Digital droplet RNA amplification detection system for prostate cancer and method for reducing false negative rate of prostate cancer

Abstract

Disclosed in the present invention are a digital droplet RNA amplification detection system for prostate cancer and a method for reducing the false negative rate of prostate cancer. The provided digital droplet RNA amplification detection system for prostate cancer comprises reagents for respectively and specifically detecting the following genes on the basis of a real-time fluorescent nucleic acid constant-temperature amplification method: PCA3, ERG and SPDEF, and a digital PCR system.

Description

A digital microdroplet RNA amplification detection system for prostate cancer and a method to reduce the false negative rate of prostate cancer.

[0001] Cross-reference to related applications

[0002] This application claims priority to application number 202410679726.6, filed with the China National Intellectual Property Administration on May 29, 2024, the entire contents of which are incorporated herein by reference. Technical Field

[0003] This invention belongs to the field of tumor diagnostic technology, specifically relating to a digital microdroplet RNA amplification detection system for prostate cancer and a method for reducing the false negative rate of prostate cancer. Background Technology

[0004] Prostate cancer is most common in men over 50 years of age and is the most common malignant tumor of the male urinary system. Statistics show that in 2022, prostate cancer ranked second in new cases among male malignant tumors worldwide and fifth in deaths. The incidence of prostate cancer is directly related to race, being most prevalent in Caucasians, followed by Africans, while the incidence is lower in East Asians. Early prostate cancer symptoms are similar to common lower urinary tract symptoms and are easily overlooked by patients. Therefore, many prostate cancer patients miss the optimal treatment window or have already experienced metastasis by the time of diagnosis. Thus, early diagnosis of prostate cancer is extremely important.

[0005] Currently, the simplest clinical examination for prostate cancer is a digital rectal exam (DRE). Clinicians, wearing gloves, use their fingers to examine the prostate gland through the rectum to check its size and for any abnormal nodules. However, this method is limited by the examiner's experience and has significant limitations in detecting early-stage prostate cancer. Serum prostate-specific antigen (PSA) is an important indicator for prostate cancer screening and monitoring. However, PSA is only a specific marker for the prostate, not for prostate cancer. Inflammation, hyperplasia, and artificial compression of the prostate can all lead to a sustained increase in serum PSA. Therefore, the specificity of serum PSA is relatively poor. The gold standard for prostate cancer diagnosis is prostate biopsy: generally using a targeted puncture combined with a systematic puncture method, a hollow needle is used to obtain prostate tissue from the patient, and cell morphology is observed under a microscope for diagnosis. Currently, the positive rate of prostate cancer biopsy is low in clinical practice, causing too many patients to undergo unnecessary biopsies, resulting in significant physical and psychological suffering. Therefore, clinical practice needs more diagnostic methods for prostate cancer to assist in the early diagnosis of prostate cancer.

[0006] Patent document CN117265112A (hereinafter referred to as Document 1) discloses a digital microdroplet RNA amplification detection system for prostate cancer. This system utilizes isothermal RNA amplification technology combined with a digital PCR system to perform absolute quantitative detection of PCA3 and SPDEF RNA levels in urine samples. The PCA3 score is calculated using the SPDEF RNA level as an internal reference, and prostate cancer can be diagnosed based on this PCA3 score. Results show that this digital microdroplet RNA amplification detection system can detect prostate cancer with high sensitivity (up to 96.55%) in patients over 50 years of age with serum PSA in the gray zone (4-10 ng / mL), and the negative predictive value is as high as 94.7%. Therefore, the digital microdroplet RNA amplification detection system provided in Document 1 can screen out 96.55% of positive patients, and up to 94.7% of the actual negative subjects are determined to be true negatives, thus avoiding unnecessary biopsies for 94.7% of the actual negative subjects. However, Reference 1 may still result in a false negative rate of approximately 3.45% for positive patients and cause approximately 5.3% of actually negative individuals to undergo unnecessary biopsies. These issues will be even more pronounced in large-scale screening. Furthermore, clinical testing of 173 urine samples from patients in the PSA gray zone using the detection system provided in Reference 1 revealed a sensitivity of 92.77% and a negative predictive value of 90.5%. This could result in a false negative rate of approximately 7.23% for positive patients and potentially cause approximately 9.5% of actually negative patients to undergo unnecessary biopsies. Therefore, it is necessary to provide a prostate cancer detection product that achieves better detection results. Summary of the Invention

[0007] In a first aspect, the present invention provides a digital microdroplet RNA amplification detection system for prostate cancer, comprising reagents for the specific detection of the following genes respectively based on a real-time fluorescence nucleic acid isothermal amplification method: PCA3, ERG and SPDEF genes, and a digital PCR system for absolute quantification of the above genes.

[0008] The SPDEF gene is used as an internal reference gene for detection.

[0009] The specific detection reagents for each gene include those corresponding to that gene:

[0010] (1) Nucleic acid extraction solution: which contains a solid support containing a specific capture probe for capturing gene sequences; the nucleotide sequences of the specific capture probes for specific detection of the following genes are shown in SEQ ID NO:23, 17 and 27 respectively: PCA3, ERG and SPDEF;

[0011] The components of the nucleic acid extraction solution include: 250-800mM HEPES, 4-10% lithium dodecyl sulfate, 1-50μM of the specific capture probe, and 50-500mg / L magnetic beads;

[0012] (2) Amplification detection solution: It contains a first primer, a second primer and a target detection probe, wherein the first primer works in conjunction with the first primer to amplify the target sequence in the gene sequence, and the target detection probe specifically binds to the RNA copy of the amplification product of the target; the nucleotide sequences of the first primer specifically detecting the following genes are shown in SEQ ID NO:24, 19 and 28 respectively: PCA3, ERG and SPDEF; the nucleotide sequences of the second primer specifically detecting the following genes are shown in SEQ ID NO:25, 21 and 29 respectively: PCA3, ERG and SPDEF; the nucleotide sequences of the target detection probe specifically detecting the following genes are shown in SEQ ID NO:26, 18 and 30 respectively: PCA3, ERG and SPDEF, and the nucleotide sequences of the target detection probe are respectively equipped with a fluorescent reporter group and a quencher group at both ends of the nucleotide sequence of the target detection probe;

[0013] The amplification detection solution comprises: 10-50 mM Tris, 5-40 mM KCl, 10-40 mM MgCl2, 1-20 mM NTP, 0.1-10 mM dNTPs, 1-10% PVP40, the first primer at 10-250 pmol / mL, the second primer at 10-250 pmol / mL, and the target detection probe at 10-250 pmol / mL.

[0014] In some embodiments, the digital microdroplet RNA amplification detection system may further include:

[0015] (3) SAT enzyme solution: It contains at least one RNA polymerase and M-MLV reverse transcriptase.

[0016] In some embodiments, the SAT enzyme solution may include: 16,000-160,000 U / mL M-MLV reverse transcriptase, 8,000-80,000 U / mL RNA polymerase, 2-10 mM HEPES pH 7.5, 10-100 mM N-acetyl-L-cysteine, 0.04-0.4 mM zinc acetate, 10-100 mM trehalose, 40-200 mM Tris-HCl pH 8.0, 40-200 mM KCl, 0.01-0.5 mM EDTA, 0.1-1% (v / v) Triton X-100, and 20-50% (v / v) glycerol.

[0017] In some embodiments, the digital microdroplet RNA amplification detection system may further include:

[0018] (4) Washing solution: It contains 5-50 mM HEPES, 50-500 mM NaCl, 0.5-1.5% SDS, 1-10 mM EDTA; and / or

[0019] (5) Positive controls: These include three systems of in vitro transcribed RNA containing the following gene nucleic acids: PCA3, ERG, and SPDEF; and / or

[0020] (6) Negative control: It is a system that does not contain the following gene nucleic acids: PCA3, ERG and SPDEF.

[0021] In a second aspect, the present invention provides an oligonucleotide combination comprising:

[0022] The specific capture probes have nucleotide sequences as shown in SEQ ID NO:23, 17 and 27, respectively; the first primers have nucleotide sequences as shown in SEQ ID NO:24, 19 and 28, respectively; the second primers have nucleotide sequences as shown in SEQ ID NO:25, 21 and 29, respectively; and the target detection probes have nucleotide sequences as shown in SEQ ID NO:26, 18 and 30, respectively.

[0023] In a third aspect, the present invention provides a digital microdroplet RNA amplification detection system for reducing the missed detection rate of prostate cancer, comprising:

[0024] The first reagent for the specific detection of the following genes based on the real-time fluorescence isothermal amplification method: PCA3;

[0025] The second reagent for the specific detection of the following gene based on the real-time fluorescence isothermal amplification method: ERG;

[0026] The third reagent for the specific detection of the following genes based on the real-time fluorescence isothermal amplification method is SPDEF, wherein SPDEF is used as an internal reference gene for detection.

[0027] A digital PCR system for absolute quantification of the above genes; and

[0028] Instruction manual;

[0029] The instruction manual mentioned therein includes:

[0030] S1) The expression of PCA3 and SPDEF genes in the sample is absolutely quantitatively detected using the first reagent, the third reagent, and a digital PCR system. The PCA3 score is calculated based on the absolute quantitative detection results, and the sample is classified into a first prostate cancer negative sample and a first prostate cancer positive sample based on the PCA3 score. When the PCA3 score of the sample is greater than 114.2, it is considered a first prostate cancer positive sample, and when the PCA3 score of the sample is less than or equal to 114.2, it is considered a first prostate cancer negative sample.

