A breast malignant tumor and breast benign tumor differential diagnosis marker

Abstract

This invention discloses a methylation marker for the differential diagnosis of malignant and benign breast tumors. The invention provides the application of the methylated SH3PXD2B gene as a marker in product preparation; the product is used for at least one of the following purposes: (1) distinguishing between benign and malignant breast tumors; (2) distinguishing between benign breast tumors and different subtypes or stages of malignant breast tumors; (3) distinguishing between different subtypes or stages of malignant breast tumors. This invention has significant scientific and clinical application value for differentiating between benign and malignant breast tumors, different subtypes or stages of malignant breast tumors, and guiding the development of reasonable clinical treatment plans.

Description

Technical Field

[0001] This invention relates to the medical field, and in particular to a methylation marker for the differential diagnosis of malignant and benign breast tumors. Background Technology

[0002] Breast cancer is the most common malignant tumor among women worldwide and a leading cause of death among women with cancer.

[0003] Currently, pathological examination is the "gold standard" for diagnosing breast cancer and benign breast tumors. However, in actual clinical diagnosis, many benign and malignant breast lesions overlap in pathological morphology, making cytopathological diagnosis difficult and potentially leading to a certain percentage of misdiagnosis or missed diagnosis [Solanki M, Visscher D. Pathology of breast cancer in the last half century. Human pathology, 2020, 95: 137-48.]. Furthermore, the interpretation of pathological diagnostic results depends on the relevant skills of the pathologist and the preparation and staining techniques of the pathological slides, making accuracy 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. Modernpathology: an official journal of the United States and Canadian Academy of Pathology, Inc., 2014, 27(2): 168-74.]. Therefore, finding an efficient and convenient molecular marker for differentiating between benign and malignant breast tumors is of significant clinical and public health importance.

[0004] Epigenetics is a heritable mechanism of gene expression regulation that does not involve alterations to the 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 mechanisms of epigenetic regulation, which refers to the covalent binding of a methyl group at the 5' carbon position of the cytosine of a CpG dinucleotide in the genome under the action of DNA methyltransferases [Bird A. Perceptions of epigenetics. Nature. 2007; 447:396-398]. Numerous 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. The tyrosine kinase substrate it encodes has an N-terminal PX domain and five SH3 domains and is essential for podosome formation, ECM degradation and invasion through matrix gum [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.]. This gene abnormality can lead to a rare genetic disorder called Frank-Ter Haar syndrome (FTHS) [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 adapter 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.].Multiple 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] CancerCells.Cells.2019;8(11):1343.]. However, there are no reports on the association between tissue SH3PXD2B gene methylation and breast cancer. Summary of the Invention

[0006] To address the aforementioned technical problems in the prior art, this invention provides a methylation marker for the differential diagnosis of malignant and benign breast tumors and its application.

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

[0008] The first objective of this invention is to provide the application of methylated SH3PXD2B gene as a biomarker in the preparation of diagnostic products, wherein the products are used for at least one of the following purposes:

[0009] (1) To differentiate or assist in the differentiation between benign breast tumors and malignant breast tumors;

[0010] (2) To differentiate or help differentiate between benign breast tumors and different subtypes of malignant breast tumors;

[0011] (3) To differentiate or assist in differentiating benign breast tumors from malignant breast tumors at different stages;

[0012] (4) To differentiate or assist in differentiating different subtypes of malignant breast tumors;

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

[0014] A second object of the present invention is to provide the use of a substance for detecting methylation levels of the SH3PXD2B gene in the preparation of diagnostic products, said use being at least one of the following:

[0015] (1) To differentiate or assist in the differentiation between benign breast tumors and malignant breast tumors;

[0016] (2) To differentiate or help differentiate between benign breast tumors and different subtypes of malignant breast tumors;

[0017] (3) To differentiate or assist in differentiating benign breast tumors from malignant breast tumors at different stages;

[0018] (4) To differentiate or assist in differentiating different subtypes of malignant breast tumors;

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

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

[0021] Furthermore, the kit also contains a medium describing the mathematical model establishment method and / or usage method.

[0022] Furthermore, the method for establishing the mathematical model is as follows:

[0023] (A1) The methylation level of the SH3PXD2B gene was detected in n1 type A samples and n2 type B samples, respectively;

[0024] (A2) Take the SH3PXD2B gene methylation level data of all samples obtained in step (A1), and establish a mathematical model according to the classification method of type A and type B, and determine the threshold for classification judgment by binary logistic regression.

[0025] The method of using the mathematical model includes the following steps:

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

[0027] (B2) Substitute the SH3PXD2B gene methylation level data of the sample to be tested obtained in step (B1) into the mathematical model to obtain the detection index; then compare the size of the detection index and the threshold, and determine whether the sample to be tested is type A or type B based on the comparison result;

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

[0029] (C1) Benign 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 at different stages;

[0032] (C4) Different subtypes of malignant breast tumors;

[0033] (C5) Malignant breast tumors at different stages.

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

[0035] (1) To differentiate or assist in the differentiation between benign breast tumors and malignant breast tumors;

[0036] (2) To differentiate or help differentiate between benign breast tumors and different subtypes of malignant breast tumors;

[0037] (3) To differentiate or assist in differentiating benign breast tumors from malignant breast tumors at different stages;

[0038] (4) To differentiate or assist in differentiating different subtypes of malignant breast tumors;

[0039] (5) To differentiate or assist in differentiating different stages of malignant breast 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 the methylation level of the SH3PXD2B gene;

[0042] (D2) Device, the 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 acquisition module is configured to acquire SH3PXD2B gene methylation level data from n1 type A samples and n2 type B samples obtained by (D1) detection;

[0045] The data analysis and processing module is configured to receive SH3PXD2B gene methylation level data of the n1 type A samples and n2 type B samples from the data acquisition module, establish a mathematical model according to the classification of type A and type B using binary logistic regression, and determine the classification threshold.

[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 the sample to be tested, including a data input module, a data processing module, a data comparison module, and a conclusion output module;

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

[0049] The data processing module is configured to receive SH3PXD2B gene methylation level data of the subject from the data input module, and substitute the SH3PXD2B gene methylation level data of the subject into the mathematical model established by the data analysis and processing module in unit X to calculate the detection index.

[0050] The data comparison module is configured to receive a detection index calculated by the data processing module and compare the detection index with the threshold determined by 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 as to whether the type of the sample to be tested is type A or type B based on the comparison result.

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

[0053] (C1) Benign 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 at different stages;

[0056] (C4) Different subtypes of malignant breast tumors;

[0057] (C5) Malignant breast tumors at different stages.

