Combination of dna methylation sites as bladder cancer markers and use thereof

Abstract

The embodiments of the present specification provide a DNA methylation site combination as a bladder cancer marker, a detection reagent of the DNA methylation site combination, and a use of the DNA methylation site combination or the detection reagent thereof in the preparation of a kit for bladder cancer screening, bladder cancer risk prediction, evaluation of bladder cancer treatment effect, and / or screening of bladder cancer treatment drugs. The DNA methylation site combination described in the present specification has good sensitivity and specificity, shows significant differences in methylation levels between known bladder cancer patients and non-bladder cancer patients, and can be used as a marker for bladder screening, bladder cancer risk prediction, etc., and can also be used to design diagnostic reagents or kits. The embodiments of the present specification also provide devices and kits for bladder cancer screening or bladder cancer risk prediction.

Description

TECHNICAL FIELD

[0001] The present specification relates to the field of biotechnology, in particular to a method and kit for low-cost, rapid and accurate detection of bladder cancer. BACKGROUND

[0002] Bladder cancer is one of the most common malignant tumors of the urinary system. Worldwide, the incidence of bladder cancer ranks 9th among malignant tumors, and the mortality rate of bladder cancer ranks 13th among malignant tumors. Bladder cancer has regional, racial and gender differences, and can occur in people of all ages, with a high incidence of 50-70 years old. In addition, the incidence of men is 3-4 times that of women.

[0003] Urine cytology is one of the important methods for the diagnosis and postoperative follow-up of bladder cancer, and the detection of cancer cells in urine is one of the diagnostic methods for renal pelvis cancer, ureter cancer and bladder cancer. The sensitivity of urine exfoliative cytology is 13%-75%, and the specificity is 85%-100%.

[0004] Current studies have shown that bladder cancer is the result of long-term effects of multiple carcinogenic factors, and its pathological process is a complex process of accumulation of multiple gene mutations, involving abnormal methylation of multiple oncogenes and tumor suppressor genes. Most of the abnormal methylation is the hypermethylation of tumor suppressor genes, which often leads to transcriptional silencing of tumor suppressor genes. DNA methylation abnormalities usually occur in the early stages of cancer and throughout the occurrence and development of cancer.

[0005] Therefore, it is desirable to provide a DNA methylation site combination as a bladder cancer marker and its application, which helps to achieve accurate, rapid and non-invasive clinical screening of bladder cancer. SUMMARY

[0006] One or more embodiments of the present specification provide a DNA methylation site combination as a biomarker or use of a detection reagent of a DNA methylation site combination in the preparation of a kit for bladder cancer screening, bladder cancer prevalence risk prediction, evaluation of bladder cancer treatment effect, and / or screening of bladder cancer treatment drugs, characterized in that the DNA methylation site combination comprises one or more of the following group: site EOMES_70 located at chromosome coordinate chr3:27765376 on the EOMES gene; site TWIST1_62 located at chromosome coordinate chr7:19157596 on the TWIST1 gene; site NKX2-6_35 located at chromosome coordinate chr8:23564229 on the NKX2-6 gene; site VIM_95 located at chromosome coordinate chr10:17271456 on the VIM gene; site HIST1H4F_53 located at chromosome coordinate chr6:26240774 on the HIST1H4F gene; site NRN1_54 located at chromosome coordinate chr6:6004485 on the NRN1 gene; site PENK-1_51 located at chromosome coordinate chr8:57358707 on the PENK-1 gene; site PENK-2_85 located at chromosome coordinate chr8:57358407 on the PENK-2 gene; site PXDN_37 located at chromosome coordinate chr2:1746846 on the PXDN gene; and site IRF4_50 located at chromosome coordinate chr6:392057 on the IRF4 gene.

[0007] In some embodiments, the DNA methylation site combination comprises any five, six, seven, eight, nine, or all of EOMES_70, TWIST1_62, NKX2-6_35, VIM_95, HIST1H4F_53, NRN1_54, PENK-1_51, PENK-2_85, PXDN_37, and IRF4_50 in combination.

[0008] In some embodiments, the DNA methylation site combination comprises a combination comprising at least EOMES_70, IRF4_50, PENK-1_51, PENK-2_85, and VIM_95.

[0009] In some embodiments, the DNA methylation site combination comprises a combination consisting of EOMES_70, IRF4_50, PENK-1_51, PENK-2_85, and VIM_95.

[0010] In some embodiments, the combination of DNA methylation sites comprises a combination consisting of EOMES_70, TWIST1_62, NKX2-6_35, VIM_95, HIST1H4F_53, NRN1_54, PENK-1_51, PENK-2_85, PXDN_37, and IRF4_50.

[0011] In some embodiments, the detection reagent comprises a primer set for amplifying the combination of DNA methylation sites; wherein the primer pair for amplifying EOMES_70 is set forth in SEQ ID NO: 1 and SEQ ID NO: 2; the primer pair for amplifying TWIST1_62 is set forth in SEQ ID NO: 3 and SEQ ID NO: 4; the primer pair for amplifying NKX2-6_35 is set forth in SEQ ID NO: 5 and SEQ ID NO: 6; the primer pair for amplifying VIM_95 is set forth in SEQ ID NO: 7 and SEQ ID NO: 8; the primer pair for amplifying HIST1H4F_53 is set forth in SEQ ID NO: 9 and SEQ ID NO: 10; the primer pair for amplifying NRN1_54 is set forth in SEQ ID NO: 11 and SEQ ID NO: 12; the primer pair for amplifying PENK-1_51 is set forth in SEQ ID NO: 13 and SEQ ID NO: 14; the primer pair for amplifying PENK-2_85 is set forth in SEQ ID NO: 15 and SEQ ID NO: 16; the primer pair for amplifying PXDN_37 is set forth in SEQ ID NO: 17 and SEQ ID NO: 18; or the primer pair for amplifying IRF4_50 is set forth in SEQ ID NO: 19 and SEQ ID NO: 20.

[0012] The one or more embodiments of the specification provide a device for bladder cancer screening, bladder cancer morbidity risk prediction, evaluation of bladder cancer treatment effect and / or screening of bladder cancer treatment drugs, the device comprising a memory, a processor and a computer program stored on the memory and executable on the processor, characterized in that the processor implements the following method when executing the program: obtaining the methylation level of a DNA methylation site combination in a biological sample of a subject, wherein the DNA methylation site combination comprises one or more of the following groups: site EOMES_70 located at chromosome coordinate chr3:27765376 on the EOMES gene; site TWIST1_62 located at chromosome coordinate chr7:19157596 on the TWIST1 gene; site NKX2-6_35 located at chromosome coordinate chr8:23564229 on the NKX2-6 gene; site VIM_95 located at chromosome coordinate chr10:17271456 on the VIM gene; site HIST1H4F_53 located at chromosome coordinate chr6:26240774 on the HIST1H4F gene; site NRN1_54 located at chromosome coordinate chr6:6004485 on the NRN1 gene; site PENK-1_51 located at chromosome coordinate chr8:57358707 on the PENK-1 gene; site PENK-2_85 located at chromosome coordinate chr8:57358407 on the PENK-2 gene; site PXDN_37 located at chromosome coordinate chr2:1746846 on the PXDN gene; and site IRF4_50 located at chromosome coordinate chr6:392057 on the IRF4 gene; based on the methylation level of the DNA methylation site combination, using a screening model to evaluate whether the subject has bladder cancer, predict the risk of the subject developing bladder cancer, evaluate the effect of the subject treating bladder cancer and / or evaluate the effect of a bladder cancer treatment drug.

[0013] The one or more embodiments of the present specification provide a detection reagent for a DNA methylation site combination, which is used as a biomarker for bladder cancer screening, bladder cancer prevalence risk prediction, evaluation of bladder cancer treatment effect, and / or screening of bladder cancer treatment drugs, characterized in that the detection reagent comprises a primer set for amplifying the DNA methylation site combination, and the DNA methylation site combination comprises one or more of the following group: a site EOMES_70 located at the chromosome coordinate of chr3:27765376 on the EOMES gene; a site TWIST1_62 located at the chromosome coordinate of chr7:19157596 on the TWIST1 gene; a site NKX2-6_35 located at the chromosome coordinate of chr8:23564229 on the NKX2-6 gene; a site VIM_95 located at the chromosome coordinate of chr10:17271456 on the VIM gene; a site HIST1H4F_53 located at the chromosome coordinate of chr6:26240774 on the HIST1H4F gene; a site NRN1_54 located at the chromosome coordinate of chr6:6004485 on the NRN1 gene; a site PENK-1_51 located at the chromosome coordinate of chr8:57358707 on the PENK-1 gene; a site PENK-2_85 located at the chromosome coordinate of chr8:57358407 on the PENK-2 gene; a site PXDN_37 located at the chromosome coordinate of chr2:1746846 on the PXDN gene; and a site IRF4_50 located at the chromosome coordinate of chr6:392057 on the IRF4 gene.

[0014] In some embodiments, the primer pair for amplifying EOMES_70 is set forth in SEQ ID NO: 1 and SEQ ID NO: 2; the primer pair for amplifying TWIST1_62 is set forth in SEQ ID NO: 3 and SEQ ID NO: 4; the primer pair for amplifying NKX2-6_35 is set forth in SEQ ID NO: 5 and SEQ ID NO: 6; the primer pair for amplifying VIM_95 is set forth in SEQ ID NO: 7 and SEQ ID NO: 8; the primer pair for amplifying HIST1H4F_53 is set forth in SEQ ID NO: 9 and SEQ ID NO: 10; the primer pair for amplifying NRN 1_54 is set forth in SEQ ID NO: 11 and SEQ ID NO: 12; the primer pair for amplifying PENK-1_51 is set forth in SEQ ID NO: 13 and SEQ ID NO: 14; the primer pair for amplifying PENK-2_85 is set forth in SEQ ID NO: 15 and SEQ ID NO: 16; the primer pair for amplifying PXDN_37 is set forth in SEQ ID NO: 17 and SEQ ID NO: 18; the primer pair for amplifying IRF4_50 is set forth in SEQ ID NO: 19 and SEQ ID NO: 20.

[0015] In some embodiments, the detection reagent further comprises other reagents for detecting the methylation level of the combination of DNA methylation sites; the other reagents comprise reagents used in one or more of the following methods: whole genome bisulfite sequencing, reduced representation bisulfite sequencing, oxidative-bisulfite sequencing, methylated DNA capture sequencing, methyl binding protein sequencing, methylated DNA immunoprecipitation sequencing, high performance liquid chromatography, methylation sensitive restriction fingerprinting, methylation sensitive amplification polymorphism, methylation microarray, pyrosequencing, digital PCR, and methylation specific PCR.

