Marker for differential diagnosis of breast malignant tumors and breast benign tumors

Abstract

The invention discloses a methylation marker for differential diagnosis of breast malignant tumors and breast benign tumors. The invention provides an application of a methylated SH3PXD2B gene as a marker in preparation of a product. The application of the product is at least one of the following applications: (1) distinguishing benign breast tumors and malignant breast tumors; (2) distinguishing breast benign tumors and breast malignant tumors of different subtypes or different stages; and (3) distinguishing different subtypes or different stages of the breast malignant 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 malignant breast tumors and benign breast tumors. 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 age group with the highest number of breast cancer diagnoses in Chinese women is 40-50 years old, with an average diagnosis age of 48-49 years old, which is more than 10 years earlier than in Western countries [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].

[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 SH3PXD2B (SH3 and PX domains 2B) gene is located at 5q35.1. It encodes a tyrosine kinase substrate with an amino-terminal PX domain and five SH3 domains, which is required for podosome formation, ECM degradation and invasion through matrix gel [Buschman MD, Bromann PA, Cejudo-Martin P, et al. The novel adaptor protein Tks4 (SH3PXD2B) is required for functional podosome formation. Mol Biol Cell. 2009 Mar; 20 (5): 1302-11.]. Abnormalities in this gene can cause a rare genetic disease, Frank-Ter Haar syndrome (FTHS), with symptoms including skeletal, cardiac, and eye abnormalities [Massadeh S, Alhabshan F, AlSudairi HN, et al. The Role of the Disrupted Podosome Adaptor Protein (SH3PXD2B) in Frank-Ter Haar Syndrome. Genes (Basel). 2022 Jan 27; 13(2): 236; Iqbal Z, Cejudo-Martin P, de Brouwer A, et al. Disruption of the podosome adaptor protein TKS4 (SH3PXD2B) causes the skeletal dysplasia, eye, and cardiac abnormalities of Frank-Ter Haar Syndrome. Am J Hum Genet. 2010 Feb 12; 86(2): 254-61.].Many studies have also found the correlation between the SH3PXD2B gene and the occurrence and development of various cancers such as gastric cancer, hepatocellular carcinoma, and colon cancer [Zhu Y, Hu Y, Wang P, et al. Comprehensive bioinformatics and experimental analysis of SH3PXD2B reveals its carcinogenic effect in gastric carcinoma. Life Sci. 2023; 326: 121792; Kui X, Wang Y, Zhang C, et al. Prognostic value of SH3PXD2B (Tks4) in human hepatocellular carcinoma: a combined multi-omics and experimental study. BMC Med Genomics. 2021; 14 (1): 115; Szeder B, Tárnoki-Zách J, Lakatos D, et al. Absence of the Tks4 Scaffold Protein Induces Epithelial-Mesenchymal Transition-Like Changes in Human Colon Cancer Cells. Cells. 2019; 8(11): 1343.]. However, there have been no reports on the correlation between tissue SH3PXD2B gene methylation and breast cancer. Summary of the invention

[0006] In order to solve the above technical problems existing in the prior art, the present invention provides a methylation marker for differential diagnosis of malignant breast tumors and benign breast tumors and its application.

[0007] The technical solution of the present invention is as follows:

[0008] The first object of the present invention is to provide a use of a methylated SH3PXD2B gene as a marker in the preparation of a diagnostic product, wherein the product is used for 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] The second object of the present invention is to provide an application of a substance for detecting the methylation level of SH3PXD2B gene in the preparation of a diagnostic product, wherein the application is at least one of the following:

[0015] (1) Differentiate or assist in differentiating benign breast tumors from malignant breast tumors;

[0016] (2) Differentiate or assist in differentiating benign breast tumors from different subtypes of malignant breast tumors;

[0017] (3) Differentiate or assist in differentiating benign breast tumors from malignant breast tumors of different stages;

[0018] (4) Differentiate or assist in differentiating different subtypes of breast malignancies;

[0019] (5) Differentiate or assist in differentiating the different stages of breast malignant tumors.

[0020] The third object of the present invention is to provide a kit comprising a substance for detecting the methylation level of the SH3PXD2B gene.

[0021] Furthermore, the kit also contains a medium recording a method for establishing a mathematical model and / or a method for using the mathematical model.

[0022] Furthermore, the mathematical model establishment method is:

[0023] (A1) Detection of SH3PXD2B gene methylation levels in n1 type A samples and n2 type B samples, respectively;

[0024] (A2) taking the methylation level data of the SH3PXD2B gene 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 of classification judgment;

[0025] The method for using the mathematical model comprises the following steps:

[0026] (B1) Detecting the methylation level of the SH3PXD2B gene of the sample to be tested;

[0027] (B2) substituting the SH3PXD2B 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;

[0028] The A-type sample and the B-type sample are any of the following:

[0029] (C1) Benign breast tumors and malignant breast tumors;

[0030] (C2) Benign breast tumors and different subtypes of malignant breast tumors;

[0031] (C3) Benign breast tumors and malignant breast tumors of different stages;

[0032] (C4) Different subtypes of breast malignancies;

[0033] (C5) Breast malignancies at different stages.

[0034] A fourth object of the present invention is to provide the use of the kit in the preparation of a diagnostic product, wherein the use is at least one of the following:

[0035] (1) Differentiate or assist in differentiating benign breast tumors from malignant breast tumors;

[0036] (2) Differentiate or assist in differentiating benign breast tumors from different subtypes of malignant breast tumors;

[0037] (3) Differentiate or assist in differentiating benign breast tumors from malignant breast tumors of different stages;

[0038] (4) Differentiate or assist in differentiating different subtypes of breast malignancies;

[0039] (5) Differentiate or assist in differentiating the different stages of breast malignant tumors.

