Differentiation of patients with and without prostate cancer using urine 1h nmr metabolomics

Abstract

The invention relates to a method of diagnosing a subject with prostate cancer, the method comprising identifying hippurate, hippuric acid, or both in a urine sample from the subject, wherein the quantity of hippurate, hippuric acid, or both is utilized in providing patients with a diagnosis and prognosis for prostate cancer.

Description

[0001] DIFFERENTIATION OF PATIENTS WITH AND WITHOUT PROSTATE CANCER USING URINE1H NMR METABOLOMICS

[0002] CROSS-REFERENCE TO RELATED APPLICATIONS

[0003] This application claims benefit of U.S. Provisional Application No. 63 / 517,624, filed on August 4, 2023, the contents of which are incorporated herein by reference in their entirety.

[0004] STATEMENT REGARDING FEDERALLY SPONSORED RESEARCH

[0005] This invention was made with government support under 5R01 CA115746-10 awarded by the NIH- NCI National Cancer Institute, 5R21 CA243255-02 awarded by the NIH-National Institutes of Health, and 1 R01 CA273010-01 awarded by the NIH-National Institutes of Health. The government has certain rights in the invention.

[0006] BACKGROUND OF THE INVENTION

[0007] This invention relates to diagnosing and treating cancer.

[0008] Prostate cancer (PCa) ranks among the highest incidence and mortality in male malignancies (Siegel et al. Cancer J Clin. 2023;73(1 ):17-48). Serum prostate specific antigen (PSA) and digital rectal examinations (DRE) are the two main screening tools for PCa detection and surveillance. In cases of suspicious results, an ultrasound or magnetic resonance imaging guided biopsy will be pursued. Issues surrounding sensitivity and specificity of DRE and PSA, which has been shown to be a prostate-specific but not PCa-specific, lead to unnecessary biopsies, undertreatment of aggressive PCa, and overtreatment of non-aggressive PCa (Martin et. Al., JAMA. 2018;319(9):883-895; Pinsky et al., Cancer. 2017;123(4):592-599; and Schroder et al., European Urology. 2012;62(5):745-752). Prostate biopsies themselves are not immune from considerable side effects, including pain, fever, hematospermia, urinary and fecal incontinence, and erectile dysfunction; psychological harms; and high public health costs (Fenton et al., JAMA. 2018;319(18):1914-1931 ). Thus, additional less- or non-invasive biomarkers are urgently needed to measure and identify clinically relevant high-risk PCa subjects, while simultaneously preventing overtreatment.

[0009] SUMMARY OF THE INVENTION

[0010] The present invention, in general, relates to assessing urine samples for the detection, evaluation, and treatment of prostate cancer in a subject.

[0011] In one aspect, the invention provides a method of diagnosing a subject with prostate cancer, the method comprising identifying hippurate, hippuric acid, or both hippurate and hippuric acid in a urine sample from the subject, wherein an elevated level of hippurate, hippuric acid, or both is taken as an indication that the subject has prostate cancer. In some embodiments, the elevated level of hippurate is an indication that the subject has prostate cancer. In some embodiments, the elevated level of hippuric acid is an indication that the subject has prostate cancer. In some embodiments, the elevated level of hippurate and hippuric acid is an indication that the subject has prostate cancer.

[0012] In some embodiments, the method of diagnosing the subject includes identifying hippurate, hippuric acid, or both hippurate and hippuric acid in a urine sample from the subject as well as identifying the levels of one or more of the following in the urine sample: acetate, alanine, acetamine, N-(4- aminobutyljacetamide, 4-acetamidobutyric acid, adenosine, choline, creatine, o-cresol, cytidine, betaine, phenylacetic acid, phenylacetylglutamine, formate, fumaric acid, folic acid, furoylglycine, glutamine, glutamate, glycine, dimethylglycine, methylguanidine, guanidinoacetate, taurine, citric acid, citrate, histidine, 2-hydroxyisobutyrate, p-cresol sulfate, pyruvate, lactate, N-acetyl-L-alanine, N- acetylphenylalanine, 5-hydroxyindole-3-acetic acid, 5-phenylpentanoic acid, malonic acid, methylamine, trimethylamine, leucine, norleucine, N-methylnicotinamide, succinate, uridine, urocanate, tryptophan, tyrosine, phenylalanine, pyridoxine, pyridoxal-5-phosphate, threonine, or trimethylamine (TMA). In some embodiments, the level of at least one of histidine, p-cresol sulfate, or TMA is elevated. In some embodiments, the level of at least one of phenylalanine, tyrosine, tryptophan, norleucine, threonine, lactate, or N-acetyl-L-alanine is reduced.

[0013] In some embodiments, the metabolomic profile of the urine sample is determined by NMR. In some embodiments, the urine sample is analyzed by1H NMR. In some embodiments, the diagnostic analysis includes determining the ratio of the metabolites in the1H NMR spectra.

[0014] In yet other embodiments, the analysis comprises determining the ratio between hippurate and at least one other metabolite. In some embodiments, the other metabolite is selected from creatine, lactate, histidine, phenylalanine, tyrosine, tryptophan, norleucine, threonine, lactate, or N-acetyl-L-alanine. In some embodiments, the1H NMR analysis utilizes a T2 filter. In some embodiments,1H NMR analysis utilizes the Carr-Purcell-Meiboom-Gill (CPMG) sequence.

[0015] In some embodiments, the subject was previously identified as prostate-specific antigen (PSA)- elevated. In some embodiments, the urine sample comprises elevated hippurate and decreased lactate. In some embodiments, a urine sample comprising elevated hippurate and decreased lactate is indicative of prostate cancer. In some embodiments, the urine sample comprises elevated hippurate and histidine. In some embodiments, the urine sample comprises elevated hippurate and histidine is indicative of prostate cancer.

[0016] In some embodiments, the urine sample comprises elevated hippurate and reduced phenylalanine, tyrosine, tryptophan, norleucine, threonine, lactate, or N-acetyl-L-alanine. In some embodiments, the urine sample comprises elevated hippurate and reduced phenylalanine, tyrosine, tryptophan, norleucine, threonine, lactate, or N-acetyl-L-alanine is indicative of prostate cancer.

