Use of a marker set for determining the aggressiveness of a prostate tumor

Abstract

The invention relates to the use of a marker set comprising at least three substances chosen from the group consisting of 5-hydroxymethyl-2-furancarboxylic acid, phenylacetylglutamine, N-acetylglutamine, L-tyrosine, dimethylamine, L-leucine, mannitol, sucrose, trigonelline, alanine, and scyllo-inositol in an in-vitro method for determining the aggressiveness of a prostate tumor.

Description

[0001] Use of a marker set for determining the aggressiveness of a prostate tumor

[0002] Description

[0003] The present invention relates to the in-vitro use of a marker set for determining the aggressiveness of a prostate tumor according to the preamble of claim 1 , to the further medical use of such a marker set according to the preamble of claim 12 as well as to an analysis method for determining the aggressiveness of a prostate tumor according to the preamble of claim 13.

[0004] Prostate cancer (PCa) affects 1 out of 6 to 8 men. 15 to 35 % of newly diagnosed prostate cancers are locally advanced and / or metastatic. The currently applied standard for diagnosing prostate cancer is determining the concentration of prostate-specific antigen (PSA). However, PSA has low specificity so that there is a high number of patients who obtain a misdiagnosis and an overtreatment.

[0005] The assessment of PCa aggressiveness is important for disease prognosis and treatment options.

[0006] When prostate cancer is suspected, a punch biopsy is typically performed to confirm the presence of the tumor and assess its aggressiveness A prostate biopsy is an invasive procedure that involves the removal of tissue core samples mainly from the peripheral zone (the outer part) of the prostate gland. Usually, 6 to 14 cores are taken and analyzed by a pathologist and, subsequently, the grade and stage of the disease are determined.

[0007] The Gleason scoring system is the most common grading system used to assess the aggressiveness of prostate cancer (i.e., for grading prostate cancer). It is based on the histological evaluation of the prostate tissue obtained from biopsy or after prostatectomy. The score ranges from 1 to 5 according to the pattern of cell growth of the tumor. The total score (Gleason sum) is the sum of two grades: A primary grade given to the predominant (most extensive) cell morphology and a secondary grade describing the cells of the next largest area of the tumor. The Gleason sum can range from 2 (non-aggressive cancer) to 10 (very aggressive cancer). The higher the score, the more aggressive is the cancer. The Gleason scoring system is described, e.g., in detail by Humphrey (Humphrey, P. A. (2004). Gleason grading and prognostic factors in carcinoma of the prostate. Modem Pathology, 173), 292- 306).

[0008] The staging gives an insight on whether the tumor has spread beyond the prostate or not. For this purpose, the TNM stage is used. TNM staging describes the size and location of the primary tumor (T), the involved nearby lymph nodes (N), and the spread or metastasis of the tumor (M). Patients are assigned into clinical risk groups (low, intermediate, or high-risk), depending on PSA-level, Gleason grade and clinical TNM-staging.

[0009] Although biopsy is a reliable diagnosis tool, it has low detection sensitivity and is susceptible to undergrade and understage the cancer due to random sampling resulting in over-treatment. The invasive nature of the biopsy is associated with a risk of infection.

[0010] A histological evaluation of the tumor after prostatectomy will give much better information on PCa aggressiveness than a punch biopsy. However, these scoring systems suffer from a high inter-observer variability leading to the risk of misclassification. More importantly, these classifications used for clinical decision making cannot consider distinct tumor phenotypes and hence fail to reliably predict patients’ individual risk.

[0011] Consequently, there exists a need for novel biomarkers to improve clinical decision-making and management of PCa.

[0012] It is an object of the present invention to provide novel methods and biomarkers for determining the aggressiveness of a prostate tumor.

[0013] This object is achieved with the in-vitro use of a marker set having the claim elements of claim 1 . Such a marker set comprises at least three (e.g., 3, 4, 5, 6, 7, 8, 9, 10, or 1 1 ) substances chosen from the group consisting of 5-hydroxymethyl-2-furancarboxylic acid (Sumiki’s acid), phenylacetylglutamine, N-acetylglutamine, L-tyrosine, dimethylamine, L-leucine, mannitol, sucrose, trigonelline, alanine, and scyllo-inositol. According to an aspect of the present invention, this marker set is used for determining the aggressiveness of a prostate tumor.

