Digital microdroplet RNA amplification detection system and method for reducing missed detection rate of prostate cancer

Abstract

Provided are a digital microdroplet RNA amplification detection system and method for reducing the missed detection rate of prostate cancer, which belong to the technical field of tumor diagnosis. The provided digital microdroplet RNA amplification detection system for reducing the missed detection rate of prostate cancer comprises: reagents based on a real-time fluorescent nucleic acid isothermal amplification method for specifically detecting the following genes, respectively: PCA3, ERG, and SPDEF; and a digital PCR system. Compared with existing kits or other products for prostate cancer detection, the provided digital microdroplet RNA amplification detection system can significantly reduce the missed detection rate of prostate cancer and improve the detection sensitivity and negative predictive value for prostate cancer.

Description

A digital microdroplet RNA amplification detection system and method for reducing the false negative rate of prostate cancer. Technical Field

[0001] This invention belongs to the field of tumor diagnostic technology, specifically relating to a digital microdroplet RNA amplification detection system or kit for reducing the false negative rate of prostate cancer and the application of the PCA3 gene combined with the ERG gene in the system or kit. It also relates to a method for reducing the false negative rate of prostate cancer. Background Technology

[0002] 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.

[0003] 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.

[0004] 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.

[0005] Summary of the Invention

[0006] In a first aspect, the present invention provides a digital microdroplet RNA amplification detection system for reducing the missed detection rate of prostate cancer, comprising:

[0007] The first reagent for the specific detection of the following genes based on the real-time fluorescence isothermal amplification method: PCA3;

[0008] The second reagent for the specific detection of the following gene based on the real-time fluorescence isothermal amplification method: ERG;

[0009] 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.

[0010] A digital PCR system for absolute quantification of the above genes; and

[0011] Instruction manual;

[0012] The instruction manual mentioned therein includes:

[0013] 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.

[0014] 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.

[0015] S3) The second prostate cancer positive sample obtained in step S2) is combined with the first prostate cancer positive sample obtained in step S1) to form the final prostate cancer positive sample, thereby reducing the false negative rate of prostate cancer.

[0016] 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.

[0017] In some embodiments, the first reagent, the second reagent, and the third reagent each comprise:

[0018] (1) Nucleic acid extraction solution: which contains a solid support containing a specific capture probe for capturing gene sequences;

[0019] (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;

[0020] (3) SAT enzyme solution: It contains at least one RNA polymerase and M-MLV reverse transcriptase.

[0021] In some embodiments, the nucleic acid extraction solution comprises: 250-800 mM HEPES, 4-10% lithium dodecyl sulfate, 1-50 μM of the specific capture probe, and 50-500 mg / L magnetic beads.

[0022] In some embodiments, 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, 10-250 pmol / mL of the first primer, 10-250 pmol / mL of the second primer, and 10-250 pmol / mL of the target detection probe.

[0023] In some embodiments, the SAT enzyme solution comprises: 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.

[0024] In some embodiments, in the first reagent, the nucleotide sequence of the PCA3-specific capture probe is shown in SEQ ID NO:1, and the nucleotide sequences of the first primer, the second primer, and the target detection probe for PCA3 are shown in SEQ ID NO:4, SEQ ID NO:7, and SEQ ID NO:10, respectively.

[0025] In some embodiments, in the second reagent, the nucleotide sequence of the specific capture probe for detecting ERG is shown in SEQ ID NO:2, and the nucleotide sequences of the first primer, the second primer, and the target detection probe for ERG are shown in SEQ ID NO:5, SEQ ID NO:8, and SEQ ID NO:11, respectively.

[0026] In some embodiments, in the first reagent, the nucleotide sequence of the specific capture probe for detecting SPDEF is shown in SEQ ID NO:3, and the nucleotide sequences of the first primer, the second primer, and the target detection probe for PCA3 are shown in SEQ ID NO:6, SEQ ID NO:9, and SEQ ID NO:12, respectively.

