CN110741255A - Urine testing method based on high-throughput mass spectrum for colorectal state - Google Patents
Urine testing method based on high-throughput mass spectrum for colorectal state Download PDFInfo
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Abstract
Methods of assessing -like colorectal polyps, particularly adenomatous polyps, by mass spectrometry-based measurements of metabolites in urine are described in embodiments certain metabolites are identified as having reduced concentrations or amounts in a subject having colorectal polyps as compared to a subject without colorectal polyps.
Description
Cross-reference to related applications:
priority of U.S. provisional patent application serial No. 62/482,004 entitled "Methods of High-throughput mass Spectrometry Based on urea Test for color Cancer Screening" filed on 5.4.2017, which is hereby incorporated by reference in its entirety.
Technical Field
The present disclosure relates to assessing colorectal cancer or colorectal polyps or both by measuring metabolites in urine.
Background
Colorectal cancer (CRC) is a major public health problem because it is classified globally as the third most common form of cancer, with an age-normalized incidence of 17.2 people per 10 million, accounting for almost 8.5% of all cancer deaths. It is also the third leading cause of cancer-related death in the western world. In 2016, the american cancer society estimated that there would be 95,270 new cases of CRC, 39,220 new cases of colorectal cancer and 49,190 deaths of colon or rectal cancer in the united states. In 2016, the canadian public health agency estimated that 26,100 canadians were diagnosed with CRC, which was the cause of 9,000 deaths. CRC occurs not only in humans but also in animal species, and occurs in both sexes. Among humans, nine-tenths of people diagnosed with CRC are over 50 years of age. However, CRC can also occur in young individuals.
CRC can be largely prevented by both population-based and individual-based screening programs. The chances of survival of CRC are closely related to the stage of the disease at diagnosis; the earlier the diagnosis, the greater the likelihood of survival. Although CRC and colorectal polyps are unique conditions, CRC is in many cases preceded by colorectal polyps, especially adenomatous colorectal polyps. CRC is more likely to be cured if found early in the colorectal polyp or precancerous stage. Thus, subjects with CRC and/or colorectal polyps would greatly benefit from early diagnosis.
Current CRC screening methods consist of items or a combination of items selected from Fecal Occult Blood Test (FOBT), flexo sigmoidoscopy, air-contrast barium enema (air-contrast barnium enema), Computed Tomography Colonography (CTC), and/or colonoscopy.
Colonoscopy is the standard test currently used to determine whether CRC and colorectal polyps are present. However, colonoscopy is expensive, invasive, and may pose unnecessary hazards and risks due to sedation or the procedure itself. Complications of colonoscopy include perforation, bleeding, respiratory depression, arrhythmia and infection. In addition, colonoscopy requires a significant amount of physical resources and skilled personnel.
The present invention relates to a method for screening for adenomatous polyps, and more particularly to a method for screening for adenomatous polyps, which comprises the steps of a non-invasive CRC screening method is FOBT, however, FOBT is very low in sensitivity in detecting adenomatous polyps based on the assumption that cancer will bleed and thus can be detected in stool using chemical or immunological assays, and involves a rough test for heme peroxidase-like activity in hemoglobin, however, several factors limit the effectiveness of stool-based testing methods as screening tests.
CTC or virtual colonoscopy is the latest non-invasive technique for colon imaging. However, their performance varies mainly due to technical differences in subject preparation and hardware and software for analysis. Other limitations of CTCs include high False Positive (FP) readings, failure to detect flat adenomas, failure to remove polyps, repetitive and cumulative radiation doses, and cost.
With the advancement of CRC-related molecular pathology, several new screening methods based on DNA analysis of stool samples have been available. These are typically Polymerase Chain Reaction (PCR) -based assays for identifying mutations known to occur in the adenoma to carcinoma series or familial CRC. Commonly screened genetic mutations include KRAS, TP53, APC and detection of microsatellite instability and hypermethylated DNA. However, whether genomics-based testing would result in high diagnostic accuracy of sporadic CRC remains to be observed.
Accordingly, there is a strong need to develop improved methods of assessing the status of CRC or colorectal polyps or both in a subject.
SUMMARY
In certain metabolites are identified as having a reduced concentration or amount in a subject having or both CRC and colorectal polyps as compared to a subject without CRC or colorectal polyps.
The present disclosure provides a clinically scalable (high throughput, low cost and high sensitivity) urine-based test for detecting adenomatous polyps, which would be a suitable tool for population-based CRC screening.
in some embodiments of , there is provided a method for assessing whether a subject is suffering from or susceptible to colorectal polyps, the method comprising (a) providing a urine sample from the subject, (b) obtaining a metabolite profile from the urine sample, (c) comparing the metabolite profile to a reference metabolite profile, (d) assessing whether the subject is suffering from or susceptible to colorectal cancer and/or colorectal polyps based on the comparison in step (c), wherein the metabolite profile is obtained using mass spectrometry.
In some embodiments the method may comprise in step (b) obtaining the metabolic profile by measuring the concentration of or more metabolites in the urine sample to produce the metabolite profile of the subject, and in step (c) determining the concentration of the corresponding metabolite in the urine of an individual in a reference population, step (b) comprises measuring the concentration of at least any one of 1, 2, 3, 4, 5, 6, 7, 8, 9 or 10 metabolites selected from succinic acid, ascorbic acid, carnitine, creatine, citric acid, creatine, pantothenic acid, fumaric acid, 1-methylnicotinamide, and trigonelline, step (b) comprises measuring the concentration of at least any one of or more metabolites selected from the group 2 metabolites of the urine sample selected from the group consisting of creatine, carnitine, creatine, 1-methylnicotinamide, and trigonelline, and a serological analysis of the urine, wherein the concentration of the citrate is determined by a chemiluminescence, folate, or folate, and the results of the clinical, the results of the test, clinical, or clinical, use of the kit, or method, or kit, or method, or kit.
in some embodiments there is provided a method for identifying a urine metabolite indicative of the presence or absence of colorectal polyps, the method comprising (a) providing a urine sample from a subject, (b) obtaining a metabolite profile from the urine sample, (c) comparing the metabolite profile to a reference metabolite profile, (d) identifying or more metabolites in the metabolite profile based on the comparison in step (c), the or more metabolites being indicative of the presence of colorectal polyps in the subject or predisposition to developing colorectal polyps in the subject, wherein the metabolite profile is obtained using mass spectrometry.
In some embodiments of , the method can include wherein the reference metabolite spectrum is obtained using or more methods selected from the group consisting of nuclear magnetic resonance spectroscopy, high performance liquid chromatography, thin layer chromatography, electrochemical analysis, mass spectrometry, liquid chromatography-mass spectrometry, refractive index spectroscopy, ultraviolet spectroscopy, fluorescence analysis, radiochemical analysis, near infrared spectroscopy, gas chromatography, and light scattering analysis, wherein the identification is further performed using a clinical characteristic of the subject, wherein the clinical characteristic is selected from the group consisting of age, gender, smoking status, and combinations thereof, wherein the identification is performed using an algorithm, wherein the algorithm is a LASSO algorithm.
in some embodiments of , a kit is provided for assessing whether a subject has or is predisposed to having colorectal polyps using mass spectrometry, the kit comprising one or more reagents for detecting the presence and/or concentration and/or amount of one or more metabolites in a urine sample of the subject, and instructions for using the kit to assess whether the subject has or is predisposed to having colorectal polyps.
