Esophageal cancer methylation early screening markers and application thereof

Abstract

The invention belongs to the technical field of biological pharmacy, and provides a group of esophageal cancer methylation early screening markers and application thereof, the group of markers is any one of ZNF693, MMP14, JAG1, RUNX1 or NOTCH1 gene sequences or gene segments containing at least one CpG methylation site, or a combination of any two or more of the ZNF693, MMP14, JAG1, RUNX1 or NOTCH1 gene sequences or gene segments containing at least one CpG methylation site; the invention also discloses an application of the group of biomarkers in preparation of a detection kit for diagnosing and / or evaluating the methylation degree of esophageal cancer or an application of the group of biomarkers in screening of drugs for treating and / or relieving esophageal cancer. According to the method, by quantifying the dynamic change of the methylation level, cancer patients can be effectively identified, and the risk of missing detection caused by tumor heterogeneity is reduced; by establishing a high-throughput and standardized detection process, a precise molecular typing tool can be provided for early intervention of esophageal cancer; the limitation that the traditional technology is insufficient in early canceration detection sensitivity and depends on invasive operation is overcome, and the clinical transformation of early screening and early diagnosis can be promoted.

Description

Technical Field

[0001] The present invention belongs to the field of biotechnology, and particularly relates to a group of early screening markers for esophageal cancer methylation and their applications. Background Art

[0002] Esophageal cancer is mainly squamous cell carcinoma (accounting for 90%), and is closely related to long-term consumption of overheated food, nitrosamine exposure and genetic factors. Although early esophageal cancer can achieve a 5-year survival rate of over 90% through endoscopic resection, 70%-80% of the existing patients are in the middle and advanced stages at the time of diagnosis, and the 5-year survival rate is only 15%-20%, mainly due to the insufficient early screening coverage. It can be seen that in the diagnosis and treatment of esophageal cancer, early screening and accurate diagnosis are the keys to improving the prognosis. However, there are still significant limitations in the existing technologies.

[0003] Traditional early screening of esophageal cancer mainly relies on endoscopic examination and biopsy. Such invasive operations may not only cause discomfort, bleeding and infection risks to patients, but also are difficult to be applied to large-scale population screening due to trauma and high costs. In the field of molecular markers, the reported gene mutations (such as TP53) or protein markers have insufficient sensitivity. The low expression level in early canceration leads to a high false negative rate. At the same time, some markers are prone to false positives in inflammation or other digestive tract diseases, and the specificity is limited. In addition, the existing non-invasive detection methods have insufficient timeliness: imaging examinations (such as CT, PET-CT) have low resolution for early tiny lesions, resulting in a limited early diagnosis window period. Although DNA methylation, as an important mechanism of epigenetic regulation, its abnormality is closely related to the occurrence of esophageal cancer, but the existing research mainly focuses on the methylation sites of single genes, lacking systematic screening and large-sample clinical verification of specific methylation combination markers for esophageal cancer, and cannot meet the needs of accurate screening. The above problems together lead to the difficulty of the existing technologies in achieving efficient, non-invasive and highly sensitive screening for early esophageal cancer.

[0004] Aiming at the core defects of the existing esophageal cancer screening technologies, such as strong invasiveness, insufficient sensitivity and lagging detection window period, the present invention constructs a non-invasive detection system based on a combination of blood DNA methylation markers, and proposes a group of early screening markers for esophageal cancer methylation; by applying this group of markers to highly sensitively capture the methylation signals of circulating tumor DNA (ctDNA) using targeted methylation sequencing technology, non-invasive and high-precision early screening can be achieved. Summary of the Invention

[0005] The purpose of the present invention is to provide a group of early screening markers for esophageal cancer methylation and their applications;

[0006] By detecting the esophageal cancer-specific multi-gene methylation panel (NOTCH1, JAG1, RUNX1, ZNF693 / CASZ1, and MMP14) in the peripheral blood of patients and quantifying the dynamic changes in methylation levels, cancer patients can be effectively identified, and the risk of missed detection caused by tumor heterogeneity can be reduced. It overcomes the limitations of traditional techniques in the insufficient sensitivity of early cancer detection and the dependence on invasive operations, and can promote the clinical transformation of "early screening and early diagnosis".

