A tumor marker associated with DNA epigenetic modification on chromosome 10 and its use

Abstract

The application is a divisional application of application No. CN202011608940.0. The present application provides a tumor marker related to DNA epigenetic modification located on chromosome 10 and its application. The tumor marker is located on human chromosome 10, and includes one or more CpG sites that can be subjected to methylation modification. The tumor marker includes the region located at chr10:50819227-50819589, taking human genome hg19 as the reference version. The present application provides a class of tumor markers related to DNA epigenetic modification. The marker shows significant hypermethylation state in tumor patients. The tumor marker can be used for clinical auxiliary screening, diagnosis, prognosis and the like of tumors, or can be used for designing diagnostic reagents and kits.

Description

[0001] This application is a divisional application of application number CN202011608940.0, filed on December 30, 2020, entitled "Tumor Markers and Their Applications". Technical Field

[0002] This invention relates to the field of biotechnology, and more particularly to a tumor marker located on chromosome 10 that is associated with DNA epigenetic modifications and its applications. Background Technology

[0003] The development and progression of tumors is a complex, multi-layered, and multifactorial dynamic process, involving the interaction of various factors such as the external environment, genetic variations, and epigenetic alterations. External environmental factors include physical, chemical, and biological carcinogens, as well as unhealthy lifestyle habits; genetic variations include gene mutations, copy number changes, and chromosomal misplacements; epigenetic alterations mainly include changes in DNA methylation, histone modifications, and non-coding RNA. In the process of tumor development and progression, these factors interact and work together, leading to the inactivation of a series of tumor suppressor genes and the activation of proto-oncogenes, ultimately resulting in tumor formation. Timely detection and diagnosis are of great significance in tumor treatment.

[0004] With a deeper understanding of tumors and advancements in science and technology, many novel tumor markers have been discovered and used in clinical diagnosis. Before 1980, tumor markers were mainly cellular secretions such as hormones, enzymes, and proteins. For example, carcinoembryonic antigen (CEA) and alpha-fetoprotein (AFP) could serve as markers for various tumors, including gastric and liver cancer. While these tumor markers are still used clinically, their sensitivity and accuracy are no longer sufficient to meet current clinical needs. Mutation-based markers are also increasingly common, such as mutations in the tumor suppressor p53, BRCA gene mutations, and microsatellite instability in colorectal cancer. However, these markers are not very effective in the early detection and diagnosis of tumors. Using DNA methylation-based markers can help diagnose tumors at an early stage of development.

[0005] Epigenetics is the study of heritable changes in gene function without alteration of the DNA sequence, ultimately leading to phenotypic changes. Epigenetics mainly includes biochemical processes such as DNA methylation, histone modification, and changes at the microRNA level. DNA methylation is a more thoroughly studied epigenetic mechanism with promising applications in clinical practice, including the diagnosis and treatment of tumors. DNA methylation refers to the process in which a methyl group is transferred to a specific base in vivo, catalyzed by DNA methyltransferase (DMT) using S-adenosylmethionine (SAM) as a methyl donor. In mammals, DNA methylation mainly occurs at the C of the 5'-CpG-3' base, generating 5-methylcytosine (5mC).

[0006] In normal cells, some CpGs are in a highly methylated / transcriptionally silent state. However, in tumor cells, these CpGs undergo extensive demethylation, leading to the transcription of repetitive sequences, activation of transposons, and resulting in high genomic instability and enhanced proto-oncogene transcription. Furthermore, some CpG islands that are hypomethylated in normal cells become hypermethylated in tumor cells, leading to transcriptional inactivation of genes, including DNA repair genes, cell cycle control genes, and anti-apoptotic genes. Genomic DNA, after bisulfite treatment, can be effectively identified for methylation at specific sites using PCR or sequencing. Utilizing these techniques, these abnormal DNA methylation states can be detected in the early stages of tumorigenesis.

[0007] Although the complete human genome sequence is known, its complexity means that it remains unclear which genes or regions are closely associated with diseases. Furthermore, the complexity of tumors themselves makes finding sensitive and specific tumor markers even more challenging. In this invention, the inventors utilize extensive data and optimized methods to identify more precise tumor markers, providing more avenues for tumor diagnosis. Summary of the Invention

[0008] This invention overcomes the shortcomings of the prior art and provides a class of DNA epigenetic modification-related tumor markers that exhibit a significant hypermethylation state in cancer patients.

[0009] In a first aspect, the present invention provides a tumor marker located on human chromosomes 1, 2, 3, 5, 7, 8, 10, 11 and 21, and comprising one or more CpG sites capable of methylation modification.

[0010] Preferably, the tumor marker is located on chromosome 10, and the tumor marker includes the region chr10:50819227-50819589 located on human genome Hg19 (coordinates starting from 0).

[0011] Preferably, the chr10:50819227-50819589 region is selected from at least one of the following: a) the base sequence shown in SEQ ID NO.1; b) the complementary sequence of the base sequence shown in SEQ ID NO.1; c) a nucleotide sequence that is at least 70% homologous to SEQ ID NO.1 or a complementary sequence of the nucleotide sequence thereof.

[0012] Preferably, the tumor markers include markers for one or more of breast cancer, cervical cancer, esophageal cancer, head and neck cancer, lung cancer, and pancreatic cancer.

[0013] Preferably, the tumor markers also include markers for one or more of the following: bladder cancer, bile duct cancer, colon cancer, glioblastoma, clear cell renal cell carcinoma, papillary renal cell carcinoma, liver cancer, pheochromocytoma and paraganglioma, prostate cancer, sarcoma, melanoma, gastric adenocarcinoma, thyroid cancer, thymic carcinoma, and endometrial cancer.

[0014] Preferably, the methylation modification includes 5-aldehyde methylation modification, 5-hydroxymethylation modification, 5-methylation modification, or 5-carboxymethylation modification.

[0015] Preferably, the tumor markers also include the following located on the human genome Hg19 (coordinates starting from 0): chr2:105459135-105459190, chr10:124902392-124902455, chr3:157812331-157812498, chr21:38378275-38378539, chr8:97170353-97170404, chr5:134880362-1348 One or more of the following regions: 80455, chr10:94835119-94835252, chr11:31826557-31826963, chr3:147114032-147114108, chr2:66809255-66809281, chr7:97361393-97361461, chr8:70984200-70984294, and chr1:6515341-6515409.

[0016] Preferably, each of the above regions is selected from at least one of the following groups: a) the base sequence shown in Table 1; b) the complementary sequence of the base sequence shown; c) a nucleotide sequence that is at least 70% homologous to the base sequence shown or a complementary sequence of the nucleotide sequence thereof.

[0017] The target sequences and their reverse complementary sequences for each of the above regions are shown in Table 1 below. In the table, bold italic font indicates CpG sites, and the numbers below the emphasis marks indicate the detection site number.