[0027] In some embodiments, the digital microdroplet RNA amplification detection system further includes:

[0028] (4) Washing solution: It contains 5-50mM HEPES, 50-500mM NaCl, 0.5-1.5% SDS, and 1-10mM EDTA;

[0029] (5) Positive controls: In vitro transcribed RNA systems containing the following gene nucleic acids: PCA3, ERG, and SPDEF; and

[0030] (6) Negative control: A system that does not contain the following gene nucleic acids: PCA3, ERG and SPDEF.

[0031] In a second aspect, the present invention provides a method for reducing the false negative rate of prostate cancer, comprising the following steps:

[0032] 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.

[0033] 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.

[0034] 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.

[0035] In some embodiments, the method for reducing the false negative rate of prostate cancer provided by the present invention includes the following steps:

[0036] M1) The absolute quantitative detection of PCA3 and SPDEF gene expression in samples was performed using a reagent combined with a digital PCR system based on the real-time fluorescence nucleic acid isothermal amplification detection principle. The PCA3 score was calculated based on the absolute quantitative results of PCA3 and SPDEF gene expression, and the samples were classified into first prostate cancer negative samples and first prostate cancer positive samples based on the PCA3 score.

[0037] M2) Using a reagent based on real-time fluorescence nucleic acid isothermal amplification detection principle to detect the biomarker gene ERG, combined with a digital PCR system, the expression of the ERG gene in the first prostate cancer negative sample obtained in step M1) was absolutely quantified. An ERG score was 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) was further classified into a second prostate cancer negative sample and a second prostate cancer positive sample.

[0038] 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.

[0039] 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.

[0040] 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.

[0041] In some implementations, the sample includes a urine sample.

[0042] In a third aspect, the present invention also provides a method for detecting prostate cancer, comprising the following steps:

[0043] 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.

[0044] 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.

[0045] 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.

[0046] In some embodiments, the method for detecting prostate cancer provided by the present invention includes the following steps:

[0047] N1) The absolute quantitative detection of PCA3 and SPDEF gene expression in the sample was performed using a reagent combined with a digital PCR system based on the real-time fluorescence nucleic acid isothermal amplification detection principle. The PCA3 score was calculated based on the absolute quantitative results, and the sample was classified into first prostate cancer negative sample and first prostate cancer positive sample according to the PCA3 score.

[0048] 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 expression of the ERG gene in the first prostate cancer negative sample obtained in step N1) was absolutely quantified. 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), an ERG score was calculated. Based on this ERG score, the first prostate cancer negative sample obtained in step N1) was further classified into a second prostate cancer negative sample and a second prostate cancer positive sample.

[0049] 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.

[0050] 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.

[0051] 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.

[0052] The digital microdroplet RNA amplification detection system or kit for reducing the false negative rate of prostate cancer 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 gene 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 that were missed by the detection system provided in Reference 1, thereby reducing the false negative rate of prostate cancer and improving the diagnostic effect of prostate cancer. The results show that the detection system or kit for combined PCA3 and ERG genes provided by this invention has higher sensitivity (up to 97.6%) and higher negative predictive value (97.7%), and can significantly reduce the false negative rate of prostate cancer. Therefore, the detection system provided by this invention, compared to the detection system in Reference 1, significantly improves diagnostic sensitivity and negative predictive value by adding only one detection target. This reduces the probability of actual negative subjects undergoing unnecessary biopsies (down to 2.3%) and also significantly reduces the false negative rate (down to 2.4%). Furthermore, in clinical sample validation trials, the detection system and method 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 detection system, kit, and method provided by this invention are more suitable for large-scale screening of prostate cancer. Detailed Implementation

[0053] The present invention will be described in detail below with reference to specific embodiments.

[0054] 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.

[0055] 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).

[0056] 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.

[0057] All primers, probes, and in vitro transcribed RNA products mentioned in this invention were synthesized using existing techniques.

[0058] Example 1: Optimization of a biomarker for detecting prostate cancer based on the principle of digital microdroplet RNA amplification detection.