[0016] One or more embodiments of the present specification provide a methylation site combination for bladder cancer screening, bladder cancer morbidity risk prediction, evaluation of bladder cancer treatment effect, and / or screening of bladder cancer treatment drugs, the DNA methylation site combination comprising one or more of the following group: a site EOMES_70 located on the EOMES gene at the chromosome coordinate of chr3: 27765376; a site TWIST1_62 located on the TWIST1 gene at the chromosome coordinate of chr7: 19157596; a site NKX2-6_35 located on the NKX2-6 gene at the chromosome coordinate of chr8: 23564229; a site VIM_95 located on the VIM gene at the chromosome coordinate of chr10: 17271456; a site HIST1H4F_53 located on the HIST1H4F gene at the chromosome coordinate of chr6: 26240774; a site NRN1_54 located on the NRN1 gene at the chromosome coordinate of chr6: 6004485; a site PENK-1_51 located on the PENK-1 gene at the chromosome coordinate of chr8: 57358707; a site PENK-2_85 located on the PENK-2 gene at the chromosome coordinate of chr8: 57358407; a site PXDN_37 located on the PXDN gene at the chromosome coordinate of chr2: 1746846; and a site IRF4_50 located on the IRF4 gene at the chromosome coordinate of chr6: 392057.

[0017] One or more embodiments of the present specification provide a kit for bladder cancer screening, bladder cancer morbidity risk prediction, evaluation of bladder cancer treatment effect, and / or screening of bladder cancer treatment drugs, the kit comprising detection reagents as described previously.

[0018] One or more embodiments of the present specification provide a method for bladder cancer screening, bladder cancer morbidity risk prediction, evaluation of bladder cancer treatment effect, and / or screening of bladder cancer treatment drugs, characterized in that the method comprises: obtaining the methylation level of a DNA methylation site combination in a biological sample of a subject, wherein the DNA methylation site combination comprises one or more of the following groups: site EOMES_70 located at chromosome coordinate chr3:27765376 on the EOMES gene; site TWIST1_62 located at chromosome coordinate chr7:19157596 on the TWIST1 gene; site NKX2-6_35 located at chromosome coordinate chr8:23564229 on the NKX2-6 gene; site VIM_95 located at chromosome coordinate chr10:17271456 on the VIM gene; site HIST1H4F_53 located at chromosome coordinate chr6:26240774 on the HIST1H4F gene; site NRN1_54 located at chromosome coordinate chr6:6004485 on the NRN1 gene; site PENK-1_51 located at chromosome coordinate chr8:57358707 on the PENK-1 gene; site PENK-2_85 located at chromosome coordinate chr8:57358407 on the PENK-2 gene; site PXDN_37 located at chromosome coordinate chr2:1746846 on the PXDN gene; and site IRF4_50 located at chromosome coordinate chr6:392057 on the IRF4 gene; based on the methylation level of the DNA methylation site combination, using a screening model to evaluate whether the subject has bladder cancer, predict the risk of the subject developing bladder cancer, evaluate the effect of the subject treating bladder cancer, and / or evaluate the effect of a bladder cancer treatment drug.

[0019] One or more embodiments of the present specification provide a method for bladder cancer screening, bladder cancer prevalence risk prediction and bladder cancer treatment, comprising: obtaining the methylation level of a DNA methylation site combination in a biological sample of a subject, wherein the DNA methylation site combination comprises one or more of the following groups: a site located at chromosome coordinate chr3:27765376 on the EOMES gene; a site TWIST1_62 located at chromosome coordinate chr7:19157596 on the TWIST1 gene; a site NKX2-6_35 located at chromosome coordinate chr8:23564229 on the NKX2-6 gene; a site VIM_95 located at chromosome coordinate chr10:17271456 on the VIM gene; a site HIST1H4F_53 located at chromosome coordinate chr6:26240774 on the HIST1H4F gene; a site NRN1_54 located at chromosome coordinate chr6:6004485 on the NRN1 gene; a site PENK-1_51 located at chromosome coordinate chr8:57358707 on the PENK-1 gene; a site PENK-2_85 located at chromosome coordinate chr8:57358407 on the PENK-2 gene; a site PXDN_37 located at chromosome coordinate chr2:1746846 on the PXDN gene; and a site IRF4_50 located at chromosome coordinate chr6:392057 on the IRF4 gene; based on the methylation level of the DNA methylation site combination, using a screening model to evaluate whether the subject has bladder cancer, predict the risk of the subject developing bladder cancer; treating the subject with bladder cancer or at risk of developing bladder cancer, the treatment comprising one or more of surgical resection, radiotherapy, hormone therapy, chemotherapy, targeted therapy and immunotherapy.

[0020] The one or more embodiments of the specification provide a use of a combination of DNA methylation sites as biomarkers for bladder cancer screening, bladder cancer prevalence risk prediction, evaluation of bladder cancer treatment effect, and / or screening of bladder cancer treatment drugs, the combination of DNA methylation sites comprising one or more of the following group: a site EOMES_70 located on the EOMES gene at the chromosome coordinate of chr3:27765376; a site TWIST1_62 located on the TWIST1 gene at the chromosome coordinate of chr7:19157596; a site NKX2-6_35 located on the NKX2-6 gene at the chromosome coordinate of chr8:23564229; a site VIM_95 located on the VIM gene at the chromosome coordinate of chr10:17271456; a site HIST1H4F_53 located on the HIST 1H4F gene at the chromosome coordinate of chr6:26240774; a site NRN1_54 located on the NRN1 gene at the chromosome coordinate of chr6:6004485; a site PENK-1_51 located on the PENK-1 gene at the chromosome coordinate of chr8:57358707; a site PENK-2_85 located on the PENK-2 gene at the chromosome coordinate of chr8:57358407; a site PXDN_37 located on the PXDN gene at the chromosome coordinate of chr2:1746846; and a site IRF4_50 located on the IRF4 gene at the chromosome coordinate of chr6:392057. BRIEF DESCRIPTION OF DRAWINGS

[0021] The specification will be further described in the manner of exemplary embodiments, which will be described in detail with the drawings. The embodiments are not restrictive, and in the embodiments, the same numbers represent the same structures.

[0022] Figure 1 is an application scenario diagram of a system for early bladder cancer screening or bladder cancer prevalence risk prediction according to some embodiments of the specification;

[0023] Figure 2 is a schematic diagram of the architecture of a computing device according to some embodiments of the specification;

[0024] Figure 3 is a module diagram of a system for early bladder cancer screening or bladder cancer prevalence risk prediction according to some embodiments of the specification;

[0025] Figure 4 is a flowchart diagram of a method for early bladder cancer screening or bladder cancer prevalence risk prediction according to some embodiments of the specification;

[0026] Figure 5is a flow chart of determining the methylation threshold of DNA methylation sites according to some embodiments of the present specification;

[0027] Figure 6 is a distribution diagram of the methylation rate of 10 specific methylation sites in the training set and the validation interference set according to some embodiments of the present specification;

[0028] Figure 7 is a sensitivity distribution diagram of 10 specific methylation sites according to some embodiments of the present specification;

[0029] Figure 8 is a sensitivity distribution diagram of the methylation sites of each combination in the comparative example according to some embodiments of the present specification. DETAILED DESCRIPTION

[0030] In order to more clearly illustrate the technical solutions of the embodiments of the present specification, the following will briefly introduce the drawings needed to be used in the embodiment description. Obviously, the drawings in the following description are only some examples or embodiments of the present specification, and for those skilled in the art, the present specification can also be applied to other similar scenarios without creative labor on the basis of these drawings. Unless it is clear from the language context or otherwise indicated, the same reference numbers in the drawings represent the same structures or operations.

[0031] It should be understood that the "system", "device", "unit" and / or "module" used herein is a method for distinguishing different components, elements, parts, portions or assemblies at different levels. However, if other words can achieve the same purpose, the words can be replaced by other expressions.

[0032] As shown in the specification and claims, unless the context clearly indicates otherwise, "one", "a", "an", and / or "the" do not refer to the singular, but can also include the plural. Generally speaking, the terms "comprise" and "include" only indicate the inclusion of the steps and elements explicitly identified, and these steps and elements do not constitute an exclusive list, and the method or device can also include other steps or elements.

[0033] Flowcharts are used in the present specification to illustrate the operations performed by the system according to the embodiments of the present specification. It should be understood that the preceding or subsequent operations are not necessarily performed in sequence. On the contrary, each step can be processed in reverse order or simultaneously. At the same time, other operations can also be added to these processes, or one or more steps of operation can be removed from these processes.

[0034] DNA methylation is one of the forms of DNA chemical modification, which refers to the process of covalently binding a methyl group (CH3-) to the 5th carbon atom of cytosine in the CpG structure under the action of DNA methyltransferase (DNMTs), and often occurs in the promoter CpG island region of genes, which is an important epigenetic marker. Existing studies have shown that abnormal DNA methylation is an important influencing factor leading to various types of cancer. For example, the hypermethylation of the promoter region of some tumor-related genes can inhibit the expression of the corresponding genes, and vice versa, hypomethylation can promote the expression of the corresponding genes. The present specification proposes that the combination of DNA methylation sites can be used as a bladder cancer marker for bladder cancer screening, bladder cancer risk prediction, evaluation of bladder cancer treatment effect, and / or screening of bladder cancer treatment drugs. The detection sample of the combination of DNA methylation sites can be widely derived from the body fluids, cells, tissues and organs of the subject, especially the urine of the subject, which can be used to realize accurate, rapid and non-invasive bladder cancer screening, risk prediction, prognosis prediction and drug evaluation. The bladder cancer here can include early, medium and late bladder cancer. "Bladder cancer screening" especially early bladder cancer screening refers to the detection before the appearance of obvious symptoms of bladder cancer, and should not be limited to the detection of early bladder cancer.

[0035] The present specification provides a method for bladder cancer screening, bladder cancer risk prediction and treatment of bladder cancer, as well as a system and device thereof, which is based on the evaluation of the methylation level of the aforementioned combination of DNA methylation sites to assess the possibility of bladder cancer or the risk of developing bladder cancer in a subject.

[0036] The present specification also provides a detection reagent for the combination of DNA methylation sites, including a reagent for amplifying the aforementioned combination of DNA methylation sites, which can be widely used in various aspects including bladder cancer screening, bladder cancer risk prediction, evaluation of bladder cancer treatment effect, and / or screening of bladder cancer treatment drugs.

[0037] The present specification also provides a kit for bladder cancer screening, bladder cancer risk prediction, evaluation of bladder cancer treatment effect, and / or screening of bladder cancer treatment drugs.

[0038] The present specification also provides related uses of the combination of DNA methylation sites as biomarkers, and related uses of the detection reagent for the combination of DNA methylation sites. The uses include but are not limited to the use in the preparation of a kit for bladder cancer screening, the use in the preparation of a kit for bladder cancer risk prediction, the use in the preparation of a kit for the evaluation of bladder cancer treatment effect, the use in the preparation of a kit for the screening of bladder cancer treatment drugs, etc., which can take into account and improve the sensitivity and specificity of screening, prediction and screening.

