CN111549137A

CN111549137A - Genetic molecular marker related to gastric cancer auxiliary diagnosis and application thereof

Info

Publication number: CN111549137A
Application number: CN202010442304.9A
Authority: CN
Inventors: 张正东; 王美林; 辛俊逸; 杜牧龙; 邬燕玲; 黎书炜; 储海燕
Original assignee: Nanjing Medical University
Current assignee: Nanjing Medical University
Priority date: 2020-05-22
Filing date: 2020-05-22
Publication date: 2020-08-18
Anticipated expiration: 2040-05-22
Also published as: CN111549137B

Abstract

The invention belongs to the technical field of genetic engineering, and discloses a genetic molecular marker related to gastric cancer auxiliary diagnosis and application thereof, wherein the genetic molecular marker comprises 42 genetic loci. The invention constructs a genetic risk prediction model and carries out genetic risk assessment on gastric cancer of target people. Provides a specific primer of the SNP marker and application thereof in preparing a gastric cancer auxiliary diagnosis kit. Provides an auxiliary diagnostic kit for gastric cancer. The invention prepares the genetic marker kit for assisting gastric cancer diagnosis, is expected to lay a foundation for screening, individual prevention and treatment of high risk groups of gastric cancer in China and provides a decision basis. The SNP genetic marker is different from the traditional biomarker, has good stability and is easy to detect. The gastric cancer auxiliary diagnosis kit is beneficial to clinicians to quickly master the genetic risk of patients with gastric cancer, carries out early diagnosis, individualized prevention and treatment, and provides decision basis for screening and intervention of high-risk groups of gastric cancer.

Description

Genetic molecular marker related to gastric cancer auxiliary diagnosis and application thereof

Technical Field

The invention belongs to the technical field of genetic engineering, and particularly relates to a genetic molecular marker related to gastric cancer auxiliary diagnosis and application thereof.

Background

Currently, stomach cancer is a common malignant tumor, the incidence rate of which accounts for the sixth place of all tumors in the world, and the stomach cancer has obvious regionality and is high in incidence rate particularly in east asia areas such as china, japan and korea. According to statistics, about 429 million new cancers occur in China in 2015, 281 million cancer patients die, 68 million gastric cancers occur, 50 million deaths occur, all tumors are located at the second place, and the health of human beings is seriously damaged. In recent years, with economic development and social progress of China, the morbidity and mortality of gastric cancer are on the trend of declining year by year, but because early gastric cancer discovery is difficult, early, specific and sensitive screening indexes are lacked, and the disease burden caused by the early gastric cancer discovery is still large. Therefore, effective markers are searched for to evaluate the morbidity risk of the gastric cancer, and conventional gastroscopy and other methods are supplemented to high-risk people to realize early discovery and early diagnosis of the gastric cancer, so that the morbidity of the gastric cancer is greatly reduced.

The occurrence and development of gastric cancer are multi-stage and multi-factor biological processes which are involved together, and are the result of environmental factors (such as smoking and eating habits), genetic factors and interaction of the two factors. However, only a few people develop gastric cancer under the same environmental exposure, suggesting that genetic factors play a key role in the development of gastric cancer. Further, the scholars found that the genetic interpretation degree of the gastric cancer in Chinese population is 20%, and the effect of genetic factors is confirmed. Therefore, the identification of the genetic variation sites related to the gastric cancer is helpful for better evaluating the genetic risk of the individual to generate the gastric cancer, thereby realizing the early detection, diagnosis and targeted therapy of the gastric cancer.

Genome-wide association study (GWAS) is an effective genetic epidemiological research means, and is currently widely applied to association studies of various complex diseases. Currently, several tens of Single Nucleotide Polymorphism (SNP) sites related to gastric cancer have been discovered by GWAS, which provides a solid early basis for genetic studies of gastric cancer. Multiple studies show that the establishment of a gastric cancer onset genetic risk prediction model based on genetic loci discovered by GWAS is of great significance for screening high-risk people and realizing early prevention.

However, many of the conventional gastric cancer genetic models are constructed using GWAS sites, and their prediction efficiency is low, and the effects of the genetic prediction models cannot be exerted to the maximum extent. Therefore, the research on gastric cancer genetic risk models is developed by screening the whole genome and combining with external data verification, reliable gastric cancer auxiliary diagnosis genetic molecular markers are identified, and an optimized gastric cancer morbidity risk prediction model is constructed, so that the method is particularly urgent and important for implementing more effective individual prevention, scientific intervention and the like in the future.

Through the above analysis, the problems and defects of the prior art are as follows: most of the traditional gastric cancer genetic models are constructed by GWAS sites, the prediction efficiency is low, and the effect of the genetic prediction model cannot be exerted to the maximum extent.

The difficulty in solving the above problems and defects is:

how to construct a gastric cancer genetic model with better prediction efficiency from the perspective of whole genes and verify the gastric cancer genetic model in external data is a relatively challenging task.

The significance of solving the problems and the defects is as follows:

the prediction accuracy of the gastric cancer genetic model can be effectively improved, so that the method is better used for screening high risk groups with gastric cancer.

Disclosure of Invention

Aiming at the problems in the prior art, the invention provides a genetic molecular marker related to gastric cancer auxiliary diagnosis and application thereof.

The invention is realized in such a way, and the genetic molecular marker related to the gastric cancer auxiliary diagnosis is a combination of rs4460629, rs4451581, rs11802956, rs236322, rs11890919, rs3771790, rs7425197, rs1403651, rs4685983, rs1504359, rs 5052037, rs1870563, rs 16997952, rs1564601, rs13195186, rs9341727, rs3857490, rs6959127, rs4305854, rs1052969, rs9791835, rs10952328, rs7782998, rs656248, rs378363, rs2460554, rs4751153, rs9329332, rs 20147, rs 356060606083, rs 27488, rs319284, rs2225046, rs 104837, rs 713083865, rs 713091752, rs 879117039, rs 2014487838 93393, rs 44933 93320 and rs 140349186520.

The invention also aims to provide a specific amplification primer of the genetic molecular marker related to the auxiliary diagnosis of gastric cancer, wherein the specific amplification primer has a sequence of SEQ ID NO. 1-SEQ ID NO. 166.

Another object of the present invention is to provide a specific probe primer for the genetic molecular marker related to gastric cancer auxiliary diagnosis, wherein the specific probe primer is: the primer sequence of rs4460629 is SEQ ID NO. 3-SEQ ID NO. 168.

The invention also aims to provide application of the genetic molecular marker related to gastric cancer auxiliary diagnosis in preparation of a gastric cancer auxiliary diagnosis kit.

The invention also aims to provide application of the genetic molecular marker related to gastric cancer auxiliary diagnosis in preparing a gastric cancer auxiliary diagnosis kit by using the specific amplification primer.

The invention also aims to provide application of the genetic molecular marker related to gastric cancer auxiliary diagnosis in preparing a gastric cancer auxiliary diagnosis kit by using the specific probe primer.

Another object of the present invention is to provide a gastric cancer auxiliary diagnostic kit comprising the genetic molecular marker related to the gastric cancer auxiliary diagnosis, which is used for detecting rs4460629, rs4451581, rs11802956, rs236322, rs11890919, rs3771790, rs7425197, rs1403651, rs4685983, rs1504359, rs 2035055057, rs1870563, rs 16997952, rs1564601, rs13195186, rs9341727, rs3857490, rs 6956959127, rs 58430912969, rs 9197835, rs10952328, rs 8297798, rs 65626548, rs2460554, rs4751153, rs9329332, rs 77610747, rs 3560606083, rs 35329286584, rs 222509286546, rs 2225094919483752, rs 10471752, 8787878720187348734838 and 008761 genes 93320 in peripheral blood DNA.

