A meQTL-SNPs biomarker associated with lung adenocarcinoma and its application

Abstract

The present application provides a meQTL-SNPs biomarker associated with lung adenocarcinoma and its application, including the application of meQTL-SNPs as a marker in the preparation of an auxiliary diagnostic kit for lung adenocarcinoma. The present application uses high-throughput technology to perform DNA methylation sequencing on a population, and then combines information from a large public meQTL database, and combines screening and verification from the bioinformatics level and the functional mechanism level. The obtained biomarker meQTL-SNPs is expected to provide assistance for the early diagnosis of patients with lung adenocarcinoma. The present application innovatively explores the role of meQTL-SNPs in the occurrence and development of lung adenocarcinoma, combines meQTL-SNPs, DNA methylation and gene expression, explores regulatory mechanisms, and provides a new basis for the early diagnosis of lung adenocarcinoma.

Description

Technical Field

[0001] The present application belongs to the field of biomedical technology, and specifically relates to a meQTL-SNPs biomarker associated with lung adenocarcinoma and its application. Background Art

[0002] Lung cancer is the second most common cancer. In men, lung cancer is the leading cause of cancer morbidity and mortality in men. In women, lung cancer ranks third in incidence, second only to breast cancer and colorectal cancer, and second only to breast cancer in mortality. Non-small cell lung cancer (NSCLC) is the most common subtype of lung cancer, accounting for about 85% of lung cancer cases, while lung adenocarcinoma (LUAD) and lung squamous cell carcinoma (LUSC) are the most common types of NSCLC. In recent decades, LUAD and LUSC have shown obvious differences in incidence trends. In China, the incidence of LUSC has shown a downward trend, with its proportion decreasing from 43.48% to 17.69%, while the incidence of LUAD has shown a significant upward trend, with its proportion increasing from 47.83% to 74.73%. Based on the trend of continued increase in incidence, the prevention of lung adenocarcinoma is of greater significance and remains one of the ongoing public health issues.

[0003] For lung cancer, smoking is the most well-known cause, but the correlation between LUAD and smoking is weaker than that of squamous cell lung carcinoma, and it is more closely related to non-smoking factors and genetic factors. DNA methylation is one of the key epigenetic regulatory modes and plays an important role in biological processes such as gene expression and cell differentiation. In addition, abnormal methylation is associated with the development of cancer, autoimmune diseases, neuropsychiatric diseases, and many other complex diseases. Studies have found some differentially expressed genes associated with epigenetic changes in DNA methylation in LUAD. Continuing to study the relationship between DNA methylation and susceptibility to lung adenocarcinoma, as well as the relationship between DNA methylation and the incidence of lung adenocarcinoma, will help provide targeted new prevention or treatment measures.

[0004] At the same time, another research factor that cannot be ignored among genetic factors is single nucleotide polymorphism (SNP), which is one of the most important factors determining individual genetic susceptibility. Genome-wide association studies (GWAS) have identified some SNPs associated with lung adenocarcinoma, but most of the loci found by GWAS are located in non-coding regions, which makes it difficult to elucidate the molecular mechanism of genetic variation. Quantitative trait loci (QTL) positioning, such as eQTL analysis, is one of the most common research strategies for evaluating the biological function of SNPs and has been proven to be a powerful tool for elucidating the relationship between SNPs and gene expression. In recent years, DNA methylation quantitative trait loci (meQTL), similar to eQTL, have also gradually attracted people's attention. meQTL is rich in functionally related features, including shared chromatin states, high-throughput chromosome conformation interactions, and associations with gene expression, metabolic variation, and clinical characteristics. It can link SNPs with DNA methylation and lung adenocarcinoma, providing new ideas for further studying the pathogenesis of lung adenocarcinoma. Summary of the invention

[0005] The present application provides a meQTL-SNPs biomarker associated with lung adenocarcinoma and its application to solve the above-mentioned technical problems.

[0006] In order to solve the above technical problems, a technical solution adopted in the present application is: use of meQTL-SNP as a marker in the preparation of a lung adenocarcinoma auxiliary diagnosis kit.

[0007] Further, the specific parameters of the meQTL-SNPs are as follows:

[0008]

[0009] Another technical solution adopted in the present application is: a lung adenocarcinoma auxiliary diagnosis kit, comprising a detection reagent, wherein the detection reagent is used to detect the above-mentioned marker.

