Site-specific glycoform marker for diagnosis of gastric cancer and / or early gastric cancer and application of site-specific glycoform marker

Abstract

The invention provides a novel site-specific glycoform marker for diagnosis of gastric cancer and early gastric cancer, and particularly relates to one or a combination of five site-specific glycoform markers. The invention relates to application of a site-specific glycoform marker in gastric cancer diagnosis, in particular to a kit, equipment, a system and / or a combination thereof for quantitatively detecting the content level of the site-specific glycoform marker in an object biological sample and used for gastric cancer diagnosis or early diagnosis of gastric cancer, which comprises a reagent and / or an instrument for determining the content of site-specific glycoforms. The module or the processor is used for calculating the content of site-specific glycoforms, and the module or the processor is used for judging whether an object suffers from gastric cancer or not according to the content of the site-specific glycoforms. Generally speaking, by measuring the content level of the site-specific glycotype marker in a biological sample, patients with gastric cancer and healthy people are effectively distinguished, and the kit is used for screening and diagnosing gastric cancer and early gastric cancer and has important fundamental research and clinical application prospects.

Description

Technical Field

[0001] The present invention relates to the field of medical biological detection technology and the diagnosis and prevention of gastric cancer. The present invention discloses a site-specific glycoform marker for gastric cancer diagnosis and its application, and in particular, the present invention relates to a novel site-specific glycoform marker and the application of measuring the content of the site-specific glycoform marker in the clinical diagnosis of gastric cancer and early gastric cancer. Background Art

[0002] Gastric cancer is the fifth most commonly diagnosed cancer and the third most deadly cancer in the world. This is mainly because early gastric cancer has no obvious symptoms and a long latent period, which leads to late diagnosis, rapid metastasis and low treatment efficiency (World J Gastroenterol, 2019, 25(17): 2029). In China, more than 80% of gastric cancer patients are diagnosed in the late stage, resulting in a five-year survival rate of only 35.1%. Traditional gastric cancer diagnosis mainly relies on endoscopy and biopsy. This invasive diagnosis and treatment method causes more pain to patients and may also lead to missed diagnosis due to the lack of obvious clinical symptoms of early gastric cancer, making it difficult to diagnose gastric cancer quickly and efficiently. However, cancer-related genes, proteins and metabolites exist in body fluids such as blood, urine and gastric juice. Detection of such body fluid-based markers is a non-invasive diagnostic method with good application prospects. At present, specific markers for gastric cancer include pepsinogen I, pepsinogen II, gastrin 17 and anti-Helicobacter pylori antibodies, but they are mainly used to identify patients at risk of developing gastric cancer. Serum markers for gastric cancer include carcinoembryonic antigen (CEA), CA125, CA72-4, and CA19-9, but they have poor specificity and sensitivity for the diagnosis of gastric cancer and are difficult to use for early diagnosis of gastric cancer.

[0003] Protein is the material basis of life activities, among which protein glycosylation is the most abundant and complex protein post-translational modification in eukaryotic cells. In protein glycosylation, the biosynthesis of sugar chains occurs through a complex metabolic and enzymatic reaction network without a template, and is therefore highly sensitive to physiological state. Abnormal changes in protein glycosylation, especially abnormal expression of polysaccharides on specific proteins or sites, have been found to be closely related to the occurrence and development of diseases. For example, the content of core fucosylated alpha-fetoprotein (abbreviated as AFP-L3) is significantly increased compared with alpha-fetoprotein (AFP) in the early stages of tumors, which can improve the early diagnosis of liver cancer and serve as a biomarker for liver cancer diagnosis (CLINICA CHIMICAACTA, 2001, 313 (1-2): 15); CA19-9 is a polysaccharide containing four sugar units, and fibrin modified by CA19-9 has been found to increase the interaction with the epidermal growth factor receptor, resulting in severe pancreatitis symptoms in mouse models (Science, 2019, 364 (6446): 1156). Therefore, protein glycosylation-related markers, especially site-specific glycoform markers, have great advantages and potential in cancer diagnosis.

[0004] Site-specific glycoforms include three types of information: glycoproteins, glycosylation sites, and sugar chains. This information can be obtained by analyzing intact glycopeptides using mass spectrometry-based glycoproteomics technology. In recent years, with the development of sample pretreatment technology, data acquisition methods, and spectrum analysis software, mass spectrometry-based glycoproteomics technology has become a powerful tool for studying changes in site-specific glycoforms in diseases (Anal Chem, 2020, 92(1): 267). At present, there is little development of site-specific glycoform markers for gastric cancer diagnosis. One of the main reasons is that the application of glycoproteomics technology in the field of biomarkers is immature. Therefore, there is an urgent need to explore the deep glycoproteomics of gastric cancer, develop site-specific glycoform evaluation or screening methods, discover highly sensitive and highly specific site-specific glycoform markers, promote early detection and early treatment of gastric cancer, and meet urgent clinical needs. This is of great significance for further clarifying the pathological mechanism and early diagnosis of gastric cancer. Summary of the invention

[0005] In view of the current lack of diagnostic markers for gastric cancer and early gastric cancer, as well as the low sensitivity and specificity, the present invention discloses a site-specific glycoform marker for gastric cancer diagnosis and its application. Specifically, the present invention relates to a novel site-specific glycoform marker for gastric cancer diagnosis, and the present invention also relates to a reagent, a kit, a device, a system and / or a combination thereof for quantitatively detecting the content level of the site-specific glycoform marker in a biological sample of a subject and for gastric cancer diagnosis or early gastric cancer diagnosis.

[0006] The first aspect of the present invention provides a novel site-specific glycoform marker.

[0007] (1) The site-specific glycoform marker comprises one or a combination of two or more (two, three, four or five) of the following site-specific glycoforms: the glycoform Hex(7)HexNAc(6)NeuAc(4)Fuc(1) (abbreviated as AACT-N 106 -H7N6S4F1), the glycoform Hex(6)HexNAc(4)NeuAc(2) linked to the 271st N-glycosylation site on antitrypsin (abbreviated as A1AT- 271 -H6N4S2), the glycoform Hex(4)HexNAc(3)NeuAc(1) linked to the 352nd N-glycosylation site on C1 esterase inhibitor (abbreviated as IC1-N 352 -H4N3S1), the glycoform Hex(5)HexNAc(4)NeuAc(1)Fuc(2) linked to the 254th N-glycosylation site on C1 esterase inhibitor (abbreviated as IC1-N 254 -H5N4S1F2) and the glycoform Hex(5)HexNAc(4)NeuAc(2) linked to the 91st N-glycosylation site on the heavy chain of trypsin inhibitor H3 (abbreviated as ITIH3-N 91 -H5N4S2).

[0008] (2) The site-specific glycoform is a sugar chain attached to a specific glycosylation site on a specific protein or protein fragment.

[0009] Another aspect of the present invention provides the use of detecting site-specific glycoform markers in the diagnosis of gastric cancer and / or early gastric cancer, specifically, a reagent, kit, device or system or a combination of two or more thereof for quantitatively detecting the content level of site-specific glycoform markers in the biological sample of the subject and used for gastric cancer detection, diagnosis and / or early diagnosis.

[0010] (1) The reagent, kit, device or system or a combination of two or more thereof comprises a reagent and / or instrument for determining the content of site-specific glycoform markers, and the determination method includes but is not limited to: one or more of chromatography, spectroscopy, mass spectrometry or chemical analysis; the chromatography includes one or more of high performance liquid chromatography or thin layer chromatography; the spectroscopy includes one or more of nuclear magnetic resonance spectroscopy, refractive index spectroscopy, ultraviolet spectroscopy or near infrared spectroscopy; the mass spectrometry includes one or more of matrix-assisted laser desorption time-of-flight mass spectrometry, high resolution mass spectrometry or liquid chromatography-mass spectrometry.

[0011] (2) The reagent, kit, device or system or a combination of two or more thereof further comprises a module or processor for calculating the site-specific glycoform content.