[0018] Table 1

[0019]

[0020]

[0021]

[0022] A second aspect of the present invention provides applications of the tumor markers described herein, wherein the applications are selected from one of the following: the application of the tumor markers in the preparation of screening reagents, prognostic reagents, detection reagents, or diagnostic reagents for tumors; the application of the tumor markers as drug targets for tumors; the application of the tumor markers in the preparation of drugs that inhibit tumor proliferation; and the application of reagents for detecting the methylation level of CpG sites of the tumor markers in the preparation of reagents for detecting tumors. The CpG sites are shown in Table 1 above.

[0023] Preferably, the tumors include: bladder cancer, cervical cancer, bile duct cancer, colon cancer, esophageal cancer, glioblastoma, head and neck cancer, clear cell renal cell carcinoma, papillary renal cell carcinoma, liver cancer, lung cancer (lung adenocarcinoma), pancreatic cancer, pheochromocytoma and paraganglioma, prostate cancer, sarcoma, melanoma, gastric adenocarcinoma, thyroid cancer, thymic carcinoma, endometrial cancer, and breast cancer; more preferably, the tumors include: breast cancer, cervical cancer, esophageal cancer, head and neck cancer, lung cancer, and pancreatic cancer. Specifically, tumors for example, whose antisense complementary sequence of SEQ ID NO.1 or its thereof can be used as markers include: bladder cancer, cervical cancer, bile duct cancer, colon cancer, esophageal cancer, glioblastoma, head and neck squamous cell carcinoma, clear cell renal cell carcinoma, papillary renal cell carcinoma, liver cancer, lung adenocarcinoma, pancreatic cancer, pheochromocytoma and paraganglioma, prostate cancer, sarcoma, melanoma, gastric adenocarcinoma, thyroid cancer, thymic carcinoma, and endometrial cancer.

[0024] Preferably, in the above applications, the detection reagent is a tumor marker detection kit, which includes primers or probes that specifically detect the tumor markers; and / or, the drug that inhibits tumor proliferation is an inhibitor of the tumor markers. More preferably, the primers or probes are primers or probes that specifically detect methylation of the CpG site of the tumor markers; and the inhibitor is a methylation inhibitor.

[0025] A third aspect of the invention provides a medicament for inhibiting tumor proliferation, said medicament comprising an inhibitor of the tumor markers described herein. Preferably, the inhibitor is a methylation inhibitor; more preferably, the inhibitor is an inhibitor that inhibits methylation of one or more CpG sites listed in Table 1 above. The medicament may also comprise a pharmaceutically acceptable carrier.

[0026] A fourth aspect of the present invention provides a method for detecting tumor markers, comprising the following steps: S1, obtaining a tissue sample to be tested; S2, extracting DNA from the tissue sample to be tested and obtaining the methylation value of the sample; S3, calculating the methylation status of each CpG site within the tumor marker sequence region or the average methylation status of the entire region.

[0027] Preferably, the method for obtaining the methylation value of the sample in step S2 includes sequencing, probes, antibodies, mass spectrometry, etc.

[0028] A fifth aspect of the present invention provides a tumor marker detection kit, comprising primers or probes for specifically detecting the tumor markers described herein. Preferably, the specific detection of the tumor marker includes specifically detecting the methylation of the CpG site of the tumor marker; wherein the methylation of the CpG site of the tumor marker is 5-methylation, including 5-aldehyde methylation, 5-hydroxymethylation, or 5-carboxymethylation.

[0029] This invention offers the following advantages over existing technologies: It provides a class of DNA epigenetic modification-related tumor markers that exhibit significant hypermethylation in cancer patients. These tumor markers can be used for clinical auxiliary screening, diagnosis, and prognosis of tumors, or for designing diagnostic reagents and kits, etc. Attached Figure Description

[0030] The accompanying drawings, which are included to provide a further understanding of the invention and form part of this invention, illustrate exemplary embodiments of the invention and are for illustrative purposes only, and do not constitute an undue limitation of the invention. In the drawings:

[0031] Figure 1 This is a graph showing the average methylation value of the target sequence in the chr2:105459135-105459190 region in the TCGA database in Example 2 of the present invention.

[0032] Figure 2 This is a graph showing the average methylation value of the target sequence in the chr3:157812331-157812498 region in the TCGA database in Example 2 of the present invention.

[0033] Figure 3 This is a graph showing the average methylation value of the target sequence in the chr21:38378275-38378539 region in the TCGA database in Example 2 of the present invention.

[0034] Figure 4 This is a graph showing the average methylation value of the target sequence in the chr8:97170353-97170404 region in the TCGA database in Example 2 of the present invention.

[0035] Figure 5 This is a graph showing the average methylation value of the target sequence in the chr5:134880362-134880455 region in the TCGA database in Example 2 of the present invention.

[0036] Figure 6 This is a graph showing the average methylation value of the target sequence in the chr11:31826557-31826963 region in the TCGA database in Example 2 of the present invention.

[0037] Figure 7 This is a graph showing the average methylation value of the target sequence (SEQ ID NO. 1) in the chr10:50819227-50819589 region in an embodiment 2 of the present invention in the TCGA database;

[0038] Figure 8This is a graph showing the average methylation value of the target sequence in the chr7:97361393-97361461 region in the TCGA database in Example 2 of the present invention.

[0039] Figure 9 This is a graph showing the average methylation value of the target sequence in the chr8:70984200-70984294 region in the TCGA database in Example 2 of the present invention.

[0040] Figure 10 This is a heatmap showing the average methylation values ​​of the 14 target sequences in different tumor cell lines in one embodiment 3 of the present invention.

[0041] Figure 11 The distribution of average methylation values ​​and ROC plot of the target sequence in the chr2:105459135-105459190 region in six types of tumors in Example 4 of the present invention;

[0042] Figure 12 The distribution of average methylation values ​​and ROC plot of the target sequence in the chr10:124902392-124902455 region in six types of tumors in Example 5 of the present invention;

[0043] Figure 13 The distribution of average methylation values ​​and ROC plot of the target sequence in the chr3:157812331-157812498 region in six types of tumors in Example 6 of the present invention;

[0044] Figure 14 The distribution of average methylation values ​​and ROC plot of the target sequence in the chr21:38378275-38378539 region in six types of tumors in Example 7 of the present invention;

[0045] Figure 15 The distribution of average methylation values ​​and ROC plot of the target sequence in the chr8:97170353-97170404 region in six types of tumors in Example 8 of the present invention;

[0046] Figure 16 The distribution of average methylation values ​​and ROC plot of the target sequence in the chr5:134880362-134880455 region in five types of tumors in Example 9 of the present invention;

[0047] Figure 17 The distribution of average methylation values ​​and ROC plot of the target sequence in the chr10:94835119-94835252 region in five types of tumors in an embodiment 10 of the present invention;