Further, the kit contains a specific amplification primer and a specific probe primer.

Further, the kit also comprises PCR reagents.

Further, the PCR reagent is Taq enzyme, dNTP mixed liquor, deionized water, standard substance and reference substance

By combining all the technical schemes, the invention has the advantages and positive effects that: the invention constructs a genetic risk prediction model and carries out genetic risk assessment on gastric cancer of target people. Provides a specific primer of the SNP marker and application thereof in preparing a gastric cancer auxiliary diagnosis kit. Provides an auxiliary diagnostic kit for gastric cancer.

The method is based on the contrast research design of the gastric cancer cases of Chinese people, utilizes the data of gastric cancer whole genome association research (GWAS), and adopts the strategy of combining minimum absolute contraction and selection operator (LASSO) with genetic algorithm to screen out a group of SNPs sites closely related to the gastric cancer morbidity risk from the whole genome; on the basis, a genetic risk prediction model is constructed, and the efficiency of predicting the gastric cancer onset risk by SNPs loci is evaluated in external data; finally, the gastric cancer auxiliary diagnosis kit is prepared, and technical support is provided for early diagnosis and prevention of gastric cancer.

The invention prepares the genetic marker kit for assisting gastric cancer diagnosis, is expected to lay a foundation for screening, individual prevention and treatment of high risk groups of gastric cancer in China and provides a decision basis. The SNP genetic marker is different from the traditional biomarker, has good stability and is easy to detect. The gastric cancer auxiliary diagnosis kit is beneficial to clinicians to quickly master the genetic risk of patients with gastric cancer, carries out early diagnosis, individualized prevention and treatment, and provides decision basis for screening and intervention of high-risk groups of gastric cancer.

Drawings

In order to more clearly illustrate the technical solutions of the embodiments of the present application, the drawings needed to be used in the embodiments of the present application will be briefly described below, and it is obvious that the drawings described below are only some embodiments of the present application, and it is obvious for those skilled in the art that other drawings can be obtained from the drawings without creative efforts.

FIG. 1 is a schematic diagram of genetic loci for susceptibility to gastric cancer screened based on LASSO algorithm provided in the present invention;

in the figure: a: LASSO coefficients for different Lambda; b: obtaining SNPs frequency number graphs based on LASSO models of different Lambda; c: the area under the ROC curve of different gastric cancer GRS models constructed based on the SNPs frequency; AUC: area under ROC curve.

FIG. 2 is a schematic diagram of genetic loci for gastric cancer susceptibility screened based on genetic algorithm provided in the embodiment of the present invention;

in the figure: a: obtaining SNPs frequency number graphs of optimal 50 sets based on a genetic algorithm; b: the area under the ROC curve of different gastric cancer GRS models constructed based on the SNPs frequency; AUC: area under ROC curve.

FIG. 3 is a schematic diagram illustrating the evaluation of a gastric cancer genetic risk prediction model according to an embodiment of the present invention;

in the figure: a: calibrating a curve; b: an ROC curve; AUC: area under ROC curve.

Detailed Description

In order to make the objects, technical solutions and advantages of the present invention more apparent, 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 merely illustrative of the invention and are not intended to limit the invention.

Aiming at the problems in the prior art, the invention provides a genetic molecular marker related to gastric cancer auxiliary diagnosis and application thereof, and the invention is described in detail below with reference to the accompanying drawings.

The technical solution of the present invention is further described below with reference to the accompanying drawings.

The invention provides a group of SNP genetic markers related to gastric cancer onset risk prediction, which are combinations of rs4460629, rs4451581, rs11802956, rs236322, rs11890919, rs3771790, rs7425197, rs1403651, rs4685983, rs1504359, rs2035057, rs1870563, rs 16997952, rs1564601, rs13195186, rs9341727, rs3857490, rs6959127, rs4305854, rs1052969, rs9791835, rs10952328, rs7782998, rs656248, rs378363, rs 6024554, rs4751153, rs9329332, rs 10747, rs 3532606083, rs 27488, rs319284, rs2225046, rs10483947, rs 6871752, rs875339, rs 309115, rs 939335, rs 10387838, and rs 4444838 20.

The invention relates to a specific amplification primer of an SNP genetic marker, which comprises the following components: the primer sequence of rs4460629 is SEQ ID NO.1 and SEQ ID NO. 2; the primer sequences of rs4451581 are SEQ ID NO.5 and SEQ ID NO. 6; the primer sequence of rs11802956 is SEQ ID NO.9 and SEQ ID NO. 10; the primer sequence of rs236322 is SEQ ID NO.13 and SEQ ID NO. 14; the primer sequence of rs11890919 is SEQ ID NO.17 and SEQ ID NO. 18; the primer sequence of rs3771790 is SEQ ID NO.21 and SEQ ID NO. 22; the primer sequence of rs7425197 is SEQ ID NO.25 and SEQ ID NO. 26; the primer sequence of rs1403651 is SEQ ID NO.29 and SEQ ID NO. 30; the primer sequence of rs4685983 is SEQ ID NO.33 and SEQ ID NO. 34; the primer sequences of rs1504359 are SEQ ID NO.37 and SEQ ID NO. 38; the primer sequence of rs2035057 is SEQ ID NO.41 and SEQ ID NO. 42; the primer sequence of rs1870563 is SEQ ID NO.45 and SEQ ID NO. 46; the primer sequence of rs 16997952 is SEQ ID NO.49 and SEQ ID NO. 50; the primer sequences of rs1564601 are SEQ ID NO.53 and SEQ ID NO. 54; the primer sequences of rs13195186 are SEQ ID NO.57 and SEQ ID NO. 58; the primer sequence of rs9341727 is SEQ ID NO.61 and SEQ ID NO. 62; the primer sequences of rs3857490 are SEQ ID NO.65 and SEQ ID NO. 66; the primer sequences of rs6959127 are SEQ ID NO.69 and SEQ ID NO. 70; the primer sequence of rs4305854 is SEQ ID NO.73 and SEQ ID NO. 74; the primer sequence of rs1052969 is SEQ ID NO.77 and SEQ ID NO. 78; the primer sequences of rs9791835 are SEQ ID NO.81 and SEQ ID NO. 82; the primer sequence of rs10952328 is SEQ ID NO.85 and SEQ ID NO. 86; the primer sequence of rs7782998 is SEQ ID NO.89 and SEQ ID NO. 90; the primer sequence of rs656248 is SEQ ID NO.93 and SEQ ID NO. 94; the primer sequence of rs378363 is SEQ ID NO.97 and SEQ ID NO. 98; the primer sequence of rs2460554 is SEQ ID NO.101 and SEQ ID NO. 102; the primer sequences of rs4751153 are SEQ ID NO.105 and SEQ ID NO. 106; the primer sequence of rs9329332 is SEQ ID NO.109 and SEQ ID NO. 110; the primer sequences of rs10777647 are SEQ ID NO.113 and SEQ ID NO. 114; the primer sequence of rs35326083 is SEQ ID NO.117 and SEQ ID NO. 118; the primer sequence of rs17027488 is SEQ ID NO.121 and SEQ ID NO. 122; the primer sequences of rs319284 are SEQ ID NO.125 and SEQ ID NO. 126; rs2225046 has the primer sequences SEQ ID NO.129 and SEQ ID NO. 130; the primer sequence of rs10483947 is SEQ ID NO.133 and SEQ ID NO. 134; the primer sequence of rs7168752 is SEQ ID NO.137 and SEQ ID NO. 138; the primer sequence of rs875339 is SEQ ID NO.141 and SEQ ID NO. 142; the primer sequence of rs3093315 is SEQ ID NO.145 and SEQ ID NO. 146; the primer sequence of rs918655 is SEQ ID NO.149 and SEQ ID NO. 150; the primer sequence of rs348793 is SEQ ID NO.153 and SEQ ID NO. 154; the primer sequence of rs17000838 is SEQ ID NO.157 and SEQ ID NO. 158; the primer sequence of rs1034420 is SEQ ID NO.161 and SEQ ID NO. 162; the primer sequences of rs2019061 are SEQ ID NO.165 and SEQ ID NO.166