[0012] (3) The reagent, kit, device or system or a combination of two or more thereof further comprises a module or processor for determining whether the subject suffers from gastric cancer based on the site-specific glycoform content in the subject's biological sample.

[0013] (4) The content of the site-specific glycoform marker is an absolute content, relative to the content of all sugar chains of all proteins or purified proteins, or relative to the content of an added internal standard (e.g., a site-specific sugar standard). The relative content can be one or more of, but not limited to, percentage, reciprocal, logarithm, or other transformation forms.

[0014] (5) The biological sample may be, but is not limited to, body fluids (such as blood, urine, gastric juice, saliva, etc.), tissues, cells, and purified proteins.

[0015] (6) The reagents, kits, equipment or systems or a combination of two or more thereof also include the combined use of other indicators of gastric cancer for the detection, diagnosis and early diagnosis of gastric cancer. The indicators include, but are not limited to: i) tumor biomarker indicators, such as one or more of CEA, CA19-9, AFP, AFP-L3, PSA or CA125. ii) basic information of the patient, such as one or more of age, gender, medical history or family history. iii) clinical manifestations of the patient, including systemic manifestations, such as one or more of fever, infection, weight loss or anemia; including local manifestations, such as one or more of lumps or secretions. iv) physical and chemical examination indicators, including imaging examinations, such as one or more of MRI, CT, B-ultrasound or endoscopy.

[0016] In other aspects of the present invention, a method for screening drugs and / or therapies is provided, the method comprising: detecting site-specific glycoform markers in biological samples of a subject before, during and / or after medication and / or treatment, and determining the content of the site-specific glycoform markers; judging the effectiveness of the drug and / or therapy based on the content of the site-specific glycoform markers in the biological sample of the subject.

[0017] Technical Solution

[0018] The purpose of the present invention is to determine whether a subject has gastric cancer by detecting the content level and changes of site-specific glycoform markers in the subject's biological sample. The diagnostic effect of the site-specific glycoform markers proposed by the present invention, when used alone or in combination, is significantly better than that of the classic gastric cancer marker serum CEA, overcoming the deficiencies and defects mentioned in the background technology, and having important prospects for basic research and clinical application.

[0019] The technical solution adopted by the present invention is as follows, taking mass spectrometry as an example, but not limited to mass spectrometry:

[0020] 1) Collection of biological samples from subjects;

[0021] 2) Extract proteins, purify proteins and / or enzymatic peptides from biological samples;

[0022] 3) separation, purification and / or enrichment of intact glycopeptides and / or site-specific glycoforms;

[0023] 4) Detection of intact glycopeptides and / or site-specific glycoforms;

[0024] 5) Retrieve, identify and / or store intact glycopeptides and / or site-specific glycoforms;

[0025] 6) Calculate the content of site-specific glycoform markers;

[0026] 7) comparing the site-specific glycoform content of the subject with that of the control to determine whether the subject suffers from gastric cancer and / or early gastric cancer;

[0027] 8) Provide test and / or diagnosis results and / or reports.

[0028] Supplementary explanation of the technical solution:

[0029] a. The collection in step 1) specifically comprises: extracting the biological sample of the subject by conventional methods known in the art, and then using fresh or frozen biological samples to perform the test of the present invention.

[0030] The biological sample includes, but is not limited to, body fluids (such as blood, urine, gastric juice, saliva, etc.), tissues, cells, and purified proteins.

[0031] The storage method is a conventional method known in the art, which can be but not limited to: a liquid nitrogen tank, a -80°C refrigerator, a -20°C refrigerator, etc.

[0032] b. The extraction in step 2) specifically comprises: obtaining the protein by extracting the whole protein or extracting the purified protein, and then hydrolyzing the protein by protease to obtain the peptide fragments.

[0033] The method for extracting whole protein includes, but is not limited to, solution method, filter-assisted sample preparation (FASP) method, organic solvent precipitation method, etc. The method for extracting and purifying protein includes, but is not limited to, purification column, liquid chromatography, affinity chromatography, etc.

[0034] The protease includes, but is not limited to: specific proteases, such as trypsin, chymotrypsin protease, Glu-C protease, etc.; non-specific proteases, such as Pronase E protease, Elastase protease, etc. The protease can be obtained commercially or expressed and separated and purified by oneself.

[0035] The peptide segment can be optionally treated with a filter membrane or a desalting column to obtain a purified or desalted peptide segment.

[0036] c. The enrichment in step 3) specifically comprises: using a glycopeptide enrichment method to separate and collect intact glycopeptides from protein enzymatic peptide fragments.

[0037] The glycopeptide enrichment method includes, but is not limited to, a chromatographic column or kit based on hydrophilic interaction chromatography, lectin affinity chromatography, immunoaffinity chromatography, metal affinity chromatography, boric acid chemistry, hydrazide chemistry, enzyme chemistry, etc. The method does not destroy the sugar chain on the site-specific glycoform marker. The chromatographic column or kit can be obtained from commercial sources, or from commercially available and / or self-synthesized materials and self-made chromatographic columns and / or kits.

[0038] d. The detection in step 4) specifically comprises: separating, ionizing, fragmenting and / or collecting glycopeptide spectra of the intact glycopeptide sample by mass spectrometry.

[0039] The mass spectrometry includes, but is not limited to, matrix-assisted laser desorption / time-of-flight mass spectrometry, high-resolution mass spectrometry, liquid chromatography-mass spectrometry, and the like.

[0040] e. The search described in step 5) is specifically: using proteomics spectrum search software to perform a database search on the complete glycopeptide spectrum, and further identifying site-specific glycoforms.

[0041] The proteomics spectrum retrieval software may be, but is not limited to, conventional proteomics spectrum retrieval software (such as MaxQuant, etc.) and glycoproteomics spectrum retrieval software (such as Glyco-Decipher, etc.).

[0042] The database may be, but is not limited to: a whole human proteomics database, a specific human proteomics database.

[0043] The complete glycopeptide and / or site-specific glycoform is specifically: the complete glycopeptide contains three parts of information, namely, protein, site and sugar chain; on the one hand, for the case where the three parts of information of protein, site and sugar chain corresponding to multiple complete glycopeptides are different, these complete glycopeptides belong to different site-specific glycoforms respectively; on the other hand, due to the influence of missed cleavage of proteases, for the case where the peptide sequences corresponding to multiple complete glycopeptides are different, but the three parts of information of protein, site and sugar chain are exactly the same, these complete glycopeptides belong to the same site-specific glycoform.

[0044] f. The calculation described in step 6) is specifically as follows: the quantitative value of the intact glycopeptide is obtained by a primary spectrum quantification method, a secondary spectrum quantification method, or a spectrum number quantification method; in the case where a site-specific glycoform corresponds to only one intact glycopeptide, the content of the site-specific glycoform is the quantitative value of the intact glycopeptide; in the case where a site-specific glycoform corresponds to multiple intact glycopeptides, the content of the site-specific glycoform is the sum of the quantitative values ​​of the multiple intact glycopeptides.

[0045] The content may be, but is not limited to, an absolute content, a relative content relative to all proteins or all sugar chains of purified proteins, or a relative content relative to an added internal standard (e.g., a site-specific sugar standard). The relative content may be, but is not limited to, a percentage, a reciprocal, a logarithm, or other transformation forms.

[0046] g. The investigation described in step 7) (comparing the site-specific glycoform content of the subject with that of the control to determine whether the subject suffers from gastric cancer and / or early gastric cancer) is specifically as follows: using statistically relevant programs or software, fitting the receiver-operating characteristic (ROC) curve through the content of site-specific glycoform markers of patients and controls, and calculating the area under the curve (AUC) to evaluate the sensitivity and specificity of a single marker or a combination of markers.

[0047] The statistics-related program or software may be, but is not limited to: pROC program package of R language, graphpadprism software, SPSS software, etc.

