SNP (Single Nucleotide Polymorphism) marker for predicting recurrence and metastasis risk of esophageal cancer patient and application

Abstract

The invention belongs to the technical field of biomedicine, and particularly relates to an SNP (Single Nucleotide Polymorphism) marker for predicting recurrence and metastasis risks of esophageal cancer patients and application. According to the method, 177 esophageal cancer patient samples which are subjected to follow-up visit for about 10 years are utilized, 39 SNP sites related to the recurrence and metastasis risk of esophageal cancer are screened out, the recurrence and metastasis risk of the esophageal cancer patient can be accurately and effectively predicted by detecting the genotypes of the SNP sites in the esophageal cancer patient, the esophageal cancer prognosis prediction precision is greatly improved, and the esophageal cancer prognosis prediction time is shortened. And a more positive and effective treatment scheme is formulated for a patient with poor prognosis, so that individualized treatment of the patient is realized.

Description

Technical Field

[0001] The present invention belongs to the field of biomedical technology, and specifically relates to a SNP marker for predicting the risk of recurrence and metastasis of esophageal cancer patients and an application thereof. Background Art

[0002] Globally, approximately 510,000 people are diagnosed with esophageal cancer each year, and approximately 445,000 people die from esophageal cancer each year. The main histological subtypes of esophageal cancer are squamous cell carcinoma and adenocarcinoma. For the convenience of description, they are referred to as esophageal cancer below. Endoscopic treatment, surgical resection and radiotherapy are currently one of the main treatments for esophageal cancer, but about 50-70% of esophageal cancer patients still relapse after receiving the above treatments. Various studies have shown that there are more aggressive subtypes of esophageal cancer, and patients with highly invasive esophageal cancer have a high risk of recurrence and metastasis after receiving the above treatments, so they may benefit from adjuvant targeted therapy. Therefore, accurately assessing the risk of recurrence and metastasis in patients with esophageal cancer is the key to determining which patients need adjuvant treatment. At present, TNM staging, pathological grade, tumor size, and the presence or absence of muscle layer and serosal infiltration are usually used to assess the risk of recurrence and metastasis in patients with esophageal cancer. However, patients with the same TNM stage, pathological grade, tumor size, and the presence or absence of muscle layer and serosa infiltration may have very different prognoses. Therefore, the predictive ability of the current postoperative recurrence assessment and staging system for esophageal cancer needs to be improved urgently, which is expected to be achieved by using verified specific tumor biomolecular markers.

[0003] Several multi-gene classifiers have been reported to predict the risk of recurrence and metastasis of esophageal cancer. However, to date, there is still no stable and reliable molecular marker used in clinical practice to predict the risk of recurrence and metastasis of esophageal cancer after surgery. Single-nucleotide polymorphisms (SNPs) refer to DNA sequence polymorphisms caused by the variation of a single nucleotide at the genome level. It is the most common type of heritable variation in humans, accounting for more than 80% of all known polymorphisms. With the continuous development of whole genome technology, the research on single nucleotide polymorphisms related to disease outcomes, including cancer, has become more and more in-depth. As a third-generation genetic marker, it has been widely used in the diagnosis and prognosis prediction of major diseases such as malignant tumors in recent years, and has shown the characteristics of rapidity, sensitivity, and accuracy, so it has broad application prospects. At present, no SNP sites that can accurately and effectively judge tumor prognosis have been applied to tumor prognosis prediction. However, some existing reports have explored the correlation between mutations in related genes and tumor prognosis, involving DNA repair genes (ERCC1, XRCC1), chemokines (CXCL12, MCP-1), matrix metalloproteinases (MMP-9, MMP-1), interleukins (IL-8), tumor suppressor genes (TP53), cell cycle-related genes (CCNE1), key genes for prostaglandin synthesis (PTGS2), ubiquitin-protein ligase (MDM2), etc.; however, since these studies involve relatively small sample sizes and are greatly affected by confounding factors such as population structure, the results obtained are still controversial, and their potential value is not enough to be further developed and applied. Summary of the invention

[0004] The technical problem to be solved by the present invention is to overcome the defects and shortcomings of single nucleotide polymorphism variation site molecular markers in predicting the risk of recurrence and metastasis of esophageal cancer, and to provide a group of SNP molecular markers for predicting the risk of recurrence and metastasis of esophageal cancer, so as to assist in guiding individualized treatment and improving the prognosis of esophageal cancer patients.

