Methylation marker for differential diagnosis of breast malignant tumors and breast benign tumors and application of methylation marker

Abstract

The invention discloses a methylation marker for differential diagnosis of breast malignant tumors and breast benign tumors and application of the methylation marker. The research finds that the methylation of the biopsy sample AJAP1 can be used as a potential marker for differential diagnosis of benign breast tumors, malignant breast tumors, different subtypes or different stages of malignant breast tumors. The invention has important scientific significance and clinical application value for identifying benign breast tumors, malignant breast tumors, different subtypes or different stages of malignant breast tumors and guiding and formulating a reasonable clinical treatment scheme.

Description

Technical Field

[0001] The present invention relates to the medical field, and in particular to a methylation marker for differential diagnosis of breast malignant tumors and benign breast tumors and application thereof. Background Art

[0002] Breast cancer is the most common malignant tumor in women worldwide and the leading cause of death in women with cancer. In 2020, there were approximately 2.261 million new cases of breast cancer worldwide, and 685,000 breast cancer patients died of breast cancer [Sung H, Ferlay J, Siegel RL, et al. Global Cancer Statistics 2020: GLOBOCAN Estimates of Incidence and Mortality Worldwide for 36 Cancers in 185 Countries. CA: a cancer journal for clinicians, 2021, 71(3): 209-49.]. The 2022 National Cancer Report released by the National Cancer Center of China pointed out that breast cancer ranks first in the incidence of female tumors, with an annual incidence of approximately 306,000, especially among urban residents [2022 National Cancer Report]. The incidence of breast cancer in China has been increasing steadily at a rate of 3%-5% per year, while the annual growth rate in Europe and the United States is only 0.2%-0.5% [Li T, Mello-Thoms C, Brennan PC. Descriptive epidemiology of breast cancer in China: incidence, mortality, survival and prevalence. Breast Cancer Res Treat. 2016; 159(3): 395-406.]. The age of Chinese women diagnosed with breast cancer is mainly between 30 and 59 years old, which is ten years earlier than the average age of onset in Europe and the United States [Chen W, Zheng R, Baade PD, Zhang S, Zeng H, Bray F, et al. Cancer statistics in China, 2015. CA Cancer J Clin. 2016; 66(2): 115-32.].

[0003] At present, pathological examination is the "gold standard" for diagnosing breast cancer and benign breast tumors. However, in actual clinical diagnosis, many benign breast lesions overlap with malignant lesions in pathological morphology, and cytopathological diagnosis is difficult, and a certain proportion of misdiagnosis or missed diagnosis may occur [Solanki M, Visscher D. Pathology of breast cancer in the last half century. Human pathology, 2020, 95: 137-48.]. In addition, the interpretation of pathological diagnosis results depends on the relevant techniques of pathologists and the preparation and staining techniques of pathological films, and the accuracy is difficult to guarantee [Smits AJ, Kummer JA, De Bruin PC, et al. The estimation of tumor cell percentage for molecular testing by pathologists is not accurate. Modern pathology: an official journal of the United States and Canadian Academy of Pathology, Inc, 2014, 27 (2): 168-74.]. Therefore, finding an efficient and simple molecular marker for distinguishing benign and malignant breast tumors has important clinical and public health significance.

[0004] Epigenetics is a heritable gene expression regulation method that does not involve changes in DNA sequence and can be passed on to the next generation [Nicoglou A, Merlin F. Epigenetics: A way to bridge the gap between biological fields. Stud Hist Philos Biol Biomed Sci. 2017; 66: 73-82]. DNA methylation is one of the important ways of epigenetic regulation, which refers to the covalent bond of a methyl group to the 5' carbon position of cytosine in genomic CpG dinucleotides under the action of DNA methyltransferase [Bird A. Perceptions of epigenetics. Nature. 2007; 447: 396-398]. A large number of studies have shown that DNA methylation can cause changes in chromatin structure, DNA conformation, DNA stability and the way DNA interacts with proteins, thereby controlling gene expression [Moore LD, LeT, Fan G. DNA methylation and its basic function. Neuropsychopharmacology. 2013; 38: 23-38].

[0005] The AJAP1 (adherens junctions associated protein 1) gene is located at 1p36.32. The protein it encodes is a novel transmembrane protein of epithelial cell adhesion junctions, which is involved in important biological processes such as cell adhesion, proliferation, differentiation and cytoskeletal remodeling [Bharti S, Handrow-Metzmacher H, Zickenheiner S, et al. Novelmembrane protein shrew-1 targets to cadherin-mediated junctions in polarized epithelial cells. Molecular biology of the cell, 2004, 15(1): 397-406. Vasioukhin V. Adherens junctions and cancer [J]. Sub-cellular biochemistry, 2012, 60: 379-414.].Abnormal expression of the AJAP1 gene has been shown to be associated with glioblastoma multiforme, prostate cancer, hepatocellular carcinoma, etc. [DiC, Mladkova N, Lin J, et al. AJAP1 expression modulates glioma cell motility and correlates with tumor growth and survival. International journal of oncology, 2018, 52(1): 47-54. Chen L, Wang Y, Zhang B. Hypermethylation in the promoter region inhibits AJAP1 expression and activates the JAK / STAT pathway topromote prostate cancer cell migration and stem cell sphereformation. Pathology, research and practice, 2023, 241: 154224. Song X, Ma J. SRRM1 promotes the proliferation, migration, and invasion of hepatocellular carcinoma cells by regulating the JAK / STAT signaling pathway. Tissue&cell, 2022, 79: 101954.]. At present, there are no reports on the relationship between tissue AJAP1 gene methylation and breast cancer in the population. Summary of the invention

[0006] The purpose of the present invention is to provide a methylation marker for differential diagnosis of malignant breast tumors and benign breast tumors and application thereof.

[0007] The purpose of the present invention can be achieved through the following technical solutions:

[0008] In a first aspect, the present invention claims the use of a methylated AJAP1 gene as a marker in the preparation of a product; the use of the product is at least one of the following:

[0009] (1) Differentiate or assist in differentiating benign breast tumors from malignant breast tumors;

[0010] (2) Differentiate or assist in differentiating benign breast tumors from different subtypes of malignant breast tumors;

[0011] (3) Differentiate or assist in differentiating benign breast tumors from malignant breast tumors of different stages;

[0012] (4) Differentiate or assist in differentiating different subtypes of breast malignancies;

[0013] (5) Differentiate or assist in differentiating the different stages of breast malignant tumors.

[0014] Furthermore, the different subtypes described in (2) and (4) may be pathological classifications, such as histological classifications.

[0015] Furthermore, the different stages described in (3) and (5) may be clinical stages.

[0016] In a specific embodiment of the present invention, the differentiation or auxiliary differentiation of benign breast tumors and different subtypes of malignant breast tumors described in (2) can specifically be any one of the following: differentiation or auxiliary differentiation of benign breast tumors and malignant breast tumors, differentiation or auxiliary differentiation of benign breast tumors and intraductal carcinoma, differentiation or auxiliary differentiation of benign breast tumors and invasive lobular carcinoma, differentiation or auxiliary differentiation of benign breast tumors and invasive ductal carcinoma, differentiation or auxiliary differentiation of benign breast tumors and inflammatory breast cancer.

[0017] In a specific embodiment of the present invention, the differentiation or auxiliary differentiation of benign breast tumors and malignant breast tumors of different stages described in (3) may specifically be any of the following: differentiation or auxiliary differentiation of benign breast tumors and stage 0 & Ⅰ malignant breast tumors, differentiation or auxiliary differentiation of benign breast tumors and stage Ⅱ malignant breast tumors, differentiation or auxiliary differentiation of benign breast tumors and stage Ⅲ malignant breast tumors, differentiation or auxiliary differentiation of benign breast tumors and stage Ⅳ malignant breast tumors.

[0018] In a specific embodiment of the present invention, the differentiation or auxiliary differentiation of different subtypes of breast malignant tumors described in (4) can specifically be any one of the following: differentiation or auxiliary differentiation of intraductal carcinoma and invasive lobular carcinoma, differentiation or auxiliary differentiation of intraductal carcinoma and invasive ductal carcinoma, differentiation or auxiliary differentiation of intraductal carcinoma and inflammatory breast cancer, differentiation or auxiliary differentiation of invasive lobular carcinoma and invasive ductal carcinoma, differentiation or auxiliary differentiation of invasive lobular carcinoma and inflammatory breast cancer, differentiation or auxiliary differentiation of invasive ductal carcinoma and inflammatory breast cancer.

[0019] In a specific embodiment of the present invention, the differentiation or auxiliary differentiation of different stages of breast malignant tumors described in (5) can specifically be any of the following: differentiation or auxiliary differentiation of stage 0&Ⅰ breast malignant tumors and stage Ⅱ breast malignant tumors, differentiation or auxiliary differentiation of stage 0&Ⅰ breast malignant tumors and stage Ⅲ breast malignant tumors, differentiation or auxiliary differentiation of stage 0&Ⅰ breast malignant tumors and stage Ⅳ breast malignant tumors, differentiation or auxiliary differentiation of stage Ⅱ breast malignant tumors and stage Ⅲ breast malignant tumors, differentiation or auxiliary differentiation of stage Ⅱ breast malignant tumors and stage Ⅳ breast malignant tumors, differentiation or auxiliary differentiation of stage Ⅲ breast malignant tumors and stage Ⅳ breast malignant tumors.

[0020] In a second aspect, the present invention claims a use of a substance for detecting the methylation level of the AJAP1 gene in preparing a product; the use of the product is at least one of the uses of (1) to (5) described above.

[0021] In a third aspect, the present invention claims a substance for detecting the methylation level of the AJAP1 gene and a medium recording a mathematical model and / or a method for using the mathematical model in preparing a product; the use of the product is at least one of (1) to (5) described above.

[0022] The mathematical model is obtained according to a method comprising the following steps:

[0023] (A1) Detect the methylation levels of the AJAP1 gene in n1 type A samples and n2 type B samples (training set);

[0024] (A2) Taking the AJAP1 gene methylation level data of all samples obtained in step (A1), according to the classification method of type A and type B, a mathematical model is established by binary classification logistic regression method to determine the threshold value of classification judgment.

[0025] Wherein, n1 and n2 can both be positive integers greater than 10.

[0026] The method for using the mathematical model comprises the following steps:

[0027] (B1) Detecting the methylation level of the AJAP1 gene in the sample to be tested;

[0028] (B2) substituting the AJAP1 gene methylation level data of the sample to be tested obtained in step (B1) into the mathematical model to obtain a detection index; then comparing the detection index with a threshold value, and determining whether the type of the sample to be tested is type A or type B according to the comparison result;

[0029] In a specific implementation of the present invention, the threshold is set to 0.5. Values ​​greater than 0.5 are classified into one category, values ​​less than 0.5 are classified into another category, and values ​​equal to 0.5 are classified into an uncertain gray area. Type A and Type B are two corresponding categories. The grouping of the two categories, which group is type A and which group is type B, should be determined according to a specific mathematical model without any agreement.

[0030] In practical applications, the threshold value can also be determined according to the maximum Youden index (specifically, it can be the value corresponding to the maximum Youden index). Those greater than the threshold value are classified into one category, those less than the threshold value are classified into another category, and those equal to the threshold value are regarded as an uncertain gray area. Type A and Type B are two corresponding categories. The grouping of the two categories, which group is type A and which group is type B, should be determined according to a specific mathematical model without any agreement.

[0031] The type A sample and the type B sample are any of the following:

[0032] (C1) Benign breast tumors and malignant breast tumors;

[0033] (C2) Benign breast tumors and different subtypes of malignant breast tumors;

[0034] (C3) Benign breast tumors and different stages of malignant breast tumors;

[0035] (C4) Different subtypes of breast malignancies;

[0036] (C5) Breast malignancies at different stages.

[0037] Furthermore, the different subtypes described in (C2) and (C4) may be pathological classifications, such as histological classifications.

[0038] Furthermore, the different stages described in (C3) and (C5) may be clinical stages.