[0048] Figure 18The distribution of average methylation values ​​and ROC plot of the target sequence in the chr11:31826557-31826963 region in six types of tumors in an embodiment 11 of the present invention;

[0049] Figure 19 The distribution of average methylation values ​​and ROC plot of the target sequence in the chr3:147114032-147114108 region in six types of tumors in an embodiment 12 of the present invention;

[0050] Figure 20 The average methylation value distribution and ROC plot of the target sequence (SEQ ID NO. 1) in the chr10:50819227-50819589 region in six tumors in an embodiment 13 of the present invention;

[0051] Figure 21 The distribution of average methylation values ​​and ROC plot of the target sequence in the chr2:66809255-66809281 region in six types of tumors in an embodiment 14 of the present invention;

[0052] Figure 22 The distribution of average methylation values ​​and ROC plot of the target sequence in the chr7:97361393-97361461 region in six types of tumors in an embodiment 15 of the present invention;

[0053] Figure 23 The average methylation value distribution and ROC plot of the target sequence in the chr8:70984200-70984294 region in six types of tumors in an embodiment 16 of the present invention;

[0054] Figure 24 The average methylation value distribution and ROC plot of the target sequence in the chr1:6515341-6515409 region in six types of tumors in Example 17 of the present invention. Detailed Implementation

[0055] The specific embodiments of the present invention will be further described below with reference to the accompanying drawings and examples. The following examples are only used to more clearly illustrate the technical solutions of the present invention and should not be construed as limiting the scope of protection of the present invention. Experimental methods in the following examples that do not specify specific conditions were performed according to conventional methods and conditions in the art, or according to the product manual.

[0056] The specific sequence information of the target sequences verified in the following embodiments is shown in Table 1 above.

[0057] Example 1 - Detection of Methylation Levels

[0058] Methylation detection methods such as RRBS (Reduced Representation Bisulfite Sequencing) and WGBS (Whole Genome Bisulfite Sequencing) were employed, with the main steps as follows: Sample acquisition: Tumor cell lines were selected, or cancerous tissue and adjacent normal tissue were obtained from clinical settings; DNA was extracted from the samples using a DNA extraction kit; the extracted DNA was subjected to whole-genome sequencing; after sequencing, the sequences were aligned to the target sequences, and the methylation status of each CpG site within the target sequence region was calculated. The average methylation value of the sequenced CpG sites in the target sequence was calculated as the average methylation value of this target sequence in this sample. Target sequence information is detailed in Table 1 above.

[0059] Example 2 - Validation of target sequences in 14 regions using methylation chip data from the TCGA database.

[0060] 2.1 Target Sequences and Database

[0061] The target sequences for the 14 validated regions are shown in Table 1. Using the TCGA database, DNA methylation microarray data of cancer tissues and adjacent normal tissues from over 20 tumor types were collected. These tumor types included: bladder cancer (BLCA), cervical cancer (CESC), cholangiocarcinoma (CHOL), colon cancer (COADREAD), esophageal cancer (ESCA), glioblastoma (GBM), head and neck squamous cell carcinoma (HNSC), clear cell renal cell carcinoma (KIRC), papillary renal cell carcinoma (KIRP), liver cancer (LIHC), lung adenocarcinoma (LUNG), pancreatic cancer (PAAD), pheochromocytoma and paraganglioma (PCPG), prostate cancer (PRAD), sarcoma (SARC), melanoma (SKCM), gastric adenocarcinoma (STAD), thyroid cancer (THCA), thymic carcinoma (THYM), and endometrial cancer (UCEC).

[0062] 2.2 Obtain the number of probes contained in each target sequence. The results are shown in Table 3.

[0063] Table 3 Number of probes contained in each target sequence

[0064] chr2:105459135-105459190 1 chr11:31826557-31826963 1 chr10:124902392-124902455 0 chr3:147114032-147114108 0 chr3:157812331-157812498 1 chr10:50819227-50819589 1 chr21:38378275-38378539 2 chr2:66809255-66809281 0 chr8:97170353-97170404 1 chr7:97361393-97361461 1 chr5:134880362-134880455 1 chr8:70984200-70984294 2 chr10:94835119-94835252 0 chr1:6515341-6515409 0

[0065] 2.3. Calculate the average methylation value of all probes within this target sequence in all cancer samples and normal tissue samples, following the method in Example 1. The results are as follows: Figures 1-9 As shown. The sample naming convention is: Cancer name_C or N (number), where C represents tumor tissue, N represents normal tissue, and the number represents the sample size.

[0066] Figure 1 The average methylation value of the target sequence in the chr2:105459135-105459190 region in the TCGA database shows that the average methylation value of the above target sequence in 17 types of cancer, including bladder cancer, cervical cancer, bile duct cancer, colon cancer, esophageal cancer, glioblastoma, head and neck squamous cell carcinoma, clear cell renal cell carcinoma, papillary renal cell carcinoma, lung adenocarcinoma, pheochromocytoma and paraganglioma, prostate cancer, melanoma, gastric adenocarcinoma, thyroid cancer, thymic carcinoma, and endometrial cancer, is significantly higher than that of normal samples.

[0067] Figure 2 The average methylation value of the target sequence in the chr3:157812331-157812498 region in the TCGA database shows that the average methylation value of the above target sequence in 20 types of cancer, including bladder cancer, cervical cancer, cholangiocarcinoma, colon cancer, esophageal cancer, glioblastoma, head and neck squamous cell carcinoma, clear cell renal cell carcinoma, papillary renal cell carcinoma, liver cancer, lung adenocarcinoma, pancreatic cancer, pheochromocytoma and paraganglioma, prostate cancer, sarcoma, melanoma, gastric adenocarcinoma, thyroid cancer, thymic cancer, and endometrial cancer, is higher than that of normal samples.

[0068] Figure 3 The average methylation values ​​of the target sequences in the chr21:38378275-38378539 region in the TCGA database show that the average methylation values ​​of these target sequences in 19 types of cancer—bladder cancer, cervical cancer, cholangiocarcinoma, colon cancer, esophageal cancer, glioblastoma, head and neck squamous cell carcinoma, clear cell renal cell carcinoma, papillary renal cell carcinoma, liver cancer, lung adenocarcinoma, pancreatic cancer, prostate cancer, sarcoma, melanoma, gastric adenocarcinoma, thyroid cancer, thymic carcinoma, and endometrial cancer—are significantly higher than the average methylation values ​​of normal samples. The average methylation values ​​of these target sequences in pheochromocytoma and paraganglioma are almost indistinguishable from the average methylation values ​​of normal samples.