[0039] According to an aspect of the present specification, a system for bladder cancer screening, bladder cancer prevalence risk prediction, bladder cancer treatment effect evaluation, and / or bladder cancer treatment drug screening is provided. Figure 1 is an application scenario diagram of a system for bladder cancer screening, bladder cancer prevalence risk prediction, bladder cancer treatment effect evaluation, and / or bladder cancer treatment drug screening according to some embodiments of the present specification. As shown in Figure 1 , the scenario 100 can include a processing device 110 and a storage device 120.

[0040] The processing device 110 can process data and / or information. In some embodiments, the processing device 110 can obtain data and / or information from the storage device 120 or other components of the scenario 100 (e.g., user terminal 140, detection device 160), and execute program instructions based on the information and / or data to perform one or more functions described in the present specification. For example, the processing device 110 can obtain a training sample set from the storage device 120 and construct a screening model based on the training sample set. For another example, the processing device 110 can obtain methylation level related information of a DNA methylation site combination of a subject biological sample 150 measured by the detection device 160 and invoke the screening model stored at the storage device 120 to process the methylation level related information to evaluate the possibility of the subject having early bladder cancer or the risk of developing bladder cancer. In some embodiments, the processing device 110 can be a server or a central processor.

[0041] The storage device 120 can be used to store data and / or information. In some embodiments, the storage device 120 can store data and / or information obtained from the processing device 110 or other components of the scenario 100 (e.g., user terminal 140, detection device 160). For example, the storage device 120 can store a screening model for the processing device 110 to invoke. For another example, the storage device 120 can obtain and store methylation level related information of a DNA methylation site combination of a subject biological sample 150 from the detection device 160. For another example, the storage device 120 can receive and store information uploaded by the user terminal 140, such as the identity information of the subject.

[0042] In some embodiments, the scenario 100 further includes a network 130. The network 130 can be used to provide a channel for information exchange. In some embodiments, the processing device 110 and other components of the scenario 100 (e.g., the storage device 120, the user terminal 140, the detection device 160) can exchange information through the network 130. For example, the processing device 110 can receive data in the storage device 120 through the network 130. For another example, the detection device 160 can transmit the information about the methylation levels of the DNA methylation site combinations of the biological sample 150 of the subject to the processing device 110 through the network. In some embodiments, the network 130 can be any one or more of a wired network or a wireless network. For example, the network 130 can include a cable network, a fiber-optic network, etc. In some embodiments, the network 130 can be of various topologies or a combination of topologies, such as point-to-point, shared, hub-and-spoke, etc. In some embodiments, the network 130 can include one or more network access points. For example, one or more components of the scenario 100 can connect to the network 130 through access points such as a base station and / or one or more network exchange points to exchange data and / or information.

[0043] In some embodiments, the scenario 100 further includes a user terminal 140. The user terminal 140 can be used to implement the services provided by the scenario 100 to a user. For example, a user can send the information about the methylation levels of the DNA methylation site combinations of the biological sample of the subject to the processing device 110 through the user terminal 140. For another example, a user can receive the evaluation result of the subject sent by the processing device 110 through the user terminal 140. For yet another example, a user can send the clinical test result of the subject to the processing device 110 through the user terminal 140, so that the processing device 110 updates the training sample set based on the clinical test result of the subject and iterates the screening model. In some embodiments, the user terminal 140 can include one or any combination of a smartphone 140-1, a tablet computer 140-2, a laptop computer 140-3, etc., or other devices with input and / or output functions.

[0044] In some embodiments, the scenario 100 further includes a detection device 160 for detecting the methylation levels of the DNA methylation site combinations of the biological sample 150. As an example, the detection device can include a device implementing one or more of the following methods: WGBS, RRBS, oxBS-seq, MethylCap-seq, MBD-seq, MeDIP-seq, HPLC, MSRF, MASP, methylation chip method, pyrosequencing method, dP CR, and MS-PCR.

[0045] According to yet another aspect of the present specification, a computing device is provided. Figure 2is a schematic diagram of an architecture of a computing device according to some embodiments of the present specification. As shown in Figure 2 The computing device 200 includes a processor 210, a memory 220, an input / output interface 230, and a communication port 240. In some embodiments, the computing device 200 can implement the processing device 110 and / or the storage device 120. For example, the processing device 110 can be implemented on the computing device 200, and the computing device 200 is configured to perform the functions of the processing device 110 described in the present specification. In some embodiments, the apparatus for early screening of bladder cancer, prediction of the risk of bladder cancer, evaluation of the treatment effect of bladder cancer, and / or screening of drugs for bladder cancer treatment can be implemented in the computing device 200.

[0046] The processor 210 can execute computing instructions (program code) and perform the functions of the processing device 110 described in the present specification. The computing instructions can include programs, objects, components, data structures, processes, modules, and functions (functions refer to specific functions described in the present application). For example, the processor 210 can process the instructions of the user inputted early screening of bladder cancer or the possibility of the risk prediction of bladder cancer. In some embodiments, the computing device 200 can include one or more processors 210; the processor 210 can include a central processing unit (CPU), an application specific integrated circuit (ASIC), and any circuit and processor capable of performing one or more functions, etc., or any combination thereof.

[0047] The memory 220 can store data / information obtained from any component of the scene 100. In some embodiments, the memory 220 can include random access memory (RAM), read only memory (ROM), etc., or any combination thereof.

[0048] The input / output interface 230 can be used to input or output signals, data or information. In some embodiments, the input / output interface 230 can be used to implement the interaction behavior of the user (e.g., the subject, the operator, etc.) with the processing device 210. In some embodiments, the user can input the relevant information of the subject (e.g., the methylation level related information of the DNA methylation site combination, and the basic identity information such as the name, the age, etc.) through the input / output interface 230. In some embodiments, the input / output interface 230 can include input devices and output devices. For example, a keyboard, a mouse, a display device, a microphone, a speaker, etc.

[0049] The communication port 240 can be connected to the network 130 for data communication. The connection can be a wired connection, a wireless connection, or a combination of both, such as a connection through a cable, an optical cable, a mobile network, WIFI, WLAN, or Bluetooth, etc. In some embodiments, the communication port 240 can be a standardized port, such as RS232, RS485, etc. In some embodiments, the communication port 240 can be a specially designed port.

[0050] Figure 3 is a module diagram of a system for bladder cancer screening, bladder cancer prevalence risk prediction, evaluation of bladder cancer treatment effect, and / or screening of bladder cancer treatment drugs according to some embodiments of the present specification. As shown in Figure 3 The system 300 for bladder cancer early screening, bladder cancer prevalence risk prediction, evaluation of bladder cancer treatment effect, and / or screening of bladder cancer treatment drugs includes an acquisition module 310 and an analysis module 320. In some embodiments, these modules can be included in the processing device 110 or the processor 210.

[0051] The acquisition module 310 can be used to acquire the methylation level of the DNA methylation site combination in the biological sample of the subject, for example, the DNA methylation site combination can include one or more of EOMES_70, TWIST1_62, NKX2-6_35, VIM_95, HIST1H4F_53, NRN1_54, PENK-1_51, PENK-2_85, PXDN_37, and IRF4_50.

[0052] In some embodiments, the acquisition module 310 can include a detection unit and an information processing unit. The detection unit can be used for DNA methylation detection on the biological sample of the subject. For example, the detection unit can include devices that implement one or more of the following methods: WGB S, RRBS, oxBS-seq, MethylCap-seq, MBD-seq, MeDIP-seq, HPLC, MSRF, MASP, methylation chip method, pyrosequencing method, dPCR, and MS-PCR. The information processing unit can be used to process the detection data of the detection unit to obtain the methylation level related information of the DNA methylation site combination of the biological sample of the subject.

[0053] The analysis module 320 can be configured to evaluate whether the subject is likely to have bladder cancer or is at risk of developing bladder cancer, evaluate the treatment effect of bladder cancer, and / or screen the drug for treating bladder cancer using a screening model based on the methylation level of the DNA methylation site combination of the subject's biological sample. In some embodiments, the analysis module 320 can be configured to perform the evaluation using a model based on a methylation threshold of the DNA methylation site combination. In some embodiments, the analysis module 320 can be configured to perform the evaluation using a model constructed based on a machine learning algorithm or a deep learning algorithm.

[0054] In some embodiments, the system 300 further comprises a determination module 330. The determination module 330 can be configured to obtain a training sample set comprising the methylation rate of DNA methylation sites of known bladder cancer patients and non-bladder cancer patients; and analyze the training sample set using a ROC curve to determine a cutoff value for distinguishing bladder cancer patients from non-bladder cancer patients. In some embodiments, the determination module 330 can determine the cutoff value as a methylation threshold of the DNA methylation site. In some embodiments, the determination module 330 can determine the methylation rate at a specificity of 100% as a methylation threshold of the DNA methylation site.

[0055] Further details regarding how the modules of the system 300 perform their functions can be found elsewhere in this specification (e.g., in the description of the system 300 and its modules, and Figure 4 , Figure 5 and their descriptions).

[0056] It should be appreciated that Figure 3 The system 300 and its modules shown for bladder cancer screening, bladder cancer prevalence risk prediction, evaluation of bladder cancer treatment effect, and / or screening of drugs for treating bladder cancer can be implemented in various ways. For example, in some embodiments, the system 300 and its modules can be implemented by hardware, software, or a combination of software and hardware. The hardware part can be implemented by using special logic; the software part can be stored in a memory and executed by a suitable instruction execution system, such as a microprocessor or a specially designed hardware. Those skilled in the art can understand that the above-mentioned methods and systems can be implemented using computer executable instructions and / or contained in processor control code, such as provided on a carrier medium, such as a magnetic disk, CD or DVD-ROM, a programmable memory, such as a read-only memory (firmware), or a data carrier, such as an optical or electronic signal carrier. The system and its modules of the present specification can not only be implemented by hardware circuitry, such as very large scale integrated circuits or gate arrays, semiconductors, such as logic chips, transistors, or programmable hardware devices, such as field programmable gate arrays, programmable logic devices, etc., but also by software, for example, executed by various types of processors, and also by a combination of the above-mentioned hardware circuitry and software (e.g., firmware).

[0057] It should be noted that the above description of system 300 and its modules is for convenience of description only and does not limit the scope of the present specification to the embodiments shown. It can be understood that, for those skilled in the art, after understanding the principles of the system, any combination of the modules or connection of the modules to other modules can be made without departing from the principles. In some embodiments, Figure 3 The acquisition module, the analysis module and the determination module disclosed in the present specification can be different modules in a system, or one module can implement the functions of two or more modules described above. For example, the modules can share one storage module, or each module can have its own storage module. Variations such as these are within the scope of protection of the present specification.

