WO2020188564A1 - Prognostic and treatment methods for prostate cancer - Google Patents

Abstract

Provided herein are prognostic and treatment methods for prostate cancer. The level of an of miR-451, miR-106a, and miR-182 is detected and compared with a threshold level of the detected miRNA, which determines the likelihood of an adverse or non-adverse prostate cancer pathology in the subject.

Description

PROGNOSTIC AND TREATMENT METHODS FOR PROSTATE CANCER

CROSS REFERENCE TO RELATED APPLICATIONS

Benefit is claimed to U.S. Provisional Patent Application No. 62/819,685 filed on March 18, 2019, the contents of which are incorporated by reference herein its entirety.

FIELD OF THE INVENTION

Provided herein are prognostic and treatment methods for prostate cancer.

BACKGROUND

Prostate cancer (PCa) is the fifth most common malignancy in the world, with over 200,000 new cases diagnosed in North America annually. While screening has decreased prostate cancer mortality rates, it has done so at the risk of detecting early stage/grade prostate cancer that might not affect a patient's life if untreated. Treating those with low risk disease results in unnecessary morbidities associated with invasive treatments such as surgery or radiation.

Active surveillance (AS) is a non-invasive therapeutic strategy developed to reduce the use of invasive treatments for patients with low-risk prostate cancer (i.e. PCa having a non- adverse pathology). Patients undergoing AS are often monitored with physical exams, selective imaging, PSA assessments, and/or repeat biopsies. More invasive treatment is then offered to those with signs of disease progression. Although AS is a viable option for men with low-risk prostate cancer, there are considerable misclassification rates when identifying candidates for AS according to current methods. Accordingly, nomograms have been developed to predict post-surgical pathology in low-risk patients utilizing clinical characteristics such as age, prostate surface antigen (PSA) levels, and PCa stage. However, existing approaches demonstrate a low accuracy rate, complicating decision-making. Further, due to the limitations of PSA as a surrogate for disease progression and the significant concerns about biopsy sampling errors, both patients and clinicians worry that delayed invasive treatment could compromise the ability to cure disease.

One metric used in prognostic determinations and treatment decisions of Prostate Cancer patients is the Gleason Score (GS). The Score is determined from biopsies extracted by inserting a thin hollow needle into the prostate gland at several locations. Each biopsy represents real harm to the patient in terms of anxiety, bleeding , discomfort, and risk of infection requiring hospitalization. GS is determined by the degree of resemblance between the cancer and healthy tissue (see Figure 1 for the GS definitions and the parallel Gleason Grading (GG) for each GS). Two scores between 3 to 5 are assigned for each patient, with a total score of 6 to 10. The primary score is given to the largest area of the tumor. Accordingly, a score of (3+3) or (3+4), means the tumor is primarily 3. Patients with GS 3+4 have a good prognosis, although not as good as a patient with GS 3+3, and patients with such scores are considered as having non-adverse PCa. Active surveillance is an acceptable alternative to radical prostatectomy or radiation therapy for patients with GS 3+3 or 3+4. However, for patients with a GS of 4+3 or higher, AS is too risky and not recommended.

Gleason scoring of tumors based on biopsy samples is known to be imprecise (Prostate Cancer Detection PMID: 25905271- ). Undergrading occurs in 26% of men and overgrading in 5%. Undergrading is mostly (35%) in GS 3+3. Thus, due to concerns of undergrading, overtreatment and repeated biopsies of Prostate Cancer patients is a common issue. Nearly 55% of Prostate Cancer patients undergoing aggressive therapy (i.e. an invasive treatment) have clinically mild disease that could have been treated instead by active surveillance. Men undergoing radical prostatectomy and radiation therapies often experience immediate complications from the therapy: mortality is 0.1 to 0.5% (1% in men>75years), urinary incontinence, sexual dysfunction, and bowel problems. Other concerns include repeated biopsies in patients with negative pathology and a 43% increased risk of infection and hospitalization. Physicians and patients struggle to choose between active surveillance and invasive treatments due to concerns of prostate biopsy undergrading. For 3+4 Gleason Score (GS) patients there is a clear trend towards active surveillance as recommended by USA NCCN Guidelines Version 4.2018

Therefore, a continuing need exists for methods of determining the actual PCa status in subjects who have been diagnosed with PCa (based on prostate biopsy pathology analysis), and particularly, considering the biopsy sampling errors, to determine whether actual PCa status is non-adverse (Gleason score is 3+3 or 3+4), and implement the most suitable treatment.

SUMMARY

The present disclosure provides methods for determining the likelihood of non-adverse prostate cancer pathology in a subject. The methods generally involve quantification of one or more Diagnostic microRNAs (miRNAs), from a group consisting of miR-451, miR-106a, and/or miR-182 in a biological sample. The quantification of one or more (e.g., a combination) of those miRNAs can be used to determine a likelihood of non-adverse prostate cancer pathology in a subject. Such a subject may be a candidate for a non-invasive AS therapeutic approach, with high level of certainty that his cancer is not-adverse. The methods of the present disclosure also find use in facilitating treatment decisions for a subject. Also provided are devices, systems, and kits that may be used in practicing methods of the present disclosure.

In the present disclosure the described methods include determining an amount of at least one miRNA, from a group consisting of miR-451, miR-106a, and/or miR-182 in a serum sample taken from a subject, comparing the amount of the at least one miRNA with a threshold amount. If the amount of the at least one miRNA of the group is below the threshold amount, then the subject has a higher likelihood for having a non-adverse PCa pathology. Further included in the described methods is generating a report indicating a likelihood of the non- adverse prostate cancer pathology in the subject based on the results of comparing the amount of the at least one miRNA with the treshold amount.

As further described herein the threshold levels of diagnostic miRNAs miR-451, miR- 106a, and/or miR-182 in the current invention is defined as the lower 80, 85, 90, 95, 97, 98, or 99 percentile of the relevant miRNA measured in a sera or plasma samples taken from a reference group of subjects diagnosed as having PCa and a Gleason Score grade of GG3, GG4 or GG5. The GGs of this group are determined based on full pathological analysis of the prostate after its removal by surgery, with the serum samples taken from the subjects just before the surgery. The number of the subject in the reference group can be at least 15, 20, 30, 50, or 100.

In another embodiment of this invention, the threshold level of diagnostic miRNAs miR-451, miR-106a, and/or miR-182 is determined as the lower 80, 85, 90, 95, 97, 98, or 99 percentile of the relevant miRNA amounts measured in a sera or plasma samples taken from a reference group of subjects diagnosed as having PCa and a Gleason Score grade of GG2, GG3, GG4 or GG5. The GGs of this group are determined based on full pathological analysis of the prostate after its removal by surgery, and the serum samples were taken from the subjects just before the surgery. The number of the subject in the reference group can be at least 15, 20, 30, 50, or 100.

The biological sample used in the methods of the present disclosure can be serum or plasma separated from the blood isolated from the subject. The methods may optionally include obtaining the biological sample from the subject. The methods can optionally include obtaining the biological sample from the subject after a prostate biopsy and before an invasive treatment involving prostate radiation, prostatectomy surgery, and/or chemotherapy.

The means of determining an amount of a diagnostic miRNA in a biological sample may vary. In some aspects of the present disclosure, determining the amount of a diagnostic miRNA involves performing quantitative real-time PCR, such as multiplexed quantitative real- time PCR. In other embodiments the relative quantity of the diagnostic miRNAs is determined relative to an amount of a reference miRNA. In yet another embodiment, before the real time PCR, the diagnostic miRNAs are reverse-transcribed to cDNA, using a specific synthetic primer, which can be a stem-loop primer, and reverse transcriptase enzyme.

The amount of the diagnostic miRNA may be compared to a reference amount, in order to normalize the calculated amounts between samples. The reference amount can be calculated in a variety of different ways. In some embodiments, the reference amount is a predefined control amount of the diagnostic miRNA prepared by chemical synthesis or purified from a biological tissue sample. In other embodiments, the reference amount is a predefined amount of a synthetic miRNA that does not exist in humans (e.g. miR 39 from C. elegans), and is added to the samples in a fixed amount prior to extraction of the miRNA.

In other embodiments, the reference amount can be calculated from the average or median values of a plurality of reference miRNAs from the biological sample, which are selected as having a low variability between PCa biological samples. The plurality may include at least 2, 10, 100, or 1000 miRNAs. Further, in some embodiments, the reference amount can be calculated based upon a biomolecule that is not a miRNA, such as a long non-coding RNA molecule, small RNA(s), and the like.

The described methods can optionally indicate a likelihood of non-adverse prostate cancer pathology in a subject by considering one or more additional risk factors. Risk factors of interest include, but are not limited to, factors that may be assessed without biopsying the subject, such as the subject's age, PSA level, and/or clinical stage by standard methods known in the art. In certain embodiments, the methods include measuring the subject's PSA level and/or determining the subject's clinical stage. Other risk factors that can be used in determining the pathology of a subject’s prostate cancer include, but are not limited to, factors that may be assessed from a biopsy (e.g., a biopsy of the subject's prostate), including the subject's Gleason score, the percentage of biopsy cores positive for PCa cells, the fraction of the biopsy that is positive for PCa cells, or any combination thereof. In certain embodiments, the methods include biopsying the subject's prostate.

In some embodiments of this method, the risk factors used in determining the PCa pathology can be results from an MRI scan of the prostate according to standard methodology. In yet other embodiments, the MRI scan can be done before or after measurement of the diagnostic miRNA levels.

In particular embodiments, the described methods include recommending or providing a treatment to a subject based on the determination of PCa pathology, such as invasive treatments or non-invasive treatments, including active surveillance, watchful waiting, or a similar non-invasive approach.

The methods of the present disclosure can involve inputting the amount of one or more diagnostic miRNAs into a computer programmed to execute an algorithm to perform the comparing step, wherein said inputting generates a result for a report. The report can be displayed to an output device, e.g., at a location remote to the computer.

