Coradduzza D, Azara E, Medici S, Arru C, Solinas T, Madonia M, Zinellu A, Carru C. A preliminary study procedure for detection of polyamines in plasma samples as a potential diagnostic tool in prostate cancer.
J Chromatogr B Analyt Technol Biomed Life Sci 2020;
1162:122468. [PMID:
33370684 DOI:
10.1016/j.jchromb.2020.122468]
[Citation(s) in RCA: 10] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/15/2020] [Revised: 11/18/2020] [Accepted: 11/19/2020] [Indexed: 12/15/2022]
Abstract
BACKGROUND
Many scientific contributions recognize polyamines as important biomarkers for the diagnosis and treatment of cancer. Several authors have suggested the use of LC/MS instruments as an elective method for their measurement, providing good detection limits and specificity; however, many of these procedures suffer from long chromatographic run times, high detection limits and lengthy and expensive sample pre-treatment steps.
METHODS
UHPLC coupled with high-resolution Orbitrap mass spectrometry (UHPLC/Orbitrap) was set up for the identification and separation ofpolyamines, together with some of their metabolites and catabolites, in the plasma of healthy and prostate cancer human patients. Thirteen metabolites were measured in deproteinized plasma samples through a new analytical approach known as the parallel reaction monitoring (PRM) for targeted quantitative analysis.
RESULTS
The calibration curves were linear and R2 ranged from 0.9913 to 0.9995 for all analytes. LOQ values are between 0.382 and 25 ng mL-1 and LOD values are between 0.109 and 7.421 ng mL-1. The method shows an accuracy and precision for intra-day and inter-day < 15% RSD and R.E.% for all the QC samples. The matrix effect calculated at different concentration levels did not exceed 15%.
CONCLUSIONS
The method developed provides rapid, easy and robust identification and measurement of a wide range of polyamines, and some of their metabolites that can be evaluated as biomarkers to predict the clinical features of prostate cancer patients, avoiding invasive diagnostic procedures.
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