Compositions and methods for detecting ovarian cancer

Abstract

To provide compositions and methods for detecting ovarian cancer. [Solution] In one embodiment, this disclosure provides a technique for detecting ovarian cancer, for example, for early detection of ovarian cancer. In another embodiment, the technique provided herein is useful for selecting and / or monitoring and / or evaluating the effectiveness of treatments administered to a subject who has or has been determined to have ovarian cancer or to be susceptible to it. In some embodiments, the technique provided herein is useful for developing companion diagnostics in conjunction with treatment, for example, by measuring tumor volume and changes in tumor volume. In some embodiments, the technique provided herein is useful for developing companion diagnostics, for example, by identifying biomarkers in a woman's blood sample associated with treatment response.

Description

[Technical Field]

[0001] Cross-reference of related applications This application claims the benefits of U.S. Provisional Patent Application No. 62 / 962,711 filed 17 January 2020 and U.S. Provisional Patent Application No. 63 / 049,063 filed 7 July 2020, both of which are incorporated herein by reference in their entirety. [Background technology]

[0002] Early detection of cancer significantly increases the likelihood of successful treatment. However, there are still no effective screening recommendations for many cancers, including ovarian cancer. Typical challenges with cancer screening tests include limited sensitivity and specificity. A high rate of false positives can be particularly concerning, as it can make management decisions difficult for clinicians and patients who would not want to administer (or be administered) anti-cancer treatments that may have undesirable side effects. Conversely, a high rate of false negatives can lead to missed patients who need treatment, resulting in delayed treatment and consequently reducing the chances of success, thus failing to fulfill the purpose of screening tests. [Overview of the project] [Means for solving the problem]

[0003] This disclosure provides insights and techniques for achieving effective ovarian cancer screening. In some embodiments, the techniques provided are effective for detecting early-stage ovarian cancer. In some embodiments, the techniques provided are also effective when applied to a population that includes or consists of asymptomatic individuals (e.g., with sufficiently high sensitivity and / or low rates of false-positive and / or false-negative results). In some embodiments, the techniques provided are effective when applied to a population that includes or consists of individuals who do not have a genetic risk of developing ovarian cancer (e.g., asymptomatic individuals). In some embodiments, the techniques provided are effective when applied to a population that includes or consists of symptomatic individuals (e.g., individuals suffering from one or more symptoms of ovarian cancer). In some embodiments, the techniques provided are effective when applied to a population that includes or consists of individuals who are at risk for ovarian cancer (e.g., individuals with genetic and / or life-related risk factors for ovarian cancer). In some embodiments, as will be apparent to those skilled in the art by reading the disclosures provided herein, the provided technology may be or may comprise one or more compositions (e.g., molecular entities or complexes, systems, cells, collectibles, combinations, kits, etc.) and / or methods (e.g., methods for manufacturing, using, evaluating, etc.).

[0004] In some embodiments, the Disclosure identifies the root cause of the problem using certain prior art, including certain conventional approaches for the detection and diagnosis of ovarian cancer. For example, the Disclosure acknowledges that many conventional diagnostic assays and / or bulk analyses of extracellular vesicles, for example, based on cell-free nucleic acids, serum proteins (e.g., CA-125, which is part of the MUC16 polypeptide), can be time-consuming, costly, and / or lack sufficient sensitivity and / or specificity to obtain a reliable and comprehensive diagnostic assessment. In some embodiments, the Disclosure provides techniques (including systems, compositions, and methods) that address such problems in particular by detecting the co-localization of a target biomarker signature of ovarian cancer in individual extracellular vesicles, comprising at least one extracellular vesicle-associated membrane-bound polypeptide and at least one target biomarker selected from the group consisting of surface protein biomarkers, internal protein biomarkers, and RNA biomarkers. In some embodiments, the Disclosure provides techniques (including systems, compositions, and methods) to solve such problems by detecting such targeted biomarker signatures of ovarian cancer using a targeted entity detection approach developed by the Applicant and described in U.S. Patent Application No. 16 / 805,637 and International Application PCT / US2020 / 020529, both filed on February 28, 2020, titled “Systems, Compositions, and Methods for Detecting Target Entities,” based in particular on the interaction and / or colocalization of at least two or more target entities (e.g., targeted biomarker signatures) in individual extracellular vesicles.

