LC-QTOF- ESI(+)/MS Metabolomic Profile Analysis Applied to Identify Blood Biomarkers of Benign Hyperplasia and Prostate Cancer

Ramona Maria Maxim, Florina Romanciuc, Nicolae Crișan, Iulia Andras, Carmen SOCACIU

Abstract


Prostate cancer (PCa) is the second leading cause of mortality in men, the present diagnosis method being based on serum prostate-specific antigen (PSA) screening, with low specificity and overestimated values. A combined untargeted and targeted metabolomic study of metabolites from blood serum samples collected from healthy (n=11), hyperplasia (n=39) and prostate cancer (n=83) patients is presented, using the HPLC-(ESI+) QTOF-MS analysis. The profile of blood serum samples provided complementary information obtained from Base Peak Chromatograms and Dissect chromatograms. Based on dissect chromatograms, two different methods of statistical analysis were used, either based on the instrument software with automated alignments with/without normalization (Profile Analysis), or based on manual alignment followed by statistical analysis (Unscrambler10.X software). Both methods used the unsupervised Principal Component Analysis which discriminated between normal, hyperplasia and cancer patients. The second method allowed a better discrimination between groups, by qualitative and quantitative parameters (m/z values versus peak areas) and better possibilities to identify the molecules responsible for such discriminations.Considering the retention time interval (6-17 min), four molecules to be considered as putative biomarkers for hyperplasia or prostate cancer were identified: Prostaglandins E2/G2, Pregnenolone/ethyltestosterone, Lysophosphatidylcholine18:2/0:0, Galactosylceramide (18:1/24:1).By using larger patient cohorts and optimizing the data processing and chemometric analysis, more reliable biomarkers for prostate hyperplasia and cancer can be discovered and quantified. This preliminary study has had promising findings for the implementation and validation of metabolomic targeted analysis in clinical laboratories.


Keywords


untargeted/targeted metabolomics, prostate cancer, biomarkers, small metabolites, LC-MS

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DOI: http://dx.doi.org/10.15835/buasvmcn-asb:11652




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