[0058] According to another aspect of the present specification, a method for bladder cancer screening, bladder cancer risk prediction, bladder cancer treatment effect evaluation and / or bladder cancer treatment drug screening is provided. Figure 4 is a flowchart of a method for bladder cancer screening, bladder cancer risk prediction, bladder cancer treatment effect evaluation and / or bladder cancer treatment drug screening according to some embodiments of the present specification. As Figure 4 shown, the flow 400 includes step 401 and step 420. In some embodiments, at least part of the steps in the flow 400 (e.g. step 401, step 420) can be completed by a computing device (e.g. Figure 2 the computing device 200 shown in Figure 1 the processing device 110 shown in Figure 1 In some embodiments, at least part of the steps in the flow 400 can be implemented as an instruction (e.g. an application) stored in the storage device 120, the memory 220. Figure 2 The processing device 110 in Figure 4 the processor 210 and / or the module can execute the instruction, and when the instruction is executed, the processing device 110, the processor 210 and / or the module can be configured to execute the flow 400. The operations of the processes shown below are for illustrative purposes only. In some embodiments, the flow 400 can be completed with one or more additional operations not described or one or more operations not described. In addition,

[0059] Step 401, acquiring the methylation level of the DNA methylation site combination in the biological sample of the subject.

[0060] In some embodiments, step 401 can be performed by a computing device (e.g. Figure 1 the processing device 110 of Figure 3 the acquisition module 310 of

[0061] In some embodiments, the methylation levels of the combination of DNA methylation sites in a biological sample of a subject having bladder cancer (e.g., early stage bladder cancer) can be distinguished from the methylation levels of the combination of DNA methylation sites in a biological sample of a non-bladder cancer subject (including a healthy subject, a subject having other diseases but not bladder cancer).

[0062] As used herein, the term "subject" (or "individual") refers to an object that receives observation, detection, or experimentation. In some embodiments, the subject can be a mammal. Mammals include, but are not limited to, primates (including humans and non-human primates) and rodents (e.g., mice and rats). In some embodiments, the mammal can be a human.

[0063] The term "biological sample" (or "sample" or "specimen") refers to a composition isolated from an organ, tissue, cell, and / or body fluid of a subject, which comprises one or more target analytes (e.g., nucleic acids, metabolites, etc.). In some embodiments, the biological sample is from a body fluid of a subject. Body fluids include, but are not limited to, whole blood, plasma, serum, interstitial fluid, saliva, urine, lavage fluid (e.g., bladder lavage fluid), etc., or a combination thereof. In some embodiments, the sample is from urine of a subject, particularly the formed elements of urine. Urine formed elements can comprise one or more of circulating free nucleic acids (e.g., circulating free DNA (cfDNA) derived from the bladder), circulating tumor cells (CTCs) (e.g., tumor cells released by bladder tumors), and exfoliated cells (e.g., cells exfoliated from the urinary system).

[0064] The term "methylation level" is an indicator of the methylation status of a DNA methylation site. In some embodiments, the methylation level can be quantitatively described by the frequency, proportion, or percentage of methylation of a DNA methylation site.

[0065] In some embodiments, the combination of DNA methylation sites is suitable for detecting different stages of bladder cancer, such as early stage (e.g., stage I, stage II) and late stage (e.g., stage III, stage IV). In some preferred embodiments, the combination of DNA methylation sites is suitable for distinguishing a population of early stage bladder cancer from a population of non-bladder cancer, wherein the early stage bladder cancer includes stage I bladder cancer and stage II bladder cancer.

[0066] The combination of DNA methylation sites includes one or more DNA methylation sites. As used herein, the term "DNA methylation site" (or "methylation site") refers to a covalent bond of a methyl group to the 5' carbon position of a cytosine in a CpG dinucleotide of genomic DNA, resulting in 5-methylcytosine (5mC). In some embodiments, the methylation status of each DNA methylation site in the combination of DNA methylation sites can be associated with the occurrence, development of bladder cancer, and the DNA methylation sites in the combination of DNA methylation sites can be located on bladder cancer-related genes (e.g., known or potentially potential bladder cancer tumor suppressor genes). Non-limiting examples of bladder cancer-related genes can include, but are not limited to: EOMES, TWIST1, NKX2-6, VIM, HIST1H4F, NRN1, PENK-1, PENK-2, PXDN, IRF4, ACOT11, NPY, AL021918.2, AC084082.3, ACTB.

[0067] In some embodiments, the combination of DNA methylation sites can include one or more DNA methylation sites located on EOMES, TWIST1, NKX2-6, VIM, HIST1H4F, NRN1, PENK-1, PENK-2, PXDN, IRF4, ACOT11, NPY, AL021918.2, AC084082.3, ACTB.

[0068] The methylation level of each DNA methylation site in the combination of DNA methylation sites is significantly associated with bladder cancer (e.g., early bladder cancer). It can be understood that for each DNA methylation site in the combination of DNA methylation sites, there is a significant difference between the methylation level in the known bladder cancer (e.g., early bladder cancer) population and the methylation level in the normal population.

[0069] In some embodiments, the combination of DNA methylation sites can comprise at least 1, 2, 3, 4, 5, 6, 7, 8, 9, or 10 sites from the following group: site EOMES_70 at chromosome coordinate chr3:27765376 on the EOMES gene; site TWIST1_62 at chromosome coordinate chr7:19157596 on the TWIST1 gene; site NKX2-6_35 at chromosome coordinate chr8:23564229 on the NKX2-6 gene; site VIM_95 at chromosome coordinate chr10:17271456 on the VIM gene; site HIST1H4F_53 at chromosome coordinate chr6:26240774 on the HIST1H4F gene; site NRN1_54 at chromosome coordinate chr6:6004485 on the NRN1 gene; site PENK-1_51 at chromosome coordinate chr8:57358707 on the PENK-1 gene; site PENK-2_85 at chromosome coordinate chr8:57358407 on the PENK-2 gene; site PXDN_37 at chromosome coordinate chr2:1746846 on the PXDN gene; and site IRF4_50 at chromosome coordinate chr6:392057 on the IRF4 gene.

[0070] It should be noted that the chromosome coordinate information used herein is derived from human reference genome hg19 (GRCh37). It should be noted that the chromosome coordinate information used herein can also be converted to human reference genome hg38 (GRCh38), which is not limited in the present application.

[0071] In some preferred embodiments, the combination of DNA methylation sites can comprise EOMES_70, TWIST1_62, NKX2-6_35, VIM_95, HIST1H4F_53, NRN1_54, PENK-1_51, PENK-2_85, PXDN_37, and IRF4_50. Alternatively, the combination of DNA methylation sites can further comprise one or more DNA methylation sites on one or more other bladder cancer related genes. In some embodiments, the combination of DNA methylation sites can comprise one or more of EOMES_70, TWIST1_62, NKX2-6_35, VIM_95, HIST1H4F_53, NRN1_54, PENK-1_51, PENK-2_85, PXDN_37, and IRF4_50 and one or more of the other methylation sites in Table 1.

[0072] In some embodiments, the combination of DNA methylation sites can include one, two, three, four, five, six, seven, eight, nine, or all of EOMES_70, TWIST1_62, NKX2-6_35, VIM_95, HIST1H4F_53, NRN1_54, PENK-1_51, PENK-2_85, PXDN_37, and IRF4_50. In some embodiments, the combination of DNA methylation sites can include at least the combination of EOMES_70, IRF4_50, PENK-1_51, PENK-2_85, and VIM_95. For example, the combination of DNA methylation sites can include the five combinations of EOMES_70, IRF4_50, PENK-1_51, PENK-2_85, and VIM_95. For another example, the combination of DNA methylation sites can include the five combinations of EOMES_70, IRF4_50, PENK-1_51, PENK-2_85, and VIM_95 and one, two, three, four, or five of the remaining ten sites. For yet another example, the combination of DNA methylation sites can include the five combinations of EOMES_70, IRF4_50, PENK-1_51, PENK-2_85, and VIM_95 and one or more of the other methylation sites in Table 1.

[0073] In some more preferred embodiments, the combination of DNA methylation sites can consist of EOMES_70, TWIST1_62, NKX2-6_35, VIM_95, HIST1H4F_53, NRN1_54, PENK-1_51, PENK-2_85, PXDN_37, and IRF4_50. In some embodiments, the combination of DNA methylation sites can consist of EOMES_70, TWIST1_62, NKX2-6_35, VIM_95, HIST1H4F_53, NRN1_54, PENK-1_51, PENK-2_85, PXDN_37, and IRF4_50 and one or more of the other methylation sites in Table 1 of the Examples.

[0074] The methylation level of the DNA methylation site combination provided in some embodiments of this specification is significantly correlated with bladder cancer. The methylation status of this DNA methylation site combination can be quantified and used to measure its methylation level. Samples containing this DNA methylation site combination can be collected broadly from organs, tissues, cells, and body fluids of subjects, particularly urine, for a comfortable, non-invasive test. The application of this DNA methylation site combination as a biomarker for bladder cancer screening, bladder cancer risk prediction, evaluation of bladder cancer treatment efficacy, and / or screening of bladder cancer treatment drugs can improve the sensitivity and specificity of screening / diagnosis, prediction, evaluation, and selection.

[0075] In some embodiments, the methylation level of a combination of DNA methylation sites can be obtained by detecting a subject's biological sample using a reagent for detecting combinations of DNA methylation sites. The reagent for detecting combinations of DNA methylation sites is used to achieve the detection of the methylation level of a combination of DNA methylation sites.

[0076] More information about reagents for detecting combinations of DNA methylation sites can be found elsewhere in this instruction manual.

[0077] Computing devices (e.g., Figure 1 Processing equipment 110 Figure 3 The acquisition module 310 can execute step 401 in various ways. In some embodiments, the processing device 110 can retrieve information related to the methylation level of the DNA methylation site combination of the subject's biological sample stored in the storage device 120. For example, the information related to the methylation level of the DNA methylation site combination of the subject's biological sample is uploaded to the storage device 120 by the user terminal 140 via the network 130, and the processing device 110 can retrieve and obtain this methylation level information for further analysis and evaluation. In some embodiments, the processing device 110 can receive information related to the methylation level of the DNA methylation site combination of the subject's biological sample obtained by the detection device 160. For example, the processing device 110 sends a detection instruction to the detection device 160 (e.g., a PCR instrument and / or an NGS sequencer), the detection device 160 detects and obtains information related to the methylation level of the DNA methylation site combination of the subject's biological sample based on the detection instruction, and sends the methylation level information to the processing device 110. In some embodiments, the processing device 110 can obtain information related to the methylation level of the DNA methylation site combination of the subject's biological sample based on user input.

