Prostate cancer biomarkers, uses and methods thereof

Abstract

The present disclosure relates to an in vitro or ex vitro use of at least a protein as a biomarker to detect or monitor prostate cancer in a sample, preferably intraductal and / or cribriform prostate cancer. Furthermore, the present disclosure relates to a method for in vitro or ex vivo method for diagnosis or prognosis of prostate cancer in a subject, and also to a kit.

Description

D E S C R I P T I O NPROSTATE CANCER BIOMARKERS, USES AND METHODS THEREOFTECHNICAL FIELD

[0001] The present disclosure pertains to the realm of medical diagnostics and / or prognosis, focusing on the in vitro or ex vitro use of at least a protein as a biomarker for the detection or monitoring of prostatic diseases and potentially poor prognosis histopathological patterns such as intraductal and / or cribriform prostate cancer in a sample, in particular in a urinary sample.BACKGROUND

[0002] Prostate cancer (PCa) is the most frequently diagnosed cancer and the second leading cause of cancer-related death among men in developed countries1. Cribriform pattern (Crib) and intraductal prostate cancer (IDC) are two histological patterns of PCa related to poor clinical outcomes and a worse prognosis, yet there are limited clinical tools for their early detection2-3. Studies that have investigated the histologic correlation between multiparametric magnetic resonance imaging (mpMRI) observation and Crib PCa have shown inconsistent results, as those are often less visible on mpMRI than non-Crib predominant tumors4. Moreover, the positive predictive value of an abnormal mpMRI remains extremely low, being less than 30% in most studies, meaning that if one has an abnormal mpMRI lesion, IDC / Crib is found in only 30% of patients at radical prostatectomy (RP). Overall, the use of mpMRI and mpMRI-guided biopsies is not sufficient for accurately categorizing these abnormalities in a way that can be reliably applied in medical practice5.

[0003] Furthermore, prostate biopsies still have a significant number of false negatives (about 50%) for the accurate diagnosis of those patterns6. The routine failure to accurately identify IDC / Crib in needle biopsies and mpMRI outcomes leads to the misclassification of potentially aggressive prostate tumors. This clinical scenario takes on even more significance due to the increasing trend of recommending active surveillance for patients with Gleason 7 (3+4) disease.

[0004] Given the above clinical challenges, it is an urgent need to develop specific biomarkers for IDC / Crib as a diagnostic tool in the clinical setting.

[0005] These facts are disclosed in order to illustrate the technical problem addressed by the present disclosure.GENERAL DESCRIPTION

[0006] The present disclosure relates to the in vitro or ex vivo use of at least a protein as a biomarker to detect or monitor prostate cancer in a sample, wherein said protein is selected from the list consisting of: TMBIM1, GNG5, IGLL5, S100A10, PTGES3, C1Q.A, C1Q.C, FGG, ALDOB, trehalase, COTL1, KIF1A, CENPF or mixtures thereof.

[0007] Unexpectedly, the inventors have observed a correlation between the amount of certain proteins in liquid biopsy samples, in particular urinary extracellular vesicles, and the histological pattern of prostate cancer. The inventors found a protein signature for diagnosis or poor prognosis of prostate cancer, in particular intraductal (IDC) and / or cribriform (Crib) prostate cancer, from urinary vesicles, which represents a pivotal advancement in diagnostic and therapeutic approaches. The most striking revelation is the unexpected functional enrichment of extracellular vesicle protein biomarkers within the androgen signaling treatment axis, clearly demonstrating a link between urinary EVs and prostate cancer cells. This unforeseen connection not only enhances the understanding of the molecular intricacies underlying prostate cancer but also unveils a novel avenue for precision diagnostics and targeted treatment strategies.

[0008] The inventors found a clear pattern of androgen response down-regulation in urinary extracellular vesicles EVs from IDC / Crib compared to non-IDC / non-Crib. They observed that urinary EV constitutes a non-invasive target to unveil proteomic signatures of IDC and Crib PCa patterns, allowing the identification of a urinary biomarker protein signature for patients with Crib and IDC. 171 proteins differentially expressed between IDC / Crib and non-IDC / Crib were identified. Furthermore, functional analysis showed that proteins involved in androgen responses are overall downregulated in IDC / Crib compared to HD. However, androgen response was less relevant when comparing non-IDC / non-Crib and HD.

[0009] It was also surprisingly found that high expression levels of at least a protein (preferably a urinary extracellular vesicle protein) selected from gene name identifiers "C1Q.A, C1Q.C, FGG, ALDOB, trehalase, COTL1, KIF1A, CENPF" or mixtures thereof, was significantly associated with an increased risk of biochemical recurrence after prostate cancer treatment.

[0010] Extracellular vesicles (EVs), particularly exosomes, which are 50-150 nm in size and enclosed by membrane, are shed by various mammalian cell types, including cancerous cells, and are also formed in the endosomal network before being released by the fusion of multi-vesicular bodies with the plasma membrane7. These vesicles contain various biomolecules, including proteins, lipids, DNA, and RNA, that reflect the molecular composition of their tissue of origin8.

[0011] In the present disclosure, ISUP refer to the International Society of Urological Pathologists (ISUP) Grade Group system, which grades prostate cancer from 1 (least aggressive) to 5 (most aggressive).

[0012] An aspect of the present disclosure relates to an in vitro or ex vivo use of a protein signature as a biomarker to detect or monitor prostatic disease and intraductal and / or cribriform prostate cancer in a sample, wherein said protein is selected from the list consisting of.: TMBIMl, GNG5, IGLL5, S100A10 ,PTGES3, C1QA, C1QC, FGG, ALDOB, trehalase, COTL1, KIF1A and CENPF or mixtures thereof.

[0013] TMBIMl is better identified by the protein name "Protein lifeguard 3" and primary accession 0.969X1 (UniProtKB). Secondary accessions are B3KQY6, Q8N1R3, Q8TAM3, Q96K13 (UniProtKB).

[0014] GNG5 is better identified by the protein name "Guanine nucleotide-binding protein G(I) / G(S) / G(O) subunit gamma-5" and primary accession P63218 (UniProtKB). Secondary accessions are B2R5A0, P30670, Q5VX54 and Q61015 (UniProtKB).

[0015] IGLL5 is better identified by the protein name "Immunoglobulin lambda-like polypeptide 5" and primary accession B9A064 (UniProtKB).

[0016] S100A10 is better identified by the protein name "Protein S100-A10" and primary accession P60903 (UniProtKB). Secondary accessions are A8K4V8, P08206 and Q.5T1C5 (UniProtKB).

[0017] PTGES3 is better identified by the protein name "Prostaglandin E synthase 3" and primary accession A0A087WYT3 (UniProtKB).

[0018] C1Q.A is better identified by the protein name "Complement Clq A Chain" and primary accession number P02745 (UniProtKB). Secondary accessions are B2R4X2 and Q.5T963 (UniProtKB).

[0019] C1Q.C is better identified by the protein name "Complement Clq C Chain" and primary accession number P02747 (UniProtKB). Secondary accessions are Q7Z502, Q96DL2 and Q96H05(UniProtKB).

[0020] FGG is better identified by the protein name "Fibrinogen Gamma Chain" and primary accession number P02679 (UniProtKB). Secondary accessions are A8K057, P04469, P04470, Q.53Y18, Q.96A14, Q.96KJ3, Q.9UC62, Q.9UC63, Q.9UCF3 (UniProtKB).

[0021] ALDOB is better identified by the protein name "Aldolase, Fructose-Bisphosphate B" and primary accession number P05062 (UniProtKB). Secondary accession numbers are Q.13741, Q13742, Q5T7D6 (UniProtKB).

[0022] TREH is better identified by the protein name Trehalase and primary accession number 043280 (UniProtKB). Secondary accessions are Q32MB9, Q53FY8.

[0023] COTL1 is better identified by the protein name "Coactosin Like F-Actin Binding Protein 1" and primary accession number Q14019 (UniProtKB). Secondary accessions are B2RDU3, D3DUL9, Q86XM5.

[0024] KIF1A is better identified by the protein name Kinesin Family Member 1A and primary accession number Q12756 (UniProtKB). Secondary accession numbers are B0I1S5, F5H045, 095068, Q13355, Q14752, Q2NKJ6, Q4LE42, Q53T78, Q59GH1, Q63Z40, Q6P1R9, Q7KZ57.

[0025] CENPF is better identified by the protein name Centromere Protein F and primary accession number P49454 (UniProtKB). Secondary accession numbers are Q.13171, Q.13246, Q.5VVM7

[0026] The Universal Protein Resource (UniProt) is a comprehensive resource for protein sequence and annotation data. The UniProt Knowledgebase (UniProtKB) is the central hub for the collection of functional information on proteins, with accurate, consistent and rich annotation. UniProtKB provides one or more accession number(s). These are stable identifiers and should be used to cite UniProtKB entries.

[0027] An aspect of the present disclosure relates to an in vitro or ex vivo use of at least a protein as a biomarker to detect or monitor prostate cancer in a sample (diagnostic or prognostic), wherein said protein is selected from the list consisting of: TMBIMl, GNG5, IGLL5, S100A10, PTGES3, C1Q.A, C1Q.C, FGG, ALDOB, trehalase, COTL1, KIF1A and CENPF or mixtures thereof, wherein the sample is a biological sample selected from the list consisting of: interstitial fluid, blood, plasma, serum or urine.

