Plasma exosomal long-chain RNA marker combination and kit for clinical diagnosis of prostate cancer and use

Abstract

The present invention belongs to the technical field of medical diagnosis. Provided are a marker and a kit for the clinical diagnosis of prostate cancer and the use. By means of integrating the expression or variation of multiple genes, the marker can more comprehensively reflect the biological characteristics of prostate cancer, thereby improving the diagnostic accuracy. Since prostate cancer may present no obvious symptoms in the early stage, such a highly sensitive marker can assist physicians in detecting prostate cancer in the early stage, and can thus enhance the therapeutic efficacy and patient survival rate. The kit and system based on the marker enable the diagnosis or prediction of prostate cancer in a subject by means of acquiring detection information of the marker and combining the information with a preset threshold, thereby allowing for the efficient processing of a large volume of data and providing accurate diagnostic results. Therefore, the present invention not only contributes to the diagnosis and treatment of prostate cancer, but may also offer new insights into the pathogenesis and prevention of prostate cancer.

Description

Plasma exosome long-chain RNA marker combination, kit and application for clinical diagnosis of prostate cancer TECHNICAL FIELD

[0001] The present application relates to the field of medical diagnosis, in particular to a plasma exosome long-chain RNA marker combination, kit and application for clinical diagnosis of prostate cancer. BACKGROUND

[0002] Prostate cancer is one of the most common malignant tumors in men worldwide, and its high incidence and mortality rate pose a serious threat to public health. Although in the past three decades, serum prostate-specific antigen (PSA) and ultrasound technology have played an important role in the clinical screening of prostate cancer, especially the introduction of PSA has significantly improved the early screening and diagnosis level of prostate cancer, but the low specificity and high false positive rate of PSA diagnosis are still prominent, leading to a large number of unnecessary follow-up examinations such as prostate biopsy, which brings economic burden and physical trauma to patients. Prostate biopsy, as the gold standard for the diagnosis of prostate cancer, its high cost and potential complications further exacerbate the problems in the diagnosis process. Therefore, finding an accurate and economical method for prostate cancer risk assessment has become an urgent need in clinical practice.

[0003] In recent years, the rapid development of liquid biopsy technology has provided a new way for the early diagnosis of prostate cancer. Liquid biopsy technology detects tumor-related molecular markers in body fluids (such as serum and urine) to achieve non-invasive diagnosis of diseases. Among the various technical paths of liquid biopsy, exosomes are considered to have great potential in the early diagnosis of prostate cancer due to their unique biological characteristics and wide sources. As an important carrier of intercellular communication, exosomes can carry a variety of biologically active molecules including DNA, RNA, proteins and small molecule metabolites. In prostate cancer, exosomes secreted by tumor cells not only reflect the biological characteristics of the tumor itself, but also may carry information reflecting the patient's overall immune status and other tissue and organ conditions. In particular, exoRNA in exosomes, due to its relatively abundant content and variety, has become an important candidate marker for liquid biopsy diagnosis.

[0004] Current research on prostate cancer liquid biopsy based on exosome RNA is still in its early stages, and most studies only focus on the screening and verification of a few indicators, lacking a high-throughput strategy that comprehensively reflects the complexity of tumor progression and the overall state of patients. In addition, some existing new indicators such as PCA3, PCA3 score, TMPRSS2:ERG score, TSP-1, CSTD, etc. have limited diagnostic efficiency in clinical practice, making it difficult to meet the needs of precise diagnosis of prostate cancer. TECHNICAL PROBLEM

[0005] In view of the high false positive rate of prostate cancer diagnosis, especially PSA screening, the high cost and risk of prostate biopsy, and the limitations of existing liquid biopsy technology, the existing research flux is low, the index is single, and the complexity of the disease course and the overall condition of the patient cannot be comprehensively reflected. No literature and patents report the technical status of plasma exosome long-chain RNA diagnosis of prostate cancer. The present application aims to provide a plasma exosome long-chain RNA marker, kit and application for clinical diagnosis of prostate cancer. By integrating multiple long-chain RNA markers, the specificity and accuracy of prostate cancer diagnosis are improved, the cost of diagnosis is reduced, and a new and effective solution is provided for early diagnosis and risk assessment of prostate cancer. Technical solution

[0006] In order to achieve the above purpose, the technical scheme adopted by the present application is as follows:

[0007] The present application provides a plasma exosome long-chain RNA marker for clinical diagnosis of prostate cancer, which comprises ENSG00000287249, ENSG00000260258, ENSG00000230149, MTATP6P26 and MBL2.

