Hearing impairment in newborn children is one of the most frequent forms of sensorineural disorders, affecting 1 in 1000 infants. In half of the cases the hearing loss has a genetic basis, and over 70 genes have been identified so far, making hearing loss genetically exceptionally heterogeneous. Early detection in newborns, in combination with a genetic diagnosis is critical for the selection of a proper intervention and the development of speech, language and communication skills.

by Dr Isabelle Schrauwen

Hearing impairment in infants can be due to environmental influences such as cytomegalovirus infection, but in industrialized countries, however, most cases of early-onset hearing impairment have a genetic basis. Genetic hearing loss is non-syndromic in 70% of cases, whereas other symptoms (apart from hearing loss) are noticeable in 30% of cases (syndromic hearing loss). Autosomal recessive non-syndromic hearing loss (ARNSHL) is most common (80%) and is typically prelingual in onset, and autosomal dominant non-syndromic hearing loss (ADNSHL), X-linked and mitochondrial hearing loss are less frequent (20 and <1% respectively). To date, over 70 genes have been found to be implicated in non-syndromic hearing loss (NSHL), of which 40 are autosomal recessive. The most frequent causes of ARNSHL in most populations are mutations in GJB2, with a frequency ranging from 10 to 50% of all ARNSHL cases.

The implementation of newborn hearing screening in many countries has lead to an early detection of hearing loss and deafness in infants. This, together with improved genetic diagnostics and neuroimaging, has lead to a better understanding and better intervention of hearing loss overall [1].

The importance of a genetic diagnosis in pediatric hearing impairment
Clinical tests are not always sufficient for an accurate diagnosis and genetic diagnostics can provide answers that clinical tests cannot. Identification of the genetic cause can help predict the progression of the hearing loss and also direct the choice of the most appropriate treatment or method of communication. In addition, some apparent forms of non-syndromic hearing loss can be diagnosed to be syndromic as they give other symptoms at a later age (such as goitre in Pendred syndrome or retinitis pigmentosa in Usher syndrome). For Usher syndrome, preventative measures can be taken including sunlight protection and vitamin therapy to minimize the rate of progression of retinitis pigmentosa [2]. Furthermore, autosomal recessive mutations in GJB2 often cause a stable form of hearing loss and patients usually have good prospects with a cochlear implant. Knowing the gene responsible can also be very important to the parents, reducing their feelings of guilt and predicting the likelihood of subsequent children having hearing loss.

In addition, more extensive screening will also be very useful in providing a more accurate picture of the prevalence of different types of deafness affecting people across the world. Finally, advances in molecular and cellular therapies for hearing loss are also gene-specific [3], and identification of the genetic cause is key.

Gene-specific sequencing
Until recently, routine molecular diagnostics for hearing impairment consisted of the gene-specific sequencing of certain deafness genes, mainly with Sanger sequencing. GJB2 testing is offered most frequently in routine diagnostics, as it is responsible for a large number of ARNSHL cases. When there is evidence of progression of the hearing loss, or the presence of a goitre, an enlarged vestibular aqueduct (EVA), or Mondini dysplasia, SLC26A4 will be analysed, and when a specific phenotype is seen, other genes might also be analysed (OTOF, TECTA, COCH, WFS1, or a mitochondrial mutation). The selection criteria are typically: (1) high frequency cause of deafness (i.e. GJB2); (2) association with another recognizable feature (i.e. SLC26A4 and EVA); or (3) a recognizable
audioprofile (i.e. WFS1) [4].

Syndromic forms of deafness usually only have one or a few candidate genes responsible for each syndrome. However, for non-syndromic deafness, it is very difficult, and often impossible, to determine candidate genes because of the large number of causative genes leading to a relatively indistinguishable phenotype. GJB2 sequencing will identify 10–50% of ARNSHL cases, but the remaining cases of hearing loss display a high degree of genetic heterogeneity and unless a specific audioprofile is present it is hard to diagnose these with a gene-specific test. Traditionally, with gene-specific tests, it has therefore been difficult to establish a genetic diagnosis due to extreme genetic heterogeneity and a lack of phenotypic variability.

