A kit for detecting gene methylation of bladder cancer

Abstract

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

Description

Technical Field

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

[0002] Cancer is a disease caused by genetic mutations, resulting in cells losing their normal growth and differentiation controls, forming malignant tumors. These cells can invade surrounding tissues and spread through the blood or lymphatic system to other parts of the body, forming metastases. Cancer development is a multi-stage process that typically takes years. Early diagnosis and intervention in the cancer's progression are key to controlling its progression.

[0003] Currently, cancer diagnosis methods vary widely, encompassing traditional imaging, biopsy, liquid biopsy, and emerging AI-assisted diagnostic technologies. Common cancer diagnostic methods include: chest X-ray (CXR), once widely used for lung cancer screening, but now less commonly 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 use tracers to detect tumor metabolic activity and can determine whether a tumor is benign or malignant, as well as whether it has metastasized, but are costly and involve high radiation exposure; magnetic resonance imaging (MRI), which is radiation-free and suitable for radiation-sensitive patients, but has limited ability to detect early-stage cancer; biopsy, which is the gold standard for confirming cancer but is an invasive procedure; liquid biopsy, which analyzes tumor DNA fragments in the blood for non-invasive diagnosis and dynamic monitoring; multicancer early detection (MCED), which can identify multiple cancers by detecting cancer signals in the blood; and other methods, such as endoscopy and tumor marker testing.

[0004] Among numerous cancers, the incidence of urinary tract tumors is increasing annually. Urothelial carcinoma (UC), including upper tract urothelial carcinoma (UTUC) and lower tract urothelial carcinoma (BC), is characterized by high incidence, multiple primary sites, and high recurrence after surgery. Bladder cancer currently has one of the highest recurrence rates. Non-muscle invasive bladder cancer (NMIBC) accounts for 75% of all new bladder cancer cases. Within five years after initial treatment, the recurrence rate is approximately 12% to 85%, and the progression rate is approximately 2.9% to 50%. Promptly identifying recurrence in cancer patients is crucial for improving prognosis and enhancing their quality of life.

[0005] Currently, the most common means for recurrence monitoring of non-muscle invasive bladder cancer (NMIBC) in clinical practice are cystoscopy and urine exfoliative cytology analysis. However, both of them have problems such as strong invasiveness, high risk of complications, poor compliance, low sensitivity, and strong subjectivity of results. In addition, a number of urine detection products already on the market at home and abroad, including NMP22 BladderChek, UroVysion, etc., are limited by insufficient detection performance and lack of sufficient demonstration of clinical benefits, and have not been widely used. Therefore, there is an urgent need in clinical practice 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 epigenetics-based detection technology that aids in the early diagnosis, risk assessment, treatment guidance, and recurrence monitoring of cancer by analyzing the DNA methylation status.

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

[0008] The commonly used sample for bladder cancer gene detection is urine sample. Urine samples face some challenges in actual detection applications. Some patients are unable to provide sufficient urine samples due to diseases or other reasons; various metabolites, electrolytes, proteins, and microbial contaminants in urine will interfere with the extraction and purification of DNA. Due to various factors, the abundance of DNA in urine is low under the existing technical conditions, which greatly limits the accuracy of urine DNA-based detection results. In addition to improving sample collection and extraction techniques, it is also necessary to optimize existing detection techniques to improve the detection ability for low-abundance DNA samples. Summary of the Invention

[0009] To address 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, rapid, and highly accurate detection kit for recurrence monitoring in patients with non-muscle invasive bladder cancer (NMIBC). Furthermore, the bladder cancer gene methylation detection kit provided herein utilizes a "one-step" gene methylation detection method using MSRE-qPCR, in which methylation-sensitive restriction enzyme (MSRE) digestion and qPCR amplification are performed in the same system.

