Urine exosome-based bladder cancer gene detection system and application

Abstract

The application provides a urine exosome-based bladder cancer gene detection system and application, and relates to the technical field of biological detection. Through the cooperative application of the internal reference gene and the diagnosis model, the application provides a reliable endogenous quality control standard for the bladder tissue-derived exosome in the urine exosome sample; meanwhile, the application realizes non-invasive, accurate, rapid screening, diagnosis, prognosis and recurrence monitoring of bladder cancer, lays a key technical foundation and detection tool for the urine exosome-based molecular diagnosis of bladder cancer, and has important clinical transformation value and application prospect.

Description

Technical Field

[0001] This invention relates to the field of biological detection technology, and in particular to a bladder cancer gene detection system and its application based on urinary exosomes. Background Technology

[0002] Bladder cancer (BC) is one of the most common malignant tumors of the urinary tract. It can be classified into non-muscle-invasive bladder cancer (NMIBC) and muscle-invasive bladder cancer (MIBC). NMIBC accounts for approximately 75% of all bladder cancers, with a high recurrence rate of 60%-70%. If detected early before muscle invasion, BC is usually curable and has minimal impact on survival. However, once it progresses to MIBC, it can metastasize to lymph nodes, bones, lungs, and liver, with a 5-year overall survival of only 15%-63%. Therefore, accurate early diagnosis and continuous recurrence monitoring are effective means to improve the poor prognosis of BC. Cystoscopy is currently the gold standard for diagnosing and monitoring BC, with high diagnostic accuracy. However, it is invasive, difficult for some patients to tolerate, and the accuracy of the results largely depends on the operator's experience and skill, and can potentially cause complications. Therefore, developing a non-invasive, convenient, and accurate method for early diagnosis and recurrence monitoring of bladder cancer is of significant clinical importance.

[0003] Urinary exosomes are nanoscale vesicle structures secreted by cells, widely distributed in urine and other biological fluids. Their surface and interior carry various biomolecules derived from parental cells, including nucleic acids and proteins. Among these, long-chain RNAs (lncRNAs and mRNAs) exhibit high stability, abundance, and non-invasive acquisition in urinary exosomes, making them ideal for early diagnosis and recurrence risk assessment of bladder cancer. Currently, using molecular markers from urinary exosomes for liquid biopsy of bladder cancer has become a research hotspot. However, existing studies often directly use traditional housekeeping genes such as GAPDH and β-actin as internal controls for data normalization. These genes show significant fluctuations in expression levels between urinary exosomes from bladder cancer patients and healthy individuals, lack bladder tissue specificity, and cannot effectively correct for background interference from non-bladder-derived exosomes, severely impacting the reliability of marker diagnosis. Furthermore, the diagnostic efficacy of a single marker is limited, failing to meet the precise clinical needs for bladder cancer diagnosis and recurrence risk assessment.

[0004] Therefore, this invention is proposed. Summary of the Invention

[0005] To address the aforementioned technical challenges, this invention provides a bladder cancer gene detection system and its application based on urinary exosomes. Through the synergistic application of internal reference genes and diagnostic models, this invention provides a reliable endogenous quality control standard for bladder-derived components in urinary exosome samples. Simultaneously, it enables non-invasive, accurate, and rapid diagnosis and recurrence monitoring of bladder cancer, laying a crucial technological foundation for molecular diagnosis of bladder cancer based on urinary exosomes. It has significant clinical translational value and promising prospects for widespread application.

[0006] In order to achieve the objective of this invention, the following technical solution is adopted: This invention provides a bladder cancer gene detection system based on urinary exosomes, the system comprising: a detection reagent for the expression level of a bladder tissue-specific internal reference gene in urinary exosomes; and a detection reagent for specifically detecting the expression level of a target gene; The internal reference gene includes: UPK1A; The target genes include at least CTSK, NEK2, CENPA, and CERS2.

[0007] Furthermore, the detection reagent for specifically detecting the expression level of the bladder tissue-specific internal reference gene UPK1A in urinary exosomes includes: PCR primers and TaqMAN probes; The PCR primers and TaqMAN probes are selected from any of the following combinations: (a) A primer pair having nucleotide sequences as shown in SEQ ID NO.1 and SEQ ID NO.2, and a TaqMAN probe having a nucleotide sequence as shown in SEQ ID NO.3; (b) A primer pair having nucleotide sequences as shown in SEQ ID NO.4 and SEQ ID NO.5, and a TaqMAN probe having a nucleotide sequence as shown in SEQ ID NO.6; (c) A primer pair having nucleotide sequences as shown in SEQ ID NO.7 and SEQ ID NO.8, and a TaqMAN probe having nucleotide sequences as shown in SEQ ID NO.9.

[0008] Furthermore, the internal reference gene can also be selected from any one of UPK1B, UPK2, or UPK3A; The target genes may also include any one or more of ZNF492, HBA2, IFNGR2, LCN2, C3orf70, RPS17, CCNA2, or SLC29A3.

[0009] Furthermore, the detection reagent for specifically detecting the expression level of the bladder tissue-specific internal reference gene UPK1B in urinary exosomes includes: PCR primers and TaqMAN probes; The PCR primers and TaqMAN probes are selected from any of the following combinations: (a) A primer pair having nucleotide sequences as shown in SEQ ID NO.10 and SEQ ID NO.11, and a TaqMAN probe having a nucleotide sequence as shown in SEQ ID NO.12; (b) A primer pair with nucleotide sequences as shown in SEQ ID NO.13 and SEQ ID NO.14, and a TaqMAN probe with a nucleotide sequence as shown in SEQ ID NO.15; (c) A primer pair having nucleotide sequences as shown in SEQ ID NO.16 and SEQ ID NO.17, and a TaqMAN probe having nucleotide sequences as shown in SEQ ID NO.18.

[0010] Furthermore, the detection reagent for specifically detecting the expression level of the bladder tissue-specific internal reference gene UPK2 in urinary exosomes includes: PCR primers and TaqMAN probes; The PCR primers and TaqMAN probes are selected from any of the following combinations: (a) A primer pair having nucleotide sequences as shown in SEQ ID NO.19 and SEQ ID NO.20, and a TaqMAN probe having a nucleotide sequence as shown in SEQ ID NO.21; (b) A primer pair with nucleotide sequences as shown in SEQ ID NO.22 and SEQ ID NO.23, and a TaqMAN probe with a nucleotide sequence as shown in SEQ ID NO.24; (c) A primer pair having nucleotide sequences as shown in SEQ ID NO.25 and SEQ ID NO.26, and a TaqMAN probe having nucleotide sequences as shown in SEQ ID NO.27.