[0010] Another technical solution adopted in this application is: a method for constructing a "SNP-DNA methylation-gene expression" diagnosis and treatment model, comprising:

[0011] S1. Determine the relationship between SNPs and DNA methylation;

[0012] S2. Detect DNA methylation level;

[0013] S3. Detect the expression level of the target gene LRRC2 to obtain the relationship between DNA methylation and gene expression.

[0014] The beneficial effects of this application are: This application uses high-throughput technology to sequence DNA methylation in the population, and then combines information from a large public meQTL database, and combines screening and verification from the bioinformatics level and the functional mechanism level. The obtained biomarker meQTL-SNPs is expected to provide assistance for the early diagnosis of patients with lung adenocarcinoma. This application innovatively explores the role of meQTL-SNPs in the occurrence and development of lung adenocarcinoma, combines meQTL-SNPs, DNA methylation and gene expression, understands the regulatory mechanism, and provides a new basis for the early diagnosis of lung adenocarcinoma. BRIEF DESCRIPTION OF THE DRAWINGS

[0015] Figure 1 is the differentially methylated CpG site map in Example 2 of the present application;

[0016] Figure 2 is the cancer and para-cancer gene expression graph in Example 5 of the present application;

[0017] Figure 3 is a relationship diagram between the SNP of Example 6 of the present application and the DNA methylation of the corresponding CpG site;

[0018] Figure 4 This is a methylation detection data diagram of cancer and adjacent tissues in Example 6 of the present application;

[0019] Figure 5 is a comparison chart of LRRC2 gene expression in the cancer and para-cancer gene detection data of Example 6 of the present application;

[0020] Figure 6 is the correlation expression diagram between cg09596674-LRRC2 in Example 6 of the present application;

[0021] Figure 7 This is the result diagram obtained by performing prognostic analysis on the target gene LRRC2 in Example 6 of the present application;

[0022] Figure 8 This is a summary diagram of the SNP-DNA methylation-gene expression pattern in Example 6 of the present application. DETAILED DESCRIPTION

[0023] In order to make the objectives, technical solutions and advantages of the present invention more clear, the present invention is further described in detail below in conjunction with specific embodiments.

[0024] In the following description, many specific details are set forth to facilitate a full understanding of the present invention. However, the present invention may also be implemented in other ways than those described herein. Therefore, the present invention is not limited to the specific embodiments of the following disclosure.

[0025] Application of meQTL-SNP as a marker in the preparation of auxiliary diagnostic kit for lung adenocarcinoma.

[0026] The specific parameters of meQTL-SNP (rs939408) are as follows:

[0027]

[0028] The present application also provides a lung adenocarcinoma auxiliary diagnosis kit, comprising a detection reagent, wherein the detection reagent is used to detect the above-mentioned marker.

[0029] The present application also provides a method for constructing a "SNP-DNA methylation-gene expression" diagnosis and treatment model, comprising the following steps:

[0030] S1. Determine the relationship between SNPs and DNA methylation;

[0031] S2. Detect DNA methylation level;

[0032] S3. Detect the expression level of the target gene LRRC2 to obtain the relationship between DNA methylation and gene expression.

[0033] meQTL-SNPs are associated with the risk of lung adenocarcinoma, are easy to detect, and are related to DNA methylation and the corresponding gene expression levels. They may have certain regulatory patterns, which will help explore the mechanism of lung adenocarcinoma and may provide new research clues for treatment options.

[0034] Example 1: Sample collection and data collation

[0035] The DNA methylation sequencing part included 10 lung adenocarcinoma cases and 10 adjacent adjacent tissue controls. The above samples were all from newly diagnosed lung adenocarcinoma cases confirmed by Nantong First People's Hospital, and all cases were confirmed by pathological histology. The baseline information of the above selected subjects is shown in Table 1.

[0036] In the validation phase, we selected the Female Lung Cancer in Asia GWAS (FLCCA) data, which included 3453 LUAD patients and 3710 control patients.

[0037] Table 1 Baseline information of selected subjects

[0038]

[0039] Example 2: Analysis of differential CpG sites

[0040] See also Figure 1 , Figure 1Medium deltabeta = β lung adenocarcinoma-β para-cancer; hypermethylated CpG: highly methylated CpG site; hypomethylated CpGs: low methylated CpG sites.