[0014] For this purpose, the concentration of the substances contained in the marker set is determined in a body fluid obtained from a patient. This concentration determination can be carried out by any appropriate measuring or analysis method, such as nuclear magnetic resonance (NMR) spectroscopy, mass spectrometry, and infrared spectroscopy such as Fourier-transform infrared (FT-IR) spectroscopy. An alteration of concentration of at least three substances of the marker set with respect to the concentration in a control group or an alteration of a concentration ratio between at least three substances with respect to the concentration ratio of the same substances in a control group was correlated in a statistically significant way with the aggressiveness of a prostate tumor.

[0015] In an embodiment, determining the aggressiveness of a prostate tumor means distinguishing an aggressive prostate tumor from an indolent prostate tumor, i.e., making a differential diagnosis between an aggressive prostate tumor and an indolent prostate tumor.

[0016] For identifying the marker set and the substances that can make up the marker set, urine (as representative body fluid) of patients suffering from an advanced prostate cancer (having a post-operation histology Gleason score of higher than 6) was used. The control group consisted of patients suffering from indolent prostate cancer having a post-operation histology Gleason score of lower than or equal to 6.

[0017] When testing individual biomarkers of the substances contained in the marker set or two biomarkers of this marker set at the same time, no significant results could be obtained for distinguishing the two groups (aggressive prostate tumor versus indolent prostate tumor). Rather, the area under the curve (AUC) values of receiver operating characteristic (ROC) plots showed values mainly lying in a range of from 0.5 to 0.65. The AUC value of ROC plots is an aggregated metric that evaluates how well a logistic regression model classifies positive and negative outcomes at all possible cut-offs. It can range from 0 to 1 .0. An AUC value of 0 represents a prediction of the opposite of the trained correlation. An AUC value of 0.5 represents a random prediction. An AUC value of higher than 0.5 represents a classification of an event as fulfilling the trained correlation wherein higher values represent better classification.

[0018] The marker sets were tested against training datasets and test datasets and iteratively crossvalidated. Cross-validation was performed by splitting the training dataset into, e.g., five parts and by using four parts for training (training subset) and the fifth part for testing (testing subset). The individual parts were iteratively removed from and returned to the training set so that each of the five parts belonged - in different training rounds - to the training subset and to the testing subset.

[0019] After all test and validation processes, 5-hydroxymethyl-2-furancarboxylic acid (Sumiki’s acid), phenylacetylglutamine, N-acetylglutamine, L-tyrosine, dimethylamine, L-leucine, mannitol, sucrose, trigonelline, alanine, and scyllo-inositol turned out to be valid biomarkers for the underlying question (i.e., distinguishing aggressive prostate tumor from indolent prostate tumor), provided that the concentration of at least three of these biomarkers was determined at the same time (i.e., in one or more body fluid samples from the same patient obtained at the same time point). The concentration determination can be made with a method being able to determine the concentration of the substances by a single measurement or by a method requiring more than one measurement for such determination. NMR spectroscopy is particularly appropriate for such a concentration determination since it enables a highly accurate concentration determination in a body fluid by a single measurement in a very short measuring time.

[0020] In an embodiment, the concentration of the substances is standardized to the concentration of creatinine in the same sample or, alternatively, to the concentration of another substance that is naturally present in the sample.

[0021] In an embodiment, the group of substances comprises either phenylacetylglutamine or N- acetylglutamine. Both substances show NMR signals in a very similar spectral region so that their NMR signals cannot always be easily distinguished from each other.

[0022] In an embodiment, the marker set comprises or consists of at least four substances, wherein two of the substances are phenylacetylglutamine and N-acetylglutamine.

[0023] In an embodiment, phenylacetylglutamine or N-acetylglutamine are not chosen at the same time as substances for the marker set.

[0024] In an embodiment, the marker set comprises or consists of alanine, mannitol, L-leucine, and at least one of phenylacetylglutamine and N-acetylglutamine.

[0025] In an embodiment, the marker set comprises or consists of tyrosine, L-leucine, sucrose, and alanine. Such a marker set showed an AUC value of 0.752 in the test dataset and an AUC value of 0.753 in the training dataset (cf. Figure 1 ).

[0026] In an embodiment, the marker set comprises or consists of L-tyrosine, L-leucine, and sucrose. Such a marker set showed also an AUC value of 0.752 in the test dataset and an AUC value of 0.737 in the training dataset (cf. Figure 2). Thus, the use of alanine as additional biomarker does not significantly increase the AUC value. Rather, L-tyrosine, L-leucine, and sucrose turned out to be very potent biomarkers without additional fourth marker. In an embodiment, the marker set comprises or consists of L-tyrosine, dimethylamine, and L- leucine. Such a marker set showed an AUC value of 0.724 in the test dataset and an AUC value of 0.708 in the training dataset (cf. Figure 3).