[0048] The site-specific glycoform marker used alone or in combination may be AACT-N 106 -H7N6S4F1、A1AT-N 271 -H6N4S2、IC1-N 352 -H4N3S1、IC1-N 254 -H5N4S1F2 and ITIH3-N 91 -Any one or combination of H5N4S2.

[0049] h. The application described in step 8) (providing detection and / or diagnosis results and / or reports) is specifically: the site-specific glycoform markers proposed in the present invention can be used alone or in combination for the clinical diagnosis of gastric cancer patients, and can also be used for the clinical diagnosis of early gastric cancer patients. Optionally, they can be used for the screening of drugs and / or therapies.

[0050] i. Those skilled in the art may arbitrarily combine the aforementioned technical solutions and technical features without departing from the inventive concept and protection scope of the present invention.

[0051] The present invention has the following advantages, including but not limited to:

[0052] (1) The present invention discloses a site-specific glycoform marker for gastric cancer diagnosis and its application. On the one hand, a new site-specific glycoform marker for gastric cancer and early gastric cancer diagnosis is provided, specifically one or two, three, four or five combinations of five site-specific glycoform markers; on the other hand, the application of site-specific glycoform markers in gastric cancer or early gastric cancer diagnosis is provided, specifically a kit, device, system and / or combination thereof for quantitatively detecting the content level of site-specific glycoform markers in the biological sample of the object and used for gastric cancer detection, diagnosis or early diagnosis, including reagents and / or instruments for determining the content of site-specific glycoform markers, modules or processors for calculating the content of site-specific glycoform markers, and modules or processors for judging whether the object suffers from gastric cancer based on the content of site-specific glycoforms in the biological sample of the object. The present invention broadens the application of glycoproteomics technology in the fields of biotechnology and medicine, and also promotes the application of new site-specific glycoform markers in the field of tumor diagnosis.

[0053] (2) The product provided by the present invention can detect gastric cancer patients and / or early gastric cancer patients efficiently, sensitively and specifically by measuring the content of site-specific glycoform markers in the subject's biological sample, and finds significant differences between healthy people and gastric cancer patients or early gastric cancer patients, providing a basis for subsequent basic research and clinical application.

[0054] (3) The site-specific glycoform markers provided by the present invention can be used alone or in combination to effectively distinguish gastric cancer patients from healthy people, with an AUC value of up to 0.95, a specificity of 90%, and a sensitivity of 90%.

[0055] (4) The site-specific glycoform markers provided by the present invention can be used alone or in combination to effectively distinguish between early gastric cancer patients and healthy people, with an AUC value of up to 0.98, a specificity of 100%, and a sensitivity of 90%.

[0056] (5) The present invention proposes a site-specific glycoform marker, which is a new biomarker for gastric cancer diagnosis. Compared with serum CEA, a classic gastric cancer marker, it has a better diagnostic effect, is conducive to early clinical intervention, and improves the survival rate of patients.

[0057] The present invention can effectively distinguish gastric cancer patients from healthy people by measuring the content level of site-specific glycoform markers in biological samples, and is used for screening and diagnosis of gastric cancer and early gastric cancer, which has important prospects for basic research and clinical application. BRIEF DESCRIPTION OF THE DRAWINGS

[0058] Figure 1 The five site-specific glycoform markers proposed in the present invention and their structural information;

[0059] Figure 2 The content distribution of serum CEA and site-specific glycoform markers used alone or in combination in cohort A and the ROC curve for diagnosing gastric cancer patients in Example 1;

[0060] Figure 3 The content distribution of serum CEA and site-specific glycoform markers used alone or in combination in cohort B and the ROC curve for diagnosing gastric cancer patients in Example 2;

[0061] Figure 4 The content distribution of serum CEA and site-specific glycoform markers used alone or in combination in cohort C and the ROC curve for diagnosing early gastric cancer patients in Example 3;

[0062] Figure 5 The content distribution of serum CEA and site-specific glycoform markers used alone or in combination in cohort D and the ROC curve for diagnosing early gastric cancer patients in Example 4;

[0063] The superscripts of the amino acids represent their order in the complete amino acid sequence of the protein.

[0064] *** represents p<0.001, ** represents p<0.01, and * represents p<0.05. The smaller the p value and the more asterisks there are, the greater the significance of the difference. ns represents p>0.05, indicating that the difference is not significant. DETAILED DESCRIPTION

[0065] The present invention is further described in detail below in conjunction with the accompanying drawings and examples. It should be noted that the following examples are intended to facilitate understanding of the present invention and do not have any limiting effect on it. The reagents used in this example are all known products and were obtained by purchasing commercially available products.

[0066] Example 1 Screening gastric cancer patients in cohort A using one, two, three, four or five of the five site-specific glycoform markers

[0067] 1.1 Sample source:

[0068] All participant samples were obtained from the Xijing Hospital of the Fourth Military Medical University. After signing informed consent with the participants and approval by the Ethics Committee of the Drug Clinical Trials of the First Affiliated Hospital of the Fourth Military Medical University, serum samples from 70 healthy people and 70 gastric cancer patients were collected as cohort A. Among them, the gender distribution of the healthy population was 40 males and 30 females, with an age range of 26-86 years old and an average age of 58 years old; the gender distribution of gastric cancer patients was 44 males and 26 females, with an age range of 20-86 years old and an average age of 58 years old; therefore, the gender distribution ratio of the healthy population and gastric cancer patients in cohort A was similar, and the average age distribution was the same, so as to exclude the differences in glycosylated proteomes caused by gender and age. All gastric cancer patients were divided into 24 cases of gastric cancer stage I, 23 cases of gastric cancer stage II, and 23 cases of gastric cancer stage III. All serum samples were measured for serum CEA using a tumor marker detection kit in the hospital laboratory, and their serum CEA values ​​were recorded. Among them, the serum CEA values ​​of healthy people ranged from 0.65 to 9.97 ng / mL, and the serum CEA values ​​of gastric cancer patients ranged from 0 to 446.9 ng / mL. All samples were stored at -80°C for use.

[0069] 1.2 Methods for preparation of intact glycopeptides, mass spectrometry analysis, database retrieval, and site-specific glycoform content analysis in clinical serum samples:

[0070] Take 5 μL of clinical serum samples, add 45 μL of 100 mM ammonium bicarbonate buffer solution (pH = 8.2) containing 8 M urea, add dithiothreitol with a final concentration of 20 mM, mix well and place in a 37 ° C water bath for 2 hours. Then add iodoacetamide with a final concentration of 40 mM, mix well and place in a 25 ° C oscillator in the dark for 40 minutes. Then add 180 μL of 100 mM ammonium bicarbonate buffer solution, add 6 μg of trypsin, mix well and place in a 37 ° C water bath for enzymatic reaction for 16 hours, which is the enzymatic solution.

[0071] After the above reaction is completed, 12 μL of 20% trifluoroacetic acid solution is added to the enzymatic hydrolyzate. Take a desalting column (the filler is PRiME HLB, the filler weight is 10 mg, the brand is Oasis, Waters), first add 600 μL of methanol solution for activation, and then add 600 μL of 0.1% trifluoroacetic acid solution for balance. Then all the enzymatic hydrolyzate is loaded into the desalting column, and after the enzymatic hydrolyzate flows through the desalting column, 600 μL of 0.1% trifluoroacetic acid solution is added for elution, and finally 400 μL of 80% acetonitrile (containing 0.1% trifluoroacetic acid) aqueous solution is added for elution, and this part of the eluate is collected and freeze-dried to obtain the enzymatic peptide segment.