In some embodiments of , the kit can comprise wherein the or more metabolites are selected from the group consisting of succinic acid, ascorbic acid, carnitine, creatine, citric acid, methylamine, pantothenic acid, fumaric acid, 1-methylnicotinamide, trigonelline, and combinations thereof.
in some embodiments of , there is provided the use of a metabolite profile (including or more of the following metabolites: succinic acid, ascorbic acid, carnitine, creatine, citric acid, methylamine, pantothenic acid, fumaric acid, 1-methylnicotinamide, and trigonelline) for assessing whether a subject is suffering from or susceptible to rectal polyps.
In embodiments, there is provided use of a urine metabolite profile (the urine metabolite profile comprising or more metabolites selected from the group consisting of succinic acid, ascorbic acid, carnitine, creatine, citric acid, methylamine, pantothenic acid, fumaric acid, 1-methylnicotinamide, and trigonelline) for assessing whether a subject is suffering from or susceptible to CRC and/or colorectal polyps.
in some embodiments of there is provided a system comprising (a) a colorectal polyp assessment device comprising a control unit and a storage unit to assess the colorectal polyp status of a subject, and (b) an information communication terminal device communicatively connected to each other to provide data on the presence and/or concentration and/or amount of a metabolite in a urine sample of the subject, wherein the data is obtained using mass spectrometry, wherein the information communication terminal device comprises (a) a data transmitting unit to transmit data on the presence and/or concentration and/or amount of the metabolite in a sample to the colorectal polyp assessment device, and (b) an assessment result receiving unit to receive an assessment result of the colorectal polyp status of the subject transmitted from the colorectal polyp assessment device, wherein the control unit of the colorectal polyp assessment device comprises (a) a data-receiving unit to receive data on the metabolite concentration and/or amount of the sample transmitted from the information communication terminal device, (b) a discrimination value calculating unit to receive data on the metabolite concentration and/or amount of the metabolite stored in the sample as a discrimination result of the subject, and (c) to calculate a discrimination value calculated by the discrimination value calculating unit based on the metabolic discrimination result of the stored in the sample and the subject's judgment result of the stored in the judgment unit.
in some embodiments of there is provided a method for identifying and assessing the effectiveness of a pharmaceutical and/or surgical and/or physical treatment against colorectal polyps, the method comprising (a) providing a th urine sample from a subject having colorectal polyps, (b) obtaining a metabolite profile from the th urine sample, wherein the th metabolite profile is obtained using mass spectrometry, (c) administering or more candidate drugs and/or performing or more physical or surgical treatments to or on the subject, (d) providing a second urine sample from the subject, (e) obtaining a metabolite profile from the second urine sample, wherein the second metabolite profile is obtained by mass spectrometry, (f) comparing the metabolite profiles obtained in steps (b) and (e) to a reference metabolite profile, and (g) assessing whether the or more candidate drugs and/or treatment against colorectal polyps and/or colorectal polyps based on the comparison in step (f).
Brief Description of Drawings
In the accompanying drawings, which illustrate embodiments of the invention by way of example only:
figure 1 depicts a representative liquid chromatography-mass spectrometry combination (LCMS) of calibrator 6 (a standard mixture of succinic acid, ascorbic acid, carnitine and corresponding internal standards);
FIG. 2 depicts a representative plate map (plate map) in which the LCMS series is performed vertically.
FIG. 3 is a graph depicting the final MS-based polypDx using three metabolites and three clinical features on (A) training data and (B) test data (including performance of stool-based tests)TMPerformance of the predictor;
figure 4 depicts the passsing and babuk regression analyses of the MS quantification for NMR quantification data for succinic acid (N685; concentration range 0-362 μmol/L; pearson correlation coefficient r 0.862, P < 0.0001). (A) Scatter plots with regression lines and regression line confidence bands. The identity line is a dashed line. Regression line equation: y is 4.17+1.32 x; the 95% CI for intercepts 2.72 to 5.33 and slopes 1.26 to 1.38 represent smaller constants and smaller proportional differences. Cusum linearity test showed significant deviation from linearity (P < 0.01). (B) The residual map shows the distribution of differences around the fitted regression line;
figure 5 depicts the passsing and babuk regression analyses for MS quantification of ascorbic acid NMR quantitative data (N685; concentration range 0-13368 μmol/L; pearson correlation coefficient r 0.800, P < 0.0001). (A) Scatter plots with regression lines and regression line confidence bands. The identity line is a dashed line. Regression line equation: y is 2.50+1.12 x; the 95% CI for an intercept of 2.50 to 2.50 and a slope of 1.06 to 1.19 indicates a smaller constant and a smaller proportional difference. Cusum linearity test showed significant deviation from linearity (P < 0.01). (B) The residual map shows the distribution of differences around the fitted regression line; and
figure 6 depicts the MS quantitative pasing and babuk regression analysis against NMR quantification data for carnitine (N685; concentration range 0-948 μmol/L; pearson correlation coefficient r 0.921, P < 0.0001). (A) Scatter plots with regression lines and regression line confidence bands. The identity line is a dashed line. Regression line equation: y is 1.73+0.99 x; the 95% CI with an intercept of 0.77 to 2.50 and a slope of 0.96 to 1.02 represents a smaller constant and a smaller proportional difference. Cusum linearity tests showed a significant deviation from linearity (P ═ 0.04). (B) The residual plot shows the distribution of differences around the fitted regression line.
Detailed description of the invention
Metabolics and assessment of CRC or colorectal polyps
Metabolomics is an emerging field of research downstream of genomics, proteomics, and transcriptomics.there are 40,000 metabolites in humans, the concentrations of which can provide a snapshot of the current health status of an individual.metabolome is a quantitative collection of low molecular weight compounds produced by metabolism (such as metabolic substrates and products, lipids, small peptides, vitamins, and other protein cofactors). metabolome is downstream of transcriptomes and proteomics, and thus any changes that occur from normal states are amplified and are numerically easier to handle.
In general, urine metabolomics represents less invasive test methods compared to tissue or serum metabolomics.
