Prostate Cancer Detection and Prognosis: From Prostate Specific Antigen (PSA) to Exosomal Biomarkers.

Xavier Filella,Laura Foj

doi:10.3390/ijms17111784

Abstract

Prostate specific antigen (PSA) remains the most used biomarker in the management of early prostate cancer (PCa), in spite of the problems related to false positive results and overdiagnosis. New biomarkers have been proposed in recent years with the aim of increasing specificity and distinguishing aggressive from non-aggressive PCa. The emerging role of the prostate health index and the 4Kscore is reviewed in this article. Both are blood-based tests related to the aggressiveness of the tumor, which provide the risk of suffering PCa and avoiding negative biopsies. Furthermore, the use of urine has emerged as a non-invasive way to identify new biomarkers in recent years, including the PCA3 and TMPRSS2:ERG fusion gene. Available results about the PCA3 score showed its usefulness to decide the repetition of biopsy in patients with a previous negative result, although its relationship with the aggressiveness of the tumor is controversial. More recently, aberrant microRNA expression in PCa has been reported by different authors. Preliminary results suggest the utility of circulating and urinary microRNAs in the detection and prognosis of PCa. Although several of these new biomarkers have been recommended by different guidelines, large prospective and comparative studies are necessary to establish their value in PCa detection and prognosis.

Highlights

Prostate cancer (PCa) remains a medical challenge, since it is one of the most frequently diagnosed tumors and a common cause of cancer death among men in western countries [1]
Preliminary results suggest the utility of circulating and urinary microRNAs in the detection and prognosis of prostate cancer (PCa). Several of these new biomarkers have been recommended by different guidelines, large prospective and comparative studies are necessary to establish their value in PCa detection and prognosis
Guazzoni et al [20] showed an improvement in the area under the curve (AUC) by including %[−2]proPSA (0.82) or the Prostate Health Index (PHI) (0.83) in a model based on the patient age, prostate volume, prostate specific antigen (PSA) and %fPSA (0.72)

Summary

Introduction

Prostate cancer (PCa) remains a medical challenge, since it is one of the most frequently diagnosed tumors and a common cause of cancer death among men in western countries [1]. Guazzoni et al [20] showed an improvement in the AUC by including %[−2]proPSA (0.82) or the PHI (0.83) in a model based on the patient age, prostate volume, PSA and %fPSA (0.72). Filella et al [21] showed that the AUC increased from 0.762 to 0.802 (using a logistic regression analysis) or 0.815 (using an artificial neural network) when the PHI and %[−2]proPSA were included in a multivariate model based on patient age, prostate volume, PSA and %fPSA. The PHI increased significantly the accuracy obtained using a multivariable logistic regression model based on patient age, prostate volume, DRE and biopsy history from 0.73 to 0.80 External validation of this model was provided by a multicenter European study based on 833 patients, showing an accuracy of 0.752 [23]. The model predicted a reduction of 23% in negative biopsies for men with PSA between 3 and 10 μg/L, concluding that PHI testing is 11% more cost-effective than screening only based on PSA

Kallikrein Panel

Urine-Based PCa Biomarkers

Exosomal Biomarkers

Clinical Results

Conclusions