[0078] At step 403, based on the methylation levels of the DNA methylation site combination, the screening model is used to evaluate whether the subject has bladder cancer, predict the risk of the subject developing bladder cancer, evaluate the effect of the subject treating bladder cancer, and / or evaluate the effect of a bladder cancer treatment drug. In some embodiments, step 403 can be performed by a computing device (e.g., the processing device 110 of the system 100, Figure 1 the analysis module 320 of the system 300). Figure 3

[0079] In some embodiments, the screening model can be a model based on a methylation threshold of the DNA methylation site combination (or threshold model). The threshold model can divide the types of the subject biological sample by a threshold judgment, realize the evaluation of the possibility of developing cancer or the risk of developing cancer, and the evaluation of the effect of bladder cancer treatment and / or the screening of bladder cancer treatment drugs. In some embodiments, the evaluation using the threshold model can include a positive site judgment step and a comprehensive evaluation step.

[0080] In the positive site judgment step, for each DNA methylation site in the DNA methylation site combination of the subject biological sample, the methylation rate of the DNA methylation site is compared with the methylation threshold corresponding to the DNA methylation site, and the number of positive sites in all DNA methylation sites of the DNA methylation site combination is determined.

[0081] In some embodiments, the methylation level of the DNA methylation site combination can be quantitatively described by the methylation rate. The determination method of the methylation rate can be set based on the specific methylation detection method. In some embodiments, the methylation level of the DNA methylation site combination of the subject biological sample is detected by methylation conversion (e.g., using a methylation conversion reagent (e.g., bisulfite) to convert non-methylated cytosine in the DNA methylation site to thymine, and methylated cytosine is not converted), specific amplification and sequencing. For each DNA methylation site of the DNA methylation site combination, the methylation rate thereof can be determined by the following formula (1):

[0082] Methylation rate = NumC / (NumC+NumT) (1)

[0083] Wherein, NumC represents the number of reads in which the specific DNA methylation site is cytosine among all sequencing reads containing the specific DNA methylation site; NumT represents the number of reads in which the specific DNA methylation site is thymine among all sequencing reads containing the specific DNA methylation site.

[0084] ​It can be understood that in other embodiments, other methylation rate determination methods can be used to match the corresponding methylation detection method, as long as the purpose of quantitatively describing the methylation level of the combination of DNA methylation sites can be achieved.

[0085] The methylation threshold can be used as a boundary for evaluating the methylation level of the DNA methylation site. In some embodiments, if the methylation rate of a single DNA methylation site in the combination of DNA methylation sites is greater than or equal to the methylation threshold corresponding to the DNA methylation site, the DNA methylation site can be judged as a positive site. Otherwise, it is a negative site.

[0086] More information about determining the methylation threshold of the DNA methylation site can be found elsewhere in this specification (for example, Figure 5 and the description thereof).

[0087] In the comprehensive evaluation step, the evaluation result is obtained based on the number of positive sites of the combination of DNA methylation sites of the biological sample of the subject. If the number of positive sites is greater than or equal to 1, it can be judged that the subject is likely to have bladder cancer, or the subject is likely to have the risk of developing bladder cancer; the treatment effect of bladder cancer is poor and / or the effect of bladder cancer treatment drug is poor. Otherwise, it indicates that the subject is less likely to have bladder cancer, or the subject is less likely to have the risk of developing bladder cancer; the treatment effect of bladder cancer is good and / or the effect of bladder cancer treatment drug is good.

[0088] The possibility of the subject developing bladder cancer can be qualitatively evaluated by the number of positive sites of the combination of DNA methylation sites. As an example, the combination of DNA methylation sites can include 2 or more DNA methylation sites (for example, 2 or more of EOMES_70, TWIST1_62, NKX2-6_35, VIM_95, HIST1H4F_53, NRN1_54, PENK-1_51, PENK-2_85, PXDN_37 and IRF4_50). If any one of the 2 or more DNA methylation sites is a positive site, it indicates that the subject is likely to have bladder cancer, or the subject is likely to have the risk of developing bladder cancer; the treatment effect of bladder cancer is poor and / or the effect of bladder cancer treatment drug is poor; if all of the 2 or more DNA methylation sites are negative sites, it indicates that the possibility of the subject having bladder cancer or the risk of developing bladder cancer can be excluded; or it indicates that the treatment effect of bladder cancer is good and / or the effect of bladder cancer treatment drug is good.

[0089] In some embodiments, the screening model can be a machine learning model or a deep learning model. Non-limiting examples of machine learning algorithms and deep learning algorithms that can be used to build the screening model include, but are not limited to, support vector machine algorithm, logistic regression algorithm model, decision tree algorithm, k-nearest neighbor algorithm, k-means algorithm, convolutional neural network algorithm, linear regression algorithm, recurrent neural network algorithm, etc., or a combination thereof.

[0090] In some embodiments, the input of the screening model built using the machine learning algorithm or the deep learning algorithm can be the methylation rates of the DNA methylation site combinations of the subject biological sample, and the output of the screening model can be a numerical value (e.g., 0-1). Through the numerical value, the probability of the subject having bladder cancer (e.g., early bladder cancer) or the probability of the subject developing bladder cancer, the treatment effect of bladder cancer treatment, and / or the treatment effect of bladder cancer treatment drug are indicated. The screening model can be obtained by training an initial model using a training sample set. The training sample set can include the methylation rates of the DNA methylation site combinations of one or more known bladder cancer (e.g., early bladder cancer) patient samples and the methylation rates of the DNA methylation site combinations of non-bladder cancer patient (e.g., healthy person) samples, as well as labels indicating whether the sample subject has bladder cancer. The term “known bladder cancer patient” refers to a subject or individual who has clinical symptoms of bladder cancer and has been verified by clinical diagnosis (e.g., the disease type and nature have been confirmed by biopsy). The term “non-bladder cancer patient” refers to a subject or individual who does not have bladder cancer and has no obstacles in daily life.

[0091] For example, in the training sample set used to train the screening model, the label of the bladder cancer patient sample can be 1, and the label of the non-bladder cancer patient sample can be 0. With the methylation rates of the DNA methylation site combinations of the subject biological sample as the model input, the evaluation value output by the corresponding screening model can be between 0 and 1. The closer the evaluation value is to 1, the higher the probability of the subject having bladder cancer or the probability of the subject developing bladder cancer, the better the treatment effect of bladder cancer, and the better the drug treatment effect.

[0092] The computing device (e.g., Figure 1 the processing device 110 of the computing device 100, Figure 3The analysis module 320) can implement the execution of step 403 in various ways. In some embodiments, the processing device 110 can call the screening model stored in the storage device 120 and use the screening model to process the methylation level related information of the DNA methylation site combination of the subject biological sample to obtain the evaluation result. In other embodiments, the processing device 110 can update the screening model stored in the storage device 120 based on user instructions and use the updated screening model to obtain the evaluation result. Among them, the processing device 110 can collect the methylation level related information of the associated DNA methylation site combination of the bladder cancer population and the normal population from the public or non-public database through the network 130, for updating the training sample set and optimizing the screening model. The processing device 110 can also update the training sample set based on user input or based on data / information uploaded by the user terminal 140 and optimize the screening model.

[0093] In some embodiments, when it is detected that the subject has bladder cancer, or the subject may have a risk of bladder cancer, further diagnosis can be made by further instruments, and for the subject after diagnosis, treatment is needed. The treatment methods include but are not limited to surgical resection (e.g., transurethral resection of bladder tumor (TURBT) and cystectomy), radiotherapy (including local radiotherapy and total bladder radiotherapy), chemotherapy, targeted therapy, immunotherapy, etc. or a combination thereof. Targeted therapy focuses on specific genes and proteins of cancer cells, as well as other molecules related to cancer growth and spread. Targeted therapies for bladder cancer include immune checkpoint inhibitors (e.g., pembrolizumab, Nivolumab), vascular endothelial growth factor receptor inhibitors, epidermal growth factor receptor antagonists, hormone receptor targeted drugs (e.g., FGFR kinase inhibitors such as Erdafitinib (Balversa) or other molecular targeted drugs. Immunotherapy utilizes the human body's own immune system to recognize and attack cancer cells. Immunotherapy for bladder cancer includes intravesical immunotherapy (e.g., Bacillus Calmette-Guerin (BCG)), immune checkpoint inhibitors (mainly PD-1 and PD-L1 inhibitors), antibody conjugate drugs (e.g., Enfortumab vedotin), etc.

[0094] It should be noted that the above description of the flow 400 is only for example and illustration, and does not limit the scope of the present specification. Various modifications and changes can be made to the flow 400 under the guidance of the present specification. However, these modifications and changes are still within the scope of the present specification.

[0095] Figure 5is a flowchart illustrating a process of determining a methylation threshold of a DNA methylation site according to some embodiments of the present disclosure. As shown in Figure 5 Flow 500 includes step 501 and step 503. In some embodiments, flow 500 can be performed by a computing device (e.g., processing device 110 of system 100, Figure 1 determination module 330 of system 100) of the present disclosure. Figure 3

[0096] Step 501, obtaining a training sample set.

[0097] In some embodiments, processing device 110 (e.g., determination module 330) can obtain a training sample set, which includes methylation rates of DNA methylation sites of known bladder cancer patients and non-bladder cancer patients.

[0098] In some embodiments, the known bladder patients can include early-stage bladder cancer patients and late-stage bladder cancer patients. The known bladder cancer patients can be individuals who have not received treatment after being diagnosed, or individuals who have received treatment after being diagnosed. In some preferred embodiments, the known bladder cancer patients are early-stage bladder cancer patients.

[0099] Step 503, analyzing the training sample set using a ROC curve, and the methylation threshold of the DNA methylation site is a cutoff value for distinguishing bladder cancer patients from non-bladder cancer patients.

[0100] In some embodiments, processing device 110 (e.g., determination module 330) can analyze the training sample set using a ROC curve, determine a cutoff value for distinguishing bladder cancer patients from non-bladder cancer patients, and use the cutoff value as the methylation threshold of the DNA methylation site.

[0101] The term “ROC curve” (or Receiver Operating Characteristic curve) is a curve plotted with experimental sensitivity (true positive rate) as the vertical coordinate and 1-specificity (false positive rate) as the horizontal coordinate. The ROC curve can be used to select the optimal cutoff value (or critical value), and to evaluate the performance of the model. In some embodiments, the methylation rate data of the training sample set can be used to make a ROC curve for a single DNA methylation site, and a suitable methylation threshold can be determined based on the cutoff value selection method that adapts to the application requirements.

[0102] ​In some embodiments, the cutoff value selection method can be using the methylation rate value corresponding to the maximum Youden index (sensitivity + specificity - 1) as the cutoff value. In other embodiments, the cutoff value selection method can be using the methylation rate value corresponding to the set sensitivity value as the cutoff value, for example, the set sensitivity value is 90% to 100%. In yet other embodiments, the cutoff value selection method can be using the methylation rate value corresponding to the set specificity value as the cutoff value, for example, the set specificity value is 90% to 100%.