[0011] Furthermore, the detection reagent for specifically detecting the expression level of the bladder tissue-specific internal reference gene UPK3A in urinary exosomes includes: PCR primers and TaqMAN probe; The PCR primers and TaqMAN probes are selected from any of the following combinations: (a) A primer pair having nucleotide sequences as shown in SEQ ID NO.28 and SEQ ID NO.29, and a TaqMAN probe having a nucleotide sequence as shown in SEQ ID NO.30; (b) A primer pair with nucleotide sequences as shown in SEQ ID NO.31 and SEQ ID NO.32, and a TaqMAN probe with a nucleotide sequence as shown in SEQ ID NO.33; (c) A primer pair having nucleotide sequences as shown in SEQ ID NO.34 and SEQ ID NO.35, and a TaqMAN probe having a nucleotide sequence as shown in SEQ ID NO.36.

[0012] Furthermore, the detection reagent for specifically detecting the expression level of the target gene includes: primer pairs and TaqMAN probes targeting the target gene; The primer pair for the target gene CTSK and the TaqMAN probe are selected from any of the following combinations: (1) Primer pairs with nucleotide sequences as shown in SEQ ID NO.37 and SEQ ID NO.38, and TaqMAN probes with nucleotide sequences as shown in SEQ ID NO.39; (2) Primer pairs with nucleotide sequences as shown in SEQ ID NO.40 and SEQ ID NO.41, and TaqMAN probes with nucleotide sequences as shown in SEQ ID NO.42; (3) Primer pairs with nucleotide sequences as shown in SEQ ID NO.43 and SEQ ID NO.44, and TaqMAN probes with nucleotide sequences as shown in SEQ ID NO.45; The primer pair and TaqMAN probe for the target gene NEK2 are selected from any of the following combinations: (1) A primer pair with nucleotide sequences as shown in SEQ ID NO.46 and SEQ ID NO.47, and a TaqMAN probe with nucleotide sequences as shown in SEQ ID NO.48; (2) A primer pair with nucleotide sequences as shown in SEQ ID NO.49 and SEQ ID NO.50, and a TaqMAN probe with a nucleotide sequence as shown in SEQ ID NO.51; (3) Primer pairs with nucleotide sequences as shown in SEQ ID NO.52 and SEQ ID NO.53, and TaqMAN probes with nucleotide sequences as shown in SEQ ID NO.54; The primer pair and TaqMAN probe for the target gene CENPA are selected from any of the following combinations: (1) A primer pair with nucleotide sequences as shown in SEQ ID NO.55 and SEQ ID NO.56, and a TaqMAN probe with nucleotide sequences as shown in SEQ ID NO.57; (2) Primer pairs with nucleotide sequences as shown in SEQ ID NO.58 and SEQ ID NO.59, and TaqMAN probes with nucleotide sequences as shown in SEQ ID NO.60; (3) Primer pairs with nucleotide sequences as shown in SEQ ID NO.61 and SEQ ID NO.62, and TaqMAN probes with nucleotide sequences as shown in SEQ ID NO.63; The primer pair and TaqMAN probe for the target gene CERS2 are selected from any of the following combinations: (1) Primer pairs with nucleotide sequences as shown in SEQ ID NO.64 and SEQ ID NO.65, and TaqMAN probes with nucleotide sequences as shown in SEQ ID NO.66; (2) Primer pairs with nucleotide sequences as shown in SEQ ID NO.67 and SEQ ID NO.68, and TaqMAN probes with nucleotide sequences as shown in SEQ ID NO.69; (3) Primer pairs with nucleotide sequences as shown in SEQ ID NO.70 and SEQ ID NO.71, and TaqMAN probe with nucleotide sequences as shown in SEQ ID NO.72.

[0013] Furthermore, the primer pair and TaqMAN probe for the target gene ZNF492 are selected from any of the following combinations: (1) Primer pairs with nucleotide sequences as shown in SEQ ID NO.73 and SEQ ID NO.74, and TaqMAN probe with nucleotide sequences as shown in SEQ ID NO.75; (2) Primer pairs with nucleotide sequences as shown in SEQ ID NO.76 and SEQ ID NO.77, and TaqMAN probes with nucleotide sequences as shown in SEQ ID NO.78; (3) Primer pairs with nucleotide sequences as shown in SEQ ID NO.79 and SEQ ID NO.80, and TaqMAN probes with nucleotide sequences as shown in SEQ ID NO.81; The primer pair and TaqMAN probe for the target gene IFNGR2 are selected from any of the following combinations: (1) Primer pairs with nucleotide sequences as shown in SEQ ID NO.82 and SEQ ID NO.83, and TaqMAN probes with nucleotide sequences as shown in SEQ ID NO.84; (2) Primer pairs with nucleotide sequences as shown in SEQ ID NO.85 and SEQ ID NO.86, and TaqMAN probes with nucleotide sequences as shown in SEQ ID NO.87; (3) Primer pairs with nucleotide sequences as shown in SEQ ID NO.88 and SEQ ID NO.89, and TaqMAN probes with nucleotide sequences as shown in SEQ ID NO.90; The primer pair and TaqMAN probe for the target gene HBA2 are selected from any of the following combinations: (1) Primer pairs with nucleotide sequences as shown in SEQ ID NO.91 and SEQ ID NO.92, and TaqMAN probes with nucleotide sequences as shown in SEQ ID NO.93; (2) Primer pairs with nucleotide sequences as shown in SEQ ID NO.94 and SEQ ID NO.95, and TaqMAN probes with nucleotide sequences as shown in SEQ ID NO.96; (3) Primer pairs with nucleotide sequences as shown in SEQ ID NO.97 and SEQ ID NO.98, and TaqMAN probes with nucleotide sequences as shown in SEQ ID NO.99; The primer pair and TaqMAN probe for the target gene LCN2 are selected from any of the following combinations: (1) A primer pair with nucleotide sequences as shown in SEQ ID NO.100 and SEQ ID NO.101, and a TaqMAN probe with nucleotide sequences as shown in SEQ ID NO.102; (2) Primer pairs with nucleotide sequences as shown in SEQ ID NO.103 and SEQ ID NO.104, and TaqMAN probes with nucleotide sequences as shown in SEQ ID NO.105; (3) Primer pairs with nucleotide sequences as shown in SEQ ID NO.106 and SEQ ID NO.107, and TaqMAN probes with nucleotide sequences as shown in SEQ ID NO.108; The primer pair and TaqMAN probe for the target gene C3orf70 are selected from any of the following combinations: (1) A primer pair with nucleotide sequences as shown in SEQ ID NO.109 and SEQ ID NO.110, and a TaqMAN probe with a nucleotide sequence as shown in SEQ ID NO.111; (2) Primer pairs with nucleotide sequences as shown in SEQ ID NO.112 and SEQ ID NO.113, and TaqMAN probes with nucleotide sequences as shown in SEQ ID NO.114; (3) Primer pairs with nucleotide sequences as shown in SEQ ID NO.115 and SEQ ID NO.116, and TaqMAN probes with nucleotide sequences as shown in SEQ ID NO.117; The primer pair and TaqMAN probe for the target gene RPS17 are selected from any of the following combinations: (1) Primer pairs with nucleotide sequences as shown in SEQ ID NO.118 and SEQ ID NO.119, and TaqMAN probes with nucleotide sequences as shown in SEQ ID NO.120; (2) Primer pairs with nucleotide sequences as shown in SEQ ID NO.121 and SEQ ID NO.122, and TaqMAN probes with nucleotide sequences as shown in SEQ ID NO.123; (3) Primer pairs with nucleotide sequences as shown in SEQ ID NO.124 and SEQ ID NO.125, and TaqMAN probes with nucleotide sequences as shown in SEQ ID NO.126; The primer pair and TaqMAN probe for the target gene CCNA2 are selected from any of the following combinations: (1) A primer pair with nucleotide sequences as shown in SEQ ID NO.127 and SEQ ID NO.128, and a TaqMAN probe with nucleotide sequences as shown in SEQ ID NO.129; (2) Primer pairs with nucleotide sequences as shown in SEQ ID NO.130 and SEQ ID NO.131, and TaqMAN probes with nucleotide sequences as shown in SEQ ID NO.132; (3) Primer pairs with nucleotide sequences as shown in SEQ ID NO.133 and SEQ ID NO.134, and TaqMAN probes with nucleotide sequences as shown in SEQ ID NO.135; The primer pair and TaqMAN probe for the target gene SLC29A3 are selected from any of the following combinations: (1) Primer pairs with nucleotide sequences as shown in SEQ ID NO.136 and SEQ ID NO.137, and TaqMAN probes with nucleotide sequences as shown in SEQ ID NO.138; (2) Primer pairs with nucleotide sequences as shown in SEQ ID NO.139 and SEQ ID NO.140, and TaqMAN probes with nucleotide sequences as shown in SEQ ID NO.141; (3) Primer pairs with nucleotide sequences as shown in SEQ ID NO.142 and SEQ ID NO.143, and TaqMAN probes with nucleotide sequences as shown in SEQ ID NO.144.