Microarrays
The analysis of multiple mutations in several genes in parallel was made possible by the development of single nucleotide extension microarrays [5]. These microarrays detect a specific mutation by hybridizing primers to patient DNA, followed by a single base extension. This technology therefore only detects known mutations, and a panel of 198 mutations in 8 genes [GJB2, GJB6, GJB3, GJA1, SLC26A4, SLC26A5 and the mitochondrial genes encoding 12S rRNA and tRNA-Ser(UCN)] underlying sensorineural (mostly non-syndromic) hearing loss has been developed [5]. Although new mutations cannot be picked up, this technique can provide some additional diagnostic value in GJB2 negative cases.

An Affymetrix resequencing microarray capable of resequencing 13 genes mutated in NSHL was also developed (GJB2, GJB6, CDH23, KCNE1, KCNQ1, MYO7A, OTOF, PDS, MYO6, SLC26A5, TMIE, TMPRSS3, USH1C) [6], but the number of genes here is also limited and specific kinds of mutations such as insertion/deletion (indel) mutations cannot be detected accurately.

Custom gene enrichment with next-generation sequencing
The need for new and better diagnostic methods for extremely heterogeneous diseases has been filled by the availability of next-generation sequencing, which has made it possible to sequence a large number of genes at the same time. This has lead to an immense growth of custom hearing-loss gene panels. Several labs have adopted this approach in-house already [7–9], and several labs offer this test for ARNSHL, ADNSHL, some cases of syndromic hearing loss, or all of the above.

The most commonly available systems for massive parallel sequencing are: Illumina, 454, or SOLiD. The Illumina platform is the most widely used platform to date and relies on cyclic reversible termination technology. Before massive parallel sequencing, DNA will be enriched for a custom selection of hearing-loss genes. In a diagnostic setting, sensitivity and specificity are important, and different enrichment methods perform differently in these criteria. Capture enrichment methods have been used more often and are easy to use, but PCR-based methods seem to have a better performance. A portion of targeted bases in repetitive regions cannot be captured, whereas PCR is able to enrich 100% of the desired target area. This is crucial to the sensitivity of detecting variants.

Although PCR-based techniques are usually more labour-intensive, microdroplet PCR methods have improved this greatly [9]. By using barcoding, custom hearing-loss panels are now offered for a competitive price in several labs across the world, and depending on the genes included in the panel, will offer a genetic diagnosis in the majority of cases.

Exome sequencing
Exome sequencing is also emerging as a diagnostic tool for many diseases and has decreased in price significantly in recent years. Exome sequencing targets every coding exon in the genome for enrichment prior to next-generation sequencing. Though current exome kits provide insufficient target enrichment in a diagnostic setting for deafness [9], as the regions of interest might not been completely covered and coverage depth may not be high enough for a diagnostic setting. Exome sequencing has therefore a decreased sensitivity to detect mutations in known genes compared to the custom panels available, but does allow the identification of new genes. In addition, given the amount of data that arises from exome sequencing, identification of the causative mutation among the list of variants will be more challenging. Although over 70 genes have already been discovered, there are still many more to be found, and the identification of new genes will greatly improve our understanding of deafness. Since its introduction, exome sequencing has lead to a fast rise in the identification of hearing-loss-related genes.

Future techniques and conclusions
Other technologies, such as Ion torrent, Pacific Biosystems, and specifically the emerging Oxford Nanopore technique, might offer very cost-effective sequencing methods for the future of molecular diagnostics in many diseases. Furthermore, genome sequencing might be shown useful in the diagnosis of hearing loss if the price of sequencing keeps dropping.

In conclusion, a genetic test ideally has to be sensitive, specific, accurate and low in cost. Gene-specific analysis of GJB2 will detect a 10–40% of ARNSHL cases, and custom gene panels with next-generation sequencing will provide a diagnosis in the majority of genetic hearing-loss cases. It is anticipated that within the coming years genetic testing will be routinely implemented in pediatric hearing loss, leading to better intervention and choice of treatment.