[0010] To solve the technical problems existing in the prior art, the present invention provides a digestion method based on methylation-sensitive restriction endonucleases (MSREs) to replace the traditional BS conversion method. Suitable endonuclease combinations are screened based on the restriction sites contained in the target region sequence to identify sites in the DNA sequence that have not undergone methylation modification and cut the DNA chain near them, while methylated sites are not affected. Subsequently, methylation-specific primers and probe combinations are used for qPCR detection and calculation of methylation levels. Compared with the BS conversion method, the MSRE method has the advantages of simple operation, low cost, and high sensitivity for low-abundance samples. It is particularly suitable for the precise detection of methylation targets with known specific sequences.

[0011] In conventional MSRE-qPCR methods, the enzyme digestion reaction and qPCR reaction are two separate steps. After the enzyme digestion is completed, the product needs to be purified and transferred to the PCR system. This increases the risk of sample loss, contamination, and confusion caused by additional steps such as opening the lid and transferring the tube. To address the above technical issues and improve the convenience of clinical use, this application combines the MSRE digestion and qPCR amplification systems. This application provides a "one-step" gene methylation detection method for MSRE-qPCR and 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 the 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 enzymes contained in the "one-step" methylation detection reagent of MSRE-qPCR in the bladder cancer gene methylation detection kit include AciI, HhaI, HinP1I, AvaI, HaeII, HpaII, and / or SmaI.

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

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

[0017] In one or more embodiments, the bladder cancer gene methylation detection kit is used for detecting bladder cancer gene methylation, and its detection steps include: I. Sample DNA extraction and purification; II. "One-step" methylation detection of MSRE-qPCR; III. Data analysis of the detection results; the "one-step" methylation detection in step II 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 "one-step" methylation detection step in step II includes: 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 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 recurrence-assisted diagnosis 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 method for detecting gene methylation of bladder cancer in the present application is used for the recurrence-assisted diagnosis of non-muscle invasive bladder cancer (NMIBC). BRIEF DESCRIPTION OF THE DRAWINGS

[0023] Figure 1 Schematic diagram of the "one-step" gene methylation detection by MSRE-qPCR;

[0024] Figure 2 Distribution diagram of the measured average methylation rate of 100% methylation reference;

[0025] Figure 3 Distribution diagram of the measured average methylation rate of 50% methylation reference;

[0026] Figure 4 Distribution diagram of the measured average methylation rate of 0% methylation reference;

[0027] Figure 5 Distribution diagram of the measured methylation rate of the anti-pollution system and the normal system;

[0028] Figure 6 Target screening process of the "one-step" gene methylation detection by MSRE-qPCR;

[0029] Figure 7 Flow chart for verifying the effect of the "one-step" gene methylation detection method by MSRE-qPCR;

[0030] Figure 8 Table 3 - qPCR detection reaction conditions;

[0031] Figure 9 Table 4 - Detection results of 100% methylation reference;

[0032] Figure 10 Table 5 - Detection results of 50% methylation reference;

[0033] Figure 11 Table 6 - Detection results of 0% methylation reference;

[0034] Figure 12 Table 10 - qPCR amplification program. DETAILED DESCRIPTION OF THE EMBODIMENTS

[0035] To more clearly illustrate the technical solution of the present invention, the technical solutions in the embodiments of the present invention will be described clearly and completely below. The following embodiments are only used to explain the present invention and should not be construed as limiting the scope of the present invention. All other embodiments obtained by those of ordinary skill in the art based on the embodiments of the present invention without creative efforts belong to the scope of protection of the present invention.

[0036] Example 1. "One-step" gene methylation detection method of MSRE-qPCR:

[0037] The "one-step" gene methylation detection method of MSRE-qPCR combines the digestion of DNA methylation-sensitive restriction endonuclease (MSRE) with the qPCR amplification system. In this method, the digestion of the methylation-sensitive restriction enzyme (MSRE) and the qPCR amplification are completed in the same system, and a uracil-DNA glycosylase (UDG) anti-pollution system is added to the reaction system.

[0038] The "one-step" methylation detection reagent of MSRE-qPCR described in this application includes a modified sensitivity restriction endonuclease, a DNA polymerase, deoxynucleoside triphosphates (dNTP / dUTP premix), uracil-DNA glycosylase (UDG), primers specifically recognizing and / or binding to the target sequence and / or probes specifically recognizing and / or binding to the target sequence, and a buffer.