[0014] Furthermore, the target genes may also include any one or more of the following: ANKRD11, BAZ2A, BCL2, CSF2RB, DAPK2, DNM2, EPHA3, ESM1, KANK2, KCTD1, KIFC1, LCP2, MEF2C, MFAP4, NCOA6, PEG10, RAD51, RWDD2A, SGMS2, ​​SLC22A7, SLC35B4, SYNPO2, TCF21, TMEM17, or TUBGCP4.

[0015] The present invention also provides a risk assessment model using the above-mentioned bladder cancer gene detection system based on urinary exosomes. The assessment model is defined by the following formula: DEUCE score = 1 / (1+exp(-(0.6610+0.2868×CTSK score+0.5696×NEK2 score+1.2581×CENPA score+0.6248×CERS2 score))); Among them, CTSK score, NEK2 score, CENPA score and CERS2 score are the expression levels of the corresponding target genes, which are normalized by the internal reference gene UPK1A and are denoted as target gene scores. The target gene score is calculated as log10[(target gene copy number + 1) / internal reference gene copy number].

[0016] Furthermore, the output threshold for the DEUCE score is 0.20 or 0.25.

[0017] A product for bladder cancer screening, diagnosis, prognosis, and / or recurrence risk assessment, said product comprising: Detection module: Includes the above-mentioned gene detection system; Calculation module: contains the risk assessment model mentioned above; Evaluation module: Used to compare the actual detection results with two preset output thresholds for the DEUCE score.

[0018] Furthermore, the aforementioned bladder cancer gene testing system, risk assessment model, or product used for bladder cancer screening, diagnosis, prognosis, and / or recurrence risk assessment may be applied to assess the proportion of bladder-derived exosomes in urine samples.

[0019] The present invention has the following technical effects: This invention screened and validated a bladder tissue-specific internal reference gene stably expressed in urinary exosomes. This gene not only exhibits highly consistent expression in urinary exosomes from bladder cancer patients and normal controls, but is also unaffected by gender, sampling time, initial urine, or midstream urine, overcoming the shortcomings of traditional housekeeping genes that lack tissue specificity and have unstable expression. Furthermore, due to its tissue specificity, it can accurately reflect the true proportion of bladder-derived exosomes in urine samples, providing a quality control standard for bladder-derived urinary exosomes. It also effectively normalizes data between samples, significantly reducing interference from non-target signals, providing a reliable internal reference basis for molecular diagnosis of bladder cancer based on urinary exosomes. Building upon this, this invention further screened a combination of differentially expressed long-chain RNA biomarkers in urinary exosomes of bladder cancer patients through bioinformatics analysis and RT-qPCR validation, and constructed a bladder cancer recurrence risk assessment model using machine learning algorithms. This provides a non-invasive, precise, and dynamically monitorable technical means for the diagnosis of bladder cancer and postoperative recurrence risk assessment, and is expected to significantly improve patient prognosis and quality of life, while reducing the medical burden.

[0020] By synergistically applying internal reference genes and diagnostic models, this invention provides a reliable endogenous quality control standard for bladder-derived components in urinary exosome samples. At the same time, it enables non-invasive, accurate, and rapid diagnosis and recurrence monitoring of bladder cancer, laying a key technological foundation for molecular diagnosis of bladder cancer based on urinary exosomes. It has significant clinical translational value and promising prospects for widespread application. Attached Figure Description

[0021] To more clearly illustrate the specific embodiments of the present invention or the technical solutions in the prior art, the drawings used in the description of the specific embodiments or the prior art will be briefly introduced below. Obviously, the drawings described below are some embodiments of the present invention. For those skilled in the art, other drawings can be obtained from these drawings without creative effort.

