Biliary tract cancer testing method

Abstract

The present invention provides a means and a method for determining biliary tract cancer in a non-invasive and simple manner. Specifically, the present invention relates to a method, a device, and a kit for determining biliary tract cancer in a subject by measuring a tumor marker in urine from a urine sample derived from a subject.

Description

Biliary tract cancer screening method

[0001] The present invention relates to a method, a kit, and an apparatus for diagnosing biliary tract cancer in a subject based on the measurement value of a urinary tumor marker.

[0002] Biliary tract cancer is a relatively common cancer in Japan, and because the 5-year survival rate, which is an indicator of prognosis, is low, early detection and treatment are desirable. Blood tumor markers such as CEA and CA19-9 are known to be useful for early detection of biliary tract cancer, but they have low tumor specificity and are not very accurate. Furthermore, blood tests are invasive, and are therefore essentially limited to testing performed at medical institutions.

[0003] Tumor markers for cancers such as biliary tract cancer have been reported in, for example, Patent Documents 1 to 5. Patent Document 1 mainly describes genes and proteomics as tumor markers. Patent Documents 2 to 5 describe metabolites as tumor markers for cancers such as colon cancer, but do not describe the urinary tumor markers disclosed in this specification.

[0004] US Patent Application Publication No. 2012 / 053073A1 US Patent Application Publication No. 2015 / 044716A1 US Patent Application Publication No. 2004 / 121375A1 US Patent Application Publication No. 2019 / 094205A1 US Patent Application Publication No. 2018 / 299448A1

[0005] An object of the present invention is to provide a means and method for non-invasively and simply diagnosing biliary tract cancer, which has long been desired.

[0006] In the process of searching for tumor markers in cancer urine, the inventors identified a group of markers associated with biliary tract cancer and discovered that by using these markers alone or in combination, it is possible to easily and non-invasively diagnose biliary tract cancer, predict the risk, and monitor biliary tract cancer.

[0007] That is, the present invention relates to a method, device, and kit for diagnosing and / or monitoring biliary tract cancer in a subject by measuring urinary metabolites that are urinary tumor markers. Specific embodiments include the following:

[0008] [1] A method for diagnosing biliary tract cancer in a subject, comprising the step of measuring urinary tumor markers in a urine sample from the subject, the urinary tumor markers being selected from the group consisting of cholate, chenodeoxycholic acid sulfate, a compound (C10H12O6S) measured to have a mass-to-charge ratio of 259.028 in LC / MS negative ion detection mode, glycochenodeoxycholic acid 3-sulfate, isoleucylhydroxyproline, pro-hydroxy-pro, kynurenine, 4-methoxyphenol sulfate, 5-hydroxylysine, trans-4-hydroxyproline, glycylleucine, glycocholate, a compound (C7H10N4O3) measured to have a mass-to-charge ratio of 197.068 in LC / MS negative ion detection mode, a compound (C28H38N4O5) measured to have a mass-to-charge ratio of 509.277 in LC / MS negative ion detection mode, 3-hydroxykynurenine, glycochenodeoxycholate, isoleucylglycine, phenylalanylhydroxyproline, and 4-hydroxyphenylpyruvic acid. the step of comprising at least one urinary tumor marker selected from salt, lactate, cyclo(pro-hydroxypro), tryptophan, N6-acetyllysine, gamma-glutamylphenylalanine, leucylhydroxyproline, a compound measured to have a mass-to-charge ratio of 328.152 in LC / MS negative ion detection mode (C14H23N3O6), a compound measured to have a mass-to-charge ratio of 146.081 in LC / MS positive ion detection mode (C6H11NO3), androsterone glucuronide, 3-hydroxyanthranilate, 11beta-hydroxyandrosterone glucuronide, cystathionine, carnosine, proline, anserine, arabitol / xylitol, 3-hydroxy-2-ethylpropionate, 2R,3R-dihydroxybutyrate, gamma-glutamyltyrosine, 1-methyladenine, dihydroorotic acid, alanine, and 17alpha-hydroxypregnenolone glucuronide; and diagnosing biliary tract cancer in the subject based on the measurement results.

[0009] [2] A device for diagnosing biliary tract cancer, comprising: a measurement unit for measuring urinary tumor markers in a urine sample, the urinary tumor markers being selected from the group consisting of cholate, chenodeoxycholic acid sulfate, a compound (C10H12O6S) measured at a mass-to-charge ratio of 259.028 in LC / MS negative ion detection mode, glycochenodeoxycholic acid 3-sulfate, isoleucylhydroxyproline, pro-hydroxy-pro, kynurenine, 4-methoxyphenol sulfate, 5-hydroxylysine, trans-4-hydroxyproline, glycylleucine, glycocholate, a compound (C7H10N4O3) measured at a mass-to-charge ratio of 197.068 in LC / MS negative ion detection mode, a compound (C28H38N4O5) measured at a mass-to-charge ratio of 509.277 in LC / MS negative ion detection mode, 3-hydroxykynurenine, glycochenodeoxycholate, isoleucylglycine, phenylalanylhydroxyproline, 4-hydroxyphenylpyruvate, a measuring unit including at least one urinary tumor marker selected from lactate, cyclo(pro-hydroxypro), tryptophan, N6-acetyl lysine, gamma-glutamyl phenylalanine, leucyl hydroxyproline, a compound (C14H23N3O6) measured at a mass-to-charge ratio of 328.152 in LC / MS negative ion detection mode, a compound (C6H11NO3) measured at a mass-to-charge ratio of 146.081 in LC / MS positive ion detection mode, androsterone glucuronide, 3-hydroxyanthranilate, 11beta-hydroxyandrosterone glucuronide, cystathionine, carnosine, proline, anserine, arabitol / xylitol, 3-hydroxy-2-ethylpropionate, 2R,3R-dihydroxybutyrate, gamma-glutamyl tyrosine, 1-methyladenine, dihydroorotic acid, alanine, and 17alpha-hydroxypregnenolone glucuronide; The apparatus comprises: a comparison unit that compares the measurement value of the urinary tumor marker measured by the measurement unit with a reference value or a previous measurement value; and a determination unit that determines biliary tract cancer based on the comparison result obtained by the comparison unit.

[0010] [3] A kit for determining biliary tract cancer, comprising: cholate, chenodeoxycholic acid sulfate, a compound (C10H12O6S) measured at a mass-to-charge ratio of 259.028 in LC / MS negative ion detection mode, glycochenodeoxycholic acid 3-sulfate, isoleucylhydroxyproline, pro-hydroxy-pro, kynurenine, 4-methoxyphenol sulfate, 5-hydroxylysine, trans-4-hydroxyproline, glycylleucine, glycocholate, a compound (C7H10N4O3) measured at a mass-to-charge ratio of 197.068 in LC / MS negative ion detection mode, a compound (C28H38N4O5) measured at a mass-to-charge ratio of 509.277 in LC / MS negative ion detection mode, 3-hydroxykynurenine, glycochenodeoxycholate, isoleucylglycine, phenylalanylhydroxyproline, 4-hydroxyphenylpyruvate, lactate, cyclo(pro-hydroxypro), tryptophan A kit comprising a means for measuring at least one urinary tumor marker selected from the group consisting of phan, N6-acetyl lysine, gamma-glutamyl phenylalanine, leucyl hydroxyproline, a compound (C14H23N3O6) measured as having a mass-to-charge ratio of 328.152 in LC / MS negative ion detection mode, a compound (C6H11NO3) measured as having a mass-to-charge ratio of 146.081 in LC / MS positive ion detection mode, androsterone glucuronide, 3-hydroxyanthranilate, 11beta-hydroxyandrosterone glucuronide, cystathionine, carnosine, proline, anserine, arabitol / xylitol, 3-hydroxy-2-ethylpropionate, 2R,3R-dihydroxybutyrate, gamma-glutamyl tyrosine, 1-methyladenine, dihydroorotic acid, alanine, and 17alpha-hydroxypregnenolone glucuronide.

[0011] [4] A method for evaluating the effectiveness of a treatment for biliary tract cancer, comprising: A step of measuring urinary tumor markers in a urine sample from a patient with biliary tract cancer who has been treated with a test therapeutic agent or therapy, wherein the urinary tumor markers are selected from the group consisting of cholate, chenodeoxycholic acid sulfate, a compound measured in LC / MS negative ion detection mode with a mass-to-charge ratio of 259.028 (C10H12O6S), glycochenodeoxycholic acid 3-sulfate, isoleucyl hydroxyproline, pro-hydroxy-pro, kynurenine, 4-methoxyphenol sulfate, 5-hydroxylysine, trans-4-hydroxyproline, glycylleucine, glycocholate, a compound measured in LC / MS negative ion detection mode with a mass-to-charge ratio of 197.068 (C7H10N4O3), a compound measured in LC / MS negative ion detection mode with a mass-to-charge ratio of 509.277 (C28H38N4O5), 3-hydroxykynurenine, glycochenodeoxycholate, isoleucylglycine, phenylalanyl hydroxyproline, 4 the step of comprising at least one urinary tumor marker selected from hydroxyphenylpyruvate, lactate, cyclo(pro-hydroxypro), tryptophan, N6-acetyllysine, gamma-glutamylphenylalanine, leucylhydroxyproline, a compound measured to have a mass-to-charge ratio of 328.152 in LC / MS negative ion detection mode (C14H23N3O6), a compound measured to have a mass-to-charge ratio of 146.081 in LC / MS positive ion detection mode (C6H11NO3), androsterone glucuronide, 3-hydroxyanthranilate, 11beta-hydroxyandrosterone glucuronide, cystathionine, carnosine, proline, anserine, arabitol / xylitol, 3-hydroxy-2-ethylpropionate, 2R,3R-dihydroxybutyrate, gamma-glutamyltyrosine, 1-methyladenine, dihydroorotic acid, alanine, and 17alpha-hydroxypregnenolone glucuronide; The method comprises a step of evaluating the efficacy of the test therapeutic drug or treatment for biliary tract cancer based on the measurement results.