[0039] In the reaction mixture of the "one-step" gene methylation detection method of MSRE-qPCR described in this application, MSRE, DNA polymerase (such as thermophilic DNA polymerase or hot start DNA polymerase system), oligonucleotide primers, and buffer are formulated together to promote the activities of MSRE and DNA polymerase.

[0040] The MSRE used in the "one-step" gene methylation detection method of MSRE-qPCR described in this application can be a naturally occurring or engineered enzyme; the qPCR method for detecting DNA amplification in this 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), digestion mixture (methylation-sensitive restriction endonuclease, including but not limited to AciI, HhaI, HinP1I, AvaI, HaeII, HpaII, SmaI). Wherein 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.

[0041] The "one-step" gene methylation detection method of MSRE-qPCR described in this application includes the following steps: 1) contacting the sample to be tested (DNA sample after extraction and purification) with the MSRE digestion and qPCR amplification reaction mixture to complete MSRE digestion and qPCR amplification; 2) data analysis of the detection results.

[0042] The amplification system (MSRE digestion and qPCR amplification reaction mixture) of the "one-step" gene methylation detection method of MSRE-qPCR includes a methylation-sensitive restriction enzyme (MSRE), deoxynucleoside triphosphate (dNTP / dUTP premix), upstream primer for target gene amplification, downstream primer, probe, nucleic acid polymerase, and the anti-contamination system can use uracil-DNA glycosylase (UDG); after the sample to be tested is digested by MSRE, qPCR amplification is carried out in the same reaction system using the upstream primer, downstream primer, and probe for target gene amplification in the system, and the detection results are obtained. The schematic diagram of the "one-step" gene methylation detection method of MSRE-qPCR is as Figure 1 shown.

[0043] The operation steps of the "one-step" gene methylation detection method of MSRE-qPCR described in this application are as follows:

[0044] (1) DNA extraction: Use a commercially available DNA extraction kit and operate according to the DNA extraction and purification methods recommended in its instruction manual to obtain the DNA sample to be tested;

[0045] (2) "One-step" gene methylation detection of MSRE-qPCR: a) Preparation of MSRE-qPCR reagents: Mix the digestion mixture, PCR reaction solution, primer-probe mixture, and buffer, and shake well; b) Preparation of the sample to be tested: Dilute the DNA sample obtained in step (1) with pure water (nuclease-free), dilute the positive control, negative control, and blank control with pure water (nuclease-free), and add the MSRE-qPCR reagents prepared in step a); c) MSRE-qPCR amplification: Set 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;

[0046] (3) Data analysis of the detection results.

[0047] Example 2. Condition screening of the "one-step" gene methylation detection method of MSRE-qPCR:

[0048] To determine the optimal digestion time of methylation-sensitive restriction endonucleases, while ensuring that non-methylated templates are fully digested and avoiding over-digestion. Taking the HOXA9 target as the research object, the methylation rates of gradient methylation rate reference products (methylation rates of 100%, 50%, and 0% respectively) were measured after being treated 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 is consistent with the expected methylation rate is determined as the optimal digestion time.

[0049] The specific implementation plan is as follows:

[0050] 1. Preparation of the reaction system: Prepare the digestion reaction system in an ice box according to Table 1. The reaction system for 0-minute digestion needs to be prepared before loading the qPCR instrument.

[0051] Table 1. Digestion PCR reaction system

[0052] Components Volume (μL) PCR reaction solution 10 HOXA9 primer-probe mixture 5 Enzyme digestion mixture 1.5 DNA 8.5 (15ng) Total volume 25

[0053] 2. Place the sample digested for 165 minutes in a common PCR instrument and run the reaction program shown in Table 2. Then, in the order of decreasing digestion time, at intervals of 15 minutes, place the samples corresponding to the digestion times in the PCR instrument. After digestion, briefly centrifuge and transfer the samples to the qPCR instrument to measure the methylation rate.