[0103] In some preferred embodiments, to avoid misjudging non-bladder cancer as bladder cancer and improve the accuracy of prediction, the methylation rate value corresponding to the set specificity value can be used as the cutoff value. More preferably, the set specificity value can be 95% to 100%. More preferably, the set specificity value can be 100%.

[0104] In some embodiments, the AUC of the screening model provided in the present specification can be greater than 0.8, 0.85 or 0.9. In some embodiments, the sensitivity of the screening model provided in the present specification can be greater than 80%, 85%, 90% or 95%. In some embodiments, the specificity of the screening model provided in the present specification can be greater than 80%, 85%, 90% or 95%.

[0105] The computing device (for example, Figure 1 the processing device 110 of the computer system 100, Figure 3 the determination module 330 of the computer system 100) can implement the execution of the flow 500 in various ways. In some embodiments, the processing device 110 can call the training sample set stored in the storage device 120 and determine the methylation threshold of the DNA methylation site based on the preset cutoff value selection method. In other embodiments, the processing device 110 can call the training sample set stored in the storage device 120 to re-determine the methylation threshold of the DNA methylation site based on the user's instruction to modify the cutoff strategy. In yet other embodiments, the processing device 110 can update the screening model stored in the storage device 120 based on the user's instruction and obtain the evaluation result using the updated screening model. Wherein, the processing device 110 can collect the methylation level related information of the associated DNA methylation site combination of the bladder cancer population and the normal population from the public or non-public database through the network 130 in real time or periodically, for the training sample set in the storage device 120, and optimize the methylation threshold of the DNA methylation site using the updated training sample set.

[0106] It should be noted that the above description of the flow 500 is only for example and illustration, and does not limit the scope of the present specification. Those skilled in the art can make various modifications and changes to the flow 500 under the guidance of the present specification. However, these modifications and changes are still within the scope of the present specification.

[0107] According to yet another aspect of the present specification, a device for bladder cancer screening, bladder cancer prevalence risk prediction, bladder cancer treatment effect evaluation and / or bladder cancer treatment drug screening is provided. The device can include a memory, a processor, and a computer program stored on the memory and executable on the processor, and the processor implements the method for bladder cancer screening, bladder cancer prevalence risk prediction, bladder cancer treatment effect evaluation and / or bladder cancer treatment drug screening shown in some embodiments of the present specification when executing the program.

[0108] More details about the method for bladder cancer screening, bladder cancer prevalence risk prediction, bladder cancer treatment effect evaluation and / or bladder cancer treatment drug screening can be found elsewhere in the present specification (e.g., in the description of Figure 4 , Figure 5 and the description thereof).

[0109] According to yet another aspect of the present specification, a detection reagent for a DNA methylation site combination is provided. The DNA methylation site combination can be used as a biomarker for detecting bladder cancer, including one or more of EOMES_70, TWIST1_62, NKX2-6_35, VIM_95, HIST1H4F_53, NRN1_54, PENK-1_51, PENK-2_85, PXDN_37 and IRF4_50.

[0110] In some embodiments, the detection reagent for the DNA methylation site combination includes a primer set for amplifying the DNA methylation site combination. The primer set for amplifying the DNA methylation site combination is used to obtain specific amplification fragments containing the DNA methylation site combination, and amplify the detection information.

[0111] In some embodiments, the primer set for amplifying the combination of DNA methylation sites comprises primer pairs for amplifying one or more of EOMES_70, TWIST1_62, NKX2-6_35, VIM_95, HIST1H4F_53, NRN1_54, PENK-1_51, PENK-2_85, PXDN_37, and IRF4_50. Optionally, the primer pair for amplifying EOMES_70 is set forth in SEQ ID NO: 1 and SEQ ID NO: 2, or the primer sequences of the primer pair have at least 95%, 96%, 97%, 98%, or 99% identity to the sequences set forth in SEQ ID NO: 1 and SEQ ID NO: 2, respectively. Optionally, the primer pair for amplifying TWIST1_62 is set forth in SEQ ID NO: 3 and SEQ ID NO: 4, or the primer sequences of the primer pair have at least 95%, 96%, 97%, 98%, or 99% identity to the sequences set forth in SEQ ID NO: 3 and SEQ ID NO: 4, respectively. Optionally, the primer pair for amplifying NKX2-6_35 is set forth in SEQ ID NO: 5 and SEQ ID NO: 6, or the primer sequences of the primer pair have at least 95%, 96%, 97%, 98%, or 99% identity to the sequences set forth in SEQ ID NO: 5 and SEQ ID NO: 6, respectively. Optionally, the primer pair for amplifying VIM_95 is set forth in SEQ ID NO: 7 and SEQ ID NO: 8, or the primer sequences of the primer pair have at least 95%, 96%, 97%, 98%, or 99% identity to the sequences set forth in SEQ ID NO: 7 and SEQ ID NO: 8, respectively. Optionally, the primer pair for amplifying HIST1H4F_53 is set forth in SEQ ID NO: 9 and SEQ ID NO: 10, or the primer sequences of the primer pair have at least 95%, 96%, 97%, 98%, or 99% identity to the sequences set forth in SEQ ID NO: 9 and SEQ ID NO: 10, respectively. Optionally, the primer pair for amplifying NRN1_54 is set forth in SEQ ID NO: 11 and SEQ ID NO: 12, or the primer sequences of the primer pair have at least 95%, 96%, 97%, 98%, or 99% identity to the sequences set forth in SEQ ID NO: 11 and SEQ ID NO: 12, respectively. Optionally, the primer pair for amplifying PENK-1_51 is set forth in SEQ ID NO: 13 and SEQ ID NO: 14, or the primer sequences of the primer pair have at least 95%, 96%, 97%, 98%, or 99% identity to the sequences set forth in SEQ ID NO: 13 and SEQ ID NO: 14, respectively.Alternatively, the primer pair for amplifying PENK-2_85 is shown as SEQ ID NO: 15 and SEQ ID NO: 16, or the primer sequences of the primer pair have at least 95%, 96%, 97%, 98%, or 99% similarity to the sequences shown in SEQ ID NO: 15 and SEQ ID NO: 16, respectively. Alternatively, the primer pair for amplifying PXDN_37 is shown as SEQ ID NO: 17 and SEQ ID NO: 18, or the primer sequences of the primer pair have at least 95%, 96%, 97%, 98%, or 99% similarity to the sequences shown in SEQ ID NO: 17 and SEQ ID NO: 18, respectively. Alternatively, the primer pair for amplifying IRF4_50 is shown as SEQ ID NO: 19 and SEQ ID NO: 20, or the primer sequences of the primer pair have at least 95%, 96%, 97%, 98%, or 99% similarity to the sequences shown in SEQ ID NO: 19 and SEQ ID NO: 20, respectively.

[0112] In some embodiments, the detection reagents of the DNA methylation site combination can further comprise other reagents for detecting the methylation level, such as methylation conversion reagents and / or sequencing reagents. As an example, the detection methods of the methylation level can include, but are not limited to, WGBS, RRBS, oxBS-seq, MethylCap-seq, MBD-seq, MeDIP-seq, HPLC, MSRF, MASP, methylation chip method, pyrosequencing method, dPCR, MS-PCR, etc., or a combination thereof. In some preferred embodiments, the other reagents can include reagents used to implement one or more of WGBS, RRBS, oxBS-seq, MethylCap-seq, MBD-seq, MeDIP-seq, HPLC, MSRF, MASP, methylation chip method, pyrosequencing method, dPCR, and MS-PCR. In some more preferred embodiments, the other reagents can include reagents used to implement WG BS or RRBS.

[0113] According to yet another aspect of the present specification, a kit for bladder cancer screening, bladder cancer prevalence risk prediction, evaluation of bladder cancer treatment effect, and / or screening of bladder cancer treatment drugs is provided. The kit comprises the detection reagents of the DNA methylation site combination shown in some embodiments of the present specification.

[0114] According to another aspect of the present specification, there is provided a use of a combination of DNA methylation sites as biomarkers or a detection reagent of the combination of DNA methylation sites in the preparation of a kit for bladder cancer screening, bladder cancer prevalence prediction, evaluation of bladder cancer treatment effect, and / or screening of bladder cancer treatment drugs. The combination of DNA methylation sites is the combination of DNA methylation sites shown in some embodiments of the present specification.

[0115] The experimental methods in the following examples are all conventional methods unless otherwise specified. The experimental materials used in the following examples are all purchased from conventional biochemical reagent companies unless otherwise specified. In the quantitative experiments in the following examples, three repeated experiments were set up, and the average value was taken as the result.

[0116] Examples

[0117] Methods and procedures

[0118] Collection of urine sample group for DNA methylation detection analysis

[0119] Morning urine samples of 76 bladder urothelial carcinoma patients (27 patients in stage I, 37 patients in stage II, 8 patients in stage III, and 4 patients in stage IV, among which 6 patients were non-muscular invasive urothelial carcinoma patients and 30 patients were muscular invasive urothelial carcinoma patients), 30 healthy normal persons, 1 bladder benign tumor, and 49 patients with other diseases (49 samples as interference samples) were collected as experimental samples, and 2 human bladder cancer cell lines HT-1197 were used as positive control samples, and 2 sterile water were used as negative control samples. The samples were stored in 50 mL urine DNA storage tubes containing 7.5 mL of additives. After sample collection, centrifugation was performed at 4000 rpm for 10 min, the supernatant was discarded, and the precipitate was washed with 1xPBS.

[0120] Statistics of specific methylation sites

[0121] A total of 141 methylation sites of known and / or potential bladder cancer related genes were statistically analyzed, and the specific information is shown in Table 1.

[0122] Table 1 Methylation site information table

[0123]

[0124]

[0125]

[0126] DNA extraction of urine sample group

[0127] The DNA of the urine sample group was extracted, 100 μL Buffer GTL was added to the above-mentioned precipitate, and the precipitate was resuspended; 20 μL protease K was added, and vortexed to mix. Incubation was carried out at 56°C for half an hour until the sample was completely dissolved, and then incubation was continued at 90°C for 1 hour. Short-term centrifugation was carried out to collect the solution on the tube wall to the bottom of the tube. 200 μL Buffer GL was added, and vortexed to mix thoroughly. 200 μL anhydrous ethanol was added, and vortexed to mix thoroughly. Short-term centrifugation was carried out to collect the solution on the tube wall to the bottom of the tube.