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

[0060] (e1) The DNA fragment shown in SEQ ID No. 1 or a DNA fragment having more than 80% identity with it;

[0061] (e2) The DNA fragment shown in SEQ ID No. 2 or a DNA fragment that has more than 80% identity with it;

[0062] (e3) The DNA fragment shown in SEQ ID No. 3 or a DNA fragment having more than 80% identity with it;

[0063] (e4) The DNA fragment shown in SEQ ID No. 4 or a DNA fragment having more than 80% identity with it;

[0064] (e5) The DNA fragment shown in SEQ ID No. 5 or a DNA fragment that is more than 80% identical to it.

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

[0066] (f1) The CpG sites shown at positions 37-38 from the 5' end of the DNA fragment represented by SEQ ID No. 1;

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

[0068] (f3) The CpG sites shown at positions 80-81 from the 5' end of the DNA fragment represented by SEQ ID No. 1;

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

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

[0071] (g1) The CpG sites shown at positions 29-30 from the 5' end of the DNA fragment represented by SEQ ID No. 2;

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

[0073] (g3) The 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 shown at positions 152-153 from the 5' end of the DNA fragment represented by SEQ ID No. 2;

[0075] (h1) The CpG sites shown at positions 94-95 from the 5' end of the DNA fragment represented by SEQ ID No. 3;

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

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

[0078] (h4) The CpG sites shown at positions 191-192 from the 5' end of the DNA fragment represented by SEQ ID No. 3;

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

[0080] (h6) The CpG sites shown at positions 221-222 from the 5' end of the DNA fragment represented by SEQ ID No. 3;

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

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

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

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

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

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

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

[0088] The reagent for detecting the methylation level of the SH3PXD2B gene contains a primer combination for amplifying the full-length or partial fragments of the SH3PXD2B gene.

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

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

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

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

[0093] (k3) The DNA fragment shown in SEQ ID No. 3 or the DNA fragment contained therein;

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

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

[0096] (k6) A DNA fragment that has more than 80% identity with the DNA fragment shown in SEQ ID No. 1 or the DNA fragment contained therein;

[0097] (k7) A DNA fragment that is more than 80% identical to the DNA fragment shown in SEQ ID No. 2 or the DNA fragment contained therein;

[0098] (k8) A DNA fragment that is more than 80% identical to the DNA fragment shown in SEQ ID No. 3 or the DNA fragment contained therein;

[0099] (k9) A DNA fragment that is more than 80% identical to the DNA fragment shown in SEQ ID No. 4 or the DNA fragment contained therein;

[0100] (k10) is a DNA fragment that has more than 80% identity with the DNA fragment shown in SEQ ID No. 5 or the 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; primer A1 is the single-stranded DNA represented by nucleotides 11-35 of SEQ ID No. 6 or SEQ ID No. 6; primer A2 is the single-stranded DNA represented by nucleotides 32-56 of SEQ ID No. 7 or SEQ ID No. 7.

[0103] Primer pair B is a primer pair consisting of primer B1 and primer B2; primer B1 is the single-stranded DNA represented by nucleotides 11-37 of SEQ ID No. 8 or SEQ ID No. 8; primer B2 is the single-stranded DNA represented by nucleotides 32-56 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; primer C1 is the single-stranded DNA represented by nucleotides 11-36 of SEQ ID No. 10 or SEQ ID No. 10; primer C2 is the single-stranded DNA represented by nucleotides 32-56 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; primer D1 is the single-stranded DNA represented by nucleotides 11-35 of SEQ ID No. 12 or SEQ ID No. 12; primer D2 is the single-stranded DNA represented by nucleotides 32-57 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; primer E1 is the single-stranded DNA represented by nucleotides 11-35 of SEQ ID No. 14 or SEQ ID No. 14; primer E2 is the single-stranded DNA represented by nucleotides 32-56 of SEQ ID No. 15 or SEQ ID No. 15.

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

[0108]

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

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

[0111] The “all or part of the CpG sites” mentioned in this invention refer to any one or more CpG sites among the five DNA fragments shown in SEQ ID No. 1 to SEQ ID No. 5 in the SH3PXD2B gene;

[0112] Alternatively, the "all or part of the CpG sites" refers to 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 of the SH3PXD2B gene;

[0113] Alternatively, the “all or part of the CpG sites” refers to 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 of the SH3PXD2B gene;

[0114] Alternatively, the “all or part of the CpG sites” refers to 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 of the SH3PXD2B gene;

[0115] Alternatively, the “all or part of the CpG sites” refers to 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 of the SH3PXD2B gene;

[0116] Alternatively, the “all or part of the CpG sites” refers to 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 of the SH3PXD2B gene;

[0117] Alternatively, the “all or part of the CpG sites” refers to 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 of the SH3PXD2B gene;

[0118] Alternatively, the “all or part of the CpG sites” refers to 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 of the SH3PXD2B gene;

[0119] Alternatively, the “all or part of the CpG sites” refers to 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 of the SH3PXD2B gene;

[0120] Alternatively, the “all or part of the CpG sites” refers to 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 of the SH3PXD2B gene;

[0121] Alternatively, the “all or part of the CpG sites” refers to 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 of the SH3PXD2B gene;

[0122] Alternatively, the “all or part of the CpG sites” refers to 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 of the SH3PXD2B gene;

[0123] Alternatively, the “all or part of the CpG sites” refers to 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 of the SH3PXD2B gene;

[0124] Alternatively, the “all or part of the CpG sites” refers to 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 of the SH3PXD2B gene;

[0125] Alternatively, the “all or part of the CpG sites” refers to 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 of the SH3PXD2B gene;

[0126] Alternatively, the “all or part of the CpG sites” refers to 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 of the SH3PXD2B gene;

[0127] Alternatively, the “all or part of the CpG sites” refers to 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 of the SH3PXD2B gene;

[0128] Alternatively, the “all or part of the CpG sites” refers to all CpG sites in the DNA fragment shown in SEQ ID No. 1 and all CpG sites in the DNA fragment shown in SEQ ID No. 2 of the SH3PXD2B gene;

[0129] Alternatively, the “all or part of the CpG sites” refers to all CpG sites in the DNA fragment shown in SEQ ID No. 1 and all CpG sites in the DNA fragment shown in SEQ ID No. 3 of the SH3PXD2B gene;

[0130] Alternatively, the “all or part of the CpG sites” refers to all CpG sites in the DNA fragment shown in SEQ ID No. 1 and all CpG sites in the DNA fragment shown in SEQ ID No. 4 of the SH3PXD2B gene;

[0131] Alternatively, the “all or part of the CpG sites” refers to all CpG sites in the DNA fragment shown in SEQ ID No. 1 and all CpG sites in the DNA fragment shown in SEQ ID No. 5 of the SH3PXD2B gene;

[0132] Alternatively, the “all or part of the CpG sites” refers to 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 of the SH3PXD2B gene;

[0133] Alternatively, the “all or part of the CpG sites” refers to 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 of the SH3PXD2B gene;

[0134] Alternatively, the “all or part of the CpG sites” refers to 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 of the SH3PXD2B gene;

[0135] Alternatively, the “all or part of the CpG sites” refers to 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 of the SH3PXD2B gene;