[0054] Table 2. Digestion reaction conditions

[0055] stage temperature time 1 37℃ 165min 2 95℃ 10min

[0056] 3. After transferring the digestion products and the non-digestion reaction system to the qPCR instrument, run the program shown in Table 3 as attached Figure 8 to detect the methylation rates of each reference product at different digestion times.

[0057] 4. After exporting the detection data, calculate the dCT values (HOXA9 CT - internal reference CT) of HOXA9 and the internal reference for the corresponding wells. Methylation rate = 1 / (2^dCT) × 100%. The inventor set 3 technical replicates for each digestion period, calculated the average value of the measured methylation rate and compared it with the expected methylation rate. The detection results and methylation rate calculation results of the 100%, 50%, and 0% methylation rate reference products are shown in Tables 4, 5, and 6 as attached Figure 9-11 respectively, and the average methylation rate distribution is as shown in Figure 2 、 Figure 3 、 Figure 4 respectively.

[0058] Test results show that the optimal digestion time range is 30-120 minutes, with good consistency between the measured and expected methylation rates. Furthermore, a digestion time of 45-75 minutes is recommended. Digestion times below 30 minutes result in incomplete digestion, increased background methylation rates, and poor detection specificity. Digestion times above 120 minutes lead to over-digestion, lower-than-expected measured methylation rates, weakened positive reference signal, and low detection sensitivity.

[0059] Example 3, Optimization of the "One-step" Gene Methylation Detection Method of MSRE-qPCR:

[0060] The "one-step" gene methylation detection method of MSRE-qPCR of the present application integrates an anti-pollution system based on UDG enzyme into the one-step enzyme digestion-qPCR system in order to reduce the impact of product contamination on the quantitative results of methylation. In order to demonstrate the actual improvement effect, the inventors 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 digestion-amplification system and the conventional enzyme digestion-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 amplified product is in an unmethylated 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 digestion-amplification reaction system is significantly lower than that of the anti-pollution enzyme digestion-amplification system, and the effect is verified.

[0061] The specific implementation plan is as follows:

[0062] 1. Prepare the test samples: Take the amplification products of the HOXA9+ACTB-M1 and SIM2+ACTB-M2 anti-contamination reaction systems. After using Qubit HS quantitative reagent to detect the concentration, dilute them to the theoretical concentration of 0.00012 ng / μL, with a total volume of 10 μL. Separately, take 180 ng 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 102 μL to obtain the test sample;

[0063] 2. Reaction system preparation: 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;

[0064] Table 7. Anti-contamination enzyme digestion-amplification reaction system

[0065] Components Volume (μL) PCR reaction solution (containing UDG) 10 Primer probe mixture 5 Enzyme digestion mixture 1.5 DNA 8.5 Total volume 25 μL

[0066] Table 8. Conventional enzyme digestion-amplification reaction system

[0067] Components Volume (μL) PCR reaction solution (without UDG) 10 Primer probe mixture 5 Enzyme digestion mixture 1.5 DNA 8.5 Total volume 25 μL

[0068] 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 Figure 12 Set up the qPCR amplification program as shown in Table 10, and then start the test;

[0069] Table 9. Signal channels selected for fluorescence detection of each target gene

[0070] 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

[0071] 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). The methylation rate = 1 / (2^dCT) × 100%. The inventors set up three technical replicates in the anti-contamination enzyme digestion-amplification system and the conventional enzyme digestion-amplification system for the two targets, respectively. The results are shown in Table 11. The methylation rate distribution is as follows Figure 5 shown.

[0072] Table 11. Measured data of the two-target anti-pollution system and the conventional system

[0073] 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%

[0074] Test results show that the anti-contamination system, UDG enzyme, can indiscriminately remove dUTP-containing target and internal reference contaminants. However, the conventional system, which only digests dUTP-containing target contaminants with a methylation-sensitive restriction endonuclease, is unable to remove internal reference contaminants. This results in a significantly lower measured methylation rate than the anti-contamination system, leading to false-negative results. The anti-contamination system effectively prevents the impact of amplification product contamination on detection sensitivity, providing more reliable test results than conventional reaction systems.