[0008] The nucleotide sequences of ENSG00000287249, ENSG00000260258, ENSG00000230149, MTATP6P26 and MBL2 are shown in SEQ ID NO: 1-SEQ ID NO: 5.

[0009] The marker further comprises any one or more of ENSG00000274173, OR51F3P, HBB, ENSG00000278943 and PGDP1.

[0010] The nucleotide sequences of ENSG00000274173, OR51F3P, HBB, ENSG00000278943 and PGDP1 are shown in SEQ ID NO: 6-SEQ ID NO: 10.

[0011] The marker further comprises any one or more of ENSG00000218730, RNA5SP182, SETD6P1, ENSG00000253993, PIGR, GPR34, ENSG00000228335, IGKV1-13, ENSG00000258971 and BTBD19.

[0012] The nucleotide sequences of the ENSG00000218730, RNA5SP182, SETD6P1, ENSG00000253993, PIGR, GPR34, ENSG00000228335, IGKV1-13, ENSG00000258971 and BTBD19 are shown in SEQ ID NO: 11-SEQ ID NO: 20.

[0013] The exosome can also be derived from any one of blood, serum or urine.

[0014] The application provides application of a reagent for clinical diagnosis of prostate cancer, which is a plasma exosome long-chain RNA marker gene expression level, in preparation of a product for clinical diagnosis of prostate cancer.

[0015] The expression level includes RNA, DNA methylation, protein, peptide or their combination expression level.

[0016] The detection is carried out by measuring the level of RNA, DNA methylation, protein or peptide, wherein the measurement of RNA and / or cDNA reverse transcribed from mRNA is amplified.

[0017] The measurement of RNA includes RNA / DNA hybridization analysis, RNA Northern blot analysis, RNA in situ analysis, real-time PCR analysis, quantitative PCR analysis, real-time quantitative PCR analysis, in situ RT-PCR analysis, digital PCR, DNA chip analysis, quantitative PCR array analysis, gene expression sequence analysis, RNA sequencing analysis, next-generation sequencing analysis, branched DNA analysis, detection of RNA and DNA expression level using fluorescence in situ hybridization, analysis using RNA amplification and detection technology and analysis using RNA capture and detection technology.

[0018] The clinical diagnosis of prostate cancer includes distinguishing a prostate cancer subject from other subjects; wherein the other subjects include healthy subjects, chronic prostatitis subjects, acute prostatitis subjects, prostatic hyperplasia subjects or other prostate cancer suspicious subjects; the other prostate cancer suspicious subjects are subjects suggested to be suspicious of prostate cancer by other clinical signs, clinical tests or clinical examinations; the clinical signs include suspicious nodules touched by rectal finger diagnosis; the clinical tests include that the serum total PSA, free PSA or the ratio of free PSA to total PSA is not within the normal range; the clinical examinations include that suspicious echoes are visible by B-ultrasound, suspicious lesions are visible by CT or MRI examination or other examinations suggest suspicious lesions in the prostate.

[0019] The product for clinical diagnosis of prostate cancer includes a chip, a kit or a nucleic acid membrane strip.

[0020] The application provides a kit for clinically diagnosing prostate cancer, which comprises the plasma exosome long-chain RNA marker for clinically diagnosing prostate cancer.

[0021] The kit further comprises exosome extraction reagents, reagents for separating mRNA from samples, cDNA reverse transcription, cDNA pre-amplification and PCR detection.

[0022] Further, the reagents for PCR detection comprise upper and lower stream primers of PCR with nucleotide sequences as shown in SEQ ID NO: 22-SEQ ID NO: 69 and PCR detection probes with nucleotide sequences as shown in SEQ ID NO: 70-SEQ ID NO: 93.

[0023] The kit further comprises one or more of DNA polymerase, PCR buffer, positive control and negative control.

[0024] Further, the positive control is a sample of target DNA sequences of each index synthesized in vitro, and the negative control is pure water free of DNase and RNase.

[0025] The application provides a system based on the above application, which comprises:

[0026] A detection module is configured to detect the expression level of the plasma exosome long-chain RNA marker gene to obtain gene expression data.

[0027] A data analysis module is configured to analyze the obtained gene expression data to obtain a gene expression test score.

[0028] A diagnosis evaluation module is configured to compare the obtained gene expression test score with a predetermined screening, diagnosis and cancer monitoring management score threshold to make a diagnosis result.

[0029] A display module is configured to display the clinical screening and diagnosis result.