[0005] To achieve the above objectives, the technical solutions adopted by the present invention include:

[0006] In the first aspect, the present invention provides a SNP marker for predicting the risk of recurrence and metastasis of patients with esophageal cancer, characterized in that the SNP markers include rs306496, rs928661, rs10896380, rs3125734, rs12925933, rs3731646, rs11664063, rs2303720, rs3739915, rs1047840, rs3736038, rs4523977, rs800292, rs1981933, rs13040543, rs6126919, rs2413429, rs11 at least one of rs814051, rs4751185, rs2508037, rs1878770, rs2519974, rs10916264, rs4939206, rs1869934, rs6499809, rs10486314, rs949827, rs4719411, rs1587578, rs9276490, rs1393232, rs2343202, rs12219270, rs907473, rs718017, rs10035541, rs11215855 and rs7095306.

[0007] Preferably, the SNP marker is rs306496, rs928661, rs10896380, rs3125734, rs12925933, rs3731646, rs11664063, rs2303720, rs3739915, rs1047840, rs3736038, rs4523977, rs800292, rs1981933, rs13040543, rs6126919, rs2413429, rs11814051, rs4751185, The combination of rs2508037, rs1878770, rs2519974, rs10916264, rs4939206, rs1869934, rs6499809, rs10486314, rs949827, rs4719411, rs1587578, rs9276490, rs1393232, rs2343202, rs12219270, rs907473, rs718017, rs10035541, rs11215855, and rs7095306.

[0008] The present invention uses samples from 177 esophageal cancer patients who were followed up for about 10 years to screen out 39 SNP sites associated with the risk of recurrence and metastasis of esophageal cancer. By detecting the genotypes of the above SNP sites in esophageal cancer patients, the risk of recurrence and metastasis of esophageal cancer patients can be accurately and effectively predicted, greatly improving the accuracy of predicting the risk of recurrence and metastasis of esophageal cancer.

[0009] In a second aspect, the present invention provides the use of the SNP marker in preparing a kit for predicting the risk of recurrence and metastasis of esophageal cancer patients.

[0010] In a third aspect, the present invention provides the use of the SNP marker in constructing a scoring model for predicting the risk of recurrence and metastasis in patients with esophageal cancer.

[0011] In a fourth aspect, the present invention provides a scoring model for predicting the risk of recurrence and metastasis of esophageal cancer patients, wherein the scoring model is to calculate the recurrence risk score value by the following recurrence risk scoring formula after detecting the SNP marker in the patient's DNA:

[0012] Said

[0013] Wherein, βi represents the coefficient of the i-th SNP; Gi represents the genotype information of the i-th SNP carried by the detected patient, and the genotype information includes: wild type, assigned value 0; heterozygous mutation, assigned value 1; homozygous mutation, assigned value 2;

[0014] The coefficient of rs1587578 is 0.953359866, the coefficient of rs10916264 is 0.459027765, the coefficient of rs928661 is -1.293093725, the coefficient of rs6499809 is -0.550901535, the coefficient of rs10035541 is -0.7330163, the coefficient of rs1393232 is 1.337773205, the coefficient of rs10896380 is -0.81936409, the coefficient of rs2508037 is 0.042944048, and the coefficient of rs4939206 is 0.054792755 The coefficient of rs3736038 is 0.87947483, the coefficient of rs9276490 is -1.010988006, the coefficient of rs2413429 is -0.491902316, the coefficient of rs4751185 is 0.797010857, the coefficient of rs12925933 is -0.284952352, the coefficient of rs13040543 is 0.274982821, the coefficient of rs6126919 is 0.130128736, the coefficient of rs3731646 is -0.033455598, and the coefficient of rs949827 is -0.319218 231, the coefficient of rs907473 is 0.90616315, the coefficient of rs10486314 is 0.187425269, the coefficient of rs3125734 is -0.199911555, the coefficient of rs4719411 is 0.270059668, the coefficient of rs11664063 is -0.167698128, the coefficient of rs3739915 is 0.305994827, the coefficient of rs2519974 is -0.094839637, the coefficient of rs7095306 is -0.312529982, and the coefficient of rs12219270 is 0.554 483179, the coefficient of rs306496 is -0.023214044, the coefficient of rs800292 is 0.102038526, the coefficient of rs1869934 is -0.261980536, the coefficient of rs2343202 is -0.725179675, the coefficient of rs2303720 is -0.914592279, the coefficient of rs11215855 is -0.92164442, the coefficient of rs1878770 is -0.045894794, the coefficient of rs4523977 is -0.101558662, and the coefficient of rs1047840 is 0.073956293, the coefficient of rs11814051 is 0.310290286, the coefficient of rs1981933 is -0.406593934, and the coefficient of rs718017 is -0.356217432. .