[0031] S2) Using the second reagent and a digital PCR system, the expression of the ERG gene in the first prostate cancer negative sample obtained in step S1) is absolutely quantified. An ERG score is calculated based on the absolute quantification of ERG gene expression and the absolute quantification of SPDEF gene expression in the corresponding sample obtained in step S1). The first prostate cancer negative sample obtained in step S1) is then further classified into a second prostate cancer negative sample and a second prostate cancer positive sample based on this ERG score. A sample with an ERG score greater than 39.1 is considered a second prostate cancer positive sample, and a sample with an ERG score less than or equal to 39.1 is considered a second prostate cancer negative sample.

[0032] S3) Combine the second prostate cancer positive sample obtained in step S2) with the first prostate cancer positive sample obtained in step S1) to obtain the final prostate cancer positive sample.

[0033] The first reagent contains a specific capture probe, a first primer, a second primer, and a target detection probe for the specific detection of the PCA3 gene, the nucleotide sequences of which are shown in SEQ ID NO:23-26, respectively.

[0034] The second reagent contains a specific capture probe for specific detection of the ERG gene, a first primer, a second primer, and a target detection probe, the nucleotide sequences of which are shown in SEQ ID NO:17, 19, 21, and 18, respectively.

[0035] The third reagent contains a specific capture probe for specific detection of the SPDEF gene, and the nucleotide sequences of the first primer, the second primer, and the target detection probe are shown in SEQ ID NO:27-30, respectively.

[0036] In some implementations, the PCA3 score is calculated as follows: PCA3 score = PCA3 copy number / SPDEF copy number * 1000, and the ERG score is calculated as follows: ERG score = ERG copy number / SPDEF copy number * 1000.

[0037] In some embodiments, the first reagent, the second reagent, and the third reagent each comprise:

[0038] (1) Nucleic acid extraction solution: It contains 250-800mM HEPES, 4-10% lithium dodecyl sulfate, 1-50μM of the specific capture probe, and 50-500mg / L magnetic beads;

[0039] (2) Amplification detection solution: This solution contains 10-50 mM Tris, 5-40 mM KCl, 10-40 mM MgCl2, 1-20 mM NTP, 0.1-10 mM dNTPs, 1-10% PVP40, the first primer at 10-250 pmol / mL, the second primer at 10-250 pmol / mL, and the target detection probe at 10-250 pmol / mL; and

[0040] (3) SAT enzyme solution: It contains 16,000-160,000 U / mL M-MLV reverse transcriptase, 8,000-80,000 U / mL RNA polymerase, 2-10 mM HEPES pH 7.5, 10-100 mM N-acetyl-L-cysteine, 0.04-0.4 mM zinc acetate, 10-100 mM trehalose, 40-200 mM Tris-HCl pH 8.0, 40-200 mM KCl, 0.01-0.5 mM EDTA, 0.1-1% (v / v) Triton X-100 and 20-50% (v / v) glycerol.

[0041] In some embodiments, the digital microdroplet RNA amplification detection system for reducing the false negative rate of prostate cancer further includes:

[0042] (4) Washing solution: It contains 5-50mM HEPES, 50-500mM NaCl, 0.5-1.5% SDS, and 1-10mM EDTA;

[0043] (5) Positive controls: These include three systems of in vitro transcribed RNA containing the following gene nucleic acids: PCA3, ERG, and SPDEF; and

[0044] (6) Negative control: It is a system that does not contain any of the following gene nucleic acids: PCA3, ERG and SPDEF.

[0045] In a fourth aspect, the present invention also provides a method for reducing the missed detection rate of prostate cancer, comprising the following steps:

[0046] M1) Absolute quantitative detection of PCA3 and SPDEF gene expression in the sample, with SPDEF gene as the internal reference for detection. PCA3 score is calculated based on the absolute quantitative results of PCA3 and SPDEF gene expression, and the sample is classified into first prostate cancer negative sample and first prostate cancer positive sample based on the PCA3 score.

[0047] M2) Absolute quantification of ERG gene expression in the first prostate cancer negative sample obtained in step M1), using the SPDEF gene as an internal reference, is performed. An ERG score is calculated based on the absolute quantification results of ERG gene expression and the absolute quantification results of SPDEF gene expression in the corresponding sample obtained in step M1). Based on this ERG score, the first prostate cancer negative sample obtained in step M1) is further classified into a second prostate cancer negative sample and a second prostate cancer positive sample.

[0048] M3) The second prostate cancer positive sample obtained in step M2) and the first prostate cancer positive sample obtained in step M1) are combined as the final prostate cancer positive sample, thereby reducing the false negative rate of prostate cancer.

[0049] The digital microdroplet RNA amplification detection system provided in the third aspect of this invention is used to perform absolute quantitative detection of the expression of PCA3, ERG and SPDEF genes in the sample.

[0050] In some implementations, in step M1), a sample with a PCA3 score greater than 114.2 is considered a first prostate cancer positive sample, and a sample with a PCA3 score less than or equal to 114.2 is considered a first prostate cancer negative sample. The PCA3 score is calculated as follows: PCA3 score = PCA3 copy number / SPDEF copy number * 1000.

[0051] In some implementations, in step M2), a sample with an ERG score greater than 39.1 is considered a second prostate cancer positive sample, and a sample with an ERG score less than or equal to 39.1 is considered a second prostate cancer negative sample. The ERG score is calculated as follows: ERG score = ERG copy number / SPDEF copy number * 1000.

[0052] In some implementations, the sample includes a urine sample.

[0053] In a fifth aspect, the present invention also provides a method for detecting prostate cancer, comprising the following steps:

[0054] N1) Absolute quantitative detection of PCA3 and SPDEF gene expression in the sample, with SPDEF gene as the internal reference for detection. PCA3 score is calculated based on the absolute quantitative results of PCA3 and SPDEF gene expression, and the sample is classified into first prostate cancer negative sample and first prostate cancer positive sample based on the PCA3 score.

[0055] N2) Absolute quantification of ERG gene expression in the first prostate cancer negative sample obtained in step N1) is performed, with SPDEF gene used as an internal reference. An ERG score is calculated based on the absolute quantification results of ERG gene expression and the absolute quantification results of SPDEF gene expression in the corresponding sample obtained in step N1). Based on this ERG score, the first prostate cancer negative sample obtained in step N1) is further classified into a second prostate cancer negative sample and a second prostate cancer positive sample.

[0056] N3) Combine the second prostate cancer positive sample obtained in step N2) and the first prostate cancer positive sample obtained in step N1) as the final prostate cancer positive sample, and take the second prostate cancer negative sample obtained in step N2) as the final prostate cancer negative sample.

[0057] The digital microdroplet RNA amplification detection system provided in the third aspect of this invention is used to perform absolute quantitative detection of the expression of PCA3, ERG and SPDEF genes in the sample.

[0058] In some implementations, in step N1), a sample with a PCA3 score greater than 114.2 is considered a first prostate cancer positive sample, and a sample with a PCA3 score less than or equal to 114.2 is considered a first prostate cancer negative sample. The PCA3 score is calculated as follows: PCA3 score = PCA3 copy number / SPDEF copy number * 1000.

[0059] In some implementations, in step N2), a sample with an ERG score greater than 39.1 is considered a second prostate cancer positive sample, and a sample with an ERG score less than or equal to 39.1 is considered a second prostate cancer negative sample. The ERG score is calculated as follows: ERG score = ERG copy number / SPDEF copy number * 1000.

[0060] The system or kit provided by this invention, based on the detection system provided in Reference 1, further includes reagents for absolute quantification of ERG gene expression in samples. Therefore, it can further perform absolute quantification of ERG genes in prostate cancer-negative urine samples identified by the detection system provided in Reference 1, and further calculate the ERG score using the RNA level of SPDEF as an internal reference. This can screen out prostate cancer-positive samples missed by the detection system provided in Reference 1, thereby reducing the false negative rate of prostate cancer and improving the diagnostic effect. Results show that the digital microdroplet RNA amplification detection system or kit combining PCA3 and ERG gene detection provided by this invention can detect prostate cancer in patients over 50 years of age with serum PSA in the gray zone (4-10 ng / mL) with higher sensitivity (up to 97.6%) and higher negative predictive value (97.7%), significantly reducing the false negative rate of prostate cancer while also exhibiting high accuracy. Therefore, the digital microdroplet RNA amplification detection system provided by this invention, compared to the diagnostic model in Reference 1, significantly improves diagnostic sensitivity and negative predictive value (reducing the probability of unnecessary biopsies for actual negative subjects (down to 2.3%)) and significantly reduces the false negative rate (down to 2.4%), based on only one additional detection target. Furthermore, in clinical sample validation trials, the digital microdroplet RNA amplification detection system provided by this invention can still screen out 97.14% of positive patients, and among actual negative subjects, as many as 97.56% of the tested subjects are still judged as true negatives. Therefore, it has better clinical application effects than the detection system provided in Reference 1. Thus, the digital microdroplet RNA amplification detection system for prostate cancer provided by this invention is more suitable for large-scale prostate cancer screening. Detailed Implementation

[0061] The present invention will be described in detail below with reference to specific embodiments.

[0062] In the following description, only certain exemplary embodiments are briefly described. As those skilled in the art will recognize, the described embodiments can be modified in various ways without departing from the spirit or scope of the invention. Therefore, the description of the embodiments is to be considered exemplary in nature and not restrictive.

[0063] Unless otherwise specified, the methods used in the following examples are conventional methods. For specific steps, please refer to: Molecular Cloning: A Laboratory Manual (Sambrook, J., Russell, David W., 3rd edition, 2001, NY, Cold Spring Harbor).

[0064] The methods for obtaining various biological materials described in the embodiments are merely to provide experimental methods for specific disclosure purposes and should not be construed as limiting the sources of biological materials used in this invention. In fact, the sources of biological materials used are wide-ranging, and any biological material that can be obtained without violating laws and ethical standards can be substituted and used according to the suggestions in the embodiments.

[0065] All primers, probes, and in vitro transcribed RNA products mentioned in this invention were synthesized using existing techniques.

