CN114774544A

CN114774544A - DNA methylation multiplex PCR kit for bladder cancer detection and application thereof

Info

Publication number: CN114774544A
Application number: CN202210391403.8A
Authority: CN
Inventors: 王行环; 肖宇; 张翼; 钱开宇; 彭旻晟; 鞠林高; 王刚
Original assignee: Beijing Youle Fusheng Technology Co ltd; Kunming Institute of Zoology of CAS; Zhongnan Hospital of Wuhan University
Current assignee: Beijing Youle Fusheng Technology Co ltd; Kunming Institute of Zoology of CAS; Zhongnan Hospital of Wuhan University
Priority date: 2022-04-14
Filing date: 2022-04-14
Publication date: 2022-07-22

Abstract

The invention discloses a DNA methylation multiplex PCR kit for detecting bladder cancer and application thereof, wherein the kit comprises: primer pair of DNA methylation markers for bladder cancer detection: the nucleotide sequences of the primer pairs 1-7 are shown in SEQ ID NO.1-SEQ ID NO. 14. The method is mainly used for auxiliary diagnosis of patients with bladder cancer, diagnosis and type identification are carried out before the operation of the patients, effective basis is provided for subsequent treatment of the patients, the operation is simple, the period is short, the diagnosis of bladder cancer and pathological typing of the bladder cancer is greatly shortened, an effective and strong-pertinence treatment scheme is provided for the patients more quickly, and the prognosis of the patients is facilitated.

Description

DNA methylation multiplex PCR kit for bladder cancer detection and application thereof

Technical Field

The embodiment of the invention relates to the technical field of biology, in particular to a DNA methylation multiplex PCR kit for detecting bladder cancer and application thereof.

Background

Bladder cancer (Bladder cancer, BCa) is the most common malignancy of the urinary system, with a worldwide increasing incidence. BCa is mainly divided into three pathological types, Bladder Urothelial Carcinoma (BLCA), squamous cell Carcinoma and adenocarcinoma, wherein BLCA accounts for 90%, and 212,500 new deaths occur in 2020 worldwide.

BLCA can be further divided into non-muscle invasive bladder cancer (NMIBC) and Muscle Invasive Bladder Cancer (MIBC), with NMIBC accounting for approximately 75% of all cases. The biological behaviors of the two types of BLCA are different, and the prognosis is very different, and needs to be treated differently. Since NIMIBC does not invade the muscular layer of the bladder, effective treatment can be achieved by transurethral cystectomy in combination with intracavitary perfusion of chemotherapeutic drugs or BCG. MIBC has stronger invasiveness, high growth speed and greatly improved metastatic potential, and bladder radical excision treatment is usually required. However, approximately 70% of clinically diagnosed NMIBC does not respond completely to standard treatment modalities and eventually relapse or even shift to MIBC. Surgical delays resulting from inaccurate initial pathological diagnosis can result in a 50% increase in the overall mortality risk ratio. Therefore, the method has important clinical significance for early diagnosis and accurate typing of the bladder cancer.

Currently, the main clinical diagnostic methods for bladder cancer include cystoscopy, apheresis cytology, B-ultrasonography, CT scan, etc. Bladder endoscopy is considered as the gold standard for diagnosis of bladder cancer, but the examination method is invasive and may cause complications such as urinary tract infection, urinary tract injury, bladder injury, etc., causing many discomforts such as pain, infection, hematuria, etc. to patients. The urine cast-off cytology examination, the FISH detection and the like can carry out auxiliary diagnosis on BCa, but the overall sensitivity and the specificity are not satisfactory and are respectively 50% and 85%. Particularly, since bladder cancer has the characteristics of unobvious early symptoms, rapid development after onset, difficult definite diagnosis of pathology, and the like, increasing the detection rate and shortening the detection time are critical.

Therefore, it is necessary to develop a new noninvasive bladder cancer detection scheme with higher sensitivity, stronger specificity and shorter detection period.

Disclosure of Invention

The embodiment of the invention aims to provide a DNA methylation multiplex PCR kit for detecting bladder cancer and application thereof, which can well distinguish invasive bladder cancer of muscle layer from non-invasive bladder cancer of muscle layer (AUC 0.83), and has better distinguishing degree between bladder cancer and normal urine (AUC 0.86).

In order to achieve the purpose, the invention adopts the following technical scheme:

in a first aspect of the embodiments of the present invention, there is provided a set of DNA methylation marker combinations for bladder cancer detection, the DNA methylation marker combinations for bladder cancer detection comprising:

the DNA methylation marker BSP _ SOX _1 is located at the positions of 181427281 and 181427781 on chromosome 3;

a DNA methylation marker BSP _ SOX _2 at the positions of 181446253 and 181446753 on chromosome 3;

the DNA methylation marker BSP _ SOX _3, located at 181499969-181500569 on chromosome 3;

the DNA methylation marker BSP _ SOX _4 is positioned on the 181430262-181431200 position on the chromosome 3;

a DNA methylation marker BSP _ SOX _5 located at positions 181438100-181438500 on chromosome 3;

the DNA methylation marker BSP _ SOX _6 is located at the positions 181428015 and 181428515 on chromosome 3;

the DNA methylation marker BSP _ SOX _7 is located at position 181436974 and 181437700 on chromosome 3.

