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 its application. Background Art

[0002] Lung adenocarcinoma is a type of lung cancer, classified as non-small cell lung cancer (NSCLC). It accounts for over half of all NSCLC cases and carries high morbidity and mortality. Traditional treatments for lung adenocarcinoma primarily rely on surgery, radiotherapy, and medications, with immunotherapy, targeted therapy, and antibody-drug conjugates (ADCs) emerging as treatments. However, advances in treatment methods have not improved prognosis.

[0003] Currently, PBMC is used for DNA methylation chip detection, with the main ones 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 advantageous populations. Although there are many detection indicators in existing technologies, it is expected that the problems of efficacy prediction and advantageous population screening will be solved. However, it has not achieved good clinical results; 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, and its related genes are C19 or f38; cg19313959, located at 2,902,708 bp on chromosome 12, and its related genes are 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, high methylation group, median survival time was 43.0 months;

[0020] β value <0.7620154, low methylation group, median survival time was 22.5 months;

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

[0022] β value ≥ 0.01045104, high methylation group, median survival time was 53.7 months;

[0023] β value < 0.01045104, low methylation group, median survival time was 23.9 months;

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

[0025] β value ≥ 0.7593206, high methylation group, median survival time was 39.9 months;

[0026] β value <0.7593206, low methylation group, median survival time was 20.9 months;

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

[0028] β value ≥ 0.4678614, high methylation group, median survival time was 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, high methylation group, median survival time was 13.2 months;

[0033] β value <0.6391096, low methylation group, median survival time was 37.2 months;

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

[0035] β value ≥ 0.01835568, high methylation group, median survival time was 43.0 months;

[0036] β value < 0.01835568, indicating 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, indicating the low methylation group, with a median survival time of 32.77 months.

[0040] Preferably, the test sample of the kit is genomic DNA from 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 genomic DNA of peripheral blood mononuclear cells, which is easy to obtain and has sufficient sample volume. It not only solves the problem of difficult acquisition and insufficient sample volume of existing pathological tissue, but also solves the problem of dynamic detection.

[0044] 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 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 the survival curve of different methylation levels of four specific methylation sites in the EGFR mutation-positive patient population;

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

[0049] Figure 5The relationship between the LUAD FKBP4 mRNA level in the TCGA database corresponding to the gene name ELN (elastin) of cg15224444 and the prognostic OS score (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 LUAD mRNA level and prognostic OS score in the TCGA database corresponding to the gene name ELN of cg25670864, ​​high expression indicates good prognosis), where n is the sample size;

[0051] Figure 7 For the EGFR gene-positive subgroup, Cox risk regression was performed based on these four specific differential Cigs (cg05802998, cg19313959, cg00685115, and cg15224444), a prognostic model was constructed, and the risk score of each sample was calculated, and then the survival curve was drawn;

[0052] Figure 8 For the EGFR gene-positive subgroup, Cox risk regression was performed based on these four specific differential Cigs (cg05802998, cg19313959, cg00685115, and cg15224444), a prognostic model was constructed, and the risk score of each sample was calculated, and then the ROC curve was drawn;

[0053] Figure 9 Survival analysis was performed on 89 patients with lung adenocarcinoma (Shanghai Xinchao) after immunohistochemistry for FKBP4;

[0054] Figure 10 Forest plot of clinical variables after FKBP4 immunohistochemistry was performed on 89 patients with lung adenocarcinoma (Shanghai Xinchao);

[0055] Figure 11 Cox risk regression was performed based on these three specific differential Cigs (cg25670864, ​​cg04490108, and cg17929042), a prognostic model was constructed, the risk score of each sample was calculated, and then the survival curve was drawn;

[0056] Figure 12 Cox risk regression was performed based on these three specific differential Cigs (cg25670864, ​​cg04490108, and cg17929042), a prognostic model was constructed, the risk score of each sample was calculated, and then the ROC curve was drawn. DETAILED DESCRIPTION

[0057] The technical solutions provided by the present invention are described in detail below with reference to the embodiments, but they should not be construed as limiting the scope of protection of the present invention.