[0128] The solution in the tube was added to the centrifuge tube in which the silicon matrix material film was placed, 500 μL Buffer GW1 to which anhydrous ethanol was added was added to the silicon matrix material film, and centrifugation was carried out at 12,000 rpm for 1 minute, the waste liquid in the collection tube was discarded, and the silicon matrix material film was placed back into the collection tube. 500 μL Buffer GW2 to which anhydrous ethanol was added was added to the silicon matrix material film, and centrifugation was carried out at 12,000 rpm for 1 minute, the waste liquid in the collection tube was discarded, and the silicon matrix material film was placed back into the collection tube. Centrifugation was carried out at 12,000 rpm for 2 minutes, the waste liquid in the collection tube was discarded, and the silicon matrix material film was placed at room temperature for several minutes to dry completely.

[0129] The silicon matrix material film was placed into a new centrifuge tube, 50-200 μL Buffer GE was added, and the tube was placed at room temperature for 2-5 minutes, centrifugation was carried out at 12,000 rpm for 1 minute, the DNA solution was collected, and the solution was stored at -20°C for further use. The DNA concentration was determined using a microspectrophotometer Nano-300 and Qubit (the concentration should be no less than 1 ng / μL).

[0130] DNA methylation conversion of the urine sample group

[0131] The urine sample group was subjected to bisulfite treatment: 50 μL urine precipitated DNA sample, 150 μL Bisulfite Mix, and 25 μL MBuffer B-protection solution were added to a PCR tube. After short-term centrifugation, the PCR tube was placed in a PCR instrument, incubation was carried out at 85°C for 60 minutes, and then the tube was cooled to room temperature, and short-term centrifugation was carried out. The urine precipitated DNA was taken from the above-mentioned DNA solution, and the DNA content in 50 μL urine precipitated DNA sample was 20-1000 ng. The preparation of Bisulfite Mix included adding 1.2 mL MBuffer A-conversion solution to a sodium bisulfite-containing dry powder tube, and vortexing to mix until the dry powder was completely dissolved.

[0132] Purification of DNA after sulfite treatment: All the solution in the PCR tube was transferred into a 1.5 mL centrifuge tube; 285 μL of MBuffer C-binding solution, 115 μL of isopropyl alcohol, and 10 μL of magnetic bead suspension (mix well before use) were added into the centrifuge tube, and shaken for 10 min; after short centrifugation, the centrifuge tube was placed on a magnetic stand for 2 min, and the supernatant was discarded; 1000 μL of MBuffer D-washing solution was added into the centrifuge tube, and the magnetic stand was not left; incubation was performed for 30 s, and the supernatant was discarded. 1000 μL of MBuffer E-incubation solution was added into the centrifuge tube, and incubation was performed at room temperature for 15 min; after short centrifugation, the centrifuge tube was placed on a magnetic stand for 2 min, and the supernatant was discarded. 1000 μL of MBuffer D-washing solution was added into the centrifuge tube, and the magnetic stand was not left; incubation was performed for 30 s, and the supernatant was discarded; this step was repeated once. After the excess washing solution in the centrifuge tube was absorbed, the centrifuge tube was placed on a clean bench, and blown dry for 5 min.

[0133] Purification and recovery of DNA from the urine sample group: 50 μL of MBuffer F-elution solution was added into the centrifuge tube, and incubation was performed at 56 °C, which helped to improve the elution efficiency; vortex shaking was performed to mix well, and incubation was performed for 5 min. After short centrifugation, the centrifuge tube was placed on a magnetic stand for 2 min. The supernatant was transferred into a clean new centrifuge tube, and the DNA solution was collected as a DNA transformation sample, which was stored at -20 °C for further use.

[0134] Multiplex PCR-NGS detection

[0135] In the first round of PCR, 160 samples of nucleic acid were subjected to PCR reaction using bladder urothelial carcinoma-specific gene methylation primers (the primer sequences and the physical positions of 141 methylation sites are shown in Table 1). The ACTB internal control gene was set to control the NGS process and the sulfite transformation process. The reaction system included: 10x ACE buffer, 3 μL; dNTP Mix (10 mM), 1 μL; primer mixed primers, 5 μL; TMAC 600 mm, 2.5 μL; 50% glycerol, 6 μL; 5x Enhancer, 2 μL; sterilized water, 5 μL; Ace Taq enzyme, 0.5 μL; DNA transformation sample (i.e., DNA after sulfite treatment), 5 μL.

[0136] The reaction conditions of the first round of PCR were as follows: 1) cycle number 1: 95 °C for 10 min; 2) cycle number 35: 95 °C for 30 s, 48 °C for 30 s, and 72 °C for 30 s; 3) cycle number 1: 72 °C for 5 min.

[0137] The reaction system of the second round of PCR comprises: 10x ACE buffer, 3 μL; dNTP Mix (10 mM), 1 μL; primer AP5 (5 μM), 2 μL; primer Index (5 μM), 2 μL; 50% glycerol, 6 μL; sterilized water, 10.5 μL; AceTaq enzyme, 0.5 μL; first round of PCR reaction product, 5 μL. The sequence of the primer AP5 is AATGATACGGCGACCACCGAGATCTACACTCTTTCCCTACACGACGCTCTTCCGATCT (SEQ ID NO: 21); the sequence of the primer index is CAAGCAGAAGACGGCATACGAGATNNNNNNNNNGTGACTGGAGTTCAGACGTGTGCTCTTCCGATCT (SEQ ID NO: 22). It should be noted that "NNNNNNNN" represents the index index used to distinguish different samples.

[0138] The reaction conditions of the second round of PCR are as follows: 1) cycle number 1: 95 °C for 10 min; 2) cycle number 20: 95 °C for 30 s, 55 °C for 30 s, 72 °C for 30 s; 3) cycle number 1: 72 °C for 5 min.

[0139] After the amplification product is purified by a nucleic acid purification reagent, a sequencing library is obtained, and then a sequencing reagent is used Miniseq TM MidOutput Reagent Cartridge (Illumina) is sequenced on a MiniSeq sequencer (Illumina).

[0140] Calculation of methylation rate of each site

[0141] Statistical analysis of NGS results of 141 sites, each site with a sequencing depth of not less than 500X, the number of reads of base C in a site is set as NumC, and the number of reads of base T in the site is set as NumT, and the ratio NumC / (NumC+NumT) is the methylation rate of the site.

[0142] Establishment of training set and validation set

[0143] The data samples were divided into a training set and a validation interference set for 156 urine samples and 4 control samples, wherein the training set samples included 56 males with an average age of 55.75 years, 6 females with an average age of 62.5 years, 31 bladder cancer subjects with an average age of 69.1 years, 31 non-bladder cancer control subjects with an average age of 43.67 years, 1 negative control, and 1 positive control, totaling 64 samples as the training set. The validation interference set samples included 87 males with an average age of 65.7 years, 7 females with an average age of 66.5 years, 45 bladder cancer subjects with an average age of 71.2 years, 49 non-bladder cancer subjects with an average age of 60.86 years, 1 negative control, and 1 positive control, totaling 96 samples as the validation interference group. The methylation conversion rate of the internal reference gene ACTB in these samples was above 99%, ensuring the normal bisulfite treatment of each site of each gene.

[0144] Example 1, target methylation sites and combinations thereof for bladder cancer prediction in the training sample set and the validation sample set

[0145] The methylation rates of the 141 methylation sites (see Table 1) of the 64 training samples were subjected to test analysis. F test was used to verify whether the methylation level distribution of each site between the bladder cancer positive group (31 bladder cancer subjects + 1 positive control) and the control group (31 non-bladder cancer subjects + 1 negative control) was homogeneous. For the methylation sites with homogeneous distribution, independent sample two-tailed Student's t test was used to verify whether there was a significant difference in the average methylation level between the bladder cancer positive group and the control group. For the methylation sites with non-homogeneous distribution, independent sample two-tailed Student's t' test was used to verify whether there was a significant difference in the average methylation rate between the bladder cancer positive group and the control group. After T test analysis of the 141 methylation sites of the 64 training samples, it was found that there was a significant difference between the 10 sites in the bladder cancer positive group samples and the control group samples, and the 10 methylation sites were EOMES_70, TWIST1_62, NKX2-6_35, VIM_95, HIST1H4F_53, NRN1_54, PENK-1_51, PENK-2_85, PXDN_37, and IRF4_50. The methylation rate distribution of the 10 specific methylation sites in the training set and the validation interference set is shown in Table 2. Figure 6

[0146] Further analysis of the methylation rates of the 10 sites in the 160 samples was performed, and under the condition of priority guaranteeing a specificity of 100% (to avoid misjudging normal people as bladder cancer), all possible combinations of the 10 sites were analyzed to determine the sensitivity of each combination, as shown in Table 3. Figure 7 ​As shown, the abscissa represents 1-10 combinations, and the ordinate represents the sensitivity of identifying 76 bladder urothelial carcinoma (27 patients in stage I, 37 patients in stage II, 8 patients in stage III, and 4 patients in stage IV, of which 6 patients are non-muscular invasive urothelial carcinoma patients and 30 patients are muscular invasive urothelial carcinoma patients) subjects and control subjects, the sensitivity of a single site ranges from 48.72% to 69.23%, two-site combinations have 45 combinations, the sensitivity ranges from 57.69% to 80.77%, three-site combinations have 120 combinations, the sensitivity ranges from 65.38% to 84.62%, four-site combinations have 210 combinations, the sensitivity ranges from 66.66% to 85.89%, five-site combinations have 252 combinations, the sensitivity ranges from 69.23% to 87.17%, six-site combinations have 210 combinations, the sensitivity ranges from 70.51% to 87.17%, seven-site combinations have 120 combinations, the sensitivity ranges from 73.07% to 87.17%, eight-site combinations have 45 combinations, the sensitivity ranges from 75.64% to 87.17%, nine-site combinations have 10 combinations, the sensitivity ranges from 79.49% to 87.17%, and the sensitivity of ten sites is 87.17%. It can be seen that when the combination of 5 sites is used, the maximum sensitivity is 87.17%, and when more sites are added, the maximum sensitivity is 87.17% and no longer increases. At this time, the combination of the 5 sites is EOMES_70, IRF4_50, PENK-1_51, PENK-2_85, and VIM_95, and the judgment thresholds are 0.0822, 0.1863, 0.1181, 0.1195, and 0.0647, respectively. The 4 control samples are consistent with the actual situation. Therefore, the 5 sites used in the specification can ensure the maximum sensitivity at a specificity of 100% in identifying 76 bladder cancer patients. Removing the 4 control samples, the overall sensitivity is 66 / 76 = 86%, in particular, the sensitivity of bladder cancer patients in stage I is 22 / 27 = 81%, the sensitivity of bladder cancer patients in stage II is 32 / 37 = 86%, the sensitivity of bladder cancer patients in stage III is 8 / 8 = 100%, the sensitivity of bladder cancer patients in stage IV is 1 / 4 = 100%, in particular, the sensitivity of non-invasive urothelial carcinoma is 5 / 6 = 83%, and the sensitivity of invasive urothelial carcinoma is 28 / 30 = 93%.