In a second aspect of the embodiments of the present invention, there is provided a kit of DNA methylation markers for bladder cancer detection, the kit comprising: primer pairs for DNA methylation markers for bladder cancer detection:

the primer pair 1 is used for detecting a DNA methylation marker BSP _ SOX _1, and the nucleotide sequence of the primer pair is shown as SEQ ID NO.1-SEQ ID NO. 2;

a primer pair 2 for detecting a DNA methylation marker BSP _ SOX _2, the nucleotide sequence of which is shown as SEQ ID NO.3-SEQ ID NO. 4;

a primer pair 3 for detecting a DNA methylation marker BSP _ SOX _3, the nucleotide sequence of which is shown as SEQ ID NO.5-SEQ ID NO. 6;

the primer pair 4 is used for detecting a DNA methylation marker BSP _ SOX _4, and the nucleotide sequence of the primer pair is shown in SEQ ID NO.7-SEQ ID NO. 8;

a primer pair 5 for detecting a DNA methylation marker BSP _ SOX _5, the nucleotide sequence of which is shown in SEQ ID NO.9-SEQ ID NO. 10;

a primer pair 6 for detecting a DNA methylation marker BSP _ SOX _6, the nucleotide sequence of which is shown in SEQ ID NO.11-SEQ ID NO. 12;

and the primer pair 7 is used for detecting a DNA methylation marker BSP _ SOX _7, and the nucleotide sequence of the primer pair is shown as SEQ ID NO.13-SEQ ID NO. 14.

Further, the kit further comprises: the kit comprises a positive quality control product, a negative quality control product, a PCR premix solution, a library adaptor primer and a library amplification enzyme, wherein the PCR premix solution comprises: 10 XBuffer, 10mMdNTPs, 25mMMgCl₂AmpliTaq Gold DNA Polymerase and NF-H₂O。

The positive quality control product is bladder cancer cell DNA with a certain concentration, and the negative quality control product is normal bladder cell DNA with a certain concentration.

In the third aspect of the embodiment of the invention, the DNA methylation marker for bladder cancer detection and the application of the kit of the DNA methylation marker for bladder cancer detection in preparing bladder cancer detection products are provided.

Further, the application includes:

extracting urine DNA of a subject to perform sulfite treatment to obtain a sample of the subject;

performing multiplex PCR on the subject sample by using the kit of the DNA methylation marker for detecting bladder cancer, and performing high-throughput sequencing to obtain a methylation spectrum of the subject;

comparing the methylation spectrum of the subject with a bladder cancer specific methylation spectrum model in the constructed classifier, identifying the characteristic of DNA methylation patterns specific to bladder cancer, and calculating the evaluation score of methylation signals characteristic to whether bladder cancer exists in urine through a generalized linear model for judging whether bladder cancer exists;

further, comparing the identified bladder cancer specific DNA methylation sequence with an invasive bladder cancer specific methylation spectrum model in a constructed typing classifier, extracting the invasive bladder cancer specific DNA methylation pattern characteristics, and calculating whether the evaluation score is the invasive bladder cancer specific methylation signal evaluation score through a generalized linear model so as to judge the bladder cancer as invasive or non-invasive bladder cancer;

the determination is made by the following determination method:

if the methylation signal evaluation score which is characteristic of the bladder cancer is positive, judging the subject to be the bladder cancer;

if the methylation signal evaluation score which is characteristic of bladder cancer is positive, and the methylation signal evaluation score which is characteristic of invasive bladder cancer is positive, judging that the subject is invasive bladder cancer;

and if the methylation signal evaluation score which is characteristic of bladder cancer is positive, and the methylation signal evaluation score which is characteristic of invasive bladder cancer is negative, judging that the subject is non-invasive bladder cancer.

In a fourth aspect of embodiments of the present invention, a system for bladder cancer detection, the system comprising:

the acquisition module is used for calculating a positive quality control methylation spectrum, a negative quality control methylation spectrum and a methylation spectrum of a subject;

and the comparison module is used for comparing the methylation spectrum obtained by the acquisition module with the bladder cancer specific methylation spectrum model in the constructed classifier, identifying the characteristic of the bladder cancer specific DNA methylation pattern, calculating whether the urine has a methylation signal evaluation score which is characteristic of the bladder cancer or not through the generalized linear model, and if the methylation signal evaluation score which is characteristic of the bladder cancer is positive, judging that the subject is the bladder cancer.

In the above technical solution, the comparison module performs the comparison by using a computer processor based on fitting using a statistical classifier. The classifier is derived from machine learning. Wherein the classifier is an elastic net classifier, lasso, support vector machine, random forest or neural network.

