Point-of-care testing (POCT) is becoming an important part of laboratory medicine although instruments are not operated by laboratory personnel. In this study, we describe the planning and insertion of regulated policies for POCT and quality management, outside of the clinical laboratory. Our results emphasize the importance of the clinical laboratory department involvement to ensure accountable and accurate results in POCT testing.

by Dr Judith Attias, Svetlana Timoshchuk and Dr Marielle Kaplan

Introduction
Point-of-care testing (POCT) refers to tests conducted outside of the central clinical laboratory division. Point-of-care (POC) tests are performed mainly by clinical staff (nurses, physicians, respiratory therapists, etc) and not by clinical lab medicine specialists who understand and work in compliance with quality control (QC) and quality assurance (QA) practices [1]. The major advantage of POCT is the improvement in turnaround time (TAT) of the results by removing transport and clinical lab processing times [2]. As a result, the global POCT market is growing steadily in recent years and it is expected to grow from 23.16 billion USD in 2016 to 36.96 billion USD in 2021 [3]. POCT can be performed in primary, secondary or tertiary healthcare institutions. The list of tests that are permitted to be performed outside the clinical lab differs from one country to another, as do the requirements for quality management, ISO 22870 insertion included [4]. In Europe, current POCT exists for complete blood count including five-part differential, pregnancy testing, blood glucose concentration, cardiac biomarkers, coagulation testing, platelet function, group A streptococcus, HIV testing, malaria screening, etc.

In Israel, a list of the tests allowed to be performed as POC tests (published by the Ministry of Health), as well as the QA requirement exists but, in fact, until recently no policy was applied for POCT insertion and specialist involvement (clinical lab staff and biomedical engineering).

The aim of our work was to list all POCT conducted in a major hospital (1000 beds) located in the north of Israel, to insert a policy for device insertion, to plan and insert a QC and QA programme and to determinate the role of the clinical lab department.

Methods
First a list of all the POCT devices dispersed all over the hospital departments was prepared by the clinical lab department while building up a strong collaboration with the biomedical engineering unit, thus allowing a multidisciplinary approach.

All the blood gas instruments were replaced by GEM family devices to ensure standardization, and connected to the hospital laboratory information system (LIS), as were the glucometers.

Then a policy for POCT insertion was written. A committee composed of representatives of the clinical lab department directors, the biomedical engineering directors and directors from the department where the POCT procedure was to be employed was formed each time. The definition of the committee’s role was to check the relevance of new POCT device insertion from professional and economic aspects.

A policy for QC performance and frequency was adopted. Four quality indices were adopted and reviewed annually:

• Optimization of the use of tests in the cartridge for blood gas.
• Cancellation of test as a result of wrong identification of the patients.
• For glucometers, performance of three QC levels by the department’s staff once a month.
• For blood gas devices, standardization in comparison to the clinical lab was performed by the lab staff monthly. The ratio between the lab results and the POCT device results was calculated. A range for acceptable results was determined (0.9–1.1 for pH, 0.8–1.2 for PCO₂ and PO₂).

Results
We have now 80 similar glucometers all over the hospital, 10 blood gas instruments from the same family, no general urine instrument (only sticks similar to the sticks used in the clinical lab) and 2 thromboelastograms (TEGs). At the start of the process only 27% of the departments performed glucose QC. After training, the percentage of departments performing QC had grown to 76%. At the end of 2017, we decided that glucose tests would not be done without QC or if the QC results did not meet the expected target of 100% QC performance (Fig. 1). In 2015, there were seven blood gas analysers in five different departments; the instruments were from three different companies and were not connected to the LIS. Now, ten blood gas devices similar to those used in the clinical lab (GEM family instrument which performed QC after every test) are connected to the LIS and dispersed in eight departments. The clinical lab staff audits the use of reagents annually and performs standardization in comparison to the clinical lab once a month. The results show that not all the reagents are used optimally in all departments. The Ambulatory Operating Theatre (Ambulatory OP, which includes outpatient surgery as well as elective caesarean sections) and Intensive Cardiac Care Unit (ICCU) used only 14% and 56% of the reagents, respectively, in 2017 (Fig. 2). The performance level of the instruments is good for the all instruments. Figure three show the standardization results of the Children’s Intensive Care Unit comparatively to the clinical lab results (Fig. 3). No irregularity was obtained. POCT result cancellation is performed only after a clinician’s request to the clinical lab division by mail to the clinical lab staff.

The cancellation percentage as a result of wrong identification in the different departments is low, less than 1% of the totals tests performed (data not shown). The two thromboelastograms are in the open heart surgery theatre and are mainly used by one specific anesthetist. The anesthetist performs internal QC once a week and also participates in an external QC programme. The clinical lab prepares the specimen to be analysed and the anesthetist perform the tests. The clinical lab staff then receive and review the results. The results demonstrate that the results are acceptable but not always performed in the time limit required.