[0136] Alternatively, the “all or part of the CpG sites” refers to 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 of the SH3PXD2B gene;

[0137] Alternatively, the “all or part of the CpG sites” refers to 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 of the SH3PXD2B gene;

[0138] Alternatively, the "all or part of the CpG sites" refers to all, any four, any three, any two, or any one of the following five CpG sites in the DNA fragment shown in SEQ ID No. 1 of the SH3PXD2B gene:

[0139] (f1) The CpG sites shown at positions 37-38 from the 5' end of the DNA fragment represented by SEQ ID No. 1;

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

[0141] (f3) The CpG sites shown at positions 80-81 from the 5' end of the DNA fragment represented by SEQ ID No. 1;

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

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

[0144] Alternatively, the "all or part of the CpG sites" refers to all, any three, any two, or any one of the following four CpG sites in the DNA fragment shown in SEQ ID No. 2 of the SH3PXD2B gene:

[0145] (g1) The CpG sites shown at positions 29-30 from the 5' end of the DNA fragment represented by SEQ ID No. 2;

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

[0147] (g3) The 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 shown at positions 152-153 from the 5' end of the DNA fragment represented by SEQ ID No. 2;

[0149] Alternatively, the "all or part of the CpG sites" refers to all, any 5, any 4, any 3, any 2, or any 1 of the following 6 CpG sites in the DNA fragment shown in SEQ ID No. 3 of the SH3PXD2B gene:

[0150] (h1) The CpG sites shown at positions 94-95 from the 5' end of the DNA fragment represented by SEQ ID No. 3;

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

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

[0153] (h4) The CpG sites shown at positions 191-192 from the 5' end of the DNA fragment represented by SEQ ID No. 3;

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

[0155] (h6) The CpG sites shown at positions 221-222 from the 5' end of the DNA fragment represented by SEQ ID No. 3;

[0156] Alternatively, the "all or part of the CpG sites" refers to all, any two, or any one of the following three CpG sites in the DNA fragment shown in SEQ ID No. 4 of the SH3PXD2B gene:

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

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

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

[0160] Alternatively, the "all or part of the CpG sites" refers to all, any two, or any one of the following three CpG sites in the DNA fragment shown in SEQ ID No. 5 of the SH3PXD2B gene:

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

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

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

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

[0165] This invention discloses a methylation biomarker for the differential diagnosis of malignant and benign breast tumors. This invention provides the application of the methylated SH3PXD2B gene as a biomarker in the preparation of diagnostic products, which can: (1) differentiate between benign and malignant breast tumors; (2) differentiate between benign breast tumors and different subtypes or stages of malignant breast tumors; (3) differentiate between different subtypes or stages of malignant breast tumors, and guide the development of reasonable clinical treatment plans. These features have significant scientific and clinical application value. Detailed Implementation

[0166] The present invention will be further explained below with reference to the embodiments, but the embodiments do not limit the present invention in any way.

[0167] Unless otherwise specified, the experimental methods used in the following examples are conventional methods, performed according to the techniques or conditions described in the literature in this field or according to the product instructions. Unless otherwise specified, the materials and reagents used in the following examples are commercially available.

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

[0169] This study selected and examined the methylation levels of CpG sites on five fragments of the SH3PXD2B gene (SH3PXD2B_A, SH3PXD2B_B, SH3PXD2B_C, SH3PXD2B_D, and SH3PXD2B_E), and analyzed the correlation between the methylation levels of CpG sites on these five gene fragments and breast cancer.

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

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

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

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

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

[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, SH3PXD2B_B, SH3PXD2B_C, SH3PXD2B_D, and SH3PXD2B_E), as shown in Table 6.

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

[0184] Table 6. SH3PXD2B methylation primer sequences

[0185]

[0186] Example 2: Detection and Analysis of SH3PXD2B Gene Methylation

[0187] I. Research Sample

[0188] With informed consent from the patients, tissue samples from 287 benign breast tumors and 318 malignant breast tumors were collected. Breast cancer staging was based on the American Joint Committee on Cancer (AJCC) 8th edition staging system. Subtypes of malignant breast tumors were determined based on histopathological findings. The 318 malignant breast tumor patients collected included 41 cases of ductal carcinoma in situ, 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 pathological staging, among the 318 malignant breast tumor patients, there were 147 stage 0 & I patients, 122 stage II patients, 45 stage III patients, and 4 stage IV patients. All diagnoses were based on histopathological evidence collected during surgery. Complete clinical data records were available for all patients. The case investigation included collecting general demographic information such as age and sex. The median age of patients with benign and malignant breast tumors was 49 years and 52 years, respectively. Information on estrogen receptor (ER) levels, progesterone receptor (PR) levels, human epidermal growth factor receptor-2 (HER2) levels, and Ki67 protein levels were also collected from the cases.

[0189] II. Methylation Detection

[0190] 1. Total DNA was extracted from the tissue using the DNA Isolation Kit (Novozymes, Nanjing, China).

[0191] 2. After the total DNA from the tissue sample prepared in step 1 is treated with bisulfite (EZ DNA Methylation Kit (ZYMO RESEARCH, USA, catalog number D5002)), the unmethylated cytosine (C) is converted to uracil (U), while the methylated cytosine remains unchanged. That is, the C base at the original CpG site is converted to 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 specific primer pairs in Table 6 with DNA polymerase according to the reaction system required for conventional PCR. All 5 primer pairs used the same conventional PCR system, and all 5 primer pairs were amplified according to the following procedure.

[0193] The PCR reaction program was as follows: 95℃, 4min → (95℃, 20s → 56℃, 30s → 72℃, 2min), 45 cycles → 72℃, 5min → 4℃, 1h.

[0194] 4. Take the amplification product from 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 then incubate in the PCR instrument according to the following procedure (37℃, 20 min → 85℃, 5 min → 4℃, 5 min);

[0196] (2) Take out 2 μl of the SAP-treated product obtained in step (1) and 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 from step (2), add 19 μl of deionized water, and then incubate with 6 μg of Resin in a rotating shaker for 1 h for deionization.

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

[0199] (5) Time-of-flight mass spectrometry analysis; the obtained data were collected using SpectroACQUIRE v3.3.1.3 software and visualized using MassArrayEpiTyper v1.2 software.

[0200] The reagents used in the above time-of-flight mass spectrometry detection were all from the kit (T-Cleavage MassCLEAVEReagent Auto Kit, catalog number: 10129A); the detection instrument used in the above time-of-flight mass spectrometry detection was... Analyzer Chip Prep Module 384, model: 41243; the above data analysis software is the software that comes with the testing instrument.