The present disclosure also provides systems that include devices for determining a likelihood of non-adverse prostate cancer pathology in a subject. The devices include an analyzing unit comprising a detection agent for one or more diagnostic miRNAs, wherein the analyzing unit is configured for determining an amount of the diagnostic miRNA(s) in a biological sample detected by the detection agent; and an evaluation unit comprising a processor programmed to compare the determined amount(s) obtained from the analyzing unit with a reference amount; and calculate a likelihood of non-adverse prostate cancer pathology in the subject, based on results of the comparing the determined amount(s) obtained from the analyzing unit with the reference amount. In certain aspects, the processor of the evaluation unit is programmed to calculate a likelihood of adverse prostate cancer pathology in the subject based on one or more additional risk factors, such as the subject's age, PSA level, clinical stage, biopsy Gleason score, percentage of biopsy cores positive, the fraction of the biopsy that is positive, MRI scan results, and the like. The device may optionally include a display comprising a user interface configured to receive user input (e.g., input as to the subject's age, PSA level, and the like) and provide the input to the processor.

Also provided by the present disclosure are kits, such as kits that include a detection agent for one or more diagnostic miRNA molecules, and optionally a device for determining a likelihood of adverse prostate cancer pathology in a subject (e.g., a device as described above).

The present disclosure also provides computer systems for determining a likelihood of non-adverse prostate cancer pathology in a subject. The computer systems include a processor and memory operably coupled to the processor, where the memory programs the processor to receive assay data including an amount of at least one diagnostic miRNA in a biological sample from a subject; compare the amount received with a threshold amount or level; and calculate a likelihood of non-adverse prostate cancer pathology in the subject, based on results of said comparing the determined amounts obtained from the analyzing unit with the threshold amount. In certain aspects, the system calculates a likelihood of non-adverse prostate cancer pathology in the subject based on one or more additional risk factors, such as the subject's age, PSA level, MRI scan results, etc. These and other features will be apparent to the ordinarily skilled artisan upon reviewing the present disclosure. The invention may be best understood from the following detailed description when read in conjunction with the accompanying drawings.

BRIEF DESCRIPTION OF THE DRAWINGS

FIG. 1 is a table describing the Gleason scoring and grading classification.

FIG. 2 is a schematic description of RT and TaqMan RT-qPCR miRNA assays.

FIG. 3 Describes the correlation between Ct of cel-miR-39 used for normalization and final RQ of miR-451.

FIGS. 4A-4C describe the distribution of miR-451, miR-106a, and miR-182, according to the final biopsy Gleason Groups.

FIGS. 5A-C describe the distribution diagnostics miRNAs RQ in the combined group of GG1 and GG2, vs GG3 and up. Optional threshold values for differentiation between the groups are denoted with a bold line. Patients having sera RQ of diagnostics miRNAs below that threshold, are favorable of having non-adverse PCa (having GG1 or GG2).

FIGS. 6A-6C describe ROC analysis (Area under the curve AUC and p value) of the ability of RQ 451, 106a, and 182 (fig.6A- 6C respectively) to differentiate between GG 1 and 2 vs GG3 and up.

FIGS. 7A-7C describe the distribution diagnostics miRNAs RQ in group of GG1 vs the combined group GG2 and up. Optional threshold values providing at least 90% specificity (equivalent to the lower 90% percentile) for differentiation between the groups are denoted with a bold line. Patients having sera RQ of diagnostics miRNAs below that threshold, are favorable of having non-adverse PSC (having GG1).

FIGS. 8A-8C describe ROC analysis (area under the curve AUC and p value) of the ability of RQ 451, 106a, and 182 (figs. 8A -8C respectively) to differentiate between GG 1 vs GG2 and up.

BRIEF DESCRIPTION OF THE DESCRIBED SEQUENCES

The nucleic and/or amino acid sequences provided herewith are shown using standard letter abbreviations for nucleotide bases as defined in 37 C.F.R. 1.822. Only one strand of each nucleic acid sequence is shown, but the complementary strand is understood as included by any reference to the displayed strand. In the attached Sequence Listing:

SEQ ID NO: 1 is the nucleic acid sequence of miRNA 451.

SEQ ID NO: 2 is the nucleic acid sequence of miRNA 106a.

SEQ ID NO: 3 is the nucleic acid sequence of miRNA 182. SEQ ID NO: 4 is the nucleic acid sequence of miRNA C.el. 39

SEQ ID NO: 5 is the nucleic acid sequence of Stem- Loop primer 451.

SEQ ID NO: 6 is the nucleic acid sequence of Stem-Loop primer 106a.

SEQ ID NO: 7 is the nucleic acid sequence of Stem- Loop primer 182.

SEQ ID NO: 8 is the nucleic acid sequence of Stem-Loop primer 39.

SEQ ID NO: 9 is the nucleic acid sequence of RTqPCR specific primer 451

SEQ ID NO: 10 is the nucleic acid sequence of RTqPCR specific primer 106a

SEQ ID NO: 11 is the nucleic acid sequence of RTqPCR specific primer 182

SEQ ID NO: 12 is the nucleic acid sequence of RTqPCR specific primer C.el. 39.

SEQ ID NO: 13 is the nucleic acid sequence of a universal primer.

SEQ ID NO: 14 is the nucleic acid sequence of TaqMAN RTqPCR probe 451

SEQ ID NO: 15 is the nucleic acid sequence of TaqMAN RTqPCR probe 106a

SEQ ID NO: 16 is the nucleic acid sequence of TaqMAN RTqPCR probe 182

SEQ ID NO: 17 is the nucleic acid sequence of TaqMAN RTqPCR probe C.el. 39 SEQ ID NO: 18 is the nucleic acid sequence of Stem and loop hsa-miR-451 MI0001729 SEQ ID NO: 19 is the nucleic acid sequence of Stem and loop hsa-miR-106a

SEQ ID NO: 20 is the nucleic acid sequence of Stem and loop hsa-miR-182

SEQ ID NO: 21 is the nucleic acid sequence of Mir-106a

SEQ ID NO: 22 is the nucleic acid sequence of Mir-182

DETAILED DESCRIPTION

Before the present invention is described in greater detail, it is to be understood that this invention is not limited to particular embodiments described, as such may, of course, vary. It is also to be understood that the terminology used herein is for the purpose of describing particular embodiments only, and is not intended to be limiting, since the scope of the present invention will be limited only by the appended claims.

Where a range of values is provided, it is understood that each intervening value, to the tenth of the unit of the lower limit unless the context clearly dictates otherwise, between the upper and lower limits of that range is also specifically disclosed. Each smaller range between any stated value or intervening value in a stated range and any other stated or intervening value in that stated range is encompassed within the invention. The upper and lower limits of these smaller ranges may independently be included or excluded in the range, and each range where either, neither or both limits are included in the smaller ranges is also encompassed within the invention, subject to any specifically excluded limit in the stated range. Where the stated range includes one or both of the limits, ranges excluding either or both of those included limits are also included in the invention.

Unless defined otherwise, all technical and scientific terms used herein have the same meaning as commonly understood by one of ordinary skill in the art to which this invention belongs. Although any methods and materials similar or equivalent to those described herein can be used in the practice or testing of the present invention, some potential and exemplary methods and materials may now be described. Any and all publications mentioned herein are incorporated herein by reference to disclose and describe the methods and/or materials in connection with which the publications are cited. It is understood that the present disclosure supersedes any disclosure of an incorporated publication to the extent there is a contradiction.

It must be noted that as used herein and in the appended claims, the singular forms“a”, “an”, and“the” include plural referents unless the context clearly dictates otherwise. Thus, for example, reference to“a biological sample” includes a plurality of such biological samples and reference to“the processor” includes reference to one or more processors, and so forth.

It is further noted that the claims may be drafted to exclude any element which may be optional. As such, this statement is intended to serve as antecedent basis for use of such exclusive terminology as“solely”,“only” and the like in connection with the recitation of claim elements, or the use of a“negative” limitation.

The publications discussed herein are provided solely for their disclosure prior to the filing date of the present application. Nothing herein is to be construed as an admission that the present invention is not entitled to antedate such publication by virtue of prior invention. Further, the dates of publication provided may be different from the actual publication dates which may need to be independently confirmed. To the extent such publications may set out definitions of a term that conflict with the explicit or implicit definition of the present disclosure, the definition of the present disclosure controls.

As will be apparent to those of skill in the art upon reading this disclosure, each of the individual embodiments described and illustrated herein has discrete components and features which may be readily separated from or combined with the features of any of the other several embodiments without departing from the scope or spirit of the present invention. Any recited method can be carried out in the order of events recited or in any other order which is logically possible.

Definitions:

The term“prostate cancer” is known in the art, and refers to a proliferative lesion or abnormality of the prostate. Accordingly, the term encompasses benign lesions, pre-malignant lesions, malignant lesions as well as solid tumors and metastatic disease (both locally metastatic and more widely, or systemically, metastatic).

The terms“staging prostate cancer” and“clinical stage” are used to differentiate between various stages of prostate cancer. The general classification of prostate tumor stages is well-known to the skilled artisan. In brief, the most commonly used staging method is the Tumor, Nodes, Metastasis (TNM) system (Brierley, J.D.; Gospodarowicz, M.K.; Wittekind, Ch., eds. (2017). TNM classification of malignant tumors (8th ed.). Chichester, West Sussex, UK: Wiley-Blackwell. ISBN 978-1-4443-3241-4.), which recognizes four stages of local tumor growth, from T1 (incidental) to T4 (invasion of neighboring organs). Each stage describes the state of pathological development of the tumor. T1 represents an‘incidental’ state, where the tumor is detected by chance following transurethral resection or by biopsy following PSA testing. At this stage, the tumor will be undetectable by palpation (Digital Rectal Examination DRE) or ultrasound. T4 represents advanced disease, where the tumor has invaded neighboring organs. The nodal stage (N0-N1) and the metastatic stage (M0-M1C) reflect the clinical spread of the disease to lymph nodes and distant sites (metastasis), respectively.

Grading systems can assess the degree of cell anaplasia (variation in size, shape and staining properties) and differentiation (how well differentiated the cells are) in the tumor. The Gleason grading system is based on the extent to which the tumor cells are arranged into recognizably glandular structures and the level of cell differentiation. The Gleason system identifies more than five levels of increasing disease aggressiveness, with Grade 1 being the least aggressive and over Grade 5 being the most aggressive cancer. The Gleason system is described in, e.g., Gleason, D. F. (1977) Urologic Pathology: The Prostate. Philadelphia: Lea and Febiger. pp. 171-198; the disclosure of which is incorporated herein by reference. As discussed herein, Figure 1 presents the Gleason scoring and grading system.

