For Physicians Managing Voiding Dysfunction, Improving the Detection Rate of Early Prostate Cancer and Discrimination From Benign Prostatic Hyperplasia, in a Molecular Biomarker Aspects

The Prostate Health Index

PSA is a glycoprotein that binds to protease inhibitors and circulates in the blood. Only a small amount of PSA is not bound to protein; this is called free PSA (fPSA). The percentage of fPSA to total PSA (%fPSA) is significantly lower in patients with CaP than in those without. fPSA comprises three isoforms: proPSA, benign PSA, and intact PSA. The [-2]proPSA isoform is the most stable form of proPSA (referred to as p2PSA). In June 2012, the U.S. Food and Drug Administration (US FDA) approved the prostate health index (PHI) for clinical use. The test was used to detect CaP in men aged >50 years with a PSA level between 4 and 10 ng/mL and nonsuspicious DRE results. The formula for the PHI is (p2PSA/fPSA)×√total PSA [8]. A meta-analysis revealed that the PHI may reduce the number of unnecessary biopsies and be better at detecting CaP than total PSA and %fPSA, with an area under the curve (AUC) from 0.703–0.77 [9]. Another meta-analysis of PHI conducted for men with PSA levels in the “gray” area reported that the PHI and %fPSA were 0.74 and 0.63, respectively. In addition, a meta-regression analysis confirmed the superiority of PHI, which showed a relative diagnostic odds ratio of 2.81 compared with %fPSA [10]. Finally, another study showed that the PHI has a sensitivity of 0.89 and a specificity of 0.34 for detecting CaP. The sensitivity for detecting high grade CaP was 0.93 and the specificity was 0.34 [11].

The 4Kscore

The 4Kscore is a commercial test from Opko Diagnostics. The panel combines total PSA, fPSA, iPSA, and human kallikrein 2 (a glycoprotein). When used alongside DRE, the panel demonstrated very good diagnostic performance for detecting high grade CaP with Gleason score ≥7, with high AUCs [12]. However, the 4Kscore was not approved by the US FDA.

PCA3

The prostate cancer gene 3 (PCA3) was identified in 1999; this gene is expressed at much higher levels in CaP tissue than in non-neoplastic tissue [13]. Use of the PCA3 test for post-DRE urine samples was approved by the US FDA in 2012. Clinicians use the information to decide whether to repeat a prostate biopsy in men with negative biopsy results on a previous biopsy. PCA3 was more accurate than the PSA test for predicting clinically significant CaP, thereby improving the accuracy of CaP detection. Filella et al. [14] suggest that PCA3 is particularly useful for selecting patients in whom a biopsy should be repeated when the first biopsy was negative, and for detection and management of early CaP. A recent meta-analysis of case control studies revealed that the sensitivity, specificity, and AUC of the urine PCA3 test were 0.65, 0.73, and 0.75, respectively [15]. Thus, the urine PCA3 test has acceptable sensitivity and specificity for the diagnosis of CaP and can be used as a noninvasive method for that purpose. However, the cutoff value that yields the best discrimination is unclear [16].

TMPRSS2: ERG Gene Fusion Biomarkers

Gene fusions result from a combination of 2 or more separate genes to form a single chimeric gene or transcript; such fusions are an important driver of cancer. Genomic rearrangements are a major mechanism that drives prostate carcinogenesis [17]. TMPRSS2: ERG is the most common gene rearrangement found in CaP [18].

The TMPRSS2: ERG fusion gene can be detected in urine samples obtained after prostate massage. Calculation of the TMPRSS2: ERG mRNA/PSA mRNA ratio yields the TMPRSS2: ERG score. Combination of the TMPRSS2: ERG and PCA3 scores has been proposed as a way to improve prediction of whether a biopsy will detect CaP. Combined analysis of TMPRSS2: ERG and PCA3 allows detection of CaP with a diagnostic accuracy of 84%, which is significantly higher than that of the PSA test [19]. A prospective multicenter study by Leyten et al. [16] reported that TMPRSS2: ERG independently improved the predictive value of PCA3 for CaP.

