WO2022242779A1 - 用于评估腺瘤及结直肠癌风险的生物标志物组合及其应用 - Google Patents

用于评估腺瘤及结直肠癌风险的生物标志物组合及其应用 Download PDF

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WO2022242779A1
WO2022242779A1 PCT/CN2022/094558 CN2022094558W WO2022242779A1 WO 2022242779 A1 WO2022242779 A1 WO 2022242779A1 CN 2022094558 W CN2022094558 W CN 2022094558W WO 2022242779 A1 WO2022242779 A1 WO 2022242779A1
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acid
colorectal cancer
combination
adenoma
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贾伟
谢国祥
周科军
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深圳市绘云生物科技有限公司
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Definitions

  • the invention relates to the field of biotechnology, and relates to a biomarker combination, application and determination method for adenoma and colorectal cancer risk assessment.
  • Colorectal cancer has high morbidity and mortality, but its classic development process follows a slow progression pattern from adenoma-dysplasia-advanced carcinoma, consisting of various genetic and epigenetic mutations over a 10-year period accumulation, leading to the occurrence of colorectal malignancies.
  • Screening objects for colorectal cancer can be divided into general risk groups and high-risk groups with sporadic colorectal cancer, with different screening methods and emphases.
  • the former is defined as people over 40 years old without personal and family history of colorectal cancer, without colorectal adenoma, inflammatory bowel disease and other diseases, and with an average or low risk of cancer; the latter refers to people with Family history or personal history of colorectal cancer, history of intestinal adenoma, long-term unhealed inflammatory bowel disease, and multiple risk factors such as body mass index, smoking and drinking history, diet and exercise are comprehensively judged.
  • Fecal occult blood test is the most widely used screening technology for early diagnosis of colorectal cancer. Its advantages of non-invasiveness and low cost are easy to be accepted by patients. It is mainly used to screen patients who should receive colonoscopy. It is supported by multiple evidence-based medical evidence. However, the sensitivity and specificity of this method are relatively low.
  • the improved occult blood detection method uses anti-human hemoglobin antibody as the primary antibody for immunohistochemical detection of feces.
  • fecal DNA detection can also detect mutated DNA, which has improved sensitivity, but the cost is high and it is difficult to be widely used as a screening method.
  • Hematological tumor markers such as carcinoembryonic antigen (CEA) and carbohydrate antigen 19-9 (CA19-9) are also less sensitive, and it is easy to miss asymptomatic patients; and CEA is not a tumor-specific antigen, but a tumor-associated antigen.
  • CT virtual endoscopy is a new non-invasive examination method produced by the combination of computer virtual reality technology and modern medical imaging. It can replace the gas-barium double-contrast radiography to observe the whole colon, but the sensitivity to the detection of colonic polyps is not as good as that of polyps. There is a direct relationship between the size of the test, and the tested population is exposed to radiation, and the cost of the test is relatively high, so it is still not suitable for natural population screening.
  • Patent CN201611090742.3 provides a kit for auxiliary diagnosis of early colorectal cancer and its use method and detection system.
  • the kit includes nucleic acid separation and purification reagents, DNA sulfite conversion reagents, KRAS gene mutation detection reagents, BMP3 and NDRG4 gene methylation detection reagent, fecal occult blood detection reagent; among them, nucleic acid separation and purification reagents are used to separate and purify human-derived DNA in fecal samples; DNA sulfite conversion reagents are used to purify part of human-derived DNA Perform sulfite conversion for subsequent detection of methylation of BMP3 and NDRG4 genes.
  • similar genetic tests are difficult to distinguish from common colorectal diseases such as colorectal polyps, and the sensitivity and specificity need to be investigated. And it is expensive, and it is difficult to achieve large-scale promotion for disease screening.
  • Patent CN201910446079.3 provides a microRNA biomarker for colorectal cancer, including: encoding hsa-miR-423-5p, encoding hsa-miR-451a, encoding hsa-miR-30b-5p, encoding hsa-miR- 27b-3p, encoding hsa-miR-199a-3p, encoding hsa-let-7d-3p, encoding at least one nucleic acid molecule in hsa-miR-423-5p, the nucleic acid molecules all encode microRNA sequences, and their nucleosides The acid sequence is shown in SEQ ID NO:1-7.
  • These microRNA biomarkers were obtained through pooled sample screening, small sample single validation and large number of sample single validation. However, similar inspections have a large randomness in sampling and low sensitivity for disease detection, making it difficult to use for disease screening.
  • the technical problem to be solved by the present invention is to overcome the defects and deficiencies of the above-mentioned prior art, and provide a combination of diagnostic markers and a determination method thereof for assessing the risk of adenoma and colorectal cancer in a subject.
  • the present invention further provides the use of the diagnostic markers in the preparation of diagnostic products and computer systems for assessing the risk of adenoma and colorectal cancer in a subject.
  • adenoma and colorectal cancer includes the situation of “adenoma or colorectal cancer", that is, in one evaluation or diagnosis process, the purpose of diagnosing or excluding adenoma and colorectal cancer at the same time can also be It is for the purpose of diagnosing or excluding one of them.
  • the "risk” refers to the possibility of the subject suffering from “adenoma and colorectal cancer”.
  • the output of evaluating the risk by the method of the present invention can be a probability value represented by a number, or it can be a probability value in accordance with a preset value.
  • a qualitative expression of "yes” or “no” or similar representations obtained by comparing with a given standard value.
  • the present invention provides technical scheme as follows:
  • the first aspect of the present invention provides a diagnostic product for risk assessment of adenoma and colorectal cancer in a subject, a diagnostic product for risk assessment of adenoma and colorectal cancer in a subject, characterized in that the diagnostic product
  • the diagnostic indicators include one or more of taurocholic acid, fumaric acid, myristic acid, histidine, tyrosine, and 3,4-dihydroxycinnamic acid in the biological sample of the subject, and optionally Include the following combination A or combination B, or both combination A and combination B:
  • Combination A 3-Hydroxyanthranilic acid, guanidinoacetic acid, azelaic acid, suberic acid, phenylpyruvate, acetoacetate, methylcysteine, alpha-hydroxyisobutyric acid, N-methylnicotinamide , salicylic acid, phenylacetic acid, homoserine, glycolic acid, 3-hydroxybutyric acid, phenyllactic acid, methylmalonic acid, succinic acid, 2-hydroxy-2-methylbutyric acid, 4-hydroxyproline, Hydroxypropionic acid, one or more of p-hydroxyphenylacetic acid;
  • Combination B Lysine, Tryptophan, Threonine, Citrulline, Lactic Acid, Carnosine, 2-Hydroxybutyrate, Suberic Acid, 3-Hydroxybutyrate, Glutamine, Pyruvate, Uridine, Succinate Acid, citric acid, aconitic acid, isocitric acid; 2-methylcitric acid, indoleacetic acid, guanidinoacetic acid, azelaic acid, tryptamine, 5-hydroxyindoleacetic acid, spermidine, hippuric acid, benzene Acetic acid, acetoacetic acid, m-hydroxyphenylpropionic acid, glycine, succinic acid, 5-hydroxyindoleacetic acid, p-hydroxyphenylacetic acid, 2-aminobutyric acid, ⁇ -hydroxybutyric acid, cystine, pantothenic acid, ⁇ -aminobutyric acid acid, isoleucine, valine, orni
  • the biological sample is selected from the subject's urine, blood, saliva and feces.
  • the diagnostic product is selected from kits, medical devices, computer systems with diagnostic modules and diagnostic devices.
  • the second aspect of the present invention provides a combination of biomarkers for the risk assessment of adenoma and colorectal cancer in a subject
  • the biomarkers are derived from biological samples of the subject
  • the biological samples include the urine of the subject Differential metabolites in biological samples such as fluid, blood, saliva and feces.
  • whole blood, serum and plasma can be selected.
  • serum derived from peripheral blood can be selected as the biological sample.
  • the present invention selects the subject's urine as the biological sample, so that sampling is easier and the subject's compliance is better.
  • the present invention provides a combination of biomarkers for the risk assessment of adenoma and colorectal cancer in a subject, the biomarkers are differential metabolites in the biological samples of the subject, and the biological samples are selected from urine, blood , saliva and feces; the combination of biomarkers includes one or more of taurocholic acid, fumaric acid, myristic acid, histidine, tyrosine, 3,4-dihydroxycinnamic acid, and any Optionally include the following combination A or combination B, or both combination A and combination B:
  • Combination A 3-Hydroxyanthranilic acid, guanidinoacetic acid, 3,4-dihydroxycinnamic acid, azelaic acid, suberic acid, phenylpyruvate, acetoacetate, methylcysteine, alpha-hydroxyiso Butyric acid, N-methylnicotinamide, salicylic acid, phenylacetic acid, homoserine, glycolic acid, 3-hydroxybutyric acid, phenyllactic acid, methylmalonic acid, succinic acid, 2-hydroxy-2-methylbutyric acid One or more of acid, 4-hydroxyproline, hydroxypropionic acid, p-hydroxyphenylacetic acid;
  • Combination B Lysine, Tryptophan, Threonine, Citrulline, Lactic Acid, Carnosine, 2-Hydroxybutyrate, Suberic Acid, 3-Hydroxybutyrate, Glutamine, Pyruvate, Uridine, Succinate Acid, citric acid, aconitic acid, isocitric acid; 2-methylcitric acid, indoleacetic acid, guanidinoacetic acid, azelaic acid, tryptamine, 5-hydroxyindoleacetic acid, spermidine, hippuric acid, benzene Acetic acid, acetoacetic acid, m-hydroxyphenylpropionic acid, glycine, succinic acid, 5-hydroxyindoleacetic acid, p-hydroxyphenylacetic acid, 2-aminobutyric acid, ⁇ -hydroxybutyric acid, cystine, pantothenic acid, ⁇ -aminobutyric acid acid, isoleucine, valine, orni
  • the biomarkers of the invention include taurocholic acid, fumaric acid, myristic acid, histidine, tyrosine, 3,4-dihydroxycinnamic acid for the purpose of the invention.
  • the biomarker combination of the present invention includes lysine, tryptophan, threonine, histidine, citrulline, tyrosine, lactic acid, carnosine, 2-hydroxybutyrate, octane Diacid, 3-hydroxybutyric acid, glutamine, pyruvic acid, uridine, succinic acid, citric acid, aconitic acid, isocitric acid; 2-methylcitric acid, indole acetic acid, guanidinoacetic acid, azelaic acid, tryptamine, 5-hydroxyindoleacetic acid, spermidine, hippuric acid, phenylacetic acid, acetoacetic acid, m-hydroxyphenylpropionic acid, glycine, succinic acid, 5-hydroxyindoleacetic acid, p-hydroxyphenylacetic acid, 2- GABA, Myristic Acid, Beta-Hydroxybutyrate, Cystine, Pantothenic Acid, Gam
  • the biomarkers include 3-hydroxyanthranilic acid, guanidinoacetic acid, 3,4-dihydroxycinnamic acid, azelaic acid, suberic acid, phenylpyruvate, acetoacetate, Methylcysteine, Alpha-Hydroxyisobutyric Acid, N-Methylnicotinamide, Salicylic Acid, Tyrosine, Taurocholic Acid, Phenylacetic Acid, Homoserine, Histidine, Glycolic Acid, 3-Hydroxy Butyric acid, phenyllactic acid, methylmalonic acid, succinic acid, 2-hydroxy-2-methylbutyric acid, 4-hydroxyproline, hydroxypropionic acid, fumaric acid, p-hydroxyphenylacetic acid, myristic acid A combination of one or more of them is used for the purpose of the present invention.