[0058] Example 1

[0059] Between April 2014 and December 2017, peripheral blood mononuclear cells (PBMCs) were collected from 312 lung cancer patients in the Department of Respiratory Medicine at Henan Cancer Hospital before treatment. DNA was extracted and analyzed using an 850K methylation array. Methylation analysis was performed using the Champ package (default program) in R software (https: / / www.bioconductor.org / packages / release / bioc / html / ChAMP.html). Differentially methylated probes (DMPs), differentially methylated regions (DMRs), and differentially methylated blocks (DMBs) were obtained, and KEGG analysis was then performed. The results are shown in the figure. Figure 1 and Figure 2 shown.

[0060] 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: 97 patients with EGFR mutation-positive status and 118 patients with EGFR mutation-negative status.

[0061] The median OS was used as the dividing line to distinguish between groups with good and poor prognosis. The Champ package in R software was used to obtain DMPs according to the Champ analysis process and perform KEGG analysis. For details, see the Champ package manual. The top five significantly differentially methylated sites (DMPs) were selected based on corrected P values. The surv_cutpoint function in the "survminer" package in R software was used to determine the optimal cutoff value for each methylation site.

[0062] The results are as follows Figure 3 and 4 As shown, in the EGFR mutation-positive patient population

[0063] For cg05802998, the optimal cutoff value was 0.7620154. Patients with a β value ≥ this cutoff value were classified as hypermethylated, with a median survival of 43.0 months. Patients with a β value < this cutoff value were classified as hypomethylated, with a median survival of 22.5 months.

[0064] For cg00685115, the optimal cutoff value was 0.01045104. Patients with a β value ≥ this cutoff value were classified as the hypermethylated group, with a median survival of 53.7 months. Patients with a β value < this cutoff value were classified as the hypomethylated group, with a median survival of 23.9 months.

[0065] For cg19313959, the optimal cutoff value was 0.7593206. Patients with a β value ≥ this cutoff value were classified as hypermethylated, with a median survival of 39.9 months. Patients with a β value < this cutoff value were classified as hypomethylated, with a median survival of 20.9 months.

[0066] For cg15224444, the optimal cutoff value was 0.4678614. A β value ≥ this cutoff value indicated the hypermethylation group, with a median survival of 49.4 months. A β value < this cutoff value indicated the hypomethylation group, with a median survival of 22.5 months.

[0067] In the EGFR mutation-negative patient population

[0068] For cg25670864, ​​the optimal cutoff value was 0.6391096. Patients with a β value ≥ this cutoff value were classified as hypermethylated, with a median survival of 13.2 months. Patients with a β value < this cutoff value were classified as hypomethylated, with a median survival of 37.2 months.

[0069] For cg04490108, the optimal cutoff value was 0.01835568. Patients with a β value ≥ this cutoff value were classified as hypermethylated, with a median survival of 43.0 months. Patients with a β value < this cutoff value were classified as hypomethylated, with a median survival of 17.3 months.

[0070] cg17929042

[0071] The optimal cutoff value was 0.9322722. Patients with a β value ≥ this cutoff value were classified as the hypermethylated group, with a median survival of 8.32 months. Patients with a β value < this cutoff value were classified as the hypomethylated group, with a median survival of 32.77 months.

[0072] Since the TCGA data set only contains data from the 450K methylation array and no methylation sites found using the 850K methylation array, we used the genes where the specific methylation sites were located to search the TCGA database for the relationship between the corresponding mRNA and survival, in order to verify the correlation between the specific methylation sites and prognosis.

[0073] In patients with EGFR mutation-positive

[0074] cg05802998 corresponds to the database gene name C19or f38

[0075] cg00685115 corresponds to the database gene name CRY1

[0076] cg19313959 corresponds to the database gene name FKBP4 (LUAD mRNA levels in the TCGA database are significantly correlated with OS, and high expression has a poor prognosis).