[0005] In some embodiments, the Disclosure provides insight that screening of asymptomatic individuals, e.g., routine screening before the onset of symptoms or otherwise in the absence of symptoms, may be advantageous and important for the effective management (e.g., successful treatment) of ovarian cancer. In some embodiments, the Disclosure provides an ovarian cancer screening system that can be implemented to detect ovarian cancer, including early-stage cancer, in asymptomatic individuals (e.g., individuals without a genetic risk for ovarian cancer). In some embodiments, the provided technology is implemented to achieve routine screening of asymptomatic individuals (e.g., individuals without a genetic risk for ovarian cancer). The Disclosure provides, for example, compositions (e.g., reagents, kits, components, etc.), as well as methods for obtaining them and / or methods for using them, including strategies involving routine examination of one or more individuals (e.g., asymptomatic individuals). The Disclosure defines the usefulness of such systems and provides compositions and methods for implementing them.

[0006] In some embodiments, the provided technology achieves detection of one or more features of ovarian cancer (e.g., onset, progression, response to treatment, recurrence, etc.) (e.g., early detection in asymptomatic individuals and / or populations) with appropriate sensitivity and / or specificity (e.g., rate of false positives and / or false negative results) to enable useful application of the provided technology to single and / or periodic (e.g., periodic) assessments. In some embodiments, the provided technology is useful in conjunction with periodic physical examinations of women, such as mammograms, HPV, and / or Pap smear screenings. In some embodiments, the provided technology is useful in conjunction with treatment regimens; in some embodiments, the provided technology can improve one or more features (e.g., success rate by acceptable parameters) of such treatment regimens.

[0007] In some embodiments, the present disclosure provides techniques for use in classifying subjects (e.g., asymptomatic subjects) as having ovarian cancer or being susceptible to cancer. In some embodiments, the present disclosure provides methods or assays for classifying subjects (e.g., asymptomatic subjects) as having ovarian cancer or being susceptible to cancer. In some embodiments, the provided method or assay (a) detects extracellular vesicles expressing a target biomarker signature for ovarian cancer in a blood-derived sample from a subject requiring it (where the target biomarker signature comprises at least one extracellular vesicle-associated membrane-bound polypeptide and at least one target biomarker selected from the group consisting of surface protein biomarkers, intravesicular protein biomarkers, and intravesicular RNA biomarkers, wherein the surface protein biomarkers include AQP5, CDH6, CHODL, CLDN3, CLDN6, CLDN16, EpCAM, FOLR1, HTR3A, LEMD1, LRRTM1, MUC16, SLC34A2, ALPL, BST2, CD24, MSLN, MUC1, PTGS1, ST14, sTn, TACSTD2, BCAM, CD74, LY6E, SLC2A1, CXCR 4, DDR1, EFNB1, NOTCH3, PLXNB1, SPINT2, TNFRSF12A, and combinations thereof; the intravesicular protein biomarkers are selected from CRABP2, KLK7, MIF, PRAME, and S100A1, and combinations thereof; and the intravesicular RNA (e.g., mRNA) biomarkers are selected from CLDN6, CRABP2, KLK7, MIF, PRAME, S100A1, and combinations thereof); (b) comparing sample information showing the level of extracellular vesicles expressing the target biomarker signature in the blood-derived sample with reference information including a reference threshold level; and (c) classifying the subject as having ovarian cancer or being susceptible to cancer if the blood-derived sample shows an elevated level of extracellular vesicles expressing the target biomarker signature compared to a classification cutoff based on the reference threshold level.

[0008] In some embodiments, the methods or assays described herein may be performed for another additional target biomarker signature. In some such embodiments, the classification cutoff may be based on an additional criterion threshold level corresponding to the additional target biomarker signature.

[0009] In some embodiments, the extracellular vesicle-associated membrane-bound polypeptides used herein and / or described in the targeted biomarker signatures for ovarian cancer may be or include tumor-specific biomarkers and / or tissue-specific biomarkers (e.g., ovarian tissue-specific biomarkers). In some embodiments, such extracellular vesicle-associated membrane-bound polypeptides may be or include nonspecific markers, for example, present in one or more non-target tumors and / or one or more non-target tissues. In some embodiments, such extracellular vesicle-associated membrane-bound polypeptide biomarkers may be one or more of AQP5, CDH6, CHODL, CLDN3, CLDN6, CLDN16, EpCAM, FOLR1, HTR3A, LEMD1, LRRTM1, MUC16, ALPL, BST2, CD24, MSLN, MUC1, PTGS1, ST14, sTn, TACSTD2, BCAM, CD74, LY6E, SLC2A1, CXCR4, DDR1, EFNB1, NOTCH3, PLXNB1, SPINT2, TNFRSF12A, and SLC34A2, or may include them.

