The role of proteomics in prostate cancer research: Biomarker discovery and validation

PurposeProstate Cancer (PCa) represents the second most frequent type of tumor in men worldwide. Incidence increases with patient age and represents the most important risk factor. PCa is mostly characterized by indolence, however in a small percentage of cases (3%) the disease progresses to a metastatic state. To date, the most important issue concerning PCa research is the difficulty in distinguishing indolent from aggressive disease. This problem frequently results in low-grade PCa patient overtreatment and, in parallel; an effective treatment for distant and aggressive disease is not yet available.ResultProteomics represents a promising approach for the discovery of new biomarkers able to improve the management of PCa patients. Markers more specific and sensitive than PSA are needed for PCa diagnosis, prognosis and response to treatment. Moreover, proteomics could represent an important tool to identify new molecular targets for PCa tailored therapy. Several possible PCa biomarkers sources, each with advantages and limitations, are under investigation, including tissues, urine, serum, plasma and prostatic fluids. Innovative high-throughput proteomic platforms are now identifying and quantifying new specific and sensitive biomarkers for PCa detection, stratification and treatment. Nevertheless, many putative biomarkers are still far from being applied in clinical practice.ConclusionsThis review aims to discuss the recent advances in PCa proteomics, emphasizing biomarker discovery and their application to clinical utility for diagnosis and patient stratification.

► PCa research main issue is to discriminate between indolent and aggressive disease.
► Proteomics allows the biomarkers discovery to improve the PCa patients management.
► Tissues and body fluids are useful sources for PCa biomarkers.
► Biomarkers improve PCa diagnosis, prognosis and cases selection for treatment.
► New high-throughput proteomic platforms identify and quantify PCa biomarkers.