Further, the system further comprises:

the subtype distinguishing module is used for distinguishing invasive bladder cancer from non-invasive bladder cancer, comparing the specific DNA methylation sequence of the bladder cancer identified by the comparison module with a specific methylation spectrum model of the invasive bladder cancer in a constructed typing classifier, extracting the specific DNA methylation pattern characteristics of the invasive bladder cancer, and calculating whether the evaluation score is the methylation signal evaluation score which is characteristic of the invasive bladder cancer through a generalized linear model:

if the methylation signal evaluation score which is characteristic of bladder cancer is positive, and the methylation signal evaluation score which is characteristic of invasive bladder cancer is positive, judging the subject to be invasive bladder cancer;

and if the methylation signal evaluation score which is characteristic of bladder cancer is positive and the methylation signal evaluation score which is characteristic of invasive bladder cancer is negative, judging that the subject is non-invasive bladder cancer.

In a fifth aspect of embodiments of the present invention, there is provided a system for bladder cancer detection, the system comprising:

a processor and a memory coupled to the processor, the memory storing instructions that when executed by the processor use the steps of:

the collection module comprises the following steps: intercepting the high-throughput sequencing data by target area reads, filtering by low-quality reads, calculating the methylation level of each sequence, counting the frequency of the sequence at each level to form a methylation spectrum, and storing the methylation spectrum in a memory;

a comparing module step: comparing the methylation spectrum with the classifier model, calculating the evaluation score of methylation signals with bladder cancer characteristics through a generalized linear model, outputting the score, and storing the score in a memory;

if the score of the last step is positive, further executing a subtype distinguishing module step, comparing the subtype distinguishing module step with a classifier model, extracting the specific DNA methylation pattern characteristics of the invasive bladder cancer, calculating the methylation signal evaluation score of the specificity of the invasive bladder cancer through a generalized linear model, outputting the score, and storing the score in a memory;

in a sixth aspect of embodiments of the present invention, there is provided a computer readable storage medium having a computer program stored thereon, the computer program being for execution by a processor to perform the steps recited.

In a seventh aspect of embodiments of the present invention, there is provided a bladder cancer detection product, comprising:

the kit of the DNA methylation marker for detecting the bladder cancer;

and said system or said computer readable storage medium.

One or more technical solutions in the embodiments of the present invention at least have the following technical effects or advantages:

the DNA methylation multiplex PCR kit for detecting the bladder cancer and the application thereof provided by the embodiment of the invention are mainly used for auxiliary diagnosis of patients with the bladder cancer, carry out diagnosis and type identification before operation of the patients, provide effective basis for subsequent treatment of the patients, and have the following advantages:

(1) the method is simple to operate and short in period, diagnosis of bladder cancer and pathological typing of the bladder cancer is greatly shortened, an effective and strong-pertinence treatment scheme is provided for a patient more quickly, and prognosis of the patient is facilitated. Patients can be identified as being diagnosable for bladder cancer and patients with bladder cancer can be classified as invasive or non-invasive. The kit has great positive significance for the diagnosis and treatment of the urinary bladder urothelial cancer in clinic, the monitoring and the prognosis evaluation in the later period, and provides a theoretical basis for further early diagnosis.

(2) The present application performed tests in model standards, biological standards, and authentic samples. In the model standard, methylation differences of 1% in most digital spots can be well identified, and the repeatability is good. In the biological standard, the gDNA template with the tumor content of 1% or more has good tumor detection rate and repeatability, so that the bladder cancer can be well detected by using the urine of a patient, and the pathological type of the bladder cancer can be diagnosed at the same time. In real samples, we included 94 specimens, including pre-operative urine from 70 bladder cancer patients, and urine from 24 normal persons. The results of the tests show that the method can be used to distinguish between muscle-invasive bladder cancer and non-muscle-invasive bladder cancer (AUC 0.83), and between bladder cancer and normal urine (AUC 0.86).

(3) The sensitivity is high, and samples with the tumor content as low as one percent can be detected.

(4) The urine before the operation of the patient is directly adopted, so that the operation is safe and noninvasive.

Drawings

In order to more clearly illustrate the technical solutions in the embodiments of the present invention, the drawings needed to be used in the description of the embodiments are briefly introduced below, and it is obvious that the drawings in the following description are some embodiments of the present invention, and it is obvious for those skilled in the art to obtain other drawings based on these drawings without creative efforts.

FIG. 1 shows the difference in methylation levels of methylated regions;

FIG. 2 is a plot of methylation levels of model standards;

FIG. 3 is the detection limit of the minimum content of the biological standard;

FIG. 4 shows the results of the measurement of 94 real samples.

Detailed Description

The embodiments of the present invention will be specifically explained below with reference to specific embodiments and examples, and the advantages and various effects of the embodiments of the present invention will be more clearly presented thereby. It should be understood by those skilled in the art that the detailed description and examples are intended to illustrate, but not limit, the embodiments of the invention.