[0028] In a preferred embodiment, the use is to detect or monitor intraductal and / or cribriform prostate cancer in a sample.

[0029] In a preferred embodiment, the protein is selected from the list consisting of: TMBIMl, GNG5, IGLL5, S100A10, PTGES3, or mixtures thereof.

[0030] In an embodiment, the protein is selected from the list consisting of e.g.: TMBIMl, GNG5, IGLL5, or mixtures thereof.

[0031] In an embodiment, the proteins are TMBIMl and GNG5; TMBIMl and IGLL5; or GNG5 and IGLL5.

[0032] In another embodiment, the proteins are S100A10 and / or PTGES3.

[0033] In an embodiment, the use is wherein a measured level of the protein or proteins (selected from the list consisting of e.g.: TMBIMl, GNG5, IGLL5, or mixtures thereof) into an isolated sample is compared to a control reference value, and wherein an increase of said measured level relative to said control reference value is indicative of diagnosis or poor prognosis of prostate cancer, more preferably intraductal (IDC) and / or cribriform (Crib) prostate cancer.

[0034] In an embodiment, the use is wherein a measured level of the protein or proteins (S100A10 and / or PTGES3) into an isolated biological sample is compared to a control reference value, and wherein a decrease of said measured level relative to said control reference value is indicative of diagnosis or poor prognosis of prostate cancer, more preferably intraductal (IDC) and / or cribriform (Crib) prostate cancer.

[0035] In a preferred embodiment, the protein is selected from the list consisting of: C1Q.A, C1Q.C, FGG, ALDOB, trehalase, COTL1, KIF1A, CENPF, or mixtures thereof; preferably to detect or monitorbiochemical relapse-free survival (bRFS) after prostate cancer treatment. In a preferred embodiment, the proteins are C1Q.A and C1Q.C; or C1Q.A and FGG; or C1QA and ALDOB; or C1Q.A and trehalase; or C1QA and COTL1; or C1Q.C and FGG; or C1Q.C and ALDOB; or C1QC and trehalase; or C1QC and COTL1; or FGG and ALDOB; or FGG and trehalase; or FGG and COTL1; or ALDOB and trehalase; or ALDOB and COTL1; or trehalase and COTL1; or KIF1A and CENPF. In a more preferred embodiment, the use is wherein a measured level of the protein or proteins into a sample is compared to a control reference value, and wherein an increase of said measured level relative to said control reference value is indicative of diagnosis or poor prognosis for prostate cancer.

[0036] Biochemical relapse-free survival (bRFS) is defined as the length of time after primary treatment during which there is no evidence of cancer recurrence, as indicated by prostate-specific antigen (PSA) levels.

[0037] In a preferred embodiment, the sample is a biological sample selected from the list consisting of: interstitial fluid, blood, plasma, serum or urine; preferably urine.

[0038] In a preferred embodiment for better results, the proteins are urinary extracellular vesicle proteins.

[0039] Another aspect of the present disclosure relates to a protein for use in in vivo diagnosis or prognosis of prostate cancer, preferably intraductal and / or cribriform prostate cancer, wherein said protein is selected from the list consisting of: TMBIMl, GNG5, IGLL5, S100A10, PTGES3, C1Q.A, C1Q.C, FGG, ALDOB, trehalase, COTL1, KIF1A, CENPF, or mixtures thereof.

[0040] Another aspect of the present disclosure relates to an in vitro or ex vivo method for diagnosis or prognosis of cancer, comprising the following steps: providing a biological sample of a patient; measuring the content or amount of at least one of the biomarkers selected from the list consisting of: TMBIMl, GNG5, IGLL5; or mixtures thereof; comparing said content or amount to a control reference value; wherein an increased presence content or amount of said biomarkers relative to said control reference value is indicative of diagnosis or poor prognosis of prostate cancer; preferably intraductal and / or cribriform prostate cancer.

[0041] In an embodiment, the method further comprises a step of measuring the content or amount of additional biomarkers.

[0042] In a preferred embodiment, the method is an in vitro or ex vivo method for diagnosis or prognosis of intraductal and / or cribriform prostate cancer.

[0043] In a preferred embodiment, the method further comprises the following steps:measuring the content or amount of at least one of the biomarkers selected from the list consisting of: S100A10 and / or PTGES3; comparing said content or amount to a control reference value; wherein a decreased presence content or amount of said biomarkers relative to said control reference value is indicative of diagnosis or poor prognosis of prostate cancer; preferably intraductal and / or cribriform prostate cancer.

[0044] In a preferred embodiment, the method further comprises the following steps: measuring the content or amount of at least one of the biomarkers selected from the list consisting of: C1QA, C1Q.C, FGG, ALDOB, trehalase, COTL1, KIF1A, CENPF, or mixtures thereof; comparing said content or amount to a control reference value; wherein an increase presence content or amount of said biomarkers relative to said control reference value is indicative of diagnostic or poor prognosis of prostate cancer; more preferably intraductal and / or cribriform prostate cancer.

[0045] In a preferred embodiment, the biological sample is selected from the list consisting of: interstitial fluid, blood, plasma, serum or urine. In a preferred embodiment for better results, the biological sample is urine.

[0046] Another aspect of the present disclosure relates to a kit for in vitro or ex vivo diagnosis or prognosis of cancer comprising an agent to detect the concentration of at least one protein selected from the list consisting of TMBIM1, GNG5, IGLL5, S100A10, PTGES3, , C1Q.A, C1Q.C, FGG, ALDOB, trehalase, COTL1, KIF1A, CENPF, or mixtures thereof. In a preferred embodiment, the kit is for in vitro or ex vivo diagnosis or prognosis of intraductal and / or cribriform prostate cancer.

[0047] In a preferred embodiment, the kit further comprises at least one reagent for the detection of agent-protein binding. In a preferred embodiment, the agent is a monoclonal antibody, a polyclonal antibody, a substrate, an aptamer, an avimer, a peptidomimetic, a receptor, a ligand or a cofactor; preferably stable isotope labelled reference peptides for accurate concentration determination.

[0048] In a preferred embodiment, the kit is formulated as a ELISA kit, a dip stick rapid kit, a microarray kit, an immunoassay kit or a multiple reaction monitoring kit; preferably a multiple reaction monitoring kit comprising stable isotope labelled peptides for multiple reaction monitoring.

[0049] Another aspect of the present disclosure relates to a protein for use in medicine, wherein said protein is selected from the list consisting of: TMBIMl, GNG5, IGLL5, S100A10, PTGES3, C1Q.A, C1Q.C, FGG, ALDOB, trehalase, COTL1, KIF1A, CENPF, or mixtures thereof.BRIEF DESCRIPTION OF THE DRAWINGS

[0050] The following figures provide preferred embodiments for illustrating the disclosure and should not be seen as limiting the scope of invention.

[0051] Figure 1: Urinary EV characterization by western blot and NTA. A) CD63 and Alix western blot of representative urinary EVP samples from each major clinical groups. B) Non-EVP markers GRP75 and TOM20 as markers of transmembrane, lipid-bound and soluble proteins associated to other intracellular compartments than plasma membrane and endosomes. NTA particle size distribution analysis of a representative urinary EVP sample from (C) BPD and (D) IDC / Crib (insert represents a zoom in). Particle size mode distribution (E) and number of particles per protein amount (F) across major clinical subgroups. The central line inside each box represents the median value. Whiskers extend from the edges of the box to the minimum and maximum values within 1.5 times the interquartile range (IQR). Individual data points beyond the whiskers are considered outliers and are plotted individually.

[0052] Figure 2: Transmission electron microscopy (TEM) analysis. A:4000x magnification, B) TEM 20000x magnification.

[0053] Figure 3: Overview of regulated proteins for three pairwise comparisons. A) Table summary of up- and down-regulated proteins applying a 0.05 adjusted P value and no threshold on effect size. The numbers in parenthesis represent regulated proteins with similar thresholds but applying regular P values. Volcano plots for the pairwise comparisons B) non-IDC / non-Crib versus HD, C) IDC / Crib versus HD, D) cancer versus HD, E) ISUP>2 versus ISUP=1 and C) ISUP>2 versus ISUP=1 considering adjustment of other clinical variables. Red horizontal line indicates 0.05 P value threshold. Red vertical lines indicate two-fold differential regulation. The number of regulated proteins indicated in the titles is based on P values and adjusted P values with an effect size greater than twofold.

[0054] Figure 4: Volcano plots for the pairwise comparisons. A) Number of significantly regulated proteins for each of the pairwise comparisons given as Nadjust-P- aiue (Nreguiar-P- aiue). B) IDC / Crib versus non- IDC / non-Crib, C) crib versus non-IDC / non-Crib, D) cribriform and IDC versus non-IDC / non-Crib, and E) IDC versus non-IDC / non-Crib. F) Crib versus IDC. Red horizontal line indicates 0.05 P value thresholds. Red vertical lines indicate two-fold differential regulation. The number of regulated proteins indicated in the titles is based on P values and adjusted P value with an effect size greater than twofold.

[0055] Figure 5: Box plot displaying the distribution of iBAQ values across increasing levels of Gleason score. The box plot showcases the median (represented by the horizontal line inside the box), interquartile range (IQR; the box's height), and the minimum and maximum values (whiskers) within each level. Increasing trends are displayed for A) HIST1H2BE, B) JCHAIN, C) HPX, and D) SERPINA1. P value calculated by Jonckheere's test.