The present invention uses urine metabolomics to identify subjects having or at risk of developing CRC and/or colorectal polyps. This is beneficial in both prophylactic and therapeutic terms in the management of risk of CRC and/or colorectal polyps. The use of urine metabolomics in the present invention has a number of potential benefits. Urine is sterile, readily available in large quantities, substantially free of interfering proteins or lipids, and chemically complex. There are more than 2,651 metabolites in human urine samples, including amino acids, nucleic acids, carbohydrates, organic acids, vitamins, lipids, minerals, food additives, drugs, toxins, pollutants and other chemicals ingested, metabolized, catabolized or exposed by humans (molecular weight < 2000D). Urine is more cost effective than existing methods of assessing the presence or absence of CRC or colorectal polyps, the present invention also allows for monitoring of an individual's susceptibility to CRC prior to or in conjunction with conventional screening methods, and provides population-based monitoring of CRC and/or colorectal polyps.
The output of such analytical techniques can be further analyzed using multivariate analysis such as Principal Component Analysis (PCA), partial least squares discriminant analysis (PLS-DA), and Orthogonal Partial Least Squares (OPLS) susceptibility, or more of the metabolome spectra obtained from the described analyses based on a reference population of known CRC and/or colorectal polyp states can be used as a reference for assessing the presence or absence of CRC or colorectal polyps in a subject or for the presence or absence thereof.
In the present disclosure, methods are described for diagnosing CRC, -like colorectal polyps and, in particular, adenomatous polyps by LCMS-based measurement of metabolites in urine, such development of the methods can be performed by (a) generating a metabolomic library of a reference population that can be composed of healthy subjects (i.e., subjects known or otherwise assessed as not containing CRC and/or colorectal polyps) and subjects who have been determined to be suffering from or susceptible to CRC or colorectal polyps, (b) identifying specific metabolic biomarkers associated with CRC or colorectal polyps, (c) developing an analytical method that quantifies the concentration of the identified metabolites in urine, (d) developing an algorithm that can predict whether a subject is suffering from or susceptible to CRC and/or colorectal polyps based on the quantified metabolite concentration values.
Providing and processing urine samples
Urine samples can be collected by known protocols from subjects known to have or suspected of having CRC or colorectal polyps as well as subjects without CRC or colorectal polyps. Subjects of the invention include amphoteric animal species, including humans, susceptible to CRC and/or colorectal polyps.
In addition to providing a urine sample, subjects may be subjected to FOBT, Fecal Immunoassay (FIT) and/or colonoscopy, the results of which may be used to determine a classification of the subject into groups subjects without CRC and/or colorectal polyps (normal group), subjects with colorectal polyps of -fold (polyp group), pathology of excised surgical specimens may be used as a standard to classify subjects as having CRC (CRC group). related clinical information, such as age, sex, family history, co-morbidities, medications, etc., may be obtained from study questionnaires and the subject's chart, which may also be used to determine a classification of the subject.
The urine sample may be collected from the subject at any time (e.g., during routine screening or in conjunction with regular examination or visits, or prior to or concurrent with administration of treatment (such as administration of a drug or surgery), the urine sample may be collected times or more for individual or combined analysis, e.g., 15-700ml at a time, the size and shape of the urine sample collection container may be different, but desirably may contain, e.g., 20-1,000ml of urine sample.
For example, as Edmonton, Canada regional colon cancer screening program (Stopping colorectal cancer by prophylaxis and education) section , 986 urine samples had been collected previously, subjects with an average or increased risk of colorectal cancer were recruited, on the day of admission, participants provided mid-stream urine samples and completed a demographic survey, colonoscopy was performed 2-6 weeks after urine collection as a reference standard, and if participants were under 40 or over 75 years of age, or had colon or ileal disease found at the time of colonoscopy, they were excluded.
In embodiments, urine samples can be processed prior to analysis.for LCMS collection, for example, simple methods of dilution and filtration can be used for sample preparation urine samples can be centrifuged at 10,000g for 3 minutes.10 μ L of each urine supernatant can then be added to an appropriate container.10 μ L of Internal Standard (ISTD) can be added to each sample to account for matrix effects (matrix effect) and facilitate absolute quantitation.the mixture can then be extracted with 200 μ L of extraction solvent (water containing 10mM ammonium formate, pH3) and filtered through a 0.45 μm filter before injection into the LCMS.
Generating a metabolomic library of a reference population
The reference population can consist of healthy subjects (i.e., subjects known to be free or otherwise assessed as free of CRC and/or colorectal polyps) and subjects who have been determined to be suffering from or susceptible to CRC or colorectal polyps or both.
In embodiments, Edmonton, Canada regional colon cancer screening program ((R))Stopping colorectal cancer by prevention and education) 685 urine samples were previously taken.colonoscopy and pathology were performed to confirm whether the enrolled participants were normal or had polyps.there are multiple types of colorectal polyps.while CRC and adenomatous polyps were in different states, adenomatous polyps are known to be precursors of mature CRC.
TABLE 1 reference statistical data
the quantification of metabolites, e.g. in concentration or absolute amounts, can be performed once analytical data are available, e.g. but not limited to GCMS, LCMS, HPLC, NMR spectroscopy, TLC, electrochemical analysis, refractive index spectroscopy, UV spectroscopy, fluorescence analysis, radiochemical analysis, near infrared spectroscopy and light scattering analysis.
In embodiments, 70 metabolites are quantified by NMR on 685 urine samples this was first done in 2010 using the targeted spectroscopic analysis technique of Chemomx NMR Suite v7.7 (Chemomx, Inc., Edmonton, Canada.) in a subsequent consistency study, re-quantification was done using the same NMR spectroscopy and the same protocol but by different operators at different time points.
Identifying specific metabolomic biomarkers associated with CRC or colorectal polyps.
The quantitative data can be used to identify reference metabolite profiles and set criteria for determining said metabolite profiles based on urine samples obtained from subjects known to be free of CRC and/or colorectal polyps.
In embodiments, 13 of the 70 metabolites that were rated "poor" were removed in order to have a more robust dataset to begin and minimize potential misleading results when combined with data analysis over time (i.e., batch effect). in addition, no consideration was given to any metabolite (e.g., 3-hydroxymandelic acid) with a sample size of 0 of more than 20%.
Table 2: the first 10 p values of the metabolites in the NMR data obtained using Wilcoxon rank sum test were used.
p-value | Metabolites |
0.0059 | Succinic acid |
0.0100 | Ascorbic acid |
0.0280 | Carnitine |
0.0595 | Creatine |
0.0739 | Citric acid |
0.0861 | Methylamine |
0.0945 | Pantothenic acid |
0.1198 | Fumaric acid |
0.1346 | 1-methylnicotinamide |
0.1703 | Trigonelline |
In general, the more metabolites that are evaluated, the more accurate the assessment of CRC and/or colorectal polyps, in exemplary embodiments, more than 70 metabolites are contemplated, and 3 metabolites may be used to assess whether a subject is suffering from or susceptible to CRC or colorectal polyps.
An assay was developed to quantify the concentration of the identified metabolites in urine.