[0007] To achieve the above object, the technical solution of the present invention is as follows:

[0008] The present invention provides a set of early screening markers for esophageal cancer methylation, characterized in that the markers are any one of the gene sequences or gene fragments of ZNF693, MMP14, JAG1, RUNX1, or NOTCH1 containing at least one CpG methylation site, or a combination of any two or more of them.

[0009] Preferably, the markers are a combination of the gene sequences or gene fragments of ZNF693, MMP14, JAG1, RUNX1, and NOTCH1 containing at least one CpG methylation site.

[0010] Preferably, the CpG methylation sites on the ZNF693 gene are chr1: 10635542-10635543, chr1: 10635544-10635545, chr1: 10635546-10635547, chr1: 10635549-10635550, chr1: 10635566-10635567, chr1: 10635601-10635602, chr1: 10635628-10635629, chr1: 10635659-10635660, chr1: 10635689-10635690, chr1: 10635696-10635697, chr1: 10635703-10635704, chr1: 10635741-10635742, chr1: 10635785-10635786, chr1: 10638995-10638996, chr1: 10639031-10639032, chr1: 10639064-10639065, chr1: 10639087-10639088, chr1: 10639102-10639103, chr1: 10639117-10639118, chr1: 10639126-10639127, chr1: 10639144-10639145, chr1: 10639219-10639220, chr1: 10668717-10668718, chr1: 10669030-10669031, chr1: 10671192-10671193, chr1: 10671310-10671311, chr1: 10671328-10671329, chr1: 10690021-10690022, chr1: 10699813-10699814, chr1: 10716943-10716944, chr1: 10717003-10717004, chr1: 10736799-10736800, chr1: 10736829-10736830, chr1: 10736891-10736892, chr1: 10737169-10737170, chr1: 10737296-10737297, chr1: 10737392-10737393, chr1: 10755964-10755965, chr1: 10755988-10755989, chr1: 10756112-10756113, chr1: 10756119-10756120, chr1: 10756170-10756171,chr1: 10756177 - 10756178, chr1: 10756206 - 10756207, chr1: 10756318 - 10756319, chr1: 10756416 - 10756417, chr1: 10756449 - 10756450, chr1: 10756456 - 10756457, chr1: 10756473 - 10756474, chr1: 10756477 - 10756478, chr1: 10818448 - 10818449, chr1: 10818536 - 10818537, chr1: 10818583 - 10818584, chr1: 10822928 - 10822929, chr1: 10822994 - 10822995, chr1: 10830178 - 10830179, chr1: 10830269 - 10830270, chr1: 10830297 - 10830298, chr1: 10835429 - 10835430, chr1: 10835472 - 10835473, chr1: 10837431 - 10837432, chr1: 10837532 - 10837533, chr1: 10837552 - 10837553, chr1: 10856877 - 10856878, chr1: 10863578 - 10863579, chr1: 10863672 - 10863673, chr1: 10866191 - 10866192, chr1: 10639090 - 10639091, chr1: 10639105 - 10639106, chr1: 10639111 - 10639112, chr1: 10639114 - 10639115, chr1: 10639285 - 10639286, chr1: 10646238 - 10646239, chr1: 10646307 - 10646308, chr1: 10646312 - 10646313, chr1: 10646324 - 10646325, chr1: 10650868 - 10650869, chr1: 10650932 - 10650933, chr1: 10651001 - 10651002, chr1: 10669025 - 10669026, chr1: 10671308 - 10671309, chr1: 10671405 - 10671406, chr1: 10690185 - 10690186, chr1: 10716914 - 10716915, chr1: 10736915 - 10736916Any one or more of chr1: 10737202-10737203, chr1: 10756010-10756011, chr1: 10756012-10756013, chr1: 10756028-10756029, chr1: 10756312-10756313, chr1: 10756441-10756442, chr1: 10756576-10756577, chr1: 10761528-10761529, chr1: 10823058-10823059, chr1: 10830317-10830318, chr1: 10835459-10835460, chr1: 10837480-10837481, chr1: 10837538-10837539, chr1: 10856937-10856938, chr1: 10866244-10866245, chr1: 10866353-10866354, chr1: 10639189-10639190, chr1: 10651142-10651143, chr1: 10830300-10830301, chr1: 10639037-10639038, chr1: 10639055-10639056, chr1: 10639264-10639265, and chr1: 10639295-10639296.

