Throat squamous cell carcinoma prognosis gene methylation marker

Abstract

The invention discloses a methylation marker for prognosis evaluation of laryngeal squamous cell carcinoma. The methylation marker comprises RPH3AL, UBE2I and MAPK1. Meanwhile, the invention provides a method for obtaining the DNA methylation marker set. Based on the RRBS technology, three methylation markers of laryngeal squamous cell carcinoma are found. The methylation levels of the genes are significantly related to clinical pathological characteristics (such as tumor staging, differentiation degree, lymph node metastasis, prognosis and the like) of patients. Through the RRBS technology, methylation changes of the genes can be comprehensively analyzed under high resolution, and the prognosis value of the markers in laryngeal squamous cell carcinoma is verified. Compared with a traditional single clinical pathology index, the methylation marker based on the molecular level has high accuracy and sensitivity, and a more accurate basis can be provided for recurrence prediction of the laryngeal squamous cell carcinoma.

Description

Technical Field

[0001] The present invention relates to the field of medical technology, and in particular to a laryngeal squamous cell carcinoma prognosis gene methylation marker. Background Art

[0002] Laryngeal squamous cell carcinoma (LSCC) is the most common laryngeal malignancy, usually originating from squamous epithelial cells of the larynx. The morbidity and mortality of LSCC are high, and due to the heterogeneity and complexity of tumorigenesis, the prognosis of patients varies significantly. Although some progress has been made in the treatment of laryngeal squamous cell carcinoma in recent years, such as surgical resection, radiotherapy and chemotherapy, the survival rate and quality of life of LSCC patients are still low due to the lack of effective methods for early diagnosis and individualized treatment strategies.

[0003] Currently, the prognosis of laryngeal squamous cell carcinoma mainly relies on clinical pathological characteristics, such as tumor stage, degree of differentiation and lymph node metastasis, but these indicators cannot accurately reflect the course of the patient's disease and treatment response. Therefore, finding new biomarkers, especially markers at the molecular level, is crucial for early prognosis assessment and the development of individualized treatment plans.

[0004] DNA methylation is one of the important epigenetic modifications, which regulates gene expression by adding methyl groups to the CpG island region. In normal cells, DNA methylation is involved in the regulation of gene expression and maintains genome stability. However, tumor cells often have genome-wide methylation disorders, including hypermethylation in the promoter region (leading to silencing of tumor suppressor genes) and hypomethylation in the gene body region (leading to activation of oncogenes). These methylation changes are closely related to the occurrence, development and prognosis of tumors.

[0005] In laryngeal squamous cell carcinoma, studies have found that the methylation status of multiple genes is significantly correlated with the patient's clinical prognosis. For example, methylation changes in tumor suppressor genes such as TP53 and CDKN2A are common in LSCC and are associated with the malignancy, invasiveness, and metastasis of the tumor. Therefore, studying DNA methylation changes in laryngeal squamous cell carcinoma is expected to discover potential prognostic markers, thereby providing new ideas for clinical diagnosis and treatment.

[0006] RRBS (Reduced Representation Bisulfite Sequencing) is an efficient technology that combines simplified representation bisulfite sequencing, which can accurately analyze DNA methylation status across the entire genome. Compared with traditional whole genome methylation sequencing (WGBS), RRBS technology greatly reduces sequencing depth and data volume by selecting regions rich in methylation sites such as CpG islands, thereby reducing costs and improving data resolution.

[0007] The advantage of RRBS technology is that it can simultaneously obtain methylation data of large-scale samples, and has high sensitivity and specificity, which is particularly suitable for the detection of low-frequency methylation events in tumor research. In tumor research, RRBS technology has been widely used to reveal the methylation characteristics of various tumor types and can discover new tumor prognostic markers.

[0008] In recent years, the research on DNA methylation markers of laryngeal squamous cell carcinoma has gradually increased. Studies have shown that multiple genes in LSCC patients undergo methylation changes in their tumor tissues, and some methylation markers have been found to be closely related to the occurrence, development and prognosis of tumors. For example, methylation changes in tumor suppressor genes such as TP53, CDKN2A, and RASSF1A are common in LSCC. In addition, studies have suggested that the combined detection of multiple methylation markers can improve the accuracy of early diagnosis of laryngeal squamous cell carcinoma and help predict the prognosis of patients.