[0201] III. Quality Control

[0202] Medical record information was entered using a dual-track system and subjected to consistency checks. Experimental procedures were strictly followed, with regular UV disinfection of the operating environment. Preliminary experiments were conducted before the formal experiments. 5% of samples were randomly selected for repeated time-of-flight mass spectrometry (TOF-MS) analysis to ensure a consistency rate of over 99%. Experimental results were interpreted by two people, and methylation data were compiled to ensure data accuracy. Through mass spectrometry experiments, 21 distinguishable peaks containing methylated fragments were obtained. The methylation level was calculated using SpectroACQUIRE v3.3.1.3 software based on the formula: methylation level = peak area of ​​methylated fragment / (peak area of ​​unmethylated fragment + peak area of ​​methylated fragment). (SpectroACQUIRE v3.3.1.3 software can automatically calculate the methylation level of each sample at each CpG site by calculating the peak area.)

[0203] IV. Statistical Analysis

[0204] Median methylation levels were used to represent methylation levels, and nonparametric tests were used to compare differences in methylation levels between two or more groups. Logistic regression and receiver operating characteristic (ROC) curves were used to evaluate the diagnostic value of single CpG sites and combinations of multiple CpG sites. A two-sided p-value < 0.05 was considered statistically significant. 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 five fragments of the SH3PXD2B gene were detected in 287 cases of benign breast tumors, 318 cases of malignant breast tumors, 41 cases of ductal carcinoma in situ, 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 the SH3PXD2B_A, SH3PXD2B_B, and SH3PXD2B_C fragments in malignant breast tumors, ductal carcinoma in situ, invasive lobular carcinoma, invasive ductal carcinoma, and inflammatory breast cancer were significantly higher than those in patients with benign breast tumors (P < 0.001); while the methylation levels of the SH3PXD2B_D and SH3PXD2B_E fragments in malignant breast tumors, ductal carcinoma in situ, invasive lobular carcinoma, invasive ductal carcinoma, and inflammatory breast cancer were significantly lower than those in patients with benign breast tumors (see Table 7).

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

[0209]

[0210]

[0211] 2. The methylation level of the SH3PXD2B gene in tissues can differentiate between benign breast tumors and different subtypes of malignant breast tumors.

[0212] By comparing and analyzing the SH3PXD2B methylation levels of 287 cases of benign breast tumors and 301 cases of malignant breast tumors (41 cases of ductal carcinoma in situ, 31 cases of invasive lobular carcinoma, 218 cases of invasive ductal carcinoma, and 11 cases of inflammatory breast cancer), significant differences in methylation levels were found between benign breast tumors and different subtypes of breast cancer (P<0.001). Specific results are shown in Table 8.

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

[0214]

[0215]

[0216] 3. The methylation level of the SH3PXD2B gene in tissues can differentiate between different subtypes of malignant breast tumors.

[0217] By comparing and analyzing the SH3PXD2B methylation levels of different subtypes of breast malignant tumors (41 cases of ductal carcinoma in situ, 31 cases of invasive lobular carcinoma, 218 cases of invasive ductal carcinoma, and 11 cases of inflammatory breast cancer), significant differences were found in the SH3PXD2B gene methylation levels among patients with ductal carcinoma in situ, invasive lobular carcinoma, invasive ductal carcinoma, and inflammatory breast cancer (P < 0.001). Specific results are shown in Table 9.

[0218] Table 9. Differences in SH3PXD2B gene methylation levels among different subtypes of malignant breast tumors.

[0219]

[0220] 4. The methylation level of the SH3PXD2B gene in tissues can differentiate between benign breast tumors and malignant breast tumors at different stages.

[0221] By comparing and analyzing the SH3PXD2B methylation levels of 287 cases of benign breast tumors and patients with breast cancer at different stages (147 stage 0 & I patients, 122 stage II patients, 45 stage III patients, and 4 stage IV patients), the results showed that the methylation levels of SH3PXD2B_A, SH3PXD2B_B, and SH3PXD2B_C fragments increased significantly with increasing stage; while the methylation levels of SH3PXD2B_D and SH3PXD2B_E fragments decreased significantly with increasing stage. Furthermore, Table 10 also shows that there were significant differences in methylation levels between benign breast tumors and breast cancer at different stages (P < 0.001). Detailed results are shown in Table 10.

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

[0223]

[0224] 5. The methylation level of the SH3PXD2B gene in tissues can differentiate between different stages of breast cancer.

[0225] By comparing and analyzing the SH3PXD2B methylation levels of breast cancer patients at different stages (147 patients in stage 0 & I, 122 patients in stage II, 45 patients in stage III, and 4 patients in stage IV), significant differences were found in the SH3PXD2B gene methylation levels among patients with breast cancer at stages 0 & I, II, III, and IV (P < 0.05). Specific results are shown in Table 11.

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

[0227]

[0228]

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

[0230] The mathematical model established in this invention can be used to achieve the following objectives:

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

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

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

[0234] The mathematical model is established as follows:

[0235] (A) Data source: The methylation levels of target CpG sites (one or more combinations of Tables 1-5) in tissue samples from 287 benign breast tumors and 301 malignant breast tumors (41 cases of ductal carcinoma in situ, 31 cases of invasive lobular carcinoma, 218 cases of invasive ductal carcinoma and 11 cases of inflammatory breast cancer) listed in Step 1 (detection method is the same as in Step 2).

[0236] The data can be supplemented with known parameters such as age to improve the discrimination efficiency, depending on actual needs.

[0237] (B) Model Establishment

[0238] Select any two different types of patient data as the training set (e.g., patients with benign breast tumors and malignant breast tumors, patients with benign breast tumors and ductal carcinoma in situ, 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 ductal carcinoma in situ and invasive lobular carcinoma, patients with ductal carcinoma in situ and invasive ductal carcinoma, patients with ductal carcinoma in situ 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 malignant breast tumors, patients with benign breast tumors and stage II malignant breast cancer). Patients with various breast cancer categories (stage I and stage II, stage III and stage IV, stage II and stage III, stage II and stage IV, and stage III and stage IV) were used as data for model building. Statistical software such as SAS, R, and SPSS were used to establish a mathematical model using binary logistic regression. The maximum Youden index calculated by the mathematical model formula was used as the threshold, or a threshold of 0.5 was directly set. Samples with a detection index greater than the threshold after testing and model calculation were classified into one category (Class B), those with an index less than the threshold were classified into another category (Class A), and those equal to the threshold were treated as an uncertain gray area. When predicting the category of a new sample to be tested, the methylation level of one or more CpG sites on the SH3PXD2B gene of the sample is first detected by DNA methylation assay. Then, the data of these methylation levels are substituted into the mathematical model to calculate the detection index corresponding to the sample. The detection index and the threshold corresponding to the sample are then compared, and the category of the sample is determined based on the comparison results.

