (Source: Google Analytics)

Metabonomic Study on Bladder Cancer by RPLC and Hilic-LC Mass Spectrometry

International Conference on Epidemiology and Evolutionary Genetics

Wei Hang

Accepted Abstracts: Epidemiol

DOI: 10.4172/2161-1165.S1.004

B ladder cancer (BC) is one of the most commonly occurring tumors in the urinary system. The incidence of BC continues to rise, and mortality rates have not changed significantly in the past three decades. Given that small molecule metabolites are freely filtered into urine, the use of metabonomics through examination of patient urine is in theory an ideal means to study BC. Urine is predominantly aqueous and may contain a large proportion of polar compounds, which would typically be unretained on reversed phase (RP) systems.3 To make up for this technical deficiency, extensive hydrophilic interaction chromatography (HILIC) separations should be performed. Furthermore, HILIC allows the use of aqueous solvents, which is fully compatible with an electrospray ionization (ESI) source.4 In this study, a LC-MS based method that utilized both RPLC and HILIC separations was carried out, followed by orthogonal partial least-squares-discriminant analysis (OPLS-DA) to discriminate the global urine profiles of BC patients and healthy controls. Both RPLC and HILIC can generate good separations. Data from both columns were combined and then evaluated by external validation tests. The combined dataset depicts a more clear separation between the BC and the healthy controls than those built on the dataset from a single column. The combined OPLS-DA model correctly predicted all BC patients and healthy controls with 100% sensitivity and 100% specificity. This result shows the great potential for the combined dataset using OPLS-DA analysis as a viable technique for non-invasive BC screening.
Wei Hang has completed his PhD at the age of 27 years from Xiamen University and postdoctoral studies from University of Florida. He is a professor at Department of Chemistry, Xiamen University. He has published more than 90 papers in reputed journals.