[0009] However, although some methylation markers have been validated in LSCC, existing studies still have certain limitations. The main problems include: small sample size, validation of methylation markers is mostly limited to specific tumor stages and clinical characteristics, and lack of high-resolution methylation data. In order to improve the accuracy and wide applicability of markers, more studies based on high-throughput methylation sequencing technology are urgently needed, especially the application of high-resolution technology such as RRBS to fully reveal the methylation variations of laryngeal squamous cell carcinoma. Summary of the invention

[0010] The technical problem to be solved by the present invention is to provide a laryngeal squamous cell carcinoma prognosis gene methylation marker, which can accurately predict the recurrence risk and prognosis of laryngeal squamous cell carcinoma patients by detecting the methylation status of RPH3AL, UBE2I and MAPK1 genes, and provide a new basis for clinical diagnosis and individualized treatment.

[0011] The technical problem to be solved by the present invention is achieved through the following technical solutions:

[0012] A methylation marker for prognosis assessment of laryngeal squamous cell carcinoma, comprising RPH3AL, UBE2I, and MAPK1.

[0013] Application of a methylation marker in the preparation of a reagent for detecting the prognostic risk assessment of laryngeal squamous cell carcinoma.

[0014] Use of a methylation marker in preparing a kit for the prognostic risk assessment of laryngeal squamous cell carcinoma. Preferably, in the above technical solution, the kit comprises reagents, primers and probes for detecting RPH3AL, UBE2I and MAPK1.

[0015] A method for obtaining a methylation marker comprises the following steps:

[0016] (1) Sample collection and processing: Cancer tissue samples from patients with laryngeal squamous cell carcinoma who had recurrence and those who had not had recurrence were collected, and DNA was extracted from the laryngeal squamous cell carcinoma tissue samples;

[0017] (2) RRBS sequencing: RRBS technology is used for high-throughput DNA methylation analysis, selecting DNA fragments containing CpG islands or other enriched regions to obtain methylation information across the entire genome;

[0018] (3) Data analysis and screening: By processing and analyzing the sequencing data, the loci associated with the prognosis of laryngeal squamous cell carcinoma were screened, especially the methylation status of RPH3AL, UBE2I and MAPK1 genes;

[0019] (4) Correlation analysis was performed between the methylation levels of RPH3AL, UBE2I, and MAPK1 and the patients’ clinical data to verify their application value in the prognosis of laryngeal squamous cell carcinoma.

[0020] Preferably, in the above technical solution, step (1) specifically comprises: collecting cancer tissue samples from patients with laryngeal squamous cell carcinoma, extracting DNA from all samples, and performing quality testing after DNA extraction, wherein the quality testing comprises detecting DNA concentration and purity by UV-Vis spectrophotometer and checking DNA integrity by gel electrophoresis.

[0021] Preferably, in the above technical solution, step (2) includes:

[0022] (21) DNA bisulfite treatment: The extracted DNA sample is treated with bisulfite to convert unmethylated cytosine (C) into uracil (U), while methylated cytosine does not undergo conversion, thereby effectively distinguishing between methylated and unmethylated cytosine;

[0023] (22) Restriction enzyme digestion and library construction: Use specific restriction endonucleases (such as MspI) to digest DNA, select DNA fragments rich in CpG islands, and then construct a library; after the library is constructed, amplify the enriched region by PCR;

[0024] (23) High-throughput sequencing: Perform high-throughput sequencing on the library, and use second-generation sequencing technologies such as the Illumina platform to perform whole-genome sequencing on the processed DNA fragments to obtain a large amount of methylation data.

[0025] Preferably, in the above technical solution, step (3) performs the following analysis on the obtained RRBS data:

[0026] (31) Quality control and data preprocessing: By removing low-quality sequences, sequencing errors and low-coverage regions are filtered out. Specifically, bioinformatics tools are used to align the bisulfite-treated data and the processed data to the reference genome;

[0027] (32) Calculation of methylation level: Calculate the methylation degree of each CpG site through the comparison results to obtain the methylation percentage;

[0028] (33) Screening of differential methylation sites: Statistical methods are used to screen out methylation sites with significant differences between laryngeal squamous cell carcinoma tissue and normal tissue, and further analysis is performed to determine whether these differential methylation sites are associated with clinical characteristics.