[0039] In a specific embodiment of the present invention, the benign breast tumor and different subtypes of malignant breast tumors described in (C2) can be any one of the following: benign breast tumor and malignant breast tumor, benign breast tumor and intraductal carcinoma, benign breast tumor and invasive lobular carcinoma, benign breast tumor and invasive ductal carcinoma, benign breast tumor and inflammatory breast cancer.

[0040] In a specific embodiment of the present invention, the benign breast tumor and malignant breast tumors of different stages described in (C3) can be any one of the following: benign breast tumor and stage 0&Ⅰ malignant breast tumor, benign breast tumor and stage Ⅱ malignant breast tumor, benign breast tumor and stage Ⅲ malignant breast tumor, benign breast tumor and stage Ⅳ malignant breast tumor.

[0041] In a specific embodiment of the present invention, the different subtypes of breast malignant tumors described in (C4) can be any one of the following: intraductal carcinoma and invasive lobular carcinoma, intraductal carcinoma and invasive ductal carcinoma, intraductal carcinoma and inflammatory breast cancer, invasive lobular carcinoma and invasive ductal carcinoma, invasive lobular carcinoma and inflammatory breast cancer, invasive ductal carcinoma and inflammatory breast cancer.

[0042] In a specific embodiment of the present invention, the different stages of breast malignant tumors in (C5) can be any one of the following: 0&Ⅰ stage breast malignant tumors and stage Ⅱ breast malignant tumors, 0&Ⅰ stage breast malignant tumors and stage Ⅲ breast malignant tumors, 0&Ⅰ stage breast malignant tumors and stage Ⅳ breast malignant tumors, stage Ⅱ breast malignant tumors and stage Ⅲ breast malignant tumors,

[0043] Stage II breast malignancy and stage IV breast malignancy, stage III breast malignancy and stage IV breast malignancy.

[0044] In a fourth aspect, the present invention seeks to protect the use of the "medium recording a mathematical model and / or a method for using a mathematical model" described in the third aspect above in the preparation of a product; the use of the product is at least one of (1) to (5) described above.

[0045] In a fifth aspect, the present invention claims protection for a kit.

[0046] The kit to be protected by the present invention includes substances for detecting the methylation level of the AJAP1 gene; the use of the kit can be at least one of the above-mentioned (1) to (5).

[0047] Furthermore, the kit also contains the "medium recording the mathematical model and / or the method for using the mathematical model" as described in the third aspect or the fourth aspect above.

[0048] In a fifth aspect, the present invention seeks protection for a system.

[0049] The system to be protected by the present invention comprises:

[0050] (D1) Reagents and / or instruments for detecting the methylation level of the AJAP1 gene;

[0051] (D2) a device comprising unit X and unit Y;

[0052] The unit X is used to establish a mathematical model, including a data acquisition module, a data analysis and processing module and a model output module.

[0053] The data collection module is configured to collect (D1) the AJAP1 gene methylation level data of n1 type A samples and n2 type B samples obtained by detection.

[0054] The data analysis and processing module is configured to receive the AJAP1 gene methylation level data of the n1 type A samples and the n2 type B samples from the data acquisition module, establish a mathematical model through a binary classification logistic regression method according to the classification method of type A and type B, and determine the threshold value of classification judgment.

[0055] The model output module is configured to receive the mathematical model established by the data analysis and processing module and output it.

[0056] The unit Y is used to determine the type of sample to be tested, and includes a data input module, a data calculation module, a data comparison module and a conclusion output module.

[0057] The data input module is configured to input (D1) the AJAP1 gene methylation level data of the subject obtained by detection.

[0058] The data operation module is configured to receive the AJAP1 gene methylation level data of the subject from the data input module, and substitute the AJAP1 gene methylation level data of the subject into the mathematical model established by the data analysis and processing module in the unit X to calculate the detection index.

[0059] The data comparison module is configured to receive the detection index calculated by the data operation module, and compare the detection index with the threshold value determined in the data analysis and processing module in the unit X.

[0060] The conclusion output module is configured to receive the comparison result from the data comparison module, and output a conclusion of whether the type of the sample to be tested is type A or type B according to the comparison result.

[0061] The type A sample and the type B sample may be any one of (C1)-(C5) described above.

[0062] Wherein, n1 and n2 can both be positive integers greater than 10.

[0063] In a specific implementation of the present invention, the threshold is set to 0.5. Values ​​greater than 0.5 are classified into one category, values ​​less than 0.5 are classified into another category, and values ​​equal to 0.5 are classified into an uncertain gray area. Type A and Type B are two corresponding categories. The grouping of the two categories, which group is type A and which group is type B, should be determined according to a specific mathematical model without any agreement.

[0064] In practical applications, the threshold value can also be determined according to the maximum Youden index (specifically, it can be the value corresponding to the maximum Youden index). Those greater than the threshold value are classified into one category, those less than the threshold value are classified into another category, and those equal to the threshold value are regarded as an uncertain gray area. Type A and Type B are two corresponding categories. The grouping of the two categories, which group is type A and which group is type B, should be determined according to a specific mathematical model without any agreement.

[0065] In the various aspects described above, the methylation level of the AJAP1 gene may be the methylation level of all or part of the CpG sites in the fragments shown below (e1)-(e5) in the AJAP1 gene; the methylated AJAP1 gene is the methylation of all or part of the CpG sites in the fragments shown below (e1)-(e5) in the AJAP1 gene;

[0066] (e1) a DNA fragment represented by SEQ ID No. 1 or a DNA fragment having 80% or more identity thereto;

[0067] (e2) a DNA fragment represented by SEQ ID No. 2 or a DNA fragment having 80% or more identity thereto;

[0068] (e3) a DNA fragment represented by SEQ ID No. 3 or a DNA fragment having 80% or more identity thereto;

[0069] (e4) a DNA fragment represented by SEQ ID No. 4 or a DNA fragment having 80% or more identity thereto;

[0070] (e5) A DNA fragment represented by SEQ ID No. 5 or a DNA fragment having 80% or more identity thereto.

[0071] Furthermore, the “all or part of the CpG sites” are any one or more CpG sites in the five DNA fragments shown in SEQ ID No. 1 to SEQ ID No. 5 in the AJAP1 gene;

[0072] Or, the “all or part of the CpG sites” are all CpG sites in the DNA fragment shown by SEQ ID No.1, all CpG sites in the DNA fragment shown by SEQ ID No.2, all CpG sites in the DNA fragment shown by SEQ ID No.3, all CpG sites in the DNA fragment shown by SEQ ID No.4, and all CpG sites in the DNA fragment shown by SEQ ID No.5 in the AJAP1 gene;

[0073] Or, the “all or part of the CpG sites” are all CpG sites in the DNA fragment shown by SEQ ID No.1, all CpG sites in the DNA fragment shown by SEQ ID No.2, all CpG sites in the DNA fragment shown by SEQ ID No.3 and all CpG sites in the DNA fragment shown by SEQ ID No.4 in the AJAP1 gene;

[0074] Or, the “all or part of the CpG sites” are all CpG sites in the DNA fragment shown by SEQ ID No.1, all CpG sites in the DNA fragment shown by SEQ ID No.2, all CpG sites in the DNA fragment shown by SEQ ID No.3 and all CpG sites in the DNA fragment shown by SEQ ID No.5 in the AJAP1 gene;

[0075] Or, the “all or part of the CpG sites” are all CpG sites in the DNA fragment shown by SEQ ID No.1, all CpG sites in the DNA fragment shown by SEQ ID No.2, all CpG sites in the DNA fragment shown by SEQ ID No.4, and all CpG sites in the DNA fragment shown by SEQ ID No.5 in the AJAP1 gene;

[0076] Or, the “all or part of the CpG sites” are all CpG sites in the DNA fragment shown by SEQ ID No.1, all CpG sites in the DNA fragment shown by SEQ ID No.3, all CpG sites in the DNA fragment shown by SEQ ID No.4, and all CpG sites in the DNA fragment shown by SEQ ID No.5 in the AJAP1 gene;

[0077] Or, the “all or part of the CpG sites” are all CpG sites in the DNA fragment shown by SEQ ID No.2, all CpG sites in the DNA fragment shown by SEQ ID No.3, all CpG sites in the DNA fragment shown by SEQ ID No.4, and all CpG sites in the DNA fragment shown by SEQ ID No.5 in the AJAP1 gene;

[0078] or

[0079] The “all or part of the CpG sites” are all CpG sites in the DNA fragment shown in SEQ ID No. 1, all CpG sites in the DNA fragment shown in SEQ ID No. 2, and all CpG sites in the DNA fragment shown in SEQ ID No. 3 in the AJAP1 gene;

[0080] Or, the “all or part of the CpG sites” are all CpG sites in the DNA fragment shown by SEQ ID No.1, all CpG sites in the DNA fragment shown by SEQ ID No.2, and all CpG sites in the DNA fragment shown by SEQ ID No.5 in the AJAP1 gene;

[0081] Or, the “all or part of the CpG sites” are all CpG sites in the DNA fragment shown by SEQ ID No.1, all CpG sites in the DNA fragment shown by SEQ ID No.4, and all CpG sites in the DNA fragment shown by SEQ ID No.5 in the AJAP1 gene;

[0082] Or, the “all or part of the CpG sites” are all CpG sites in the DNA fragment shown by SEQ ID No.3, all CpG sites in the DNA fragment shown by SEQ ID No.4, and all CpG sites in the DNA fragment shown by SEQ ID No.5 in the AJAP1 gene;

[0083] Or, the “all or part of the CpG sites” are all CpG sites in the DNA fragment shown by SEQ ID No. 2, all CpG sites in the DNA fragment shown by SEQ ID No. 4, and all CpG sites in the DNA fragment shown by SEQ ID No. 5 in the AJAP1 gene;

[0084] Or, the “all or part of the CpG sites” are all CpG sites in the DNA fragment shown by SEQ ID No. 2, all CpG sites in the DNA fragment shown by SEQ ID No. 3, and all CpG sites in the DNA fragment shown by SEQ ID No. 5 in the AJAP1 gene;

[0085] Or, the “all or part of the CpG sites” are all CpG sites in the DNA fragment shown by SEQ ID No. 2, all CpG sites in the DNA fragment shown by SEQ ID No. 3, and all CpG sites in the DNA fragment shown by SEQ ID No. 4 in the AJAP1 gene;

[0086] Or, the “all or part of the CpG sites” are all CpG sites in the DNA fragment shown by SEQ ID No.1, all CpG sites in the DNA fragment shown by SEQ ID No.3, and all CpG sites in the DNA fragment shown by SEQ ID No.5 in the AJAP1 gene;

[0087] Or, the “all or part of the CpG sites” are all CpG sites in the DNA fragment shown in SEQ ID No.1, all CpG sites in the DNA fragment shown in SEQ ID No.3, and all CpG sites in the DNA fragment shown in SEQ ID No.4 in the AJAP1 gene;

[0088] Or, the “all or part of the CpG sites” are all CpG sites in the DNA fragment shown by SEQ ID No.1, all CpG sites in the DNA fragment shown by SEQ ID No.2, and all CpG sites in the DNA fragment shown by SEQ ID No.4 in the AJAP1 gene;

[0089] Or, the “all or part of the CpG sites” are all the CpG sites in the DNA fragment shown in SEQ ID No. 1 and all the CpG sites in the DNA fragment shown in SEQ ID No. 2 in the AJAP1 gene;

[0090] Or, the “all or part of the CpG sites” are all the CpG sites in the DNA fragment shown in SEQ ID No.1 and all the CpG sites in the DNA fragment shown in SEQ ID No.3 in the AJAP1 gene;

[0091] Or, the “all or part of the CpG sites” are all the CpG sites in the DNA fragment shown in SEQ ID No.1 and all the CpG sites in the DNA fragment shown in SEQ ID No.4 in the AJAP1 gene;

[0092] Or, the “all or part of the CpG sites” are all the CpG sites in the DNA fragment shown by SEQ ID No.1 and all the CpG sites in the DNA fragment shown by SEQ ID No.5 in the AJAP1 gene;