[0027] In an embodiment, the marker set comprises or consists of 5-hydroxymethyl-2-furancarboxylic acid, L-tyrosine, L-leucine, and sucrose. Such a marker set showed an AUC value of 0.715 in the test dataset and an AUC value of 0.777 in the training dataset (cf. Figure 4).

[0028] In an embodiment, the marker set comprises or consists of L-tyrosine, L-leucine, mannitol, and scyllo-inositol. Such a marker set showed an AUC value of 0.698 in the test dataset and an AUC value of 0.776 in the training dataset (cf. Figure 5).

[0029] In an embodiment, the marker set comprises or consists of L-tyrosine, L-leucine, and scyllo- inositol. Such a marker set showed an AUC value of 0.661 in the test dataset and an AUC value of 0.762 in the training dataset (cf. Figure 6). Thus, the performance of this marker set was only slightly less good than the performance of the marker set additionally comprising mannitol. While mannitol slightly increases the performance of the marker set, very good result can already be obtained with the marker set comprising or consisting of L-tyrosine, L-leucine, and scyllo-inositol.

[0030] In an embodiment, the marker set comprises or consists of dimethylamine, L-leucine, sucrose, and alanine. Such a marker set showed an AUC value of 0.652 in the test dataset and an AUC value of 0.786 in the training dataset (cf. Figure 7).

[0031] In an embodiment, the marker set comprises or consists of L-tyrosine, dimethylamine, L- leucine, and scyllo-inositol.

[0032] In an embodiment, the marker set comprises or consists of L-tyrosine, dimethylamine, L- leucine, and at least one of phenylacetylglutamine and N-acetylglutamine.

[0033] In an embodiment, the marker set comprises L- tyrosine and L-leucine. It turned out that these two substances are, in combination with any other of the possible substances, very potent biomarkers for distinguishing aggressive prostate tumor from indolent prostate tumor.

[0034] In an embodiment, the marker set comprises or consist of at least three (e.g., 3, 4, 5, 6, 7, 8, or 9) substances chosen from the group consisting of L-tyrosine, L-leucine, sucrose, trigonelline, alanine, dimethylamine, 5-hydroxymethyl-2-furancarboxylic acid, mannitol, and scyllo-inositol.

[0035] In an embodiment, the marker set comprises or consist of at least three (e.g., 3, 4, 5, 6, or 7) substances chosen from the group consisting of L-tyrosine, L-leucine, sucrose, dimethylamine, 5-hydroxymethyl-2-furancarboxylic acid, mannitol, and scyllo-inositol.

[0036] In an embodiment, the marker set comprises or consist of at least three (e.g., 3, 4, 5, or 6) substances chosen from the group consisting of L-tyrosine, L-leucine, sucrose, dimethylamine, 5-hydroxymethyl-2-furancarboxylic acid, and scyllo-inositol.

[0037] In an embodiment, the marker set comprises or consist of at least three (e.g., 3, 4, or 5) substances chosen from the group consisting of L-tyrosine, L-leucine, sucrose, dimethylamine, and scyllo-inositol.

[0038] In an embodiment, the marker set comprises or consist of at least three (e.g., 3 or 4) substances chosen from the group consisting of L-tyrosine, L-leucine, sucrose, and dimethylamine.

[0039] Upon analyzing a plurality of NMR spectra for identifying appropriate biomarkers for the underlying question, the inventors were able to identify NMR signals in bin A232 that appeared to be highly appropriate for determining the aggressiveness of a prostate tumor. This bin comprises a doublet signal around 5.60 ppm, wherein a first line of the doublet lies under exemplary measuring conditions at approximately 5.620 ppm and a second line of the doublet lies under the same measuring conditions at approximately 5.607 ppm. So far, the inventors were not yet successful in assigning a specific metabolite to these signals observed in bin A232. Therefore, the metabolite being responsible for the signals in bin A232 will be referred to in the following as substance Y.

[0040] In an independently claimed aspect, the present invention relates to uses of a marker set comprising the substances listed above and additionally comprising substance Y, as well as to related methods.