[0030] The application provides a computer device comprising a memory, a processor and a computer program stored in the memory and executable on the processor, wherein the processor executes the computer program to implement the steps of the above application.

[0031] The application provides a computer readable storage medium storing a computer program, wherein the computer program is executable on a processor to implement the steps of the above application. Advantages

[0032] Compared with the prior art, the application has the following technical effects:

[0033] The application provides an exosome-derived long-chain RNA marker combination for clinical diagnosis of prostate cancer. Exosomes are important mediators of intercellular communication, and the long-chain RNA contained therein often exhibits a specific expression pattern under disease conditions, which provides a new biomarker for early diagnosis of prostate cancer. By combining the expression or variation of multiple genes, the biological characteristics of prostate cancer can be more comprehensively reflected, and the diagnostic specificity and accuracy are higher than those of a single marker, the false positive rate is reduced, unnecessary further examination (such as prostate biopsy) and medical burden of patients are reduced; since long-chain RNA plays an important regulatory role in the occurrence and development of tumors, detection of the marker combination helps to find lesions in the early stage of prostate cancer, provides the possibility for early intervention and treatment, and thus improves the survival rate and quality of life of patients; long-chain RNA not only comes from tumor cells, but also may reflect the state of other tissues and organs in the body, so the marker combination can more comprehensively evaluate the overall condition of patients, including immune status and tumor microenvironment, and provide an important reference for developing personalized treatment plans.

[0034] The application provided by the application significantly improves the accuracy of clinical diagnosis of prostate cancer by detecting the expression level of the exosome-derived long-chain RNA marker combination. The detection range is not limited to RNA expression level, but also includes DNA methylation, protein, peptide or their combination. This multi-level and multi-dimensional detection strategy can more comprehensively reflect the disease state and further improve the sensitivity and specificity of diagnosis. Various detection methods such as RNA / DNA hybridization analysis, RNA Northern blotting analysis, real-time PCR analysis, quantitative PCR analysis, etc. are common techniques in modern molecular biology, with high sensitivity, high specificity and high throughput, suitable for large-scale clinical sample detection, not only suitable for early screening of prostate cancer, but also can assist doctors in differential diagnosis under complex clinical background, with broad clinical application prospect. It can be applied to various product forms such as chips, kits or nucleic acid membrane strips, especially as a kit, which is convenient for widespread use in medical institutions, and also facilitates standardized operation and quality control. By detecting the expression level of the exosome-derived long-chain RNA marker combination, the application shows significant technical advantages and application potential in the clinical diagnosis of prostate cancer, and is expected to provide strong support for early diagnosis, differential diagnosis and personalized treatment of prostate cancer.

[0035] The kit for clinically diagnosing prostate cancer provided by the application integrates exosome extraction reagents and exosome-derived long-chain RNA marker combination detection reagents, so that the whole process from sample collection to result analysis becomes efficient and convenient, and clinicians and laboratory technicians can quickly complete the preliminary screening and diagnosis of prostate cancer; the kit can accurately identify specific biomarkers related to prostate cancer, thereby improving the sensitivity and specificity of diagnosis, which is of great significance for early detection of prostate cancer and avoiding misdiagnosis and missed diagnosis; the kit contains upstream and downstream primers and detection probes for PCR, which are carefully designed to specifically amplify and detect target RNA sequences, and the selection of fluorescent groups (such as FAM, HEX, ROX, Cy5, and Cy5.5) provides diversified detection signals for multi-channel simultaneous detection; the kit for clinically diagnosing prostate cancer integrates exosome extraction, RNA marker detection, and advanced PCR technology, which provides strong support for early diagnosis, differential diagnosis, and personalized treatment of prostate cancer, and its efficient convenience, high sensitivity and specificity, standardization, and repeatability make the kit have a broad prospect in clinical application.