[0059] 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%), in order to further improve its detection and diagnostic effect, 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, RPL) Biomarkers that can be used in conjunction with the PCA3 gene absolute quantification system described in Reference 1 were screened from 7P16, PIP5K1A, CCND1, GSTP1, CST1, CST3, CST4, HOXC6, HOXC4, CCNA1, LMTK2, 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, etc., to further optimize the detection and diagnostic results of the system. It has been found that the combined use of ERG, HOXC6, HOXC4, DLX1, TDRD1, AMACR, MALAT1 genes and PCA3 gene (using SPDEF as an internal reference gene) can achieve relatively good diagnostic results. However, compared with the other six genes, the combined use of ERG and PCA3 genes has the best diagnostic effect, which can minimize the number of missed cases and improve detection sensitivity and negative predictive value, meeting the needs of clinical and large-scale screening. Details are as follows.

[0060] 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:

[0061] 1.1 Collection of test samples (random pre-urine sample from the test subject)

[0062] 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.

[0063] 1.2 Sample Preparation

[0064] 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.

[0065] 1.3 Nucleic acid extraction

[0066] For each sample processing tube available in section 1.2, perform the following operations:

[0067] (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.

[0068] (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.

[0069] (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.

[0070] 1.4 Detection of RNA amplification from digital microdroplets

[0071] For each sample processing tube available in section 1.3, perform the following operations:

[0072] (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).

[0073] (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.

[0074] (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.

[0075] (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.

[0076] 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.

[0077] 1.5 Result Judgment

[0078] 1.5.1 Determination of positive and negative controls

[0079] 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.

[0080] 1.5.2 Determination of each detection gene in the sample to be tested

[0081] 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.

[0082] 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.

[0083] in:

[0084] Sensitivity (SE) = Number of cancer patients with values ​​above the cutoff value / Number of patients in the sample;

[0085] Specificity (SP) = Number of cancer patients with values ​​below the cutoff value / Number of control samples;

[0086] 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;

[0087] 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;

[0088] Accuracy = (Number of true positive samples + Number of true negative samples) / Total number of samples.

[0089] 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).

[0090] Table 1: Correlation between clinical gold standard prostate biopsy results and PCA3 score results

[0091] Table 2: Correlation analysis results of PCA3 score for prostate cancer diagnosis

[0092] 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.

[0093] To reduce the number of missed cases in the prostate cancer detection system based on the PCA3 gene disclosed in Reference 1, this embodiment further utilizes the ERG, HOXC6, HOXC4, DLX1, TDRD1, AMACR, and MALAT1 genes for secondary detection 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 primers, second primers, and target detection probes used for the HOXC6, HOXC4, DLX1, TDRD1, AMACR, and MALAT1 genes are shown in Table 1 of patent document CN115851926A (also referred to as Reference 2 in this document), and the specific capture probes, first primers, second primers, and target detection probes used for the ERG gene are shown in Table 3 below). The ERG score, HOXC6 score, HOXC4 score, DLX1 score, TDRD1 score, AMACR score, and MALAT1 score results were obtained respectively. The scoring calculation methods are as follows: 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 the other 7 genes to compensate for missed detections, based on a negative PCA3 gene result. Based on the output results in Table 4, the correlation analysis results of the seven genes combined with PCA3 for the diagnosis of prostate cancer are shown in Table 5 below.

[0094] Table 3: Primers and probes targeting the ERG gene

[0095] Table 4: Results of compensating for missed diagnoses by combining the results of PCA3 gene negative detection with those of the other 7 genes.

[0096] Table 5: Correlation analysis results of the seven genes combined with PCA3 for the diagnosis of prostate cancer.

[0097] 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 ERG, HOXC6, DLX1, HOXC4, MALAT1, TDRD1, and AMACR genes respectively, the detection effect of combining the ERG gene was the most outstanding, able to compensate for 3 positive patients missed based on the PCA3 gene alone. The detection sensitivity and negative predictive value were significantly improved, and the overall diagnostic specificity and positive predictive value only decreased slightly, with a relatively small decrease in accuracy. The compensation effect of combining the HOXC6 gene was the second best, able to compensate for 2 missed patients, but it significantly reduced specificity, positive predictive value, and accuracy. DLX1 and HOXC4 each compensated for only 1 missed patient, while MALAT1, TDRD1, and AMACR did not compensate for any missed cases.