[0041] Therefore, in an independently claimed aspect, the present invention relates to the in-vitro use of a marker set comprising at least three (e.g., 3, 4, 5, 6, 7, 8, 9, 10, 1 1 , or 12) substances chosen from the group consisting of 5-hydroxymethyl-2-furancarboxylic acid (Sumiki’s acid), phenylacetylglutamine, N-acetylglutamine, L-tyrosine, dimethylamine, L-leucine, mannitol, sucrose, trigonelline, alanine, scyllo-inositol, and substance Y for determining the aggressiveness of a prostate tumor.

[0042] In an embodiment, the marker set comprises or consists of substance Y, L-tyrosine, L-leucine, and sucrose. Such a marker set showed an AUC value of 0.678 in the test dataset and an AUC value of 0.784 in the training dataset (cf. Figure 8).

[0043] In an aspect, the present invention relates to the further medical use of a marker set comprising at least three (e.g., 3, 4, 5, 6, 7, 8, 9, 10, or 1 1 ) substances chosen from the group consisting of 5-hydroxymethyl-2-furancarboxylic acid (Sumiki’s acid), phenylacetylglutamine, N- acetylglutamine, L-tyrosine, dimethylamine, L-leucine, mannitol, sucrose, trigonelline, alanine, and scyllo-inositol in in-vivo diagnostics of the aggressiveness of a prostate tumor.

[0044] In an aspect, the present invention relates to the further medical use of a marker set comprising at least three (e.g., 3, 4, 5, 6, 7, 8, 9, 10, 11 , or 12) substances chosen from the group consisting of 5-hydroxymethyl-2-furancarboxylic acid (Sumiki’s acid), phenylacetylglutamine, N-acetylglutamine, L-tyrosine, dimethylamine, L-leucine, mannitol, sucrose, trigonelline, alanine, scyllo-inositol, and substance Y in in-vivo diagnostics of the aggressiveness of a prostate tumor.

[0045] In an aspect, the present invention relates to the further medical use of L-tyrosine and L-leucine in in-vivo diagnostics of the aggressiveness of a prostate tumor.

[0046] In an aspect, the present invention relates to a method for analyzing an isolated body fluid sample in vitro, comprising the steps explained in the following. This method is carried out on an isolated body fluid sample originating from an individual.

[0047] In a first step, the concentration of at least three (e.g., 3, 4, 5, 6, 7, 8, 9, 10, or 11 ) substances in the body fluid sample is determined by analyzing the body fluid sample with a suited measuring technique. The at least three substances are chosen from the group consisting of 5-hydroxymethyl-2-furancarboxylic acid (Sumiki’s acid), phenylacetylglutamine, N- acetylglutamine, L-tyrosine, dimethylamine, L-leucine, mannitol, sucrose, trigonelline, alanine, and scyllo-inositol. A very well suited measuring technique for determining the concentration of the individual substances is nuclear magnetic resonance spectroscopy (NMR spectroscopy). Afterwards, a score is calculated from the determined concentrations, wherein the score is indicative for the aggressiveness of a prostate tumor.

[0048] The score can be calculated by taking into consideration the concentrations measured or expected in a body fluid sample from a control group. To give a simple example, the score can be the median of the concentration ratios of the at least three substances between the body fluid test sample of the patient and corresponding control values of a body fluid control sample that have been measured the past. If the score is above a predetermined threshold value, a significant increase of the marker substances is present in the body fluid test sample that is indicative for an aggressive prostate tumor. It should be noted that other calculation methods as well as a weighting of individual marker concentrations with respect to other marker concentrations can also be performed in an embodiment.

[0049] A suited way to calculate the score is disclosed on pages 25 to 27 of WO 2012 / 045773 A9. Another suited way to calculate the score is the following: a = const. bx= substance specific coefficient

[0050] I = parameter being indicative for the concentration of substance x

[0051] Thereby, the individual factors a, b need to be adjusted according to the underlying model and can vary in dependence on the specific substances considered in the marker set. Parameter “I” can be, e.g., the signal intensity or signal integral of an according signal observed in the evaluated measuring result. To give an example, “I” can be the signal intensity or signal integral of an NMR signal in an NMR spectrum if NMR spectroscopy is used as measuring technique.

[0052] In an embodiment, “I” is a ratio between two signal intensities or two signal integrals. In such a case, it is, e.g., possible to standardize the concentration of a first substance (or a plurality of substances) by the concentration of a second substance such as, e.g., creatinine.