References
1. Paludetti G, et al. Infant hearing loss: from diagnosis to therapy Official Report of XXI Conference of Italian Society of Pediatric Otorhinolaryngology. Acta Otorhinolaryngol Ital 2012; 32: 347–70.
2. Hamel C. Retinitis pigmentosa. Orphanet J Rare Dis 2006; 1: 40.
3. Hildebrand MS, et al. Advances in molecular and cellular therapies for hearing loss. Mol Ther 2008; 16: 224–36.
4. Hilgert N, et al. Forty-six genes causing nonsyndromic hearing impairment: which ones should be analyzed in DNA diagnostics? Mutation Res 2009; 681: 189–96.
5. Gardner P, et al. Simultaneous multigene mutation detection in patients with sensorineural hearing loss through a novel diagnostic microarray: a new approach for newborn screening follow-up. Pediatrics 2006; 118: 985–94.
6. Kothiyal P, et al. High-throughput detection of mutations responsible for childhood hearing loss using resequencing microarrays. BMC Biotechnol 2010; 10: 10.
7. Shearer AE, et al. Comprehensive genetic testing for hereditary hearing loss using massively parallel sequencing. Proc Natl Acad Sci U S A 2010; 107: 21104–9.
8. Brownstein Z, et al. Targeted genomic capture and massively parallel sequencing to identify genes for hereditary hearing loss in Middle Eastern families. Genome Biol 2011; 12: R89.
9. Schrauwen I, et al. (2013) A sensitive and specific diagnostic test for hearing loss using a microdroplet PCR-based approach and next generation sequencing. Am J Med Genet A 2013; 161A: 145–52.

The author
Isabelle Schrauwen PhD ^1,2
1 Department of Medical Genetics, University of Antwerp, Antwerp, Belgium
² The Translational Genomics Research Institute (TGen), Phoenix, AZ, USA
E-mail: isabelle.schrauwen@ua.ac.be

Inflammation is of importance for the progression of coronary artery disease. Until now, there has been no biomarker to monitor the effect of treatment regimes. YKL-40 is a new biomarker of inflammation, which if highly elevated in the disease, is a strong prognostic predictor of death and potentially can be used to monitor disease activity.

by Prof. J. Kastrup, Dr M. Harutyunyan-Bønsager and Dr N. D. Mygind

Clinical background
The number of patients with coronary artery disease (CAD) is increasing worldwide, and CAD is the most common cause of death in western countries. Although the prognosis and quality of life for patients has improved due to more aggressive and invasive treatment regimes, in the US someone will have a coronary event approximately every 25 seconds, and someone will die of one approximately every minute. Therefore CAD is an increasing economic burden and the total estimated direct and indirect costs of CAD in the US in 2010 were $503.2 billion [1].

Currently, there is a lack of new biomarkers for monitoring the effect of the patients’ treatment and for predicting their risk of a heart attack, heart failure and cardiac death.

Coronary artery disease and inflammation
It has been well established that inflammation plays an important role in development and progression of atherosclerosis in the coronary arteries [2]. Moreover, inflammation is also involved in the inflammatory pathways inducing extracellular matrix remodelling and heart failure progression [3]. The inflammatory biomarker high-sensitivity C-reactive protein (hs-CRP) is associated with atherosclerosis and the incidence of coronary events [4], but its association with the extent and severity of atherosclerosis remains controversial. Therefore, it is not very useful for continuous monitoring of treatment effects and progression of the disease.

The inflammatory biomarker YKL-40
YKL-40 is a glycoprotein mainly produced by macrophages and neutrophils, which are important for the development of atherosclerosis, and is stimulated by hypoxia [5]. Serum YKL-40 is suggested to be a biomarker of diseases characterized by inflammation [5] and its plasma concentration has been shown to increase reversibly in patients by more than 25% following an inflammatory stimulus.

YKL-40 is not a disease specific biomarker, but plays a role in cell migration and adhesion, angiogenesis, remodelling of the extracellular matrix, cell proliferation and differentiation [5]. Macrophages in atherosclerotic plaques, especially those located more deeply in the atherosclerotic lesion, express YKL-40 [6], and macrophages in early atherosclerotic lesions express the highest amount of YKL-40 mRNA. As Hs-CRP is mainly produced in the liver, it is likely that biomarkers such as YKL-40 (secreted from inflammatory cells within the atherosclerotic plaque) could be superior for monitoring CAD.

YKL-40 in healthy subjects
The normal YKL-40 value in a healthy subject from the general population has recently been published [7]. In 3130 subjects the median YKL-40 value was 40 µg/L and increased exponentially with age.

