Application of E33 region methylation level in evaluation of myeloblastoma prognosis products

Abstract

The invention belongs to the technical field of biomedicine, and particularly relates to application of an E33 region methylation level in evaluation of prognosis of myeloblastoma. The nucleotide sequence of the E33 region is as shown in SEQ ID NO: 1; the myeloblastoma comprises a G3 subtype myeloblastoma and / or a G4 subtype myeloblastoma. The invention finds that the low methylation state of the E33 region is directly associated with the prognosis of the patient suffering from the myeloblastoma Group3 / 4, the clinical result of the patient can be effectively predicted by detecting the methylation level of the E33 region, and a foundation is laid for the early prognosis evaluation and personalized treatment strategy of the patient suffering from the myeloblastoma Group3 / 4 by detecting the methylation level of the E33 region.

Description

Technical Field

[0001] The present invention belongs to the technical field of biomedicine, and specifically relates to the application of the methylation level of the E33 region in the prognosis evaluation of medulloblastoma. Background Art

[0002] Medulloblastoma (MB) is the most common malignant central nervous system tumor in children, accounting for 8-10% of childhood brain tumors. Early detection and early treatment can effectively improve the five-year survival rate of patients. Medulloblastoma is not a single disease, but a brain tumor composed of multiple different molecular subtypes. Currently, the generally recognized molecular subtypes of medulloblastoma mainly include 4 subtypes: WNT type (WNT subgroup), SHH type (Sonic Hedgehog Subgroup), Group3 type (Group3), and Group4 type (Group4). These subtypes are different in terms of treatment and prognosis, corresponding to different clinical strategies.

[0003] Currently, the alternative schemes for the prognosis evaluation of medulloblastoma mainly include analysis methods based on gene mutations, copy number variations, traditional epigenetic markers (such as DNA methylation profiles), RNA expression characteristics, and specific molecular markers (such as Myc amplification). These alternative schemes can provide prognostic information to a certain extent, especially for different subtypes of medulloblastoma, but usually have the following limitations: (1) Low prediction accuracy: A single gene mutation or copy number variation is difficult to accurately reflect the biological complexity and heterogeneity of tumors, and the specificity and sensitivity of the prediction results are relatively low, especially for G3 and G4 subtype medulloblastomas with high molecular heterogeneity. (2) Lack of information on the cell differentiation state: Traditional DNA methylation profile and RNA expression characteristic analysis methods mostly focus on the overall sample level and are difficult to capture the characteristics of different differentiation stages at the cell level, while the prognosis of medulloblastoma patients is often closely related to the cell differentiation state.

[0004] Otx2 is known to be highly expressed in the G3 subtype of medulloblastoma and is closely related to the undifferentiated state and increased invasiveness. However, the regulatory mechanism of Otx2 and the impact of specific epigenetic regulatory regions on the prognosis have not been clearly understood. Summary of the Invention

[0005] The purpose of the present invention is to provide the application of the methylation level of the E33 region in the prognosis evaluation of medulloblastoma, effectively predicting the clinical outcome of medulloblastoma patients, evaluating the prognosis of medulloblastoma, with strong sensitivity and high specificity.

[0006] The present invention provides the application of a substance for detecting the methylation level of the E33 region in the preparation of a product for evaluating the prognosis of medulloblastoma;

[0007] The nucleotide sequence of the E33 region is shown in SEQ ID NO: 1;

[0008] The medulloblastoma includes medulloblastoma of G3 subtype and / or medulloblastoma of G4 subtype.

[0009] Preferably, the prognosis includes one or more of the clinical outcome of the prognostic subject, the treatment effect of the prognostic subject, and the survival of the prognostic subject.

[0010] Preferably, the survival of the prognostic subject includes the survival period of the prognostic subject.

[0011] Preferably, the survival period of the prognostic subject includes one or more of the one-year survival rate, the three-year survival rate, and the five-year survival rate.

[0012] Preferably, the methylation level of the E33 region is significantly up-regulated in patients with high-risk medulloblastoma.

[0013] Preferably, the product includes: a kit, a gene chip, or a device containing a gene detection module for detecting the methylation level of the E33 region.

[0014] The present invention provides a prognostic assessment device for medulloblastoma, comprising: a gene detection module and a prognostic assessment module;

[0015] The medulloblastoma includes medulloblastoma of G3 subtype and / or medulloblastoma of G4 subtype;

[0016] The gene detection module is used to detect the methylation rate of the E33 region; the nucleotide sequence of the E33 region is shown in SEQ ID NO: 1;

[0017] The prognostic assessment module is used to determine the prognosis of medulloblastoma patients according to the methylation rate of the E33 region, including: when the methylation rate of the E33 region ≤ 1%, the patient is a high-risk patient and the prognosis is poor; when the methylation rate of the E33 region ≥ 20%, the patient is a low-risk patient and the prognosis is good.