[0017] In another aspect, the invention provides a method of treating prostate cancer, the method comprising first identifying a subject diagnosed with prostate cancer according to any of the previously mentioned claim, and then administering a therapeutically effective amount of a treatment for prostate cancer to the diagnosed subject or imaging the prostate of the subject.

[0018] In some embodiments, the treatment is surgery, radiation, prostate brachytherapy, cryosurgery, chemotherapy, immunotherapy, or targeted drug therapy. In some embodiments, the imaging of the subjected comprises magnetic resonance imaging (MRI), a computed computer (CT) scan, a positron emission tomography (PET) scan, an ultrasound, an ultrasound-guided biopsy, nuclear scintigraphy, a radionuclide scan, or multimodal imaging.

[0019] In another aspect, the invention provides a method for diagnosing or prognosing prostate cancer in a subject or determining a subject's risk of developing prostate cancer comprising monitoring one or more metabolites in said subject's urine according to any of the previously described methods at a first time, and during at least one second time monitoring said one or more metabolites in said subject's urine according to any of the previously described methods.

[0020] In some embodiments, the method further comprises administering an effective amount of treatment to the subject in need thereof based on the prognosis. In some embodiments, a prognosis that the subject may have prostate cancer includes further treatment by clinical evaluation.

[0021] In some embodiments, the method further comprises imaging the prostate of the subject. In some embodiments, the imaging of the subjected comprises magnetic resonance imaging (MRI), a computed computer (CT) scan, a positron emission tomography (PET) scan, an ultrasound, an ultrasound-guided biopsy, nuclear scintigraphy, a radionuclide scan, or multimodal imaging.

[0022] In some embodiments, the method further comprises administering an effective amount of treatment to the subject diagnosed with prostate cancer. In yet other embodiments, the treatment is surgery, radiation, chemotherapy, immunotherapy, or targeted drug therapy.

[0023] Other features and advantages of the invention will be apparent from the following detailed description and figures, and from the claims.

[0024] Definitions

[0025] Unless otherwise defined, all technical and scientific terms used herein have the same meaning as commonly understood by one of ordinary skill in the art to which this invention belongs. Methods and materials are described herein for use in the present invention; other, suitable methods and materials known in the art can also be used. The materials, methods, and examples are illustrative only and not intended to be limiting. All publications, patent applications, patents, sequences, database entries, and other references mentioned herein are incorporated by reference in their entirety. In case of conflict, the present specification, including definitions, will control.

[0026] As used herein, the terms “diagnosis” or “diagnosing’ mean a determination (by one or more individuals) that the cause or nature of a problem, situation, or condition in a subject is prostate cancer, or a confirmation of the diagnosis of the disease that includes alternative prostate cancer diagnostics, other signs and / or symptoms (e.g., based in whole or in part on the level(s) of the one or more prostate cancerindicating metabolites described herein). A diagnosis may include a “prognosis,” that is, a future prediction of the progression of prostate cancer, based on the observed disease state (e.g., based in whole or in part on the different level(s) of the one or more prostate cancer-indicating metabolites described herein). A diagnosis or prognosis may be based on one or more biological samples obtained from a subject and may involve a prediction of disease response to a particular treatment or combination of treatments for prostate cancer.

[0027] As used herein, the term “prostate cancer” means a malignant neoplasm of the prostate characterized by the abnormal proliferation of cells, the growth of which cells exceeds and is uncoordinated with that of the normal tissues around it. Of note, most men without prostate cancer have prostate-specific antigen (PSA) levels under 4 ng / mL of blood. When prostate cancer develops, the PSA level often is elevated above 4. Still, a level below 4 is not a guarantee that a man does not have cancer. Indeed, about 15% of men with a PSA below 4 will typically have prostate cancer if a biopsy is done.

[0028] As used herein, the term “subject” or “patient” as used herein refers to a mammal, preferably a human male, for whom a classification as prostate cancer-positive or prostate cancer-negative is desired, and for whom further treatment can be provided.

[0029] As used herein, a “reference patient” or “reference group” refers to a group of patients or subjects to which a test sample from a patient suspected of having or being susceptible to prostate cancer may be compared. In some embodiments, such a comparison may be used to determine whether the test subject has prostate cancer. A reference patient or group may serve as a control for testing or diagnostic purposes. As described herein, a reference patient or group may be a sample obtained from a single patient, or may represent a group of samples, such as a pooled group of samples.

[0030] As used herein, “healthy” refers to an individual having a healthy prostate, or normal, noncompromised prostatic function. A healthy patient or subject has no symptoms of prostate cancer or other prostatic disease. In some embodiments, a healthy patient or subject may be used as a reference patient for comparison to diseased or suspected diseased samples for determination of prostate cancer in a patient or a group of patients.

[0031] As used herein, “treating,” “treatment,” and the like means the administration of therapy to an individual who already manifests at least one symptom of a disease or condition or who has previously manifested at least one symptom of a disease or condition. For example, “treating” can include alleviating, abating, or ameliorating a disease or condition symptoms, preventing additional symptoms, ameliorating the underlying metabolic causes of symptoms, inhibiting the disease or condition, e.g., arresting the development of the disease or condition, relieving the disease or condition, causing regression of the disease or condition, relieving a condition caused by the disease or condition, or stopping the symptoms of the disease or condition. For example, the term “treating” in reference to a disorder means a reduction in severity of one or more symptoms associated with that particular disorder. Therefore, treating a disorder does not necessarily mean a reduction in severity of all symptoms associated with a disorder and does not necessarily mean a complete reduction in the severity of one or more symptoms associated with a disorder. As related to the present disclosure, the term may also mean the administration of pharmacological substances or formulations, or the performance of non- pharmacological methods including, but not limited to, radiation therapy (e.g., external beam radiation) and surgery. Pharmacological substances as used herein may include, but are not limited to, substances used in immunotherapy or targeted drug therapy. Treatment may include a multiplicity of pharmacological substances, or a multiplicity of treatment methods, including, but not limited to, surgery and chemotherapy. As related to the present disclosure, the term may also include the imaging of a subject, the imaging methods may include, but are not limited to, magnetic resonance imaging (MRI), a computed tomography (CT) scan, positron emission tomography (PET), ultrasound, ultrasound-guided biopsies, nuclear scintigraphy, radionuclide, or multimodal imaging.

