Bladder cancer gene methylation detection kit

Abstract

The invention provides a bladder cancer gene methylation detection kit, which adopts a one-step gene methylation detection method of MSRE-qPCR, and in the method, methylation sensitive restriction enzyme (MSRE) digestion and qPCR amplification are completed in the same system. According to the present invention, the bladder cancer gene methylation detection kit can be used for the recurrence monitoring of the non-muscle invasive bladder cancer (non-muscle invasive bladder cancer, NMIBC) patient, and can be used for the recurrence monitoring of the non-muscle invasive bladder cancer (non-muscle invasive bladder cancer, NMIBC).

Description

Technical Field

[0001] The present invention relates to the field of biomedicine, and further to the field of gene diagnosis, and to a bladder cancer gene methylation detection kit. Background Art

[0002] Cancer is a disease caused by gene mutations, in which cells lose normal growth and differentiation control, forming malignant tumors. These cells can invade surrounding tissues and spread to other parts of the body through the blood or lymphatic system to form metastases. The formation of cancer is a multi-stage process that usually takes many years. Early diagnosis and early intervention in the cancer development process are a means of controlling the development of cancer.

[0003] There are many methods for cancer diagnosis, including traditional imaging examinations, pathological biopsies, liquid biopsies, and emerging artificial intelligence-assisted diagnosis technologies. Common cancer diagnosis methods include imaging examinations: chest X-ray examination (CXR), which was once widely used for lung cancer screening, but is now rarely used for early screening due to its low resolution and high false negative rate; low-dose spiral CT (LDCT); positron emission tomography / CT (PET / CT) and PET / MR, which detect the metabolic activity of tumors through tracers to determine whether the tumor is benign or malignant and whether it has metastasized, but are costly and have high radiation exposure; magnetic resonance imaging (MRI), which is radiation-free and suitable for patients who are sensitive to radiation, but has limited ability to detect early cancer; pathological examination, biopsy is the "gold standard" for diagnosing cancer, but it is an invasive procedure; liquid biopsy, circulating tumor DNA (ctDNA) detection, which achieves non-invasive diagnosis and dynamic monitoring by analyzing tumor DNA fragments in the blood; multi-cancer early detection (MCED), which can identify multiple cancers by detecting cancer signals in the blood; other methods include endoscopic examination and tumor marker detection.

[0004] Among many cancers, the incidence of urinary system tumors is increasing year by year. Urothelial carcinoma (UC), including upper urinary tract urothelial carcinoma (UTUC) and lower urinary tract urothelial carcinoma (BC), has the characteristics of high incidence, multiple primary sites, and easy recurrence after surgery. Among them, bladder cancer is one of the cancers with the highest recurrence rate. Among them, non-muscle invasive bladder cancer (NMIBC) accounts for 75% of all new cases of bladder cancer. The recurrence rate within 5 years after the initial treatment is about 12%~85%, and the progression rate is about 2.9%~50%. Timely identification of recurrence in cancer patients is crucial to improving the prognosis and quality of life of patients.

[0005] At present, the most common clinical methods for monitoring recurrence of non-muscle invasive bladder cancer (NMIBC) are cystoscopy and urine cytology analysis. However, both have problems including high invasiveness, high risk of complications, poor compliance, low sensitivity and strong subjectivity of results. In addition, many urine testing products that have been launched on the market at home and abroad, including NMP22 BladderChek and UroVysion, have not been widely used due to insufficient detection performance and lack of sufficient clinical benefit demonstration. Therefore, there is an urgent need for a non-invasive, fast and highly accurate detection product to provide a more effective solution for recurrence monitoring of patients with non-muscle invasive bladder cancer (NMIBC).

[0006] Genetic testing for cancer has become an important tool for cancer diagnosis and treatment, and is widely used in early screening, diagnosis, treatment guidance and recurrence monitoring. Among them, gene methylation testing is an epigenetic-based detection technology that assists in the early diagnosis, risk assessment, treatment guidance and recurrence monitoring of cancer by analyzing the DNA methylation status.

[0007] The most widely used methylation detection method is a chemical conversion method based on bisulfite or bisulfite (BS) combined with qPCR quantification (BS-qPCR method). In the DNA conversion step, unmethylated cytosine is converted into uracil, while methylated cytosine (5-methylcytosine, 5mC) remains unchanged. The conversion process takes a long time, and drastic changes in temperature and pH will cause DNA degradation and breakage, which will interfere with subsequent qPCR quantification and affect the stability and accuracy of the test results.

[0008] Urine samples are commonly used for bladder cancer gene testing. Urine samples face some challenges in actual testing applications. Some patients cannot provide sufficient urine samples due to illness or other reasons. Various metabolites, electrolytes, proteins and microbial contamination in urine can interfere with DNA extraction and purification. Due to various factors, the abundance of DNA in urine is low under existing technical conditions, which greatly limits the accuracy of urine DNA-based test results. In addition to improving sample collection and extraction techniques, it is also necessary to optimize existing detection technologies to improve the ability to detect low-abundance DNA samples. Summary of the invention

[0009] In order to solve the technical problems existing in the prior art, the present invention provides a bladder cancer gene methylation detection kit. Furthermore, the present invention provides a non-invasive, fast and highly accurate detection product for the recurrence monitoring of patients with non-muscle invasive bladder cancer (NMIBC). Furthermore, the bladder cancer gene methylation detection kit provided by the present application adopts a "one-step" gene methylation detection method of MSRE-qPCR, in which methylation sensitive restriction enzyme (MSRE) digestion and qPCR amplification are completed in the same system.

[0010] In order to solve the technical problems existing in the prior art, the present invention provides a digestion method based on methylation-sensitive restriction endonuclease (MSRE) to replace the traditional BS conversion method. According to the restriction sites contained in the target region sequence, the applicable endonuclease combination is screened to identify the sites in the DNA sequence where no methylation modification has occurred, and the DNA chain is cut near it, while the sites where methylation has occurred are not affected. Subsequently, a methylation-specific primer and probe combination is used for qPCR detection and the methylation level is calculated. Compared with the BS conversion method, the MSRE method has the characteristics of simple operation, low cost, and high sensitivity for low-abundance samples. It is particularly suitable for the accurate detection of methylation targets with known specific sequences.