[0239] For example, data on the methylation levels of a single CpG site or a combination of multiple CpG sites in the SH3PXD2B gene from the training set are used in statistical software such as SAS, R, and SPSS to establish a mathematical model for distinguishing between classes A and B using a binary logistic regression formula. This 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 by substituting the methylation values ​​of one or more methylation sites of the sample into the model; b0 is a constant; x1~xn are the independent variables, i.e., the methylation values ​​of one or more methylation sites of the sample (each value is between 0 and 1); and b1~bn are the weights assigned to each methylation value by the model. In practical applications, a mathematical model is first established based on the methylation degree (x1~xn) of one or more DNA methylation sites in the samples already tested in the training set and their known classification (class A or class B, with y assigned values ​​of 0 and 1 respectively). This model determines the constant b0 and the weights b1~bn of each methylation site. The threshold value corresponding to the maximum Yangen index, calculated by the mathematical model, is used as the dividing threshold, or a threshold of 0.5 is directly set. After testing and inputting the sample into the model, the detection index (y value) is assigned to class B if it is greater than the threshold, class A if it is less than the threshold, and an uncertain gray area if it equals the threshold. Class A and class B are corresponding binary classifications (the grouping of binary classification, which group is class A and which is class B, depends on the specific mathematical model and is not specified here). When predicting the category of a subject's sample, a biopsy sample is first collected from the subject, and then DNA is extracted from it. After the extracted DNA is converted by bisulfite, the methylation level of a single CpG site or the methylation level of a combination of multiple CpG sites in the subject's SH3PXD2B gene is detected using a DNA methylation assay. The methylation data obtained are then substituted into the mathematical model mentioned above (if known parameters such as age were included when the model was constructed, this step also substitutes the specific values ​​of the corresponding parameters of the sample to be tested into the model formula). If the methylation level of one or more CpG sites in the subject's SH3PXD2B gene, calculated using the mathematical model, is greater than the threshold, then the subject is classified into the same category (Category B) as those in the training set whose methylation level is greater than the threshold. If the methylation level of one or more CpG sites in the subject's SH3PXD2B gene, calculated using the mathematical model, is less than the threshold, then the subject is classified into the same category (Category A) as those in the training set whose methylation level is less than the threshold. If the methylation level of one or more CpG sites in the subject's SH3PXD2B gene, calculated using the mathematical model, is equal to the threshold, then it is impossible to determine whether the subject belongs to Category A or Category B.

[0240] Example: This example illustrates the application of methylation data and mathematical modeling of all CpG sites (SH3PXD2B_C_1, SH3PXD2B_C_2, SH3PXD2B_C_3, SH3PXD2B_C_4, SH3PXD2B_C_5, SH3PXD2B_C_6) of SH3PXD2B_C in differentiating between benign and malignant breast tumors in women. Using data on the methylation levels of all CpG sites of SH3PXD2B_C detected in a training set of patients with benign and malignant breast tumors (in this case, 287 patients with benign breast tumors and 301 patients with malignant breast tumors) and patient age, a mathematical model for differentiating between benign and malignant breast tumors in women was established using a binary logistic regression formula with SPSS or R software. This mathematical model is a binary logistic regression model, thus determining the constant b0 and the weights b1 to bn of each methylation site, 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 to the nearest integer), where y is the dependent variable, which is the detection index obtained by substituting the methylation values ​​of all CpG sites of SH3PXD2B_C in the sample and the age into the model. With a threshold of 0.5, the methylation level of all CpG sites of SH3PXD2B_C in the sample, after testing, is combined with the age information and substituted into the model for calculation. The resulting detection index, i.e., y value less than the threshold, is classified as a benign breast tumor patient; greater than the threshold, it is classified as a malignant breast tumor patient; and equal to the threshold, it is uncertain whether the patient has a benign or malignant breast tumor. The area under the curve (AUC) of this model is 0.92 (Table 12). The specific method for determining the subjects is illustrated below. Biopsy samples were collected from two subjects (A and B) to extract DNA. After bisulfite conversion, the extracted DNA was used to detect the methylation levels of six CpG sites (SH3PXD2B_C_1, SH3PXD2B_C_2, SH3PXD2B_C_3, SH3PXD2B_C_4, SH3PXD2B_C_5, and SH3PXD2B_C_6) using a DNA methylation assay. The obtained methylation level data, along with the subjects' age information, was then substituted into the mathematical model described above. Subject A's SH3PXD2B_C value calculated using the mathematical model is 0.36, which is less than 0.5. Therefore, Subject A is diagnosed as a benign breast tumor patient (consistent with the clinical diagnosis). Subject B's SH3PXD2B_C methylation level data for all CpG sites is calculated using the same mathematical model. The calculated value is 0.81, which is greater than 0.5. Therefore, Subject B is diagnosed as a malignant breast tumor patient (consistent with the clinical diagnosis).

[0243] (C) Model Performance Evaluation

[0244] Based on the above methods, separate diagnostic tools were established for patients with benign breast tumors and malignant breast tumors, benign breast tumors and ductal carcinoma in situ, benign breast tumors and invasive lobular carcinoma, benign breast tumors and invasive ductal carcinoma, benign breast tumors and inflammatory breast cancer, ductal carcinoma in situ and invasive lobular carcinoma, ductal carcinoma in situ and invasive ductal carcinoma, ductal carcinoma in situ and inflammatory breast cancer, invasive lobular carcinoma and invasive ductal carcinoma, invasive ductal carcinoma and inflammatory breast cancer, invasive ductal carcinoma and inflammatory breast cancer, benign breast tumors and stage 0 & I malignant breast tumors, and benign breast tumors. Mathematical models were constructed for patients with stage II breast cancer, benign breast cancer and stage III breast cancer, benign breast cancer and stage IV breast cancer, stage 0 & I breast cancer and stage II breast cancer, stage 0 & I breast cancer and stage III breast cancer, stage 0 & I breast cancer and stage IV breast cancer, stage II breast cancer and stage III breast cancer, stage II breast cancer and stage IV breast cancer, and stage III breast cancer and stage IV breast cancer. The effectiveness of these models was evaluated using receiver operating characteristic (ROC) curves. A larger area under the ROC curve (AUC) indicates better model discrimination and more effective molecular markers. The evaluation results after constructing mathematical models using different CpG sites are shown in Tables 12, 13, 14, and 15. In Tables 12, 13, 14, and 15, one CpG site represents any one CpG site in the SH3PXD2B_A / SH3PXD2B_B / SH3PXD2B_C / SH3PXD2B_D / SH3PXD2B_E amplified fragment; two CpG sites represent any combination of two CpG sites in the SH3PXD2B_A / SH3PXD2B_B / SH3PXD2B_C / SH3PXD2B_D / SH3PXD2B_E amplified fragment; and three CpG sites represent...

[0245] The table lists any three CpG sites from the amplified fragments SH3PXD2B_A / SH3PXD2B_B / SH3PXD2B_C / SH3PXD2B_D / SH3PXD2B_E, and so on. The values ​​in the table represent the range of evaluation results for different site combinations (i.e., the results for any combination of CpG sites are within this range).

