Methods for calculating prostate cancer diagnostic scores and uses thereof - Patents.com

Abstract

The present specification provides a method for calculating a diagnostic score for prostate cancer by combining at least two values. The method includes preparing a sample, obtaining a first value, obtaining a second value, and calculating a diagnostic score. The sample is a urine sample from a subject, and the first value corresponds to the amount of hsa-miR-3659 or hsa-miR-3679-5p derived from extracellular vesicles in the sample, and the second value corresponds to the amount of miRNA derived from extracellular vesicles in the sample. Both the first value and the second value contain information about whether the subject has developed prostate cancer, and the second value corresponds to a normalization coefficient specialized for the first value. The diagnostic score for prostate cancer calculated according to the method is characterized by being able to diagnose prostate cancer. The present specification provides uses of the diagnostic score for prostate cancer.

Description

[Technical field]

[0001] The present invention relates to a technique for a method for calculating a diagnostic score that can provide information about the diagnosis of the onset of prostate cancer by measuring the expression levels of biomarkers contained in the urine of a subject. [Background technology]

[0002] In principle, the standard method for diagnosing prostate cancer is a biopsy, in which a small amount of prostate tissue is taken from a subject, and then the onset of cancer cells is determined. However, a biopsy involves a very painful process for the subject. Therefore, it is not desirable to perform a biopsy only because the subject shows symptoms that are suspicious of the onset of prostate cancer (e.g., urinary symptoms, such as polyuria and painful urination). Therefore, when a subject shows symptoms that are suspicious of the onset of prostate cancer, it is common to take a body fluid (e.g., blood or urine) from the subject, perform an indirect test to check for the onset of prostate cancer, and then determine whether a biopsy is necessary based on these results. Currently, in clinical practice, a prostate-specific antigen (PSA) test has been commonly performed, in which blood is taken from a subject and the concentration of PSA in the blood sample is measured. However, the PSA test has caused controversy regarding its accuracy and diagnostic ability, so there is a need to develop a reliable method for diagnosing prostate cancer non-invasively. Summary of the Invention [Problem to be solved by the invention]

[0003] One aspect of the present invention is to provide a method for calculating a diagnostic score that can provide information about whether a subject will develop prostate cancer.

[0004] Another aspect of the present invention is to provide a method for determining a diagnostic standard for diagnosing prostate cancer from the diagnostic score.

[0005] Yet another aspect of the present invention is to provide a method for providing information about the diagnosis of prostate cancer from a diagnostic score. [Means for solving the problem]

[0006] According to the present specification, a method for calculating a diagnostic score for prostate cancer by combining at least two values ​​is provided. The method includes the steps of preparing a sample from a subject, where the sample is a urine sample; obtaining a first value related to the amount of a first target in the sample, where the first target is hsa-miR-3659 or hsa-miR-3679 derived from extracellular vesicles in the sample, where the first value reflects first information having the ability to diagnose prostate cancer in the subject, but the first value itself cannot be used alone to diagnose prostate cancer in the subject because the first value reflects the first information as well as a first noise, where the first noise is caused by endogenous factors independent of factors related to prostate cancer; obtaining a first value related to the amount of a first target in the sample, where the first target is hsa-miR-3659 or hsa-miR-3679 derived from extracellular vesicles in the sample, where the first value reflects first information as well as a first noise, where the first noise is caused by endogenous factors independent of factors related to prostate cancer; obtaining a second value related to the amount of a second target, where the second target is an miRNA derived from extracellular vesicles in the sample, where the second value reflects second information related to whether the subject has prostate cancer, where the second value reflects third information related to an endogenous factor, where the third information is strongly correlated with the first noise, whereby the first noise reflected in the first value can be controlled by using the second value; and calculating a diagnostic score for prostate cancer by using the first value and the second value, whereby the diagnostic score can be used to diagnose prostate cancer.

[0007] In one embodiment, the second target is hsv2-miR-H9-5p or hsa-miR-1913.

[0008] In one embodiment, the diagnostic score is calculated herein by the ratio of the first value to the second value.

[0009] In one embodiment, the endogenous factors herein include a first condition associated with the sample and a second condition associated with the subject.

[0010] In one embodiment, the first condition comprises one or more selected from the group consisting of: amount of sample, time of sample collection, method of collecting the sample, sample storage period, sample storage temperature, and method of subdividing the sample.

[0011] In one embodiment, the second condition comprises one or more selected from the group consisting of the subject's sex, the subject's age, the subject's race, the subject's weight, the subject's renal function, and the subject's hydration status.

[0012] In one embodiment, the step of obtaining the first value further comprises the steps of: synthesizing a first cDNA of the first target in the sample; amplifying the first cDNA by polymerase chain reaction using a first primer, wherein the first primer is selected from the group consisting of SEQ ID NO:1 to SEQ ID NO:2; and determining the first value from the amplification result of the first cDNA.

[0013] In one embodiment, the step of obtaining the second value may further include the steps of: synthesizing a second cDNA of the second target in the sample; amplifying the second cDNA by polymerase chain reaction using a second primer, wherein the second primer has a sequence that is homologous to the sequence of the second target or a sequence that can bind complementarily to the sequence of the second target; and determining the second value from the results of amplification of the second cDNA.

[0014] In one embodiment, the second target may be hsv2-miR-H9-5p or hsa-miR-1913, and the second primer may be selected from the group consisting of SEQ ID NO:3 and SEQ ID NO:5.

[0015] According to the present specification, a method for determining diagnostic criteria for diagnosing prostate cancer is provided.The method includes: obtaining a first data set, wherein the first data set includes a list of whether each subject of a cohort develops prostate cancer, and a list of diagnostic scores calculated for each subject of the cohort according to the method for calculating diagnostic scores for prostate cancer, wherein the cohort includes at least one subject that is normal or develops benign prostatic hyperplasia, and at least one subject that develops prostate cancer; and determining a diagnostic criterion for diagnosing prostate cancer from the first data set.

[0016] In one embodiment, the diagnostic criterion herein comprises a single value having the same dimensionality as the diagnostic score.

[0017] In one embodiment, the diagnostic criteria herein include one or more probability values ​​for developing prostate cancer.

[0018] According to the present disclosure, there is provided a method for providing information about the diagnosis of onset of prostate cancer in a subject, the method comprising the steps of calculating a diagnostic score for prostate cancer in the subject according to a method for calculating a diagnostic score, and determining a risk factor from the diagnostic score for prostate cancer with reference to at least one predetermined value.

[0019] In one embodiment, the predetermined value herein is a diagnostic criterion determined according to a method for determining a diagnostic criterion. Effect of the Invention

[0020] Information for the non-invasive diagnosis of prostate cancer from a subject's urine sample can be provided using the methods of calculating the diagnostic scores provided herein. [Brief description of the drawings]

[0021] [Figure 1]1 shows a flow chart of a method for calculating a diagnostic score for prostate cancer, where the steps of obtaining a first value and obtaining a second value represent steps that may be performed independently in parallel.

[0022] [Diagram 2] Graphs showing the statistical significance of the difference in diagnostic scores between groups of benign prostatic hyperplasia (BPH) subjects and groups of prostate cancer (PCa) subjects for all subject experimental groups as described in Examples 1 and 2. (a) shows the results of Example 1 (hsv2-miR-H9 vs. hsa-miR-3659), and (b) shows the results of Example 2 (hsa-miR-1913 vs. hsa-miR-3659).