[0040] A fifth object of the present invention is to provide a system for detecting the methylation level of the SH3PXD2B gene, the system comprising:

[0041] (D1) Reagents and / or instruments for detecting methylation levels of SH3PXD2B genes;

[0042] (D2) a device comprising unit X and unit Y;

[0043] 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;

[0044] The data collection module is configured to collect (D1) the SH3PXD2B gene methylation level data of n1 type A samples and n2 type B samples obtained by detection;

[0045] The data analysis and processing module is configured to receive the SH3PXD2B 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;

[0046] The model output module is configured to receive the mathematical model established by the data analysis and processing module and output it;

[0047] 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;

[0048] The data input module is configured to input (D1) the methylation level data of the SH3PXD2B gene of the subject to be tested obtained by the detection;

[0049] The data operation module is configured to receive the SH3PXD2B gene methylation level data of the subject to be tested from the data input module, and substitute the SH3PXD2B 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;

[0050] 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;

[0051] 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;

[0052] The A-type sample and the B-type sample are any of the following:

[0053] (C1) Benign breast tumors and malignant breast tumors;

[0054] (C2) Benign breast tumors and different subtypes of malignant breast tumors;

[0055] (C3) Benign breast tumors and malignant breast tumors of different stages;

[0056] (C4) Different subtypes of breast malignancies;

[0057] (C5) Breast malignancies at different stages.

[0058] The methylation level of the SH3PXD2B gene of the present invention refers to the methylation level of one or more CpG sites in at least one fragment as shown below (e1)-(e5) in the SH3PXD2B gene;

[0059] The methylated SH3PXD2B gene refers to the methylation of one or more CpG sites in at least one fragment as shown below (e1)-(e5) in the SH3PXD2B gene;

[0060] (e1) a DNA fragment represented by SEQ ID No. 1 or a DNA fragment having 80% or more identity thereto;

[0061] (e2) a DNA fragment represented by SEQ ID No. 2 or a DNA fragment having 80% or more identity thereto;

[0062] (e3) a DNA fragment represented by SEQ ID No. 3 or a DNA fragment having 80% or more identity thereto;

[0063] (e4) a DNA fragment represented by SEQ ID No. 4 or a DNA fragment having 80% or more identity thereto;

[0064] (e5) A DNA fragment represented by SEQ ID No. 5 or a DNA fragment having 80% or more identity thereto.

[0065] Furthermore, the CpG site of the present invention is selected from any one or more of the following:

[0066] (f1) the CpG site at position 37-38 from the 5' end of the DNA fragment shown in SEQ ID No. 1;

[0067] (f2) the CpG site at positions 62-65 from the 5' end of the DNA fragment shown in SEQ ID No. 1;

[0068] (f3) the CpG site at position 80-81 from the 5' end of the DNA fragment shown in SEQ ID No. 1;

[0069] (f4) the CpG site at position 87-88 from the 5' end of the DNA fragment shown in SEQ ID No. 1;

[0070] (f5) the CpG site at position 106-107 from the 5' end of the DNA fragment shown in SEQ ID No. 1;

[0071] (g1) the CpG site at position 29-30 from the 5' end of the DNA fragment shown in SEQ ID No. 2;

[0072] (g2) the CpG site at positions 43-46 from the 5' end of the DNA fragment shown in SEQ ID No. 2;

[0073] (g3) CpG sites at positions 63-64 and 67-68 from the 5' end of the DNA fragment shown in SEQ ID No. 2;

[0074] (g4) the CpG site at position 152-153 from the 5' end of the DNA fragment shown in SEQ ID No. 2;

[0075] (h1) the CpG site at position 94-95 from the 5' end of the DNA fragment shown in SEQ ID No.3;

[0076] (h2) the CpG site at position 136-137 from the 5' end of the DNA fragment shown in SEQ ID No. 3;

[0077] (h3) the CpG site at positions 181-182 from the 5' end of the DNA fragment shown in SEQ ID No. 3;

[0078] (h4) the CpG site at position 191-192 from the 5' end of the DNA fragment shown in SEQ ID No. 3;

[0079] (h5) the CpG site at position 208-209 from the 5' end of the DNA fragment shown in SEQ ID No. 3;

[0080] (h6) the CpG site at position 221-222 from the 5' end of the DNA fragment shown in SEQ ID No. 3;

[0081] (i1) the CpG site at position 107-108 from the 5' end of the DNA fragment shown in SEQ ID No. 4;

[0082] (i2) the CpG site at position 157-158 from the 5' end of the DNA fragment shown in SEQ ID No. 4;

[0083] (i3) the CpG site at position 186-187 from the 5' end of the DNA fragment shown in SEQ ID No. 4;

[0084] (j1) the CpG site at position 58-59 from the 5' end of the DNA fragment shown in SEQ ID No.5;

[0085] (j2) the CpG site at position 123-124 from the 5' end of the DNA fragment shown in SEQ ID No.5;

[0086] (j3) The DNA fragment shown in SEQ ID No. 5 has a CpG site at position 166-167 from the 5' end.

[0087] The material for detecting the methylation level of the SH3PXD2B gene of the present invention comprises a primer combination for amplifying the full length of the SH3PXD2B gene (Gene ID: 285590, NCBI Reference Sequence: NG_027746.2) or a primer combination for amplifying a partial fragment of the SH3PXD2B gene;

[0088] The reagent for detecting the methylation level of the SH3PXD2B gene comprises a primer combination for amplifying the full length of the SH3PXD2B gene or a partial fragment of the SH3PXD2B gene;

[0089] The full length of the SH3PXD2B gene is a DNA fragment of Gene ID: 285590, or NCBI Reference Sequence: NG_027746.2;

[0090] The SH3PXD2B gene partial fragment refers to at least one of the following fragments:

[0091] (k1) the DNA fragment shown in SEQ ID No. 1 or a DNA fragment contained therein;

[0092] (k2) the DNA fragment shown in SEQ ID No. 2 or a DNA fragment contained therein;

[0093] (k3) a DNA fragment represented by SEQ ID No. 3 or a DNA fragment contained therein;

[0094] (k4) the DNA fragment shown in SEQ ID No. 4 or a DNA fragment contained therein;

[0095] (k5) the DNA fragment shown in SEQ ID No.5 or a DNA fragment contained therein;

[0096] (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;

[0097] (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;

[0098] (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;

[0099] (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;

[0100] (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.