[0011] In the conventional MSRE-qPCR method, the enzyme digestion reaction and the qPCR reaction are two independent steps. After the enzyme digestion is completed, the product needs to be purified and transferred to the PCR system, which increases the risk of sample loss, contamination, confusion, etc. caused by additional operation steps such as opening the lid and transferring the tube. In order to solve the above technical problems and improve the convenience in clinical use, the present application combines the MSRE digestion and qPCR amplification system, and provides a "one-step" gene methylation detection method of MSRE-qPCR, and provides a kit for bladder cancer gene methylation detection using this method.

[0012] The present application provides a bladder cancer gene methylation detection kit, which comprises: a "one-step" methylation detection reagent for MSRE-qPCR and a quality control reagent.

[0013] In one or more embodiments, the "one-step" methylation detection reagent of MSRE-qPCR of the bladder cancer gene methylation detection kit comprises a methylation modification sensitive restriction endonuclease, a DNA polymerase, a deoxyribonucleoside triphosphate (dNTP / dUTP premix), a uracil-DNA glycosylase, a primer that specifically recognizes and / or binds to a target sequence, a probe that specifically recognizes and / or binds to a target sequence, and a buffer.

[0014] In one or more embodiments, the methylation modification sensitive restriction endonuclease contained in the "one-step" methylation detection reagent of MSRE-qPCR of the bladder cancer gene methylation detection kit comprises AciI, HhaI, HinP1I, AvaI, HaeII, HpaII and / or SmaI.

[0015] In one or more embodiments, the primer sequence that specifically recognizes and / or binds to the target sequence in the "one-step" methylation detection reagent of the MSRE-qPCR of the bladder cancer gene methylation detection kit is SEQ ID NO: 1-70; the probe sequence that specifically recognizes and / or binds to the target sequence is SEQ ID NO: 71-81.

[0016] In one or more embodiments, the quality control reagents of the bladder cancer gene methylation detection kit include a negative control, a positive control, and a blank control.

[0017] In one or more embodiments, the bladder cancer gene methylation detection kit is used for bladder cancer gene methylation detection, and the detection steps include: I. sample DNA extraction and purification; II. "one-step" methylation detection of MSRE-qPCR; III. data analysis of detection results; the step II. "one-step" methylation detection of MSRE-qPCR uses the bladder cancer gene methylation detection kit described in the present application.

[0018] In one or more embodiments, in the application of the bladder cancer gene methylation detection kit, the step II. MSRE-qPCR "one-step" methylation detection step comprises: a) mixing the DNA sample extracted and purified in step I. with the MSRE-qPCR "one-step" methylation detection reagent in the bladder cancer gene methylation detection kit of the present application to obtain a mixed solution; b) enzyme digestion; c) PCR amplification.

[0019] In one or more embodiments, the bladder cancer gene methylation detection kit of the present application is used for early diagnosis, risk assessment, treatment guidance and recurrence monitoring of bladder cancer.

[0020] In one or more embodiments, the bladder cancer gene methylation detection kit of the present application is used for auxiliary diagnosis of recurrence of non-muscle invasive bladder cancer (NMIBC).

[0021] In one or more embodiments, the bladder cancer gene methylation detection method of the present application is used for early diagnosis, risk assessment, treatment guidance and recurrence monitoring of bladder cancer.

[0022] In one or more embodiments, the bladder cancer gene methylation detection method of the present application is used for auxiliary diagnosis of recurrence of non-muscle invasive bladder cancer (NMIBC). BRIEF DESCRIPTION OF THE DRAWINGS

[0023] Figure 1 , Schematic diagram of “one-step” gene methylation detection by MSRE-qPCR; Figure 2 , distribution diagram of the measured average methylation rate of 100% methylated reference; Figure 3 , distribution diagram of the measured average methylation rate of 50% methylation reference; Figure 4 , distribution diagram of the measured average methylation rate of 0% methylation reference; Figure 5 , distribution diagram of measured methylation rate of anti-pollution system and normal system; Figure 6 , “One-step” gene methylation detection target screening process of MSRE-qPCR; Figure 7 , Flow chart for validation of the effect of the “one-step” gene methylation detection method of MSRE-qPCR; Figure 8 , Table 3 - qPCR detection reaction conditions; Fig. 9 , Table 4 - 100% methylation reference test results; Fig.10 , Table 5-50% methylation reference test results; Fig.11 , Table 6 - 0% methylation reference test results; Fig.12 , Table 10 - qPCR amplification procedure. DETAILED DESCRIPTION

[0024] In order to more clearly illustrate the technical solution of the present invention, the technical solution in the embodiments of the present invention will be clearly and completely described below. The following embodiments are only used to explain the present invention and should not be regarded as limiting the scope of the present invention. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without making creative work belong to the scope of protection of the present invention. Example 1, "One-step" gene methylation detection method of MSRE-qPCR:

[0025] The "one-step" gene methylation detection method of MSRE-qPCR combines DNA methylation-sensitive restriction endonuclease (MSRE) digestion with the qPCR amplification system. In this method, methylation-sensitive restriction enzyme (MSRE) digestion and qPCR amplification are completed in the same system, and a uracil-DNA glycosylase (UDG) anti-contamination system is added to the reaction system.

[0026] The "one-step" methylation detection reagent of MSRE-qPCR described in the present application comprises a modification-sensitive restriction endonuclease, a DNA polymerase, a deoxyribonucleoside triphosphate (dNTP / dUTP premix), a uracil-DNA glycosylase (UDG), a primer that specifically recognizes and / or binds to a target sequence and / or a probe that specifically recognizes and / or binds to a target sequence, and a buffer.

[0027] In the reaction mixture of the "one-step" gene methylation detection method of MSRE-qPCR described in the present application, MSRE, DNA polymerase (such as thermophilic DNA polymerase or hot start DNA polymerase system), oligonucleotide primers and buffer are prepared together to promote the activity of MSRE and DNA polymerase.

[0028] The MSRE used in the "one-step" gene methylation detection method of MSRE-qPCR described in the present application can be a naturally occurring or engineered enzyme; the qPCR method for detecting DNA amplification in the present method is a qPCR amplification method known in the art. PCR reaction solution (Taq DNA polymerase, 10×Buffer, dNTP / dUTP premix, PCR enhancer, UNG enzyme, ROX reference dye), enzyme digestion mixture (methylation-sensitive restriction endonuclease, including but not limited to AciI, HhaI, HinP1I, AvaI, HaeII, HpaII, SmaI). The dNTP / dUTP premix includes dUTP, dTTP, dATP, dCTP and / or dGTP; further, the dNTP / dUTP premix contains dUTP and dTTP, and the ratio of the two is 1:10 to 10:1, preferably 1:1.