[0018] Preferably, the prognostic assessment device further includes a calibration module; the calibration module is used to construct a multi-factor COX regression model with the methylation rate of the E33 region and the patient's clinical data.

[0019] Preferably, the patient's clinical data includes gender, age, subtype, and metastasis status.

[0020] Beneficial effects:

[0021] The present invention provides the use of a substance for detecting the methylation level of the E33 region in the preparation of a product for evaluating the prognosis of medulloblastoma; the nucleotide sequence of the E33 region is shown as SEQ ID NO: 1; the medulloblastoma includes Group 3 medulloblastoma and / or Group 4 medulloblastoma. The present invention discovers the direct association between the low methylation state of the E33 region and the prognosis of Group 3 / 4 patients with medulloblastoma. By detecting the methylation level of the E33 region, the clinical outcome of patients can be effectively predicted. By detecting the methylation level of the E33 region, it lays a foundation for the early prognosis evaluation and personalized treatment strategy of Group 3 / 4 patients with medulloblastoma. The methylation level of the E33 region is significantly up-regulated in high-risk medulloblastoma patients. This innovative achievement is expected to improve the treatment response of patients and ultimately increase the survival rate. BRIEF DESCRIPTION OF THE DRAWINGS

[0022] In order to more clearly illustrate the technical solutions in the embodiments of the present invention or the prior art, the following will briefly introduce the drawings required for use in the embodiments.

[0023] Figure 1 For the enhancer interaction network between a specific enhancer (SE) unit and its corresponding gene;

[0024] Figure 2 For the number and connectivity of enhancer network patterns;

[0025] Figure 3 For the interaction network of enhancers related to Otx2;

[0026] Figure 4 For the survival curve of Group 3 medulloblastoma;

[0027] Figure 5 For the survival curves of Group 3 and Group 4 medulloblastoma;

[0028] Figure 6 For the result of evaluating the effectiveness of the methylation level of the E33 region as an independent prognostic indicator by the COX regression model;

[0029] Figure 7 For the ROC curve of evaluating the prognosis of medulloblastoma by the methylation level of the E33 region. DETAILED DESCRIPTION OF THE EMBODIMENTS

[0030]

[0031] As an implementation manner, the prognosis includes one or more of the clinical outcome of the subject for prognosis, the treatment effect of the subject for prognosis, and the survival of the subject for prognosis; as another implementation manner, the prognosis includes the clinical outcome of the subject for prognosis, the treatment effect of the subject for prognosis, and the survival of the subject for prognosis. As an implementation manner, the survival of the subject for prognosis includes the survival period of the subject for prognosis. As an implementation manner, the survival period of the subject for prognosis includes one or more of the one-year survival rate, the three-year survival rate, and the five-year survival rate; as another implementation manner, the survival period of the subject for prognosis includes the one-year survival rate, the three-year survival rate, and the five-year survival rate.

[0032] The present invention constructs an enhancer interaction network between a specific enhancer (SE) unit and its corresponding gene, discovers a direct association between the hypomethylated state of the E33 region and the prognosis of patients with medulloblastoma Group 3 / 4, and can effectively predict the clinical outcome of patients by detecting the methylation level of the E33 region. The methylation state of the E33 region is expected to be used as an independent prognostic indicator, providing a new perspective for the clinical management of medulloblastoma and a novel biomarker for the field of tumor epigenetics. Detecting the methylation level of the E33 region lays a foundation for the early prognostic evaluation and personalized treatment strategy of patients with medulloblastoma Group 3 / 4. The methylation level of the E33 region is significantly up-regulated in patients with high-risk medulloblastoma. This innovative achievement is expected to improve the treatment response of patients and ultimately increase the survival rate.

[0033] As an implementation manner, the product includes: a kit, a gene chip, or a device containing a gene detection module, and the gene detection module is used to detect the methylation level of the E33 region.

[0034] The present invention provides a prognostic evaluation device for medulloblastoma, including: a gene detection module and a prognostic evaluation module; the medulloblastoma includes medulloblastoma of G3 subtype and / or medulloblastoma of G4 subtype;

[0035] The gene detection module is used to detect the methylation rate of the E33 region; the nucleotide sequence of the E33 region is shown as SEQ ID NO:1;

[0036] The prognostic evaluation module is used to determine the prognosis of medulloblastoma patients according to the methylation rate of the E33 region, including: when the methylation rate of the E33 region ≤ 1%, the patient is a high-risk patient and the prognosis is poor; when the methylation rate of the E33 region ≥ 20%, the patient is a low-risk patient and the prognosis is good.

