Increased Plasmatic Levels of PSA-Expressing Exosomes Distinguish Prostate Cancer Patients from Benign Prostatic Hyperplasia: A Prospective Study

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Prostate Specific Antigen (PSA) fails to discriminate between benign prostatic hyperplasia (BPH) and Prostate Cancer (PCa), resulting in large numbers of unnecessary biopsies and missed cancer diagnoses. Nanovesicles called exosomes are directly
  cancers  Article Increased Plasmatic Levels of PSA-ExpressingExosomes Distinguish Prostate Cancer Patientsfrom Benign Prostatic Hyperplasia:A Prospective Study Mariantonia Logozzi  1  , Daniela F. Angelini  2  , Alessandro Giuliani  3  , Davide Mizzoni  1  ,Rossella Di Raimo  1  , Martina Maggi  4  , Alessandro Gentilucci  4  , Vittorio Marzio  4  ,Stefano Salciccia  4  , Giovanna Borsellino  2  , Luca Battistini  2  , Alessandro Sciarra  4 and Stefano Fais  1, * 1 Department of Oncology and Molecular Medicine, Istituto Superiore di Sanit à , Viale Regina Elena 299,00161 Rome, Italy; (M.L.); (D.M.); (R.D.R.) 2 Neuroimmunology Unit, IRCCS Santa Lucia Foundation, 00179 Rome, Italy; (D.F.A.); (G.B.); (L.B.) 3 Environment and Health Department Istituto Superiore di Sanit à , Viale Regina Elena 299, 00161 Rome, Italy; 4 Department of Urology, Policlinico Umberto I, Universit à  La Sapienza, Viale dell’Universit à  33,00161 Rome, Italy; (M.M.); (A.G.); (V.M.); (S.S.); (A.S.) *  Correspondence:; Tel.: + 39-0649903195; Fax: + 39-0649902436Received: 18 July 2019; Accepted: 25 September 2019; Published: 27 September 2019      Abstract:  Prostate Specific Antigen (PSA) fails to discriminate between benign prostatic hyperplasia (BPH) and Prostate Cancer (PCa), resulting in large numbers of unnecessary biopsies and missedcancer diagnoses. Nanovesicles called exosomes are directly detectable in patient plasma and herewe explore the potential use of plasmatic exosomes expressing PSA (Exo-PSA) in distinguishinghealthy individuals, BPH, and PCa. Exosomes were obtained from plasma samples of 80 PCa, 80 BPH, and 80 healthy donors (CTR). Nanoparticle Tracking Analysis (NTA), immunocapture-basedELISA (IC-ELISA), and nanoscale flow-cytometry (NSFC), were exploited to detect and characterize plasmatic exosomes. Statistical analysis showed that plasmatic exosomes expressing both CD81and PSA were significantly higher in PCa as compared to both BPH and CTR, reaching 100% specificity and sensitivity in distinguishing PCa patients from healthy individuals. IC-ELISA, NSFC,and Exo-PSA consensus score (EXOMIX) showed 98% to 100% specificity and sensitivity for BPH-PCadiscrimination. This study outperforms the conventional PSA test with a minimally invasive widely exploitable approach. Keywords:  prostate cancer (PCa); benign prostatic hyperplasia (BPH); exosomes; ELISA; nanoscale flow cytometry 1. Introduction Prostate cancer (PCa) is the most commonly diagnosed cancer and the second leading causeof cancer-related deaths in human males; diagnosis of PCa and subsequent treatments have high medical, psychological, and economic impact [1]. The current standard method for PCa diagnosis is transrectal ultrasound (TRUS)-guided prostate biopsy,whichismainlyperformedonthebasisofabnormalplasmaticlevelsofprostate-specificantigen Cancers  2019 ,  11 , 1449; doi:10.3390  /  cancers11101449  /   journal  /  cancers  Cancers  2019 ,  11 , 1449 2 of 11 (PSA) [ 2 ]. However, PSA is organ- but not cancer-specific and PCa screening using a PSA–based threshold as the sole indication for prostate biopsy results in large numbers of unnecessary biopsies. Moreover, the low specificity of this test leads to high numbers of undiagnosed PCa [3]. InordertoaddsensitivityandspecificitytoPSAtestingandtoavoidunnecessarybiopsies, several alternative approaches have been developed over the years [ 4 , 5 ] but none can yet be implementedfor routine screening programs. To date, digital rectal examination remains a primary test for the initial diagnosis of PCa [ 1 – 4 ] and although serum PSA determination is used worldwide for PCa earlydiagnosis[ 6 ], itsusehasbecomecontroversialforthehighnumberoffalsepositivesandfalsenegatives it provides [1,3,7–11]. Extracellular vesicles, which include nanovesicles (30–100 nm) called exosomes, are carriers for biomolecules including proteins, lipids, and nucleic acids [ 12 ], thus representing potential source of disease biomarkers including cancer [13]. Exosomes are released in human body fluids, including plasma, sperm, and urine by a variety of cells both in physiological and pathological conditions [ 12 ]. Exosome release dramatically increasesduringtumorigenesisandwhenexposedtosomemicro-environmentalfactorssuchaslowextracellular pH [ 14 ], independently from the tumor histotype [ 15 ]. Tumor exosomes circulate in the body, shuttling bio-markers including coding and non-coding