[0029] The "one-step" gene methylation detection method of MSRE-qPCR described in the present application comprises the following steps: 1) contacting the sample to be tested (DNA sample after extraction and purification) with the MSRE enzyme digestion and qPCR amplification reaction mixture to complete MSRE enzyme digestion and qPCR amplification; 2) analyzing the detection result data.

[0030] The amplification system (MSRE digestion and qPCR amplification reaction mixture) of the "one-step" gene methylation detection method of MSRE-qPCR includes methylation-sensitive restriction enzyme (MSRE), deoxyribonucleoside triphosphate (dNTP / dUTP premix), upstream primers, downstream primers, probes, and nucleic acid polymerase for target gene amplification. The anti-pollution system can use uracil-DNA glycosylase (UDG). After the sample to be tested is digested by MSRE, the upstream primers, downstream primers, and probes for target gene amplification in the system are used for qPCR amplification in the same reaction system to obtain the test results. The schematic diagram of the "one-step" gene methylation detection method of MSRE-qPCR is shown in the figure. Figure 1 shown.

[0031] The operating steps of the "one-step" gene methylation detection method of MSRE-qPCR described in this application are as follows: (1) DNA extraction: Use a commercially available DNA extraction kit and follow the DNA extraction and purification methods recommended in its instructions to obtain the DNA sample to be tested; (2) "One-step" gene methylation detection by MSRE-qPCR: a) Preparation of MSRE-qPCR reagents: Mix the enzyme digestion mixture, PCR reaction solution, primer probe mixture, and buffer, and oscillate to mix; b) Preparation of test samples: Use pure water (nuclease-free) to dilute the DNA sample obtained in step (1), use pure water (nuclease-free) to dilute the positive control, negative control, and blank control, and add the MSRE-qPCR reagent prepared in step a); c) MSRE-qPCR amplification: Set up the PCR amplification program, adjust the PCR reaction conditions according to the characteristics of different target genes and different methylation-sensitive restriction enzymes, and perform PCR amplification; (3) Data analysis of test results. Example 2, screening of conditions for the “one-step” gene methylation detection method of MSRE-qPCR:

[0032] In order to determine the optimal methylation-sensitive restriction endonuclease digestion time, we ensured that the non-methylated template was fully digested while avoiding over-digestion. Taking HOXA9 as the research object, we measured the methylation rates of the gradient methylation rate reference (methylation rates were 100%, 50%, and 0%) after treatment with the methylation-sensitive restriction endonuclease in the target technical solution for 0, 15, 30, 45, 60, 75, 90, 105, 120, 135, 150, and 165 minutes, respectively. The time period when the measured methylation rate was consistent with the expected methylation rate was determined as the optimal digestion time.

[0033] The specific implementation plan is as follows: 1. Prepare the reaction system. Prepare the enzyme digestion reaction system in an ice box according to Table 1. The 0-minute enzyme digestion reaction system needs to be prepared before the qPCR machine.

[0034] Table 1. Enzyme digestion PCR reaction system Components Volume (μL) PCR reaction solution 10 HOXA9 Primer Probe Mixture 5 Enzyme Digestion Mix 1.5 DNA 8.5 (15 ng) Total volume 25 2. Place the sample digested for 165 minutes in a common PCR instrument and run the reaction program in Table 2. Then, in the order of digestion time from high to low, place the samples with corresponding digestion time in the PCR instrument every 15 minutes. After digestion, centrifuge briefly and transfer the sample to the qPCR instrument to determine the methylation rate.

[0035] Table 2. Enzyme digestion reaction conditions stage temperature time 1 37℃ 165min 2 95℃ 10min 3. After the enzyme digestion products and non-enzyme digestion reaction system are transferred to the qPCR instrument, run as shown in the attached Figure 8 The program shown in Table 3 was used to detect the methylation rate of each reference product at different enzyme cutting times.

[0036] 4. After exporting the test data, calculate the dCT value of HOXA9 and the internal reference at the corresponding well (HOXA9 CT-internal reference CT), and the methylation rate = 1 / (2^dCT) × 100%. The inventors set up 3 technical replicates in each enzyme digestion period, calculated the mean of the measured methylation rate and compared it with the expected methylation rate. The test results of the 100%, 50%, and 0% methylation rate reference products and the methylation rate calculation results are shown in the attached figure. Figure 9-11 As shown in Tables 4, 5 and 6, the average methylation rate distribution is as follows Figure 2 , Figure 3 , Figure 4 shown.

[0037] The test results show that the enzyme cutting time is 30-120 minutes, and the measured and expected methylation rates are consistent, which is the optimal enzyme cutting time range. Furthermore, the enzyme cutting time is 45-75 minutes. If the enzyme cutting time is less than 30 minutes, the enzyme cutting is incomplete, the background methylation rate increases, and the detection specificity is poor. If it is higher than 120 minutes, over-enzyme cutting occurs, the measured methylation rate is lower than expected, the positive reference signal is weakened, and the detection sensitivity is low. Example 3, optimization of the "one-step" gene methylation detection method of MSRE-qPCR:

[0038] The "one-step" gene methylation detection method of MSRE-qPCR of the present application integrates an anti-pollution system based on UDG enzyme in the one-step enzyme-qPCR system, in order to reduce the impact of product contamination on the quantitative results of methylation. In order to prove the actual improvement effect, the inventor mixed 0.0001ng of amplified product DNA with 15ng of methylation-positive clinical sample (known methylation rate) DNA to prepare a simulated contaminated sample. The anti-pollution enzyme-amplification system and the conventional enzyme-amplification system without UDG and dNTP / dUTP premix anti-pollution components were used to detect methylation abundance and calculate the methylation rate. Because the mixed amplification product is in a non-methylated state, the methylation-sensitive restriction endonuclease used in the target technical solution can cut the target contaminated template but cannot cut the internal reference contaminated template. As a result, the measured methylation rate of the conventional enzyme-amplification reaction system will be significantly lower than that of the anti-pollution enzyme-amplification system, and the effect is verified.