Analytical techniques that make it possible to obtain a metabolite profile from a urine sample may include, but are not limited to, or combinations of Mass Spectrometry (MS) in combination with Gas Chromatography (GCMS) or Liquid Chromatography (LCMS), HPLC, NMR spectroscopy, thin layer chromatography, electrochemical analysis, refractive index spectroscopy, ultraviolet spectroscopy, fluorescence analysis, radiochemical analysis, near infrared spectroscopy, and light scattering analysis.
In embodiments, targeted liquid chromatography-mass spectrometry (LCMS/MS) methods can be developed to quantitatively analyze key metabolites (e.g., succinic acid, ascorbic acid, and carnitine) in urine samples using Multiple Reaction Monitoring (MRM), obtaining commercially available standards for succinic acid, ascorbic acid, and carnitine, in addition, isotopically labeled internal standards succinic acid-D4, ascorbic acid-13C, and carnitine-D9. stock solutions of individual compounds are prepared by dissolving appropriate amounts of the standards in MS grade water, calibration solutions (Cal1-Cal 56) at concentrations of 5 μ M, 10 μ M, 100 μ M, 200 μ M, 400 μ M, 600 μ M, 800 μ M, and 1000 μ M are prepared by mixing the stocks of succinic acid, ascorbic acid, and carnitine in water, calibration solutions (Cal1-Cal 56) containing isotopically labeled internal standards of 100 μ M succinic acid-D4, 200 μ M, and 13 μ M ascorbic acid and 1000 μ M are prepared by mixing the stock solutions in water, and storing the internal standard solutions (isd 5980C).
In embodiments, MS parameter optimization can be performed on AB Sciex 4000Qtrap using a standard solution of 5 μ M compound in 1:1 water acetonitrile buffer (containing 0.1% formic acid) for each metabolite, two of the most abundant MRM pairs can be selected for each compound, and the corresponding MS parameters such as Declustering Potential (DP), Collision Energy (CE), and Collision Cell Exit (Collision Cell Exit) (CXP). Table 3 summarizes all MS parameters.
Table 3. optimized MS parameters for each compound. MRM pair 1 was used for quantitative analysis and MRM pair 2 was used for identification.
Compound (I) | Polarity | Q1 | Q3 | DP | CE | CXP |
Succinic acid 1 | - | 117.0 | 73.0 | -40 | -16 | -1 |
Succinic acid 2 | - | 117.0 | 55.1 | -40 | -22 | -7 |
Succinic acid-D4 | - | 121.0 | 77.0 | -40 | -16 | -1 |
Ascorbic acid 1 | - | 175.0 | 114.9 | -45 | -18 | -7 |
Ascorbic acid 2 | - | 175.0 | 86.8 | -45 | -28 | -13 |
Ascorbic acid-13C | - | 176.0 | 116.0 | -45 | -18 | -7 |
Carnitine 1 | + | 162.1 | 103.1 | 51 | 25 | 6 |
|
+ | 162.1 | 43.2 | 51 | 47 | 6 |
Carnitine-D9 | + | 171.0 | 103.0 | 51 | 25 | 6 |
In embodiments, LCMS spectra can be obtained on AB Sciex 4000Qtrap paired with Agilent UHPLC 1290 isocratic LC separation of targeted metabolites (succinic acid, ascorbic acid and carnitine) can be performed on a Waters acquisition UPLC 18 column (2.1mM x 150mM, 1.7 μm) using 95:5 water acetonitrile (10mM ammonium formate, pH3) for mobile phase (flow rate of 0.3 ml/min.) injection volume can be 5 μ L for total LC run time of 3 minutes MRM detection is under optimal parameters for each analyte.
The LCMS analysis can be performed on unlabeled urine, labeled urine, and labeled urine samples in triplicate in . the recovery and accuracy of extraction for each metabolite are calculated and summarized in Table 4. all metabolites are in the range of 90% -110%.
Table 4. recovery and accuracy of extraction for each metabolite.
Metabolites | Recovery (%)a | Accuracy (%)b |
Succinic acid | 101.0 | 110.2 |
Ascorbic acid | 93.8 | 98.7 |
Carnitine | 93.1 | 102.7 |
a. Recovery (%) — (response (spiked sample))/(response (spiked sample)) x 100
b. Accuracy (%) - (spiked sample-untagged sample)/(spiked quantity) x 100
For example, 986 urine samples were randomly assigned and run using an LCMS method developed with a 96-well plate format, each plate contained 1 blank, 1 ISTD, 8 calibrators, 6 QC (pooled urine samples generated in the laboratory) and 80 participant urine samples representative plate maps are shown in fig. 2 for each plate sets of calibration curves were generated and used, a linear regression (R2) of all plates for 3 metabolites was greater than 0.99. LLOQ at the calibration point where 5uM was the lowest, metabolite concentrations below LLOQ were half-replaced with at the limit of detection for statistical analysis, 6 QC samples were placed into each plate to obtain the coefficient of variation (CV%) between the plate and 13 different plates.cv% of each metabolite within each plate was calculated as the standard deviation and summarized in table 5. the average of each metabolite concentration in QC sample was found to be within 15%. the average of each metabolite concentration in the succinic acid, 13. the ascorbic acid concentration in the plate, . the average concentration of each metabolite is found in the alcaline test range.
TABLE 5 CV% of QC samples for each metabolite in each plate.
Developing an algorithm that predicts whether a subject is suffering from or susceptible to CRC and/or colorectal polyps
The level of a particular metabolite above or below a certain threshold (either concentration or amount) may indicate a generalized CRC or colorectal polyp, particularly an adenomatous polyp, the concentration or amount of the metabolite may be interpreted independently using separate cutoff values for each metabolite, or they may be interpreted in total .
A multivariate statistical analysis can be applied to the collected data or complex spectral data to identify differences that occur between sets of datasets obtained from urine samples the metabolite measurements of subjects with generic CRC or colorectal polyps, or particularly adenomatous polyps, can be compared to the metabolite measurements of samples of subjects without CRC or colorectal polyps to identify metabolites that contribute significantly to distinguishing between different groups.
After determining which specific metabolites are important contributors to data separation between the CRC and normal group samples or the polyp group and normal group samples or the adenoma group and normal group samples, or more spectra of these specific metabolites can be established or more metabolite spectra or a combination thereof can be used as reference metabolite spectra to assess -like CRC or colorectal polyps or particularly adenomatous polyps in a subject.
In some embodiments of , the first 10 metabolites useful for separating the normal group from the polyp group are identified as succinic acid, ascorbic acid, carnitine, creatine, citric acid, methylamine, pantothenic acid, fumaric acid, 1-methylnicotinamide, and trigonelline.
In order to determine which specific metabolites are the strongest contributors to data separation between CRC and normal group samples or between polyp and normal group samples or between adenoma and normal group samples, a further step of data analysis may be performed.