[0023] [Diagram 3] Graphs showing the statistical significance of the difference in diagnostic scores between the group of benign prostatic hyperplasia (BPH) subjects and the group of prostate cancer (PCa) subjects described in Example 3 and Example 4 for all subject experimental groups. (a) shows the results of Example 3 (hsv2-miR-H9 vs. hsa-miR-3679-5p), and (b) shows the results of Example 4 (hsa-miR-1913 vs. hsa-miR-3679-5p).

[0024] [Figure 4] Graphs showing the statistical significance of the difference in diagnostic scores between groups of benign prostatic hyperplasia (BPH) subjects and groups of prostate cancer (PCa) subjects described in Examples 5 and 6 for all subject experimental groups. (a) shows the results of Example 5 (hsv1-miR-H18 vs. hsa-miR-3659), and (b) shows the results of Example 6 (hsv1-miR-H18 vs. hsa-miR-3679-5p).

[0025] [Diagram 5]Graphs showing the statistical significance of the difference in diagnostic scores between the group of benign prostatic hyperplasia subjects (BPH) and the group of prostate cancer subjects (PCa) described in Comparative Example 1 and Comparative Example 2 for all subject experimental groups. (a) shows the results of Comparative Example 1 (hsa-miR-30a-5p vs. hsa-miR-31-5p), and (b) shows the results of Comparative Example 2 (hsa-miR-30c-5p vs. hsa-miR-31-5p).

[0026] [Figure 6] 1 shows graphs showing the statistical significance of the difference in diagnostic scores between groups of benign prostatic hyperplasia (BPH) and prostate cancer (PCa) subjects described in Examples 1 and 2 for groups of subjects in the PSA gray zone (3-10 ng / mL). (a) shows the results of Example 1 (hsv2-miR-H9 vs. hsa-miR-3659), and (b) shows the results of Example 2 (hsa-miR-1913 vs. hsa-miR-3659).

[0027] [Figure 7] Graphs showing the statistical significance of the difference in diagnostic scores between groups of benign prostatic hyperplasia (BPH) and prostate cancer (PCa) subjects described in Examples 3 and 4 for groups of subjects in the PSA gray zone (3-10 ng / mL). (a) shows the results of Example 3 (hsv2-miR-H9 vs. hsa-miR-3679-5p), and (b) shows the results of Example 4 (hsa-miR-1913 vs. hsa-miR-3679-5p).

[0028] [Figure 8] 1 shows graphs showing the statistical significance of the difference in diagnostic scores between groups of benign prostatic hyperplasia (BPH) and prostate cancer (PCa) subjects described in Examples 5 and 6 for groups of subjects in the PSA gray zone (3-10 ng / mL). (a) shows the results of Example 5 (hsv1-miR-H18 vs. hsa-miR-3659), and (b) shows the results of Example 6 (hsv1-miR-H18 vs. hsa-miR-3679-5p).

[0029] [Figure 9] 1 shows graphs showing the statistical significance of the difference in diagnostic scores between groups of benign prostatic hyperplasia (BPH) and prostate cancer (PCa) subjects described in Comparative Example 1 and Comparative Example 2 for groups of subjects in the PSA gray zone (3-10 ng / mL). (a) shows the results of Comparative Example 1 (hsa-miR-30a-5p vs. hsa-miR-31-5p), and (b) shows the results of Comparative Example 2 (hsa-miR-30c-5p vs. hsa-miR-31-5p).

[0030] [Figure 10] 1 is a graph showing receiver operating characteristic (ROC) curves for all groups of subjects in a PSA test.

[0031] [Figure 11] Graphs showing ROC curves for all groups of subjects described in Example 1 and Example 2. (a) shows the ROC curve for Example 1 (hsv2-miR-H9 vs. hsa-miR-3659), and (b) shows the ROC curve for Example 2 (hsa-miR-1913 vs. hsa-miR-3659).

[0032] [Figure 12] Graphs showing ROC curves for all groups of subjects described in Example 3 and Example 4. (a) shows the ROC curve for Example 3 (hsv2-miR-H9 vs. hsa-miR-3679-5p), and (b) shows the ROC curve for Example 4 (hsa-miR-1913 vs. hsa-miR-3679-5p).

[0033] [Figure 13]Graphs showing ROC curves for all groups of subjects described in Example 5 and Example 6. (a) shows the ROC curve for Example 5 (hsv1-miR-H18 vs. hsa-miR-3659), and (b) shows the ROC curve for Example 6 (hsv1-miR-H18 vs. hsa-miR-3679-5p). In this case, the sensitivity and specificity values ​​are not shown separately because the diagnostic performance did not reach the criteria.

[0034] [Figure 14] Graphs showing ROC curves for all groups of subjects described in Comparative Example 1 and Comparative Example 2. (a) shows the ROC curve for Comparative Example 1 (hsa-miR-30a-5p vs. hsa-miR-31-5p), and (b) shows the ROC curve for Comparative Example 2 (hsa-miR-30c-5p vs. hsa-miR-31-5p). In this case, the sensitivity and specificity values ​​are not shown separately because the diagnostic performance did not reach the standard.

[0035] [Figure 15] Graph showing the ROC curve for the group of subjects in the PSA gray zone (3-10 ng / mL) for PSA testing. In this case, the sensitivity and specificity values ​​are not shown separately because the diagnostic performance did not reach the criteria.

[0036] [Figure 16] Graphs showing ROC curves for groups of subjects in the PSA gray zone (3 to 10 ng / mL) in Example 1 and Example 2. (a) shows the ROC curve for Example 1 (hsv2-miR-H9 vs. hsa-miR-3659), and (b) shows the ROC curve for Example 2 (hsa-miR-1913 vs. hsa-miR-3659).

[0037] [Figure 17]Graphs showing ROC curves for groups of subjects in the PSA gray zone (3 to 10 ng / mL) in Example 3 and Example 4. (a) shows the ROC curve for Example 3 (hsv2-miR-H9 vs. hsa-miR-3679-5p), and (b) shows the ROC curve for Example 4 (hsa-miR-1913 vs. hsa-miR-3679-5p).

[0038] [Figure 18] Graphs showing ROC curves for groups of subjects in the PSA gray zone (3-10 ng / mL) in Example 5 and Example 6. (a) shows the ROC curve for Example 5 (hsv1-miR-H18 vs. hsa-miR-3659), and (b) shows the ROC curve for Example 6 (hsv1-miR-H18 vs. hsa-miR-3679-5p). In this case, the sensitivity and specificity values ​​are not shown separately because the diagnostic performance did not reach the standard.

