1. A PSA-guided approach for a better diagnosis of prostatic adenocarcinoma based on MALDI profiling and peptide identification.
- Author
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Fania C, Sogno I, Vasso M, Torretta E, Leone R, Bruno A, Consonni P, Albini A, and Gelfi C
- Subjects
- Adenocarcinoma blood, Adenocarcinoma immunology, Aged, Aged, 80 and over, False Negative Reactions, Humans, Male, Middle Aged, Prostate-Specific Antigen immunology, Prostatic Neoplasms blood, Prostatic Neoplasms immunology, Adenocarcinoma diagnosis, Prostate-Specific Antigen blood, Prostatic Neoplasms diagnosis, Spectrometry, Mass, Matrix-Assisted Laser Desorption-Ionization
- Abstract
Background: Prostate cancer (PCa) is the second cause of mortality in men worldwide. The prostate-specific antigen (PSA) test is routinely adopted in diagnosis; nevertheless more reliable biomarkers are continuously under investigation by monitoring the release of molecules into the bloodstream. The serum protein profiles appear to provide cancer-specific fingerprints that help to discriminate patients (especially with low PSA level) from controls, improving the performance of existing clinical tests., Methods: Samples from healthy controls and PCa patients with low (≤4 ng/mL) and high PSA (>4 ng/mL) levels were analyzed by MALDI profiling, and by a multi fractionation approach coupled to ESI-MS for peaks identification., Results: MALDI profiling achieved to detect 10 and 14 changed peaks (p-value <0.05), respectively, in PCa patients with low and high PSA versus controls. In particular, a peak identified as C3f fragment, resulted overexpressed in low PSA PCa patients., Conclusions: PSA test, coupled to MALDI profiling, is able to detect changes, specifically related to PCa, in low molecular weight protein range. Furthermore, for the first time in prostate cancer research, the identification and quantification of the small peptide C3f appears to be relevant for the detection of false negatives, providing an additive diagnostic power to PSA (p<0.01) and suggesting its use in clinical tests., (Copyright © 2014 Elsevier B.V. All rights reserved.)
- Published
- 2015
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