RNAs [ 12 , 14 , 16 , 17 ]. Recently, liquid biopsieshave emerged as valid alternatives to standard tumor biopsies. Tumor-derived exosomes, released or spilled-over into the body fluids, may well represent key prototypes as liquid biopsies, with both diagnostic and prognostic applications. This study aimed at evaluating the clinical relevance of plasmatic exosomes expressingPSA in a large cohort of prostate cancer (PCa) and benign prostatic hyperplasia (BPH) patients,and in healthy subjects. The experimental protocol included the use of both nanoscaleflow-cytometry and immunocapture-based ELISA for extracellular vesicles characterization and quantification, and nanoparticle tracking analysis (NTA) for quality control of plasmatic samples after the ultracentrifugation. These tests have been performed in up to 240 plasma samples deriving from either PCa and BPH and healthy individuals. In each individual, the levels of of plasmatic exosomes expressing PSA were compared to the standard serum PSA, but in healthy controls that were all males under 30. The results have shown that plasmatic exosomes expressing PSA distinguished between PCa patients and both BPH and healthy individuals, with both sensitivity and specificity significantly higher than serum PSA with all the exploited tests. 2. Results 2.1. Identification and Characterization of Exosomes from Patients and Controls The NTA provided a quality control for the exosome preparations, showing that the distribution profiles of plasmatic exosomes obtained from both healthy donors and BPH patients were moreheterogeneous in size and distribution [ 18 ]; while the profile of exosomes obtained from the plasmaof PCa patients was homogeneous in terms of size and distribution (Supplementary Figure S1A). The investigation on the importance of exosomes number and size, as assessed by NTA, deserves anentirely dedicated study in which exosome levels before and after surgery have to be investigated as well, in order to understand better whether both these parameters are indeed due to the presence of the malignant tumors, as shown for other cancers [ 19 ]. Exosomal preparations from CTR, BPH and PCa plasma were further characterized by Western blot analysis for housekeeping markers of exosomes, Tsg 101 and CD81 (Supplementary Figure S1B). Each plasma sample underwent both immunocapture-based ELISA (IC-ELISA) and NanoScale Flow Cytometry (NSFC), In both the analyses an antibody specific for a typical exosome antigen (CD81)was exploited to identify exosomes within the pool of extracellular vesicles, and an antibody for PSAwas used for the detection of plasmatic exosomes expressing PSA. Using this approach, we compared the levels of PSA-expressing exosomes (Exo-PSA) between patients with PCa and patients with BPH  Cancers  2019 ,  11 , 1449 3 of 11 and CTR. In a separate set of statistical analysis, we related the levels of serum PSA (S-PSA) in PCaand BPH to Exo-PSA as assessed by either IC-ELISA, NSFC, or both. All samples that did not meet thequalityrequirements(emolysis,hyperlipidemia,andinsu ffi cientvolume)andtypicalcharacteristics of exosomes (size, distribution, and number of the exosomes analyzed by NTA) were excluded fromfurther analysis (i.e., 10 PCa, 9 BPH, and 10 CTR were excluded from IC-ELISA, and 13 PCa, 18 BPH, and 27 CTR were not analyzed by NFSC). 2.2. Analysis of the PSA-Expressing Exosomes in the Plasma of Either PCa or BPH Patients or Healthy Donors 2.2.1. IC-ELISA Clinical evaluation of the plasmatic levels of exosomes expressing PSA (from 1 mL of plasma) wasperformedbyIC-ELISAonplasma fromBPH, PCa, andhealthyindividuals. Exosome UCpreparations were seeded on anti-CD81-covered plates and then an anti-PSA antibody was added. Figure 1 shows the values distribution in PCa vs. CTR (Figure 1A), PCa vs. BPH (Figure 1B), and BPH vs. CTR (Figure 1C). The performance of IC-ELISA was further evaluated with receiving operatingcharacteristics(ROC)analysis(Figure1D–F).Thedatashowed100%sensitivityandspecificity comparing: (1) PCa vs. CTR (Figure 1D)—AUC: 1.00,  p  <  0.001; Cut-o ff  :  µ  g  /  mL Exo-PSA  =  17.07; (2)PCavs.BPH:98.57sensitivityand80.28%specificity(Figure1E)—AUC:0.98,  p < 0.001;Cut-o ff  : µ  g  /  mL Exo-PSA = 23.32; (3) BPH vs. CTR: 98.57 sensitivity and 80.28% specificity (Figure 1F)—AUC: 0.90,  p < 0.001; Cut-o ff  :  µ  g  /  mL Exo-PSA = 23.32. Figure 1.  Distribution and receiving operating characteristics (ROC) curve of plasmatic exosomes  Cancers  2019 ,  11 , 1449 4 of 11 expressing PSA (Exo-PSA) from healthy donors (CTR), benign prostatic hyperplasia (BPH),and prostate cancer (PCa) plasma samples analyzed with immunocapture-based ELISA (IC-ELISA). ( A )DistributionbetweenPCaandCTR.( B )DistributionbetweenPCaandBPH.( C )Distributionbetween BPH and CTR. ( D ) ROC curve between PCa and BPH. ( E ) ROC curve between PCa and BPH.