In certain embodiments, the described methods can differentiate between a subject with high risk, an intermediate risk and a low risk of pathological disease progression. A subject at “low risk” is generally a subject suffering from prostate cancer with a Gleason score of 6 or lower than 6.“Low risk” subjects may include those with Gleason Grade 1 or 2, and clinical T1-T2 stage disease. Subjects with a Gleason Grade of 2 are said to have a“favorable intermediate” risk of having adverse disease progression. A subject being at“intermediate or high risk” in the context of the method of the present invention relates to subjects suffering from prostate cancer with a Gleason Grade 3, 4 or 5. A Gleason Grade 3 of higher is associated with an increased risk of disease-specific mortality, and suggests a risk of adverse clinical progression.

The terms“adverse pathology” with reference to a subject having, at risk of having or suspected of having prostate cancer and“adverse prostate cancer pathology” denote a Gleason Grade of 3 or higher. Such a Gleason score is associated with an increased risk of prostate cancer-specific mortality, as described in, e.g., Albertsen P C, et al. (2005) JAMA 293:2095- 2101; the disclosure of which is incorporated herein by reference.

The terms“non-adverse pathology” with reference to a subject having“non-adverse prostate cancer pathology” denote a Gleason Grade of 1 or 2. Such a Gleason score is associated with an decreased risk of prostate cancer-specific mortality, as described in, e.g., Albertsen P C, et al. (2005) JAMA 293:2095-2101; the disclosure of which is incorporated herein by reference.

The term“MRI” or“MRI scan” refer Magnetic Resonance Imaging methods used for imaging of the prostate in order to identify malignant tissue.

A“biomarker” or“marker” as used herein generally refers to an organic biomolecule (e.g., a microRNA) which is differentially present in a sample taken from a subject of one phenotypic status (e.g., having a disease) as compared with another phenotypic status (e.g., not having the disease or having a different disease). A biomarker is differentially present between different phenotypic statuses if the mean or median level of the biomarker in a first phenotypic status relative to a second phenotypic status is calculated to represent statistically significant differences. Common tests for statistical significance include, among others, t-test, ANOVA, Kruskal-Wallis, Wilcoxon, Mann-Whitney and odds ratio. Biomarkers, alone or in

combination, provide measures of relative likelihood that a subject belongs to a phenotypic status of interest. As such, biomarkers can find use as markers for, for example, the presence of a disease (diagnostics), risk stratification for disease progression, and the like. Biomarkers are thus analytes in assays that facilitate diagnosis, prognosis, risk stratification, determination of appropriate therapeutic treatments, and the like.

The terms“microRNA” and“miRNA” are used in accord with their ordinary usage in the art. Generally speaking, miRNAs are short (e.g., about 18-24 nucleotides in length), non coding RNAs, which regulate gene expression post-transcriptionally by destabilizing messenger RNAs (mRNA) and/or inhibiting their translation. Canonical miRNAs derive from longer polymerase II transcripts, called pri-miRNAs. A complex consisting of the proteins DGCR8 and Drosha process the pri-miRNAs to pre-miRNAs, which are then exported to the cytoplasm and cleaved by the protein Dicer to mature miRNAs. Exceptions to this processing include non-canonical miRNAs that bypass DGCR8/Drosha, while still being processed by Dicer. Knockout models of Dgcr8 and Dicer have been developed that remove only canonical miRNAs or both canonical and non-canonical miRNAs, respectively.

The term“diagnostic miRNAs” can in certain contexts be understood generally, but in the present disclosure refers specifically to the group of diagnostic miRNAs encompassing miR-451, miR-106a, and miR-182. Each of these miRNAs can be understood individually as a “diagnostic miRNA”. A diagnostic miRNA is a biomarker. Accordingly, a diagnostic miRNA may be differentially present in a sample taken from a subject having a certain risk level of a disease (e.g., a patient with low-risk prostate cancer, and/or a patient without adverse prostate cancer pathology) as compared with another phenotypic status (e.g., a patient with

intermediate- or high-risk prostate cancer, and/or a patient with adverse prostate cancer pathology).

In contrast to a diagnostic miRNA, the term“reference miRNA” is used to refer to a miRNA present in a sample that is not a diagnostic miRNA. As such, one or more reference miRNA(s) may be used to establish a reference amount against which an amount of a diagnostic miRNA may be compared and normalized to, as described more fully herein.

Examples of reference miRNAs of interest include, but are not limited to, synthetic miRNAs that are not existing in humans such as miRNA-39 from C. elegans and which are added to the human sample.

The terms“individual,”“subject,” and“patient,” are used interchangeably herein, refer to a male human in need of the diagnostic methods and treatments described in the present disclosure.

The term“healthy individual” in the context of the methods of the present disclosure refers to an individual who is unaffected by a detectable illness, particularly prostate cancer.

A“biological sample” encompasses a variety of sample types obtained from an individual. The definition encompasses biological fluids (e.g., blood fractions (e.g., serum, plasma)); and other liquid samples of biological origin (e.g., saliva, urine, bile fluid), suitable for analysis in the present methods. In general, separation of cellular components and non- cellular components in a blood sample (e.g., by centrifugation) without coagulation provides a blood plasma sample, while such separation of coagulated (clotted) blood provides a blood serum sample. Examples of biological samples of blood include peripheral blood or samples derived from peripheral blood. The definition also includes samples that have been

manipulated after their procurement, such as by treatment with reagents, solubilization, or enrichment for certain components, such as one or more miRNAs to be assayed. For example, a biological sample (e.g., blood) can be enriched for a fraction containing an analyte(s) of interest.

The“threshold amounts” or“threshold levels” of diagnostic miRNAs miR-451, miR- 106a, and/or miR-182 in the current invention is determined as the lower 80, 85, 90, 95, 97, 98, or 99 percentile of the relevant miRNA amounts measured in a sera or plasma samples taken from a reference group of subjects diagnosed as having PCa, and in which a PCa grade, such as GG3, GG4 or GG5, has been established. The GGs of a reference group can be determined from pathological analysis of the prostate after its removal by surgery, and from analysis of serum samples taken from subjects directly prior to prostatectomy. The number of the subject in the reference group can be at least 15, 20, 30, 50, or 100.

In another embodiment of this invention, the“threshold amounts” or“threshold levels” of diagnostic miRNAs miR-451, miR-106a, and/or miR-182 in the current invention is determined as the lower 80, 85, 90, 95, 97, 98, or 99 percentile of the relevant miRNA amounts measured in a sera or plasma samples taken from a reference group of subjects diagnosed as having PCa of grade GG2, GG3, GG4 or GG5. The GGs of this group can be determined from pathological analysis of the prostate after its removal by surgery, from analysis of serum samples taken from subjects directly prior to prostatectomy. The number of the subject in the reference group can be at least 15, 20, 30, 50, or 100.

“Isolated” refers to a material of interest that is in an environment different from that in which the compound may naturally occur.“Isolated” is meant to include compounds that are within samples that are substantially enriched for the compound of interest and/or in which the compound of interest is partially or substantially purified.

By“purified” is meant a compound of interest (e.g., miRNA) has been separated from components that accompany it in nature.“Purified” can also be used to refer to a compound of interest separated from components that can accompany it during manufacture (e.g., in chemical synthesis). In some embodiments, a compound is substantially pure when it is at least 50% to 60%, by weight, free from organic molecules with which it is naturally associated or with which it is associated during manufacture. In some embodiments, the preparation is at least 75%, at least 90%, at least 95%, or at least 99%, by weight, of the compound of interest.

A substantially pure compound can be obtained, for example, by extraction from a natural source (e.g., bacteria), by chemically synthesizing a compound, or by a combination of purification and chemical modification. A substantially pure compound can also be obtained by, for example, enriching a sample that contains the compound. A substantially pure compound can also be obtained by recombinant or chemical synthetic production. Purity can be measured by any appropriate method, e.g., chromatography, mass spectroscopy, high performance liquid chromatography analysis, etc.

As used herein, the terms“determining”,“assessing”,“assaying”,“measuring” and “detecting” refer to both quantitative and semi -quantitative determinations and as such, the term“determining” is used interchangeably herein with“assaying,”“measuring,” and the like. Where a quantitative determination is intended, the phrase“determining an amount” of an analyte and the like is used. Where either a quantitative and semi-quantitative determination is intended, the phrase“determining a level” of an analyte or“detecting” an analyte is used.

“Quantitative” assays in general provide information on the amount of an analyte in a sample relative to a reference (control), and are usually reported numerically, where a“zero” value can be assigned where the analyte is below the limit of detection.“Semi-quantitative” assays involve presentation of a numeric representation of the amount of the analyte in the specimen that is relative to a reference (e.g., a threshold, e.g., normal threshold or an abnormal threshold), where a“zero” value can be assigned where the analyte is below the limit of detection. In general, semi-quantitative results are compared against an accompanying reference interval to provide a qualitative interpretation of the result.

“Sensitivity” refers to the fraction of people with the specific disease risk level (e.g., low risk prostate cancer) that a test correctly identifies as positive.“Specificity” refers to the fraction of people without the specific disease or disease risk level that the test correctly identifies as negative. The fractions with respect to sensitivity and/or specificity may be presented as a percentage. Where expressed as percentages, specificity can be calculated as by subtracting the sensitivity value for incorrect diagnosis from 100.

The term“primer” may refer to more than one primer and refers to an oligonucleotide, whether occurring naturally, in a purified restriction digest, or produced synthetically, which is capable of acting as a point of initiation of nucleic acid synthesis along a complementary strand when placed under conditions in which synthesis of a primer extension product which is complementary to a nucleic acid strand is catalyzed. Such conditions include the presence of four different deoxyribonucleoside triphosphates and a polymerization-inducing agent such as DNA polymerase or reverse transcriptase, in a suitable buffer (“buffer” includes substituents which are cofactors, or which affect pH, ionic strength, etc.), and at a suitable temperature. The primer is preferably single-stranded for maximum efficiency in amplification.