[0069] Figure 4 The average methylation values ​​of the target sequences in the chr8:97170353-97170404 region in the TCGA database show that the average methylation values ​​of these target sequences in 19 types of cancer—bladder cancer, cervical cancer, cholangiocarcinoma, colon cancer, esophageal cancer, glioblastoma, head and neck squamous cell carcinoma, clear cell renal cell carcinoma, papillary renal cell carcinoma, liver cancer, lung adenocarcinoma, pancreatic cancer, prostate cancer, sarcoma, melanoma, gastric adenocarcinoma, thyroid cancer, thymic carcinoma, and endometrial cancer—are significantly higher than the average methylation values ​​of normal samples. The average methylation values ​​of these target sequences in pheochromocytoma and paraganglioma are lower than the average methylation values ​​of normal samples.

[0070] Figure 5The average methylation values ​​of the target sequences in the chr5:134880362-134880455 region in the TCGA database show that the average methylation values ​​of these target sequences in 18 types of cancer—bladder cancer, cervical cancer, cholangiocarcinoma, colon cancer, esophageal cancer, head and neck squamous cell carcinoma, clear cell renal cell carcinoma, papillary renal cell carcinoma, liver cancer, lung adenocarcinoma, pancreatic cancer, prostate cancer, sarcoma, melanoma, gastric adenocarcinoma, thyroid cancer, thymic carcinoma, and endometrial cancer—are significantly higher than the average methylation values ​​of normal samples. The average methylation values ​​of these target sequences in glioblastoma, pheochromocytoma, and paraganglioma are lower than the average methylation values ​​of normal samples.

[0071] Figure 6 The average methylation values ​​of the target sequences in the chr11:31826557-31826963 region in the TCGA database show that the average methylation values ​​of these target sequences in 19 types of cancer—bladder cancer, cervical cancer, cholangiocarcinoma, colon cancer, esophageal cancer, glioblastoma, head and neck squamous cell carcinoma, clear cell renal cell carcinoma, papillary renal cell carcinoma, liver cancer, lung adenocarcinoma, pancreatic cancer, prostate cancer, sarcoma, melanoma, gastric adenocarcinoma, thyroid cancer, thymic carcinoma, and endometrial cancer—are significantly higher than the average methylation values ​​of normal samples. The average methylation values ​​of these target sequences in pheochromocytoma and paraganglioma are lower than the average methylation values ​​of normal samples.

[0072] Figure 7 The average methylation value of the target sequence (SEQ ID NO.1) in the chr10:50819227-50819589 region in the TCGA database shows that the average methylation value of the above target sequence in 20 types of cancer, including bladder cancer, cervical cancer, cholangiocarcinoma, colon cancer, esophageal cancer, glioblastoma, head and neck squamous cell carcinoma, clear cell renal cell carcinoma, papillary renal cell carcinoma, liver cancer, lung adenocarcinoma, pancreatic cancer, pheochromocytoma and paraganglioma, prostate cancer, sarcoma, melanoma, gastric adenocarcinoma, thyroid cancer, thymic cancer, and endometrial cancer, is higher than that of normal samples.

[0073] Figure 8 The average methylation value of the target sequence in the chr7:97361393-97361461 region in the TCGA database shows that the average methylation value of the above target sequence in 20 types of cancer, including bladder cancer, cervical cancer, cholangiocarcinoma, colon cancer, esophageal cancer, glioblastoma, head and neck squamous cell carcinoma, clear cell renal cell carcinoma, papillary renal cell carcinoma, liver cancer, lung adenocarcinoma, pancreatic cancer, pheochromocytoma and paraganglioma, prostate cancer, sarcoma, melanoma, gastric adenocarcinoma, thyroid cancer, thymic cancer, and endometrial cancer, is higher than that of normal samples.

[0074] Figure 9The average methylation value of the target sequence in the chr8:70984200-70984294 region in the TCGA database shows that the average methylation value of the above target sequence in 20 types of cancer, including bladder cancer, cervical cancer, cholangiocarcinoma, colon cancer, esophageal cancer, glioblastoma, head and neck squamous cell carcinoma, clear cell renal cell carcinoma, papillary renal cell carcinoma, liver cancer, lung adenocarcinoma, pancreatic cancer, pheochromocytoma and paraganglioma, prostate cancer, sarcoma, melanoma, gastric adenocarcinoma, thyroid cancer, thymic cancer, and endometrial cancer, is higher than that of normal samples.

[0075] It can be seen that, in the vast majority of the tumor types mentioned above, the average methylation value of the target sequences verified above is higher in tumor samples than in normal tissues.

[0076] Methylation levels of target sequences in tumor cell lines in Examples 3-14

[0077] Eleven tumor cell lines were collected: cholangiocarcinoma, breast cancer, colorectal cancer, gallbladder cancer, renal cancer, leukemia, liver cancer, lung cancer, pancreatic cancer, prostate cancer, and gastric cancer. The average methylation values ​​of 14 target sequences in each sample were obtained using RRBS methylation sequencing technology according to the method in Example 1. The results are as follows... Figure 10 In the figure, white indicates no detection or substandard sequencing quality, and darker colors indicate higher average methylation values. It can be seen that the methylation of the target sequences in the regions chr2:105459135-105459190, chr10:124902392-124902455, chr3:157812331-157812498, chr21:38378275-38378539, chr8:97170353-97170404, chr11:31826557-31826963, chr3:147114032-147114108, chr7:97361393-97361461, and chr8:70984200-70984294 can be detected in all 11 tumor cell lines, and the average methylation values ​​in all 11 tumor cell lines are very high. Methylation of the target sequences in the regions chr5:134880362-134880455, chr10:94835119-94835252, chr10:50819227-50819589 (SEQ ID NO.1), chr2:66809255-66809281, and chr1:6515341-6515409 was detected only in some tumor cell lines.

[0078] Example 4 - Application of the target sequence in the chr2:105459135-105459190 region in clinical testing

[0079] Samples: Six types of tumor tissue and adjacent normal tissue samples, namely breast cancer (5 cancer tissue samples, 5 adjacent normal tissue samples), cervical cancer (4 cancer tissue samples, 5 adjacent normal tissue samples), esophageal cancer (3 cancer tissue samples, 1 adjacent normal tissue sample), head and neck cancer (4 cancer tissue samples, 5 adjacent normal tissue samples), lung cancer (5 cancer tissue samples, 5 adjacent normal tissue samples), and pancreatic cancer (5 cancer tissue samples, 5 adjacent normal tissue samples).

[0080] According to the method in Example 1, the average methylation value of the target sequence in the chr2:105459135-105459190 region was obtained in 26 tumor tissues and 26 adjacent normal tissues using RRBS methylation sequencing technology. The results are as follows: Figure 11 As shown in the figure, there are six groups of images: A, B, C, D, E, and F. Each group contains two images. The left image is a box plot showing the distribution of the average methylation value of the target sequence in tumor samples and normal cancer samples (controls), which shows the difference in methylation of the target sequence between tumor and normal samples. The right image is the ROC curve of the detection, which shows the specificity of the difference results. A: Breast cancer sample and control; B: Cervical cancer sample and control; C: Esophageal cancer sample and control; D: Head and neck cancer sample and control; E: Lung cancer sample and control; F: Pancreatic cancer sample and control. It can be seen that in all six types of tumors, the average methylation value of the target sequence in the chr2:105459135-105459190 region in tumor samples is higher than that in adjacent normal tissue. Based on the average methylation value of the target sequence in the chr2:105459135-105459190 region, tumor samples and normal cancer tissues can be accurately distinguished.