[0036] The system for clinically diagnosing prostate cancer provided by the application integrates subject information acquisition, clinical screening, and diagnosis evaluation modules, realizes the automation process from information input to result output, and greatly improves the efficiency of prostate cancer diagnosis; by detecting specific exosome-derived long-chain RNA marker combinations and using machine learning algorithms to analyze the detection information, whether the subject is suffering from prostate cancer can be accurately determined; the built-in data analysis and diagnosis evaluation module of the system uses computer programs for data processing and diagnosis decision-making, realizing intelligent diagnosis. The expression test score calculated by the algorithm is compared with the predetermined critical value, and the diagnosis result can be automatically made, reducing the interference of human factors; the detection module can automatically detect the exosome-derived long-chain RNA marker combination, and the display module can automatically display the clinical screening and diagnosis results, improving the work efficiency and timeliness of diagnosis; the system supports multiple display modes (such as display, printing, and broadcasting), which can be flexibly selected and expanded according to actual needs; by detecting the exosome-derived long-chain RNA marker combination, the system can find abnormal signals in the early stage of prostate cancer, which helps to realize early diagnosis and intervention, improve treatment effect and patient survival rate; the system provides a basis for doctors to develop personalized treatment plans, selects appropriate treatment methods and drugs according to the specific conditions of patients, and improves the pertinence and effectiveness of treatment; the large amount of detection data and diagnosis results collected by the system can also provide strong support for the research work of prostate cancer, promote the research progress and technological innovation in related fields. BRIEF DESCRIPTION OF DRAWINGS

[0037] Figure 1 is a ROC curve diagram of the 5-gene combination kit of the present application for detection;

[0038] Figure 2 is a ROC curve diagram of the 10-gene combination kit of the present application for detection;

[0039] Figure 3 is a ROC curve diagram of the 20-gene combination kit of the present application for detection;

[0040] Figure 4 is a flow chart of the application process and simplified application process of the present application;

[0041] Figure 5 is a ROC curve diagram of the 20-gene combination kit of the present application for detection;

[0042] Figure 6 is the sensitivity and specificity of the 5-gene, 10-gene, and 20-gene combination kits of the present application for detection;

[0043] Figure 7 is the sensitivity and specificity of the 5-gene combination kit of the present application for detection;

[0044] Figure 8 is the sensitivity and specificity of the 10-gene combination kit of the present application for detection;

[0045] Figure 9 is the sensitivity and specificity of the 20-gene combination kit of the present application for detection. Embodiments of the present application

[0046] In order to enable persons skilled in the art to better understand the present application, the technical solutions in the embodiments of the present application will be described clearly and completely below in conjunction with the accompanying drawings of the embodiments of the present application. Obviously, the described embodiments are only a part of the embodiments of the present application, rather than all the embodiments. Based on the embodiments in the present application, all other embodiments obtained by persons skilled in the art without creative labor should fall within the scope of protection of the present application.

[0047] The specific experimental steps or conditions not mentioned in the embodiments can be performed according to the conventional experimental steps or conditions described in the literature in the art. The reagents or instruments not mentioned by the manufacturer are all conventional reagent products that can be obtained by purchase.

[0048] The patient samples designed in the present application have obtained the approval of Xijing Hospital Ethics Committee (ID: KY20242271-C-1) and the informed consent forms of the patients have been signed.

[0049] Example 1

[0050] 1. Sample collection and pretreatment

[0051] 1.1 Sample collection

[0052] Collect 431 cases of PSA elevated patients before prostate biopsy, using negative pressure blood collection tube with EDTA anticoagulant (blood volume about 4-5 mL) to extract 4 mL of patient's venous blood, and record the patient's basic treatment process and information, including tPSA, fPSA and testosterone levels of hospitalized patients.

[0053] 1.2 Sample processing

[0054] Turn the blood collection tube upside down 3-5 times after blood collection to mix the blood and anticoagulant thoroughly; place the sample tube in a 4°C refrigerator and centrifuge within 2 hours; pre-cool the 4°C centrifuge 15 minutes in advance, centrifuge at 3000 rpm for 10 minutes to separate the plasma and blood cells; use a pipette to aspirate the plasma sample, try not to aspirate the lower blood cells to avoid the influence of hemoglobin on subsequent experiments; if possible, also save the white film-like sample between the plasma and blood cells, store another tube for subsequent experiments.

[0055] 1.3 Sample freezing and transportation

[0056] Use an external spin-freezing tube to sub-pack the centrifuged sample (recommended to use Corning), considering that the plasma sample should be minimized to reduce repeated freezing and thawing, the plasma and blood cells can be frozen for 5-10 tubes, each 200 μL~400 μL, which can meet the needs of daily experiments; mark the patient's name, sample number and collection time on each freezing tube; store the sub-packed sample in a -80°C refrigerator to minimize repeated freezing and thawing; express delivery can choose to place the sample in a freezing box (it is best to have a plastic bag outside to avoid sample scattering) in 1 d~2 d to arrive.

[0057] 2. Exosome RNA extraction

[0058] Use QIAGEN's exoRNeasy Midi Kit (Cat. No.77144) to extract plasma exosome RNA (exoRNA), follow the kit instructions to ensure the extraction process is pollution-free and efficient.