[0039] The specific implementation plan is as follows: 1. Test sample preparation: Take the amplification products of HOXA9+ACTB-M1 and SIM2+ACTB-M2 anti-pollution reaction systems. After using Qubit HS quantitative reagent to detect the concentration, dilute them to the theoretical concentration of 0.00012ng / μL, with a total volume of 10μL. Take 180ng of urine precipitated DNA sample with a clear methylation rate and mix it thoroughly with the above two amplification products. Add nuclease-free water to 102μL to obtain the sample to be tested; 2. Preparation of reaction system: prepare the anti-contamination enzyme digestion-amplification reaction system and the conventional enzyme digestion-amplification reaction system in an ice box according to Tables 7 and 8 and add the sample to be tested; Table 7. Anti-pollution enzyme digestion-amplification reaction system Components Volume (μL) PCR reaction solution (including UDG) 10 Primer probe mixture 5 Enzyme Digestion Mix 1.5 DNA 8.5 Total volume 25μL Table 8. Conventional enzyme digestion-amplification reaction system Components Volume (μL) PCR reaction solution (without UDG) 10 Primer probe mixture 5 Enzyme Digestion Mix 1.5 DNA 8.5 Total volume 25μL 3. qPCR detection: Place the reaction system on the heating module of the qPCR instrument, confirm that the tube cover is sealed again, and close the sample compartment door. Set the fluorescence channel selected for each detection tube according to Table 9, and Fig.12 The qPCR amplification program was set up according to the amplification program in Table 10, and then the detection was started; Table 9. Signal channels selected for fluorescence detection of each target gene Reagents Gene Signal Channel PCR working solution 1 (tube 1) HOXA9 FAM PCR working solution 1 (tube 1) ACTB-M1 VIC PCR working solution 2 (tube 2) SIM2 FAM PCR working solution 1 (tube 1) ACTB-M2 VIC 4. After exporting the test data, calculate the dCT value of HOXA9 and the internal reference at the corresponding well (HOXA9 CT-internal reference CT), and the methylation rate = 1 / (2^dCT) × 100%. The inventors set up 3 technical replicates in the anti-contamination enzyme digestion-amplification system and the conventional enzyme digestion-amplification system group of the two targets, and the results are shown in Table 11. The methylation rate distribution is as follows Figure 5 shown.

[0040] Table 11. Measured data of two-target anti-pollution system and conventional system Well Sample Name Target Name Target Cт Internal reference CT dCT Methylation rate A1 Anti-pollution system HOXA9 25.68 25.38 0.30 81.0% A2 Anti-pollution system HOXA9 25.71 25.45 0.27 83.1% A3 Anti-pollution system HOXA9 25.66 25.36 0.30 81.3% G1 Conventional system HOXA9 33.61 25.79 7.82 0.4% G2 Conventional system HOXA9 33.14 25.86 7.28 0.6% G3 Conventional system HOXA9 33.50 26.04 7.46 0.6% A4 Anti-pollution system SIM2 25.98 25.86 0.12 91.9% A5 Anti-pollution system SIM2 25.85 25.71 0.14 90.9% A6 Anti-pollution system SIM2 25.92 25.77 0.14 90.4% G4 Conventional system SIM2 31.86 26.11 5.75 1.9% G5 Conventional system SIM2 32.00 26.32 5.68 2.0% G6 Conventional system SIM2 32.06 25.83 6.24 1.3% The test results show that the anti-pollution system UDG enzyme can indiscriminately remove dUTP-containing target and internal reference contaminants, while the conventional system can only digest dUTP-containing target contaminants with methylation-sensitive restriction endonucleases and cannot remove internal reference contaminants, resulting in a significantly lower measured methylation rate than the anti-pollution system, causing false negative results. The anti-pollution system can effectively avoid the impact of amplification product contamination on detection sensitivity, and the detection results are more reliable than conventional reaction systems. Example 4: Target screening for early diagnosis, early screening and auxiliary diagnosis of bladder cancer:

[0041] By performing gene methylation testing on a large number of bladder cancer initial diagnosis samples and follow-up samples, it was found that the methylation levels of CpG sites in specific regions of 6 target genes were different in bladder cancer initial diagnosis positive samples and initial diagnosis negative samples, and in bladder cancer follow-up positive samples and follow-up negative samples, which can be used as marker genes for bladder cancer detection.

[0042] Through Figure 6 The target screening process shown was used to screen target genes, and a total of 6 genes, including HOXA9, SIM2, ZNF154, KCNMA1, FOXF2, and VIM, were selected as candidate targets.

[0043] A total of 90 samples were used for target gene screening, including 45 positive samples (including 20 positive samples of bladder cancer at initial diagnosis and 25 positive samples at follow-up), and 45 negative samples (including 20 negative samples of bladder cancer at initial diagnosis and 25 negative samples at follow-up). The deltaCT value of the gene was detected using the preferred MSRE-qPCR "one-step" gene methylation detection method in Example 3, and then a logistic regression model was performed. The detection performance of the target was obtained by the model, and the target with the best performance was finally selected.

[0044] According to the expected performance target, the sensitivity is set to be above 90.00%. In this embodiment, the value when the sensitivity is above 90.00% is 91.11% (41 / 45). At this sensitivity, the specificity of the target is compared and the target with high specificity is selected.

[0045] The detection performance of single target gene modeling for bladder cancer is shown in Table 12 below: Table 12. Detection performance of single target gene for bladder cancer Target genes Gene interval Sensitivity (%) Specificity (%) SIM2 chr21:38077091-38077341 91.11 77.78 SIM2 chr21: 38077592-38077842 91.11 68.89 SIM2 chr21: 38077341-38077592 91.11 64.44 SIM2 chr21: 38076841-38077091 91.11 60.00 HOXA9 chr7:27206751-27207001 91.11 71.11 HOXA9 chr7:27207001-27207251 91.11 68.89 HOXA9 chr7:27206251-27206501 91.11 62.22 HOXA9 chr7:27206001-27206251 91.11 64.44 ZNF154 chr19:58219992-58220242 91.11 48.89 ZNF154 chr19:58219742-58219992 91.11 46.67 ZNF154 chr19:58220242-58220492 91.11 46.67 ZNF154 chr19:58220492-58220742 91.11 44.44 KCNMA1 chr10:79396690-79396940 91.11 31.11 KCNMA1 chr10:79396440-79396690 91.11 28.89 KCNMA1 chr10:79396940-79397190 91.11 31.11 KCNMA1 chr10:79397190-79397440 91.11 26.67 FOXF2 chr6:1384439-1384689 91.11 37.78 FOXF2 chr6:1384189-1384439 91.11 33.33 FOXF2 chr6:1384689-1384939 91.11 31.11 FOXF2 chr6:1384939-1385189 91.11 31.11 VIM chr10:17271339-17271589 91.11 57.78 VIM chr10:17271089-17271339 91.11 51.11 VIM chr10:17270839-17271089 91.11 55.56 VIM chr10:17271589-17271839 91.11 48.89 When the sensitivity was 91.11%, the specificity of the targets was compared. From the results in the table, it can be seen that the specificity of the SIM2 interval chr21:38077091-38077341 was the highest, which was 77.78%, and the specificity of the HOXA9 interval chr7:27206751-27207001 was the second, which was 71.11%.