[0066] Example 1: Optimization of a biomarker for detecting prostate cancer based on the principle of digital microdroplet RNA amplification detection.

[0067] In this embodiment, based on the digital microdroplet RNA amplification detection system for prostate cancer based on absolute quantitative detection of the PCA3 gene disclosed in Reference 1 (which, after clinical sample validation, has a sensitivity of 92.77% and a negative predictive value of 90.5%), to further improve its detection and diagnostic efficacy, specifically to further reduce the false negative rate of prostate cancer-positive patients and improve the sensitivity and negative predictive value for prostate cancer detection, the inventors further selected a large number of biomarkers that may be related to prostate cancer detection (e.g., DLX1, SChLAP1, TDRD1, TTTY15-USP9Y, SPON2, PCAT14, OR51E2, ERG, RPL7P16, PIP5K1A, CCND1, GSTP1, CST1, CST3, CST4, HOXC6, HOXC4, CCNA1, LMTK2, ... Biomarkers that can be used in conjunction with the digital microdroplet RNA amplification detection system for prostate cancer based on absolute quantification of the PCA3 gene in the above-mentioned literature 1 were screened from MYO6, HPN, CDK1, PSCA, PTEN, GOLM1, PMP22, EZH2, FGFR1, FN1, VEGFA, TMPRSS2, ANXA3, CRISP3, BIRC5, AMACR, HIF1A, KLK3, KLK2, MSMB, FLT1, MMP9, AR, TERT, PGC, SPINK1, STAT3, STAT5, TFF3, RELA, NDUFB4, EHD3, PFKL, RAN, ACSM1, PLXNA1, ID1, APC, RASSF1, PCDH9, SPOP, ARV7, PSMA, etc., to further optimize the detection and diagnostic results of the system. It has been found that the combined use of ARV7, PSMA, ERG, HOXC6, HOXC4, DLX1, TDRD1, AMACR, MALAT1 genes and PCA3 gene (using SPDEF as an internal reference gene) can yield relatively good diagnostic results. This will be detailed below.

[0068] In this embodiment, the level of the PCA3 gene in the urine sample to be tested is first absolutely quantitatively detected based on the digital microdroplet RNA amplification detection technology disclosed in Reference 1, and SPDEF is also absolutely quantitatively detected as an internal reference gene. The specific steps are as follows:

[0069] 1.1 Collection of test samples (random pre-urine sample from the test subject)

[0070] 50 mL of random pre-void urine was collected from 118 subjects undergoing menstrual blood PSA testing (including 42 positive and 76 negative prostate cancer cases). The sample was mixed with sample preservation solution (containing a high concentration of detergent, a commercially available product from Shanghai Rendu Biotechnology Co., Ltd.) at a 1:1 ratio, and stored at -70℃ as the test sample.

[0071] 1.2 Sample Preparation

[0072] Take 6 mL of PCA3 and SPDEF gene positive control (prepared in Example 1 of Literature 1 above) (one tube for each gene), 6 mL of negative control (sample preservation solution) (one tube for each gene), and 6 mL of test sample (nine tubes for each test subject) and place them into sample processing tubes, for a total of 1066 tubes (2 tubes for positive control, 2 tubes for negative control, and 1062 tubes for test sample) for testing.

[0073] 1.3 Nucleic acid extraction

[0074] For each sample processing tube available in section 1.2, perform the following operations:

[0075] (1) Add 1.5 mL of nucleic acid extraction buffer to the sample processing tube: HEPES 500 mM, LLS 8%, specific capture probe corresponding to the detection gene 25 μM, and magnetic beads 150 mg / L. Add the sample to be tested / positive control / negative control and mix well. Incubate at 60℃ for 10 minutes, then let stand at room temperature for 10 minutes.

[0076] (2) Place the sample processing tube on the magnetic bead separation device and let it stand for 10 minutes. After the magnetic beads are adsorbed onto the tube wall, keep the sample processing tube on the magnetic bead separation device, discard the liquid, and keep the magnetic beads. Add 1 mL of washing buffer (HEPES 25 mM, NaCl 150 mM, 1% SDS, EDTA 2.5 mM), shake well, and let it stand for 2-5 minutes. Discard the liquid and keep the magnetic beads. Then add 800 μL of washing buffer, shake well, and let it stand for 2-5 minutes. Discard the liquid and keep the magnetic beads.

[0077] (3) Remove the sample processing tube from the magnetic bead separation device. The tube contains magnetic bead-nucleic acid complex. Add 100 μl of DEPC water to wash it off. After repeated mixing, keep the tube containing magnetic bead-nucleic acid complex at 60°C for 10 minutes. Place it on the magnetic bead separation device and aspirate it for 3 minutes. Take all the elution solution and put it into a 1.5 mL centrifuge tube without nuclease for later use.

[0078] 1.4 Detection of RNA amplification from digital microdroplets

[0079] For each sample processing tube available in section 1.3, perform the following operations:

[0080] (1) Turn on and debug the Zhenzhun Biochip Digital PCR System (including sample pretreatment system, PCR amplification instrument, and biochip reader), and place the corresponding consumables (chip, cap, scraper (single row), and sealing oil).

[0081] (2) Add 15 μL of detection solution to the 1.5 ml centrifuge tube prepared in 1.3: Tris 15 mM, MgCl2 15 mM, dNTP 2.5 mM, NTP 3 mM, PVP40 1%, KCl 10 mM, the first primer corresponding to the detection gene 10 pmol / mL, the second primer 10 pmol / mL, the target detection probe corresponding to the detection gene 10 pmol / mL, and HEX dye 10 pmol / mL. Add 17 μL of the elution buffer from 1.3(3) and mix thoroughly.

[0082] (3) Heat the thoroughly mixed solution from (2) in a 60°C device for 10 minutes and incubate at 42°C for 5 minutes. Immediately add 10 μL of SAT enzyme solution (preheated at 42°C beforehand, containing M-MLV reverse transcriptase 60000 U / mL, T7 RNA polymerase 40000 U / mL, 10 mM HEPES pH 7.5, 15 mM N-acetyl-L-cysteine, 0.15 mM zinc acetate, 20 mM trehalose, 100 mM Tris-HCl pH 8.0, 80 mM KCl, 0.25 mM EDTA, 0.5% (v / v) Triton X-100 and 30% (v / v) glycerol), and quickly and thoroughly shake to mix. Take 20 μL of the mixture and add it to a scraper (single row). Immediately start the sample pretreatment system to prepare the chip.

[0083] (4) Place the prepared chip in a PCR amplification instrument and react at 42°C for 40 minutes. Place the amplified chip in a biochip reader, selecting the FAM channel for fluorescence and the HEX channel for reference.

[0084] The specific capture probes, first primers, second primers, and target detection probes for each gene (PCA3 and SPDEF) involved in steps 1.3 and 1.4 above are the primers and probes of group 1 determined in Example 2 of the above-mentioned literature 1.

[0085] 1.5 Result Judgment

[0086] 1.5.1 Determination of positive and negative controls

[0087] Readings were taken from the positive control and corresponding negative control chips of PCA3 and SPDEF. If the positive control was within the quantitative range (±25% accuracy) and the negative control had no quantitative value, it indicates that the quality control product passed the test and the sample can be tested.

[0088] 1.5.2 Determination of each detection gene in the sample to be tested

[0089] The quantitative values ​​of PCA3 and SPDEF in the test samples were read separately, and the PCA3 gene score was calculated using SPDEF as an internal reference gene (calculation method shown below) for the detection and diagnosis of prostate cancer. PCA3 score = PCA3 copy number / SPDEF copy number * 1000.

[0090] The above calculation results were statistically analyzed using SPSS (version 21.0). The clinical gold standard prostate biopsy results and the PCA3 gene scores were used to evaluate the sensitivity, specificity, negative predictive value, positive predictive value, and accuracy of the combined PCA3 gene score using receiver operating characteristic (ROC) curves to determine the final cutoff value. The cutoff value can be used as a diagnostic value for prostate cancer patients.

[0091] in:

[0092] Sensitivity (SE) = Number of cancer patients with values ​​above the cutoff value / Number of patients in the sample;

[0093] Specificity (SP) = Number of cancer patients with values ​​below the cutoff value / Number of control samples;

[0094] Positive predictive value (PPV) = Number of cancer patients with values ​​higher than the cutoff value / Total number of all patients with values ​​higher than the cutoff value;

[0095] Negative predictive value (NPV) = Number of cancer patients whose values ​​are below the cutoff value / Total number of all patients whose values ​​are below the cutoff value;

[0096] Accuracy = (Number of true positive samples + Number of true negative samples) / Total number of samples.

[0097] The correlation analysis results between the clinical gold standard prostate biopsy results and the PCA3 score results are shown in Table 1 below. The final determined cutoff value of the PCA3 score for the diagnosis of prostate cancer is 114.2 (a PCA3 score greater than 114.2 represents a positive sample, and a PCA3 score less than or equal to 114.2 represents a negative sample). That is, when the cutoff is 114.2, the PCA3 score has a sensitivity of 90.48%, a specificity of 69.74%, a positive predictive value of 62.3%, a negative predictive value of 93%, and an area under the AUC curve of 0.831 (as shown in Table 2 below).

[0098] Table 1: Correlation between clinical gold standard prostate biopsy results and PCA3 score results

[0099] Table 2: Correlation analysis results of PCA3 score for prostate cancer diagnosis

[0100] Based on the results in Tables 1 and 2 above, it can be seen that, according to the method disclosed in Reference 1, in the diagnosis of 118 patients based solely on the PCA3 gene, 61 cases were PCA3 positive (for these patients, a biopsy is recommended, requiring clinicians to combine other diagnostic indicators to determine whether the patient has prostate cancer), and 57 cases were negative. Among the 57 patients with negative results, prostate biopsy pathology results showed that 53 cases were true negative, and 4 cases were prostate cancer positive. Therefore, using the PCA3 single gene for diagnosis would result in the missed detection of 4 prostate cancer patients.