[0059] 3. RNA reverse transcription, library construction and sequencing

[0060] Reverse transcribe the extracted exosome RNA to generate cDNA; use a high-throughput sequencing platform (such as Illumina) to construct and sequence the cDNA library, and Wuhan Kangmei Technology Co., Ltd. is responsible for completing the reverse transcription, library construction and sequencing work.

[0061] 4. Data processing and analysis

[0062] 4.1 Sequencing data quality control

[0063] Quality control of sequencing raw data, removal of low-quality sequences and adapter sequences, statistics of exoRNA species and quantity of each patient,

[0064] After obtaining the sequencing information of all patients, it was found that the known species of exoRNA of each patient was more than 15000, and the average number of new exoRNA species was more than 40000. The above sequencing library capacity and depth can completely meet the screening of a group of optimal RNA combinations for diagnosing prostate cancer.

[0065] 4.2 Differential expression analysis

[0066] Differential expression analysis between prostate cancer (PCA) and benign prostate disease (BPD) patients was performed using bioinformatics tools (such as DESeq2), and differential expression genes were screened, including up-regulated and down-regulated genes. It was found that there were 3121 differential expression genes between prostate cancer patients and benign prostate disease patients: 1499 up-regulated genes and 1622 down-regulated genes.

[0067] 4.3 Machine learning model construction

[0068] Random forest method (Random Forest) was used for machine learning according to all differential genes, and five-fold cross-validation method was used to evaluate the model performance, and the optimal RNA combination was screened.

[0069] The diagnostic accuracy of the model for prostate cancer was evaluated, and the specific results are shown in Figure 1.

[0070] As shown in Figure 1, the results show that the 5-gene kit consisting of ENSG00000287249, ENSG00000260258, ENSG00000230149, MTATP6P26 and MBL2 can distinguish prostate cancer and benign prostate in prostate tissue samples, and the diagnostic accuracy for prostate cancer is 80.56%, and the area under the ROC curve is 0.873.

[0071] As shown in Figure 2, the results show that the 10-gene kit consisting of ENSG00000287249, ENSG00000260258, ENSG00000230149, MTATP6P26, MBL2, ENSG00000274173, OR51F3P, HBB, ENSG00000278943 and PGDP1 can distinguish prostate cancer and benign prostate in prostate tissue samples, and the diagnostic accuracy for prostate cancer is 91.47%, and the area under the ROC curve is 0.918.

[0072] From the data of FIG. 3, the results show that the 20-gene set consisting of ENSG00000287249, ENSG00000260258, ENSG00000230149, MTATP6P26, MBL2, ENSG00000274173, OR51F3P, HBB, ENSG00000278943, PGDP1, ENSG00000218730, RNA5SP182, SETD6P1, ENSG00000253993, PIGR, GPR34, ENSG00000228335, IGKV1-13, ENSG00000258971 and BTBD19 can distinguish prostate cancer and benign prostate in prostate tissue samples, with a diagnosis accuracy of 94.7% for prostate cancer, and an area under the ROC curve value of 0.974, which is a very high area under the ROC curve value for the diagnosis of prostate cancer.

[0073] Further analysis of the differential genes was performed using unsupervised autonomous learning algorithm to identify the most core gene combination. Five, ten and twenty core genes were selected as markers for the diagnosis of prostate cancer. First, the entire sample data was converted into R language recognizable data, and the data was converted into NumPy array to ensure serializability. Five-fold cross-validation was defined, and four-fifths of the samples were extracted for establishing a diagnostic model, and the remaining one-fifth of the samples were used to verify the established sample model. By initializing variables, setting parameter distribution, creating a random forest model, using random search for hyperparameter optimization, the best RNA combination and related parameters for diagnosing prostate cancer were generated. The model was retrained using the best parameters and evaluated. Subsequently, the data was standardized, the best model was trained, and the receiver operating characteristic curve (ROC) was plotted and the accuracy of the previously established training model was calculated. The true label and predicted probability of the entire test set were saved and output, and the above five, ten and twenty core genes and prediction model were obtained.

[0074] The long-chain RNA marker combination for the clinical diagnosis of prostate cancer is: ENSG00000287249, ENSG00000260258, ENSG00000230149, MTATP6P26 and MBL2, the nucleotide sequence is shown as SEQ ID NO: 1-SEQ ID NO: 5, and the highest number of Reads is selected for the exon (Exon).