[0037] As an implementation manner, the prognosis evaluation device further includes a calibration module; the calibration module is used to construct a multi-factor COX regression model based on the methylation rate of the E33 region and the patient's clinical data; the patient's clinical data includes gender, age, subtype, and metastasis status.

[0038] By using the above prognosis evaluation device to detect the methylation status of the E33 region, the present invention can more accurately predict the prognosis of tumor patients, improve the feasibility, accuracy, strong sensitivity, and high specificity of clinical applications.

[0039] To further illustrate the present invention, the application of the methylation level of the E33 region in evaluating the prognosis of medulloblastoma provided by the present invention will be described in detail below in conjunction with the drawings and embodiments, but they should not be construed as limiting the protection scope of the present invention.

[0040] Example 1

[0041] 1. Referring to the prior art (doi:10.1093 / bib / bbac508, doi:10.1016 / j.devcel.2022.11.011), use the eNET algorithm to construct an enhancer interaction network between specific enhancer (SE) units and their corresponding genes ( Figure 1 ).

[0042] 2. Conduct in-depth analysis on each enhancer network, evaluate the number and connectivity of network patterns, and thus identify three different network patterns: complex pattern, multiple pattern, and simple pattern. In these networks, genes with the highest ranking and the most interactions (such as Celf4 and Otx2) are predicted to be key factors in maintaining cell characteristics and disease progression ( Figure 2 ). The "hub enhancer" is distinguished from other SE regions that co-regulate gene expression due to its higher chromatin interaction frequency. The "hub enhancer" network related to Otx2 has extensive interactions, and multiple core regions in this network show obvious hypomethylation characteristics ( Figure 3 ). This finding indicates that the hypomethylated state of the E33 region, defined by WGBS (whole-genome bisulfite sequencing) data, is a newly discovered region that could not be covered by previous methylation chip data.

[0043] 3. Perform survival analysis using the patient's clinical indicators and prognosis

[0044] (1) Tumor tissues from 56 patients with Group 3 subtype of medulloblastoma (G3-MB) were collected, and the E33 region was precisely located using whole-genome bisulfite sequencing (WGBS) technology. WGBS converts unmethylated C bases through bisulfite treatment to distinguish C bases with methylation modifications, and combines high-throughput sequencing technology to determine whether CpG sites are methylated. The methylation rate of the E33 region in the tumor tissues of patients was obtained in the following manner: First, calculate the methylation rate of a single CpG site: CpG methylation rate (%) = mC / (UmC + mC) × 100%; where mC is the number of reads supporting methylated C, and UmC is the number of reads supporting unmethylated C; then calculate the average of the methylation rates of individual CpG sites within the region: E33 region methylation rate = Σ methylation rate of each CpG site / number of CpGs within the region. Sort the patients from high to low according to the methylation rate of the E33 region. Eleven patients in the top 20% after sorting were used as the high-methylation group, and eleven patients in the bottom 20% were used as the low-methylation group. Survival analysis was performed on the two groups of patients. The results showed that patients with low methylation of Group 3 subtype of medulloblastoma usually had a poor prognosis ( Figure 4 ), and the threshold of the methylation rate of the E33 region in the low-methylation group was 1%, while the threshold of the methylation rate of the E33 region in the high-methylation group was 20%.

[0045] (2) Tumor tissues from patients with Group 3 subtype of medulloblastoma and tumor tissues from patients with Group 4 subtype of medulloblastoma were collected. The methylation rate of the E33 region was detected in the same way as in step (1), and grouping and survival analysis were performed. Among them, the threshold of the methylation rate of the E33 region in the low-methylation group (10 patients with Group 3 subtype of medulloblastoma, 17 patients with Group 4 subtype of medulloblastoma) was 1%, and in the high-methylation group (11 patients with Group 3 subtype of medulloblastoma, 16 patients with Group 4 subtype of medulloblastoma), the threshold of the methylation rate of the E33 region was 20%. The results showed that patients with low methylation of Group 3 subtype and Group 4 subtype of medulloblastoma usually had a poor prognosis ( Figure 5 ).

[0046] 4. Multivariate analysis verification

[0047] Collect the tumor tissues of 56 patients with medulloblastoma Group 3 subtype and 80 patients with medulloblastoma Group 4 subtype, as well as the clinical data of the patients, such as gender, age, subtype, and metastasis status. Calculate the methylation rate of the E33 region in patients in the manner of Step 3, sort them from high to low according to the methylation rate of the E33 region, and divide them into groups by taking the top 20% and the bottom 20% respectively. Combine the clinical data to establish a Cox proportional hazards model to evaluate the independent effects of these factors on the prognosis of patients. By the maximum likelihood estimation method, estimate the coefficient (β value) of each variable in the model, and then calculate the hazard ratio (HR) of each variable, that is, the exponentiated result of the coefficient, to measure the degree of influence of each variable on the patient's risk. Then, calculate the 95% confidence interval (CI) of the hazard ratio of each variable, which is obtained by multiplying the HR by e to the power of plus or minus 1.96 times the coefficient standard error. This interval provides a range of uncertainty for the parameter estimation. At the same time, calculate the P value of the coefficient of each variable to evaluate the statistical significance of its influence on the prognosis of patients; a P value less than 0.05 is usually considered statistically significant.