[0101] 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;

[0102] 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 to 35 of SEQ ID No.6 or SEQ ID No.6; the primer A2 is a single-stranded DNA represented by nucleotides 32 to 56 of SEQ ID No.7 or SEQ ID No.7;

[0103] 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 37 of SEQ ID No.8; the primer B2 is a single-stranded DNA represented by nucleotides 32 to 56 of SEQ ID No.9 or SEQ ID No.9;

[0104] 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 36 of SEQ ID No.10; the primer C2 is a single-stranded DNA represented by nucleotides 32 to 56 of SEQ ID No.11 or SEQ ID No.11;

[0105] 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 35 of SEQ ID No. 12; the primer D2 is a single-stranded DNA represented by nucleotides 32 to 57 of SEQ ID No. 13 or SEQ ID No. 13

[0106] 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.

[0107] Specifically, the primer combination sequence is as follows:

[0108]

[0109] The different subtypes of breast malignant tumors described in the present invention include: intraductal carcinoma, invasive lobular carcinoma, invasive ductal carcinoma, and inflammatory breast cancer.

[0110] The breast malignant tumors of different stages described in the present invention include: stage 0&Ⅰ breast malignant tumors, stage Ⅱ breast malignant tumors, stage Ⅲ breast malignant tumors, and stage Ⅳ breast malignant tumors.

[0111] The "all or part of the CpG sites" mentioned in the present invention 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 SH3PXD2B gene;

[0112] 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, 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 SH3PXD2B gene;

[0113] 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 SH3PXD2B gene;

[0114] 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 SH3PXD2B gene;

[0115] 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 SH3PXD2B gene;

[0116] 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 SH3PXD2B gene;

[0117] 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 SH3PXD2B gene;

[0118] 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 SH3PXD2B gene;

[0119] 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 SH3PXD2B gene;

[0120] 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 SH3PXD2B gene;

[0121] 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 SH3PXD2B gene;

[0122] 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 SH3PXD2B gene;

[0123] 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 SH3PXD2B gene;

[0124] 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 SH3PXD2B gene;

[0125] 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 SH3PXD2B gene;

[0126] 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 SH3PXD2B gene;

[0127] 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 SH3PXD2B gene;

[0128] 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 SH3PXD2B gene;

[0129] 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 SH3PXD2B gene;

[0130] 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 SH3PXD2B gene;

[0131] 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 SH3PXD2B gene;

[0132] 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 SH3PXD2B gene;

[0133] 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 SH3PXD2B gene;

[0134] 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 SH3PXD2B gene;

[0135] 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 SH3PXD2B gene;

[0136] 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 SH3PXD2B gene;

[0137] 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 SH3PXD2B gene;

[0138] 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. 1 in the SH3PXD2B gene:

[0139] (f1) the CpG site at position 37-38 from the 5' end of the DNA fragment shown in SEQ ID No. 1;

[0140] (f2) the CpG site at positions 62-65 from the 5' end of the DNA fragment shown in SEQ ID No. 1;

[0141] (f3) the CpG site at position 80-81 from the 5' end of the DNA fragment shown in SEQ ID No. 1;

[0142] (f4) the CpG site at position 87-88 from the 5' end of the DNA fragment shown in SEQ ID No. 1;

[0143] (f5) the CpG site at position 106-107 from the 5' end of the DNA fragment shown in SEQ ID No. 1;

[0144] Or, the “all or part of the CpG sites” are all or any three or any two or any one of the following four CpG sites in the DNA fragment shown in SEQ ID No. 2 in the SH3PXD2B gene:

[0145] (g1) the CpG site at position 29-30 from the 5' end of the DNA fragment shown in SEQ ID No. 2;

[0146] (g2) the CpG site at positions 43-46 from the 5' end of the DNA fragment shown in SEQ ID No. 2;

[0147] (g3) CpG sites at positions 63-64 and 67-68 from the 5' end of the DNA fragment shown in SEQ ID No. 2;

[0148] (g4) the CpG site at position 152-153 from the 5' end of the DNA fragment shown in SEQ ID No. 2;

[0149] Or, the “all or part of the CpG sites” are all or any 5 or any 4 or any 3 or any 2 or any 1 of the following 6 CpG sites in the DNA fragment shown in SEQ ID No. 3 in the SH3PXD2B gene:

[0150] (h1) the CpG site at position 94-95 from the 5' end of the DNA fragment shown in SEQ ID No.3;

[0151] (h2) the CpG site at position 136-137 from the 5' end of the DNA fragment shown in SEQ ID No. 3;

[0152] (h3) the CpG site at positions 181-182 from the 5' end of the DNA fragment shown in SEQ ID No. 3;

[0153] (h4) the CpG site at position 191-192 from the 5' end of the DNA fragment shown in SEQ ID No. 3;

[0154] (h5) the CpG site at position 208-209 from the 5' end of the DNA fragment shown in SEQ ID No. 3;

[0155] (h6) the CpG site at position 221-222 from the 5' end of the DNA fragment shown in SEQ ID No. 3;

[0156] Or, the “all or part of the CpG sites” are all or any two or any one of the following three CpG sites in the DNA fragment shown in SEQ ID No. 4 in the SH3PXD2B gene:

[0157] (i1) the CpG site at position 107-108 from the 5' end of the DNA fragment shown in SEQ ID No. 4;

[0158] (i2) the CpG site at position 157-158 from the 5' end of the DNA fragment shown in SEQ ID No. 4;

[0159] (i3) the CpG site at position 186-187 from the 5' end of the DNA fragment shown in SEQ ID No. 4;

[0160] Or, the “all or part of the CpG sites” are all or any two or any one of the following three CpG sites in the DNA fragment shown in SEQ ID No. 5 in the SH3PXD2B gene:

[0161] (j1) the CpG site at position 58-59 from the 5' end of the DNA fragment shown in SEQ ID No.5;

[0162] (j2) the CpG site at position 123-124 from the 5' end of the DNA fragment shown in SEQ ID No.5;

[0163] (j3) The DNA fragment shown in SEQ ID No. 5 has a CpG site at position 166-167 from the 5' end.