Mathematical methods for correlating metabolite combinations with disease occurrences may employ methods such as, but not limited to, Discriminant Analysis (DA) (i.e., linear, quadratic, regularized DA), kernel methods (i.e., SVM), non-parametric methods (i.e., k-nearest neighbor classifiers), PLS (partial least squares), tree-based methods (i.e., logistic regression, CART, random forest methods, enhancement/bagging methods), -sense linear models (i.e., logarithmic regression), principal component-based methods (i.e., SIMCA), -sense additive models, fuzzy logic-based methods, neural network and genetic algorithm-based methods.
When comparing test results of two different populations (e.g., diseased and not), perfect separation between the two groups is rarely observed-in fact, the distributions of test results overlap, so when selecting and applying cutoff or standard values that distinguish the two populations, the disease will be correctly classified as positive (true positive score) in cases, but disease cases will be classified as negative (false negative score). on the other side some disease-free cases will be correctly classified as negative (true negative score) and some disease-free cases will be classified as positive (false positive score).
Tools such as ROC curve analysis can be used to assess the performance of such tests, or to test the accuracy of distinguishing disease groups from healthy groups. The ROC curve is a graphical representation of sensitivity and specificity spectra generated using sensitivity as the y-axis, 1-specificity as the x-axis, and various cut-offs. In the ROC curve, the true positive rate (sensitivity) is plotted as a function of FP rate (100-specificity) for different cut-off points. Each point on the ROC curve represents a sensitivity/specificity pair corresponding to a particular decision threshold. The ROC curve for the test with perfect discriminatory power (no overlap in the two distributions) passes through the upper left corner (sensitivity 100%, specificity 100%). Thus, qualitatively, the closer the graph is to the upper left corner, the higher the overall accuracy of the test. The area under the ROC curve (AUC) reflects the accuracy of the test and is shown in the lower left corner of the graph.
The predictor's ability to predict the markers for new unlabeled instances can be evaluated using standard machine learning methods that apply external datasets two thirds of the training data and one third of the testing data of the two datasets can be balanced according to age, gender and rank distribution in instances, MS quantification is logarithmically transformed and used in conjunction with three clinical features (age, gender and smoking status) and labels (particularly "polyps" or "normals") to train the predictor using the LASSO algorithm unlike previous studies where GI bleeding features are not used in the predictor, because, regardless of the outcome of the prediction algorithm, patients who are bleeding from the colon will relay a colonoscopy.
In addition, the ability to develop multi-analyte panels using the single MS method can save more time, labor, and expense, which is good examples of immunosuppressant assays.
The prediction threshold of the developed algorithm can be adjusted to change the trade-off between sensitivity and specificity. As sensitivity increases, more samples are predicted to be positive (i.e., a colonoscopy is required). At the same time, the specificity is reduced. To optimize predictors for a particular market, the requirements of test sensitivity, specificity, or prediction rate must be met. For example, PolypDxTMThe predicted performance of the test was compared to the given requirements. Selecting training data results (along RO)C-curve) and then evaluated against the test data set the results are summarized in table 6 the thresholds for the tests are sensitivity 70%, 80% and 90%, and specificity 70%, 80% and 90%.
Table 6. extrapolatable nature of the prediction thresholds from training set to test set when choosing the thresholds for the training set, performance for the test set with the same thresholds would yield similar performance.
Prediction rate ═ true positives/test positives
This is repeated 100 times, in 100 permutation tests, no AUC values are better than 0.692 based on the original un-permuted data, this supports the predictor performance not being the result of random chance, i.e., the chance of invalid hypothesis (only by chance we will see 0.692 AUC performance) is p < 0.01.
In embodiments, the reference metabolic profile can relate to assessing whether a subject is suffering from or susceptible to CRC and includes measurements of concentrations of at least any 1, 2, 3, 4, 5, 6, 7, 8, 9, or 10 metabolites selected from the group consisting of succinic acid, ascorbic acid, carnitine, creatine, citric acid, methylamine, pantothenic acid, fumaric acid, 1-methylnicotinamide, and trigonelline in a urine sample.
Although the examples provided herein indicate that the three metabolites may be most relevant, but not necessarily means that they must be included to make the method predictive, in various embodiments, the reference spectrum for detecting CRC may include or more metabolites from the group of metabolites selected from:
a. succinic acid, ascorbic acid, carnitine, creatine, citric acid, methylamine, pantothenic acid, fumaric acid, 1-methylnicotinamide and trigonelline;
b. succinic acid, ascorbic acid, carnitine, creatine, citric acid, methylamine, pantothenic acid, fumaric acid and 1-methylnicotinamide;
c. succinic acid, ascorbic acid, carnitine, creatine, citric acid, methylamine, pantothenic acid and fumaric acid;
d. succinic acid, ascorbic acid, carnitine, creatine, citric acid, methylamine, and pantothenic acid;
e. succinic acid, ascorbic acid, carnitine, creatine, citric acid and methylamine;
f. succinic acid, ascorbic acid, carnitine, creatine and citric acid;
g. succinic acid, ascorbic acid, carnitine and creatine;
h. succinic acid, ascorbic acid and carnitine;
i. succinic acid and ascorbic acid;
j. succinic acid.
In embodiments of the invention, the measured is the concentration of a metabolite in urine (e.g., measured in μ M), and a higher or lower concentration of the metabolite in the urine of the test subject (based on the original or normalized concentration) relative to the concentration in the reference metabolite spectrum is indicative of colorectal polyps.
In embodiments, a decreased concentration of any or more metabolites selected from the group consisting of succinic acid, ascorbic acid, carnitine, creatine, citric acid, methylamine, pantothenic acid, fumaric acid, 1-methylnicotinamide, and trigonelline indicates that the subject is suffering from or susceptible to rectal polyps.
It will be understood that by "reduced" is meant that the concentration of a metabolite in the urine of a subject who has developed or is predisposed to develop colorectal polyps is lower than the concentration of said metabolite in the urine of a subject who has not developed or is not predisposed to develop colorectal polyps.
The reference metabolite profile that is diagnostic of colorectal polyps may be different from the reference metabolite profile of CRC itself-that is, the reference diagnostic profile may consist of different sets of related metabolites, and different relative concentrations of these metabolites may be relevant.
In certain embodiments, the reference metabolite profile may be for colorectal polyps, such as adenomatous polyps, and include concentrations of at least any 1, 2, 3, 4, 5, 6, 7, 8, 9, or 10 metabolites selected from: succinic acid, ascorbic acid, carnitine, creatine, citric acid, methylamine, pantothenic acid, fumaric acid, 1-methylnicotinamide and trigonelline.
In embodiments, a reduced concentration of any or more metabolites selected from the group consisting of succinic acid, ascorbic acid, carnitine, creatine, citric acid, methylamine, pantothenic acid, fumaric acid, 1-methylnicotinamide, and trigonelline indicates that the subject is suffering from or susceptible to adenomatous polyps.
In embodiments, the reference metabolite profile is designed to identify subjects suffering from or susceptible to colorectal polyps, but not necessarily distinguish types of polyps from another types of polyps.