[0081] Example 5 - Application of the target sequence in the chr10:124902392-124902455 region in clinical testing

[0082] Samples: Six types of tumor tissue and adjacent normal tissue samples, namely breast cancer (4 cancer tissues, 5 adjacent normal tissues), cervical cancer (4 cancer tissues, 5 adjacent normal tissues), esophageal cancer (3 cancer tissues, 1 adjacent normal tissue), head and neck cancer (4 cancer tissues, 5 adjacent normal tissues), lung cancer (5 cancer tissues, 5 adjacent normal tissues), and pancreatic cancer (5 cancer tissues, 5 adjacent normal tissues).

[0083] According to the method in Example 1, the average methylation value of the target sequence in the chr10:124902392-124902455 region was obtained in 25 tumor tissues and 26 adjacent normal tissues using RRBS methylation sequencing technology. The results are as follows: Figure 12As shown in the figure, there are six groups of images: A, B, C, D, E, and F. Each group contains two images. The left image is a box plot showing the distribution of the average methylation value of the target sequence in tumor samples and normal cancer samples (controls), which shows the difference in methylation of the target sequence between tumor and normal samples. The right image is the ROC curve of the detection, which shows the specificity of the difference results. A: Breast cancer sample and control; B: Cervical cancer sample and control; C: Esophageal cancer sample and control; D: Head and neck cancer sample and control; E: Lung cancer sample and control; F: Pancreatic cancer sample and control. It can be seen that in all six types of tumors, the average methylation value of the target sequence in the chr10:124902392-124902455 region in tumor samples is higher than that in adjacent normal tissue. Based on the average methylation value of the target sequence in the chr10:124902392-124902455 region, tumor samples and normal cancer tissues can be accurately distinguished.

[0084] Example 6 - Application of the target sequence in the chr3:157812331-157812498 region in clinical testing

[0085] Samples: Six types of tumor tissue and adjacent normal tissue samples, namely breast cancer (5 cancer tissue samples, 5 adjacent normal tissue samples), cervical cancer (5 cancer tissue samples, 5 adjacent normal tissue samples), esophageal cancer (5 cancer tissue samples, 4 adjacent normal tissue samples), head and neck cancer (5 cancer tissue samples, 5 adjacent normal tissue samples), lung cancer (4 cancer tissue samples, 2 adjacent normal tissue samples), and pancreatic cancer (2 cancer tissue samples, 2 adjacent normal tissue samples).

[0086] According to the method in Example 1, the average methylation value of the target sequence in the chr3:157812331-157812498 region was obtained in 26 tumor tissues and 23 adjacent normal tissues using RRBS methylation sequencing technology. The results are as follows: Figure 13As shown in the figure. The figure contains six groups of images: A, B, C, D, E, and F. Each group contains two images. The left image is a box plot showing the distribution of average methylation values ​​on the target sequence in tumor samples and normal cancer samples (controls), illustrating the difference in methylation of the target sequence between tumor and normal samples. The right image is the ROC curve, demonstrating the specificity of the differential results. Specifically, A: breast cancer sample and control; B: cervical cancer sample and control; C: esophageal cancer sample and control; D: head and neck cancer sample and control; E: lung cancer sample and control; F: pancreatic cancer sample and control. It is evident that, among the five types of tumors, the average methylation value of the target sequence in the chr3:157812331-157812498 region in tumor samples was higher than that in adjacent normal tissues. In esophageal cancer, the average methylation value of most tumor samples was higher than that of adjacent normal tissues. Based on the average methylation value of the target sequence in the chr3:157812331-157812498 region, most tumor samples can be accurately distinguished from cancerous normal tissues.

[0087] Example 7 - Application of the target sequence in the chr21:38378275-38378539 region in clinical testing

[0088] Samples: Six types of tumor tissue and adjacent normal tissue samples, namely breast cancer (4 cancer tissues, 4 adjacent normal tissues), cervical cancer (5 cancer tissues, 2 adjacent normal tissues), esophageal cancer (5 cancer tissues, 4 adjacent normal tissues), head and neck cancer (2 cancer tissues, 4 adjacent normal tissues), lung cancer (5 cancer tissues, 5 adjacent normal tissues), and pancreatic cancer (5 cancer tissues, 5 adjacent normal tissues).

[0089] According to the method in Example 1, the average methylation value of the target sequence in the chr21:38378275-38378539 region was obtained in 26 tumor tissues and 24 adjacent normal tissues using RRBS methylation sequencing technology. The results are as follows: Figure 14As shown in the figure, there are six groups of images: A, B, C, D, E, and F. Each group contains two images. The left image is a box plot showing the distribution of the average methylation value of the target sequence in tumor samples and normal cancer samples (controls), which shows the difference in methylation of the target sequence between tumor and normal samples. The right image is a ROC curve, which shows the specificity of the difference results. A: Breast cancer sample and control; B: Cervical cancer sample and control; C: Esophageal cancer sample and control; D: Head and neck cancer sample and control; E: Lung cancer sample and control; F: Pancreatic cancer sample and control. It can be seen that the average methylation value of the target sequence in the chr21:38378275-38378539 region is higher than that of adjacent normal tissue in breast cancer, head and neck cancer, and esophageal cancer samples. In esophageal cancer, cervical cancer, and lung cancer samples, the average methylation value of the target sequence in the chr21:38378275-38378539 region was mostly higher than that of adjacent normal tissue, and the mean of its average methylation value was also higher than that of adjacent normal tissue. Based on the average methylation value of the target sequence in the chr21:38378275-38378539 region, most tumor samples can be distinguished from cancerous normal tissue.

[0090] Example 8 - Application of regional target sequences in clinical testing (chr8:97170353-97170404)

[0091] Samples: Six types of tumor tissue and adjacent normal tissue samples, namely breast cancer (5 cancer tissues, 5 adjacent normal tissues), cervical cancer (3 cancer tissues, 4 adjacent normal tissues), esophageal cancer (4 cancer tissues, 3 adjacent normal tissues), head and neck cancer (4 cancer tissues, 5 adjacent normal tissues), lung cancer (2 cancer tissues, 2 adjacent normal tissues), and pancreatic cancer (3 cancer tissues, 2 adjacent normal tissues).