[0246] The above results show that SH3PXD2B gene methylation has a significant effect on the differentiation between different groups (patients with benign breast tumors and malignant breast tumors, patients with benign breast tumors and ductal carcinoma in situ, 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 ductal carcinoma in situ and invasive lobular carcinoma, patients with ductal carcinoma in situ and invasive ductal carcinoma, patients with ductal carcinoma in situ and inflammatory breast cancer, patients with invasive lobular carcinoma and invasive ductal carcinoma, patients with invasive ductal carcinoma and inflammatory breast cancer, patients with benign breast tumors and stage 0 & I malignant breast cancer). The number of patients with breast cancer (including those with benign breast tumors and stage II malignant breast tumors, those with benign breast tumors and stage III malignant breast tumors, those with benign breast tumors and stage IV malignant breast tumors, those with stage 0 & I malignant breast tumors and stage II malignant breast tumors, those with stage 0 & I malignant breast tumors and stage III malignant breast tumors, those with stage 0 & I malignant breast tumors and stage IV malignant breast tumors, those with stage II malignant breast tumors and stage III malignant breast tumors, and those with stage II malignant breast tumors and stage IV malignant breast tumors) increased with 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, the CpG sites and their various combinations on the SH3PXD2B_A fragment, the CpG sites and their various combinations on the SH3PXD2B_B fragment, the CpG sites and their various combinations on the SH3PXD2B_C fragment, the CpG sites and their various combinations on the SH3PXD2B_D fragment, the CpG sites and their various combinations on the SH3PXD2B_E fragment, and the methylation levels of methylation sites and their various combinations on the SH3PXD2B_A, SH3PXD2B_B, SH3PXD2B_C, SH3PXD2B_D, and SH3PXD2B_E genes are important for patients with benign and malignant breast tumors, patients with benign breast tumors and ductal carcinoma in situ, 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 system has the ability to differentiate between patients with fibrocystic and inflammatory breast cancer, ductal carcinoma in situ and invasive lobular carcinoma, ductal carcinoma in situ and invasive ductal carcinoma, ductal carcinoma in situ 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 malignant breast tumors, benign breast tumors and stage II malignant breast tumors, benign breast tumors and stage III malignant breast tumors, benign breast tumors and stage IV malignant breast tumors, stage 0 & I malignant breast tumors and stage II malignant breast tumors, stage 0 & I malignant breast tumors and stage III malignant breast tumors, stage 0 & I malignant breast tumors and stage IV malignant breast tumors, stage II malignant breast tumors and stage III malignant breast tumors, stage II malignant breast tumors and stage IV malignant breast tumors, and stage III malignant breast tumors and stage IV malignant breast tumors.

[0248] Table 12. Value of five CpG sites and their combinations in the SH3PXD2B gene for differentiating benign and malignant breast tumors and their subtypes.

[0249]

[0250]

[0251]

[0252]

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

[0254] Table 13. Value of five CpG sites and their combinations in the SH3PXD2B gene for differentiating different subtypes of breast cancer.

[0255]

[0256]

[0257]

[0258]

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

[0260] Table 14. Value of five CpG sites and their combinations in the SH3PXD2B gene for differentiating benign breast tumors from malignant breast tumors at different stages.

[0261]

[0262]

[0263]

[0264]

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

[0266] Table 15. Value of five CpG sites and their combinations in the SH3PXD2B gene for differentiating breast cancers at different stages.

[0267]

[0268]

[0269]

[0270]

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

[0272] Example 3: Validation Set Data

[0273] I. Sample Selection

[0274] A separate sample was selected as the validation set (completely different from the training set in this application). With informed consent, a total of 132 benign breast tumor tissue samples and 165 malignant breast tumor tissue samples were collected. Breast cancer staging was based on the American Joint Committee on Cancer (AJCC) 8th edition staging system. Subtypes of malignant breast tumors were determined based on pathological histology. The validation set of 165 malignant breast tumor patients included 24 cases of ductal carcinoma in situ, 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 pathological staging, among the 165 malignant breast tumor patients, there were 68 stage 0 & I patients, 70 stage II patients, 24 stage III patients, and 3 stage IV patients. The diagnosis of all patients was based on histopathological evidence collected during surgery. All patients had complete clinical data records. The case investigation included collecting general demographic information such as age and sex of the subjects. The median age of patients with benign and malignant breast tumors was 49 years and 51 years, respectively. Information on estrogen receptor (ER), progesterone receptor (PR), human epidermal growth factor receptor-2 (HER2), and Ki67 protein levels was also collected.

[0275] II. Methylation Detection and Data Analysis

[0276] Same as Example 2 in this application.

[0277] III. Results Analysis

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

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

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

[0281]

[0282]

[0283] 2. The methylation level of the SH3PXD2B gene in tissues can differentiate between benign breast tumors and different subtypes of malignant breast tumors.

[0284] A comparative analysis of SH3PXD2B methylation levels in 132 cases of benign breast tumors and 165 cases of malignant breast tumors (24 cases of ductal carcinoma in situ, 16 cases of invasive lobular carcinoma, 106 cases of invasive ductal carcinoma, and 9 cases of inflammatory breast cancer) in the validation set revealed significant differences in methylation levels between benign breast tumors and different subtypes of breast cancer (P<0.001). Specific results are shown in Table 17.

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

[0286]

[0287]

[0288] 3. The methylation level of the SH3PXD2B gene in tissues can differentiate between different subtypes of malignant breast tumors.

[0289] Comparative analysis of SH3PXD2B methylation levels in different subtypes of breast malignant tumors (24 cases of ductal carcinoma in situ, 16 cases of invasive lobular carcinoma, 106 cases of invasive ductal carcinoma, and 9 cases of inflammatory breast cancer) in a validation set revealed significant differences in SH3PXD2B gene methylation levels among patients with ductal carcinoma in situ, invasive lobular carcinoma, invasive ductal carcinoma, and inflammatory breast cancer (P < 0.001). Specific results are shown in Table 18.

[0290] Table 18. Differences in SH3PXD2B gene methylation levels among different subtypes of malignant breast tumors.

[0291]

[0292]

[0293] 4. The methylation level of the SH3PXD2B gene in tissues can differentiate between benign breast tumors and malignant breast tumors at different stages.

[0294] A comparative analysis of SH3PXD2B methylation levels in 132 cases of benign breast tumors and malignant breast tumors at different stages (68 stage 0 & I patients, 70 stage II patients, 24 stage III patients, and 3 stage IV patients) was conducted. The results showed that the methylation levels of SH3PXD2B_A, SH3PXD2B_B, and SH3PXD2B_C fragments significantly increased with increasing stage; while the methylation levels of SH3PXD2B_D and SH3PXD2B_E fragments significantly decreased with increasing stage. Significant differences in methylation levels were observed between benign breast tumors and breast cancer at different stages (P < 0.001). Detailed results are shown in Table 19.

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

[0296]

[0297] 5. The methylation level of the SH3PXD2B gene in tissues can differentiate between different stages of breast cancer.