[0029] (34) Bioinformatics analysis: Bioinformatics tools were used to screen out genes related to tumor occurrence and development, including RPH3AL, UBE2I, and MAPK1.

[0030] Preferably, in the above technical solution, in step (33), the clinical characteristics include: staging, metastasis, and recurrence.

[0031] Preferably, in the above technical solution, in step (34), the bioinformatics tools include gene enrichment analysis, signal pathway enrichment analysis, and LASSO independent variable screening.

[0032] A method for evaluating the predictive accuracy of a methylation marker comprises the following steps:

[0033] (1) Whole genome DNA methylation detection was performed on the samples to obtain the methylation levels of genes including RPH3AL, UBE2I and MAPK1; (2) The LASSO model and random forest model were used to construct a prognostic prediction model; (3) The relationship between methylation markers and disease-free survival (DFS) was analyzed by Kaplan-Meier survival analysis and Cox regression model, and the prognostic prediction accuracy of the marker set was evaluated.

[0034] Preferably, in the above technical solution, in step (2), the method for constructing the prognosis prediction model includes the following steps: (21) randomly dividing the samples into a training set and a validation set, wherein the training set accounts for 70% and the validation set accounts for 30%; (22) using the training set samples to construct a LASSO model and a random forest model; (23) evaluating the model performance on the training set and the validation set respectively, including the evaluation of sensitivity, specificity and accuracy.

[0035] The above technical solution of the present invention has the following beneficial effects:

[0036] Based on RRBS technology, the present invention discovered three prognostic methylation markers for laryngeal squamous cell carcinoma: RPH3AL, UBE2I and MAPK1. The methylation levels of these genes are significantly correlated with the patient's clinical pathological characteristics (such as tumor stage, degree of differentiation, lymph node metastasis, prognosis, etc.). Through RRBS technology, we can comprehensively analyze the methylation changes of these genes at high resolution and verify the prognostic value of these markers in laryngeal squamous cell carcinoma. Compared with traditional single clinical pathological indicators, the molecular-based methylation markers provided by the present invention have higher accuracy and sensitivity, and can provide a more accurate basis for the prediction of recurrence of laryngeal squamous cell carcinoma. BRIEF DESCRIPTION OF THE DRAWINGS

[0037] The accompanying drawings, which are incorporated in and constitute a part of the specification, illustrate embodiments of the invention and, together with the description, serve to explain the principles of the invention.

[0038] Figure 1 This is the analysis of methylation differences between recurrent and non-recurrent samples of laryngeal squamous cell carcinoma. a is the comparison of methylation differences between recurrent group 1 and non-recurrent group, and the comparison of methylation differences between recurrent group 2 and non-recurrent group.

[0039] Figure 2 Figure 2 is the LASSO analysis result of methylation markers for laryngeal squamous cell carcinoma, a is the LASSO regression coefficient path diagram, and b is the cross-validation error diagram.

[0040] Figure 3 This is the result of LASSO regression analysis of methylation markers in laryngeal squamous cell carcinoma.

[0041] Figure 4 This is a performance evaluation table for the laryngeal squamous cell carcinoma recurrence prediction model.

[0042] Figure 5 Performance evaluation of laryngeal squamous cell carcinoma recurrence prediction model and error analysis of random forest model. a is the training set prediction performance evaluation table, and b is the random forest model error diagram.

[0043] Figure 6 The figure shows the error analysis of LASSO model feature selection and random forest model. a is the feature importance graph, and b is the list of factors selected by LASSO model.

[0044] Figure 7 Figure 2 is a correlation analysis diagram between the risk model of laryngeal squamous cell carcinoma and clinical factors. A is a relationship diagram between the risk score and tumor stage. B is a relationship diagram between the risk score and tumor differentiation degree. C is a relationship diagram between the risk score and patient age.

[0045] Figure 8 This is the Kaplan-Meier survival analysis diagram.

[0046] Fig. 9Figure 3 is the Kaplan-Meier survival curve of disease-free survival (DFS) in patients with laryngeal squamous cell carcinoma at different stages.

[0047] Fig.10 This is a survival analysis chart of disease-free survival (DFS) in patients with laryngeal squamous cell carcinoma based on risk score and tumor stage.

[0048] Fig.11 This is a survival analysis chart of disease-free survival (DFS) in patients with laryngeal squamous cell carcinoma stratified by age.