[0015] Preferably, when the recurrence risk score value is greater than -1.3, the detected patient is at high risk of recurrence and metastasis of esophageal cancer, i.e., a high-risk group; when the recurrence risk score value is less than or equal to -1.3, the detected patient is at low risk of recurrence and metastasis of esophageal cancer, i.e., a low-risk group.

[0016] In a fifth aspect, the present invention provides a kit for predicting the risk of recurrence and metastasis of patients with esophageal cancer, wherein the kit comprises a reagent for detecting the SNP marker.

[0017] Preferably, the reagent for detecting SNP markers includes PCR specific primers, and the sequences of the specific primers are shown in SEQ ID NOs: 1-78.

[0018] Preferably, the primer sequence for detecting the rs306496 site is as shown in SEQ No: 1-2; the primer sequence for detecting the rs928661 site is as shown in SEQ No: 3-4; the primer sequence for detecting the rs10896380 site is as shown in SEQ No: 5-6; the primer sequence for detecting the rs3125734 site is as shown in SEQ No: 7-8; the primer sequence for detecting the rs12925933 site is as shown in SEQ No: 9-10; the primer sequence for detecting the rs3731646 site is as shown in SEQ No: 11-12; the primer sequence for detecting the rs11664063 site is as shown in SEQ No: 13-14; the primer sequence for detecting the rs2303720 site is as shown in SEQ No: 15-16; the primer sequence for detecting the rs3739915 site is as shown in SEQ No: 17-18; the primer sequence for detecting the rs1047840 site is as shown in SEQ No: 19-20; the primer sequence for detecting the rs3736038 site is shown in SEQ No: 21-22; the primer sequence for detecting the rs4523977 site is shown in SEQ No: 23-24; the primer sequence for detecting the rs800292 site is shown in SEQ No: 25-26; the primer sequence for detecting the rs1981933 site is shown in SEQ No: 27-28; the primer sequence for detecting the rs13040543 site is shown in SEQ No: 29-30; the primer sequence for detecting the rs6126919 site is shown in SEQ No: 31-32; the primer sequence for detecting the rs2413429 site is shown in SEQ No: 33-34; the primer sequence for detecting the rs11814051 site is shown in SEQ No: 35-36; the primer sequence for detecting the rs4751185 site is shown in SEQ No: 37-38; the primer sequence for detecting the rs2508037 site is shown in SEQ No: 39-40; the primer sequence for detecting the rs1878770 site is shown in SEQ No: 41-42; the primer sequence for detecting the rs2519974 site is shown in SEQ No: 43-44; the primer sequence for detecting the rs10916264 site is shown in SEQ No: 45-46; the primer sequence for detecting the rs4939206 site is shown in SEQ No: 47-48; the primer sequence for detecting the rs1869934 site is shown in SEQ No: 49-50; the primer sequence for detecting the rs6499809 site is shown in SEQ No: 51-52; the primer sequence for detecting the rs10486314 site is shown in SEQ No: 53-54;The primer sequence for detecting the rs949827 site is shown in SEQ No: 55-56; the primer sequence for detecting the rs4719411 site is shown in SEQ No: 57-58; the primer sequence for detecting the rs1587578 site is shown in SEQ No: 59-60; the primer sequence for detecting the rs9276490 site is shown in SEQ No: 61-62; the primer sequence for detecting the rs1393232 site is shown in SEQ No: 63-64; the primer sequence for detecting the rs2343202 site is shown in SEQ No: 65-66; the primer sequence for detecting the rs12219270 site is shown in SEQ No: 67-68; the primer sequence for detecting the rs907473 site is shown in SEQ No: 69-70; the primer sequence for detecting the rs718017 site is shown in SEQ No: No: 71-72; the primer sequence for detecting the rs10035541 site is shown in SEQ No: 73-74; the primer sequence for detecting the rs11215855 site is shown in SEQ No: 75-76; the primer sequence for detecting the rs7095306 site is shown in SEQ No: 77-78. ;

[0019] Preferably, the kit further comprises PCR buffer, dNTP, magnesium chloride, DNA polymerase and deionized water.