[0032] As used herein, “amount” or “level” refers to a typically quantifiable measurement for a biomarker, e.g., a metabolite, described herein, wherein the measurement enables comparison of the marker between samples and / or to control samples. In some embodiments, an amount or level is quantifiable and refers to the levels of a particular marker in a biological sample (e.g., urine), as determined by laboratory methods or tests such as an immunoassay, (e.g., antibodies), nuclear magnetic resonance (such as described herein), mass spectrometry, or liquid chromatography. In some embodiments, a marker may be present in the sample in an increased amount, or in a decreased amount. Marker comparisons may be based on direct measurement of the levels of a biomarker described herein.

[0033] As used herein, the term “elevated” refers to a metabolite level in a given subject that is greater relative to the same metabolite level in a given set of healthy patients or subjects.

[0034] As used herein, the term “reduced” refers to a metabolite level in a given subject that is lower relative to the same metabolite level in a given set of healthy patients or subjects.

[0035] Accordingly, a “reduced level” or an “elevated level” of a metabolite refer to the amount of expression or concentration of a metabolite in a biological sample from a patient compared to statistically validated thresholds, e.g., the amount of the metabolite in biological sample(s) from individual(s) that do not have prostate cancer or have prostate cancer (or a particular severity or stage of prostate cancer). For example, a metabolite has a “reduced level” in the urine from a subject when the metabolite is present at a lower concentration in the subject’s urine sample than in urine from a subject who does not have prostate cancer; and a metabolite has an “elevated level” in the urine from a subject when the metabolite is present at a higher concentration in the subject’s urine sample than in urine from a subject who does not have prostate cancer. For certain metabolites, elevated levels in a biological sample indicate the presence of or a risk for prostate cancer; at the same time, other metabolites may be present in reduced levels in patients or subjects with prostate cancer. In either of these example situations, metabolites are at a “different level” in prostate cancer subjects versus healthy controls. In the present invention, a “level” of a metabolite may be determined by the relative intensity of the metabolite in an NMR spectrum (e.g.,1H NMR spectra).

[0036] As used herein, the term “Wilcoxon rank sum test,” also known as the Mann-Whitney U test, Mann-Whitney-Wilcoxon test, or Wilcoxon-Mann-Whitney test, refers to a specific statistical method used for comparison of two populations. For example, the test can be used herein to link an observable trait, in particular a metabolite level, to the absence or presence of prostate cancer in subjects of a certain population, e.g., males having an elevated PSA test as described herein.

[0037] As used herein, the term “intensity”, when used in reference to NMR signals, is displayed along the vertical axis of a spectrum, and is proportional to the molar concentration of the sample. Thus, a small or dilute sample will give a reduced signal, and doubling or tripling the sample concentration elevates the signal strength proportionally. A relative intensity can be determined by, e.g., the signal strength as compared to the vertical axis, the signal strength as compared to the signal strength of another component in the sample, the signal area as determined by a signal integrator, or the signal area compared to the signal area of another component in the sample.

[0038] As used herein, the term “ROC” refers to receiver operating characteristic, which is a graphical plot used herein to gauge the performance of a certain diagnostic method at various cutoff points. A ROC plot can be constructed from the fraction of true positives and false positives at various cutoff points.

[0039] As used herein, the term “AUC” refers to the area under the curve of the ROC plot. AUC can be used to estimate the predictive power of a certain diagnostic test. Generally, a larger AUC corresponds to increasing predictive power, with decreasing frequency of prediction errors. Possible values of AUC range from 0.5 to 1 .0, with the latter value being characteristic of an error- free prediction method.

[0040] As used herein, the term “p-value” or “p” refers to the probability that the distributions of biomarker (e.g., metabolite) scores for positive-prostate cancer and non-positive-prostate cancer subjects are identical in the context of a Wilcoxon rank sum test. Generally, a p-value close to zero indicates that a particular statistical method will have high predictive power in classifying a subject.

[0041] As used herein, a “sample” refers to a test substance to be tested for the presence of, and levels or concentrations thereof, of a biomarker (e.g., metabolite) as described herein. A sample may be any substance appropriate in accordance with the present disclosure, including, but not limited to, urine, or any part thereof.

[0042] As used herein, a “metabolite” refers to small molecules that are intermediates and / or products of cellular metabolism. Metabolites may perform a variety of functions in a cell, for example, structural, signaling, stimulatory and / or inhibitory effects on enzymes.

[0043] The phrase "therapeutically effective" is intended to qualify the amount of active ingredients used in the treatment of a disease or disorder or on the effecting of a clinical endpoint.

[0044] The term “patient” is generally synonymous with the term “subject” and includes all mammals including humans. Preferably, the patient or subject is a male human. BRIEF DESCRIPTION OF THE DRAWINGS

[0045] The patent or application file contains at least one drawing executed in color. Copies of this patent or patent application with color drawings will be provided by the Office upon request and payment of the necessary fee.

[0046] Fig. 1 shows a urine1H NMR spectra from PCa and controls. Spectral regions identified from urine spectra (A) one-pulse, without T2 filters, and (C) Carr-Purcell-Meiboom-Gill (CPMG) sequences with T2 filters. Contributions of spectral regions towards calculated (B) PC2 for spectra without T2 filters, and (D) PC3, with T2 filters, are displayed as loading factors.

[0047] Fig. 2 shows a spectral region differentiation of PCa from control groups. Spectral data were measured from (A) one-pulse and (B) CPMG sequences. Dashed purple lines indicate level of significance p=0.05, and purple circles denote regions that were significantly different between the two groups according to paired-Wilcoxon signed-rank analysis. Blue dots represent regions that contribute more significantly to the control group according to the loading factors obtained from principal component analysis (PCA) calculations. Red dots contribute more significantly to the PCa group. Red arrows and labels indicate spectral regions with increased intensities in PCa, seen in spectra with and without T2 filters, of both individual spectral regions analyses and contributions to PCA. Blue arrows and labels indicate decreased intensities in PCa, and purple arrows and labels indicate opposite changes seen in spectra with and without T2 filters.