[0056] Figure 6: Linear Discriminant Analysis (LDA) of three groups: HD (green), non-IDC / non-Crib (red), and I DC / Crib (blue).

[0057] Figure 7. Diagnostic test pipeline.

[0058] Figure 8: Functional enrichment analysis of cancer hallmark proteins based on significant regulated proteins for pairwise comparisons to control. Scatter plot displaying -logic P value for enrichment as a function of the number of proteins matching for each functional group based on the pairwise comparisons A) non-IDC / non-Crib vs HD, B) I DC / Crib vs HD and C) cancer vs HD.

[0059] Figure 9. Kaplan-Meier Survival Analysis of Patients Stratified by ALDOB (Aldolase, Fructose- Bisphosphate B) Expression Levels Kaplan-Meier survival curves comparing the survival probabilities of patients with high and low ALDOB expression. Shaded regions represent the 95% confidence intervals for each group. The x-axis denotes time (days), while the y-axis represents the survival probability. The p-value (p = 5e-04) indicates a statistically significant difference between the two groups, suggesting that ALDOB expression levels are associated with patient survival outcomes. Censoring events are marked with small vertical ticks along the survival curves.

[0060] Figure 10. Forest plot of Cox regression analysis for gene expression levels adjusted for age. The hazard ratio (HR) and 95% confidence intervals (Cis) are shown for each gene. The HR is represented by blue dots, and the horizontal blue lines indicate the corresponding Cis. The dashed red line represents HR = 1, indicating no association with survival. P-values for each gene are displayed next to their respective points. The analysis was performed using Cox proportional hazards regression.DETAILED DESCRIPTION

[0061] The present disclosure relates to an in vitro or ex vitro use of at least a protein as a biomarker to detect or monitor cancer in a sample, in particular intraductal and / or cribriform prostate cancer, in particular a liquid sample. Furthermore, the present disclosure relates to a method for in vitro or ex vivo method for diagnosis or prognosis of prostate cancer in a subject, and also to a kit.Clinical study

[0062] Liquid biopsies (urine samples) were collected from healthy donors and PCa patients. More specifically, small EVs' proteome profiles from 100 individuals were analyzed using liquid chromatography coupled to high-resolution mass spectrometry (LC-MS / MS). EVs from three cohorts: healthy donors (HD, N=24), patients without Crib and IDC histological prostate patterns (non-IDC / non- Crib, N=21); and patients with Crib and / or IDC histological prostate patterns ( I DC / Crib, N=55) at biopsy were interrogated by LC-MS / MS-based proteomics.Patient samples

[0063] Clinical characteristics of the whole study population with urinary EV samples available are described in Table 1. The study population consisted of 100 males, with a median age of 72 years at diagnosis. Most patients (N= 55, 55%) were diagnosed with either cribriform and / or intraductal carcinoma of prostate (IDC / Crib). Non-IDC / non-Crib (N= 21, 21%) and HD (N= 24, 24%) were collected as control groups. HD group constituted of patients with prostate pathologies other than cancer. Non- IDC / non-Crib consisted of patients who underwent radical prostatectomy and were subsequently verified to be non-IDC / non-Crib. Clinical parameters such as pre-biopsy, number of positive cores, Gleason grade, and maximum percentage of core involvement are all significantly and positively correlated with histological patterns with either cribriform and / or intraductal carcinoma of prostate.Table 1. Clinicopathological features of 100 subjects. Abbreviations: HD, healthy donors (non cancer, benign prostatic hyperplasia).1Median (IQR); n (%),2Kruskal-Wallis rank sum test; Pearson's Chi-squared test; Fisher's exact test. Numbers in square brackets indicates number subjects with IDC and Crib, with IDC and with Crib, respectively.Variable N NHD= 241NnOn-iDc / non-crib = 211N|Dc / cnb = 551p-value2prePSA 92 2.8 (0.7, 4.2) 7.0 (5.0, 8.8) 11.4 (7.7, 31.8) <0.001Cribriform 100 <0.001NA 24 (100%) 0 (0%) 0 (0%)No 0 (0%) 21 (100%) 11 (20%)Yes 0 (0%) 0 (0%) 44 (80%)IDC 100 <0.001NA 24 (100%) 0 (0%) 0 (0%)No 21 (100%) 36 (65%)Yes 0 (0%) 19 (35%)#positive 74 5 (3, 6) 7 (4, 12) 0.011 coresGleason grade 74 <0.0013+3 6 (32%) 0 [0 / 0 / 0] (0%)3+4 10 (53%) 14 [4 / 2 / 8](25%)4+3 3 (16%) 14 [1 / 0 / 13](25%)4+4 0 (0%) 7 [1 / 0 / 6] (13%)>=9 0 (0%) 20 [2 / 9 / 9](36%)Workflow for analyzing urinary EV proteome

[0064] The workflow used for the analysis of urinary extracellular vesicles (EVs) includes the steps of EV isolation, trypsin digestion, and liquid chromatography mass spectrometry (LC-MS) analysis. Urine samples were collected and immediately frozen within two hours of collection, and stored at -80°C untilfurther processing. EVs were isolated by differential centrifugation and small urinary EVs were further digested with trypsin and analyzed by liquid chromatography mass spectrometry (LC-MS). The acquired data were analyzed using multivariate statistics and functional enrichment analysis.Quality control of urinary small EV preparations from prostate cancer patients

[0065] Multiple subsets of urinary small EV (sEV) preparations were analyzed by western blotting for EV and non-EV markers (Figure 1A-B). The immunoblots assays of sEV preparations isolated from all major clinical subgroups such as urine of HD, patients without Crib and IDC histological prostate patterns (non- IDC / non-Crib) and patients with Crib and / or IDC histological prostate patterns (IDC / Crib) were performed. As for MISEV 2018 recommendations on protein content-based EV characterization, CD63 (Category 1, Figure 1A) and ALIX (Category 2, Figure 1A) demonstrated the presence of EVs. As for specificity of small EV subtypes (Category 4) we have used GRP75 and TOM20 as markers of transmembrane, lipid-bound and soluble proteins associated to other intracellular compartments than plasma membrane and endosomes (Figure IB). Detailed immunoblot methods are described in the methods section and MISEV 2018 check list is available below in "Additional Data".

[0066] Nanoparticle tracking analysis (NTA) was performed on all urinary sEV samples. Figure 1C-D display two representative particle size distributions from two distinct urinary sEV samples. The highest peak is close to 100 nm as expected for sEVs. Figure IE displays distribution of the most abundant particle size across all the major clinical subgroups. The size distributions by NTA for urinary sEV samples were highly reproducible across multiple measurements. Figure IF show distribution of number of particles per protein amount across all the major clinical subgroups. The obtained particles per protein amount is consistent with moderate to high quality sEVs preparations10.

[0067] MS-based proteome data from urinary sEV preparations of 100 individuals were quality checked using principal component analysis (PCA) and linear discriminant analysis (LDA) based on all quantitative data. PCA exhibited reasonable separation with minor overlaps between groups when the first two components were plotted. Supervised LDA resulted in excellent separation except for three data points, one from each of the three subgroups analyzed (Figure 6). The scatter plot shows the projection of the data points onto the first two linear discriminant functions (LD1 and LD2), which are derived from the LDA analysis. The discriminant functions (LD1 and LD2) are plotted on the x-axis and y-axis, respectively, with the scale indicated on the corresponding axes. The scatter plot reveals the separation of the three groups in two-dimensional space based on the LDA analysis.

[0068] MS-based proteome data based on urinary sEV preparations from 100 patients were quality checked for exosome markers. The urinary sEVs from the present disclosure showed the highest expression of established small EV markers compared to previous studies based on sEV samples from other sources, such as cell lines11 13, lung fluids14, and blood plasma15. Urinary sEVs were devoid ofmicrosomes or large EVs protein markers. For markers indicating contamination from other subcellular organelles, a low level of calnexin was detected in urinary sEVs. However, the expression levels were lower than what had been observed in previous studies. On the other hand, the contaminant Tamm- Horsfall Protein (THP, uromodulin) was abundant in urinary sEVs isolated in this study. Despite THP abundance, high protein coverage by mass spectrometry analysis was achieved as well as a high number of identified proteins. Moreover, there was no regulation of THP across clinical subgroups. In conclusion, sEV preparation was enriched in small EVs, according to the analysis performed, which focused on described EV and contaminant markers.

[0069] Transmission electron microscopy (TEM) analysis at 4000x magnification were consistent with NTA analysis in that the majority of the particles were around 100 nm (Figure 2A). Magnification at 20000x revealed characteristic cup-shape of sEVs as a known artifact result of drying procedure (Figure 2B).Comparison of prostate tissue and urinary sEV proteome

[0070] The proteome of prostate, kidney, and bladder tissues were analysed. Urinary sEVs proteome obtained in the present study was benchmarked against different human datasets reported in the literature. Based on the bottom-up proteomics proteome profile of prostate tissue samples and baseline protein expression in human tissues extracted from previous publications16-17in comparison with the urinary sEV proteome, it was estimated that approximately 75% of the observed proteins in urinary sEVs were also detected in prostate tissue . Assuming the entire human proteome as background, this overlap was estimated to be highly significant based on the hypergeometric probability function. Nevertheless, the overlap between the proteomes of urinary sEVs and kidney and bladder were similar . Kidney tissue displayed the largest overlap with urinary sEVs, although the difference was marginal compared to urinary sEVs overlap with the other two organ tissues ). The high significance in overlap was also identified for all other tissues tested from Prakash et al16. Restricting the analysis to the 50% most abundant proteins expressed in each tissue and ranking based on the significance of the overlap the five highest ranked tissues were kidney, adipose tissue, pancreas, gall-bladder, and prostate. The largest overlap is between the three tissue proteomes. The second largest is between all four proteomes (urinary sEVs and tissue proteomes). Finally, each of the three tissue proteomes has unique overlap with urinary sEVs ranging from 11 to 43 proteins. Although most proteins in urinary sEVs are present in all three tissues, there are 367 proteins from other tissue sources. Overall, it was found that urinary sEVs are a promising source of markers for prostate-related pathologies.Sensitivity and specificity

[0071] The method herein described provides the following sensitivity and specificity for predicting prostate cancer, comparing with the standard method (multiparametric magnetic resonance imaging (mpMRI)).