[0298] A comparative analysis of SH3PXD2B methylation levels was conducted on breast cancer patients at different stages (68 patients in stage 0 & I, 70 patients in stage II, 24 patients in stage III, and 3 patients in stage IV). The results showed significant differences in SH3PXD2B gene methylation levels among patients with stage 0 & I, stage II, stage III, and stage IV breast cancer (P < 0.05). Specific results are shown in Table 20.

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

[0300]

[0301] 6. Model Validation

[0302] The methylation levels of corresponding sites of the SH3PXD2B gene in different types of samples from the validation set were input into various models in the training set of Example 2 of this invention for validation. The results are shown in Tables 21, 22, 23, and 24. The experimental results obtained by substituting the methylation levels of CpG sites and their various combinations on the SH3PXD2B gene, the CpG sites and their various combinations on the SH3PXD2B_A fragment, the CpG sites and their various combinations on the SH3PXD2B_B fragment, the CpG sites and their various combinations on the SH3PXD2B_C fragment, the CpG sites and their various combinations on the SH3PXD2B_D fragment, the CpG sites and their various combinations on the SH3PXD2B_E fragment, and the methylation levels of methylation sites and their various combinations on the SH3PXD2B_A, SH3PXD2B_B, SH3PXD2B_C, SH3PXD2B_D, and SH3PXD2B_E genes into the models were consistent with those of the training set, and all groups showed discriminative ability.

[0303] Table 21. Value of CpG sites and their combinations on five segments of the SH3PXD2B gene in differentiating benign and malignant breast tumors and their subtypes.

[0304]

[0305]

[0306]

[0307]

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

[0309] Table 22. Value of five CpG sites and their combinations in the SH3PXD2B gene for differentiating different subtypes of breast cancer.

[0310]

[0311]

[0312]

[0313]

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

[0315] Table 23. Value of five CpG sites and their combinations in the SH3PXD2B gene for differentiating benign breast tumors from malignant breast tumors at different stages.

[0316]

[0317]

[0318]

[0319]

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

[0321] Table 24. Value of five CpG sites and their combinations in the SH3PXD2B gene for differentiating breast cancers at different stages.

[0322]

[0323]

[0324]

[0325]

[0326]

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

[0328] In summary, the validation set results demonstrate that both the AUC and the model in this invention are effective. Therefore, the methylation level of the SH3PXD2B gene marker can effectively distinguish between patients with benign breast tumors and malignant breast tumors, patients with benign breast tumors and ductal carcinoma in situ, 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 ductal carcinoma in situ and invasive lobular carcinoma, patients with ductal carcinoma in situ and invasive ductal carcinoma, patients with ductal carcinoma in situ 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 malignant breast tumors, patients with benign breast tumors and stage II malignant breast tumors, patients with benign breast tumors and stage III malignant breast tumors, patients with benign breast tumors and stage IV malignant breast tumors, patients with stage 0 & I malignant breast tumors and stage II malignant breast tumors, patients with stage 0 & I malignant breast tumors and stage III malignant breast tumors, patients with stage 0 & I malignant breast tumors and stage IV malignant breast tumors, patients with stage II malignant breast tumors and stage III malignant breast tumors, patients with stage II malignant breast tumors and stage IV malignant breast tumors, patients with stage III malignant breast tumors and stage IV malignant breast tumors.

[0329] This invention discloses a methylation biomarker for the differential diagnosis of malignant and benign breast tumors. The invention provides the application of methylated SH3PXD2B gene as a biomarker in product preparation; the product is used to assist in the differential diagnosis of patients with benign and malignant breast tumors, patients with benign breast tumors and ductal carcinoma in situ, 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 ductal carcinoma in situ and invasive lobular carcinoma, patients with ductal carcinoma in situ and invasive ductal carcinoma, patients with ductal carcinoma in situ 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. This invention demonstrates that SH3PXD2B methylation in biopsy samples can serve as a potential biomarker for the differential diagnosis of benign and malignant breast tumors, as well as different subtypes or stages of malignant breast tumors. This invention has significant scientific and clinical value in differentiating between benign and malignant breast tumors, different subtypes or stages of malignant breast tumors, and in guiding the development of reasonable clinical treatment plans.

[0330] The above description is only a preferred embodiment of the present invention. It should be noted that for those skilled in the art, several improvements and modifications can be made without departing from the principle of the present invention, and these improvements and modifications should also be considered within the scope of protection of the present invention.

Claims

1. The use of a substance for detecting the methylation level of a SH3PXD2B gene fragment in the preparation of a product for assisting in the differentiation of subtypes of breast benign tumors and breast malignant tumors, characterized in that, The subtypes of malignant breast tumors mentioned are ductal carcinoma in situ, invasive lobular carcinoma, invasive ductal carcinoma, or inflammatory breast cancer. The methylation level of the SH3PXD2B gene fragment is the methylation level of the CpG site combination in at least one fragment as shown in (e1)-(e5) of the SH3PXD2B gene. (e1) The DNA fragment shown in SEQ ID No. 1; (e2) The DNA fragment shown in SEQ ID No. 2; (e3) The DNA fragment shown in SEQ ID No. 3; (e4) The DNA fragment shown in SEQ ID No. 4; (e5) The DNA fragment shown in SEQ ID No. 5; The CpG site combinations are (f1)-(f5), (g1)-(g4), (h1)-(h6), (i1)-(i3), or (j1)-(j3): (f1) The CpG sites shown at positions 37-38 from the 5' end of the DNA fragment represented by SEQ ID No. 1; (f2) The CpG sites shown at positions 62-65 from the 5' end of the DNA fragment represented by SEQ ID No. 1; (f3) The CpG sites shown at positions 80-81 from the 5' end of the DNA fragment represented by SEQ ID No. 1; (f4) The CpG sites shown at positions 87-88 from the 5' end of the DNA fragment represented by SEQ ID No. 1; (f5) The CpG site shown at positions 106-107 from the 5' end of the DNA fragment represented by SEQ ID No. 1; (g1) The CpG sites shown at positions 29-30 from the 5' end of the DNA fragment represented by SEQ ID No. 2; (g2) The CpG sites shown at positions 43-46 from the 5' end of the DNA fragment represented by SEQ ID No. 2; (g3) The CpG sites shown at positions 63-64 and 67-68 from the 5' end of the DNA fragment represented by SEQ ID No. 2; (g4) The CpG site shown at positions 152-153 from the 5' end of the DNA fragment shown in SEQ ID No. 2; (h1) The CpG sites shown at positions 94-95 from the 5' end of the DNA fragment represented by SEQ ID No. 3; (h2) The CpG sites shown at positions 136-137 from the 5' end of the DNA fragment represented by SEQ ID No. 3; (h3) The CpG sites shown at positions 181-182 from the 5' end of the DNA fragment represented by SEQ ID No. 3; (h4) The CpG sites shown at positions 191-192 from the 5' end of the DNA fragment represented by SEQ ID No. 3; (h5) The CpG sites shown at positions 208-209 from the 5' end of the DNA fragment represented by SEQ ID No. 3; (h6) The CpG sites shown at positions 221-222 from the 5' end of the DNA fragment represented by SEQ ID No. 3; (i1) The CpG site shown at positions 107-108 from the 5' end of the DNA fragment shown in SEQ ID No. 4; (i2) The CpG sites shown at positions 157-158 from the 5' end of the DNA fragment shown in SEQ ID No. 4; (i3) The CpG site shown at positions 186-187 from the 5' end of the DNA fragment shown in SEQ ID No. 4; (j1) The CpG sites at positions 58-59 from the 5' end of the DNA fragment shown in SEQ ID No. 5; (j2) The CpG sites shown at positions 123-124 from the 5' end of the DNA fragment shown in SEQ ID No. 5; (j3) The CpG site shown at positions 166-167 from the 5' end of the DNA fragment shown in SEQ ID No.