[0039] [Figure 19] Graphs showing ROC curves for groups of subjects in the PSA gray zone (3-10 ng / mL) in Comparative Example 1 and Comparative Example 2. (a) shows the ROC curve (hsa-miR-30a-5p vs. hsa-miR-31-5p) for Comparative Example 1, and (b) shows the ROC curve (hsa-miR-30c-5p vs. hsa-miR-31-5p) for Comparative Example 2. In this case, the values ​​of sensitivity and specificity are not shown separately because the diagnostic performance did not reach the standard. DETAILED DESCRIPTION OF THE PREFERRED EMBODIMENTS

[0040] [Best form] The subject matter disclosed herein will be described in more detail below with reference to the accompanying drawings with respect to some specific embodiments and examples. It should be noted that the accompanying drawings encompass some, but not all, embodiments of the present invention. The subject matter disclosed herein may be embodied in many different forms and should not be construed as being limited to the specific embodiments described herein. Rather, these embodiments are provided so that this disclosure will satisfy applicable legal requirements. Indeed, many modifications and other embodiments of the present invention will occur to those skilled in the art to which the subject matter disclosed herein pertains. Therefore, it should be understood that the subject matter disclosed herein is not limited to the specific embodiments disclosed, and that modifications and other embodiments are intended to be included within the scope of the appended claims.

[0041] Definition of Terms about The term "about" as used herein refers to an amount, level, value, number, frequency, percentage, dimension, number, weight, or length that is modified to the extent of 30, 25, 20, 15, 10, 9, 8, 7, 6, 5, 4, 3, 2, or 1% relative to a reference amount, level, value, number, frequency, percentage, dimension, size, weight, or length.

[0042] Subject The term "subject" as used herein refers to an individual organism exposed to a certain substance (e.g., peptide, etc.). Subject may refer to an independent organism, such as humans and animals, and may also refer to some components of an independent organism, such as tissues and cell parts. This meaning may be interpreted appropriately in the context. The term "subject" may also encompass all other meanings recognized by those skilled in the art.

[0043] diagnosis The term "diagnosis" as used herein collectively refers to all types of direct and indirect actions of determining whether a subject is associated with a certain disease. In this case, the phrase "associated with a certain disease" may include information about the onset of the associated disorder, and the progression of the disorder when the associated disorder develops. In this specification, when the term "diagnosing a certain disease" is described herein, this term should be broadly understood to include confirmation of the onset of a certain disease, as well as the probability, risk, and / or likelihood of the onset of a certain disease. This meaning may be interpreted appropriately in the context. The term "diagnosis" may also include all other meanings recognized by those skilled in the art.

[0044] Biomarkers The term "biomarker" as used herein generally refers to an indicator that can detect changes in a subject's body and includes proteins, DNA, RNA, and / or other metabolic substances. In a narrower sense, the term "biomarker" often refers to a target substance (e.g., a specific protein or miRNA) that reflects information about whether a subject has a specific disease. This meaning may be interpreted appropriately in the context, and the term "biomarker" may include all other meanings recognized by those skilled in the art.

[0045] miRNA The term "miRNA" or "microRNA" as used herein refers to a small unexpressed RNA molecule consisting of 20-25 nucleotides found in plants, animals, viruses, etc. miRNA is known to have functions such as, for example, the control of gene expression. miRNA is found in cells and also in extracellular fluids. In humans, miRNA is particularly found in almost all body fluids, such as serum, plasma, urine, saliva, and tears. Thus, miRNA found in extracellular fluids has been actively investigated for use as a diagnostic biomarker for certain diseases (e.g., cancer). The term "miRNA" or "microRNA" may encompass all other meanings recognized by those skilled in the art.

[0046] Extracellular vesicles The term "extracellular vesicles" as used herein refers to a structure in the form of a microparticle surrounded by a lipid bilayer derived from a cell and having no self-replicating function. The diameter of the extracellular vesicles varies widely from about 20 to 30 nanometers, up to about 10 microns. The extracellular vesicles have various functions in the body of a subject. In this case, the extracellular vesicles have a representative function of wrapping proteins and lipids having various functions in the extracellular vesicles and delivering them to the outside of the cell. The extracellular vesicles are referred to as including all types of ectosomes, microvesicles, microparticles, exosomes, apoptotic bodies, large oncosomes, and exosomes, but the present invention is not limited thereto. The term "extracellular vesicles" may include all other meanings recognized by those skilled in the art.

[0047] Background: Prostate cancer diagnosis Prostate Cancer Diagnosis – Overview In principle, the standard method for diagnosing prostate cancer is a biopsy, in which a small amount of prostate tissue is taken from a subject, and then the development of cancer cells is determined. However, a biopsy involves a very painful process for the subject. Therefore, it is not desirable to perform a biopsy only because the subject shows symptoms that are suspicious of the onset of prostate cancer (e.g., urinary symptoms, such as polyuria and painful urination). Therefore, when a subject shows symptoms that are suspicious of the onset of prostate cancer, it is common to first determine whether a biopsy is necessary by PSA testing. Prostate-specific antigen (PSA) testing is a diagnostic method that includes taking blood from a subject and measuring the concentration of PSA in the blood sample to estimate the probability that the subject will develop prostate cancer. Each of the diagnostic methods is described in more detail below.

[0048] PSA testing PSA testing is a kind of diagnostic method that involves taking blood from a vein of a subject suspected of developing prostate cancer, measuring the concentration of prostate-specific antigen (hereinafter referred to as "PSA") in the blood, and predicting the probability of developing prostate cancer based on the concentration of PSA. Prostate-specific antigen is a protein mainly produced by cells of the prostate gland. PSA is contained in small amounts in the blood of normal subjects without prostate cancer, but the concentration of PSA generally tends to increase in the blood of patients with prostate cancer. Therefore, the concentration of PSA in the blood may be usefully used as an indicator for determining the development of prostate cancer, but experts have various views on the accuracy of the PSA concentration, such as 1) the concentration of PSA in the blood generally tends to increase with age, and 2) the concentration of PSA in the blood does not increase with the type of prostate cancer even if the subject develops cancer. While there is some variability in the specific values ​​disclosed in the literature, generally, when PSA levels in the blood are measured to be in the range of 3 ng / mL to 10 ng / mL, they are considered to be in the gray zone, where it is difficult to ascertain, using a PSA test alone, whether a subject is in a high-risk group for developing prostate cancer.

[0049] biopsy In practice, in order to determine whether a subject will develop prostate cancer, it is necessary to diagnose the onset of prostate cancer by biopsy. This is achieved by a method that involves taking a small amount of prostate tissue from a subject and directly testing whether cancer cells are present in the prostate tissue. This has problems in that 1) the patient experiences considerable pain as a biopsy needle is passed through the subject's anus to take the desired sample, 2) if the site where the cancer cells are present is not accurately located, samples from the area around the site where the biopsy needle passes are taken, which creates a risk of misdiagnosis, and 3) the subject's rectum may be injured during the testing process, which may lead to infection, etc. Therefore, there is a need for auxiliary diagnostic methods to improve the reliability of biopsies and limit them to patients who actually need them. The PSA test has been used as one of these auxiliary diagnostic methods, but its reliability has decreased and it has many limitations in that it is impossible to accurately determine whether prostate cancer will develop, such as when the test result is in the gray zone.