[0041] After quality control of the 850k sequencing results of cancer and adjacent tissues according to the above method, one cancer tissue sample with abnormal results was eliminated, and differential methylation analysis was performed between 9 cancer tissue samples and 10 adjacent tissue samples from patients with early lung adenocarcinoma. Based on the FDR less than 0.05, a total of 57,659 CpG sites with abnormally high methylation and 95,768 CpG sites with abnormally low methylation in patients with early lung adenocarcinoma were screened ( Figure 1 ); then, the screened abnormal differential methylation sites were intersected with the lung adenocarcinoma methylation data of TCGA (455 lung adenocarcinoma tissues and 32 adjacent tissues) that had also undergone quality control, and finally the target CpGs were obtained.

[0042] Example 3: Selection of functional meQTL-SNPs

[0043] The above data obtained from the laboratory experiment and the lung adenocarcinoma differential CpG sites obtained from the public database were further screened and processed, and the intersection was taken with two large public meQTL databases, namely the lung tissue (URL https: / / gtexportal.org / home / datasets) and the multi-ethnic blood database (URL https: / / zenodo.org / record / 5196216#.YRZ3TfJxe Uk), which achieved consistency at the tissue and blood levels. A total of 3987 target meQTLs were obtained, including 3634 SNPs and 3987 CpGs. Then, the correlation analysis and gene difference analysis of the above CpGs and gene expression were performed, and then the obtained candidate meQTL-SNPs were screened by MAF and LD methods, and finally 93 meQTL-SNPs were obtained. Subsequently, the FLCCA GWAS data was verified, and 7 confirmed meQTL-SNPs were obtained. The specific meQTL-SNPs information is shown in Table 2.

[0044] Table 2 Information of multiple candidate meQTL-SNPs

[0045]

[0046] Example 4: Logical verification

[0047] Based on the information obtained from the screening, we can know the changing trends between the SNPs and CpGs at the above 7 candidate sites, as well as the methylation levels obtained by sequencing the CpG sites. We can also know the correlation coefficients between the CpG sites and the corresponding gene expressions. Based on the prediction model SNP-DNA methylation-gene expression, we can infer the relationship between the SNP mutation and the risk of lung adenocarcinoma. At this time, we compare it with the OR value of the meQTL-SNP and the risk of lung adenocarcinoma obtained in the verification stage to see if there is any logic error. Finally, we obtained three meQTL-SNPs, and the information is shown in Table 3.

[0048] Table 3 Information of three candidate meQTL-SNPs

[0049]

[0050] Among them, OR and p value were calculated by FLCCA, and confounding factors such as age, gender and smoking were adjusted.

[0051] Example 5: Experimental verification

[0052] See also Figure 2 qRT-PCR technology was used to verify the expression levels of the above three genes in the tissue samples of 850k sequencing batches. The primer sequences are as follows:

[0053] LRRC2:Forward:5'-CAAGTTGACCTACCTTCCCTATTCC-3';

[0054] LRRC2:Reverse:5'-GCCATCTTCACATTGGGCATTA-3';

[0055] MYOM2:Forward:5'-GAGAGACACACATTTGAAGAGCG-3';

[0056] MYOM2:Reverse:5'-TCCTGTACTTTCCCGGTTCAG-3'

[0057] SLC1A4:Forward:5'-CATGGACGGAGCAGCCATC-3';

[0058] SLC1A4:Reverse:5'-GGCAGTCACTAGAATGGTGAAAA-3';

[0059] β-act in:Forward:5'-CATGTACGTTGCTATCCAGGC-3';

[0060] β-act in:Reverse:5'-CTCCTTAATGTCACGCACGAT-3';

[0061] The experimental acquisition of LRRC2 gene is of great significance, such as Figure 2 As shown in the figure, rs939408-cg09596674-LRRC2 can be used as a marker for subsequent functional exploration. Wherein, normal: adjacent tissue; LUAD: lung adenocarcinoma tissue; ** indicates p < 0.01.

[0062] The results of the case-control study on the relationship between the final meQTL-SNP (rs939408) and the risk of lung adenocarcinoma are shown in Table 4. This site is expected to serve as a biomarker related to lung adenocarcinoma.