[0048] Based on the results of the above multivariate regression analysis, it can be seen that after considering multiple clinical variables such as gender, age, and metastasis status, the methylation level in the E33 region is the only independent variable with significant predictive value for the prognosis of patients. The hazard ratio (HR) of the hypomethylation level is greater than 1, and the P value is less than 0.05, indicating that as the methylation level in the E33 region decreases, the survival risk of patients increases, that is, the survival time of patients may be shortened and the survival rate may be reduced ( Figure 6 ). This finding emphasizes the importance of the methylation status in the E33 region in clinical prognosis assessment and may provide new biomarkers for future treatment strategies and interventions. Therefore, the methylation level in the E33 region can be used as a strong prognostic indicator to help clinicians better evaluate the treatment response and survival expectancy of patients.

[0049] 5. Sensitivity and specificity analysis

[0050] Based on the conclusion of Step 4, the sensitivity, false positive rate, specificity, and AUC key performance indicators of the multivariate cox model were calculated to comprehensively evaluate the predictive ability of the model. Finally, the model performances at different survival periods (1 year, 3 years, 5 years) were compared and analyzed to determine the predictive accuracy and stability of the model at different time points, and the results are as Figure 7 shown in Table 1.

[0051] Table 1 Results of sensitivity and specificity analysis

[0052] Survival period Sensitivity False positive rate Specificity AUC 1 year 0.5714286 0.23404255 0.76595745 0.67 3 years 0.69064786 0.08695652 0.91304348 0.84 5 years 0.94857222 0.36363636 0.63636364 0.79

[0053] According to Figure 7As can be seen from Table 1, the methylation level of E33 can effectively evaluate the prognosis of the Group 3 and Group 4 subtypes of medulloblastoma, with strong sensitivity and high specificity.

[0054] As can be seen from the above content, the methylation level in the E33 region can effectively predict the clinical outcomes of medulloblastoma patients and evaluate the prognosis of medulloblastoma, with strong sensitivity and high specificity.

[0055] Although the above embodiments have described the present invention in detail, they are only a part of the embodiments of the present invention, rather than all of them. People can also obtain other embodiments based on these embodiments without creative efforts, and these embodiments all fall within the protection scope of the present invention.

Claims

1. Application of substances for detecting the methylation level of the E33 region in the preparation of products for evaluating the prognosis of medulloblastoma; The nucleotide sequence of the E33 region is shown in SEQ ID NO: 1; The medulloblastoma includes G3 subtype medulloblastoma and / or G4 subtype medulloblastoma.

2. The use according to claim 1, characterized in that: The prognosis includes one or more of prognosticating the clinical outcome of the subject, prognosticating the treatment effect of the subject, and prognosticating the survival of the subject.

3. The use according to claim 2, characterized in that: The prognosing the survival of the subject includes prognosing the survival period of the subject.

4. The use according to claim 3, characterized in that: The survival period of the prognostic subject includes one or more of a one-year survival rate, a three-year survival rate, and a five-year survival rate.

5. The use according to claim 1, characterized in that: The methylation level of the E33 region was significantly upregulated in high-risk medulloblastoma patients.

6. The use according to any one of claims 1 to 5, characterized in that: The product includes: a test kit, a gene chip or a device containing a gene detection module, and the gene detection module is used to detect the methylation level of the E33 region.

7. A prognosis assessment device for medulloblastoma, characterized in that: include: Gene detection module and prognosis assessment module; The medulloblastoma includes G3 subtype medulloblastoma and / or G4 subtype medulloblastoma; The gene detection module is used to detect the methylation rate of the E33 region; the nucleotide sequence of the E33 region is shown in SEQ ID NO: 1; The prognosis evaluation module is used to determine the prognosis of medulloblastoma patients according to the E33 region methylation rate, including: when the E33 region methylation rate is ≤1%, the patient is a high-risk patient and the prognosis is not good; When the methylation rate of the E33 region is ≥20%, the patient is a low-risk patient with a good prognosis.

8. The prognosis evaluation device according to claim 7, characterized in that: The prognosis evaluation device also includes a calibration module; the calibration module is used to construct a multi-factor COX regression model based on the E33 region methylation rate and the patient's clinical data.

9. The prognosis evaluation device according to claim 8, characterized in that: The patient clinical data included gender, age, subtype and metastatic status.

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