[0012] This specification includes the disclosure of Japanese Patent Application No. 2022-090965, filed on June 3, 2022, from which this application claims priority.

[0013] The present invention provides a method, device, and kit for diagnosing biliary tract cancer in a minimally invasive, simple, and low-cost manner. Because the test is based on urine, the collection method in clinical settings is extremely simple, greatly improving convenience for medical professionals. Therefore, the present invention is useful in fields such as the diagnosis, testing, treatment evaluation, and drug development of biliary tract cancer.

[0014] Graphs showing the top 30 metabolites when biliary tract cancer-related urinary metabolites are ranked using random forest (RF). Graph (A) shows the calculation results of predicted values ​​when 10 markers are applied to a cancer testing model for biliary tract cancer, and graph (B) shows the AUC of the cancer testing model. Graph (A) shows the calculation results of predicted values ​​when 10 markers are applied to a cancer testing model for biliary tract cancer, and graph (B) shows the AUC of the cancer testing model. Graph (A) shows the calculation results of predicted values ​​when 20 markers are applied to a cancer testing model for biliary tract cancer, and graph (B) shows the AUC of the cancer testing model. Graph (A) shows the calculation results of predicted values ​​when 20 markers are applied to a cancer testing model for biliary tract cancer, and graph (B) shows the AUC of the cancer testing model. Graph (A) shows the calculation results of predicted values ​​when 20 markers are applied to a cancer testing model for biliary tract cancer, and graph (B) shows the AUC of the cancer testing model. Graph (A) shows the calculation results of predicted values ​​when 6 markers considered important for biliary tract cancer are applied to a cancer testing model, and graph (B) shows the AUC of the cancer testing model. Graph (A) shows the calculation results of predicted values ​​when three markers considered important for biliary tract cancer are applied to a cancer testing model, and graph (B) shows the AUC of the cancer testing model. Graph (A) shows the calculation results of predicted values ​​when two markers considered important for biliary tract cancer are applied to a cancer testing model, and graph (B) shows the AUC of the cancer testing model. An example of the configuration of a device to which the present invention is applied is shown. Graph (A) shows the top 20 metabolites when urinary metabolites related to differences between biliary tract cancer and healthy subjects are ranked using random forest (RF). Graph (A) shows the calculation results of predicted values ​​when 20 markers considered important for biliary tract cancer are applied to a cancer testing model, and graph (B) shows the AUC of the cancer testing model. Graph (A) shows the calculation results of predicted values ​​when 10 markers considered important for biliary tract cancer are applied to a cancer testing model, and graph (B) shows the AUC of the cancer testing model. Graph (A) shows the calculation results of the prediction values ​​when five markers considered to be important for biliary tract cancer are applied to a cancer testing model, and graph (B) shows the AUC of the cancer testing model.

[0015] The methods, devices, and kits provided by the present invention utilize novel urinary tumor markers and marker groups associated with biliary tract cancer. These urinary tumor markers are metabolites whose levels in urine vary depending on the presence or absence of biliary tract cancer, and are therefore useful for detecting biliary tract cancer, predicting the risk of biliary tract cancer, staging biliary tract cancer, determining the prognosis of biliary tract cancer, monitoring biliary tract cancer, and / or monitoring the effectiveness of treatment for biliary tract cancer.

[0016] The method for diagnosing biliary tract cancer according to the present invention includes the steps of measuring a urinary tumor marker in a urine sample derived from a subject, and diagnosing biliary tract cancer in the subject based on the measurement results.

[0017] In the present invention, biliary tract cancer is diagnosed. Biliary tract cancer refers to cancer (malignant tumor) that occurs in the biliary tract and is classified into intrahepatic bile duct cancer, extrahepatic bile duct cancer (perihilar bile duct cancer, distal bile duct cancer), gallbladder cancer, and ampullary cancer. Biliary tract cancer can be primary, metastatic, or recurrent, and is classified into stages based on the degree of progression and spread. The required treatment (surgery, chemotherapy, radiation therapy, immunotherapy, etc.) varies depending on whether it is primary, metastatic, or recurrent, and the stage.

[0018] In one embodiment, the step of measuring urinary tumor markers measures urinary tumor markers associated with biliary tract cancer. The "urinary metabolites" or "urinary tumor markers" to be measured in the present invention refer to the urinary metabolites listed in Table 1 below. Compared to substances in blood, urinary metabolites are less susceptible to enzymes and are structurally stable, making them highly convenient tumor markers. Furthermore, since urine is used as the sample, it can be easily collected from subjects, making it highly useful for cancer screening. Furthermore, a "marker group" refers to a combination of two or more urinary tumor markers.

[0019] "Measuring" refers to determining the relative abundance or absolute concentration of a metabolite in a urine sample. Relative abundance refers to the ratio of the measured intensity of a target metabolite to that of an intentionally added standard substance. On the other hand, absolute concentration refers to a method in which a calibration curve (the relationship between the concentration of a metabolite and the measured intensity of the metabolite) is prepared in advance using the same metabolite for the target metabolite, and the absolute concentration is calculated from the measured intensity. Furthermore, in the present invention, "measuring a urinary tumor marker" may refer to measuring a metabolite that is a urinary tumor marker, or to measuring a derivative or derivative thereof. "Derivative" and "derivative" refer to a substance derived from a metabolite that is a urinary tumor marker and a substance derived from the metabolite, respectively. "Derivative" and "derivative" include, for example, but are not limited to, fragments of a metabolite and modified metabolites.

[0020] The main urinary tumor markers used in the present invention are summarized in Table 1 below. In the table, the "Metabolite" column shows the name of the metabolite whose structure was determined as a result of a database search, or the symbol and estimated chemical formula if the structure is unknown. The estimated chemical formula was estimated from the "Measured Mass" and "Measurement Mode" and a metabolite database such as the Human Metabolome Database (HMDB). The CAS Registry Number in Table 1 is the de facto standard for chemical substance IDs and is a number used to identify chemical substances, and the HMDB ID is the ID of the HMDB online database of small molecule metabolites in the human body. In Table 1, the "Measured Mass" column shows the mass-to-charge ratio when detected using the detection method listed in the "Measurement Mode" column. In the "Measurement Mode" column, "Neg," "Pos Early," and "Polar" refer to the negative ion detection mode of a liquid chromatography / mass spectrometer (LC / MS), the positive ion detection mode of a liquid chromatography / mass spectrometer (LC / MS) optimized for hydrophilic compounds, and the negative ion detection mode of a liquid chromatography / mass spectrometer (LC / MS) using a hydrophilic interaction liquid chromatography (HILIC) column, optimized for polar compounds, respectively. In this specification, "LC / MS pos early" is also referred to simply as the positive ion detection mode of a liquid chromatography / mass spectrometer (LC / MS). The measured masses in Table 1 are essentially the masses of ionized metabolites, which vary by ±1 from the mass of the original metabolite due to the addition or loss of one proton. However, depending on the measurement conditions, multiple protons or sodium may be added or lost, resulting in corresponding variations in the measured mass. Alternatively, mass spectra of fragment ions generated by applying energy to metabolites may be measured.

[0021]

[0022] In one embodiment, the cholate salts shown in Table 1 are measured, i.e., the compound measured as mass 407.280 in LC / MS negative ion detection mode.

[0023] In one embodiment, chenodeoxycholic acid sulfate (2) shown in Table 1 is measured, i.e., the compound measured as mass 235.118 in LC / MS negative ion detection mode is measured.

[0024] In one embodiment, X-17686 (C10H12O6S) shown in Table 1 is measured, i.e., the compound (C10H12O6S) measured as a mass of 259.028 in LC / MS negative ion detection mode is measured.

[0025] In one embodiment, glycochenodeoxycholic acid 3-sulfate shown in Table 1 is measured, i.e., the compound measured as mass 263.628 in LC / MS negative ion detection mode is measured.

[0026] In one embodiment, isoleucylhydroxyproline shown in Table 1 is measured, i.e., the compound measured as mass 245.150 in LC / MS positive ion detection mode.

[0027] In one embodiment, the pro-hydroxy-pro shown in Table 1 is measured, i.e., the compound measured as mass 229.118 in LC / MS positive ion detection mode is measured.

[0028] In one embodiment, the kynurenines shown in Table 1 are measured, i.e., the compound measured as mass 209.092 in LC / MS positive ion detection mode.

[0029] In one embodiment, the 4-methoxyphenol sulfate salt shown in Table 1 is measured, i.e., the compound measured as mass 203.002 in LC / MS negative ion detection mode.

[0030] In one embodiment, the 5-hydroxylysine shown in Table 1 is measured, i.e., the compound measured as mass 163.108 in LC / MS positive ion detection mode.

[0031] In one embodiment, trans-4-hydroxyproline shown in Table 1 is measured, i.e., the compound measured as mass 130.051 in LC / MS polar detection mode.

[0032] In one embodiment, the glycylleucine shown in Table 1 is measured, i.e., the compound measured as mass 189.123 in LC / MS positive ion detection mode.

[0033] In one embodiment, the glycocholate salts shown in Table 1 are measured, i.e., the compound measured as mass 464.302 in LC / MS negative ion detection mode.

