Methylation biomarkers or combinations for detecting bladder cancer treatment efficacy and their applications

Abstract

The present invention discloses methylation biomarkers for diagnosing and predicting the efficacy of bladder cancer treatment and their uses. The methylation biomarkers are selected from at least one of the following: chr8:132053505-132054221, chr1:146551513-146551739, and chr7:37488937-chr7:37488859. The methylation biomarkers provided by the present invention can be used to predict the efficacy of bladder cancer treatment with good accuracy and discriminatory power.

Description

Technical Field

[0001] The present invention belongs to the field of biotechnology, and specifically relates to a methylation biomarker or combination for detecting the therapeutic efficacy of bladder cancer and applications thereof. Background Art

[0002] Bladder cancer (BCa) originates in the bladder mucosa and is a common malignant tumor of the urinary system. Bladder cancer ranks ninth in cancer mortality worldwide.

[0003] Neoadjuvant therapy (NAT) for bladder cancer refers to systemic treatment performed prior to radical surgery (such as radical cystectomy). Its goal is to shrink the tumor, downstage the disease, and reduce micrometastases, thereby increasing surgical success rates and improving long-term survival. Cisplatin-based combined neoadjuvant chemotherapy and neoadjuvant chemotherapy plus immunotherapy (chemoimmunotherapy) combined with immune checkpoint inhibitors are widely used and have been incorporated into bladder cancer diagnosis and treatment guidelines and are gradually becoming more widely used clinically.

[0004] Neoadjuvant therapy has heterogeneous efficacy, with some patients experiencing tumor shrinkage or even complete disappearance, while others experience treatment failure or even tumor progression. Therefore, if chemotherapy sensitivity can be assessed using molecular biological methods before neoadjuvant therapy, ineffective chemotherapy or chemoimmunotherapy can be avoided, treatment delays can be prevented, and treatment costs can be reduced. Predicting neoadjuvant therapy sensitivity and preventing treatment delays are urgent clinical challenges. Although some studies support the use of genetic alterations as potential biomarkers of neoadjuvant therapy sensitivity, these biomarkers are not yet recommended in MIBC treatment guidelines for predicting neoadjuvant therapy efficacy due to the small number of cases included in these studies.

[0005] DNA methylation plays an important role in cell differentiation and disease development by regulating gene transcription and expression. Over the past few decades, research on gene promoter methylation has rapidly developed and successfully entered clinical translation and application, initially demonstrating its clinical value in tumor risk screening and early diagnosis. DNA methylation biomarkers have been used in the early diagnosis and recurrence monitoring of bladder cancer. However, to date, there are very limited reports on DNA methylation markers that accurately assess the efficacy of bladder cancer treatment. Summary of the Invention

[0006] Based on this, the purpose of the present invention is to provide a methylation biomarker or a combination thereof for detecting the efficacy of neoadjuvant therapy for bladder cancer, using DNA methylation biomarkers to detect the efficacy of neoadjuvant therapy for bladder cancer, and to achieve the purpose of detection and accurate prediction through single or multiple methylation marker combinations.

[0007] In a first aspect of the present invention, a methylation biomarker or a combination thereof for diagnosing the efficacy of neoadjuvant therapy for bladder cancer is provided, wherein the methylation biomarker is selected from at least one of the following: chr8:132053505-132054221, chr1:146551513-146551739, and chr7:37488937-chr7:37488859, and the methylation sites are aligned to the corresponding positions of hg19.

[0008] In some embodiments, the combination of methylation biomarkers is: chr8:132053505-132054221 and at least one selected from the following: chr1:146551513-146551739, chr7:37488937-chr7:37488859.

[0009] In some embodiments, the combination of methylation biomarkers is at least one of the following:

[0010] Group 1) chr8:132053505-132054221, and chr1:146551513-146551739;

[0011] Group 2) chr8:132053505-132054221, and chr7:37488937-chr7:37488859;

[0012] Group 3) chr8:132053505-132054221, chr1:146551513-146551739 and chr7:37488937-chr7:37488859.

[0013] In some embodiments, the combination of methylation biomarkers is: chr1:146551513-146551739 and at least one selected from the following: chr8:132053505-132054221, chr7:37488937-chr7:37488859.

[0014] In some embodiments, the combination of methylation biomarkers is: chr7:37488937-chr7:37488859 and at least one selected from the following: chr1:146551513-146551739, chr8:132053505-132054221.

[0015] In some embodiments, the methylation biomarker combination is chr1:146551513-146551739, and chr7:37488937-chr7:37488859.