[0075] Example 4: Target screening for early diagnosis, early screening, and auxiliary diagnosis of bladder cancer:

[0076] 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 there were differences in methylation levels in bladder cancer follow-up positive samples and follow-up negative samples, which can be used as marker genes for bladder cancer detection.

[0077] After 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.

[0078] A total of 90 samples were used for target gene screening, including 45 positive samples (including 20 newly diagnosed positive samples and 25 follow-up positive samples of bladder cancer) and 45 negative samples (including 20 newly diagnosed negative samples and 25 follow-up negative samples of bladder cancer). The deltaCT values of the genes were detected using the "one-step" gene methylation detection method of the preferred MSRE-qPCR in Example 3, and then logistic regression modeling was performed. The detection performance of the target was obtained through the model, and finally the target with the best performance was selected.

[0079] According to the expected performance target, the sensitivity was set to more than 90.00%. In this example, the value when the sensitivity was more than 90.00% was 91.11% (41 / 45). At this sensitivity, the specificities of the targets were compared, and the target with a high specificity was selected.

[0080] Single target gene modeling, the detection performance for bladder cancer is shown in Table 12 below:

[0081] Table 12. Detection performance of single target gene for bladder cancer

[0082] 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

[0083] When the sensitivity was 91.11%, the specificities of the targets were 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 highest, which was 71.11%.

[0084] Select the interval with the highest specificity in each gene as the target used for the gene. The target genes were combined in pairs for modeling, and the detection performance for bladder cancer is shown in Table 13 below:

[0085] Table 13. Detection performance of target gene combinations for bladder cancer

[0086] 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

[0087] When the sensitivity was 91.1%, the specificities of the target gene combinations were compared. From the results in Table 13, it can be seen that when the two targets of 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.

[0088] A new biomarker combination composed of HOXA9 / SIM2 methylation targets was obtained through screening and was used for the auxiliary diagnosis of the initial diagnosis and recurrence of NMIBC patients.

[0089] Example 5. Gene methylation detection for early diagnosis, early screening and auxiliary diagnosis of bladder cancer:

[0090] The gene combination of HOXA9 gene and SIM2 gene obtained by screening according to Example 4 was used as the target gene combination. The target gene intervals and primer probe sequences included in the gene combination are shown in Table 14.

[0091] Table 14. Primer and probe sequences for bladder cancer recurrence monitoring gene methylation detection

[0092] 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 CACATATTGGGATCCTGGAGCT 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

[0093] 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:

[0094] 1. Preparation of MSRE enzyme digestion-qPCR system:

[0095] The concentration of the DNA sample to be tested was determined using the Qubit HS quantification kit. 15 ng was transferred to a PCR tube and the components were mixed according to the MSRE digestion-qPCR reaction system (contamination-proof digestion and amplification system) shown in Table 7 of Example 3. The MSRE-qPCR "one-step" methylation detection reagent includes a modification-sensitive restriction endonuclease, DNA polymerase, a deoxyribonucleoside triphosphate (dNTP / dUTP) premix, uracil-DNA glycosylase (UDG), primers that specifically recognize and / or bind to the target sequence, and / or a probe that specifically recognizes and / or binds to the target sequence, and buffer. These components were mixed together. After adding the sample, the tube was capped, vortexed to mix, and centrifuged for 30 seconds (avoiding bubbles; if bubbles occur, gently flick with a finger and re-centrifuge). PCR amplification was then immediately performed.

[0096] 2. qPCR Amplification: Place the reaction plate / tubes on the thermal cycler heating block according to the pre-set sequence. Re-confirm that the tube seals / caps are sealed, and close the sample compartment. Set the "Number of tubes per sample" to 2, select the fluorescence channel for each test tube according to Table 9 in Example 3, and set the PCR amplification program according to Table 10 in Example 3.