[0072] The above enzymatic peptide fragments were taken and redissolved in 36 μL of 80% acetonitrile (containing 0.1% trifluoroacetic acid) aqueous solution, and the entire solution was loaded into a liquid chromatograph equipped with a hydrophilic interaction chromatography column (model: Waters Acuity UPLC, Waters Company) (the preparation process of the hydrophilic interaction chromatography column is: a silane coupling agent (structure: X 3 Si-(CH 2 ) 3 -A, where X is -OCH 2 CH 3 , A is Br -), sodium azide and catalyst (potassium iodide) were mixed in acetonitrile solvent in a molar ratio of 1:2:0.08, with each gram of silane coupling agent corresponding to 20 mL of acetonitrile solvent, and reacted at 110°C for 16 h; then microspherical silica gel (particle size 5 μm) was added, with each gram of silica gel corresponding to 8 mmol of silane coupling agent, and heated at 160°C for 16 h, and then heated at 120°C for 16 h. The product was filtered and washed with dichloromethane, ethanol, water, and acetone in turn to obtain an azidized derivative. Silica; maltose and propargylamine are mixed, with 80 mL of propargylamine for each gram of maltose, and the mixture is reacted at 80°C for 24 hours, and then the reaction system is poured into an acetonitrile solvent for precipitation, with 80 mL of acetonitrile solvent for each gram of maltose, to obtain alkynyl-derivatized maltose; then the azide-derivatized silica prepared above is added to a water / ethanol mixed solvent (volume ratio 1:1), with 30 mL of the mixed solvent for each gram of silica gel, and then the alkynyl-derivatized maltose (alkynyl-derivatized The mass ratio of maltose and azide-derivatized silica is 2:1) and a catalyst (the catalyst is copper sulfate and sodium ascorbate, the molar ratio is 1:1; the molar amount of the catalyst is 30% of the molar amount of the alkynyl-derivatized maltose), react at 60°C for 60h, and the modified alkynyl-derivatized maltose is bonded to the silica gel surface by click chemistry reaction to obtain click maltose microspheres with a particle size of 5μm; then the click maltose microspheres are loaded into a capillary chromatographic column as a filler to prepare a hydrophilic interaction chromatographic column with a specification of 50mm in length × 2.1mm in inner diameter); after loading, first rinse for 11min under the condition that the mobile phase is an acetonitrile (containing a trifluoroacetic acid) aqueous solution with a volume concentration of 80%; then rinse and elute for 2min under the condition that the mobile phase is an acetonitrile (containing a trifluoroacetic acid) aqueous solution with a volume concentration of 30%, collect this part of the eluate and freeze-dry it, which is the N-intact glycopeptide sample.

[0073] The above-mentioned N-intact glycopeptide sample was taken and redissolved in 10 μL of a 0.1% formic acid aqueous solution, and all of it was loaded into a liquid chromatograph (model Dionex Ultimate 3000, Thermo Fisher Scientific) equipped with a C18 chromatographic column (filler is C18 microspheres, filler particle size is 2 μm, chromatographic column specifications are inner diameter 1 mm×length 15 cm, product number 164711, Thermo Fisher Scientific) and a tandem mass spectrometer (model Orbitrap Exploris480, Thermo Fisher Scientific) for liquid chromatography-mass spectrometry (LC-MS / MS) analysis. The separation parameters of the LC-MS / MS analysis method are: flow rate of 50 μL / min, mobile phase A is 0.1% by volume formic acid aqueous solution, mobile phase B is 80% by volume acetonitrile (containing 0.1% by volume formic acid) aqueous solution, liquid phase gradient (volume ratio) is: maintain 4% B phase within 0.5 min, linearly increase from 4% B phase to 9% B phase within 0.5 min, linearly increase from 9% B phase to 45% B phase within 51 min, maintain 95% B phase within 2 min, adjust the mobile phase ratio in steps and maintain 4% B phase within 6 min. The detection parameters of the LC-MS / MS analysis method are as follows: the mass spectrometer detector adopts the scanning mode of positive ions and the acquisition mode of DDA; the primary spectrum acquisition parameters are the resolution of 60000, the maximum gain control of 300, the maximum ion injection time of 25ms, and the acquisition mass-to-charge ratio range of 350-1800; the secondary spectrum acquisition parameters are the resolution of 30000, the maximum gain control of 200, the maximum ion injection time of 100ms, the isolation window of 2 mass-to-charge ratios, and the step-by-step normalized collision fragmentation energy of 20%-30%-40%.

[0074] The raw files obtained from the above LC-MS / MS analysis were searched by the glycopeptide search software Glyco-Decipher to obtain the identification and quantification results of complete glycopeptides. The database search parameters were set as follows: the human proteome database was released by the UniProt website (https: / / www.uniprot.org / ) in March 2019, containing 20,404 proteins; the sugar database was the GlyTouCan sugar library built into the software (database website: https: / / glytoucan.org / ); the mass deviations of the parent ion and fragment ion were set to 10 ppm and 20 ppm, respectively; the enzyme cleavage specificity was full trypsin cleavage, allowing up to 3 missed cleavage sites; the fixed modification was alkylation of cysteine ​​residues, and the variable modification was oxidation of methionine residues. The complete glycopeptide identification strategy of the software is to identify peptides by matching the peptide fragment ions of the secondary spectra in the raw files, identify sugar chains by matching sugar fragment ions, and finally achieve the identification of complete glycopeptides. The complete glycopeptide quantitative strategy of the software is: extract the chromatographic elution curve of the complete glycopeptide parent ion in the primary spectrum of the raw file, and use the peak area under the curve as the quantitative value of the complete glycopeptide. Finally, the software exports a corresponding result file (.xlsx) based on each raw file. The result file contains information such as complete glycopeptide, sugar chain, glycosylation site, protein, and quantitative value.

[0075] Subsequently, the quantitative values ​​of intact glycopeptides are converted to the content of site-specific glycoforms in the result file. The rule is: intact glycopeptides (G+P) are composed of sugar chains (G) and peptide sequences (P), and site-specific glycoforms (G+S) are composed of sugar chains (G) and glycosylation sites (S); among them, a peptide sequence corresponds to only one glycosylation site (e.g. P a Corresponding to S 1 , P b Corresponding to S 2 , P c Corresponding to S 2 ), and a glycosylation site can correspond to a peptide sequence (e.g. S 1 Corresponding to P a ) or multiple peptide sequences (e.g. S 2 Corresponding to P b and P c , at this time P b and P c When a glycosylation site corresponds to only one peptide sequence, the site-specific glycoform (G x +S 1 ) content is equal to that of the complete glycopeptide (G x +P a ) quantitative value; when a glycosylation site corresponds to multiple peptide sequences, the site-specific glycoform (G x+S 2 ) is equal to multiple complete glycopeptides (G x +P b , G x +P c ) is the sum of the quantitative values ​​of .

[0076] 1.3 Identification, structure, content and distribution of site-specific glycoform markers, and the content and distribution of serum CEA:

[0077] 1.3.1 Site-specific glycoform marker AACT-N 106 -H7N6S4F1:

[0078] In the raw file, at the retention time of 34.2 min, the sugar chain was identified as Hex(7)HexNAc(6)NeuAc(4)Fuc(1) (the sugar chain molecular weight is 3663.3 Da) by matching the sugar fragment ion of the secondary spectrum, and the peptide sequence was identified as FN by matching the peptide fragment ion of the secondary spectrum. 106 LTETSEAEIHQSFQHLLR (peptide molecular weight is 2399.2Da), so the complete glycopeptide is FN 106 LTETSEAEIHQSFQHLLR connected sugar chain Hex(7)HexNAc(6)NeuAc(4)Fuc(1); and / or at the retention time of 32.9min, the sugar chain was identified as Hex(7)HexNAc(6)NeuAc(4)Fuc(1) by matching the sugar fragment ion of the secondary spectrum (the molecular weight of the sugar chain is 3663.3Da), and the peptide sequence was identified as GLKFN by matching the peptide fragment ion of the secondary spectrum. 106 LTETSEAEIHQSFQHLLR (peptide molecular weight is 2697.4Da), so the complete glycopeptide is GLKFN 106 LTETSEAEIHQSFQHLLR connected sugar chain Hex(7)HexNAc(6)NeuAc(4)Fuc(1). Both of these complete glycopeptides are from antichymotrypsin (UniProt number is P01011, the full name is Alpha-1-antichymotrypsin, abbreviated as AACT, the complete peptide sequence of this protein is shown in Table 1); the N-glycosylation site of these two complete glycopeptides is the 106th asparagine residue on AACT; the sugar chain connected to these two complete glycopeptides is Hex(7)HexNAc(6)NeuAc(4)Fuc(1); therefore, these two complete glycopeptides belong to the site-specific glycoform AACT-N 106 -H7N6S4F1, structure as Figure 1 In the result file, find the quantitative values ​​of the two complete glycopeptides and add them together as AACT-N 106-H7N6S4F1 content. In cohort A, AACT-N 106 -H7N6S4F1 content distribution is as follows Figure 2 As shown in a, each sample has its corresponding AACT-N 106 -H7N6S4F1 content value (y-axis), according to the 70 healthy people and 70 gastric cancer patients grouped (x-axis), T-test analysis was performed between the two groups, and the p value was <0.001 (shown in the figure ***).