[0093] Or, the “all or part of the CpG sites” are all the CpG sites in the DNA fragment shown by SEQ ID No. 2 and all the CpG sites in the DNA fragment shown by SEQ ID No. 3 in the AJAP1 gene;

[0094] Or, the “all or part of the CpG sites” are all the CpG sites in the DNA fragment shown by SEQ ID No. 2 and all the CpG sites in the DNA fragment shown by SEQ ID No. 4 in the AJAP1 gene;

[0095] Or, the “all or part of the CpG sites” are all the CpG sites in the DNA fragment shown by SEQ ID No. 2 and all the CpG sites in the DNA fragment shown by SEQ ID No. 5 in the AJAP1 gene;

[0096] Or, the “all or part of the CpG sites” are all the CpG sites in the DNA fragment shown by SEQ ID No.3 and all the CpG sites in the DNA fragment shown by SEQ ID No.4 in the AJAP1 gene;

[0097] Or, the “all or part of the CpG sites” are all the CpG sites in the DNA fragment shown by SEQ ID No.3 and all the CpG sites in the DNA fragment shown by SEQ ID No.5 in the AJAP1 gene;

[0098] Or, the “all or part of the CpG sites” are all the CpG sites in the DNA fragment shown by SEQ ID No.4 and all the CpG sites in the DNA fragment shown by SEQ ID No.5 in the AJAP1 gene;

[0099] Or, the “all or part of the CpG sites” are all or any five or any four or any three or any two or any one of the following six CpG sites in the DNA fragment shown in SEQ ID No. 1 in the AJAP1 gene:

[0100] (f1) the CpG site at position 33-34 from the 5' end of the DNA fragment shown in SEQ ID No. 1;

[0101] (f2) the CpG site at position 48-49 from the 5' end of the DNA fragment shown in SEQ ID No. 1;

[0102] (f3) the CpG site at position 54-55 from the 5' end of the DNA fragment shown in SEQ ID No. 1;

[0103] (f4) the CpG site at position 72-73 from the 5' end of the DNA fragment shown in SEQ ID No. 1;

[0104] (f5) the CpG site at position 105-106 from the 5' end of the DNA fragment shown in SEQ ID No. 1;

[0105] (f6) the CpG site at position 112-113 from the 5' end of the DNA fragment shown in SEQ ID No. 1;

[0106] Or, the “all or part of the CpG sites” are all or any 6 or any 5 or any 4 or any 3 or any 2 or any 1 of the following 7 CpG sites in the DNA fragment shown in SEQ ID No. 2 in the AJAP1 gene:

[0107] (g1) CpG sites at positions 35-36, 55-56 and 63-64 from the 5' end of the DNA fragment shown in SEQ ID No. 2;

[0108] (g2) the CpG site at positions 99-100 from the 5' end of the DNA fragment shown in SEQ ID No. 2;

[0109] (g3) the CpG site at position 114-115 from the 5' end of the DNA fragment shown in SEQ ID No. 2;

[0110] (g4) CpG sites at positions 125-126 and 131-132 from the 5' end of the DNA fragment shown in SEQ ID No. 2;

[0111] (g5) CpG sites at positions 134-135 and 138-139 from the 5' end of the DNA fragment shown in SEQ ID No. 2;

[0112] (g6) the CpG site at position 151-152 from the 5' end of the DNA fragment shown in SEQ ID No. 2;

[0113] (g7) the CpG site at positions 164-165 from the 5' end of the DNA fragment shown in SEQ ID No. 2;

[0114] Or, the “all or part of the CpG sites” are all or any 4 or any 3 or any 2 or any 1 of the following 5 CpG sites in the DNA fragment shown in SEQ ID No. 3 in the AJAP1 gene:

[0115] (h1) the CpG site at position 47-48 from the 5' end of the DNA fragment shown in SEQ ID No.3;

[0116] (h2) CpG sites at positions 101-102 and 104-105 from the 5' end of the DNA fragment shown in SEQ ID No. 3;

[0117] (h3) the CpG site at position 395-396 from the 5' end of the DNA fragment shown in SEQ ID No. 3;

[0118] (h4) the CpG site at position 418-419 from the 5' end of the DNA fragment shown in SEQ ID No.3;

[0119] (h5) the CpG site at position 466-467 from the 5' end of the DNA fragment shown in SEQ ID No. 3;

[0120] Or, the “all or part of the CpG sites” are all or any 4 or any 3 or any 2 or any 1 of the following 5 CpG sites in the DNA fragment shown in SEQ ID No. 4 in the AJAP1 gene:

[0121] (i1) the CpG site at position 31-32 from the 5' end of the DNA fragment shown in SEQ ID No. 4;

[0122] (i2) the CpG site at position 62-63 from the 5' end of the DNA fragment shown in SEQ ID No. 4;

[0123] (i3) the CpG site at position 77-78 from the 5' end of the DNA fragment shown in SEQ ID No. 4;

[0124] (i4) the CpG sites at positions 140-141 and 152-153 from the 5' end of the DNA fragment shown in SEQ ID No. 4;

[0125] (i5) the CpG site at position 163-164 from the 5' end of the DNA fragment shown in SEQ ID No. 4;

[0126] Or, the “all or part of the CpG sites” are all or any 6 or any 5 or any 4 or any 3 or any 2 or any 1 of the following 7 CpG sites in the DNA fragment shown in SEQ ID No. 5 in the AJAP1 gene:

[0127] (j1) the CpG site at position 62-63 from the 5' end of the DNA fragment shown in SEQ ID No.5;

[0128] (j2) the CpG site at position 305-306 from the 5' end of the DNA fragment shown in SEQ ID No.5;

[0129] (j3) the CpG site at position 353-354 from the 5' end of the DNA fragment shown in SEQ ID No.5;

[0130] (j4) the CpG site at position 373-374 from the 5' end of the DNA fragment shown in SEQ ID No.5;

[0131] (j5) the CpG site at positions 401-402 from the 5' end of the DNA fragment shown in SEQ ID No.5;

[0132] (j6) the CpG site at position 406-407 from the 5' end of the DNA fragment shown in SEQ ID No.5;

[0133] (j7) The DNA fragment shown in SEQ ID No. 5 has a CpG site at position 442-443 from the 5' end.

[0134] In a specific embodiment of the present invention, some adjacent methylation sites are treated as one methylation site when performing DNA methylation analysis using time-of-flight mass spectrometry because several CpG sites are located on one methylation fragment and the peak graph cannot be distinguished (the indistinguishable sites are recorded in Table 7). Therefore, when performing methylation level analysis and constructing and using relevant mathematical models, they are treated as one methylation site. (g1), (g4), (g5), (h2) and (i4) mentioned above are such cases.

[0135] In the above aspects, the substance for detecting the methylation level of the AJAP1 gene comprises (or is) a primer combination for amplifying the full length or a partial fragment of the AJAP1 gene; the reagent for detecting the methylation level of the AJAP1 gene comprises (or is) a primer combination for amplifying the full length or a partial fragment of the AJAP1 gene.

[0136] The instrument for detecting the methylation level of the AJAP1 gene can be a time-of-flight mass spectrometer. Of course, the reagent for detecting the methylation level of the AJAP1 gene can also include other conventional reagents used for time-of-flight mass spectrometry.

[0137] Furthermore, the partial fragment is at least one of the following fragments:

[0138] (k1) the DNA fragment shown in SEQ ID No. 1 or a DNA fragment contained therein;

[0139] (k2) the DNA fragment shown in SEQ ID No. 2 or a DNA fragment contained therein;

[0140] (k3) a DNA fragment represented by SEQ ID No. 3 or a DNA fragment contained therein;

[0141] (k4) the DNA fragment shown in SEQ ID No. 4 or a DNA fragment contained therein;

[0142] (k5) the DNA fragment shown in SEQ ID No.5 or a DNA fragment contained therein;

[0143] (k6) a DNA fragment having 80% or more identity with the DNA fragment represented by SEQ ID No. 1 or a DNA fragment contained therein;

[0144] (k7) a DNA fragment having 80% or more identity with the DNA fragment represented by SEQ ID No. 2 or a DNA fragment contained therein;

[0145] (k8) a DNA fragment having 80% or more identity with the DNA fragment shown in SEQ ID No. 3 or a DNA fragment contained therein;

[0146] (k9) a DNA fragment having 80% or more identity with the DNA fragment shown in SEQ ID No. 4 or a DNA fragment contained therein;

[0147] (k10) a DNA fragment having 80% or more identity with the DNA fragment represented by SEQ ID No. 5 or a DNA fragment contained therein;

[0148] Furthermore, the primer combination is primer pair A and / or primer pair B and / or primer pair C and / or primer D and / or primer E; the primer pair A is a primer pair consisting of primer A1 and primer A2; the primer A1 is a single-stranded DNA represented by nucleotides 11-36 of SEQ ID No.6 or SEQ ID No.6; the primer A2 is a single-stranded DNA represented by nucleotides 32-56 of SEQ ID No.7 or SEQ ID No.7;

[0149] The primer pair B is a primer pair consisting of primer B1 and primer B2; the primer B1 is a single-stranded DNA represented by nucleotides 11 to 35 of SEQ ID No.8; the primer B2 is a single-stranded DNA represented by nucleotides 32 to 53 of SEQ ID No.9 or SEQ ID No.9;

[0150] The primer pair C is a primer pair consisting of primer C1 and primer C2; the primer C1 is a single-stranded DNA represented by nucleotides 11 to 35 of SEQ ID No.10; the primer C2 is a single-stranded DNA represented by nucleotides 32 to 58 of SEQ ID No.11 or SEQ ID No.11;

[0151] The primer pair D is a primer pair consisting of primer D1 and primer D2; the primer D1 is a single-stranded DNA represented by nucleotides 11 to 38 of SEQ ID No. 12; the primer D2 is a single-stranded DNA represented by nucleotides 32 to 56 of SEQ ID No. 13 or SEQ ID No. 13;

[0152] The primer pair E is a primer pair consisting of primer E1 and primer E2; the primer E1 is a single-stranded DNA represented by SEQ ID No.14 or nucleotides 11-35 of SEQ ID No.14; the primer E2 is a single-stranded DNA represented by SEQ ID No.15 or nucleotides 32-56 of SEQ ID No.15.

[0153] In addition, the present invention also claims a method for distinguishing whether a sample to be tested is a type A sample or a type B sample. The method may include the following steps:

[0154] (A) A mathematical model may be established according to a method comprising the following steps:

[0155] (A1) Detect the methylation levels of the AJAP1 gene in n1 type A samples and n2 type B samples (training set);

[0156] (A2) Taking the AJAP1 gene methylation level data of all samples obtained in step (A1), according to the classification method of type A and type B, a mathematical model is established by binary classification logistic regression method to determine the threshold value of classification judgment.

[0157] In addition, n1 and n2 in (A1) are both positive integers greater than 10.

[0158] (B) Whether the sample to be tested is a type A sample or a type B sample can be determined by a method comprising the following steps:

[0159] (B1) detecting the methylation level of the AJAP1 gene in the sample to be tested;

[0160] (B2) Substituting the AJAP1 gene methylation level data of the sample to be tested obtained in step (B1) into the mathematical model to obtain a detection index; then comparing the detection index and the threshold, and determining whether the type of the sample to be tested is type A or type B according to the comparison result.

[0161] In a specific implementation of the present invention, the threshold is set to 0.5. Values ​​greater than 0.5 are classified into one category, values ​​less than 0.5 are classified into another category, and values ​​equal to 0.5 are classified into an uncertain gray area. Type A and Type B are two corresponding categories. The grouping of the two categories, which group is type A and which group is type B, should be determined according to a specific mathematical model without any agreement.

[0162] In practical applications, the threshold value can also be determined according to the maximum Youden index (specifically, it can be the value corresponding to the maximum Youden index). Those greater than the threshold value are classified into one category, those less than the threshold value are classified into another category, and those equal to the threshold value are regarded as an uncertain gray area. Type A and Type B are two corresponding categories. The grouping of the two categories, which group is type A and which group is type B, should be determined according to a specific mathematical model without any agreement.