Tissue miRNAs as Biomarkers

miRNAs are small RNAs (20 to 22 nucleotides in length) that modulate important cellular processes/pathways that contribute to cancer. Several studies have examined differences in expression of miRNAs between CaP and adjacent tissues [20-23]. Zhu et al. [20] reported that expression of miR-30c and miR-29b in CaP tissues was significantly lower than that in adjacent tissues. Feng et al. [21] found that tissue miR-17-92 could discriminate patients with CaP from those with BPH, making it a potential diagnostic biomarker for CaP; also, combination of the miR-17-92 cluster and serum PSA levels may increase the accuracy of CaP diagnosis. Paziewska et al. [22] showed differential expression of miR-187-3p, miR-183-5p, miR-32-5p, and miR-141-5p between BPH and CaP tissues; they also suggested that these miRNAs can differentiate between nonmalignant and malignant prostate tissue even when no neoplastic cells are detected in a biopsy specimen. We reported previously that expression of hsv1-miR-H18 and hsv2-miR-H9-5p was significantly higher in CaP tissues than in surrounding noncancerous tissues, and suggested that hsv1-miR-H18 and hsv2-miR-H9-5p might be associated with tumorigenesis in the prostate [23].

Blood miRNAs as Biomarkers

Circulating miRNAs are highly stable in the circulation; therefore, they may be useful biomarkers for improving disease diagnosis [24]. Several studies have been conducted to discriminate CaP from BPH [24-28]. Dybos et al. [25] reported that serum miR-148-3p is higher in men with CaP than in healthy controls and also located in prostate tissue. Al-Kafaji et al. [24] found that levels of miR-15a, miR-126, miR-192, and miR-377 were significantly lower in blood samples from CaP patients than in those from individuals with BPH or those from healthy patients. Receiver operating characteristic curve analysis revealed that miRNAs distinguished patients with CaP from those with BPH. Porzycki et al. [26] reported that miR-141-3p, miR-21, and miR-375 were expressed at higher levels in a CaP group than in a healthy control group; miR-375 showed an AUC value of 0.906. Tinay et al. [27] showed that expression of miR-345-5p was much higher in serum from CaP patients than in that serum from individuals without cancer, whereas Matin et al. [28] showed that miR-152-3p was elevated in plasma of CaP patients (AUC=0.88) and has the potential to improve early CaP diagnosis. However, McDonald et al. [29] reported that, after adjusting for age and P-values, no miRNAs in plasma were associated with a diagnosis of CaP. Thus, further studies are needed to identify miRNAs in blood that are suitable for CaP diagnosis.

Urine miRNAs as Biomarkers

Urinary miRNAs may be useful diagnostic markers. Many studies show the utility of urinary miRNAs [30-34]. For example, Bryant et al. [30] found that miR-107 and miR-574-3p were present in urine from CaP patients at significantly higher concentrations than in urine from controls. Rodríguez et al. [31] reported downregulation of miR-196a-5p and miR-501-3p in urinary exosomes from CaP patients, and suggested that these might serve as noninvasive biomarkers for CaP. Korzeniewski et al. [32] found that patients with CaP express higher levels of miR-483-5p in the cell-free urine fraction than control patients, whereas Lewis et al. [33] reported that expression of miR-888 in EPS urine was higher in CaP patients with high grade disease than in those with low grade disease. Srivastava et al. [34] found that imR-205 and miR-214 were significantly downregulated in urine from CaP patients, and that these miRNAs can discriminate CaP patients from healthy individuals with 89% sensitivity and 80% specificity. However, the methods used for quantitation and normalization in these studies were not standardized. Whereas most studies used urine sediment, others used supernatant or cell-free urine. Also, some samples were obtained after prostate massage and others were not. miRNA biomarkers for CaP were summarized in Table 1.

Table 1.