[0079] 1.3.2 Site-specific glycoform marker A1AT-N 271 -H6N4S2:

[0080] In the raw file, at the retention time of 36.1 min, the sugar chain was identified as Hex(6)HexNAc(4)NeuAc(2) (the sugar chain molecular weight is 2366.8 Da) by matching the sugar fragment ions of the secondary spectrum, and the peptide sequence was identified as YLGN by matching the peptide fragment ions of the secondary spectrum. 271 ATAIFFLPDEGK (peptide molecular weight is 1754.9Da), so the complete glycopeptide is YLGN 271 ATAIFFLPDEGK linked sugar chain Hex(6)HexNAc(4)NeuAc(2); and / or at a retention time of 41.1min, the sugar chain was identified as Hex(6)HexNAc(4)NeuAc(2) by matching the sugar fragment ion of the secondary spectrum (the molecular weight of the sugar chain is 2366.8Da), and the peptide sequence was identified as YLGN by matching the peptide fragment ion of the secondary spectrum. 271 ATAIFFLPDEGKLQHLENELTHDIITK (peptide molecular weight is 3539.8Da), so the complete glycopeptide is YLGN 271 ATAIFFLPDEGKLQHLENELTHDIITK linked sugar chain Hex(6)HexNAc(4)NeuAc(2). Both of these complete glycopeptides are derived from antitrypsin (UniProt number P01009, the full name is Alpha-1-antitrypsin, abbreviated as A1AT, the complete peptide sequence of this protein is shown in Table 1); the N-glycosylation site of these two complete glycopeptides is the 271st asparagine residue on A1AT; the sugar chain connected to these two complete glycopeptides is Hex(6)HexNAc(4)NeuAc(2); therefore, these two complete glycopeptides belong to the site-specific glycoform A1AT-N 271 -H6N4S2, structure as Figure 1 b. Find the quantitative values ​​of the above two complete glycopeptides in the result file and add them together as A1AT-N 271-H6N4S2 content. In cohort A, all samples contained A1AT-N 271 -H6N4S2 content distribution is as follows Figure 2 As shown in b, each sample has its corresponding A1AT-N 271 -H6N4S2 content value (y-axis), according to the grouping of 70 healthy people and 70 gastric cancer patients (x-axis), a T-test analysis was performed between the two groups (using the "T.TEST" formula in Excel), and the p value was <0.001 (shown in the figure ***).

[0081] 1.3.3 Site-specific glycoform marker IC1-N 352 -H4N3S1:

[0082] In the raw file, at the retention time of 35.4 min, the sugar chain identified by the matching secondary spectrum sugar fragment ion is Hex(4)HexNAc(3)NeuAc(1) (sugar chain molecular weight is 1548.5 Da), and the peptide sequence identified by the matching secondary spectrum peptide fragment ion is VGQLQLSHN 352 LSLVILVPQNLK (peptide molecular weight is 2312.4Da), so the complete glycopeptide is VGQLQLSHN 352 LSLVILVPQNLK linked sugar chain Hex(4)HexNAc(3)NeuAc(1). The complete glycopeptide is derived from C1 esterase inhibitor (UniProt number P05155, the full name of which is Plasma protease C1 inhibitor or C1esterase inhibitor, abbreviated as IC1 in English, and the complete peptide sequence of the protein is shown in Table 1); the N-glycosylation site of the complete glycopeptide is the 352nd asparagine residue on IC1; the sugar chain to which the complete glycopeptide is linked is Hex(4)HexNAc(3)NeuAc(1); therefore, the complete glycopeptide belongs to the site-specific glycoform IC1-N 352 -H4N3S1, structure as Figure 1 c. Find the quantitative value of the above intact glycopeptide in the result file as IC1-N 352 -H4N3S1 content. In cohort A, IC1-N 352 -H4N3S1 content distribution is as follows Figure 2 As shown in c, each sample has its corresponding IC1-N 352 -H4N3S1 content value (y-axis), according to the 70 healthy people and 70 gastric cancer patients grouped (x-axis), T-test analysis was performed between the two groups, and the p value was <0.001 (shown in the figure ***).

[0083] 1.3.4 Site-specific glycoform marker IC1-N254 -H5N4S1F2:

[0084] In the raw file, at the retention time of 34.4 min, the sugar chain was identified as Hex(5)HexNAc(4)NeuAc(1)Fuc(2) (the sugar chain molecular weight is 2205.8 Da) by matching the sugar fragment ions of the secondary spectrum, and the peptide sequence was identified as VLSNN by matching the peptide fragment ions of the secondary spectrum. 254 SDANLELINTWVAK (peptide molecular weight is 2100.1Da), so the complete glycopeptide is VLSNN 254 SDANLELINTWVAK linked sugar chain Hex(5)HexNAc(4)NeuAc(1)Fuc(2). The complete glycopeptide is from IC1; the N-glycosylation site of the complete glycopeptide is the 254th asparagine residue on IC1; the sugar chain linked to the complete glycopeptide is Hex(5)HexNAc(4)NeuAc(1)Fuc(2); therefore, the complete glycopeptide belongs to the site-specific glycoform IC1-N 254 -H5N4S1F2, structure as Figure 1 d. Find the quantitative value of the above intact glycopeptide in the result file as IC1-N 254 -H5N4S1F2 content. In cohort A, IC1-N 254 -H5N4S1F2 content distribution is as follows Figure 2 As shown in d, each sample has its corresponding IC1-N 254 -H5N4S1F2 content (y-axis), according to the 70 healthy people and 70 gastric cancer patients grouped (x-axis), a T-test analysis was performed between the two groups, and the p value was <0.001 (shown in the figure ***). 1.3.5 Site-specific glycoform marker ITIH3-N 91 -H5N4S2:

[0085] In the raw file, at the retention time of 39.9 min, the sugar chain was identified as Hex(5)HexNAc(4)NeuAc(2) (the sugar chain molecular weight was 2204.8 Da) by matching the sugar fragment ions of the secondary spectrum, and the peptide sequence was identified as TAFITN by matching the peptide fragment ions of the secondary spectrum. 91 FTLTIDGVTYPGNVK (peptide molecular weight is 2271.2Da), so the complete glycopeptide is TAFITN 91FTLTIDGVTYPGNVK linked sugar chain Hex(5)HexNAc(4)NeuAc(2). The complete glycopeptide is from trypsin inhibitor heavy chain H3 (UniProt number is Q06033, the full name is Inter-alpha-trypsin inhibitor heavy chain H3, abbreviated as ITIH3 in English, the complete peptide sequence of the protein is shown in Table 1); the N-glycosylation site of the complete glycopeptide is the 91st asparagine residue on ITIH3; the sugar chain connected to the complete glycopeptide is Hex(5)HexNAc(4)NeuAc(2); therefore, the complete glycopeptide belongs to the site-specific glycoform ITIH3-N 91 -H5N4S2, structure as Figure 1 e. Find the quantitative value of the above intact glycopeptide in the result file as ITIH3-N 91 -H5N4S2 content. In cohort A, all samples contained ITIH3-N 91 -The distribution of H5N4S2 content is as follows Figure 2 As shown in e, each sample has its corresponding ITIH3-N 91 -H5N4S2 content value (y-axis), according to the 70 healthy people and 70 gastric cancer patients grouped (x-axis), a T-test analysis was performed between the two groups, and the p value was <0.001 (shown in the figure ***). 1.3.6 Serum CEA content and distribution in cohort A:

[0086] In cohort A, the distribution of serum CEA levels in all samples was as follows: Figure 2 f. Each sample has its corresponding serum CEA value (y-axis), and 70 healthy people and 70 gastric cancer patients were grouped (x-axis). T-test analysis was performed between the two groups, and the p value was <0.05 (shown in the figure *).