[0098] In summary, combining PCA3 and ERG genes, and utilizing real-time fluorescence nucleic acid isothermal amplification and digital PCR systems, can achieve superior results in the detection and diagnosis of prostate cancer, with a sensitivity of 97.6% and a negative predictive value of 97.7%, significantly reducing the risk of missed detection of prostate cancer. This can provide clinicians with a basis for prostate cancer diagnosis, 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 system disclosed in Reference 1, it further includes a reagent for detecting the biomarker gene ERG based on the principle of real-time fluorescence nucleic acid isothermal amplification, and thus provides a method for reducing the missed detection rate of prostate cancer, which may include the following steps:

[0099] 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.

[0100] 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.

[0101] 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.

[0102] 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 results are not satisfactory. At that time, its diagnostic effect on prostate cancer was not ideal, as shown in Tables 6 and 7 below. The logistic regression score for the combination of PCA3, ERG, and SPDEF was calculated as follows: 0.006 * PCA3 score + 0.002 * ERG score; the logistic regression score for the combination of PCA3, ERG, SPDEF, and PSA was calculated as follows: 0.035 * PCA3 new score + 0.044 * ERG new score + 0.009 * SPDEF new 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 6, compared to the diagnostic effect of PCA3 alone as shown in Table 2, the regression diagnostic effect of PCA3 combined with ERG was lower, and it could not reduce the false negative rate of prostate cancer. As clearly shown in Table 7, using PSA as an internal reference gene significantly reduced the overall diagnostic effectiveness of the logistic regression model and failed to reduce the false negative rate of prostate cancer. Therefore, using logistic regression alone will not improve diagnostic effectiveness; on the contrary, it will reduce diagnostic capability.

[0103] Table 6: Diagnostic efficacy of a model combining PCA3 and ERG genes for prostate cancer diagnosis

[0104] Table 7: Diagnostic efficacy of a model combining PCA3, ERG, and SPDEF genes for prostate cancer diagnosis.

[0105] Example 2: Digital microdroplet RNA amplification detection system for prostate cancer

[0106] Based on the results of Example 1 above, the combined model of PCA3 and ERG (with SPDEF as an internal reference) exhibits high sensitivity and negative predictive value in the digital microdroplet RNA amplification detection system, and can reduce the false negative rate of prostate cancer. Furthermore, 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. Therefore, 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:

[0107] (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.

[0108] Specifically, the specific detection reagents for each of the above genes include those corresponding to that gene:

[0109] (1) Nucleic acid extraction solution: which contains a solid support containing a specific capture probe for capturing gene sequences;

[0110] (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;

[0111] It may also include:

[0112] (3) SAT enzyme solution: It contains at least one RNA polymerase and M-MLV reverse transcriptase.

[0113] More specifically, the nucleotide sequences of the specific capture probes for the specific detection of PCA3, ERG and SPDEF genes are shown in SEQ ID NO:1-3, the nucleotide sequences of the first primers are shown in SEQ ID NO:4-6, the nucleotide sequences of the second primers are shown in SEQ ID NO:7-9, and the nucleotide sequences of the target detection probes are shown in SEQ ID NO:10-12. Furthermore, the nucleotide sequences of the target detection probes are equipped with fluorescent reporter groups and quencher groups at both ends.

[0114] More specifically, the specific detection reagents for each of the above genes provided in this embodiment include:

[0115] (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;

[0116] (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;

[0117] (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.

[0118] 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):

[0119] (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.

[0120] (2.3) Positive control: A system of in vitro transcribed RNA containing the following gene nucleic acids: PCA3, ERG and SPDEF, prepared as in Example 1 of Reference 2 above.

[0121] (2.4) Negative control: A system that does not contain the following genes and nucleic acids: PCA3, ERG and SPDEF, such as deionized water or sample preservation solution (which contains high concentrations of detergent and physiological saline).

[0122] (2.5) Instruction Manual

[0123] When using the digital microdroplet RNA amplification detection system provided in this embodiment to detect clinical urine samples, the following steps are included:

[0124] 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.

[0125] 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.

[0126] 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.

[0127] Example 3: A digital microdroplet RNA amplification detection system or kit for reducing the false negative rate of prostate cancer

[0128] Based on the results of Example 1, 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:

[0129] The first reagent for the specific detection of the following genes based on the real-time fluorescence isothermal amplification method: PCA3;

[0130] The second reagent for the specific detection of the following gene based on the real-time fluorescence isothermal amplification method: ERG;

[0131] 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.