[0063] Table 4 Case-control study results on the relationship between rs939408 and the risk of lung adenocarcinoma

[0064]

[0065] Example 6: Preliminary construction of the "SNP-DNA methylation-gene expression" early diagnosis and treatment model

[0066] (1) See Figure 3 , through the large population meQTL database, we can clearly know the relationship between SNP and the corresponding CpG site DNA methylation. The rs939408-cg09596674 obtained in this application is a negatively correlated relationship ( Figure 3 ), rs939408 mutates, the genotype changes, and the DNA methylation level at the corresponding cg09596674 site also changes. By performing SNP typing on the blood samples of the testers, the methylation level of the corresponding site can be inferred.

[0067] (2) See Figure 4 The data of methylation detection in cancer and adjacent tissues clearly show the DNA methylation level of this site. The methylation level of cg09596674 in cancer is higher than that in adjacent tissues ( Figure 4 ), combined with the inference in step (1), evaluate the methylation level of this person. Figure 4 *** indicates p<0.001.

[0068] (3) See Figure 5-6 , cancer and paracancerous gene detection data showed that LRRC2 gene ( Figure 5 ) is expressed in cancer at a lower level than in the adjacent areas of cancer, and it may be a tumor suppressor gene that inhibits cancer. Figure 6), DNA methylation can affect gene expression. In treatment, the expression level of the corresponding gene LRRC2 is changed by affecting the level of methylation, thereby achieving the purpose of treating lung adenocarcinoma.

[0069] (4) The risk of disease in the population at the SNP site (rs939408) is shown in Table 4. Under the additive model, the AA genotype of rs939408 significantly reduced the risk of disease compared with the CC genotype (OR=0.89, p=0.019). The above indicates that the AA genotype has a protective effect and reduces the possibility of disease.

[0070] (5) See Figure 7 , the prognosis analysis of the screened target gene LRRC2 was performed, and the survival of lung adenocarcinoma was analyzed using the GSE68465 dataset in the GEO public database, and the result was HR=0.71, P=0.031 ( Figure 7 ). It means that the survival probability of people with high expression of LRRC2 gene is higher than that of people with low expression, and the difference is statistically significant. High expression of the above target genes is beneficial to the prognosis and survival of patients with lung adenocarcinoma.

[0071] (6) See Figure 8 , Summary of the “SNP-DNA methylation-gene expression” model ( Figure 8 ). This pattern reflects the connection between the various parts. Through the detection of the meQTL-SNP (rs939408) determined in this application, the situation of other parts can be inferred accordingly; by changing the DNA methylation level, the gene expression level can be changed accordingly, which can help the treatment of lung adenocarcinoma.

[0072] This application uses high-throughput technology to perform DNA methylation sequencing on the population, and then combines information from a large public meQTL database, combining screening and verification from the bioinformatics level and the functional mechanism level. The biomarker meQTL-SNPs obtained can provide assistance for the early diagnosis of patients with lung adenocarcinoma, in order to achieve clinical application value.

[0073] This application innovatively explores the role of meQTL-SNPs in the development of lung adenocarcinoma, combines meQTL-SNPs, DNA methylation and gene expression, explores regulatory mechanisms, provides new basis for early diagnosis of lung adenocarcinoma, achieves the prevention and control goal of "early screening, early diagnosis, early treatment", and provides a scientific basis for early personalized intervention of lung adenocarcinoma. In addition, the exploration of DNA methylation can provide effect index evaluation during the treatment process, can observe the treatment effect at any time, and may explore new treatment methods through this regulatory mechanism model. At the same time, this early diagnostic biomarker can be detected by providing 5ml of blood from the patient. The peripheral blood detection-related genomic technology is mature, reliable and convenient, which can minimize the trauma to the patient during the test.

[0074] The above description is only an embodiment of the present application and does not limit the patent scope of the present application. Any equivalent structure or equivalent process transformation made using the contents of the present application specification and drawings, or directly or indirectly used in other related technical fields, are also included in the patent protection scope of the present application.

Claims

1. Application of reagents for detecting meQTL-SNP site rs939408 in the preparation of auxiliary diagnostic kits for lung adenocarcinoma.

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