[0034] In one embodiment, X-13728 (C7H10N4O3) shown in Table 1 is measured, i.e., the compound (C7H10N4O3) measured as a mass of 197.068 in LC / MS negative ion detection mode is measured.

[0035] In one embodiment, X-21851 (C28H38N4O5) shown in Table 1 is measured, i.e., the compound (C28H38N4O5) measured as mass 509.277 in LC / MS negative ion detection mode is measured.

[0036] In one embodiment, the 3-hydroxykynurenine shown in Table 1 is measured, i.e., the compound measured as mass 225.087 in LC / MS positive ion detection mode.

[0037] In one embodiment, the glycochenodeoxycholate shown in Table 1 is measured, i.e., the compound measured as mass 448.307 in LC / MS negative ion detection mode.

[0038] In one embodiment, the isoleucylglycine shown in Table 1 is measured, i.e., the compound measured as mass 187.116 in LC / MS negative ion detection mode.

[0039] In one embodiment, the phenylalanylhydroxyproline shown in Table 1 is measured, i.e., the compound measured as mass 279.134 in LC / MS positive ion detection mode.

[0040] In one embodiment, the 4-hydroxyphenylpyruvate salt shown in Table 1 is measured, i.e., the compound measured as mass 179.035 in LC / MS negative ion detection mode.

[0041] In one embodiment, lactate is measured as shown in Table 1, i.e., the compound measured as mass 89.024 in LC / MS polar detection mode.

[0042] In one embodiment, the cyclo(pro-hydroxypro) shown in Table 1 is measured, i.e., the compound measured as mass 211.108 in LC / MS positive ion detection mode.

[0043] In one embodiment, the tryptophan shown in Table 1 is measured, i.e., the compound measured as mass 205.097 in LC / MS positive ion detection mode.

[0044] In one embodiment, the N6-acetyl lysine shown in Table 1 is measured, i.e., the compound measured as mass 187.109 in LC / MS polar detection mode.

[0045] In one embodiment, gamma-glutamylphenylalanine shown in Table 1 is measured, i.e., the compound measured as mass 295.129 in LC / MS positive ion detection mode.

[0046] In one embodiment, the leucylhydroxyproline shown in Table 1 is measured, i.e., the compound measured as mass 245.150 in LC / MS positive ion detection mode.

[0047] In one embodiment, X-18887 (C14H23N3O6) shown in Table 1 is measured, i.e., the compound (C14H23N3O6) measured as mass 328.152 in LC / MS negative ion detection mode is measured.

[0048] In one embodiment, X-24475 (C6H11NO3) shown in Table 1 is measured, i.e., the compound (C6H11NO3) measured as mass 146.081 in LC / MS positive ion detection mode is measured.

[0049] In one embodiment, the androsterone glucuronide shown in Table 1 is measured, i.e., the compound measured as mass 465.249 in LC / MS negative ion detection mode.

[0050] In one embodiment, the 3-hydroxyanthranilate shown in Table 1 is measured, i.e., the compound measured as mass 154.050 in LC / MS positive ion detection mode.

[0051] In one embodiment, the 11beta-hydroxyandrosterone glucuronide shown in Table 1 is measured, i.e., the compound measured as mass 481.244 in LC / MS negative ion detection mode.

[0052] In one embodiment, the cystathionine shown in Table 1 is measured, i.e., the compound measured as mass 221.060 in LC / MS positive ion detection mode.

[0053] In one embodiment, the carnosine shown in Table 1 is measured, i.e., the compound measured as mass 227.114 in LC / MS positive ion detection mode.

[0054] In one embodiment, the proline shown in Table 1 is measured, i.e., the compound measured as mass 116.071 in LC / MS positive ion detection mode.

[0055] In one embodiment, anserine, as shown in Table 1, is measured, i.e., the compound measured as mass 239.115 in LC / MS negative ion detection mode.

[0056] In one embodiment, the arabitol / xylitol shown in Table 1 is measured, i.e., the compound measured as mass 151.061 in LC / MS polar detection mode is measured.

[0057] In one embodiment, the 3-hydroxy-2-ethylpropionate shown in Table 1 is measured, i.e., the compound measured as mass 117.056 in LC / MS polar detection mode.

[0058] In one embodiment, the 2R,3R-dihydroxybutyrate shown in Table 1 is measured, i.e., the compound measured as mass 119.035 in LC / MS polar detection mode.

[0059] In one embodiment, the gamma-glutamyltyrosine shown in Table 1 is measured, i.e., the compound measured as mass 311.124 in LC / MS negative ion detection mode.

[0060] In one embodiment, 1-methyladenine shown in Table 1 is measured, i.e., the compound measured as mass 150.077 in LC / MS positive ion detection mode.

[0061] In one embodiment, the dihydroorotic acid shown in Table 1 is measured, i.e., the compound measured as mass 157.026 in LC / MS polar detection mode.

[0062] In one embodiment, the alanine shown in Table 1 is measured, i.e., the compound measured as mass 90.055 in LC / MS positive ion detection mode.

[0063] In one embodiment, 17alpha-hydroxypregnenolong glucuronide, shown in Table 1, is measured, i.e., the compound measured as mass 509.276 in LC / MS negative ion detection mode.

[0064] The mass spectrometer used to analyze the metabolites shown in Table 1 has very high resolution and can measure masses to about five decimal places, but to take measurement errors into account, the masses are listed to three decimal places in Table 1. If a mass spectrometer with low resolution is used, the masses will be measured to integer masses or to one or two decimal places.

[0065] In one embodiment of the present invention, at least one of the urinary tumor markers shown in Table 1 can be used to diagnose biliary tract cancer and monitor the effectiveness of treatment.

[0066] Furthermore, in the present invention, the use of a combination of at least two or three or more urinary tumor markers enables more accurate and highly precise determination and monitoring of the effects of treatment. For example, at least two, at least three, at least four, at least five, at least six, at least seven, at least eight, at least nine, at least ten, at least 11, at least 12, at least 13, at least 14, at least 15, at least 16, at least 17, at least 18, at least 19, at least 20, or more can be combined. The combination of markers is not particularly limited. For example, in one embodiment, at least three types of urinary tumor markers are measured.

[0067] Any of the urinary tumor markers shown in Table 1 can be used alone to determine biliary tract cancer. In one embodiment, the markers include at least glycochenodeoxycholic acid 3-sulfate, glycocholate, or 4-hydroxyphenylpyruvate.

[0068] Although a single urinary tumor marker can be compared and analyzed individually, when two or more urinary tumor markers are being studied, the comparison and analysis becomes extremely complicated due to the wide variety of combinations. Therefore, the evaluation variables shown below, the accuracy variable R2Y and the prediction variable Q2, can be used as criteria for determining which combination is best for two or more markers.

[0069]

[0070] Here, Yobs is the measured value, Ycalc is the calculated value by OPLS, and Ypred is the predicted value when cross-validation is performed. represents the average value. Cross-validation is a method of dividing data, first analyzing a portion of it, and then testing the analysis on the remaining portion, in order to verify and confirm the validity of the analysis itself. According to this, the closer the value of the accuracy variable R2Y is to 1, the higher the accuracy of the model, and the closer the Q2 value of the predictor variable is to 1, the higher the predictive ability of the model. It is believed that using combinations with high values ​​of this accuracy variable and predictor variable to diagnose biliary tract cancer will enable more accurate diagnosis.

[0071] The combination of urinary tumor markers can be selected appropriately depending on the type, sex, and age of the subject, the purpose including the determination of biliary tract cancer, the follow-up of subjects at high risk (e.g., based on family history) or subjects without abnormalities (monitoring of biliary tract cancer), or the monitoring of treatment.

[0072] As an example of a method for identifying urinary tumor markers, partial least squares, a type of multivariate analysis, particularly OPLS-DA, can be used. When performing multivariate analysis by combining multiple metabolites that vary between two groups, using multidimensional data as is can make it difficult to understand the characteristics of the data, so it is preferable to visualize the data by reducing it to two- or three-dimensional data. Analytical methods known in the art, such as principal component analysis, can also be used for multivariate analysis.

[0073] A urine sample refers to urine collected from a subject, and samples obtained by treating the urine (for example, urine to which a preservative such as toluene, xylene, or hydrochloric acid has been added).

[0074] The subject is human urine. Because metabolic activity in the human body is expected to vary depending on race, etc., monoglot individuals, including Japanese, are preferred, but not limited to, the subjects of the present invention. For example, the subject may be a mass screening test such as a health checkup or cancer test, a follow-up test after such mass screening, or a test before or after surgery at a hospital or during treatment such as chemotherapy or radiation therapy. Furthermore, even for the same individual, the concentration of urinary metabolites can easily vary depending on the timing of urine collection and water intake. To standardize the content of urinary metabolites in random urine samples, the amount of creatinine or osmolality in the urine is generally measured and then normalized by dividing the amount of each metabolite. Hereinafter, the term "urinary metabolite amount" essentially refers to the normalized amount.

[0075] Measuring a urinary tumor marker means measuring its amount or concentration in a urine sample, preferably semi-quantitatively or quantitatively, and the amount may be absolute or relative. Measurement can be performed directly or indirectly. Direct measurement involves measuring the amount or concentration based on a signal that directly correlates with the number of molecules of a urinary metabolite present in the sample. Such a signal is based, for example, on specific physical or chemical properties of the urinary metabolite. Indirect measurement is the measurement of a signal obtained from a secondary component (i.e., a component other than a urinary metabolite), such as a ligand, a label, or an enzymatic reaction product.