In certain embodiments, the reference metabolite profile may be for a colorectal polyp that is an adenomatous polyp or a hyperplastic polyp and includes urine concentrations of at least any 1, 2, 3, 4, 5, 6, 7, 8, 9, or 10 metabolites selected from the group consisting of: succinic acid, ascorbic acid, carnitine, creatine, citric acid, methylamine, pantothenic acid, fumaric acid, 1-methylnicotinamide and trigonelline.
Thus, if less than all of the above 10 metabolites are contained in the reference metabolite spectrum, then the spectrum may comprise or more metabolites from the group of metabolites selected from:
a. succinic acid, ascorbic acid, carnitine, creatine, citric acid, methylamine, pantothenic acid, fumaric acid, 1-methylnicotinamide and trigonelline;
b. succinic acid, ascorbic acid, carnitine, creatine, citric acid, methylamine, pantothenic acid, fumaric acid and 1-methylnicotinamide;
c. succinic acid, ascorbic acid, carnitine, creatine, citric acid, methylamine, pantothenic acid and fumaric acid;
d. succinic acid, ascorbic acid, carnitine, creatine, citric acid, methylamine, and pantothenic acid;
e. succinic acid, ascorbic acid, carnitine, creatine, citric acid and methylamine;
f. succinic acid, ascorbic acid, carnitine, creatine and citric acid;
g. succinic acid, ascorbic acid, carnitine and creatine;
h. succinic acid, ascorbic acid and carnitine;
i. succinic acid and ascorbic acid; and
j. succinic acid.
In , a reduced concentration of any or more metabolites selected from the group consisting of succinic acid, ascorbic acid, carnitine, creatine, citric acid, methylamine, pantothenic acid, fumaric acid, 1-methylnicotinamide, and trigonelline indicates that the subject is suffering from or susceptible to colorectal polyps, which may be adenomatous or hyperplastic polyps.
Assessing whether a subject is suffering from or susceptible to CRC and/or colorectal polyps
The present invention provides a method of assessing whether a subject is suffering from or susceptible to CRC and/or colorectal polyps, the method comprising: (a) providing a urine sample from the subject; (b) obtaining a metabolite profile from the urine sample; (c) comparing the metabolite profile to a reference metabolite profile; and (d) assessing whether said subject is suffering from or susceptible to CRC and/or colorectal polyps based on said comparison in step (c).
Urine samples may be obtained as described above. As described above, the metabolite profile from the subject comprises the corresponding information about the urine sample of the subject as comprised in the selected reference metabolite profile. Comparison of a metabolite profile from a subject with a reference metabolite profile allows assessment of whether the subject is suffering from or susceptible to CRC and/or colorectal polyps.
By way of example only, the method may be a method for assessing whether a subject is suffering from or susceptible to CRC and/or colorectal polyps.A sample of urine may be taken and the concentration of each of succinic acid, ascorbic acid, carnitine, creatine, citric acid, methylamine, pantothenic acid, fumaric acid, 1-methylnicotinamide, and trigonelline may be measured.the concentration of each of these metabolites in the urine of the subject is then compared to the concentration of the corresponding metabolite in a reference metabolite spectrum.detection of any or more of succinic acid, ascorbic acid, carnitine, creatine, citric acid, methylamine, pantothenic acid, fumaric acid, 1-methylnicotinamide, and trigonelline in the metabolite spectrum of the subject below the reference metabolite spectrum may indicate that the subject is suffering from or susceptible to CRC and/or colorectal polyps.
Diagnostic kit
Such kits may comprise one or more reagents for detecting the presence and/or concentration of one or more metabolites in a urine sample from a subject, and may include instructions for using the kit to assess whether a subject is suffering from or susceptible to CRC and/or colorectal polyps.
In cases, it may be more important than high degree of accuracy for tests that are portable, prepackaged, -time, usable by the subject without assistance or guidance, etc. in many cases, preliminary tests may be performed, even tests with reduced sensitivity and/or specificity may be sufficient, especially with physician visits.
Such kits may take the form of test strips, dipsticks, cartridges, chip-based or bead-based arrays, multi-well plates, or series containers, etc. or more reagents are provided to detect the presence and/or concentration and/or amount of a selected urine metabolite.
In embodiments, a kit can comprise a solid substrate such as a chip, slide, array, or the like, having reagents capable of detecting and/or quantifying or more urine metabolites immobilized at predetermined locations on the substrate as illustrative examples, reagents immobilized at discrete predetermined locations can be provided to the chip for detecting and quantifying the concentration of succinic acid, ascorbic acid, carnitine, creatine, citric acid, methylamine, pantothenic acid, fumaric acid, 1-methylnicotinamide, and trigonelline, any number thereof, or any combination thereof in a urine sample.
System for performing CRC or colorectal polyp assessment
In embodiments, the invention provides a system for assessing whether a subject is suffering from or susceptible to CRC and/or colorectal polyps.
A CRC and/or colorectal polyp assessment apparatus comprising a control unit and a memory unit for assessing a CRC and/or colorectal polyp status of a subject; and
information communication terminal devices communicatively connected to each other, which provide data on the presence and/or concentration and/or amount of a metabolite in a urine sample from a subject,
wherein the information communication terminal device includes:
a data transmission unit which transmits data regarding the presence and/or concentration and/or amount of a metabolite in the sample to a CRC and/or colorectal polyp assessment device; and
an evaluation result receiving unit that receives an evaluation result of the CRC and/or colorectal polyp status of the subject transmitted from the CRC and/or colorectal polyp evaluation device,
wherein the control unit of the CRC and/or colorectal polyp assessment apparatus comprises:
a data receiving unit that receives data on the concentration and/or amount of the metabolite of the sample transmitted from the information communication terminal device;
a discrimination value calculation unit that calculates a discrimination value as a multivariate discrimination value based on the concentration and/or amount value of the metabolite in the sample received by the data reception unit and the multivariate discrimination having the concentration and/or amount of the metabolite as an explanatory variable stored in a storage unit;
a discrimination value criterion evaluation unit that evaluates the CRC or colorectal polyp state in the subject based on the discrimination value calculated by the discrimination value calculation unit; and
an evaluation result transmitting unit that transmits the evaluation result of the subject obtained by the discrimination value reference evaluation unit to an information communication terminal device.
Evaluation of the efficacy of pharmaceutical and/or physical and/or surgical treatments
Metabolomics analysis is a desirable choice for identifying and evaluating the efficacy of potential agents and/or new physical and/or surgical treatments for CRC, colorectal polyps and/or adenomatous polyps through the methods described previously herein, urine samples can be collected or more times from a subject before and after treatment may include or more agents at or more doses to or on a subject and/or or more physical and/or surgical treatments to or on a subject.
Similarly, subjects' comorbidities and drugs can be studied in subsequent analyses to determine their effects on metabolomics test results, particularly whether they have resulted in results other than .
The invention is further illustrated by the following non-limiting example .
Example 1 MS-based metabolomics testing was compared to NMR-based testing.