[0101] To reduce the number of false negatives in the prostate cancer detection system based on the PCA3 gene disclosed in Reference 1, this embodiment further performed secondary detection using the ARV7, PSMA, ERG, HOXC6, HOXC4, DLX1, TDRD1, AMACR, and MALAT1 genes in the 57 subjects who tested negative using the PCA3 gene. The specific detection methods are as described in 1.1-1.5 above (wherein the specific capture probes, first primer, second primer, and target detection probes for ARV7 and PSMA detection are...). The sequence information is shown in Table 3 below. The specific capture probes, first primers, second primers, and target detection probes used for the ERG, HOXC6, HOXC4, DLX1, TDRD1, AMACR, and MALAT1 genes are shown in Table 1 of patent document CN115851926A (also referred to as document 2 in this paper). The ARV7 score, PSMA score, ERG score, HOXC6 score, HOXC4 score, DLX1 score, TDRD1 score, AMACR score, and MALAT1 score were obtained respectively. The scoring methods are as follows: ARV7 score = ARV7 copy number / SPDEF copy number * 1000; PSMA score = PSMA copy number / SPDEF copy number * 1000; AMACR score = AMACR copy number / SPDEF copy number * 1000; ERG score = ERG copy number / SPDEF copy number * 1000; MALAT1 score = MALAT1 copy number / SPDEF copy number * 1000; TDRD1 score = DRD1 copy number / SPDEF copy number * 1000; HOXC6 score = HOXC6 copy number / SPDEF copy number * 1000; HOXC4 score = HOXC4 copy number / SPDEF copy number * 1000; DLX1 score = DLX1 copy number / SPDEF copy number * 1000. If the second test result is negative, a negative result is output. If the second test result is positive, a positive result is output. The results are shown in Table 4 below, illustrating the results of combining nine other genes to compensate for missed diagnoses based on a negative result for the PCA3 gene. The correlation analysis results of the nine genes combined with PCA3 for prostate cancer diagnosis, based on the output of Table 4, are shown in Table 5 below.

[0102] Table 3: Primer and probe sequence information for ARV7 and PSMA detection

[0103] Table 4: Results of compensating for missed diagnoses by combining the results of PCA3 gene negative detection with those of the other 9 genes.

[0104] Note: The results of the number of missed diagnoses and misdiagnoses in Table 4 above were obtained under the condition of the cutoff value at the optimal Youden index for each target gene. If the cutoff value is adjusted downward in order to forcibly increase the number of missed diagnoses, it will lead to a further increase in the number of misdiagnoses, thereby significantly increasing the false positive rate (which will lead to too many false positive patients undergoing unnecessary puncture biopsies). On the other hand, in patients with positive PCA3 missed diagnoses, a certain target gene may not be detectable (i.e., the score for that target gene is 0). Therefore, even if the cutoff value is adjusted downward, it may not help to increase the number of missed diagnoses. Therefore, adjusting the cutoff value downward from the optimal value in order to forcibly increase the number of missed diagnoses is meaningless for clinical testing.

[0105] Table 5: Correlation analysis results of the nine genes combined with PCA3 for the diagnosis of prostate cancer.

[0106] As shown in Tables 4 and 5 above, among the 57 negative cases identified based on the PCA3 gene, after secondary testing of this population using combined ARV7, PSMA, ERG, HOXC6, DLX1, HOXC4, MALAT1, TDRD1, and AMACR genes, at the optimal cutoff value, the combination of PSMA, ERG, MALAT1, TDRD1, and AMACR did not compensate for the number of missed cases. While the combination of ARV7, HOXC6, DLX1, and HOXC4 could compensate for some missed cases, it only compensated for a maximum of 2 / 4 (i.e., 50%), indicating a limited ability to compensate for missed cases. These results suggest that although existing technologies have disclosed the combination of PCA3 and PSMA (e.g., "Effective diagnosis of prostate cancer based on mRNAs from urinary exosomes," J Gan et al., Frontiers in...), this approach is not feasible. The combination of PCA3 and ERG (e.g., Reference 3 or Patent Document CN113528660A, also referred to as Reference 4 in this article) has shown good efficacy in the diagnosis of prostate cancer, for example, it has high accuracy and an AUC value exceeding 0.85. However, in the detection system of this invention (digital microdroplet RNA amplification detection system based on the principle of real-time fluorescence nucleic acid isothermal amplification), the parallel detection of PCA3 and PSMA (with SPDEF as an internal control) or PCA3 and ERG (with SPDEF as an internal control) does not necessarily compensate for the number of people missed by PCA3. As can be seen from the results in Table 4 above, the combination of PCA3 and PSMA or PCA3 and ERG does not compensate for the number of people missed. Only when PCA3 and ARV7 or PCA3 and HOXC6 are combined can at most 2 / 4 of the number of people missed be compensated.

[0107] Furthermore, given that Reference 4 has disclosed that combining PCA3 and ERG with a real-time quantitative PCR detection system can improve the accuracy of prostate cancer diagnosis, and that Patent Document US20090170075A1 (also referred to as Reference 5 in this paper) has disclosed that combining ERG (actually ERG1) and PCA3 (also referred to as DD3 in Reference 5) with a real-time QRT-PCR detection system can improve the detection capability of prostate cancer, in order to determine whether these PCR detection primers and probes are also suitable for detection systems based on the principle of real-time fluorescence nucleic acid isothermal amplification to improve the detection capability of prostate cancer, the inventors, based on Reference 4 and Reference 5... 5. PCR primers and probes targeting ERG were designed based on the principle of real-time fluorescence nucleic acid isothermal amplification (sequence information is shown in Table 6 below, where group 1 is the primer and probe combination for ERG designed based on reference 4, and group 2 is the primer and probe combination for ERG designed based on reference 5). Following the detection methods described in 1.1-1.5 above, the primer and probe combinations for ERG targeting groups 1 and 2 were used to perform a secondary test on the subjects (i.e., 57 cases) who were negative using the PCA3 gene assay, obtaining ERG (group 1) scores and ERG (group 2) scores respectively. The scoring method is as follows: ERG (group 1) score = ERG (group 1) copy number / SPDEF copy number * 1000; ERG (group 2) score = ERG (group 2) copy number / SPDEF copy number * 1000. If the secondary test result is negative, a negative result is output. If the secondary test result is positive, a positive result is output. The results are shown in Table 7 below, which illustrates the results of combining ERG gene (groups 1 and 2) with PCA3 gene to compensate for the number of missed cases, based on the negative result of PCA3 gene.

[0108] Table 6: Primers and probes for real-time fluorescent nucleic acid isothermal amplification targeting ERG designed based on References 4 and 5, respectively.

[0109] Table 7: Results of compensating for missed cases when combining ERG gene testing with PCA3 gene negative results

[0110] As shown in Table 7, although the PCA3+ERG combination based on PCR detection principles disclosed in References 4 and 5 can improve the accuracy or detection capability of prostate cancer, the PCR primers and probes disclosed in these references, when used in a detection system based on real-time fluorescence isothermal amplification, cannot effectively compensate for the number of cases missed by PCA3. At the optimal cutoff value, only the primer and probe combination of group 2 can compensate for 1 case of missed PCA3, while the primer and probe combination of group 1 cannot compensate for any missed PCA3 cases. Furthermore, adjusting the cutoff value of group 1 to 15.36 still cannot compensate for the number of missed PCA3 positive cases; adjusting the cutoff value of group 2 to 10.21 can compensate for 2 cases of missed PCA3, but at the same time, it will increase the number of false positives to 48. Therefore, even adjusting the cutoff value of ERG may not further increase the number of cases compensated for, and even if it does increase the number of cases compensated for, it may also lead to an excessive number of false positives, which is meaningless for clinical testing.

[0111] Based on the above results, the inventors speculate that the cause may be related to the primer and probe combinations used for ARV7, PSMA, ERG, HOXC6, DLX1, HOXC4, MALAT1, TDRD1, and AMACR based on the principle of real-time fluorescence isothermal amplification detection. In view of this, the inventors designed multiple sets (specifically 4 sets) of primer and probe combinations for ARV7, PSMA, ERG, HOXC6, DLX1, HOXC4, MALAT1, TDRD1, and AMACR, respectively. These were then used to retest 57 individuals who tested negative using the PCA3 gene assay, following steps 1.1-1.5 above. However, under optimal cutoff values ​​for each target gene, only the new primer and probe combination designed for ERG could significantly compensate for the number of individuals missed by PCA3 (compensating for 3 / 4 (75%)) without causing too many false positives. The newly designed primer and probe combinations for the other 8 genes could not effectively compensate for the number of individuals missed by PCA3 (the highest compensation was only 2 / 4 (50%)), and the number of false positives was relatively high (over 33 individuals). The following only describes the optimization design and validation process of the primer and probe combination for ERG.

[0112] (1) The inventors replaced the specific capture probe in the original primer and probe set (i.e., the primer and probe combination for ERG disclosed in Table 1 of Reference 2, as the original set) with a new ERG-specific capture probe (its nucleotide sequence is: TGATCTCCTGGGGGGCTCATATGGTAAATTTTAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAA (SEQ ID NO: 17)). This new combination (as group 3) was formed by combining the first primer, the second primer, and the target detection probe in the original set. Using the primers and probes of group 3, the subjects who were negative for PCA3 gene detection (i.e., 57 cases) were retested according to the above steps 1.1-1.5. The results are shown in Table 8 below. It can be seen that after replacing the specific capture probe, under the condition of the optimal cutoff value of 20.23, 1 / 4 of the PCA3 missed detections can be compensated (if the cutoff value of ERG is adjusted to 10.15, 2 / 4 of the missed detections can be compensated, but the number of false diagnoses will increase to 49).