[0076] In one embodiment of the present invention, urinary tumor markers, i.e., urinary metabolites, are measured. The measurement method can be any method or means known in the art and is not particularly limited. For example, urinary tumor markers can be measured using a means for measuring physical or chemical properties specific to urinary metabolites, such as accurate molecular weight or NMR spectrum. Examples of means for measuring urinary metabolites include analytical devices such as mass spectrometers, NMR analyzers, two-dimensional electrophoresis devices, chromatographs, and liquid chromatography / mass spectrometry (LC / MS). Urinary tumor markers can be measured using a single analytical device, or multiple analytical devices.

[0077] Alternatively, if a reagent for detecting the metabolite to be measured, such as an immunoreaction reagent or an enzyme reaction reagent, is available, the metabolite in urine can be measured using such a reagent.

[0078] The urinary metabolites shown in Table 1 were found by LC / MS, and therefore, these urinary metabolites can be measured using LC / MS.

[0079] In this manner, it is possible to measure urinary tumor markers contained in a urine sample collected from a subject and diagnose biliary tract cancer in the subject based on the results. Furthermore, urinary tumor markers may be measured in urine samples collected from the subject at multiple time points.

[0080] The method for diagnosing biliary tract cancer of the present invention enables early detection of the presence and progression of biliary tract cancer, which is useful for determining detailed testing and treatment strategies. Diagnosing biliary tract cancer with a simple test is expected to prevent the invasive risks associated with testing as well as treatment. This allows subjects to receive early treatment for biliary tract cancer, or, if the risk is high, to undergo follow-up observation for the onset of biliary tract cancer. It also allows monitoring of the effectiveness of biliary tract cancer treatment, making it possible to consider halting, continuing, or changing treatment depending on its effectiveness. Furthermore, since it uses a urine sample, it is minimally invasive, has very few psychological barriers, and allows for simple, low-cost detection of biliary tract cancer. Therefore, it is highly suitable for screening purposes for early detection, and since urine can be collected repeatedly, it is also suitable for routine monitoring.

[0081] The method of the present invention for diagnosing biliary tract cancer can be carried out easily and simply by using a kit and / or device equipped with a means for measuring urinary tumor markers, which are urinary metabolites.

[0082] The kit for assessing biliary tract cancer according to the present invention comprises at least a means for measuring at least one (preferably at least three) of the urinary tumor markers shown in Table 1 above.

[0083] One example of the kit of the present invention is a mass spectrometry reagent set, which may be composed of, for example, an isotope-labeled reagent, a fractionation minicolumn, a buffer solution, etc. Another example of the kit is an immune reaction reagent set, which may be composed of, for example, a substrate on which a primary antibody is immobilized, a secondary antibody, etc. Another example is an enzymatic reaction reagent set, which may be composed of, for example, an enzyme, a buffer solution, etc. The kit of the present invention may also include instructions describing the procedures and protocols for carrying out the method of the present invention, a table showing reference values ​​or reference ranges to be used in the diagnosis of biliary tract cancer, etc.

[0084] The components included in the kit of the present invention may be provided individually or in a single container. Preferably, the kit of the present invention contains all of the components necessary to carry out the method of the present invention, for example, as components in adjusted concentrations, so that they can be used immediately.

[0085] The biliary tract cancer diagnosis device of the present invention comprises the following means: a measurement unit that measures at least one (preferably at least three) of the urinary tumor markers shown in Table 1 above in a urine sample; a comparison unit that compares the measurement value of the urinary tumor marker measured by the measurement unit with a reference value or a previous measurement value; and a determination unit that determines biliary tract cancer from the comparison result obtained by the comparison unit.

[0086] Furthermore, when multivariate analysis is used, the biliary tract cancer diagnosis device of the present invention comprises the following means: a measurement unit that measures at least one (preferably at least three) of the urinary tumor markers shown in Table 1 above in a urine sample; a comparison unit that compares the calculated value obtained by multivariate analysis of the explanatory variables measured by the measurement unit (the amount or concentration of the urinary tumor marker, or, for example, the observed ion intensity ratio of the urinary tumor marker that increases or decreases in biliary tract cancer patients compared to benign or no abnormality) with a reference value, which is the calculated value of the objective variable (an indicator showing whether the patient has biliary tract cancer or no abnormality) calculated based on a cancer testing model obtained by multivariate analysis based on accumulated data, or the calculated value of the objective variable up to the previous time; and a judgment unit that judges biliary tract cancer from the comparison result obtained by the comparison unit.

[0087] The device of the present invention is preferably a system in which the above-mentioned measurement unit, comparison unit, and determination unit are operatively connected to each other so that the method of the present invention can be carried out. One embodiment of the device of the present invention is shown in Figure 6.

[0088] Here, the measurement unit includes a means for measuring urinary tumor markers in a urine sample, as described above, and is equipped with an analytical device such as a mass spectrometer, an NMR analyzer, a two-dimensional electrophoresis device, a chromatograph, or a liquid chromatography mass spectrometry (LC / MS) device.

[0089] The measurement unit includes a data analysis unit consisting of software and a computer for processing measurements obtained from the above-described analytical device. The data analysis unit calculates the amount or concentration of urinary tumor markers contained in urine samples by referring to data such as calibration curves based on measurements obtained from the above-described analytical device. On the other hand, when multivariate analysis is used, the data analysis unit calculates a calculated value of a response variable (an index indicating whether a patient has biliary tract cancer or no abnormalities) based on a cancer testing model obtained by multivariate analysis of explanatory variables measured by the measurement unit (such as the amount or concentration of urinary tumor markers, or, for example, the observed ion intensity ratio of urinary tumor markers, which increases or decreases in patients with biliary tract cancer compared to benign or no abnormalities). The data analysis unit can include, for example, a signal display unit, a unit for analyzing measurements, a computer unit, etc.

[0090] The comparison unit also reads out reference values ​​for the amount or concentration of urinary tumor markers from a storage device (database) or the like, and compares the measured values ​​of the urinary tumor markers measured by the measurement unit with the reference values. Meanwhile, when multivariate analysis is used, the comparison unit reads out reference values ​​for the objective variables from a storage device (database) or the like, and compares the calculated values ​​of the objective variables obtained by the measurement unit with the reference values. At this time, the comparison unit selects and reads out appropriate reference values ​​depending on the type of urinary tumor marker. Alternatively, in the case of longitudinal monitoring of the same subject, the comparison unit reads out the previous measured values ​​from a storage device (database) or the like, and compares them with the measured values ​​of the urinary tumor markers measured by the measurement unit.

[0091] Furthermore, the determination unit determines biliary tract cancer based on the results of the comparison unit comparing the measured values ​​of urinary tumor markers with reference values, or based on the results of the comparison unit comparing the measured values ​​of urinary tumor markers at multiple time points. Meanwhile, when multivariate analysis is used, the determination unit determines biliary tract cancer based on the results of the comparison unit comparing the calculated values ​​of the objective variable with reference values, or based on the results of the comparison unit comparing the calculated values ​​of the objective variable at multiple time points. Here, the determination unit acquires information indicating the presence of biliary tract cancer in the subject, the stage of biliary tract cancer, whether there are any abnormalities, etc. A preferred device is one that can be used without the knowledge of a specialized clinician, such as an electronic device that simply requires the addition of a sample.

[0092] For example, the determination unit determines that the subject may have biliary tract cancer if the urinary tumor marker is equal to or greater than a reference value or a previous measurement value, or determines that the subject may be normal if the urinary tumor marker is lower than a reference value or a previous measurement value.

[0093] The device of the present invention may further include a data storage unit, a data output / display unit, and the like.

[0094] As used herein, "(assistance in) diagnosing biliary tract cancer" means not only detecting biliary tract cancer in a subject, but also predicting the risk of biliary tract cancer in a subject, determining the stage of biliary tract cancer in a subject, determining the prognosis of biliary tract cancer in a subject, monitoring biliary tract cancer in a subject, monitoring the effects of treatment for biliary tract cancer present in a subject, and assisting in the diagnosis of biliary tract cancer. Furthermore, in the present invention, "diagnosing" also encompasses continuous monitoring of biliary tract cancer that has already been detected or diagnosed, and confirmation of an existing detection or diagnosis of biliary tract cancer.

[0095] The "determination" by the biliary tract cancer determination method, determination kit, and determination device of the present invention is intended to determine a statistically significant proportion of subjects. Therefore, the "determination" by the biliary tract cancer determination method, determination kit, and determination device of the present invention includes cases where the correct result is not necessarily obtained for all subjects (i.e., 100%). Statistically significant proportions can be determined using various well-known statistical evaluation tools, such as determining confidence intervals, p-values, Student's t-tests, and Mann-Whitney tests. A preferred confidence interval is at least 90%. The p-value is preferably 0.1, 0.01, 0.05, 0.005, or 0.0001. More preferably, at least 60%, at least 80%, or at least 90% of subjects can be appropriately determined by the biliary tract cancer determination method, determination kit, and determination device of the present invention.

[0096] A specific example of how biliary tract cancer can be diagnosed is as follows: In one embodiment, urinary tumor markers are measured in a urine sample from a subject, and the measured values ​​are compared with reference values ​​or previous measured values. When multiple urinary tumor markers are measured, each urinary tumor marker may be compared with its respective reference value or previous measured value, or a calculated value of a response variable obtained by multivariate analysis may be obtained and compared with the reference value or previous measured value.

[0097] The standard (reference value) is the amount or concentration of a urinary tumor marker associated with biliary tract cancer, or a range of such amounts or concentrations, or the amount or concentration of a urinary tumor marker indicative of normal or normal. On the other hand, when multivariate analysis is used, the calculated value of the objective variable that distinguishes between biliary tract cancer and normal is the reference value. For example, the reference value can be derived from a population of healthy individuals or individuals at low risk of biliary tract cancer. Alternatively, the reference value can be derived from a patient population with biliary tract cancer (e.g., biliary tract cancer at a particular stage) or biliary tract cancer with a particular prognosis. The reference value applied to an individual subject may vary depending on various physiological parameters, such as the species, age, and sex of the subject animal.

