Abstract
The ability to distinguish indolent from aggressive prostate tumors remains one of the greatest challenges in the management of this disease. Ongoing efforts to establish a panel of molecular signatures, comprising gene expression profiles, proteins, epigenetic patterns, or a combination of these alterations, are being propelled by rapid advancements in 'omics' technologies. The identification of such biomarkers in biological fluids is an especially attractive goal for clinical applications. Here, we summarize recent progress in the identification of candidate prognostic biomarkers of prostate cancer using biological fluid samples.
Highlights
The ability to distinguish indolent from aggressive prostate tumors remains one of the greatest challenges in the management of this disease
Possible reasons are the complex nature of this disease leading to frequent misclassification of patients, intra-institutional variability, and patient variability, all of which contribute to the lack of well-defined and validated prognostic biomarkers
Verification and validation platforms have improved significantly; mass spectrometry-based assays with multiplexing capability can be established for the targeted quantification of specific peptides of interest
Summary
Label-free comparative analysis of the Pten-null animals and age-matched wildtype mice revealed 111 candidates from the prostate tissue and 12 candidates from the sera that were significantly differentially expressed These authors utilized SRM-MS assays to reliably quantify the 39 protein orthologs (selected on the basis of consistent quantification) in the sera of prostate cancer patients and controls, and used the resulting profiles to build predictive regression models for the diagnosis and grading of prostate cancer. Future studies will be dedicated to the verifi cation of all differentially expressed candidates, using SRM-MS in a medium-sized cohort of urinary EPS samples from clinically stratified prostate cancer patients, in order to demonstrate the application of SRM-MS as a useful verification tool for protein biomarker candidates in these fluids.
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