The complement of a nucleic acid sequence as used herein refers to an oligonucleotide which, when aligned with the nucleic acid sequence such that the 5' end of one sequence is paired with the 3' end of the other, is in“antiparallel association.” Complementarity need not be perfect or“complete”; it is understood that stable duplexes between nucleic acid strands may contain mismatched base pairs or unmatched bases. Those skilled in the art of nucleic acid technology can determine duplex stability empirically considering a number of variables including, for example, the length of the oligonucleotide, percent concentration of cytosine and guanine bases in the oligonucleotide, ionic strength, and incidence of mismatched base pairs.

The terms“treatment,”“treating,” and the like, refer to obtaining a desired therapeutic outcome for a patient with a disease, such as a desired pharmacologic and/or physiologic effect. The effect may be prophylactic in terms of completely or partially preventing a disease or symptom thereof and/or may be therapeutic in terms of a partial or complete cure for a disease and/or adverse effect attributable to the disease.“Treatment,” as used herein, covers any treatment of a disease in a mammal, particularly in a human, and includes: (a) preventing the disease from occurring in a subject which may be predisposed to the disease but has not yet been diagnosed as having it; (b) inhibiting the disease, i.e., arresting its development; and (c) relieving the disease, i.e., causing regression of the disease; and (d) actively determining the status of the disease to determine the requirement for additional therapy. Specific prostate cancer therapies of interest include non-invasive treatments that include, but are not limited to, active surveillance, as well as invasive treatments that include, but are not limited to, surgery, irradiation, systemic chemotherapy, cell therapy, immunotherapy, and the like. Suitable prostate cancer therapies are known in the art and described in, e.g., Suardi N, et al.

(2008) Cancer 113:2068-2072; Heidenreich A, et al. (2008) Eur Urol 53:68-80; and in NCCN Clinical Practice Guidelines in Oncology Prostate Cancer, Version 1.2008; the disclosures of which are incorporated herein by reference.

Methods of Determining a Likelihood of Non-Adverse Prostate Cancer Pathology:

As summarized above, aspects of the present disclosure include methods for determining a likelihood of non-adverse prostate cancer pathology in a subject. Such a determination of the likelihood of non-adverse prostate cancer pathology may include computing a likelihood of adverse prostate cancer pathology in the subject so as to differentiate the subject from an individual with an adverse prostate cancer pathology. A determination of the likelihood of non-adverse prostate cancer pathology can involve differentiating the subject from an individual with adverse prostate cancer pathology.

In general, the methods involve determining an amount of at least one diagnostic miRNA in a biological sample from the subject, comparing the amount of the at least one diagnostic miRNA with a threshold amount or level, comparing the amount of the at least one diagnostic miRNA with the threshold amount to determine a likelihood of non-adverse prostate cancer pathology in the subject, and optionally generating a report based on the results of said comparison. The detection of one or more such diagnostic miRNAs can be used to determine a likelihood of non-adverse prostate cancer pathology in a subject.

In more specific description, the methods involve determining an amount of at least one diagnostic miRNA in a biological sample from the subject, comparing the amount of the at least one diagnostic miRNA with a threshold amount, and if the amounts of the one or more diagnostic miRNA is below the threshold amounts, determining a high likelihood of non- adverse prostate cancer pathology in the subject and optionally generating a report based on results of said comparing the amount of the at least one diagnostic miRNA with the threshold amount.

The methods of the present disclosure also find use in facilitating treatment decisions for a subject, and more specifically whether to pursue a non-invasive treatment such as active surveillance if the likelihood of a non-adverse prostate cancer pathology is determined, or to start a more invasive treatment such as surgery, radiation therapy, or chemotherapy, if there is a higher likelihood of an adverse prostate cancer pathology.

The diagnostic miRNAs used in the methods of the present disclosure, as well as the methods of detection and analysis, are described in more detail below.

Diagnostic miRNAs for Detection

The methods of the present disclosure involve determining the amount of a diagnostic miRNA in a biological sample of a patient. Specifically, the present methods involve determining the amount of miR-106a, miR-451, and/or miR-182.

In certain embodiments, the methods involve determining the amount of one of miR- 106a, miR-451, and/or miR-182. In other embodiments, the methods involve determining the amount of miR-106a and miR-451. In other embodiments, the methods involve determining the amount of miR-451 and miR-182. In still other embodiments, the methods involve detection of miR-182 and miR-106a.

The methods can further involve detection of other biomarkers.

miR-451

The diagnostic miRNA miR-451 is also be referred to as“hsa/mmu miR-451” or“hsa- miR-451”, or“hsa-miR-451a”. Examples of the stem-loop sequence for hsa-miR-451 include those comprising a nucleic acid sequence of miRBase Accession No. MIMAT0001631 and EntrezGene Gene ID 574411, and naturally occurring variants thereof. For example, the nucleic acid stem-loop sequence of MI0001729 is SEQ ID NO: 18. The stem- loop sequence may be processed to the mature sequence of miR-451.

Examples of the mature sequence include those comprising a nucleic acid sequence of miRBase Accession Nos. MIMAT0001631. For example, the nucleic acid sequence of MIMAT0001631 is SEQ ID NO:l.

Detection of miR-451 encompasses detection of the mature miRNA, as well as detection of naturally occurring variants and fragments thereof found in a biological sample, and detection of a precursor molecule of the aforementioned miRNAs, such as the

corresponding pri-miRNAs or pre-miRNAs. Detection of miR-451 can involve detection using one or more Stem-Loop primer for Reverse Transcription (SLPRT), polymerase chain reaction (PCR) forward and backward primers, and a probe such as primers and/or probe comprising SEQ ID NOs:5, 9, 13, 14 (Table 1).

miR-106a

The diagnostic miRNA miR-106a is also be referred to as“hsa/mmu miR-106a” or “hsa-miR-106a,”. Examples of the stem-loop sequence for hsa-miR-106a include those comprising a nucleic acid sequence of miRBase Accession No. MIMAT0000103 and

EntrezGene Gene ID 406899, and naturally occurring variants thereof. For example, the nucleic acid stem-loop sequence of MI0000113 is SEQ ID NO: 19.

The stem- loop sequence may be processed to the mature sequence of miR-106a.

Examples of the mature sequence include those comprising a nucleic acid sequence of miRBase Accession Nos. MIMAT0000103 and MIMAT0004517. For example, the nucleic acid sequence of MIMAT0000103 is SEQ ID NO:2.

For example, the nucleic acid sequence of MIMAT0004517 is SEQ ID NO: 21.

Detection of miR-106a encompasses detection of the mature miRNA, as well as detection of naturally occurring variants and fragments thereof found in a biological sample, and detection of a precursor molecule of the aforementioned miRNAs, such as the

corresponding pri-miRNAs or pre-miRNAs. Detection of miR-106a can involve detection using one or more Stem-Loop primer for Reverse Transcription (SLPRT), polymerase chain reaction (PCR) forward and backward primers, and a probe such as primers and/or probe comprising SEQ ID NOs:6, 10, 13, 15 (Table 1).

miR-182

The diagnostic miRNA miR-182 is also be referred to as“hsa miR-182” or“hsa-miR- 182,”. Examples of the stem-loop sequence for hsa-miR-182 include those comprising a nucleic acid sequence of miRBase Accession No. MIMAT0000259 and EntrezGene Gene ID 406958, and naturally occurring variants thereof. For example, the nucleic acid stem-loop sequence of MI0000272 is: SEQ ID NO: 20.

The stem- loop sequence may be processed to the mature sequence of miR-182.

Examples of the mature sequences include those comprising a nucleic acid sequence of miRBase Accession Nos. MIMAT0000259 and MIMAT0000260. For example, the nucleic acid sequence of MIMAT0000259 is SEQ ID NO:3.

For example, the nucleic acid sequence of MIMAT0000260 is SEQ ID NO: 22.

Detection of miR-182 encompasses detection of the mature miRNA, as well as detection of naturally occurring variants and fragments thereof found in a biological sample, and detection of a precursor molecule of the aforementioned miRNAs, such as the

corresponding pri-miRNAs or pre-miRNAs. Detection of miR-182 can involve detection using one or more Stem-Loop primer for Reverse Transcription (SLPRT), polymerase chain reaction (PCR) forward and backward primers, and a probe such as primers and/or probe comprising SEQ ID NOs:7, 11, 13, 16 (Table 1).

Reference miRNAs for Detection

The reference miRNA miR-39, which may also be referred to as“cel-miR-39” or“cel- miR-39-3p”, is a miRNA existing in the worm C. elegans that does not exist in humans.

Therefore cel-miR-39 can be used as a reference miRNA when a known and fixed amount is added to the human biological samples before the measurement. Examples of the mature sequence include those comprising a nucleic acid sequence found at miRBase Accession No. MIMAT0000010. For example, the nucleic acid sequence of MIMAT0000010 is SEQ ID NO:4.

Detection of cel-miR-39 encompasses detection of the mature miRNA. Detection of cel-miR-39 can involve detection using one or more cel-miR-39 specific Stem-Loop primer for Reverse Transcription (SLPRT), polymerase chain reaction (PCR) forward and backward primers, and a probe such as primers and/or probe comprising SEQ ID NOs:8, 12, 13, 17 (Table 1).

In certain aspects, one or more reference miRNA(s) may be used to establish a reference amount against which an amount of a diagnostic miRNA may be compared.

Reference miRNAs may be detectable in a biological sample from a subject.

Accordingly, specific reference miRNAs may vary depending on, e.g., the particular type of biological sample, the specific assay employed, purification and/or concentration steps, and other factors known to those of skill in the art. In certain aspects, a plurality of reference miRNAs may be detected from a biological sample, such as 2 or more, including 10 or more, e.g., about 2 to 10, about 10 to 20, about 20 to 30, about 30 to 40, about 40 to 50, or about 50 to 100.

Detection of reference miRNAs encompasses detection of the mature miRNA, as well as detection of naturally occurring variants and fragments thereof found in a biological sample, and detection of their precursor molecule.