  • the biomarkers include 3-hydroxyanthranilic acid, guanidinoacetic acid, 3,4-dihydroxycinnamic acid, azelaic acid, suberic acid, phenylpyruvate, acetoacetate, Methylcysteine, Alpha-Hydroxyisobutyric Acid, N-Methylnicotinamide, Salicylic Acid, Tyrosine, Taurocholic Acid, Phenylacetic Acid, Homoserine, Histidine, Glycolic Acid, 3-Hydroxy Butyric acid, phenyllactic acid, methylmalonic acid, succinic acid, 2-hydroxy-2-methylbutyric acid, 4-hydroxyproline, hydroxypropionic acid, fumaric acid, p-hydroxyphenylacetic acid, myristic acid
  • One or several combinations are used for the purpose of the present invention.
  • the biomarker includes taurocholic acid, and optionally, further combined with fumaric acid, myristic acid, histidine, tyrosine, 3-hydroxyanthranilic acid , guanidinoacetic acid, 3,4-dihydroxycinnamic acid, azelaic acid, suberic acid, phenylpyruvate, acetoacetate, methylcysteine, alpha-hydroxyisobutyric acid, N-methylnicotinamide, Salicylic Acid, Phenylacetic Acid, Homoserine, Glycolic Acid, 3-Hydroxybutyric Acid, Phenyllactic Acid, Methylmalonic Acid, Succinic Acid, 2-Hydroxy-2-Methylbutyric Acid, 4-Hydroxyproline, Hydroxy One or more combinations of propionic acid and p-hydroxyphenylacetic acid are used for the purpose of the present invention.
  • the third aspect of the present invention provides a quantitative detection method for the aforementioned combination of biomarkers, the method comprising processing the biological sample of the subject, and then using liquid chromatography tandem mass spectrometry and/or gas chromatography tandem mass spectrometry Methods Quantitative detection of biomarker combinations in biological samples.
  • the fourth aspect of the present invention provides a kit for quantitatively detecting the aforementioned combination of biomarkers, the kit using the biomarkers as detection indicators. It includes the standard product of the biomarker and the extractant of the biomarker, the extractant of the biomarker is selected from a mixture of organic solvent and water, and the organic solvent is selected from one or more of isopropanol, methanol, and acetonitrile. In some specific embodiments, and where necessary, the kit includes internal standards.
  • kit when used for gas chromatography-mass spectrometry, it may optionally further include a derivatization reagent.
  • the fifth aspect of the present invention provides the use of the aforementioned biomarker combination in preparing a diagnostic product for assessing the risk of adenoma and colorectal cancer in a subject, and the diagnostic product uses the expression level of the aforementioned biomarker combination as an assessment index.
  • the diagnostic product is selected from a kit, a diagnostic device, and a computer system.
  • the computer system for assessing the risk of adenoma and colorectal cancer in the subject can be a set of programs that can be installed in a suitable computer, or it can be an independent or combined computer device.
  • the computer system includes an information acquisition module and an adenoma and colorectal cancer risk assessment module; wherein, the information acquisition module is at least used to perform the following operations: acquire the biomarker combination in the subject sample Detection information, the biomarker combination is selected from the aforementioned biomarker combination; the adenoma and colorectal cancer risk assessment module is at least used to perform the following operations: according to the biomarker group obtained by the information acquisition module Level, assessing whether the subject suffers from adenoma and colorectal cancer or has the risk of adenoma and colorectal cancer.
  • the adenoma and colorectal cancer risk assessment module is at least used to perform the following operations: input the level of the biomarker group acquired by the information acquisition module into a diagnostic model, and evaluate the Whether the subject has adenoma and colorectal cancer or has the risk of adenoma and colorectal cancer.
  • the fifth aspect of the present invention provides a method for screening biomarkers related to adenoma and colorectal cancer, see the exemplary description in Embodiment 1 of the present invention for details.
  • the present invention uses liquid chromatography-mass spectrometry (LC-QTOFMS) and gas chromatography-mass spectrometry (GC-TOFMS) to perform full-spectrum analysis and testing of metabolites on adenoma and colorectal cancer patients and healthy human biological samples, combining Bioinformatics tools, looking for differential metabolites, and confirming them as diagnostic markers for adenoma and colorectal cancer through verification, can be used for early detection and diagnosis of adenoma and colorectal cancer, and improve the treatment effect of colorectal cancer.
  • LC-QTOFMS liquid chromatography-mass spectrometry
  • GC-TOFMS gas chromatography-mass spectrometry
  • the present invention proposes for the first time the unique biomarker and its combination as a detection index, which, as a biomarker for assessing the risk of adenoma and colorectal cancer, has high sensitivity and High specificity, and also has high sensitivity and specificity for the diagnosis of early colorectal adenocarcinoma, it can be used for early detection of colorectal cancer, buy time for patients, start treatment as soon as possible, and improve clinical treatment effect.
  • Figure 1A is a distribution diagram of PCA score values for distinguishing colorectal cancer patients (CRC) from normal controls (control), and the P value indicates the statistical significance of the difference between this group and the normal group.
  • Figure 1B is a distribution graph of OPLS-DA score values for distinguishing colorectal cancer patients (CRC) from normal controls (control).
  • Figure 1C is the correlation coefficient for the model permutation test.
  • Figure 2A is a volcano plot of differential metabolites of colorectal cancer patients relative to controls identified by OPLS-DA (VIP>1,
  • Figure 2B is a volcano plot of metabolites identified in colorectal cancer patients versus controls by unidimensional statistical analysis (p ⁇ 0.05, metabolites in CRC were significantly increased (FC>1, red dots), Metabolites were significantly reduced (FC ⁇ 1, blue dots).
  • Figure 2C is a heat map of differential biomarkers in colorectal cancer patients and controls (Z scores range from ).
  • Figure 2D is a box plot of representative differential metabolites between colorectal cancer patients and healthy controls (p ⁇ 0.05).
  • Figure 3 is a training set of 27 metabolites (3-hydroxyanthranilic acid, guanidinoacetic acid, 3,4-dihydroxycinnamic acid, azelaic acid, suberic acid, Phenylpyruvate, Acetoacetate, Methylcysteine, Alpha-Hydroxyisobutyrate, N-Methylnicotinamide, Salicylic Acid, Tyrosine, Taurocholic Acid, Phenylacetic Acid, Homoserine, Histidine , glycolic acid, 3-hydroxybutyric acid, phenyllactic acid, methylmalonic acid, succinic acid, 2-hydroxy-2-methylbutyric acid, 4-hydroxyproline, hydroxypropionic acid, fumaric acid, p-hydroxy Phenylacetic acid, myristic acid) ROC curve.
  • Figure 4 is a validation set of 27 metabolites (3-hydroxyanthranilic acid, guanidinoacetic acid, 3,4-dihydroxycinnamic acid, azelaic acid, suberic acid, Phenylpyruvate, Acetoacetate, Methylcysteine, Alpha Phenylhydroxyisobutyrate, N-Methylnicotinamide, Salicylic Acid, Tyrosine, Taurocholic Acid, Phenylacetic Acid, Homoserine, Histidine , glycolic acid, 3-hydroxybutyric acid, phenyllactic acid, methylmalonic acid, succinic acid, 2-hydroxy-2-methylbutyric acid, 4-hydroxyproline, hydroxypropionic acid, fumaric acid, p-hydroxy Phenylacetic acid, myristic acid) ROC curve.
  • Figure 5 shows 27 metabolites (3-hydroxyanthranilic acid, guanidinoacetic acid, 3,4-dihydroxycinnamic acid, azelaic acid, Acid, suberic acid, phenylpyruvate, acetoacetate, methylcysteine, alpha-hydroxyisobutyric acid, N-methylnicotinamide, salicylic acid, tyrosine, taurocholic acid, phenylacetic acid, Homoserine, Histidine, Glycolic Acid, 3-Hydroxybutyric Acid, Phenyllactic Acid, Methylmalonic Acid, Succinic Acid, 2-Hydroxy-2-Methylbutyric Acid, 4-Hydroxyproline, Hydroxypropionic Acid, ROC curves of fumaric acid, p-hydroxyphenylacetic acid, myristic acid).
  • Figure 6 is a ROC curve diagram for distinguishing colorectal cancer patients from adenoma patients (contains a metabolite group composed of 27 metabolites 3-hydroxyanthranilic acid, guanidinoacetic acid, 3,4-dihydroxycinnamic acid, nonanoic acid Diacid, suberic acid, phenylpyruvate, acetoacetate, methylcysteine, alpha-hydroxyisobutyric acid, N-methylnicotinamide, salicylic acid, tyrosine, taurocholic acid, phenylacetic acid , homoserine, histidine, glycolic acid, 3-hydroxybutyric acid, phenyllactic acid, methylmalonic acid, succinic acid, 2-hydroxy-2-methylbutyric acid, 4-hydroxyproline, hydroxypropionic acid , fumaric acid, p-hydroxyphenylacetic acid, myristic acid).
  • Figure 7 shows 27 metabolites (3-hydroxyanthranilic acid, guanidinoacetic acid, 3,4-dihydroxycinnamic acid, azelaic acid, suberic acid, propiophenone Acid, Acetoacetate, Methylcysteine, Alpha-Hydroxyisobutyric Acid, N-Methylnicotinamide, Salicylic Acid, Tyrosine, Taurocholic Acid, Phenylacetic Acid, Homoserine, Histidine, Ethanol Acid, 3-hydroxybutyric acid, phenyllactic acid, methylmalonic acid, succinic acid, 2-hydroxy-2-methylbutyric acid, 4-hydroxyproline, hydroxypropionic acid, fumaric acid, p-hydroxyphenylacetic acid , myristic acid) ROC curve.
  • Figure 8 is the six metabolites (including fumaric acid, myristic acid, histidine, tyrosine, 3,4-dihydroxycinnamic acid, taurocholic acid) used to distinguish colorectal cancer patients and healthy controls ROC curve plot for urine samples.
  • metabolites including fumaric acid, myristic acid, histidine, tyrosine, 3,4-dihydroxycinnamic acid, taurocholic acid
  • Fig. 9 is a ROC curve diagram for distinguishing colorectal cancer patients from adenoma patients (the metabolite group consisting of 6 metabolites includes fumaric acid, myristic acid, histidine, tyrosine, 3,4-di hydroxycinnamic acid, taurocholic acid).
  • Figure 10 shows six metabolites (including fumaric acid, myristic acid, histidine, tyrosine, 3,4-dihydroxycinnamic acid, taurocholic acid) in urine samples of adenoma patients and healthy controls The ROC curve graph.
  • the inventors provide examples for the discovery steps of biomarkers for adenoma and colorectal cancer risk assessment, including the screening method of the biomarkers and the quantitative determination method of the screened biomarker combinations, specifically Include the following steps:
  • Step 1 taking biological samples from patients with adenoma and colorectal cancer and healthy people and performing appropriate pretreatment;
  • Step 2 analyzing and identifying preliminary differential metabolites in biological samples of adenoma and colorectal cancer patients and healthy people through chromatography-mass spectrometry combined with metabolomics analysis method;
  • Step 3 under the selection criteria that the variable weight (VIP) value of the multidimensional OPLS-DA model is greater than 1 and the P value of the non-parametric test is less than 0.05, further differential metabolites are obtained;
  • VIP variable weight
  • Step 4 Validate with logistic regression model to obtain differential metabolites.