Throughout the specification, unless otherwise specifically noted, terms used herein should be understood as having meanings as commonly used in the art. Accordingly, unless defined otherwise, all technical and scientific terms used herein have the same meaning as commonly understood by one of ordinary skill in the art to which embodiments of the invention belong. If there is a conflict, the present specification will control.

Unless otherwise specifically stated, various raw materials, reagents, instruments, equipment and the like used in the examples of the present invention are commercially available or can be prepared by an existing method.

The following will describe in detail a DNA methylation multiplex PCR kit for bladder cancer detection and its application in combination with examples, comparative examples and experimental data.

Example 1 DNA methylation marker combination for bladder cancer detection

The region with obvious DNA methylation difference between a bladder urothelial cancer patient and a normal person, and the DNA differential methylation gene and the specific region (DMR) between MIBC and NMIBC. In the examples of the present application, the methylation difference region screening conditions are shown in FIG. 1. The regions of differential methylation used to detect bladder cancer SOX2 gene are shown in table 1:

TABLE 1 regions of differential methylation of the SOX2 Gene

Name(s)	DMR ID NO.	Chromosome numbering	Physical location	Genome version number
					BSP_SOX_1	1	3	181427281-181427781	hg19
BSP_SOX_2	2	3	181446253-181446753	hg19
					BSP_SOX_3	3	3	181499969-181500569	hg19
BSP_SOX_4	4	3	181430262-181431200	hg19
					BSP_SOX_5	5	3	181438100-181438500	hg19
BSP_SOX_6	6	3	181428015-181428515	hg19
					BSP_SOX_7	7	3	181436974-181437700	hg19

Example 2 kit of DNA methylation markers for bladder cancer detection

1. Primer pair

Based on the results of example 1, the present invention, example 2, developed a kit of DNA methylation markers for bladder cancer detection. The methylation multiplex PCR primer combinations corresponding to the 7 important methylation regions for the analysis of the present application are shown in Table 2:

TABLE 2 methylated multiplex PCR primer combinations

Note: all the primers are provided with a joint universal sequence and a single molecular marker sequence consisting of 7 basic groups,

forward Primer linker Universal sequence:

5’-TTTCCCTACACGACGCTCTTCCGATCTNNNNNNN-3’，

reverse Primer adaptor universal sequence:

5’-TTAATGCAACGATCGTCGAAATTCGCNNNNNNN-3。

the primers used in the present invention were synthesized from Shanghai Bioengineering Co., Ltd.

2. The kit further comprises: the kit comprises a positive quality control product, a negative quality control product, a PCR premix solution, a library adaptor primer and a library amplification enzyme, wherein the PCR premix solution comprises: 10 XBuffer, 10mMdNTPs, 25mMMgCl₂AmpliTaq Gold DNA Polymerase and NF-H₂O。

The positive quality control substance is bladder cancer cell DNA with a certain concentration, and the negative quality control substance is normal urine DNA with a certain concentration.

The library adaptor primer:

5’-AATGATACGGCGACCACCGAGATCTACAC-3’(Index-A)

5’-ACACTCTTTCCCTACACGACGCAAGCAGAAGACGGCATACGAGAT-3’(Index-B)

TCGCGAGTTAATGCAACGATCGTCG

the specific sequence of Index-A, Index-B is shown in Table 3.

TABLE 3 library adaptor primer Index sequences

The library adaptor primers used in the present invention were synthesized from Integrated DNAtechnologies, Inc.

The PCR master mix was ordered from Thermo Fisher company.

Example 3 method for detection of bladder cancer and detection sensitivity verification of methylation Difference

Detection of 7 methylated regions was performed using a commercial complete methylation as well as non-methylation pattern standard (purchased from Zymo corporation).

The specific process is as follows:

DNA bisulfite conversion (BS treatment)

DNA bisulfite conversion kits were purchased from Zymo, Inc., according to kit instructions, and the conversion products were NF-H₂And eluting for later use.

2. Model Standard gradient incorporation

And (3) carrying out single-chain quantification after completely methylating the BS after treatment and ultrasonically cutting off the non-methylated mode standard substance. Gradient incorporation was performed according to DNA concentration, and a total of 13 model standard gradients (methylation levels of 100%, 99%, 98%, 95%, 90%, 80%, 50%, 20%, 10%, 5%, 2%, 1%, 0%) were set up.

3. Preparation of methylated multiplex PCR primer combination

7 pairs of primers were mixed for use.

4, preparing PCR premix solution

The premix was prepared according to table 4. Reagents for multiplex PCR reactions were purchased from Thermo Fisher (N8080241).

TABLE 4 methylation multiplex PCR premix protocol

reagent	volume(uL)
		DNA (20ng initial amount)	X
10X Buffer	2
		10mMdNTPs	0.4
25mMMgCl2	1.2
		AmpliTaq Gold DNA Polymerase	0.1
Primer set	2.8
		NF-H2O	13.5-X
total	20

PCR reaction procedure: 10min at 95 ℃; 25 × (95 ℃ 30s, 65 ℃ 30s, 54 ℃ 2min, 65 ℃ 30s, 72 ℃ 30 s); 10min at 72 ℃; 4 ℃ forever.