[0098] Preferably, the correlation between the amount or concentration of the urinary tumor marker and the presence or specific prognosis of biliary tract cancer is recorded as a database. Then, the measured value of the urinary tumor marker in the measured urine sample can be compared with the reference value in the database. Such a database is useful as a reference value or reference range that serves as an indicator of the presence or absence of biliary tract cancer (or a specific stage of biliary tract cancer) or as an indicator of prognosis.

[0099] The amount or concentration of the urinary tumor markers listed in Table 1 varies depending on whether or not biliary tract cancer is present, and the amount or concentration changes depending on the presence of biliary tract cancer and before or after the start of treatment. Specifically, the amount or concentration of the markers listed in Table 1 increases in patients with biliary tract cancer compared to subjects without biliary tract cancer. Therefore, if the markers listed in Table 1 are higher than the reference values ​​derived from a population without abnormalities (subjects without biliary tract cancer) or are equal to or higher than the reference values ​​derived from a population of patients with biliary tract cancer, it can be said that the subject may have biliary tract cancer or is at high risk of having biliary tract cancer.

[0100] When comparing with a standard, it is also possible to determine a predicted value and make a judgment. In cancer testing using urinary tumor markers, multiple urinary tumor markers are often used to assess cancer risk, and in such cases it may be desirable to determine a predicted value. For example, if three urinary tumor markers are selected, the cancer risk is assessed using the predicted value given by the following prediction formula. Note that the intensity in the formula is the area value of the mass chromatogram corresponding to each mass. [Equation 2] Predicted value = α x (intensity of urinary tumor marker 1) + β x (intensity of urinary tumor marker 2) + γ x (intensity of urinary tumor marker 3) + δ (where α, β, γ, and δ are constants)

[0101] In the above cancer screening model, for example, if the predicted value is 0 or greater, the risk of cancer is determined to be high, and if it is less than 0, the risk of cancer is determined to be low. However, the threshold value of the predicted value is not limited to 0 and may be variable. Also, without clearly defining the threshold value, the magnitude of the predicted value may quantitatively correspond to the risk (probability) of cancer.

[0102] For example, the prediction formula is expressed as follows: [Equation 3] Prediction formula = 0.3336 × (intensity of urinary tumor marker 1) + 0.2408 × (intensity of urinary tumor marker 2) + 0.4132 × (intensity of urinary tumor marker 3) + 0.1234

[0103] In another embodiment, urine samples are collected from a subject at multiple time points, the urinary tumor marker contained in the urine sample at each measurement time point is measured, and the measured values ​​of the urinary tumor marker at each measurement time point are compared. More specifically, the amount or concentration of the urinary tumor marker at a first time point (a) is compared with the amount or concentration of the urinary tumor marker at a second time point (b). When multivariate analysis is performed, for example, the calculated value of one component at a first time point is compared with the calculated value at a second time point. Measurements can be performed at least two, three, four, five, ten, fifteen, twenty, thirty, or more times over time, for example, at intervals of one day, two days, five days, one week, two weeks, three weeks, one month, two months, three months, six months, one year, two years, three years, five years, or more. This comparison allows for time-course monitoring and makes it possible to evaluate the progression of biliary tract cancer, metastasis or recurrence of biliary tract cancer, malignant transformation of benign tumors, and the development of biliary tract cancer from no abnormality.

[0104] In another embodiment, the urinary tumor markers used in the present invention can be used to monitor the effectiveness of a treatment (therapeutic agent or therapy) for biliary tract cancer in a subject, specifically comprising the steps of: (a) measuring the urinary tumor markers in a urine sample from a patient with biliary tract cancer before treatment with the therapeutic agent or therapy, (b) measuring the urinary tumor markers in a urine sample from the patient with biliary tract cancer after treatment with the therapeutic agent or therapy, (c) repeating step (b) as necessary, and (d) monitoring the effectiveness of the therapeutic agent or therapy for biliary tract cancer based on the measurement results of steps (a) to (c).

[0105] In the above method, a urine sample is collected from a patient with biliary tract cancer before treatment with a therapeutic drug or therapy, and urinary tumor markers in the urine sample are measured. After treatment with a therapeutic drug or therapy, urine samples are collected at appropriate times to measure urinary tumor markers in the urine sample. For example, urine samples are collected immediately after treatment, 30 minutes, 1 hour, 3 hours, 5 hours, 10 hours, 15 hours, 20 hours, 24 hours (1 day), 2 to 10 days, 10 to 20 days, 20 to 30 days, and 1 month to 6 months after treatment. Measurement of urinary tumor markers in urine samples can be performed as described above. Measuring urinary tumor markers before and after treatment makes it possible to monitor the effectiveness of the treatment with the therapeutic drug or therapy. Monitoring results can help determine whether to stop, continue, or change treatment.

[0106] Furthermore, the method for diagnosing biliary tract cancer may be performed in combination with other conventionally known methods for diagnosing biliary tract cancer, such as blood tests (measurement of blood cancer markers, liver function tests, etc.), imaging tests (e.g., abdominal ultrasound, computed tomography (CT), MRI, positron emission tomography (PET), etc.), endoscopic examination, and pathological tests such as biopsy or cytology.

[0107] Based on the above-described assessment results, a physician can diagnose biliary tract cancer in a subject and provide appropriate treatment. That is, the present invention also relates to a method for diagnosing and treating biliary tract cancer in a subject. For example, if biliary tract cancer is diagnosed in a subject using the method of the present invention and the subject is assessed as having a high probability of having biliary tract cancer, treatment for biliary tract cancer or treatment to prevent the progression of biliary tract cancer is administered to the subject. Furthermore, if the subject's biliary tract cancer is assessed as having an advanced stage or a high probability of having a poor prognosis, treatment can be continued or, if necessary, a change in treatment can be considered. Alternatively, if the subject is assessed as being at high risk but has not yet developed biliary tract cancer, biliary tract cancer can be monitored over time by measuring urinary tumor markers to avoid excessive testing and treatment. Furthermore, if the subject is assessed as having a high probability of having biliary tract cancer, other biliary tract cancer diagnostic methods such as those described above can be used to confirm the presence of biliary tract cancer. Furthermore, based on the pre- and post-treatment assessment results, the effectiveness of treatment can be monitored to determine whether to discontinue, continue, or change treatment. If no abnormalities are found, the tumor markers in urine can be measured over time to allow for follow-up observation.

[0108] Biliary tract cancer can be treated with surgery (surgical resection), chemotherapy, radiation therapy, immunotherapy, proton therapy, heavy ion therapy, etc., either alone or in appropriate combination. A person skilled in the art can appropriately select a treatment for biliary tract cancer, taking into consideration the type, stage, malignancy, sex, age and condition of the biliary tract cancer, responsiveness to treatment, and genetic polymorphisms (SNPs) present.

[0109] As an example of application of the present invention, we will explain cancer testing at a testing center. The testing center provides information about cancer testing in response to a request from the subject. The subject may select the number of biomarkers to be tested when applying for the initial test. For example, the number of biomarkers may include one to three types of urinary tumor markers. This can also be used in combination with other biomarkers as a pan-cancer test (analyzing various cancers at once).

[0110] Next, the testing center will hand over the test kit required for urine collection to the subject. If necessary, it will be sent by mail. After receiving the test kit, the subject will hand over or send the sample to the testing center. At the testing center, the sample will be frozen at approximately -80°C as needed for subsequent testing. However, if it is known that the target urinary metabolites are stable over time and temperature, the sample may be stored frozen at approximately -5°C, refrigerated at approximately 5°C, or at room temperature, rather than at -80°C. The testing center will then perform the initial test and send the test results to the subject.

[0111] After receiving the results of the primary examination, the patient can apply for a secondary examination or undergo a more detailed diagnosis depending on the results, which can confirm the suspicion of biliary tract cancer in the primary examination and further identify the stage of biliary tract cancer.

[0112] Furthermore, the urinary tumor markers used in the present invention can be used to evaluate the effectiveness of treatments (therapeutic agents or therapies) for biliary tract cancer or to screen candidate therapeutic agents for biliary tract cancer. Specifically, a method for evaluating the effectiveness of treatments for biliary tract cancer or a method for screening candidate therapeutic agents for biliary tract cancer comprises the steps of: (a) measuring urinary tumor markers in urine samples from animals with biliary tract cancer that have been treated with a test therapeutic agent or therapy; and (b) evaluating the effectiveness of the test therapeutic agent or therapy for biliary tract cancer based on the measurement results of (a).

[0113] In the method of the present invention, urine samples are collected from patients with biliary tract cancer or humans without biliary tract cancer, and urinary tumor markers in the urine samples are measured. Preferably, urine samples are collected from humans with biliary tract cancer before treatment with a test therapeutic drug or therapy, and urinary tumor markers in the urine samples are measured. After treatment of an animal with biliary tract cancer with a test therapeutic drug or therapy, urine samples are collected at appropriate time points, and urinary tumor markers in the urine samples are measured. For example, urine samples are collected immediately after treatment, 30 minutes, 1 hour, 3 hours, 5 hours, 10 hours, 15 hours, 20 hours, 24 hours (1 day), 2 to 10 days, 10 to 20 days, 20 to 30 days, and 1 month to 6 months later. Measurement of urinary tumor markers in urine samples and assessment of biliary tract cancer can be performed as described above.