[0113] Table 8: Results of mitigation of missed cases when combined with ERG gene (group 3 primers and probes) on the basis of PCA3 gene negative result.

[0114] (2) Based on group 3, the inventors further replaced the target detection probe in the original group with a new ERG target detection probe (its nucleotide sequence is: CCCCAGCGUCCUCAGUUAGAUGGGG (SEQ ID NO: 18)), and formed a new combination with the first and second primers in the original group (as group 4). Using the primers and probes of group 4, the subjects who were negative for PCA3 gene detection (i.e., 57 cases) were retested according to the above steps 1.1-1.5. The results are shown in Table 9 below. It can be seen that after replacing the specific capture probe and the target detection probe, under the condition of the optimal cutoff value of 25.66, 2 / 4 of the PCA3 missed detections can be made up (if the cutoff value of ERG is adjusted to 12.57, the number of missed detections cannot be further increased, and the number of false diagnoses will increase to 46).

[0115] Table 9: Results of mitigation of missed cases when combined with ERG gene (group 4 primers and probes) on the basis of PCA3 gene negative result.

[0116] (3) Based on group 4, the inventors further replaced the first primer in the original group with a new first primer targeting ERG (its nucleotide sequence is: AAGCGTGCTCAACCATCTCCTTCCAC (SEQ ID NO: 19)), and combined it with the second primer in the original group to form a new combination (as group 5). Using the primers and probes of group 5, a second test was performed on the subjects (i.e., 57 cases) who were negative for PCA3 gene detection, following the steps 1.1-1.5 above. The results are shown in Table 10 below. It can be seen that after replacing the specific capture probe, the target detection probe, and the first primer, under the condition of an optimal cutoff value of 39.10, 3 / 4 of the PCA3 missed detections can be made up, and the number of false diagnoses is relatively low. In this experiment, the correlation between combined PCA3 and ERG in the diagnosis of prostate cancer was also analyzed, and the analysis results are shown in Table 11 below.

[0117] Table 10: Results of mitigation of missed cases when combined with ERG gene (group 5 primers and probe) on the basis of PCA3 gene negative result

[0118] Table 11: Correlation analysis results of combined PCA3 and ERG (group 5) in the diagnosis of prostate cancer

[0119] (4) Based on group 5, the inventors further replaced the second primer in the original group (the nucleotide sequence of which is: AATTTTAATACGACTCACTATAGGGAGAGGTCCAACCTGGATTTGCAAGGCGG (SEQ ID NO:20)) with a new second primer targeting ERG (the nucleotide sequence of which is: AATTTTAATACGACTCACTATAGGGAGACAAGGCGGCTACTTGTTGGTCCAAG (SEQ ID NO:21)) to form a new combination (as group 6). Using the primers and probes of group 6, the subjects who were negative for PCA3 gene detection (i.e., 57 cases) were retested according to the above steps 1.1-1.5. The results are shown in Table 12 below. It can be seen that after replacing the specific capture probe, the target detection probe, the first primer and the second primer, under the condition of the optimal cutoff value of 42.45, only 1 / 4 of the PCA3 missed detections can be compensated (if the cutoff value of ERG is adjusted to 21.24, only 2 / 4 of the missed detections can be compensated, and the number of false positives will increase to 48).

[0120] Table 12: Results of mitigation of missed cases when combined with ERG gene (group 6 primers and probe) on the basis of PCA3 gene negative result

[0121] (5) Based on group 5, the inventors replaced the new specific capture probe (SEQ ID NO: 17) with the specific capture probe from the original group (its nucleotide sequence is: AGGAGGAACTGCCAAAGCTTTTAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAA (SEQ ID NO: 22)) to form a new combination (as group 7). Using the primers and probes of group 7, a second test was performed on the subjects (i.e., 57 cases) who were negative for PCA3 gene detection, according to the above steps 1.1-1.5. The results are shown in Table 13 below. It can be seen that after replacing the specific capture probe, the target detection probe, the first primer and the second primer, under the condition of the optimal cutoff value of 31.66, only 2 / 4 of the PCA3 missed detections can be compensated (if the cutoff value of ERG is adjusted to 15.26, the number of missed detections cannot be further increased, and the number of false diagnoses will also increase to 47).

[0122] Table 13: Results of mitigation of missed cases when combined with ERG gene (group 7 primers and probes) on the basis of PCA3 gene negative result

[0123] In summary, the results of (1)-(5) show that, compared with the primer and probe combinations of groups 3, 4, and 6-7, the primer and probe combination of group 5 has a better effect in making up for the number of PCA3 missed cases. It can make up for 3 / 4 (75%) of the PCA3 missed cases and the number of misdiagnoses is relatively low. In contrast, the other three groups can only make up for 2 / 4 (50%) of the PCA3 missed cases at most (even if the cutoff value of ERG is adjusted, it may not further increase the number of missed cases made up) and the number of misdiagnoses is too high.

[0124] To further determine whether the effect of ERG in compensating for the number of missed cases in PCA3 is related to the detection sensitivity of the primer and probe combination, the inventors further tested the detection sensitivity of the primer and probe combinations in groups 5, 7, and the original group. Specifically, the primers and probes in groups 5, 7, and the original group were used to perform digital microdroplet RNA amplification detection on positive standards of the ERG gene (concentrations of 200 copies / reaction, 100 copies / reaction, 10 copies / reaction, and 1 copy / reaction, respectively, prepared from the ERG standard prepared in Example 1 of Reference 2) and negative controls, as described in sections 1.3 and 1.4 above. The results are shown in Table 14 below. It can be seen that there is no difference in the detection sensitivity of the primers and probes of group 5 and the original group against positive standards with a concentration of 1-200 copies / reaction, both of which are higher than the detection sensitivity of the primer and probe combination of group 7. These results indicate that the primer and probe combination of group 5 can make up for more of the number of missed cases of PCA3 and has fewer false diagnoses compared to the primer and probe combination of the original group and group 7. This may be related to the detection sensitivity of the primer and probe combination, as well as the position and length of primer amplification (which affects primer amplification efficiency), and the capture ability and efficiency of specific capture probes.

[0125] Table 14: Sensitivity detection results of primers and probes for ERG gene positive standards in groups 5, 7, and the original group.

[0126] In summary, the results indicate that compared to the detection efficacy of PCA3 combined with ARV7, PSMA, HOXC6, DLX1, HOXC4, MALAT1, TDRD1, or AMACR for prostate cancer (which at most compensates for 2 / 4 (50%) of the missed cases by PCA3), PCA3 combined with the ERG gene (with the primer and probe combination used for detecting the ERG gene being group 5 (i.e., the nucleotide sequences of the specific capture probe, first primer, second primer, and target detection probe for detecting ERG are shown in SEQ ID NO:17, SEQ ID NO:19, SEQ ID NO:21, and SEQ ID NO:18, respectively) and the primer and probe combination used for detecting the PCA3 gene and the internal reference gene SPDEF being the primer and probe combination in group 1 determined in Example 2 of Reference 1, specifically, the nucleotide sequences of the specific capture probe, first primer, second primer, and target detection probe for detecting PCA3 are shown in SEQ ID NO:17, SEQ ID NO:19, SEQ ID NO:21, and SEQ ID NO:18, respectively) are as follows: As shown in NO:23-26, the nucleotide sequences of the specific capture probe, first primer, second primer and target detection probe for detecting SPDEF are shown in SEQ ID NO:27-30. The detection effect is the most outstanding. It can make up for the missed detection of 3 positive patients (3 / 4 (75%)) based on PCA3 gene. The detection sensitivity and negative predictive value are significantly improved. The specificity and positive predictive value of the overall diagnostic effect are only slightly reduced, and the accuracy is not significantly reduced (i.e. the number of misdiagnosed cases is relatively small).

[0127] In summary, combining the PCA3 and ERG genes, and using a real-time fluorescence nucleic acid isothermal amplification method (which uses primers and probes specifically targeting PCA3 and ERG) and a digital PCR system, can achieve better results in the detection and diagnosis of prostate cancer, with a sensitivity of 97.6% and a negative predictive value of 97.7%. This can significantly reduce the risk of missed detection of prostate cancer while minimizing misdiagnosis. It can provide clinicians with a basis for prostate cancer diagnosis, thus assisting in the clinical diagnosis of prostate cancer. Therefore, this invention provides a digital microdroplet RNA amplification detection system or kit to reduce the missed detection rate of prostate cancer. Based on the detection system disclosed in Reference 1, it further includes reagents for detecting the biomarker gene ERG based on the real-time fluorescence nucleic acid isothermal amplification detection principle (which includes a specific capture probe for detecting ERG, a first primer, a second primer, and a target detection probe, with nucleotide sequences as shown in SEQ ID NO:17, SEQ ID NO:19, SEQ ID NO:21, and SEQ ID NO:18, respectively). This also provides a method for reducing the missed detection rate of prostate cancer, which may include the following steps:

[0128] M1) A digital PCR system using reagents based on the real-time fluorescence nucleic acid isothermal amplification detection principle to detect the biomarker genes PCA3 and SPDEF can be used to distinguish, for example, urine samples from a population into prostate cancer-negative and prostate cancer-positive samples. Specifically, absolute quantification of PCA3 and SPDEF gene expression in the samples is performed, with SPDEF gene used as an internal control. A PCA3 score is calculated based on the absolute quantification results of PCA3 and SPDEF gene expression, and the samples are distinguished into prostate cancer-negative and prostate cancer-positive samples based on this PCA3 score. A sample with a PCA3 score greater than 114.2 is considered a prostate cancer-positive sample, and a sample with a PCA3 score less than or equal to 114.2 is considered a prostate cancer-negative sample. The PCA3 score is calculated as: PCA3 score = PCA3 copy number / SPDEF copy number * 1000.