[0049] Fig.12 This is a survival analysis chart of disease-free survival (DFS) in patients with laryngeal squamous cell carcinoma stratified by tumor differentiation degree. DETAILED DESCRIPTION

[0050] Various exemplary embodiments of the present invention will now be described in detail with reference to the accompanying drawings. It should be noted that the relative arrangement of components and steps, numerical expressions and numerical values ​​set forth in these embodiments do not limit the scope of the present invention unless otherwise specifically stated.

[0051] The experimental methods used in the following examples are all conventional methods unless otherwise specified. The materials and reagents used are all commercially available unless otherwise specified. The equipment used in the experiments are all well known to those skilled in the art unless otherwise specified.

[0052] Example 1

[0053] 1. Sample Collection and Processing

[0054] Cancer tissue samples from 111 patients with laryngeal squamous cell carcinoma were collected. DNA was extracted from all samples using a commercial DNA extraction kit. After DNA extraction, quality testing was performed (such as testing DNA concentration and purity using a UV-Vis spectrophotometer and checking DNA integrity using gel electrophoresis). The specific steps are as follows:

[0055] The samples were cancer tissue samples from 111 patients with laryngeal squamous cell carcinoma, including 78 newly diagnosed samples (44 without recurrence and 34 with recurrence) and 33 recurrence samples. Among them, the newly diagnosed samples were mostly male (97.4%), 52.6% were younger than 60 years old, the degree of differentiation was mainly low-moderate differentiation (71.8%), the tumor stage was mainly stage I / II (75.6%), 60.3% were smokers, 47.4% were drinkers, and the recurrence rate was 43.6%. During the sample collection process, ethical principles were strictly followed and informed consent was obtained from the patients.

[0056] The specific steps are as follows:

[0057] (1) DNA extraction:

[0058] DNA was extracted from cancer tissue samples using a commercial DNA extraction kit.

[0059] The concentration and purity of the extracted DNA were tested by UV-Vis spectrophotometer, and the integrity and degradation of the DNA were checked by agarose gel electrophoresis.

[0060] (2) DNA quality control:

[0061] DNA concentration and purity were determined by UV-Vis spectrophotometer, and DNA integrity was checked by gel electrophoresis.

[0062] 2. RRBS technology implementation

[0063] RRBS (Reduced Representation Bisulfite Sequencing) technology was used for high-throughput DNA methylation analysis.

[0064] The specific steps are as follows:

[0065] (1) DNA bisulfite treatment:

[0066] The extracted DNA samples are treated with bisulfite to convert unmethylated cytosine (C) into uracil (U), while methylated cytosine is not converted. This step can effectively distinguish between methylated and unmethylated cytosine.

[0067] (2) Restriction enzyme digestion and library construction:

[0068] Use specific restriction endonucleases (such as MspI) to digest DNA and select DNA fragments rich in CpG islands to construct RRBS libraries. After library construction, PCR amplification is used to enrich the target region.

[0069] (3) High-throughput sequencing:

[0070] The library was subjected to high-throughput sequencing, and the processed DNA fragments were sequenced throughout the genome using second-generation sequencing technologies such as the Illumina platform to obtain a large amount of methylation data.

[0071] 3. Data analysis and screening

[0072] The following analyses were performed on the obtained RRBS sequencing data to screen for methylation markers associated with the prognosis of laryngeal squamous cell carcinoma:

[0073] (1) Quality control and data preprocessing:

[0074] By removing low-quality sequences, sequencing errors and low-coverage regions are filtered out. Bioinformatics tools (such as Bismark, BS-Seeker, etc.) are used to align the bisulfite-treated data to the reference genome.

[0075] CpG sites with sequencing depth lower than 10x were filtered out (sliding windows with depth lower than 10x were set as missing values, and sliding windows with missing value ratios not exceeding 10% were selected for differential analysis) to ensure the reliability and accuracy of the data.

[0076] (2) Calculation of methylation level:

[0077] The average methylation level (AMF) method was used to calculate the methylation level of each CpG site using the sliding window method. The sliding window was extended 200 bp downstream from each CpG site, and the AMF within each sliding window was calculated.

[0078] The methylation degree of each CpG site was calculated by comparing the results to obtain the methylation percentage (i.e., the ratio of methylated cytosine to total cytosine).