[0072] Table 2. Comparison between the method of the present invention and the standard method (sensitivity, specificity and balanced accuracy).

[0073] It was found that the method of the present disclosure provides similar sensitivity and specificity in comparison with the standard method, which represents excellent results, since the method of the present disclosure is much cheaper, faster and non-invasive for the patient. These estimates are for significant prostate cancer. IDC and Cribriform is not detected by mpMRI.Unique identified proteins across clinical subgroups

[0074] Data-dependent acquisition with two technical replicates was applied for the identification of proteins.. The unique proteins for each clinical subgroup were typically not consistently identified throughout the subgroup. Nevertheless, the proteins unique to non-IDC / non-Crib and Crib displayed unique proteins that were shared between four to six patients. For example, proteins such as NPTN (Neuroplastin), KRTAP11-1 (Keratin associated protein 11-1) and CD99 (CD99 molecule)Significant differentially expressed proteins

[0075] Three pairwise comparisons were performed using the R package limma18. Figure 3 provides an overview table and volcano plots visualizing regulated proteins for three pairwise comparisons. The comparison between non-IDC / non-Crib and HD resulted in the most regulated proteins (Figure 3A, 3B). For this comparison, 238 of the proteins were found down-regulated in non-IDC / non-Crib compared to HD, with a log2range of regulation from -6.57 to -0.25 (Figure 3B ). The range for the 118 up-regulated proteins ranged from 0.19 to 4.25. The comparison between IDC / Crib and HD exhibited less regulated proteins (Figure 3A, 3C). The range of significantly regulated proteins was 0.58 to 3.89 for up-regulated proteins and -3 to -0.23 for down-regulated proteins. Comparing the merged non-IDC / non-Crib and IDC / Crib into the group cancer for comparison with HD resulted in a similar pattern of regulation as for the IDC / Crib and HD comparison (Figure 3D). Suggesting that IDC / Crib and non-IDC / non-Crib are identified as distinct entities based on urinary EV proteome. Therefore, merging IDC / Crib and non- IDC / non-Crib results in large variance for statistical comparisons. The regulated proteins parsed forfunctional analysis were additionally filtered to be at least twofold regulated (indicated in Figure 3B, 3F, in sub-title). Grouping patients into significant PCa (ISUP > 2) and non-significant PCa (ISUP = 1) also resulted in regulated proteins after correction of multiple testing (Figure 3E ). Adjusting the linear models for prePSA, age and batch number resulted in only minor differences in the list of regulated proteins (Figure 3F, Figure 3E).

[0076] To look for significant differences between IDC / Crib versus non-IDC / non-Crib and IDC versus cribriform at EV proteome level, the IDC / Crib group characteristic of aggressive PCa was divided into more precise subgroups. Pairwise comparisons of different combinations of cribriform and IDC samples versus non-IDC / non-Crib patient samples resulted in many significantly regulated proteins after correction for multiple testing (Figure 4) compared to the comparisons using HD group as a reference. Comparison between cribriform and IDC patient samples also revealed significantly regulated proteins, but not after correction for multiple testing (Figure 4F). Again model adjustments by prePSA, age and batch effect resulted in only minor differences. However, including adjustment for ISUP or Gleason grade eliminated almost all significantly regulated proteins. Nevertheless, for the comparison IDC / Crib versus non-IDC / non-Crib two proteins (S100A10 and PTGES3) showed significant dysregulation after correction for multiple testing and including adjustment for ISUP in the linear model.Proteins correlated with Gleason score and pre-PSA

[0077] Several protein expression patterns in urinary EVs were observed to correlate with clinical parameters such as pre-biopsy PSA, Gleason grade, and number of positive cores. Figure 5 displays box plots and P values calculated by Jonckheere's test for the four significant increased protein expressions as Gleason score severity increase. These proteins include histone cluster 1, H2be (HIST1H2BE), immunoglobulin J chain (JCHAIN), HPX (hemopexin) and alpha-l-antitrypsin (SERPINA1). In addition, to JCHAIN and a number of other immunoglobulin related proteins displayed significant increased trends as a severity of Gleason score increase (not shown).

[0078] prePSA measurements were also significantly correlated with increasing Gleason score (Jonckheere's test P value < 0.001). Therefore the proteins correlated with prePSA were similar to the ones correlating with Gleason score. The four most correlated proteins to prePSA were SERPINA1, IGLV3-21 (Immunoglobulin lambda variable 3-21), SERPINA3 and C9 (Complement component C9) were also among the most significantly correlated to Gleason score.Functional analysis of regulated proteins

[0079] Significantly regulated proteins with an effect size of at least two fold were subjected to functional enrichment analysis. In the first analysis, all regulated proteins with at least two-fold regulation were submitted for each of the comparisons using the HD group as reference. Fatty acid metabolism appeared as the most relevant functional group when comparing non-IDC / non-Crib and HDgroups (. When comparing IDC / Crib group or whole PCa cancer group versus HD, androgen response related proteins surfaced as the most relevant functional group. To provide additional information on the overall direction of regulation in the functional groups, heatmaps summarizing p value enrichment based on all regulated proteins with a twofold effect size for all comparisons with HD as reference group, all regulated proteins with two-fold up-regulation and all regulated proteins with two-fold downregulation were plotted. Androgen response appears overall down-regulated for cancer group compared to HD group. Furthermore, IDC / Crib group has the most significant down-regulation of androgen response compared to non-IDC / non-Crib group. For up-regulated proteins, fatty acid metabolism showed a correlation in non-IDC / non-Crib group whereas epithelial-mesenchymal transition is involved in the IDC / Crib groupFor the more detailed, subgroups androgen response, epithelial- mesenchymal transition, and reactive oxygen species appeared as the main functional entities playing a role in distinguishing the subgroups.

[0080] In the present disclosure, small urinary EVs were isolated from 100 individuals (Table 1). The isolated urinary EVs displayed the highest level of established EV markers compared to previous cell line studies and studies performed on other types of biofluids. Although THP was identified as an abundant contaminant protein, THP was not identified as significantly regulated among samples. It was found that small urinary EVs are promising sources of biomarkers for diseases affecting the kidney, bladder, or prostate. Concerning the number of uniquely identified proteins per clinical subgroup, IDC+Crib and Crib displayed the highest number of identified proteins. Most of the uniquely identified proteins in the current study were identified in a few individuals, but for crib and non-IDC / non-Crib, one protein was consistently identified only within the specific clinical group.

[0081] TMBIM1, also known as Bax inhibitor 1 (Bl-l), was among those most upregulated in Crib and IDC compared to cancer without IDC / Crib (Figure 4B-E). Bax inhibitor 1 (Bl-l), plays a crucial role in regulating apoptosis and calcium homeostasis by inhibiting the activity of the pro-apoptotic protein Bax and protecting cells from apoptosis induced by various stimuli.

[0082] Another protein factor consistently up-regulated in Crib and IDC found in the present study is GNG5 (guanine nucleotide-binding protein G(I) / G(S) / G(O) subunit gamma-5) and IGLL5 (immunoglobulin lambda-like polypeptide 5). In this study it was specifically identified an immunoglobulin subclass that correlated with the Gleason score. GNG5 and IGLL5 are involved in immune regulation and B-cell activation, respectively, suggesting dysregulated immune function.

[0083] Gleason grade and IDC / Crib are correlated (Table 1). However, adjusting for ISUP in the limma regression models still resulted in the proteins S100A10, also known as pll, and Prostaglandin E synthase enzyme3 (PTGES3) significantly dysregulated after correction for multiple testing. S100A10 is considered a significant cancer promotor. Although, in urinary sEVs from IDC / Crib S100A10 wassignificantly down regulated in urinary sEVs whereas in advanced tumor stages it is reported up regulated. PTGES3 is a well-studied oncogene, also named p23. PTGES3 has been suggested to be overexpressed in multiple cancers, including breast cancer, colorectal cancer, cervical cancer and lung31. PTGES3 also correlate with poor prognosis. PTGES3 required for proper functioning of the glucocorticoid and other steroid receptors. Again, PTGES3 exhibited a significant downregulation in urinary small extracellular vesicles (sEVs), contrasting with the observed reverse dysregulation in tissue.

