Biomarker for predicting prognosis of advanced lung adenocarcinoma and application of biomarker

Abstract

The invention provides a biomarker combination for predicting prognosis of advanced lung adenocarcinoma and application of the biomarker combination, and belongs to the technical field of disease prognosis prediction.The biomarker combination provided by the invention comprises one or more of specific methylation sites cg05802998, cg19313959, cg00685115, cg15224444, cg25670864, cg04490108 and cg17929042, and further comprises one or more of the specific methylation sites cg05802998, cg19313959, cg00685115, cg15224444, cg25670864, cg04490108 and cg17929042. According to the biomarker combination provided by the invention, in the detection process, an adopted detection sample is genome DNA of peripheral blood mononuclear cells, the detection sample is convenient to obtain, the sample size is sufficient, the problems that existing pathological tissues are not easy to obtain and the sample amount is insufficient are solved, and the problem of dynamic detection can also be solved; the prognosis time of the advanced lung adenocarcinoma patient can be predicted more conveniently and more accurately, screening of dominant people is facilitated, and the treatment effectiveness is further improved.

Description

Technical Field

[0001] The present invention belongs to the technical field of disease prognosis prediction, and in particular relates to a biomarker combination for predicting the prognosis of advanced lung adenocarcinoma and an application thereof. Background Art

[0002] Lung adenocarcinoma is a type of lung cancer and belongs to non-small cell carcinoma. Lung adenocarcinoma accounts for more than half of non-small cell lung cancer and has high morbidity and mortality. Currently, the traditional treatment methods for lung adenocarcinoma are mainly surgical treatment, radiotherapy and drug therapy, and immunotherapy, targeted therapy and antibody-drug conjugate ADC therapy have been newly added. However, the progress of treatment methods has not improved its prognosis.

[0003] Currently, PBMC is used for DNA methylation chip detection, with the main force being the 850K chip and the 935K chip. Most studies focus on early screening and diagnosis of cancer, and have not solved the problem of prognosis prediction for clinically diagnosed patients. Especially with the increase in treatment options for advanced lung cancer, there is a lack of prediction of the efficacy of immunotherapy, targeted therapy, and antibody-drug conjugate ADC therapy, as well as screening of the superior population. Although there are many detection indicators in the existing technology, it is expected to solve the problems of efficacy prediction and superior population screening. However, it has not achieved a good clinical effect; especially for patients with advanced lung cancer, pathological tissue is not easy to obtain, and specimens for genetic testing and immunohistochemistry are often insufficient. Summary of the invention

[0004] In view of this, the object of the present invention is to provide a biomarker combination for predicting the prognosis of advanced lung adenocarcinoma and its application.

[0005] The present invention provides a biomarker for predicting the prognosis of advanced lung adenocarcinoma, comprising one or more of the specific methylation sites cg05802998, cg19313959, cg00685115, cg15224444, cg25670864, ​​cg04490108, and cg17929042;

[0006] In the EGFR mutation-positive patient population, including one or more of cg05802998, cg19313959, cg00685115, and cg15224444;

[0007] In the EGFR mutation-negative patient population, including one or more of cg25670864, ​​cg04490108, and cg17929042;

[0008] cg05802998, located at 10,967,043 bp on chromosome 19, the related gene is C19 or f38; cg19313959, located at 2,902,708 bp on chromosome 12, the related gene is RP11-885B4.1, RP4-816N1.3 or FKBP4;

[0009] cg00685115, located at 107486488 bp on chromosome 12, the related gene is CRY1 or RP11-797M17.1;

[0010] cg15224444, located at 73440688 bp on chromosome 7, and the related gene is ELN;

[0011] cg25670864, ​​located at 73457080 bp on chromosome 7, and the related gene is ELN;

[0012] cg04490108, located at 150337032 bp on chromosome 1, and the related gene is RPRD2;

[0013] cg17929042, located at 70200532bp on chromosome 7, and the related gene is AUTS2.

[0014] The present invention provides the use of a reagent for detecting the biomarker in preparing a kit for predicting the prognosis of advanced lung adenocarcinoma.

[0015] Preferably, the reagent includes a methylation detection chip or a methylation detection primer.

[0016] Preferably, the predicting of the prognosis of advanced lung adenocarcinoma includes predicting the prognosis survival time of advanced lung adenocarcinoma.