From 2015 to 2017, three new blood gas devices were inserted in the Intensive Care Unit (ICU), ICCU and ambulatory surgery theatre via the POCT device committee. In 2017 the delivery room requested a blood gas device. The number of blood gas tests ordered monthly by this department was reviewed and found to be low. As the clinical lab agreed to give priority to this department for very quick results, the request for a POC blood gas device in the delivery room was rejected by the POCT committee. At the beginning of 2018, a POCT coagulation device was inserted in one department without any consultation with the POCT committee. As in Israel partial thromboplastin time is not a part of the POC allowed tests, the instrument was removed immediately as a result of the committee’s intervention.

Discussion and Conclusion
Our results demonstrate that clinical lab involvement in POCT management led to QC performance and increase QA and insertion procedure supervision. Our results demonstrate that POCT device insertion may be considerate even when it means no optimum reagent use (depending on the need of immediate results). Laboratories all over the world work according to strict QA standard and improve continually QC performance and QC review to ensure results quality. In clinical lab testing, the majority of quality errors occur in the preanalytical phase, which is performed outside the laboratory [5]. In contrast, for POCT the majority of quality errors occurred in the analytic phase [6]. There is no doubt that POCT reduces TAT but we must consider if there is a price to pay and ensure that we do not significantly lower quality. Catherine Zimmerman proposes in her review to improve clinical lab TAT by reducing the transport time of the tubes to the clinical lab and the analytic processes inside the lab, as well as at the post-analytic phase [7]. Another aspect of this issue is whether POCT improves clinical parameters significantly; for example, the length of patient stay in the Emergency Department or mortality. Some results show that rapid results with POCT did not necessarily lead to shorter stays in the Emergency Department [8]. Larsson et al. show that when properly used, POCT improves patient care, workflow and even provides significant financial benefits [9]. They also agree with Pecoraro et al. who demonstrate that further studies may be required for defining the real utility of POCT on clinical decision making [10].
Our results show only a few cancellations owing to wrong patient identification. It is important to take into consideration the possibility of underestimation because of underreporting and unknown errors. In the clinical lab, results are reviewed before release to the clinicians. If an error of any kind is suspected (for example, identification error), the clinical lab staff call the physician, inquire about the quality of the sample and ask for a new sample if there is any doubt. The source of POCT errors are usually operator incompetence, not adhering to test procedures, and use of uncontrolled reagents and devices. Consequences of POCT error may affect patient management decisions and treatment [11]. In the literature, we cannot find data about the percentage of POCT error, especially when the clinical lab is not involved in the processes.
In conclusion, in a world where everything is happening so fast and any data can be obtained so quickly, the real challenge for the clinical lab profession is to overcome POCT antagonism and, on the contrary, to be involved with and supervise all POCT processes.

References
1. Shaw JLV. Practical challenges related to point of care testing. Pract Lab Med 2015; 4: 22–29.
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4. Boursier G, Vukasovic I, Brguljan PM, Lohmander M, Ghita I, Bernabeu Andreu FA, Barrett E, Brugnoni D, et al. Accreditation process in European countries and EFLM survey. Clin Chem Lab Med 2016; 54(4): 545–551.
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8. Florkowski C, Don-Wauchop A, Gimenez N, Rodriguez-Capot K Wils J, Zemlin A. Point-of-care testing (POCT) and evidence-based laboratory medicine (EBLM) – does it leverage any advantage in clinical decision making? Clin Lab Sci 2017; 54(7–8): 471–494.
9.Larsson A, Greig-Pylypczuk R, Huisman A. The state of point-of-care testing: a European perspective. Ups J Med Sci 2015; 120(1): 1–10.
10. Pecoraro V, Germagnoli L, Banfi G. Point-of-care testing: where is the evidence? A systematic survey. Clin Chem Lab Med 2014; 52(3): 313–324.
11. Meir FA, Jones BA. Point-of-care testing error: sources and amplifiers, taxonomy, prevention strategies, and detection monitors. Arch Pathol Lab Med 2005; 129: 1262–1267.

The authors
Judith Attias* PhD, Svetlana Timoshchuk and Marielle Kaplan PhD
Rambam Health Care Campus,
POB9602, Haifa 3109601, Israel

*Corresponding author
E-mail: J_attias@rmc.gov.il

Extracellular microRNAs recently provided valuable information including the site and the status of cancers. miR141 and miR375 are the most pronounced biomarkers for the diagnosis of high-risk prostate cancer. Here, we describe attomolar detection of miR141 and miR375 released from living prostate cancer cells through the use of a plasmonic nanowire interstice (PNI) sensor.

by Dr Taejoon Kang and Professor Bongsoo Kim

Background
Prostate-specific antigen
Prostate cancer (PC) represents 27% of all cancers in men and the second leading cause of cancer death for men worldwide [1]. In 2017 for the USA alone, there were approximately 161 360 cases of PC. PC has been diagnosed by digital rectal examination and the prostate-specific antigen (PSA) test. PSA is the only tissue-specific biomarker that can aid the early diagnosis of PC. The PSA blood test, however, has limited diagnostic accuracy for PC because PSA can be increased owing to other factors including benign prostatic hyperplasia or prostatitis as well as PC. The US Preventive Services Task Force even recommended that physicians should not routinely perform PC screening based on serum PSA levels [2]. Clearly, new biomarkers are needed to overcome this problem.