[0050] Background: Screening miRNA biomarkers In order to use a certain miRNA as a biomarker to determine whether a subject has a certain disease, it is first necessary to determine whether a certain miRNA is abnormally expressed in a subject with a certain disease compared to a normal subject. miRNA microarray represents a method for screening a certain miRNA. miRNA microarray is a method for screening the expression levels of most miRNAs known to be expressed in humans from a body fluid sample of a subject. In this case, the expression levels of miRNAs in a sample of a subject are mainly measured using kits (e.g., RNA 6000 Pico Chip Kit, Agilent Technologies, Santa Clara, CA, USA) that are pre-manufactured in the art. The type of miRNA expressed in humans includes about 1,400 miRNAs (including about 1,200 miRNAs from humans and about 150 miRNAs from viruses), which is relatively lower than the number of known human genes. Moreover, the sequences of miRNAs are known in the art. Therefore, it is possible to screen almost all miRNAs in a subject. When using commercially available kits, it is possible to obtain the approximate expression amount of miRNA in the sample of a subject. Based on these results, when the expression amount of miRNA in the sample from the subject with prostate cancer and the normal subject is compared, it is possible to find out which miRNA is abnormally expressed in the subject with prostate cancer. However, the kit can only be used for screening purposes to obtain the approximate expression amount, and also has a problem of normalization, so additional analysis is still required to find biomarkers with accurate analysis ability. miRNA microarrays have the advantage that they can quickly find a group of candidates for biomarkers that can be used for diagnosing prostate cancer, and therefore have been widely used to screen subjects for analysis prior to full analysis work.

[0051] Prior Art Limitations Advantages of using urine samples When it is necessary to diagnose infection of a certain disease and the degree of progression of the disease from a body fluid sample of a subject, the urine of the subject is used as a body fluid sample, and thus has various advantages. First, unlike the case where blood or tissue is used as a sample, it is easy to collect a sample because it does not require the use of a needle, and there is no risk of causing pain to the subject. Furthermore, when a certain disease is a male urological disease, the urological disease occurs in a relatively close vicinity of the urinary tract by the flow of urine. Therefore, it is believed that direct information about the male urological disease is contained in a urine sample compared to a blood sample. Therefore, in many aspects, it is desirable to use a urine sample when a male urological disease is diagnosed.

[0052] Advantages of targeting extracellular vesicle-derived biomarkers Extracellular vesicles are characterized by being composed of a lipid bilayer and therefore having a stable structure. Therefore, the nucleic acids (e.g., DNA, RNA, or miRNA, etc.) or protein fragments, etc., contained in the extracellular vesicles can be kept stable over time unless the extracellular vesicles are intentionally destroyed. This is opposite to the fact that the nucleic acids or protein fragments, etc., directly contained in body fluid samples (blood and urine, etc.) are easily degraded over time by external factors. Therefore, when a substance contained in an extracellular vesicle is used as a biomarker target, there is an advantage that the sample can be stored for a long period of time. Since extracellular vesicles are also contained in urine samples, substances derived from extracellular vesicles may be used as biomarker targets in urine samples after being subjected to an appropriate pretreatment process.

[0053] Problems in measuring extracellular vesicle-derived biomarkers in urine When substances derived from extracellular vesicles in urine are used as biomarker targets, it has the advantages of 1) easy to secure samples, 2) it is advantageous to diagnose male urological diseases, and 3) it is easy to store samples due to the above-mentioned characteristics. However, substances derived from extracellular vesicles have not only advantages but also obvious disadvantages. That is, it has disadvantages in that 1) the absolute amount of substances derived from extracellular vesicles contained in urine (e.g., miRNA, etc.) is small, and 2) the amount of biomarker targets contained in urine varies greatly depending on the condition of the sample or subject. In order to diagnose a certain disease based on the expression amount of a biomarker target contained in a sample, it is necessary to take multiple samples from multiple subjects and compare the expression amount of the biomarker target in each sample. Therefore, it is necessary to develop a diagnostic method that uses substances derived from extracellular vesicles in urine as a biomarker target by overcoming the above-mentioned disadvantages. In order to overcome the above-mentioned disadvantages, a reliable normalization process for the expression amount of the biomarker target in a sample is required.

[0054] Technical Solutions and Limitations of the Prior Art According to the prior art, as one of the normalization processes, it has been attempted to find housekeeping genes for urinary extracellular vesicle-derived biomarkers (e.g., miRNA), but this attempt has failed.It has also been attempted to normalize using the total amount of miRNA in samples (Yun et al., Int Neurourol J 2015;19:17-84), and to avoid the need for normalization by calculating the ratio of up-expressed biomarkers to down-expressed biomarkers (US15 / 550416), but this has limitations in that it has limited effect.

[0055] Methods for calculating diagnostic scores for prostate cancer How to Calculate Diagnostic Scores – An Overview The present specification provides a method for calculating a diagnostic score for prostate cancer using at least two values. The method for calculating a diagnostic score includes preparing a sample, measuring a first value, measuring a second value, and calculating a diagnostic score. In this case, a urine sample from a subject is used as the sample. The first value is a value associated with a first target, i.e., hsa-miR-3659 or hsa-miR-3679 derived from extracellular vesicles. In this case, the miRNA contains information about the onset of prostate cancer. However, since the first value reflects the action of endogenous factors, it is necessary to normalize the first value for use in diagnosing prostate cancer. The second value is a value associated with a second target, i.e., a miRNA derived from extracellular vesicles in the sample. For example, the second target may be hsv2-miR-H9-5p or hsa-miR-1913 derived from extracellular vesicles, but the present invention is not limited thereto. The second value may be used as a normalization factor for the first value, and the second value also includes information about the onset of prostate cancer. The step of measuring the first value and / or the step of measuring the second value may include amplifying the first target and / or the second target by polymerase chain reaction (PCR) and determining the result. A diagnostic score is calculated based on the first value and the second value obtained in the above steps. In this case, the diagnostic score can diagnose the onset of prostate cancer in the subject.

[0056] First feature of the method for calculating the diagnostic score: Use of urine samples The method of calculating diagnostic score provided herein can be used to diagnose whether a subject develops prostate cancer.The method of calculating diagnostic score is characterized by using urine sample to measure the biomarker contained in urine sample.This has the advantage that the method of collecting sample is simple and inexpensive, and does not cause pain to the subject.In addition, since the substance secreted by prostate cells can be directly contained in urine, the method of calculating diagnostic score has the advantage that it can be a more direct method compared to the method of measuring the biomarker associated with prostate cancer from blood sample.

[0057] The second feature of the method for calculating the diagnostic score: measuring miRNA derived from extracellular vesicles The method for calculating a diagnostic score provided herein is to calculate a diagnostic score for prostate cancer by measuring the expression levels of at least two biomarkers in a sample. In this case, the biomarker is characterized in that it is miRNA contained in extracellular vesicles in urine. Since extracellular vesicles have a stable structure surrounded by lipid bilayers, the substances (e.g., miRNA) contained in the extracellular vesicles are effectively protected from the effects of the external environment. Therefore, the extracellular vesicles have the characteristic of retaining the substances therein as long as the extracellular vesicles are not destroyed. Therefore, when the miRNA contained in the extracellular vesicles is used as the target to be measured, it has the advantage that the sample can be stored for a long period of time after it is collected from the subject. In addition, it has the advantage that the storage condition of the sample does not have a large effect on the calculation result of the diagnostic score.