[0163] The type A sample and the type B sample may be any one of the above (C1)-(C5).

[0164] Any of the above mathematical models may vary in practical applications depending on the detection method and fitting method of DNA methylation. It should be determined based on the specific mathematical model without the need for agreement.

[0165] In an embodiment of the present invention, the model is specifically log(y / (1-y))=b0+b1x1+b2x2+b3x3+…+bnXn, wherein y is the dependent variable, i.e., the detection index obtained by substituting the methylation values ​​of one or more methylation sites of the test sample into the model, b0 is a constant, x1~xn are independent variables, i.e., the methylation values ​​of one or more methylation sites of the test sample (each value is a value between 0 and 1), and b1~bn are the weights assigned to the methylation value of each site by the model.

[0166] In an embodiment of the present invention, the establishment of the model may also add known parameters such as age as appropriate to improve the discrimination efficiency. A specific model established in an embodiment of the present invention is a model for distinguishing or assisting in distinguishing benign breast tumors from malignant breast tumors, and the model is specifically: log(y / (1-y))=5.572+3.367*AJAP1_D_CpG_1-2.78*AJAP1_D_CpG_2-5.843*AJAP1_D_CpG_3+2.58*AJAP1_D_CpG_4.5-5.829*AJAP1_D_CpG_6+0.012*age (integer), where y is the dependent variable, that is, the detection index obtained by substituting the methylation values ​​of all CpG sites of AIAP1_D of the sample to be tested and the age into the model.

[0167] The AJAP1_D_CpG_1 is the methylation level of the CpG site shown at positions 31-32 from the 5' end of the DNA fragment shown in SEQ ID No.4; the AJAP1_D_CpG_2 is the methylation level of the CpG site shown at positions 62-63 from the 5' end of the DNA fragment shown in SEQ ID No.4; the AJAP1_D_CpG_3 is the methylation level of the CpG site shown at positions 77-78 from the 5' end of the DNA fragment shown in SEQ ID No.4; the AJAP1_D_CpG_4.5 is the methylation level of the CpG site shown at positions 140-141 and 152-153 from the 5' end of the DNA fragment shown in SEQ ID No.4; the AJAP1_D_CpG_6 is the methylation level of the CpG site shown at positions 163-164 from the 5' end of the DNA fragment shown in SEQ ID No.4.

[0168] The threshold of the model is 0.5. Patient candidates whose detection index calculated by the model is greater than 0.5 are breast malignant tumor patients, and patients whose detection index is less than 0.5 are breast benign tumor patients.

[0169] In the above aspects, the detecting of the methylation level of the AJAP1 gene is detecting the methylation level of the AJAP1 gene in a tumor tissue sample.

[0170] In the present invention, the methylation levels of the methylation sites on the DNA fragments shown in SEQ ID No. 1 and 2 in the AJAP1 gene in breast malignant tumor tissues are significantly higher than those in breast benign tumors. The methylation levels of the methylation sites on the DNA fragments shown in SEQ ID No. 3, 4 and 5 in the AJAP1 gene in breast malignant tumor tissues are significantly lower than those in breast benign tumors.

[0171] In the present invention, as the stage of breast malignant tumor increases, the methylation level of the methylation sites on the DNA fragments shown in SEQ ID No. 1 and 2 in the AJAP1 gene in the tissue becomes higher and higher. The methylation level of the methylation sites on the DNA fragments shown in SEQ ID No. 3, 4 and 5 in the AJAP1 gene in the tissue becomes lower and lower.

[0172] For details of any of the above-mentioned AJAP1 genes, please refer to Genbank accession number: NC_000001.11.

[0173] Beneficial effects of the present invention:

[0174] The present invention has found that the methylation of the AJAP1 gene in biopsy samples can be used as a potential marker for differential diagnosis of benign breast tumors and malignant breast tumors, and different subtypes or stages of malignant breast tumors. The present invention has important scientific significance and clinical application value for distinguishing benign breast tumors and malignant breast tumors, different subtypes or stages of malignant breast tumors, and guiding the formulation of reasonable clinical treatment plans. DETAILED DESCRIPTION

[0175] The present invention is further described in detail below in conjunction with specific embodiments, and the examples provided are only for illustrating the present invention, rather than for limiting the scope of the present invention. The examples provided below can be used as a guide for further improvements by those of ordinary skill in the art, and do not constitute a limitation of the present invention in any way.

[0176] The experimental methods in the following examples, unless otherwise specified, are all conventional methods, and are performed according to the techniques or conditions described in the literature in the field or according to the product instructions. The materials, reagents, etc. used in the following examples, unless otherwise specified, can all be obtained from commercial channels.

[0177] Example 1: Primer design for detecting methylation sites of the AJAP1 gene

[0178] This study selected and detected the methylation levels of CpG sites on five fragments of the AJAP1 gene (AJAP1_A fragment, AJAP1_B fragment, AJAP1_C fragment, AJAP1_D fragment and AJAP1_E fragment), and analyzed the correlation between the methylation levels of CpG sites on the five gene fragments and breast malignancies.

[0179] The AJAP1_A fragment (SEQ ID No. 1) is located at chr1:4713673-4713900 of the hg19 reference genome, positive strand.

[0180] The AJAP1_B fragment (SEQ ID No. 2) is located in the hg19 reference genome chr1:4715958-4716148, positive strand.

[0181] The AJAP1_C fragment (SEQ ID No. 3) is located in the hg19 reference genome chr1:4744750-4745244, positive strand.

[0182] The AJAP1_D fragment (SEQ ID No. 4) is located in the hg19 reference genome chr1:4790424-4790612, positive strand.

[0183] The AJAP1_E fragment (SEQ ID No. 5) is located in the hg19 reference genome chr1:4805482-4805959, positive strand.

[0184] The site information in the AJAP1_A fragment is shown in Table 1.

[0185] The site information in the AJAP1_B fragment is shown in Table 2.

[0186] The site information in the AJAP1_C fragment is shown in Table 3.

[0187] The site information in the AJAP1_D fragment is shown in Table 4.

[0188] The site information in the AJAP1_E fragment is shown in Table 5.

[0189] Table 1 CpG site information in AJAP1_A fragment

[0190] CpG sites The location of the CpG site in the sequence AJAP1_A_1 SEQ ID No.1 from 5' end 33-34 AJAP1_A_2 SEQ ID No.1 from 5' end 48-49 AJAP1_A_3 SEQ ID No.1 from 5' end 54-55 AJAP1_A_4 SEQ ID No.1 from 5' end 72-73 AJAP1_A_5 SEQ ID No.1 from 105 to 106 at the 5' end AJAP1_A_6 SEQ ID No.1 from 112 to 113 at the 5' end

[0191] Table 2 CpG site information in AJAP1_B fragment

[0192]

[0193]

[0194] Table 3 CpG site information in AJAP1_C fragment

[0195] CpG sites The location of the CpG site in the sequence AJAP1_C_1 SEQ ID No.3 from 5' end 47-48 AJAP1_C_2 SEQ ID No.3 from 5' end 101-102 AJAP1_C_3 SEQ ID No.3 from 104 to 105 at the 5' end AJAP1_C_4 SEQ ID No.3 from 5' end 395-396 AJAP1_C_5 SEQ ID No.3 from 5' end 418-419 AJAP1_C_6 SEQ ID No.3 from 5' end 466-467

[0196] Table 4 CpG site information in AJAP1_D fragment

[0197] CpG sites The location of the CpG site in the sequence AJAP1_D_1 SEQ ID No.4 from 5' end 31-32 AJAP1_D_2 SEQ ID No.4 from 5' end 62-63 AJAP1_D_3 SEQ ID No.4 from 5' end 77-78 AJAP1_D_4 SEQ ID No.4 from 140 to 141 at the 5' end AJAP1_D_5 SEQ ID No.4 from 152 to 153 at the 5' end AJAP1_D_6 SEQ ID No.4 from 163 to 164 at the 5' end

[0198] Table 5 CpG site information in AJAP1_E fragment

[0199] CpG sites The location of the CpG site in the sequence AJAP1_E_1 SEQ ID No.5 from 5' end 62-63 AJAP1_E_2 SEQ ID No.5 from 5' end 305-306 AJAP1_E_3 SEQ ID No.5 from 5' end 353-354 AJAP1_E_4 SEQ ID No.5 from 5' end 373-374 AJAP1_E_5 SEQ ID No.5 from 5' end 401-402 AJAP1_E_6 SEQ ID No.5 from 5' end 406-407 AJAP1_E_7 SEQ ID No.5 from 5' end 442-443

[0200] Specific PCR primers were designed for the five fragments (AJAP1_A fragment, AJAP1_B fragment, AJAP1_C fragment, AJAP1_D fragment, and AJAP1_E fragment), as shown in Table 6. Among them, SEQ ID No.6, SEQ ID No.8, SEQ ID No.10, SEQ ID No.12 and SEQ ID No.14 are forward primers, and SEQ ID No.7, SEQ ID No.9, SEQ ID No.11, SEQ ID No.13 and SEQ ID No.15 are reverse primers; from the 1st to the 10th position from the 5' end of SEQ ID No.6, SEQ ID No.8, SEQ ID No.10, SEQ ID No.12 and SEQ ID No.14 are non-specific tags, and from the 11th to the 36th position of SEQ ID No.6, from the 11th to the 35th position of SEQ ID No.14, and from the 11th to the 38th position of SEQ ID No.12 are specific primer sequences; from the 1st to the 31st position from the 5' end of SEQ ID No.7, SEQ ID No.9, SEQ ID No.11, SEQ ID No.13 and SEQ ID No.15 are non-specific tags, and from the 32nd to the 56th position of SEQ ID No.7, SEQ ID No.8, SEQ ID No.10 and SEQ ID No.14, and from the 11th to the 38th position of SEQ ID No.12 are specific primer sequences. SEQ ID No. 9, positions 32 to 53, SEQ ID No. 11, positions 32 to 58, SEQ ID No. 13 and SEQ ID No. 15, positions 32 to 56 are specific primer sequences. The primer sequences do not contain SNP and CpG sites.

[0201] Table 6 AJAP1 methylation primer sequences

[0202]

[0203]

[0204] Example 2: AJAP1 gene methylation detection and result analysis

[0205] 1. Research Sample

[0206] With the informed consent of the patients, a total of 287 cases of benign breast tumor tissues and 318 cases of malignant breast tumor tissues were collected. The staging of breast cancer was based on the eighth edition of the American Joint Committee on Cancer (AJCC) staging system. The subtype of patients with malignant breast tumors was determined based on pathological histology. The 318 patients with malignant breast tumors collected this time included 41 cases of intraductal carcinoma, 218 cases of invasive ductal carcinoma, 31 cases of invasive lobular carcinoma, 11 cases of inflammatory breast cancer, 9 cases of medullary carcinoma, 5 cases of mucinous carcinoma, and 3 cases of tubular carcinoma. According to the pathological stage, there were 147 patients with stage 0&Ⅰ, 122 patients with stage Ⅱ, 45 patients with stage Ⅲ, and 4 patients with stage Ⅳ among the 318 patients with malignant breast tumors. The diagnosis of all patients was based on histopathological evidence collected during surgery. All patients had complete clinical data records. The case survey included collecting general demographic information such as age and gender of the subjects. The median age of patients with benign breast tumors and malignant breast tumors was 49 and 52 years old, respectively. At the same time, information such as estrogen receptor (ER) level, progesterone receptor (PR) level, human epidermal growth factor receptor-2 (HER2) level and Ki67 protein level were collected.

[0207] 2. Methylation Detection

[0208] 1. Total DNA from tissues was extracted using DNA Isolation Kit (Novizan, Nanjing, China).

[0209] 2. After the total DNA of the tissue sample prepared in step 1 is treated with bisulfite (EZ DNA Methylation Kit (ZYMO RESEARCH, USA, Cat. No. D5002)), the unmethylated cytosine (C) is converted into uracil (U), while the methylated cytosine remains unchanged, that is, the C base of the original CpG site is converted into C or U after bisulfite treatment.

