title: HR-MAS NMR tissue metabolomic signatures cross-validated by mass spectrometry distinguish bladder cancer from benign disease.
abstract: Effective diagnosis and surveillance of bladder cancer (BCa) is currently challenged by detection methods that are of poor sensitivity, particularly for low-grade tumors, resulting in unnecessary invasive procedures and economic burden. We performed HR-MAS NMR-based global metabolomic profiling and applied unsupervised principal component analysis (PCA) and hierarchical clustering performed on NMR data set of bladder-derived tissues and identified metabolic signatures that differentiate BCa from benign disease. A partial least-squares discriminant analysis (PLS-DA) model (leave-one-out cross-validation) was used as a diagnostic model to distinguish benign and BCa tissues. Receiver operating characteristic curve generated either from PC1 loadings of PCA or from predicted Y-values resulted in an area under curve of 0.97. Relative quantification of more than 15 tissue metabolites derived from HR-MAS NMR showed significant differences (P < 0.001) between benign and BCa samples. Noticeably, striking metabolic signatures were observed even for early stage BCa tissues (Ta-T1), demonstrating the sensitivity in detecting BCa. With the goal of cross-validating metabolic signatures derived from HR-MAS NMR, we utilized the same tissue samples to analyze 8 metabolites through gas chromatography-mass spectrometry (GC-MS)-targeted analysis, which undoubtedly complements HR-MAS NMR-derived metabolomic information. Cross-validation through GC-MS clearly demonstrates the utility of a straightforward, nondestructive, and rapid HR-MAS NMR technique for clinical diagnosis of BCa with even greater sensitivity. In addition to its utility as a diagnostic tool, these studies will lead to a better understanding of aberrant metabolic pathways in cancer as well as the design and implementation of personalized cancer therapy through metabolic modulation.
authors.affiliation: Departments of Chemistry and Biophysics, University of Michigan, Ann Arbor, Michigan 48109, USA.
authors.forename: Pratima
authors.initials: P
authors.lastname: Tripathi
authors.forename: Bagganahalli S
authors.initials: BS
authors.lastname: Somashekar
authors.forename: M
authors.initials: M
authors.lastname: Ponnusamy
authors.forename: Amy
authors.initials: A
authors.lastname: Gursky
authors.forename: Stephen
authors.initials: S
authors.lastname: Dailey
authors.forename: Priya
authors.initials: P
authors.lastname: Kunju
authors.forename: Cheryl T
authors.initials: CT
authors.lastname: Lee
authors.forename: Arul M
authors.initials: AM
authors.lastname: Chinnaiyan
authors.forename: Thekkelnaycke M
authors.initials: TM
authors.lastname: Rajendiran
authors.forename: Ayyalusamy
authors.initials: A
authors.lastname: Ramamoorthy
mesh_terms: D000328:Adult; D000368:Aged; D000369:Aged, 80 and over; D002849:Chromatography, Gas; D003937:Diagnosis, Differential; D004734:Energy Metabolism; D005260:Female; D006801:Humans; D009682:Magnetic Resonance Spectroscopy; D008297:Male; D013058:Mass Spectrometry; D053858:Metabolic Networks and Pathways / Q000235:genetics*; D055442:Metabolome; D008875:Middle Aged; D009367:Neoplasm Staging; D009369:Neoplasms; D025341:Principal Component Analysis; D001743:Urinary Bladder / Q000473:pathology*; D001749:Urinary Bladder Neoplasms / Q000175:diagnosis* / Q000378:metabolism* / Q000473:pathology