[0058] Third feature of the method for calculating the diagnostic score: measuring the expression level of hsa-miR-3659 or hsa-miR-3679 As disclosed in Korean Patent Application No. 10-2018-0045062, hsa-miR-3659 or hsa-miR-3679 may be used as a biomarker for prostate cancer. The method for calculating a diagnostic score provided herein basically uses a value associated with the expression level of hsa-miR-3659 or hsa-miR-3679 in a subject, and therefore the diagnostic score calculated by the method can diagnose the onset of prostate cancer.

[0059] The fourth feature of the method for calculating diagnostic scores--using a normalization coefficient specialized for hsa-miR-3659 or hsa-miR-3679 The method for calculating diagnostic scores provided herein is characterized by using a normalization coefficient specialized for the expression level of hsa-miR-3659 or hsa-miR-3679 contained in a urine sample. Generally, a biomarker for a housekeeping gene is found and used to normalize the expression level of the biomarker, but the method for calculating diagnostic scores provided herein uses a normalization coefficient specialized for the target hsa-miR-3659 or hsa-miR-3679. When a biomarker for a housekeeping gene is used as a normalization coefficient, it is difficult in that 1) it is generally a very difficult task to find a biomarker for a housekeeping gene, and 2) for miRNA derived from extracellular vesicles in urine, a biomarker associated with a housekeeping gene has not been clearly revealed. On the other hand, if a normalization factor specialized for a target is used, it has the advantages that 1) it is possible to avoid the difficulty of finding biomarkers for housekeeping genes, and 2) it is possible to obtain more reliable results regarding the expression level of the target.

[0060] Fifth feature of the method for calculating the diagnostic score - using factors associated with prostate cancer as normalization coefficients In the method of calculating diagnostic score provided herein, the normalization coefficient is also characterized by comprising information about whether the subject develops prostate cancer.Therefore, one or more types of processed information can be deduced by combining the information about prostate cancer, comprising the expression level of hsa-miR-3659 or hsa-miR-3679, and the information about prostate cancer contained in the normalization coefficient.For example, the processed information can be obtained by amplifying the information about the onset of prostate cancer.

[0061] Use of diagnostic scores The diagnostic scores provided herein 1) may be used to determine diagnostic criteria for the development of prostate cancer, and 2) may be used for methods of diagnosing prostate cancer that reference the diagnostic criteria.

[0062] Sample preparation Sample Preparation – Overview The sample preparation for the subject included in the method for calculating diagnostic score provided herein includes preparing a urine sample for the subject.The urine sample preparation may further include carrying out appropriate pretreatment to measure the amount of miRNA derived from extracellular vesicles contained in the urine sample.According to one embodiment, the sample preparation may include destroying the extracellular vesicles contained in the urine sample.

[0063] Sample Type The sample is a urine sample from a subject. According to one embodiment, the urine sample may be a urine sample collected from a subject first thing in the morning. According to one embodiment, the urine sample may be a supernatant sample of urine collected from a subject. According to one embodiment, the urine sample may be a supernatant sample of a product obtained after the urine of a subject is centrifuged.

[0064] Sample volume The volume of the urine sample is not particularly limited and may be appropriately selected as needed.

[0065] Sample Storage Temperature The storage temperature of the urine sample is not particularly limited, so long as the target biomarkers contained in the sample can be safely stored at that temperature.

[0066] Samples containing extracellular vesicles The urine sample contains extracellular vesicles secreted from the subject's cells. According to one embodiment, the extracellular vesicles may be exosomes. According to one embodiment, the extracellular vesicles may include one or more selected from the group consisting of exosomes, microvesicles, and apoptotic bodies.

[0067] Sample subdivision The urine sample may be used after subdivision if necessary. According to one embodiment, the first sample may be divided into a first subsample and a second subsample. According to one embodiment, the second sample may be divided into three or more subsamples.

[0068] Sample preparation – example In the preparation of the sample, the preparation of the urine sample is not particularly limited as long as it is a step required to obtain the first value and the second value. According to one embodiment, the preparation of the sample may include preparing a urine supernatant sample from the subject. The preparation of the sample may further include pre-treating the sample. The pre-treatment of the sample is not particularly limited as long as it is a step required to measure a value corresponding to the expression level of the miRNA derived from the extracellular vesicles of interest. According to one embodiment, the preparation of the urine sample may further include extracting miRNA in urine using a kit suitable for the urine sample of the subject. In this case, a known kit may be used as the kit, for example, Genolution Urinary miRNA Purification Kit (Genolution Pharmaceuticals Inc., Seoul, Korea), but the present invention is not limited thereto.

[0069] Obtaining a first value Getting the first value - overview In the method of calculating a diagnostic score provided herein, the first value is a value associated with hsa-miR-3659 or hsa-miR-3679 derived from extracellular vesicles, which can diagnose prostate cancer. According to one embodiment, the first value may be a value corresponding to the amount of a first target contained in a sample. In this case, the first target is hsa-miR-3659 and / or hsa-miR-3679 derived from extracellular vesicles. The first value reflects information about whether a subject has prostate cancer. However, since the first value reflects the effects of various endogenous factors together with information about whether a subject has prostate cancer, it is difficult to determine whether a subject has prostate cancer by using the first value alone. According to one embodiment, the first value may simultaneously reflect the first information capable of diagnosing prostate cancer and the first noise caused by endogenous factors independent of the first information. The method for obtaining the first value is not particularly limited as long as it is a method capable of calculating a value corresponding to the amount of hsa-miR-3659 or hsa-miR-3679 derived from extracellular vesicles. According to one embodiment, the step of obtaining the first value may include a step of amplifying one or more miRNAs in the sample using polymerase chain reaction (PCR) and a step of calculating the amount of one or more miRNAs in the sample from the result of the amplification.

[0070] Targeting extracellular vesicles-derived hsa-miR-3659 or hsa-miR-3679 in urine The first value is a value associated with extracellular vesicles-derived hsa-miR-3659 or hsa-miR-3679 that can diagnose prostate cancer. This corresponds to a biomarker found using miRNA assay method that contains information about the onset of prostate cancer. The inventors conducted research and found that extracellular vesicles-derived hsa-miR-3659 and hsa-miR-3679 in the urine of a subject are down-expressed in subjects with prostate cancer compared to normal subjects. Therefore, the method of calculating a diagnostic score provided herein comprises using extracellular vesicles-derived hsa-miR-3659 and / or hsa-miR-3679 contained in a urine sample of a subject as a target to calculate the amount of target contained in the sample.

[0071] Example of how to get the first value - PCR According to one embodiment, the step of obtaining the first value may include amplifying hsa-miR-3659 or hsa-miR-3679 derived from extracellular vesicles in a urine sample by polymerase chain reaction (PCR), and obtaining the first value from the result of the amplification. In this case, the method of amplification using PCR may be appropriately selected from methods known to those skilled in the art. According to one embodiment, the step of obtaining the first value may further include synthesizing cDNA of the first target using hsa-miR-3659 and / or hsa-miR-3679 derived from extracellular vesicles in the sample as the first target; mixing the cDNA with a reaction reagent including one or more primers selected from the group consisting of SEQ ID NO: 1 and SEQ ID NO: 2 to prepare a mixture for PCR amplification; amplifying the mixture for PCR amplification by RT-PCR; and calculating the amount of the first target contained in the sample from the result of RT-PCR. According to one embodiment, the RT-PCR result may include a graph of reaction cycle number versus fluorescent signal intensity and / or a melting curve. According to one embodiment, the step of obtaining the first value may be performed using a known PCR device. In particular, the PCR device may be a Rotor Gene 6000 instrument (Qiagen, Hilden, Germany), but the present invention is not limited thereto.