[0011] Preferably, the CpG methylation sites on the ZNF693 gene are the above-mentioned 108 CpG methylation sites.

[0012] Preferably, the CpG methylation sites on the MMP14 gene are any one or more of chr14: 22837821-22837822, chr14: 22837883-22837884, chr14: 22838262-22838263, chr14: 22838287-22838288, chr14: 22838534-22838535, chr14: 22843476-22843477, chr14: 22852832-22852833, chr14: 22837947-22837948, chr14: 22838083-22838084, chr14: 22838122-22838123, chr14: 22838291-22838292.

[0013] Preferably, the CpG methylation sites on the MMP14 gene are the above-mentioned 11 CpG methylation sites.

[0014] Preferably, the CpG methylation sites on the JAG1 gene are any one or more of chr20: 10623294-10623295, chr20: 10627195-10627196, chr20: 10637056-10637057, chr20: 10637156-10637157, chr20: 10652533-10652534, chr20: 10652637-10652638, chr20: 10665892-10665893, chr20: 10665920-10665921, chr20: 10667181-10667182, chr20: 10667188-10667189, chr20: 10667192-10667193, chr20: 10667233-10667234, chr20: 10667263-10667264, chr20: 10667273-10667274, chr20: 10667294-10667295, chr20: 10670759-10670760, chr20: 10670784-10670785, chr20: 10671542-10671543, chr20: 10637204-10637205, chr20: 10670857-10670858, chr20: 10670885-10670886, chr20: 10670925-10670926, chr20: 10671545-10671546.

[0015] Preferably, the CpG methylation sites on the JAG1 gene are the above 23 CpG methylation sites.

[0016] Preferably, the CpG methylation sites on the RUNX1 gene are any one or more of chr21: 34807988-34807989, chr21: 34808054-34808055, chr21: 34808184-34808185, chr21: 34808228-34808229, chr21: 34808272-34808273, chr21: 34865974-34865975, chr21: 34866023-34866024, chr21: 34866150-34866151, chr21: 34866320-34866321, chr21: 34885409-34885410, chr21: 34907708-34907709, chr21: 34907820-34907821, chr21: 34989786-34989787, chr21: 35017274-35017275, chr21: 35017360-35017361, chr21: 35017598-35017599, chr21: 35017872-35017873, chr21: 35019857-35019858, chr21: 35026859-35026860, chr21: 35026901-35026902, chr21: 35026948-35026949, chr21: 35045071-35045072, chr21: 34866281-34866282, chr21: 35017770-35017771, chr21: 35017803-35017804, chr21: 35019855-35019856, chr21: 35026851-35026852, chr21: 35026898-35026899, chr21: 35045139-35045140, chr21: 35020003-35020004.

[0017] Preferably, the CpG methylation sites on the RUNX1 gene are the above 30 CpG methylation sites.

[0018] Preferably, the CpG methylation sites on the NOTCH1 gene are chr9: 136512062-136512063, chr9: 136512085-136512086, chr9: 136512102-136512103, chr9: 136526210-136526211, chr9: 136529699-136529700, chr9: 136529806-136529807, chr9: 136529826-136529827, chr9: 136529856-136529857, chr9: 136529874-136529875, chr9: 136530469-136530470, chr9: 136530661-136530662, chr9: 136530663-136530664, chr9: 136530864-136530865, chr9: 136530984-136530985, chr9: 136538550-136538551, chr9: 136538623-136538624, chr9: 136538700-136538701, chr9: 136540156-136540157, chr9: 136540161-136540162, chr9: 136540208-136540209, chr9: 136540265-136540266, chr9: 136540288-136540289, chr9: 136540304-136540305, chr9: 136540312-136540313, chr9: 136540353-136540354, chr9: 136540393-136540394, chr9: 136512045-136512046, chr9: 136512074-136512075, chr9: 136526269-136526270, chr9: 136526398-136526399, chr9: 136526485-136526486, chr9: 136530616-136530617, chr9: 136530773-136530774, chr9: 136540133-136540134, chr9: 136542897-136542898, chr9: 136542921-136542922, chr9: 136542966-136542967, chr9: 136512176-136512177, chr9: 136526357-136526358,Any one or more of chr9: 136542962-136542963, chr9: 136512128-136512129, chr9: 136512131-136512132, chr9: 136512155-136512156.