[0210] 3. Using the DNA treated with bisulfite in step 2 as a template, PCR amplification was performed using the 5 pairs of specific primers in Table 6 by DNA polymerase according to the reaction system required for conventional PCR reaction. The 5 pairs of primers all used the same conventional PCR system, and the 5 pairs of primers were amplified according to the following procedure.

[0211] The PCR reaction program was: 95°C, 4 min→(95°C, 20 s→56°C, 30 s→72°C, 2 min), 45 cycles→72°C, 5 min→4°C, 1 h.

[0212] 4. Take the amplified product of step 3 and perform DNA methylation analysis by time-of-flight mass spectrometry. The specific method is as follows:

[0213] (1) Add 2 μl of shrimp alkaline phosphate (SAP) solution (0.3 ml SAP [0.5 U] + 1.7 ml H2O) to 5 μl of PCR product and incubate in a PCR instrument according to the following procedure (37°C, 20 min → 85°C, 5 min → 4°C, 5 min);

[0214] (2) Take out 2 μl of the SAP-treated product obtained in step (1), add it to 5 μl of T-Cleavage reaction system according to the instructions, and then incubate at 37°C for 3 h;

[0215] (3) Take the product of step (2), add 19 μl of deionized water, and then incubate with 6 μg of Resin on a rotary shaker for 1 h for deionization;

[0216] (4) Centrifuge at 2000 rpm for 5 min at room temperature, and load a small amount of supernatant onto 384 SpectroCHIP using a Nanodispenser robot;

[0217] (5) Time-of-flight mass spectrometry analysis; the data were collected using SpectroACQUIRE v3.3.1.3 software and visualized using MassArrayEpiTyper v1.2 software.

[0218] The reagents used in the above-mentioned time-of-flight mass spectrometry detection are all from the kit (T-Cleavage MassCLEAVEReagent Auto Kit, catalog number: 10129A); the detection instrument used in the above-mentioned time-of-flight mass spectrometry detection is Analyzer Chip Prep Module 384, model: 41243; the above data analysis software is the software provided by the detection instrument.

[0219] 3. Quality Control

[0220] Medical record information is entered on two tracks and consistency checked. The experimental operation requirements are strictly followed, and the operating environment is regularly disinfected with ultraviolet light; a preliminary experiment is conducted before the formal experiment; 5% of the samples are randomly selected to repeat the time-of-flight mass spectrometry test to ensure that the result consistency rate reaches more than 99%. Two people interpret the experimental results and organize the methylation data to ensure the authenticity and accuracy of the data. Through the mass spectrometry experiment, a total of 30 distinguishable peak graphs containing methylated fragments were obtained. The methylation level was calculated using the SpectroACQUIRE v3.3.1.3 software according to the formula of methylation level = peak area of ​​methylated fragments / (peak area of ​​non-methylated fragments + peak area of ​​methylated fragments) (SpectroACQUIRE v3.3.1.3 software can automatically obtain the methylation level of each sample at each CpG site by calculating the peak area).

[0221] Statistical Analysis

[0222] The median was used to represent the methylation level, and the difference in methylation levels between two or more groups was compared using nonparametric tests. The differential diagnostic value of a single CpG site and a combination of multiple CpG sites was evaluated by logistic regression and receiver operating characteristic curve (ROC). The difference was considered statistically significant when the bilateral P value was less than 0.05. All data were statistically analyzed using SPSS 25.0.

[0223] 5. Results Analysis

[0224] 1. Analysis of AJAP1 gene methylation levels in benign and malignant breast tumors

[0225] The methylation levels of five fragments of AJAP1 gene in 287 cases of benign breast tumors, 318 cases of malignant breast tumors, 41 cases of intraductal carcinoma, 31 cases of invasive lobular carcinoma, 218 cases of invasive ductal carcinoma and 11 cases of inflammatory breast cancer were analyzed. The results showed that the methylation levels of AJAP1_A and AJAP1_B fragments in patients with malignant breast tumors, intraductal carcinoma, invasive lobular carcinoma, invasive ductal carcinoma and inflammatory breast cancer were significantly higher than those of the corresponding fragments in patients with benign breast tumors (P < 0.001); while the methylation levels of AJAP1_C, AJAP1_D and AJAP1_E fragments in patients with malignant breast tumors, intraductal carcinoma, invasive lobular carcinoma, invasive ductal carcinoma and inflammatory breast cancer were significantly lower than those of the corresponding fragments in patients with benign breast tumors (see Table 7).

[0226] Table 7. AJAP1 gene methylation levels in benign and malignant breast tumors and their subtypes

[0227]

[0228]

[0229] 2. The methylation level of AJAP1 gene in tissues can distinguish benign breast tumors from different subtypes of malignant breast tumors

[0230] By comparing and analyzing the AJAP1 methylation levels in 287 cases of benign breast tumors and 301 cases of malignant breast tumors (41 cases of intraductal carcinoma, 31 cases of invasive lobular carcinoma, 218 cases of invasive ductal carcinoma, and 11 cases of inflammatory breast cancer), it was found that there was a significant difference in the methylation levels between benign breast tumors and different subtypes of breast cancer (P<0.001). The specific results are shown in Table 8.

[0231] Table 8. Differences in AJAP1 gene methylation levels between benign breast tumors and different subtypes of malignant breast tumors

[0232]

[0233]

[0234] 3. The methylation level of AJAP1 gene in tissues can distinguish different subtypes of breast malignancies

[0235] By comparing and analyzing the AJAP1 methylation levels of different types of breast malignancies (41 cases of intraductal carcinoma, 31 cases of invasive lobular carcinoma, 218 cases of invasive ductal carcinoma, and 11 cases of inflammatory breast cancer), it was found that there were significant differences in the methylation levels of the AJAP1 gene among patients with intraductal carcinoma, invasive lobular carcinoma, invasive ductal carcinoma, and inflammatory breast cancer (P < 0.001). The specific results are shown in Table 9.

[0236] Table 9. Differences in AJAP1 gene methylation levels among breast cancer subtypes

[0237]

[0238]

[0239] 4. The methylation level of AJAP1 gene in tissues can distinguish benign breast tumors from breast malignant tumors of different stages

[0240] By comparing and analyzing the AJAP1 methylation levels of 287 cases of benign breast tumors and patients with different stages of breast malignant tumors (147 patients with stage 0 & I, 122 patients with stage II, 45 patients with stage III and 4 patients with stage IV), the results showed that the methylation levels of AJAP1_A and AJAP1_B fragments increased significantly with the increase of stage (see Table 10); while the methylation levels of AJAP1_C, AJAP1_D and AJAP1_E fragments in 147 patients with stage 0 & I, 122 patients with stage II, 45 patients with stage III and 4 patients with stage IV decreased significantly with the increase of stage (see Table 10). In addition, Table 10 also shows that there are significant differences in methylation levels between benign breast tumors and breast cancers of different stages (P < 0.001). The specific results are shown in Table 10.

[0241] Table 10. AJAP1 gene methylation levels and differences in different stages of breast malignancies

[0242]

[0243]

[0244] 5. The methylation level of AJAP1 gene in tissues can distinguish different stages of breast malignancies

[0245] By comparing and analyzing the AJAP1 methylation levels of patients with breast malignancies at different stages (147 patients with stage 0&Ⅰ, 122 patients with stage Ⅱ, 45 patients with stage Ⅲ and 4 patients with stage Ⅳ), it was found that there were significant differences in the methylation levels of the AJAP1 gene among patients with breast malignancies at stage 0&Ⅰ, stage Ⅱ, stage Ⅲ and stage Ⅳ (P<0.05). The specific results are shown in Table 11.

[0246] Table 11. Differences in AJAP1 gene methylation levels in different stages of breast malignancies

[0247]

[0248]

[0249] 6. Establishment of a mathematical model for AJAP1 gene methylation to assist cancer diagnosis

[0250] The mathematical model established by the present invention can be used to achieve the following purposes:

[0251] (1) Differentiate or assist in differentiating benign breast tumors from malignant breast tumors;

[0252] (2) Differentiate or assist in differentiating benign breast tumors from different subtypes of malignant breast tumors;

[0253] (3) Differentiate or assist in differentiating benign breast tumors from malignant breast tumors of different stages;

[0254] (4) Differentiate or assist in differentiating different subtypes of breast malignancies;

[0255] (5) Differentiate or assist in differentiating the different stages of breast malignant tumors.

[0256] The mathematical model is established as follows:

[0257] (A) Data source: The methylation levels of target CpG sites (a combination of one or more of Tables 1-5) of tissue samples from 287 cases of benign breast tumors and 301 cases of malignant breast tumors (41 cases of intraductal carcinoma, 31 cases of invasive lobular carcinoma, 218 cases of invasive ductal carcinoma, and 11 cases of inflammatory breast cancer) listed in step 1 (the detection method is the same as step 2).

[0258] The data can be added with known parameters such as age according to actual needs to improve the recognition efficiency.

[0259] (B) Model building

[0260] According to the needs, select any two different types of patient data, namely the training set (for example: patients with benign breast tumors and malignant breast tumors, patients with benign breast tumors and intraductal carcinoma, patients with benign breast tumors and invasive lobular carcinoma, patients with benign breast tumors and invasive ductal carcinoma, patients with benign breast tumors and inflammatory breast cancer, patients with intraductal carcinoma and invasive lobular carcinoma, patients with intraductal carcinoma and invasive ductal carcinoma, patients with intraductal carcinoma and inflammatory breast cancer, patients with invasive lobular carcinoma and invasive ductal carcinoma, patients with invasive lobular carcinoma and inflammatory breast cancer, patients with invasive ductal carcinoma and inflammatory breast cancer, patients with inflammatory ductal carcinoma and inflammatory breast cancer, patients with benign breast tumors and stage 0&Ⅰ breast malignant tumors, patients with benign breast tumors and stage Ⅱ breast malignant tumors) Patients with breast cancer, patients with benign breast tumors and stage III breast malignant tumors, patients with benign breast tumors and stage IV breast malignant tumors, patients with stage 0&Ⅰ breast malignant tumors and stage II breast malignant tumors, patients with stage 0&Ⅰ breast malignant tumors and stage III breast malignant tumors, patients with stage 0&Ⅰ breast malignant tumors and stage IV breast malignant tumors, patients with stage II breast malignant tumors and stage III breast malignant tumors, patients with stage II breast malignant tumors and stage IV breast malignant tumors, patients with stage III breast malignant tumors and stage IV breast malignant tumors) were used as data for model building, and the mathematical model was established by formula using statistical software such as SAS, R, and SPSS using the statistical method of binary logistic regression. The value corresponding to the maximum Youden index calculated by the mathematical model formula is the threshold value or 0.5 is directly set as the threshold value. After the test sample is tested and substituted into the model calculation, the detection index obtained is greater than the threshold value and is classified into one category (category B), less than the threshold value and is classified into another category (category A), and equal to the threshold value as an uncertain gray area. When predicting a new sample to be tested to determine which category it belongs to, firstly, the methylation level of one or more CpG sites on the AJAP1 gene of the sample to be tested is detected by a DNA methylation determination method, and then the data of these methylation levels are substituted into the above-mentioned mathematical model to calculate the detection index corresponding to the sample to be tested, and then the detection index corresponding to the sample to be tested is compared with the threshold value, and the category of the sample to be tested is determined according to the comparison result.