[0048] Fig. 3 shows principal component differentiations of PCa from benign biopsy groups. Principal components, PC2 and PC3, calculated from spectral data measured from (A) one-pulse, and (B) CPMG sequences, respectively, show statistically significant differences between the two groups. Group and pairwise differences were evaluated according to group Wilcoxon rank sum tests and PCa-control paired Wilcoxon signed-rank tests. Blue lines between groups link PCa patients with their matched controls.

[0049] Fig. 4 shows summaries of spectral regions and principal components in their potential for differentiating PCa from benign biopsy groups. A). PC2 loading factors, and B). PC2 loading factors modified by the factor of mean / standard deviation (MO / SD) following the formulas for PCA calculations. Both panels A and B were obtained from the same spectral region, calculated from 50 spectral regions measured with one-pulse T2 unfiltered spectra. Red bars represent spectral region PC2 contributing coefficient values that are above the 75th percentile (representing tendencies towards PCa), and blue bars show values below the 25th percentile (representing tendencies towards control). Both red and blue bars are major contributors to PC2 values. Grey bars represent values between the 25th and 75th percentiles, which have less contribution to the final PC2 values. The purple (*) shown between panels A and B label spectral regions that are statistically significant (p<0.05) in differentiating PCa from controls using both Wilcoxon and paired-Wilcoxon analyses. Panels C) and D) present PC3 loading factors and PC3 loading factors modified by (MO / SD), respectively, calculated from 50 spectral regions measured with CPMG T2 filter. Spectral regions highlighted with purple rectangles denote regions that show significances in both Wilcoxon and paired-Wilcoxon analyses, and have major contributions to both PC2 and PC3. Green rectangles indicate regions that are major contributors to both PC2 and PC3.

[0050] Fig. 5 shows plots of the metabolomic profile data collected from the urine samples of subjects identified as having elevated PSA levels and underwent tumor biopsy. In Fig. 5(a), the study population included 17 cancer subjects and 17 benign subjects. In Fig. 5(b), the study population included 68 cancer subjects (two outliers removed) and 26 benign subjects (three outlier removed). Thresholds for accessing the level of hippurate in each population were established using group means and standard deviation. The figure shows plotted dots to indicate the level of hippurate detected by1H NMR as well as a box and whisker plot and violin plot (shading) of the data collected for each subject population. The dashed purple line indicates the level of significance p = 0.05. The table on the plot presents the sensitivity (Sen), specificity (Spc), positive predictive value (PPV), and negative predictive value (NPV) calculated from the presented data and used to assess the urine sample analysis method as a diagnositic predictor of PCa.

[0051] Fig. 6 shows plots of a canonical-correlation analysis. The canonical scores calculated and presented in the figures are from PC2 and PC5 present in the urine samples of subjects identified as having elevated PSA levels. Fig. 6(a) shows the canonical score analysis of the “training cohort”, which consits of subjects that underwent tumor biopsy. Fig. 6(b) shows the canonical score analysis of the “validation cohort”. Fig. 6(c) shows the canonical score analysis of the “testing cohort”. Each plot shows data from subjects identified as benign along side data from subjects identified as having cancer. The plotted data is from the metabolomics profiling of each subject population relative to the correlation between PC2 and PC5. The plots present the data with box and whisker plots, violin plots (shading), and dots which correspond to the frequency distribution. The dashed purple line indicates the level of significance p = 0.05. The tables on the plots present the sensitivity (Sen), specificity (Spc), positive predictive value (PPV), and negative predictive value (NPV) calculated from the presented data and used to assess the urine sample analysis method as a diagnositic predictor of PCa.

[0052] DETAILED DESCRIPTION OF THE INVENTION

[0053] Prostate cancer (PCa) is one of the most prevalent cancers in men worldwide. For its detection, serum prostate specific antigen (PSA) screening is commonly used, despite its lack of specificity, high false positive rate, and inability to discriminate indolent from aggressive PCa. Following increases in serum PSA levels, clinicians often conduct prostate biopsies with or without advanced imaging. Nuclear magnetic resonance (NMR)-based metabolomics has proven to be promising for advancing early- detection and elucidation of disease progression, through the discovery and characterization of novel biomarkers.

[0054] Our retrospective study of urine-NMR samples described below, from prostate biopsy patients with and without PCa, identified several metabolites involved in energy metabolism, amino acid metabolism, and the hippuric acid pathway. Of note, lactate and hippurate - key metabolites involved in cellular proliferation and microbiome effects, respectively - were significantly altered, unveiling widespread metabolomic modifications associated with PCa development.

[0055] In short, human urine samples were collected at the time of prostate biopsies from patients suspicious of harboring prostate cancer. We followed these patients for 5~15 years and selected 17 age- and PSA-value-matched PCa-positive samples with 17 PCa-negative samples for retrospective NMR analyses. We discovered that by using a ratio of metabolites: hippurate / lactate, we can significantly differentiate cases with prostate cancer from those without with p=0.0077, and ROC AUC=0.77. This test is useful for assisting a prostate cancer clinic to confirm true and reduce false negatives.

[0056] EXAMPLES

[0057] Below we describe a retrospective study of urine-NMR samples, from prostate biopsy patients with and without prostate cancer (PCa), which has identified several metabolites involved in energy metabolism, amino acid metabolism, and the hippuric acid pathway. Of note, lactate and hippurate - key metabolites involved in cellular proliferation and microbiome effects, respectively - were significantly altered, unveiling widespread metabolomic modifications associated with PCa development. These findings support urine metabolomics profiling as a promising strategy to identify new clinical biomarkers for PCa detection and diagnosis.

[0058] Results

[0059] Urine1H NMR spectra with and without T2 filter and principal component analysis.