[0019] Preferably, the CpG methylation sites on the NOTCH1 gene are the above-mentioned 43 CpG methylation sites.

[0020] The present invention also provides the use of the above-mentioned set of early esophageal cancer methylation screening markers in the preparation of a detection kit for diagnosing and / or evaluating the methylation degree of esophageal cancer and / or in the screening of drugs for treating and / or alleviating esophageal cancer.

[0021] The present invention also provides the use of a product for detecting the above-mentioned set of early esophageal cancer methylation screening markers in the preparation of a product for diagnosing the methylation degree of esophageal cancer and / or predicting the risk.

[0022] Advantages of the present invention:

[0023] 1. The present invention abandons the dependence on invasive instruments in traditional methods, adopts a non-invasive method, and uses the detection of trace biomarkers in blood to achieve rapid screening. It is not only simple and non-invasive in operation, but also avoids side effects, greatly improving patient compliance and the applicability of general screening.

[0024] 2. By optimizing the molecular combination and algorithm analysis of methylation detection, the present invention can identify multiple stages of early tumors, thus making a more detailed distinction, having multi-stage adaptability, being more advantageous in disease progression monitoring, and being able to provide more accurate grading diagnosis information for clinical practice. In contrast, the detection rate of early lesions by traditional methods is extremely low and the cost is high: for example, the resolution of imaging for lesions less than 5 mm is insufficient, and the diagnostic accuracy is only about 50%-60%, and there is a risk of radiation; for PET-CT, although the diagnostic accuracy is high, the price is expensive, increasing the economic burden on patients.

[0025] 3. Although the existing esophageal exfoliative cytology examination has good simplicity and low false positives and can be used for large-scale general surveys, the sensitivity of this method is only 46% and the specificity is 84%, with relatively low sensitivity and prone to false negative results. More importantly, this examination is not applicable to patients with severe heart diseases, hypertension, esophageal varices, and lung diseases, restricting its applicable population range. The present invention can overcome the above population restrictions and achieve a wider applicability, especially for high-risk patient groups who cannot tolerate traditional examinations.

[0026] 4. The present invention constructs a multi-dimensional detection system by integrating multiple molecular markers, thoroughly breaking through the limitations of single markers, where signal instability caused by tumor heterogeneity restricts both detection sensitivity and specificity, and abnormal expression of markers induced by inflammation or other non-cancerous diseases leads to false positives. The results of the model constructed by the present invention are as follows: the specificity and sensitivity in the validation set are both close to 90%; the specificity > 91% and the sensitivity > 97% in the training set, indicating that a higher detection rate can be achieved at the precancerous lesion and early cancer stages, effectively reducing the risks of false negatives and false positives, and laying a reliable foundation for early screening. More importantly, while ensuring high accuracy, the present invention completes the detection relying only on 215 detection sites, significantly reducing the detection cost and achieving a double optimization of detection efficiency and economic cost. Description of the Drawings

[0027] Figure 1 is the AUC value corresponding to the candidate gene locus;

[0028] Figure 2 are the sensitivity and specificity of 215 sites in the binary classification model in ESCC;

[0029] Figure 3 are the sensitivity and specificity of 215 sites in the binary classification model in ESCC at different stages. Detailed Implementation Modes

[0030] Unless otherwise specified, the experimental methods used in the following examples are all conventional methods.

[0031] Unless otherwise specified, the materials, reagents, etc. used in the following examples can all be obtained from commercial channels.

[0032] In order to make the objectives, technical solutions and advantages of the present invention clearer, the present invention will be further described in detail below with reference to specific embodiments. It should be understood that the specific embodiments described herein are only used to explain the present invention and are not used to limit the present invention.

[0033] Example 1 Methylation Sequencing and Analysis

[0034] 1. Experimental Materials

[0035] 1.1 Tissue samples: including esophageal squamous cell carcinoma tissues (205 cases), adjacent normal tissues (201 cases), high-grade intraepithelial neoplasia (20 cases), and low-grade intraepithelial neoplasia (13 cases).

[0036] 1.2 Plasma samples: plasma from cancer patients (204 cases) and plasma from non-cancer controls (814 cases).

[0037] All the experiments involved in the present invention have been approved by the Ethics Committee of the National Cancer Center / Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, and each patient has signed an informed consent form.