[0084] Significantly regulated proteins identified in the present study based on pairwise comparisons were compared with previous proposed biomarkers based on either prostate tissue-specific32, prostate tissue marker17-33-34or urinary and cell line EVs marker19-22-35(Table 3). Note there are no previous studies on IDC and Crib targeting urinary EV proteome.Table 3. Overview of past prostate cancer MS-based proteomics studies.First author Year Target sampleDhondt et al192020 Urinary EVsSequeiros et a!222017 Urinary EVsFujita et al202017 Urinary EVsZhang et al212020 Human Seminal PlasmaPrincipe et al322012 Prostatic secretionsKawahara et al332019 Prostate tissueTuriak et al342019 Prostate tissueIglesias-Gato172016 Prostate tissueBijnsdorp et al352013 Cell line

[0085] Strikingly, the present study did not show any particular overlap with the previous studies by Fujita et al 201720and Kawahara et al 201933. Most overlapping proteins are well described in association with cancer. For example, Fetuin-A (AHSG) is described as driving pancreatic, prostate, and glioblastoma tumors36. Circulating blood and urine B2M is a well-established marker of cancer37. ELANE and CD177 are neutrophil markers with previous association with prostate cancer.

[0086] On the other hand, the peripheral zone constitutes the most common site of origin of neoplasms in the aged prostate and its stroma contains, among other cell types, fibroblasts. These, by inducing epithelial transformation (EMT) and stimulating survival signaling, contribute to an increase in cancer cells invasion and metastisation.

[0087] A previous study on PCa38identified HIST1H2BE as predictor of Gleason grade, which we identified as correlating with Gleason score (Figure 5). According to research conducted on a cohort of acute lymphoblastic leukemia (ALL) patients that deceased, the overexpression of JCHAIN waspresumably connected to tumor aggression39. JCHAIN encodes the immunoglobulin J chain and joins the monomer units of IgA and IgM. HPX has long been regarded as the ultimate scavenger of labile heme and the plasma protein with the highest affinity for heme. A previous study observed low levels of HPX in prostate tumors and in the plasma of prostate cancer patients40. Perhaps increased urinary secretion of HPX occurs in cancer. Lung cancer, gastric cancer, and colorectal cancer were demonstrated to have altered invasive and metastatic capacities in response to the serine protease inhibitor serpinAl41. serpinAl was also identified when comparing to PCa to HD (Figure 3D) and when correlating protein expression with prePSA.

[0088] Androgen response (AR) refers to the ability of PCa cells to respond to androgens. Indeed, AR plays a crucial role in both the onset and spread of PCa42. The majority of androgen-independent or hormone-refractory PCa express AR, and AR expression is sustained throughout disease progression. AR transcriptional activation in reaction to antiandrogens or other endogenous hormones, mutations of the androgen receptor, particularly mutations that result in a relaxation of AR ligand specificity, may contribute to the progression of prostate cancer and the failure of endocrine therapy. There is evidence to suggest that androgen response can decline in advanced or aggressive PCa43. Interestingly, we also observed IL2 Stat5 pathway dysregulation, which might be related to the fact that, in PCa cells, transcription factor Stat5 synergizes with the androgen receptor44.

[0089] Overall, significantly dysregulated proteins in urinary EVs mostly resemble the profiles characterized in previous publications on PCa as well as other cancers.

[0090] In the present study, the sample size was estimated to obtain proof of concept as a pilot study and is single centered. Global label free quantitation was performed to target many proteins in an unbiased manner. More precise targeted protein quantitation can be performed in follow up studies to measure concentration of biomarkers. Participants were randomly assigned into two experimental batches except from non-IDC / non-Crib and potential batch effect was corrected for in the analysis. All patients fulfilling the eligibility criteria were enrolled thereby minimizing selection bias. Reporting bias was minimized by only addressing pairwise comparisons related to the objectives in the study design.

[0091] In conclusion, it was surprisingly found that the proteome of small urinary EVs reflect the proteome of prostate tissue and can be use in vitro / ex vivo as a biomarker to detect or monitor intraductal (IDC) and / or cribriform (Crib) prostate cancer. Urinary EV proteome highlighted proteins with a role in androgen response, epithelial mesenchymal transition, fatty acid metabolism and reactive oxygen species as prognostic factors for prostate cancer.

[0092] In an independent cohort, it was surprisingly found that high expression levels of several key proteins (urinary extracellular vesicle proteins), in particular components of the Clq complement complex (C1QA and C1Q.C), COTL1 (Coactosin-Like Protein 1, important for cell mobility), fibrinogengamma chain (FGG), fructose-bisphosphate aldolase B (ALDOB), and trehalase (TREH), were significantly associated with an increased risk of biochemical recurrence after prostate cancer treatment (P value < 0.0005, Figure 9 and Figure 10). Among 25 other clinical parameters evaluated as potential predictors of biochemical recurrence, only two factors - tumor TMN stage T3b (p value = 6.00 x 10-5) (indicative of seminal vesicle invasion) and cribriform pattern status (p value = 4.7 x 10-4, achieved comparable significance to that of the urinary extracellular vesicle proteins.

[0093] Notably, all of these proteins (C1Q.A, C1Q.C, fibrinogen gamma chain (FGG), fructose- bisphosphate aldolase B (ALDOB), trehalase and COTL1) are known to be upregulated in prostate tumor tissue, suggesting their potential role as biomarkers for aggressive disease. Furthermore, only TMN stage and cribriform pattern status post-surgery displayed similar significance as the urinary extracellular vesicle proteins mentioned above.

[0094] In an independent study, it was surprisingly found that high expression levels of KIF1A (HR = 2.9) and CENPF (HR = 3.2) proteins (detected as urinary extracellular vesicle proteins) were associated with an increased risk of biochemical recurrence after prostate cancer treatment.Methods and MaterialsPatients

[0095] Patients were selected for EV isolation followed by EV proteome profiling based on below criteria. Information was collected prospectively in a single time for each patient before any treatment (treatment naive). Patient enrollments started in April 2020 and ended in May 2022. All enrollments were from a single center, Centro Hospitalar e Universitario Lisboa Central, Lisbon, Portugal. Enrollment was continued untill the number samples were in accordance with the study protocol. The final cohort were composed of healthy donors (HD, N=24), patients without Crib and IDC histological prostate patterns (non-IDC / non-Crib, N=21), and patients with Crib and / or IDC histological prostate patterns (I DC / Crib, N=55) at biopsy.

[0096] Inclusion Criteria:1. Men over 18 years old.2. No previous history of PCa treatments.Exclusion Criteria1. History of other forms of focal treatment of PCa2. Radical surgery performed in the context of "salvage" strategy, due to recurrence or local persistence.3. Neoadjuvant and / or adjuvant treatment (includes any type of hormonotherapy as LHRH agonists / antagonists)4. History of urothelial cancer (bladder or upper urinary tract)

[0097] Mid-stream urine (30 - 120 mL) from PCa suspects were collected, immediately frozen at -80° C and stored upon collection until EV isolation. The experimental protocols were approved by the medical agencies and ethics committees of NOVA Medical School (82 / 2020 / CEFCM). All patients signed informed consent before trial participation.

[0098] Clinical data collected were prePSA (ELISA), histological type, Gleason grade / score (World Health Organization (WHO) and the College of American Pathologists (CAP)), number of positive cores, histological patterns Crib and IDC-p at biopsy. Samples were organized into two experimental batches for urinary EV isolation followed by LC-MS analysis with random batch allocation of the three sample groups HD, non-IDC / non-Crib and IDC / Crib. Subsequent analysis confirmed balanced allocation of sample groups in each experiment batch to minimize confounding batch effects. All clinical measurements were obtained in a blinded manner without knowledge of the final clinical outcome. This approach ensured that the assessors performing the measurements remained unbiased and uninfluenced by the eventual results, minimizing potential researcher bias. The numbers of samples to collect were estimated based on standard error obtained on LC-MS from previous studies performed in our group and estimated with the R function pwr assuming paired testing. The number of samples collected and the single center collection were considered appropriate for a pilot study. Strobe check list is presented below in "Additional Data".Isolation of Extracellular Vesicles from urine

[0099] Frozen urine specimens were thawed and centrifuged at 3000x g for 20 min at 4 °C and then at 12,000x g for 60 min at 4 °C. Clarified urine was ultracentrifuged in an Optima TM L-80XP ultracentrifuge (Beckman Coulter, Brea, CA, USA) at 170,000x g at 4 °C for 120 min with a Type 32 Ti rotor to pellet EVs. The supernatant was carefully removed, and crude EV-containing pellets were resuspended in ice-cold PBS.Protein Measurements

[0100] Following manufacturer's instructions, a bicinchoninic acid (BCA) protein assay kit (Pierce Biotechnology, Rockford, IL, USA) was used to measure the protein concentrations in isolated exosome fractions.Western blotting

[0101] For western blotting (WB) assay, 5 microg sEVs were mixed with Laemmli sample buffer (BioRad) boiled for 10 min at 100°C. Then, the samples were resolved by SDS-PAGE followed by transfer onto nitrocellulose membranes (Cytiva). Blocking was performed during lh with 5% skim milk in TBST 0.1% or PBST 0.1 % Tween or 5% BSA in TBST 0.1% Tween. Primary antibodies (CD63, SICGEN (AB0047);Alix, SICGEN (AB0327), TOM20, BD Biosciences (612278), GRP75, Cell Signaling Technology (2816S)) were incubated overnight at 4°C and secondary antibodies (HRP-AffiniPure Donkey Anti-Goat IgG (H+L), HRP-AffiniPure Goat Anti-Mouse IgG (H+L), HRP- Affini Pure Goa Anti-Rabbit IgG (H+L), Jackson ImmunoResearch) during lh at room temperature (RT). Development was performed using ECL™ prime Western blotting detection reagent (Cytiva) and the Chemidoc Touch Imager (BioRad).Nanoparticle tracking EV measurements