[0164] The technical solution of the present invention has the following beneficial effects

[0165] The present invention discloses a methylation marker for differential diagnosis of breast malignant tumors and benign breast tumors. The present invention provides the use of methylated SH3PXD2B gene as a marker in the preparation of diagnostic products, which can: (1) distinguish between benign breast tumors and breast malignant tumors; (2) distinguish between benign breast tumors and breast malignant tumors of different subtypes or different stages; (3) distinguish between different subtypes or different stages of breast malignant tumors, and guide the formulation of reasonable clinical treatment plans, which have important scientific significance and clinical application value. DETAILED DESCRIPTION

[0166] The present invention is further explained below with reference to the examples, but the examples do not limit the present invention in any form.

[0167] 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.

[0168] Example 1: Primer design for detecting methylation sites of SH3PXD2B gene

[0169] In this study, we selected and detected the methylation levels of CpG sites on five fragments of the SH3PXD2B gene (SH3PXD2B_A fragment, SH3PXD2B_B fragment, SH3PXD2B_C fragment, SH3PXD2B_D fragment and SH3PXD2B_E fragment), and analyzed the correlation between the methylation levels of CpG sites on the five gene fragments and breast malignancies.

[0170] The SH3PXD2B_A fragment (SEQ ID No. 1) is located in the hg19 reference genome chr5:171879574-171879770, positive strand.

[0171] The SH3PXD2B_B fragment (SEQ ID No. 2) is located in the hg19 reference genome chr5:171845974-171846198, positive strand.

[0172] The SH3PXD2B_C fragment (SEQ ID No. 3) is located in the hg19 reference genome chr5:171830821-171831066, positive strand.

[0173] The SH3PXD2B_D fragment (SEQ ID No. 4) is located in the hg19 reference genome chr5:171788781-171789000, positive strand.

[0174] The SH3PXD2B_E fragment (SEQ ID No. 5) is located in the hg19 reference genome chr5:171765665-171765864, positive strand.

[0175] The CpG site information in the SH3PXD2B_A fragment is shown in Table 1.

[0176] The CpG site information in the SH3PXD2B_B fragment is shown in Table 2.

[0177] The CpG site information in the SH3PXD2B_C fragment is shown in Table 3.

[0178] The CpG site information in the SH3PXD2B_D fragment is shown in Table 4.

[0179] The CpG site information in the SH3PXD2B_E fragment is shown in Table 5.

[0180]

[0181]

[0182] Specific PCR primers were designed for the five fragments (SH3PXD2B_A fragment, SH3PXD2B_B fragment, SH3PXD2B_C fragment, SH3PXD2B_D fragment and SH3PXD2B_E fragment), as shown in Table 6.

[0183] 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 of SEQ ID No.6, SEQ ID No.8, SEQ ID No.10, SEQ ID No.12 and SEQ ID No.14 from the 5' end is a non-specific tag, and from the 11th to the 35th position of SEQ ID No.6, SEQ ID No.12 and SEQ ID No.14, from the 11th to the 37th position of SEQ ID No.8, and from the 11th to the 36th position of SEQ ID No.10 are specific primer sequences; from the 1st to the 31st position of SEQ ID No.7, SEQ ID No.9, SEQ ID No.11, SEQ ID No.13 and SEQ ID No.15 from the 5' end is a non-specific tag, and from the 1st to the 31st position of SEQ ID No.7, SEQ ID No.9, SEQ ID No.11 and SEQ ID No.15, positions 32 to 56, and SEQ ID No.13, positions 32 to 57 are specific primer sequences. The primer sequences do not contain SNP and CpG sites.

[0184] Table 6. SH3PXD2B methylation primer sequences

[0185]

[0186] Example 2: SH3PXD2B gene methylation detection and result analysis

[0187] 1. Research Sample

[0188] 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.

[0189] 2. Methylation Detection

[0190] 1. Total DNA from tissues was extracted using DNA Isolation Kit (Novizan, Nanjing, China).

[0191] 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.

[0192] 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.

[0193] 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.

[0194] 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:

[0195] (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);

[0196] (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;

[0197] (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;

[0198] (4) Centrifuge at 2000 rpm for 5 min at room temperature, and load a small amount of supernatant onto 384 SpectroCHIP using the Nanodispenser robot;

[0199] (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.

[0200] 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.

[0201] 3. Quality Control

[0202] 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 21 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).

[0203] Statistical Analysis

[0204] 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.

[0205] V. Results Analysis

[0206] 1. Analysis of SH3PXD2B gene methylation levels in benign and malignant breast tumors

[0207] The methylation levels of 5 fragments of SH3PXD2B gene were detected 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. The results showed that the methylation levels of SH3PXD2B_A fragment, SH3PXD2B_B fragment and SH3PXD2B_C fragment 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 SH3PXD2B_D fragment and SH3PXD2B_E fragment 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).