[0097] 3. Analysis of test results:

[0098] (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 the "Amplification curve algorithm" in the "Parameter setting" and set the baseline threshold of each gene according to Table 15.

[0099] Table 15. Baseline threshold setting requirements

[0100] Target gene Manual threshold Baseline start point Baseline end point HOXA9 0.12 6 12 ACTB-M1 0.12 6 12 SIM2 0.12 6 12 ACTB-M2 0.12 6 12

[0101] Note: In the "Baseline Optimization" column of the baseline threshold setting of the fully automatic medical PCR analysis system SLAN-96S, the default is the "Automatic Optimization" mode, and it should not be adjusted unless necessary.

[0102] (2)Quality control: 1) Control quality control: ① The Ct value or ΔCt value of the detection signals of each channel of the positive control, negative control, and blank control should meet the requirements of Table 16; ② After the Ct value or ΔCt value of the positive control, negative control, and blank control is qualified, the results of the test samples can be judged.

[0103] Table 16. Requirements for Ct value or ΔCt value of detection signals of positive control, negative control, and blank control

[0104] Control product name Tube name Gene Signal channel Amplification result 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

[0105] 2) Internal control: For the internal reference gene ACTB in the test sample, the Ct value in signal channel 19 ≤ Ct value ≤ 28, otherwise the sample is judged invalid.

[0106] (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. Analyze the.txt file using the data analysis software for multi-gene combined detection of non-muscle invasive bladder cancer version V1 to obtain the Score value and give the comprehensive judgment result of the kit.

[0107] Example 6. Performance verification in the early diagnosis and early screening of bladder cancer:

[0108] According to the method for detecting gene methylation in the initial diagnosis and recurrence monitoring 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.

[0109] After determining the optimal targets HOXA9 and SIM2, the performance of the model was verified through 293 initial diagnosis samples of bladder cancer (171 positive samples and 122 negative samples for initial diagnosis of bladder cancer). The delta CT of HOXA9 and SIM2 in the initial diagnosis samples was used as the input and input into the logistic regression model to obtain the model prediction results. The process is as Figure 7 shown. The results of predicting initial diagnosis samples of bladder cancer by HOXA9 and SIM2 targets are shown in Table 17 below.

[0110] Table 17. Results of predicting initial diagnosis samples of bladder cancer by HOXA9 and SIM2 targets

[0111] Sensitivity (%) Specificity (%) Positive predictive value (%) (PPV) Negative predictive value (%) (NPV) Initial diagnosis sample 90.64 91.80 93.93 87.50

[0112] In newly diagnosed bladder cancer samples, the combined performance of HOXA9 and SIM2 targets had a sensitivity of 90.64%, a specificity of 91.80%, a PPV of 93.93%, and an NPV of 87.50%.

[0113] Example 7: Verification of the effectiveness of the methylation gene detection method in auxiliary diagnosis of bladder cancer:

[0114] According to the gene methylation detection method for monitoring bladder cancer initial diagnosis and recurrence 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 bladder cancer follow-up patients.

[0115] The effectiveness of gene methylation detection was validated in urine samples from patients with non-muscle invasive bladder cancer (NMIBC).

[0116] 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 in predicting bladder cancer follow-up samples are shown in Table 18 below.

[0117] Table 18. Results of HOXA9 and SIM2 targets in predicting bladder cancer follow-up samples

[0118] Sensitivity (%) Specificity (%) Positive predictive value (%) (PPV) Negative predictive value (%) (NPV) Follow-up sample 89.74 90.41 83.30 94.30

[0119] In bladder cancer follow-up samples, the performance of the HOXA9 and SIM2 target combination was 89.74% sensitive, 90.41% specific, 83.30% PPV, and 94.30% NPV.

[0120] Example 8: Verification of the detection effect of bladder cancer auxiliary diagnosis sample:

[0121] 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.