[0102] A NanoSight NS300 instrument (Malvern Panalytical, Malvern, UK) was used to determine the concentrations and sizes of the EVs in the samples. Samples were diluted in PBS to a final volume of 1 ml to reach the ideal particle concentration of 1 x 108- 2 x 109particles / mL. The samples were loaded to the sample chamber in a continuous flow by a syringe pump. The instrument was equipped with a 488 nm laser and a sCMOS camera. The focus for each sample was manually adjusted to achieve optimal visualization of particles and for each measurement five videos of 60 seconds were captured. For all experiments the following settings were used: temperature: 25°C; Syringe speed: 20; Viscosity: 0.9 cP; camera level setting ranged from 13-14 in light scatter mode (LSM). After capture, the videos have been analysed by the in-build NanoSight Software NTA 3.4 Build 3.4.4 with a detection threshold of 5. To minimize variability, all camera and detection threshold settings were kept the same and all particles over 300 nm of diameter were excluded from the analysis.Electron Microscopy

[0103] 5 pL of each sample was incubated on glow-discharged (0.5 min) formvar-carbon coated copper mesh grids (Electron Microscopy Sciences) for 2 min, before washing 10 times with dH2O. Samples were negatively stained with 2% uranyl acetate in dH2O for 2 minutes, before blotting dry and imaging with a Hitachi H-7650 TEM equipped with an AMT XR41 M digital camera.Peptide Sample Preparation

[0104] Samples containing a minimum of 20 pg of total EV proteins were further processed by the filter-aided sample preparation (FASP) method. In short, protein solutions containing SDS and DTT were loaded onto filtering columns (Millipore, Billerica, MA, USA) and washed exhaustively with 8M urea (GE, Healthcare, Marlborough, MA, USA) in HEPES buffer (Sigma-Aldrich, Saint Louis, MO, USA) as previously described45-46. Proteins were equilibrated with ammonium bicarbonate solution prior to trypsin digestion overnight at 37°C (Sigma-Aldrich, Saint Louis, MO, USA). Overnight cleavage of proteins was carried out using sequencing-grade trypsin (Promega, Madison, Wl, USA).Mass Spectrometry Analysis

[0105] As previously described13, samples were analyzed by mass spectrometry-based proteomics using nano-LC-MSMS equipment (Dionex RSLCnano 3000) coupled to an Exploris 480 Orbitrap massspectrometer (Thermo Scientific, Hemel Hempstead, UK). In brief, samples were loaded onto a custom- made fused capillary pre-column (2 cm length, 360 pm OD, 75 pm ID, flowrate 5 pL per minute for 6 min) packed with ReproSil Pur C18 5.0 pm resin (Dr. Maisch, Ammerbuch-Entringen, Germany), and separated using a capillary column (25 cm length, 360 pm outer diameter, 75 pm inner diameter) packed with ReproSil Pur C18 1.9-pm resin (Dr. Maisch, Ammerbuch-Entringen, Germany) at a flow of 250 nL per minute. A 56 min linear gradient from 89% A (0.1% formic acid) to 32% B (0.1% formic acid in 80% acetonitrile) was applied. Mass spectra were acquired in positive ion mode in a data-dependent manner by switching between one Orbitrap survey MS scan (mass range m / z 350 to m / z 1200) followed by the sequential isolation and higher-energy collision dissociation (HCD) fragmentation and Orbitrap detection of fragment ions of the most intense ions with a cycle time of 2 s between each MS scan. MS and MSMS settings: maximum injection times were set to "Auto", normalized collision energy was 30%, ion selection threshold for MSMS analysis was 10,000 counts, and dynamic exclusion of sequenced ions was set to 30 s.Database Search

[0106] The data obtained from the 200 LC-MS runs of urine EV samples from 24 controls and 76 PCa cases, characterized following radical prostatectomy (55 with and 21 without Cribriform pattern and / or IDC) each run as technical duplicates were analyzed. The LC-MS data were searched using VEMS47and MaxQuant48(Version 2.1.0.0). The MSMS spectra were searched against a standard human proteome database from UniProt (3AUP000005640).Permuted protein sequences, where arginine and lysine were not permuted, were included in the database for VEMS and FDR in MaxQuant version 2.1.0.0 were based on reversed sequences. 1% FDR threshold was applied for peptide and protein identifications. Trypsin cleavage allowing a maximum of four missed cleavages was used. Carbamidomethyl cysteine was included as fixed modification. Methionine oxidation, lysine and N-terminal protein acetylation, were included as variable modifications. No restriction was applied for minimal peptide length for VEMS search. All other search parameters were default values. The downstream analysis presented is based on the MaxQuant results.Estimation of analytical variability

[0107] In the comprehensive proteomic investigation performed, the precision of the experimental raw measurements was evaluated (prior to quality filtering or normalization), as evidenced by a calculated average coefficient of variation (CV) of 34.1%. The mean CV was estimated to 13.1% after normalization. This average CV is based on all measurements on all proteins in the technical replicas. This indicative measure underscores the reliability and consistency of protein abundance quantification across technical replicates, affirming the robustness of our proteomic profiling methodology.Statistical Analysis

[0108] Statistical analysis of identified proteins was performed in R statistical programming language. Quantitative data from MaxQuant and VEMS were analyzed in R statistical programming language version 4.04 (The R Foundation, Vienna, Austria). Protein label free quantitation (iBAQ) and protein spectral counts from the two programs were preprocessed by removing common MS contaminants, followed by a Iog2(x + 1) transformation and removing common MS contaminants. iBAQ values from the duplicated measurements were averaged. No imputation of missing or zero value protein quantitation values were performed in the analysis. Information on sample grouping based on histological patterns which were used for pairwise comparisons were complete for all samples. Protein iBAQ values were subjected to statistical analysis utilizing the R package limma18, where the contrast for different pairwise comparisons was specified for the main clinical groups HD, non-IDC / non-Crib and IDC / Crib. Samples were processed in two large batches to minimize experimental bias. For sensitivity analysis, various linear regression models including terms to correct for batch effect and PSA were tested and these models displayed minimal effect on the number significantly regulated proteins called after correction for multiple testing. For example, batch effect had no effect for the comparison IDC / Crib versus HD and cancer versus HD. For non-IDC / non-Crib versus HD only a difference of two more significantly regulated proteins were observed.

[0109] Correction for multiple testing was applied using the method of Benjamini & Hochberg49. Volcano plots were constructed with ggplot software (The R Foundation, Vienna, Austria). To test for increasing trend in iBAQ values as Gleason grade increase, the Jonckheere's test were calculated using the R package clinfun50. It examined whether there is a significant trend in iBAQ values across the increasing levels of Gleason grade. A low p-value indicates strong evidence against the null hypothesis of no trend, suggesting a significant increasing pattern. For correlation analysis a few missing values were present for same patients and cases with missing values for correlation analysis were excluded. Sensitivity of the analysis was assessed by comparing protein markers obtained by correlating to clinical parameters that are known to correlate with sample grouping.Functional Enrichment Analysis

[0110] Functional enrichment based on the hypergeometric probability test was performed as described previously in R51-52. Functional enrichment was based on extracting all functional categories for which at least one of the samples showed a significant enrichment based on the hypergeometric probability test51-52. For these functional categories, the matching proteins' gene names and numbers of proteins matching the functional categories were extracted, and the estimated p values were -logic transformed and plotted as heatmaps. Functional enrichment was performed for all identified proteinsin each sample group and for deregulated proteins when comparing sample groups. Cellular component (CC), biological process (BP), molecular function (MF), KEGG and cancer hallmark functional annotations were considered in the analysis.ADDITIONAL DATAData availability

[0111] The mass spectrometry proteomics data that support the findings of this study have been deposited in ProteomeXchange Consortium53via the PRIDE54partner with the PXD043874 accession codes, which is currently in private mode.MISEV 2018 check list

[0112] 1-NomenclatureMandatory+++ Generic term extracellular vesicle (EV): With demonstration of extracellular (no intact cells) and vesicular nature per these characterization (Section 4) and function (Section 5) guidelines OR+++ Generic term, e.g., extracellular particle (EP): no intact cells but MISEV guidelines not satisfied Encouraged (choose one)+ Generic term extracellular vesicle (EV) + specification(size, density, other)+ Specific term for subcellular origin: e.g., ectosome, microparticle, microvesicle (from plasma membrane), exosome (from endosomes), with demonstration of the subcellular origin+ Other specific term: with definition of specific criteria

[0113] It was applied the generic term extracellular vesicle (EV) throughout present patent application.

[0114] 2-Collection and pre-processing++ Donor status if available (age, sex, food / water intake, collection time, disease, medication, other)+++ Volume of biofluid or volume / mass of tissue sample collected per donor++ Total volume / mass used for EV isolation (if pooled from several donors)+++ All known collection conditions, including additives, at time of collection+++ Pre-treatment to separate major fluid-specific contaminants before EV isolation+++ Temperature and time of biofluid / tissue handlingbefore and during pre-treatment+++ Storage and recovery (e.g., thawing) of CCM, biofluid, or tissue before EV isolation (storage temperature, vessel, time; method of thawing or other sample preparation)+++ Storage and recovery of EVs after isolation (temperature, vessel, time, additive(s)...)Mid-stream urine (30 - 150 mL) from PCa suspects were collected, immediately frozen at -80°C and stored upon collection until EV isolation. The time length from urine collection and EV isolation varied between 2 and 6 months. Frozen stored urine was thawed at room temperature, followed by consecutive increased centrifugation speed. Isolated EVs were resuspended in PBS filtered with 0.2pm filter and stored in low binding protein microcentrifuge tubes at -80°C.