[0087] Figure 2 af shows that the five site-specific glycoform markers (p<0.001, showing ***) are higher than serum CEA (p<0.05, showing *) in terms of the significant difference between the groups. The smaller the p value, the greater the significant difference.

[0088] 1.4 Use one or two, three, four or five of the five site-specific glycoform markers to distinguish gastric cancer patients in cohort A:

[0089] The pROC package in R language was used with a confidence interval of 95%. The ROC curve was fitted to the content of a marker or a combination of markers in gastric cancer patients and healthy people, and the AUC value was calculated to evaluate the sensitivity and specificity of the marker (reference: Robin, X.; Turck, N.; Hainard, A.; Tiberti, N.; Lisacek, F.; Sanchez, J.-C.; Müller, M. pROC: an open-source package for R and S+ to analyze and compare ROC curves. BMC Bioinformatics 2011, 12, 77.).

[0090] The AUC value of serum CEA was only 0.542, the specificity was 0.300, and the sensitivity was 0.943 (e.g. Figure 2 g).

[0091] The diagnostic effect of using site-specific glycoform markers alone is as follows (eg Figure 2 g): Using AACT-N 106 -H7N6S4F1 was detected, with an AUC value of 0.906, a specificity of 0.900, and a sensitivity of 0.784; 271 -H6N4S2 was detected, with an AUC value of 0.879, a specificity of 0.943, and a sensitivity of 0.743; IC1-N 352 -H4N3S1 was used for detection, with an AUC value of 0.863, a specificity of 0.786, and a sensitivity of 0.929; IC1-N 254 -H5N4S1F2 was used for detection, with an AUC value of 0.861, a specificity of 0.800, and a sensitivity of 0.829; using ITIH3-N 91 -H5N4S2 was detected with an AUC value of 0.873, a specificity of 0.871, and a sensitivity of 0.800.

[0092] The diagnostic effect of the combined use of five site-specific glycoform markers was 0.937, with a specificity of 0.829 and a sensitivity of 0.900 (e.g. Figure 2 g).

[0093] Combination of two site-specific glycoform markers AACT-N 106 -H7N6S4F1 and A1AT-N 271The diagnostic effect of -H6N4S2 was 0.917, specificity 0.900, and sensitivity 0.786. The combination of three site-specific glycoform markers AACT-N 106 -H7N6S4F1、A1AT-N 271 -H6N4S2 and ITIH3-N 91 -The diagnostic effect of H5N4S2 was as follows: its AUC value was 0.930, specificity was 0.857, and sensitivity was 0.871.

[0094] The above results indicate that one, two, three, four or five of the five site-specific glycoform markers proposed in the present invention can well distinguish gastric cancer patients, and the effect is significantly better than the traditional gastric cancer marker serum CEA.

[0095] Example 2 Screening gastric cancer patients in cohort B using one, two, three, four or five of the five site-specific glycoform markers

[0096] 2.1 Sample source:

[0097] All participant samples were obtained from the Xijing Hospital of the Fourth Military Medical University. After signing informed consent with the participants and approval by the Ethics Committee of the Drug Clinical Trial of the First Affiliated Hospital of the Fourth Military Medical University, serum samples from 30 healthy people and 30 gastric cancer patients were collected for cohort B. Among them, the gender distribution of the healthy population was 17 males and 13 females, with an age range of 30-82 years old and an average age of 57 years old; the gender distribution of gastric cancer patients was 18 males and 12 females, with an age range of 26-89 years old and an average age of 57 years old; therefore, the gender distribution ratio of the healthy population and gastric cancer patients in cohort B was similar, and the average age distribution was the same, so as to exclude the differences in glycosylated proteomes caused by gender and age. All gastric cancer patients were divided into 10 cases of gastric cancer stage I, 10 cases of gastric cancer stage II, and 10 cases of gastric cancer stage III. All serum samples were measured for serum CEA using a tumor marker detection kit in the hospital laboratory, and their serum CEA values ​​were recorded. Among them, the serum CEA values ​​of healthy people ranged from 0.77-8.50 ng / mL, and the serum CEA values ​​of gastric cancer patients ranged from 0.42-337.0 ng / mL. All samples were stored at -80℃ for use.

[0098] 2.2 Methods for preparation, mass spectrometry analysis, database search, and site-specific glycoform content analysis of intact glycopeptides in clinical serum samples:

[0099] Same as step 1.2 of Example 1.

[0100] 2.3 Identification, structure, content and distribution of site-specific glycoform markers, and the content and distribution of serum CEA:

[0101] Site-specific glycoform marker AACT-N 106 -H7N6S4F1、A1AT-N 271 -H6N4S2、IC1-N 352 -H4N3S1、IC1-N 254 -H5N4S1F2 and ITIH3-N 91 -The identification method, structural information and content calculation method of H5N4S2 are the same as those in step 1.3 of Example 1.

[0102] In cohort B, the site-specific glycoform marker AACT-N was detected by dividing healthy subjects into two groups: 106 -H7N6S4F1、A1AT-N 271 -H6N4S2、IC1-N 352 -H4N3S1、IC1-N 254 -H5N4S1F2 and ITIH3-N 91 -The distribution of H5N4S2 content is as follows Figure 3 The distribution of serum CEA content is shown in ae. Figure 3 f.

[0103] Figure 3 af shows that for the significant difference between the groups, these five site-specific glycoform markers (p<0.01, showing **; p<0.001, showing ***) are higher than serum CEA (p>0.05, showing ns, indicating not significant). Among them, the smaller the p value, the greater the significant difference.

[0104] 2.4 Use one or two, three, four or five of the five site-specific glycoform markers to distinguish gastric cancer patients in cohort B:

[0105] The ROC curve analysis method is the same as step 1.4 of Example 1.

[0106] The AUC value of serum CEA was 0.509, the specificity was 0.200, and the sensitivity was 0.967 (e.g. Figure 3 g).

[0107] The diagnostic effect of using site-specific glycoform markers alone is as follows (eg Figure 3 g): Using AACT-N 106 -H7N6S4F1 was detected, with an AUC value of 0.850, a specificity of 0.800, and a sensitivity of 0.800; using A1AT-N 271 -H6N4S2 was detected, with an AUC value of 0.828, a specificity of 0.867, and a sensitivity of 0.767; IC1-N 352-H4N3S1 was tested, with an AUC value of 0.864, a specificity of 0.767, and a sensitivity of 0.967; IC1-N 254 -H5N4S1F2 was used for detection, with an AUC value of 0.909, a specificity of 0.900, and a sensitivity of 0.900; using ITIH3-N 91 -H5N4S2 was detected with an AUC value of 0.947, a specificity of 0.900, and a sensitivity of 0.900.

[0108] The diagnostic effect of the combined use of five site-specific glycoform markers was 0.952, with a specificity of 0.900 and a sensitivity of 0.900 (e.g. Figure 3 g).

[0109] Combination of two site-specific glycoform markers AACT-N 106 -H7N6S4F1 and A1AT-N 271 The diagnostic effect of -H6N4S2 was 0.878, specificity 0.867, and sensitivity 0.800. The combination of three site-specific glycoform markers AACT-N 106 -H7N6S4F1、A1AT-N 271 -H6N4S2 and ITIH3-N 91 The diagnostic effect of -H5N4S2 was as follows: its AUC value was 0.934, specificity was 0.867, and sensitivity was 0.900.