The specific probe primer of the SNP genetic marker of the invention is as follows: the primer sequence of rs4460629 is SEQ ID NO.3 and SEQ ID NO. 4; the primer sequences of rs4451581 are SEQ ID NO.7 and SEQ ID NO. 8; the primer sequence of rs11802956 is SEQ ID NO.11 and SEQ ID NO. 12; the primer sequence of rs236322 is SEQ ID NO.15 and SEQ ID NO. 16; the primer sequences of rs11890919 are SEQ ID NO.19 and SEQ ID NO. 20; the primer sequence of rs3771790 is SEQ ID NO.23 and SEQ ID NO. 24; the primer sequence of rs7425197 is SEQ ID NO.27 and SEQ ID NO. 28; the primer sequence of rs1403651 is SEQ ID NO.31 and SEQ ID NO. 32; the primer sequence of rs4685983 is SEQ ID NO.35 and SEQ ID NO. 36; the primer sequences of rs1504359 are SEQ ID NO.39 and SEQ ID NO. 40; the primer sequence of rs2035057 is SEQ ID NO.43 and SEQ ID NO. 44; the primer sequence of rs1870563 is SEQ ID NO.47 and SEQ ID NO. 48; the primer sequence of rs 16997952 is SEQ ID NO.51 and SEQ ID NO. 52; the primer sequences of rs1564601 are SEQ ID NO.55 and SEQ ID NO. 56; the primer sequences of rs13195186 are SEQ ID NO.59 and SEQ ID NO. 60; the primer sequence of rs9341727 is SEQ ID NO.63 and SEQ ID NO. 64; the primer sequences of rs3857490 are SEQ ID NO.67 and SEQ ID NO. 68; the primer sequences of rs6959127 are SEQ ID NO.71 and SEQ ID NO. 72; the primer sequence of rs4305854 is SEQ ID NO.75 and SEQ ID NO. 76; the primer sequence of rs1052969 is SEQ ID NO.79 and SEQ ID NO. 80; the primer sequences of rs9791835 are SEQ ID NO.83 and SEQ ID NO. 84; rs10952328 has the primer sequence of SEQ ID NO.87 and SEQ ID NO. 88; the primer sequence of rs7782998 is SEQ ID NO.91 and SEQ ID NO. 92; the primer sequence of rs656248 is SEQ ID NO.95 and SEQ ID NO. 96; the primer sequence of rs378363 is SEQ ID NO.99 and SEQ ID NO. 100; the primer sequence of rs2460554 is SEQ ID NO.103 and SEQ ID NO. 104; the primer sequence of rs4751153 is SEQ ID NO.107 and SEQ ID NO. 108; the primer sequence of rs9329332 is SEQ ID NO.111 and SEQ ID NO. 112; the primer sequences of rs10777647 are SEQ ID NO.115 and SEQ ID NO. 116; the primer sequence of rs35326083 is SEQ ID NO.119 and SEQ ID NO. 120; the primer sequence of rs17027488 is SEQ ID NO.123 and SEQ ID NO. 124; the primer sequence of rs319284 is SEQ ID NO.127 and SEQ ID NO. 128; rs2225046 has the primer sequences SEQ ID NO.131 and SEQ ID NO. 132; the primer sequence of rs10483947 is SEQ ID NO.135 and SEQ ID NO. 136; the primer sequence of rs7168752 is SEQ ID NO.139 and SEQ ID NO. 140; the primer sequence of rs875339 is SEQ ID NO.143 and SEQ ID NO. 144; the primer sequence of rs3093315 is SEQ ID NO.147 and SEQ ID NO. 148; the primer sequence of rs918655 is SEQ ID NO.151 and SEQ ID NO. 152; the primer sequence of rs348793 is SEQ ID NO.155 and SEQ ID NO. 156; the primer sequence of rs17000838 is SEQ ID NO.159 and SEQ ID NO. 160; the primer sequence of rs1034420 is SEQ ID NO.163 and SEQ ID NO. 164; the primer sequences of rs2019061 are SEQ ID NO.167 and SEQ ID NO.168

The SNP genetic marker disclosed by the invention is applied to the construction of a genetic risk prediction model and the preparation of a gastric cancer auxiliary diagnosis kit.

The invention discloses application of a specific amplification primer of an SNP genetic marker in preparation of a gastric cancer auxiliary diagnosis kit.

The specific probe primer of the SNP genetic marker is applied to the preparation of a gastric cancer auxiliary diagnosis kit.

The invention provides a gastric cancer auxiliary diagnostic kit, which is used for detecting rs4460629, rs4451581, rs11802956, rs236322, rs11890919, rs3771790, rs7425197, rs1403651, rs4685983, rs1504359, rs2035057, rs1870563, rs 16997952, rs1564601, rs13195186, rs9341727, rs3857490, rs6959127, rs4305854, rs1052969, rs9791835, rs10952328, rs7782998, rs656248, rs378363, rs2460554, rs4751153, rs9329332, rs10777647, rs35326083, rs 170488, rs 3184, rs 22246, rs 104947, rs7168752, rs 538739, rs 30538715, rs 911705, rs 20187838 87838, 10344838 and 9334420 in peripheral blood DNA.

The stomach cancer auxiliary diagnosis kit contains the specific amplification of the SNP genetic marker and a probe primer; also comprises reagents commonly used in PCR, such as Taq enzyme, dNTP mixed solution, deionized water and the like; and standards and controls.

(1) Collecting samples: determining sample inclusion and exclusion criteria, and collecting blood samples meeting the criteria by the system;

(2) genotype detection and site screening: selecting gastric cancer cases and health controls thereof, acquiring individual genotype data by using a whole-genome high-density SNP chip, and identifying SNPs related to the gastric cancer morbidity risk by using a strategy of combining LASSO and a genetic algorithm;

(3) and (3) evaluating a model: constructing a genetic risk prediction model based on SNPs identified to have risk effects, and judging the calibration degree and the discrimination degree of the model by using a calibration curve and a receiver operating characteristic curve (ROC) in an external data set so as to detect the prediction capability of risk SNPs sites on the gastric cancer onset risk;

(4) preparation of the gastric cancer auxiliary diagnosis kit: and constructing an auxiliary diagnosis kit based on the screened SNP genetic marker.

The technical effects of the present invention will be described in detail with reference to experiments.

The experimental method comprises the following steps:

1. collecting study objects

(1) Pathologically confirmed cases of gastric cancer;

(2) a healthy control;

the present invention includes 1835 gastric cancer cases and 2613 healthy controls (training set: 1625 cases and 2100 controls; test set: 210 cases and 513 controls) to identify risk sites.

2. Extracting peripheral blood genome DNA by phenol-chloroform method, and performing conventional method. 20-50 ng/. mu.l DNA can be obtained usually, and the purity (the ratio of ultraviolet 260OD to 280 OD) is 1.6-2.0.

3. Whole genome SNPs locus detection in training set and primary screening of risk locus

(1) Taking a whole genome DNA sample of a subject in a training set, wherein the whole genome DNA sample comprises 1625 cases and 2100 controls;

(2) carrying out genotyping by adopting an Illumina Human 660W-Quad Chips genotyping chip;

(3) carrying out genotype filling on training set data by adopting IMPUTE2 software;

(4) comparing the distribution difference of each genotype in the gastric cancer cases and the contrast in the training set by fitting logistic regression analysis, and screening inclusion sites by taking the relevance P value of less than 0.01 as a standard;

(5) and primarily screening the sites related to the gastric cancer morbidity risk by adopting a LASSO algorithm strategy.