[0053] The score is a (semi-)quantitative measure for the aggressiveness of a prostate tumor. Thus, the score serves for (semi-)quantitatively determining the aggressiveness of a prostate tumor. Calculating the score comprises multiplying each of the concentrations of the substances by a substance-specific weighting factor to provide a plurality of weighted values and combining the weighted values into a risk equation. Afterwards, an output of the risk equation is compared to a predefined threshold. If the score is above the threshold, the aggressiveness of the prostate tumor is increased. In an embodiment, the aggressiveness of the prostate tumor is higher, the higher the score is (i.e., the aggressiveness of the prostate tumor increases with increasing distance of the score from the threshold).

[0054] In an embodiment, the calculated score is output and presented to the individual and / or to a third person such as a physician or medical staff. The output can be performed on a display (i.e., in an electronic way) or in printed form. Thereby, it is also possible to generate a report indicating the score, optionally in combination with a comparative scale of possible scores and their meaning with respect to the prostate tumor aggressiveness.

[0055] In an embodiment, the method is a computer-implemented method. In particular, all steps of spectral analysis and concentration determination as well as of score calculation are performed on a computer. Such steps are far too complex to be done in a manual way. The computer- implemented concentration determination is, in an embodiment, based on a spectral analysis, such as an analysis of NMR spectra. The spectral analysis and the further required steps until the score can be output can be done on the same computer that is used for controlling a spectrometer performing the spectral analysis or on a different computer.

[0056] In an embodiment, the body fluid sample is a urine sample or a blood sample. In an embodiment, the blood sample is a whole blood sample, a blood serum sample, a blood plasma sample, or any other blood preparation derivable from whole blood or from other blood preparations.

[0057] In an embodiment, the body fluid sample (and therewith the patient from whom the body fluid sample originates) is grouped into one of at least two predefined groups based on the calculated score. Typically, one group encompasses patients suffering from an aggressive prostate tumor, wherein the other group encompasses patients suffering from an indolent prostate tumor. The resulting grouping can also be indicated on an according report.

[0058] In an aspect, the present invention relates to another method for analyzing an isolated body fluid sample in vitro, comprising the steps explained in the following. This method is carried out on an isolated body fluid sample originating from an individual. In a first step, the concentration of L-tyrosine and L-leucine in the body fluid sample is determined by analyzing the body fluid sample with a suited measuring technique. A very well suited measuring technique for determining the concentration of the individual substances is nuclear magnetic resonance spectroscopy (NMR spectroscopy).

[0059] Afterwards, a score is calculated from the determined concentrations, wherein the score is indicative for the aggressiveness of a prostate tumor.

[0060] In an aspect, the present invention relates to another method for analyzing an isolated body fluid sample in vitro, comprising the steps explained in the following. This method is carried out on an isolated body fluid sample originating from an individual.

[0061] In a first step, the concentration of at least three (e.g., 3, 4, 5, 6, 7, 8, 9, 10, 1 1 , or 12) substances in the body fluid sample is determined by analyzing the body fluid sample with a suited measuring technique. The at least three substances are chosen from the group consisting of 5-hydroxymethyl-2-furancarboxylic acid (Sumiki’s acid), phenylacetylglutamine, N-acetylglutamine, L-tyrosine, dimethylamine, L-leucine, mannitol, sucrose, trigonelline, alanine, scyllo-inositol, and substance Y. A very well suited measuring technique for determining the concentration of the individual substances is nuclear magnetic resonance spectroscopy (NMR spectroscopy).

[0062] Afterwards, a score is calculated from the determined concentrations, wherein the score is indicative for the aggressiveness of a prostate tumor.

[0063] In an aspect, the present invention relates to a medical method for making a differential diagnosis between prostate cancer due to an aggressive prostate tumor and prostate cancer due to an indolent prostate tumor. This method comprises the steps explained in the following.

[0064] In a first step, a body fluid sample is gathered from a patient. In a second step, the concentration of at least three (e.g., 3, 4, 5, 6, 7, 8, 9, 10, or 1 1 ) substances in the body fluid sample is determined by analyzing the body fluid sample with a suited measuring technique. The at least three substances are chosen from the group consisting of 5-hydroxymethyl-2- furancarboxylic acid (Sumiki’s acid), phenylacetylglutamine, N-acetylglutamine, L-tyrosine, dimethylamine, L-leucine, mannitol, sucrose, trigonelline, alanine, and scyllo-inositol. Afterwards, a score is calculated from the determined concentrations, wherein the score is indicative for distinguishing an aggressive prostate tumor from an indolent prostate tumor.