[0072] Restrictions on using the first value alone - Effects of endogenous factors Even if the amount of hsa-miR-3659 or hsa-miR-3679 derived from extracellular vesicles contained in a sample of a subject reflects information about whether the subject has developed prostate cancer, the first value alone cannot be used to diagnose the onset of prostate cancer and / or the degree of progression of prostate cancer.This is because the information about the onset of prostate cancer and the action of endogenous factors independent of the information are simultaneously reflected in the first value.Therefore, unless the action of endogenous factors is eliminated, reduced and / or controlled, it is difficult to diagnose the onset of prostate cancer and / or the degree of progression of prostate cancer using the first value alone.Endogenous factors refer to various factors independent of prostate cancer, and are described in more detail as follows.

[0073] Endogenous factors Endogenous factors - definition When the expression level of a biomarker related to a certain disease is measured, there are various factors that have an influence on the expression level of the biomarker. In this specification, the term "endogenous factors" collectively refers to factors associated with the sample or subject itself, not factors associated with a certain disease (e.g., the onset and progression of a certain disease), among factors that affect the expression level of the biomarker. Since the amount of the biomarker contained in the sample reflects not only the effect of a certain disease but also the effect of endogenous factors, it is very important to remove, reduce, and / or control the effect of endogenous factors in order to diagnose a certain disease using the expression level of the biomarker.

[0074] First example of endogenous factors – sample-related factors The endogenous factors may include sample-related factors. The phrase "sample-related factors" collectively refers to factors associated with the attributes of the sample itself, among other factors that may affect the expression level of a biomarker in a sample. According to one embodiment, the endogenous factors may include one or more sample-related factors. In particular, the sample-related factors may include, but are not limited to, the volume of the sample, the time of sample collection, the method of collecting the sample, the sample storage period, the sample storage temperature, or the method of subdividing the sample.

[0075] Second Example of Endogenous Factors – Subject-Related Factors The endogenous factors may include subject-related factors. The phrase "subject-related factors" collectively refers to factors associated with physiological activities and conditions in a subject that are independent of the onset of prostate cancer, among other factors that may affect the expression level of a biomarker in a sample. According to one embodiment, the endogenous factors may include one or more subject-related factors. Specifically, the subject-related factors may include, but are not limited to, the subject's sex, the subject's age, the subject's race, the subject's weight, the subject's renal function, or the subject's hydration status before the sample is collected.

[0076] Obtaining a second value Getting the second value - overview The second value is a value associated with the miRNA derived from extracellular vesicles in the sample. According to one embodiment, the second value may be a value corresponding to the amount of miRNA derived from extracellular vesicles contained in the sample. Specifically, the miRNA derived from extracellular vesicles may be hsv2-miR-H9-5p or hsa-miR-1913, but the present invention is not limited thereto. The second value also includes information on whether the subject has developed prostate cancer. Furthermore, the effect of the endogenous factor is reflected in the second value. In this case, the effect of the endogenous factor reflected in the second value has a close correlation with the degree of the effect of the endogenous factor reflected in the first value. Therefore, the first value may be normalized using the second value. In other words, the effect of the endogenous factor reflected in the first value may be removed, reduced, and / or controlled using the second value. According to one embodiment, the second value may be a value reflecting second information about whether the subject has prostate cancer and third information associated with endogenous factors, where the third information has a close correlation with the first noise, and therefore the first value may be normalized using the second value.

[0077] Targeting miRNAs from extracellular vesicles The second value is a value associated with the miRNA derived from extracellular vesicles in the sample. In order to eliminate the effect of the endogenous factor reflected in the first value, a value that is independent of the first value and reflects the effect of the same endogenous factor is required. The value associated with the expression level of the miRNA derived from extracellular vesicles is preferably used as the second value, since it is considered to have the same or similar effect of the endogenous factor since the first value is also a value associated with the expression level of the miRNA (hsa-miR-3659 or hsa-miR-3679) derived from extracellular vesicles. According to one embodiment, the second value may be a value corresponding to the amount of the miRNA derived from extracellular vesicles contained in the sample.

[0078] First characteristic of the second value: it contains information about endogenous factors Like the first value, the second value reflects the effect of endogenous factors. As noted above, endogenous factors include one or more sample-related factors and / or one or more subject-related factors.

[0079] A second characteristic of the second value, the second characteristic comprising information associated with prostate cancer. Like the first value, the second value also includes information about whether the subject develops prostate cancer. However, the information about the onset of prostate cancer contained in the second value is independent of the information contained in the first value. According to one embodiment, the second value may be a value corresponding to the amount of the second target contained in the sample. In this case, the second value may reflect the second information about whether the subject develops prostate cancer. According to one embodiment, the second target may be upregulated in the subject developing prostate cancer compared to a normal subject or a subject having benign prostatic hyperplasia. According to yet another embodiment, the second target may be downregulated in the subject developing prostate cancer compared to a normal subject or a subject having benign prostatic hyperplasia. According to one embodiment, the second target may be hsv2-miR-H9-5p, hsv1-miR-H18, or hsa-miR-1913 derived from extracellular vesicles.

[0080] The third feature of the second value--close correlation with the effect of the endogenous factor reflected in the first value. Therefore, the second value is characterized by 1) targeting miRNA from extracellular vesicles, 2) including information associated with prostate cancer, and 3) including information about the endogenous factor. However, even if the second value meets these three conditions, it may not be utilized as the second value in the method of calculating the diagnostic score provided herein. This is because the purpose of obtaining the second value is to eliminate, reduce, and / or control the effect of the endogenous factor reflected in the first value. Therefore, the effect of the endogenous factor reflected in the second value must have a close correlation with the effect of the endogenous factor reflected in the first value. When the second value provided herein is used, the effect of the endogenous factor reflected in the first value may be eliminated, reduced, and / or controlled. According to one embodiment, the second value may include a third information that has a close correlation with the first noise, which is the effect of the endogenous factor reflected in the first value.

[0081] Example of how to get the second value - PCR According to one embodiment, the step of acquiring the second value may include amplifying the miRNA derived from the extracellular vesicles in the urine sample by PCR, and acquiring the second value from the result of the amplification. A specific PCR method is as described in the section "Example of a method for acquiring a first value-PCR". In this case, the specific sequence of the primer contained in the reaction reagent mixed with the cDNA may vary depending on the sequence of the miRNA derived from the extracellular vesicles as a target for calculating the second value. According to one embodiment, when the step of acquiring the second value is performed using the hsv2-miR-H9-5p and / or hsa-miR-1913 derived from the extracellular vesicles as the second target, the primer contained in the reaction reagent may have one or more sequences selected from the group consisting of SEQ ID NO: 3 to SEQ ID NO: 4.