[0016] In a second aspect of the present invention, there is provided use of the above-mentioned methylation biomarkers or a combination thereof in the preparation of a reagent or kit for detecting or predicting the efficacy of neoadjuvant therapy for bladder cancer.

[0017] Or use of the above-mentioned methylation biomarkers or detection reagents of their combination in the preparation of a kit for diagnosing the therapeutic efficacy of bladder cancer.

[0018] In a third aspect of the present invention, a kit for detecting or predicting the therapeutic efficacy of bladder cancer is provided, wherein the kit comprises a reagent for detecting the methylation level of any one of the above-mentioned methylation biomarkers or a combination thereof in a test sample.

[0019] In some embodiments, the reagent is a reagent used in the following methods for detecting methylation levels: one or more of fluorescent quantitative PCR, methylation-specific PCR, digital PCR, DNA methylation chip, targeted DNA methylation sequencing, whole genome methylation sequencing, and DNA methylation mass spectrometry.

[0020] In some embodiments, the bladder cancer is bladder cancer with a T stage of T2 or above.

[0021] In some embodiments, the sample to be tested is selected from one or more of tissue, whole blood, plasma, saliva, serum, urine, urine exfoliated cells, urine sediment, and urine supernatant. Preferably, the sample to be tested is tissue, urine, urine exfoliated cells, urine sediment, and urine supernatant.

[0022] In some embodiments, the sample to be tested is from a subject; optionally, the subject is a mammal; preferably, the mammal is a human.

[0023] This study identified three methylation biomarkers that are highly correlated with bladder cancer treatment efficacy. These three methylation biomarkers can be used to detect or predict bladder cancer treatment efficacy with good accuracy and discriminatory power. When used in combination to detect or predict the efficacy of neoadjuvant therapy for bladder cancer, these three methylation biomarkers exhibit improved sensitivity and specificity, resulting in more stable detection results, providing a more accurate and sensitive test service for clinical prediction of bladder cancer treatment efficacy. BRIEF DESCRIPTION OF THE DRAWINGS

[0024] Figure 1 . Methylation signal heat map of the three methylation markers of the present invention in the bladder cancer tissue sample discovery set.

[0025] Figure 2 . ROC curves of the model combination of the three methylation marker combination models of the present invention in the bladder cancer tissue sample training set, validation set and independent validation set.

[0026] Figure 3 . Distribution of the combined model scores of the three methylation markers of the present invention in two groups of people in the independent validation set of bladder cancer tissue samples. DETAILED DESCRIPTION

[0027] To facilitate understanding of the present invention, the present invention will be described more fully below. The present invention can be implemented in many different forms and is not limited to the embodiments described herein. On the contrary, the purpose of providing these embodiments is to make the understanding of the present disclosure more thorough and comprehensive.

[0028] Experimental procedures in the following examples, where specific conditions are not specified, generally followed conventional conditions, such as those in Molecular Cloning: A Laboratory Manual (4th edition, edited by Green and Sambrook, published in 2013), or according to manufacturer recommendations. All commonly used chemical reagents used in the examples were commercially available.

[0029] Unless otherwise defined, all technical and scientific terms used herein have the same meanings as commonly understood by those skilled in the art to which this invention pertains. The terms used in this specification are for the purpose of describing specific embodiments only and are not intended to limit the invention. The term "and / or" as used herein includes any and all combinations of one or more of the associated listed items.

[0030] As used herein, "methylation level," "methylation degree," "methylation state," "methylation profile," and "methylation status" of a nucleic acid molecule refer to the presence or absence of one or more methylated nucleotide bases in a nucleic acid molecule. For example, a nucleic acid molecule comprising methylated cytosine is considered methylated (e.g., the methylation state of the nucleic acid molecule is methylated). A nucleic acid molecule that does not contain any methylated nucleotides is considered unmethylated.

[0031] In this specification, the methylation status can optionally be represented or indicated by a "methylation value" (e.g., representing the methylation frequency, score, ratio, percentage, etc.). The methylation value can be generated by quantifying the amount of intact nucleic acid present after restriction digestion with a methylation-dependent restriction enzyme, or by comparing the amplification spectrum after a bisulfite reaction, or by comparing the sequences of bisulfite-treated and untreated nucleic acids. Therefore, a value such as a methylation value represents the methylation status and can therefore be used as a quantitative indicator of the methylation status in multiple copies of a locus. The degree of co-methylation is represented or indicated by the methylation status of more than one methylation site, and co-methylation is defined as when the methylation status of more than one methylation site in a methylated region is all methylated.