The reaction product can be stored temporarily at-20 ℃.

5. Multiplex PCR product recovery

1) The product from the PCR tube was snap-aspirated into a corresponding 1.5ml centrifuge tube to which 24. mu.L of XP Beads were added.

2) Vortex mix 15S immediately after 3S isolation, and incubate at room temperature for 5 min.

3) After the incubation was completed, a 1.5ml centrifuge tube was placed on a magnetic rack, and left to stand until the liquid was clear (about 5min), and the supernatant was discarded.

4) Adding 180ul of freshly prepared 80% ethanol, reversing each of the two sides for 2 times, incubating the mixture on a magnetic frame at room temperature for 30s, and discarding the supernatant.

5) Repeating the step 4) once.

6) The 1.5ml centrifuge tube was removed from the magnetic rack and centrifuged for 30 s. The 1.5ml centrifuge tube was returned to the magnetic stand, allowed to stand for 1min, and the residue was removed by pipetting with a 20. mu.l pipette.

7) The 1.5ml centrifuge tube cap was opened and air dried at room temperature until the surface of the beads was matt (about 1-3 min).

8) The 1.5ml centrifuge tube was removed from the magnetic rack and 25. mu.l NF-H was added₂And (O). Flicking with a finger, mixing by Vortex for 5s, and incubating at room temperature for 5 min.

9) After the incubation is finished, a 1.5ml centrifuge tube is placed on a magnetic frame and is kept stand until the liquid is clear for later use.

6.Index PCR

Library amplification enzymes for index PCR were purchased from KAPA Biosystems (KK 2602).

The reaction system is shown in Table 5:

TABLE 5 Index PCR reaction System

reagent	volume(uL)
		Recovering the product of the previous step	23
2×PCR mix	25
		i5 index(A1-A8)	1
i7 index(B1-B8)	1
		total	50

PCR reaction procedure: 45s at 98 ℃; 13 × (98 ℃ C. for 15s, 60 ℃ C. for 30s, 72 ℃ C. for 30 s); 5min at 72 ℃; 4 ℃ forever.

The reaction product can be placed at-20 ℃ and recovered the next day.

Recovery and quantitation of Index PCR products

1) The product from the PCR tube was snap-aspirated into a corresponding 1.5ml centrifuge tube to which 60. mu.L of XP Beads were added.

2) Vortex mix 15S immediately after 3S, incubate at room temperature for 5 min.

4) Adding 180 μ l of freshly prepared 80% ethanol, inverting each of the two sides for 2 times, incubating the mixture on a magnetic frame at room temperature for 30s, and discarding the supernatant.

5) Repeating the step 4) once.

7) The 1.5ml centrifuge tube lid was opened and air dried at room temperature until the surface of the beads was matt (about 1-3 min).

8) A1.5 ml centrifuge tube was removed from the magnetic rack and 36. mu.l EB was added. Flicking with a finger and mixing by Vortex 5S, and incubating at room temperature for 5 min.

9) After incubation, the 1.5ml centrifuge tube was placed on a magnetic rack, allowed to stand until the liquid was clear (about 5min), and transferred to a new 1.5ml centrifuge tube.

10) Double strand quantification was performed using dsDNA Qubit.

8. Library machine

After the concentration of the library is determined by fluorescent quantitative PCR and qualified, PE150 sequencing is carried out by using an Illumina Novaseq platform, and the data volume of each library is 5-8M reads.

9. As a result:

the methylation level differential degree of the 13 detected pattern standard products with different gradients is excellent, the detection sensitivity of the methylation difference can reach 1% in DNA templates with hypermethylation or hypomethylation, and the repeatability of 3 times is not different, which indicates that the pattern standard products have good stability. FIG. 2 is a graph of methylation levels of 13 standards of different gradient patterns after amplification with 7 pairs of primers.

The detection result shows that the currently used library establishing system can well distinguish methylation differences as low as 1%, which provides a powerful guarantee for detecting bladder cancer according to the DNA methylation marker.

Example 4 determination of minimum detection Limit

The detection of biological standard substances is carried out by using the bladder cancer cell strains RT4 and 5637 so as to clarify the lowest content detection limit of the bladder cancer and the classification thereof.

The specific process is as follows:

DNA extraction

Bladder cancer cell lines were purchased from the cell bank of the Chinese academy of sciences. The extraction kit was purchased from QIAGEN (69506) according to the kit instructions.

Normal urine DNA extraction kit was purchased from Zymo (D3601) according to the kit instructions.

DNA bisulfite conversion reference example 2

3. Biological standard gradient incorporation

Single strand quantification of BS-treated RT4/5637gDNA and normal urine DNA was performed. Gradient incorporation was performed according to DNA concentration, and 8 model standard gradients (bladder cancer gDNA content 100%, 20%, 10%, 5%, 2%, 1%, 0.5%, 0%) were set for each group.