YKL-40 in coronary artery disease
Serum YKL-40 has been found to be increased in both acute and coronary artery disease [8]. Serum YKL-40 levels were also significantly increased in patients with acute ST-elevation myocardial infarction and thereafter consistently decreased from a maximum value just after the myocardial infarction and during a 360 day follow-up period towards its normal levels. Plasma YKL-40 levels were found to correlate inversely with left ventricular ejection fraction (LVEF) recovery, but not with infarct size in patients with STEMI [9, 10].

Although highly increased in patients with stable CAD, it has not been possible to detect any relationship between serum YKL-40 level and the degree of CAD as evaluated by the number of vessels involved or the degree of artery stenosis [11]. In patients with stable CAD, revascularization with balloon angioplasty of significant stable coronary artery lesions has no effect on YKL-40 levels within a 6 month follow-up period (unpublished data).

This indicates that YKL-40 not is a measurement of the amount of ischemia within the myocardium. Serum YKL-40 seems to be more a measurement of ongoing inflammatory activity rather than the presence of stabilized chronic lesions.

Therefore, it is very interesting that serum YKL-40 was a very strong prognostic biomarker for death within a 2.6 and 6 year follow-up period in patients with stable CAD [12, 13] [Fig. 1].

YKL-40 and heart failure
The consequence of CAD is often the development of severe heart failure. It has recently been demonstrated that serum YKL-40 is increased in heart failure and that YKL-40 is an independent significant prognostic biomarker for death [15]. It is interesting that serum YKL-40 measured in all-comers at acute hospital admission is a very strong predictor of death, especially within the first year, in patients with heart disease [16]. Of patients admitted with disease of the heart, those with elevated YKL-40 had a hazard ratio of death within the first year after discharge from the hospital at 2.5 compared to heart patients with normal serum YKL-40 levels. YKL-40 remained an independent biomarker of mortality, even after adjusting for other known risk factors such as age, hs-CRP and NT-proBNP [16].

YKL-40 for monitoring CAD activity
Statin treatment is used in CAD for lowering cholesterol levels. However, it also has an anti-inflammatory action. Therefore, it is very interesting that serum YKL-40 is significantly lower in patients with stable CAD on statin treatment compared to patients without [14] [Fig. 2].

This difference seems to be independent of the effect that statins have on lowering cholesterol levels, indicating that the YKL-40 level can be regulated by the direct anti-inflammatory action of statins [14]. This is unlike the situation with the inflammatory biomarker hs-CRP, which has been shown to correlate to cholesterol levels in statin-treated CAD patients [14].

Moreover, the mortality is also lower in stable CAD on statins compared to non-statins [12, 13]. This indicates that YKL-40 could be used to monitor the anti-inflammatory effect of statin treatment. Whether YKL-40 is also useful for
monitoring the effects of other anti-angina medications remains to be investigated.

Conclusion and future perspective
YKL-40 is a new inflammatory biomarker in ischemic heart disease. It is increased in both acute and chronic coronary artery disease and is a very strong diagnostic biomarker for death. It is suggested to be a mirror of the active inflammatory atherosclerotic processes in CAD, more than a measurement of degree of myocardial ischemia induced by stable coronary lesions. Since YKL-40 is lower in patients on statin treatment, it can potentially be used to monitor disease activity and the effect of anti-inflammatory or stabilizing treatment regimes.

Conflict of interest
A patent application (WO 2009/092382) is published and pending.