[0032] As used herein, "methylation rate," "methylation frequency," or "methylation percentage (%)" refers to the number of instances in which a molecule or locus is methylated relative to the number of instances in which the molecule or locus is unmethylated. For example, in some embodiments, the methylation rate of each target region is calculated as the number of comethylated reads divided by the total number of reads, where a comethylated read is defined as a read in which three or more CpG sites within a window of five consecutive CpG sites within the target region are C.

[0033] In this specification, sequences are referred to as "differentially methylated" or as having a "methylation difference" or "different methylation status" when they differ in the degree (e.g., one has increased or decreased methylation relative to another), frequency, or pattern of methylation. The term "differential methylation" refers to a difference in the level or pattern of nucleic acid methylation in a cancer-positive sample compared to the level or pattern of nucleic acid methylation in a cancer-negative sample.

[0034] In this specification, the term "differentially methylated region" (DMR) refers to a DNA region containing one or more differentially methylated sites.

[0035] As used herein, the term "methylation assay" or "methylation level detection" or "methylation degree detection" refers to any assay for determining the methylation status of one or more CpG dinucleotide sequences within a nucleic acid sequence.

[0036] In this specification, the term "sample" refers to any substance including biological samples that may contain target molecules that need to be analyzed. As used herein, "sample" or "biological sample" is a sample or biological sample that can be a sample obtained directly from a biological source or a processed sample. Samples or biological samples include, but are not limited to, body fluids (such as whole blood, plasma, serum, cerebrospinal fluid, synovial fluid, urine, sweat, semen, feces, sputum, tears, mucus, amniotic fluid, etc.), exudates, bone marrow samples, ascites, pelvic lavage fluid, pleural fluid, spinal fluid, lymph, eye fluid, extracts of nasal, throat or genital swabs, cell suspensions of digested tissue, or extracts of fecal matter, as well as samples from humans, animals (such as non-human mammals) and organs, and processed samples derived therefrom.

[0037] In this specification, the term "AUC" is an abbreviation for "area under the curve". Specifically, it refers to the area under the receiver operating characteristic (ROC) curve. The ROC curve is a graph of the true positive ratio relative to the false positive ratio for different possible block cut points of a diagnostic test. It shows the compromise between sensitivity and specificity according to the selected cut point (any increase in sensitivity will be accompanied by a decrease in specificity). The area under the ROC curve (AUC) is a measure of the accuracy of a diagnostic test (the larger the area, the better; the best is 1; a random test will have an ROC curve on the diagonal with an area of ​​0.5).

[0038] The T stage (primary tumor stage) of bladder cancer is mainly based on the depth of the tumor invasion of the bladder wall, using the internationally accepted TNM staging system, among which T2 (muscle-invasive cancer), T3: the tumor penetrates the muscle layer and invades the fatty tissue around the bladder; T4: the tumor invades adjacent organs or tissues.

[0039] In this article, the term "sensitive" for neoadjuvant therapy in bladder cancer refers to patients experiencing significant tumor regression or disappearance after neoadjuvant therapy, complete response (CR) or partial response (PR) as assessed by pathology or imaging, and clear long-term survival benefits. Core manifestations include tumor downstaging and control of micrometastases.

[0040] Pathological evaluation (gold standard): Pathological complete response (pCR, ypT0N0): No residual tumor cells (including primary tumor and lymph nodes) are found in the specimen after radical cystectomy. Pathological partial response (pPR): Residual tumor but downstaging (e.g., from cT2-4 to ypT1).

[0041] Radiographic evaluation (auxiliary criteria), RECIST v1.1 criteria: Complete response (CR): All target lesions disappear. Partial response (PR): The total diameter of target lesions decreases by ≥30%.

[0042] Resistance to neoadjuvant therapy for bladder cancer (Resistant): refers to bladder cancer patients who do not respond significantly to neoadjuvant therapy (the tumor does not shrink or progress), or who experience intolerable toxicity during treatment and need to terminate treatment, resulting in delayed surgery or loss of survival benefit.

[0043] Pathological and radiological assessment: Non-response: Residual tumor ≥ypT2 in the postoperative specimen. Progressive disease (PD): An increase of ≥20% in the sum of target lesion diameters or the appearance of new lesions according to RECIST criteria.

[0044] The technical solution of the present invention is described in detail below, but is not intended to limit the scope of protection of the present invention.

[0045] Example 1 Genome-wide methylation sequencing and marker discovery

[0046] This embodiment discloses a methylation-specific biomarker for detecting and predicting the therapeutic efficacy of bladder cancer, and a method for detecting the biomarker.