[0261] For example: the data of the methylation level of a single CpG site of the AJAP1 gene in the training set or the methylation level of a combination of multiple CpG sites are used to establish a mathematical model for distinguishing between Class A and Class B using a binary logistic regression formula using statistical software such as SAS, R, and SPSS. The mathematical model is a binary logistic regression model, specifically: log(y / (1-y))=b0+b1x1+b2x2+b3x3+…+bnXn, where y is the dependent variable, i.e., the detection index obtained after substituting the methylation value of one or more methylation sites of the sample to be tested into the model, b0 is a constant, x1-xn are independent variables, i.e., the methylation value of one or more methylation sites of the test sample (each value is a value between 0 and 1), and b1-bn are the weights assigned to the methylation value of each site by the model. In specific applications, a mathematical model is first established based on the methylation degree (x1~xn) of one or more DNA methylation sites of the samples that have been tested in the training set and their known classification (A or B, y is assigned 0 and 1 respectively), thereby determining the constant b0 of the mathematical model and the weights b1~bn of each methylation site, and the numerical value corresponding to the maximum Youden index calculated by the mathematical model is used as the threshold or 0.5 is directly set as the threshold for division. The detection index obtained after the test sample is tested and substituted into the model calculation, that is, the y value is greater than the threshold and is classified as Class B, less than the threshold and classified as Class A, and equal to the threshold as an uncertain gray area. Among them, Class A and Class B are two corresponding categories (the grouping of the two categories, which group is Class A and which group is Class B, should be determined according to the specific mathematical model, and no agreement is made here). When predicting the subject's sample to determine which category it belongs to, first collect the subject's biopsy sample, and then extract DNA from it. After the extracted DNA is converted by bisulfite, the methylation level of a single CpG site of the AJAP1 gene of the subject or the methylation level of a combination of multiple CpG sites is detected by a DNA methylation determination method, and then the methylation data obtained by the detection are substituted into the above-mentioned mathematical model (if known parameters such as age are included in the construction of the model, this step simultaneously substitutes the specific values ​​of the corresponding parameters of the sample to be tested into the model formula). If the value calculated after substituting the methylation level of one or more CpG sites of the AJAP1 gene of the subject into the above mathematical model, that is, the detection index is greater than the threshold value, then the subject is determined to belong to the same category (category B) as the subjects in the training set with a detection index greater than the threshold value; if the value calculated after substituting the methylation level data of one or more CpG sites of the AJAP1 gene of the subject into the above mathematical model, that is, the detection index is less than the threshold value, then the subject is determined to belong to the same category (category A) as the subjects in the training set with a detection index less than the threshold value; if the value calculated after substituting the methylation level data of one or more CpG sites of the AJAP1 gene of the subject into the above mathematical model, that is, the detection index is equal to the threshold value, it cannot be determined whether the subject is category A or category B.

[0262] Example: The methylation of all CpG sites of AJAP1_D (AJAP1_D_CpG_1, AJAP1_D_CpG_2, AJAP1_D_CpG_3, AJAP1_D_CpG_4.5, AJAP1_D_CpG_6) and the application of mathematical modeling in distinguishing female benign breast tumor and breast malignant tumor tissues are illustrated: the data of methylation levels of all CpG sites of AJAP1_D that have been detected in the training set of patients with benign breast tumors and breast malignant tumors (here: 287 patients with benign breast tumors and 301 patients with breast malignant tumors) and the age of the patients are used through SPSS software or R software using the formula of binary logistic regression to establish a mathematical model for distinguishing female patients with breast malignancy. The mathematical model here is a two-class logistic regression model, which determines the constant b0 of the mathematical model and the weights b1~bn of each methylation site, which are specifically: log(y / (1-y))=5.572+3.367*AJAP1_D_CpG_1-2.78*AJAP1_D_CpG_2-5.843*AJAP1_D_CpG_3+2.58*AJAP1_D_CpG_4.5-5.829*AJAP1_D_CpG_6+0.012*age (integer), where y is the dependent variable, that is, the detection index obtained by substituting the methylation values ​​of all CpG sites of AIAP1_D of the sample to be tested and the age into the model. When 0.5 is set as the threshold, the methylation levels of all CpG sites of AJAP1_D of the sample to be tested are tested and substituted into the model together with the information of age for calculation. The obtained detection index, i.e., the y value is less than the threshold and classified as a patient with benign breast tumor, greater than the threshold and classified as a patient with malignant breast tumor, and equal to the threshold, it is uncertain whether it is a patient with benign breast tumor or a patient with malignant breast tumor. The area under the curve (AUC) calculation result of this model is 0.90 (Table 12). The specific subject judgment method is exemplified as follows, biopsy samples are collected from two subjects (A, B) to extract DNA, and the extracted DNA is converted by bisulfite, and the methylation levels of the five CpG sites (AJAP1_D_CpG_1, AJAP1_D_CpG_2, AJAP1_D_CpG_3, AJAP1_D_CpG_4.5, AJAP1_D_CpG_6) of the subject are detected by the DNA methylation determination method. Then the methylation level data obtained by the test were substituted into the above mathematical model together with the age information of the subject. The value calculated by the mathematical model for subject A was 0.27, which was less than 0.5, so subject A was determined to be a patient with benign breast tumor (consistent with the clinical diagnosis); the methylation level data of all CpG sites of AJAP1_D of subject B were substituted into the above mathematical model, and the value calculated was 0.73, which was greater than 0.5, so subject B was determined to be a patient with malignant breast tumor (consistent with the clinical diagnosis).

[0263] (C) Model effect evaluation

[0264] According to the above methods, the detection methods for detecting patients with benign breast tumors and malignant breast tumors, benign breast tumors and intraductal carcinomas, benign breast tumors and invasive lobular carcinomas, benign breast tumors and invasive ductal carcinomas, benign breast tumors and inflammatory breast cancer, intraductal carcinomas and invasive lobular carcinomas, intraductal carcinomas and invasive ductal carcinomas, intraductal carcinomas and inflammatory breast cancer, invasive lobular carcinomas and invasive ductal carcinomas, invasive lobular carcinomas and inflammatory breast cancer, invasive ductal carcinomas and inflammatory breast cancer, benign breast tumors and patients with stage 0&Ⅰ malignant breast tumors, and benign breast tumors were established respectively. The mathematical model of patients with stage Ⅱ and stage Ⅱ breast malignant tumors, patients with benign breast tumors and stage Ⅲ breast malignant tumors, patients with benign breast tumors and stage Ⅳ breast malignant tumors, patients with stage 0&Ⅰ breast malignant tumors and stage Ⅱ breast malignant tumors, patients with stage 0&Ⅰ breast malignant tumors and stage Ⅲ breast malignant tumors, patients with stage 0&Ⅰ breast malignant tumors and stage Ⅳ breast malignant tumors, patients with stage Ⅱ breast malignant tumors and stage Ⅲ breast malignant tumors, patients with stage Ⅱ breast malignant tumors and stage Ⅳ breast malignant tumors, and the effectiveness of the mathematical model was evaluated by the receiver operating characteristic curve (ROC curve). The larger the area under the curve (AUC) obtained by the ROC curve, the better the discrimination of the model and the more effective the molecular marker. The evaluation results after the mathematical model was constructed using different CpG sites are shown in Tables 12, 13, 14 and 15. In Tables 12, 13, 14 and 15, 1 CpG site represents any one CpG site in the AJAP1_A / AJAP1_B / AJAP1_C / AJAP1_D / AJAP1_E amplified fragments, 2 CpG sites represent any combination of 2 CpG sites in the AJAP1_A / AJAP1_B / AJAP1_C / AJAP1_D / AJAP1_E amplified fragments, 3 CpG sites represent any combination of 3 CpG sites in the AJAP1_A / AJAP1_B / AJAP1_C / AJAP1_D / AJAP1_E amplified fragments, and so on. The values ​​in the table are the range values ​​of the evaluation results of different site combinations (i.e., the results of any combination of CpG sites are within this range).

[0265] The above research results showed that the methylation of AJAP1 gene had a significant ability to distinguish each group (patients with benign breast tumors and malignant breast tumors, patients with benign breast tumors and intraductal carcinoma, patients with benign breast tumors and invasive lobular carcinoma, patients with benign breast tumors and invasive ductal carcinoma, patients with benign breast tumors and inflammatory breast cancer, patients with intraductal carcinoma and invasive lobular carcinoma, patients with intraductal carcinoma and invasive ductal carcinoma, patients with intraductal carcinoma and inflammatory breast cancer, patients with invasive lobular carcinoma and invasive ductal carcinoma, patients with invasive lobular carcinoma and inflammatory breast cancer, patients with invasive ductal carcinoma and inflammatory breast cancer, patients with benign breast tumors and stage 0&Ⅰ breast malignant tumors). The number of methylation sites on the AJAP1 gene increased in the following three groups: patients with tumors, patients with benign breast tumors and stage II breast malignant tumors, patients with benign breast tumors and stage III breast malignant tumors, patients with benign breast tumors and stage IV breast malignant tumors, patients with stage 0&Ⅰ breast malignant tumors and stage II breast malignant tumors, patients with stage 0&Ⅰ breast malignant tumors and stage III breast malignant tumors, patients with stage 0&Ⅰ breast malignant tumors and stage IV breast malignant tumors, patients with stage II breast malignant tumors and stage III breast malignant tumors, patients with stage II breast malignant tumors and stage IV breast malignant tumors, and patients with stage III breast malignant tumors and stage IV breast malignant tumors).

[0266] In summary, the CpG sites on the AJAP1 gene and their various combinations, the CpG sites on the AJAP1_A fragment and their various combinations, the CpG sites on the AJAP1_B fragment and their various combinations, the CpG sites on the AJAP1_C fragment and their various combinations, the CpG sites on the AJAP1_D fragment and their various combinations, the CpG sites on the AJAP1_E fragment and their various combinations, and the methylation levels of the methylation sites on the AJAP1_A, AJAP1_B, AJAP1_C, AJAP1_D and AJAP1_E genes and their various combinations are related to patients with benign breast tumors and malignant breast tumors, patients with benign breast tumors and intraductal carcinoma, patients with benign breast tumors and invasive lobular carcinoma, patients with benign breast tumors and invasive ductal carcinoma, patients with benign breast tumors and inflammatory breast cancer, and patients with intraductal carcinoma and invasive The clinical diagnosis and treatment of breast cancer in patients with lobular carcinoma, intraductal carcinoma and invasive ductal carcinoma, intraductal carcinoma and inflammatory breast cancer, invasive lobular carcinoma and invasive ductal carcinoma, invasive lobular carcinoma and inflammatory breast cancer, invasive ductal carcinoma and inflammatory breast cancer, benign breast tumors and stage 0&Ⅰ breast malignant tumors, benign breast tumors and stage Ⅱ breast malignant tumors, benign breast tumors and stage Ⅲ breast malignant tumors, benign breast tumors and stage Ⅳ breast malignant tumors, 0&Ⅰ breast malignant tumors and stage Ⅱ breast malignant tumors, 0&Ⅰ breast malignant tumors and stage Ⅲ breast malignant tumors, 0&Ⅰ breast malignant tumors and stage Ⅳ breast malignant tumors, stage Ⅱ breast malignant tumors and stage Ⅲ breast malignant tumors, stage Ⅱ breast malignant tumors and stage Ⅳ breast malignant tumors, stage Ⅲ breast malignant tumors and stage Ⅳ breast malignant tumors have the ability to distinguish.

[0267] Table 12. The value of CpG sites and their combinations in the five segments of the AJAP1 gene for distinguishing benign breast tumors from malignant breast tumors and their subtypes

[0268]

[0269]

[0270]

[0271]

[0272] Note: The CpG sites in the table refer to distinguishable CpG sites.

[0273] Table 13. The value of CpG sites and their combinations in the five segments of the AJAP1 gene for distinguishing different subtypes of breast malignancies

[0274]

[0275]

[0276]

[0277]

[0278]

[0279] Note: The CpG sites in the table refer to distinguishable CpG sites.

[0280] Table 14. The value of CpG sites and their combinations in the five segments of the AJAP1 gene for distinguishing benign breast tumors from malignant breast tumors of different stages

[0281]

[0282]

[0283]

[0284] Note: The CpG sites in the table refer to distinguishable CpG sites.

[0285] Table 15. The value of CpG sites and their combinations in the five segments of the AJAP1 gene for distinguishing breast malignancies of different stages

[0286]

[0287]

[0288]

[0289] Note: The CpG sites in the table refer to distinguishable CpG sites.