Concentration values of 685 samples measured by LCMS were compared to NMR quantification using paging and babok regression. The correlation between MS and NMR quantification of each of the three metabolites is shown in FIGS. 4-6. The MS data strongly correlated with the NMR data for all three metabolites (R >0.8, P < 0.01). The regression line equation of ascorbic acid is 2.50+1.12 x; the 95% CI for an intercept of 2.50 to 2.50 and a slope of 1.06 to 1.19 indicates a smaller constant and a smaller proportional difference. The regression line equation of carnitine is 1.73+0.99 x; the 95% CI with an intercept of 0.77 to 2.50 and a slope of 0.96 to 1.02 indicates a small constant and no proportional difference. The regression line equation of succinic acid is 4.17+1.32 x; the 95% CI for intercepts 2.72 to 5.33 and slopes 1.26 to 1.38 represent smaller constants and smaller proportional differences. For all three metabolites, the two methods were different in the 95% CI range; however, the values measured by both methods are comparable.
For test performance comparisons, NMR predictors were also constructed and evaluated using the same analytical workflow for constructing MS predictors. The AUC for NMR measurements was 0.670, slightly lower than AUC 0.692 for MS-based measurements. This may be due to the fact that MS is more sensitive in the lower concentration range.
Example 2 comparison of urine-based metabolomics assays with commercially available feces-based assays
The diagnostic accuracy of the MS-based colonic adenomatous polyp test we developed was compared to three stool-based tests ( stool Guaiac and two stool immunoassays.) the sensitivity and specificity of each test was calculated for the same 685 sample set for adenomatous polyp detectionFecalImmuneAnd Fecal ImmuneTo carry outThe sensitivity of polyp detection of (1) was 2.6%, 13.2% and 17.6%, respectively, and the specificity was 99.0%, 97.1% and 94.2%, respectively. All three stool-based tests have high specificity for polyps, but very low sensitivity (c: (b))<18%), which questions their use in polyp detection and early cancer screening. These stool-based tests focus on the detection of colon cancer, rather than the presence or susceptibility of polyps. MS-based PolypDxTMExhibit much higher sensitivity, are designed specifically for adenomatous polyp detection, and are useful as better population-based screening tools for CRC. Figure 3 also shows the three stool-based tests and MS-based PolypDxTMAll three stool tests were located on/under the ROC curve of the urine-based predictor, indicating MS-based PolypDxTMPredictors are consistently superior to stool detection.
Table 7 summarizes MS-based PolypDxTMMetabolites and clinical features used in the algorithm. The correlation can be calculated by encoding a patient requiring colonoscopy as a "1" and a patient not requiring colonoscopy as a "0". The higher concentration of the 3 metabolites of interest is inversely proportional to the need for colonoscopy (e.g., a lower concentration of each metabolite indicates that the patient is more in need of colonoscopy). Since the gender profile codes for male 1 and female 0, male patients are directly related to the need for colonoscopy (i.e., male is more likely to require colonoscopy). Age is also directly related to colonoscopy, and older patients are more in need of colonoscopy. Finally, the fact that the patient smokes is directly related to the need for colonoscopy (i.e., smokers are more susceptible to polyps). Although the correlation of each feature has no large absolute value, it is important to linearly combine the features by the LASSO algorithm.
TABLE 7 for PolypDxTMMore information on the features used in the MS predictor.
The citation of any publication herein is for its disclosure prior to the filing date and should not be construed as an admission that the present invention is not entitled to antedate such publication by virtue of prior invention.
As used in this specification and the appended claims, the singular forms " (a)", " (an)" and "the" include plural referents unless the context clearly dictates otherwise.
Although the foregoing invention has been described in some detail by way of illustration and example for purposes of clarity of understanding, it will be readily apparent to those of ordinary skill in the art in light of the teachings of this invention that certain changes and modifications may be made thereto without departing from the spirit or scope of the appended claims.
Reference data
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Claims (24)
1, a method of assessing whether a subject is suffering from or susceptible to colorectal polyps, the method comprising:
(a) providing a urine sample from the subject;
(b) obtaining a metabolite profile from the urine sample;
(c) comparing the metabolite profile to a reference metabolite profile; and
(d) assessing whether said subject is suffering from or susceptible to colorectal polyps based on said comparison in step (c);
wherein the metabolite profiles are obtained using mass spectrometry.
2. The method of claim 1, wherein:
in step (b), the metabolic profile is obtained by measuring the concentration of metabolites or more in the urine sample to produce the metabolite profile of the subject, and in step (c), the reference metabolite profile is determined from the concentration of the corresponding metabolite in urine of individuals in a reference population.
3. The method of claim 2, which is a method for assessing whether said subject is suffering from or susceptible to colorectal polyps, and wherein step (b) comprises measuring the concentration of at least any 1, 2, 3, 4, 5, 6, 7, 8, 9, or 10 metabolites selected from the group consisting of: succinic acid, ascorbic acid, carnitine, creatine, citric acid, methylamine, pantothenic acid, fumaric acid, 1-methylnicotinamide and trigonelline.
4. The method of claim 3, wherein step (b) comprises measuring the concentration of at least any or more metabolites of the group metabolites in the urine sample, the group of metabolites being selected from the group consisting of:
(i) succinic acid, ascorbic acid, carnitine, creatine, citric acid, methylamine, pantothenic acid, fumaric acid, 1-methylnicotinamide and trigonelline;
(ii) succinic acid, ascorbic acid, carnitine, creatine, citric acid, methylamine, pantothenic acid, fumaric acid and 1-methylnicotinamide;
(iii) succinic acid, ascorbic acid, carnitine, creatine, citric acid, methylamine, pantothenic acid and fumaric acid;
(iv) succinic acid, ascorbic acid, carnitine, creatine, citric acid, methylamine, and pantothenic acid;
(v) succinic acid, ascorbic acid, carnitine, creatine, citric acid and methylamine;
(vi) succinic acid, ascorbic acid, carnitine, creatine and citric acid;
(vii) succinic acid, ascorbic acid, carnitine and creatine;
(viii) succinic acid, ascorbic acid and carnitine;
(vix) succinic acid and ascorbic acid;
(x) Succinic acid.
5. The method of any of claims 3 to 4, wherein a reduced urine concentration of any or more metabolites selected from the group consisting of succinic acid, ascorbic acid, carnitine, creatine, citric acid, methylamine, pantothenic acid, fumaric acid, 1-methylnicotinamide and trigonelline indicates that the subject is suffering from or susceptible to colorectal polyps.
6. The method of claim 1, wherein said colorectal polyp is an adenomatous polyp or a hyperplastic polyp, and wherein step (b) comprises measuring the concentration of at least any 1, 2, 3, 4, 5, 6, 7, 8, 9, or 10 metabolites selected from the group consisting of: succinic acid, ascorbic acid, carnitine, creatine, citric acid, methylamine, pantothenic acid, fumaric acid, 1-methylnicotinamide and trigonelline.