References
1. Roger VL, Go AS, Lloyd-Jones DM, Benjamin EJ, Berry JD, Borden WB, et al. Circulation 2012; 125(1): e2–e220.
2. Hansson GK. J Thromb Haemost 2009; 7 Suppl 1: 328–331.
3. Radauceanu A, Ducki C, Virion JM, Rossignol P, Mallat Z, McMurray J, et al. J Card Fail 2008; 14(6): 467–474.
4. Corrado E, Rizzo M, Coppola G, Fattouch K, Novo G, Marturana I, et al. J Atheroscler Thromb 2010; 17(1): 1–11.
5. Kastrup J. Immunobiology 2012; 217(5): 483–491.
6. Boot RG, van Achterberg TA, van Aken BE, Renkema GH, Jacobs MJ, Aerts JM, et al. Arterioscler Thromb Vasc Biol 1999; 19(3): 687–694.
7. Bojesen SE, Johansen JS, Nordestgaard BG. Clin Chim Acta 2011; 412: 709–712.
8. Wang Y, Ripa RS, Johansen JS, Gabrielsen A, Steinbruchel DA, Friis T, et al. Scand Cardiovasc J 2008; 42(5): 295–302.
9. Nojgaard C, Host NB, Christensen IJ, Poulsen SH, Egstrup K, Price PA, et al. Coron Artery Dis 2008; 19(4): 257–263.
10. Hedegaard A, Ripa RS, Johansen JS, Jorgensen E, Kastrup J. Scand J Clin Lab Invest 2010; 70(2): 80–86.
11. Mathiasen AB, Harutyunyan MJ, Jorgensen E, Helqvist S, Ripa R, Gotze JP, et al. Scand J Clin Lab Invest 2011; 71(5): 439–447.
12. Kastrup J, Johansen JS, Winkel P, Hansen JF, Hildebrandt P, Jensen GB, et al. Eur Heart J 2009; 30(9): 1066–1072.
13. Harutyunyan M, Gotze JP, Winkel P, Johansen JS, Hansen JF, Jensen GB, Hilden J, Kjøller E, Kolmos HJ, Gluud C, Kastrup J. Immunobiology 2013; 218(7): 945–951.
14. Mygind ND, Harutyunyan MJ, Mathiasen AB, Ripa RS, Thune JJ, Gotze JP, et al. Inflamm Res 2011; 60(3): 281–287.
15. Harutyunyan M, Christiansen M, Johansen JS, Køber L, Torp-Petersen C, Kastrup J. Immunobiology. 2012; 217(6): 652–656.
16. Mygind ND, Iversen K, Køber L, Goetze JP, Nielsen H, Boesgaard S, Bay M, Johansen JS, Nielsen OW, Kirk V, Kastrup J. J Intern Med 2013; 273(2): 205–216.

The authors
Jens Kastrup* MD, DMSc; Marina Harutyunyan-Bønsager MD; and Naja Dam Mygind MD

Department of Cardiology B, The Heart Centre, Rigshospitalet Copenhagen University Hospital, Copenhagen, Denmark

*Corresponding author
E-mail: jens.kastrup@regionh.dk

Prostate specific antigen (PSA) has significantly improved the early detection of prostate cancer (PCa), reducing the related mortality rate. However, PSA has a low specificity, being affected by many benign conditions. [-2]proPSA, a PSA precursor, is a more specific and accurate biomarker indicating prostate biopsy in men at real risk of PCa.

by Dr A. Abrate, Dr M. Lazzeri and Prof. G. Guazzoni

PSA as a marker for prostate cancer
Prostate specific antigen (PSA) is a serum marker widely used for the early detection of prostate cancer (PCa). Its introduction into clinical practice in the early 1990s had an extraordinary impact on the diagnosis and management of PCa. In fact, 20 years after its introduction, the PSA-based PCa opportunistic or systematic screening has resulted in a stage migration to more organ-confined tumours at the time of diagnosis, and consequently to a consistent reduction in PCa related mortality [1, 2]. However, PSA is not a perfect marker for the detection of PCa because of its low specificity and sensitivity. Its levels may increase as a result of benign conditions, such as benign prostatic hyperplasia (BPH) and chronic prostatitis. Moreover, PSA levels are also affected by biologic variability, which may be related to differences in androgen levels, prostate manipulation or ejaculation. Finally, alterations in PSA levels may be related to sample handling, laboratory processing, or assay standardization. All these factors made it difficult to find an appropriate PSA cut-off point diagnostic for PCa (for many years considered to be 4 ng/ml).

Thus, prostate biopsy is still mandatory to confirm the diagnosis. However, this is positive in only approximately 30% of patients [3], and the European Association of Urology suggests a repeat biopsy if PSA is persistently elevated, the digital rectal examination (DRE) is suspicious, or there is a pathological diagnosis of atypical small acinar proliferation (ASAP) or high-grade prostatic intraepithelial neoplasia (HG-PIN) [4]. Finally, PCa (also high-grade cancer) is not rare (approximately 15.2%) among men with PSA levels lower than 4 ng/ml, the previously widely accepted cut-off point [5].

Considering all these observations, it is clear that PSA is an organ-specific rather than an ideal cancer-specific marker.