[0065] In a further method step, a differential diagnosis between prostate cancer due to an aggressive prostate tumor and prostate cancer due to an indolent prostate tumor is made on the basis of the previously calculated score. The respective result is then output to the patient or to a third person like a physician or medical staff.

[0066] In an aspect, the present invention relates to another medical method for making a differential diagnosis between prostate cancer due to an aggressive prostate tumor and prostate cancer due to an indolent prostate tumor. This method comprises the steps explained in the following.

[0067] In a first step, a body fluid sample is gathered from a patient. In a second step, the concentration of L-tyrosine and L-leucine in the body fluid sample is determined by analyzing the body fluid sample with a suited measuring technique.

[0068] Afterwards, a score is calculated from the determined concentrations, wherein the score is indicative for distinguishing an aggressive prostate tumor from an indolent prostate tumor.

[0069] In a further method step, a differential diagnosis between prostate cancer due to an aggressive prostate tumor and prostate cancer due to an indolent prostate tumor is made on the basis of the previously calculated score. The respective result is then output to the patient or to a third person like a physician or medical staff.

[0070] In an aspect, the present invention relates to another medical method for making a differential diagnosis between prostate cancer due to an aggressive prostate tumor and prostate cancer due to an indolent prostate tumor. This method comprises the steps explained in the following.

[0071] In a first step, a body fluid sample is gathered from a patient. In a second step, the concentration of at least three (e.g., 3, 4, 5, 6, 7, 8, 9, 10, 1 1 , 12) substances in the body fluid sample is determined by analyzing the body fluid sample with a suited measuring technique. The at least three substances are chosen from the group consisting of 5-hydroxymethyl-2- furancarboxylic acid (Sumiki’s acid), phenylacetylglutamine, N-acetylglutamine, L-tyrosine, dimethylamine, L-leucine, mannitol, sucrose, trigonelline, alanine, scyllo-inositol, and substance Y. Afterwards, a score is calculated from the determined concentrations, wherein the score is indicative for distinguishing an aggressive prostate tumor from an indolent prostate tumor.

[0072] In a further method step, a differential diagnosis between prostate cancer due to an aggressive prostate tumor and prostate cancer due to an indolent prostate tumor is made on the basis of the previously calculated score. The respective result is then output to the patient or to a third person like a physician or medical staff.

[0073] In a further aspect, the present invention relates to a decision support system for analyzing an isolated body fluid sample in vitro, the decision support system comprising: a) a unit for providing a body fluid sample from an individual; b) a unit for determining the concentration of at three substances chosen from the group consisting of 5-hydroxymethyl-2-furancarboxylic acid, phenylacetylglutamine, N- acetylglutamine, L-tyrosine, dimethylamine, L-leucine, mannitol, sucrose, trigonelline, alanine, and scyllo-inositol in the body fluid sample by analyzing the body fluid sample with a suited measuring technique; and c) a unit for calculating a score from the determined concentrations, the score being indicative for the aggressiveness of a prostate tumor of the individual.

[0074] In an embodiment, the unit for determining the concentration of the at least three substances is configured to determine the concentration of any substance combination of the embodiments explained above.

[0075] While some of the explained uses and methods are described as in vitro uses and methods and some of the explained uses and methods are described as in vivo uses and methods, it should be noted that each in vitro use or method can also be carried out as in vivo use or method, and vice versa.

[0076] All embodiments of the use of the marker set can be combined in any desired way and can be transferred either individually or in any arbitrary combination to the further medical use of the marker set as well as to the different methods and to the decision support system. Likewise, all embodiments of the further medical use of the marker set can be combined in any desired way and can be transferred either individually or in any arbitrary combination to the use of the marker set, to the different methods, and to the decision support system. Finally, all embodiments of the different methods can be combined in any desired way and can be transferred either individually or in any arbitrary combination to the use of the marker set, to the further medical use of the marker set, to any other of the described methods, and to the decision support system.