[0046] The interval with the highest specificity in each gene was selected as the target for the gene, and the target genes were combined in pairs to perform modeling. The detection performance for bladder cancer is shown in Table 13 below: Table 13. Detection performance of target gene combination for bladder cancer Target combination Sensitivity (%) Specificity (%) HOXA9, SIM2 91.11 86.67 HOXA9, ZNF154 91.11 75.56 SIM2, VIM 91.11 75.56 SIM2, KCNMA1 91.11 75.56 SIM2, ZNF154 91.11 71.11 HOXA9, KCNMA1 91.11 68.89 SIM2, FOXF2 91.11 66.67 ZNF154, VIM 91.11 60.00 HOXA9, VIM 91.11 57.78 FOXF2, VIM 91.11 53.33 HOXA9, FOXF2 91.11 53.33 KCNMA1, VIM 91.11 51.11 ZNF154, KCNMA1 91.11 42.22 ZNF154, FOXF2 91.11 40.00 KCNMA1, FOXF2 91.11 37.78 When the sensitivity was 91.1%, the specificity of the target gene combination was compared. From the results in Table 13, it can be seen that when HOXA9 and SIM2 were combined, the specificity was the highest, which was 86.67%. Therefore, the optimal target combination was determined to be HOXA9 and SIM2.

[0047] A new marker combination consisting of HOXA9 / SIM2 methylation targets was obtained through screening for auxiliary diagnosis of initial diagnosis and recurrence of NMIBC patients. Example 5: Early diagnosis, screening and auxiliary diagnosis of bladder cancer gene methylation detection:

[0048] According to Example 4, the gene combination of HOXA9 gene and SIM2 gene was screened and obtained as the target gene combination. The target gene interval and primer probe sequence included in the gene combination are shown in Table 14.