[0038] 2. Experimental Methods and Results

[0039] 1) Whole-genome bisulfite sequencing (WGBS) was used to identify differentially methylated regions (DMRs) in tissues (this esophageal squamous cell carcinoma tissue, adjacent normal tissue, high-grade intraepithelial neoplasia, and low-grade intraepithelial neoplasia) and cell-free DNA (cfDNA) using metilene. Wilcox was used to calculate the significance of differences at each CpG site between the esophageal squamous cell carcinoma group and the adjacent normal group, high-grade intraepithelial neoplasia group, and low-grade intraepithelial neoplasia group respectively.

[0040] 2) Among the union intervals of DMRs in tissues and cfDNA, CpG sites with significant differences in the Wilcox test between the esophageal squamous cell carcinoma group and the healthy control group were screened, and the distribution differences in the expression of the sites were evaluated according to the interquartile range (Q1 - Q3).

[0041] 3) Based on the significantly highly differential sites in the union intervals of DMRs in tissues and cfDNA, supplemented by highly differential sites outside some intervals, targeted probes were designed for targeted methylation sequencing. Finally, a total of 290,297 CpG sites were captured by the probes.

[0042] Example 2 Screening of Markers

[0043] 1. Experimental Materials and Methods

[0044] 1.1 Plasma Samples

[0045] Esophageal squamous cell carcinoma group: 530 cancer plasma samples; Healthy control group: 1212 non-cancer plasma samples.

[0046] 1.2 Experimental Methods

[0047] The targeted probes designed in Example 1 were used to perform targeted methylation sequencing on the plasma samples in this example, and the methylation values of a total of 290,297 CpG sites were captured.

[0048] 1.3 Screening Criteria for Markers

[0049] To determine predictive markers with high predictive performance, the following screening methods were used:

[0050] ① Statistical method: The Wilcoxon rank-sum test was used to calculate whether the differences at each CpG site between the esophageal squamous cell carcinoma group and the healthy control group in the plasma samples were significant.

[0051] ② Gene-level evaluation: Each CpG site was annotated to a gene according to the nearest transcription start site (TSS). All significantly differential sites in each gene in the training set were included in the support vector machine (SVM) model for training, and the area under the curve (AUC) of the model in the validation set was calculated.

[0052] 2. Experimental Results

[0053] As shown in Table 1 and Figure 1 Figure [not provided], invasive cells are the most numerous and methylation changes are the most intense in esophageal squamous cell carcinoma. Among them, the top 5 genes ranked by AUC are ZNF693 (CASZ1), MMP14, JAG1, RUNX1, and NOTCH1, and the AUC values are all greater than 0.8, which can be used alone as biomarkers for early methylation screening of esophageal cancer. Considering the degree of difference in binding sites (p-value after BH correction, Q1-Q3) and the biological functions of genes, a total of 215 CpG sites located on ZNF693 / MMP14 / JAG1 / RUNX1 / NOTCH1 were finally identified as biomarkers for early methylation screening of esophageal cancer. The gene location information of these 215 sites is shown in Table 3.

[0054] Table 1 AUC Value Results of Genes

[0055]

[0056] Table 2 AUC Value Results of Single Sites and Combined Sites of the Top 5 Genes

[0057]

[0058]

[0059] Table 3 Genomic Location Information Table of 215 CpG Sites

[0060]

[0061]

[0062]

[0063]

[0064]

[0065]

[0066]

[0067]

[0068]

[0069]

[0070]

[0071] Note: In the original text, there is a reference to "Figure [not provided]" which is left as such in the translation as the original text doesn't specify the figure number. If there was a specific figure number, it should be used instead. Also, for the tags

[0052] -

[0071] , they are preserved as per the instruction.Note: Distal Intergenic means distal intergenic region, Exon means exon, Intron means intron, Promoter means promoter, 3'UTR means 3' untranslated region, Downstream means downstream.

[0072] Table 4 Statistical count of the number of sites on each gene

[0073] gene ZNF693 NOTCH1 JAG1 MMP14 RUNX1 number of loci 108 43 23 11 30

[0074] Example 3 Model training and validation of biomarker combinations

[0075] 1. Experimental method

[0076] 1) Model training: Using the cfDNA methylation data of 734 cancer plasma and 2026 non-cancer plasma participants, extract the methylation information of the 215 sites identified in Example 2, and establish a binary classification model for distinguishing cancer from non-cancer through a machine learning SVM model.