[0010] In some embodiments, the extracellular vesicle-associated membrane-bound polypeptide biomarker may be or include SLC34A2 polypeptide, AQP5 polypeptide, MUC16 polypeptide, CLDN3 polypeptide, CLDN6 polypeptide, FOLR1 polypeptide, ALPL polypeptide, BST2 polypeptide, CD24 polypeptide, MSLN polypeptide, MUC1 polypeptide, PTGS1 polypeptide, glycosylated sTn polypeptide, TACSTD2 polypeptide, and / or LRRTM1 polypeptide. In some embodiments, such extracellular vesicle-associated membrane-bound polypeptide may be or include SLC34A2 polypeptide. In some embodiments, such extracellular vesicle-associated membrane-bound polypeptide may be or include MUC16 polypeptide. In some embodiments, such extracellular vesicle-associated membrane-bound polypeptide may be or include FOLR1 polypeptide. In some embodiments, such extracellular vesicle-associated membrane-bound polypeptide may be or include LRRTM1 polypeptide. In some embodiments, such extracellular vesicle-associated membrane-bound polypeptide may be or include TACSTD2 polypeptide. In some embodiments, such extracellular vesicle-associated membrane-binding polypeptides may be or include CD24 polypeptides. In some embodiments, such extracellular vesicle-associated membrane-binding polypeptides may be or include PTGS1 polypeptides. In some embodiments, such extracellular vesicle-associated membrane-binding polypeptides may be or include MUC1 polypeptides. In some embodiments, such extracellular vesicle-associated membrane-binding polypeptides may be or include sTn polypeptide glycosylation. In some embodiments, such extracellular vesicle-associated membrane-binding polypeptides may be or include MSLN polypeptides. In some embodiments, such extracellular vesicle-associated membrane-binding polypeptides may be or include ALPL polypeptides.In some embodiments, such extracellular vesicle-associated membrane-bound polypeptides can be or include BST2 polypeptides. In some embodiments, such extracellular vesicle-associated membrane-bound polypeptides can be or include CLDN3 polypeptides.

[0011] In some embodiments, an ovarian cancer target biomarker signature can include an extracellular vesicle-associated membrane-bound polypeptide (e.g., those described herein) and, in some embodiments, at least one additional target surface protein biomarker, which can be or include AQP5, CDH6, CHODL, CLDN3, CLDN6, CLDN16, EpCAM, FOLR1, HTR3A, LEMD1, LRRTM1, MUC16, SLC34A2, ALPL, BST2, CD24, MSLN, MUC1, PTGS1, ST14, sTn, TACSTD2, BCAM, CD74, LY6E, SLC2A1, CXCR4, DDR1, EFNB1, NOTCH3, PLXNB1, SPINT2, TNFRSF12A, and / or any combination thereof.

[0012] In some embodiments, an ovarian cancer target biomarker signature can include an extracellular vesicle-associated membrane-bound polypeptide (e.g., those described herein) and, in some embodiments, at least one target intracellular RNA (e.g., mRNA) biomarker, which can be or include CLDN6, CRABP2, KLK7, MIF, PRAME, S100A1, and combinations thereof.

[0013] In some embodiments, an ovarian cancer target biomarker signature can include an extracellular vesicle-associated membrane-bound polypeptide (e.g., those described herein) and, in some embodiments, at least one additional target intracellular protein biomarker, which can be or include CRABP2, KLK7, MIF, PRAME, and S100A1, and combinations thereof.

[0014] In some embodiments, the target biomarker signature comprises an SCL34A2 polypeptide and / or a CLDN6 polypeptide, or at least one extracellular vesicle-associated membrane-bound polypeptide comprising the same; and at least one target biomarker MUC16.

[0015] In some embodiments, the target biomarker signature comprises a MUC16 polypeptide, or at least one extracellular vesicle-associated membrane-bound polypeptide comprising the same; and at least one target biomarker MUC16.

[0016] In some embodiments, the target biomarker signature comprises an SLC34A2 polypeptide, or at least one extracellular vesicle-associated membrane-bound polypeptide comprising the same; and at least two target biomarkers MUC16 and FOLR1.