[0115] 3-EV separation and concentration

[0116] Experimental details of the method++ Centrifugation: reference number of tube(s), rotor(s), adjusted k factor(s) of each centrifugation step (= time+ speed+ rotor, volume / density of centrifugation conditions), temperature, brake settings++ Filtration: reference of filter type (=nature of membrane, pore size...), time and speed of centrifugation, volume before / after (in case of concentration)++ Antibody-based : reference of antibodies, mass Ab / amount of EVs, nature of Ab carrier (bead, surface) and amount of Ab / carrier surface++ Other...: all necessary details to allow replication++ Additional step(s) to concentrate, if any++ Additional step(s) to wash matrix and / or sample, if any Specify category of the chosen EV separation / concentration method (Table 1):+ High recovery, low specificity = mixed EVs and non-EV components OR+ Intermediate recovery, intermediate specificity =mixed EVs with limited non-EV components OR+ Low recovery, high specificity = subtype(s) of EVs with as little non-EV as possible OR+ High recovery, high specificity = subtype(s) of EVs with as little non-EV as possible

[0117] Frozen urine specimens were thawed at room temperature centrifuged at 3000x g for 20 min at 4°C and then at 12,000 xg for 60 min at 4°C using polypropylene centrifuge tubes (Beckman Coulter, cat. no. 326823). Clarified urine was ultracentrifuged in an Optima L-100XP ultracentrifuge (Beckman Coulter, Brea, CA, USA) at 170,000x g at 4°C for 120 min with a Type 32 Ti rotor (Beckman Coulter) to pellet EVs with acceleration and deacceleration at maximum. The supernatant was carefully removed,and crude EV-containing pellets were resuspended in ice-cold PBS and stored at -80°C until further analysis.4-EV characterization

[0118] Quantification (Table 2a, Section 4-a)+++ Volume of fluid, and / or cell number, and / or tissue mass used to isolate EVs+++ Global quantification by at least 2 methods: protein amount, particle number, lipid amount, expressed per volume of initial fluid or number of producing cells / mass of tissue+++ Ratio of the 2 quantification figures Global characterization (Section 4-b, Table 3)+++ Transmembrane or GPI-anchored protein localized in cells at plasma membrane or endosomes+++ Cytosolic protein with membrane-binding or -association capacity+++ Assessment of presence / absence of expected contaminants (At least one each of the three categories above)++ Presence of proteins associated with compartments other than plasma membrane or endosomes++ Presence of soluble secreted proteins and their likely transmembrane ligands+ Topology of the relevant functional components (Section 4-d) Single EV characterization (Section 4-c)+++ Images of single EVs by wide-field and close-up: e.g. electron microscopy, scanning probe microscopy, super-resolution fluorescence microscopy+++ Non-image-based method analysing large numbers of single EVs: NTA, TRPS, FCS, high- resolution flow cytometry, multi-angle light-scattering, Raman spectroscopy, etc.

[0119] Thirty-six milliliters from each patient sample were used to isolate EVs. Total protein EV preparations were quantified using BCA assay. Particle count and particle size analysis were performed using Nanotracking analysis by NanoSight NS300. The ratio of the number of particles per microgram of total EV protein was calculated. As for MISEV 2018 recommendations on protein content-based EV characterization, CD63 (Category 1) and ALIX (Category 2) demonstrated the presence of EVs. As for specificity of small EV subtypes (Category 4) we have used GRP75 and TOM20 as markers of transmembrane, lipid-bound and soluble proteins associated to other intracellular compartments than PM / endosomes. Detailed immunoblot methods are described in the methods section .

[0120] 6-Reporting+++ Submission of data (proteomic, sequencing, other) to relevant public, curated databases or open-access repositories++ Temper EV-specific claims when MISEV requirements cannot be entirely satisfied (Section 6-b)

[0121] The mass spectrometry proteomics data that support the findings of this study have been deposited in ProteomeXchange Consortium via the PRIDE partner with the PXD043874 accession codes (DOI: 10.6019 / PXD043874), which is currently in private mode.Table 4. STROBE check listSTROBE Statement— checklist of items that should be included in reports of observational studiesItemNo Recommendation1 (a) Indicate the study's design with a commonly usedProfiling of urinary extracellular term in the title or the abstract vesicle protein signatures from (b) Provide in the abstract an informative and balanced patients with cribriform and summary of what was done and what was found intraductal prostate carcinoma in a cross-sectional study p.lIntroductionBackground / rationale 2 p.2Objectives 3 p.2MethodsStudy design 4 Present key elements of study design early in the paper:P. 3 topSetting 5 Describe the setting, locations, and relevant dates, including periods of recruitment, exposure, follow-up, and data collection: P. 3 topParticipants 6 Cross-sectional study— Give the eligibility criteria, and the sources and methods of selection of participants: P. 3 topVariables 7 Clearly define all outcomes, exposures, predictors, potential confounders, and effect modifiers. Give diagnostic criteria, if applicable. P.3Data sources / measurement 8* For each variable of interest, give sources of data and details of methods of assessment (measurement). Describe comparability of assessment methods if there is more than one group: P.3Bias 9 Describe any efforts to address potential sources of bias.P.3Study size 10 Explain how the study size was arrived at P.3Quantitative variables 11 Explain how quantitative variables were handled in the analyses. If applicable, describe which groupings were chosen and why. P.5Statistical methods 12 Describe all statistical methods, including those used to control for confounding. P4-5(b) Describe any methods used to examine subgroups and interactions. P4-5(c) Explain how missing data were addressed. P.4-5(e) Describe any sensitivity analyses. P.5Table 5. ResultsParticipants 13 (a) Report numbers of individuals at each stage of study— eg numbers* potentially eligible, examined for eligibility, confirmed eligible, included in the study, completing follow-up, and analysed. All patients that fulfilled the inclusion and exclusion criteria and provided informed consent were analysed.(b) Give reasons for non-participation at each stage. NA(c) Consider use of a flow diagram. NADescriptive 14 (a) Give characteristics of study participants (eg demographic, clinical, data * social) and information on exposures and potential confounders. P.3(b) Indicate number of participants with missing data for each variable of interest. P.6 Table 1.(c) Cohort study— Summarise follow-up time (eg, average and total amount) NAOutcome data 15 Cohort study— Report numbers of outcome events or summary * measures over time NACase-control study— eport numbers in each exposure category, or summary measures of exposure NACross-sectional study— Report numbers of outcome events or summary measures P.6Main results 16 (a) Give unadjusted estimates and, if applicable, confounder-adjusted estimates and their precision (eg, 95% confidence interval). Make clear which confounders were adjusted for and why they were included(b) Report category boundaries when continuous variables were categorized NA(c) If relevant, consider translating estimates of relative risk into absolute risk for a meaningful time period NAOther 17 Report other analyses done— eg analyses of subgroups and interactions, analyses and sensitivity analyses P.5DiscussionKey results 18 Summarise key results with reference to study objectives P.18Limitations 19 Discuss limitations of the study, taking into account sources of potential bias or imprecision. Discuss both direction and magnitude of any potential bias P.18Interpretation 20 Give a cautious overall interpretation of results considering objectives, limitations, multiplicity of analyses, results from similar studies, and other relevant evidenceGeneralisabilit 21 Discuss the generalisability (external validity) of the study results P.17 yOther informationFunding 22 P.19

[0123] Table 6: Overview of protein signature regulation for different comparisons. The right list is non-redundant list of the specific protein markers.Prostate vs HD logFC PanelSERPINA3 3.7 ACOT2PPAP2A -2.3 AQ.P1SERPINA1 3.6 CA2ISUP>=2 CHMP2BCA2 4.1 CYBRD1GNAI3 4.0 DPP4HRG -3.9 GNAI3ACOT2 -1.3 GNG5CHMP2B 3.1 HRGCYBRD1 4.0 LAMTOR4RAC1 2.6 PPAP2ANON-CRIB / IDC vs IDC / CRIB PPIAGNG5 -6.3 RAC1S100A6 -3.3 RANSFN -5.2 S100A6RAN -3.4 SERPINA1LAMTOR4 -4.3 SERPINA3DPP4 -1.7 SERPINB6SLC15A2 -3.6 SFNAQ.P1 -5.2 SLC15A2PPIA 1.3 TGM4TMEM256 -6.6 TMBIM1TMBIM1 -5.9 TMEM256IDC / CRIB vs HD XPNPEP2SERPINA3 3.9 JCAINTGM4 -2.9 HIST1H2BESERPINB6 -1.7 ELANEXPNPEP2 -2.3 CKBPPAP2A -2.3 CD177SERPINA1 3.5 AHSG

[0124] The project is funded by Terry fox. R.M. is supported by Fundagao para a Ciencia e a Tecnologia (CEEC position, CEECIND / 03906 / 2017). R.B is supported by FCT (Grant number 2022.13386.BD). R.M. and A.S.C. receive funding by programme and National Funds through FCT— Portuguese Foundation for Science and Technology under the projects number PTDC / BTM-TEC / 1746 / 2021 and European Union to advance EV research (Horizon2020 GA n° 101079264, EVCA). We acknowledge the COST Action CA20113388"PROTEOCURE" supported by COST (European Cooperation in Science and Technology). The present study is a result of the projects (iNOVA4Health - UIDB / 04462 / 2020 and UIDP / 04462 / 2020, and by the Associated Laboratory LS4FUTURE (LA / P / 0087 / 2020), two programs financially supported by Fundagao para a Ciencia e Tecnologia / Ministerio da Ciencia, Tecnologia e Ensino Superior.