[0075] The long-chain RNA marker combination for clinical diagnosis of prostate cancer also includes ENSG00000274173, OR51F3P, HBB, ENSG00000278943 and PGDP1, the nucleotide sequence is shown as SEQ ID NO: 6-SEQ ID NO: 10, and the highest number of screened exons (Exon) is Reads.

[0076] The long-chain RNA marker combination for clinical diagnosis of prostate cancer also includes ENSG00000218730, RNA5SP182, SETD6P1, ENSG00000253993, PIGR, GPR34, ENSG00000228335, IGKV1-13, ENSG00000258971 and BTBD19, the nucleotide sequence is shown as SEQ ID NO: 11-SEQ ID NO: 20, the sequence number of the internal reference gene GADPH is shown as SEQ ID NO: 21, and the highest number of screened exons (Exon) is Reads.

[0077] Example 2

[0078] The screened RNA combination is verified using another set of independent sample set (containing prostate cancer patients and benign prostate disease patients) to evaluate its stability and reliability in different populations. The verified RNA combination is compared with the existing diagnostic method (such as prostate biopsy) to evaluate its clinical application value in early diagnosis of prostate cancer, prediction of disease progression and prognosis evaluation.

[0079] Prostate biopsy: Prostate biopsy of 431 patients showed that 259 patients were prostate cancer patients and 172 patients were benign prostate disease patients, which was consistent with the actual situation of prostate biopsy in the clinic.

[0080] Based on Example 1, the long-chain RNA marker combination screened in Example 1 is verified by ENSG00000287249, ENSG00000260258, ENSG00000230149, MTATP6P26, MBL2, ENSG00000274173, OR51F3P, HBB, ENSG00000278943, PGDP1, ENSG00000218730, RNA5SP182, SETD6P1, ENSG00000253993, PIGR, GPR34, ENSG00000228335, IGKV1-13, ENSG00000258971 and BTBD19 to form a 5-gene, 10-gene and 20-gene kit for diagnosing prostate cancer in prostate tissue samples.

[0081] The specific evaluation process and application flow are shown in FIG. 4.

[0082] 1. Sample collection

[0083] Patient group: 431 blood samples were collected from patients before prostate biopsy;

[0084] 2. Sample processing

[0085] The blood sample exosome RNA was extracted and purified according to the method of Example 1, and long-chain RNA was isolated from the extracellular vesicle.

[0086] 3. Long-chain RNA detection

[0087] Primers were designed for the screened long-chain RNA markers (ENSG00000287249, ENSG00000260258, ENSG00000230149, MTATP6P26, MBL2, ENSG00000274173, OR51F3P, HBB, ENSG00000278943, PGDP1, ENSG00000218730, RNA5SP182, SETD6P1, ENSG00000253993, PIGR, GPR34, ENSG00000228335, IGKV1-13, ENSG00000258971, and BTBD19), and detection was performed using multiplex fluorescence digital quantitative PCR (ddPCR, digital droplet-PCR) or other high-sensitivity and high-specificity detection methods.

[0088] By comparing the above sequences, we obtained the similarity of the above 20 genes as follows, in order to separate similar genes in the experiment to obtain the best detection effect of the multiplex fluorescence digital quantitative PCR (ddPCR, digital droplet-PCR).

[0089] The weight and parameters of the following 20 genes obtained by unsupervised deep machine learning are as follows:

[0090] Feature Importance Abs Weight ENSG00000287249 0.00795 0.00795 ENSG00000260258 0.006474 0.006474 MTATP6P26 0.005618 0.005618 MBL2 0.005434 0.005434 ENSG00000230149 0.004772 0.004772 ENSG00000274173 0.004365 0.004365 ENSG00000228335 0.004192 0.004192 HBB 0.004119 0.004119 PIGR 0.004087 0.004087 RNA5SP182 0.00378 0.00378 ENSG00000278943 0.003759 0.003759 GPR34 0.003636 0.003636 OR51F3P0 0.003493 0.003493 ENSG00000287103 0.003485 0.003485 BTBD19 0.003481 0.003481 PGDP1 0.003451 0.003451 ENSG00000253993 0.00344 0.00344 ENSG00000260798 0.003379 0.003379 HBA2 0.003365 0.003365 ENSG00000218730 0.003129 0.003129

[0091] .

[0092] Based on the above research foundation, we design 20 primers and probe sequences of the genes to be detected and GADPH internal reference genes as shown in SEQ ID NO: 22-SEQ ID NO: 93 (if there is no gene name, only the last 4 digits of the ENSG number gene is used for preliminary naming).