[0129] M2) Using a reagent based on the real-time fluorescence nucleic acid isothermal amplification detection principle to detect the biomarker gene ERG, combined with a digital PCR system, the first prostate cancer negative sample obtained in step M1) is further classified into a second prostate cancer negative sample and a second prostate cancer positive sample. Specifically, the expression of the ERG gene in the first prostate cancer negative sample obtained in step M1) is absolutely quantified, with the SPDEF gene used as an internal reference. An ERG score is calculated based on the absolute quantification results of ERG gene expression and the absolute quantification results of SPDEF gene expression in the corresponding sample obtained in step M1). Based on this ERG score, the first prostate cancer negative sample obtained in step M1) is further classified into a second prostate cancer negative sample and a second prostate cancer positive sample. Specifically, a sample with an ERG score greater than 39.1 is considered a second prostate cancer positive sample, and a sample with an ERG score less than or equal to 39.1 is considered a second prostate cancer negative sample. The ERG score is calculated as: ERG score = ERG copy number / SPDEF copy number * 1000.

[0130] M3) Combine the second prostate cancer positive sample obtained in step M2) with the first prostate cancer positive sample obtained in step M1) as the final prostate cancer positive sample (the subjects corresponding to these positive samples are recommended to undergo puncture biopsy, and clinicians need to combine other diagnostic indicators to determine whether the patient has prostate cancer), so as to reduce the rate of missed prostate cancer detection.

[0131] As can be seen from the results and descriptions of the above embodiments, firstly, using a reagent combined with a digital PCR system to detect the biomarker genes PCA3 and SPDEF based on the principle of real-time fluorescence nucleic acid isothermal amplification detection to determine the prostate cancer positivity or positivity of the sample, and then using a reagent combined with a digital PCR system to detect the biomarker genes ERG and SPDEF based on the principle of real-time fluorescence nucleic acid isothermal amplification detection to determine the prostate cancer positivity or positivity again for the negative samples, can reduce the false negative rate of prostate cancer and improve the prostate cancer detection and diagnosis effect. However, when using a digital PCR system to simultaneously detect biomarker genes PCA3, ERG, and SPDEF (as an internal reference gene) based on the principle of real-time fluorescence nucleic acid isothermal amplification, or to simultaneously use a digital PCR system to detect biomarker genes PCA3, ERG, SPDEF, and PSA (as an internal reference gene, namely KLK3 in reference 2, whose detection primer and probe sequences are shown in Table 1 of reference 2) to detect prostate cancer in samples (specific detection methods can be found in 1.1-1.5 above), and evaluating the detection and diagnostic efficacy using the logistic regression method for combining multiple biomarker genes disclosed in reference 2, The diagnostic efficacy of this method for prostate cancer is not ideal, as shown in Tables 15 and 16 below. The logistic regression score for combining PCA3, ERG, and SPDEF is calculated as follows: PCA3 score = 0.006 * PCA3 score + 0.002 * ERG score; PCA3 score = 0.035 * new PCA3 score + 0.044 * new ERG score + 0.009 * new SPDEF score (PCA3 new score = PCA3 quantitative value / PSA quantitative value) * 1000; ERG new score = (ERG quantitative value / PSA quantitative value) * 1000; SPDEF new score = (SPDEF quantitative value / PSA quantitative value) * 1000). As clearly shown in Table 15, compared to the diagnostic efficacy of PCA3 alone (as shown in Table 2), the regression diagnostic efficacy of PCA3 combined with ERG is lower, and it does not reduce the false negative rate of prostate cancer. As clearly shown in Table 16, when PSA is used as an internal reference gene, the overall diagnostic effectiveness of the logistic regression model is significantly reduced, and it does not reduce the false negative rate of prostate cancer. Therefore, using logistic regression alone will not improve the diagnostic effect; on the contrary, it will reduce the diagnostic capability.

[0132] Table 15: Diagnostic efficacy of a model combining PCA3 and ERG genes for prostate cancer diagnosis

[0133] Table 16: Diagnostic efficacy of a model combining PCA3, ERG, and SPDEF genes for prostate cancer diagnosis.

[0134] Example 2: Digital microdroplet RNA amplification detection system for prostate cancer

[0135] Based on the results of Example 1 above, it is evident that the combined model of PCA3 and ERG (where SPDEF is used as an internal control for detection, and the nucleotide sequences of the specific capture probe, first primer, second primer, and target detection probe for ERG detection are shown in SEQ ID NO:17, SEQ ID NO:19, SEQ ID NO:21, and SEQ ID NO:18, respectively) exhibits high sensitivity and negative predictive value in the digital microdroplet RNA amplification detection system. Furthermore, it can reduce the false negative rate of prostate cancer while minimizing misdiagnosis. Moreover, when using these two biomarkers (PCA3 and ERG) in combination to detect prostate cancer, urine (e.g., random pre-micturition urine) can be used as the test sample, eliminating the need for prostate biopsy, thus facilitating large-scale population screening. Based on this, this embodiment provides a digital microdroplet RNA amplification detection system for prostate cancer based on real-time fluorescence nucleic acid isothermal amplification detection and digital PCR quantitative detection systems, which may include:

[0136] (2.1) Reagents for the specific detection of the following genes respectively based on the real-time fluorescence nucleic acid isothermal amplification method: PCA3, ERG and SPDEF, wherein the SPDEF gene is used as an internal reference gene for detection, and a digital PCR system (e.g., a chip-based digital PCR system) for the absolute quantification of the above genes.

[0137] Specifically, the specific detection reagents for each of the above genes include those corresponding to that gene:

[0138] (1) Nucleic acid extraction solution: which contains a solid support containing a specific capture probe for capturing gene sequences;

[0139] (2) Amplification detection solution: It contains a first primer, a second primer and a target detection probe, wherein the first primer works in conjunction with the first primer to amplify the target sequence in the gene sequence, and the target detection probe specifically binds to the RNA copy of the amplification product of the target;

[0140] It may also include:

[0141] (3) SAT enzyme solution: It contains at least one RNA polymerase and M-MLV reverse transcriptase.

[0142] More specifically, the nucleotide sequences of the specific capture probe, first primer, second primer, and target detection probe for the specific detection of the PCA3 gene are shown in SEQ ID NO:23-26, the nucleotide sequences of the specific capture probe, first primer, second primer, and target detection probe for the specific detection of the ERG gene are shown in SEQ ID NO:17, 19, 21, and 18, respectively, and the nucleotide sequences of the specific capture probe, first primer, second primer, and target detection probe for the specific detection of the SPDEF gene are shown in SEQ ID NO:27-30, respectively, and the target detection probe carries a fluorescent reporter group and a quencher group at both ends of its nucleotide sequence.

[0143] More specifically, the specific detection reagents for each of the above genes provided in this embodiment include:

[0144] (1) Nucleic acid extraction solution, the components of which include: 250-800mM HEPES, 4-10% lithium dodecyl sulfate, 1-50μM of the specific capture probe, and 50-500mg / L magnetic beads;

[0145] (2) Amplification detection solution, the components of which include: 10-50mM Tris, 5-40mM KCl, 10-40mM MgCl2, 1-20mM NTP, 0.1-10mM dNTPs, 1-10% PVP40, the first primer described above at 10-250pmol / mL, the second primer described above at 10-250pmol / mL, and the target detection probe described above at 10-250pmol / mL;

[0146] (3) SAT enzyme solution, the components of which include: 16000-160000U / mL M-MLV reverse transcriptase, 8000-80000U / mL RNA polymerase, 2-10mM HEPES pH7.5, 10-100mM N-acetyl-L-cysteine, 0.04-0.4mM zinc acetate, 10-100mM trehalose, 40-200mM Tris-HCl pH 8.0, 40-200mM KCl, 0.01-0.5mM EDTA, 0.1-1% (v / v) Triton X-100 and 20-50% (v / v) glycerol.

[0147] For ease of detection and / or accuracy, the digital microdroplet RNA amplification detection system provided in this embodiment further includes one or more of the following components (2.2)-(2.5):

[0148] (2.2) Washing solution: It contains NaCl and SDS, and optionally contains 5-50mM HEPES, 50-500mM NaCl, 0.5-1.5% SDS and 1-10mM EDTA.

[0149] (2.3) Positive control: It contains three systems of in vitro transcribed RNA containing the following gene nucleic acids respectively: PCA3, ERG and SPDEF, as prepared in Example 1 of Reference 2 above.

[0150] (2.4) Negative control: A system that does not contain any of the following gene nucleic acids: PCA3, ERG and SPDEF, such as deionized water or sample preservation solution (which contains high concentrations of detergent and physiological saline).

[0151] (2.5) Instruction Manual

[0152] When using the digital microdroplet RNA amplification detection system provided in this embodiment to detect clinical urine samples, the following steps are included:

[0153] N1) A digital PCR system using reagents based on the real-time fluorescence nucleic acid isothermal amplification detection principle to detect the biomarker genes PCA3 and SPDEF distinguishes samples into prostate cancer-negative and prostate cancer-positive samples. Specifically, absolute quantification of PCA3 and SPDEF gene expression in the samples is performed, with SPDEF gene used as an internal control. A PCA3 score is calculated based on the absolute quantification results of PCA3 and SPDEF gene expression, and the samples are distinguished into prostate cancer-negative and prostate cancer-positive samples based on this PCA3 score. A sample with a PCA3 score greater than 114.2 is considered a prostate cancer-positive sample, and a sample with a PCA3 score less than or equal to 114.2 is considered a prostate cancer-negative sample. The PCA3 score is calculated as: PCA3 score = PCA3 copy number / SPDEF copy number * 1000.

