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NMR-based metabolomic profiling of urine: Evaluation for application in prostate cancer detection

MacKinnon, N.; Ge, W.; Han, P.; Siddiqui, J.; Wei, J. T.; Raghunathan, T.; Chinnaiyan, A. M.; Rajendiran, T. M.; Ramamoorthy, A.

Detection of prostate cancer (PCa) and distinguishing indolent versus aggressive forms of the disease is a critical clinical challenge. The current clinical test is circulating prostate-specific antigen levels, which faces particular challenges in cancer diagnosis in the range of 4 to 10 ng/mL. Thus, a concerted effort toward building a noninvasive biomarker panel has developed. In this report, the hypothesis that nuclear magnetic resonance (NMR)-derived metabolomic profiles measured in the urine of biopsy-negative versus biopsy-positive individuals would nominate a selection of potential biomarker signals was investigated. 1H NMR spectra of urine samples from 317 individuals (111 biopsy-negative, 206 biopsy-positive) were analyzed. A double cross-validation partial least squares-discriminant analysis modeling technique was utilized to nominate signals capable of distinguishing the two classes. It was observed that after variable selection protocols were applied, a subset of 29 variables produced an area under the curve (AUC) value of 0.94 after logistic regression analysis, whereas a “master list” of 18 variables produced a receiver operating characteristic ROC) AUC of 0.80. ... mehr

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Verlagsausgabe §
DOI: 10.5445/IR/1000095852
Veröffentlicht am 26.06.2019
DOI: 10.1177/1934578X19849978
Zitationen: 3
Web of Science
Zitationen: 3
Zitationen: 3
Cover der Publikation
Zugehörige Institution(en) am KIT Institut für Mikrostrukturtechnik (IMT)
Publikationstyp Zeitschriftenaufsatz
Publikationsjahr 2019
Sprache Englisch
Identifikator ISSN: 1555-9475, 1934-578X
KITopen-ID: 1000095852
HGF-Programm 47.01.03 (POF III, LK 01) Biol.Netzwerke u.Synth.Regulat. IMT
Erschienen in Natural product communications
Verlag SAGE Publications
Band 14
Heft 5
Vorab online veröffentlicht am 28.05.2019
Nachgewiesen in Web of Science
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