[0047] Methylation library construction and whole-genome methylation sequencing were performed on 40 confirmed bladder cancer tissue samples (20 bladder cancer samples sensitive to neoadjuvant therapy and 20 bladder cancer samples resistant to neoadjuvant therapy). The process and steps are as follows:

[0048] DNA extraction and methylation detection

[0049] 1.1 DNA Extraction

[0050] The DNA extraction steps of the above bladder cancer samples were followed in accordance with the QIAamp® DNA FFPE Tissue kit operating instructions of QIAGEN for methylation detection.

[0051] The Illumina TruSeq Methyl Capture EPIC Library Prep Kit was used to construct a methylation library and perform targeted methylation enrichment according to the instructions. The specific detection process is as follows:

[0052] 1.1.1 DNA fragmentation

[0053] Take 800 ng of the above DNA and add shearing buffer (prepared by adding 10 μL of 0.5 M EDTA to every 5 mL of RSB) to make up to 50 μL, shake to mix, and transfer to the shearing tube;

[0054] After centrifugation, the cells were placed in a Covaris disruptor and reacted according to the following disrupting conditions:

[0055]

[0056] Add 80 μL of SPB to the fragmentation product, vortex to mix, incubate at room temperature for 5 minutes, let it stand on a magnetic rack, discard the supernatant, wash twice with 500 μL of 80% ethanol, discard the ethanol, dry the magnetic beads at room temperature for 2-3 minutes, add 60 uL of RSB to resuspend, let it stand at room temperature for 1 minute, transfer the suspension to a 200 μL PCR tube, and proceed to the next step.

[0057] 1.1.2 End Repair

[0058] Add 40 μL of ERP3 to the suspension in the previous step, mix thoroughly by pipetting, centrifuge briefly, and place in a PCR instrument to perform the reaction according to the following procedure:

[0059]

[0060] Transfer all samples after the reaction to new 1.5ml centrifuge tubes. Add 120µl of SPM to each sample and mix thoroughly with a Vortex. Incubate at room temperature for 5 minutes. After a brief centrifugation, place on a magnetic stand for 5 minutes. Discard the supernatant and wash twice with 500µl of 80% ethanol. After discarding the ethanol, let the beads dry at room temperature for 2-3 minutes. Resuspend in 17.5µl of RSB and let stand at room temperature for 1 minute. Transfer the suspension to a 200µl PCR tube and proceed to the next step.

[0061] 1.1.3. 3'-end adenylation

[0062] Add 12.5 μL of ATL2 to the suspension in the previous step, mix thoroughly by pipetting, centrifuge briefly, and place in a PCR instrument to perform the reaction according to the following procedure:

[0063]

[0064] 1.1.4 Connecting joints

[0065] The product from the previous step was added to the following reagents for reaction:

[0066]

[0067] Place in a PCR instrument and perform the reaction according to the following procedure:

[0068]

[0069] After the reaction is complete, add 5 μL of STL, mix thoroughly, then add 43 μL of SPM, mix thoroughly, and incubate at room temperature for 5 minutes. After a brief centrifugation, place on a magnetic stand for 5 minutes. Discard the supernatant and wash the beads twice with 200 μL of 80% ethanol. After discarding the ethanol, dry the beads at room temperature for 2-3 minutes. Resuspend four samples (four samples with different indices) in 40 μL of RSB and proceed to the next step.

[0070] 1.1.5 Hybridization I

[0071] The product from the previous step was added to the following reagents for reaction:

[0072]

[0073] Mix by pipetting, incubate at room temperature for 5 minutes, centrifuge briefly, and place on a magnetic stand for 5 minutes. Discard the supernatant and wash twice with 500 μL of 80% ethanol. After discarding the ethanol, dry the magnetic beads at room temperature for 2-3 minutes. Add 7.7 μL of CT4, resuspend, and let stand for 2 minutes. Pipette 7.5 μL of supernatant and add it to a PCR tube containing 2.5 μL of EHB2. After centrifugation, place the product in a PCR instrument and react according to the following procedure:

[0074]

[0075] 1.1.6 Elution I

[0076] 10 μL of hybridization I product was mixed with 250 μL of SMB, incubated at room temperature for 25 min, centrifuged briefly, and then placed on a magnetic stand for 2 min, and the supernatant was discarded.

[0077] Add 200 μL of EWS to the centrifuge tube from the previous step, resuspend, incubate at 50°C for 20 minutes, centrifuge briefly, place on a magnetic stand for 2 minutes, and discard the supernatant. Repeat the EWS washing process once.

[0078] Prepare the reaction solution and add the following reagents:

[0079]

[0080] Add 30 μL of the above mixture to the magnetic beads, resuspend, and incubate at room temperature for 5 minutes. Centrifuge briefly, place on a magnetic stand for 2 minutes, and pipette 29 μL of the supernatant into a PCR tube containing 5 μL of ET2. Mix thoroughly and proceed to the next step.