5.

2. The application of the kit in the preparation of products that help differentiate between benign and malignant breast tumor subtypes, characterized in that, The subtypes of malignant breast tumors mentioned are ductal carcinoma in situ, invasive lobular carcinoma, invasive ductal carcinoma, or inflammatory breast cancer. The kit includes substances for detecting the methylation level of the SH3PXD2B gene fragment; The methylation level of the SH3PXD2B gene fragment is the methylation level of the CpG site combination in at least one fragment as shown in (e1)-(e5) of the SH3PXD2B gene. (e1) The DNA fragment shown in SEQ ID No. 1; (e2) The DNA fragment shown in SEQ ID No. 2; (e3) The DNA fragment shown in SEQ ID No. 3; (e4) The DNA fragment shown in SEQ ID No. 4; (e5) The DNA fragment shown in SEQ ID No. 5; The CpG site combinations are (f1)-(f5), (g1)-(g4), (h1)-(h6), (i1)-(i3), or (j1)-(j3): (f1) The CpG sites shown at positions 37-38 from the 5' end of the DNA fragment represented by SEQ ID No. 1; (f2) The CpG sites shown at positions 62-65 from the 5' end of the DNA fragment represented by SEQ ID No. 1; (f3) The CpG sites shown at positions 80-81 from the 5' end of the DNA fragment represented by SEQ ID No. 1; (f4) The CpG sites shown at positions 87-88 from the 5' end of the DNA fragment represented by SEQ ID No. 1; (f5) The CpG site shown at positions 106-107 from the 5' end of the DNA fragment represented by SEQ ID No. 1; (g1) The CpG sites shown at positions 29-30 from the 5' end of the DNA fragment represented by SEQ ID No. 2; (g2) The CpG sites shown at positions 43-46 from the 5' end of the DNA fragment represented by SEQ ID No. 2; (g3) The CpG sites shown at positions 63-64 and 67-68 from the 5' end of the DNA fragment represented by SEQ ID No. 2; (g4) The CpG site shown at positions 152-153 from the 5' end of the DNA fragment shown in SEQ ID No. 2; (h1) The CpG sites shown at positions 94-95 from the 5' end of the DNA fragment represented by SEQ ID No. 3; (h2) The CpG sites shown at positions 136-137 from the 5' end of the DNA fragment represented by SEQ ID No. 3; (h3) The CpG sites shown at positions 181-182 from the 5' end of the DNA fragment represented by SEQ ID No. 3; (h4) The CpG sites shown at positions 191-192 from the 5' end of the DNA fragment represented by SEQ ID No. 3; (h5) The CpG sites shown at positions 208-209 from the 5' end of the DNA fragment represented by SEQ ID No. 3; (h6) The CpG sites shown at positions 221-222 from the 5' end of the DNA fragment represented by SEQ ID No. 3; (i1) The CpG site shown at positions 107-108 from the 5' end of the DNA fragment shown in SEQ ID No. 4; (i2) The CpG sites shown at positions 157-158 from the 5' end of the DNA fragment shown in SEQ ID No. 4; (i3) The CpG site shown at positions 186-187 from the 5' end of the DNA fragment shown in SEQ ID No. 4; (j1) The CpG sites at positions 58-59 from the 5' end of the DNA fragment shown in SEQ ID No. 5; (j2) The CpG sites shown at positions 123-124 from the 5' end of the DNA fragment shown in SEQ ID No. 5; (j3) The CpG site shown at positions 166-167 from the 5' end of the DNA fragment shown in SEQ ID No.

5.

3. The application according to claim 2, characterized in that, The kit also contains a medium that describes the mathematical model establishment method and / or usage method.

4. The application according to claim 3, characterized in that, The mathematical model is established as follows: (A1) Detect the methylation level of the SH3PXD2B gene fragment in n1 type A samples and n2 type B samples, respectively; (A2) Take the methylation level data of the SH3PXD2B gene fragment of all samples obtained in step (A1), and establish a mathematical model by binary logistic regression according to the classification method of type A and type B to determine the threshold for classification. The method of using the mathematical model includes the following steps: (B1) Detect the methylation level of the SH3PXD2B gene fragment in the sample to be tested; (B2) Substitute the methylation level data of the SH3PXD2B gene fragment of the sample to be tested obtained in step (B1) into the mathematical model to obtain the detection index; then compare the size of the detection index and the threshold, and determine whether the sample to be tested is type A or type B based on the comparison result; The type A samples and the type B samples are: Benign breast tumors and subtypes of malignant breast tumors, wherein the malignant breast tumor subtypes are ductal carcinoma in situ, invasive lobular carcinoma, invasive ductal carcinoma, or inflammatory breast cancer.

5. The application according to any one of claims 1 to 4, characterized in that, The substance used to detect the methylation level of the SH3PXD2B gene fragment contains a primer combination for amplifying 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; primer A1 is the single-stranded DNA represented by nucleotides 11-35 of SEQ ID No. 6 or SEQ ID No. 6; primer A2 is the 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; primer B1 is the single-stranded DNA represented by nucleotides 11-37 of SEQ ID No. 8 or SEQ ID No. 8; primer B2 is the single-stranded DNA represented by nucleotides 32-56 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; primer C1 is the single-stranded DNA represented by nucleotides 11-36 of SEQ ID No. 10 or SEQ ID No. 10; primer C2 is the single-stranded DNA represented by nucleotides 32-56 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; primer D1 is the single-stranded DNA represented by nucleotides 11-35 of SEQ ID No. 12 or SEQ ID No. 12; primer D2 is the single-stranded DNA represented by nucleotides 32-57 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; primer E1 is the single-stranded DNA represented by nucleotides 11-35 of SEQ ID No. 14 or SEQ ID No. 14; primer E2 is the single-stranded DNA represented by nucleotides 32-56 of SEQ ID No. 15 or SEQ ID No. 15.

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