  • the biological samples can be selected from urine samples, blood samples and saliva samples of colorectal cancer patients, benign adenoma patients and healthy people; those of ordinary skill in the art can understand that in a test process, these should be selected The same type of biological sample as the subject.
  • the metabolomics analysis method coupled with chromatography-mass spectrometry in the step 2 includes a liquid phase/gas chromatography-mass spectrometry coupled metabolomics analysis method.
  • gas chromatography mass spectrometry is selected, and the chromatographic conditions of the test can be: Rxi-5ms capillary column, carrier gas: ultrapure helium, flow rate: 1.0mL/min, sample inlet Temperature: 260°C, transfer line temperature: 260°C, ion source temperature: 210°C, sample volume: 1 ⁇ L, sample injection method: splitless injection, heating program: start at 80°C and continue for 2 minutes, at a rate of 10°C/min The heating rate was raised to 220°C, then raised to 240°C at a heating rate of 5°C/min, then raised to 290°C at a heating rate of 25°C/min, and finally kept at 290°C for 8 minutes.
  • Mass spectrometer ion source EI source, electron Bombardment energy: 70eV, mass spectrometer scanning range: m/z, 40-600, full scan mode.
  • liquid chromatography-mass spectrometry is selected in the step 2, and the chromatographic conditions tested include: Agilent ZORBAX Eclipse XDB-C18 column (4.6 ⁇ .6ent, 5 ⁇ m), column temperature: 30°C.
  • Mobile phase A water (0.1% formic acid)
  • B acetonitrile (0.1% formic acid,)
  • the mobile phase elution gradient is 0-25min: 1-100% B
  • flow rate 0.4mL/min
  • injection volume 10 ⁇ L.
  • the optimal conditions for time-of-flight mass spectrometry are: (1) positive ion mode (ES+), capillary voltage 3500V, nebulizer 45psig, drying gas temperature 325°C, dryer flow rate 11L/min; (2) negative ion mode (ES-), capillary voltage 3000V , and other parameters are consistent with the positive ion mode.
  • ES+ positive ion mode
  • nebulizer 45psig
  • drying gas temperature 325°C drying gas temperature 325°C
  • dryer flow rate 11L/min dryer flow rate 11L/min
  • ES- negative ion mode
  • capillary voltage 3000V capillary voltage
  • the pretreatment steps include: take 50 ⁇ L serum, add 10 ⁇ l chlorphenylalanine (0.1 mg /mL, water soluble) and 10 ⁇ L heptadecanic acid (1mg/mL, alcohol soluble) as internal standard to monitor the reproducibility of the sample; then add 175 ⁇ L chloroform methanol mixed solvent (1:3, v/v), vortex for 30s ; Place the centrifuge tube at -20°C for 10 minutes to promote protein precipitation; then centrifuge at 13,000 rpm for 10 minutes, take 200 ⁇ L of the supernatant into a high-recovery sample bottle, and dry it in vacuum at room temperature to obtain a sample; use a two-step method to derivatize the obtained sample, First add 50 ⁇ L of methoxyamine (15 mg/mL, dissolved in pyridine), vortex for 30 seconds, and react at
  • chlorinated phenylalanine 5 ⁇ g/mL, water-soluble
  • methanol-acetonitrile mixture 5:3, v/v
  • the assay method of the present invention can comprehensively and comprehensively reflect the mutation status of metabolites between patients with adenoma and colorectal cancer and healthy people, and find diagnostic markers for adenoma and colorectal cancer, which can be used for early detection of adenoma and colorectal cancer.
  • diagnostic markers for adenoma and colorectal cancer which can be used for early detection of adenoma and colorectal cancer.
  • Embodiment 2 Subject, biological sample and grouping
  • Urine samples from clinically confirmed colorectal adenoma patients, colorectal cancer patients and healthy people were collected, and the samples and collection were approved by the ethics committee of the medical institution.
  • the collected samples there were 220 patients with colorectal cancer, 20 patients with adenoma, and 180 healthy controls.
  • the samples are processed, they are detected and analyzed by a chromatographic mass spectrometer, and a multidimensional statistical model is established to visually display the differences in metabolic profiles between adenoma and colorectal cancer patients and healthy controls to obtain differential metabolic profiles. things.
  • the subjects in the embodiments include colorectal cancer patients, colorectal adenoma patients and healthy subjects confirmed according to clinical diagnostic indicators; they are divided into training set and verification set according to the following scheme, and the biological samples tested are subjects Fasting mid-morning urine sample.
  • Embodiment 3 Gas Chromatography-Mass Spectrometry (GC-TOFMS) Testing Urine Samples
  • the training set samples were measured by gas chromatography-mass spectrometry.
  • Urine sample pretreatment Take 50 ⁇ L of urine in a 1.5 mL centrifuge tube, add 10 ⁇ L of chlorophenylalanine (0.1 mg/mL, water-soluble) and 10 ⁇ L of heptadecanic acid (1 mg/mL, alcohol-soluble) as internal standards to monitor sample reproducibility. Then add 175 ⁇ L of chloroform methanol mixed solvent (1:3, v/v), vortex for 30 s; place the centrifuge tube at -20°C for 10 min to promote protein precipitation. Then centrifuge at 13,000 rpm for 10 min, take 200 ⁇ L of the supernatant into a high-recovery injection bottle, and dry it in vacuum at room temperature.
  • the sample was derivatized using a two-step method after being drained. First, 50 ⁇ L of methoxyamine (15 mg/mL, dissolved in pyridine) was added, vortexed for 30 s, and reacted at 30 ° C for 90 min, and then 50 ⁇ L of BSTFA (containing 1% TMCS ) was reacted at 70°C for 60min. The reaction product was analyzed by GC-TOFMS after standing at room temperature for 1 h.
  • GC-TOFMS determination Leco Pegasus HT gas chromatography tandem time-of-flight mass spectrometry (like company, the United States), chromatographic column: Rxi-5ms capillary column (filling 5% biphenyl/95% dimethyl polysiloxane, Restek, Pennsylvania, USA), carrier gas: ultrapure helium, flow rate: 1.0mL/min, inlet temperature: 260°C, transfer line temperature: 260°C, ion source temperature: 210°C, injection volume: 1 ⁇ L, injection Method: splitless injection, heating program: start at 80°C and last for 2 minutes, raise the temperature to 220°C at a rate of 10°C/min, then increase to 240°C at a rate of 5°C/min, and then increase to 25°C/min The heating rate of min was raised to 290°C, and lasted at 290°C for 8min.
  • Mass spectrometry ion source EI source, electron bombardment energy: 70eV, mass
  • ChromaTOF software (v4.33, Leco, USA) was used for data analysis and processing.
  • the samples in the training set were measured by liquid chromatography-mass spectrometry.
  • Urine sample pretreatment Take 50 ⁇ l urine sample and mix with 200 ⁇ l methanol-acetonitrile mixture (5:3, v/v) containing chlorphenylalanine (5 ⁇ g/mL, water-soluble), vortex for 2 minutes, and let stand for 10 minutes Afterwards, centrifuge at 13,000 rpm for 20 min, and take the supernatant for LC-TOFMS analysis.
  • LC-QTOFMS test ultra-high performance liquid chromatography (Waters Company, the U.S.), equipped with solvent controller, column thermostat and sample controller. Mass spectrometry was performed using a Waters mass spectrometer (Waters, USA) equipped with an electrospray ionization source. Chromatographic column: ACQUITY UPLC BEH C18 (100mm ⁇ 2.1mm, 1.7 ⁇ m) chromatographic column, column temperature: 40°C. Mobile phase A: water (0.1% formic acid), B: acetonitrile (containing 30% isopropanol), mobile phase elution gradient is 0-20min: 5-100% B, flow rate: 0.4mL/min, injection volume: 5 ⁇ L.
  • the optimal conditions for tandem mass spectrometry are: (1) positive ion mode (ES+), capillary voltage 1500V, ion source temperature 150°C, drying gas temperature 550°C, dryer flow rate 1000L/hr; (2) negative ion mode (ES-), capillary The voltage is 2000V, and other parameters are consistent with the positive ion mode.
  • the metabolite full-spectrum analysis test was performed on the training set samples by LC-QTOFMS and GC-TOFMS.
  • the variable weight VIP value (VIP>1) provided by the DA model and the selection criteria of the P value (P ⁇ 0.05) provided by the Mann-Whitney U test are obtained from the training set samples to distinguish colorectal cancer from normal healthy people 77 preliminary differential metabolites for the control, including lysine, tryptophan, threonine, histidine, citrulline, tyrosine, lactic acid, carnosine, 2-hydroxybutyric acid, suberic acid, 3 -Hydroxybutyric acid, glutamine, pyruvate, uridine, succinic acid, citric acid, aconitic acid, isocitric acid; 2-methylcitric acid, indoleacetic acid, guanidinoacetic acid, azelaic acid, tryptamine , 5-hydroxy
  • Fig. 2A is a volcano plot (VIP>1,
  • Figure 2B is a volcano plot of metabolites identified in colorectal cancer patients versus controls by unidimensional statistical analysis (p ⁇ 0.05, metabolites in CRC were significantly increased (FC>1, red dots), Metabolites were significantly reduced (FC ⁇ 1, blue dots);
  • Figure 2C is a heat map of differential biomarkers between colorectal cancer patients and controls (Z score ranges from -2 to 2);
  • a logistic regression model is exemplarily used to study the correlation between preliminary differential metabolites and colorectal cancer.
  • ROC curve clinical diagnostic performance curve
  • the 27 biomarkers and their combinations (3-hydroxyanthranilic acid, guanidinoacetic acid, 3,4-dihydroxycinnamic acid, azelaic acid, suberic acid, benzene Pyruvate, Acetoacetate, Methylcysteine, Alpha-Hydroxyisobutyrate, N-Methylnicotinamide, Salicylic Acid, Tyrosine, Taurocholic Acid, Phenylacetic Acid, Homoserine, Histidine, Glycolic acid, 3-hydroxybutyric acid, phenyllactic acid, methylmalonic acid, succinic acid, 2-hydroxy-2-methylbutyric acid, 4-hydroxyproline, hydroxypropionic acid, fumaric acid, p-hydroxybenzene Acetic acid, myristic acid) are very good markers for the early diagnosis of colorectal adenoma and colorectal cancer, which can be used for clinical diagnosis, can improve the early detection rate of adenoma
  • the logistic regression model was further used for optimization and verification.
  • fumaric acid myristic acid, histidine, tyrosine, 3,4-dihydroxycinnamic acid, taurochol
  • acid is used as a risk assessment marker for adenoma and colorectal cancer, according to comprehensive factors such as the difference multiple, significance and concentration range of each diagnostic marker between adenoma and colorectal cancer and the normal control group, Build a score diagnostic model via a logistic regression model:
  • Model score P 4.059*C1-0.019*C2-0.017*C3-0.011*C4-0.056*C5-0.25*C6+5.873
  • C1 is the concentration of fumaric acid in biological samples
  • C2 is the concentration of 3,4-dihydroxycinnamic acid in biological samples
  • C3 is the concentration of histidine in biological samples
  • C4 is the concentration of taurocholic acid in biological samples.
  • the concentration in the biological sample is the concentration of tyrosine in the biological sample
  • C6 is the concentration of myristic acid in the biological sample, and the units of the above concentrations are ⁇ M.