7. The method of claim 6, wherein step (b) comprises measuring the concentration of at least any or more metabolites of the group metabolites in the urine sample, the group of metabolites being selected from the group consisting of:
(i) succinic acid, ascorbic acid, carnitine, creatine, citric acid, methylamine, pantothenic acid, fumaric acid, 1-methylnicotinamide and trigonelline;
(ii) succinic acid, ascorbic acid, carnitine, creatine, citric acid, methylamine, pantothenic acid, fumaric acid and 1-methylnicotinamide;
(iii) succinic acid, ascorbic acid, carnitine, creatine, citric acid, methylamine, pantothenic acid and fumaric acid;
(iv) succinic acid, ascorbic acid, carnitine, creatine, citric acid, methylamine, and pantothenic acid;
(v) succinic acid, ascorbic acid, carnitine, creatine, citric acid and methylamine;
(vi) succinic acid, ascorbic acid, carnitine, creatine and citric acid;
(vii) succinic acid, ascorbic acid, carnitine and creatine;
(viii) succinic acid, ascorbic acid and carnitine;
(vix) succinic acid and ascorbic acid; and
(vx) succinic acid.
8. The method of any of claim 6 or 7, wherein a decreased urine concentration of any or more metabolites selected from the group consisting of succinic acid, ascorbic acid, carnitine, creatine, citric acid, methylamine, pantothenic acid, fumaric acid, 1-methylnicotinamide and trigonelline as compared to the reference metabolite profile indicates that the subject is suffering from or susceptible to colorectal polyps that are adenomatous or hyperplastic polyps.
9. The method of of any one of claims 1-8, wherein the reference metabolite spectrum is obtained using or more methods selected from the group consisting of nuclear magnetic resonance spectroscopy, high performance liquid chromatography, thin layer chromatography, electrochemical analysis, mass spectrometry, liquid chromatography-mass spectrometry, refractive index spectroscopy, ultraviolet spectroscopy, fluorescence analysis, radiochemical analysis, near infrared spectroscopy, gas chromatography, and light scattering analysis.
10. The method of any of claims 1-9, wherein the assessment is also made by using clinical characteristics of the subject.
11. The method of claim 10, wherein the clinical characteristic is selected from the group consisting of age, gender, smoking status, and combinations thereof.
12. The method of any of claims 1-10, wherein the evaluating is further performed by using an algorithm.
13. The method of claim 12, wherein the algorithm is a LASSO algorithm.
14, a method for identifying a urine metabolite indicative of the presence or absence of a colorectal polyp, the method comprising:
(a) providing a urine sample from a subject;
(b) obtaining a metabolite profile from the urine sample;
(c) comparing the metabolite profile to a reference metabolite profile; and
(d) identifying or more metabolites in said metabolite spectrum that are indicative of the presence of colorectal polyps in said subject or that are susceptible to said colorectal polyps based on said comparison in step (c);
wherein the metabolite profiles are obtained using mass spectrometry.
15. The method of claim 14, wherein the reference metabolite spectrum is obtained using or more methods selected from the group consisting of nuclear magnetic resonance spectroscopy, high performance liquid chromatography, thin layer chromatography, electrochemical analysis, mass spectrometry, liquid chromatography-mass spectrometry, refractive index spectroscopy, ultraviolet spectroscopy, fluorescence analysis, radiochemical analysis, near infrared spectroscopy, gas chromatography, and light scattering analysis.
16. The method of any of claims , wherein the identification is further made by using a clinical characteristic of the subject.
17. The method of claim 16, wherein the clinical characteristic is selected from the group consisting of age, gender, smoking status, and combinations thereof.
18. The method of any of claims 14-17, wherein the identifying is further performed by using an algorithm.
19. The method of claim 18, wherein the algorithm is a LASSO algorithm.
20, a kit for assessing whether a subject is suffering from or susceptible to colorectal polyps using mass spectrometry, the kit comprising or more reagents for detecting the presence and/or concentration and/or amount of or more metabolites in a urine sample of the subject and instructions for using the kit to assess whether a subject is suffering from or susceptible to colorectal polyps.
21. The kit of claim 20, wherein the one or more metabolites are selected from the group consisting of succinic acid, ascorbic acid, carnitine, creatine, citric acid, methylamine, pantothenic acid, fumaric acid, 1-methylnicotinamide, trigonelline, and combinations thereof.
22. Use of a metabolite profile comprising or more of the following metabolites for assessing whether a subject is suffering from or susceptible to colorectal polyps:
succinic acid, ascorbic acid, carnitine, creatine, citric acid, methylamine, pantothenic acid, fumaric acid, 1-methylnicotinamide and trigonelline.
A system of species, comprising:
(a) a colorectal polyp evaluation device comprising a control unit and a storage unit for evaluating a colorectal polyp state of a subject; and
(b) information communication terminal devices communicatively connected to each other providing data on the presence and/or concentration and/or amount of a metabolite in a urine sample from a subject, wherein the data is obtained using mass spectrometry,
wherein the information communication terminal device includes:
(a) a data transmission unit that transmits data regarding the presence and/or concentration and/or amount of a metabolite in the sample to the colorectal polyp assessment device; and
(b) an evaluation result receiving unit that receives an evaluation result of the colorectal polyp state of the subject transmitted from the colorectal polyp evaluation apparatus,
wherein the control unit of the colorectal polyp evaluation device comprises:
(a) a data receiving unit that receives data on the concentration and/or amount of the metabolite of the sample transmitted from the information communication terminal device;
(b) a discrimination value calculation unit that calculates a discrimination value as a multivariate discrimination value based on the concentration and/or amount value of the metabolite in the sample received by the data reception unit and multivariate discrimination having the concentration and/or amount of the metabolite as an explanatory variable stored in the storage unit;
(c) a discrimination value criterion evaluation unit that evaluates the colorectal polyp state in the subject based on the discrimination value calculated by the discrimination value calculation unit; and
(d) an evaluation result transmitting unit that transmits the evaluation result of the subject obtained by the discrimination value reference evaluation unit to the information communication terminal device.
24, a method for identifying and evaluating the effect of a pharmaceutical agent and/or a surgical treatment and/or a physical treatment against colorectal polyps, the method comprising:
(a) providing a urine sample from a subject having a colorectal polyp;
(b) obtaining a metabolite profile from the th urine sample, wherein the th metabolite profile is obtained using mass spectrometry;
(c) administering or more drug candidates and/or or more physical or surgical treatments to or on the subject;
(d) providing a second urine sample from the subject in step (c);
(e) obtaining a metabolite profile from the second urine sample, wherein the second metabolite profile is obtained by mass spectrometry;
(f) comparing the metabolite profile obtained in steps (b) and (e) with a reference metabolite profile; and
(g) assessing whether said one or more drug candidates and/or treatments are effective against colorectal polyps based on said comparing in step (f).
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