[0114] The type of test therapeutic agent or treatment to be evaluated or screened is not particularly limited. For example, the test therapeutic agent or treatment may be any material factor, specifically, naturally occurring molecules such as amino acids, peptides, oligopeptides, polypeptides, proteins, nucleic acids, lipids, carbohydrates (such as sugars), steroids, glycopeptides, glycoproteins, and proteoglycans; synthetic analogs or derivatives of naturally occurring molecules such as peptidomimetics, nucleic acid molecules (such as aptamers, antisense nucleic acids, and double-stranded RNA (RNAi)); non-naturally occurring molecules such as small organic compounds (such as inorganic and organic compound libraries or combinatorial libraries); and mixtures thereof. The test therapeutic agent or treatment may be a single substance, a complex composed of multiple substances, or a food or diet. Furthermore, the test therapeutic agent or treatment may be radiation, ultraviolet light, or the like in addition to the material factors described above.

[0115] The efficacy of a test therapeutic agent or treatment can also be examined under several conditions. Such conditions include the time or duration of treatment with the test therapeutic agent or treatment, the amount (large or small), and the number of times. For example, multiple doses can be established by preparing a dilution series of the test therapeutic agent. Furthermore, when examining the additive or synergistic effects of multiple test therapeutic agents or treatments, a combination of therapeutic agents or treatments may be used.

[0116] By measuring the urinary tumor marker in a urine sample collected after treatment with the test therapeutic drug or therapy and comparing the amount or concentration with that before treatment, it is possible to evaluate whether the test therapeutic drug or therapy is effective in eliminating biliary tract cancer, shrinking biliary tract cancer, improving symptoms caused by biliary tract cancer, or stopping or slowing the progression of biliary tract cancer.

[0117] For example, in the case of the markers shown in Table 1, a lower post-treatment measurement value compared to a pre-treatment measurement value in a patient with biliary tract cancer indicates that the test therapeutic drug or therapy has eliminated, reduced, or improved symptoms of biliary tract cancer, or stopped or is effective in preventing or halting the progression of biliary tract cancer. On the other hand, a higher post-treatment measurement value compared to a pre-treatment measurement value or no significant difference from a pre-treatment measurement value indicates that the test therapeutic drug or therapy is not effective in treating biliary tract cancer.

[0118] As described above, the method for evaluating the effectiveness of treatment of biliary tract cancer according to the present invention makes it possible to find therapeutic agents or therapies for treating or preventing biliary tract cancer, and further to confirm the effectiveness of the therapeutic agents or therapies.

[0119] The present invention will be specifically described below by way of examples, but these examples are provided merely to illustrate the present invention and are not intended to limit or restrict the scope of the invention disclosed in this application.

[0120] Example 1 Comprehensive Analysis of Urinary Metabolites Associated with Biliary Tract Cancer At Nagoya University Hospital, with permission, urine samples were collected from 27 biliary tract cancer patients before tumor resection and two and four weeks after tumor resection (62 samples in total). Patient information was recorded, including sample ID, date of sample collection, age, sex, pre- and post-operative status, osmolality, prognosis, diagnosis, surgical procedure, histopathological type, pathological margin, pathological lymph node metastasis, stage, intraoperative blood transfusion, medical history, and other marker measurements. The specific breakdown of urine samples is as follows:

[0121]

[0122] The patient's urinary metabolites (metabolome) were comprehensively analyzed using a liquid chromatography mass spectrometer (LC / MS), which is suitable for highly sensitive analysis of mixed components in solution. To detect as many metabolites as possible, positive and negative electrospray ionization was used for ionization, and multiple separation modes, including reversed-phase chromatography and hydrophilic interaction chromatography, were used to separate the mixed components.

[0123] From the mass spectrum obtained, metabolites are identified, i.e., peak annotation is performed, using a database. If a metabolite not registered in the database is detected, structure estimation may be performed using tandem mass spectrometry (MS / MS), which actively generates fragment ions from target ions. Although MS / MS does not always provide a clear structure estimate, it is much easier to estimate structure than isolating the target component and analyzing it with a nuclear magnetic resonance (NMR) spectrometer. Once candidate substances have been narrowed down using MS / MS, the estimated structure can be confirmed by actually synthesizing them and comparing the mass and MS / MS spectra.

[0124] From the above analysis, 1,524 metabolites were detected in urine, of which 1,027 were identified as substances with known structures. For compounds with unknown structures, information on the mass-to-charge ratio (m / z), MS spectrum, MS / MS spectrum, retention time, and separation mode was available from the measurements, so IDs were assigned and identification of chemical formulas was carried out.

[0125] As data preprocessing for the following analyses, the measured values ​​of each metabolite were normalized by osmolality. Furthermore, they were normalized by the median (median = 1), and missing values ​​were substituted with the minimum value. Finally, logarithmic transformation was performed. In some analyses, markers with large missing rates were excluded (for example, markers with missing rates of 50% or more were excluded in 27 preoperative cases). In marker discovery, exogenous metabolites such as drugs and foods were excluded. In OPLS-DA, standardization (auto scaling) was performed with a mean of 0 and a standard deviation of 1 to unify the weights of each variable.

[0126] First, we performed principal component analysis (PCA) using all metabolites. As a result, the marker principal component values ​​were separated before and after resection. A separation was also observed between two and four weeks after surgery, with the four-week period being closer to the preoperative period. This suggests that the two-week period reflects the transient effects of surgery and metabolic activity during healing. However, no clear separation was observed for gender, disease location, or prognosis (life or death).

[0127] Next, matched pair t-tests were performed between each group using all metabolites. Results showed significant differences in 494 metabolites between pre-surgery and 2 weeks post-surgery (p<=0.05). 113 metabolites were significantly different between pre-surgery and 4 weeks post-surgery. As with PCA, we speculate that metabolites related to biochemical changes associated with the effects of surgery or recovery from surgery were also extracted in the 2-week post-surgery period. 85 metabolites were evaluated as being significantly different between pre-surgery and both 2 and 4 weeks post-surgery.

[0128] Next, of the 113 metabolites that showed significant differences between preoperative and 4 weeks postoperatively, 86 metabolites were excluded, including those with exogenous and high deficiency rates. Random forest (RF) analysis was then performed on (i) preoperative vs. 2 weeks postoperatively, (ii) preoperative vs. 4 weeks postoperatively, and (iii) preoperative vs. 2 weeks and 4 weeks postoperatively. Because this analysis had the largest N number and was compared to the tumor-free group (2 weeks and 4 weeks postoperatively), the results for (iii) preoperative vs. 2 weeks and 4 weeks postoperatively were used as the marker importance. The top 30 markers, ranked by the average ranking of three RF runs, are shown in Table 3 and the graph in Figure 1.

[0129]

[0130] As described above, 30 markers related to biliary tract cancer (presence or absence of tumors) were identified. The abundance of these markers changes depending on the presence or absence of biliary tract cancer, so measuring these markers makes it possible to determine the presence or absence of biliary tract cancer and monitor it after surgery.

[0131] [Example 2] ROC curves were created for the top 20 RF markers identified in Example 1 before and after surgery (presence or absence of tumor), and AUC was calculated. The results are shown in the table below. The AUC value represents the discriminatory ability for biliary tract cancer when the indicated marker is used alone. The closer the AUC value is to 1, the higher the discriminatory ability; generally, an AUC value of 0.7 or higher is considered to be a good model or to have good discriminatory ability.

[0132]

[0133] It was found that the markers shown in Table 4 above are capable of evaluating the presence or absence of biliary tract cancer with high discriminatory ability even when used alone.

[0134] Example 3: Construction of a cancer screening model combining multiple markers A cancer screening model was constructed by combining multiple markers identified in Example 1. To evaluate the validity of the combined markers, an evaluation was performed using explanatory variables (representing the fit to the training data used to construct the model) and predictive variables (indicating the predictive performance of the model (leave-one-out cross-validation)). The closer the values ​​of these variables are to 1, the better the model, and they are very effective indices for verifying which models are highly valid. Specifically, a cancer screening model was obtained using the following indices by OPLS discriminant analysis.

[0135]

[0136] Here, Yobs is the measured value, Ycalc is the calculated value by OPLS, and Ypred is the predicted value when cross-validation is performed. represents the average value. Cross-validation is a method of dividing data, first analyzing a portion of it, and then testing the analysis on the remaining portion, in order to verify and confirm the validity of the analysis itself. According to this, the explanatory variable R2Y value represents the fit to the training data used to build the model; the closer it is to 1, the higher the accuracy of the model, and the predictor variable Q2 value indicates the predictive performance of the model (leave-one-out cross-validation), and the closer it is to 1, the higher the predictive power of the model.

[0137] A cancer testing model is constructed for a combination of multiple markers. Here, the cancer testing model, for example, uses five markers. The cancer risk is determined using a predicted value calculated using the following formula: α × (marker 1 intensity) + β × (marker 2 intensity) + γ × (marker 3 intensity) + δ × (marker 4 intensity) + ε × (marker 5 intensity) + ζ (α, β, γ, δ, ε, and ζ are constants) based on the concentration of each marker in a urine sample or the intensity of the ions corresponding to each marker (actually, the area of ​​the mass chromatogram obtained by LC / MS measurement). Specifically, a higher predicted value indicates a higher cancer risk, and a lower predicted value indicates a lower cancer risk. To accurately determine whether a patient has cancer or is healthy, an appropriate threshold value is set for the predicted value.

[0138] The top 10 or top 20 RF markers identified in Example 1 were used to evaluate cancer testing models using OPLS discriminant analysis. Specifically, cancer testing models were constructed for the following six items. In Figures 2 to 8, white bars represent urine samples collected before resection for biliary tract cancer, black bars represent urine samples collected two weeks after surgery, and shaded bars represent urine samples collected four weeks after surgery.