  • the diagnostic threshold for colorectal cancer ranged from -0.13 to -0.11, and the optimal diagnostic threshold was -0.12; the diagnostic threshold for adenoma ranged from -0.105 to -0.09, and the optimal diagnostic threshold was Threshold value -0.10; detect the concentration value of the diagnostic markers of each sample, and then calculate the score value according to the diagnostic model, and evaluate whether the subject is diseased or has the risk of disease by comparing with the diagnostic threshold.
  • ROC receiver operating characteristic curve
  • FIG. 9 is a graph of ROC curves for colorectal cancer patients and adenoma patients.
  • Figure 10 is a graph of ROC curves for adenoma patients and healthy controls.
  • Embodiment 8 Establishment of a computer system for detecting adenoma and colorectal cancer
  • this embodiment establishes a computer system for assessing the risk of adenoma and colorectal cancer in a subject, including an information acquisition module, a risk assessment module for adenoma and colorectal cancer, a sample detection module and a sample pre-test module. processing module.
  • the information obtaining module is at least used for performing the following operations: obtaining the detection information of the combination of biomarkers in the sample of the subject, and the combination of biomarkers is selected from the combination of biomarkers mentioned above.
  • the adenoma and colorectal cancer risk assessment module is at least used to perform the following operations: according to the biomarker group levels acquired by the information acquisition module, assess whether the subject suffers from adenoma and colorectal cancer, or has The risk of adenoma and colorectal cancer; specifically including inputting the level of the biomarker group acquired by the information acquisition module into a diagnostic model, and evaluating whether the subject has adenoma and colorectal cancer or not according to the diagnostic model There is a risk of adenoma and colorectal cancer.
  • the computer system of this embodiment may optionally include or not include a sample detection module and/or a sample pretreatment module.
  • the sample detection module is at least used to perform the operation of detecting the level of the biomarker in the sample; specifically, it includes at least performing a liquid chromatography tandem mass spectrometry operation or a gas chromatography tandem mass spectrometry operation for detecting biomarkers,
  • detection conditions refer to the relevant part of this manual.
  • the sample pretreatment model is at least used to perform operations before testing samples for testing samples; refer to relevant parts of this specification for details.

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Abstract

一种用于评估腺瘤及结直肠癌风险的生物标志物组合及其应用，具体为一种用于评估受试者腺瘤及结直肠癌风险的代谢标志物及其在制备评估腺瘤及结直肠癌风险的诊断产品中的应用。诊断标记物具有灵敏度和特异性高的特点，对于早期结直肠癌诊断具有较高的灵敏度和特异性，可用于结直肠癌的早期发现，为患者争取时间，尽早开始治疗，提高临床治疗效果。

Description

用于评估腺瘤及结直肠癌风险的生物标志物组合及其应用
本申请要求申请日为2021/5/21的中国专利申请2021105578395的优先权。本申请引用上述中国专利申请的全文。
技术领域
本发明涉及生物技术领域，涉及一种用于腺瘤及结直肠癌风险评估的生物标志物组合、应用及其测定方法。
背景技术
结直肠癌发病率及死亡率高，但其经典发展过程遵循从腺瘤-不典型增生-进展期癌的缓慢进展模式，由各种基因和表观遗传突变在10年为单位的时间段内累积，导致结直肠恶性肿瘤的发生。
结直肠癌的早期和癌前病变阶段，患者往往没有明显的临床症状，如果及时发现可以完整切除，治疗效果较好。但很大一部分高危人群没能获得筛查机会，出现症状时多数已属于进展期甚至发生远处转移，即使行规范化外科手术及综合治疗，预后仍然较差，治疗成本高昂。因此，早期发现结直肠癌及其癌前病变对提高患者的总生存率至关重要，有助于降低疾病本身的治疗难度，同时降低诊疗费用。基于人群的大规模筛查，可以显著减少结直肠癌的发病率、提高治愈率并降低死亡率，已成为世界各国癌症防控的主要手段。
结直肠癌的筛查对象可分为一般风险人群和散发性结直肠癌高危人群两类，筛查方法和侧重有所不同。前者定义为年龄大于40岁不伴结直肠癌个人史及家族史、不伴结直肠腺瘤、炎症性肠病等疾病、患癌风险处于平均或较低水平的人群；后者则是指具有结直肠癌家族史或个人史、肠道腺瘤史、长期不愈的炎症性肠病、并综合体质指数、吸烟饮酒史、饮食锻炼等多种危险因素综合判定。此外，还有一类特殊风险人群即遗传性结直肠癌，包括家族性腺瘤性息肉病及遗传性非息肉病性结直肠癌等。高风险组及特殊风险人群应直接进行结肠镜检查，其作为诊断的金标准，在早期发现癌前病变、降低结直肠肿瘤风险方面起着重要作用。而一般风险人群规模庞大，结肠镜属于侵入性有创检查，需要进行肠道准备且存在并发症风险，患者顺应性较低；无痛肠镜检查则费用较昂贵，不适于作为大规模筛查工具。针对这一组自然人群，有必要开发具有低侵入性、低成本、且高效可靠的结直肠癌及腺瘤等癌前病变的筛查手段。
目前临床常用的结直肠癌筛查手段包括肛门指检、粪便潜血、血液肿瘤标志物检测、 内窥镜、影像学检查(CT仿真内镜和气钡双重对比造影)等。粪便潜血试验是应用最广泛的结直肠癌早诊筛查技术，其无创、低成本的优势易使患者接受，主要用于筛选哪些患者应接受结肠镜检查，具有多个循证医学证据支持，但该方法灵敏度和特异性相对较低。改良的潜血检测方式以抗人血红蛋白抗体作为一抗对粪便进行免疫组化检测，相对过氧化物酶检测亚铁血红素，该方法特异性有所提高，但灵敏度仍不超过50％，且结果的判定具有一定的主观性。粪便DNA检测除了粪便隐血之外，还能检测突变的DNA，灵敏度有所提高，但成本高昂，难以作为筛查手段广泛开展。血液肿瘤标志物如癌胚抗原(CEA)和糖类抗原19-9(CA19-9)等，敏感性同样较低，容易遗漏无症状患者；且CEA并非肿瘤特异性抗原，而是肿瘤相关性抗原，其他内胚层来源肿瘤(如胃癌、肺癌、乳腺癌、胰腺癌等)甚至慢性结肠炎均可导致CEA升高，因此特异性不高，目前仅作为结直肠癌辅助诊断指标和疗效监测手段。CT仿真内镜是应用计算机虚拟现实技术与现代医学影像结合后产生的一种新的无创伤检查手段，可以替代气钡双重造影对全结肠进行观察，但对结肠息肉检出的敏感性与息肉大小有直接关系，且受检人群暴露于辐射，检查成本较高，仍不适用于自然人群筛查。