[0079] (3) Screening of differentially methylated sites:

[0080] Statistical methods (such as t-test, chi-square test, etc.) were used to screen out methylation sites with significant differences between laryngeal squamous cell carcinoma tissues and normal tissues. Further analysis was performed to determine whether these differentially methylated sites were associated with clinical characteristics (such as stage, metastasis, recurrence, etc.).

[0081] Specifically, the methylation levels of the relapse group and the non-relapse group were compared using the t test and u test, and the FDR (False Discovery Rate) correction was used to screen the differential methylation windows with p≤0.01. A total of 921 differential methylation windows were obtained and merged into 306 differential methylation regions.

[0082] (4) Bioinformatics analysis: Bioinformatics tools such as gene enrichment analysis, signal pathway enrichment analysis, and LASSO independent variable screening were used to screen out genes related to tumor occurrence and development. Through this analysis, it was found that methylation changes in genes such as RPH3AL, UBE2I, and MAPK1 were closely related to the prognosis of laryngeal squamous cell carcinoma.

[0083] The specific steps are as follows: LASSO regression analysis was used to further screen methylation markers that were closely related to the prognosis of laryngeal squamous cell carcinoma.

[0084] 70% of the newly diagnosed samples were randomly selected as the training set, and four markers were screened out through LASSO regression analysis, namely:

[0085] chr17:234844-235043 (RPH3AL gene promoter region);

[0086] chr13:31618219-31618418 (distal intergenic region);

[0087] chr16:1360035-1360234 (UBE2I gene promoter region);

[0088] chr22:22221911-22222110 (MAPK1 gene promoter region),

[0089] Of the four markers, three are associated with gene promoter regions (RPH3AL, UBE2I, and MAPK1). The methylation status of these genes may directly affect their expression levels, thereby affecting the biological behavior of the tumor. The fourth marker is located in the distal intergenic region and may be associated with regulatory elements, but its function is not as clear as that of the gene promoter region, so it was temporarily shelved in subsequent discussions.

[0090] 4. Clinical data association and verification

[0091] The correlation analysis between RPH3AL, UBE2I, and MAPK1 methylation levels and the patients' clinical data (such as tumor stage, degree of differentiation, lymph node metastasis, prognosis, etc.) was performed to evaluate the predictive value of these markers for the prognosis of patients with laryngeal squamous cell carcinoma. The specific steps are as follows:

[0092] (1) Construction and validation of prognostic model:

[0093] The LASSO model and random forest model were used to construct the prognostic prediction model for the screened markers (RPH3AL, UBE2I, MAPK1), and the model performance was evaluated on the training set and validation set.

[0094] 70% of the first-diagnosis samples were randomly selected as the training set, and the remaining 30% were used as the validation set. The model was constructed using the training set samples and the model performance was further optimized.

[0095] LASSO model results: In the training set, the model had a sensitivity of 96%, a specificity of 100%, and an accuracy of 98.2%. These indicators show that the model has a high predictive performance on the training set and can better distinguish patients with recurrence and those without recurrence. In the validation set, the model had a sensitivity of 88.9%, a specificity of 100%, and an accuracy of 95.7%. The results of the validation set also show that the model has a high predictive performance. Although the sensitivity is slightly lower than that of the training set, it still has high specificity and accuracy. In short, the model shows a high predictive performance and can effectively distinguish patients with recurrence and those without recurrence.

[0096] Random forest model results: Consistent with the LASSO model, the sensitivity was 96%, the specificity was 100%, and the accuracy was 98.2%. The random forest model further verified the reliability of the markers.

[0097] (2) Correlation analysis of clinical factors

[0098] Methods: The correlation between the risk model and the clinical characteristics of patients (such as stage, age, degree of differentiation, etc.) was analyzed.

[0099] Conclusion: The risk model is independent of stage, age, degree of differentiation and other factors, indicating that methylation markers are independent of traditional clinical pathological features and have independent prognostic value.

[0100] (3) Survival analysis:

[0101] Kaplan-Meier survival analysis and Cox regression model were used to analyze the relationship between methylation markers and disease-free survival (DFS).

[0102] The results of univariate analysis showed that the risk model was significantly associated with DFS (p < 2.2e -16 ), the risk coefficient is 4.3724 and the risk ratio is 79.2302.