[0208] Table 7. Methylation levels of SH3PXD2B gene in benign and malignant breast tumors and their subtypes

[0209]

[0210]

[0211] 2. The methylation level of SH3PXD2B gene in tissues can distinguish benign breast tumors from different subtypes of malignant breast tumors

[0212] By comparing and analyzing the methylation levels of SH3PXD2B 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.

[0213] Table 8. Differences in methylation levels of SH3PXD2B gene between benign breast tumors and different subtypes of malignant breast tumors

[0214]

[0215]

[0216] 3. The methylation level of SH3PXD2B gene in tissues can distinguish different subtypes of breast malignancies

[0217] By comparing and analyzing the methylation levels of SH3PXD2B in cases 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 SH3PXD2B 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.

[0218] Table 9. Differences in methylation levels of SH3PXD2B gene in various subtypes of breast malignancies

[0219]

[0220] 4. The methylation level of SH3PXD2B gene in tissues can distinguish benign breast tumors from breast malignant tumors of different stages

[0221] By comparing and analyzing the methylation levels of SH3PXD2B in 287 cases of benign breast tumors and patients with different stages of breast malignant tumors (147 patients in stage 0 & I, 122 patients in stage II, 45 patients in stage III and 4 patients in stage IV), it was found that the methylation levels of SH3PXD2B_A, SH3PXD2B_B and SH3PXD2B_C fragments increased significantly with the increase of stage; while the methylation levels of SH3PXD2B_D and SH3PXD2B_E fragments decreased significantly with the increase of stage. In addition, it can be seen from Table 10 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.

[0222] Table 10. Methylation levels and differences of SH3PXD2B gene in different stages of breast malignancies

[0223]

[0224] 5. The methylation level of SH3PXD2B gene in tissues can distinguish different stages of breast malignancies

[0225] By comparing and analyzing the methylation levels of SH3PXD2B in patients with breast malignancies of 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 SH3PXD2B gene among patients with breast malignancies of stage 0&Ⅰ, stage Ⅱ, stage Ⅲ and stage Ⅳ (P<0.05). The specific results are shown in Table 11.

[0226] Table 11. Differences in methylation levels of SH3PXD2B gene in different stages of breast malignancies

[0227]

[0228]

[0229] 6. Establishment of a mathematical model for SH3PXD2B gene methylation to assist cancer diagnosis

[0230] The mathematical model established by the present invention can be used to achieve the following purposes:

[0231] (1) Differentiate between patients with malignant breast tumors and benign breast tumors;

[0232] (2) Differentiate between different subtypes of breast malignancies;

[0233] (3) Differentiate between different stages of breast malignancies.

[0234] The mathematical model is established as follows:

[0235] (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).

[0236] The data can be added with known parameters such as age according to actual needs to improve the recognition efficiency.

[0237] (B) Model building

[0238] 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 SH3PXD2B 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.

[0239] For example: The data of the methylation level of a single CpG site of the SH3PXD2B 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 subject's SH3PXD2B gene or the methylation level of a combination of multiple CpG sites is detected using a DNA methylation determination method, and then the methylation data obtained by the detection is 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 subject's SH3PXD2B gene 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 class (Class 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 subject's SH3PXD2B gene 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 class (Class 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 subject's SH3PXD2B gene into the above mathematical model, that is, the detection index is equal to the threshold value, it cannot be determined whether the subject is Class A or Class B.

[0240] Example: The methylation of all CpG sites of SH3PXD2B_C (SH3PXD2B_C_1, SH3PXD2B_C_2, SH3PXD2B_C_3, SH3PXD2B_C_4, SH3PXD2B_C_5, SH3PXD2B_C_6) and the application of mathematical modeling in distinguishing female benign breast tumors and breast malignant tumor tissues are illustrated: the methylation level data of all CpG sites of SH3PXD2B_C that have been detected in the training set of patients with benign breast tumors and breast malignant tumors (here: 287 cases of benign breast tumors and 301 cases of breast malignant tumors) and the age of the patients are used to establish a mathematical model for distinguishing female breast malignant tumor patients using the formula of binary logistic regression through SPSS software or R software. The mathematical model here is a binary logistic regression model, which determines the constant b0 of the mathematical model and the weights b1~bn of each methylation site, which are specifically as follows in this example:

[0241] log(y / (1-y))=3.316+2.351*SH3PXD2B_C_1+1.359*SH3PXD2B_C_2+4.672*SH3PXD2B_C_3

[0242] -0.518*SH3PXD2B_C_4+1.794*SH3PXD2B_C_5-2.669*SH3PXD2B_C_6+0.031* age (rounded), wherein y is dependent variable, the methylation value of all CpG sites of SH3PXD2B_C of the sample to be tested and the detection index obtained after the age is substituted into the model. When 0.5 is set as the threshold value, the methylation level of all CpG sites of SH3PXD2B_C of the sample to be tested is substituted into the model together with the information of its age after testing, and the detection index obtained, i.e., the y value is less than the threshold value and is classified as a patient with benign breast tumor, and is greater than the threshold value and is classified as a patient with malignant breast tumor, and is equal to the threshold value and is not determined to be 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 0.92 (table 12). The specific subject judgment method is shown below. Biopsy samples are collected from two subjects (A and B) to extract DNA. After the extracted DNA is converted by bisulfite, the methylation levels of the six CpG sites (SH3PXD2B_C_1, SH3PXD2B_C_2, SH3PXD2B_C_3, SH3PXD2B_C_4, SH3PXD2B_C_5, and SH3PXD2B_C_6) of the subjects are detected by the DNA methylation determination method. The methylation level data obtained by the detection and the age information of the subjects are then substituted into the above mathematical model. The value of SH3PXD2B_C of subject A calculated by the mathematical model is 0.36, which is less than 0.5, so subject A is determined to be a patient with benign breast tumor (consistent with the clinical diagnosis); the methylation level data of all CpG sites of SH3PXD2B_C of subject B are substituted into the above mathematical model and the calculated value is 0.81, which is greater than 0.5, so subject B is determined to be a patient with malignant breast tumor (consistent with the clinical diagnosis).