[0017] In some embodiments, the target biomarker signature comprises an SLC34A2 polypeptide, or at least one extracellular vesicle-associated membrane-bound polypeptide comprising the same; and at least two target biomarkers SLC34A2 and FOLR1.

[0018] In some embodiments, the target biomarker signature comprises an SLC34A2 polypeptide, or at least one extracellular vesicle-associated membrane-bound polypeptide comprising the same; and at least one target biomarker MUC16.

[0019] In some embodiments, the target biomarker signature comprises an SCL34A2 polypeptide, or at least one extracellular vesicle-associated membrane-bound polypeptide comprising the same; and at least one target biomarker FOLR1.

[0020] In some embodiments, the target biomarker signature comprises the MUC16 polypeptide or at least one extracellular vesicle-associated membrane-bound polypeptide containing it; and at least two target biomarkers, MUC16 and CLDN6.

[0021] In some embodiments, the target biomarker signature comprises the MUC16 polypeptide or at least one extracellular vesicle-associated membrane-bound polypeptide containing it; and at least two target biomarkers, MUC16 and CLDN3.

[0022] In some embodiments, the target biomarker signature comprises the MUC16 polypeptide or at least one extracellular vesicle-associated membrane-bound polypeptide containing it; and at least two target biomarkers FOLR1 and CLDN3.

[0023] In some embodiments, the target biomarker signature comprises the MUC16 polypeptide or at least one extracellular vesicle-associated membrane-bound polypeptide containing it; and at least two target biomarkers MUC16 and FOLR1.

[0024] In some embodiments, the target biomarker signature comprises the MUC16 polypeptide or at least one extracellular vesicle-associated membrane-bound polypeptide containing it; and at least one target biomarker FOLR1.

[0025] In some embodiments, the target biomarker signature comprises the MUC16 polypeptide or at least one extracellular vesicle-associated membrane-bound polypeptide containing it; and at least two target biomarkers, SLC34A2 and MUC16.

[0026] In some embodiments, the target biomarker signature comprises the MUC16 polypeptide or at least one extracellular vesicle-associated membrane-bound polypeptide containing it; and at least two target biomarkers, SLC34A2 and FOLR1.

[0027] In some embodiments, the target biomarker signature comprises the MUC16 polypeptide or at least one extracellular vesicle-associated membrane-bound polypeptide containing it; and at least two target biomarkers, MUC16 and AQP5.

[0028] In some embodiments, the target biomarker signature comprises the MUC16 polypeptide or at least one extracellular vesicle-associated membrane-bound polypeptide containing it; and at least two target biomarkers, FOLR1 and AQP5.

[0029] In some embodiments, the target biomarker signature comprises a FOLR1 polypeptide or at least one extracellular vesicle-associated membrane-bound polypeptide containing it; and at least one target biomarker MUC16.

[0030] In some embodiments, the target biomarker signature comprises a FOLR1 polypeptide or at least one extracellular vesicle-associated membrane-bound polypeptide containing the same; and at least one target biomarker FOLR1.

[0031] In some embodiments, the target biomarker signature comprises a FOLR1 polypeptide or at least one extracellular vesicle-associated membrane-bound polypeptide containing it; and at least two target biomarkers, FOLR1 and CLDN6.

[0032] In some embodiments, the target biomarker signature comprises a FOLR1 polypeptide or at least one extracellular vesicle-associated membrane-bound polypeptide containing it; and at least two target biomarkers, SLC34A2 and CLDN3.

[0033] In some embodiments, the target biomarker signature comprises the FOLR1 polypeptide or at least one extracellular vesicle-associated membrane-bound polypeptide containing it; and at least two target biomarkers MUC16 and FOLR1.

[0034] In some embodiments, the target biomarker signature comprises a FOLR1 polypeptide or at least one extracellular vesicle-associated membrane-bound polypeptide containing it; and at least two target biomarkers MUC16 and CLDN3.

[0035] In some embodiments, the target biomarker signature comprises a FOLR1 polypeptide or at least one extracellular vesicle-associated membrane-bound polypeptide containing it; and at least two target biomarkers, SLC34A2 and MUC16.

[0036] In some embodiments, the target biomarker signature comprises the FOLR1 polypeptide or at least one extracellular vesicle-associated membrane-bound polypeptide containing it; and at least two target biomarkers, FOLR1 and CLDN3.

[0037] In some embodiments, the target biomarker signature comprises a FOLR1 polypeptide or at least one extracellular vesicle-associated membrane-bound polypeptide containing it; and at least two target biomarkers, FOLR1 and AQP5.