[0077] 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 2). Figure 5 ).

[0078] Differences in methylation sites may affect mRNA levels. This methylation site is located in the target gene and therefore has the potential to affect FKBP4 mRNA.

[0079] cg15224444 corresponds to the gene name ELN elastin in the database (LUAD mRNA levels are correlated with OS in the TCGA database, and high expression has a good prognosis).

[0080] The TCGA database showed that LUAD ELN mRNA levels were associated with OS (5-year survival rates were 45% and 32% in the high- and low-expression groups, respectively). This methylation site, cg15224444, is located in the target gene and may affect LUAD ELN mRNA levels.

[0081] Cox risk regression was performed based on these four specific differential Cigs to construct a prognostic model and calculate the risk score for each sample. Survival curves were then drawn and divided into high-risk group and low-risk group according to the median value as the cutoff value. The survival curves of the two groups showed significant differences ( Figure 7 ) and ROC curve, the prognostic model was used to predict prognosis, and the test efficiency was excellent ( Figure 8 ), 89 patients with lung adenocarcinoma (Shanghai Xinchao Biotechnology Co., Ltd.) underwent FKBP4 immunohistochemistry and survival analysis was performed. The survival curves of patients with high and low FKBP4 immunohistochemistry expression were significantly different ( Figure 9 ); Forest plot of clinical variables shows that even after correction of key clinical factors, FKBP4 immunohistochemical expression can still predict survival. Patients in the FKBP4 low expression group have a better prognosis ( Figure 10 ).

[0082] In the EGFR mutation-negative patient population

[0083] cg25670864, ​​corresponding database gene name ELN (LUAD mRNA level in TCGA database is correlated with OS, high expression has a good prognosis, specific survival curves are as follows Figure 6 );

[0084] cg04490108, corresponding database gene name RPRD2;

[0085] cg17929042, corresponding to the database gene name AUTS2.

[0086] Based on these three specific difference Cigs, Cox risk regression was performed to construct a prognostic model, calculate the risk score of each sample, and then draw the survival curve and ROC curve respectively, as shown in Figure 2. Figure 11 and Figure 12 As shown, in EGFR-negative patients, a prognostic model was constructed using Cox regression to calculate a risk score. Using the median as the cutoff, the patients were divided into a high-risk group and a low-risk group. The survival curves of the two groups showed significant differences. This prognostic model has excellent efficacy in predicting prognosis.

[0087] As can be seen from the above examples, 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, are more conducive to screening out the advantageous population, and further improve the effectiveness of treatment.

[0088] 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 principles of the present invention. These improvements and modifications should also be regarded as within 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, and its related genes are C19 or f38; cg19313959, located at 2,902,708 bp on chromosome 12, and its related genes are 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, high methylation group, median survival time was 43.0 months; β value <0.7620154, low methylation group, median survival time was 22.5 months; For the specific methylation site cg00685115, the optimal cutoff value is: 0.01045104; β value ≥ 0.01045104, high methylation group, median survival time was 53.7 months; β value < 0.01045104, low methylation group, median survival time was 23.9 months; For the specific methylation site cg19313959, the optimal cutoff value was 0.7593206; β value ≥ 0.7593206, high methylation group, median survival time was 39.9 months; β value <0.7593206, low methylation group, median survival time was 20.9 months; For the specific methylation site cg15224444, the optimal cutoff value is: 0.4678614; β value ≥ 0.4678614, high methylation group, median survival time was 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, high methylation group, median survival time was 13.2 months; β value <0.6391096, low methylation group, median survival time was 37.2 months; For the specific methylation site cg04490108, the optimal cutoff value is: 0.01835568; β value ≥ 0.01835568, high methylation group, median survival time was 43.0 months; β value < 0.01835568, indicating 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, indicating the low methylation group, with a median survival time of 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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