[0022] Figure 1 Urine samples were collected from healthy men and women, male bladder cancer patients and healthy men, and pre- and midstream urine samples from healthy men. Urine exosomes were extracted and the number of exosome particles in different urine samples was detected. Figure 2 The ratio of candidate gene copy number to corresponding urinary exosome particle number was calculated to compare the differences in the ratio between healthy men and healthy women. Figure 3 The ratio of candidate gene copy number to corresponding urinary exosome particle number was calculated to compare the differences in the ratio between male bladder cancer patients and healthy men. Figure 4 The ratio of candidate gene copy number to corresponding urinary exosome particle number was calculated to compare the differences in the ratio of candidate gene to particle number in the anterior and middle segments of healthy males. Figure 5 RT-qPCR was used to detect the number of exosome particles and the copy number of each candidate gene in normal urine samples (n=35), and the correlation between the two was analyzed. Figure 6 RT-qPCR was used to detect the copy number of the endogenous quality control gene EEF1A1 and each candidate gene in normal urine samples (n=22), and the correlation between the two was analyzed. Figure 7 Compare the expression stability of each candidate gene under the same number of exosome particles; Figure 8 Compare the CT value distribution of each candidate gene under the same number of exosome particles; Figure 9 Comparative analysis was conducted on the differential expression of the target gene MALAT1, which was normalized by UPK1A and UPK2, in bladder cancer (n=32) and healthy controls (n=32). Figure 10 Comparative analysis was conducted on the differential expression of the target gene PCAT-1, which was normalized by UPK1A and UPK2, in bladder cancer (n=32) and healthy controls (n=32). Figure 11 The selection of internal reference genes was determined by comparing the AUC of MALAT1 and PCAT-1 normalized by UPK1A and UPK2 in the diagnosis of bladder cancer. Figure 12 This is a schematic diagram showing the results of RT-qPCR detection of 37 genes. The vertical axis represents the differential expression of target genes in first-episode bladder cancer and healthy controls, and the horizontal axis represents different genes. Among them, A represents the results of SLC29A3, MEF2C, C3orf70, BAZ2A, ANKRD11, KIFC1, ZNF492, RAD51, CENPA, NCOA6, and NEK2; B represents the results of ESM1, LCN2, SLC22A7, RPS17, CERS2, CCNA2, IFNGR2, PEG10, and DNM2; and C represents the results of SYNPO2, MFAP4, KANK2, TCF21, EPHA3, CTSK, TMEM17, LCP2, SGMS2, ​​HBA2, KCTD1, DAPK2, BLC2, RWDD2A, and SLC35B4. Figure 13The example shows a schematic diagram of the detection results of CTSK, CENPA, NEK2, CERS2, ZNF492, HBA2, IFNGR2, LCN2, C3orf70, RPS17, CCNA2, and SLC29A3. The vertical axis represents the fold change in differential expression of the target gene in first-episode bladder cancer and healthy controls, and the horizontal axis represents different genes. Figure 14 The schematic diagram of the detection results of CENPA, ZNF492, NEK2, CERS2, IFNGR2, CTSK, HBA2, and CCNA2 in the example shows that the vertical axis represents the fold change of differential expression of the target gene in recurrent bladder cancer and non-recurrent bladder cancer, and the horizontal axis represents different genes. Figure 15 The schematic diagram of CTSK, NEK2, CENPA and CERS2 detection results in the example shows that the vertical axis represents the score of the corresponding target gene (score = (target gene copy number + 1) / internal reference gene copy number), and the horizontal axis represents different test populations: non-recurrent bladder cancer (n=119), recurrent bladder cancer (n=32). Figure 16 ROC curves for the combined diagnosis of recurrent bladder cancer using CTSK, NEK2, CENPA, and CERS2 in the examples; Figure 17 The schematic diagram of CTSK, NEK2, CENPA and CERS2 detection results in the example shows that the vertical axis represents the score of the corresponding target gene (score = (target gene copy number + 1) / internal reference gene copy number), and the horizontal axis represents different detection populations: non-cancer patients (n=64) and first-episode bladder cancer (n=48). Figure 18 The ROC curve of CTSK, NEK2, CENPA and CERS2 combined for the diagnosis of first-episode bladder cancer in the example. Detailed Implementation

[0023] To make the objectives, technical solutions, and advantages of this invention clearer, the technical solutions of this invention will be clearly and completely described below. Obviously, the described embodiments are only a part of the embodiments of this invention, and not all of them. Based on the embodiments of this invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of this invention.

[0024] The candidate gene primer pairs used in the RT-qPCR of this invention are shown in Tables 1-16.

[0025] Table 1: UPK1A Table 2: UPK1B Table 3: UPK2 Table 4: UPK3A Table 5: CTSK Table 6: NEK2 Table 7: CENPA Table 8: CERS2 Table 9: ZNF492 Table 10: IFNGR2 Table 11: HBA2 Table 12: LCN2 Table 13: C3orf70 Table 14: RPS17 Table 15: CCNA2 Table 16: SLC29A3 Amplified region sequence of internal reference gene UPK1A: 5'-AGGGCTGCTTCGAACACATCGGCCACGCCATCGACAGCTACACGTGGGGTATCTCGTGGTTTGGGTTTGCCATCCTGATGTGGACGCTCCCGGTCATG-3'.

[0026] Amplified region sequence of the internal reference gene UPK1B: 5'-TTTATCACAATCAGGGCTGCTATGAACTGATCTCTGGTCCAATGAACCGACACGCCTGGGGGGTTGCCTGGTTTGGATTTGC-3'.

[0027] Amplified region sequence of the internal reference gene UPK2: 5'-GTCACCTCACAGGAGGCAATGCCACACTGATGGTCCGGAGAGCCAATGACAGCAAAGTGGTGACGTCCAGC-3'.

[0028] Amplified region sequence of internal reference gene UPK3A: 5'-GGCCTTGGAAAAGCCTCTCTGCATGTTTGACAGCAAAGAGGCCCTCACTGGCACCCACGAGGTCTACCTGTATGTCCTGGTCGACTCAGCCATTTCCAGG-3'.

[0029] Amplified region sequence of target gene CTSK: 5'-TCCCCGAGGGGAATGAGAAAGCCCTGAAGAGGGCAGTGGCCCGAGTGGGACCTGTCTCTGTGGCCATTGATGCAAGCCT-3'.

[0030] Amplified region sequence of target gene NEK2: 5'-CAAGGACCTGAAGAAAAGGCTTCACGCTGCCCAGCTGCGGGCTCAAGCCCTGTCAGATATTGAGAAAAATTACCAACTGAAAAGCAGACAGATCCTGGGC-3'.

[0031] Amplified region sequence of the target gene CENPA: 5'-ATTCACTCGTGGTGTGGACTTCAATTGGCAAGCCCAGGCCCTATTGGCCCTACAAGAGGCAGCAGAAGCA-3'.

[0032] Amplified region sequence of target gene CERS2: 5'-AGCCCAAGCAGGTGGAAGTAGAGCTTTTGTCCCGGCAGAGCGGGCTCTCTGGCCGCCAGGTAGAGCGTTGGTT-3'.

[0033] Amplified region sequence of target gene ZNF492: 5'-CGCTGCAGTCGGAGTATGGTCTAGTGTTCGCTGTTCTGCGTCCTCTGGTCCTAGAGGCCCATCCTCTGTGGCCCTGTGACCTGCAGGTATTGGGAGATCCA-3'.

[0034] Amplified region sequence of target gene IFNGR2: 5'-CTCTACGCCTTCGAGCTGAGCTGGGAGCACTCCATTCTGCCTGGGTGACAATGCCTTGGTTTCCAACACTATCGGAATGTGACTGTCGGGCCT-3'.

[0035] Amplified region sequence of target gene HBA2: 5'-GCCCTGGAGAGGATGTTCCTGTCCTTCCCCACCACCAAGACCTACTTCCCGCACTTCGACCTGAGCCACGGCTCTGCCCAGGTTAAGGGCCACGGCAAGA-3'.