The introduction into clinical practice of measuring the levels of several derivatives of PSA (free PSA, percentage of free PSA, PSA density, PSA velocity) improved the accuracy of total PSA (tPSA) in detecting PCa. Recently, free PSA (fPSA) has been found to include several subforms, such as proPSA. In particular [-2]proPSA seems to be specific for PCa, opening new ways for early cancer detection.

Biological basis of proPSA
The currently measurable serum tPSA consists of either a complexed form (cPSA, 70–90%), bound by protease inhibitors (primarily alpha1-antichymotrypsin), and a non-complexed form (fPSA). Recently fPSA has been discovered to exist in at least three molecular forms: proPSA, benign PSA (BPSA), and inactive intact PSA (iPSA), covering approximately 33%, 28%, and 39% of fPSA respectively (Fig. 1) [6]. In particular, proPSA is a proenzyme (precursor) of PSA, which is associated with PCa [7].

PSA is synthesized with a 17-amino acid leader sequence (preproPSA) that is cleaved co-translationally to generate an inactive 244-amino acid precursor protein (proPSA, with seven additional amino acids compared to mature PSA). proPSA is normally secreted from the prostate luminal epithelial cells. Immediately after its release into the lumen, the pro-leader part is removed, creating the active form, by the effect of human kallikrein (hK)-2 and hK-4, which have a trypsin-like activity and are expressed predominantly by prostate secretory epithelium. Other kallikreins, localized in the prostate, such as hK216 or prostin17, are involved in the conversion and activation of proPSA. Cleavage of the N-terminal seven amino acids from proPSA generates the active enzyme, which has a mass of 33 kDa.

The partial removal of this leader sequence leads to other truncated forms of proPSA. Thus, theoretically seven isoforms of proPSA could exist, although only [-1], [-2], [-4], [-5], [-7]proPSA were found;  there is still no evidence of [-3], [-6]proPSA. However, all forms of proPSA are enzymatically inactive [8]. It is possible to detect three truncated forms of proPSA in serum: [-5/-7], [-4] and [-2]proPSA, which is the most stable form (Fig. 1).

Notably, in vitro experiments showed that the [-2]proPSA form cannot be activated by either hK2 or trypsin; thus, once it is formed, [-2]proPSA is resistant to activation into the mature PSA form and consequently this is the most reliable test.

Mikolajczyk et al. [7], using a monoclonal antibody recognizing [-2]proPSA, found increased staining in the secretions from malignant prostate glands. In particular [-2]proPSA is differentially elevated in peripheral gland cancer tissue; conversely transition zone tissue contains little or no proPSA.

The increased serum tPSA concentrations in patients with PCa do not result from increased expression but rather from an increased release of PSA into the bloodstream, due to disruption of the epithelial architecture. fPSA is catalytically inactive because of internal cleavages, occurring in seminal plasma, and does not form complexes with protease inhibitors or other proteins: in PCa %fPSA is lower presumably because, consequently to an increased release of PSA into the bloodstream, a very low part is still degraded into the ducts.

In another later study [9], Mikolajczyk et al. found that [-2]proPSA was specifically higher in patients with PCa. Analysing a small number of patients with biopsy positive for PCa and tPSA between 6 and 24 ng/ml, they found that [-2]proPSA constituted a high fraction of fPSA (25% to 95%), which was greater than in patients with a negative biopsy. However, the molecular basis for the proPSA elevation in PCa is uncertain, although a decreased cleavage by hK2 could be the cause.