[0147] Comparative Example 1

[0148] As a suboptimal contrast analysis, the methylation rates of 141 methylation sites of the training set of 64 samples (including 56 male samples with an average age of 55.75 years old, 6 female samples with an average age of 62.5 years old, 31 bladder cancer subjects with an average age of 69.1 years old, 31 non-bladder cancer control subjects with an average age of 43.67 years old, 1 negative control sample, and 1 positive control sample, totaling 64) were analyzed, and the sensitivity ranges of each combination were calculated under the condition of ensuring a specificity of 100%, as shown in Table 1. Figure 8 As shown in Table 1, the sensitivity range of a single site is 0-74.19%, the sensitivity range of a two-site combination is 64.51%-87.09%, the sensitivity range of a three-site combination is 80.65%-90.32%, the sensitivity range of a four-site combination is 90.32%-93.55%, the sensitivity range of a five-site combination is 90.32%-93.55%, the sensitivity of a six-site combination, a seven-site combination, an eight-site combination, a nine-site combination, a ten-site combination, an eleven-site combination, and a twelve-site combination is 93.55%.

[0149] Further analysis of the combinations with a maximum sensitivity of 93.55% at a specificity of 100% showed that there were 81 four-site combinations, 5,895 five-site combinations, 5,454 six-site combinations, 4,554 seven-site combinations, 3,879 eight-site combinations, 3,366 nine-site combinations, 2,144 ten-site combinations, 1,304 eleven-site combinations, and 456 twelve-site combinations.

[0150] Next, the sensitivity and specificity of the combination with the specificity of 100% and the maximum sensitivity of 93.55% in the training set were analyzed randomly. The random four-site combination (EOMES_82, NRN1_54, PXDN_74, IRF4_87) with the thresholds of 0.087, 0.104, 0.058, and 0.115, respectively, had a sensitivity of 43 / 46 = 93% and a specificity of 23 / 50 = 46% in the validation interference set. The random ten-site combination (EOMES_82, HIST1H4F_41, IRF4_87, NKX2-6_70, NRN1_54, PENK-1_98, PENK-2_85, PXDN_46, TWIST1_48, VIM_81) with the thresholds of 0.087, 0.221, 0.115, 0.159, 0.104, 0.475, 0.087, 0.045, 0.301, and 0.042, respectively, had a sensitivity of 43 / 46 = 93% and a specificity of 21 / 50 = 42% in the validation interference set. The random twelve-site combination (ACOT11_90, EOMES_82, HIST1H4F_50, IRF4_87, NKX2-6_70, NPY-2_50, NRN1_54, PENK-1_98, PENK-2_46, PXDN_46, TWIST1_78, VIM_31) with the thresholds of 0.636, 0.087, 0.208, 0.115, 0.159, 0.193, 0.104, 0.475, 0.183, 0.045, 0.136, and 0.052, respectively, had a sensitivity of 44 / 46 = 95% and a specificity of 20 / 50 = 40% in the validation interference set. The sensitivity and specificity of the remaining combinations with the specificity of 100% and the maximum sensitivity of 93.55% in the validation interference set are not described herein, and the results showed that the sensitivity and specificity were about 95% and about 40%, respectively.

[0151] As can be seen from Example 1 and Comparative Example 1, the five-site combination (EOMES_70, IRF4_50, PENK-1_51, PENK-2_85, VIM_95) with the thresholds of 0.0822, 0.1863, 0.1181, 0.1195, and 0.0647, respectively, in Example 1 can more accurately identify bladder cancer patients in the training set and the validation interference set.

[0152] Some embodiments of the present specification, based on the methylation level of DNA methylation site combination, use screening model to evaluate whether the subject has bladder cancer, predict the risk of the subject developing bladder cancer, evaluate the effect of the subject treating bladder cancer and / or evaluate the effect of bladder cancer treatment drug, which can realize accurate, rapid and non-invasive clinical screening of bladder cancer (especially early bladder cancer).

[0153] Having described the basic concepts, it is obvious that the above detailed disclosure is only as an example, and does not constitute a limitation of the present specification. Although it is not explicitly stated here, those skilled in the art can make various modifications, improvements and corrections to the present specification. Such modifications, improvements and corrections are suggested in the present specification, so such modifications, improvements and corrections still belong to the spirit and scope of the exemplary embodiments of the present specification.

[0154] At the same time, the present specification uses specific words to describe the embodiments of the present specification. As "one embodiment", "an embodiment", and / or "some embodiments" means a certain feature, structure or characteristic related to at least one embodiment of the present specification. Therefore, it should be emphasized and noted that the "an embodiment" or "one embodiment" or "one alternative embodiment" mentioned in different places in the present specification does not necessarily refer to the same embodiment. In addition, some features, structures or characteristics in one or more embodiments of the present specification can be properly combined.

[0155] Some embodiments use numbers to describe components, attribute quantities. It should be understood that such numbers used in the description of the embodiments are, in some examples, modified by the adjectives "about", "approximately" or "generally". Unless otherwise stated, "about", "approximately" or "generally" indicates that the stated number allows for a ±20% variation. Accordingly, in some embodiments, the numerical parameters used in the specification and claims are approximations that can vary depending on the desired characteristics of the individual embodiments. In some embodiments, numerical parameters should be considered in the context of the number of significant digits and by applying ordinary rounding off methods. Although the numerical ranges and parameters in some embodiments of the present specification are approximations, in specific embodiments, the numerical values set forth in such ranges and parameters are intended to be as precise as possible.

[0156] Each patent, patent application, patent publication, and other material cited in this specification is hereby incorporated by reference in its entirety herein for the teachings relevant to the sentence and / or paragraph in which the reference is presented. Document histories, to the extent not inconsistent with the pertinent U.S. patent application file history, are also incorporated by reference herein. To the extent that material incorporated by reference contradicts or contradicts any portion of this specification, including definition, the portion of the material incorporated by reference prevails. Note, however, that in the event of inconsistencies between any such material and the present specification, including definitions, the present specification, including definitions, will control.

[0157] Finally, it should be understood that the embodiments described herein are merely exemplary of the principles of the present description. Other embodiments can be devised without departing from the scope of the present description. Accordingly, the embodiments described herein are not intended to limit the scope of the present description, but rather are intended to be exemplary thereof.

Claims

1. Use of a combination of DNA methylation sites as biomarker or detection reagents for a combination of DNA methylation sites for the manufacture of a kit for the screening of bladder cancer and / or the prediction of the risk of suffering bladder cancer, characterized in that, The DNA methylation site combination comprises a combination consisting of the following sites located on the human reference genome hg19: a site EOMES_70 located on the EOMES gene at the chromosome coordinate of chr3: 27765376; a site VIM_95 located on the VIM gene at the chromosome coordinate of chr10: 17271456; a site PENK-1_51 located on the PENK-1 gene at the chromosome coordinate of chr8: 57358707; a site PENK-2_85 located on the PENK-2 gene at the chromosome coordinate of chr8: 57358407; and a site IRF4_50 located on the IRF4 gene at the chromosome coordinate of chr6: 392057. The detection reagent comprises a primer set for amplifying the DNA methylation site combination; wherein, the primer pair for amplifying EOMES_70 is shown as SEQ ID NO: 1 and SEQ ID NO: 2; the primer pair for amplifying VIM_95 is shown as SEQ ID NO: 7 and SEQ ID NO: 8; the primer pair for amplifying PENK-1_51 is shown as SEQ ID NO: 13 and SEQ ID NO: 14; the primer pair for amplifying PENK-2_85 is shown as SEQ ID NO: 15 and SEQ ID NO: 16; and the primer pair for amplifying IRF4_50 is shown as SEQ ID NO: 19 and SEQ ID NO:

20. The processor implements the following method when executing the program:

2. A device for bladder cancer screening and / or prediction of risk of suffering from bladder cancer, said device comprising a memory, a processor and a computer program stored on said memory and executable on said processor, characterized in that, obtaining the methylation level of a DNA methylation site combination in a biological sample of a subject, wherein the DNA methylation site combination comprises a combination consisting of the following sites located on the human reference genome hg19: a site EOMES_70 located on the EOMES gene at the chromosome coordinate of chr3: 27765376; a site VIM_95 located on the VIM gene at the chromosome coordinate of chr10: 17271456; a site PENK-1_51 located on the PENK-1 gene at the chromosome coordinate of chr8: 57358707; a site PENK-2_85 located on the PENK-2 gene at the chromosome coordinate of chr8: 57358407; and a site IRF4_50 located on the IRF4 gene at the chromosome coordinate of chr6: 392057. based on the methylation level of the DNA methylation site combination, using a screening model to assess whether the subject has bladder cancer and / or predict the risk of the subject developing bladder cancer. The detection reagent comprises a primer set for amplifying the DNA methylation site combination, which comprises a combination consisting of the following sites located on the human reference genome hg19:

3. A DNA methylation site panel as a biomarker for bladder cancer screening and / or prediction of bladder cancer prevalence, characterized in that, a site EOMES_70 located on the EOMES gene at the chromosome coordinate of chr3: 27765376; ​ a site, VIM_95, located on the VIM gene at chromosome coordinate chrlO: 17271456; a site, PENK-l_51, located on the PENK-l gene at chromosome coordinate chr8: 57358707; a site, PENK-2_85, located on the PENK-2 gene at chromosome coordinate chr8: 57358407; and a site, IRF4_50, located on the IRF4 gene at chromosome coordinate chr6: 392057. a primer pair for amplifying EOMES_70 is shown as SEQ ID NO: 1 and SEQ ID NO: 2; a primer pair for amplifying VIM_95 is shown as SEQ ID NO: 7 and SEQ ID NO: 8; a primer pair for amplifying PENK-l_51 is shown as SEQ ID NO: 13 and SEQ ID NO: 14; a primer pair for amplifying PENK-2_85 is shown as SEQ ID NO: 15 and SEQ ID NO: 16; and a primer pair for amplifying IRF4_50 is shown as SEQ ID NO: 19 and SEQ ID NO:

20. The detection reagent also comprises other reagents for detecting the methylation level of the combination of DNA methylation sites; the other reagents comprise reagents used in one or more of the following methods:

4. The detection reagent of claim 3, wherein whole genome bisulfite sequencing, reduced representation bisulfite sequencing, oxidative-bisulfite sequencing, methylated DNA capture sequencing, methyl binding protein sequencing, methylated DNA immunoprecipitation sequencing, high performance liquid chromatography, methylation sensitive restriction fingerprinting, methylation sensitive amplification polymorphism, methylation microarray, pyrosequencing, digital PCR, and methylation specific PCR.

5. A kit for bladder cancer screening and / or bladder cancer risk prediction, the kit comprising the detection reagent of any one of claims 3-4. ​

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