[0092] According to the method in Example 1, the average methylation value of the target sequence in the chr8:97170353-97170404 region was obtained in 21 tumor tissues and 21 adjacent normal tissues using RRBS methylation sequencing technology. The results are as follows: Figure 15As shown in the figure, there are six groups of images: A, B, C, D, E, and F. Each group contains two images. The left image is a box plot showing the distribution of the average methylation value of the target sequence in tumor samples and normal cancer samples (controls), which shows the difference in methylation of the target sequence between tumor and normal samples. The right image is the ROC curve of the detection, which shows the specificity of the difference results. A: Breast cancer sample and control; B: Cervical cancer sample and control; C: Esophageal cancer sample and control; D: Head and neck cancer sample and control; E: Lung cancer sample and control; F: Pancreatic cancer sample and control. It can be seen that the average methylation value of the target sequence in the chr8:97170353-97170404 region is higher than the average methylation value of adjacent normal tissue in breast cancer, cervical cancer, and lung cancer samples. In esophageal cancer, head and neck cancer, and lung cancer samples, the average methylation value of the target sequence in the chr8:97170353-97170404 region was mostly higher than that of adjacent normal tissue, and the mean of its average methylation value was also higher than that of adjacent normal tissue. Based on the average methylation value of the target sequence in the chr8:97170353-97170404 region, most tumor samples can be distinguished from cancerous normal tissue.

[0093] Example 9 - Application of the target sequence in the chr5:134880362-134880455 region in clinical testing

[0094] Samples: Five types of tumor tissue and adjacent normal tissue samples, namely breast cancer (5 cancer tissue samples and 5 adjacent normal tissue samples), esophageal cancer (2 cancer tissue samples and 1 adjacent normal tissue sample), head and neck cancer (5 cancer tissue samples and 5 adjacent normal tissue samples), lung cancer (3 cancer tissue samples and 1 adjacent normal tissue sample) and pancreatic cancer (2 cancer tissue samples and 1 adjacent normal tissue sample).

[0095] According to the method in Example 1, the average methylation value of the target sequence in the chr5:134880362-134880455 region was obtained in 17 tumor tissues and 13 adjacent normal tissues using RRBS methylation sequencing technology. The results are as follows: Figure 16As shown in the figure, there are five groups of images: A, B, C, D, and E. Each group contains two images. The left image is a box plot showing the distribution of average methylation values ​​of the target sequence in tumor samples and normal cancer samples (controls), illustrating the difference in methylation of the target sequence between tumor and normal samples. The right image is the ROC curve, showing the specificity of the difference results. A: Breast cancer sample and control; B: Esophageal cancer sample and control; C: Head and neck cancer sample and control; D: Lung cancer sample and control; E: Pancreatic cancer sample and control. It can be seen that in all five types of tumors, the average methylation value of the target sequence in the chr5:134880362-134880455 region in tumor samples is higher than that in adjacent normal tissue. Based on the average methylation value of the target sequence in the chr5:134880362-134880455 region, tumor samples and normal cancer tissues can be accurately distinguished.

[0096] Example 10 - Application of regional target sequences in clinical testing (chr10:94835119-94835252)

[0097] Samples: Five types of tumor tissue and adjacent normal tissue samples, namely breast cancer (5 cancer tissue samples and 4 adjacent normal tissue samples), cervical cancer (2 cancer tissue samples and 1 adjacent normal tissue sample), head and neck cancer (2 cancer tissue samples and 2 adjacent normal tissue samples), lung cancer (3 cancer tissue samples and 3 adjacent normal tissue samples), and pancreatic cancer (4 cancer tissue samples and 5 adjacent normal tissue samples).

[0098] According to the method in Example 1, the average methylation value of the target sequence in the chr10:94835119-94835252 region was obtained in 16 tumor tissues and 15 adjacent normal tissues using RRBS methylation sequencing technology. The results are as follows: Figure 17 As shown in the figure, there are five groups of images: A, B, C, D, and E. Each group contains two images. The left image is a box plot showing the distribution of average methylation values ​​of the target sequence in tumor samples and normal cancer samples (controls), illustrating the difference in methylation between tumor and normal samples. The right image is the ROC curve, demonstrating the specificity of the results. A: Breast cancer sample and control; B: Cervical cancer sample and control; C: Head and neck cancer sample and control; D: Lung cancer sample and control; E: Pancreatic cancer sample and control. It can be seen that in all five types of tumors, the average methylation value of the target sequence in the chr10:94835119-94835252 region is higher in tumor samples than in adjacent normal tissue. Based on the average methylation value of the target sequence in the chr10:94835119-94835252 region, tumor samples and normal cancer tissues can be accurately distinguished.

[0099] Example 11 - Application of target sequences in the chr11:31826557-31826963 region in clinical testing

[0100] Samples: Six types of tumor tissue and adjacent normal tissue samples, namely breast cancer (5 cancer tissues, 5 adjacent normal tissues), cervical cancer (4 cancer tissues, 5 adjacent normal tissues), esophageal cancer (4 cancer tissues, 5 adjacent normal tissues), head and neck cancer (4 cancer tissues, 5 adjacent normal tissues), lung cancer (5 cancer tissues, 5 adjacent normal tissues), and pancreatic cancer (4 cancer tissues, 5 adjacent normal tissues).

[0101] According to the method in Example 1, the average methylation value of the target sequence in the chr11:31826557-31826963 region was obtained in 26 tumor tissues and 30 adjacent normal tissues using RRBS methylation sequencing technology. The results are as follows: Figure 18 As shown in the figure, there are six groups of images: A, B, C, D, E, and F. Each group contains two images. The left image is a box plot showing the distribution of the average methylation value of the target sequence in tumor samples and normal cancer samples (controls), which shows the difference in methylation of the target sequence between tumor and normal samples. The right image is the ROC curve of the detection, which shows the specificity of the difference results. A: Breast cancer sample and control; B: Cervical cancer sample and control; C: Esophageal cancer sample and control; D: Head and neck cancer sample and control; E: Lung cancer sample and control; F: Pancreatic cancer sample and control. It can be seen that the average methylation value of the target sequence in the chr11:31826557-31826963 region is higher than the average methylation value of adjacent normal tissue in breast cancer, cervical cancer, lung cancer, head and neck cancer, and pancreatic cancer samples. In esophageal cancer samples, the average methylation value of the target sequence in the chr11:31826557-31826963 region was mostly higher than that of adjacent normal tissue, and the mean of its average methylation value was also higher than that of adjacent normal tissue. Based on the average methylation value of the target sequence in the chr11:31826557-31826963 region, most tumor samples can be distinguished from cancerous normal tissue.