4. TaqMan MGB probe method genotyping and risk site determination for single SNP in test set

(1) Taking DNA samples in a test set, wherein the DNA samples comprise 210 cases and 513 controls;

(2) designing specific amplification primers and probe primers of a single SNP;

(3) performing PCR amplification reaction;

(4) and further determining the sites related to the gastric cancer onset risk by using a genetic algorithm based on the sites preliminarily screened in the training set.

5. Construction and evaluation of genetic risk prediction model

(1) SNPs loci identified based on the above strategy and closely related to gastric cancer onset risk, including rs4460629, rs4451581, rs11802956, rs236322, rs11890919, rs3771790, rs7425197, rs1403651, rs4685983, rs1504359, rs2035057, rs1870563, rs 16997952, rs1564601, rs13195186, rs9341727, rs3857490, rs 916959127, rs4305854, rs1052969, rs9791835, rs10952328, rs7782998, rs656248, rs378363, rs2460554, rs4751153, rs 932977647, rs 35606083, rs 170488, rs319284, rs 22246, rs10483947, rs 71752, rs 7187533039, rs 93393315, rs 915, rs 34329087838, 10344838, and 50838 10320;

(2) a weighted genetic risk score model (wGRS model) was constructed with LASSO regression coefficients as weights.

(3) And (3) performing risk assessment on the test set samples by using a wGRS model, and evaluating the calibration degree and the discrimination degree of the model by using a calibration curve and an ROC curve so as to detect the prediction capability of the identified risk SNPs on the stomach cancer onset risk.

6. Preparation of gastric cancer auxiliary diagnosis kit

The diagnostic kit comprises the screened SNPs (rs4460629, rs4451581, rs11802956, rs236322, rs11890919, rs3771790, rs7425197, rs1403651, rs4685983, rs1504359, rs2035057, rs1870563, rs 16997952, rs1564601, rs13195186, rs9341727, rs3857490, rs 916959127, rs4305854, rs1052969, rs9791835, rs10952328, rs7782998, rs656248, rs378363, rs2460554, rs4751153, rs9329332, rs10777647, rs35326083, rs17027488, rs319284, rs2225046, rs10483947, rs7168752, rs875339, rs 93330915, rs 3486593, rs 17034838, 103838 and 10320). The diagnostic reagent comprises specific amplification and probe primers of the SNP genetic marker; also comprises reagents commonly used in PCR, such as Taq enzyme, dNTP mixed solution, deionized water and the like; and standards and controls.

7. Statistical analysis

The additive model of logistic regression was used to analyze the intensity of association of SNPs with the risk of gastric cancer while adjusting confounding variables (e.g., gender, age). And screening SNPs sites associated with the gastric cancer onset risk from the whole genome perspective by adopting a strategy of combining LASSO with a genetic algorithm.

The genetic risk prediction model was fitted by calculating wGRS. The method comprises the following basic steps:

(1) quantitative scoring is carried out on three genotypes of each SNP, for example, the wild homozygous type is '0', the heterozygous type is '1', the homozygous mutant type is '2', and the effect scoring of all loci is adjusted to be positive correlation;

(2) the weight coefficient of each SNP is the regression coefficient obtained in the LASSO regression model, and the construction equation is as follows: wGRS 4460629 × 0.395+ rs4451581 × 0.188+ rs11802956 × 0.049+ rs236322 × 0.102+ rs11890919 × 0.081+ rs3771790 × 0.039+ rs7425197 × 0.113+ rs1403651 × 0.11+ rs4685983 × 0.096+ rs1504359 × 0.09+ rs2035057 × 0.156+ rs1870563 × 0.111+ rs 9797 × 0.157+ rs1564601 × 0.058+ rs 1319519510.073 + rs 41727 × 0.123+ rs3857490 × 0.167+ rs6959127 × 0.114+ rs 203584300.112 × 0.0522969 × 0.9719 + rs 979197919719 × 0.058+ rs 1319164048 + rs 3583579263 × 0.9 × 6092608363 × 0.0919 × 0.9 + rs 64048 × 6092609264048 + rs 64048 × 609264048 + us 92609264048 × 609264048 + us 9264048 × 0.09579 + rs 64048 × 09579 × 0.0919 × 0.9 × 0964048 + rs 64048 × 0.9 × 0.05 × 0964048 + us 92470.0964048 + us 92470.300 × 0.095 × 095 × 0.300 × 0.0919 × 0.8 + rs 64048 × 0.300 × 0.8 × 09579 + rs 64048 × 0.8 × 0.300 × 0964048 × 09579 + rs 6405 × 0.8 + us 64048 × 0.9 + rs 6405 × 0919 × 0.8 + rs 6405 ×;

(3) the predicted performance of the GRS model was assessed using the calibration curve and the area under the ROC curve (AUC).

All statistical analyses were done using PLINK1.90 and R3.5.1 software. The statistical significance P value was 0.05 and both were two-sided.

The results show that:

(1) the GRS model is continuously fitted based on the importance score obtained by LASSO regression, cross-validated AUC is used as an evaluation index, 1076 gastric cancer genetic loci are initially screened in a training set, and the AUC reaches 1 (shown in figure 1).

(2) By adopting a genetic algorithm, acquiring an optimal 50 variable sets by taking AUC of a test set as an index, continuously fitting a GRS model based on the frequency of the locus in the 50 variable sets, and finally finding that the AUC of the GRS model constructed by 42 genetic loci in the test set reaches the highest value (see figure 2), wherein the AUC comprises rs4460629, rs4451581, rs11802956, rs236322, rs 11890919919919919, rs3771790, rs7425197, rs1403651, rs4685983, rs 4315059, rs2035057, rs1870563, rs 169971699716, rs 1564604601, rs13195186, rs 9341727727, rs 385769569527, rs4305854, rs1052969, rs9791835, rs10952328, rs7782998, rs656248, rs 952 83952 952 8363, rs 6060554, rs4751153, rs 29332, rs 2910777647, rs 35323535488, rs 318346608383, rs 20182984, rs 2017782939, rs 448746 and rs 4483752, and rs 448746 (see tables 3491348746 and 3473752).

(3) And constructing GRS based on the screened 42 gastric cancer genetic loci, and constructing a gastric cancer onset risk prediction model by a logistic regression method. Based on the calibration curve and the ROC curve, the model is found to have better calibration degree (goodness of fit test P value is 0.866) and discrimination degree (AUC)_{Training set}＝0.672；AUC_{Test set}0.7, see fig. 3).

Based on the above results, the present inventors prepared a gastric cancer auxiliary diagnostic kit comprising primers specific to the identified 42 SNPs and other reagents.

In general, the gastric cancer auxiliary diagnosis kit prepared by the specific primers of the 42 SNPs is helpful for clinicians to quickly master the genetic risk of patients with diseases, and provides powerful support for timely taking treatment measures.

The technical solution of the present invention is further described with reference to the following specific examples.

EXAMPLE 1 Collection of samples and data interpretation

Training set: the inventor obtains the stomach cancer GWAS data of Chinese population from a genotype and phenotype database (dbGaP, phs000361.v1.p1), wherein the data come from a digestive tract tumor genetic project and a nutritional intervention experimental project in Lin county in Shanxi, and comprise 1625 cases and 2100 healthy controls.

And (3) test set: the inventor collects and arranges gastric cancer blood samples from local hospitals of Nanjing, Shanghai and Xuzhou and the like in 2010 to 2018, wherein the samples comprise 210 gastric cancer samples and 513 controls of health examination in hospitals at the same time, and collects related epidemiological and clinical data.