[0081] 1.1.7 Hybridization II

[0082] The product from the previous step was added to the following reagents for reaction:

[0083]

[0084] Place in a PCR instrument and perform the reaction according to the following procedure:

[0085]

[0086] 1.1.8 Elution II

[0087] 100 μL of hybridization II product was mixed with 250 μL of SMB, incubated at room temperature for 25 min, centrifuged briefly, and then placed on a magnetic stand for 2 min, and the supernatant was discarded.

[0088] Add 200 μL of EWS to the centrifuge tube from the previous step, resuspend, incubate at 50°C for 30 minutes, centrifuge briefly, place on a magnetic stand for 2 minutes, and discard the supernatant. Repeat the EWS washing process once.

[0089] Prepare the reaction solution and add the following reagents:

[0090]

[0091] Add 18 μL of the above mixture to the magnetic beads, resuspend, and incubate at room temperature for 5 minutes. Centrifuge briefly, place on a magnetic stand for 2 minutes, and pipette 17.1 μL of the supernatant into a PCR tube containing 2.9 μL of ET2. Mix thoroughly and proceed to the next step.

[0092] 1.1.9. Conversion

[0093] Add 130 μl of Lighting Conversion Reagent to the Elution II product, mix well, and place in a PCR instrument to perform the reaction according to the following procedure:

[0094]

[0095] Add the reaction product to a 1.5 mL centrifuge tube containing 600 μL M-Binding Buffer and 10 μL MagBinding Beads. Mix well and incubate at room temperature for 5 minutes. Centrifuge briefly, place on a magnetic stand for 2 minutes, and discard the supernatant.

[0096] Add 400ul M-Wash Buffer to wash the magnetic beads.

[0097] Add 200 μl of L-Desulphonation Buffer to the magnetic beads, mix thoroughly by vortexing, incubate at room temperature for 15 minutes, centrifuge briefly, and discard the supernatant. Wash the magnetic beads twice with M-Wash Buffer.

[0098] Uncap and dry at 50°C for 4 minutes. Add 23 μL of RSB, mix thoroughly by pipetting, and incubate at 50°C for 4 minutes. Place on a magnetic rack for 2 minutes until the liquid becomes clear. Pipette 20 μL of the supernatant into a 200 μL PCR tube.

[0099] 1.1.10 Library Enrichment

[0100] Add 20ul of the converted sample to the following reagents for reaction:

[0101]

[0102] Place in a PCR instrument and perform the reaction according to the following procedure:

[0103]

[0104] 1.1.11 Library purification

[0105] Add 50 μL of SPB to the above product, shake to mix, incubate at room temperature for 5 min, centrifuge briefly, and place on a magnetic stand for 5 min.

[0106] The supernatant was discarded and the cells were washed twice with 200 μL of 80% ethanol.

[0107] Dry at room temperature for 2-3 minutes, add 40μL RSB, resuspend, let stand at room temperature for 5 minutes, centrifuge briefly, place on a magnetic stand for 5 minutes, and aspirate 39μL of the supernatant into a new PCR tube.

[0108] 1.2. Use Illumina's sequencer to sequence the sample after hybridization capture to obtain sequencing results.

[0109] 1.3 Analysis of Offboard Data

[0110] The sequencing quality of each batch of data was analyzed using fastp 0.19.6 software. Low-quality reads (such as those with poor quality control, short length, and excessive N residues) were filtered out. A batch of data was considered to pass quality control if its Q30 base ratio was greater than 75%. Adapter sequences and low-quality base fragments introduced during library construction were removed from the sequencing reads to generate clean fastq files. These clean reads were aligned to the human genome (hg19) using bismark v0.22.1 to generate aligned bam files. Bisulfite conversion efficiencies of ≥97% were considered to pass quality control. Reads were deduplicated based on UMIs to generate deduplicated bam files. The number of methylated and unmethylated reads targeting CpG sites within the target region was then extracted from the bam files. The site methylation beta value was calculated as the ratio of methylated reads to (methylated reads + unmethylated reads). The beta values ​​of the CpG sites in the targeted region were then averaged as the methylation level of the methylation marker of the sample for subsequent analysis.