[0102] Example 12 - Application of the target sequence in the chr3:147114032-147114108 region in clinical testing

[0103] Samples: Six types of tumor tissue and adjacent normal tissue samples, namely breast cancer (5 cancer tissues, 5 adjacent normal tissues), cervical cancer (4 cancer tissues, 5 adjacent normal tissues), esophageal cancer (5 cancer tissues, 4 adjacent normal tissues), head and neck cancer (4 cancer tissues, 4 adjacent normal tissues), lung cancer (5 cancer tissues, 4 adjacent normal tissues), and pancreatic cancer (5 cancer tissues, 5 adjacent normal tissues).

[0104] According to the method in Example 1, the average methylation value of the target sequence in the chr3:147114032-147114108 region was obtained in 28 tumor tissues and 27 adjacent normal tissues using RRBS methylation sequencing technology. The results are as follows: Figure 19 As shown in the figure, there are six groups of images: A, B, C, D, E, and F. Each group contains two images. The left image is a box plot showing the distribution of the average methylation value of the target sequence in tumor samples and normal cancer samples (controls), which shows the difference in methylation of the target sequence between tumor and normal samples. The right image is the ROC curve of the detection, which shows the specificity of the difference results. A: Breast cancer sample and control; B: Cervical cancer sample and control; C: Esophageal cancer sample and control; D: Head and neck cancer sample and control; E: Lung cancer sample and control; F: Pancreatic cancer sample and control. It can be seen that the average methylation value of the target sequence in the chr3:147114032-147114108 region is higher than the average methylation value of adjacent normal tissue in breast cancer, cervical cancer, lung cancer, head and neck cancer, and pancreatic cancer samples. In esophageal cancer samples, the average methylation value of the target sequence in the chr3:147114032-147114108 region was mostly higher than that of adjacent normal tissue, and the mean of its average methylation value was also higher than that of adjacent normal tissue. Based on the average methylation value of the target sequence in the chr3:147114032-147114108 region, most tumor samples can be distinguished from cancerous normal tissue.

[0105] Example 13: Application of the target sequence (SEQ ID No. 1) of chr10:50819227-50819589 in clinical testing

[0106] Samples: Six types of tumor tissue and adjacent normal tissue samples, namely breast cancer (5 cancer tissues, 5 adjacent normal tissues), cervical cancer (4 cancer tissues, 3 adjacent normal tissues), esophageal cancer (4 cancer tissues, 5 adjacent normal tissues), head and neck cancer (4 cancer tissues, 5 adjacent normal tissues), lung cancer (4 cancer tissues, 3 adjacent normal tissues) and pancreatic cancer (4 cancer tissues, 5 adjacent normal tissues).

[0107] According to the method in Example 1, the average methylation value of the target sequence in the chr10:50819227-50819589 region was obtained in 25 tumor tissues and 26 adjacent normal tissues using RRBS methylation sequencing technology. The results are as follows: Figure 20 As shown in the figure, there are six groups of images: A, B, C, D, E, and F. Each group contains two images. The left image is a box plot showing the distribution of the average methylation value of the target sequence in tumor samples and normal cancer samples (controls), which shows the difference in methylation of the target sequence between tumor and normal samples. The right image is the ROC curve of the detection, which shows the specificity of the difference results. A: Breast cancer sample and control; B: Cervical cancer sample and control; C: Esophageal cancer sample and control; D: Head and neck cancer sample and control; E: Lung cancer sample and control; F: Pancreatic cancer sample and control. It can be seen that the average methylation value of the target sequence in the chr10:50819227-50819589 region is higher than the average methylation value of adjacent normal tissue in breast cancer, cervical cancer, lung cancer, head and neck cancer, and pancreatic cancer samples. In esophageal cancer samples, the average methylation value of the target sequence in the chr10:50819227-50819589 region was mostly higher than that of adjacent normal tissue, and the mean of its average methylation value was also higher than that of adjacent normal tissue. Based on the average methylation value of the target sequence in the chr10:50819227-50819589 region, most tumor samples can be distinguished from cancerous normal tissue.

[0108] Example 14 - Application of the target sequence in the chr2:66809255-66809281 region in clinical testing

[0109] Samples: Six types of tumor tissue and adjacent normal tissue samples, namely breast cancer (5 cancer tissues, 5 adjacent normal tissues), cervical cancer (2 cancer tissues, 5 adjacent normal tissues), esophageal cancer (1 cancer tissue, 3 adjacent normal tissues), head and neck cancer (5 cancer tissues, 5 adjacent normal tissues), lung cancer (4 cancer tissues, 4 adjacent normal tissues), and pancreatic cancer (3 cancer tissues, 3 adjacent normal tissues).

[0110] According to the method in Example 1, the average methylation value of the target sequence in the chr2:66809255-66809281 region was obtained in 20 tumor tissues and 25 adjacent normal tissues using RRBS methylation sequencing technology. The results are as follows: Figure 21As shown in the figure, there are six groups of images: A, B, C, D, E, and F. Each group contains two images. The left image is a box plot showing the distribution of the average methylation value of the target sequence in tumor samples and normal cancer samples (controls), which shows the difference in methylation of the target sequence between tumor and normal samples. The right image is the ROC curve of the detection, which shows the specificity of the difference results. A: Breast cancer sample and control; B: Cervical cancer sample and control; C: Esophageal cancer sample and control; D: Head and neck cancer sample and control; E: Lung cancer sample and control; F: Pancreatic cancer sample and control. It can be seen that the average methylation value of the target sequence in the chr2:66809255-66809281 region is higher than the average methylation value of adjacent normal tissue in breast cancer, cervical cancer, lung cancer, esophageal cancer, and pancreatic cancer samples. In head and neck cancer samples, the average methylation value of the target sequence in the chr2:66809255-66809281 region was mostly higher than that of adjacent normal tissue, and the mean of its average methylation value was also higher than that of adjacent normal tissue. Based on the average methylation value of the target sequence in the chr2:66809255-66809281 region, most tumor samples can be distinguished from cancerous normal tissue.

[0111] Example 15 - Application of regional target sequences in clinical testing (chr7:97361393-97361461)

[0112] Samples: Six types of tumor tissue and adjacent normal tissue samples, namely breast cancer (5 cancer tissue samples and 5 adjacent normal tissue samples), cervical cancer (3 cancer tissue samples and 5 adjacent normal tissue samples), esophageal cancer (4 cancer tissue samples and 3 adjacent normal tissue samples), head and neck cancer (5 cancer tissue samples and 5 adjacent normal tissue samples), lung cancer (5 cancer tissue samples and 5 adjacent normal tissue samples), and pancreatic cancer (5 cancer tissue samples and 5 adjacent normal tissue samples).