Example 2 Whole genome scanning of SNPs in peripheral blood DNA in training set

Genotyping was performed using Illumina Human 660W-Quad Chips in 1625 gastric cancer cases and 2100 healthy controls meeting the requirements. The method comprises the following specific steps:

(1) preparation of lysate: 40 portions of the mixture of 219.72g of sucrose, 2.02g of magnesium chloride and 20ml of TrissHcl solution were mixed and the volume of the mixture was adjusted to 2000ml by using the TrisHcl solution. (2) Add lysis solution to peripheral blood in 2ml cryopreserved tube, reverse and mix well. (3) Removing red blood cells: adding 5ml centrifuge tube to 4ml scale with lysis solution, mixing, centrifuging at 4000rpm for 10min, and discarding supernatant. And 4ml of lysis solution is added into the precipitate, mixed evenly again, washed once, centrifuged at 4000rpm for 10 minutes, and the supernatant is discarded. (4) Preparing an extraction solution: each 300ml of the solution contains 122.5ml of 0.2M sodium chloride, 14.4ml of 0.5M ethylenediaminetetraacetic acid, 15ml of 10% sodium lauryl sulfate and 148.1ml of double distilled water. (5) DNA extraction: to the resulting precipitate, 1ml of the extract and 8. mu.l of proteinase K were added, mixed well with shaking on a shaker, and then incubated overnight in a water bath at 37 ℃. (6) Protein removal: 1ml of saturated phenol was added and mixed well, centrifuged at 4000rpm for 10 minutes and the supernatant was transferred to a new 5ml centrifuge tube. The supernatant was added with a mixture of chloroform and isoamyl alcohol (chloroform: isoamyl alcohol: 24:1, v/v) at the same volume, and after mixing well, the mixture was centrifuged at 4000rpm for 10 minutes, and the supernatant was collected and put into two 1.5ml centrifuge tubes, respectively. (7) DNA precipitation: adding 60 μ l of 3M sodium acetate into the supernatant, adding ice anhydrous ethanol with the same volume as the supernatant, shaking up and down to obtain white flocculent precipitate, and centrifuging at 12000rpm for 10 min. (8) DNA washing: adding ice anhydrous ethanol 1ml into the precipitate, centrifuging at 12000rpm for 10min, and discarding the supernatant. And finally placing the mixture in a clean and dry environment for evaporation. (9) And (3) measuring the concentration: 20-50 ng/. mu.l DNA can be obtained usually, and the purity (the ratio of ultraviolet 260OD to 280 OD) is 1.6-2.0. (10) Whole genome scanning: whole genome scans were performed on a Human 660W-Quad Chips chip. (11) Adopting IMPUTE2 software to fill in the genotype; (12) data analysis and processing: screening SNPs with significant differences from a training set case group and a healthy control group by fitting a logistic regression model, and screening inclusion sites by taking a relevance P value of less than 0.01 as a standard; further adopting a LASSO algorithm strategy to preliminarily screen the sites related to the gastric cancer onset risk.

Example 3 TaqMan probe method genotyping of Single SNP in test set

Corresponding tests were carried out in 210 cases and 513 controls which met the requirements.

(1) The DNA extraction method was as above. (2) Genotyping by TaqMan probe real-time PCR method:

firstly, designing probes and primers aiming at the initially screened sites in the training set, meeting the requirements of the probes and the primers and being capable of successfully typing. ② the primer dilution is 10 times of the working concentration, and the probe dilution is 20 times of the working concentration. Preparing real-timePCR reaction system: each 5. mu.l portion includes sterile double distilled water 1.25. mu.l, 1 XqqPCR Mix (THUNDER BERDProbe qPCR Mix, available from TOYOBD Co., Ltd.) 2.5. mu.l, each of the upstream and downstream primers (1 pmol/. mu.l) 0.25. mu.l, FAM probe (0.25 pmol/. mu.l) 0.125. mu.l, HEX probe (0.25 pmol/. mu.l) 0.125. mu.l, 1.25 XROX solution (0.25 pmol/. mu.l) 0.125. mu.l, and DNA template (10 ng/. mu.l) 0.5. mu.l. The prepared real-time PCR reaction system was added to a 384-well plate (available from AXYGEN, USA) through a discharge gun (available from Eppendorf, Germany) and subjected to a membrane sealing treatment. Typing SNPs: the 384-well plate with the sealed membrane is placed in ABI PRISM 7900HT type fluorescent quantitative PCR instrument for typing, and the experimental program is as follows: 1) activating enzyme at 95 deg.C for 2 min; 2) denaturing the DNA at 95 ℃ for 15 s; 3) the primers and probes were annealed and extended at 60 ℃ for 60s for 40 cycles. Sixthly, carrying out genotyping by using SDS 2.4 software. Where blue and red represent two different homozygotes, green represents heterozygote, gray represents negative control (NTC), and x represents typing failure, respectively. Analysis of data: and further determining the sites related to the gastric cancer onset risk by using a genetic algorithm based on the sites preliminarily screened in the training set.

Example 4 a genetic risk prediction model was constructed using wGRS, a wGRS model was constructed based on the above identified 42 risk SNPs sites, using LASSO regression coefficients as weights, and evaluated using calibration curves and ROC curves to evaluate the risk sites for the risk of gastric cancer. The results showed that 42 SNPs were identified (rs4460629, rs4451581, rs11802956, rs236322, rs11890919, rs3771790, rs7425197, rs1403651, rs4685983,rs1504359, rs2035057, rs1870563, rs 16997952, rs1564601, rs13195186, rs9341727, rs3857490, rs6959127, rs4305854, rs1052969, rs9791835, rs10952328, rs7782998, rs656248, rs378363, rs2460554, rs4751153, rs9329332, rs10777647, rs35326083, rs17027488, rs319284, rs2225046, rs10483947, rs7168752, rs875339, rs3093315, rs918655, rs348793, rs17000838, rs 4420 and rs 20110361) can better distinguish gastric cancer cases from controls (see table 1), and the GRS model has better calibration degree (goodness of fit P value ═ 0.auc 866) and differentiation degree (AUC 103866)_{Training set}＝0.672；AUC_{Test set}0.7, see fig. 3), suggesting that these 42 genetic loci are better able to predict the genetic risk of gastric cancer development.

Example 5 preparation of gastric cancer auxiliary diagnostic kit, the kit contains a batch of SNPs specific amplification primers and specific probe primers (see Table 2), and also includes PCR commonly used reagents, such as Taq enzyme, dNTP mixed solution, deionized water, and the like. And standards and controls. Compared with other diagnostic instruments, the kit has the advantages of simplicity, high stability and capability of predicting disease states and genetic risks. Therefore, the kit is proposed to be put into clinical work, and decision basis is provided for screening and intervening of high-risk people with gastric cancer.

Table 142 basic information of SNPs sites associated with gastric cancer risk

^aBased on NCBI genome build 37(hg 19);^ba reference/effect allele; c from thousand people genome project data (china + japan);^dLASSO regression coefficient

TABLE 2.42 typing primer information for SNPs sites associated with gastric cancer Risk

Note: f: forward Primer, upstream Primer; r: reverse Primer, downstream Primer; FAM and HEX: fluorescence signals of different alleles.

The above description is only for the purpose of illustrating the present invention and the appended claims are not to be construed as limiting the scope of the invention, which is intended to cover all modifications, equivalents and improvements that are within the spirit and scope of the invention as defined by the appended claims.