[0036] Amplified region sequence of target gene LCN2: 5'-TGAGTGCACAGGTGCCGCCAGCTGCCGCACCAGCCCGAACACCATTGAGGGAGCTGGGAGACCCTCCCCACAGTG-3'.

[0037] Amplified region sequence of target gene C3orf70: 5'-TGATGAACCCTGCCCGAGGTTCTCGGTGCCTCCCGTGCATGAGTGGCTCACTGAAGGCAGGTGTGGAAGCCAAATGCCTGCAAGCCGTGTGTCAG-3'.

[0038] Amplified region sequence of target gene RPS17: 5'-TGGGCAACGACTTCCACACGAACAAGCGCGTGTGCGAGGAGATCGCCATTATCCCCAGCAAAAAGCTCCGCAACAAGATAGCAGGTTATGTCACGCATCT-3'.

[0039] Amplified region sequence of target gene CCNA2: 5'-CTGGCGGTACTGAAGTCCGGGAACCCGCGGGGTCTAGCGCAGCAGCAGAGGCCGAAGACGAGACGGGTTGCACCC-3'.

[0040] Amplified region sequence of target gene SLC29A3: 5'-GCTGGAGTATGCCAGGTACTACATGAGGCCTGTTCTTGCGGCCCATGTGTTTTCTGGTGAAGAGGAGCTTCCCCAGGACTCCCTCAGTGC-3'.

[0041] Example 1 The primer concentrations used in RT-qPCR are shown in Table 17.

[0042] Table 17: Primer ratios 1.1 Determination of primer pairs and primer ratios required for RT-qPCR detection of candidate genes ① cDNA template preparation Total RNA was extracted from T24 bladder cancer cells and reverse transcribed into cDNA. Using the cDNA as a template, five concentration gradients were prepared by sequentially diluting the cells 10-fold with enzyme-free water. Reverse transcription was performed according to the Takara reverse transcription kit instructions. The reverse transcription program was: 37 ℃ for 15 min, 85 ℃ for 5 s. The reverse transcription system is shown in Table 18.

[0043] Table 18: Reverse Transcription System ② RT-qPCR to determine primer pairs and primer ratios For each candidate gene, three primer pairs were used sequentially, with a four-primer ratio, and the reaction system (2 μL of cDNA sample to be tested) was prepared accordingly. After thorough mixing, the corresponding target gene fragment was amplified and FAM fluorescence signal was detected on an RT-qPCR instrument. The quantitative PCR program was as follows: 50 ℃ for 2 min; 95 ℃ pre-denaturation for 10 min; 95 ℃ denaturation for 15 s, 60 ℃ annealing for 1 min, for 60 cycles. Fluorescence signals were collected after each cycle, and the PCR amplification reaction and fluorescence signal data were analyzed. By plotting a standard curve, the amplification efficiency was compared, and the most suitable primer pairs and primer concentrations for each candidate gene were selected.

[0044] 1.2 Establishment of the RT-qPCR absolute quantification standard curve ① Standard formulation and serial dilution The copy concentration of the candidate internal reference gene for expression in the cDNA template of the aforementioned reverse-transcribed T24 bladder cancer cells was determined to be 1.0 × 10⁻⁶. 6 The copy concentration of the target gene for bladder cancer expression was 1.0 × 10⁻¹¹ μL. 5 Copies / μL. Dilute the T24 cell standard with enzyme-free water to a uniform concentration of 1.0 × 10⁻⁶ copies / μL. 5Up to 10 copies / μL.

[0045] ② Establish a standard curve using RT-qPCR For each candidate gene, a reaction system (2 μL of cDNA sample to be tested) was prepared according to the optimized primer ratio. After thorough mixing, the corresponding target gene fragment was amplified and the FAM fluorescence signal was detected on an RT-qPCR instrument. The quantitative PCR program was as follows: 50 ℃ for 2 min; 95 ℃ pre-denaturation for 10 min; 95 ℃ denaturation for 15 s, 60 ℃ annealing for 1 min, for 60 cycles. Fluorescence signals were collected after each cycle to complete the PCR amplification reaction and analyze the collected fluorescence signals. A standard curve was plotted, aiming for an amplification efficiency of 90%-110%, R0. 2 Greater than 0.99.

[0046] 1.3 Extraction of urinary exosomes and detection of related genes ① Extraction of urinary exosomes Urinary exosomes were extracted from urine samples of healthy individuals, patients with benign urinary tract diseases, those with first-episode bladder cancer, those with recurrent bladder cancer, or those without recurrent bladder cancer. 20 mL of urine was collected and processed at 2,000 g × 20 min; the supernatant was collected and processed at 10,000 g × 30 min; the supernatant was then filtered through a 0.22 μm filter and processed at 100,000 g × 70 min. The precipitate was resuspended in 1 mL of DPBS, and the process was repeated at 100,000 g × 70 min. The precipitate was then resuspended in 100 μl of DPBS to obtain urinary exosomes.

[0047] ② RNA extraction from urinary exosomes The extracted urinary exosomes were extracted using a magnetic bead-total RNA extraction kit, following the instructions in the TRANS product manual. The concentration and purity of the RNA were then measured to determine its template RNA for the next reverse transcription step.

[0048] ③Reverse transcription The eluted RNA was reverse transcribed into cDNA, and the reaction system and reverse transcription procedure were performed according to the Takara reverse transcription kit instructions.

[0049] ④ RT-qPCR gene detection For different target genes, reaction systems (2 μL of cDNA sample) were prepared according to pre-optimized primer ratios. After thorough mixing, the target gene fragments were amplified and FAM fluorescence signals were detected on an RT-qPCR instrument. The quantitative PCR program was as follows: 50 ℃ for 2 min; 95 ℃ pre-denaturation for 10 min; 95 ℃ denaturation for 15 s, 60 ℃ annealing for 1 min, for 60 cycles. Fluorescence signals were collected after each cycle. After completing the PCR amplification reaction and analyzing the collected fluorescence signals, absolute quantification of the target gene was performed using an absolute quantification method.

[0050] 1.4 Identification and Validation of Bladder Tissue-Specific Internal Reference Genes from Urinary Exosomes ① Screening of internal reference genes This patent identified 20 bladder tissue-specific genes based on RNA sequencing data from the TissGDB database and previous literature on urinary exosomes, and confirmed their expression in urinary exosomes using exoRBase 3.0. Five of these genes (UPK1A, UPK1B, UPK2, UPK3A, and SHROOM1) were significantly enriched in the urothelial cell differentiation and apical development pathways, indicating a high correlation with bladder development. Four of these genes belong to the UPK family (UPK1A, UPK1B, UPK2, and UPK3A), which is the most enriched and representative gene family expressed in bladder tissue. Therefore, we screened and validated UPK family genes as candidate internal control genes.