[0111] Based on the methylation sequencing data of 20 bladder cancer treatment-sensitive and 20 bladder cancer treatment-resistant samples in the whole genome, the limma toolkit of R software was used to perform a differential methylation spectrum test analysis between the two groups, and the differentially methylated loci (DML) of the whole genome were obtained. The differentially co-methylated regions were identified, and the co-methylation status and gene function annotations were combined to find three methylation markers (hereinafter referred to as markers) as shown in Table 1. The AUC of the three markers in the discrimination performance of treatment-sensitive and treatment-resistant populations is 0.729-0.776. The methylation signal levels of these three markers in the two comparison groups are as follows: Figure 1 As shown, the results showed that the methylation levels of the three methylation markers were significantly differentiated in the two populations, and had good application potential.

[0112] Table 1. 3 methylation markers

[0113]

[0114] The methylation sites were aligned to the corresponding positions in hg19.

[0115] Example 2 Targeted Methylation Sequencing

[0116] This example provides a method for performing targeted methylation sequencing of DNA methylation markers on clinical samples. The specific process and steps are as follows:

[0117] DNA extraction and methylation library construction

[0118] 2.1 DNA Extraction

[0119] The DNA extraction steps for the above-mentioned bladder cancer samples were performed according to the operating instructions of QIAGEN's QIAamp® DNA FFPE Tissue kit;

[0120] 2.1.1 Conversion

[0121] Extracted DNA (50 ng; if the sample did not have enough input DNA, it was mixed with DNA from another sample for library construction and measurement) was bisulfite-converted to deaminize unmethylated cytosines to uracil, while methylated cytosines remained unchanged. This yielded bisulfite-converted DNA. The conversion procedure was performed according to the instructions for the Zymo Research EZ DNA Methylation-Lightning Kit.

[0122] 2.1.2 End Repair

[0123] Add 17ul of the converted sample to the following reagents for reaction:

[0124]

[0125] Place in a PCR instrument and perform the reaction according to the following procedure:

[0126]

[0127] When the second step of the PCR reaction (95°C) reaches 5 minutes, immediately remove the sample from the PCR instrument, directly insert it into ice, and leave it for more than 2 minutes before proceeding to the next step.

[0128] 2.1.3 Connection I

[0129] Prepare the following reaction solution:

[0130]

[0131] Place in a PCR instrument and perform the reaction according to the following procedure:

[0132]

[0133] 2.1.4 Amplification I

[0134] Prepare the following reaction solution

[0135]

[0136] Place in a PCR instrument and perform the reaction according to the following procedure:

[0137]

[0138] 2.1.5. Purification I

[0139] Add 166 μl of 1:6 diluted Agencourt AMPure Beads (need to be equilibrated at room temperature for half an hour in advance) to purify the product of the Amplification I reaction and elute with 21 μl of EB. The specific purification steps are as follows:

[0140] Take the reaction product from the previous step and centrifuge it. Add 166μl of 1:6 diluted Agencourt AMPure Beads to each sample and mix thoroughly with a pipette. Incubate at room temperature for 5 minutes. Centrifuge and place on a magnetic stand for 5 minutes. Aspirate the supernatant. Add 200μl of 80% EtOH, let it stand for 30 seconds, and aspirate the ethanol. Repeat this process once, centrifuge, place the PCR tube on a magnetic stand, aspirate the remaining ethanol, and dry the beads with the lid open for 2-3 minutes, being careful not to overdry them. Add 21μl of EB for elution, mix thoroughly with a pipette, and let it stand at room temperature for 3 minutes. Centrifuge and place the PCR tube on a magnetic stand and let it stand for 3 minutes. Aspirate 20μl of the supernatant into a new PCR tube.

[0141] 2.1.6 Connection II

[0142] Prepare the following reaction solution:

[0143]

[0144] Place in PCR instrument and perform reaction according to the following procedure

[0145]

[0146] 2.1.7 Indexing PCR (Construction of Amplified Product Library)

[0147] Prepare the following reaction solution:

[0148]

[0149] Place in PCR instrument and perform reaction according to the following procedure

[0150]

[0151] 2.1.8 Purification II

[0152] Add Agencourt AM Pure Beads (equilibrated at room temperature for half an hour in advance) to purify the product after the Indexing PCR reaction and elute with 41μl EB. The specific purification steps are as follows:

[0153] Take the reaction product from the previous step and centrifuge it. Add 71μl of undiluted Agencourt AM PureBeads to each sample and mix well with a pipette. Incubate at room temperature for 5 minutes. Centrifuge and place on a magnetic stand for 5 minutes. Aspirate the supernatant. Add 200μl of 80% EtOH, let it stand for 30 seconds, aspirate the ethanol, repeat the steps once, centrifuge, place the PCR tube on a magnetic stand, and aspirate the remaining ethanol. Open the lid and dry the magnetic beads for 2-3 minutes, being careful not to overdry. Add 41μl of EB for elution, mix well with a pipette, and let it stand at room temperature for 3 minutes. Centrifuge, place the PCR tube on a magnetic stand, and let it stand for 3 minutes. Aspirate 20μl of supernatant into a new PCR tube. Qubit quantification: Take 1μl and quantify the library using the Qubit dsDNA HS Assay Kit. 2.1.9、

[0155] The final library for a specific region was generated by oligonucleotide capture enrichment (including the three methylation marker sequences described in Example 1 and Table 1) on the pre-library samples. The hybridization capture kit was IDT's xGen Lockdown Reagents, and the specific instructions were followed.