[0049] Table 14. Primer probe sequences for methylation detection of bladder cancer recurrence monitoring genes Gene Interval SEQ ID NO Oligo ID Oligo sequence HOXA9 chr7:27206751-27207001 1 F1-1 CTCACCAGCAGTTCCAGTAATC HOXA9 chr7:27206751-27207001 2 F1-2 ATCCTCACCAGCAGTTCCAG HOXA9 chr7:27206751-27207001 3 F1-3 CTTCATCCTCACCAGCAGTTC HOXA9 chr7:27206751-27207001 4 F1-4 CCTGACACACTTCCGGCT HOXA9 chr7:27206751-27207001 5 R1-1 GTCGGCCACTTCCCTCTTC HOXA9 chr7:27206751-27207001 6 R1-2 GGCCACTTCCCTCTTCCAG HOXA9 chr7:27206751-27207001 7 R1-3 TTCATTGTGTCGGCCACTTC HOXA9 chr7:27206751-27207001 8 R1-4 GGGGCCATTTCGGAGTTCAT HOXA9 chr7: 27207001-27207251 9 F2-1 CACAGTCCACCGTGTCCT HOXA9 chr7: 27207001-27207251 10 F2-2 CCACCACAGTCCACCGT HOXA9 chr7: 27207001-27207251 11 F2-3 GCCCCATAAATTCCTCTAGGTCAT HOXA9 chr7: 27207001-27207251 12 F2-4 CTAATATTTTCCTTGCCCCATAAATTCCT HOXA9 chr7: 27207001-27207251 13 R2-1 CAGCCCATTTGCAGACACT HOXA9 chr7: 27207001-27207251 14 R2-2 TGGAAAAGGCATCCAGACATG HOXA9 chr7: 27207001-27207251 15 R2-3 GAAATAATCAGTGTCTTCTCAGGCAT HOXA9 chr7: 27207001-27207251 16 R2-4 AAACGTGGAAAAGGCATCCAG HOXA9 chr7:27206251–27206501 17 F3-1 GCCTAAGACCCCGCAG HOXA9 chr7:27206251–27206501 18 F3-2 AAAAGGCAGCCTCGCCT HOXA9 chr7:27206251–27206501 19 F3-3 ATGAATGGAAGGCAAGTTCGGT HOXA9 chr7:27206251–27206501 20 F3-4 GGAAAAAACTACAAGTGGCATGAATG HOXA9 chr7:27206251–27206501 21 R3-1 GAAGGAGCCCTGAAAGGCT HOXA9 chr7:27206251–27206501 22 R3-2 GCCCGGAGTAGCAGCT HOXA9 chr7:27206251–27206501 23 R3-3 GGCGAGGCCCGGAGT HOXA9 chr7:27206251–27206501 24 R3-4 CCGGGCCCCGTAGGT HOXA9 chr7: 27206001-27206251 25 F4-1 CCTCGACCCCACGCAC HOXA9 chr7: 27206001-27206251 26 F4-2 GAGGGCCTGGTTGGTTGT HOXA9 chr7: 27206001-27206251 27 F4-3 GCGAAGGTTTTGAGGGCCT HOXA9 chr7: 27206001-27206251 28 F4-4 CACCAGGGCGAAGGTTTTG HOXA9 chr7: 27206001-27206251 29 R4-1 AGCCGCCTGCGCCT HOXA9 chr7: 27206001-27206251 30 R4-2 TCTGAGGCTGGAGCACAG HOXA9 chr7: 27206001-27206251 31 R4-3 ATGGTTAGAGCCTCTGAGGCT HOXA9 chr7: 27206001-27206251 32 R4-4 GCTTGCAGCGCTCATGGT SIM2 chr21:38077091–38077341 33 F1-1 CAGTTTGGAAAAAGGCGCAAG SIM2 chr21:38077091–38077341 34 F1-2 CCCCTTCTCACCCGGTC SIM2 chr21:38077091–38077341 35 F1-3 CCGCGGGAGGCTTTCT SIM2 chr21:38077091-38077341 36 F1-4 GGATCCCAGTAAATTGTCGCAAT SIM2 chr21:38077091-38077341 37 R1-1 CACAAAAGGATCCCAGTAAATTGTC SIM2 chr21:38077091-38077341 38 R1-2 TTGAGCCTCTAAGCCTCCTTTC SIM2 chr21:38077091-38077341 39 R1-3 CTTGGGGCGTCCCCAC SIM2 chr21:38077091-38077341 40 R1-4 CTTCAATCCTTCTCCCGCGT SIM2 chr21: 38077592-38077842 41 F2-1 CGAAAGTGAGACCTTGAGTCCT SIM2 chr21: 38077592-38077842 42 F2-2 GCAATCCGAAAGTGAGACCTT SIM2 chr21: 38077592-38077842 43 F2-3 AAGTGGTTTGCAATCCGAAAGT SIM2 chr21: 38077592-38077842 44 F2-4 TTGACTTCGAAGTGGTTTGCAAT SIM2 chr21: 38077592-38077842 45 R2-1 TCCCTCTCTGGCTTTCCCA SIM2 chr21: 38077592-38077842 46 R2-2 GTGCCTCCCTCTCTGGCT SIM2 chr21: 38077592-38077842 47 R2-3 CGGGCTGCCATCACTTTGT SIM2 chr21: 38077592-38077842 48 R2-4 GTTTGCCGGGCTGCCAT SIM2 chr21: 38077341-38077592 49 F3-1 CCCGGCGACTGGTGTTC SIM2 chr21: 38077341-38077592 50 F3-2 ACAGGTTCCCGGCGACT SIM2 chr21: 38077341-38077592 51 F3-3 TACGCCCTGGCACAGGT SIM2 chr21: 38077341-38077592 52 F3-4 GAGAACCTGGCCCCAAACT SIM2 chr21: 38077341-38077592 53 R3-1 CGGGCAGCCTCTACAGCT SIM2 chr21: 38077341-38077592 54 R3-2 DEFECTSGGGATCCTGGAGCT SIM2 chr21: 38077341-38077592 55 R3-3 CACGCAAGCACATATTGGGAT SIM2 chr21: 38077341-38077592 56 R3-4 CTGCTCCACGCAAGCACAT SIM2 chr21: 38076841-38077091 57 F4-1 GGCGGAAAGGGAGCCT SIM2 chr21: 38076841-38077091 58 F4-2 GAGGGGACCTGGATCCCTG SIM2 chr21: 38076841-38077091 59 F4-3 CTAGAGGAGGGGACCTGGAT SIM2 chr21: 38076841-38077091 60 F4-4 CGCGCGCTGCAGATTC SIM2 chr21: 38076841-38077091 61 R4-1 CGCAGACCTGGGGAGTTC SIM2 chr21: 38076841-38077091 62 R4-2 CCCGGTGCCCCCATTG SIM2 chr21: 38076841-38077091 63 R4-3 CGCGGGTATCCTACGTATTCT SIM2 chr21: 38076841-38077091 64 R4-4 CGCCCGCGGGTATCCT ACTB chr7:5567833-5568195 65 F1 GTCAGGCAGCTCGTAGCTCT ACTB chr7:5567833-5568195 66 R1 ATCGTGCGTGACATTAAGGAG ACTB chr7:5573618-5574043 67 F2 TGTCTCCAACTCCTGGGCT ACTB chr7:5573618-5574043 68 R2 AAAGGCTGTTTGAAAGTCGGAAT ACTB chr7:5573010-5573251 69 F3 GTGAGAAGCCATACCTCTACAGAT ACTB chr7:5573010-5573251 70 R3 TGCAGCCTCGACCTCCT HOXA9 chr7:27206751-27207001 71 Probe1 TGGCAGCCTCGCTGGTATTTG HOXA9 chr7: 27207001-27207251 72 Probe2 ACCCTGGAGGAAACCCTGGC HOXA9 chr7:27206251-27206501 73 Probe3 ATGTGGCCTGTCCCGGGG HOXA9 chr7: 27206001-27206251 74 Probe4 TCTCATCAGCTGGCAATCAGGATTC SIM2 chr21:38077091-38077341 75 Probe1 TGTTCTCCCCGGGGTCCCT SIM2 chr21: 38077592-38077842 76 Probe2 TCACGCTCCCCAGAAACACCC SIM2 chr21: 38077341-38077592 77 Probe3 TGCTGCGGCTTCTGGGTCAT SIM2 chr21: 38076841-38077091 78 Probe4 CTCGGAGCCAGCAGCTGCT ACTB chr7:5567833-5568195 79 Probe1 CCGTGGCCATCTCTTGCTCGAAGT ACTB chr7:5573618-5574043 80 Probe2 CCATCACACCCCAGTGGGAGAG ACTB chr7:5573010-5573251 81 Probe3 TTAGCCAGGCTTGGAAGTGTGTG According to the preferred "one-step" gene methylation detection method of MSRE-qPCR in Example 3, the gene combination of HOXA9 gene and SIM2 gene screened and obtained in Example 4 was used as the target gene combination, and the ACTB gene was used as the internal reference gene to perform gene methylation detection and analysis for bladder cancer recurrence monitoring. The specific experimental steps are as follows: 1. Preparation of MSRE enzyme digestion-qPCR system: The concentration of the DNA sample to be tested is determined using the Qubit HS quantitative kit, 15 ng is taken into a PCR tube, and the components are mixed according to the MSRE enzyme digestion-qPCR reaction system (anti-pollution enzyme digestion amplification system) shown in Table 7 of Example 3. The "one-step" methylation detection reagent of MSRE-qPCR includes modification-sensitive restriction endonucleases, DNA polymerases, deoxyribonucleoside triphosphates (dNTP / dUTP premix), uracil-DNA glycosylase (UDG), primers that specifically recognize and / or bind to target sequences and / or probes that specifically recognize and / or bind to target sequences, and buffer, and the above substances are mixed; after adding the sample, make sure that the tube cap is covered, shake and mix, centrifuge for 30 seconds (avoid bubbles, if there are bubbles, flick with your fingers, and re-centrifuge), and immediately perform PCR amplification reaction.