Recently, it has been reported that the level of free PSA (f-PSA) is decreased in men who have PC compared with those with benign conditions [3]. Therefore, various immunoassay technologies including enzyme-linked immunosorbent assay, fluorescence immunoassay, surface plasmon resonance (SPR), electrochemical immunosensor, dark-field microscopy, chemiluminescence, surface-enhanced Raman scattering (SERS), and dynamic light scattering have been employed for the quantitative analysis of f-PSA [3].

RNAs as prostate cancer biomarkers
Long noncoding RNAs (lncRNAs, ≥200 nucleotides) are often expressed in a disease-, tissue- or developmental-specific manner. Since lncRNAs are highly dysregulated in several cancer types and exhibit a high degree of tissue- and disease-specificity, lncRNAs are regarded as candidates for cancer diagnostic biomarkers [4]. Prostate Cancer Antigen 3 (PCA3) is a prostate-specific lncRNA that is overexpressed by 60- to 100-fold in >90% of prostate tumours compared to benign prostatic tissue. Urinary PCA3 has been used as a diagnostic biomarker for PC with a sensitivity of 58–82% and a specificity of 56–76%. The sensitivity and accuracy of PCA3 are increased when used in combination with α-methylacyl-CoA racemase. Urinary PCA3 is now widely used for PC diagnosis and has been approved by the US Food and Drug Administration (FDA). MicroRNAs (miRNAs) are single-stranded, small, and noncoding RNAs. The expression patterns of miRNAs in tissue and blood samples of patients are often closely associated with disease types and also disease stages, hinting that certain miRNAs can be compelling diagnostic markers [5]. In 2008, it was first reported that the level of miR141 is upregulated in the serum of metastatic PC compared with healthy controls and benign prostatic hyperplasia patients. Since then, miR141 and miR375 have been the most pronounced biomarkers for high-risk PC, including castrate-resistant PC and metastatic PC, which account for approximately 15% of PC diagnoses and have the potential to progress to a lethal phenotype [6].

Detection methods for nucleic acid biomarkers
For the detection of nucleic acid biomarkers, polymerase chain reaction (PCR) is the most extensively used analytical tool. Although PCR is considered the gold standard for the detection of gene biomarkers, it has drawbacks including a long amplification time and the risk of erroneously amplifying contaminants or unrelated gene sequences. To overcome these limitations, PCR-free assays have been developed by taking various sensing approaches such as fluorescence resonance energy transfer, colorimetry, SPR, electrochemistry, SERS, and so on. These methods have contributed to the advance of cancer diagnosis by reducing the drawbacks of PCR. SERS is a fascinating phenomenon that significantly increases the Raman signal of molecules located within nanoscale metallic interstices (hot spots). SERS has been employed for the sensitive detection of nucleic acid because of its single-molecule sensitivity, molecular specificity, and insensitivity to quenching. It is known that the SERS enhancement strongly depends on the detailed morphology of the metal nanostructure. Although a number of promising nanostructures that can be used as efficient SERS-active platforms have been proposed, it still remains a challenging task to develop a practical SERS sensor that can detect multiple nucleic acid biomarkers simultaneously while retaining high sensitivities. The use of single-crystalline noble metal nanowires (NWs) is highly advantageous for SERS-based detection because of their well-defined geometries, atomically smooth surfaces, and simple fabrication process [7]. Previously, we developed several noble metal NW-based SERS sensors including plasmonic nanowire interstice (PNI) sensor, particle-on-NW sensor, NW on a graphene sensor, and nanogap-rich Au NW sensor [8–15]. Among them, PNI nanostructures have been widely employed for the detection of several biochemical molecules. Particularly, by combining the PNI nanostructure with the bi-temperature hybridization process, we were able to detect miRNAs with near-perfect accuracy of single nucleotide polymorphism (SNPs) and at the extremely low detection limit of 100 aM. Here, we introduce a PNI sensor which can detect the extracellular miR141 and miR375 released from living PC cells into a culture medium. This sensor shows an extremely low detection limit of 100 aM for both miR141 and miR375, and a wide dynamic range from 100 aM to 100 pM, covering the typical concentration range of extracellular miRNAs in the bloodstreams of patients. Additionally, the PNI sensor can completely discriminate the single-base mismatches of miR141 and miR375. This excellent sensing capability of the PNI sensor enables the simultaneous detection of miR141 and miR375 released from the cells of PC cell lines (LNCaP and PC-3), showing the potential applicability to a novel PC diagnostic method.