Sequence listing

<110> Nanjing university of medical science

<120> gastric cancer auxiliary diagnosis related genetic molecular marker and application thereof

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<213> Artificial Sequence (Artificial Sequence)

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<213> Artificial Sequence (Artificial Sequence)

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<213> Artificial Sequence (Artificial Sequence)

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<212>DNA

<213> Artificial Sequence (Artificial Sequence)

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<212>DNA

<213> Artificial Sequence (Artificial Sequence)

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<213> Artificial Sequence (Artificial Sequence)

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<212>DNA

<213> Artificial Sequence (Artificial Sequence)

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<212>DNA

<213> Artificial Sequence (Artificial Sequence)

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<213> Artificial Sequence (Artificial Sequence)

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<212>DNA

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<212>DNA

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<212>DNA

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<212>DNA

<213> Artificial Sequence (Artificial Sequence)

<400>43

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<400>44

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<212>DNA

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<212>DNA

<213> Artificial Sequence (Artificial Sequence)

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<212>DNA

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<212>DNA

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<212>DNA

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<400>50

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<212>DNA

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<212>DNA

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<212>DNA

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<212>DNA

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<212>DNA

<213> Artificial Sequence (Artificial Sequence)

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<212>DNA

<213> Artificial Sequence (Artificial Sequence)

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<212>DNA

<213> Artificial Sequence (Artificial Sequence)

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<212>DNA

<213> Artificial Sequence (Artificial Sequence)

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<212>DNA

<213> Artificial Sequence (Artificial Sequence)

<400>60

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<212>DNA

<213> Artificial Sequence (Artificial Sequence)

<400>61

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<212>DNA

<213> Artificial Sequence (Artificial Sequence)

<400>62

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<212>DNA

<213> Artificial Sequence (Artificial Sequence)

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<212>DNA

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<400>64

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<212>DNA

<213> Artificial Sequence (Artificial Sequence)

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<212>DNA

<213> Artificial Sequence (Artificial Sequence)

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<212>DNA

<213> Artificial Sequence (Artificial Sequence)

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<212>DNA

<213> Artificial Sequence (Artificial Sequence)

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<212>DNA

<213> Artificial Sequence (Artificial Sequence)

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<212>DNA

<213> Artificial Sequence (Artificial Sequence)

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<212>DNA

<213> Artificial Sequence (Artificial Sequence)

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<212>DNA

<213> Artificial Sequence (Artificial Sequence)

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<212>DNA

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<212>DNA

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<400>76

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<212>DNA

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<212>DNA

<213> Artificial Sequence (Artificial Sequence)

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<212>DNA

<213> Artificial Sequence (Artificial Sequence)

<400>82

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<400>83

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<212>DNA

<213> Artificial Sequence (Artificial Sequence)

<400>84

ccatgcggtc tgg 13

<210>85

<211>25

<212>DNA

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<400>85

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<210>86

<211>22

<212>DNA

<213> Artificial Sequence (Artificial Sequence)

<400>86

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<210>87

<211>18

<212>DNA

<213> Artificial Sequence (Artificial Sequence)

<400>87

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<210>88

<211>18

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<400>88

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<210>89

<211>18

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<400>89

ccagccttgc cttttcca 18

<210>90

<211>23

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<400>90

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<210>91

<211>17

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<400>91

ctttgcatat ggttcag 17

<210>92

<211>17

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<400>92

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<210>93

<211>27

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<400>93

catagactgc tcccataagt atttcct 27

<210>94

<211>23

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<400>94

tttgaccacg gatgaagaat tct 23

<210>95

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<400>95

ccacaattga ccttc 15

<210>96

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<400>96

cacaattgac attctccaga 20

<210>97

<211>25

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<400>97

aacaaaaatc gcaagagtac caact 25

<210>98

<211>27

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<400>98

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<210>99

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<400>99

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<210>100

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<400>100

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<210>101

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<400>101

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<210>102

<211>19

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<400>102

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<210>103

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<400>103

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<210>104

<211>13

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<400>104

ccccaggcgg ctg 13

<210>105

<211>24

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<400>105

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<210>106

<211>26

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<400>106

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<210>107

<211>17

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<400>107

tttgccctat cacgaaa 17

<210>108

<211>16

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<400>108

ttgccctatc acaaaa 16

<210>109

<211>21

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<400>109

catggaaaca gaagcccaaa g 21

<210>110

<211>26

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<400>110

ttcccatatc catcatctga ataaaa 26

<210>111

<211>19

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<400>111

aagcataaga tctgggtgt 19

<210>112

<211>21

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<400>112

aagcataaaa tctgggtgta g 21

<210>113

<211>31

<212>DNA

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<400>113

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<210>114

<211>25

<212>DNA

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<400>114

actgacagca cttagacata ttcca 25

<210>115

<211>23

<212>DNA

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<400>115

ttgatataat tttctttccc tcg 23

<210>116

<211>24

<212>DNA

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<400>116

ttgatataat tttttttccc tcgc 24

<210>117

<211>26

<212>DNA

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<400>117

cctctcctgg aatacagtta cctgtt 26

<210>118

<211>26

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<400>118

gcagatttca gctcagtatg agaaag 26

<210>119

<211>20

<212>DNA

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<400>119

aggctctttc aatcgactgt 20

<210>120

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<212>DNA

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<400>120

tctttcaatc tactgtct 18

<210>121

<211>26

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<400>121

tggagtaatg aagttttaag tgctca 26

<210>122

<211>32

<212>DNA

<213> Artificial Sequence (Artificial Sequence)

<400>122

gcatgactac actatattaa taaatgaaac cc 32

<210>123

<211>20

<212>DNA

<213> Artificial Sequence (Artificial Sequence)

<400>123

aactctttta cagcctaatg 20

<210>124

<211>20

<212>DNA

<213> Artificial Sequence (Artificial Sequence)

<400>124

aactctttta tagcctaatg 20

<210>125

<211>28

<212>DNA

<213> Artificial Sequence (Artificial Sequence)

<400>125

ggatgaacgg aatatacaaa gtattgaa 28

<210>126

<211>25

<212>DNA

<213> Artificial Sequence (Artificial Sequence)

<400>126

tgttccaccc acattaaaaa aatct 25

<210>127

<211>15

<212>DNA

<213> Artificial Sequence (Artificial Sequence)

<400>127

acaaagcaca gagcc 15

<210>128

<211>15

<212>DNA

<213> Artificial Sequence (Artificial Sequence)

<400>128

aaagcacaga accct 15

<210>129

<211>27

<212>DNA

<213> Artificial Sequence (Artificial Sequence)

<400>129

ggagaaaata agggaaagag ctctaga 27

<210>130

<211>29

<212>DNA

<213> Artificial Sequence (Artificial Sequence)

<400>130

cttgtcatgg aattagtaaa ggtgtgtat 29

<210>131

<211>14

<212>DNA

<213> Artificial Sequence (Artificial Sequence)

<400>131

caagtgcggt gcca 14

<210>132

<211>14

<212>DNA

<213> Artificial Sequence (Artificial Sequence)

<400>132

caagtgcgat gcca 14

<210>133

<211>30

<212>DNA

<213> Artificial Sequence (Artificial Sequence)

<400>133

aatcagggta aacatagtaa atgacatagg 30

<210>134

<211>27

<212>DNA

<213> Artificial Sequence (Artificial Sequence)

<400>134

cagcaggatg ttgtgatgta aactatt 27

<210>135

<211>21

<212>DNA

<213> Artificial Sequence (Artificial Sequence)

<400>135

tagactttct gttataccct c 21

<210>136

<211>19

<212>DNA

<213> Artificial Sequence (Artificial Sequence)

<400>136

caagctatag actttccgt 19

<210>137

<211>27

<212>DNA

<213> Artificial Sequence (Artificial Sequence)

<400>137

tttgtcattt gagctgttac tgtcttt 27

<210>138

<211>28

<212>DNA

<213> Artificial Sequence (Artificial Sequence)

<400>138

gatgagataa tgtgggtcaa tagatgag28

<210>139

<211>16

<212>DNA

<213> Artificial Sequence (Artificial Sequence)