[0051] ② Validation and determination of internal reference genes To verify whether these candidate genes are stably expressed in urinary exosomes and are unaffected by sex, disease state, initial urine, or midstream urine, six urinary exosomes were first extracted from different individuals. The exosome particle count was detected using NTA, and the results are as follows: Figure 1 As shown, there was no significant difference in the number of exosome particles in urinary exosomes from different states (p>0.05). Subsequently, RT-qPCR was used to detect gene copy numbers, and the expression of four candidate genes in urinary exosomes from different states, including healthy men and healthy women, was compared. Figure 2 ), male bladder cancer patients and healthy men ( Figure 3 ), the first and midstream urine of a healthy male ( Figure 4 The results showed that there was no significant difference in the ratio of the copy number of the four genes to the corresponding number of exosome particles in urine (p>0.05), indicating that the candidate genes have the ability to be stably expressed in urine exosomes and are not affected by the state of urine.

[0052] Subsequently, to verify whether these candidate genes were significantly enriched in urinary exosomes and whether they were correlated with the number of urinary exosomes, urine samples were collected from 35 healthy individuals. The exosome particle number and candidate gene copy number were detected using NTA and RT-qPCR, respectively, and a correlation analysis was performed. The results are as follows: Figure 5 As shown, UPK1A, UPK1B, UPK2, and UPK3A were all significantly positively correlated with the number of exosome particles (p<0.05). EEF1A1 is a gene with high abundance and stable expression in urinary exosomes and can be used as an endogenous quality control gene for urinary exosome recovery. The correlation between candidate genes and EEF1A1 was further compared. Urine samples were collected from 22 healthy individuals. The copy numbers of candidate genes and EEF1A1 were detected by RT-qPCR, and the correlation between the two was analyzed. The results are shown below. Figure 6 As shown, UPK1A, UPK1B, UPK2, and UPK3A were all significantly positively correlated with EEF1A1 (p<0.05), with UPK1A and UPK2 showing stronger correlations.

[0053] In addition to assessing the enrichment and expression of candidate genes, stability at the same number of exosome particles is also crucial. Therefore, the expression stability of each candidate gene (n=24) was compared using the RefFinder online website at the same number of exosome particles. The results are as follows: Figure 7 As shown, UPK1A and UPK2 had lower stability scores, indicating better expression stability. Furthermore, compared to UPK1B, UPK2, and UPK3A, UPK1A had a lower median CT value, indicating a higher expression level of UPK1A in exosomes. Figure 8 ).

[0054] Since the overall expression and stability of UPK1A and UPK2 are similar, candidate genes were further screened based on the diagnostic performance of the target genes for bladder cancer. Urine samples were collected from 32 healthy individuals and 32 bladder cancer patients. After exosome extraction, RT-qPCR was used to detect the copy numbers of candidate genes (UPK1A and UPK2) and target genes (MALAT1 and PCAT-1). The copy number ratio of target genes to candidate genes was calculated to compare the differences in target gene expression scores between healthy individuals and bladder cancer patients. Results are as follows: Figure 9 and Figure 10 As shown, when UPK1A and UPK2 were used as internal reference genes to normalize the target genes, the expression scores of MALAT1 and PCAT-1 in urinary exosomes from bladder cancer patients were significantly higher than those in healthy individuals. Subsequently, ROC curves were used to evaluate the diagnostic performance of these two genes for bladder cancer, and the results are as follows: Figure 11As shown, when UPK1A was used as an internal reference gene, both MALAT1 and PCAT-1 showed higher AUC, indicating that UPK1A is more advantageous as an internal reference gene for the diagnosis of bladder cancer.

[0055] In summary, by analyzing and comparing the enrichment and expression of four candidate genes in urine under different conditions, their correlation with the number of urinary exosome particles and EEF1A1, the stability of gene expression and the distribution of CT values ​​under the same number of exosome particles, and the diagnostic performance of the target gene normalization score for bladder cancer, UPK1A was finally determined as the internal reference gene for the molecular diagnosis of urinary exosome bladder cancer.

[0056] 1.5 Construction and Effectiveness Evaluation of Bladder Cancer Risk Assessment Model ① Screening of target genes In the discovery phase of bladder cancer target genes, this invention systematically screened multiple publicly published sequencing datasets. A total of nine tissue sequencing datasets (including seven primary bladder cancer samples and two recurrent bladder cancer samples) and two primary bladder cancer urine exosome sequencing datasets were included. Through cross-analysis of multiple datasets, genes differentially expressed in both tissues and urine exosomes were screened and compared with the exoRBase database. Subsequently, the TCGA database was used to further identify genes highly expressed in bladder cancer tissues. RT-qPCR was used to detect differential expression of 37 candidate target genes (CTSK, NEK2, CENPA, CERS2, ZNF492, HBA2, IFNGR2, LCN2, C3orf70, RPS17, CCNA2, SLC29A3, ANKRD11, BAZ2A, BCL2, CSF2RB, DAPK2, DNM2, EPHA3, ESM1, KANK2, KCTD1, KIFC1, LCP2) in primary bladder cancer and healthy controls. Twelve genes (MEF2C, MFAP4, NCOA6, PEG10, RAD51, RWDD2A, SGMS2, ​​SLC22A7, SLC35B4, SYNPO2, TCF21, TMEM17, TUBGCP4) were significantly upregulated in first-episode bladder cancer: CTSK, CENPA, NEK2, CERS2, ZNF492, HBA2, IFNGR2, LCN2, C3orf70, RPS17, CCNA2, and SLC29A3. Experimental results are as follows: Figure 12 A- Figure 12 As shown in C. In the analysis of first-time bladder cancer and healthy controls, a total of 12 genes were significantly upregulated in first-time bladder cancer: CTSK, CENPA, NEK2, CERS2, ZNF492, HBA2, IFNGR2, LCN2, C3orf70, RPS17, CCNA2, and SLC29A3 (…). Figure 13 Of the 12 genes that were significantly upregulated, 8 target genes were significantly upregulated in recurrent bladder cancer: CTSK, CENPA, NEK2, CERS2, ZNF492, HBA2, IFNGR2, and CCNA2. Figure 14 Furthermore, a random forest ranking system based on feature importance was applied for optimization selection, which identified four key target genes: CENPA, NEK2, CERS2, and CTSK, for use in the construction of subsequent bladder cancer diagnostic models.