[0122] Table 19. Results of HOXA9 and SIM2 target prediction for bladder cancer samples

[0123] Sensitivity (%) Specificity (%) Positive predictive value (%) (PPV) Negative predictive value (%) (NPV) Bladder cancer sample 90.00 90.80 91.30 89.40

[0124] In bladder cancer samples, the sensitivity of the HOXA9 and SIM2 target combination is 90.00%, the specificity is 90.80%, the PPV is 91.30%, and the NPV is 89.40%.

[0125] In the applicant's previous patent CN202410585603.6 of the present application, a kit for detecting gene methylation in urothelial carcinoma has been disclosed, which contains the HOXA9 gene and a gene combination with 26 other genes. However, the traditional BS conversion method was used in patent CN202410585603.6. In Example 4 of patent CN202410585603.6, combination 2 is the gene combination of the HOXA9 gene and the SIM2 gene, and the sensitivity of combination 2 for detecting 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 the HOXA9 gene and the SIM2 gene for detecting urothelial carcinoma can reach 90.00%, and the detection effect is significantly better than that of the applicant's previous generation gene methylation detection kit.

[0126] The existing product NMP22 BladderChek is a rapid and non-invasive detection tool mainly used for the auxiliary diagnosis and monitoring of bladder cancer. The sensitivity of this product is only 45.9%, the specificity is 86.3%, and the PPV is 36.6%.

[0127] Table 20. Statistical results of detection performance of different products

[0128] Product name Sensitivity (95% CI), % Specificity (95% CI), % Positive predictive value (PPV) (95% CI), % Negative predictive value (NPV) (95% CI), % "One-step" gene methylation detection kit for MSRE-qPCR 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)

[0129] The bladder cancer gene methylation detection kit provided by 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 by the present application has good diagnostic performance for bladder cancer recurrence and meets the clinical use requirements. Compared with existing products, the detection sensitivity of the detection kit provided by the present application is 90.0% (95% CI: 79.9%-95.5%), the specificity is 90.8% (95% CI: 80.3%-96.2%), the positive predictive value (PPV) is 91.3% (95% CI: 81.4%-96.4%), and the negative predictive value (NPV) is 89.4% (95% CI: 78.8%-95.3%). All detection performance indicators are better than existing products.

[0130] 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 higher credibility in eliminating the risk of recurrence, can assist clinical decision-making, reduce or postpone invasive examinations, and improve compliance; it saves testing costs and reduces the burden on patients and the medical system.

Claims

1. Use of a kit for detecting gene methylation of bladder cancer in the preparation of a reagent for detecting gene methylation of bladder cancer, characterized in that, The kit includes: "one-step" methylation detection reagents for MSRE-qPCR, and quality control reagents; the "one-step" methylation detection reagents for MSRE-qPCR include methylation modification-sensitive restriction endonucleases, DNA polymerases, dNTP / dUTP premixes, uracil-DNA glycosylases, primers that specifically recognize and / or bind to the target sequence, probes that specifically recognize and / or bind to the target sequence, and buffers; the methylation modification-sensitive restriction endonucleases include AciI, HhaI, HinP1I, AvaI, HaeII, HpaII, and / or SmaI; the primer sequences that specifically recognize and / or bind to the target sequence are SEQ ID NO: 1-70; the probe sequences that specifically recognize and / or bind to the target sequence are SEQ ID NO: 71-81; the detection steps include: Ⅰ. Sample DNA extraction and purification; Ⅱ. "One-step" methylation detection by MSRE-qPCR: The sample obtained in step Ⅰ is mixed with the methylation detection reagents to obtain a mixed solution, and restriction enzyme digestion and PCR amplification are completed in the same system; Ⅲ. Data analysis of the detection results; The methylation detection of bladder cancer genes includes early diagnosis, risk assessment, treatment guidance, and recurrence monitoring of bladder cancer.

2. Use of a kit for detecting gene methylation of bladder cancer according to claim 1 in the preparation of a reagent for detecting gene methylation of bladder cancer, characterized in that, The methylation detection of bladder cancer genes is for the auxiliary diagnosis of recurrence of NMIBC of bladder cancer.

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