[0125] The term "comprising" whenever used in this document is intended to indicate the presence of stated features, integers, steps, components, but not to preclude the presence or addition of one or more other features, integers, steps, components or groups thereof.

[0126] As used in the specification and claims, the singular forms "a", "an" and "the" include plural references unless the context clearly dictates otherwise. For example, the term "a sample" includes a plurality of samples, including mixtures thereof.

[0127] Whenever the term "at least," "greater than," or "greater than or equal to" precedes the first numerical value in a series of two or more numerical values, the term "at least," "greater than" or "greater than or equal to" applies to each of the numerical values in that series of numerical values. For example, greater than or equal to 1, 2, or 3 is equivalent to greater than or equal to 1, greater than or equal to 2, or greater than or equal to 3.

[0128] The terms "determining," "measuring," "evaluating," "assessing," "assaying," and "analyzing" are often used interchangeably herein to refer to forms of measurement. The terms include determining if an element is present or not (for example, detection). These terms can include quantitative, qualitative or quantitative and qualitative determinations. Assessing can be relative or absolute. "Detecting the presence of" can include determining the amount of something present in addition to determining whether it is present or absent depending on the context.

[0129] As used herein, the term "about" a number refers to that number plus or minus 10% of that number. The term "about" a range refers to that range minus 10% of its lowest value and plus 10% of its greatest value.

[0130] The disclosure should not be seen in any way restricted to the embodiments described and a person with ordinary skill in the art will foresee many possibilities to modifications thereof.

[0131] The above described embodiments are combinable.

[0132] The following claims further set out particular embodiments of the disclosure.References1 Sung, H. et al. Global Cancer Statistics 2020: GLOBOCAN Estimates of Incidence and Mortality Worldwide for 36 Cancers in 185 Countries. CA: a cancer journal for clinicians 71, 209-249, doi:10.3322 / caac.21660 (2021).2 Bernardino, R. M. et al. Prostate cancer with cribriform pattern: Exclusion criterion for active surveillance? Archivio Italiano di urologia, andrologia : organo ufficiale [di] Societa italiana di ecografia urologica e nefrologica 92, doi:10.4081 / aiua.2020.3.235 (2020).3 Masoomian, M. et al. Concordance of biopsy and prostatectomy diagnosis of intraductal and cribriform carcinoma in a prospectively collected data set. Histopathology 74, 474-482, doi:10.1111 / his.13747 (2019).4 Truong, M. et al. Impact of Gleason Subtype on Prostate Cancer Detection Using Multiparametric Magnetic Resonance Imaging: Correlation with Final Histopathology. 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Claims

C L A I M S1. An in vitro or ex vivo use of at least a protein as a biomarker to detect or monitor prostate cancer in a sample, wherein said protein is selected from the list consisting of: TMBIMl, GNG5, IGLL5, S100A10, PTGES3, C1Q.A, C1Q.C, FGG, ALDOB, trehalase, COTL1, KIF1A, CENPF, or mixtures thereof; wherein the sample is a biological sample selected from the list consisting of: interstitial fluid, blood, plasma, serum or urine.

2. The use according to the previous claim to detect or monitor poor prognosis of intraductal and / or cribriform prostate cancer in a sample.

3. The use according to any of the previous claims wherein the protein is selected from the list consisting of: TMBIMl, GNG5, IGLL5, S100A10, PTGES3, or mixtures thereof.

4. The use according to any of the previous claims wherein the protein is selected from the list consisting of: TMBIMl, GNG5, IGLL5, or mixtures thereof.

5. The use according to any of the previous claims wherein the proteins are TMBIMl and GNG5; TMBIMl and IGLL5; or GNG5 and IGLL5.

6. The use according to any of the previous claims wherein the proteins are S100A10 and / or PTGES3.

7. The use according to any of the previous claims 4-5 wherein a measured level of the protein or proteins into a sample is compared to a control reference value, and wherein an increase of said measured level relative to said control reference value is indicative of diagnosis or poor prognosis of prostate cancer, preferably of intraductal (IDC) and / or cribriform (Crib) prostate cancer.

8. The use according to the previous claim 6 wherein a measured level of the protein or proteins into a sample is compared to a control reference value, and wherein a decrease of said measured level relative to said control reference value is indicative of diagnosis or poor prognosis of cancer, preferably prostate cancer, more preferably intraductal (IDC) and / or cribriform (Crib) prostate cancer.

9. The use according to the previous claim 1 wherein the protein is selected from the list consisting of: C1QA, C1Q.C, FGG, ALDOB, trehalase, COTL1, KIF1A, CENPF, or mixtures thereof; preferably to detect or monitor biochemical relapse-free survival (bRFS) after prostate cancer treatment.

10. The use according to the previous claim wherein the proteins are C1Q.A and C1Q.C; or C1Q.A and FGG; or C1Q.A and ALDOB; or C1Q.A and trehalase; or C1Q.A and COTL1; or C1Q.C and FGG; or C1Q.C and ALDOB; or C1QC and trehalase; or C1QC and COTL1; or FGG and ALDOB; or FGG and trehalase; or FGG and COTL1; or ALDOB and trehalase; or ALDOB and COTL1; or trehalase and COTL1; or KIF1A and CENPF.

11. The use according to any of the previous claims 9-10 wherein a measured level of the protein or proteins into a sample is compared to a control reference value, and wherein an increase of said measured level relative to said control reference value is indicative of diagnosis or poor prognosis for prostate cancer.

12. The use according to any of the previous claims wherein the biological sample is urine.

13. A protein for use in vivo, diagnosis or prognosis of prostate cancer, wherein said protein is selected from the list consisting of: TMBIM1, GNG5, IGLL5, S100A10, PTGES3, C1Q.A, C1Q.C, FGG, ALDOB, trehalase, COTL1, KIF1A, CENPF, or mixtures thereof.

14. The protein for use according to the previous claim for intraductal and / or cribriform prostate cancer.

15. An in vitro or ex vivo method for diagnosis or prognosis of prostate cancer, comprising the following steps: providing a biological sample of a patient; measuring the content or amount of at least one of the biomarkers selected from the list consisting of: TMBIMl, GNG5, IGLL5; or mixtures thereof; comparing said content or amount to a control reference value; wherein an increased presence content or amount of said biomarkers relative to said control reference value is indicative of diagnosis or poor prognosis of prostate cancer; preferably intraductal and / or cribriform prostate cancer.

16. The method according to the previous claim for diagnosis or prognosis of intraductal and / or cribriform prostate cancer.

17. The method according to any of the previous claims 15-16 further comprising the following steps: measuring the content or amount of at least one of the biomarkers selected from the list consisting of: S100A10 and / or PTGES3;comparing said content or amount to a control reference value; wherein a decreased presence content or amount of said biomarkers relative to said control reference value is indicative of diagnosis or poor prognosis of prostate cancer; more preferably intraductal and / or cribriform prostate cancer.

18. The method according to any of the previous claims 15-17 further comprising the following steps: measuring the content or amount of at least one of the biomarkers selected from the list consisting of: C1QA, C1Q.C, FGG, ALDOB, trehalase, COTL1, KIF1A, CENPF, or mixtures thereof; comparing said content or amount to a control reference value; wherein an increase presence content or amount of said biomarkers relative to said control reference value is indicative of diagnostic or poor prognosis of prostate cancer; more preferably intraductal and / or cribriform prostate cancer.

19. The method according to any of the previous claims 15-18 wherein the biological sample is selected from the list consisting of: interstitial fluid, blood, plasma, serum or urine.

20. The method according to the previous claim wherein the biological sample is urine.

21. A kit for in vitro or ex vivo diagnostic of prostate cancer comprising an agent to detect the concentration of at least one protein selected from the list consisting of TMBIMl, GNG5, IGLL5, S100A10, PTGES3, C1Q.A, C1Q.C, FGG, ALDOB, trehalase, COTL1, KIF1A, CENPF, or mixtures thereof.

22. The kit according to the previous claim for in vitro or ex vivo diagnosis or prognosis of intraductal and / or cribriform prostate cancer.

23. The kit according to any of the previous claims 21-22 further comprising at least one reagent for the detection of agent-protein binding.

24. The kit according to the previous claim 21 wherein the agent is a monoclonal antibody, a polyclonal antibody, a substrate, an aptamer, an avimer, a peptidomimetic, a receptor, a ligand, a cofactor or stable isotope labelled reference peptides; preferably stable isotope labelled reference peptides.

25. The kit according to any of the previous claims 21-24 wherein the kit is formulated as a ELISA kit, a dip stick rapid kit, a microarray kit, an immunoassay kit or a multiple reaction monitoring kit; preferably a multiple reaction monitoring kit comprising stable isotope labelled peptides for multiple reaction monitoring.