[0077] 2) Model validation: From the cfDNA methylation data of 112 cancer and 285 non-cancer participants, extract the methylation information of the 215 sites identified in Example 2. Use the binary classification model trained in step 1) to predict whether the participants belong to cancer / non-cancer, compare with the true grouping of the participants, and calculate the sensitivity and specificity.

[0078] 3) Classify the patients into stages 1-4 according to the TNM staging, and evaluate the sensitivity and specificity of the model established with 215 sites in ESCC at different stages.

[0079] 2. Experimental results

[0080] As Figure 2 shown in and Table 5, a binary classification model was constructed using the training set of the present invention for esophageal cancer prediction: the AUC of the validation set was as high as 0.96, the specificity was 88.07%, and the sensitivity was 89.29%; the AUC value of the training set was 0.98, the specificity was 91.96%, and the sensitivity was 97.96%. It shows that the combination of 215 sites can be used as a biomarker, and the diagnostic effect is significantly better than that of a single gene. From the results in Table 2 of Example 2, it can be seen that a single site of the top 5 genes and a combination of multiple sites on the top 5 genes can also be used as biomarkers for early screening of esophageal cancer.

[0081] Table 5 Statistical results of the specificity and sensitivity of diagnosis based on the training set and validation set of the binary classification model

[0082]

[0083] In addition, from Figure 3As shown, based on the binary classification model, among different stages of ESCC, in the validation set, except that the sensitivity of stage II is close to 0.7, the sensitivities of stages I, III, and IV are all greater than 0.85, and the sensitivity of the whole stage is close to 0.9; in the training set, the sensitivities of stages I, II, III, and IV and the whole stage are all high, all > 0.9. This shows that the combination of 215 loci as a biomarker can identify multiple stages of early esophageal cancer tumors, can make more detailed distinctions, and has multi-stage adaptability.

[0084] In summary, the biomarker provided by the present invention can effectively overcome multiple limitations of traditional esophageal cancer detection methods in terms of invasiveness, accuracy, early detection ability, and resource consumption. It has the characteristics of non-invasiveness, high sensitivity and specificity, multi-marker integration, and applicability to large-scale screening, providing a new solution for the early screening and precise diagnosis of esophageal cancer. Especially in the environment with limited primary medical resources, it can significantly improve the screening efficiency and coverage, provide important support for improving the early detection rate and cure rate of esophageal cancer, and has significant clinical application value and promotion prospects.

[0085] The above-described embodiments only represent the preferred embodiments of the present invention, and their descriptions are relatively specific and detailed, but they should not be construed as limiting the scope of the present invention. It should be noted that for those of ordinary skill in the art, without departing from the concept of the present invention, several modifications and improvements can still be made, and these all belong to the protection scope of the present invention. Therefore, the protection scope of the present invention should be subject to the appended claims.

Claims

1. A group of early screening markers for esophageal cancer methylation, characterized in that, The biomarker is any one of the ZNF693, MMP14, JAG1, RUNX1 or NOTCH1 gene sequences or gene fragments containing at least one CpG methylation site, or a combination of any two or more of them.

2. The set of early screening markers for esophageal cancer methylation according to claim 1, characterized in that, The biomarker is a combination of the ZNF693, MMP14, JAG1, RUNX1 and NOTCH1 gene sequences or gene fragments containing at least one CpG methylation site.