<400>139

ccataaggtg ctgagc 16

<210>140

<211>19

<212>DNA

<213> Artificial Sequence (Artificial Sequence)

<400>140

ttaccataaa gtgctgagc 19

<210>141

<211>25

<212>DNA

<213> Artificial Sequence (Artificial Sequence)

<400>141

ccccatgata tccctatttt ctcca 25

<210>142

<211>25

<212>DNA

<213> Artificial Sequence (Artificial Sequence)

<400>142

gagtggagat agaaggggag aattc 25

<210>143

<211>19

<212>DNA

<213> Artificial Sequence (Artificial Sequence)

<400>143

tatggagaat cggtactta 19

<210>144

<211>20

<212>DNA

<213> Artificial Sequence (Artificial Sequence)

<400>144

tatggagaat tggtacttac 20

<210>145

<211>23

<212>DNA

<213> Artificial Sequence (Artificial Sequence)

<400>145

tttgccaaaa tcagtcctgt ttt 23

<210>146

<211>22

<212>DNA

<213> Artificial Sequence (Artificial Sequence)

<400>146

cagaacttgt cggtggagtg aa 22

<210>147

<211>15

<212>DNA

<213> Artificial Sequence (Artificial Sequence)

<400>147

tgctggaact agctc 15

<210>148

<211>15

<212>DNA

<213> Artificial Sequence (Artificial Sequence)

<400>148

tgctggaact atctc 15

<210>149

<211>20

<212>DNA

<213> Artificial Sequence (Artificial Sequence)

<400>149

tgggctgaaa tgttgctttg 20

<210>150

<211>21

<212>DNA

<213> Artificial Sequence (Artificial Sequence)

<400>150

cagaagttcc ccgtcatatg c 21

<210>151

<211>16

<212>DNA

<213> Artificial Sequence (Artificial Sequence)

<400>151

agatggacaa tacgac 16

<210>152

<211>16

<212>DNA

<213> Artificial Sequence (Artificial Sequence)

<400>152

agatggacaa tacaac 16

<210>153

<211>24

<212>DNA

<213> Artificial Sequence (Artificial Sequence)

<400>153

cattttgcat cttcgtggtc atga 24

<210>154

<211>25

<212>DNA

<213> Artificial Sequence (Artificial Sequence)

<400>154

gatgatcatg ggagaggaag gtaaa 25

<210>155

<211>16

<212>DNA

<213> Artificial Sequence (Artificial Sequence)

<400>155

actctcccac tccact 16

<210>156

<211>14

<212>DNA

<213> Artificial Sequence (Artificial Sequence)

<400>156

actctcccgc tcca 14

<210>157

<211>16

<212>DNA

<213> Artificial Sequence (Artificial Sequence)

<400>157

cccaggctgg ctgcaa16

<210>158

<211>21

<212>DNA

<213> Artificial Sequence (Artificial Sequence)

<400>158

tgctgtgaca gggtgaatga g 21

<210>159

<211>16

<212>DNA

<213> Artificial Sequence (Artificial Sequence)

<400>159

ctcagcaaat ccgtca 16

<210>160

<211>16

<212>DNA

<213> Artificial Sequence (Artificial Sequence)

<400>160

ctcagcaaat ccatca 16

<210>161

<211>21

<212>DNA

<213> Artificial Sequence (Artificial Sequence)

<400>161

cccaaagtgc tgggattaca g 21

<210>162

<211>27

<212>DNA

<213> Artificial Sequence (Artificial Sequence)

<400>162

ccttccagct ttatattagt gacaaca 27

<210>163

<211>21

<212>DNA

<213> Artificial Sequence (Artificial Sequence)

<400>163

ctacttctac ttattatctt t 21

<210>164

<211>22

<212>DNA

<213> Artificial Sequence (Artificial Sequence)

<400>164

tgctacttct acttattata tt 22

<210>165

<211>25

<212>DNA

<213> Artificial Sequence (Artificial Sequence)

<400>165

aataaaggca acatctcaac aaggt 25

<210>166

<211>19

<212>DNA

<213> Artificial Sequence (Artificial Sequence)

<400>166

gtcccttgct tgcctggat 19

<210>167

<211>19

<212>DNA

<213> Artificial Sequence (Artificial Sequence)

<400>167

acaaattgag gatacagtg 19

<210>168

<211>18

<212>DNA

<213> Artificial Sequence (Artificial Sequence)

<400>168

acaaattgag gacacagt 18

Claims

1. A genetic molecular marker related to gastric cancer auxiliary diagnosis is a combination of rs4460629, rs4451581, rs11802956, rs236322, rs11890919, rs3771790, rs7425197, rs1403651, rs4685983, rs1504359, rs 5052032032032037, rs1870563, rs 16997952, rs 1561, rs13195186, rs9341727, rs3857490, rs6959127, rs4305854, rs1052969, rs9791835, rs10952328, rs7782998, rs656248, rs378363, rs2460554, rs4751153, rs9329332, rs 10747, rs 3560606083, rs 27488, rs319284, rs 22246, rs 1048330507, rs 7168309130865, rs 714530865, rs 5391752, rs 107918715, rs 20132448793, rs 443493393 and rs 1403493320.

2. The specific amplification primer for gastric cancer auxiliary diagnosis related genetic molecular marker according to claim 1, wherein the specific amplification primer is specific amplification primer

The primer sequence of rs4460629 is SEQ ID NO.1 and SEQ ID NO. 2;

the primer sequences of rs4451581 are SEQ ID NO.5 and SEQ ID NO. 6;

the primer sequence of rs11802956 is SEQ ID NO.9 and SEQ ID NO. 10;

the primer sequence of rs236322 is SEQ ID NO.13 and SEQ ID NO. 14;

the primer sequence of rs11890919 is SEQ ID NO.17 and SEQ ID NO. 18;

the primer sequence of rs3771790 is SEQ ID NO.21 and SEQ ID NO. 22;

the primer sequence of rs7425197 is SEQ ID NO.25 and SEQ ID NO. 26;

the primer sequence of rs1403651 is SEQ ID NO.29 and SEQ ID NO. 30;

the primer sequence of rs4685983 is SEQ ID NO.33 and SEQ ID NO. 34;

the primer sequences of rs1504359 are SEQ ID NO.37 and SEQ ID NO. 38;

the primer sequence of rs2035057 is SEQ ID NO.41 and SEQ ID NO. 42;

the primer sequence of rs1870563 is SEQ ID NO.45 and SEQ ID NO. 46;

the primer sequence of rs 16997952 is SEQ ID NO.49 and SEQ ID NO. 50;

the primer sequences of rs1564601 are SEQ ID NO.53 and SEQ ID NO. 54;

the primer sequences of rs13195186 are SEQ ID NO.57 and SEQ ID NO. 58;

the primer sequence of rs9341727 is SEQ ID NO.61 and SEQ ID NO. 62;

the primer sequences of rs3857490 are SEQ ID NO.65 and SEQ ID NO. 66;

the primer sequence of rs6959127 is SEQ ID NO.69 and SEQ ID NO. 70;

the primer sequence of rs4305854 is SEQ ID NO.73 and SEQ ID NO. 74;

the primer sequence of rs1052969 is SEQ ID NO.77 and SEQ ID NO. 78;

the primer sequences of rs9791835 are SEQ ID NO.81 and SEQ ID NO. 82;

the primer sequence of rs10952328 is SEQ ID NO.85 and SEQ ID NO. 86;

the primer sequence of rs7782998 is SEQ ID NO.89 and SEQ ID NO. 90;

the primer sequence of rs656248 is SEQ ID NO.93 and SEQ ID NO. 94;

the primer sequence of rs378363 is SEQ ID NO.97 and SEQ ID NO. 98;