Specific and sensitive detection of miRNA
To accurately determine the expression patterns of miRNAs in biological fluid samples, it is necessary to overcome the inconsistent measurement results caused by low specificities and complicated sensing procedures. For the ultra-specific and ultra-sensitive detection of miRNAs, we applied miRNA-specific bi-temperature hybridizations to Au NW surfaces, where short miRNAs can readily crawl into the narrow hot spots of the PNI sensor for effective SERS detection. The probe locked nucleic acid (LNA)-modified PNI sensors were incubated with miRNAs at 42 °C and subsequently incubated with Cy5-labeled reporter LNA at 64 °C (Fig. 1a). If the target miRNAs have perfectly complementary sequences to both probe and reporter LNAs, sandwiched complexes of probe LNA-miRNA-reporter LNA can be stably formed on a PNI sensor, providing strong SERS signals of Cy5. In contrast, when the sample only contains single-base mismatched miRNAs, little signal was observed. Figure 1(b) displays the intensity of the Cy5 1580 cm⁻¹ band plotted as a function of the miR141 (magenta) and miR375 (blue) concentrations. Both intensities were quite linearly increased throughout the concentration range from 100 aM to 100 pM in spite of the different sequences of miR141 and miR375. To investigate the specificity of a PNI sensor, we prepared four kinds of single-base mismatched miRNAs (miR141 A, miR141 B, miR375 A, and miR375 B). The miR141 A and miR375 A had a mismatched single base on the probe LNA recognition site, respectively, and the miR141 B and miR375 B had a mismatched single base on the reporter LNA recognition site. Figure 1(c,d) shows the plot of Cy5 1580 cm⁻¹ band intensity obtained from the PNI sensors for perfectly matched and single-base mismatched miRNAs. The concentration of all miRNAs was 100 pM. When the single-base mismatched miRNAs (miR141 A, B and miR375 A, B) were present, featureless SERS signals were obtained from the PNI sensors. In contrast, significantly strong SERS signals were measured from the PNI sensors in the presence of miR141 and miR375 with intact sequences. In the miRNA sensing procedure using the PNI sensor, the unstable single-base mismatched miRNA–LNA hybridized structures were destroyed at the temperature over T_m. Therefore, we near-perfectly excluded the possibility of detecting single-base mismatched miRNAs.

Detection of miRNAs released from cells in culture
The PNI sensors were also employed to detect miR141 and miR375 released from the living PC cells. We prepared four types of media in which different human cancer cell lines were cultured. The cultured cell lines were LNCaP (PC cells), PC-3 (PC cells), RWPE-1 (noncancerous prostate epithelial cells), and HeLa (cervical cancer cells). For the detection of miR141 and miR375 using PNI sensors, the total extracellular miRNA released from the cells into the media were isolated and purified. Figure 2(a,b) represent the extracellular miR141 and miR375 levels determined by the PNI sensor for LNCaP, PC-3, RWPE-1, and HeLa, respectively. The levels of miR141 and miR375 in LNCaP and PC-3 culture supernatants were higher than those in RWPE-1 and HeLa, indicating that the PNI sensor can detect extracellular miRNAs released from living PC cells accurately. The well-defined PNI nanostructure which provides a highly reproducible SERS hot spot line, straightforward probe LNA immobilization, and simple miRNA–LNA hybrid formation with equalized stabilities seems to collectively contribute to the observed equally enhanced and highly reproducible SERS signals for miR141 and miR375.

Conclusion
We have developed a PNI sensor that can detect extracellular miR141 and miR375 released from the cultured cells of PC cell lines. The proposed PNI sensor exhibited a low detection limit of 100 aM, a wide dynamic range from 100 aM to 100 pM, and a perfect discrimination of single-base mismatches in target miRNAs. By using the PNI sensor, we were able to estimate the absolute amount of the released miR141 and miR375 from each PC cell line. The highly sensitive and exactly quantifiable PNI sensor could be useful for the precise diagnosis of PC patients and will be further valuable for detecting other disease-related extracellular miRNAs.