[0017] Preferred EGFR mutation-positive patient population:

[0018] For the specific methylation site cg05802998, the optimal cutoff value is: 0.7620154;

[0019] β value ≥ 0.7620154, which was the high methylation group, with a median survival time of 43.0 months;

[0020] β value <0.7620154, which is the low methylation group, with a median survival time of 22.5 months;

[0021] For the specific methylation site cg00685115, the optimal cutoff value is: 0.01045104;

[0022] β value ≥ 0.01045104, which is the high methylation group, with a median survival time of 53.7 months;

[0023] β value < 0.01045104, which is the low methylation group, with a median survival time of 23.9 months;

[0024] For the specific methylation site cg19313959, the optimal cutoff value was 0.7593206;

[0025] β value ≥ 0.7593206, which is the high methylation group, with a median survival time of 39.9 months;

[0026] β value <0.7593206, which is the low methylation group, with a median survival time of 20.9 months;

[0027] For the specific methylation site cg15224444, the optimal cutoff value is: 0.4678614;

[0028] β value ≥ 0.4678614, which is the high methylation group, with a median survival time of 49.4 months;

[0029] The β value was less than 0.4678614, which was the low methylation group, and the median survival time was 22.5 months.

[0030] Preferred, EGFR mutation-negative patient population:

[0031] For the specific methylation site cg25670864, ​​the optimal cutoff value is: 0.6391096;

[0032] β value ≥ 0.6391096, which is the high methylation group, with a median survival time of 13.2 months;

[0033] β value <0.6391096, which is the low methylation group, with a median survival time of 37.2 months;

[0034] For the specific methylation site cg04490108, the optimal cutoff value is: 0.01835568;

[0035] β value ≥ 0.01835568, which was the high methylation group, with a median survival time of 43.0 months;

[0036] β value < 0.01835568, which is the low methylation group, with a median survival time of 17.3 months;

[0037] For the specific methylation site cg17929042, the optimal cutoff value is: 0.9322722,

[0038] β value ≥ 0.9322722, which is the high methylation group, with a median survival time of 8.32 months;

[0039] The β value was less than 0.9322722, which was the low methylation group, and the median survival time was 32.77 months.

[0040] Preferably, the test sample of the kit is genomic DNA of peripheral blood mononuclear cells.

[0041] Compared with the prior art, the present invention has the following beneficial effects: the present invention provides a biomarker for predicting the prognosis of advanced lung adenocarcinoma, including one or more of the specific methylation sites cg05802998, cg19313959, cg00685115, cg15224444, cg25670864, ​​cg04490108, and cg17929042; in the EGFR mutation-positive patient population, including one or more of cg05802998, cg19313959, cg00685115, and cg15224444; in the EGFR mutation-negative patient population, including one or more of cg25670864, ​​cg04490108, and cg17929042.

[0042] The specific methylation sites provided by the present invention can accurately predict the prognosis survival time of advanced lung adenocarcinoma, which is consistent with the trend in the TCGA database.

[0043] Furthermore, the detection sample of the kit described in the present invention is the genomic DNA of peripheral blood mononuclear cells, which is easy to obtain and has a sufficient sample volume. It not only solves the problem that pathological tissues are difficult to obtain and the sample volume is insufficient, but also solves the problem of dynamic detection.

[0044] The biomarkers and kit provided by the present invention can more conveniently and accurately predict the prognosis time of patients with advanced lung adenocarcinoma, provide ideas for further research on advanced lung adenocarcinoma, and are more conducive to screening out advantageous populations and improving the effectiveness of treatment. BRIEF DESCRIPTION OF THE DRAWINGS

[0045] Figure 1 The KEGG analysis results of differentially methylated sites in the mutation-positive patient population;

[0046] Figure 2 The KEGG analysis results of differentially methylated sites in the mutation-negative patient population;

[0047] Figure 3 This is a survival curve of different methylation levels of four specific methylation sites in the EGFR mutation-positive patient population;

[0048] Figure 4 This is a survival curve of different methylation levels of three specific methylation sites in the EGFR mutation-negative patient population;

[0049] Figure 5is the relationship between the LUAD FKBP4 mRNA level and the prognostic OS score in the TCGA database corresponding to the gene name ELN (elastin) of cg15224444 (the 5-year survival rates of the high expression group and the low expression group were 23% and 46%, respectively), where n is the sample size;

[0050] Figure 6 is the relationship between the LUAD mRNA level and the prognostic OS score in the TCGA database corresponding to the gene name ELN of cg25670864, ​​high expression indicates a good prognosis), where n is the sample size. DETAILED DESCRIPTION

[0051] The technical solutions provided by the present invention are described in detail below in conjunction with the embodiments, but they should not be construed as limiting the protection scope of the present invention.