[0077] Further details of aspects of the present invention will be explained in the following making reference to exemplary embodiments and accompanying Figures. In the Figures:

[0078] Figure 1 shows an ROC plot of the ability of a first marker set for distinguishing an aggressive prostate tumor from an indolent prostate tumor and thus for determining the aggressiveness of a prostate tumor;

[0079] Figure 2 shows an ROC plot of the ability of a second marker set for distinguishing an aggressive prostate tumor from an indolent prostate tumor and thus for determining the aggressiveness of a prostate tumor;

[0080] Figure 3 shows an ROC plot of the ability of a third marker set for distinguishing an aggressive prostate tumor from an indolent prostate tumor and thus for determining the aggressiveness of a prostate tumor;

[0081] Figure 4 shows an ROC plot of the ability of a fourth marker set for distinguishing an aggressive prostate tumor from an indolent prostate tumor and thus for determining the aggressiveness of a prostate tumor;

[0082] Figure 5 shows an ROC plot of the ability of a fifth marker set for distinguishing an aggressive prostate tumor from an indolent prostate tumor and thus for determining the aggressiveness of a prostate tumor;

[0083] Figure 6 shows an ROC plot of the ability of a sixth marker set for distinguishing an aggressive prostate tumor from an indolent prostate tumor and thus for determining the aggressiveness of a prostate tumor;

[0084] Figure 7 shows an ROC plot of the ability of a seventh marker set for distinguishing an aggressive prostate tumor from an indolent prostate tumor and thus for determining the aggressiveness of a prostate tumor; and Figure 8 shows an ROC plot of the ability of a eighth marker set for distinguishing an aggressive prostate tumor from an indolent prostate tumor and thus for determining the aggressiveness of a prostate tumor.

[0085] All ROC plots shown in Figures 1 to 8 were obtained by analyzing urine samples of patients suffering from advanced prostate cancer (having a Gleason score of higher than 6). The control group consisted of patients suffering from indolent prostate cancer having a Gleason score of lower than or equal to 6.

[0086] NMR measurements

[0087] All measurements were carried out on a Broker Avance II+ 600MHz or a Broker Avance III HD 600MHz NMR spectrometer, each using a PATXI 1 H / D-13C / 15N Z-GRD probe. All samples were kept at 5-7°C in the SampleJet and brought to the target temperature in the integrated preheating block before measurement. A standard pulse program with 30-degree excitation pulse and pre-saturation for water suppression was used (zgpr30).

[0088] Samples were measured in batches of up to 93 samples per run. In addition to the analytical samples, each run included one Axinon® urine calibrator sample and two Axinon® urine control samples (before and after the analytical urine samples, respectively) in order to assure ideal measurement conditions throughout the run.

[0089] Signal analysis

[0090] NMR spectra underwent automatic referencing, phase correction and baseline correction before further analysis.

[0091] Subsequently, the NMR spectra underwent an automatic standardization and calibration procedure to minimize between-device, between-day and between-run effects. The quality of each of these spectra was assessed by a custom spectrum qualification algorithm that analyzes general spectral properties, e.g., offset and tilt of the baseline in selected spectral regions, and properties of selected indicator signals, e.g., signal position, shape and width. Spectra that did not meet the predefined quality criteria were excluded from further analysis.

[0092] Successfully qualified spectra (typically covering a chemical shift from -5 to 14 ppm) were subjected to further modifications. In particular, broad background signals were separated with a suitable algorithm, e.g., background intensities (such as generated from proteins) were subtracted from the spectra, resulting in spectral intensities devoid of such background signals. The cohort (i.e., the plurality) of modified spectra was checked for regions in which the cohort does not show a significant number of signals. These regions - like the region of the water signal and the regions with signals arising from substances, e.g. buffer substances, added during sample preparation - were ignored in the steps explained in the following.

[0093] The remaining spectral regions were subject to an adaptive binning, which divides the spectrum in bins of differing size or extent (typically covering 0.01 to 0.05 ppm, but in extreme cases also covering 0.005 to 0.5 ppm).

[0094] Depending on the cohort of modified spectra, the size and thus the number of bins varies. Typical numbers of bins lie in a range of from 350 to 450. In the present case, 407 bins resulted from the precedingly explained analytic steps.

[0095] Quantification of specific signal peaks (in particular signals resulting from L-leucine, alanine and dimethylamine) was done by fitting Pseudo-Voigt functions, which represent a linear combination of a Gaussian and a Lorentzian function, to each peak of interest. The resulting signal fits were checked for goodness of fit in order to reject results of insufficient fit quality.