References
1. Siegel RL, Miller KD, Jemal A. Cancer statistics, 2016. CA Cancer J Clin 2016; 66: 7–30.
2. Moyer VA. Screening for prostate cancer: U.S. Preventive Services Task Force recommendation statement. Ann Intern Med 2012; 157: 120–134.
3. Cheng Z, Choi N, Wang R, Lee S, Moon KC, Yoon S-Y, Chen L, Choo J. Simultaneous detection of dual prostate specific antigens using surface-enhanced Raman scattering-based immunoassay for accurate diagnosis of prostate cancer. ACS Nano 2017; 11: 4926–4933.
4. Gupta SC, Tripatchi YN. Potential of long non-coding RNAs in cancer patients: from biomarkers to therapeutic targets. Int J Cancer 2017; 140: 1955–1967.
5. Kang T, Kim H, Lee JM, Lee H, Choi Y-S, Kang G, Seo M-K, Chung BH, Jung Y, Kim B. Ultra-specific zeptomole microRNA detection by plasmonic nanowire interstice sensor with bi-temperature hybridization. Small 2014; 10: 4200–4206.
6. Yang S, Kim H, Lee KJ, Hwang SG, Lim E-K, Jung J, Lee TJ, Park H-S, Kang T, Kim B. Attomolar detection of extracellular microRNAs released from living prostate cancer cells by a plasmonic nanowire interstice sensor. Nanoscale 2017; 9: 17387–17395.
7. Mohanty P, Yoon I, Kang T, Seo K, Varadwaj KSK, Choi W, Park Q-H, Ahn JP, Suh YD, Ihee H, Kim B. Simple vapor phase synthesis of single-crystalline ag nanowires and single nanowire surface-enhanced Raman scattering. J Am Chem Soc 2007; 129: 9576–9577.
8. Yoon I, Kang T, Choi W, Kim J, Yoo Y, Joo S-W, Park Q-H, Ihee H, Kim B. Single nanowire on a film as an efficient SERS-active platform. J Am Chem Soc 2009; 131: 758–762.
9. Kang T, Yoon I, Kim J, Ihee H, Kim B. Au nanowire-Au nanoparticles conjugated system which provides micrometer size molecular sensors. Chem Eur J 2010; 16: 1351–1355.
10. Kang T, Yoo SM, Kim B, Lee SY. Detection of single nucleotide polymorphism by a gold nanowire-on-film SERS sensor coupled with S1 nuclease treatment. Chem Eur J 2011; 17: 8657–8662.
11. Kang T, Yoo SM, Kang H, Lee H, Kang M, Lee SY, Kim B. Combining a nanowire SERRS sensor and a target recycling reaction for ultrasensitive and multiplex identification of pathogenic fungi. Small 2011; 7: 3371–3376.
12. Kang T, Yoo SM, Kang M, Lee H, Kim H, Lee SY, Kim B. Single-step multiplex detection of toxic metal ions by Au nanowires-on-chip sensor using reporter elimination. Lab Chip 2012; 12: 3077–3081.
13. Gwak R, Kim H, Yoo SM, Lee SY, Lee G-J, Lee M-K, Rhee C-K, Kang T, Kim B. Precisely determining ultralow level UO22+ in natural water with plasmonic nanowire interstice sensor. Sci Rep 2016; 6: 19646.
14. Lee JM, Hwang A, Choi HJ, Jo Y, Kim B, Kang T, Jung Y. A multivalent structure-specific RNA binder with extremely stable target binding but reduced interactions to nonspecific RNAs. Angew Chem Int Ed 2017; 56: 15998–16002.
15. Eom G, Kim H, Hwang A, Son H-Y, Choi Y, Moon J, Kim D, Lee M, Lim E-K, Jeong J, Huh Y-M, Seo M-K, Kang T, Kim B. Nanogap-rich Au nanowire SERS sensor for ultrasensitive telomerase activity detection: application to gastric and breast cancer tissue diagnosis. Adv Funct Mater 2017; 27: 1701832.

The authors
Taejoon Kang*¹ PhD, Bongsoo Kim*² PhD
¹Hazards Monitoring Bionano Research Center, KRIBB, Daejeon 34141, Republic of Korea
²Department of Chemistry, KAIST, Daejeon 34141, Republic of Korea

*Corresponding author
E-mail: kangtaejoon@kribb.re.kr;
bongsoo@kaist.ac.kr

CTC-derived AR-V7 detection as a prognostic and predictive biomarker in advanced prostate cancer
^{Bastos DA, Antonarakis ES. Expert Rev Mol Diagn 2018; 18(2): 155–163}

Prostate cancer is a highly heterogeneous disease, with remarkably different prognosis across all stages. Increased circulating tumour cell (CTC) count (≥5) using the CellSearch assay has been identified as one of the markers that can be used to predict survival, with added value beyond currently available prognostic factors. Recently, androgen receptor splice variant 7 (AR-V7) detection has been associated with worse outcomes for patients with castration-resistant prostate cancer (CRPC) treated with novel androgen receptor-signalling (ARS) inhibitors such as abiraterone and enzalutamide but not taxane chemotherapies. Areas covered: In this manuscript, the authors review the available biomarkers in CRPC and discuss emerging data on the value of CTC-derived AR-V7 status to assess prognosis and its potential role to guide treatment selection for patients with advanced prostate cancer. Expert commentary: Current evidence supports AR-V7 status as a prognostic biomarker and also as a potential predictive biomarker for patients with mCRPC. The authors expect that the incorporation of AR-V7 status and other biomarkers (e.g. AR mutations) in the sequential assessment of patients with advanced prostate cancer will lead to a more rational use of available and future therapies, with significant improvements in outcomes for our patients.

Defining a cohort of men who may not require repeat prostate biopsy based on PCA3 score and MRI: The dual negative effect
^{Perlis N, Al-Kasab T, Ahmad A, Goldberg E, Fadak K, Sayid R, et al. J Urol 2017; doi: 10.1016/j.juro.2017.11.07}

PURPOSE: Prostate cancer over diagnosis and overtreatment are concerns for clinicians and policy makers. Multiparametric magnetic resonance imaging and the PCA3 (prostate cancer antigen 3) urine test select for clinically significant cases. We explored how well the tests performed together in with previous biopsies.

MATERIALS AND METHODS: In accordance with ethics committee approval we collected clinicopathological data on all patients in whom a PCA3 test from was done 2011 to June 2016. This included patients on active surveillance for low-risk prostate cancer and those without prostate cancer who had previous negative biopsies and suspicion of occult disease. We explored whether age, prostate-specific antigen, PCA3 score, multiparametric magnetic resonance imaging, digital rectal examination, family history and prostate size would predict clinically significant prostate cancer on repeat biopsy. The negative predictive value of multiparametric magnetic resonance imaging and PCA3 score was calculated.