[0110] The above results indicate that one, two, three, four or five of the five site-specific glycoform markers proposed in the present invention can well distinguish gastric cancer patients, and the effect is significantly better than the traditional gastric cancer marker serum CEA.

[0111] Example 3 Screening of patients with early gastric cancer in cohort C using one, two, three, four or five of the five site-specific glycoform markers

[0112] 3.1 Sample source and data source:

[0113] The samples and data of the 70 healthy subjects are the same as those in Example 1. The samples and data of the 24 early gastric cancer patients are from the 24 stage I gastric cancer patients among the 70 gastric cancer patients in Example 1. Here, the C cohort is composed of the 70 healthy subjects and the 24 early gastric cancer patients.

[0114] 3.2 Content and distribution of site-specific glycoform markers and serum CEA:

[0115] In cohort C, the site-specific glycoform marker AACT-N was detected by dividing healthy subjects into groups with patients. 106-H7N6S4F1、A1AT-N 271 -H6N4S2、IC1-N 352 -H4N3S1、IC1-N 254 -H5N4S1F2 and ITIH3-N 91 -H5N4S2 content distribution is as follows Figure 4 The distribution of serum CEA content is shown in ae. Figure 4 f.

[0116] Figure 4 af shows that the five site-specific glycoform markers (p<0.001, showing ***) are higher than serum CEA (p>0.05, showing ns, indicating not significant) in terms of the degree of difference between the groups. Among them, the smaller the p value, the greater the degree of difference.

[0117] 3.3 Use one or two, three, four or five of the five site-specific glycoform markers to distinguish gastric cancer patients in cohort C:

[0118] The ROC curve analysis method is the same as step 1.4 of Example 1.

[0119] The AUC value of serum CEA was 0.543, the specificity was 0.542, and the sensitivity was 0.657 (e.g. Figure 4 g).

[0120] The diagnostic effect of using site-specific glycoform markers alone is as follows (eg Figure 4 g): Using AACT-N 106 -H7N6S4F1 was detected, with an AUC value of 0.901, a specificity of 0.917, and a sensitivity of 0.786; 271 -H6N4S2 was detected, with an AUC value of 0.873, a specificity of 1.000, and a sensitivity of 0.714; IC1-N 352 -H4N3S1 was tested, with an AUC value of 0.890, a specificity of 0.833, and a sensitivity of 0.929; IC1-N 254 -H5N4S1F2 was used for detection, with an AUC value of 0.832, a specificity of 0.792, and a sensitivity of 0.829; using ITIH3-N 91 -H5N4S2 was detected with an AUC value of 0.790, a specificity of 0.708, and a sensitivity of 0.800.

[0121] The diagnostic effect of the combined use of five site-specific glycoform markers was 0.919, with a specificity of 0.833 and a sensitivity of 0.871 (e.g. Figure 4g).

[0122] Combination of two site-specific glycoform markers AACT-N 106 -H7N6S4F1 and A1AT-N 271 The diagnostic effect of -H6N4S2 was 0.908, specificity 0.917, and sensitivity 0.786. The combination of three site-specific glycoform markers AACT-N 106 -H7N6S4F1、A1AT-N 271 -H6N4S2 and ITIH3-N 91 -The diagnostic effect of H5N4S2 was as follows: its AUC value was 0.904, specificity was 0.833, and sensitivity was 0.871.

[0123] The above results indicate that one, two, three, four or five combinations of the five site-specific glycoform markers proposed in the present invention can well distinguish patients with early gastric cancer, and the effect is significantly better than the traditional gastric cancer marker serum CEA.

[0124] Example 4 Screening of patients with early gastric cancer in cohort D using one, two, three, four or five of the five site-specific glycoform markers

[0125] 4.1 Sample source and data source:

[0126] The samples and data of the 30 healthy subjects are the same as those in Example 2. The samples and data of the 10 early gastric cancer patients are from 10 stage I gastric cancer patients among the 20 gastric cancer patients in Example 2. Here, the D cohort is composed of 30 healthy subjects and 10 early gastric cancer patients.

[0127] 4.2 Content and distribution of site-specific glycoform markers and serum CEA:

[0128] In cohort D, the site-specific glycoform marker AACT-N was detected by dividing healthy subjects into groups with patients. 106 -H7N6S4F1、A1AT-N 271 -H6N4S2、IC1-N 352 -H4N3S1、IC1-N 254 -H5N4S1F2 and ITIH3-N 91 -H5N4S2 content distribution is as follows Figure 5 The distribution of serum CEA content is shown in ae. Figure 5 f.

[0129] Figure 5af shows that for the significant difference between the groups, these five site-specific glycoform markers (p<0.05, showing *; p<0.01, showing **; p<0.001, showing ***) are higher than serum CEA (p>0.05, showing ns, indicating not significant). Among them, the smaller the p value, the greater the significant difference.

[0130] 4.3 Use one or two, three, four or five of the five site-specific glycoform markers to distinguish patients with early gastric cancer in cohort D:

[0131] The ROC curve analysis method is the same as step 1.4 of Example 1.

[0132] The AUC value of serum CEA was 0.663, the specificity was 0.400, and the sensitivity was 0.967 (e.g. Figure 5 g).

[0133] The diagnostic effect of using site-specific glycoform markers alone is as follows (eg Figure 5 g): Using AACT-N 106 -H7N6S4F1 was detected, with an AUC value of 0.897, a specificity of 0.900, and a sensitivity of 0.767; A1AT-N 271 -H6N4S2 was detected, with an AUC value of 0.810, a specificity of 0.900, and a sensitivity of 0.767; IC1-N 352 -H4N3S1 was used for detection, with an AUC value of 0.867, a specificity of 0.800, and a sensitivity of 0.967; IC1-N 254 -H5N4S1F2 was used for detection, with an AUC value of 0.927, a specificity of 0.900, and a sensitivity of 0.933; using ITIH3-N 91 -H5N4S2 was detected with an AUC value of 0.967, a specificity of 1.000, and a sensitivity of 0.867.

[0134] The diagnostic effect of the combined use of five site-specific glycoform markers was 0.980, with a specificity of 1.000 and a sensitivity of 0.900 (e.g. Figure 5 g).

[0135] Combination of two site-specific glycoform markers AACT-N 106 -H7N6S4F1 and A1AT-N 271 The diagnostic effect of -H6N4S2 was 0.920, specificity 1.000, and sensitivity 0.800. The combination of three site-specific glycoform markers AACT-N 106-H7N6S4F1、A1AT-N 271 -H6N4S2 and ITIH3-N 91 The diagnostic effect of -H5N4S2 was, with an AUC value of 0.963, a specificity of 1.000, and a sensitivity of 0.900.

[0136] The above results indicate that one, two, three, four or five combinations of the five site-specific glycoform markers proposed in the present invention can well distinguish patients with early gastric cancer, and the effect is significantly better than the traditional gastric cancer marker serum CEA.

[0137] Table 1

[0138]

[0139]

[0140]

[0141] Table 1 shows the complete amino acid sequence of the protein. The superscripts of the amino acids represent their order in the complete amino acid sequence of the protein. *** represents p<0.001, ** represents p<0.01, and * represents p<0.05. The smaller the p value and the more asterisks, the greater the significant difference; ns represents p>0.05, indicating that the difference is not significant.