[0243] (C) Model effect evaluation

[0244] 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 SH3PXD2B_A / SH3PXD2B_B / SH3PXD2B_C / SH3PXD2B_D / SH3PXD2B_E amplified fragments, 2 CpG sites represent a combination of any two CpG sites in the SH3PXD2B_A / SH3PXD2B_B / SH3PXD2B_C / SH3PXD2B_D / SH3PXD2B_E amplified fragments, and 3 CpG sites represent

[0245] Any combination of three CpG sites in the amplified fragments of SH3PXD2B_A / SH3PXD2B_B / SH3PXD2B_C / SH3PXD2B_D / SH3PXD2B_E, 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).

[0246] The above research results show that the methylation of SH3PXD2B gene has 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 SH3PXD2B gene increased with the increase of the number of methylation sites on the SH3PXD2B gene.

[0247] In summary, the methylation levels of CpG sites and their various combinations on the SH3PXD2B gene, CpG sites and their various combinations on the SH3PXD2B_A fragment, CpG sites and their various combinations on the SH3PXD2B_B fragment, CpG sites and their various combinations on the SH3PXD2B_C fragment, CpG sites and their various combinations on the SH3PXD2B_D fragment, CpG sites and their various combinations on the SH3PXD2B_E fragment, and methylation sites and their various combinations on the SH3PXD2B_A, SH3PXD2B_B, SH3PXD2B_C, SH3PXD2B_D and SH3PXD2B_E genes are significant for 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, and patients with benign breast tumors. The clinical diagnosis and treatment of breast cancer in China are as follows: the clinical diagnosis and treatment of breast cancer in China are as follows: 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 benign breast tumors and stage Ⅲ breast malignant tumors, patients with benign breast tumors and stage Ⅳ breast malignant tumors, patients with 0&Ⅰ breast malignant tumors and stage Ⅱ breast malignant tumors, patients with 0&Ⅰ breast malignant tumors and stage Ⅲ breast malignant tumors, patients with 0&Ⅰ breast malignant tumors and stage Ⅳ breast malignant tumors, patients with 0&Ⅰ breast malignant tumors and stage Ⅲ breast malignant tumors, patients with 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.

[0248] Table 12. The value of CpG sites and their combinations in the five segments of SH3PXD2B gene for distinguishing benign breast tumors from malignant breast tumors and their subtypes

[0249]

[0250]

[0251]

[0252]

[0253] Note: The CpG sites in the table refer to distinguishable CpG sites.

[0254] Table 13. The value of the five CpG sites and their combinations in the SH3PXD2B gene for distinguishing different subtypes of breast malignancies

[0255]

[0256]

[0257]

[0258]

[0259] Note: The CpG sites in the table refer to distinguishable CpG sites.

[0260] Table 14. The value of CpG sites and their combinations in the five segments of SH3PXD2B gene for distinguishing benign breast tumors from malignant breast tumors of different stages

[0261]

[0262]

[0263]

[0264]

[0265] Note: The CpG sites in the table refer to distinguishable CpG sites.

[0266] Table 15. The value of CpG sites and their combinations in the five segments of SH3PXD2B gene for distinguishing breast malignancies at different stages

[0267]

[0268]

[0269]

[0270]

[0271] Note: The CpG sites in the table refer to distinguishable CpG sites.

[0272] Example 3: Validation set data

[0273] 1. Sample Selection

[0274] Another set of samples was selected as a validation set (completely different from the training set in this application). With the informed consent, a total of 132 cases of benign breast tumor tissues and 165 cases of malignant breast tumor tissues were collected. The staging of breast cancer was based on the eighth edition of the staging system of the American Joint Committee on Cancer (AJCC). The subtype of patients with malignant breast tumors was determined based on pathological histology. The validation set of 165 patients with malignant breast tumors included 24 cases of intraductal carcinoma, 106 cases of invasive ductal carcinoma, 16 cases of invasive lobular carcinoma, 9 cases of inflammatory breast cancer, 5 cases of medullary carcinoma, 3 cases of mucinous carcinoma and 2 cases of tubular carcinoma. According to the pathological stage, there were 68 patients with stage 0&Ⅰ, 70 patients with stage Ⅱ, 24 patients with stage Ⅲ and 3 patients with stage Ⅳ in the 165 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 51 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.

[0275] 2. Methylation Detection and Data Analysis

[0276] Same as Example 2 in this application.

[0277] 3. Results Analysis

[0278] 1. Analysis of SH3PXD2B gene methylation levels in benign and malignant breast tumors

[0279] The methylation levels of 5 fragments of SH3PXD2B gene were detected in 132 cases of benign breast tumors, 165 cases of malignant breast tumors, 24 cases of intraductal carcinoma, 16 cases of invasive lobular carcinoma, 106 cases of invasive ductal carcinoma and 9 cases of inflammatory breast cancer. The results showed that the methylation levels of SH3PXD2B_A fragment, SH3PXD2B_B fragment and SH3PXD2B_C fragment in breast malignant tumors, intraductal carcinoma, invasive lobular carcinoma, invasive ductal carcinoma and inflammatory breast cancer were still significantly higher than the methylation levels of the corresponding fragments in patients with benign breast tumors (P < 0.001); while the methylation levels of SH3PXD2B_D fragment and SH3PXD2B_E fragment in breast malignant tumors, intraductal carcinoma, invasive lobular carcinoma, invasive ductal carcinoma and inflammatory breast cancer were significantly lower than the methylation levels of the corresponding fragments in patients with benign breast tumors (see Table 16).