[0156] 2.2. Use Illumina's sequencer to sequence the sample after hybridization capture to obtain sequencing results.

[0157] 2.3 Analysis of Offboard Data

[0158] The sequencing quality of each batch of data was analyzed using fastp 0.19.6 software. Low-quality reads (such as those with poor quality control, short length, and excessive N residues) were filtered out. A batch of data was considered to pass quality control if its Q30 base ratio was greater than 75%. Adapter sequences and low-quality base fragments introduced during library construction were removed from the sequencing reads to generate clean fastq files. These clean reads were aligned to the human genome (hg19) using bismark v0.22.1 to generate aligned bam files. Bisulfite conversion efficiencies of ≥97% were considered to pass quality control. Reads were deduplicated based on UMIs to generate deduplicated bam files. The number of methylated and unmethylated reads targeting CpG sites within the target region was then extracted from the bam files. The site methylation beta value was calculated as the ratio of methylated reads to (methylated reads + unmethylated reads). The beta values ​​of the CpG sites in the targeted region were then averaged as the methylation level of the methylation marker of the sample for subsequent analysis.

[0159] Example 3 Establishment and verification of a prediction model for the therapeutic efficacy of bladder cancer

[0160] This embodiment provides a methylation-specific biomarker combination model for detecting and predicting the therapeutic efficacy of bladder cancer and its application.

[0161] Methods: Tissue samples from 62 patients with clinically confirmed neoadjuvant therapy-resistant or neoadjuvant therapy-sensitive bladder cancer were collected from multiple clinical centers (32 treatment-sensitive and 30 treatment-resistant). The treatment-sensitive group served as the control group, and the treatment-resistant group served as the case group.

[0162] The three DNA methylation markers in Example 1 were detected using the technical solution described in Example 2.

[0163] Furthermore, the DNA methylation data from these 62 clinical samples were randomly divided into training and validation sets based on clinical information. The training set consisted of 38 samples (20 treatment-sensitive and 18 treatment-resistant), and the validation set consisted of 24 samples (12 treatment-sensitive and 12 treatment-resistant). Detailed clinical information is shown in Table 2.

[0164] Table 2. Clinical information of 62 bladder cancer tissue samples.

[0165]

[0166] The above methylation markers were used to build a logistic regression model on the training set and the performance was verified in the validation set. Logistic regression models were constructed from any two or all three of the three methylation markers and a positive judgment value was set. When the methylation level of the sample was higher than the positive judgment value, it was judged as treatment resistance. The performance of these three markers and their combined model in predicting the efficacy in the training set and validation set is shown in Table 3. The ROC is as follows: Figure 2 shown.

[0167] Table 3. Performance of the three DNA methylation markers and their combination models in the training and validation sets.

[0168]

[0169] The above results show that the efficacy prediction performance of a single methylation marker is better than the performance of the methylation panel constructed from 11 genes ARHGDIB, SHANK2, PROM1, RASGRF2, SEC31B, PXDNL, TRIM27, GPR75-ASB3, GALR1, PP12613 and NRN1 reported in the literature in predicting the efficacy of bladder cancer treatment (AUC is 0.67), and the performance of the combination model of any two or three markers based on these three markers has higher sensitivity or specificity than that of a single marker.

[0170] The marker combination Marker 1 + Marker 2 achieved an AUC of 0.778, a sensitivity of 0.950, and a specificity of 0.667 in the training set, and an AUC of 0.764, a sensitivity of 1.000, and a specificity of 0.500 in the validation set.

[0171] The marker combination Marker 1 + Marker 3 achieved an AUC of 0.831, a sensitivity of 0.800, and a specificity of 0.833 in the training set, and an AUC of 0.819, a sensitivity of 0.750, and a specificity of 0.917 in the validation set.

[0172] The marker combination Marker2+Marker3 achieved an AUC of 0.828, a sensitivity of 0.750, and a specificity of 0.778 in the training set, and an AUC of 0.847, a sensitivity of 0.917, and a specificity of 0.750 in the validation set.