[0020] In a sixth aspect, the present invention provides use of the SNP marker, the scoring model, and / or the kit in the preparation of a product for predicting the risk of recurrence and metastasis in patients with esophageal cancer.

[0021] Compared with the prior art, the present invention has the following beneficial effects:

[0022] The present invention provides SNP markers associated with the risk of recurrence and metastasis of esophageal cancer and their applications, as well as a detection kit that can be used to predict the recurrence and metastasis of esophageal cancer, to assist in guiding individualized treatment and improving the prognosis of esophageal cancer patients. The detection kit provided by the present invention can accurately predict the prognosis of esophageal cancer patients by detecting SNP sites on the peripheral blood DNA or esophageal cancer tissue DNA of esophageal cancer patients; after the kit of the present invention is applied to clinical testing, the prognosis of the patient can be evaluated before treatment, and a more active and effective treatment plan can be formulated for patients with poor prognosis, thereby achieving individualized treatment of the patient and providing survival rate; in addition, the kit only needs to detect peripheral blood, and has the characteristics of convenient sampling, simple operation, and high timeliness. BRIEF DESCRIPTION OF THE DRAWINGS

[0023] Figure 1 Schematic diagram of the overall progression-free survival curve for high-risk patients and low-risk patients. DETAILED DESCRIPTION

[0024] In order to make the purpose, technical scheme and effect of the present invention clearer and more specific, the present invention is further described in detail with reference to the following 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.

[0025] Unless otherwise specified, the reagents used in the examples are conventional reagents in the art and can be purchased through commercial channels. The experimental operations not specifically described in the examples are conventional operations in the art or can be understood or known by those skilled in the art based on the existing technology or common knowledge they master.

[0026] Example 1. Screening of SNP sites for predicting the risk of recurrence and metastasis in patients with esophageal cancer

[0027] (1) Selection of research samples:

[0028] The samples included in this invention (a total of 177 patients) are all esophageal cancer patients diagnosed by pathology at the Sun Yat-sen University Cancer Center, with complete medical records (including tumor stage, medical history, examination results, previous treatment plans, etc.); patients must be newly diagnosed patients with no history of tumor, and have not received tumor-related radiotherapy, chemotherapy and other anti-tumor treatments before admission; patients are all voluntary participants in the study and signed informed consent. Patients included in the study were followed up regularly, every three months within two years after the end of treatment, and every six months thereafter.

[0029] (2) Genomic DNA extraction from peripheral blood or esophageal cancer tissue:

[0030] Before the first treatment, peripheral blood is collected from patients using EDTA anticoagulant tubes or surgical resection samples are stored in a -80°C refrigerator; genomic DNA is extracted from peripheral blood or esophageal cancer tissue using the phenol-chloroform method according to routine operating procedures. The concentration of the obtained DNA samples is usually 20-50 ng / μL, and the purity (OD260 / 280) is generally between 1.6-2.0.

[0031] (3) Amplification of SNP sites:

[0032] Use specific primers to amplify the following SNP sites. The primer sequences used are shown in Table 1:

[0033] rs306496, rs928661, rs10896380, rs3125734, rs12925933, rs3731646, rs1166 4063, rs2303720, rs3739915, rs1047840, rs3736038, rs4523977, rs800292, rs 12925933, rs1981933, rs13040543, rs13040543, rs13040543, rs6126919, rs24 13429, rs11814051, rs4751185, rs2508037, rs1878770, rs2519974, rs1091626 4. rs4939206, rs1869934, rs1869934, rs6499809, rs10486314, rs949827, rs4719411, rs1587578, rs9276490, rs1393232, rs2343202, rs12219270, rs907473, rs718017, rs10035541, rs11215855, rs7095306; PCR amplification also included PCR buffer, dNTP, magnesium chloride, polymerase, and deionized water. The PCR reaction program was set as: 94℃, 2min; 98℃, 10s, 56℃, 30s, 68℃, 40s, 33cycles; 4℃, ∞.