专利CN201611090742.3提供一种用于早期结直肠癌辅助诊断的试剂盒及其使用方法和检测系统，试剂盒包括核酸分离与纯化试剂，DNA亚硫酸盐转化试剂，KRAS基因突变检测试剂，BMP3和NDRG4基因甲基化检测试剂，粪便潜血检测试剂；其中核酸分离与纯化试剂用于分离及纯化出粪便样本中的人源性DNA；DNA亚硫酸盐转化试剂用于将纯化的部分人源性DNA进行亚硫酸盐转化，用于后续BMP3和NDRG4基因甲基化的检测。但类似的基因检测都存在难以与结直肠息肉等普通结直肠病区分的难题，灵敏度和特异性有待考察。并且价格昂贵，难以实现大规模推广用于疾病筛查使用。
专利CN201910446079.3提供一种用于结直肠癌的microRNA生物标志物，包括：编码hsa-miR-423-5p、编码hsa-miR-451a、编码hsa-miR-30b-5p、编码hsa-miR-27b-3p、编码hsa-miR-199a-3p、编码hsa-let-7d-3p、编码hsa-miR-423-5p中的至少一种核酸分子，所述核酸分子均编码microRNA序列，其核苷酸序列如SEQIDNO:1～7所示。通过混合样本筛选、少量样本单个验证和大量样本单个验证获得这些microRNA生物标志物。但类似检查都存在取样随机性大，针对疾病检测灵敏度偏低的情况，导致很难用于疾病筛查使用。
鉴于此，对腺癌及结直肠癌的筛查和早期诊断，迫切需要更简单无创、顺应性好、以及高敏感性和特异性的检测技术以更便利、可靠地评估受试体腺瘤及结直肠癌的风险。
发明内容
本发明要解决的技术问题是克服上述现有技术的缺陷与不足，提供一种用于评估受试体腺瘤和结直肠癌风险的诊断标志物组合及其测定方法。
本发明进一步提供所述诊断标志物在制备用于评估受试体腺瘤和结直肠癌风险的诊断产品和计算机系统中的应用。
本发明中“腺瘤和结直肠癌”包含“腺瘤或结直肠癌”的情形，即在一次评估或诊断过程中，可以是以同时诊断或排除腺瘤和结直肠癌为目的，也可以是诊断或排除其中之一种为目的。
所述“风险”指受试体患有“腺瘤及结直肠癌”的可能性，通过本发明方法对其风险进行评估的输出可以是一个以数字表示的概率值，也可以是与预先设定的标准值相比较而得出的“有”或“无”或类似表示的定性表述。
为达到上述目的，本发明提供技术方案如下：
本发明第一方面，提供用于受试体腺瘤及结直肠癌风险评估的诊断产品，用于受试体腺瘤及结直肠癌风险评估的诊断产品，其特征在于，所述诊断产品的诊断指标包括受试体生物样本中的牛磺胆酸、富马酸、肉豆蔻酸、组氨酸、酪氨酸、3,4-二羟基肉桂酸中之一种或几种，及任选地包括以下组合A或组合B，或同时包括组合A和组合B：
组合A：3-羟基邻氨基苯甲酸，胍基乙酸，壬二酸，辛二酸，苯丙酮酸，乙酰乙酸，甲基半胱氨酸，α-羟基异丁酸，N-甲基烟酰胺，水杨酸，苯乙酸，高丝氨酸，乙醇酸，3-羟基丁酸，苯乳酸，甲基丙二酸，琥珀酸，2-羟基-2-甲基丁酸，4-羟基脯氨酸，羟丙酸，对羟基苯乙酸中之一种或多种；
组合B：赖氨酸，色氨酸，苏氨酸，瓜氨酸，乳酸，肌肽，2-羟基丁酸，辛二酸，3-羟基丁酸，谷氨酰胺，丙酮酸，尿苷，琥珀酸，柠檬酸，乌头酸、异柠檬酸；2-甲基柠檬酸，吲哚乙酸，胍基乙酸，壬二酸，色胺、5-羟基吲哚乙酸、亚精胺、马尿酸、苯乙酸、乙酰乙酸，间羟基苯丙酸、甘氨酸、琥珀酸、5-羟基吲哚乙酸、对羟基苯乙酸、2-氨基丁酸、β-羟基丁酸、胱氨酸、泛酸、γ-氨基丁酸、异亮氨酸、缬氨酸、鸟氨酸、磷酸甘油、氨氧基乙酸、4-羟基-L-脯氨酸、二十二碳六烯酸、苯丙氨酸、3,4-二羟基丁酸、3-甲基己二酸、假尿苷、丝氨酸、高丝氨酸，腐胺、黄原酸、α-羟基戊二酸、马尿酸、3-羟基苯甲酸、3-羟基异戊酰肉碱，3-羟基邻氨基苯甲酸，β-丙氨酸、棕榈油酸、半胱氨酸、谷氨酸、尿嘧啶、5-氧代脯氨酸、2-氨基丁酸、天冬氨酸、天冬酰胺，肌醇，同瓜氨酸，氧戊二酸，3,4-二羟基扁桃酸，4-羟基苯甲酸，羟基丙酸，3,4-二羟基肉桂酸，香草酸中的一种或多种；
所述生物样本选自受试体的尿液、血液、唾液和粪便。
所述诊断产品选自试剂盒、医疗器械、具有诊断模块的计算机系统和诊断装置。
本发明第二方面，提供了用于受试体腺瘤及结直肠癌风险评估的生物标志物组合，所述生物标志物来源于受试体生物样本，所述生物样本包括受试体的尿液、血液、唾液和粪便等生物样本中的差异性代谢物。在采用血液作为样本时，可选择全血、血清和血浆。在一些具体的实施方式中，可选择来源于外周血的血清作为生物样本。在一些具体的实施方式中，本发明选用受试体尿液作为生物样本，从而取样更为简便，受试者顺应性更佳。
本发明提供用于受试体腺瘤及结直肠癌风险评估的生物标志物组合，所述生物标志物为受试体生物样本中的差异性代谢物，所述生物样本选自尿液、血液、唾液和粪便；所述生物标志物组合包括牛磺胆酸、富马酸、肉豆蔻酸、组氨酸、酪氨酸、3,4-二羟基肉桂酸之一种或几种，及任选地包括以下组合A或组合B，或同时包括组合A和组合B：
组合A：3-羟基邻氨基苯甲酸，胍基乙酸，3,4-二羟基肉桂酸，壬二酸，辛二酸，苯丙酮酸，乙酰乙酸，甲基半胱氨酸，α-羟基异丁酸，N-甲基烟酰胺，水杨酸，苯乙酸，高丝氨酸，乙醇酸，3-羟基丁酸，苯乳酸，甲基丙二酸，琥珀酸，2-羟基-2-甲基丁酸，4-羟基脯氨酸，羟丙酸，对羟基苯乙酸中之一种或多种；
组合B：赖氨酸，色氨酸，苏氨酸，瓜氨酸，乳酸，肌肽，2-羟基丁酸，辛二酸，3-羟基丁酸，谷氨酰胺，丙酮酸，尿苷，琥珀酸，柠檬酸，乌头酸、异柠檬酸；2-甲基柠檬酸，吲哚乙酸，胍基乙酸，壬二酸，色胺、5-羟基吲哚乙酸、亚精胺、马尿酸、苯乙酸、乙酰乙酸，间羟基苯丙酸、甘氨酸、琥珀酸、5-羟基吲哚乙酸、对羟基苯乙酸、2-氨基丁酸、β-羟基丁酸、胱氨酸、泛酸、γ-氨基丁酸、异亮氨酸、缬氨酸、鸟氨酸、磷酸甘油、氨氧基乙酸、4-羟基-L-脯氨酸、二十二碳六烯酸、苯丙氨酸、3,4-二羟基丁酸、3-甲基己二酸、假尿苷、丝氨酸、高丝氨酸，腐胺、黄原酸、α-羟基戊二酸、马尿酸、3-羟基苯甲酸、3-羟基异戊酰肉碱，3-羟基邻氨基苯甲酸，β-丙氨酸、棕榈油酸、半胱氨酸、谷氨酸、尿嘧啶、5-氧代脯氨酸、2-氨基丁酸、天冬氨酸、天冬酰胺，肌醇，同瓜氨酸，氧戊二酸，3,4-二羟基扁桃酸，4-羟基苯甲酸，羟基丙酸，3,4-二羟基肉桂酸，香草酸中的一种或多种。
在一些具体的实施方式中，本发明生物标志物包括牛磺胆酸、富马酸、肉豆蔻酸、组氨酸、酪氨酸、3,4-二羟基肉桂酸用于本发明目的。
在一些具体的实施方式中，本发明生物标志物组合包括赖氨酸，色氨酸，苏氨酸，组氨酸，瓜氨酸，酪氨酸，乳酸，肌肽，2-羟基丁酸，辛二酸，3-羟基丁酸，谷氨酰胺，丙酮酸，尿苷，琥珀酸，柠檬酸，乌头酸、异柠檬酸；2-甲基柠檬酸，吲哚乙酸，胍基乙酸，壬二酸，色胺、5-羟基吲哚乙酸、亚精胺、马尿酸、苯乙酸、乙酰乙酸，间羟基苯丙酸、甘氨酸、琥珀酸、5-羟基吲哚乙酸、对羟基苯乙酸、2-氨基丁酸、肉豆蔻酸、β -羟基丁酸、胱氨酸、泛酸、γ-氨基丁酸、异亮氨酸、缬氨酸、鸟氨酸、磷酸甘油、氨氧基乙酸、4-羟基-L-脯氨酸、富马酸、二十二碳六烯酸、苯丙氨酸、3,4-二羟基丁酸、3-甲基己二酸、假尿苷、丝氨酸、高丝氨酸，腐胺、黄原酸、α-羟基戊二酸、马尿酸、3-羟基苯甲酸、3-羟基异戊酰肉碱，3-羟基邻氨基苯甲酸，β-丙氨酸、棕榈油酸、半胱氨酸、谷氨酸、尿嘧啶、5-氧代脯氨酸、2-氨基丁酸、天冬氨酸、天冬酰胺，肌醇，同瓜氨酸，氧戊二酸，牛磺胆酸、3,4-二羟基扁桃酸，4-羟基苯甲酸，羟基丙酸，3,4-二羟基肉桂酸，香草酸中的一种或多种的组合用于本发明目的。
在一些具体的实施方式中，所述生物标志物包括3-羟基邻氨基苯甲酸，胍基乙酸，3,4-二羟基肉桂酸，壬二酸，辛二酸，苯丙酮酸，乙酰乙酸，甲基半胱氨酸，α-羟基异丁酸，N-甲基烟酰胺，水杨酸，酪氨酸，牛磺胆酸，苯乙酸，高丝氨酸，组氨酸，乙醇酸，3-羟基丁酸，苯乳酸，甲基丙二酸，琥珀酸，2-羟基-2-甲基丁酸，4-羟基脯氨酸，羟丙酸，富马酸，对羟基苯乙酸，肉豆蔻酸中的一种或多种的组合用于本发明目的。
在一些具体的实施方式中，所述生物标志物包括3-羟基邻氨基苯甲酸，胍基乙酸，3,4-二羟基肉桂酸，壬二酸，辛二酸，苯丙酮酸，乙酰乙酸，甲基半胱氨酸，α-羟基异丁酸，N-甲基烟酰胺，水杨酸，酪氨酸，牛磺胆酸，苯乙酸，高丝氨酸，组氨酸，乙醇酸，3-羟基丁酸，苯乳酸，甲基丙二酸，琥珀酸，2-羟基-2-甲基丁酸，4-羟基脯氨酸，羟丙酸，富马酸，对羟基苯乙酸，肉豆蔻酸中一种或几种组合用于本发明目的。
在一些具体的实施方式中，所述生物标志物包括牛磺胆酸，以及任选地，可进一步与富马酸，肉豆蔻酸，组氨酸，酪氨酸，3-羟基邻氨基苯甲酸，胍基乙酸，3,4-二羟基肉桂酸，壬二酸，辛二酸，苯丙酮酸，乙酰乙酸，甲基半胱氨酸，α-羟基异丁酸，N-甲基烟酰胺，水杨酸，苯乙酸，高丝氨酸，乙醇酸，3-羟基丁酸，苯乳酸，甲基丙二酸，琥珀酸，2-羟基-2-甲基丁酸，4-羟基脯氨酸，羟丙酸，对羟基苯乙酸中一种或几种组合用于本发明目的。
本发明第三方面提供一种前述生物标志物组合的定量检测方法，所述方法包括对受试者的生物样本进行处理后，以液相色谱串联质谱联用和/或气相色谱串联质量联用方法对生物样本中的生物标志物组合进行定量检测。
本发明第四方面提供一种定量检测前述的生物标志物组合的试剂盒，所述试剂盒以所述生物标志物为检测指标。包括所述生物标志物的标准品和生物标志物提取剂，所述生物标志物提取剂选自有机溶剂和水的混合物，有机溶剂选自异丙醇、甲醇、乙腈之一种或多种。在一些具体的实施方式中，以及必要时，所述试剂盒包括内标物。
在一些具体实施方式中，当所述试剂盒用于气相色谱质谱联用时，可选择地，可进一步包括衍生化试剂。
本发明第五方面提供前述生物生物标志物组合在制备评估受试体腺瘤及结直肠癌风险的诊断产品中的用途，所述诊断产品以前述的生物标志物组合的表达水平作为评估指标。