[0113] According to the method in Example 1, the average methylation value of the target sequence in the chr7:97361393-97361461 region was obtained in 27 tumor tissues and 28 adjacent normal tissues using RRBS methylation sequencing technology. The results are as follows: Figure 22As shown in the figure, there are six groups of images: A, B, C, D, E, and F. Each group contains two images. The left image is a box plot showing the distribution of the average methylation value of the target sequence in tumor samples and normal cancer samples (controls), which shows the difference in methylation of the target sequence between tumor and normal samples. The right image is the ROC curve of the detection, which shows the specificity of the difference results. A: Breast cancer sample and control; B: Cervical cancer sample and control; C: Esophageal cancer sample and control; D: Head and neck cancer sample and control; E: Lung cancer sample and control; F: Pancreatic cancer sample and control. It can be seen that the average methylation value of the target sequence in the chr7:97361393-97361461 region is higher than the average methylation value of adjacent normal tissue in breast cancer, cervical cancer, head and neck cancer, esophageal cancer, and pancreatic cancer samples. In lung cancer samples, the average methylation value of the target sequence in the chr7:97361393-97361461 region was mostly higher than that of adjacent normal tissue, and the mean of its average methylation value was also higher than that of adjacent normal tissue. Based on the average methylation value of the target sequence in the chr7:97361393-97361461 region, most tumor samples can be distinguished from cancerous normal tissue.

[0114] Example 16 - Application of the target sequence in the chr8:70984200-70984294 region in clinical testing

[0115] Samples: Six types of tumor tissue and adjacent normal tissue samples, namely breast cancer (5 cancer tissue samples and 5 adjacent normal tissue samples), cervical cancer (1 cancer tissue sample and 5 adjacent normal tissue samples), esophageal cancer (2 cancer tissue samples and 1 adjacent normal tissue sample), head and neck cancer (5 cancer tissue samples and 5 adjacent normal tissue samples), lung cancer (4 cancer tissue samples and 5 adjacent normal tissue samples), and pancreatic cancer (5 cancer tissue samples and 5 adjacent normal tissue samples).

[0116] According to the method in Example 1, the average methylation value of the target sequence in the chr8:70984200-70984294 region was obtained in 22 tumor tissues and 26 adjacent normal tissues using RRBS methylation sequencing technology. The results are as follows: Figure 23As shown in the figure, there are six groups of images: A, B, C, D, E, and F. Each group contains two images. The left image is a box plot showing the distribution of the average methylation value of the target sequence in tumor samples and normal cancer samples (controls), which shows the difference in methylation of the target sequence between tumor and normal samples. The right image is a ROC curve, which shows the specificity of the difference results. A: Breast cancer sample and control; B: Cervical cancer sample and control; C: Esophageal cancer sample and control; D: Head and neck cancer sample and control; E: Lung cancer sample and control; F: Pancreatic cancer sample and control. It can be seen that the average methylation value of the target sequence in the chr8:70984200-70984294 region is higher than the average methylation value of adjacent normal tissue in breast cancer, cervical cancer, head and neck cancer, esophageal cancer, and pancreatic cancer samples. In lung cancer samples, the average methylation value of the target sequence in the chr8:70984200-70984294 region was mostly higher than that of adjacent normal tissue, and the mean of its average methylation value was also higher than that of adjacent normal tissue. Based on the average methylation value of the target sequence in the chr8:70984200-70984294 region, most tumor samples can be distinguished from cancerous normal tissue.

[0117] Example 17 - Application of the target sequence in the chr1:6515341-6515409 region in clinical testing

[0118] Samples: Six types of tumor tissue and adjacent normal tissue samples, namely breast cancer (5 cancer tissues, 5 adjacent normal tissues), cervical cancer (3 cancer tissues, 5 adjacent normal tissues), esophageal cancer (3 cancer tissues, 1 adjacent normal tissue), head and neck cancer (4 cancer tissues, 5 adjacent normal tissues), lung cancer (3 cancer tissues, 3 adjacent normal tissues), and pancreatic cancer (2 cancer tissues, 2 adjacent normal tissues).

[0119] According to the method in Example 1, the average methylation value of the target sequence in the chr1:6515341-6515409 region was obtained in 20 tumor tissues and 21 adjacent normal tissues using RRBS methylation sequencing technology. The results are as follows: Figure 24As shown in the figure, there are six groups of images: A, B, C, D, E, and F. Each group contains two images. The left image is a box plot showing the distribution of the average methylation value of the target sequence in tumor samples and normal cancer samples (controls), which shows the difference in methylation of the target sequence between tumor and normal samples. The right image is the ROC curve of the detection, which shows the specificity of the difference results. A: Breast cancer sample and control; B: Cervical cancer sample and control; C: Esophageal cancer sample and control; D: Head and neck cancer sample and control; E: Lung cancer sample and control; F: Pancreatic cancer sample and control. It can be seen that the average methylation value of the target sequence in the chr1:6515341-6515409 region is higher than the average methylation value of adjacent normal tissue in breast cancer, cervical cancer, head and neck cancer, esophageal cancer, and lung cancer samples. In pancreatic cancer samples, the average methylation value of the target sequence in the chr1:6515341-6515409 region was mostly higher than that of adjacent normal tissue, and the mean of its average methylation value was also higher than that of adjacent normal tissue. Based on the average methylation value of the target sequence in the chr1:6515341-6515409 region, most tumor samples can be distinguished from cancerous normal tissue.

[0120] The specific embodiments of the present invention have been described in detail above, but they are only examples, and the present invention is not limited to the specific embodiments described above. For those skilled in the art, any equivalent modifications and substitutions to the present invention are also within the scope of the present invention. Therefore, all equivalent changes and modifications made without departing from the spirit and scope of the present invention should be covered within the scope of the present invention.

Claims

1. The application of a reagent for detecting the methylation level of tumor marker CpG sites in the preparation of auxiliary detection or diagnostic reagents for tumors, characterized in that, The tumor marker is located on human chromosome 10 and includes one or more CpG sites that can undergo methylation modification; wherein the tumor marker is located in the region chr10: 50819227-50819589 with human genome hg19 as a reference version, and its sequence is the base sequence shown in SEQ ID NO.1 or its complementary sequence, and the tumor marker is used as a marker for one or more of cervical cancer, head and neck cancer, lung cancer and pancreatic cancer.

2. The application according to claim 1, characterized in that, The methylation modification includes 5-aldehyde methylation, 5-hydroxymethylation, 5-methylation, or 5-carboxymethylation.

3. The application according to claim 1, characterized in that, The reagent used to detect the methylation level of the tumor marker CpG site is a tumor marker detection kit, which includes primers or probes that specifically detect the methylation level of the tumor marker CpG site.

4. The application according to claim 3, characterized in that, The method of using the reagent for detecting the methylation level of the tumor marker CpG site includes the following steps: S1. Obtain the tissue sample to be tested; S2. Extract DNA from the tissue sample to be tested and obtain the methylation value of the sample; S3. Calculate the methylation status of each CpG site within the tumor marker sequence region or the average methylation status of the entire region.

5. The application according to claim 4, characterized in that, The methods for obtaining the methylation value of a sample as described in step S2 include: sequencing, probes, antibodies, and mass spectrometry.

Images