[0034] (4) SNP locus typing:

[0035] The SNP sites included rs306496, rs928661, rs10896380, rs3125734, rs12925933, rs3731646, rs11664063, rs2303720, rs3739915, rs1047840, rs3736038, rs4523977, rs800292, rs12925933, rs1981933, rs13040543, rs6126919, rs2413429, rs11814051, rs4751185, The DNA amplification products of rs2508037, rs1878770, rs2519974, rs10916264, rs4939206, rs1869934, rs1869934, rs6499809, rs10486314, rs949827, rs4719411, rs1587578, rs9276490, rs1393232, rs2343202, rs12219270, rs907473, rs718017, rs10035541, rs11215855, and rs7095306 were sequenced to obtain the genotype information of the above loci.

[0036] (5) Statistical analysis methods:

[0037] The chi-square analysis, the least absolute shrinkage and selection operator (LASSO algorithm), and the proportional hazards regression model were used. The correlation between SNP typing, demographic factors and clinical factors (including gender, age, clinical stage, CEA level, CA125 level, CA19-9 level, squamous cell carcinoma antigen level, serum albumin level, pathological differentiation grade, presence or absence of surrounding tissue invasion, tumor size, presence or absence of supraclavicular lymph node enlargement, whether concurrent chemoradiotherapy is used, whether postoperative adjuvant chemotherapy is used, whether neoadjuvant chemotherapy is used, etc.) and the prognosis of esophageal cancer was analyzed; factors significantly associated with tumor prognosis (including gender, age, clinical stage, CEA level, CA125 level, CA19-9 level, squamous cell carcinoma antigen level, serum albumin level, pathological differentiation grade, presence or absence of surrounding tissue invasion, tumor size, presence or absence of supraclavicular lymph node enlargement, whether concurrent chemoradiotherapy is used, whether postoperative adjuvant chemotherapy is used, whether neoadjuvant chemotherapy is used, etc.) were further used as covariates to calculate the hazard ratio (HR) and 95% confidence interval (95% confidence interval) of SNP genotype for tumor prognosis. The statistical analysis was performed using R software, with a statistical significance level of P < 0.05, and all tests were two-sided.

[0038] (6) Result analysis:

[0039] By detecting the genotype of the above SNP loci and using the prediction formula to obtain the recurrence risk score index of the subject, the formula is as follows:

[0040] Said

[0041] Wherein, βi represents the coefficient of the i-th SNP; Gi represents the genotype information of the i-th SNP carried by the detected patient, and the genotype information includes: wild type, assigned value 0; heterozygous mutation, assigned value 1; homozygous mutation, assigned value 2; the coefficient values ​​corresponding to the SNP sites are shown in Table 1.

[0042] After calculation by the above formula, the subjects with a recurrence risk score greater than -1.3 were classified as having a high risk of recurrence and metastasis, i.e., the high-risk group, and the subjects with a recurrence risk score less than or equal to -1.3 were classified as having a low risk of recurrence and metastasis, i.e., the low-risk group. The patients in the low-risk group had a longer progression-free survival (HR = 0.039, 95% CI = 0.017-0.093, P = 1.41 × 10 -13), these patients do not need to be given adjuvant chemotherapy after radical surgery; patients in the high-risk group should be given adjuvant treatment to prevent recurrence, such as immune checkpoint inhibitors (ICIs) such as cardunilizumab, HER2 receptor inhibitors such as trastuzumab, or combined chemotherapy drugs such as PF (cisplatin + fluorouracil) and FOLFOX (oxaliplatin + fluorouracil + capecitabine).

[0043] Table 1

[0044]

[0045]

[0046]

[0047]

[0048] Example 2. Scoring model for predicting the risk of recurrence and metastasis in patients with esophageal cancer

[0049] This embodiment provides a scoring model for predicting the risk of recurrence and metastasis of esophageal cancer patients. The scoring model is based on the detection of 39 SNP markers (rs306496, rs928661, rs10896380, rs3125734, rs12925933, rs3731646, rs11664063, rs2303720, rs3739915, rs1047840, rs3736038, rs4523977, rs800292, rs1981933, rs13040543, rs6126919, rs2413429, rs11814051, rs4751185, rs25080 37, rs1878770, rs2519974, rs10916264, rs4939206, rs1869934, rs6499809, rs10486314, rs949827, rs4719411, rs1587578, rs9276490, rs1393232, rs2343202, rs12219270, rs907473, rs718017, rs10035541, rs11215855 and rs7095306), the SNP markers were used to construct a scoring model formula for predicting the risk of recurrence and metastasis of esophageal cancer patients using a proportional hazard regression model to calculate the recurrence risk score value. The specific model formula is:

[0050] Said

[0051] Wherein, βi represents the coefficient of the i-th SNP; Gi represents the genotype information of the i-th SNP carried by the detected patient, and the genotype information includes: wild type, assigned value 0; heterozygous mutation, assigned value 1; homozygous mutation, assigned value 2; the coefficient values ​​corresponding to the SNP sites are shown in Table 1.