the primer sequence of rs2460554 is SEQ ID NO.101 and SEQ ID NO. 102;

the primer sequences of rs4751153 are SEQ ID NO.105 and SEQ ID NO. 106;

the primer sequence of rs9329332 is SEQ ID NO.109 and SEQ ID NO. 110;

the primer sequences of rs10777647 are SEQ ID NO.113 and SEQ ID NO. 114;

the primer sequence of rs35326083 is SEQ ID NO.117 and SEQ ID NO. 118;

the primer sequence of rs17027488 is SEQ ID NO.121 and SEQ ID NO. 122;

the primer sequences of rs319284 are SEQ ID NO.125 and SEQ ID NO. 126;

rs2225046 has the primer sequences SEQ ID NO.129 and SEQ ID NO. 130;

the primer sequence of rs10483947 is SEQ ID NO.133 and SEQ ID NO. 134;

the primer sequence of rs7168752 is SEQ ID NO.137 and SEQ ID NO. 138;

the primer sequence of rs875339 is SEQ ID NO.141 and SEQ ID NO. 142;

the primer sequence of rs3093315 is SEQ ID NO.145 and SEQ ID NO. 146;

the primer sequences of rs918655 are SEQ ID NO.149 and SEQ ID NO. 150;

the primer sequence of rs348793 is SEQ ID NO.153 and SEQ ID NO. 154;

the primer sequence of rs17000838 is SEQ ID NO.157 and SEQ ID NO. 158;

the primer sequence of rs1034420 is SEQ ID NO.161 and SEQ ID NO. 162;

the primer sequence of rs2019061 is SEQ ID NO.165 and SEQ ID NO. 166.

3. The specific probe primer for gastric cancer auxiliary diagnosis related genetic molecular marker according to claim 1, wherein the specific probe primer is

The primer sequence of rs4460629 is SEQ ID NO.3 and SEQ ID NO. 4;

the primer sequences of rs4451581 are SEQ ID NO.7 and SEQ ID NO. 8;

the primer sequence of rs11802956 is SEQ ID NO.11 and SEQ ID NO. 12;

the primer sequence of rs236322 is SEQ ID NO.15 and SEQ ID NO. 16;

the primer sequences of rs11890919 are SEQ ID NO.19 and SEQ ID NO. 20;

the primer sequence of rs3771790 is SEQ ID NO.23 and SEQ ID NO. 24;

the primer sequence of rs7425197 is SEQ ID NO.27 and SEQ ID NO. 28;

the primer sequence of rs1403651 is SEQ ID NO.31 and SEQ ID NO. 32;

the primer sequence of rs4685983 is SEQ ID NO.35 and SEQ ID NO. 36;

the primer sequence of rs1504359 is SEQ ID NO.39 and SEQ ID NO. 40;

the primer sequence of rs2035057 is SEQ ID NO.43 and SEQ ID NO. 44;

the primer sequence of rs1870563 is SEQ ID NO.47 and SEQ ID NO. 48;

the primer sequence of rs 16997952 is SEQ ID NO.51 and SEQ ID NO. 52;

the primer sequences of rs1564601 are SEQ ID NO.55 and SEQ ID NO. 56;

the primer sequences of rs13195186 are SEQ ID NO.59 and SEQ ID NO. 60;

the primer sequence of rs9341727 is SEQ ID NO.63 and SEQ ID NO. 64;

the primer sequences of rs3857490 are SEQ ID NO.67 and SEQ ID NO. 68;

the primer sequence of rs6959127 is SEQ ID NO.71 and SEQ ID NO. 72;

the primer sequence of rs4305854 is SEQ ID NO.75 and SEQ ID NO. 76;

the primer sequence of rs1052969 is SEQ ID NO.79 and SEQ ID NO. 80;

the primer sequences of rs9791835 are SEQ ID NO.83 and SEQ ID NO. 84;

rs10952328 has the primer sequence of SEQ ID NO.87 and SEQ ID NO. 88;

the primer sequence of rs7782998 is SEQ ID NO.91 and SEQ ID NO. 92;

the primer sequence of rs656248 is SEQ ID NO.95 and SEQ ID NO. 96;

the primer sequence of rs378363 is SEQ ID NO.99 and SEQ ID NO. 100;

the primer sequence of rs2460554 is SEQ ID NO.103 and SEQ ID NO. 104;

the primer sequence of rs4751153 is SEQ ID NO.107 and SEQ ID NO. 108;

the primer sequence of rs9329332 is SEQ ID NO.111 and SEQ ID NO. 112;

the primer sequences of rs10777647 are SEQ ID NO.115 and SEQ ID NO. 116;

the primer sequence of rs35326083 is SEQ ID NO.119 and SEQ ID NO. 120;

the primer sequence of rs17027488 is SEQ ID NO.123 and SEQ ID NO. 124;

the primer sequences of rs319284 are SEQ ID NO.127 and SEQ ID NO. 128;

rs2225046 has the primer sequences SEQ ID NO.131 and SEQ ID NO. 132;

the primer sequence of rs10483947 is SEQ ID NO.135 and SEQ ID NO. 136;

the primer sequences of rs7168752 are SEQ ID NO.139 and SEQ ID NO. 140;

the primer sequence of rs875339 is SEQ ID NO.143 and SEQ ID NO. 144;

the primer sequence of rs3093315 is SEQ ID NO.147 and SEQ ID NO. 148;

the primer sequence of rs918655 is SEQ ID NO.151 and SEQ ID NO. 152;

the primer sequence of rs348793 is SEQ ID NO.155 and SEQ ID NO. 156;

the primer sequence of rs17000838 is SEQ ID NO.159 and SEQ ID NO. 160;

the primer sequence of rs1034420 is SEQ ID NO.163 and SEQ ID NO. 164;

the primer sequence of rs2019061 is SEQ ID NO.167 and SEQ ID NO. 168.

4. Use of the gastric cancer auxiliary diagnosis related genetic molecular marker of claim 1 in the preparation of a gastric cancer auxiliary diagnosis kit.

5. The use of the gastric cancer auxiliary diagnosis related genetic molecular marker of claim 1 in the preparation of a gastric cancer auxiliary diagnosis kit by using specific amplification primers.

6. The use of the genetic molecular marker related to gastric cancer auxiliary diagnosis according to claim 1 in the preparation of a gastric cancer auxiliary diagnosis kit by using a specific probe primer.

7. A gastric cancer auxiliary diagnostic kit comprising genetic molecular markers related to the auxiliary diagnosis of gastric cancer as defined in claim 1, wherein the gastric cancer auxiliary diagnostic kit is used for detecting rs4460629, rs4451581, rs11802956, rs236322, rs11890919, rs3771790, rs7425197, rs1403651, rs4685983, rs1504359, rs2035057, rs1870563, rs 16997952, rs1564601, rs13195186, rs9341727, rs3857490, rs 695695916959127, rs 5843054, rs 2969, rs 9197835, rs10952328, rs 8297798, rs 65626548, rs2460554, rs4751153, rs9329332, rs 77610747, rs 3560606083, rs 353286584, rs 31509246, rs 2225094919446, rs 10471752, 8787752, 2018787348727, rs 44933 and 34933 9193, rs 44349127, rs 35606083752, rs 44915739 and rs 34915739 and RS 349120 genes in peripheral blood DNA.

8. The gastric cancer auxiliary diagnostic kit according to claim 7, which comprises a specific amplification primer and a specific probe primer.

9. The gastric cancer auxiliary diagnostic kit according to claim 7 or 8, wherein the kit further comprises PCR reagents.

10. The gastric cancer auxiliary diagnostic kit of claim 9, wherein the PCR reagent is Taq enzyme, dNTP mixture, deionized water, and standard and control.