[0050] 2. qPCR amplification: Place the reaction plate / reaction tubes on the heating module of the PCR instrument in the preset order, confirm that the tube sealing film / tube cover is sealed again, and then close the sample compartment door. Set the "number of test tubes contained in a single sample" to 2, set the fluorescent channel selected for each detection tube according to Table 9 in Example 3, and set the PCR amplification program according to Table 10 in Example 3.

[0051] 3. Analysis of test results: (1) Condition setting and reading: After the reaction is completed, use the software supporting the fully automatic medical PCR analysis system SLAN-96S to read and analyze the data. Select "Relative fluorescence value method-log" in "Amplification curve algorithm" in "Parameter setting" and set the baseline threshold of each gene according to Table 15.

[0052] Table 15. Baseline threshold setting requirements Target genes Manual Threshold Baseline start point Baseline endpoint HOXA9 0.12 6 12 ACTB-M1 0.12 6 12 SIM2 0.12 6 12 ACTB-M2 0.12 6 12 Note: The "Baseline Optimization" column of the baseline threshold setting of the fully automated medical PCR analysis system SLAN-96S defaults to the "Automatic Optimization" mode and should not be adjusted unless necessary.

[0053] (2) Quality control: 1) Quality control of reference materials: ① The Ct value or △Ct value of the detection signal of each channel of the positive control, negative control and blank control should meet the requirements of Table 16; ② The results of the test samples can only be judged after the Ct value or △Ct value of the positive control, negative control and blank control is qualified.

[0054] Table 16. Requirements for the Ct value or △Ct value of the detection signal of positive control, negative control and blank control Reference substance name Tube Name Gene Signal Channel Amplification results Positive Control Tube 1 HOXA9 FAM △Ct≤6 Positive Control Tube 1 ACTB-M1 VIC 19≤Ct≤28 Positive Control Tube 2 SIM2 FAM △Ct≤6 Positive Control Tube 2 ACTB-M2 VIC 19≤Ct≤28 Negative Control Tube 1 HOXA9 FAM △Ct>9 Negative Control Tube 1 ACTB-M1 VIC 19≤Ct≤28 Negative Control Tube 2 SIM2 FAM △Ct>8 Negative Control Tube 2 ACTB-M2 VIC 19≤Ct≤28 Blank control Tube 1 HOXA9 FAM 40<Ct Blank control Tube 1 ACTB-M1 VIC 40<Ct Blank control Tube 2 SIM2 FAM 40<Ct Blank control Tube 2 ACTB-M2 VIC 40<Ct 2) Internal control: The internal reference gene ACTB signal channel 19 ≤ Ct value ≤ 28 of the sample to be tested, otherwise the sample is considered invalid.

[0055] (3) Software automated result analysis: Export a .txt file containing Ct value result information (curve information should not be included) through the supporting software of the fully automatic medical PCR analysis system SLAN-96S. Use the V1 version of the non-muscle-invasive bladder cancer multi-gene joint detection data analysis software to analyze the .txt file, obtain the score value and give the comprehensive judgment result of the kit. Example 6: Performance verification in early diagnosis and screening of bladder cancer:

[0056] According to the gene methylation detection method for monitoring the initial diagnosis and recurrence of bladder cancer described in Example 5, the "one-step" gene methylation detection system of MSRE-qPCR was used to verify the effect of gene methylation detection on urine samples of patients with initial diagnosis of bladder cancer.

[0057] After the optimal targets HOXA9 and SIM2 were determined, the model performance was verified using 293 newly diagnosed bladder cancer samples (171 newly diagnosed positive samples and 122 newly diagnosed negative samples). The delta CT of HOXA9 and SIM2 of the newly diagnosed samples was used as input to the logistic regression model to obtain the model prediction results. The process is as follows: Figure 7 The results of HOXA9 and SIM2 targets in predicting bladder cancer samples at initial diagnosis are shown in Table 17.

[0058] Table 17. Results of HOXA9 and SIM2 targets in predicting bladder cancer initial diagnosis samples Sensitivity (%) Specificity (%) Positive predictive value (%) (PPV) Negative predictive value (%) (NPV) Initial diagnosis sample 90.64 91.80 93.93 87.50 In the newly diagnosed bladder cancer samples, the sensitivity of the HOXA9 and SIM2 target combination was 90.64%, the specificity was 91.80%, the PPV was 93.93%, and the NPV was 87.50%. Example 7: Verification of the effect of methylation gene detection method in auxiliary diagnosis of bladder cancer:

[0059] According to the gene methylation detection method for monitoring the initial diagnosis and recurrence of bladder cancer described in Example 5, the urine samples of bladder cancer follow-up patients were used to verify the effect of gene methylation detection using the "one-step" gene methylation detection system of MSRE-qPCR.

[0060] The effect of gene methylation detection was verified in urine samples of patients with non-muscle invasive bladder cancer (NMIBC).

[0061] After the optimal targets HOXA9 and SIM2 were determined, the model performance was verified using 112 bladder cancer follow-up samples (39 bladder cancer follow-up positive samples and 73 follow-up negative samples). The delta CT of HOXA9 and SIM2 in the follow-up samples was used as input to the logistic regression model to obtain the model prediction results. The process is as follows Figure 7 As shown, the results of HOXA9 and SIM2 targets predicting bladder cancer follow-up samples are shown in Table 18 below.

[0062] Table 18. Results of HOXA9 and SIM2 targets in predicting bladder cancer follow-up samples Sensitivity (%) Specificity (%) Positive predictive value (%) (PPV) Negative predictive value (%) (NPV) Follow-up samples 89.74 90.41 83.30 94.30 In the follow-up samples of bladder cancer, the performance of the combination of HOXA9 and SIM2 targets was 89.74% sensitive, 90.41% specific, 83.30% PPV, and 94.30% NPV. Example 8: Verification of the detection effect of auxiliary diagnosis samples for bladder cancer:

[0063] The bladder cancer initial diagnosis samples and follow-up samples were combined, and the delta CT of HOXA9 and SIM2 of all samples were used as input to the logistic regression model to obtain the model prediction results. The process is as follows Figure 7 As shown, the results of HOXA9 and SIM2 target prediction of bladder cancer samples are shown in Table 19 below.