[0057] ② Evaluation of the diagnostic efficacy of recurrent bladder cancer Subsequently, to detect the expression levels of target genes in recurrent and non-recurrent bladder cancer, and their diagnostic efficacy for recurrent bladder cancer, urine samples were collected from 32 patients with recurrent bladder cancer and 119 patients with non-recurrent bladder cancer. After exosome extraction, the copy numbers of UPK1A, CTSK, NEK2, CENPA, and CERS2 were detected using RT-qPCR. The target gene score was calculated as (target gene copy number + 1) / internal reference gene copy number. Results are as follows: Figure 15 As shown, the scores of CTSK, NEK2, CENPA, and CERS2 in recurrent bladder cancer were significantly higher than those in non-recurrent bladder cancer (p<0.0001). Based on the target gene scores, the DEUCE model score was calculated using logistic regression: DEUCE score = 1 / (1+exp(-(0.6610+0.2868×CTSK score+0.5696×NEK2 score+1.2581×CENPA score+0.6248×CERS2 score)). If the DEUCE model score is less than or equal to 0.25, it indicates a negative result and is diagnosed as non-recurrent bladder cancer; a result greater than 0.25 indicates a recurrent bladder cancer diagnosis. Subsequently, the diagnostic efficacy of the DEUCE model for recurrent bladder cancer was evaluated using ROC curves, and the results are as follows: Figure 16 As shown, the AUC is 0.975.

[0058] ③ Evaluation of the diagnostic effectiveness of first-episode bladder cancer Subsequently, to investigate the expression levels of target genes in first-episode bladder cancer and non-cancerous patients (including healthy individuals and patients with benign urinary tract diseases), and to assess their diagnostic efficacy for first-episode bladder cancer, urine samples were collected from 48 first-episode bladder cancer patients and 64 non-cancerous patients. Exosomes were extracted, and RT-qPCR was used to detect the copy numbers of UPK1A, CTSK, NEK2, CENPA, and CERS2. The target gene score was calculated as (target gene copy number + 1) / internal reference gene copy number. Results are as follows: Figure 17As shown, the scores of CTSK, NEK2, CENPA, and CERS2 in patients with first-episode bladder cancer were significantly higher than those in non-cancer patients (p<0.0001). Based on the target gene scores, the DEUCE model score was calculated using logistic regression: DEUCE score = 1 / (1+exp(-(0.6610+0.2868×CTSK score+0.5696×NEK2 score+1.2581×CENPA score+0.6248×CERS2 score))). If the DEUCE model score is less than or equal to 0.20, it indicates a negative result, and the patient is diagnosed as non-cancer; a score greater than 0.20 indicates a diagnosis of first-episode bladder cancer. Subsequently, the diagnostic efficacy of the DEUCE model for first-episode bladder cancer was evaluated using ROC curves, and the results are as follows. Figure 18 As shown, the AUC is 0.975.

[0059] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention, and not to limit them; although the present invention has been described in detail with reference to the foregoing embodiments, those skilled in the art should understand that modifications can still be made to the technical solutions described in the foregoing embodiments, or equivalent substitutions can be made to some or all of the technical features; and these modifications or substitutions do not cause the essence of the corresponding technical solutions to deviate from the technical solutions of the embodiments of the present invention.

Claims

1. A bladder cancer gene detection system based on urinary exosomes, characterized in that, The system includes: a reagent for detecting the expression level of a bladder tissue-specific internal reference gene in urinary exosomes; and a reagent for specifically detecting the expression level of a target gene. The internal reference gene includes: UPK1A; The target genes include at least CTSK, NEK2, CENPA, and CERS2.

2. The bladder cancer gene detection system based on urinary exosomes according to claim 1, characterized in that, The detection reagent for specifically detecting the expression level of the bladder tissue-specific internal reference gene UPK1A in urinary exosomes includes: PCR primers and TaqMAN probe; The PCR primers and TaqMAN probes are selected from any of the following combinations: (a) A primer pair having nucleotide sequences as shown in SEQ ID NO.1 and SEQ ID NO.2, and a TaqMAN probe having a nucleotide sequence as shown in SEQ ID NO.3; (b) A primer pair having nucleotide sequences as shown in SEQ ID NO.4 and SEQ ID NO.5, and a TaqMAN probe having a nucleotide sequence as shown in SEQ ID NO.6; (c) A primer pair having nucleotide sequences as shown in SEQ ID NO.7 and SEQ ID NO.8, and a TaqMAN probe having nucleotide sequences as shown in SEQ ID NO.

9.

3. The bladder cancer gene detection system based on urinary exosomes according to claim 1, characterized in that, The internal reference gene may also be selected from any one of UPK1B, UPK2, or UPK3A; The target genes may also include any one or more of ZNF492, HBA2, IFNGR2, LCN2, C3orf70, RPS17, CCNA2, or SLC29A3.

4. The bladder cancer gene detection system based on urinary exosomes according to claim 1, characterized in that, The detection reagent for specifically detecting the expression level of target genes includes: primer pairs and TaqMAN probes targeting the target genes; The primer pair for the target gene CTSK and the TaqMAN probe are selected from any of the following combinations: (1) Primer pairs with nucleotide sequences as shown in SEQ ID NO.37 and SEQ ID NO.38, and TaqMAN probes with nucleotide sequences as shown in SEQ ID NO.39; (2) Primer pairs with nucleotide sequences as shown in SEQ ID NO.40 and SEQ ID NO.41, and TaqMAN probes with nucleotide sequences as shown in SEQ ID NO.42; (3) Primer pairs with nucleotide sequences as shown in SEQ ID NO.43 and SEQ ID NO.44, and TaqMAN probes with nucleotide sequences as shown in SEQ ID NO.45; The primer pair and TaqMAN probe for the target gene NEK2 are selected from any of the following combinations: (1) A primer pair with nucleotide sequences as shown in SEQ ID NO.46 and SEQ ID NO.47, and a TaqMAN probe with nucleotide sequences as shown in SEQ ID NO.48; (2) A primer pair with nucleotide sequences as shown in SEQ ID NO.49 and SEQ ID NO.50, and a TaqMAN probe with a nucleotide sequence as shown in SEQ ID NO.51; (3) Primer pairs with nucleotide sequences as shown in SEQ ID NO.52 and SEQ ID NO.53, and TaqMAN probes with nucleotide sequences as shown in SEQ ID NO.54; The primer pair and TaqMAN probe for the target gene CENPA are selected from any of the following combinations: (1) A primer pair with nucleotide sequences as shown in SEQ ID NO.55 and SEQ ID NO.56, and a TaqMAN probe with nucleotide sequences as shown in SEQ ID NO.57; (2) Primer pairs with nucleotide sequences as shown in SEQ ID NO.58 and SEQ ID NO.59, and TaqMAN probes with nucleotide sequences as shown in SEQ ID NO.60; (3) Primer pairs with nucleotide sequences as shown in SEQ ID NO.61 and SEQ ID NO.62, and TaqMAN probes with nucleotide sequences as shown in SEQ ID NO.63; The primer pair and TaqMAN probe for the target gene CERS2 are selected from any of the following combinations: (1) Primer pairs with nucleotide sequences as shown in SEQ ID NO.64 and SEQ ID NO.65, and TaqMAN probes with nucleotide sequences as shown in SEQ ID NO.66; (2) Primer pairs with nucleotide sequences as shown in SEQ ID NO.67 and SEQ ID NO.68, and TaqMAN probes with nucleotide sequences as shown in SEQ ID NO.69; (3) Primer pairs with nucleotide sequences as shown in SEQ ID NO.70 and SEQ ID NO.71, and TaqMAN probe with nucleotide sequences as shown in SEQ ID NO.