[0132] A digital PCR system for absolute quantification of the above genes; and

[0133] Instruction manual;

[0134] 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:

[0135] 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.

[0136] 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

[0137] 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.

[0138] Example 4: Clinical Sample Validation

[0139] 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 3 parts. First, the biomarker genes (PCA3 and SPDEF) in 2 of the urine samples were absolutely quantitatively detected, and the PCA3 score was calculated. The detection results are shown in Tables 8 and 9 below. Table 10 shows the diagnostic results based on the PCA3 score. It can be seen that 53 negative samples were detected from the clinical urine samples of 111 patients in the PSA gray zone based on the PCA3 score. Then, the biomarker gene ERG in these 53 negative samples was absolutely quantitatively detected, and the ERG score was calculated. The detection results are shown in Tables 8 and 11 below. Table 12 shows the diagnostic results based on the PCA3 score combined with the ERG score. It can be seen that the ERG score can compensate for 2 cases (specifically samples 53 and 79 in Table 8 below, which were judged as negative based on the PCA3 score, but as positive based on the ERG score, and were actually positive samples for prostate cancer) that were missed based on the 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 10, the combined PCA3 score and ERG score shown in Table 12 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.

[0140] Table 8: Detection results of clinical urine samples from 111 patients in the PSA gray zone.

[0141] Table 9: Clinical Sample Validation Results of PCA3 Scores

[0142] Table 10: Correlation analysis results of PCA3 score in clinical samples with prostate cancer diagnosis (%)

[0143] Table 11: Clinical sample validation results of PCA3 score combined with ERG score

[0144] Table 12: Correlation analysis results of PCA3 score combined with ERG score in clinical samples for prostate cancer diagnosis (%)

[0145] 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.

[0146] Industrial application

[0147] This invention provides a digital microdroplet RNA amplification detection system and 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 of prostate cancer, and is suitable for industrial applications.

Claims

1. A digital microdroplet RNA amplification detection system for reducing the false negative rate of prostate cancer, comprising: a first reagent for specifically detecting the following gene based on a real-time fluorescent nucleic acid isothermal amplification method: PCA3; a second reagent for specifically detecting the following gene based on a real-time fluorescent nucleic acid isothermal amplification method: ERG; a third reagent for specifically detecting the following gene based on a real-time fluorescent nucleic acid isothermal amplification method: SPDEF, wherein the SPDEF serves as an internal reference gene for detection; a digital PCR system for absolute quantification of the above genes; and an instruction manual; wherein the instruction manual comprises: S1) absolute quantification of the PCA3 and SPDEF gene expressions in a sample using the first reagent, the third reagent and the digital PCR system, and calculating a PCA3 score according to the absolute quantification results, and dividing the sample into a first prostate cancer negative sample and a first prostate cancer positive sample according to the PCA3 score; wherein when the PCA3 score of the sample is greater than 114.2, it is considered as 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 as a first prostate cancer negative sample; S2) absolute quantification of the ERG gene expression in the first prostate cancer negative sample obtained in step S1) using the second reagent and the digital PCR system, and calculating an ERG score according to the absolute quantification results of the ERG gene expression and the absolute quantification results of the SPDEF gene expression in the corresponding sample obtained in step S1), and dividing the first prostate cancer negative sample obtained in step S1) into a second prostate cancer negative sample and a second prostate cancer positive sample again according to the ERG score; wherein when the ERG score of the sample is greater than 39.1, it is considered as a second prostate cancer positive sample, and when the ERG score of the sample is less than or equal to 39.1, it is considered as a second prostate cancer negative sample; and S3) combining the second prostate cancer positive sample screened in step S2) with the first prostate cancer positive sample obtained in step S1) as the final prostate cancer positive sample, thereby achieving the purpose of reducing the false negative rate of prostate cancer. 2.The digital microdroplet RNA amplification detection system according to claim 1, wherein the PCA3 score is calculated by the formula: PCA3 score = PCA3 copy number / SPDEF copy number * 1000, and the ERG score is calculated by the formula: ERG score = ERG copy number / SPDEF copy number * 1000. 3.The digital microdroplet RNA amplification detection system according to claim 1, wherein each of the first reagent, the second reagent and the third reagent comprises: (1) a nucleic acid extraction solution comprising a solid support containing a specific capture probe for capturing a gene sequence; (2) an amplification detection solution comprising a first primer, a second primer and a target detection probe, wherein the first primer cooperates with the first primer to amplify a target sequence in the gene sequence, and the target detection probe specifically binds to the amplified product RNA copy of the target. (3) SAT enzyme solution: which comprises at least one RNA polymerase and M-MLV reverse transcriptase.