( F ) ROC curve between BPH and CTR. ( G ) IC-ELISA distribution of CTR, BPH, and PCa included within the 25th and 75th percentiles. The AUC is a general estimate of the method’s discriminant power (being 1.00 the maximal value correspondent to a perfect classifier and 0.50 to a random choice). On the other hand, given the trade-off  between sensitivity and specificity, the reported values of these parameters must be intended as a possible compromise among different solutions located in the top left part of the ROC plot. Intra- and inter- test variability were calculated on six replicates of the same preparation run on three different plates and were 17.39% and 33%, respectively. The analysis by the ROC curve fixed the cut-off values to 23.32  µ  g  /  mL Exo-PSA (Figure 1E), allowing to discriminate PCa from BPH patients. The graph in Figure 1G represents the distribution of PCa, BPH, and CTR included within the 25th and 75th percentiles. PSA detection through exosome quantification by IC-ELISA discriminates PCa from BPH and CTR.2.2.2. Correlation Between IC-ELISA, NSFC and Serum PSA (S-PSA) This set of experiments clearly showed that IC-ELISA was able to measure significantly higher plasmatic levels of Exo-PSAin patients withPCa as compared to bothhealthy controls (100%specificity and 100% sensitivity, perfect classifier 1.00) and patients with BPH (98.57% specificity and 80.28% sensitivity, 0.98 AUC). However, we used NSFC to further support the data obtained with IC-ELISA in those samples endowed with both information (and thus limiting to PCa and BPH groups:  n = 132). Only in this way, we can both clarify to what extent they refer to the same latent phenomenonand devise a prognostic strategy based on a combination of di ff  erent biomarkers. The derived Log-NSFC descriptor, correspondent to the logarithm of NSFC, was added to the srcinal biomarkers in order to eliminate the extremely high variability of NSFC Exo that could bias the observed correlation structure. Supplementary Table S1 clearly shows that the exosome-related measures are significantlycorrelated, thus pointing to the same biological phenomenon: Serum PSA and exosome PSA are independent of each other. This confirms the impossibility of serum PSA for discriminating PCa and BPH patients. Principal component analysis, as applied to the above correlation structure (the principalcomponents are the eigenvectors of the correlation matrix and point to the latent independentfactors getting rid of data set variance [ 20 , 21 ]), gave rise to two significant principal components cumulatively explaining 83% of the total variance. Principal components are the linear combinations of srcinal variables maximizing the total variance of the data set, and are each other orthogonal by construction; they correspond to the “latent variables” at the basis of the observed biomarker variance[ 20 ]. ThePearsoncorrelationcoe ffi cients(loadings)betweensrcinalvariablesandcomponents allow for a straightforward interpretation of component meanings (Supplementary Table S2). Principal component analysis is a data-driven procedure, thus the isolation of a pure cancer subsetat values greater than PC1 mean value (components have by construction zero mean and unit standard deviation) was an emergent property pointing to a clear-cut discrimination of BPH and PCa patients  by exosome biomarkers (S-PSA, IC-ELISA, Log-NSFC). The complete lack of discrimination ability of S-PSA was evident as well (Figure 2). InordertogenerateacompositeindexcollatingtheNSFCandIC-ELISAinformationwecomputed, another principal component analysis on the NSFC, Log-NSFC space ( Supplementary Table S3 ),was carried out. In this case, the extracted components correspond to the “consensus” (PC1) and“divergent” (PC2) information carried by the two biomarkers and, by construction, correspond to a rotation of the log-NSFC  /  IC-ELISA space explaining the total initial information.  Cancers  2019 ,  11 , 1449 5 of 11   Figure 2.  Projection (component scores) of the patients in the bi-dimensional space spanned by the two principal components (PC1 = exosome component and PC2 = serum component). We extracted the first principal component scores (EXOMIX) to perform a ROC analysis of the combined NSFC  /  ELISA information together with the srcinal biomarkers. The top panel (Figure 3A) highlights how the convergence between NSFC and IC-ELISA approaches only holds at the “gross scale” of PCa  /  BPH discrimination (BPH patients occupy the left  /   bottom part of the graph while PCa group distributes in the right  /  top quadrants). On the contrary, the “within-group” variance of the twovariables is largely independent (intra class Pearson correlation r = 0.05 (NS) and r = –0.14(NS) for PCa and BPH groups, respectively). Figure 3.  Cont .
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