[0060] Spectra of means (M) with standard deviations (SD) for PCa and control (non-PCa) groups, with and without T2 filters, are presented in Fig. 1 A and C. T2 filters reduce broad unwanted resonances produced by macro-molecules, and its effect is evident when comparing the small peaks between 4.0-3.5 ppm in Fig 1 A with the same region in Fig 1 C. For both T2 filtered and unfiltered spectra, 50 spectral regions-of-interest were identified where greater than 80% of the samples had non-zero values. Principal component analysis (PCA), an unsupervised dimension reduction method, was used to calculate the principal components (PC) for each series. The loading factors of PC2 for T2 filtered spectra, and PC3 for unfiltered spectra, are illustrated in Fig. 1 B and D for each region. The significances of these two PCs are discussed below.

[0061] Spectral regions of urine 1H NMR spectra with and without T2 filter differ between cancer and controls.

[0062] Among the 50 identified spectral regions, 11 regions between the T2 filtered and unfiltered series presented p values less than 0.05 between PCa and control groups according to Wilcoxon analysis. Among these 11 regions, seven of them simultaneously showed p values less than 0.05 between matched pairs, as shown in Fig. 2.

[0063] Principal components of spectral regions differentiate PCa and controls.

[0064] PCs obtained from PCA can be evaluated directly for their ability in differentiating PCa from control groups, if intrinsic metabolomic differences exist between these groups. Fig. 3 presents group and pairwise comparisons of PC2 and PC3 obtained from T2 unfiltered and filtered spectra, respectively. Based on groupwise Wilcoxon analysis, pairwise Wilcoxon signed-rank tests, PC2 for T2 unfiltered spectra, and PC3 for filtered spectra (with the PC’s loading factors from each spectral region contributing to the final PC values illustrated in Fig 1 B and D), we present significant differentiations between the two tested groups.

[0065] Further evaluation of PC structures can reveal their major contributing spectral regions and the potential presentations of metabolites in these spectral regions. A summary of spectral regions and calculated principal components are presented in Fig. 4. From data observed in Fig. 4, spectral regions with potentially significant differentiating capabilities can be identified, labeled by rectangular boxes in Fig. 4 and detailed in Table 1 , together with their potential urine metabolites.

[0066] Table 1. Significant spectral regions and their potential major contributing metabolites in PCa.

[0067] Note: As described in the legend of Fig. 4, spectral regions highlighted with purple rectangles denote regions that show significances in both Wilcoxon and paired-Wilcoxon analyses and have major contributions to both PC2 and PC3, while green rectangles indicate regions that are major contributors to both PC2 and PC3. The arrows under “PCa vs. Control” indicates potential metabolites contributing direction towards PCa measured with one-pulse and CPMG sequences, respectively. Boldfaced names indicate most likely metabolites, which were determined with search results from “Biological Magnetic Resonance Data Bank (BMRM)” and “Human Metabolome Database (HMDB)”. Of a special note, metabolites listed in this table only present them as possible candidates solely based on the fact that these metabolites have resonances that are in the stated ppm regions. Five spectral regions (denoted with a purple asterisk in Fig. 4) were statistically significant in differentiating PCa and control, obtained from both Wilcoxon and paired-Wilcoxon analyses. Spectral regions highlighted in green (i.e., 7.85-7.82, 7.66-7.64, 7.56-7.53, 7.21 -7.19, and 2.89-2.87 ppm) are major contributors to both PC2 and PC3, while spectral regions highlighted in purple (i.e., 7.37-7.36, 2.46- 2.44, 1 .99-1 .98, and 1 .34-1 .32 ppm) are also not only major contributors to PC2 and PC3, but also significant according to Wilcoxon and paired-Wilcoxon analyses. Among these significant spectral regions, increases in hippurate (7.85-7.82, 7.66-7.64, 7.56-7.53 ppm), and decreases in lactate (1 .34- 1 .32 ppm) were observed, and agreed with Capillary Electrophoresis-Mass Spectrometry (CE-MS) measured conducted on the same urine samples (detailed results not included). Of a further note, considering potential clinical utility of hippurate as a new PCa biomarker, for clinical evaluations, we examine the hippurate-to-creatinine ratio measured from both T2 filtered and unfiltered spectra, and observed significant results in differentiating patients with and without PCa (T2 unfiltered, PCa: 5.65±3.09, Control: 2.39±1 .1 1 , Wilcoxon p = 0.0269; T2 filtered, PCa: 0.44±0.07, Control: 0.34±0.09, Wilcoxon p = 0.0476).

[0068] Hippurate or Hippuric Acid Biomarker.

[0069] Hippurate and hippuric acid were found to be probative of PCa. In the study, hippurate levels in the urine samples of subjects with and without PCa that had elevated PSA levels and underwent prostate biopsy were analyzed (see Fig. 5). Such an analysis allowed for the determination of the reliability of a hippurate biomarker test for PCa in subjects with suspicious PSA levels. Hippurate levels taken from1H NMR analysis using a T2-filtered pulse sequence were compared using group mean and standard deviation of each subject population as the thresholds. A positive predictive value (PPV) analysis revealed a PPV = 0.9286, indicating that the urine analysis for hippurate by1H NMR can serve as a highly reliable test for prostate cancer (see Fig. 5(b)).

[0070] The present analysis can serve as a diagnostic tool for PCa as elevated hippurate is correlated with PCa. In a diagnostic setting, the urine sample from the subject would be analyzed by1H NMR for hippurate and other key metabolites, including by not limited to acetate, alanine, acetamine, adenosine, choline, creatine, betaine, phenylacetylglutamine, formate, fumaric acid, glutamine, glutamate, glycine, dimethylglycine, methylguanidine, guanidinoacetate, taurine, citric acid, citrate, histidine, 2- hydroxyisobutyrate, p-cresol sulfate, pyruvate, lactate, N-acetyl-L-alanine, malonic acid, methylamine, trimethylamine, leucine, norleucine, N-methylnicotinamide, succinate, uridine, tryptophan, tyrosine, phenylalanine, threonine, or trimethylamine (TMA). Based on the relative intensity of the principal components from each key metabolite in the spectra, a diagnosis or prognosis for PCa can be given to the subject. For example, PCa was found to be associated with a hippurate or hippuric acid level greater than 0.1 % relative spectral intensity. After determining the diagnosis or prognosis of the subject, a recommendation can be made for treatment, e.g., imaging or administration of radiation, surgery, or a pharmaceutical composition. Canonical Scores Calculated from PC2 and PC5 Present Significant Cancer Positive Predictive Value (PPV).