4. The digital microdroplet RNA amplification detection system according to claim 3, wherein: The components of the nucleic acid extraction solution include: 250-800 mM HEPES, 4-10% lithium dodecyl sulfate, 1-50 μΜ of the specific capture probe, 50-500 mg / L magnetic beads; The components of the amplification detection solution include: 10-50 mM Tris, 5-40 mM KCl, 10-40 mM MgCl2, 1-20 mM NTP, 0.1-10 mM dNTPs, 1-10% PVP40, 10-250 pmol / mL of the first primer, 10-250 pmol / mL of the second primer, 10-250 pmol / mL of the target detection probe; The components of the SAT enzyme solution include: 16000-160000 U / mL of M-MLV reverse transcriptase, 8000-80000 U / mL of 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.

5. The digital microdroplet RNA amplification detection system according to claim 3, wherein: In the first reagent, the nucleotide sequence of the specific capture probe for detecting PCA3 is shown as SEQ ID NO: 1, and the nucleotide sequences of the first primer, the second primer and the target detection probe for PCA3 are shown as SEQ ID NO: 4, SEQ ID NO: 7 and SEQ ID NO: 10, respectively; In the second reagent, the nucleotide sequence of the specific capture probe for detecting ERG is shown as SEQ ID NO: 2, and the nucleotide sequences of the first primer, the second primer and the target detection probe for ERG are shown as SEQ ID NO: 5, SEQ ID NO: 8 and SEQ ID NO: 11, respectively; In the first reagent, the nucleotide sequence of the specific capture probe for detecting SPDEF is shown as SEQ ID NO: 3, and the nucleotide sequences of the first primer, the second primer and the target detection probe for PCA3 are shown as SEQ ID NO: 6, SEQ ID NO: 9 and SEQ ID NO: 12, respectively.

6. The digital microdroplet RNA amplification detection system according to claim 3, further comprising: (4) washing solution: which contains 5-50 mM HEPES, 50-500 mM NaCl, 0.5-1.5% SDS, 1-10 mM EDTA; (5) Positive control: in vitro transcription RNA system containing nucleic acids of the following genes: PCA3, ERG and SPDEF; and (6) Negative control: a system not containing nucleic acids of the following genes: PCA3, ERG and SPDEF.

7. A method for reducing the false negative rate of prostate cancer, comprising the steps of: M1) performing absolute quantitative detection of the expression of the PCA3 and SPDEF genes in the sample, taking the SPDEF gene as an internal reference, calculating a PCA3 score according to the absolute quantitative results of the expression of the PCA3 and SPDEF genes, and dividing the sample into a first prostate cancer negative sample and a first prostate cancer positive sample according to the PCA3 score; M2) performing absolute quantitative detection of the expression of the ERG gene in the first prostate cancer negative sample obtained in step M1), taking the SPDEF gene as an internal reference, calculating an ERG score according to the absolute quantitative results of the expression of the ERG gene and the absolute quantitative results of the expression of the SPDEF gene in the corresponding sample obtained in step M1), and further dividing the first prostate cancer negative sample obtained in step M1) into a second prostate cancer negative sample and a second prostate cancer positive sample according to the ERG score; and M3) combining the second prostate cancer positive sample obtained in step M2) and the first prostate cancer positive sample obtained in step M1) as the final prostate cancer positive sample, thereby reducing the false negative rate of prostate cancer.