[0093] 4. Data analysis

[0094] The long-chain RNA markers are compared with the existing prostate cancer diagnosis method of prostate biopsy. According to the diagnosis results of the subjects and the plasma exosome RNA detection results, the ROC curve of the plasma exosome RNA is drawn respectively by SPSS13.0 software, and the advantages in diagnosis accuracy, sensitivity and specificity are evaluated; if all genes are used for analysis, a very high diagnosis efficiency can be generated for prostate cancer and non-prostate cancer patients, and 20 main genes for diagnosing prostate cancer are obtained by using the unsupervised autonomous deep machine learning method, and the ROC curve is shown in FIG. 5.

[0095] As shown in the data of FIG. 5, the results show that the 20-gene group consisting of ENSG00000287249, ENSG00000260258, ENSG00000230149, MTATP6P26, MBL2, ENSG00000274173, OR51F3P, HBB, ENSG00000278943, PGDP1, ENSG00000218730, RNA5SP182, SETD6P1, ENSG00000253993, PIGR, GPR34, ENSG00000228335, IGKV1-13, ENSG00000258971 and BTBD19 can distinguish prostate cancer and benign prostate in prostate tissue samples, and the diagnostic accuracy for prostate cancer is 92.64%, and the area under the ROC curve is 0.930, which is a very high area under the ROC curve for the diagnosis of prostate cancer.

[0096] According to the above results, we used the 5-gene, 10-gene and 20-gene group of plasma exosome long-chain RNA combinations for preliminary verification in 200 suspected prostate cancer patients, and the specific results are shown in FIGS. 6-9.

[0097] As shown in the data of FIGS. 6-9, the diagnostic sensitivity and specificity: the diagnostic sensitivity of the 5-gene RNA combination is 85%, and the specificity is 86.0%, showing good diagnostic performance; the diagnostic sensitivity of the 10-gene RNA combination is 88.0%, and the specificity is 90.0%, which is obviously improved compared with the 5-gene combination; the diagnostic sensitivity of the 20-gene RNA combination is 93.0%, and the specificity is 93.0%, showing extremely high diagnostic accuracy.

[0098] The area under the ROC curve and the Youden index: the diagnostic ROC curve area of the 5-gene RNA combination is 0.855, and the Youden index is 0.710, the diagnostic ROC curve area of the 10-gene RNA combination is 0.890, and the Youden index is 0.780; the diagnostic ROC curve area of the 20-gene RNA combination is 0.930, and the Youden index is 0.860. With the increase of the number of genes, the AUC value gradually increases, and the Youden index increases from 0.710 (5-genes) to 0.860 (20-genes), indicating that the 20-gene combination has the best comprehensive ability in identifying true prostate cancer patients and excluding non-patients.

[0099] In summary, the present experiment successfully verified the efficiency of different numbers of plasma exosome long-chain RNA combinations in the diagnosis of prostate cancer. With the increase of the number of genes, the sensitivity and specificity of the diagnosis are significantly improved, and the area under the ROC curve and the Youden index also show a gradual increasing trend. In particular, the 20-gene RNA combination has extremely high diagnostic accuracy and comprehensive ability, indicating its great potential and application prospects in the early screening and diagnosis of prostate cancer, providing a new idea and direction for personalized medicine and early intervention of prostate cancer.

[0100] The above is only to illustrate the technical idea of the present application, and cannot limit the protection scope of the present application. Any modification made according to the technical idea of the present application on the basis of the technical scheme falls within the protection scope of the claims of the present application.

Claims

1. A plasma exosomal long-chain RNA marker for clinical diagnosis of prostate cancer, characterized in that, The marker comprises ENSG00000287249, ENSG00000260258, ENSG00000230149, MTATP6P26 and MBL2; The nucleotide sequences of the ENSG00000287249, ENSG00000260258, ENSG00000230149, MTATP6P26 and MBL2 are shown in SEQ ID NO: 1-SEQ ID NO:

5. 2.The plasma exosomal long RNA marker for clinical diagnosis of prostate cancer according to claim 1, characterized in that, The marker further comprises any one or more of ENSG00000274173, OR51F3P, HBB, ENSG00000278943 and PGDP1; The nucleotide sequences of the ENSG00000274173, OR51F3P, HBB, ENSG00000278943 and PGDP1 are shown in SEQ ID NO: 6-SEQ ID NO:

10. 3.The plasma exosomal long RNA marker for clinical diagnosis of prostate cancer according to claim 2, characterized in that, The marker further comprises any one or more of ENSG00000218730, RNA5SP182, SETD6P1, ENSG00000253993, PIGR, GPR34, ENSG00000228335, IGKV1-13, ENSG00000258971 and BTBD19; The nucleotide sequences of the ENSG00000218730, RNA5SP182, SETD6P1, ENSG00000253993, PIGR, GPR34, ENSG00000228335, IGKV1-13, ENSG00000258971 and BTBD19 are shown in SEQ ID NO: 11-SEQ ID NO:

20. 4.The plasma exosomal long RNA marker for clinical diagnosis of prostate cancer according to any one of claims 1-3, characterized in that, The exosome can also be derived from any one of blood, serum or urine.

5. Use of a reagent for detecting the expression level of the plasma exosome long-chain RNA marker gene for clinical diagnosis of prostate cancer according to any one of claims 1-3 in the preparation of a product for clinical diagnosis of prostate cancer.

6. Use according to claim 5, characterized in that, The expression level comprises RNA, DNA methylation, protein, peptide or a combination thereof expression level.

7. Use according to claim 5, characterized in that, The detection is carried out by measuring the level of RNA, DNA methylation, protein or peptide; wherein the measurement of RNA and / or cDNA reverse transcribed from mRNA is amplified.

8. Use according to claim 7, characterized in that, The measurement of RNA comprises RNA / DNA hybridization analysis, RNA Northern blot analysis, RNA in situ analysis, real-time PCR analysis, quantitative PCR analysis, real-time quantitative PCR analysis, in situ RT-PCR analysis, digital PCR, DNA chip analysis, quantitative PCR array analysis, gene expression sequence analysis, RNA sequencing analysis, next-generation sequencing analysis, branched DNA analysis, detection of RNA and DNA expression level using fluorescence in situ hybridization, analysis using RNA amplification and detection technology and analysis using RNA capture and detection technology.

9. Use according to claim 5, characterized in that, The clinical prostate cancer diagnosis comprises distinguishing the prostate cancer subject from other subjects; wherein the other subjects comprise healthy subjects, chronic prostatitis subjects, acute prostatitis subjects, benign prostatic hyperplasia subjects or other prostate cancer suspicious subjects; the other prostate cancer suspicious subjects are subjects suggested to be suspicious of prostate cancer by other clinical signs, clinical tests or clinical examinations; the clinical signs comprise suspicious nodules touched by rectal digital examination; the clinical tests comprise serum total PSA, free PSA or the ratio of free PSA to total PSA out of the normal range; the clinical examinations comprise suspicious echoes visible by B-ultrasound, suspicious lesions visible by CT or MRI examination or other examinations suggesting suspicious lesions in the prostate.

10. Use according to claim 5, characterized in that, The product for clinical prostate cancer diagnosis comprises a chip, a kit or a nucleic acid membrane strip.

11. A kit for the clinical diagnosis of prostate cancer, characterized in that, The kit comprises the plasma exosome long-chain RNA marker for clinical diagnosis of prostate cancer according to any one of claims 1-3.

12. The kit for the clinical diagnosis of prostate cancer according to claim 11, characterized in that, The kit further comprises exosome extraction reagents, reagents for mRNA separation from samples, cDNA reverse transcription, cDNA pre-amplification and PCR detection.

13. The kit for the clinical diagnosis of prostate cancer according to claim 12, characterized in that, The reagents for PCR detection comprise PCR upper and lower stream primers with nucleotide sequences shown in SEQ ID NO: 22-SEQ ID NO: 69 and PCR detection probes with nucleotide sequences shown in SEQ ID NO: 70-SEQ ID NO:

93.

14. A system based on the use of claim 5, characterized by, The system comprises: a detection module for detecting the gene expression level of the plasma exosome long-chain RNA marker to obtain gene expression data; a data analysis module for analyzing the obtained gene expression data to obtain a gene expression test score; a diagnosis evaluation module for comparing the obtained gene expression test score with a predetermined screening, diagnosis and cancer monitoring management score threshold to make a diagnosis result; a display module for displaying the clinical screening and diagnosis result.

15. A computer device comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, characterized in that, The processor executes the computer program to implement the steps of the application according to any one of claims 5-9.

16. A computer-readable storage medium, the computer-readable storage medium storing a computer program, characterized in that, The computer program is executed by the processor to implement the steps of the application according to any one of claims 5-9.

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