[0071] The canonical correlation between the principal components identified in the urine metabolomics analysis were evaluated in view of their correlation with a PCa diagnosis. The principal component analysis involved transforming the intensity values from a normalized1H NMR using the principal component scores to calculate the fractional contribution of each component to the intensity (see Fig. 6(a), 6(b), 6(c)). The study utilized subject populations for the training and validation cohort that were identified as having elevated PSA and also underwent prostate biopsy to histologically confirmed PCa. Samples in all three cohorts are independent samples. Training cohort included 16 benign and 34 cancer, validation cohort included 17 benign and 17 cancer, and testing cohort included 10 benign and 34 cancer samples. The analysis revealed that principal components PC2 and PC5 are reliable biomarkers for PCa, as the method evaluation revealed a PPV = 0.888 in the testing cohort.

[0072] Discussion

[0073] In this study, we retrospectively measured the potential of urine1H NMR spectroscopy generated PCa metabolomics in differentiating patients of PCa from controls all after their prostate biopsies due to elevated PSA levels. Observations of broad resonances seen in Figure 1 A obtained from one-pulse sequence led us to conduct our tests both using this one-pulse and CPMG sequences, with the latter capable of removing these broad resonances. Urine samples obtained from patients with and without PCa were measured with both sequences, then compared according to their respective pulse sequences.

[0074] Our significant results obtained from matched patients with and without PCa after more than six- year follow-up show that the screening of non-invasive urine biomarkers can contribute to the detection and risk stratification of PCa and can be considered as a promising tool for improving the diagnosis of PCa, as well as preventing overtreatment of indolent prostate conditions.1H NMR spectroscopy is inherently robust, exhibits high reproducibility and selectivity, and requires minimum sample preparation (Ge et al., Clinica chimica acta. 2020;510:291 -297). As a biological liquid specimen, urine is regarded as a valid option for metabolomics analysis due to its ease of availability, non-invasive collection, and high- volume availability, which allows for repeated analysis. Our study utilizes these advantages and establishes preliminary and comparative urinary metabolomic profiles for PSA elevated patients with and without PCa. We identified several metabolic characteristics that are useful.

[0075] Energy metabolism plays an important role in all cells and is a particularly important target for cancer therapies. Originally hypothesized to be a metabolic waste product, lactate is now increasingly regarded as a signaling molecule and a significant player in energy metabolism during tumor growth (Sutinen et al., European journal of nuclear medicine and molecular imaging. 2004;31 (3):317-324). Lactate-mediated signaling activates tumor cell proliferation and inhibits immune cell effects; additionally, lactate can be absorbed by cancer cells to enhance the tricarboxylic acid (TCA) cycle for additional energy (Sutinen et al., European journal of nuclear medicine and molecular imaging. 2004;31 (3):317- 324). Agreeing with other published results on lactate (Yang et al., Diagnostics. 2021 ;11 (2):149), our observed decrease in L-lactate levels in urine for patients with PCa may be associated with citrate in energy metabolism. Normal prostate cells preferentially accumulate and secrete citrate, due to a high intracellular concentration of zinc which inhibits citrate oxidation (Lima et al., Metabolites. 2021 ;11 (3):181 . doi: 110.3390 / metabo11030181 ). However, malignant prostatic tissue is unable to accumulate zinc, resulting in increased citrate oxidation and TCA cycle activity (Eidelman et al., Frontiers in Oncology. 2017;7). Increased citrate oxidation is frequently observed in malignant cells, resulting in decreased citrate levels in prostatic and seminal fluid in PCa groups (Buszewska-Forajta et al., Metabolites. 2022;12(3):268). Since citrate can be converted to lactate via the intermediates oxaloacetate and pyruvate, decreased citrate levels could lead to decreased conversion to lactate, which accounts for the observed decreased lactate. Nonetheless, our results that indicate the alteration of lactate in PCa suggest changes in cellular energy metabolism during cancer development.

[0076] Amino acid metabolism is closely related to energy metabolism. When energy availability is low, amino acids either undergo transamination to generate metabolic intermediates that can supply energy or undergo lipogenesis to be stored as fats. Cancer cells also require amino acids for protein synthesis to support rapid proliferation. As such, we observed potential decreases in many amino acid levels in urine for patients with PCa, particularly those of L-phenylalanine, L-tyrosine, L-tryptophan, L-norleucine, L- threonine, and N-acetyl-L-alanine. However, L-histidine, if present, was increased in urine for PCa patients.

[0077] Phenylalanine can be converted into tyrosine, which can produce hormones, neurotransmitters, or melanin. It can also be metabolized to fumarate and acetoacetate, which are intermediates in the TCA cycle and can be used to produce energy or synthesize fatty acids. The observed decrease in phenylalanine and tyrosine could account for the enhanced utilization of fatty acids as a source of energy and biomass in tumors (Deane et al., Nature Chemical Biology. 2019;15(2):95). Tryptophan is involved in kynurenine, serotonin, and indole synthesis, and the tryptophan-kynurenine metabolic pathway is strongly activated in response to interferons and other cytokines released upon inflammation (Sorgdrager et al., Frontiers in Immunology. 2019;10). Our observation of decreased tryptophan not only supports this hypothesis, but also suggests tryptophan’s potential role as a biomarker for diseases characterized by excessive or chronic inflammation, including malignancies (Sorgdrager et al., Frontiers in Immunology. 2019;10). Threonine is an important contributor to the TCA cycle and influenced by the androgen receptor, which has already been used as a potential therapeutic target for PCa, through the administration of antiandrogen agents (Risstalpers et al., Biochemical and biophysical research communications. 1993; 196(1 ):173-180; Wang et al., BMC Proceedings. 2012;6(3):P23). Although L- alanine has been highly linked to both energy metabolism and cancer metabolism, there has been little evidence thus far for the involvement of N-acetyl-L-alanine in PCa. Similarly, norleucine has not yet been implicated in PCa; however, both N-acetyl-L-alanine and norleucine may be potentially related to PCa progression as well.