8. The method of claim 7, comprising the steps of: M1) performing absolute quantitative detection of the expression of the PCA3 and SPDEF genes in the sample using a reagent combined with a digital PCR system based on the principle of real-time fluorescent nucleic acid isothermal amplification detection for detecting biomarker genes PCA3 and SPDEF, calculating a PCA3 score according to the absolute quantitative results of the expression of the PCA3 and SPDEF genes, and dividing the sample into a first prostate cancer negative sample and a first prostate cancer positive sample according to the PCA3 score; M2) performing absolute quantitative detection of the expression of the ERG gene in the first prostate cancer negative sample obtained in step M1) using a reagent combined with a digital PCR system based on the principle of real-time fluorescent nucleic acid isothermal amplification detection for detecting biomarker gene ERG, calculating an ERG score according to the absolute quantitative results of the expression of the ERG gene and the absolute quantitative results of the expression of the SPDEF gene in the corresponding sample obtained in step M1), and further dividing the first prostate cancer negative sample obtained in step M1) into a second prostate cancer negative sample and a second prostate cancer positive sample according to the ERG score; and M3) combining the second prostate cancer positive sample obtained in step M2) and the first prostate cancer positive sample obtained in step M1) as the final prostate cancer positive sample, thereby reducing the false negative rate of prostate cancer.

9. The method according to claim 7, wherein in step Ml) the sample is classified as a first prostate cancer positive sample when the PCA3 score of the sample is greater than 114.2, and as a first prostate cancer negative sample when the PCA3 score of the sample is less than or equal to 114.2, and the PCA3 score is calculated by: PCA3 score = PCA3 copy number / SPDEF copy number*1000.

10. The method according to claim 7, wherein in step M2) the sample is classified as a second prostate cancer positive sample when the ERG score of the sample is greater than 39.1, and as a second prostate cancer negative sample when the ERG score of the sample is less than or equal to 39.1, and the ERG score is calculated by: ERG score = ERG copy number / SPDEF copy number*1000.

11. The method according to claim 7, wherein the sample comprises a urine sample.

12. A method for detecting prostate cancer, comprising the steps of: Nl) detecting the absolute quantification of the expression of the PCA3 and SPDEF genes in a sample, taking the SPDEF gene as an internal control, calculating a PCA3 score according to the absolute quantification results of the expression of the PCA3 and SPDEF genes, and classifying the sample into a first prostate cancer negative sample and a first prostate cancer positive sample according to the PCA3 score; N2) detecting the absolute quantification of the expression of the ERG gene in the first prostate cancer negative sample obtained in step Nl), taking the SPDEF gene as an internal control, calculating an ERG score according to the absolute quantification results of the expression of the ERG gene and the absolute quantification results of the expression of the SPDEF gene in the corresponding sample obtained in step Nl), and classifying the first prostate cancer negative sample obtained in step Nl) into a second prostate cancer negative sample and a second prostate cancer positive sample again according to the ERG score; and N3) combining the second prostate cancer positive sample obtained in step N2) and the first prostate cancer positive sample obtained in step Nl) as a final prostate cancer positive sample, and taking the second prostate cancer negative sample obtained in step N2) as a final prostate cancer negative sample.

13. The method according to claim 12, comprising the steps of: Nl) detecting the absolute quantification of the expression of the PCA3 and SPDEF genes in a sample by using a reagent combination of a digital PCR system based on the principle of real-time fluorescent nucleic acid isothermal amplification detection, calculating a PCA3 score according to the absolute quantification results, and classifying the sample into a first prostate cancer negative sample and a first prostate cancer positive sample according to the PCA3 score; ​ ​ ​ ​ ​ N2) using a reagent for detecting biomarker gene ERG based on the detection principle of real-time fluorescent nucleic acid isothermal amplification to detect the expression of ERG gene in the first prostate cancer negative sample obtained in step N1) by absolute quantification, and calculating the ERG score according to the absolute quantification result of the expression of ERG gene and the absolute quantification result of the expression of SPDEF gene in the corresponding sample obtained in step N1), and according to the ERG score, the first prostate cancer negative sample obtained in step N1) is again divided into a second prostate cancer negative sample and a second prostate cancer positive sample; and N3) combining 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 taking the second prostate cancer negative sample obtained in step N2) as the final prostate cancer negative sample.

Images