3. The set of early esophageal cancer methylation screening markers according to claim 1 or 2, characterized in that, The CpG methylation sites on the ZNF693 gene are chr1: 10635542-10635543, chr1: 10635544-10635545, chr1: 10635546-10635547, chr1: 10635549-10635550, chr1: 10635566-10635567, chr1: 10635601-10635602, chr1: 10635628-10635629, chr1: 10635659-10635660, chr1: 10635689-10635690, chr1: 10635696-10635697, chr1: 10635703-10635704, chr1: 10635741-10635742, chr1: 10635785-10635786, chr1: 10638995-10638996, chr1: 10639031-10639032, chr1: 10639064-10639065, chr1: 10639087-10639088, chr1: 10639102-10639103, chr1: 10639117-10639118, chr1: 10639126-10639127, chr1: 10639144-10639145, chr1: 10639219-10639220, chr1: 10668717-10668718, chr1: 10669030-10669031, chr1: 10671192-10671193, chr1: 10671310-10671311, chr1: 10671328-10671329, chr1: 10690021-10690022, chr1: 10699813-10699814, chr1: 10716943-10716944, chr1: 10717003-10717004, chr1: 10736799-10736800, chr1: 10736829-10736830, chr1: 10736891-10736892, chr1: 10737169-10737170, chr1: 10737296-10737297, chr1: 10737392-10737393, chr1: 10755964-10755965, chr1: 10755988-10755989, chr1: 10756112-10756113, chr1: 10756119-10756120, chr1: 10756170-10756171chr1: 10756177 - 10756178, chr1: 10756206 - 10756207, chr1: 10756318 - 10756319, chr1: 10756416 - 10756417, chr1: 10756449 - 10756450, chr1: 10756456 - 10756457, chr1: 10756473 - 10756474, chr1: 10756477 - 10756478, chr1: 10818448 - 10818449, chr1: 10818536 - 10818537, chr1: 10818583 - 10818584, chr1: 10822928 - 10822929, chr1: 10822994 - 10822995, chr1: 10830178 - 10830179, chr1: 10830269 - 10830270, chr1: 10830297 - 10830298, chr1: 10835429 - 10835430, chr1: 10835472 - 10835473, chr1: 10837431 - 10837432, chr1: 10837532 - 10837533, chr1: 10837552 - 10837553, chr1: 10856877 - 10856878, chr1: 10863578 - 10863579, chr1: 10863672 - 10863673, chr1: 10866191 - 10866192, chr1: 10639090 - 10639091, chr1: 10639105 - 10639106, chr1: 10639111 - 10639112, chr1: 10639114 - 10639115, chr1: 10639285 - 10639286, chr1: 10646238 - 10646239, chr1: 10646307 - 10646308, chr1: 10646312 - 10646313, chr1: 10646324 - 10646325, chr1: 10650868 - 10650869, chr1: 10650932 - 10650933, chr1: 10651001 - 10651002, chr1: 10669025 - 10669026, chr1: 10671308 - 10671309, chr1: 10671405 - 10671406, chr1: 10690185 - 10690186, chr1: 10716914 - 10716915, chr1: 10736915 - 10736916Any one or more of chr1: 10737202 to 10737203, chr1: 10756010 to 10756011, chr1: 10756012 to 10756013, chr1: 10756028 to 10756029, chr1: 10756312 to 10756313, chr1: 10756441 to 10756442, chr1: 10756576 to 10756577, chr1: 10761528 to 10761529, chr1: 10823058 to 10823059, chr1: 10830317 to 10830318, chr1: 10835459 to 10835460, chr1: 10837480 to 10837481, chr1: 10837538 to 10837539, chr1: 10856937 to 10856938, chr1: 10866244 to 10866245, chr1: 10866353 to 10866354, chr1: 10639189 to 10639190, chr1: 10651142 to 10651143, chr1: 10830300 to 10830301, chr1: 10639037 to 10639038, chr1: 10639055 to 10639056, chr1: 10639264 to 10639265, and chr1: 10639295 to 10639296.

4. The set of early esophageal cancer methylation screening markers according to claim 3, characterized in that The CpG methylation site on the ZNF693 gene is the 108 CpG methylation sites described in claim 3.

5. The set of early esophageal cancer methylation screening markers according to claim 4, wherein, The CpG methylation site on the MMP14 gene is any one or more of chr14: 22837821-22837822, chr14: 22837883-22837884, chr14: 22838262-22838263, chr14: 22838287-22838288, chr14: 22838534-22838535, chr14: 22843476-22843477, chr14: 22852832-22852833, chr14: 22837947-22837948, chr14: 22838083-22838084, chr14: 22838122-22838123, chr14: 22838291-22838292.

6. The set of early esophageal cancer methylation screening markers according to claim 5, wherein, The CpG methylation site on the MMP14 gene is the 11 CpG methylation sites described in claim 5.