[0052] Example 1

[0053] From April 2014 to December 2017, peripheral blood mononuclear cells (PBMCs) were collected from 312 lung cancer patients before treatment in the Department of Respiratory Medicine, Henan Cancer Hospital, and DNA was extracted for 850K methylation chip detection. Methylation analysis was performed using the Champ package (default program) of R software (https: / / www.bioconductor.org / packages / release / bioc / html / ChAMP.html), and differential methylation probes (DMPs), differential methylation regions (DMRs), and differential methylation blocks (DMBs) were obtained, and then KEGG analysis was performed; the analysis results are shown in the figure. Figure 1 and Figure 2 shown.

[0054] Further research focused on lung adenocarcinoma, a major type of lung cancer. Among the 312 lung cancer patients, 174 had lung adenocarcinoma and were divided into two groups based on EGFR mutation status, including 97 EGFR mutation-positive patients and 118 EGFR mutation-negative patients.

[0055] The median OS was used as the dividing line to distinguish the two groups with good prognosis and poor prognosis. The Champ package of R software was run to obtain DMPs according to the Champ analysis process and perform KEGG analysis. For details, see the instructions of the Champ package. According to the corrected P value, the top five differential methylation sites (DMPs) were significantly selected. The surv_cutpoint function in the "survminer" package in R software was used to achieve the optimal cutoff value of the methylation site.

[0056] The results are as follows Figure 3 and 4 As shown, in the EGFR mutation-positive patient population

[0057] cg05802998, the best cutoff value is: 0.7620154. β value ≥ the cutoff value, it is the high methylation group, the median survival time is 43.0 months. β value < the cutoff value, it is the low methylation group, the median survival time is 22.5 months.

[0058] cg00685115, the best cutoff value is: 0.01045104. β value ≥ the cutoff value, it is the high methylation group, the median survival time is 53.7 months. β value < the cutoff value, it is the low methylation group, the median survival time is 23.9 months.

[0059] cg19313959, the best cutoff value is: 0.7593206. β value ≥ the cutoff value, it is the high methylation group, the median survival time is 39.9 months. β value < the cutoff value, it is the low methylation group, the median survival time is 20.9 months.

[0060] cg15224444, the best cutoff value is: 0.4678614. β value ≥ the cutoff value, it is the high methylation group, the median survival time is 49.4 months. β value < the cutoff value, it is the low methylation group, the median survival time is 22.5 months.

[0061] In the EGFR mutation-negative patient population

[0062] cg25670864, ​​the best cutoff value is: 0.6391096. β value ≥ the cutoff value, it is the high methylation group, the median survival time is 13.2 months. β value < the cutoff value, it is the low methylation group, the median survival time is 37.2 months.

[0063] cg04490108, the best cutoff value is: 0.01835568. β value ≥ this cutoff value, it is the high methylation group, the median survival time is 43.0 months. β value < this cutoff value, it is the low methylation group, the median survival time is 17.3 months.

[0064] cg17929042

[0065] The optimal cutoff value is: 0.9322722. β value ≥ the cutoff value, it is the high methylation group, and the median survival time is 8.32 months. β value < the cutoff value, it is the low methylation group, and the median survival time is 32.77 months.

[0066] Since there are only 450K methylation chip data in TCGA data, and no methylation sites found by 850K methylation chip data, we applied the genes where the specific methylation sites found above are located to search for the relationship between the mRNA corresponding to the gene and survival in the TCGA database to verify the correlation between the corresponding specific methylation sites and prognosis.

[0067] In the EGFR mutation-positive patient population

[0068] cg05802998 corresponds to the database gene name C19 or f38

[0069] cg00685115 corresponds to the database gene name CRY1

[0070] cg19313959 corresponds to the database gene name FKBP4 (the LUAD mRNA level in the TCGA database is significantly correlated with OS, and high expression has a poor prognosis).

[0071] The relationship between LUAD FKBP4 mRNA level and OS in the TCGA database (the 5-year survival rates of the high expression group and the low expression group were 23% and 46%, respectively, and the specific survival curves are shown in Figure 5 ).

[0072] Differences in methylation sites may affect mRNA levels. The methylation sites are located in the target gene and therefore have the potential to affect FKBP4 mRNA.

[0073] The gene name of cg15224444 in the corresponding database is ELN elastin (the LUAD mRNA level in the TCGA database is correlated with OS, and high expression has a good prognosis).

[0074] In the TCGA database, the LUAD ELN mRNA level and OS (the 5-year survival rates of the high expression group and the low expression group were 45% and 32%, respectively). The methylation site cg15224444 is located in the target gene and has the possibility of affecting the LUAD ELN mRNA level.