RESULTS: A total of 470 patients were included in study. The PCA3 score was abnormal at 35 or greater in 32.5 % of cases. In the multivariate model including 154 men only age (OR 1.08, 95 % CI 1.01–1.16), multiparametric magnetic resonance imaging PI-RADS™ (Prostate Imaging-Reporting and Data System) score 4 (OR 16.6, 95 % CI 3.9–70.0) or 5 (OR 28.3, 95 % CI 5.7–138) and PCA3 score (OR 2.9, 95 % CI 1.0–8.8) predicted clinically significant cancer on biopsy. No patient with negative multiparametric magnetic resonance imaging and a normal PCA3 score had clinically significant prostate cancer on biopsy for a negative predictive value of 100 % (p<0.0001).

CONCLUSIONS: In patients with dual negative tests (multiparametric magnetic resonance imaging and PCA3 score) clinically significant prostate cancer was never found on biopsy, which may be unnecessary in this group. This study was limited by its retrospective design, selection bias and lack of cost-effectiveness data.

Quantitative mass spectrometry-based proteomic profiling for precision medicine in prostate cancer
^{Flores-Morales A, Iglesias-Gato D. Front Oncol 2017; 7: 267}

Prostate cancer (PCa) is one of the most frequently diagnosed cancer among men in the western societies. Many PCa patients bear tumours that will not threat their lives if left untreated or if treatment is delayed. Our inability for early identification of these patients has resulted in massive overtreatment. Therefore, there is a great need of finding biomarkers for patient stratification according to prognostic risk; as well as there is a need for novel targets that can allow the development of effective treatments for patients that progress to castration-resistant PCa. Most biomarkers in cancer are proteins, including the widely-used prostate-specific antigen (PSA). Recent developments in mass spectrometry allow the identification and quantification of thousands of proteins and posttranslational modifications from small amounts of biological material, including formalin-fixed paraffin-embedded tissues, and biological fluids. Novel diagnostic and prognostic biomarkers have been identified in tissue, blood, urine, and seminal plasma of PCa patients, and new insights in the ethology and progression of this disease have been achieved using this technology. In this review, we summarize these findings and discuss the potential of this technology to pave the way toward the clinical implementation of precision medicine in PCa.

Biomarkers for prostate biopsy and risk stratification of newly diagnosed prostate cancer patients
^{Loeb S. Urol Pract 2017; 4(4): 315–321}

INTRODUCTION: Many new markers are now available as an aid for decisions about prostate biopsy for men without prostate cancer, and/or to improve risk stratification for men with newly diagnosed prostate cancer.

METHODS: A literature review was performed on currently available markers for use in decisions about prostate biopsy and initial prostate cancer treatment.

RESULTS: Although total prostate-specific antigen cutoffs were traditionally used for biopsy decisions, PSA elevations are not specific. Repeating the PSA test, and adjusting for factors like age, prostate volume and changes over time can increase specificity for biopsy decisions. The Prostate Health Index (phi) and 4K Score are new PSA-based markers that can be offered as second-line tests to decide on initial or repeat prostate biopsy. The PCA3 urine test and ConfirmMDx tissue test are additional options for repeat biopsy decisions. For men with newly diagnosed prostate cancer, genomic tests are available to refine risk classification and may influence treatment decisions.

CONCLUSIONS: Numerous secondary testing options are now available that can be offered to patients deciding whether to undergo prostate biopsy and those with newly diagnosed prostate cancer.

Bidirectional electrochemiluminescence color switch: an application in detecting multimarkers of prostate cancer
^{Wang YZ, Ji SY, Xu HY, Zhao W, Xu JJ, Chen HY. Anal Chem 2018; doi: 10.1021/acs.analchem.8b00014}

A selective excitation of [Ir(df-ppy)₂(pic)] and [Ru(bpy)3]²⁺ through tuning the electrode potential is reported in this work. Bidirectional colour change from blue-green to red could be observed along with increase and decrease of the potential, which was ascribed to the dual-potential excitation property of [Ir(df-ppy)₂(pic)]. Similar to the three-electrode system, selective excitation of ECL could be achieved at the anode of the bipolar electrode (BPE). Both increase and decrease of the faradic reactions at the cathode of the BPE could induce ECL reporting colour at the other pole switched from blue-green to red. We applied a closed BPE device for the bioanalysis of multicolour ECL since the organic solvent containing electrochemiluminophores could be separated from the bioanalytes. On the basis of BPE arrays coupled with the ECL switch, the detection of three biomarkers of prostate cancer, PSA, microRNA-141, and sarcosine were integrated in a same device. The cutoff values of the biomarkers could be recognized directly by the naked eye. Such a device holds great potential in the early diagnosis of prostate cancer.

Molecular biomarkers in the clinical management of prostate cancer
^{Udager AM, Tomlins SA. Cold Spring Harb Perspect Med 2018; doi: 10.1101/cshperspect.a030601}

Prostate cancer, one of the most common non-cutaneous malignancies in men, is a heterogeneous disease with variable clinical outcome. Although the majority of patients harbour indolent tumours that are essentially cured by local therapy, subsets of patients present with aggressive disease or recur/progress after primary treatment. With this in mind, modern clinical approaches to prostate cancer emphasize the need to reduce overdiagnosis and overtreatment via personalized medicine. Advances in our understanding of prostate cancer pathogenesis, coupled with recent technologic innovations, have facilitated the development and validation of numerous molecular biomarkers, representing a range of macromolecules assayed from a variety of patient sample types, to help guide the clinical management of prostate cancer, including early detection, diagnosis, prognostication, and targeted therapeutic selection. Herein, we review the current state of the art regarding prostate cancer molecular biomarkers, emphasizing those with demonstrated utility in clinical practice.