7. The set of early esophageal cancer methylation screening markers according to claim 6, wherein The CpG methylation sites on the JAG1 gene are any one or more of chr20: 10623294-10623295, chr20: 10627195-10627196, chr20: 10637056-10637057, chr20: 10637156-10637157, chr20: 10652533-10652534, chr20: 10652637-10652638, chr20: 10665892-10665893, chr20: 10665920-10665921, chr20: 10667181-10667182, chr20: 10667188-10667189, chr20: 10667192-10667193, chr20: 10667233-10667234, chr20: 10667263-10667264, chr20: 10667273-10667274, chr20: 10667294-10667295, chr20: 10670759-10670760, chr20: 10670784-10670785, chr20: 10671542-10671543, chr20: 10637204-10637205, chr20: 10670857-10670858, chr20: 10670885-10670886, chr20: 10670925-10670926, chr20: 10671545-10671546.

8. The set of early esophageal cancer methylation screening markers according to claim 7, wherein, The CpG methylation sites on the JAG1 gene are the 23 CpG methylation sites described in claim 7.

9. The set of early esophageal cancer methylation screening markers according to claim 8, wherein, The CpG methylation sites on the RUNX1 gene are any one or more of chr21: 34807988-34807989, chr21: 34808054-34808055, chr21: 34808184-34808185, chr21: 34808228-34808229, chr21: 34808272-34808273, chr21: 34865974-34865975, chr21: 34866023-34866024, chr21: 34866150-34866151, chr21: 34866320-34866321, chr21: 34885409-34885410, chr21: 34907708-34907709, chr21: 34907820-34907821, chr21: 34989786-34989787, chr21: 35017274-35017275, chr21: 35017360-35017361, chr21: 35017598-35017599, chr21: 35017872-35017873, chr21: 35019857-35019858, chr21: 35026859-35026860, chr21: 35026901-35026902, chr21: 35026948-35026949, chr21: 35045071-35045072, chr21: 34866281-34866282, chr21: 35017770-35017771, chr21: 35017803-35017804, chr21: 35019855-35019856, chr21: 35026851-35026852, chr21: 35026898-35026899, chr21: 35045139-35045140, chr21: 35020003-35020004 in claim 9.

10. The set of early esophageal cancer methylation screening markers according to claim 9, wherein, The CpG methylation sites on the RUNX1 gene are the 30 CpG methylation sites described in claim 9.

11. The set of early esophageal cancer methylation screening markers according to claim 10, characterized in that, CpG methylation sites on the NOTCH1 gene chr9: 136512062-136512063, chr9: 136512085-136512086, chr9: 136512102-136512103, chr9: 136526210-136526211, chr9: 136529699-136529700, chr9: 136529806-136529807, chr9: 136529826-136529827, chr9: 136529856-136529857, chr9: 136529874 - 136529875, chr9: 136530469 - 136530470, chr9: 136530661 - 136530662, chr9: 136530663 - 136530664, chr9: 136530864 - 136530865, chr9: 136530984 - 136530985, chr9: 136538550 - 136538551, chr9: 136538623 - 136538624, chr9: 136538700 - 136538701, chr9: 136540156 - 136540157, chr9: 136540161 - 136540162, chr9: 136540208 - 136540209, chr9: 136540265 - 136540266, chr9: 136540288 - 136540289, chr9: 136540304 - 136540305, chr9: 136540312 - 136540313, chr9: 136540353 - 136540354, chr9: 136540393 - 136540394, chr9: 136512045 - 136512046, chr9: 136512074 - 136512075, chr9: 136526269 - 136526270, chr9: 136526398 - 136526399, chr9: 136526485 - 136526486, chr9: 136530616 - 136530617, chr9: 136530773 - 136530774, chr9: 136540133 - 136540134, chr9: 136542897 - 136542898, chr9: 136542921 - 136542922, chr9: 136542966 - 136542967, chr9: 136512176 - 136512177, chr9: 136526357 - 136526358, chr9: 136542962 - 136542963, chr9: 136512128 - 136512129, chr9: 136512131 - 136512132, chr9: 136512155 - 136512156, any one or more of them.

12. The set of early esophageal cancer methylation screening markers according to claim 11, wherein The CpG methylation sites on the NOTCH1 gene are the 43 CpG methylation sites described in claim 9.

13. Use of a set of early screening markers for esophageal cancer methylation as claimed in any one of claims 1 to 12 in the preparation of a detection kit for diagnosing and / or evaluating the degree of esophageal cancer methylation or in the screening of drugs for treating and / or alleviating esophageal cancer.

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