[0103] The results of multivariate analysis showed that after adjusting for age, differentiation degree and tumor stage, the risk model was still significant (p = 1.39e -08 ), indicating that methylation markers are independent of traditional clinical features and can significantly predict the prognosis of patients.

[0104] (4) Joint analysis of staging and risk model:

[0105] Methods: The prognostic stratification ability of the risk model in different tumor stages (stage I / II and stage III / IV) was analyzed.

[0106] Conclusion: The risk model can significantly stratify patients in both stage I / II and stage III / IV, indicating that the model is suitable for patients with laryngeal squamous cell carcinoma of different stages and has broad clinical application prospects.

[0107] (5) Clinical application:

[0108] By monitoring changes in methylation marker levels after treatment, disease progression can be detected early and provide timely reference for clinical treatment.

[0109] In summary, the present invention screened out methylation markers of RPH3AL, UBE2I and MAPK1 genes by RRBS technology, and verified the high sensitivity, high specificity and high accuracy of these markers in the prognosis assessment of laryngeal squamous cell carcinoma. The method and markers provided by the present invention have broad clinical application prospects and can provide strong support for early diagnosis, recurrence monitoring and individualized treatment of laryngeal squamous cell carcinoma.

[0110] The present invention discovers the prognostic methylation markers RPH3AL, UBE2I and MAPK1 for laryngeal squamous cell carcinoma based on RRBS technology, and has the following significant technical effects:

[0111] 1. High-precision methylation marker screening

[0112] RRBS technology greatly improves the resolution and accuracy of methylation analysis by selecting CpG island regions or other enriched methylation sites. Compared with traditional methylation sequencing technology, RRBS can not only cover methylation sites across the entire genome, but also effectively reduce sequencing depth and data volume due to its simplified representative method, thereby reducing costs while also ensuring high accuracy and reliability of the data.

[0113] Through this high-precision technology, the present invention can screen out methylation markers (such as RPH3AL, UBE2I, MAPK1) that are closely related to the prognosis of laryngeal squamous cell carcinoma from complex tumor samples. These markers can accurately reflect the occurrence, development and clinical prognosis of the tumor, providing a reliable basis for subsequent clinical applications.

[0114] 2. Improve the accuracy of prognostic assessment

[0115] The methylation status of the RPH3AL, UBE2I and MAPK1 genes found in the present invention has significant differences in patients with laryngeal squamous cell carcinoma. By detecting the methylation levels of these genes, normal tissues and tumor tissues can be accurately distinguished, and are significantly correlated with the disease-free survival (DFS) and overall survival (OS) of patients. This makes RPH3AL, UBE2I and MAPK1 important markers for prognostic evaluation.

[0116] Compared with traditional clinical pathological indicators (such as stage, degree of differentiation, lymph node metastasis, etc.), markers based on methylation status have higher sensitivity and specificity and can predict the prognosis of patients in the early stages of tumors. Therefore, these markers can provide doctors with more information, help develop more personalized treatment plans, and identify high-risk patients in advance.

[0117] 3. Broad prospects for clinical application

[0118] Through verification in a large number of clinical samples, the methylation status of RPH3AL, UBE2I and MAPK1 genes is closely related to the clinical characteristics of patients (such as tumor stage, degree of differentiation, metastatic disease, etc.), proving that these methylation markers have strong clinical practicality. Prognostic evaluation based on methylation markers can provide clinicians with effective auxiliary diagnostic tools.

[0119] Monitoring recurrence and metastasis: Methylation markers can also be used to monitor recurrence and metastasis of patients after treatment, helping to detect disease progression early, thereby improving the timeliness and effectiveness of treatment.

[0120] In summary, the methylation marker and the detection method thereof provided by the present invention have significant technical advantages, can provide strong support for the prognosis evaluation and individualized treatment of laryngeal squamous cell carcinoma, and have broad market application prospects.

[0121] Although the present invention has been disclosed as above by the embodiments, it is not intended to limit the present invention. Any person skilled in the art may make various choices and modifications without departing from the spirit and scope of the present invention. Therefore, the protection scope of the present invention is limited by the claims and their equivalents.

Claims

1. A methylation marker for the prognosis assessment of laryngeal squamous cell carcinoma, characterized in that: The markers include RPH3AL, UBE2I, and MAPK1.

2. Use of the methylation marker according to claim 1 in the preparation of a reagent for detecting the prognosis risk assessment of laryngeal squamous cell carcinoma.