Table 1: miRNAs, Primers and probes sequences:

Table legend - G/A/T/C + is Locked Nucleic Acid, FAM - Fluorescein amine ester. IABkFQ - Iowa Black Fluorescence Quencher

The methods of the present disclosure can be used to determine a likelihood of non- adverse prostate cancer pathology in a male subject. The subject can be any subject having, suspected of having, or at risk of, prostate cancer, and includes subjects having, suspected of having, or at risk of having any proliferative lesion or abnormality of the prostate. Subjects to be tested using a method of the present disclosure include individuals who present with or have presented with one or more symptoms of prostate cancer. Examples of such symptoms include any symptoms indicative of prostate cancer such as trouble urinating, decreased force in the stream of urine, blood in the urine, blood in the semen, swelling in the legs, discomfort in the pelvic area, bone pain, and/or any abnormal levels of PSA. Abnormal levels are considered as plasma or serum levels higher than 5ng/ml.

Subjects at risk for developing prostate cancer include aged subjects (e.g., 50 or older, or 65 or older), subjects of particular races (e.g., African or of African descent), and subjects with a family history of cancer, including prostate cancer.

Suitable biological samples useful in the methods of the present disclosure include biological fluids (e.g., a blood sample or a blood fraction (e.g., serum, plasma)), Where the biological sample is a blood sample, the blood sample can be obtained from freshly isolated blood or stored blood (e.g. in a blood bank). The biological sample can be a blood sample expressly obtained for an assay of the present disclosure or a blood sample obtained for another purpose which can be subsampled for an assay of the present disclosure.

Samples can be manipulated after procurement, such as by treatment with reagents, solubilization, and/or enrichment for certain components, such as for an analyte(s) to be assayed. Samples can be pretreated as necessary by dilution in an appropriate buffer solution, concentrated if desired, or fractionated by any number of methods including but not limited to ultracentrifugation, fractionation by fast performance liquid chromatography (FPLC), or precipitation. For example, in certain embodiments, the sample is sub fractionated into, e.g., vesicular and non- vesicular components (e.g. naked ribonucleoproteins) before subsequent analysis. Suitable means of sub-fractioning a sample are known in the art and described in, e.g., Duttagupta R, et al. (2011) PLoS ONE 6(6): e20769; the disclosure of which is incorporated herein by reference. Any of a number of standard aqueous buffer solutions, employing one of a variety of buffers, such as phosphate, Tris, or the like, at physiological pH can be used. In general, after isolation, samples (such as blood samples) are stored at -80° C. until assaying.

Biomarkers for analysis in connection with the methods of the present disclosure (e.g., miR-451, miR-106a, and/or miR-182) can be detected using a variety of methods, with methods suitable for quantitative and semi-quantitative assays being of particular interest. Examples of detection methods include, but are not limited to, various assays involving reverse transcription of RNA and nucleic acid amplification (e.g., PCR, quantitative real time PCR, nucleic acid microarrays, sequencing, bead arrays, high throughput sequencing, and the like). For example, isolated miRNA from a biological sample can be used in hybridization or amplification assays that include, but are not limited to, Southern or Northern analyses, polymerase chain reaction (PCR) analyses and probe arrays. One method for the detection of miRNA levels involves contacting the isolated miRNA with a nucleic acid molecule (probe) that can hybridize to a biomarker-encoding nucleic acid. The nucleic acid probe can be for example, a full-length cDNA, or a portion thereof, such as an oligonucleotide of at least 5,6,7, 15, 30, 50, 100, 250 or 500 nucleotides in length and sufficient to specifically hybridize under stringent conditions to biomarker-encoding nucleic acid. Examples of suitable probes include, but are not limited to, probes listed in Table 1 (e.g., SEQ ID NOs: 14-17).

In one embodiment, the miRNA from a biological sample is immobilized on a solid surface and contacted with a probe. In an alternative embodiment, the probe(s) are immobilized on a solid surface and the miRNA isolated from the biological sample is contacted with the probe(s), e.g., as in an array format.

Methods of detecting levels of biomarker expression in a sample can involve any suitable method of nucleic acid amplification, e.g., by RT-PCR, ligase chain reaction, or any other nucleic acid amplification method, followed by the detection of the amplified molecules using techniques well known to those of skill in the art. In one example, biomarker expression is assessed by quantitative fluorogenic RT-PCR (e.g., such as using TaqMan™, SYBR Green, and the like). Such methods typically utilize pairs of oligonucleotide primers that are specific for a biomarker-encoding nucleic acid. Methods for designing oligonucleotide primers specific for a known sequence are well known in the art.

In certain embodiments, the method employs a detection approach that involves extraction of the miRNA from serum samples using methods known in the art such as using commercial kit e.g. miRNeasy Serum/Plasma Kit (Qiagen Cat. 217184) according to manufacturer instructions. In particular embodiments, a fixed amount of a reference miRNA (cel-miR-39) can be added to each sample before extraction for normalization and quality control (QC).

In yet other embodiment of this invention, measurement of the amount of miRNA extracted from the patient samples is done by Reverse transcription using stem- loop primers mix and TaqMan technology as described in C. Chen et al.“Real-time quantification of microRNAs by stem-loop RT-PCR”, Nucleic Acids Research, Volume 33, Issue 20, 1 January 2005, Pages el79, with some modifications in the probe design as described in Table 1. Figure 2 is a schematic description of RT and TaqMan RT-qPCR miRNA assays. It includes two steps, stem- loop RT and real-time PCR. Stem- loop RT primers bind to the 3' portion of miRNA molecules and are reverse transcribed with reverse transcriptase. This is done for all miRNAs analyzed in the test. The RT product is then quantified using conventional TaqMan PCR that includes miRNA- specific forward primer, reverse primer and a dye-labeled TaqMan probes that are synthesized using Locked Nucleic Acid (LNA) embedded in the probe. The purpose of LNA to increase its melting temperature (Tm) of the probe in order to increase its specificity. The test normalization method is based on adding a fixed number of synthetic samples with non-human C. elegans miR-39 as a reference control.

In certain embodiments, the method employs a detection approach that involves multiplex qRT-PCR, such as the microfluidic-based multiplex qRT-PCR method as described in Moltzahn, et al. (2010) Cancer Res 71:550-560; the disclosure of which is incorporated herein by reference. Detection methods of interest further include, but are not limited to, those described in Mitchell P S, et al. (2008) AL5105(30): 10.513- 10518 and U.S. Patent

Publication Nos. 2011/0275534 and 2012/0264638 the disclosures of which are incorporated herein by reference.

The methods of the present disclosure include methods for determining a likelihood of non-adverse prostate cancer pathology in a subject. Such methods generally involve

determining an amount of at least one diagnostic miRNA using an assay or detection method as described herein). The amount of the diagnostic miRNA(s) may be compared with a threshold amount, and the results of the comparison may be used to indicate the likelihood of non- adverse prostate cancer pathology in the subject.

In certain aspects, a threshold amount is calculated using the level of one or more miRNA(s). In certain aspects, a reference amount is instead, or also, calculated using one or more biomolecule(s) that are not miRNA(s), such as polypeptides (e.g., peptides, proteins, etc.), and/or nucleic acids (e.g., DNA, long non-coding RNA molecules, small RNA(s), spiked- in RNAs, etc.).

In certain aspects, the threshold amount may, in some aspects, be the amount of the diagnostic miRNA from a different individual or group of individuals, such as a control population that does have adverse prostate cancer pathology, e.g., a control population as described in Examples.

The threshold levels of diagnostic miRNAs miR-451, miR-106a, and/or miR-182 in the current invention is determined as the lower 80, 85, 90, 95, 97, 98, or 99 percentile of the relevant miRNA amounts measured in a sera or plasma samples taken from a reference group of subjects diagnosed as having PCa, and having a PCa grade of GG3, GG4 or GG5. The GGs of this group can be determined based on full pathological analysis of the prostate after surgical removal, and the serum samples were taken from the subjects prior to prostatectomy. The number of the subject in the reference group can be at least 15, 20, 30, 50, or 100.

In yet another embodiment of this invention, the threshold levels of diagnostic miRNAs miR-451, miR-106a, and/or miR-182 in the current invention is determined as the lower 80,

85, 90, 95, 97, 98, or 99 percentile of the relevant miRNA amounts measured in a sera or plasma samples taken from a reference group of subjects diagnosed as having PCa, and having a PCa grade of GG2, GG3, GG4 or GG5. The GGs of this group was determined based on full pathological analysis of the prostate after surgical surgery, and the serum samples were taken from the subjects prior to prostatectomy. The number of the subject in the reference group can be at least 15, 20, 30, 50, or 100.

In some embodiments, the threshold amount is an amount of the diagnostic miRNA from the same subject, measured at a prior time point. For instance, the prior time point may be a time point that is prior to the subject exhibiting clinical symptoms of prostate cancer and/or at an earlier stage of the disease.

In particular embodiments, the described methods further include calculating the reference RNA amount using small RNAs added in fixed quantities to the samples being assayed. The use of such RNAs are described in, e.g., Cronin M, et al. (2004) Clin.

Chem 50(8): 1464-1471 and M N McCall and R A Irizarry (2008) Nucleic Acids Res. 36(17): el08; the disclosures of which are incorporated by reference.

In some embodiments, a reference amount is determined using one or more of the method(s) described in Peltier H J and Latham G J (2008) RNA 4(5):844-852; Timoneda O, et al. (2012) PLoS One 7(9):e44413; Meyer S U, et al. (2012) PLoS <9ne7(6):e38946; Wylie D, et al. (2011) BMC Res Notes 4:555; Kirschner M B, et al. (2011) PLoS One 6(9):e24145; Roa W, et al. (2010) Clin Invest Med 33(2):E124; Schaefer A, et al. (2010) Exp. Mol. Med. 42(11):749- 58; Galiveti C R, et al. (2010) RNA 16(2):450-461; Bissels U, et al. (2009) RNA 15(12):2375- 2384; Mestdagh P, et al. (2009) Genome Biol. 10(6):R64; and/or variant(s) or comparable method(s) to the method(s) of any of the foregoing, the disclosures of which are incorporated herein by reference.

In addition to the amount of one or more diagnostic miRNA(s), methods of the present disclosure may involve the use of one or more additional risk factors to determine a likelihood of an adverse prostate cancer pathology. Such additional risk factors include factors that may be ascertained without a biopsy of the subject (e.g., a biopsy of the subject's prostate). Such risk factors include, but are not limited to, the subject's age, race, PSA level, clinical stage, MRI scan of the prostate, and the like. Accordingly, in such embodiments the subject methods may be performed on a subject without requiring a biopsy of the subject.