[0078] Interestingly, we observed an increase in histidine, which contradicts our expectations and many previous findings (Bruzzone et al., Journal of Proteome Research. 2020;19(6):2419-2428). Histidine is required for protein synthesis and nucleotide formation, and its metabolism contributes to a cell’s energy sources (Brosnan et al., The Journal of Nutrition. 2020;150(Supplement_1 ):2570S-2575S). Furthermore, it can also undergo decarboxylation to produce histamine, which is important to the body’s inflammatory response. Histamine has been implicated in cell proliferation and in the differentiation between normal and malignant cells, and high histamine biosynthesis has been reported in various malignancies, including melanoma, breast, and colon cancer (Sarasola et al., Pharmacology Research & Perspectives. 2021 ;9(5):e00778). As such, increased histidine levels could correspond to increased histamine production, which may result in increased inflammation.

[0079] We also observed possible increased trimethylamine (TMA) levels in the PCa cohort.

[0080] A recent study investigated the role of gut microbiome-dependent metabolic pathways and their associated risk of lethal PCa, and found that higher levels of choline, betaine, and phenylacetylglutamine (PAGIn) double the odds of being diagnosed with incident lethal prostate cancer (Reichard et al., Cancer epidemiology, biomarkers & prevention: a publication of the American Association for Cancer Research, cosponsored by the American Society of Preventive Oncology. 2022;31 (1 ):192-199). Higher levels of hippuric acid and p-cresol sulfate were linked with an increased risk of lethal PCa {Id.).

[0081] Our study tested the potential of1H NMR urinary metabolomics to distinguish PSA elevated patients with and without PCa. We identified novel urine metabolites that may be involved in PCa development, including hippurate, N-acetyl-L-alanine, norleucine, TMA, and others. Here, the dysregulation of hippurate was comprehensively identified in the discrimination of PCa from PCa-free patients by means of urine analysis.

[0082] Our current study has a few limitations, including a small study cohort and the inherent confounding factor of peak overlaps from multiple metabolites in NMR spectroscopy. Other possible clinical confounding factors include smoking, drinking, diet, and microbiome effects. The strengths of our study include a matched cohort of prostate-biopsy patients with and without histologically confirmed PCa, and the robust, reproducible results provided by NMR analysis.

[0083] Conclusion

[0084] PSA tests have been widely used as a tool for PCa screening and diagnosis; however, it also results in a significant number of false-positive and false-negative PCa diagnoses. The need for discovering new reliable biomarkers, particularly through non-invasive methods such as urine analysis, are indicated to avoid overtreatment and enhance personalized care. The present study investigated the comparative metabolomic signatures of PCa and control patients. Observed urine metabolomic profiles may reflect cancer-associated alterations in energy and amino acid metabolism, as well as the hippuric acid pathway. Overall, our results present evidence of1H NMR measurable urine metabolomic profiles that, with further validations, may be used in future clinical practice to non-invasively diagnose PCa status in patients with suspicious PSA levels. Materials and Methods

[0085] This study is approved by the Institutional Review Board (IRB) of the Massachusetts General Hospital (MGH). Written informed consent was obtained from each participant before study inclusion.

[0086] Samples and preparations.

[0087] Between September 2007 and November 2017, 133 urine samples were collected from patients with elevated PSA levels at the time immediately prior to undergoing ultrasound-guided 12-core biopsies for suspicions of harboring PCa. These samples were analyzed between December 2015 and January 2018, and we identified 17 age- and PSA-value-matched PCa-positive samples with 17 PCa-negative samples with follow-up until December 2022. Electronic health records were obtained and examined (Table 2). The follow-up duration for PCa cases were started from patient prostatectomies, while followup duration for PCa-negative cases were calculated from the time of urine collection immediately prior to their biopsy.

[0088] Table 2. Patient demographic characteristics of the matched study populations.

[0089] Note: Benign prostate hyperplasia (BPH) is defined as prostate enlargement. Gleason scores are used to evaluate the prognosis of PCa using samples from prostate biopsy. A Gleason score of 6 (i.e. 3+3) is considered low-grade cancer, while a Gleason score of 7 (i.e. 3+4 or 4+3) is considered medium-grade, which grows more quickly and is more likely to spread than a low-grade cancer. a) representing Mean ± SD (Min, Max; Median); b) indicating 14 cases out of 17 cases studied have clinical values; c) indicating follow-up duration for PCa cases started from patient prostatectomy of definitive PCa diagnosis, while duration for controls started from time of urine collection at biopsy.

[0090] Urine samples were frozen after collection and kept frozen at -80 °C until NMR analysis. Before analysis, samples were centrifuged at room temperature (22 °C) for 10 minutes at 13.000 rpm. 950 pL of the supernatant were mixed with 50 pL deuterium oxide which contained 3% of trimethylsilylpropionic- 2,2,3,3-d4 acid for initial calibration of NMR resonance (ppm). Subsequently, samples were adjusted for pH in the range from 6.95 to 7.05, using HCI and NaOH. Then, 1000 pL of the mixture was transferred to a 5-mm NMR tube.

[0091] NMR. Spectra were acquired using a 14.1 T Bruker AVANCE HD III NMR (BrukerBioSpin, Billerica, MA) spectrometer operating at 600 MHz. Both one-pulse and Carr-Purcell-Meiboom-Gill (CPMG) sequences were used with water-suppression to measure spectra for each sample. Data obtained from CPMG sequence, to minimize macro-molecular, or probe background inference, are referred to as “T2 Filtered” spectral results, while one-pulse results are referred to as “T2 Unfiltered”. Both types of spectra were measured with 12 s repetition time, with 58 k data points and 20 ppm spectral width, and with 64 and 128 averages for unfiltered and filtered, respectively. For the CPMG sequence, every loop included one IT pulse sandwiched by 0.6 ms delays, and with a total of 1200 loops that resulted in the total filtering time of 1 ,44s.