[0154] N2) Using a reagent based on the real-time fluorescence nucleic acid isothermal amplification detection principle to detect the biomarker gene ERG, combined with a digital PCR system, the first prostate cancer negative sample obtained in step N1) is further classified into a second prostate cancer negative sample and a second prostate cancer positive sample. Specifically, the absolute quantitative detection of ERG gene expression in the first prostate cancer negative sample obtained in step N1) is performed, with the SPDEF gene as an internal reference. An ERG score is calculated based on the absolute quantitative results of ERG gene expression and the absolute quantitative results of SPDEF gene expression in the corresponding sample obtained in step N1). Based on this ERG score, the first prostate cancer negative sample obtained in step N1) is further classified into a second prostate cancer negative sample and a second prostate cancer positive sample. A sample with an ERG score greater than 39.1 is considered a second prostate cancer positive sample, and a sample with an ERG score less than or equal to 39.1 is considered a second prostate cancer negative sample. The ERG score is calculated as: ERG score = ERG copy number / SPDEF copy number * 1000.

[0155] N3) Combine the second prostate cancer positive sample obtained in step N2) and the first prostate cancer positive sample obtained in step N1) as the final prostate cancer positive sample, and take the second prostate cancer negative sample obtained in step N2) as the final prostate cancer negative sample.

[0156] Example 3: A digital microdroplet RNA amplification detection system or kit for reducing the false negative rate of prostate cancer

[0157] Based on the results of Example 1 above, it is evident that the combined model of PCA3 and ERG (using SPDEF as an internal control) in the digital microdroplet RNA amplification detection system can reduce the false negative rate of prostate cancer. Therefore, this example provides a digital microdroplet RNA amplification detection system or kit for reducing the false negative rate of prostate cancer based on real-time fluorescence nucleic acid isothermal amplification detection and digital PCR quantitative detection systems, which may include:

[0158] The first reagent for the specific detection of the following genes based on the real-time fluorescence isothermal amplification method: PCA3;

[0159] The second reagent for the specific detection of the following gene based on the real-time fluorescence isothermal amplification method: ERG;

[0160] The third reagent for the specific detection of the following genes based on the real-time fluorescence isothermal amplification method is SPDEF, wherein SPDEF is used as an internal reference gene for detection.

[0161] A digital PCR system for absolute quantification of the above genes; and

[0162] Instruction manual;

[0163] The first, second, and third reagents may be those reagents targeting the corresponding genes as described in Example 2 above; and the instruction manual includes:

[0164] S1) Using the first reagent, the third reagent, and the digital PCR system, the absolute quantitative detection of PCA3 gene expression and SPDEF gene expression in the sample was performed, with SPDEF gene as an internal reference. The PCA3 score (PCA3 score = PCA3 copy number / SPDEF copy number * 1000) was calculated based on the absolute quantitative results of PCA3 gene and SPDEF gene expression. Based on the PCA3 score, the sample was classified into first prostate cancer negative sample and first prostate cancer positive sample. Among them, when the PCA3 score of the sample is greater than 114.2, it is regarded as first prostate cancer positive sample, and when the PCA3 score of the sample is less than or equal to 114.2, it is regarded as first prostate cancer negative sample.

[0165] S2) Using the second reagent and a digital PCR system, the expression of the ERG gene in the first prostate cancer negative sample obtained in step S1) is absolutely quantified, with the SPDEF gene used as an internal reference. Based on the absolute quantification results of ERG gene expression and the absolute quantification results of SPDEF gene expression in the corresponding sample obtained in step S1), an ERG score is calculated (ERG score = ERG copy number / SPDEF copy number * 1000). Based on this ERG score, the first prostate cancer negative sample obtained in step S1) is further divided into a second prostate cancer negative sample and a second prostate cancer positive sample; whereby a sample with an ERG score greater than 39.1 is considered a second prostate cancer positive sample, and a sample with an ERG score less than or equal to 39.1 is considered a second prostate cancer negative sample; and

[0166] S3) Combine the second prostate cancer positive sample obtained in step S2) with the first prostate cancer positive sample obtained in step S1) as the final prostate cancer positive sample (it is recommended that the test subjects corresponding to this part of the positive sample undergo puncture biopsy, and the clinician determines whether they have prostate cancer in combination with other diagnostic indicators) to reduce the false negative rate of prostate cancer.

[0167] Example 4: Clinical Sample Validation

[0168] Using the digital microdroplet RNA amplification detection system for reducing the false negative rate of prostate cancer provided in Example 3 above, and its instruction manual, digital microdroplet RNA amplification detection was performed on clinical urine samples from 111 patients (35 prostate cancer positive, 76 prostate cancer negative, numbered: sample 1-111) in the PSA gray zone to verify the reliability of the digital microdroplet RNA amplification detection system provided by the present invention. For specific detection methods, please refer to Example 1. Each urine sample was divided into three parts. Absolute quantification of the biomarker genes (PCA3 and SPDEF) in two of the urine samples was performed, and the PCA3 score was calculated. The detection results are shown in Tables 17 and 18 below. Table 19 shows the diagnostic results based on the PCA3 score. It can be seen that based on the PCA3 score, 53 negative samples were detected from the clinical urine samples of 111 patients in the PSA gray zone. Absolute quantification of the biomarker gene ERG in these 53 negative samples was then performed, and the ERG score was calculated. The detection results are shown in Tables 17 and 20 below. Table 21 shows the diagnostic results based on the combined PCA3 and ERG scores. It can be seen that by using the ERG score... The G score can compensate for two cases (specifically, samples 53 and 79 in Table 17 below, which were negative based on the PCA3 score but positive based on the ERG score, and were actually positive for prostate cancer. If samples 53 and 79 were tested using the original primer and probe combination for ERG, both were negative; if samples 53 and 79 were tested using the primer and probe combination for ERG group 7, only sample 79 was positive, while sample 53 was negative. These results further indicate that the original primer and probe combination for ERG detection and group 7 cannot effectively compensate for patients missed by PCA3) of patients missed by PCA3 score, thereby reducing the false negative rate of prostate cancer. Furthermore, compared to the diagnostic results based on the PCA3 score shown in Table 19, the combined PCA3 score and ERG score shown in Table 21 demonstrated significantly better prostate cancer detection results in the above 111 clinical samples. Specifically, the sensitivity was 97.14%, the specificity was 52.63%, the negative predictive value was 97.56%, and the positive predictive value was 48.57%. This also proves that the digital microdroplet RNA amplification detection system provided by this invention has extremely high sensitivity and negative predictive value in detecting prostate cancer, and reduces the number of missed patients. In this way, it can assist in the clinical diagnosis of prostate cancer, especially in large-scale prostate cancer screening and diagnosis, where it can effectively reduce the positive missed detection rate.

[0169] Table 17: Detection results of clinical urine samples from 111 patients in the PSA gray zone.

[0170] Table 18: Clinical Sample Validation Results of PCA3 Scores

[0171] Table 19: Correlation analysis results of PCA3 score in clinical samples with prostate cancer diagnosis (%)

[0172] Table 20: Clinical sample validation results of PCA3 score combined with ERG score

[0173] Table 21: Correlation analysis results of PCA3 score combined with ERG score in clinical samples for prostate cancer diagnosis (%)

[0174] The embodiments described herein are for illustrative purposes only, and various modifications or alterations made by those skilled in the art based on the embodiments should also be included within the substantive scope of the patent application.

[0175] Industrial application

[0176] This invention provides a digital microdroplet RNA amplification detection system for prostate cancer and a method for reducing the false negative rate of prostate cancer. It can significantly reduce the false negative rate of prostate cancer, improve the diagnostic effect, and is suitable for industrial applications.

Claims

1. A digital microdroplet RNA amplification detection system for prostate cancer, comprising reagents for the specific detection of the following genes respectively based on a real-time fluorescence nucleic acid isothermal amplification method: PCA3, ERG and SPDEF genes, and a digital PCR system for absolute quantification of the above genes; The SPDEF gene is used as an internal reference gene for detection. The specific detection reagents for each gene include those corresponding to that gene: (1) Nucleic acid extraction solution: which contains a solid support containing a specific capture probe for capturing gene sequences; the nucleotide sequences of the specific capture probes for specific detection of the following genes are shown in SEQ ID NO:23, 17 and 27 respectively: PCA3, ERG and SPDEF; The components of the nucleic acid extraction solution include: 250-800mM HEPES, 4-10% lithium dodecyl sulfate, 1-50μM of the specific capture probe, and 50-500mg / L magnetic beads; (2) Amplification detection solution: It contains a first primer, a second primer and a target detection probe, wherein the first primer works in conjunction with the first primer to amplify the target sequence in the gene sequence, and the target detection probe specifically binds to the RNA copy of the amplification product of the target; the nucleotide sequences of the first primer specifically detecting the following genes are shown in SEQ ID NO:24, 19 and 28 respectively: PCA3, ERG and SPDEF; the nucleotide sequences of the second primer specifically detecting the following genes are shown in SEQ ID NO:25, 21 and 29 respectively: PCA3, ERG and SPDEF; the nucleotide sequences of the target detection probe specifically detecting the following genes are shown in SEQ ID NO:26, 18 and 30 respectively: PCA3, ERG and SPDEF, and the nucleotide sequences of the target detection probe are respectively equipped with a fluorescent reporter group and a quencher group at both ends of the nucleotide sequence of the target detection probe; The amplification detection solution comprises: 10-50 mM Tris, 5-40 mM KCl, 10-40 mM MgCl2, 1-20 mM NTP, 0.1-10 mM dNTPs, 1-10% PVP40, the first primer at 10-250 pmol / mL, the second primer at 10-250 pmol / mL, and the target detection probe at 10-250 pmol / mL.

2. The digital microdroplet RNA amplification detection system according to claim 1, further comprising: (3) SAT enzyme solution: It contains at least one RNA polymerase and M-MLV reverse transcriptase.