在一些具体的实施方式中，所述诊断产品选自试剂盒、诊断装置和计算机系统。
所述用于评估受试体腺瘤及结直肠癌风险的计算机系统，可以是可设置于适宜的计算机内的一套程序，也可以是独立或组合的计算机装置。为实现本发明目的，所述计算机系统包括信息获取模块和腺瘤及结直肠癌风险评估模块；其中，所述信息获取模块至少用于执行以下操作：获取受试者样品中的生物标志物组合检测信息，所述生物标志物组合选自前所述的生物标志物组合；所述腺瘤及结直肠癌风险评估模块至少用于执行以下操作：根据所述信息获取模块获取的生物标志物组水平，评估所述受试者是否患有腺瘤及结直肠癌或具有腺瘤及结直肠癌的患病风险。
在一些具体的实施方式中，所述腺瘤及结直肠癌风险评估模块至少用于执行以下操作：将所述信息获取模块获取的生物标志物组的水平输入诊断模型，根据诊断模型评估所述受试者是否患有腺瘤及结直肠癌或具有腺瘤及结直肠癌的患病风险。
本发明第五方面提供了腺瘤和结直肠癌相关生物标志物的筛选方法，具体见本发明实施例一示例性描述。
本发明有益的技术效果：
本发明通过运用液相色谱质谱联用仪(LC-QTOFMS)和气相色谱质谱联用仪(GC-TOFMS)对腺瘤及结直肠癌病人及健康人生物样本进行代谢物全谱分析测试，结合生物信息学工具，寻找差异性代谢物，并通过验证确定其作为腺瘤及结直肠癌的诊断标记物，可以用于腺瘤及结直肠癌的早期发现和诊断，提高结直肠癌治疗效果。相对于现有技术，本发明首次提出所述的独特的生物标志物及其组合作为检测指标，其作为评估腺瘤和结直肠癌风险的生物标志物，对结直肠癌的诊断具有高灵敏度和高特异性，并且对于早期结直肠腺癌诊断也具有较高的灵敏度和特异性，可用于结直肠癌的早期发现，为患者争取时间，尽早开始治疗，提高临床治疗效果。
附图说明
构成本发明的一部分的附图用来提供对本发明的进一步理解，本发明的示意性实施例及其说明用于解释本发明，并不构成对本发明的任何限定。在附图中：
图1A是区分结直肠癌患者(CRC)和正常对照(control)的PCA得分值的分布图，P值表示该组与正常组之间差异的统计显著性。
图1B是区分结直肠癌患者(CRC)和正常对照(control)的OPLS-DA得分值的分 布图。
图1C是模型置换检验的相关系数。
图2A是通过OPLS-DA鉴定的结直肠癌患者相对于对照的差异代谢产物的火山图(VIP＞1，|相关系数|＞0.3)。
图2B是通过单维统计分析在结直肠癌患者与对照组中鉴别出的代谢物的火山图(p<0.05，CRC中的代谢物显着增加(FC>1，红点)，CRC中的代谢物显着减少(FC<1，蓝点)。
图2C是结直肠癌患者与对照的差异生物标志物的热图(Z评分范围为
Figure PCTCN2022094558-appb-000001
)。
图2D是结直肠癌患者与健康对照之间的代表性差异代谢物的箱形图(p<0.05)。
图3是训练集结直肠癌患者和健康对照的尿液样本中27种代谢物(3-羟基邻氨基苯甲酸，胍基乙酸，3,4-二羟基肉桂酸，壬二酸，辛二酸，苯丙酮酸，乙酰乙酸，甲基半胱氨酸，α-羟基异丁酸，N-甲基烟酰胺，水杨酸，酪氨酸，牛磺胆酸，苯乙酸，高丝氨酸，组氨酸，乙醇酸，3-羟基丁酸，苯乳酸，甲基丙二酸，琥珀酸，2-羟基-2-甲基丁酸，4-羟基脯氨酸，羟丙酸，富马酸，对羟基苯乙酸，肉豆蔻酸)的ROC曲线图。
图4是验证集结直肠癌患者和健康对照的尿液样本中27种代谢物(3-羟基邻氨基苯甲酸，胍基乙酸，3,4-二羟基肉桂酸，壬二酸，辛二酸，苯丙酮酸，乙酰乙酸，甲基半胱氨酸，α苯羟基异丁酸，N-甲基烟酰胺，水杨酸，酪氨酸，牛磺胆酸，苯乙酸，高丝氨酸，组氨酸，乙醇酸，3-羟基丁酸，苯乳酸，甲基丙二酸，琥珀酸，2-羟基-2-甲基丁酸，4-羟基脯氨酸，羟丙酸，富马酸，对羟基苯乙酸，肉豆蔻酸)的ROC曲线图。
图5是早期结直肠癌(I+II期)患者和健康对照的尿液样本中27种代谢物(3-羟基邻氨基苯甲酸，胍基乙酸，3,4-二羟基肉桂酸，壬二酸，辛二酸，苯丙酮酸，乙酰乙酸，甲基半胱氨酸，α-羟基异丁酸，N-甲基烟酰胺，水杨酸，酪氨酸，牛磺胆酸，苯乙酸，高丝氨酸，组氨酸，乙醇酸，3-羟基丁酸，苯乳酸，甲基丙二酸，琥珀酸，2-羟基-2-甲基丁酸，4-羟基脯氨酸，羟丙酸，富马酸，对羟基苯乙酸，肉豆蔻酸)的ROC曲线图。
图6是区分结直肠癌患者和腺瘤患者的ROC曲线图(包含27个代谢物组合成的代谢物组3-羟基邻氨基苯甲酸，胍基乙酸，3,4-二羟基肉桂酸，壬二酸，辛二酸，苯丙酮酸，乙酰乙酸，甲基半胱氨酸，α-羟基异丁酸，N-甲基烟酰胺，水杨酸，酪氨酸，牛磺胆酸，苯乙酸，高丝氨酸，组氨酸，乙醇酸，3-羟基丁酸，苯乳酸，甲基丙二酸，琥珀酸，2-羟基-2-甲基丁酸，4-羟基脯氨酸，羟丙酸，富马酸，对羟基苯乙酸，肉豆蔻酸)。
图7是腺瘤患者和健康对照的尿液样本中27种代谢物(3-羟基邻氨基苯甲酸，胍基乙酸，3,4-二羟基肉桂酸，壬二酸，辛二酸，苯丙酮酸，乙酰乙酸，甲基半胱氨酸，α-羟基异丁酸，N-甲基烟酰胺，水杨酸，酪氨酸，牛磺胆酸，苯乙酸，高丝氨酸，组氨酸， 乙醇酸，3-羟基丁酸，苯乳酸，甲基丙二酸，琥珀酸，2-羟基-2-甲基丁酸，4-羟基脯氨酸，羟丙酸，富马酸，对羟基苯乙酸，肉豆蔻酸)的ROC曲线图。
图8是6种代谢物(包括富马酸、肉豆蔻酸、组氨酸、酪氨酸、3,4-二羟基肉桂酸、牛磺胆酸)用于区分结直肠癌患者和健康对照的尿液样本的ROC曲线图。
图9是区分结直肠癌患者和腺瘤患者的ROC曲线图(包含6个代谢物组合成的代谢物组包括富马酸、肉豆蔻酸、组氨酸、酪氨酸、3,4-二羟基肉桂酸、牛磺胆酸)。
图10是腺瘤患者和健康对照的尿液样本中6种代谢物(包括富马酸、肉豆蔻酸、组氨酸、酪氨酸、3,4-二羟基肉桂酸、牛磺胆酸)的ROC曲线图。
具体实施方式
下面将结合本发明具体实施例及附图，对本发明的技术方案进行详细地描述。显然，本部分所描述的具体实施例仅仅是实现本发明技术方案的一部分实施例，而不应理解为全部的实施方式。应当理解，本部分所描述的具体实施例仅用以解释本发明，并不用于限定本发明。基于本部分实施例，本领域一般技术人员可基于其启示，在没有进行创造性劳动前提下所能够获得的所有其他实施方式，都应属于本发明保护的范围。
实施例一 生物标志物的发现及测定方法
在本部分，发明人以示例目的提供腺瘤及结直肠癌风险评估的生物标志物的发现步骤，包括所述生物标志物的筛选方法及所筛查的生物标志物组合的定量测定方法，具体包括以下步骤：
步骤1，取腺瘤及结直肠癌病人和健康人生物样本并进行适当前处理；
步骤2，通过色谱质谱联用代谢组学分析方法，分析鉴定腺瘤及结直肠癌病人及健康人的生物样本中的初步差异性代谢物；
步骤3，在多维OPLS-DA模型的变量权重(VIP)值大于1及非参检验的P值小于0.05的选择标准下，得到进一步差异性代谢物；
步骤4，以逻辑回归模型进行验证，得到差异性代谢物。
所述步骤1中生物样本可以选自结直肠癌患者、良性腺瘤患者和健康人的尿液样本、血液样本和唾液样本；本领域一般技术人员可理解，在一次试验过程中，应选择这些受试体的同类型生物样本。
所述步骤2中的色谱质谱联用代谢组学分析方法包括液相/气相色谱质谱联用代谢组学分析方法。
作为具体实施方式之一，所述步骤2中选择气相色谱质谱联用，测试的色谱条件可以是：Rxi-5ms毛细管柱，载气：超纯氦气，流量：1.0mL/min，进样口温度：260℃， 传输线温度：260℃，离子源温度：210℃，进样量：1μL，进样方式：不分流进样，升温程序：从80℃开始并持续2min，以10℃/min的升温速度升至220℃，之后以5℃/min的升温速度升至240℃，再以25℃/min的升温速度升至290℃，最后在290℃持续8min，质谱离子源：EI源，电子轰击能量：70eV，质谱扫描范围：m/z，40-600，全扫描方式。
作为具体实施方式之一，所述步骤2中选择液相色谱质谱联用，测试的色谱条件包括：Agilent ZORBAX Eclipse XDB-C18柱(4.6×.6ent，5μm)，柱温：30℃。流动相A：水(0.1％甲酸)，B：乙腈(0.1％甲酸，)，流动相洗脱梯度为0-25min：1-100％B，流速：0.4mL/min，进样量：10μL。飞行时间质谱优化条件为：(1)正离子模式(ES+)，毛细管电压3500V，喷雾器45psig，干燥气温度325℃，干燥器流速11L/min；(2)负离子模式(ES-)，毛细管电压3000V，其他参数与正离子模式一致。在代谢物谱分析时，数据采集形式为plot和centroid同时进行，采集质量范围为50-1000Da。
所述步骤1中所述的样本前处理，以应用于气相色谱质谱联用测试的尿液和血清样本为例，其前处理步骤包括：取50μL血清，加入10μl氯苯丙氨酸(0.1mg/mL，水溶)和10μL十七酸(1mg/mL，醇溶)作为内标来监测样本的重现性；再加入175μL氯仿甲醇混合溶剂(1:3，v/v)，涡旋振荡30s；置离心管于-20℃放置10min以促进蛋白沉淀；然后13000rpm离心10min，取上清200μL于高回收进样瓶中，室温下真空干燥得到样品；将得到的样品使用两步法进行衍生，首先加入50μL甲氧胺(15mg/mL，吡啶溶)，涡旋振荡30s，在30℃下反应90min，然后再加入50μL BSTFA(含1％TMCS)在70℃反应60min，静置后进行GC-TOFMS分析。
所述步骤1中所述的样本前处理，以应用于液相色谱质谱联用测试的尿液和血清样本为例，其前处理步骤包括：取50μl血清样本与200μl含氯苯丙氨酸(5μg/mL，水溶)的甲醇乙腈混合液(5:3，v/v)混合，涡旋振荡2min，静置10min后，用13000rpm离心20min，取上清液作为待检测样本。
本发明的测定方法可以全面、综合地体现腺瘤及结直肠癌病人及健康人之间的代谢产物的变异状况，找到腺瘤及结直肠癌的诊断标记物，为腺瘤结直肠癌的早期诊断和预后提供有利的技术支持。
实施例二 受试体、生物样本及分组
收集临床确诊的结直肠腺瘤患者、结直肠癌患者及健康人的尿液样本，所述样本及收集经所在医疗机构伦理委员会批准。所收集的样本中，结直肠癌患者220例、腺瘤患者20例、健康人对照180例。结合实施例一，所述样本经处理后通过色谱质谱联用仪检测分析，通过建立多维统计模型可视化地显示腺瘤及结直肠癌病人及健康人对照之间的代谢谱差异，获得差异性代谢物。