[0092] Spectral processing.

[0093] Relative spectral intensities were processed with Bruker TopSpin 3.6.2 (Bruker BioSpin, Billerica, MA). All free induction decay signals (FIDs) underwent Fourier transformation, phase, and baseline correction. The chemical shift reference was assigned to the peak of creatinine at 3.026 ppm. After excluding water resonance regions between 4.5-5.2 ppm, spectral regions of interest (ROI, n=50), within 9.5-0.5 ppm, were defined for regions where >80% of samples had a detectable value.

[0094] Statistical data analysis.

[0095] Statistical analyses were performed with JMP (SAS Institute, Cary, USA) and included Principal Component Analysis (PCA), ordinal regression test, Wilcoxon test, and Wilcoxon paired signed rank test (with significance p less than 0.05). Listed potential metabolites were combined with search results from “Biological Magnetic Resonance Data Bank (BMRB)” and “Human Metabolome Database (HMDB)”.

[0096] OTHER EMBODIMENTS

[0097] While the invention has been described in connection with specific embodiments thereof, it will be understood that it is capable of further modifications and this application is intended to cover any variations, uses, or adaptations of the invention following, in general, the principles of the invention and including such departures from the present disclosure come within known or customary practice within the art to which the invention pertains and may be applied to the essential features hereinbefore set forth.

[0098] All publications, patents, and patent applications are herein incorporated by reference in their entirety to the same extent as if each individual publication, patent, or patent application was specifically and individually indicated to be incorporated by reference in its entirety.

[0099] Other embodiments are within the following claims.

[0100] What is claimed is:

Claims

CLAIMS1 . A method of diagnosing a subject with prostate cancer, the method comprising identifying hippurate, hippuric acid, or both in a urine sample from the subject, wherein an elevated level of hippurate, hippuric acid, or both is taken as an indication that the subject has prostate cancer.

2. The method of claim 1 , wherein an elevated level of hippurate is an indication that the subject has prostate cancer.

3. The method of claim 1 , wherein an elevated level of hippuric acid is an indication that the subject has prostate cancer.

4. The method of claim 1 , wherein elevated levels of hippurate and hippuric acid are an indication that the subject has prostate cancer.

5. The method of claim 1 , further comprising identifying the levels of one or more of the following: acetate, alanine, acetamine, N-(4-aminobutyl)acetamide, 4-acetamidobutyric acid, adenosine, choline, creatine, o-cresol, cytidine, betaine, phenylacetic acid, phenylacetylglutamine, formate, fumaric acid, folic acid, furoylglycine, glutamine, glutamate, glycine, dimethylglycine, methylguanidine, guanidinoacetate, taurine, citric acid, citrate, histidine, 2-hydroxyisobutyrate, p-cresol sulfate, pyruvate, lactate, N-acetyl-L-alanine, N-acetylphenylalanine, 5-hydroxyindole-3-acetic acid, 5-phenylpentanoic acid, malonic acid, methylamine, trimethylamine, leucine, norleucine, N-methylnicotinamide, succinate, uridine, urocanate, tryptophan, tyrosine, phenylalanine, pyridoxine, pyridoxal-5-phosphate, threonine, or trimethylamine (TMA).

6. The method of claim 5, wherein the level of at least one of histidine, p-cresol sulfate, or TMA is elevated.

7. The method of claim 5, wherein the level of at least one of phenylalanine, tyrosine, tryptophan, norleucine, threonine, lactate, or N-acetyl-L-alanine is reduced.

8. The method of claim 1 , wherein the urine sample is analyzed by1H NMR.

9. The method of claim 8, further comprising determining a ratio between hippurate and at least one other metabolite.

10. The method of claim 9, wherein the other metabolite is selected from creatine, lactate, histidine, phenylalanine, tyrosine, tryptophan, norleucine, threonine, lactate, or N-acetyl-L-alanine.11 . The method of claim 8, wherein the1H NMR analysis utilizes a T2 filter.

12. The method of claim 8, wherein the Carr-Purcell-Meiboom-Gill (CPMG) sequence is utilized.

13. The method of claim 1 , wherein the subject was previously identified as prostate-specific antigen(PSA)-elevated.

14. The method of claim 1 , wherein the urine sample comprises elevated hippurate and decreased lactate.

15. The method of claim 1 , wherein the urine sample comprises elevated hippurate and histidine.

16. The method of claim 1 , wherein the urine sample comprises elevated hippurate and reduced phenylalanine, tyrosine, tryptophan, norleucine, threonine, lactate, or N-acetyl-L-alanine.

17. A method of treating prostate cancer, the method comprising(i) identifying a subject diagnosed with prostate cancer according to any of the previously mentioned claim; and(ii) administering a therapeutically effective amount of a treatment for prostate cancer to the diagnosed subject or imaging the prostate of the subject.

18. The method of claim 17, wherein the treatment is surgery, radiation, prostate brachytherapy, cryosurgery, chemotherapy, immunotherapy, or targeted drug therapy.

19. The method of claim 17, wherein the imaging of the subjected comprises magnetic resonance imaging (MRI), a computed computer (CT) scan, a positron emission tomography (PET) scan, an ultrasound, an ultrasound-guided biopsy, nuclear scintigraphy, a radionuclide scan, or multimodal imaging.

20. A method of diagnosing or prognosing prostate cancer in a subject or determining a subject's risk of developing prostate cancer comprising:(i) monitoring one or more metabolites in said subject's urine according to any of the methods in claims 1 -16 at a first time; and(ii) during at least one second time monitoring said one or more metabolites in said subject's urine according to any of the methods in claims 1 -16.21 . The method of claim 20, further comprising administering an effective amount of treatment to the subject in need thereof based on the prognosis.

22. The method of claim 20, further comprising imaging the prostate of the subject.

23. The method of claim 20, further comprising administering an effective amount of treatment to the subject diagnosed with prostate cancer.

24. The method of claim 23, wherein the treatment is surgery, radiation, chemotherapy, immunotherapy, or targeted drug therapy.