72.

5. The bladder cancer gene detection system based on urinary exosomes according to claim 3, characterized in that, The primer pair and TaqMAN probe for the target gene ZNF492 are selected from any of the following combinations: (1) Primer pairs with nucleotide sequences as shown in SEQ ID NO.73 and SEQ ID NO.74, and TaqMAN probe with nucleotide sequences as shown in SEQ ID NO.75; (2) Primer pairs with nucleotide sequences as shown in SEQ ID NO.76 and SEQ ID NO.77, and TaqMAN probes with nucleotide sequences as shown in SEQ ID NO.78; (3) Primer pairs with nucleotide sequences as shown in SEQ ID NO.79 and SEQ ID NO.80, and TaqMAN probes with nucleotide sequences as shown in SEQ ID NO.81; The primer pair and TaqMAN probe for the target gene IFNGR2 are selected from any of the following combinations: (1) Primer pairs with nucleotide sequences as shown in SEQ ID NO.82 and SEQ ID NO.83, and TaqMAN probes with nucleotide sequences as shown in SEQ ID NO.84; (2) Primer pairs with nucleotide sequences as shown in SEQ ID NO.85 and SEQ ID NO.86, and TaqMAN probes with nucleotide sequences as shown in SEQ ID NO.87; (3) Primer pairs with nucleotide sequences as shown in SEQ ID NO.88 and SEQ ID NO.89, and TaqMAN probes with nucleotide sequences as shown in SEQ ID NO.90; The primer pair and TaqMAN probe for the target gene HBA2 are selected from any of the following combinations: (1) Primer pairs with nucleotide sequences as shown in SEQ ID NO.91 and SEQ ID NO.92, and TaqMAN probes with nucleotide sequences as shown in SEQ ID NO.93; (2) Primer pairs with nucleotide sequences as shown in SEQ ID NO.94 and SEQ ID NO.95, and TaqMAN probes with nucleotide sequences as shown in SEQ ID NO.96; (3) Primer pairs with nucleotide sequences as shown in SEQ ID NO.97 and SEQ ID NO.98, and TaqMAN probes with nucleotide sequences as shown in SEQ ID NO.99; The primer pair and TaqMAN probe for the target gene LCN2 are selected from any of the following combinations: (1) A primer pair with nucleotide sequences as shown in SEQ ID NO.100 and SEQ ID NO.101, and a TaqMAN probe with nucleotide sequences as shown in SEQ ID NO.102; (2) Primer pairs with nucleotide sequences as shown in SEQ ID NO.103 and SEQ ID NO.104, and TaqMAN probes with nucleotide sequences as shown in SEQ ID NO.105; (3) Primer pairs with nucleotide sequences as shown in SEQ ID NO.106 and SEQ ID NO.107, and TaqMAN probes with nucleotide sequences as shown in SEQ ID NO.108; The primer pair and TaqMAN probe for the target gene C3orf70 are selected from any of the following combinations: (1) A primer pair with nucleotide sequences as shown in SEQ ID NO.109 and SEQ ID NO.110, and a TaqMAN probe with a nucleotide sequence as shown in SEQ ID NO.111; (2) Primer pairs with nucleotide sequences as shown in SEQ ID NO.112 and SEQ ID NO.113, and TaqMAN probes with nucleotide sequences as shown in SEQ ID NO.114; (3) Primer pairs with nucleotide sequences as shown in SEQ ID NO.115 and SEQ ID NO.116, and TaqMAN probes with nucleotide sequences as shown in SEQ ID NO.117; The primer pair and TaqMAN probe for the target gene RPS17 are selected from any of the following combinations: (1) Primer pairs with nucleotide sequences as shown in SEQ ID NO.118 and SEQ ID NO.119, and TaqMAN probes with nucleotide sequences as shown in SEQ ID NO.120; (2) Primer pairs with nucleotide sequences as shown in SEQ ID NO.121 and SEQ ID NO.122, and TaqMAN probes with nucleotide sequences as shown in SEQ ID NO.123; (3) Primer pairs with nucleotide sequences as shown in SEQ ID NO.124 and SEQ ID NO.125, and TaqMAN probes with nucleotide sequences as shown in SEQ ID NO.126; The primer pair and TaqMAN probe for the target gene CCNA2 are selected from any of the following combinations: (1) A primer pair with nucleotide sequences as shown in SEQ ID NO.127 and SEQ ID NO.128, and a TaqMAN probe with nucleotide sequences as shown in SEQ ID NO.129; (2) Primer pairs with nucleotide sequences as shown in SEQ ID NO.130 and SEQ ID NO.131, and TaqMAN probes with nucleotide sequences as shown in SEQ ID NO.132; (3) Primer pairs with nucleotide sequences as shown in SEQ ID NO.133 and SEQ ID NO.134, and TaqMAN probes with nucleotide sequences as shown in SEQ ID NO.135; The primer pair and TaqMAN probe for the target gene SLC29A3 are selected from any of the following combinations: (1) Primer pairs with nucleotide sequences as shown in SEQ ID NO.136 and SEQ ID NO.137, and TaqMAN probes with nucleotide sequences as shown in SEQ ID NO.138; (2) Primer pairs with nucleotide sequences as shown in SEQ ID NO.139 and SEQ ID NO.140, and TaqMAN probes with nucleotide sequences as shown in SEQ ID NO.141; (3) Primer pairs with nucleotide sequences as shown in SEQ ID NO.142 and SEQ ID NO.143, and TaqMAN probes with nucleotide sequences as shown in SEQ ID NO.

144.

6. A risk assessment model, characterized in that, Using the bladder cancer gene detection system based on urinary exosomes as described in any one of claims 1-5, the evaluation model is defined by the following formula: DEUCE score = 1 / (1+exp(-(0.6610+0.2868×CTSK score+0.5696×NEK2 score+1.2581×CENPA score+0.6248×CERS2 score))); Among them, CTSK score, NEK2 score, CENPA score, and CERS2 score are the expression levels of the corresponding target genes, normalized by the internal reference gene UPK1A, and denoted as the target gene score. The target gene score = log 10 [(target gene copy number + 1) / internal reference gene copy number].

7. The risk assessment model according to claim 6, characterized in that, The output threshold for the DEUCE score is 0.20 or 0.

25.

8. A product for bladder cancer screening, diagnosis, prognosis, and / or recurrence risk assessment, characterized in that, The products include: Detection module: The gene detection system as described in any one of claims 1-5; Calculation module: The risk assessment model as described in any one of claims 6-7; Evaluation module: Used to compare the actual detection results with two preset output thresholds for the DEUCE score.

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