3. The digital microdroplet RNA amplification detection system according to claim 2, wherein the SAT enzyme solution comprises: 16000-160000 U / mL M-MLV reverse transcriptase, 8000-80000 U / mL RNA polymerase, 2-10 mM HEPES pH 7.5, 10-100 mM N-acetyl-L-cysteine, 0.04-0.4 mM zinc acetate, 10-100 mM trehalose, 40-200 mM Tris-HCl pH 8.0, 40-200 mM KCl, 0.01-0.5 mM EDTA, 0.1-1% (v / v) Triton X-100 and 20-50% (v / v) glycerol.

4. The digital microdroplet RNA amplification detection system according to claim 2, further comprising: (4) Washing solution: It contains 5-50 mM HEPES, 50-500 mM NaCl, 0.5-1.5% SDS, 1-10 mM EDTA; and / or (5) Positive controls: These include three systems of in vitro transcribed RNA containing the following gene nucleic acids: PCA3, ERG, and SPDEF; and / or (6) Negative control: It is a system that does not contain the following gene nucleic acids: PCA3, ERG and SPDEF.

5. An oligonucleotide combination comprising: The specific capture probes have nucleotide sequences as shown in SEQ ID NO:23, 17 and 27, respectively; the first primers have nucleotide sequences as shown in SEQ ID NO:24, 19 and 28, respectively; the second primers have nucleotide sequences as shown in SEQ ID NO:25, 21 and 29, respectively; and the target detection probes have nucleotide sequences as shown in SEQ ID NO:26, 18 and 30, respectively.

6. A digital microdroplet RNA amplification detection system for reducing the false negative rate of prostate cancer, comprising: The first reagent for the specific detection of the following genes based on the real-time fluorescence isothermal amplification method: PCA3; The second reagent for the specific detection of the following gene based on the real-time fluorescence isothermal amplification method: ERG; The third reagent for the specific detection of the following genes based on the real-time fluorescence isothermal amplification method is SPDEF, wherein SPDEF is used as an internal reference gene for detection. A digital PCR system for absolute quantification of the above genes; and Instruction manual; The instruction manual mentioned therein includes: S1) The expression of PCA3 and SPDEF genes in the sample is absolutely quantitatively detected using the first reagent, the third reagent, and a digital PCR system. The PCA3 score is calculated based on the absolute quantitative detection results, and the sample is classified into a first prostate cancer negative sample and a first prostate cancer positive sample based on the PCA3 score. When the PCA3 score of the sample is greater than 114.2, it is considered a first prostate cancer positive sample, and when the PCA3 score of the sample is less than or equal to 114.2, it is considered a first prostate cancer negative sample. S2) Using the second reagent and a digital PCR system, the expression of the ERG gene in the first prostate cancer negative sample obtained in step S1) is absolutely quantified. An ERG score is calculated based on the absolute quantification of ERG gene expression and the absolute quantification of SPDEF gene expression in the corresponding sample obtained in step S1). The first prostate cancer negative sample obtained in step S1) is then further classified into a second prostate cancer negative sample and a second prostate cancer positive sample based on this ERG score. A sample with an ERG score greater than 39.1 is considered a second prostate cancer positive sample, and a sample with an ERG score less than or equal to 39.1 is considered a second prostate cancer negative sample. S3) Combine the second prostate cancer positive sample obtained in step S2) with the first prostate cancer positive sample obtained in step S1) to obtain the final prostate cancer positive sample. The first reagent contains a specific capture probe, a first primer, a second primer, and a target detection probe for the specific detection of the PCA3 gene, the nucleotide sequences of which are shown in SEQ ID NO:23-26, respectively. The second reagent contains a specific capture probe for specific detection of the ERG gene, a first primer, a second primer, and a target detection probe, the nucleotide sequences of which are shown in SEQ ID NO:17, 19, 21, and 18, respectively. The third reagent contains a specific capture probe for specific detection of the SPDEF gene, and the nucleotide sequences of the first primer, the second primer, and the target detection probe are shown in SEQ ID NO:27-30, respectively.

7. The digital microdroplet RNA amplification detection system according to claim 6, wherein the PCA3 score is calculated as follows: PCA3 score = PCA3 copy number / SPDEF copy number * 1000, and the ERG score is calculated as follows: ERG score = ERG copy number / SPDEF copy number * 1000.

8. The digital microdroplet RNA amplification detection system according to claim 6, wherein the first reagent, the second reagent, and the third reagent each comprise: (1) Nucleic acid extraction solution: It contains 250-800mM HEPES, 4-10% lithium dodecyl sulfate, 1-50μM of the specific capture probe, and 50-500mg / L magnetic beads; (2) Amplification detection solution: This solution contains 10-50 mM Tris, 5-40 mM KCl, 10-40 mM MgCl2, 1-20 mM NTP, 0.1-10 mM dNTPs, 1-10% PVP40, the first primer described above at 10-250 pmol / mL, the second primer described above at 10-250 pmol / mL, and the target detection probe described above at 10-250 pmol / mL; and (3) SAT enzyme solution: It contains 16,000-160,000 U / mL M-MLV reverse transcriptase, 8,000-80,000 U / mL RNA polymerase, 2-10 mM HEPES pH 7.5, 10-100 mM N-acetyl-L-cysteine, 0.04-0.4 mM zinc acetate, 10-100 mM trehalose, 40-200 mM Tris-HCl pH 8.0, 40-200 mM KCl, 0.01-0.5 mM EDTA, 0.1-1% (v / v) Triton X-100 and 20-50% (v / v) glycerol.

9. The digital microdroplet RNA amplification detection system according to claim 8, further comprising: (4) Washing solution: It contains 5-50mM HEPES, 50-500mM NaCl, 0.5-1.5% SDS, and 1-10mM EDTA; (5) Positive controls: These include three systems of in vitro transcribed RNA containing the following gene nucleic acids: PCA3, ERG, and SPDEF; and (6) Negative control: It is a system that does not contain any of the following gene nucleic acids: PCA3, ERG and SPDEF.

10. A method for reducing the rate of missed detection of prostate cancer, comprising the following steps: M1) Absolute quantitative detection of PCA3 and SPDEF gene expression in the sample, with SPDEF gene as the internal reference for detection. PCA3 score is calculated based on the absolute quantitative results of PCA3 and SPDEF gene expression, and the sample is classified into first prostate cancer negative sample and first prostate cancer positive sample based on the PCA3 score. M2) The expression of ERG gene in the first prostate cancer negative sample obtained in step M1) is absolutely quantitatively detected, and SPDEF gene is used as the detection internal reference. Based on the absolute quantitative result of ERG gene expression and the absolute quantitative result of SPDEF gene expression in the corresponding sample obtained in step M1), the ERG score is calculated, and based on the ERG score, the first prostate cancer negative sample obtained in step M1) is further divided into a second prostate cancer negative sample and a second prostate cancer positive sample. and M3) The second prostate cancer positive sample obtained in step M2) and the first prostate cancer positive sample obtained in step M1) are combined as the final prostate cancer positive sample, thereby reducing the false negative rate of prostate cancer. The digital microdroplet RNA amplification detection system according to claim 6 is used to perform absolute quantitative detection of the expression of PCA3, ERG and SPDEF genes in the sample.

11. The method according to claim 10, wherein in step M1), a sample with a PCA3 score greater than 114.2 is considered a first prostate cancer positive sample, and a sample with a PCA3 score less than or equal to 114.2 is considered a first prostate cancer negative sample, and the PCA3 score is calculated as: PCA3 score = PCA3 copy number / SPDEF copy number * 1000; and In step M2), a sample with an ERG score greater than 39.1 is considered a second prostate cancer positive sample, and a sample with an ERG score less than or equal to 39.1 is considered a second prostate cancer negative sample. The ERG score is calculated as follows: ERG score = ERG copy number / SPDEF copy number * 1000.

12. The method of claim 10, wherein the sample comprises a urine sample.

13. A method for detecting prostate cancer, comprising the following steps: N1) Absolute quantitative detection of PCA3 and SPDEF gene expression in the sample, with SPDEF gene as the internal reference for detection. PCA3 score is calculated based on the absolute quantitative results of PCA3 and SPDEF gene expression, and the sample is classified into first prostate cancer negative sample and first prostate cancer positive sample based on the PCA3 score. N2) The expression of ERG gene in the first prostate cancer negative sample obtained in step N1) is absolutely quantitatively detected, and SPDEF gene is used as the detection internal reference. ERG score is calculated based on the absolute quantitative result of ERG gene expression and the absolute quantitative result of SPDEF gene expression in the corresponding sample obtained in step N1). Based on the ERG score, the first prostate cancer negative sample obtained in step N1) is further divided into a second prostate cancer negative sample and a second prostate cancer positive sample. and N3) Combine the second prostate cancer positive sample obtained in step N2) and the first prostate cancer positive sample obtained in step N1) as the final prostate cancer positive sample, and take the second prostate cancer negative sample obtained in step N2) as the final prostate cancer negative sample. The digital microdroplet RNA amplification detection system according to claim 6 is used to perform absolute quantitative detection of the expression of PCA3, ERG and SPDEF genes in the sample.

14. The method according to claim 13, wherein in step N1), a sample with a PCA3 score greater than 114.2 is considered a first prostate cancer positive sample, and a sample with a PCA3 score less than or equal to 114.2 is considered a first prostate cancer negative sample, and the PCA3 score is calculated as: PCA3 score = PCA3 copy number / SPDEF copy number * 1000; and In step N2), a sample with an ERG score greater than 39.1 is considered a second prostate cancer positive sample, and a sample with an ERG score less than or equal to 39.1 is considered a second prostate cancer negative sample. The ERG score is calculated as follows: ERG score = ERG copy number / SPDEF copy number * 1000.

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