Genomic markers in prostate cancer decision making
^{Cucchiara V, Cooperberg MR, Dall’Era M, Lin DW, Montorsi F, Schalken JA, et al. Eur Urol. 2017; doi: 10.1016/j.eururo.2017.10.036}

CONTEXT: Although the widespread use of prostate-specific antigen (PSA) has led to an early detection of prostate cancer (PCa) and a reduction of metastatic disease at diagnosis, PSA remains one of the most controversial biomarkers due to its limited specificity. As part of emerging efforts to improve both detection and management decision making, a number of new genomic tools have recently been developed.

OBJECTIVE: This review summarizes the ability of genomic biomarkers to recognize men at high risk of developing PCa, discriminate clinically insignificant and aggressive tumours, and facilitate the selection of therapies in patients with advanced disease.

EVIDENCE ACQUISITION: A PubMed-based literature search was conducted up to May 2017. The most recent and relevant original articles and clinical trials that have provided indispensable information to guide treatment decisions were selected.

EVIDENCE SYNTHESIS: Genome-wide association studies have identified several genetic polymorphisms and inherited variants associated with PCa susceptibility. Moreover, the urine-based assays SelectMDx, Mi-Prostate Score, and ExoDx have provided new insights into the identification of patients who may benefit from prostate biopsy. In men with previous negative pathological findings, Prostate Cancer Antigen 3 and ConfirmMDx predicted the outcome of subsequent biopsy. Commercially available tools (Decipher, Oncotype DX, and Prolaris) improved PCa risk stratification, identifying men at the highest risk of adverse outcome. Furthermore, other biomarkers could assist in treatment selection in castration-resistant PCa. AR-V7 expression predicts resistance to abiraterone/enzalutamide, while poly(ADP-ribose) polymerase-1 inhibitor and platinum-based chemotherapy could be indicated in metastatic patients who are carriers of mutations in DNA mismatch repair genes.

CONCLUSIONS: Introduction of genomic biomarkers has dramatically improved the detection, prognosis, and risk evaluation of PCa. Despite the progress made in discovering suitable biomarker candidates, few have been used in a clinical setting. Large-scale and multi-institutional studies are required to validate the efficacy and cost utility of these new technologies.

PATIENT SUMMARY: Prostate cancer is a heterogeneous disease with a wide variability. Genomic biomarkers in combination with clinical and pathological variables are useful tools to reduce the number of unnecessary biopsies, stratify low-risk from high-risk tumours, and guide personalized treatment decisions.

The use of biomarkers in prostate cancer screening and treatment
^{Ashley VA, Joseph MB, Kamlesh KY, Shalini SY, Ashutosh KT, Joseph R. Rev Urol 2017; 19(4): 221–234}

Prostate cancer screening and diagnosis has been guided by prostate-specific antigen levels for the past 25 years, but with the most recent US Preventive Services Task Force screening recommendations, as well as concerns regarding overdiagnosis and overtreatment, a new wave of prostate cancer biomarkers has recently emerged. These assays allow the testing of urine, serum, or prostate tissue for molecular signs of prostate cancer, and provide information regarding both diagnosis and prognosis. In this review, we discuss 12 commercially available biomarker assays approved for the diagnosis and treatment of prostate cancer. The results of clinical validation studies and clinical decision-making studies are presented. This information is designed to assist urologists in making clinical decisions with respect to ordering and interpreting these tests for different patients. There are numerous fluid and biopsy-based genomic tests available for prostate cancer patients that provide the physician and patient with different information about risk of future disease and treatment outcomes. It is important that providers be able to recommend the appropriate test for each individual patient; this decision is based on tissue availability and prognostic information desired. Future studies will continue to emphasize the important role of genomic biomarkers in making individualized treatment decisions for prostate cancer patients.

A four-kallikrein panel and β-microseminoprotein in predicting high-grade prostate cancer on biopsy: an independent replication from the Finnish Section of the European Randomized Study of Screening for Prostate Cancer
^{Assel M, Sjöblom L, Murtola TJ, Talala K, Kujala P, Stenman UH, et al. Eur Urol Focus 2017; doi: 10.1016/j.euf.2017.11.002}

BACKGROUND: A panel of four kallikrein markers (total, free, and intact prostate-specific antigen [PSA] and human kallikrein-related peptidase 2 [hK2]) improves predictive accuracy for Gleason score ≥7 (high-grade) prostate cancer among men biopsied for elevated PSA. A four-kallikrein panel model was originally developed and validated by the Dutch centre of the European Randomized Study of Screening for Prostate Cancer (ERSPC). The kallikrein panel is now commercially available as 4Kscore™.

OBJECTIVE: To assess whether these findings could be replicated among participants in the Finnish section of ERSPC (FinRSPC) and whether β-microseminoprotein (MSP), a candidate prostate cancer biomarker, adds predictive value.