[0290] The present invention discloses a methylation marker for differential diagnosis of malignant breast tumors and benign breast tumors. The present invention provides the use of methylated AJAP1 gene as a marker in the preparation of products; the product has the function of assisting in differential diagnosis of patients with benign breast tumors and malignant breast tumors, patients with benign breast tumors and intraductal carcinoma, patients with benign breast tumors and invasive lobular carcinoma, patients with benign breast tumors and invasive ductal carcinoma, patients with benign breast tumors and inflammatory breast cancer, patients with intraductal carcinoma and invasive lobular carcinoma, patients with intraductal carcinoma and invasive ductal carcinoma, patients with intraductal carcinoma and inflammatory breast cancer, patients with invasive lobular carcinoma and invasive ductal carcinoma, patients with invasive lobular carcinoma and inflammatory breast cancer, patients with invasive ductal carcinoma and inflammatory breast cancer. The present invention proves that AJAP1 methylation in biopsy samples can be used as a potential marker for differential diagnosis of benign breast tumors and breast malignant tumors, and breast malignant tumors of different subtypes or stages. The present invention has important scientific significance and clinical application value in distinguishing benign breast tumors from malignant breast tumors, different subtypes or different stages of malignant breast tumors, and guiding the formulation of reasonable clinical treatment plans.

[0291] The present invention has been described in detail above. It will be apparent to those skilled in the art that the present invention may be implemented in a wide range under equivalent parameters, concentrations and conditions without departing from the spirit and scope of the present invention and without the need for unnecessary experimentation. Although the present invention provides specific embodiments, it should be understood that further improvements may be made to the present invention. In short, according to the principles of the present invention, this application intends to include any changes, uses or improvements to the present invention, including changes made by conventional techniques known in the art that depart from the scope disclosed in this application. Applications of some of the basic features may be made within the scope of the following appended claims.

Claims

1. Use of the methylated AJAP1 gene as a marker in the preparation of a product; the product is used for at least one of the following: (1) Differentiate or assist in differentiating benign breast tumors from malignant breast tumors; (2) Differentiate or assist in differentiating benign breast tumors from different subtypes of malignant breast tumors; (3) Differentiate or assist in differentiating benign breast tumors from malignant breast tumors of different stages; (4) Differentiate or assist in differentiating different subtypes of breast malignancies; (5) Differentiate or assist in differentiating the different stages of breast malignant tumors.

2. Use of a substance for detecting the methylation level of the AJAP1 gene in the preparation of a product; the product is used for at least one of the following purposes: (1) Differentiate or assist in differentiating benign breast tumors from malignant breast tumors; (2) Differentiate or assist in differentiating benign breast tumors from different subtypes of malignant breast tumors; (3) Differentiate or assist in differentiating benign breast tumors from malignant breast tumors of different stages; (4) Differentiate or assist in differentiating different subtypes of breast malignancies; (5) Differentiate or assist in differentiating the different stages of breast malignant tumors.

3. Use of a substance for detecting the methylation level of the AJAP1 gene and a medium recording a mathematical model and / or a method for using the mathematical model in preparing a product; the product has at least one of the following uses: (1) Differentiate or assist in differentiating benign breast tumors from malignant breast tumors; (2) Differentiate or assist in differentiating benign breast tumors from different subtypes of malignant breast tumors; (3) Differentiate or assist in differentiating benign breast tumors from malignant breast tumors of different stages; (4) Differentiate or assist in differentiating different subtypes of breast malignancies; (5) Differentiate or assist in differentiating the different stages of breast malignancies; The mathematical model is obtained according to a method comprising the following steps: (A1) The methylation levels of the AJAP1 gene were detected in n1 type A samples and n2 type B samples, respectively; (A2) taking the AJAP1 gene methylation level data of all samples obtained in step (A1), establishing a mathematical model by binary logistic regression method according to the classification of type A and type B, and determining the threshold for classification judgment; The method for using the mathematical model comprises the following steps: (B1) Detecting the methylation level of the AJAP1 gene in the sample to be tested; (B2) substituting the AJAP1 gene methylation level data of the sample to be tested obtained in step (B1) into the mathematical model to obtain a detection index; then comparing the detection index with a threshold value, and determining whether the type of the sample to be tested is type A or type B according to the comparison result; The type A sample and the type B sample are any of the following: (C1) Benign breast tumors and malignant breast tumors; (C2) Benign breast tumors and different subtypes of malignant breast tumors; (C3) Benign breast tumors and malignant breast tumors of different stages; (C4) Different subtypes of breast malignancies; (C5) Breast malignancies at different stages.

4. Use of a medium containing a mathematical model and / or a method for using a mathematical model in the preparation of a product; the product is used for at least one of the following purposes: (1) Differentiate or assist in differentiating benign breast tumors from malignant breast tumors; (2) Differentiate or assist in differentiating benign breast tumors from different subtypes of malignant breast tumors; (3) Differentiate or assist in differentiating benign breast tumors from malignant breast tumors of different stages; (4) Differentiate or assist in differentiating different subtypes of breast malignancies; (5) Differentiate or assist in differentiating different stages of breast malignancies; The mathematical model is obtained according to a method comprising the following steps: (A1) The methylation levels of the AJAP1 gene were detected in n1 type A samples and n2 type B samples, respectively; (A2) taking the AJAP1 gene methylation level data of all samples obtained in step (A1), establishing a mathematical model by binary logistic regression method according to the classification of type A and type B, and determining the threshold for classification judgment; The method for using the mathematical model comprises the following steps: (B1) Detecting the methylation level of the AJAP1 gene in the sample to be tested; (B2) substituting the AJAP1 gene methylation level data of the sample to be tested obtained in step (B1) into the mathematical model to obtain a detection index; then comparing the detection index with a threshold value, and determining whether the type of the sample to be tested is type A or type B according to the comparison result; The type A sample and the type B sample are any of the following: (C1) Benign breast tumors and malignant breast tumors; (C2) Benign breast tumors and different subtypes of malignant breast tumors; (C3) Benign breast tumors and malignant breast tumors of different stages; (C4) Different subtypes of breast malignancies; (C5) Breast malignancies at different stages.

5. A kit comprising a substance for detecting the methylation level of the AJAP1 gene; the kit is used for at least one of the following purposes: (1) Differentiate or assist in differentiating benign breast tumors from malignant breast tumors; (2) Differentiate or assist in differentiating benign breast tumors from different subtypes of malignant breast tumors; (3) Differentiate or assist in differentiating benign breast tumors from malignant breast tumors of different stages; (4) Differentiate or assist in differentiating different subtypes of breast malignancies; (5) Differentiate or assist in differentiating the different stages of breast malignant tumors.

6. The kit according to claim 5, characterized in that: The kit further comprises a medium having a mathematical model and / or a method for using the mathematical model as described in claim 3 or 4.

7. A system comprising: (D1) Reagents and / or instruments for detecting the methylation level of the AJAP1 gene; (D2) a device comprising unit X and unit Y; The unit X is used to establish a mathematical model, including a data acquisition module, a data analysis and processing module and a model output module; The data collection module is configured to collect (D1) the AJAP1 gene methylation level data of n1 type A samples and n2 type B samples obtained by detection; The data analysis and processing module is configured to receive the AJAP1 gene methylation level data of the n1 type A samples and the n2 type B samples from the data acquisition module, establish a mathematical model through a binary classification logistic regression method according to the classification method of type A and type B, and determine the threshold value of classification judgment; The model output module is configured to receive the mathematical model established by the data analysis and processing module and output it; The unit Y is used to determine the type of sample to be tested, and includes a data input module, a data calculation module, a data comparison module and a conclusion output module; The data input module is configured to input (D1) the AJAP1 gene methylation level data of the subject to be tested obtained by the test; The data operation module is configured to receive the AJAP1 gene methylation level data of the subject to be tested from the data input module, and substitute the AJAP1 gene methylation level data of the subject to be tested into the mathematical model established by the data analysis and processing module in the unit X to calculate the detection index; The data comparison module is configured to receive the detection index calculated by the data operation module and compare the detection index with the threshold value determined in the data analysis and processing module in the unit X; The conclusion output module is configured to receive the comparison result from the data comparison module, and output a conclusion of whether the type of the sample to be tested is type A or type B according to the comparison result; The type A sample and the type B sample are any of the following: (C1) Benign breast tumors and malignant breast tumors; (C2) Benign breast tumors and different subtypes of malignant breast tumors; (C3) Benign breast tumors and malignant breast tumors of different stages; (C4) Different subtypes of breast malignancies; (C5) Breast malignancies at different stages.

8. The use, kit or system according to any one of claims 1 to 7, characterized in that: The AJAP1 gene methylation level is the methylation level of all or part of the CpG sites in the fragments shown below (e1)-(e5) in the AJAP1 gene; The methylated AJAP1 gene is a gene in which all or part of the CpG sites in the fragments shown in the following (e1)-(e5) in the AJAP1 gene are methylated; (e1) a DNA fragment represented by SEQ ID No. 1 or a DNA fragment having 80% or more identity thereto; (e2) a DNA fragment represented by SEQ ID No. 2 or a DNA fragment having 80% or more identity thereto; (e3) a DNA fragment represented by SEQ ID No. 3 or a DNA fragment having 80% or more identity thereto; (e4) a DNA fragment represented by SEQ ID No. 4 or a DNA fragment having 80% or more identity thereto; (e5) A DNA fragment represented by SEQ ID No. 5 or a DNA fragment having 80% or more identity thereto.