3. Use of the methylation marker according to claim 1 in preparing a kit for prognostic risk assessment of laryngeal squamous cell carcinoma.

4. A method for obtaining the methylation marker according to claim 1, characterized in that: The following steps are involved: (1) Sample collection and processing: Cancer tissue samples from patients with laryngeal squamous cell carcinoma who had recurrence and those who had not had recurrence were collected, and DNA was extracted from the laryngeal squamous cell carcinoma tissue samples; (2) RRBS sequencing: RRBS technology is used for high-throughput DNA methylation analysis, selecting DNA fragments containing CpG islands or other enriched regions to obtain methylation information across the entire genome; (3) Data analysis and screening: By processing and analyzing the sequencing data, the loci associated with the prognosis of laryngeal squamous cell carcinoma were screened, especially the methylation status of RPH3AL, UBE2I and MAPK1 genes; (4) Clinical data association: Correlation analysis was performed between the methylation levels of RPH3AL, UBE2I, and MAPK1 and the patients’ clinical data to verify their application value in the prognosis of laryngeal squamous cell carcinoma.

5. The method for obtaining methylation markers according to claim 4, characterized in that: Step (1) specifically includes: collecting cancer tissue samples from patients with laryngeal squamous cell carcinoma, extracting DNA from all samples, and performing quality testing after DNA extraction. The quality testing includes detecting DNA concentration and purity using a UV-Vis spectrophotometer and checking DNA integrity using gel electrophoresis.

6. The method for obtaining methylation markers according to claim 4, characterized in that: Step (2) includes: (21) DNA bisulfite treatment: The extracted DNA sample is treated with bisulfite to convert unmethylated cytosine (C) into uracil (U), while methylated cytosine does not undergo conversion, thereby effectively distinguishing between methylated and unmethylated cytosine; (22) Restriction enzyme digestion and library construction: Use specific restriction endonucleases (such as MspI) to digest DNA, select DNA fragments rich in CpG islands, and then construct a library; after the library is constructed, amplify the enriched region by PCR; (23) High-throughput sequencing: Perform high-throughput sequencing on the library, and use second-generation sequencing technologies such as the Illumina platform to perform whole-genome sequencing on the processed DNA fragments to obtain a large amount of methylation data.

7. The method for obtaining methylation markers according to claim 4, characterized in that: Step (3) Perform the following analysis on the obtained RRBS data: (31) Quality control and data preprocessing: By removing low-quality sequences, sequencing errors and low-coverage regions are filtered out. Specifically, bioinformatics tools are used to align the bisulfite-treated data and the processed data to the reference genome; (32) Calculation of methylation level: Calculate the methylation degree of each CpG site through the comparison results to obtain the methylation percentage; (33) Screening of differential methylation sites: Statistical methods are used to screen out methylation sites with significant differences between laryngeal squamous cell carcinoma tissue and normal tissue, and further analysis is performed to determine whether these differential methylation sites are associated with clinical characteristics. (34) Bioinformatics analysis: Bioinformatics tools were used to screen out genes related to tumor occurrence and development, including RPH3AL, UBE2I, and MAPK1.

8. The method for obtaining methylation markers according to claim 7, characterized in that: In step (33), clinical characteristics include: stage, metastasis, and recurrence; in step (34), bioinformatics tools include gene enrichment analysis, signal pathway enrichment analysis, and LASSO independent variable screening.

9. A method for evaluating the prediction accuracy of the methylation marker according to claim 1, characterized in that: The following steps are involved: (1) Whole genome DNA methylation detection was performed on the samples to obtain the methylation levels of RPH3AL, UBE2I and MAPK1 genes; (2) The LASSO model and random forest model were used to construct a prognostic prediction model; (3) The relationship between methylation markers and disease-free survival (DFS) was analyzed by Kaplan-Meier survival analysis and Cox regression model, and the prognostic prediction accuracy of the marker set was evaluated.

10. The method according to claim 9, characterized in that In step (2), the method for constructing the prognosis prediction model includes the following steps: (21) randomly dividing the samples into a training set and a validation set, wherein the training set accounts for 70% and the validation set accounts for 30%; (22) using the training set samples to construct a LASSO model and a random forest model; (23) evaluating the model performance on the training set and the validation set, respectively, including the evaluation of sensitivity, specificity, and accuracy.

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