[0082] Relationship between the step of acquiring the first value and the step of acquiring the second value As long as the steps of obtaining a first value and obtaining a second value included in the method of calculating a diagnostic score for prostate cancer provided herein satisfy the above-mentioned conditions and characteristics, the order and method of each step are not particularly limited. According to one embodiment, the steps of obtaining a first value and obtaining a second value may be performed simultaneously. According to another embodiment, the steps of obtaining a first value and obtaining a second value may be performed sequentially. For example, the first value may be obtained, and then the second value may be obtained. As another example, the first value may be obtained, and then the second value may be obtained. According to one embodiment, the steps of obtaining a first value and obtaining a second value may be performed by the same method. Specifically, the steps of obtaining a first value and obtaining a second value may be performed by the same PCR method. Furthermore, the steps of obtaining a first value and obtaining a second value may be performed using the same PCR device. According to yet another embodiment, the steps of obtaining a first value and obtaining a second value may be performed by different methods. According to one embodiment, the steps of obtaining a first value and obtaining a second value may be performed in a sample without another separation step. According to another embodiment, after the sample is subdivided into two or more sub-samples, the steps of obtaining the first value and obtaining the second value may be performed separately for the sub-samples. In particular, the sample may be subdivided into a first sub-sample and a second sub-sample, the first value may be obtained from the first sub-sample and then the second value may be obtained from the second sub-sample.

[0083] Calculating a diagnostic score Steps to Calculate Diagnostic Scores - Overview The method of calculating a diagnostic score provided herein may comprise calculating a diagnostic score using the first and second values ​​obtained from the obtaining a first value and obtaining a second value steps as described above. According to one embodiment, calculating a diagnostic score for prostate cancer is performed using the first and second values. As a result, the diagnostic score may be used to diagnose prostate cancer.

[0084] Characteristics of a diagnostic score - reflecting information about prostate cancer-related biomarkers Because the diagnostic score is obtained by normalizing the effect of endogenous factors reflected in the first value using the second value, the diagnostic score contains information associated with the onset of prostate cancer and / or the degree of progression of prostate cancer reflected in the first value, and thus the diagnostic score is capable of diagnosing prostate cancer.

[0085] Example of how to calculate diagnostic scores The calculation of the diagnostic score is not particularly limited as long as it satisfies the following two conditions: 1) using both the first value and the second value, and 2) removing, reducing, and / or controlling the effect of endogenous factors reflected in the first value and the second value on the diagnostic score. According to one embodiment, the diagnostic score may be calculated by the ratio of the first value to the second value.

[0086] Methods for determining test criteria for the diagnosis of prostate cancer - Patents.com Methods for determining testing criteria for the diagnosis of prostate cancer - an overview The present specification provides a method for determining the test standard for diagnosing prostate cancer using a diagnostic score for prostate cancer.Since the diagnostic score for prostate cancer has different patterns (e.g., different average values ​​of diagnostic scores for individual groups of subjects) for a group of subjects who develop prostate cancer and a group of subjects who do not develop prostate cancer, the diagnostic standard for prostate cancer testing can be determined when the distribution of diagnostic scores for individual subjects is analyzed for a cohort in which the onset of prostate cancer in individual subjects is previously known.According to one embodiment, the method for determining the test standard for diagnosing prostate cancer comprises: obtaining a data set comprising information about the onset of prostate cancer and a diagnostic score for prostate cancer from the subjects included in the cohort; and determining the test standard for diagnosing prostate cancer from the data set.In this case, the cohort comprises one or more subjects who develop prostate cancer and one or more subjects who do not develop prostate cancer.In addition, the diagnostic score for prostate cancer is calculated by the method for calculating the diagnostic score for prostate cancer provided herein.

[0087] cohort The method for determining the test standard for diagnosing prostate cancer requires information about the onset of prostate cancer in one or more subjects, and a diagnostic score for prostate cancer.Therefore, the method targets a cohort that includes one or more subjects that do not develop prostate cancer and one or more subjects that develop prostate cancer.According to one embodiment, the method for determining the test standard for diagnosing prostate cancer can be carried out on a cohort that includes one or more subjects that are normal or develop benign prostatic hyperplasia, and the subjects that develop prostate cancer.

[0088] Obtaining the Data Set The method for determining the test standard for diagnosing prostate cancer comprises obtaining a data set comprising information on the onset of prostate cancer from each of the subjects included in a cohort and a diagnostic score for prostate cancer.According to one embodiment, the method for determining the test standard for diagnosing prostate cancer comprises calculating a first data set, wherein the first data set comprises a list of information on whether each subject of the cohort develops prostate cancer, and a list of diagnostic scores for each subject of the cohort.In this case, the diagnostic score is calculated by the method for calculating the diagnostic score for prostate cancer provided herein.

[0089] Determining test criteria for diagnosing prostate cancer The method for determining a test standard for the diagnosis of prostate cancer comprises determining a test standard for the diagnosis of prostate cancer from a dataset. The test standard for the diagnosis of prostate cancer provides a standard for determining whether a subject develops prostate cancer when a diagnostic score is obtained from a subject whose onset of prostate cancer is unknown. According to one embodiment, the step of determining a test standard for the diagnosis of prostate cancer from a dataset may be performed taking into account the sensitivity and specificity of the test standard. For example, the test standard may provide a standard for maximizing the sensitivity and specificity. As another example, the test standard may provide a standard for representing a value greater than or equal to a certain sensitivity value. As yet another example, the test standard may provide a standard for representing a value greater than or equal to a certain specificity value. According to one embodiment, the test standard for the diagnosis of prostate cancer may provide a probability of developing prostate cancer depending on the diagnostic score value.

[0090] Methods for Providing Information About a Diagnosis of Prostate Cancer - Patent application The present specification discloses a method for providing information on the diagnosis of prostate cancer using a diagnostic score. In this case, a test standard for the diagnosis of prostate cancer may be used. According to one embodiment, the method for providing information on the diagnosis of prostate cancer may comprise: calculating a diagnostic score for prostate cancer in a subject; and determining risk factors for prostate cancer from the diagnostic score with reference to one or more predetermined values. In this case, the one or more predetermined values ​​may be the test standard for the diagnosis of prostate cancer.

[0091] Methods for calculating diagnostic scores for prostate cancer - an overview The present specification provides a method for calculating a diagnostic score for prostate cancer by combining at least two values. The method for calculating a diagnostic score for prostate cancer includes preparing a sample, obtaining a first value, obtaining a second value, and calculating a diagnostic score. The sample is characterized in that it is a urine sample of a subject, the first value is a value corresponding to the amount of a first target contained in the sample, where hsa-miR-3659 or hsa-miR-3679-5p derived from extracellular vesicles contained in the sample is used as the first target, and the second value is a value corresponding to the amount of a second target contained in the sample, where miRNA derived from extracellular vesicles contained in the sample is used as the second target. Both the first value and the second value include information about whether the subject has developed prostate cancer, and the second value corresponds to a normalization coefficient specialized for the first value. Thus, the diagnostic score for prostate cancer calculated according to the method is characterized in that it can diagnose prostate cancer. The present specification provides a use of the diagnostic score for prostate cancer. 1) diagnostic criteria for prostate cancer may be determined using a diagnostic score for prostate cancer, and 2) information about the diagnosis of onset of prostate cancer and diagnostic criteria for prostate cancer using the diagnostic score for prostate cancer may be provided. EXAMPLES

[0092] [Mode of invention] The present invention provided herein will be described in more detail below with reference to experimental examples and examples thereof. However, it will be apparent to those skilled in the art that these examples are provided for the purpose of illustrating the present invention only and are not intended to be construed as limiting the scope of the present disclosure described herein.