[0173] The marker combination marker1+Marker 2+Marker 3 had an AUC of 0.833, a sensitivity of 0.800, and a specificity of 0.778 in the training set, and an AUC of 0.861, a sensitivity of 0.833, and a specificity of 0.833 in the validation set.

[0174] Example 4 Independent Validation of Bladder Cancer Treatment Efficacy Model

[0175] In addition, tissue samples from 64 patients with clinically confirmed neoadjuvant therapy-resistant or neoadjuvant therapy-sensitive bladder cancer were collected as an independent validation set. The detection method was described in Example 2. This set included 30 treatment-sensitive patients and 34 treatment-resistant patients. Their clinical information is detailed in Table 4.

[0176] Table 4. Clinical information of 64 bladder cancer tissue samples.

[0177]

[0178] The methylation levels of the three methylation markers were detected using the detection method in Example 2, and the performance of the model in Example 3 was verified for the above samples. The performance is shown in Table 5. The distribution of the combined model scores of the three methylation markers in the two groups of the bladder cancer tissue sample independent validation set is shown in Table 5. Figure 3 The results showed that the scores of these marker combination models can significantly distinguish between treatment-sensitive and treatment-resistant populations.

[0179] In the independent validation set, the AUC of the single marker was 0.763-0.781, the sensitivity was 0.647-0.765, and the specificity was 0.700-0.933.

[0180] The marker combination marker1+marker2 had an AUC of 0.783, a sensitivity of 0.967, and a specificity of 0.647.

[0181] The marker combination marker1+marker3 had an AUC of 0.814, a sensitivity of 0.833, and a specificity of 0.735.

[0182] The marker combination marker2+marker3 had an AUC of 0.796, a sensitivity of 0.800, and a specificity of 0.735.

[0183] The marker combination marker1+marker2+marker3 had an AUC of 0.823, a sensitivity of 0.867, and a specificity of 0.706.

[0184] These markers and their combined models have performance close to that of the training set and validation set in the independent validation set, which once again verifies the stable generalization ability of the markers and models, indicating that the model has stable detection capabilities for predicting the efficacy of bladder cancer treatment.

[0185] Table 5. Different combination model performance for the discrimination of 64 bladder cancer samples.

[0186]

[0187] In summary, the methylation markers or their combinations are highly correlated with the detection or prediction of bladder cancer treatment efficacy, and their performance is superior to that of the methylation panel constructed from 11 genes, ARHGDIB, SHANK2, PROM1, RASGRF2, SEC31B, PXDNL, TRIM27, GPR75-ASB3, GALR1, PP12613, and NRN1, reported in existing literature, with an AUC of 0.67 in predicting bladder cancer treatment efficacy (A novel prognostic biomarker for muscleinvasive bladder urothelial carcinoma based on 11 DNA methylation signature).

[0188] The technical features of the above-mentioned embodiments can be combined arbitrarily. In order to make the description concise, not all possible combinations of the technical features in the above-mentioned embodiments are described. However, as long as there is no contradiction in the combination of these technical features, they should be considered to be within the scope of this specification.

[0189] The above-described embodiments merely illustrate several implementations of the present invention, and while their descriptions are relatively specific and detailed, they should not be construed as limiting the scope of the patent. It should be noted that a person skilled in the art would be able to make numerous variations and improvements without departing from the spirit of the present invention, all of which fall within the scope of protection of the present invention. Therefore, the scope of protection of the patent for this invention shall be determined by the appended claims.

Claims

1. Use of a detection reagent for a methylation biomarker or a combination thereof in the preparation of a kit for detecting or predicting the efficacy of neoadjuvant therapy for bladder cancer, wherein the methylation biomarker is selected from at least one of the following: chr8:132053505-132054221, chr1:146551513-146551739, and chr7:37488937-chr7:37488859, and the methylation sites are aligned to the positions corresponding to hg19.

2. The use according to claim 1, characterized in that The combination of methylation biomarkers is: chr8:132053505-132054221, and at least one selected from chr1:146551513-146551739, chr7:37488937-chr7:37488859.

3. The use according to claim 1, characterized in that The combination of methylation biomarkers is: chr1:146551513-146551739, and at least one selected from chr8:132053505-132054221, chr7:37488937-chr7:37488859.

4. The use according to claim 3, characterized in that The methylation biomarker combination is chr1:146551513-146551739, and chr7:37488937-chr7:37488859.

5. The use according to claim 1, characterized in that The combination of methylation biomarkers is: chr7:37488937-chr7:37488859, and at least one selected from chr1:146551513-146551739, chr8:132053505-132054221.

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