4. Methylation multiplex PCR, index PCR and 2 times of recovery, sequencing refer to the above examples;

5. the degree of methylation of each region of methylation difference was calculated according to the multiplex PCR off-set data. Sequencing data were first aligned to the human genome using bwa-meth (version GRCh 37), and then DNA fragments aligned to each methylation difference region were extracted using the htslib library (0.7.9), and the number of C and T was calculated for the base corresponding to the CpG island of the reference genome on this fragment, and the degree of methylation of this fragment was: T/(C + T).

6. And (4) judging a result:

(1) for the methylation level of the characteristic DNA sequence of the bladder cancer and the normal sample, a t-test is carried out to obtain a set of methylation sites with obvious difference (Pvalue <0.01), and the frequency distribution of the methylation level is called as a methylation spectrum and is used for constructing a model and training. And comparing the DNA methylation sequence to be detected with the bladder cancer specific methylation spectrum model in the constructed typing classifier, and extracting the bladder cancer specific DNA methylation pattern characteristics. The methylation degree of the fragment can be calculated specifically as T/(C + T);

calculating a methylation signal evaluation score which is characteristic of the bladder cancer through a generalized linear model, and judging whether the bladder cancer is the bladder cancer; as a specific implementation mode, the generalized linear model can specifically adopt R (R is very powerful data visualization software), the formula is y to x, and the link function is Gaussian distribution; wherein the content of the first and second substances,

x is a vector, each component is the methylation level of a bladder cancer characteristic differential methylation region, the differential methylation region is a series of methylation fragments on each primer region which can obviously distinguish bladder cancer from normal, namely the bladder cancer specific methylation spectrum contained in the classifier model is compared and evaluated with a bladder cancer to be measured;

in the training samples, let y be 0 when the sample is from a non-bladder cancer individual;

in the training sample, when the sample is from a bladder cancer individual, let y be 1;

with the generalized linear model trained, a new value y is generated for each x input.

If the methylation level of the sample in the characteristic differential methylation region is similar to the bladder cancer specific methylation spectrum, and the significance of the distribution similarity of the methylation level in the 95% confidence interval reaches 0.01, namely judging that the methylation signal evaluation score which is characteristic of the bladder cancer is positive, judging that the subject is bladder cancer (as shown in the left graph of figure 4); where y is greater than a certain number. There may be variations in the cleavage value of y for different detection methods, which are not described herein redundantly.

(2) Furthermore, for the methylation level of the characteristic DNA sequence of invasive and non-invasive bladder cancer samples, a t test is carried out to obtain a set of a series of methylation sites with significant difference (Pvalue <0.01), and the frequency distribution of the methylation level (namely, methylation spectrum) is used for constructing a model and training. Comparing the DNA methylation sequence identified as bladder cancer specificity with the invasive bladder cancer specific methylation spectrum model in the established typing classifier, extracting the specific DNA methylation pattern characteristics of invasive bladder cancer, and calculating whether the DNA methylation pattern characteristics are methylation signal evaluation scores of invasive bladder cancer characteristics through a generalized linear model for judging invasive bladder cancer or non-invasive bladder cancer;

as a specific implementation manner, the generalized linear model in this step can specifically be made by using R (R is a very powerful data visualization software), the formula is y to x, and the link function is gaussian distribution; wherein the content of the first and second substances,

x is a vector, each component is the methylation level of a differential methylation region which is characteristic of invasive bladder cancer, the differential methylation region is a set of a series of methylation sites on each primer region which can obviously distinguish invasive bladder cancer from non-invasive bladder cancer, namely, the specific methylation spectrum of invasive bladder cancer contained in the classifier model is compared with a to-be-measured value and evaluated;

in the training sample, when the sample is from a non-invasive bladder cancer individual, let y be 0;

in the training sample, when the sample is from an invasive bladder cancer individual, let y be 1;

with the trained generalized linear model, a new value y is generated for each x input.

If the methylation level of the sample in the characteristic differential methylation region is similar to the specific methylation spectrum of the invasive bladder cancer, and the significance of the distribution similarity of the methylation level in a 95% confidence interval reaches 0.01, judging that the evaluation score of the methylation signal characteristic of the bladder cancer is positive, and judging that the evaluation score of the methylation signal characteristic of the invasive bladder cancer is positive, and judging that the subject is the invasive bladder cancer; where y is greater than a certain number. There may be variations in the cleavage value of y for different detection methods, which are not redundantly described here.

And if the methylation level of the sample in the characteristic differential methylation region is similar to the specific methylation spectrum of the non-invasive bladder cancer and the significance of the distribution similarity of the methylation level in the 95% confidence interval reaches 0.01, judging that the evaluation score of the methylation signal of the characteristic bladder cancer is positive, and simultaneously judging that the evaluation score of the methylation signal of the characteristic invasive bladder cancer is negative, and judging that the subject is the non-invasive bladder cancer. Where y is less than a certain number. There may be variations in the cleavage value of y for different detection methods, which are not redundantly described here.