[0093] Experimental Example 1: Preparation of test subjects and samples Experimental Example 1.1: Test Subject To calculate the diagnostic score for prostate cancer, prepare an experimental group of subjects to be sampled.The experimental group of subjects includes both patients with benign prostatic hyperplasia (BPH) who do not develop prostate cancer, and patients who develop prostate cancer.The characteristics of the experimental group of subjects are listed in Table 1 below. [Table 1] BPH: benign prostatic hyperplasia; PCa: prostate cancer; SD: standard deviation; PSA: prostate-specific antigen; TURP: transurethral resection of the prostate. P values ​​are calculated by Mann-Whitney U test using urine samples from subjects with BPH and PCa.

[0094] Example 1.2: Sample preparation Samples were prepared from each group of subjects prepared in Example 1.1. The sample preparation was as follows: (1) Urine was collected from the subjects in the morning. (2) The urine samples were centrifuged at 2,500 rpm for 15 minutes using a centrifuge. (3) Urine supernatant was collected as a sample and stored at -20°C until use in the next step.

[0095] Example 1.3: Sample preparation The urine sample prepared in Experimental Example 1.2 was subjected to a pretreatment process for calculating the first value and the second value, which was as follows. (1) Urine samples were purified using the Genolution Urinary miRNA Purification Kit (Genolution Pharmaceuticals Inc., Seoul, Korea). (2) 500 μL of urine sample supernatant was added to a tube containing Genolution's proprietary miRNA isolation solution and vortexed for 20 seconds. (3) 200 μL of chloroform was added to the tube and vortexed for 10 seconds. (4) After step (3), the tubes were centrifuged at 4° C. and 13,000 rpm for 10 minutes. (5) After step (4), 650 μL of the liquid phase was removed from the top of the tube, taking care not to remove the white precipitate in the tube. (6) After step (5), the sample remaining in the tube was transferred to a new 1.5 mL tube, to which 0.8 mL of isopropanol was added. (7) After step (6), the tubes were centrifuged at 4° C. and 15,000 rpm for 20 minutes. (8) After step (7), the tube was tilted away from the RNA pellet and the liquid phase was poured off. (9) After step (8), 500 μL of 70% EtOH was added to the tube. (10) After step (9), the tubes were centrifuged at 4° C. and 15,000 rpm for 20 minutes. (11) After step (10), the remaining ethanol was removed from the tube, and the remaining pellet was then dissolved in 40 μL of RNase-free water and stored at −80° C. until use.

[0096] Experimental Example 2: Measurement of the amount of target miRNA contained in a sample The amount of target miRNA contained in the sample prepared in Experimental Example 1 was calculated by PCR. The specific PCR method is as follows. (1) Using the Mir-XTM miRNA First Strand cDNA Synthesis Kit (TAKARA BIO, Otsu, Japan), cDNA was synthesized from the samples prepared in Example 1.3. In this case, the cDNA synthesis method was performed according to the manufacturer's protocol. (2) The products of step (1) were added to a microreaction tube (Corbett Research, Mortlake, Australia) containing SYBR Premix EX Taq (TAKARA BIO) in a final volume of 10 μL and subjected to RT-PCR analysis using a Rotor-Gene Q instrument (Qiagen, Valencia, CA, USA). In this case, a standard curve of the target miRNA was plotted using primers (RNA oligonucleotides) (Integrated DNA Technologies (IDT), Seoul, Korea) corresponding to each target miRNA. The sequences of the target miRNA and primers used are listed in Table 2 below. [Table 2] (3) A standard curve was plotted in the range of 2.25 × 105 to 2.25 × 108, and all samples were measured in triplicate. In this case, the RT-PCR conditions were set according to the manufacturer's protocol. (4) The output spectral data was collected and analyzed using Rotor-Gene Q software 2.3.1.49.

[0097] Experimental example 3: Statistical analysis Experimental Example 3.1: Calculation of diagnostic score The diagnostic score was calculated using the amount of target miRNA contained in the sample obtained in Experimental Example 2 as the first value or the second value. The diagnostic score was calculated by the ratio of the amount of two target miRNAs contained in the sample. The specific targets used in the examples are listed in Table 3 below. [Table 3]

[0098] Experimental Example 3.2: Verification of analytical performance in each example In order to confirm the ability to diagnose prostate cancer using the diagnostic scores of each Example calculated in Experimental Example 3.1, statistical analysis was performed as follows. (1) A Mann-Whitney U test was used to calculate the diagnostic score for each example and to determine whether there was a statistically significant difference in the diagnostic score between groups of subjects. Statistical significance was calculated for i) all subjects with prostate cancer versus all BPH subjects, and ii) the group of BPH subjects in the PSA gray zone (PSA concentration: 3 ng / L - 10 ng / L) versus the group of prostate cancer subjects in the PSA gray zone. (2) In order to set the optimal cut-off standard by which the highest specificity and sensitivity can be deduced, the receiver operating characteristic (ROC) curve was derived for the subject experimental group in each example. Also, the area under the curve (AUC) and the optimal sensitivity and specificity were derived for the ROC curve. The ROC curve was derived for i) all groups of subjects, and ii) each group of subjects in the PSA gray zone.

Claims

1. 1. A method for providing information for diagnosing prostate cancer by combining at least two values, comprising: Preparing a sample from a subject, comprising: preparing a sample from a subject, said sample being a urine sample; obtaining a first value related to the amount of a first target in the sample, obtaining a first value related to the amount of the first target in the sample, wherein the first target is hsa-miR-3659 or hsa-miR-3679 derived from extracellular vesicles in the sample; obtaining a second value related to the amount of a second target in the sample, obtaining a second value related to the amount of the second target in the sample, wherein the second target is hsv2-miR-H9-5p or hsa-miR-1913 derived from extracellular vesicles in the sample; determining a diagnostic score by normalizing the first value by the second value, determining a diagnostic score by normalizing the first value by the second value, wherein the normalization comprises calculating a ratio of the first value to the second value; Providing the diagnostic score for use in diagnosing prostate cancer. method.

2. The method of claim 1 , wherein the diagnostic score is a ratio of the first value to the second value.

3. The step of obtaining the first value comprises: synthesizing a first cDNA of said first target in said sample; amplifying said first cDNA by polymerase chain reaction using a first primer, amplifying the first cDNA, wherein the first primer has a sequence selected from the group consisting of SEQ ID NO 1 to SEQ ID NO 2; and determining said first value from the results of said amplifying said first cDNA. The method of claim 1 or 2, further comprising:

4. The step of obtaining the second value comprises: synthesizing a second cDNA for said second target in said sample; amplifying said second cDNA by polymerase chain reaction using a second primer, amplifying said second cDNA, wherein said second primer has a sequence selected from the group consisting of SEQ ID NO:3 and SEQ ID NO:5; determining the second value from the result of the amplifying step of the second cDNA; The method of claim 1 , further comprising:

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