实施例中的受试者包括按照临床诊断指标确认的结直肠癌患者、结直肠腺瘤患者和健康受试者；按照以下方案分为训练集和验证集，所测试的生物样本为受试者空腹中段晨尿样本。
(1)训练集
结直肠癌患者临床尿液样本100例，健康人对照尿液样本100例。
(2)验证集
结直肠癌患者临床尿液样本120例，健康人对照尿液样本80例；结直肠腺瘤患者尿液样本20例。
实施例三 气相色谱质谱联用仪(GC-TOFMS)测试尿液样本
采用气相色谱质谱联用仪测定训练集样本。
尿液样本前处理：取50μL尿液于1.5mL的离心管中，分别加入10μl氯苯丙氨酸(0.1mg/mL，水溶)和10μL十七酸(1mg/mL，醇溶)作为内标来监测样本的重现性。再加入175μL氯仿甲醇混合溶剂(1:3，v/v)，涡旋振荡30s；置离心管于-20℃放置10min以促进蛋白沉淀。然后13000rpm离心10min，取上清200μL于高回收进样瓶中，室温下真空干燥。
样本品经抽干后使用两步法进行衍生，首先加入50μL甲氧胺(15mg/mL，吡啶溶)，涡旋振荡30s，在30℃下反应90min，然后再加入50μL BSTFA(含1％TMCS)在70℃反应60min。反应产物在室温下静置1h后进行GC-TOFMS分析。
GC-TOFMS测定：Leco Pegasus HT气相色谱串联飞行时间质谱(力可公司，美国)，色谱柱：Rxi-5ms毛细管柱(填充5％联二苯/95％二甲基聚硅氧烷,Restek,宾夕法尼亚州,美国)，载气：超纯氦气，流量：1.0mL/min，进样口温度：260℃，传输线温度：260℃，离子源温度：210℃，进样量：1μL，进样方式：不分流进样，升温程序：从80℃开始并持续2min，以10℃/min的升温速度升至220℃，之后以5℃/min的升温速度升至240℃，再以25℃/min的升温速度升至290℃，最后在290℃持续8min。质谱离子源：EI源，电子轰击能量：70eV，质谱扫描范围：m/z，40-600，全扫描方式。
数据分析处理使用ChromaTOF软件(v4.33,力可公司，美国)。
实施例四 液相色谱串联质谱联用仪(LC-TQMS)测试尿液样本
采用液相色谱质谱联用仪测定训练集样本。
尿液样本前处理：取50μl尿液样本与200μl含氯苯丙氨酸(5μg/mL，水溶)的甲醇乙腈混合液(5:3，v/v)混合，涡旋振荡2min，静置10min后，用13,000rpm离心20min，取上清液用于LC-TOFMS分析。
LC-QTOFMS测试:超高效液相色谱(沃特斯公司，美国)，配备溶剂控制器、柱温 箱和样品控制器。质谱分析采用沃特斯质谱仪(沃特斯，美国)，配备电喷雾电离源。色谱柱:ACQUITY UPLC BEH C18(100mm×2.1mm,1.7μm)色谱柱，柱温：40℃。流动相A：水(0.1％甲酸)，B：乙腈(含30％异丙醇)，流动相洗脱梯度为0-20min：5-100％B，流速：0.4mL/min，进样量：5μL。串联质谱优化条件为：(1)正离子模式(ES+)，毛细管电压1500V，离子源温度150℃，干燥气温度550℃，干燥器流速1000L/hr；(2)负离子模式(ES-)，毛细管电压2000V，其他参数与正离子模式一致。
数据分析处理使用MassLynx软件(v4.1,沃特斯，美国)。
实施例五 差异代谢标志物的筛查
根据实施例三和实施例四，将训练集样本通过LC-QTOFMS和GC-TOFMS进行代谢物全谱分析测试，结果如图1A、1B、2A、2B和2C中所示，通过多维PCA以及OPLS-DA模型提供的变量权重VIP值(VIP＞1)及Mann-Whitney U检验所提供的P值(P＜0.05)的选择标准，从训练集样本中得到用于区分结直肠癌及健康人正常对照的77种初步差异性代谢物，包括赖氨酸，色氨酸，苏氨酸，组氨酸，瓜氨酸，酪氨酸，乳酸，肌肽，2-羟基丁酸，辛二酸，3-羟基丁酸，谷氨酰胺，丙酮酸，尿苷，琥珀酸，柠檬酸，乌头酸、异柠檬酸；2-甲基柠檬酸，吲哚乙酸，胍基乙酸，壬二酸，色胺、5-羟基吲哚乙酸、亚精胺、马尿酸、苯乙酸、乙酰乙酸，间羟基苯丙酸、甘氨酸、琥珀酸、5-羟基吲哚乙酸、对羟基苯乙酸、2-氨基丁酸、肉豆蔻酸、β-羟基丁酸、胱氨酸、泛酸、γ-氨基丁酸、异亮氨酸、缬氨酸、鸟氨酸、磷酸甘油、氨氧基乙酸、4-羟基-L-脯氨酸、富马酸、二十二碳六烯酸、苯丙氨酸、3,4-二羟基丁酸、3-甲基己二酸、假尿苷、丝氨酸、高丝氨酸，腐胺、黄原酸、α-羟基戊二酸、马尿酸、3-羟基苯甲酸、3-羟基异戊酰肉碱，3-羟基邻氨基苯甲酸，β-丙氨酸、棕榈油酸、半胱氨酸、谷氨酸、尿嘧啶、5-氧代脯氨酸、2-氨基丁酸、天冬氨酸、天冬酰胺，肌醇，同瓜氨酸，氧戊二酸，3,4-二羟基扁桃酸，4-羟基苯甲酸，羟基丙酸，3,4-二羟基肉桂酸，香草酸。
结果见图2A、2B、2C和2D。其中，图2A是通过OPLS-DA鉴定的结直肠癌患者相对于对照的差异代谢产物的火山图(VIP＞1，|相关系数|＞0.3)。图2B是通过单维统计分析在结直肠癌患者与对照组中鉴别出的代谢物的火山图(p<0.05，CRC中的代谢物显着增加(FC>1，红点)，CRC中的代谢物显着减少(FC<1，蓝点)；图2C是结直肠癌患者与对照的差异生物标志物的热图(Z评分范围为-2～2)；图2D是结直肠癌患者与健康对照之间的代表性差异代谢物的箱形图(p<0.05)。由结果可见，模型置换检验结果(图1C)中R2Y＝0.687，Q2Y＝0.64，同时R2截距小于0.3，Q2截距小于0.05，证明建立的PCA和OPLS-DA模型非常稳健。
实施例六 逻辑回归模型验证生物标志物
本实施例示例性地采用逻辑回归模型对初步差异代谢物与结直肠癌的关联性进行研究。
利用逻辑回归模型对实施例五筛查得到初步差异代谢物进行验证，发现表1所示的27个代谢物，即：3-羟基邻氨基苯甲酸，胍基乙酸，3,4-二羟基肉桂酸，壬二酸，辛二酸，苯丙酮酸，乙酰乙酸，甲基半胱氨酸，αα羟基异丁酸，N-甲基烟酰胺，水杨酸，酪氨酸，牛磺胆酸，苯乙酸，高丝氨酸，组氨酸，乙醇酸，3-羟基丁酸，苯乳酸，甲基丙二酸，琥珀酸，2-羟基-2-甲基丁酸，4-羟基脯氨酸，羟丙酸，富马酸，对羟基苯乙酸，肉豆蔻酸作为腺瘤及结直肠癌标记物的作用尤为重要。
表1.鉴定差异代谢物列表
代谢物 分类 P值 变化倍数(病人/健康对照) VIP值
3,4-二羟基肉桂酸 苯丙烷 6.21E-06 0.42 1.85
苯乳酸 苯丙烷酸 1.49E-03 1.52 1.19
壬二酸 脂肪酸 4.43E-05 2.14 1.44
辛二酸 脂肪酸 8.43E-03 1.20 1.94
肉豆蔻酸 脂肪酸 1.41E-02 1.02 0.03
胍基乙酸 有机酸 1.16E-04 0.63 1.57
α-羟基异丁酸 有机酸 1.26E-04 0.49 1.87
乙醇酸 有机酸 2.17E-04 0.58 1.66
2-羟基-2-甲基丁酸 有机酸 4.09E-04 0.61 1.69
羟丙酸 有机酸 1.28E-03 0.52 1.36
甲基丙二酸 有机酸 1.81E-02 0.54 1.57
琥珀酸 有机酸 2.11E-02 0.66 1.42
乙酰乙酸 有机酸 2.36E-02 1.54 2.04
3-羟基丁酸 有机酸 4.19E-02 1.45 1.92
富马酸 有机酸 4.72E-02 1.37 1.79
3-羟基邻氨基苯甲酸 苯甲酸 5.27E-04 1.92 1.81
水杨酸 苯甲酸 1.42E-04 0.57 1.17
苯丙酮酸 苯甲酸酯类 1.88E-02 1.35 1.14
苯乙酸 苯甲酸酯类 2.36E-02 1.51 1.11
对羟基苯乙酸 酚类 1.78E-02 0.74 0.98
牛磺胆酸 胆汁酸 2.30E-04 0.44 1.41
甲基半胱氨酸 氨基酸 3.12E-04 0.51 1.31
4-羟基脯氨酸 氨基酸 9.75E-03 0.56 1.25
高丝氨酸 氨基酸 7.14E-04 0.58 1.44
酪氨酸 氨基酸 9.48E-04 0.60 1.88
组氨酸 氨基酸 9.72E-04 0.44 1.83
N-甲基烟酰胺 吡啶类 1.43E-02 1.70 1.05
随后应用临床诊断性能曲线(ROC曲线)对上述得到的生物标志物在结直肠癌尿液样本进行评价。应用ROC曲线得到了满意的结果，对于训练集尿液样本AUC＝0.997,95％置信区间(CIs):0.991-1.000(图3)，其灵敏度为97％，特异度为100％。
通过训练集得到的这27个代谢物组对结直肠癌的预测概率参数使用验证集样本进行验证。用预测的概率来构建ROC曲线，其中验证集的AUC＝0.962(95％CIs:0.933-0.99)，曲线的灵敏度为87.5％，特异度为94.4％(图4)；而在早期结直肠癌患者(I+II期)和健康人对照的区分上，AUC＝0.974(95％CIs:0.949-1.00)，曲线的灵敏度为87.9％，特异度为100.0％(如图5中所示)；27个代谢物组用于区分40个结直肠癌患者和20个结直肠腺瘤患者时AUC＝0.89，灵敏度为78.9％，特异度为87.5％(图6)；对于区分腺瘤患者和健康对照，AUC＝0.934，灵敏度为79.1％，特异度为100.0％(图7)。
如图3所示，本实施例的这27种生物标志物及其组合(3-羟基邻氨基苯甲酸，胍基乙酸，3,4-二羟基肉桂酸，壬二酸，辛二酸，苯丙酮酸，乙酰乙酸，甲基半胱氨酸，α-羟基异丁酸，N-甲基烟酰胺，水杨酸，酪氨酸，牛磺胆酸，苯乙酸，高丝氨酸，组氨酸，乙醇酸，3-羟基丁酸，苯乳酸，甲基丙二酸，琥珀酸，2-羟基-2-甲基丁酸，4-羟基脯氨酸，羟丙酸，富马酸，对羟基苯乙酸，肉豆蔻酸)是很好的结直肠腺瘤及结直肠癌早期诊断标记物，可用于临床诊断，能提高腺瘤及结直肠癌的早期检出率，改善腺瘤及结直肠癌的临床治疗效果，减轻病人的痛苦，提高临床病人的生存率。
实施例七 生物标志物诊断模型的建立