Clinical utility of proPSA
Sokoll et al. [10] were the first to study the role of proPSA in the early detection of PCa. The study involved archival serum from 119 men (31 PCa, 88 non-cancer), obtained before biopsy and in the tPSA range of 2.5–4.0 ng/ml. The serum levels of tPSA, fPSA, proPSA, and proPSA/fPSA ratio (%proPSA) were analysed: PSA and %fPSA values were similar between the non-cancer and PCa groups, and %proPSA was relatively higher in the PCa group (50.1±4.4%) compared to the non-cancer group (35.5±6.7%; P=0.07). Concerning the clinical utility, the area under the curve (AUC) for %proPSA was 0.688 compared to 0.567 for %fPSA. At fixed sensitivity of 75%, the specificity was significantly greater for %proPSA at 59% compared with %fPSA at 33% (P<0.0001). Afterwards, the Prostate Health Index (PHI) has been proposed as a mathematical algorithm combining tPSA, fPSA and [-2]proPSA according to the formula: ([-2]proPSA/fPSA) × √tPSA. A large American prospective trial [11], involving 892 men who had tPSA levels of 2–10 ng/ml and negative digital rectal examination results, showed that PHI had greater predictive accuracy for prostate biopsy outcome (AUC 0.703) than [-2]proPSA (AUC 0.557), %fPSA (AUC 0.648) and PSA (AUC 0.525), directly correlating with Gleason score (GS) (P=0.013), with an AUC of 0.724 for GS ≥4+3 disease. Moreover, men with PHI >55 had a 42% likelihood of being diagnosed with high-grade disease on biopsy compared to 26% of men with PHI 0–24.9.
Accordingly, an observational European multicenter cohort study involved 646 men with tPSA levels of 2–10 ng/ml, who had undergone prostate biopsy [12]. [-2]proPSA and PHI improved the predictive accuracy for the detection of overall PCa (and also GS ≥7 disease) compared to PSA and derivatives. In fact, at 90% sensitivity, the PHI cut-off of 27.6 could avoid 100 (15.5%) biopsies, missing 26 (9.8%) cancers (23 with GS 6, three with GS 3+4).

Moreover, a PHI based nomogram to predict PCa at extended prostate biopsy was developed and validated over 729 patients [13]. Including PHI in a multivariable logistic regression model, based on patient age, prostate volume, digital rectal examination and biopsy history, significantly increased predictive accuracy by 7% from 0.73 to 0.80 (P<0.001). Decision curve analysis showed that using the PHI based nomogram resulted in the highest net benefit. Recently, it was demonstrated that PHI might have a role in screening patients at high risk of PCa [14]. Specifically, the study involved 158 men with a positive family history undergoing prostate biopsy within the multicentre European PROMEtheuS cohort. Similarly to previous studies in the general population, PHI outperformed tPSA and %fPSA for PCa detection on biopsy (AUC 0.73, 0.55 and 0.60, respectively). In addition, both [-2]proPSA and PHI were directly associated with GS in men with a positive family history. Overall, the authors reported that using a PHI cutoff value of 25.5 would have avoided 17.2% of biopsies while missing only two GS 7 cancers. On decision curve analysis, the addition of PHI to a base predictive model that included age, prostate volume, tPSA, fPSA and %fPSA resulted in net benefit at threshold probabilities of 35–65%. This result suggests that PHI should be incorporated into a multivariable risk assessment for high-risk patients because it offers improved performance for PCa detection. Conclusions
[-2]proPSA and PHI are more accurate than the currently used tests (PSA and derivatives) in predicting the presence of PCa at biopsy. Their implementation in clinical practice has the potential to significantly increase physicians’ ability to detect PCa and avoid unnecessary biopsies. Further work is needed to confirm and generalize these data on wider populations.

References
1. Hoffman RM, Stone SN, Espey D, Potosky AL. Differences between men with screening-detected versus clinically diagnosed prostate cancers in the USA. BMC Cancer 2005; 5: 27.
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12. Lazzeri M, Haese A, de la Taille A, et al. Serum isoform [-2]proPSA derivatives significantly improve prediction of prostate cancer at initial biopsy in a total PSA range of 2-10 ng/ml: a multicentric European study. Eur Urol. 2013; 63: 986–994.
13. Lughezzani G, Lazzeri M, Larcher A, et al. Development and internal validation of a Prostate Health Index based nomogram for predicting prostate cancer at extended biopsy. J Urol. 2012; 188: 1144–1150.
14. Lazzeri M, Haese A, Abrate A, et al. Clinical performance of serum prostate-specific antigen isoform [-2]proPSA (p2PSA) and its derivatives, %p2PSA and the prostate health index (PHI), in men with a family history of prostate cancer: results from a multicentre European study, the PROMEtheuS project. BJU Int. 2013; 112: 313–321.

The author
Alberto Abrate* MD; Massimo Lazzeri MD, PhD; and Giorgio Guazzoni MD
Dept of Urology, Ospedale San Raffaele Turro, San Raffaele
Scientific Institute, Milan, Italy
*Corresponding author
E-mail: alberto.abrate@gmail.com