DESIGN, SETTING, AND PARTICIPANTS: Among 4861 biopsied screening-positive participants in the first three screening rounds of FinRSPC, a case-control subset was selected that included 1632 biopsy-positive cases matched by age at biopsy to biopsy-negative controls.

OUTCOME MEASUREMENTS AND STATISTICAL ANALYSIS: The predictive accuracy of prespecified prediction models was compared with biopsy outcomes.

RESULTS AND LIMITATIONS: Among men with PSA of 4.0–25 ng/ml, 1111 had prostate cancer, 318 of whom had high-grade disease. Total PSA and age predicted high-grade cancer with an area under the curve of 0.648 (95 % confidence interval [CI] 0.614–0.681) and the four-kallikrein panel increased discrimination to 0.746 (95 % CI 0.717–0.774). Adding MSP to the four-kallikrein panel led to a significant (Wald test; p=0.015) but small increase (0.003) in discrimination. Limitations include a risk of verification bias among men with PSA of 3.0–3.99 ng/ml and the absence of digital rectal examination results.
CONCLUSIONS: These findings provide additional evidence that kallikrein markers can be used to inform biopsy decision making. Further studies are needed to define the role of MSP.

PATIENT SUMMARY: Four kallikrein markers and β-microseminoprotein in blood improve discrimination of high-grade prostate cancer at biopsy in men with elevated prostate-specific antigen.

Combinations of elevated tissue miRNA-17-92 cluster expression and serum prostate-specific
antigen as potential diagnostic biomarkers for prostate cancer
^{Feng S, Qian X, Li H, Zhang X. Oncol Lett 2017; 14(6): 6943–6949}

The aim of the present study was to investigate the effectiveness of the miR-17-92 cluster as a disease progression marker in prostate cancer (PCa). Reverse transcription-quantitative polymerase chain reaction analysis was used to detect the microRNA (miR)-17-92 cluster expression levels in tissues from patients with PCa or benign prostatic hyperplasia (BPH), in addition to in PCa and BPH cell lines. Spearman correlation was used for comparison and estimation of correlations between miRNA expression levels and clinicopathological characteristics such as the Gleason score and prostate-specific antigen (PSA). Receiver operating curve (ROC) analysis was performed for evaluation of specificity and sensitivity of miR-17-92 cluster expression levels for discriminating patients with PCa from patients with BPH. Kaplan-Meier analysis was plotted to investigate the predictive potential of miR-17-92 cluster for PCa biochemical recurrence. Expression of the majority of miRNAs in the miR-17-92 cluster was identified to be significantly increased in PCa tissues and cell lines. Bivariate correlation analysis indicated that the high expression of unregulated miRNAs was positively correlated with Gleason grade, but had no significant association with PSA. ROC curves demonstrated that high expression of miR-17-92 cluster predicted a higher diagnostic accuracy compared with PSA. Improved discriminating quotients were observed when combinations of unregulated miRNAs with PSA were used. Survival analysis confirmed a high combined miRNA score of miR-17-92 cluster was associated with shorter biochemical recurrence interval. miR-17-92 cluster could be a potential diagnostic and prognostic biomarker for PCa, and the combination of the miR-17-92 cluster and serum PSA may enhance the accuracy for diagnosis of PCa.


Prostate-specific antigen screening impacts on biochemical recurrence in patients with clinically localized prostate cancer
^{Hashimoto T, Ohori M, Shimodaira K, Kaburaki N, Hirasawa Y, Satake N, Gondo T, Nakagami Y, Namiki K, Ohno Y. Int J Urol 2018; doi: 10.1111/iju.13563}

OBJECTIVE: To clarify the impact of prostate-specific antigen screening on surgical outcomes of prostate cancer.

METHODS: Patients who underwent radical prostatectomy were divided into two groups according to prostate-specific antigen testing opportunity (group 1, prostate-specific antigen screening; group 2, non-prostate-specific antigen screening). Perioperative clinical characteristics were compared using the Wilcoxon rank-sum and χ2 -tests. Cox proportional hazards models were used to identify independent predictors of postoperative biochemical recurrence-free survival.

RESULTS: In total, 798 patients (63.2 %) and 464 patients (36.8 %) were categorized into groups 1 and 2, respectively. Group 2 patients were more likely to have a higher prostate-specific antigen level and age at diagnosis and larger prostate volume. Clinical T stage, percentage of positive cores and pathological Gleason score did not differ between the groups. The 5-year biochemical recurrence-free survival rate was 83.9 % for group 1 and 71.0 % for group 2 (p<0.001). On multivariate analysis, prostate-specific antigen testing opportunity (hazard ratio 2.530; p<0.001) was an independent predictive factor for biochemical recurrence after surgery, as well as pathological T stage, pathological Gleason score, positive surgical margin and lymphovascular invasion. Additional analyses showed that prostate-specific antigen screening had a greater impact on biochemical recurrence in a younger patients, patients with a high prostate-specific antigen level, large prostate volume and D’Amico high risk, and patients meeting the exclusion criteria of the Prostate Cancer Research International Active Surveillance study.

CONCLUSIONS: Detection by screening results in favourable outcomes after surgery. Prostate-specific antigen screening might contribute to reducing biochemical recurrence in patients with localized prostate cancer.