Background: Lower urinary tract symptoms (LUTS) and prostate specific antigen-based parameters seem to have only a limited utility for the differential diagnosis of prostate cancer (PCa). MALDI-TOF/MS peptidomic profiling could be a useful diagnostic tool for biomarker discovery, although reproducibility issues have limited its applicability until now. The current study aimed to evaluate a new MALDI-TOF/MS candidate biomarker. Methods: Within-and between-subject variability of MALDI-TOF/MS-based peptidomic urine and serum analyses were evaluated in 20 and 15 healthy donors, respectively. Normalizations and approaches for accounting below limit of detection (LOD) values were utilized to enhance reproducibility, while Monte Carlo experiments were performed to verify whether measurement error can be dealt with LOD data. Post-prostatic massage urine and serum samples from 148 LUTS patients were analysed using MALDI-TOF/MS. Regression-calibration and simulation and extrapolation methods were used to derive the unbiased association between peptidomic features and PCa. Results: Although the median normalized peptidomic variability was 24.9%, the within-and between-subject variability showed that median normalization, LOD adjustment, and log(2) data transformation were the best combination in terms of reliability; in measurement error conditions, intraclass correlation coefficient was a reliable estimate when the LOD/2 was substituted for below LOD values. In the patients studied, 43 peptides were shared by the urine and serum, and several features were found to be associated with PCa. Only few serum features, however, show statistical significance after the multiple testing procedures were completed. Two serum fragmentation patterns corresponded to the complement C4-A. Conclusions: MALDI-TOF/MS serum peptidome profiling was more efficacious with respect to post-prostatic massage urine analysis in discriminating PCa.

MALDI-TOF peptidomic analysis of serum and post-prostatic massage urine specimens to identify prostate cancer biomarkers

Padoan, Andrea;Basso, Daniela
;
Zambon, Carlo-Federico;Arrigoni, Giorgio;Bozzato, Dania;Moz, Stefania;Zattoni, Filiberto;Plebani, Mario
2018

Abstract

Background: Lower urinary tract symptoms (LUTS) and prostate specific antigen-based parameters seem to have only a limited utility for the differential diagnosis of prostate cancer (PCa). MALDI-TOF/MS peptidomic profiling could be a useful diagnostic tool for biomarker discovery, although reproducibility issues have limited its applicability until now. The current study aimed to evaluate a new MALDI-TOF/MS candidate biomarker. Methods: Within-and between-subject variability of MALDI-TOF/MS-based peptidomic urine and serum analyses were evaluated in 20 and 15 healthy donors, respectively. Normalizations and approaches for accounting below limit of detection (LOD) values were utilized to enhance reproducibility, while Monte Carlo experiments were performed to verify whether measurement error can be dealt with LOD data. Post-prostatic massage urine and serum samples from 148 LUTS patients were analysed using MALDI-TOF/MS. Regression-calibration and simulation and extrapolation methods were used to derive the unbiased association between peptidomic features and PCa. Results: Although the median normalized peptidomic variability was 24.9%, the within-and between-subject variability showed that median normalization, LOD adjustment, and log(2) data transformation were the best combination in terms of reliability; in measurement error conditions, intraclass correlation coefficient was a reliable estimate when the LOD/2 was substituted for below LOD values. In the patients studied, 43 peptides were shared by the urine and serum, and several features were found to be associated with PCa. Only few serum features, however, show statistical significance after the multiple testing procedures were completed. Two serum fragmentation patterns corresponded to the complement C4-A. Conclusions: MALDI-TOF/MS serum peptidome profiling was more efficacious with respect to post-prostatic massage urine analysis in discriminating PCa.
2018
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11577/3292902
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