根据实施例五和实施例六，从训练集样本中得到用于区分腺瘤及结直肠癌及正常对照的27种差异性代谢物，包括：3-羟基邻氨基苯甲酸，胍基乙酸，3,4-二羟基肉桂酸，壬二酸，辛二酸，苯丙酮酸，乙酰乙酸，甲基半胱氨酸，α-羟基异丁酸，N-甲基烟酰胺，水杨酸，酪氨酸，牛磺胆酸，苯乙酸，高丝氨酸，组氨酸，乙醇酸，3-羟基丁酸，苯乳酸，甲基丙二酸，琥珀酸，2-羟基-2-甲基丁酸，4-羟基脯氨酸，羟丙酸，富马酸，对羟基苯乙酸，肉豆蔻酸。
以建立有效的临床诊断模型为目的，进一步利用逻辑回归模型进行优化和验证，当 采用富马酸，肉豆蔻酸，组氨酸，酪氨酸，3,4-二羟基肉桂酸，牛磺胆酸作为腺瘤及结直肠癌风险评估标志物时，根据各诊断标志物在腺瘤及结直肠癌和正常对照组之间的差异倍数大小、显著性大小及其浓度值大小范围等综合因素，通过逻辑回归模型建立得分诊断模型：
模型得分P＝4.059*C1-0.019*C2-0.017*C3-0.011*C4-0.056*C5-0.25*C6+5.873
其中，C1为富马酸在生物样本中的浓度，C2为3,4-二羟基肉桂酸在生物样本中的浓度，C3为组氨酸在生物样本中的浓度，C4为牛磺胆酸在生物样本中的浓度，C5为酪氨酸在生物样本中的浓度，C6为肉豆蔻酸在生物样本中的浓度，以上浓度单位均为μM。通过受试者工作特征曲线(ROC)曲线分析，对结直肠癌的诊断阈值范围为-0.13至-0.11，最佳诊断阈值-0.12；腺瘤诊断阈值范围为-0.105至-0.09，最佳诊断阈值-0.10；通过每个样本的诊断标志物检测其浓度值，再根据诊断模型计算得分值，通过与诊断阈值的比较评估受试者是否患病或具有患病风险。
将诊断模型应用于训练集和验证集区分结直肠癌和健康人，训练集ROC曲线下面积：0.980，灵敏度96.6％，特异性100％，验证集ROC曲线下面积：0.980，灵敏度96.6％，特异性90.5％，见附图8。图9是结直肠癌患者和腺瘤患者的ROC曲线图。图10是腺瘤患者和健康对照的ROC曲线图。
采用上述方法，分别采用以下生物标志物组合建立诊断模型：
(一)富马酸，肉豆蔻酸，组氨酸，3,4-二羟基肉桂酸，牛磺胆酸
(二)组氨酸，3,4-二羟基肉桂酸，牛磺胆酸
(三)富马酸，牛磺胆酸
(四)牛磺胆酸、酪氨酸，3,4-二羟基肉桂酸
(五)富马酸，肉豆蔻酸，组氨酸，酪氨酸，3,4-二羟基肉桂酸
(六)富马酸，牛磺胆酸、组氨酸
(七)3,4-二羟基肉桂酸，牛磺胆酸
(八)富马酸，牛磺胆酸、组氨酸、3-羟基邻氨基苯甲酸、胍基乙酸、羟丙酸、富马酸、对羟基苯乙酸、肉豆蔻酸
(九)3,4-二羟基肉桂酸，壬二酸，辛二酸，苯丙酮酸，乙酰乙酸，甲基半胱氨酸，α-羟基异丁酸，N-甲基烟酰胺，水杨酸，酪氨酸，牛磺胆酸
(十)3-羟基邻氨基苯甲酸、胍基乙酸、3,4-二羟基肉桂酸、水杨酸、苯乳酸、甲基丙二酸、琥珀酸、2-羟基-2-甲基丁酸、4-羟基脯氨酸、羟丙酸、富马酸、对羟基苯乙酸、肉豆蔻酸
对上述建立的诊断模型对测试集进行验证，结果表明上述组合均对结直肠癌和健康 人、腺瘤和健康人、结直肠癌和腺瘤均有区分和诊断能力。见表2。
表2.部分生物标记物组合的诊断能力
Figure PCTCN2022094558-appb-000002
实施例八 检测腺瘤及结直肠癌的计算机系统的建立
根据实施例一至九，本实施例建立一种用于评估受试体腺瘤及结直肠癌风险的计算机系统，包括信息获取模块、腺瘤及结直肠癌风险评估模块、样品检测模块和样品前处理模块。
其中，所述信息获取模块至少用于执行以下操作：获取受试者样品中的生物标志物组合检测信息，所述生物标志物组合选自前所述的生物标志物组合。
所述腺瘤及结直肠癌风险评估模块至少用于执行以下操作：根据所述信息获取模块 获取的生物标志物组水平，评估所述受试者是否患有腺瘤及结直肠癌，或具有腺瘤及结直肠癌的患病风险；具体包括将所述信息获取模块获取的生物标志物组的水平输入诊断模型，根据诊断模型评估所述受试者是否患有腺瘤及结直肠癌或具有腺瘤及结直肠癌的患病风险。
所述诊断模型的建立及使用评估模型进行评估的方法参见前述实施例。本实施例计算机系统还可任选地，包括或不包括样品检测模块和/或样品前处理模块。所述样品检测模块，至少用于执行检测样品中所述生物标志物水平的操作；具体包括至少用于执行检测生物标志物的液相色谱串联质谱联用操作或气相色谱串联质谱联用操作，检测条件参见本说明书相关部分。所述样品前处理模型，至少用于执行检测样品用于检测进样前的操作；具体参照本说明书相关部分。
以上对本发明的具体实施例进行了详细描述，但只是作为示例目的，本发明并不限制于以上描述的具体实施例。对于本领域技术人员而言，任何对本发明进行的等同修改和替代也都在本发明的范畴之中。因此，在不脱离本发明的精神和范围下所作的均等变换和修改，都应涵盖在本发明的范围内。

Claims (9)

  1. 用于受试体腺瘤及结直肠癌风险评估的诊断产品，其特征在于，所述诊断产品的诊断指标包括受试体生物样本中的牛磺胆酸、富马酸、肉豆蔻酸、组氨酸、酪氨酸、3,4-二羟基肉桂酸中之一种或几种，及任选地包括以下组合A或组合B，或同时包括组合A和组合B：
    组合A：3-羟基邻氨基苯甲酸，胍基乙酸，壬二酸，辛二酸，苯丙酮酸，乙酰乙酸，甲基半胱氨酸，α-羟基异丁酸，N-甲基烟酰胺，水杨酸，苯乙酸，高丝氨酸，乙醇酸，3-羟基丁酸，苯乳酸，甲基丙二酸，琥珀酸，2-羟基-2-甲基丁酸，4-羟基脯氨酸，羟丙酸，对羟基苯乙酸中之一种或多种；
    组合B：赖氨酸，色氨酸，苏氨酸，瓜氨酸，乳酸，肌肽，2-羟基丁酸，辛二酸，3-羟基丁酸，谷氨酰胺，丙酮酸，尿苷，琥珀酸，柠檬酸，乌头酸、异柠檬酸；2-甲基柠檬酸，吲哚乙酸，胍基乙酸，壬二酸，色胺、5-羟基吲哚乙酸、亚精胺、马尿酸、苯乙酸、乙酰乙酸，间羟基苯丙酸、甘氨酸、琥珀酸、5-羟基吲哚乙酸、对羟基苯乙酸、2-氨基丁酸、β基羟基丁酸、胱氨酸、泛酸、γ-氨基丁酸、异亮氨酸、缬氨酸、鸟氨酸、磷酸甘油、氨氧基乙酸、4-羟基-L-脯氨酸、二十二碳六烯酸、苯丙氨酸、3,4-二羟基丁酸、3-甲基己二酸、假尿苷、丝氨酸、高丝氨酸，腐胺、黄原酸、α-羟基戊二酸、马尿酸、3-羟基苯甲酸、3-羟基异戊酰肉碱，3-羟基邻氨基苯甲酸，β-丙氨酸、棕榈油酸、半胱氨酸、谷氨酸、尿嘧啶、5-氧代脯氨酸、2-氨基丁酸、天冬氨酸、天冬酰胺，肌醇，同瓜氨酸，氧戊二酸，3,4-二羟基扁桃酸，4-羟基苯甲酸，羟基丙酸，3,4-二羟基肉桂酸，香草酸中的一种或多种；
    所述生物样本选自受试体的尿液、血液、唾液和粪便。
  2. 如权利要求1所述的用于受试体腺瘤及结直肠癌风险评估的生物标志物组合，其特征在于，所述诊断产品选自试剂盒、医疗器械、具有诊断模块的计算机系统和诊断装置。
  3. 用于受试体腺瘤及结直肠癌风险评估的生物标志物组合，其特征在于，所述生物标志物为受试体生物样本中的差异性代谢物，所述生物样本选自尿液、血液、唾液和粪便；所述生物标志物组合包括牛磺胆酸、富马酸、肉豆蔻酸、组氨酸、酪氨酸、3,4-二羟基肉桂酸之一种或几种，及任选地包括以下组合A或组合B，或同时包括组合A和组合B：
    组合A：3-羟基邻氨基苯甲酸，胍基乙酸，3,4-二羟基肉桂酸，壬二酸，辛二酸，苯丙酮酸，乙酰乙酸，甲基半胱氨酸，α-羟基异丁酸，N-甲基烟酰胺，水杨酸，苯乙酸， 高丝氨酸，乙醇酸，3-羟基丁酸，苯乳酸，甲基丙二酸，琥珀酸，2-羟基-2-甲基丁酸，4-羟基脯氨酸，羟丙酸，对羟基苯乙酸中之一种或多种；
    组合B：赖氨酸，色氨酸，苏氨酸，瓜氨酸，乳酸，肌肽，2-羟基丁酸，辛二酸，3-羟基丁酸，谷氨酰胺，丙酮酸，尿苷，琥珀酸，柠檬酸，乌头酸、异柠檬酸；2-甲基柠檬酸，吲哚乙酸，胍基乙酸，壬二酸，色胺、5-羟基吲哚乙酸、亚精胺、马尿酸、苯乙酸、乙酰乙酸，间羟基苯丙酸、甘氨酸、琥珀酸、5-羟基吲哚乙酸、对羟基苯乙酸、2-氨基丁酸、β-羟基丁酸、胱氨酸、泛酸、γ-氨基丁酸、异亮氨酸、缬氨酸、鸟氨酸、磷酸甘油、氨氧基乙酸、4-羟基-L-脯氨酸、二十二碳六烯酸、苯丙氨酸、3,4-二羟基丁酸、3-甲基己二酸、假尿苷、丝氨酸、高丝氨酸，腐胺、黄原酸、α-羟基戊二酸、马尿酸、3-羟基苯甲酸、3-羟基异戊酰肉碱，3-羟基邻氨基苯甲酸，β-丙氨酸、棕榈油酸、半胱氨酸、谷氨酸、尿嘧啶、5-氧代脯氨酸、2-氨基丁酸、天冬氨酸、天冬酰胺，肌醇，同瓜氨酸，氧戊二酸，3,4-二羟基扁桃酸，4-羟基苯甲酸，羟基丙酸，3,4-二羟基肉桂酸，香草酸中的一种或多种。
  4. 如权利要求3所述的用于受试体腺瘤及结直肠癌风险评估的生物标志物组合用于制备评估腺瘤及结直肠癌的诊断产品的用途，其特征在于，所述诊断产品以权利要求3所述的生物标志物的含量作为评估指标。
  5. 如权利要求4所述的用途，其特征在于，所述诊断产品包括试剂盒、医疗器械、具有诊断模块的计算机系统和诊断装置。
  6. 一种定量检测权利要求3所述的生物标志物组合的试剂盒，其特征在于，所述试剂盒包括生物标志物的标准品和生物标志物提取剂，所述生物标志物提取剂选自有机溶剂和水的混合物，有机溶剂选自异丙醇、甲醇、乙腈之一种或多种。
  7. 如权利要求6所述的试剂盒，其特征在于，所述试剂盒包括衍生化试剂。
  8. 权利要求3所述的生物标志物组合的定量检测方法，其特征在于，所述方法包括对受试者的生物样本进行处理后，以色谱质谱联用代谢组学分析方法对生物样本中的生物标志物组合进行定量检测，所述色谱质谱联用代谢组学分析方法包括液相色谱质谱联用代谢组学分析方法和气相色谱质谱联用代谢组学分析方法。
  9. 一种用于评估受试体腺瘤及结直肠癌风险的计算机系统，其特征在于，所述系统包括信息获取模块和受试体腺瘤及结直肠癌风险评估模块；
    其中，所述信息获取模块至少用于执行以下操作：获取受试者样品中的代谢标志物组合检测信息，所述代谢标志物组合选自权利要求3所述的代谢标志物组合；
    所述受试体腺瘤及结直肠癌风险评估模块至少用于执行以下操作：根据所述信息获取模块获取的代谢标志物组水平，评估所述受试者是否患有腺瘤及结直肠癌风险或具有 腺瘤及结直肠癌的患病风险。
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