Additional risk factors of interest further include risk factors that require a biopsy. Such risk factors include, but are not limited to, the subject's primary biopsy Gleason score, secondary biopsy Gleason score, Gleason score sum, percentage cancer in biopsy cores, and the like.

The amounts of diagnostic miRNA(s) and/or one or more additional risk factors may be combined to provide an assessment of the likelihood of adverse prostate cancer pathology in a subject. For example, the diagnostic miRNA(s) can be combined with one or more risk factors as described above in an algorithm, which facilitates an assessment of the likelihood of adverse prostate cancer pathology in a subject.

In certain aspects, the detection of one or more diagnostic miRNA may be incorporated into an existing prostate cancer prediction algorithm, such as the CAPRA score described in Cooperberg, et al. (2005) J. Urol. 173(6): 1938- 1942; the disclosure of which is incorporated herein by reference.

In certain aspects, combination of the detection of one or more diagnostic miRNA (e.g., miR-451, miR-106a, miR-182, or any combination thereof) with an existing tool may use a statistical and/or learning machine algorithm(s) to find an optimal combination of the one or more diagnostic miRNA(s) with the other factor(s) considered by the prediction tool. A variety of statistical or machine learning algorithms are known in the art and may facilitate such a combination, such as genetic algorithms, support vector machines, neural networks, hidden Markov models, Bayesian networks, and the like.

The methods of the present disclosure can include generating a report indicating the results of the method and providing guidance as to how the results might be applied to the care of the subject. A“report,” as described herein, refers generally to an electronic document or file (e.g., pdf file, monitor display), as well as a tangible document (e.g., paper report). A subject report can be completely or partially electronically generated, e.g., presented on an electronic display (e.g., computer monitor).

The method results that are included in the report can include, for example, one or more of the amounts of the diagnostic miRNA assayed. The level can be reported as a quantitative score (e.g., a concentration, e.g., pg/ml serum) and/or a semi-quantitative score (e.g., a score reflecting an amount of a biomarker relative to a control level or a selected threshold level).

The method results can optionally include assay results for a control biomarker. Reports can include information such as a predicted risk that the patient has or will develop an adverse prostate cancer pathology. Reports can include guidance to a clinician as to a treatment recommendation for the subject based on the likelihood of adverse prostate cancer pathology in a subject. For example, reports can include a recommendation regarding non- invasive treatments or invasive treatments. In particular examples, the reports can recommend further evaluation and/or recommendations for avoiding expensive and invasive evaluations and/or a recommendations regarding therapeutic intervention (e.g., administering a drug, recommending surgical intervention, etc.), modifying a treatment regimen (e.g., adjusting a drug dose (e.g., increasing or decreasing a dose), adjusting a dosage regimen (e.g., increasing or decreasing dose frequency and/or amount), and the like.

A report can further include one or more of: 1) patient information (e.g., name, medical information (e.g., age, gender, symptoms (e.g., symptoms that may be relevant to diagnosis of prostate cancer), etc.), 2) information about the biological sample (e.g., type, when obtained); 3) information regarding where and how the assay was performed (e.g., testing facility, assay format); 4) service provider information; and/or 5) an interpretive report, which can provide a narrative providing an at least partial interpretation of the results so as to facilitate a diagnosis by a clinician.

Accordingly, the methods disclosed herein can further include a step of generating or outputting a report providing the method results and, optionally, other information such as treatment guidance as described herein. The report can be provided in the form of an electronic medium (e.g., an electronic display on a computer monitor), or in the form of a tangible medium (e.g., a report printed on paper or other tangible medium). An assessment as to the likelihood can be referred to as“risk report” or, simply, a“diagnostic result”. The person or entity that prepares a report (“report generator”) may also perform steps such as sample gathering, sample processing, and the like. Alternatively, an entity other than the report generator can perform steps such as sample gathering, sample processing, and the like. A report can be provided to a user. A“user” can be, for example, a health professional (e.g., a clinician, a laboratory technician, a physician, etc.).

The methods of the present disclosure can be computer-implemented, such that method steps (e.g., assaying, comparing, calculating, and the like) are be automated in whole or in part. Accordingly, the present disclosure provides methods, computer systems, devices and the like in connection with computer-implemented methods of determining a likelihood of adverse prostate cancer pathology in a subject. For example, the method steps, including obtaining values for the diagnostic

miRNA(s), comparing diagnostic miRNA amount(s) to a reference amount, generating a report, and the like, can be completely or partially performed by a computer program product. Values obtained can be stored electronically, e.g., in a database, and can be subjected to an algorithm executed by a programmed computer.

For example, the methods of the present disclosure can involve inputting the amount of a diagnostic miRNA (e.g., an amount of miR451, miR-106a, miR-182, and/or miR-345) into a computer programmed to execute an algorithm to perform the comparing step described herein, and generate a report as described herein, e.g., by displaying or printing a report to an output device at a location local or remote to the computer.

The present invention thus provides a computer program product including a computer readable storage medium having a computer program stored on it. The program can, when read by a computer, execute relevant calculations based on values obtained from analysis of one or more biological sample from an individual. The computer program product has stored therein a computer program for performing the calculation(s).

The present disclosure provides systems for executing the program described above, which system generally includes: a) a central computing environment; b) an input device, operatively connected to the computing environment, to receive patient data, wherein the patient data can include, for example, biomarker level or other value obtained from an assay using a biological sample from the patient, as described above; c) an output device, connected to the computing environment, to provide information to a user (e.g., medical personnel); and d) an algorithm executed by the central computing environment (e.g., a processor), where the algorithm is executed based on the data received by the input device, and wherein the algorithm calculates a value, which value is indicative of the likelihood the subject has an adverse prostate cancer pathology, as described herein.

The present disclosure also provides computer systems for determining a likelihood of adverse prostate cancer pathology in a subject. The computer systems include a processor and memory operably coupled to the processor, wherein the memory programs the processor to receive assay data including an amount of at least one diagnostic miRNA in a biological sample from a subject; compare the amount received with a reference amount; and calculate a likelihood of adverse prostate cancer pathology in the subject, based on results of said comparing the determined amounts obtained from the analyzing unit with the threshold amount. In certain aspects, the system calculates a likelihood of adverse prostate cancer pathology in the subject based on one or more additional risk factors, such as the subject's age, PSA level, MRI scan results, etc.

Computer systems may include a processing system, which generally comprises at least one processor or processing unit or plurality of processors, memory, at least one input device and at least one output device, coupled together via a bus or group of buses. In certain embodiments, an input device and output device can be the same device. The memory can be any form of memory device, for example, volatile or non-volatile memory, solid state storage devices, magnetic devices, etc. The processor can comprise more than one distinct processing device, for example to handle different functions within the processing system.

An input device receives input data and can comprise, for example, a keyboard, a pointer device such as a pen-like device or a mouse, audio receiving device for voice- controlled activation such as a microphone, data receiver or antenna such as a modem or wireless data adaptor, data acquisition card, etc. Input data can come from different sources, for example keyboard instructions in conjunction with data received via a network.

Output devices produce or generate output data and can comprise, for example, a display device or monitor in which case output data is visual, a printer in which case output data is printed, a port for example a USB port, a peripheral component adaptor, a data transmitter or antenna such as a modem or wireless network adaptor, etc. Output data can be distinct and derived from different output devices, for example a visual display on a monitor in conjunction with data transmitted to a network. A user can view data output, or an

interpretation of the data output, on, for example, a monitor or using a printer. The storage device can be any form of data or information storage means, for example, volatile or non volatile memory, solid state storage devices, magnetic devices, etc.

In use, the processing system may be adapted to allow data or information to be stored in and/or retrieved from, via wired or wireless communication means, at least one database.

The interface may allow wired and/or wireless communication between the processing unit and peripheral components that may serve a specialized purpose. In general, the processor can receive instructions as input data via input device and can display processed results or other output to a user by utilizing output device. More than one input device and/or output device can be provided. A processing system may be any suitable form of terminal, server, specialized hardware, or the like.

A processing system may be a part of a networked communications system. A processing system can connect to a network, for example the Internet or a WAN. Input data and output data can be communicated to other devices via the network. The transfer of information and/or data over the network can be achieved using wired communications means or wireless communications means. A server can facilitate the transfer of data between the network and one or more databases. A server and one or more databases provide an example of an information source.

Thus, a processing computing system environment may operate in a networked environment using logical connections to one or more remote computers. The remote computer may be a personal computer, a server, a router, a network PC, a peer device, or other common network node, and typically includes many or all of the elements described above.

Certain embodiments may be described with reference to acts and symbolic

representations of operations that are performed by one or more computing devices. As such, it will be understood that such acts and operations, which are at times referred to as being computer-executed, include the manipulation by the processor of the computer of electrical signals representing data in a structured form. This manipulation transforms the data or maintains them at locations in the memory system of the computer, which reconfigures or otherwise alters the operation of the computer in a manner understood by those skilled in the art. The data structures in which data is maintained are physical locations of the memory that have particular properties defined by the format of the data. However, while an embodiment is being described in the foregoing context, it is not meant to be limiting as those of skill in the art will appreciate that the acts and operations described hereinafter may also be implemented in hardware.

Embodiments may be implemented with numerous other general-purpose or special- purpose computing devices and computing system environments or configurations. Examples of well-known computing systems, environments, and configurations that may be suitable for use with an embodiment include, but are not limited to, personal computers, handheld or laptop devices, personal digital assistants, multiprocessor systems, microprocessor-based systems, programmable consumer electronics, network, minicomputers, server computers, web server computers, mainframe computers, and distributed computing environments that include any of the above systems or devices.

Embodiments may be described in a general context of computer-executable instructions, such as program modules, being executed by a computer. Generally, program modules include routines, programs, objects, components, data structures, etc., that perform particular tasks or implement particular abstract data types. An embodiment may also be practiced in a distributed computing environment where tasks are performed by remote processing devices that are linked through a communications network. In a distributed computing environment, program modules may be located in both local and remote computer storage media including memory storage devices.