The results are shown in fig. 3, and according to the data analysis results, the invention can well detect tumors according to key areas. Wherein, in the cell line RT4 (non-invasive), when the content of tumor DNA is more than 1%, normal urine DNA sample and sample containing tumor DNA can be correctly distinguished by the method; whereas in cell line 5637 (invasive), it was well distinguishable from normal urine DNA samples with 3-fold reproducibility with tumor content > 0.5%.

Example 5 evaluation of clinical Properties

A total of 94 samples were included in this application, including pre-operative urine from 70 patients with bladder cancer, and urine from 24 normal persons.

The application carries out methylation multiplex PCR library construction on 94 samples to determine the judgment of distinguishing the non-muscle layer infiltrative property and the muscle layer infiltrative property of the normal person and the bladder cancer, and the specific flow is as follows:

DNA extraction

Urine DNA extraction kits were purchased from Zymo (D3061) according to kit instructions.

Bisulfite conversion of DNA

Reference example 2

100ng of DNA was subjected to BS treatment (less than 100ng was made up with. lamda.DNA purchased from Takala (3010)

3. Methylation multiplex PCR, index PCR and 2-time recovery of reference example 2

4. The degree of methylation of each region of methylation difference was calculated according to the multiplex PCR off-set data. The sequencing data were first aligned to the human genome using bwa-meth (version GRCh 37), and then the htslib library (0.7.9) was used to extract DNA fragments aligned to each methylation difference region, which were counted as C and T for the bases corresponding to the CpG island of the reference genome on the fragment, and the degree of methylation of the fragment was: T/(C + T).

5. And (3) constructing a generalized linear model by using the methylation degree of each methylation difference region, and distinguishing urine of a bladder cancer patient from normal human urine, or bladder cancer with muscle layer invasion and non-muscle layer invasion. And predicting a sample result through the model.

6. As a result:

as shown in fig. 4, the results of the off-line data analysis and the verification results showed that the present method was able to distinguish between muscle-invasive bladder cancer and non-muscle-invasive bladder cancer (AUC 0.83), and that the bladder cancer was also distinguished from normal urine (AUC 0.86).

EXAMPLE 6 bladder cancer detection System

The embodiment of the invention provides a bladder cancer detection system, which comprises:

an acquisition module for receiving a positive standard positive sample methylation profile, a negative standard sample methylation profile, and a subject methylation profile;

and the comparison module is used for comparing the methylation spectrum of the subject with the methylation spectrum of the positive standard sample and the methylation spectrum of the negative standard sample, and if the methylation spectrum of the subject is statistically significant similar to the methylation spectrum of the positive standard sample, the subject is judged to be the bladder cancer.

The system further comprises:

a subtype distinguishing module used for distinguishing invasive bladder cancer from non-invasive bladder cancer, comparing the DNA methylation sequence identified by the comparison module with the invasive bladder cancer specific methylation spectrum model in the established typing classifier, extracting the specific DNA methylation pattern characteristics of the invasive bladder cancer, and calculating the methylation signal evaluation score whether the specific methylation pattern characteristics of the invasive bladder cancer are the specific methylation signal evaluation scores of the invasive bladder cancer through a generalized linear model:

Specifically, the system comprises:

the bladder cancer detection score is obtained from the input of DNA methylation markers for bladder cancer detection into the prediction system described in example 2.

Example 7 computer-readable storage Medium

Embodiments of the present invention provide a computer-readable storage medium, on which a computer program is stored, which, when executed by a processor, implements the steps of the method of embodiment 4 and/or the method of embodiment 5.

Of course, the storage medium provided by the embodiment of the present invention contains computer-executable instructions, and the computer-executable instructions are not limited to the method operations described above, and may also perform related operations in the method provided by any embodiment of the present invention.

From the above description of the embodiments, it is obvious for those skilled in the art that the present invention can be implemented by software and necessary general hardware, and certainly, can also be implemented by hardware, but the former is a better embodiment in many cases. Based on such understanding, the technical solutions of the present invention may be embodied in the form of a software product, which may be stored in a computer-readable storage medium, such as a floppy disk, a Read-Only Memory (ROM), a Random Access Memory (RAM), a FLASH Memory (FLASH), a hard disk or an optical disk of a computer, and includes instructions for enabling an electronic device (which may be a personal computer, a server, or a network device) to execute the methods according to the embodiments of the present invention.

It should be noted that, in the foregoing embodiment, each included unit and each included module are only divided according to functional logic, but are not limited to the above division as long as the corresponding functions can be implemented; in addition, specific names of the functional units are only for convenience of distinguishing from each other, and are not used for limiting the protection scope of the present invention.

Finally, it should also be noted that the terms "comprises," "comprising," or any other variation thereof, are intended to cover a non-exclusive inclusion, such that a process, method, article, or apparatus that comprises a list of elements does not include only those elements but may include other elements not expressly listed or inherent to such process, method, article, or apparatus.