[0280] Table 16. SH3PXD2B gene methylation levels in benign and malignant breast tumors and their subtypes

[0281]

[0282]

[0283] 2. The methylation level of SH3PXD2B gene in tissues can distinguish benign breast tumors from different subtypes of malignant breast tumors

[0284] Comparative analysis of SH3PXD2B methylation levels in 132 cases of benign breast tumors and 165 cases of malignant breast tumors (24 cases of intraductal carcinoma, 16 cases of invasive lobular carcinoma, 106 cases of invasive ductal carcinoma and 9 cases of inflammatory breast cancer) in the validation set showed that there was still a significant difference in methylation levels between benign breast tumors and different subtypes of breast cancer (P<0.001). The specific results are shown in Table 17.

[0285] Table 17. Differences in methylation levels of SH3PXD2B gene between benign breast tumors and different subtypes of malignant breast tumors

[0286]

[0287]

[0288] 3. The methylation level of SH3PXD2B gene in tissues can distinguish different subtypes of breast malignancies

[0289] Comparative analysis of SH3PXD2B methylation levels in different types of breast malignancies in the validation set (24 cases of intraductal carcinoma, 16 cases of invasive lobular carcinoma, 106 cases of invasive ductal carcinoma and 9 cases of inflammatory breast cancer) showed that there were significant differences in SH3PXD2B gene methylation levels 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 18.

[0290] Table 18. Differences in methylation levels of SH3PXD2B gene in various subtypes of breast malignancies

[0291]

[0292]

[0293] 4. The methylation level of SH3PXD2B gene in tissues can distinguish benign breast tumors from breast malignant tumors of different stages

[0294] The methylation levels of SH3PXD2B in 132 cases of benign breast tumors and patients with different stages of breast malignant tumors (68 patients in stage 0 & I, 70 patients in stage II, 24 patients in stage III, and 3 patients in stage IV) in the validation set were compared and analyzed. The results showed that the methylation levels of SH3PXD2B_A, SH3PXD2B_B, and SH3PXD2B_C fragments increased significantly with the stage; while the methylation levels of SH3PXD2B_D and SH3PXD2B_E fragments decreased significantly with the stage. There were 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 19.

[0295] Table 19. Methylation levels and differences of SH3PXD2B gene in different stages of breast malignancies

[0296]

[0297] 5. The methylation level of SH3PXD2B gene in tissues can distinguish different stages of breast malignancies

[0298] The methylation levels of SH3PXD2B in patients with breast malignancies of different stages (68 patients in stage 0&Ⅰ, 70 patients in stage Ⅱ, 24 patients in stage Ⅲ and 3 patients in stage Ⅳ) in the validation set were compared and analyzed. The results showed that there were significant differences in the methylation levels of SH3PXD2B gene among patients with breast malignancies of stage 0&Ⅰ, stage Ⅱ, stage Ⅲ and stage Ⅳ (P<0.05). The specific results are shown in Table 20.

[0299] Table 20. Differences in SH3PXD2B gene methylation levels in different stages of breast malignancies

[0300]

[0301] 6. Model Validation

[0302] The methylation levels of the corresponding sites of the SH3PXD2B gene of different types of samples in the validation set were brought into each model in the training set of Example 2 of the present invention for verification. The results are shown in Tables 21, 22, 23 and 24. The CpG sites on the SH3PXD2B gene and their various combinations, the CpG sites on the SH3PXD2B_A fragment and their various combinations, the CpG sites on the SH3PXD2B_B fragment and their various combinations, the CpG sites on the SH3PXD2B_C fragment and their various combinations, the CpG sites on the SH3PXD2B_D fragment and their various combinations, the CpG sites on the SH3PXD2B_E fragment and their various combinations, and the methylation sites on the SH3PXD2B_A, SH3PXD2B_B, SH3PXD2B_C, SH3PXD2B_D and SH3PXD2B_E genes and their various combinations of methylation levels were substituted into the model to obtain the experimental results consistent with the training set, and all groups have the ability to discriminate.

[0303] Table 21. The value of CpG sites and their combinations in the five segments of SH3PXD2B gene for distinguishing benign breast tumors from malignant breast tumors and their subtypes

[0304]

[0305]

[0306]

[0307]

[0308] Note: The CpG sites in the table refer to distinguishable CpG sites.

[0309] Table 22. The value of CpG sites and their combinations in the five segments of SH3PXD2B gene for distinguishing different subtypes of breast malignant tumors

[0310]

[0311]

[0312]

[0313]

[0314] Note: The CpG sites in the table refer to distinguishable CpG sites.

[0315] Table 23. The value of CpG sites and their combinations in the five segments of SH3PXD2B gene for distinguishing benign breast tumors from malignant breast tumors of different stages

[0316]

[0317]

[0318]

[0319]

[0320] Note: The CpG sites in the table refer to distinguishable CpG sites.

[0321] Table 24. The value of CpG sites and their combinations in the five segments of SH3PXD2B gene for distinguishing breast malignancies of different stages

[0322]

[0323]

[0324]

[0325]

[0326]

[0327] Note: The CpG sites in the table refer to distinguishable CpG sites.

[0328] In summary, it can be concluded from the validation set results that the AUC and model in the present invention are effective. Therefore, the methylation level of the marker SH3PXD2B gene can effectively distinguish 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, and patients with invasive ductal carcinoma. Patients with cancer 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 benign breast tumors and stage Ⅲ breast malignant tumors, patients with benign breast tumors and stage Ⅳ breast malignant tumors, patients with 0&Ⅰ breast malignant tumors and stage Ⅱ breast malignant tumors, patients with 0&Ⅰ breast malignant tumors and stage Ⅲ breast malignant tumors, patients with 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.

[0329] 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 SH3PXD2B gene as a marker in the preparation of a product; 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, patients with invasive lobular carcinoma and invasive ductal carcinoma, patients with invasive lobular carcinoma and inflammatory breast cancer, and patients with invasive ductal carcinoma and inflammatory breast cancer. The present invention proves that SH3PXD2B 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.