The present disclosure provides computer program products that, when executed on a programmable computer such as that described above, can carry out the methods of the present disclosure. As discussed above, the subject matter described herein may be embodied in systems, apparatus, methods, and/or articles depending on the desired configuration. These various implementations may include implementation in one or more computer programs that are executable and/or interpretable on a programmable system including at least one programmable processor, which may be special or general purpose, coupled to receive data and instructions from, and to transmit data and instructions to, a storage system, at least one input device (e.g. video camera, microphone, joystick, keyboard, and/or mouse), and at least one output device (e.g. display monitor, printer, etc.).

Computer programs (also known as programs, software, software applications, applications, components, or code) include instructions for a programmable processor, and may be implemented in a high-level procedural and/or object-oriented programming language, and/or in assembly/machine language. As used herein, the term“machine-readable medium” refers to any computer program product, apparatus and/or device (e.g., magnetic discs, optical disks, memory, etc.) used to provide machine instructions and/or data to a programmable processor, including a machine-readable medium that receives machine instructions as a machine-readable signal.

It will be apparent from this description that aspects of the present invention may be embodied, at least in part, in software, hardware, firmware, or any combination thereof. Thus, the techniques described herein are not limited to any specific combination of hardware circuitry and/or software, or to any particular source for the instructions executed by a computer or other data processing system. Rather, these techniques may be carried out in a computer system or other data processing system in response to one or more processors, such as a microprocessor, executing sequences of instructions stored in memory or other computer- readable medium including any type of ROM, RAM, cache memory, network memory, floppy disks, hard drive disk (HDD), solid-state devices (SSD), optical disk, CD-ROM, and magnetic- optical disk, EPROMs, EEPROMs, flash memory, or any other type of media suitable for storing instructions in electronic format.

In addition, the processor(s) may be, or may include, one or more programmable general-purpose or special-purpose microprocessors, digital signal processors (DSPs), programmable controllers, application specific integrated circuits (ASICs), programmable logic devices (PLDs), trusted platform modules (TPMs), or the like, or a combination of such devices. In alternative embodiments, special-purpose hardware such as logic circuits or other hardwired circuitry may be used in combination with software instructions to implement the techniques described herein.

The methods of the present disclosure can provide results which can then be applied to facilitate decisions as to the care of the subject. Examples are provided below.

The methods of the present disclosure can help a clinician in making a treatment decision for the subject and/or for treatment of the subject, e.g., whether the results of the method suggest the subject may or may not benefit from invasive therapeutic intervention for treatment of prostate cancer. For example, based on the method results, a therapy can be selected and implemented for the subject based on the likelihood he has a low risk of having an adverse prostate cancer pathology. Clinical signs, symptoms and other factors such as family history can also be considered to facilitate selecting a therapy.

The method results can guide a clinician as to whether or not any therapy for treatment of prostate cancer should be administered.

The methods of the present disclosure can facilitate monitoring therapy of a subject undergoing treatment for prostate cancer, such as active surveillance, and the like.

Kits of the present disclosure can include a detection agent(s) for one or more, two or more, or three or more diagnostic miRNAs. As used herein, a“detection reagent” refers to a binding partner for a biomarker that is suitable for use in detection of a biomarker, and is optionally detectably labeled. Detection agent(s) for one or more reference miRNA(s) can also be included. Kits can include one or more devices, computer systems, devices and the like, including such devices and computer systems as described herein.

Kits can include instructions for using the components of the kit to practice a method of the present disclosure. The instructions are generally recorded on a suitable recording medium, such as paper, plastic, electronic storage, medium, and the like. For example, the instructions may be present in the kits as a package insert, in the labeling of the container of the kit or components thereof (e.g., associated with the packaging or sub-packaging), etc. In other embodiments, the instructions are present as an electronic storage data file present on a suitable computer readable storage medium, e.g. compact disc-read only memory (CD-ROM), digital versatile disk (DVD), diskette, etc. In other examples, the instructions provided do not contain many or all assay details, but rather provide direction as to a remote source for obtaining detailed instructions, e.g. via the internet. EXAMPLES

Example 1 - Differentiation between PCa patients with non-adverse disease vs PCa patients with adverse disease, using serum RQ levels of miR-451, miR-106a, and/or miR- 182.

Study Design and Patient Samples:

Study design was a cross sectional, retrospective, case control, one side blinded, study. The study is based on frozen sera samples and clinical data collected by the MIDGAM-The Israeli Biorepository Network for Research (available on-line at midgam.org.il). The study included analysis of sera samples selected from MIDGAM biorepository according to the following criteria: Sera taken patients who were referred for prostate removal surgery. Sera was obtained before the surgery, and pathology report of the removed prostate was available. Sera from subject not having PCa was tested as well. The study was approved by the local ethical committee. The objective of the study was to compare between the following patient groups:

• Non-aggressive PCa (Gleason Grade 1 or 2).

· Aggressive PCa (Gleason Grade 3 and up).

• Age matched control without PCa.

Patient Inclusion Criteria:

• Male Patient that have signed consent to include his samples and data in the MIDGAM biorepository.

· Patients were referred for prostate removal surgery following PCa diagnosis based on prostate biopsy. Prostate biopsy results were available.

• Sera was obtained just before the prostate removal, and pathologic analysis results of the removed prostate are available.

• Age 40-85 years

· Control group of subjects were PCa was not diagnosed, or patients diagnosed with non- malignant, Benign Prostate Hyperplasia (BPH)

Patient Exclusion Criteria:

• Discovery of a disorder other than PCa

• Prior chemotherapy

· Prior therapy for cancer

• Prior urology-related surgery

• The subject has known human immunodeficiency virus, hepatitis B surface antigen, or hepatitis C antibody. Detection of miRNAs:

Frozen (-80°C) selected sera was transported frozen (dry ice) from MIDGAM to the CureWize facility, with study identification numbers only. Samples were stored in sample repository at -80°C till miRNA extraction. miRNA extraction was performed using miRNeasy Semm/Plasma Kit (Qiagen Cat. 217184) according to manufacturer instructions. Fixed amount of reference miRNA (miRNA C. el. 39) was added to each sample before extraction for normalization and QC according to manufacturer instructions.

Reverse Transcription (RT) was done using TaqMan miRNA RT kit (Applied Biosystems cat. 4366596) and a mix of Stem- Loop primers for RT of miRNAs miR-451, miR-106a, and miR- 182 (see Table 1), according to manufacturer’s instructions. Real time quantitative PCR (RT- qPCR) was performed using PCR primers and probes for each of measured miRNAs, and PCR mix (Fast Advanced TaqMan PCR mix, Applied biosystems Cat.4444555). See Table 1 for primer and probe sequences.

Preparation of the PCR mix, pipetting of samples and controls to the 96-well plates (in duplicates), was done using the automatic pipetting system (ARISE biotech, EazyMate 400). Plates were analyzed using StepOnePlus Real Time PCR system. Relative quantities (RQ) of miRNAs miR-451, miR-106a, and miR-182 were calculated using the ddCt method (as described by Livak KJ and Schmittgen TD. Analysis of relative gene expression data using real-time quantitative PCR and the 2(-Delta C(T)) Method. Methods. 2001 Dec;25(4):402-8, incorporate here as a whole). The RQ was calculated by the StepOne V2.3 proprietary software, where added cel-miR-39 was used as a reference miRNA, and a mix of synthetic miRNAs (miR-451, miR 106a, miR-182, and cel-miR-39) were used as a calibrator (reference sample).

Statistical Analysis:

Statistical analysis was performed using MedCalc Statistical Software version 17.8.2 (MedCalc Software bvba, Ostend, Belgium; available online at medcalc.org; 2017). Initial analyses compared distributions of RQ values from miRNAs between patients grouped according to their Gleason Grade, using graphical summaries and the Wilcoxon rank-sum test to assess significance. Analysis of the ability of each of the miRNAs to differentiate between patients with Non-adverse PCa vs Adverse PCa was done using receiver operating characteristic (ROC) area under the curve (AUC) values. miRNAs RQ cut-off values, or threshold values, for differentiate between patients with non-adverse PCa vs adverse PCa were set using the lower 99% percentile RQ of the miRNAs in the adverse disease groups.

Diagnostic performance for the chosen threshold values were characterize in terms of sensitivity and specificity. Results

Clinical characteristic and sera miRNAs RQ distribution in the different study groups:

Figure 3 describes the correlation between Ct of cel-miR-39 used for normalization and final RQ of miR451. There is no correlation between the level of the added reference miRNA- 39 Ct and RQ of miRNA 451 (r=-0.13 Pearson p=0.3), thus indicating that the normalization was effective. However, 3 samples had relatively high values of Ct miR-39 (>30), indicating a very low yield of the extraction procedures, and those samples were excluded from further analysis. Serum samples (n=5) that appeared red due to hemolysis of red blood cell during serum separation were excluded as well.

The following table describes the patient’s characteristic samples that was identified in MIDGAM biorepository to meet the study criteria:

Figures 4 A, B, and C describe the distribution of miR-451, miR-106a, and miR-182, according to the final biopsy Gleason Groups.

Mann Whitney rank sum test for significant differences between GG1, GG2, and GG3 groups was also performed. Results shown in the tables below (significant p-values <0.05, are denoted in bold):

and up) :

Figures 5 A, B, and C describe the distribution of diagnostic miRNAs RQ in the combined group of GG1 and GG2, vs GG3 and up. Optional threshold values for differentiation between the groups, providing at least 94% specificity (equivalent to the lower 94% percentile) are denoted with a bold line. Results showing patients having sera RQ of diagnostic miRNAs below that threshold are favorable of having non-adverse PCa (having GG1 or GG2).

The diagnostic performance for differentiating patients having non-adverse PCa (GG1 and GG2) vs adverse PCa (GG3 and up) using the above-mentioned threshold values are described in the following table:

Figure 6 describes ROC analysis (Area under the curve AUC and p-value) of the ability of RQ of miR-451, miR-106a, and miR-182 (panels A,B,C respectively) to differentiate between GG1 and 2 vs GG3 and up.

5 Differentiation between patients with non-adverse (GG1) and adverse disease (GG2 and up):

Figure 7 (Panels A, B, C) describes the distribution of diagnostic miRNAs RQ in the GG1 group vs the combined group of patients classified as GG2 and up. Optional threshold values providing at least 90% specificity (equivalent to the lower 90% percentile) for differentiation between the groups are denoted with a bold line. Patients having sera RQ of 0 diagnostics miRNAs below that threshold, are favorable of having non-adverse PCa (having GG1).