While preferred embodiments of the present invention have been described, additional variations and modifications of those embodiments may occur to those skilled in the art once they learn of the basic inventive concepts. Therefore, it is intended that the appended claims be interpreted as including preferred embodiments and all such alterations and modifications as fall within the scope of the embodiments of the invention.

It will be apparent to those skilled in the art that various modifications and variations can be made in the embodiments of the present invention without departing from the spirit or scope of the embodiments of the invention. Thus, provided that such modifications and variations of the embodiments of the present invention fall within the scope of the claims of the embodiments of the present invention and their equivalents, the embodiments of the present invention are intended to include such modifications and variations as well.

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Claims

1. A DNA methylation marker combination for bladder cancer detection, wherein the DNA methylation marker combination for bladder cancer detection comprises:

the DNA methylation marker BSP _ SOX _1, located at positions 181427281 and 181427781 on chromosome 3;

a DNA methylation marker BSP _ SOX _3 at the positions 181499969-one 181500569 on chromosome 3;

the DNA methylation marker BSP _ SOX _6, located at 181428015-181428515 on chromosome 3;

the DNA methylation marker BSP _ SOX _7 is located at the positions 181436974 and 181437700 on chromosome 3.

2. A kit of DNA methylation markers for detection of bladder cancer, the kit comprising: primer pairs for DNA methylation markers for bladder cancer detection:

a primer pair 4 for detecting a DNA methylation marker BSP _ SOX _4, the nucleotide sequence of which is shown as SEQ ID NO.7-SEQ ID NO. 8;

the primer pair 7 is used for detecting a DNA methylation marker BSP _ SOX _7, and the nucleotide sequence of the primer pair is shown in SEQ ID NO.13-SEQ ID NO. 14.

3. The kit of DNA methylation markers for bladder cancer detection according to claim 2, wherein the kit further comprises: the kit comprises a positive quality control product, a negative quality control product, a PCR premix solution, a library adaptor primer and a library amplification enzyme, wherein the PCR premix solution comprises: 10 XBuffer, 10mMdNTPs, 25mMMgCl₂AmpliTaq Gold DNApolymerase and NF-H₂O。

4. Use of the DNA methylation marker for bladder cancer detection of claim 1, the DNA methylation marker for bladder cancer detection of claims 2-3, and a kit for preparing a bladder cancer detection product.

5. The application according to claim 4, characterized in that it comprises: diagnosing whether the bladder cancer is caused by urine assistance; further aiding in the identification of bladder cancer typing: invasive and non-invasive bladder cancer; the method specifically comprises the following steps:

extracting urine cfDNA of a subject to perform sulfite treatment to obtain a sample of the subject;

performing multiplex PCR on the sample of the subject by using the kit of the DNA methylation marker for bladder cancer detection, according to the claims 2-3, and then performing high-throughput sequencing to obtain a methylation profile of the subject;

further comparing the identified bladder cancer specific DNA methylation sequence with an invasive bladder cancer specific methylation spectrum model in a constructed typing classifier, extracting the invasive bladder cancer specific DNA methylation pattern characteristics, and calculating whether the evaluation score is the invasive bladder cancer specific methylation signal evaluation score through a generalized linear model so as to judge the bladder cancer or non-invasive bladder cancer;

the determination is made by the following determination method:

6. A system for bladder cancer detection, the system comprising:

7. The system for bladder cancer detection according to claim 6, further comprising:

a subtype distinguishing module used for distinguishing invasive bladder cancer from non-invasive bladder cancer, comparing the specific DNA methylation sequence of bladder cancer identified by the comparison module with the specific methylation spectrum model of invasive bladder cancer in the established typing classifier, extracting the specific DNA methylation pattern characteristics of invasive bladder cancer, and calculating whether the evaluation score is the methylation signal evaluation score which is the characteristic of invasive bladder cancer through a generalized linear model:

8. A system for bladder cancer detection, the system comprising:

the acquisition module comprises the following steps: intercepting the high-throughput sequencing data by target area reads, filtering low-quality reads, calculating the methylation level of each sequence, counting the frequency of the sequence appearing at each level to form a methylation spectrum, and storing the methylation spectrum in a memory;

and if the score of the last step is positive, further executing a subtype distinguishing module step, comparing the subtype distinguishing module step with the classifier model, extracting the specific DNA methylation pattern characteristics of the invasive bladder cancer, calculating the methylation signal evaluation score which is the characteristic of the invasive bladder cancer through a generalized linear model, outputting the score, and storing the score in a memory.

9. A computer-readable storage medium, on which a computer program is stored, characterized in that the computer program is executed by a processor to perform the steps of claim 8.

10. A bladder cancer detection product, comprising:

a kit of DNA methylation markers for bladder cancer detection according to claims 2 to 3;

and the system of any one of claims 6-8 or the computer-readable storage medium of claim 9.