[0139] (1) A model was constructed using the top 10 RF markers for pre-surgery versus 2 weeks post-surgery, and applied to samples 4 weeks post-surgery. The results are shown in Figure 2, A (prediction value) and B (AUC). The shaded bars represent test samples. This cancer screening model had an explanatory variable R2Y of 0.706, a predictive variable Q2 of 0.632, and an AUC value (N = 62) of 0.929. As can be seen from the figure, using a combination of multiple markers enables more accurate identification. Furthermore, similar results were obtained for both the training data and the test data, demonstrating the model's high versatility.

[0140] (2) Using the top 10 RF markers, a model was constructed for pre-operative versus 4 weeks post-operative data, and applied to samples taken 2 weeks post-operatively. The results are shown in Figure 3, A (prediction value) and B (AUC). The black bars represent test samples. This cancer screening model had an explanatory variable R2Y of 0.694, a predictive variable Q2 of 0.537, and an AUC value (N = 62) of 0.930. As can be seen from the figure, using a combination of multiple markers enables more accurate identification. Furthermore, similar results were obtained for both the training data and the test data, demonstrating the high versatility of the model.

[0141] (3) Using the top 20 RF markers, a model was constructed for pre-operative versus 2-week post-operative data and applied to samples 4 weeks post-operative. The results are shown in Figure 4, A (prediction value) and B (AUC). The shaded bars represent test samples. This cancer screening model had an explanatory variable R2Y of 0.773, a predictive variable Q2 of 0.689, and an AUC value (N = 62) of 0.91. As can be seen from the figure, using a combination of multiple markers enables more accurate identification. Furthermore, similar results were obtained for both the training data and the test data, demonstrating the high versatility of the model.

[0142] (4) Using the top 20 RF markers, a model was constructed for pre-operative versus 4 weeks post-operative data and applied to samples taken 2 weeks post-operatively. The results are shown in Figure 5, A (prediction value) and B (AUC). The black bars represent test samples. This cancer screening model had an explanatory variable R2Y of 0.755, a predictive variable Q2 of 0.561, and an AUC value (N = 62) of 0.939. As can be seen from the figure, using a combination of multiple markers enables more accurate classification. Furthermore, similar results were obtained for both the training data and the test data, demonstrating the model's high versatility.

[0143] (5) Using six of the top 20 RF markers deemed particularly important, a model was constructed for preoperative versus postoperative (both 2-week and 4-week) comparisons. These six markers are metabolites that are also highly capable of discriminating between biliary tract cancer and healthy controls, as described below (Example 4). Specifically, the six markers are glycochenodeoxycholate 3-sulfate (Table 3: position 4, Table 6: position 1), glycocholate (Table 3: position 12, Table 6: position 2), 4-hydroxyphenylpyruvate (Table 3: position 19, Table 6: position 6), glycochenodeoxycholate (Table 3: position 16, Table 6: position 9), trans-4-hydroxyproline (Table 3: position 10, Table 6: position 12), and kynurenine (Table 3: position 7, Table 6: position 18). The results are shown in Figure 6, A (prediction value) and B (AUC). Here, the black bars represent postoperative samples (both 2-week and 4-week). This cancer testing model had an explanatory variable R2Y of 0.447, a predictive variable Q2 of 0.359, and an AUC value (N = 62) of 0.903. As can be seen from the figure, using a combination of multiple markers enables more accurate identification.

[0144] (6) Using three markers deemed particularly important among the top 20 RF markers, a model was constructed for preoperative versus postoperative (both 2-week and 4-week) comparisons. These three markers are metabolites with a high ability to distinguish between biliary tract cancer and healthy controls, as described below (Example 4). Specifically, the three markers were glycochenodeoxycholate 3-sulfate (Table 3: 4th, Table 6: 1st), glycocholate (Table 3: 12th, Table 6: 2nd), and 4-hydroxyphenylpyruvate (Table 3: 19th, Table 6: 6th). The results are shown in Figure 7, A (predicted value) and B (AUC). Here, the black bars represent postoperative samples (both 2-week and 4-week). This cancer testing model had an explanatory variable R2Y of 0.412, a predictive variable Q2 of 0.350, and an AUC value (N = 62) of 0.883. As can be seen from the figure, using a combination of multiple markers enables more accurate discrimination.

[0145] (7) Using two of the top 20 RF markers deemed particularly important, a model was constructed for preoperative versus postoperative (both 2-week and 4-week) comparisons. These two markers are metabolites with a high ability to distinguish between biliary tract cancer and healthy controls, as described below (Example 4). Specifically, glycochenodeoxycholate 3-sulfate (Table 3: 4th, Table 6: 1st) and glycocholate (Table 3: 12th, Table 6: 2nd). The results are shown in Figure 8, A (predicted value) and B (AUC). Here, the black bars represent postoperative samples (both 2-week and 4-week). This cancer testing model had an explanatory variable R2Y of 0.306, a predictive variable Q2 of 0.241, and an AUC value (N = 62) of 0.809. As can be seen from the figure, using a combination of multiple markers enables more accurate discrimination.

[0146] [Example 4] Comprehensive analysis of urinary metabolites by comparing biliary tract cancer patients and healthy individuals. With permission, urine samples were collected from 25 biliary tract cancer patients before tumor resection. As a control group, urine samples were also collected with permission from 25 individuals who were determined to be healthy by health checkup. The specific breakdown of urine samples is as follows:

[0147]

[0148] The subjects' urinary metabolites (metabolome) were comprehensively analyzed using a liquid chromatography mass spectrometer (LC / MS), which is suitable for highly sensitive analysis of mixed components in solution. To detect as many metabolites as possible, positive and negative electrospray ionization was used for ionization, and multiple separation modes, including reversed-phase chromatography and hydrophilic interaction chromatography, were used to separate the mixed components.

[0149] From the mass spectrum obtained, metabolites are identified, i.e., peak annotation is performed, using a database. If a metabolite not registered in the database is detected, structure estimation may be performed using tandem mass spectrometry (MS / MS), which actively generates fragment ions from target ions. Although MS / MS does not always provide a clear structure estimate, it is much easier to estimate structure than isolating the target component and analyzing it with a nuclear magnetic resonance (NMR) spectrometer. Once candidate substances have been narrowed down using MS / MS, the estimated structure can be confirmed by actually synthesizing them and comparing the mass and MS / MS spectra.

[0150] From the above analysis, 1,574 metabolites were detected in urine, of which 1,070 were identified as substances with known structures.

[0151] As data preprocessing for the following analyses, the measured values ​​of each metabolite were normalized by osmolality. Furthermore, they were normalized by the median (median = 1), and missing values ​​were substituted with the minimum value. Finally, logarithmic transformation was performed. In some analyses, markers with large missing rates were excluded. In marker search, exogenous metabolites such as drugs and foods were excluded. In OPLS-DA, standardization (auto scaling) was performed with a mean of 0 and a standard deviation of 1 to unify the weights of each variable.

[0152] A significant difference test was performed between groups using all metabolites. Here, the Wilcoxon rank-sum test, which can be applied to unpaired nonparametric analyses, was used. As a result, significant differences were found between cancer patients and healthy controls for 293 metabolites, excluding exogenous metabolites (p<=0.05). Thirty-two metabolites were common to the 86 metabolites used in the random forest analysis in Example 1 and the 293 metabolites used here.

[0153] Next, we performed random forest analysis (RF) to distinguish between cancer patients and healthy controls using 32 metabolites that showed significant differences after tumor resection of biliary tract cancer and between cancer patients and healthy controls. The top 20 markers, ranked by the average of three RF runs, are shown in Table 6 below and the graph in Figure 10.

[0154]

[0155] As described above, 20 markers were identified that correlate with the presence or absence of biliary tract cancer tumors (Examples 1 to 3) and that differ from healthy controls. Measuring these markers enables early detection and screening of biliary tract cancer.

[0156] [Example 5] Cancer testing models were evaluated using the OPLS discriminant analysis method for the top 20, top 10, or top 5 RF markers identified in Example 4. Specifically, cancer testing models were constructed for the following three cases. In Figures 11 to 13, white bars represent urine samples from biliary tract cancer patients (before tumor resection), and black bars represent urine samples from healthy individuals.

[0157] (1) A model was constructed for cancer patients versus healthy individuals using the top 20 RF markers. The results are shown in Figure 11, A (prediction value) and B (AUC). This cancer screening model had an explanatory variable R2Y of 0.598, a predictive variable Q2 of 0.405, and an AUC value (N = 50) of 0.934. As can be seen from the figure, highly accurate discrimination is possible by using a combination of multiple markers.

[0158] (2) A model was constructed for cancer patients versus healthy individuals using the top 10 RF markers. The results are shown in Figure 12, A (prediction value) and B (AUC). This cancer screening model had an explanatory variable R2Y of 0.471, a predictive variable Q2 of 0.333, and an AUC value (N = 50) of 0.941. As can be seen from the figure, highly accurate discrimination is possible by using a combination of multiple markers.

[0159] (3) A model was constructed for cancer patients versus healthy controls using the top five RF markers. The results are shown in Figure 13, A (predicted value) and B (AUC). This cancer testing model had an explanatory variable R2Y of 0.346, a predictive variable Q2 of 0.254, and an AUC value (N = 50) of 0.899. Although the values ​​of the explanatory and predictive variables decreased as the number of markers decreased, the AUC value remained high. Furthermore, a smaller number of markers reduces the testing time, reagent costs, and data analysis costs per sample.