[0052] The recurrence risk score value was calculated by the above model formula. The subjects with a recurrence risk score value greater than -1.3 were classified as having a high risk of recurrence and metastasis, i.e., a high-risk group, and the subjects with a recurrence risk score value less than or equal to -1.3 were classified as having a low risk of recurrence and metastasis, i.e., a low-risk group.

[0053] Example 3. Kit for predicting the risk of recurrence and metastasis in patients with esophageal cancer

[0054] This embodiment provides a kit for predicting the risk of recurrence and metastasis of esophageal cancer patients, which includes: specific primers for detecting each SNP site in Example 1 (primer sequences are shown in Table 1), PCR buffer, dNTP, magnesium chloride, DNA polymerase and deionized water.

[0055] Kit usage: Take peripheral blood or esophageal cancer tissue samples from patients with esophageal cancer and process them according to the phenol-chloroform method standard process to extract genomic DNA. The DNA concentration is 30-60ng / μL and the purity (OD 260 / 280 ) is between 1.6 and 2.0, and specific amplification primers (see Table 1) are used for PCR amplification. The reaction system is shown in Table 2.

[0056] After the PCR reaction was completed, DNA electrophoresis (1% agarose gel, voltage: 120V, time: 30 minutes) was performed to detect the PCR products, and the PCR products with the expected fragment size (673bp), single band and moderate brightness were selected for sequencing using a sequencer.

[0057] Table 2 PCR reaction system

[0058]

[0059] The PCR amplification reaction program was set as: 94°C, 2 min; 98°C, 10 s, 56°C, 30 s, 68°C, 40 s, 33 cycles; 4°C, ∞.

[0060] The risk score is calculated by the recurrence risk scoring formula of the present invention, and the subjects with a recurrence risk score value greater than -1.3 are classified as having a high risk of recurrence and metastasis, i.e., a high-risk group, and the subjects with a recurrence risk score value less than or equal to -1.3 are classified as having a low risk of recurrence and metastasis, i.e., a low-risk group; for patients in the low-risk group, no adjuvant chemotherapy or other treatments may be given after radical surgery; for patients in the high-risk group, adjuvant treatments for preventing recurrence should be given, such as immune checkpoint inhibitors (ICIs) such as cardunilizumab, HER2 receptor inhibitors such as trastuzumab, or combined chemotherapy drug regimens such as PF (cisplatin + fluorouracil), FOLFOX (oxaliplatin + fluorouracil + capecitabine). The correlation analysis based on the results of gene SNP analysis and the follow-up data of included esophageal cancer patients showed that the recurrence-free survival of low-risk patients was significantly longer than that of high-risk patients, with an overall recurrence-free survival (HR = 0.039, 95% CI = 0.017-0.093, P = 1.41 × 10 -13 ,like Figure 1 shown).

[0061] Finally, it should be noted that the above embodiments are only used to illustrate the technical solution of the present invention rather than to limit the scope of protection of the present invention. Although the present invention has been described in detail with reference to the preferred embodiments, those skilled in the art should understand that the technical solution of the present invention can be modified or replaced by equivalents without departing from the essence and scope of the technical solution of the present invention.

Claims

1. A SNP marker for predicting the risk of recurrence and metastasis in patients with esophageal cancer, characterized in that: The SNP markers include rs306496, rs928661, rs10896380, rs3125734, rs12925933, rs3731646, rs11664063, rs2303720, rs3739915, rs1047840, rs3736038, rs4523977, rs800292, rs1981933, rs13040543, rs6126919, rs2413429, rs11814051, rs4751185, rs2 at least one of rs508037, rs1878770, rs2519974, rs10916264, rs4939206, rs1869934, rs6499809, rs10486314, rs949827, rs4719411, rs1587578, rs9276490, rs1393232, rs2343202, rs12219270, rs907473, rs718017, rs10035541, rs11215855 and rs7095306.