[0064] Table 19. Results of HOXA9 and SIM2 target prediction for bladder cancer samples Sensitivity (%) Specificity (%) Positive predictive value (%) (PPV) Negative predictive value (%) (NPV) Bladder cancer samples 90.00 90.80 91.30 89.40 In bladder cancer samples, the performance of the combination of HOXA9 and SIM2 targets was 90.00% sensitive, 90.80% specific, 91.30% PPV, and 89.40% NPV.

[0065] The applicant of the present application has previously disclosed a kit for detecting gene methylation of urothelial carcinoma in patent CN202410585603.6, which includes the HOXA9 gene and a gene combination with 26 other genes. However, the traditional BS conversion method is used in patent CN202410585603.6. In specific embodiment 4 of patent CN202410585603.6, combination 2 is a gene combination of HOXA9 gene and SIM2 gene. The sensitivity of combination 2 to the detection performance of urothelial carcinoma is only 73.83% (see Table 4 in the specification of patent CN202410585603.6). The bladder cancer detection kit used in the present application adopts the "one-step" gene methylation detection method of MSRE-qPCR. The sensitivity of the gene combination of HOXA9 gene and SIM2 gene to the detection performance of urothelial carcinoma can reach 90.00%, and the detection effect is significantly better than the previous generation gene methylation detection kit of the applicant.

[0066] The existing product NMP22 BladderChek is a rapid, non-invasive detection tool mainly used to assist in the diagnosis and monitoring of bladder cancer. The product has a sensitivity of only 45.9%, a specificity of 86.3% and a PPV of 36.6%.

[0067] Table 20. Statistics of testing performance of different products Product Name Sensitivity (95% CI), % Specificity (95% CI), % Positive predictive value (PPV) (95% CI), % Negative predictive value (NPV) (95% CI), % MSRE-qPCR "one-step" gene methylation detection kit 90.00（79.9-95.5） 90.80（80.3-96.2） 91.30（81.4-96.4） 89.40（78.8-95.3） Combination 2 in CN202410585603.6 73.83 92.31 - - NMP22 BladderCheck 45.9(35.8-56.3) 86.3(83.2- 89.0) 36.6(28.1-45.8) 90.3(87.5-92.6) The bladder cancer gene methylation detection kit provided in the present application uses the "one-step" gene methylation detection method of MSRE-qPCR. The test results show that, compared with the clinical reference standard, the detection kit provided in the present application has good diagnostic performance for bladder cancer recurrence and meets the needs of clinical use. Compared with existing products, the detection kit provided in the present application has a detection sensitivity of 90.0% (95% CI: 79.9%-95.5%), a specificity of 90.8% (95% CI: 80.3%-96.2%), a positive predictive value (PPV) of 91.3% (95% CI: 81.4%-96.4%), and a negative predictive value (NPV) of 89.4% (95% CI: 78.8%-95.3%). All detection performance indicators are better than existing products.

[0068] The bladder cancer gene methylation detection kit provided in this application can more accurately identify bladder cancer recurrence, allowing patients to receive more timely clinical intervention; at the same time, it has a higher credibility in excluding the risk of recurrence, can assist clinical decision-making, reduce or postpone invasive examinations, and improve compliance; save testing costs and reduce the burden on patients and the medical system.

Claims

1. A bladder cancer gene methylation detection kit, characterized in that: The kit comprises: a "one-step" methylation detection reagent for MSRE-qPCR and a quality control reagent.

2. A bladder cancer gene methylation detection kit according to claim 1, characterized in that: The "one-step" methylation detection reagent of the MSRE-qPCR comprises a methylation modification-sensitive restriction endonuclease, a DNA polymerase, a dNTP / dUTP premix, a uracil-DNA glycosylase, a primer that specifically recognizes and / or binds to a target sequence, a probe that specifically recognizes and / or binds to a target sequence, and a buffer.

3. A bladder cancer gene methylation detection kit according to claim 2, characterized in that: The methylation modification sensitive restriction endonuclease contained in the "one-step" methylation detection reagent of the MSRE-qPCR comprises AciI, HhaI, HinP1I, AvaI, HaeII, HpaII and / or SmaI.

4. A bladder cancer gene methylation detection kit according to claim 2, characterized in that: The primer sequences for specifically recognizing and / or binding to the target sequence in the "one-step" methylation detection reagent of the MSRE-qPCR are SEQ ID NOs: 1-70; the probe sequences for specifically recognizing and / or binding to the target sequence are SEQ ID NOs: 71-81.

5. A bladder cancer gene methylation detection kit according to any one of claims 1 to 4, characterized in that: The quality control reagents include a negative control substance, a positive control substance, and a blank control substance.

6. Use of a bladder cancer gene methylation detection kit according to any one of claims 1 to 5, characterized in that: The bladder cancer gene methylation detection kit is used for bladder cancer gene methylation detection, and the detection steps include: Ⅰ. sample DNA extraction and purification; Ⅱ. "One-step" methylation detection of MSRE-qPCR; Ⅲ. Data analysis of detection results; The step Ⅱ. "One-step" methylation detection of MSRE-qPCR uses the bladder cancer gene methylation detection kit described in any one of claims 1-5.

7. Use of a bladder cancer gene methylation detection kit according to claim 6, characterized in that: The step II. The "one-step" methylation detection step of MSRE-qPCR comprises: a) mixing the DNA sample extracted and purified in step I. with the "one-step" methylation detection reagent of MSRE-qPCR in the bladder cancer gene methylation detection kit according to any one of claims 1 to 5 to obtain a mixed solution; b) enzyme digestion; c) PCR amplification.

8. Use of a bladder cancer gene methylation detection kit according to any one of claims 1 to 5, characterized in that: The bladder cancer gene methylation detection kit is used for early diagnosis, risk assessment, treatment guidance and recurrence monitoring of bladder cancer.

9. The use of a bladder cancer gene methylation detection kit according to claim 8, characterized in that: The bladder cancer gene methylation detection kit is used for auxiliary diagnosis of recurrence of bladder cancer NMIBC.

10. Use of a bladder cancer gene methylation detection kit according to any one of claims 6-7, characterized in that: The bladder cancer gene methylation detection is used for early diagnosis, risk assessment, treatment guidance and recurrence monitoring of bladder cancer.

11. Use of a bladder cancer gene methylation detection kit according to claim 10, characterized in that: The bladder cancer gene methylation detection is used for auxiliary diagnosis of recurrence of bladder cancer NMIBC.

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