9. The use, kit or system according to claim 8, characterized in that: The "all or part of the CpG sites" are any one or more CpG sites in the five DNA fragments shown in SEQ ID No. 1 to SEQ ID No. 5 in the AJAP1 gene; Best The “all or part of the CpG sites” are all CpG sites in the DNA fragment shown in SEQ ID No.1, all CpG sites in the DNA fragment shown in SEQ ID No.2, all CpG sites in the DNA fragment shown in SEQ ID No.3, all CpG sites in the DNA fragment shown in SEQ ID No.4, and all CpG sites in the DNA fragment shown in SEQ ID No.5 in the AJAP1 gene; or The “all or part of the CpG sites” are all CpG sites in the DNA fragment shown in SEQ ID No.1, all CpG sites in the DNA fragment shown in SEQ ID No.2, all CpG sites in the DNA fragment shown in SEQ ID No.3, and all CpG sites in the DNA fragment shown in SEQ ID No.4 in the AJAP1 gene; or The “all or part of the CpG sites” are all CpG sites in the DNA fragment shown in SEQ ID No. 1, all CpG sites in the DNA fragment shown in SEQ ID No. 2, all CpG sites in the DNA fragment shown in SEQ ID No. 3, and all CpG sites in the DNA fragment shown in SEQ ID No. 5 in the AJAP1 gene; or The “all or part of the CpG sites” are all CpG sites in the DNA fragment shown in SEQ ID No.1, all CpG sites in the DNA fragment shown in SEQ ID No.2, all CpG sites in the DNA fragment shown in SEQ ID No.4, and all CpG sites in the DNA fragment shown in SEQ ID No.5 in the AJAP1 gene; or The “all or part of the CpG sites” are all CpG sites in the DNA fragment shown in SEQ ID No.1, all CpG sites in the DNA fragment shown in SEQ ID No.3, all CpG sites in the DNA fragment shown in SEQ ID No.4, and all CpG sites in the DNA fragment shown in SEQ ID No.5 in the AJAP1 gene; or The “all or part of the CpG sites” are all CpG sites in the DNA fragment shown in SEQ ID No. 2, all CpG sites in the DNA fragment shown in SEQ ID No. 3, all CpG sites in the DNA fragment shown in SEQ ID No. 4, and all CpG sites in the DNA fragment shown in SEQ ID No. 5 in the AJAP1 gene; or The "all or part of the CpG sites" are all CpG sites in the DNA fragment shown in SEQ ID No.1, all CpG sites in the DNA fragment shown in SEQ ID No.2, and all CpG sites in the DNA fragment shown in SEQ ID No.3 in the AJAP1 gene; or The "all or part of the CpG sites" are all CpG sites in the DNA fragment shown in SEQ ID No.1, all CpG sites in the DNA fragment shown in SEQ ID No.2, and all CpG sites in the DNA fragment shown in SEQ ID No.5 in the AJAP1 gene; or The "all or part of the CpG sites" are all CpG sites in the DNA fragment shown in SEQ ID No.1, all CpG sites in the DNA fragment shown in SEQ ID No.4, and all CpG sites in the DNA fragment shown in SEQ ID No.5 in the AJAP1 gene; or The "all or part of the CpG sites" are all CpG sites in the DNA fragment shown in SEQ ID No.3, all CpG sites in the DNA fragment shown in SEQ ID No.4, and all CpG sites in the DNA fragment shown in SEQ ID No.5 in the AJAP1 gene; or The "all or part of the CpG sites" are all CpG sites in the DNA fragment shown in SEQ ID No. 2, all CpG sites in the DNA fragment shown in SEQ ID No. 4, and all CpG sites in the DNA fragment shown in SEQ ID No. 5 in the AJAP1 gene; or The "all or part of the CpG sites" are all CpG sites in the DNA fragment shown in SEQ ID No. 2, all CpG sites in the DNA fragment shown in SEQ ID No. 3, and all CpG sites in the DNA fragment shown in SEQ ID No. 5 in the AJAP1 gene; or The "all or part of the CpG sites" are all CpG sites in the DNA fragment shown in SEQ ID No. 2, all CpG sites in the DNA fragment shown in SEQ ID No. 3, and all CpG sites in the DNA fragment shown in SEQ ID No. 4 in the AJAP1 gene; or The "all or part of the CpG sites" are all CpG sites in the DNA fragment shown in SEQ ID No.1, all CpG sites in the DNA fragment shown in SEQ ID No.3, and all CpG sites in the DNA fragment shown in SEQ ID No.5 in the AJAP1 gene; or The "all or part of the CpG sites" are all the CpG sites in the DNA fragment shown in SEQ ID No.1, all the CpG sites in the DNA fragment shown in SEQ ID No.3, and all the CpG sites in the DNA fragment shown in SEQ ID No.4 in the AJAP1 gene; or The "all or part of the CpG sites" are all CpG sites in the DNA fragment shown in SEQ ID No.1, all CpG sites in the DNA fragment shown in SEQ ID No.2, and all CpG sites in the DNA fragment shown in SEQ ID No.4 in the AJAP1 gene; or The "all or part of the CpG sites" are all the CpG sites in the DNA fragment shown in SEQ ID No.1 and all the CpG sites in the DNA fragment shown in SEQ ID No.2 in the AJAP1 gene; or The "all or part of the CpG sites" are all the CpG sites in the DNA fragment shown in SEQ ID No.1 and all the CpG sites in the DNA fragment shown in SEQ ID No.3 in the AJAP1 gene; or The "all or part of the CpG sites" are all the CpG sites in the DNA fragment shown in SEQ ID No.1 and all the CpG sites in the DNA fragment shown in SEQ ID No.4 in the AJAP1 gene; or The "all or part of the CpG sites" are all the CpG sites in the DNA fragment shown in SEQ ID No.1 and all the CpG sites in the DNA fragment shown in SEQ ID No.5 in the AJAP1 gene; or The "all or part of the CpG sites" are all the CpG sites in the DNA fragment shown in SEQ ID No. 2 and all the CpG sites in the DNA fragment shown in SEQ ID No. 3 in the AJAP1 gene; or The "all or part of the CpG sites" are all the CpG sites in the DNA fragment shown in SEQ ID No. 2 and all the CpG sites in the DNA fragment shown in SEQ ID No. 4 in the AJAP1 gene; or The "all or part of the CpG sites" are all the CpG sites in the DNA fragment shown in SEQ ID No. 2 and all the CpG sites in the DNA fragment shown in SEQ ID No. 5 in the AJAP1 gene; or The "all or part of the CpG sites" are all the CpG sites in the DNA fragment shown in SEQ ID No.3 and all the CpG sites in the DNA fragment shown in SEQ ID No.4 in the AJAP1 gene; or The "all or part of the CpG sites" are all the CpG sites in the DNA fragment shown in SEQ ID No.3 and all the CpG sites in the DNA fragment shown in SEQ ID No.5 in the AJAP1 gene; or The "all or part of the CpG sites" are all the CpG sites in the DNA fragment shown in SEQ ID No.4 and all the CpG sites in the DNA fragment shown in SEQ ID No.5 in the AJAP1 gene; or The "all or part of the CpG sites" are all or any five or any four or any three or any two or any one of the following six CpG sites in the DNA fragment shown in SEQ ID No. 1 in the AJAP1 gene: (f1) the CpG site at position 33-34 from the 5' end of the DNA fragment shown in SEQ ID No. 1; (f2) the CpG site at position 48-49 from the 5' end of the DNA fragment shown in SEQ ID No. 1; (f3) the CpG site at position 54-55 from the 5' end of the DNA fragment shown in SEQ ID No. 1; (f4) the CpG site at position 72-73 from the 5' end of the DNA fragment shown in SEQ ID No. 1; (f5) the CpG site at position 105-106 from the 5' end of the DNA fragment shown in SEQ ID No. 1; (f6) the CpG site at position 112-113 from the 5' end of the DNA fragment shown in SEQ ID No. 1; or The "all or part of the CpG sites" are all or any 6 or any 5 or any 4 or any 3 or any 2 or any 1 of the following 7 CpG sites in the DNA fragment shown in SEQ ID No. 2 in the AJAP1 gene: (g1) CpG sites at positions 35-36, 55-56 and 63-64 from the 5' end of the DNA fragment shown in SEQ ID No. 2; (g2) the CpG site at positions 99-100 from the 5' end of the DNA fragment shown in SEQ ID No. 2; (g3) the CpG site at position 114-115 from the 5' end of the DNA fragment shown in SEQ ID No. 2; (g4) CpG sites at positions 125-126 and 131-132 from the 5' end of the DNA fragment shown in SEQ ID No. 2; (g5) CpG sites at positions 134-135 and 138-139 from the 5' end of the DNA fragment shown in SEQ ID No. 2; (g6) the CpG site at position 151-152 from the 5' end of the DNA fragment shown in SEQ ID No. 2; (g7) the CpG site at positions 164-165 from the 5' end of the DNA fragment shown in SEQ ID No. 2; or The "all or part of the CpG sites" are all or any four or any three or any two or any one of the following five CpG sites in the DNA fragment shown in SEQ ID No. 3 in the AJAP1 gene: (h1) the CpG site at position 47-48 from the 5' end of the DNA fragment shown in SEQ ID No.3; (h2) CpG sites at positions 101-102 and 104-105 from the 5' end of the DNA fragment shown in SEQ ID No. 3; (h3) the CpG site at position 395-396 from the 5' end of the DNA fragment shown in SEQ ID No. 3; (h4) the CpG site at position 418-419 from the 5' end of the DNA fragment shown in SEQ ID No.3; (h5) the CpG site at position 466-467 from the 5' end of the DNA fragment shown in SEQ ID No. 3; or The “all or part of the CpG sites” are all or any four or any three or any two or any one of the following five CpG sites in the DNA fragment shown in SEQ ID No. 4 in the AJAP1 gene: (i1) the CpG site at position 31-32 from the 5' end of the DNA fragment shown in SEQ ID No. 4; (i2) the CpG site at position 62-63 from the 5' end of the DNA fragment shown in SEQ ID No. 4; (i3) the CpG site at position 77-78 from the 5' end of the DNA fragment shown in SEQ ID No. 4; (i4) the CpG sites at positions 140-141 and 152-153 from the 5' end of the DNA fragment shown in SEQ ID No. 4; (i5) the CpG site at position 163-164 from the 5' end of the DNA fragment shown in SEQ ID No. 4; or The "all or part of the CpG sites" are all or any 6 or any 5 or any 4 or any 3 or any 2 or any 1 of the following 7 CpG sites in the DNA fragment shown in SEQ ID No. 5 in the AJAP1 gene: (j1) the CpG site at position 62-63 from the 5' end of the DNA fragment shown in SEQ ID No.5; (j2) the CpG site at position 305-306 from the 5' end of the DNA fragment shown in SEQ ID No.5; (j3) the CpG site at position 353-354 from the 5' end of the DNA fragment shown in SEQ ID No.5; (j4) the CpG site at position 373-374 from the 5' end of the DNA fragment shown in SEQ ID No.5; (j5) the CpG site at positions 401-402 from the 5' end of the DNA fragment shown in SEQ ID No.5; (j6) the CpG site at position 406-407 from the 5' end of the DNA fragment shown in SEQ ID No.5; (j7) The DNA fragment shown in SEQ ID No. 5 has a CpG site at position 442-443 from the 5' end.

10. The use, kit or system according to any one of claims 1 to 9, characterized in that: The material for detecting the methylation level of the AJAP1 gene comprises a primer combination for amplifying the full length or partial fragment of the AJAP1 gene; The reagent for detecting the methylation level of the AJAP1 gene comprises a primer combination for amplifying the full length or partial fragment of the AJAP1 gene; Furthermore, the partial fragment is at least one of the following fragments: (k1) the DNA fragment shown in SEQ ID No. 1 or a DNA fragment contained therein; (k2) the DNA fragment shown in SEQ ID No. 2 or a DNA fragment contained therein; (k3) a DNA fragment represented by SEQ ID No. 3 or a DNA fragment contained therein; (k4) the DNA fragment shown in SEQ ID No. 4 or a DNA fragment contained therein; (k5) the DNA fragment shown in SEQ ID No.5 or a DNA fragment contained therein; (k6) a DNA fragment having 80% or more identity with the DNA fragment represented by SEQ ID No. 1 or a DNA fragment contained therein; (k7) a DNA fragment having 80% or more identity with the DNA fragment represented by SEQ ID No. 2 or a DNA fragment contained therein; (k8) a DNA fragment having 80% or more identity with the DNA fragment shown in SEQ ID No. 3 or a DNA fragment contained therein; (k9) a DNA fragment having 80% or more identity with the DNA fragment shown in SEQ ID No. 4 or a DNA fragment contained therein; (k10) a DNA fragment having 80% or more identity with the DNA fragment represented by SEQ ID No. 5 or a DNA fragment contained therein; Furthermore, the primer combination is primer pair A and / or primer pair B and / or primer pair C and / or primer D and / or primer E; the primer pair A is a primer pair consisting of primer A1 and primer A2; the primer A1 is a single-stranded DNA represented by nucleotides 11-36 of SEQ ID No.6 or SEQ ID No.6; the primer A2 is a single-stranded DNA represented by nucleotides 32-56 of SEQ ID No.7 or SEQ ID No.7; The primer pair B is a primer pair consisting of primer B1 and primer B2; the primer B1 is a single-stranded DNA represented by nucleotides 11 to 35 of SEQ ID No.8 or SEQ ID No.8; the primer B2 is a single-stranded DNA represented by nucleotides 32 to 53 of SEQ ID No.9 or SEQ ID No.9; The primer pair C is a primer pair consisting of primer C1 and primer C2; the primer C1 is a single-stranded DNA represented by nucleotides 11 to 35 of SEQ ID No. 10; the primer C2 is a single-stranded DNA represented by nucleotides 32 to 58 of SEQ ID No. 11 or SEQ ID No. 11; The primer pair D is a primer pair consisting of primer D1 and primer D2; the primer D1 is a single-stranded DNA represented by nucleotides 11 to 38 of SEQ ID No. 12; the primer D2 is a single-stranded DNA represented by nucleotides 32 to 56 of SEQ ID No. 13 or SEQ ID No. 13; The primer pair E is a primer pair consisting of primer E1 and primer E2; the primer E1 is a single-stranded DNA represented by nucleotides 11-35 of SEQ ID No.14 or SEQ ID No.14; the primer E2 is a single-stranded DNA represented by nucleotides 32-56 of SEQ ID No.15 or SEQ ID No.15.

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