2. The SNP marker according to claim 1, wherein The SNP markers are rs306496, rs928661, rs10896380, rs3125734, rs12925933, rs3731646, rs11664063, rs2303720, rs3739915, rs1047840, rs3736038, rs4523977, rs800292, rs1981933, rs13040543, rs6126919, rs2413429, rs11814051, rs4751185, rs The combination of rs2508037, rs1878770, rs2519974, rs10916264, rs4939206, rs1869934, rs6499809, rs10486314, rs949827, rs4719411, rs1587578, rs9276490, rs1393232, rs2343202, rs12219270, rs907473, rs718017, rs10035541, rs11215855 and rs7095306.

3. Use of the SNP marker according to claim 1 or 2 in preparing a kit for predicting the risk of recurrence and metastasis in patients with esophageal cancer.

4. Use of the SNP marker as described in claim 1 or 2 in constructing a scoring model for predicting the risk of recurrence and metastasis in patients with esophageal cancer.

5. A scoring model for predicting the risk of recurrence and metastasis in patients with esophageal cancer, characterized in that: The scoring model is to calculate the recurrence risk score value by detecting the SNP markers of claim 2 in the patient's DNA using the following recurrence risk scoring formula: Wherein, βi represents the coefficient of the i-th SNP; Gi represents the genotype information of the i-th SNP carried by the detected patient, and the genotype information includes: wild type, assigned value 0; heterozygous mutation, assigned value 1; homozygous mutation, assigned value 2; The coefficient of rs1587578 is 0.953359866, the coefficient of rs10916264 is 0.459027765, the coefficient of rs928661 is -1.293093725, the coefficient of rs6499809 is -0.550901535, the coefficient of rs10035541 is -0.7330163, the coefficient of rs1393232 is 1.337773205, the coefficient of rs10896380 is -0.81936409, the coefficient of rs2508037 is 0.042944048, and the coefficient of rs4939206 is 0.054792755 The coefficient of rs3736038 is 0.87947483, the coefficient of rs9276490 is -1.010988006, the coefficient of rs2413429 is -0.491902316, the coefficient of rs4751185 is 0.797010857, the coefficient of rs12925933 is -0.284952352, the coefficient of rs13040543 is 0.274982821, the coefficient of rs6126919 is 0.130128736, the coefficient of rs3731646 is -0.033455598, and the coefficient of rs949827 is -0.319218 231, the coefficient of rs907473 is 0.90616315, the coefficient of rs10486314 is 0.187425269, the coefficient of rs3125734 is -0.199911555, the coefficient of rs4719411 is 0.270059668, the coefficient of rs11664063 is -0.167698128, the coefficient of rs3739915 is 0.305994827, the coefficient of rs2519974 is -0.094839637, the coefficient of rs7095306 is -0.312529982, and the coefficient of rs12219270 is 0.554 483179, the coefficient of rs306496 is -0.023214044, the coefficient of rs800292 is 0.102038526, the coefficient of rs1869934 is -0.261980536, the coefficient of rs2343202 is -0.725179675, the coefficient of rs2303720 is -0.914592279, the coefficient of rs11215855 is -0.92164442, the coefficient of rs1878770 is -0.045894794, the coefficient of rs4523977 is -0.101558662, and the coefficient of rs1047840 is 0.073956293, the coefficient of rs11814051 is 0.310290286, the coefficient of rs1981933 is -0.406593934, and the coefficient of rs718017 is -0.356217432. .

6. The scoring model according to claim 5, characterized in that: When the recurrence risk score value is greater than -1.3, the detected patient is at high risk of recurrence and metastasis of esophageal cancer, that is, the high-risk group; when the recurrence risk score value is less than or equal to -1.3, the detected patient is at low risk of recurrence and metastasis of esophageal cancer, that is, the low-risk group.

7. A kit for predicting the risk of recurrence and metastasis of esophageal cancer patients, characterized in that: The kit comprises a reagent for detecting the SNP marker according to claim 1.

8. The kit according to claim 7, characterized in that The reagent for detecting the SNP marker according to claim 1 comprises PCR specific primers, and the sequences of the specific primers are shown in SEQ ID NOs: 1-78.

9. The kit according to claim 7, characterized in that The kit also includes PCR buffer, dNTPs, magnesium chloride, DNA polymerase and deionized water.

10. Use of the SNP marker according to claim 1 or 2, the scoring model according to claim 5 or 6, and / or the kit according to any one of claims 7 to 9 in the preparation of a product for predicting the risk of recurrence and metastasis in patients with esophageal cancer.

Images