Studies to identify miRNA biomarkers for CaP

GC-MS

GC-MS is an analytical method that combines the features of gas chromatography and mass spectrometry to identify different substances within test samples. Many studies have used GC-MS to identify new protein biomarkers [35-40]. Jentzmik et al. [35] reported that the median sarcosine-creatinine ratio in urine was 13% lower in CaP patients (n=107) than in controls (n=45), and that sarcosine detected in urine after DRE was not a marker for detection of CaP or aggressive tumors. Wu et al. [36] used microwave-assisted derivatization together with GC/MS to obtain urinary metabolomics information from 20 CaP patients and compared it with information from eight BPH patients and 20 healthy men. There was no difference between the CaP group and the control groups in terms of urinary sarcosine levels. However, levels of propenoic acid, dihydroxybutanoic acid, and xylonic acid were significantly higher in the CaP group; these were suggested as biomarkers for CaP. Bianchi et al. [37] developed and validated a solid-phase microextraction-fast GC/MS method for direct measurement of sarcosine and N-ethylglycine in urine from CaP patients. They reported that sarconine may be a urinary biomarker for CaP, with 79% sensitivity and 87% specificity. Shamsipur et al. [38] proposed that combined measurement of sarcosine, leucine, and proline may reveal candidate biomarkers for CaP. They showed that urinary sarcosine levels in CaP patients were higher than those in controls, while urinary leucine levels were lower. Struck-Lewicka et al. [39] used GC-MS to show that alanine, acetic acid, arabitol, threonine, and glyceryl-glycoside were lower in CaP patients. Khalid et al. [40] investigated volatile organic compounds emanating from urine samples and identified four: 2,6-dimethyl-7-octen-2-ol, pentanal, 3-onctanone, and 2-ontanone. Pentanal levels were higher in CaP patients, while the levels of the other three were lower, than in healthy controls.

LC-MS

LC is a pressure-driven liquid-based separation method in which analytes are separated according to their adsorption/desorption kinetics. When coupled with MS, this technique provides high-efficiency separation and identification during a single analysis [41]. Several reports have used LC-MS to identify protein biomarkers for CaP [39,42-48]. Jiang et al. [42] developed a novel method (high performance liquid chromatography/MS) for detecting 6 compounds (sarcosine, proline, kynurenine, uracil, glycerol 3-phosphate, and creatinine) in urine samples that may show potential with respect to CaP screening. Struck-Lewicka et al. [39] used LC-MS to show that cresol, aoxo-benzeneacetic acid, xylonate, propylmalate, and hippuric acid were downregulated in urine of CaP patients. Heger et al. [43] investigated various urine parameters in CaP patients and healthy controls. They found that levels of urinary sarcosine and proline were high in CaP patients but absent from control samples. Tsoi et al. [44] used ultra-high performance LC-MS to evaluate the potential of urinary polyamines, putrescine, spermidine, and spermine as CaP biomarkers. Spermine demonstrated good diagnostic performance when discriminating between patients with CaP and those with BPH, making it a potential novel biomarker for CaP. Sroka et al. [45] revealed that arginine, homoserine, and proline were more abundant in urine samples from CaP patients; also, sarcosine was not a definitive indicator of CaP when analyzed in urine samples collected either before or after prostate massage. Fernández-peralbo et al. [46] found that 27 metabolites were present at lower concentrations in urine of CaP patients than in controls, while 7-methylguanine levels were higher in CaP patients. A connection between biochemical pathways (e.g., DNA methylation, epigenetic markers on histones, and RNA cap methylation) could explain the changes in the concentrations of potential biomarkers in individuals with CaP. Gkotsos et al. [47] observed that the median levels of sarcosine and kynurenic acid were lower, and those of uracil were higher, in CaP patients. Kynurenic acid was identified as a promising urine biomarker for CaP, while sarcosine and uracil were not significant. Finally, Dereziński et al. [48] showed that metabolic pathways associated with ethanolamine, arginine, and branched-chain amino acids could be a valuable source of markers for CaP; they also suggested that these metabolites might play a role in pathogenesis of CaP.