[0330] The above is only a preferred embodiment of the present invention. It should be pointed out that for ordinary technicians in this technical field, several improvements and modifications can be made without departing from the principle of the present invention. These improvements and modifications should also be regarded as the scope of protection of the present invention.

Claims

1. Use of methylated SH3PXD2B gene as a marker in the preparation of diagnostic products, characterized in that: 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.

2. Use of a substance for detecting SH3PXD2B gene methylation level in the preparation of a diagnostic product, characterized in that: The application is 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.

3. A kit, characterized in that The kit comprises substances for detecting the methylation level of SH3PXD2B gene.

4. The kit according to claim 3, characterized in that The kit also contains a medium recording a method for establishing and / or using a mathematical model.

5. The kit according to claim 4, characterized in that The mathematical model establishment method is: (A1) Detection of SH3PXD2B gene methylation levels in n1 A-type samples and n2 B-type samples, respectively; (A2) taking the methylation level data of the SH3PXD2B gene 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 of classification judgment; The method for using the mathematical model comprises the following steps: (B1) Detecting the methylation level of the SH3PXD2B gene of the sample to be tested; (B2) substituting the SH3PXD2B 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 the threshold, and determining whether the type of the sample to be tested is type A or type B according to the comparison result; The A-type sample and the B-type 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.

6. Use of the kit according to any one of claims 3 to 5 in the preparation of a diagnostic product, characterized in that: The application is 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.

7. A system for detecting methylation level of SH3PXD2B gene, characterized in that: The system comprises: (D1) Reagents and / or instruments for detecting methylation levels of SH3PXD2B genes; (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 acquisition module is configured to collect (D1) the SH3PXD2B 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 SH3PXD2B 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 methylation level data of the SH3PXD2B gene of the subject to be tested obtained by the detection; The data operation module is configured to receive the SH3PXD2B gene methylation level data of the subject to be tested from the data input module, and substitute the SH3PXD2B 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 A-type sample and the B-type 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 methylation level of the SH3PXD2B gene is the methylation level of one or more CpG sites in at least one of the fragments shown in (e1)-(e5) below in the SH3PXD2B gene; The methylated SH3PXD2B gene is methylated at one or more CpG sites in at least one fragment as shown in (e1)-(e5) below in the SH3PXD2B gene; (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 CpG site is selected from any one or more of the following: (f1) the CpG site at position 37-38 from the 5' end of the DNA fragment shown in SEQ ID No. 1; (f2) the CpG site at positions 62-65 from the 5' end of the DNA fragment shown in SEQ ID No. 1; (f3) the CpG site at position 80-81 from the 5' end of the DNA fragment shown in SEQ ID No. 1; (f4) the CpG site at position 87-88 from the 5' end of the DNA fragment shown in SEQ ID No. 1; (f5) the CpG site at position 106-107 from the 5' end of the DNA fragment shown in SEQ ID No. 1; (g1) the CpG site at position 29-30 from the 5' end of the DNA fragment shown in SEQ ID No. 2; (g2) the CpG site at positions 43-46 from the 5' end of the DNA fragment shown in SEQ ID No. 2; (g3) CpG sites at positions 63-64 and 67-68 from the 5' end of the DNA fragment shown in SEQ ID No. 2; (g4) the CpG site at position 152-153 from the 5' end of the DNA fragment shown in SEQ ID No. 2; (h1) the CpG site at position 94-95 from the 5' end of the DNA fragment shown in SEQ ID No.3; (h2) the CpG site at position 136-137 from the 5' end of the DNA fragment shown in SEQ ID No. 3; (h3) the CpG site at positions 181-182 from the 5' end of the DNA fragment shown in SEQ ID No. 3; (h4) the CpG site at position 191-192 from the 5' end of the DNA fragment shown in SEQ ID No. 3; (h5) the CpG site at position 208-209 from the 5' end of the DNA fragment shown in SEQ ID No. 3; (h6) the CpG site at position 221-222 from the 5' end of the DNA fragment shown in SEQ ID No. 3; (i1) the CpG site at position 107-108 from the 5' end of the DNA fragment shown in SEQ ID No. 4; (i2) the CpG site at position 157-158 from the 5' end of the DNA fragment shown in SEQ ID No. 4; (i3) the CpG site at position 186-187 from the 5' end of the DNA fragment shown in SEQ ID No. 4; (j1) the CpG site at position 58-59 from the 5' end of the DNA fragment shown in SEQ ID No.5; (j2) the CpG site at position 123-124 from the 5' end of the DNA fragment shown in SEQ ID No.5; (j3) The DNA fragment shown in SEQ ID No. 5 has a CpG site at position 166-167 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 SH3PXD2B gene comprises a primer combination for amplifying the full length of the SH3PXD2B gene or a primer combination for amplifying a partial fragment of the SH3PXD2B gene; The reagent for detecting the methylation level of the SH3PXD2B gene comprises a primer combination for amplifying the full length of the SH3PXD2B gene or a partial fragment of the SH3PXD2B gene; 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 SEQ ID No.6 or nucleotides 11 to 35 of SEQ ID No.6; the primer A2 is a single-stranded DNA represented by SEQ ID No.7 or nucleotides 32 to 56 of 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 37 of SEQ ID No. 8 or SEQ ID No. 8; the primer B2 is a single-stranded DNA represented by nucleotides 32 to 56 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 SEQ ID No.10 or nucleotides 11-36 of SEQ ID No.10; the primer C2 is a single-stranded DNA represented by SEQ ID No.11 or nucleotides 32-56 of 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 35 of SEQ ID No. 12; the primer D2 is a single-stranded DNA represented by nucleotides 32 to 57 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 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.

Images