[0160] All publications, patents, and patent applications cited herein are hereby incorporated by reference in their entirety.

Claims

1. A method for determining biliary tract cancer in a subject, comprising: measuring urinary tumor markers in a urine sample from a subject, the urinary tumor markers including at least one urinary tumor marker including glycochenodeoxycholic acid 3-sulfate and / or glycocholate; A step of comparing the measured value of the urinary tumor marker with a reference value derived from a healthy individual or a population of healthy individuals, or a low-risk individual or a population of low-risk individuals for biliary tract cancer, or with a previous measured value. Including, The method comprises determining whether the subject has biliary tract cancer based on the result.

2. The urinary tumor marker is selected from the group consisting of cholate, chenodeoxycholic acid sulfate, a compound measured as having a mass of 259.028 in LC / MS negative ion detection mode (C10H12O6S), isoleucyl hydroxyproline, pro-hydroxy-pro, kynurenine, 4-methoxyphenol sulfate, 5-hydroxylysine, trans-4-hydroxyproline, glycylleucine, a compound measured as having a mass of 197.068 in LC / MS negative ion detection mode (C7H10N4O3), a compound measured as having a mass of 509.277 in LC / MS negative ion detection mode (C28H38N4O5), 3-hydroxykynurenine, glycochenodeoxycholate, isoleucylglycine, phenylalanyl hydroxyproline, 4-hydroxyphenylpyruvate, lactate, cyclo(pro-hydroxypro), tryptophan, N6- 2. The method of claim 1, further comprising at least one urinary tumor marker selected from acetyl lysine, gamma-glutamyl phenylalanine, leucyl hydroxyproline, a compound measured as having a mass of 328.152 in LC / MS negative ion detection mode (C14H23N3O6), a compound measured as having a mass of 146.081 in LC / MS positive ion detection mode (C6H11NO3), androsterone glucuronide, 3-hydroxyanthranilate, 11beta-hydroxyandrosterone glucuronide, cystathionine, carnosine, proline, anserine, arabitol / xylitol, 3-hydroxy-2-ethylpropionate, 2R,3R-dihydroxybutyrate, gamma-glutamyl tyrosine, 1-methyladenine, dihydroorotic acid, alanine, and 17alpha-hydroxypregnenolong glucuronide.

3. The method according to claim 2, wherein at least three types of urinary tumor markers are measured.

4. The method of claim 1, wherein the urinary tumor marker, when equal to or greater than a baseline value or a previous measurement, indicates that the subject is likely to have biliary tract cancer.

5. The method of claim 1, wherein the assessment of biliary tract cancer is detection of biliary tract cancer in a subject, prediction of the risk of biliary tract cancer in a subject, assessment of the stage of biliary tract cancer in a subject, assessment of the prognosis of biliary tract cancer in a subject, monitoring of biliary tract cancer in a subject, or monitoring the effect of a treatment for biliary tract cancer present in a subject.

6. 2. The method of claim 1, wherein the biliary tract cancer is selected from the group consisting of intrahepatic cholangiocarcinoma, perihilar cholangiocarcinoma, distal bile duct cancer, gallbladder cancer, and ampullary carcinoma.

7. The method according to claim 1, wherein the measurement of the urinary tumor marker is carried out by liquid chromatography / mass spectrometry (LC / MS).

8. A device for determining biliary tract cancer, comprising: A measurement unit for measuring a urinary tumor marker in a urine sample, the urinary tumor marker including at least one urinary tumor marker including glycochenodeoxycholic acid 3-sulfate and / or glycocholate; a comparison unit for comparing the measured value of the urinary tumor marker by the measurement unit with a reference value or a previous measured value; a determination unit for determining biliary tract cancer based on the comparison results obtained from the comparison unit; An apparatus comprising:

9. The urinary tumor marker is selected from the group consisting of cholate, chenodeoxycholic acid sulfate, a compound measured as having a mass of 259.028 in LC / MS negative ion detection mode (C10H12O6S), isoleucyl hydroxyproline, pro-hydroxy-pro, kynurenine, 4-methoxyphenol sulfate, 5-hydroxylysine, trans-4-hydroxyproline, glycylleucine, a compound measured as having a mass of 197.068 in LC / MS negative ion detection mode (C7H10N4O3), a compound measured as having a mass of 509.277 in LC / MS negative ion detection mode (C28H38N4O5), 3-hydroxykynurenine, glycochenodeoxycholate, isoleucylglycine, phenylalanyl hydroxyproline, 4-hydroxyphenylpyruvate, lactate, cyclo(pro-hydroxypro), tryptophan, N6- 10. The device of claim 8, further comprising at least one urinary tumor marker selected from acetyl lysine, gamma-glutamyl phenylalanine, leucyl hydroxyproline, a compound measured as having a mass of 328.152 in LC / MS negative ion detection mode (C14H23N3O6), a compound measured as having a mass of 146.081 in LC / MS positive ion detection mode (C6H11NO3), androsterone glucuronide, 3-hydroxyanthranilate, 11beta-hydroxyandrosterone glucuronide, cystathionine, carnosine, proline, anserine, arabitol / xylitol, 3-hydroxy-2-ethylpropionate, 2R,3R-dihydroxybutyrate, gamma-glutamyl tyrosine, 1-methyladenine, dihydroorotic acid, alanine, and 17alpha-hydroxypregnenolong glucuronide.

10. The device according to claim 8 , wherein the determination unit determines that the subject is likely to have biliary tract cancer when the urinary tumor marker is equal to or greater than a reference value or a previous measured value.

11. The device according to claim 9 , wherein the measurement unit measures at least three types of the urinary tumor markers.

12. The apparatus of claim 8 , wherein the measurement portion comprises a liquid chromatography mass spectrometry (LC / MS) device.

13. A kit for determining biliary tract cancer, comprising: A kit comprising a means for measuring at least one urinary tumor marker, comprising glycochenodeoxycholic acid 3-sulfate and / or glycocholate.

14. The urinary tumor marker is selected from the group consisting of cholate, chenodeoxycholic acid sulfate, a compound measured as having a mass of 259.028 in LC / MS negative ion detection mode (C10H12O6S), isoleucyl hydroxyproline, pro-hydroxy-pro, kynurenine, 4-methoxyphenol sulfate, 5-hydroxylysine, trans-4-hydroxyproline, glycylleucine, a compound measured as having a mass of 197.068 in LC / MS negative ion detection mode (C7H10N4O3), a compound measured as having a mass of 509.277 in LC / MS negative ion detection mode (C28H38N4O5), 3-hydroxykynurenine, glycochenodeoxycholate, isoleucylglycine, phenylalanyl hydroxyproline, 4-hydroxyphenylpyruvate, lactate, cyclo(pro-hydroxypro), tryptophan, N6-acetylglucosamine ...

14. The kit of claim 13, further comprising at least one urinary tumor marker selected from cetyl lysine, gamma-glutamyl phenylalanine, leucyl hydroxyproline, a compound measured as having a mass of 328.152 in LC / MS negative ion detection mode (C14H23N3O6), a compound measured as having a mass of 146.081 in LC / MS positive ion detection mode (C6H11NO3), androsterone glucuronide, 3-hydroxyanthranilate, 11beta-hydroxyandrosterone glucuronide, cystathionine, carnosine, proline, anserine, arabitol / xylitol, 3-hydroxy-2-ethylpropionate, 2R,3R-dihydroxybutyrate, gamma-glutamyl tyrosine, 1-methyladenine, dihydroorotic acid, alanine, and 17alpha-hydroxypregnenolong glucuronide.

15. The kit according to claim 13, which is a reagent set for mass spectrometry.

16. A method for evaluating the efficacy of a treatment for biliary tract cancer, comprising: measuring urinary tumor markers in urine samples from animals having biliary tract cancer treated with a test therapeutic agent or therapy, the urinary tumor markers comprising at least one urinary tumor marker comprising glycochenodeoxycholic acid 3-sulfate and / or glycocholate; The method comprises evaluating the efficacy of a test therapeutic agent or treatment for biliary tract cancer based on the above measurement results.

17. The urinary tumor marker is selected from the group consisting of cholate, chenodeoxycholic acid sulfate, a compound measured as having a mass of 259.028 in LC / MS negative ion detection mode (C10H12O6S), isoleucyl hydroxyproline, pro-hydroxy-pro, kynurenine, 4-methoxyphenol sulfate, 5-hydroxylysine, trans-4-hydroxyproline, glycylleucine, a compound measured as having a mass of 197.068 in LC / MS negative ion detection mode (C7H10N4O3), a compound measured as having a mass of 509.277 in LC / MS negative ion detection mode (C28H38N4O5), 3-hydroxykynurenine, glycochenodeoxycholate, isoleucylglycine, phenylalanyl hydroxyproline, 4-hydroxyphenylpyruvate, lactate, cyclo(pro-hydroxypro), tryptophan, N6- 17. The method of claim 16, further comprising at least one urinary tumor marker selected from acetyl lysine, gamma-glutamyl phenylalanine, leucyl hydroxyproline, a compound measured as having a mass of 328.152 in LC / MS negative ion detection mode (C14H23N3O6), a compound measured as having a mass of 146.081 in LC / MS positive ion detection mode (C6H11NO3), androsterone glucuronide, 3-hydroxyanthranilate, 11beta-hydroxyandrosterone glucuronide, cystathionine, carnosine, proline, anserine, arabitol / xylitol, 3-hydroxy-2-ethylpropionate, 2R,3R-dihydroxybutyrate, gamma-glutamyl tyrosine, 1-methyladenine, dihydroorotic acid, alanine, and 17alpha-hydroxypregnenolong glucuronide.