Claims

1. A site-specific glycoform marker for the diagnosis of gastric cancer and / or early gastric cancer, characterized in that: The site-specific glycoform markers include AACT-N 106 -H7N6S4F1、A1AT-N 271 -H6N4S2、IC1-N 352 -H4N3S1、IC1-N 254 -H5N4S1F2 and ITIH3-N 91 -One or more (two, three, four or five) combinations of H5N4S2; specifically: The site-specific glycoform marker AACT-N 106 -H7N6S4F1, where: AACT stands for protein antichymotrypsin (full name in English: Alpha-1-antichymotrypsin, UniProt number: P01011); N 106 Indicates that the 106th asparagine residue on the protein is glycosylated; N 106 The three amino acid sequences before and after are LKFN 106 LTE; H7N6S4F1 represents the sugar chain connected to the glycosylation site is Hex(7)HexNAc(6)NeuAc(4)Fuc(1); the structure is shown below: The site-specific glycoform marker A1AT-N 271 -H6N4S2, where A1AT represents the protein α-1-antitrypsin (full name: Alpha-1-antitrypsin, UniProt number: P01009); N 271 Indicates that the 271st asparagine residue on the protein is glycosylated; N 271 The three amino acid sequences before and after are YLGN 271 ATA; H6N4S2 represents the sugar chain connected to the glycosylation site is Hex(6)HexNAc(4)NeuAc(2); the structure is shown below: The site-specific glycoform marker IC1-N 352 -H4N3S1, where: IC1 stands for protein C1 esterase inhibitor (full name: Plasma protease C1 inhibitor or C1 esterase inhibitor, UniProt number: P05155); N 352 Indicates that the 352nd asparagine residue on the protein is glycosylated; N 352 The three amino acid sequences before and after are LSHN 352 LSL; H4N3S1 represents the sugar chain connected to the glycosylation site is Hex(4)HexNAc(3)NeuAc(1); the structure is shown below: The site-specific glycoform marker IC1-N 254 -H5N4S1F2, where: IC1 stands for protein C1 esterase inhibitor (full name: Plasma protease C1 inhibitor or C1 esterase inhibitor, UniProt number: P05155); N 254 Indicates that the 254th asparagine residue on the protein is glycosylated; N 254 The three amino acid sequences before and after are LSNN 254 SDA; H5N4S1F2 represents the sugar chain connected to the glycosylation site is Hex(5)HexNAc(4)NeuAc(1)Fuc(2); the structure is shown below: The site-specific glycoform marker ITIH3-N 91 -H5N4S2, where: ITIH3 stands for protein trypsin inhibitor heavy chain H3 (full name: Inter-alpha-trypsin inhibitor heavy chain H3, UniProt number: Q06033); N 91 Indicates that the 91st asparagine residue on the protein is glycosylated; N 91 The three amino acid sequences before and after are FITN 91 FTL; H5N4S2 represents the sugar chain connected to the glycosylation site is Hex(5)HexNAc(4)NeuAc(2); the structure is shown below:

2. The site-specific glycoform marker according to claim 1, characterized in that: Site-specific glycoforms contain three pieces of information: ① glycosylation site; ② complete protein and / or protein fragment containing the glycosylation site; ③ sugar chains covalently attached to the glycosylation site; The protein, UniProt is the abbreviation of Universal Protein, which is the most commonly used protein database. The database website is https: / / www.uniprot.org / ; in UniProt, each protein has a specific number and provides the complete amino acid sequence information of the protein; The glycosylation site is a site where the sugar chain is covalently bonded to the side chain amino group of asparagine (Asn, abbreviated as N) on a specific protein through the hydroxyl group of HexNAc; the superscript to the right of N indicates the position information of the amino acid in the complete amino acid sequence of the protein; The sugar chain, Hex is hexose, usually mannose and / or galactose; HexNAc is N-acetylhexosamine, usually N-acetylglucosamine and / or N-acetylgalactosamine; NeuAc is sialic acid; Fuc is fucose; all monosaccharides are polyhydroxy compounds, and monosaccharides are covalently linked by dehydration to form sugar chains.

3. A reagent, kit, device or system or a combination of two or more thereof for quantitatively detecting the content level of the site-specific glycoform marker according to claim 1 or 2 in a biological sample of a subject and for diagnosing gastric cancer and / or early gastric cancer.

4. The reagent, kit, device or system according to claim 3, or a combination of two or more thereof, characterized in that: The biological sample may be, but is not limited to: human or animal body fluids (e.g., one or more of human or animal blood, urine, gastric juice, saliva, etc.), tissues, cells, purified proteins, or more; The content of the site-specific glycoform marker is its absolute content, or the relative content relative to all proteins in the biological sample or all sugar chains of the purified protein, or the relative content relative to the internal standard (such as site-specific sugar standard) added to the biological sample; the relative content can be one or more of, but not limited to, percentage, reciprocal or logarithm or other transformation forms; The reagent, kit, device or system or a combination of two or more thereof comprises a reagent and / or instrument for measuring the content of site-specific glycoform markers, and the measuring method includes but is not limited to: one or more of chromatography, spectroscopy, mass spectrometry or chemical analysis; the chromatography includes one or more of high performance liquid chromatography or thin layer chromatography; the spectroscopy includes one or more of nuclear magnetic resonance spectroscopy, refractive index spectroscopy, ultraviolet spectroscopy or near infrared spectroscopy; the mass spectrometry includes one or more of matrix-assisted laser desorption time-of-flight mass spectrometry, high resolution mass spectrometry or liquid chromatography-mass spectrometry; The reagent, kit, device or system or a combination of two or more thereof further comprises a module and / or processor for calculating the site-specific glycoform content; The reagent, kit, device or system or a combination of two or more thereof further comprises a module and / or a processor for determining whether a subject suffers from gastric cancer based on the site-specific glycoform content in the subject's biological sample.

5. The reagent, kit, device or system according to claim 3 or 4, or a combination of two or more thereof, characterized in that: The detection includes but is not limited to one or more of the following steps: (1) Collect biological samples from subjects; (2) extracting proteins from biological samples, purifying proteins and / or enzymatically hydrolyzing protein peptides; (3) separation, purification and / or enrichment of intact glycopeptides and / or site-specific glycoforms; (4) detection of intact glycopeptides and / or site-specific glycoforms; (5) retrieve, identify and / or store site-specific glycoforms; (6) Calculate the content of site-specific glycoforms; (7) comparing the site-specific glycoform content of the subject with that of the control to determine whether the subject has gastric cancer and / or early gastric cancer; (8) Provide test and / or diagnosis results and / or reports.

6. The reagent, kit, device or system according to claim 3 or 4, or a combination of two or more thereof, characterized in that: Also included are reagents, instruments, modules and / or processors for detecting the content of site-specific glycoform markers in biological samples, including but not limited to one or more of the following: (a) Reagents and / or instruments used to collect biological samples; (b) Reagents and / or instruments for extracting proteins from biological samples, purifying proteins and / or protein enzymatic peptide fragments; (c) reagents and / or instruments for separation, purification and / or enrichment of intact glycopeptides and / or site-specific glycoforms; (d) Reagents and / or instruments for detecting intact glycopeptides and / or site-specific glycoforms; (e) a module and / or processor for retrieving, identifying and / or storing site-specific glycoforms of a subject; (f) a module and / or processor for calculating site-specific glycoform content of a subject; (g) a module and / or processor for comparing the site-specific glycoform content of the subject with that of the control to determine whether the subject suffers from gastric cancer; (h) A module and / or processor for providing detection and / or diagnosis results and / or reports.

7. The reagent, kit, device or system according to claim 3 or 4, or a combination of two or more thereof, characterized in that: It also includes the combined use of other gastric cancer indicators for the detection, diagnosis or early diagnosis of gastric cancer; the indicators include but are not limited to: i) Tumor biomarkers, such as one or more of CEA, CA19-9, AFP, AFP-L3, PSA, CA125, etc.; ii) Physical and chemical examination indicators, including imaging examinations, such as one or more of MRI, CT, B-ultrasound, endoscopy, etc.; iii) Basic information of the patient, such as one or more of age, gender, medical history, family history, etc.; iv) Clinical manifestations of the patient, including one or more of systemic manifestations (such as fever, infection, weight loss, anemia, etc.) and local manifestations (such as lumps, secretions, etc.).

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