The diagnostic performance for differentiating patients having non-adverse PCa (GG1) vs adverse PCa (GG2 and up) using the above-mentioned threshold values are described in the following table:

Figure 8 describes ROC analysis (Area under the curve AUC and p value) of the ability o RQ of miR-451, miR-106a, and miR-182 (panels A,B,C respectively) to differentiate between GG1 vs GG2 and up.

Discussion:

In this example we have shown that the serum RQ of diagnostic miRNAs in PCa patients having non-adverse disease is significantly lower than in PCa patients with adverse disease. We have showed that it possible to differentiate PCa patients with GG1 disease vs GG2 and up, and non-adverse patients having GG1 or GG2 disease grade vs GG3 and up. In both cases the specificity of the differentiation is very high (above 90% or above 94%) and the sensitivity is between 44-50%.

Previous studies used certain diagnostic miRNAs for prognosing PCa pathology, however, the current study can be distinguished from the previous studies as follows:

In US patent application publication 2016/0237505 A1 the inventors tested a group of miRNAs, including miR-451, 106, and 182, in the sera of a group of PCa patients with low- grade prostate cancer (Gleason score 6 (3+3) or GG1)) and high-grade prostate cancer

(Gleason Grade 4 and 5). The inventors therein teach that the RQs of miR-451, 106 and 182 are higher in the sera of low grade PCa patients vs high grade PCa patients (see FIG 1 in2016/0237505 Al) . In contrast, the present disclosure demonstrates that the RQ of miR-451, 106 and 182 are lower in the sera of low grade PCa patients vs high grade PCa patients, see Figures 4, 5, and 7 in this application. Another distinction is that in the prior disclosure, the inventors do not show the ability to differentiate between GG1 vs GG2 and GG3, or GG1 and GG2 vs GG3 and up. Whereas in our invention this is feasible.

In US patent 9,790,557 B2 the inventors also test the level of miR-106a and miR-451 in the sera of PCa with non-adverse disease vs PCa having adverse disease, but in contrast to the current disclosure, the‘557 patent did not find any significant difference between the patient groups regarding those miRNAs. See figure 16 in the‘557 patent, showing no significant difference regarding miR-106a.

In Moltzahn F et al, Microfluidic -based multiplex qRT-PCR identifies diagnostic and prognostic microRNA signatures in the sera of prostate cancer patients. Cancer Res. 2011 Jan 15;71(2):550-60. The authors tested miR-451 and-106a in sera of low, medium, and high risk

PCa patients. For the RQ of miR-451, there was no significant difference between groups of low and medium risk patients, and there was no significant trend among the 3 risk groups. See Table 2 and Figure 3 in the above-mentioned reference. For miR-106a the authors show a significant trend as RQs of the increase from low risk group to high risk groups. However, the risk classification method used by the author therein is the CAPRA index, a scoring scheme based on the patients’ age, PSA level, clinical tumor stage, Gleason score, and percentage of biopsy cores positive for cancer at diagnosis. The medium risk group encompass patients with Gleason sum score from 6-7 (see Table 1) which equivalent to GG1 (Gleason sum 3+3= 6), GG2 (Gleason sum 3+4 =7), up to GG3 (Gleason sum 4+3=7). Therefore, Moltzahn does not describe the ability to differentiate between GG1 vs GG2 and up or GG1 and GG2 vs GG3 and up as demonstrated in the current disclosure.

In conclusion, this study identifies for the first time 3 serum miRNAs that can act as independent prognostic markers for PCa. Furthermore, it shows how those serum miRNAs can be used to identify relatively small steps in tumor progression allowing increasing clinical refinement of disease status.

Although the foregoing invention has been described in some detail by way of illustration and example for purposes of clarity of understanding, it is readily apparent to those of ordinary skill in the art in light of the teachings of this invention that certain changes and modifications may be made thereto without departing from the spirit or scope of the appended claims. It is also to be understood that the terminology used herein is for the purpose of describing particular embodiments only, and is not intended to be limiting, since the scope of the present invention will be limited only by the appended claims.

Accordingly, the preceding merely illustrates the principles of the invention. It will be appreciated that those skilled in the art will be able to devise various arrangements which, although not explicitly described or shown herein, embody the principles of the invention and are included within its spirit and scope. Furthermore, all examples and conditional language recited herein are principally intended to aid the reader in understanding the principles of the invention and the concepts contributed by the inventors to furthering the art, and are to be construed as being without limitation to such specifically recited examples and conditions. Moreover, all statements herein reciting principles, aspects, and embodiments of the invention as well as specific examples thereof, are intended to encompass both structural and functional equivalents thereof. Additionally, it is intended that such equivalents include both currently known equivalents and equivalents developed in the future, i.e., any elements developed that perform the same function, regardless of structure. The scope of the present invention, therefore, is not intended to be limited to the exemplary embodiments shown and described herein. Rather, the scope and spirit of present invention is embodied by the appended claims.

Claims

We claim:

1. A method for determining the pathology of prostate cancer in a subject, comprising: detecting the level of a miRNA selected from the group consisting of miR-451, miR-

106a, and miR-182 in a sample from a subject; and

comparing the detected level with a threshold level of the detected miRNA,

wherein if the detected level is below an 80^ώ-99^ώ percentile of the threshold level, the subject has an increased likelihood of a non-adverse prostate cancer pathology, and wherein if the detected level is above an 80^ώ-99^ώ percentile of the threshold level, the subject has an increased likelihood of an adverse prostate cancer pathology.

2. The method of claim 1, wherein the subject has been previously diagnosed with prostate cancer.

3. The method of claim 1 or claim 2, wherein one of miR-451, miR-106a, and miR-182 is detected.

4. The method of claim 1 or claim 2, wherein more than one miRNA is detected.

5. The method of claim 4, wherein miR-451 and miR-106a, miR-451 and miR-182, miR- 182 and miR-106a, or miR-451, miR-106a, and miR-182 are detected.

6. The method of any one of claims 1-5, wherein the threshold level is determined from miRNAs isolated from a group of patients diagnosed with prostate cancer, and having a Gleason Grade (GG) of GG3, GG4, GG5, or GG6.

7. The method of any one of claims 1-5, wherein the threshold level is determined from miRNAs isolated from a group of patients diagnosed with prostate cancer, and having a Gleason Grade (GG) of GG2, GG3, GG4, GG5, or GG6.

8. The method of any one of claims 1-7, wherein if the level of detected miRNAs is below the 80, 85, 90, 95, 97, or 99^th percentile of the threshold level, the subject has an increased likelihood of a non-adverse prostate cancer pathology, and if the level of detected miRNAs is above the 80, 85, 90, 95, 97, or 99^th percentile of the threshold level, the subject has an increased likelihood of an adverse prostate cancer pathology.

9. The method of any one of claims 1-8, wherein the non-adverse prostate cancer pathology is equivalent to a GG1 or GG2 prostate cancer.

10. The method of any one of claims 1-9, wherein determining the prostate cancer pathology further includes determining a prostate serum antigen level, physical examination, MRI or ultrasound imaging of the prostate, computed tomography scan of the prostate, and/or prostate tumor biopsy.

11. The method of any one of claims 1-10, wherein if a non-adverse pathology is indicated, a non-invasive treatment is recommended to the subject, and if an adverse pathology is indicated, an invasive treatment is recommended to the subject.

12. The method of any one of claims 1-11, wherein the miR-451, miR-106a, and miR-182 are detected through use of an oligonucleotide listed on Table 1.

13. A method for treatment of a subject with prostate cancer comprising:

detecting the level of a miRNA selected from the group consisting of miR-451, miR- 106a, and miR-182 in a sample from a subject; and

comparing the detected level with a threshold level of the detected miRNA,

wherein if the detected level is below an 80^ώ-99^ώ percentile of the threshold level, the subject has an increased likelihood of a non-adverse prostate cancer pathology, and wherein if the detected level is above an 80^ώ-99^ώ percentile of the threshold level, the subject has an increased likelihood of an adverse prostate cancer pathology, and

if a non-adverse pathology is indicated, treating the subject with a non-invasive treatment; and

if an adverse pathology is indicated, treating the subject with an invasive treatment.

14. The method of claim 13, wherein the subject has been previously diagnosed with prostate cancer.

15. The method of claim 13 or claim 14, wherein one of miR-451, miR-106a, and miR-182 is detected.

16. The method of claim 13 or claim 14, wherein more than one miRNA is detected.

17. The method of claim 16, wherein miR-451 and miR-106a, miR-451 and miR-182, miR- 182 and miR-106a, or miR-451, miR-106a, and miR-182 are detected.

18. The method of any one of claims 13-17, wherein the threshold level is determined from miRNAs isolated from a group of patients diagnosed with prostate cancer, and having a Gleason Grade (GG) of GG3, GG4, GG5, or GG6.

19. The method of any one of claims 13-17, wherein the threshold level is determined from miRNAs isolated from a group of patients diagnosed with prostate cancer, and having a Gleason Grade (GG) of GG2, GG3, GG4, GG5, or GG6.

20. The method of any one of claims 13-19, wherein if the level of detected miRNAs is below the 80, 85, 90, 95, 97, or 99^th percentile of the threshold level, the subject has an increased likelihood of a non-adverse prostate cancer pathology, and if the level of detected miRNAs is above the 80, 85, 90, 95, 97, or 99^th percentile of the threshold level, the subject has an increased likelihood of an adverse prostate cancer pathology.

21. The method of any one of claims 13-20, wherein the non-adverse prostate cancer pathology is equivalent to a GG1 or GG2 prostate cancer.

22. The method of any one of claims 13-21, wherein determining the prostate cancer pathology further includes determining a prostate serum antigen level, physical examination, MRI or ultrasound imaging of the prostate, computed tomography scan of the prostate, and/or prostate tumor biopsy.

23. The method of any one of claims 13-22, wherein the miR-451, miR-106a, and miR-182 are detected through use of an oligonucleotide listed on Table 1.

24. The method of any one of claims 13-23, wherein the non-invasive treatment is active surveillance.

25. The method of any one of claims 13-24, wherein the invasive treatment is surgery, radiotherapy, chemotherapy, and/or biological (immuno-oncology/cell-based) therapy.