[0075] In the EGFR mutation-negative patient population

[0076] cg25670864, ​​corresponding to the database gene name ELN (the LUAD mRNA level in the TCGA database is related to OS, and high expression has a good prognosis. The specific survival curve is as follows Figure 6 );

[0077] cg04490108, corresponding to database gene name RPRD2;

[0078] cg17929042, corresponding to the database gene name AUTS2.

[0079] It can be seen from the above examples that the biomarkers and kits provided by the present invention can more conveniently and accurately predict the prognosis time of patients with advanced lung adenocarcinoma, provide ideas for further research on advanced lung adenocarcinoma, and are more conducive to screening out advantageous populations and further improving the effectiveness of treatment.

[0080] The above is only a preferred embodiment of the present invention. It should be pointed out that for ordinary technicians in this technical field, several improvements and modifications can be made without departing from the principle of the present invention. These improvements and modifications should also be regarded as the scope of protection of the present invention.

Claims

1. A biomarker for predicting the prognosis of advanced lung adenocarcinoma, characterized in that: Including one or more of the specific methylation sites cg05802998, cg19313959, cg00685115, cg15224444, cg25670864, ​​cg04490108, and cg17929042; In the EGFR mutation-positive patient population, including one or more of cg05802998, cg19313959, cg00685115, and cg15224444; In the EGFR mutation-negative patient population, including one or more of cg25670864, ​​cg04490108, and cg17929042; cg05802998, located at 10,967,043 bp on chromosome 19, the related gene is C19 or f38; cg19313959, located at 2,902,708 bp on chromosome 12, the related gene is RP11-885B4.1, RP4-816N1.3 or FKBP4; cg00685115, located at 107486488 bp on chromosome 12, the related gene is CRY1 or RP11-797M17.1; cg15224444, located at 73440688 bp on chromosome 7, and the related gene is ELN; cg25670864, ​​located at 73457080 bp on chromosome 7, and the related gene is ELN; cg04490108, located at 150337032 bp on chromosome 1, and the related gene is RPRD2; cg17929042, located at 70200532bp on chromosome 7, and the related gene is AUTS2.

2. Use of a reagent for detecting the biomarker according to claim 1 in preparing a kit for predicting the prognosis of advanced lung adenocarcinoma.

3. The use according to claim 2, characterized in that: The reagents include a methylation detection chip or a methylation detection primer.

4. The use according to claim 2, characterized in that: The predicting of the prognosis of advanced lung adenocarcinoma includes predicting the prognosis survival time of advanced lung adenocarcinoma.

5. The use according to claim 2, characterized in that: EGFR mutation-positive patient population: For the specific methylation site cg05802998, the optimal cutoff value is: 0.7620154; β value ≥ 0.7620154, which was the high methylation group, with a median survival time of 43.0 months; β value <0.7620154, which is the low methylation group, with a median survival time of 22.5 months; For the specific methylation site cg00685115, the optimal cutoff value is: 0.01045104; β value ≥ 0.01045104, which is the high methylation group, with a median survival time of 53.7 months; β value < 0.01045104, which is the low methylation group, with a median survival time of 23.9 months; For the specific methylation site cg19313959, the optimal cutoff value was 0.7593206; β value ≥ 0.7593206, which is the high methylation group, with a median survival time of 39.9 months; β value < 0.7593206, which is the low methylation group, with a median survival time of 20.9 months; For the specific methylation site cg15224444, the optimal cutoff value is: 0.4678614; β value ≥ 0.4678614, which is the high methylation group, with a median survival time of 49.4 months; The β value was less than 0.4678614, which was the low methylation group, and the median survival time was 22.5 months.

6. The use according to claim 2, characterized in that: EGFR mutation-negative patient population: For the specific methylation site cg25670864, ​​the optimal cutoff value is: 0.6391096; β value ≥ 0.6391096, which is the high methylation group, with a median survival time of 13.2 months; β value <0.6391096, which is the low methylation group, with a median survival time of 37.2 months; For the specific methylation site cg04490108, the optimal cutoff value is: 0.01835568; β value ≥ 0.01835568, which was the high methylation group, with a median survival time of 43.0 months; β value < 0.01835568, which is the low methylation group, with a median survival time of 17.3 months; For the specific methylation site cg17929042, the optimal cutoff value is: 0.9322722, β value ≥ 0.9322722, which is the high methylation group, with a median survival time of 8.32 months; The β value was less than 0.9322722, which was the low methylation group, and the median survival time was 32.77 months.

7. The use according to claim 2, characterized in that: The detection sample of the kit is genomic DNA of peripheral blood mononuclear cells.

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