[0096] Signals resulting from other substances were not fitted. Rather, quantification models making use of the previously assigned bins were applied. After substance identification, substance labels have been assigned to these bins. The quantification was then determined by the bin value, which calculates as [(sum of intensities in bin) / (number of data points in bin)]. The standardization by data points is used to compensate for a varying number of data points in the bins. The number of data points in a bin may vary by one data point due to shifts of the applied discretization grid. A true numerical integration would use a multiplication by the bin extent. However, this is a constant factor and can be omitted.

[0097] Test of identified marker substances

[0098] The identified marker substances were tested in different combinations to assess their suitability for distinguishing an aggressive prostate tumor from an indolent prostate tumor. In doing so, the result of the determination based on the marker substances (probability of prostate tumor aggressiveness) has been checked against clinical signs of an aggressive prostate tumor in the patient who donated the urine sample, as already explained above.

[0099] The results are summarized in receiver operating characteristic (ROC) plots. In these plots, the area under the curve (AUC) indicates the fitness of the prediction. If the AUC is 0.5, the prediction is to be considered random and thus not well suited. The higher the AUC, the better is the prediction model.

[0100] All marker sets, the ROC plots of which are shown in Figures 1 to 8, were able to distinguish between the patient group and the control group in a statistically significant way. The results shown in Figures 1 to 8 are summarized in the following Table 1 .

[0101] Table 1 : Summary of results depicted in Figures 1 to 8. Summarizing, the presented marker sets comprise highly appropriate biomarkers for distinguishing an aggressive prostate tumor from an indolent prostate tumor, i.e., for determining the aggressiveness of a prostate tumor.

Claims

Claims1 . Use of a marker set comprising at least three substances chosen from the group consisting of 5-hydroxymethyl-2-furancarboxylic acid, phenylacetylglutamine, N-acetylglutamine, L- tyrosine, dimethylamine, L-leucine, mannitol, sucrose, trigonelline, alanine, and scyllo- inositol in an in-vitro method for determining the aggressiveness of a prostate tumor.

2. Use according to claim 1 , characterized in that the group of substances comprises either phenylacetylglutamine or N-acetylglutamine.

3. Use according to claim 1 , characterized in that the marker set comprises at least four substances, wherein two of the substances are phenylacetylglutamine and N- acetylglutamine.

4. Use according to any of the preceding claims, characterized in that marker set comprises alanine, mannitol, L-leucine, and at least one of phenylacetylglutamine and N- acetylglutamine.

5. Use according to any of the preceding claims, characterized in that marker set comprises L-tyrosine, L-leucine, sucrose, and alanine.

6. Use according to any of the preceding claims, characterized in that marker set comprises L-tyrosine, L-leucine, and sucrose.

7. Use according to any of the preceding claims, characterized in that marker set comprises L-tyrosine, dimethylamine, and L-leucine.

8. Use according to any of the preceding claims, characterized in that marker set comprises 5-hydroxymethyl-2-furancarboxylic acid, L-tyrosine, L-leucine, and sucrose.

9. Use according to any of the preceding claims, characterized in that marker set comprises L-tyrosine, L-leucine, mannitol, and scyllo-inositol10. Use according to any of the preceding claims, characterized in that marker set comprises L-tyrosine, L-leucine, and scyllo-inositol.11 . Use according to any of the preceding claims, characterized in that marker set comprises dimethylamine, L-leucine, sucrose, and alanine.

12. Marker set comprising at least three substances chosen from the group consisting of 5- hydroxymethyl-2-furancarboxylic acid, phenylacetylglutamine, N-acetylglutamine, L- tyrosine, dimethylamine, L-leucine, mannitol, sucrose, trigonelline, alanine, and scyllo- inositol for use in in-vivo diagnostics of the aggressiveness of a prostate tumor.

13. Method for analyzing an isolated body fluid sample in vitro, comprising the following steps: a) determining the concentration of at least three substances chosen from the group consisting of 5-hydroxymethyl-2-furancarboxylic acid, phenylacetylglutamine, N- acetylglutamine, L-tyrosine, dimethylamine, L-leucine, mannitol, sucrose, trigonelline, alanine, and scyllo-inositol in an isolated body fluid sample from an individual by analyzing the body fluid sample by analyzing the body fluid sample with a suited measuring technique, and b) calculating a score from the determined concentrations, the score being indicative for the aggressiveness of a prostate tumor.

14. Method according to claim 13, characterized in that the body fluid sample is a urine sample or a blood sample.

15. Method according to claim 13 or 14, characterized in that that the sample is grouped into one of at least two predefined groups on the basis of the calculated score.

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