[0038] In some embodiments, the target biomarker signature comprises the LRRTM1 polypeptide or at least one extracellular vesicle-associated membrane-bound polypeptide containing it; and at least two target biomarkers MUC16 and MUC16.

[0039] In some embodiments, the target biomarker signature comprises a CLDN3 polypeptide or at least one extracellular vesicle-associated membrane-bound polypeptide containing it; and at least one target biomarker FOLR1.

[0040] In some embodiments, the target biomarker signature comprises a CLDN3 polypeptide or at least one extracellular vesicle-associated membrane-bound polypeptide containing the same; and at least one target biomarker MUC16.

[0041] In some embodiments, the target biomarker signature comprises a CLDN3 polypeptide or at least one extracellular vesicle-associated membrane-bound polypeptide containing it; and at least two target biomarkers, SLC34A2 and MUC16.

[0042] In some embodiments, the target biomarker signature comprises a CLDN3 polypeptide or at least one extracellular vesicle-associated membrane-bound polypeptide containing it; and at least two target biomarkers MUC16 and FOLR1.

[0043] In some embodiments, the target biomarker signature comprises a CLDN3 polypeptide or at least one extracellular vesicle-associated membrane-bound polypeptide containing it; and at least two target biomarkers MUC16 and CLDN3.

[0044] In some embodiments, the target biomarker signature comprises a CLDN3 polypeptide or at least one extracellular vesicle-associated membrane-bound polypeptide containing it; and at least two target biomarkers MUC16 and CLDN6.

[0045] In some embodiments, a reference threshold level for use in the provided method or assay described herein is determined by the level of extracellular vesicles expressing a target biomarker signature observed in comparable samples from a non-ovarian cancer population.

[0046] In some embodiments, extracellular vesicle-associated membrane-binding polypeptides contained in a target biomarker signature can be detected using an antibody-based activator. In some embodiments, such extracellular vesicle-associated membrane-binding polypeptides can be detected using a capture assay that includes an antibody-based activator. For example, in some embodiments, a capture assay for detecting the presence of extracellular vesicle-associated membrane-binding polypeptides in extracellular vesicles may involve contacting a blood-derived sample containing extracellular vesicles with a capture factor that directs such extracellular vesicle-associated membrane-binding polypeptides. In some embodiments, such a capture factor may include a binding moiety that directs to an extracellular vesicle-associated membrane-binding polypeptide (e.g., those described herein), which may be optionally conjugated to a solid substrate. Exemplary capture factors for extracellular vesicle-associated membrane-binding polypeptides may be, or include, a solid substrate (e.g., magnetic beads) and a binding moiety that directs to an extracellular vesicle-associated membrane-binding polypeptide (e.g., an antibody factor).

[0047] In some embodiments, the target biomarker contained in the target biomarker signature can be detected using appropriate methods known in the art, which may vary depending on the type of analyte being detected (e.g., surface protein, intravesicular protein, intravesicular RNA (e.g., mRNA)). For example, those skilled in the art will see, by reading this disclosure, that in some embodiments, surface protein biomarkers and / or intravesicular protein biomarkers can be detected using antibody-based activators, while in some embodiments, intravesicular RNA (e.g., mRNA) biomarkers can be detected using nucleic acid-based activators, for example, by quantitative reverse transcription PCR.

[0048] For example, in some embodiments in which the target biomarker is a surface protein biomarker and / or an intravesicular protein marker, such target biomarkers can be detected by including a proximity ligation assay after, for example, a capture assay (e.g., as described herein) for capturing extracellular vesicles expressing an extracellular vesicle-associated membrane-bound polypeptide (e.g., as used and / or described herein). In some embodiments, such a proximity ligation assay may include contacting a blood-derived sample containing extracellular vesicles with a set of detection probes each directed to a target biomarker, wherein the set includes at least two distinct detection probes, so that a combination of the extracellular vesicles and the set of detection probes is made, each of the two detection probes, comprising: (i) a binding portion directed to the surface protein biomarker and / or intravesicular protein biomarker; and (ii) an oligonucleotide domain coupled to the binding portion, comprising a double-stranded portion and a single-stranded overhang portion extending from one end of the oligonucleotide domain. Such single-stranded overhang portions of the detection probes are characterized in that they can hybridize with each other when the detection probes bind to the same extracellular vesicles. Then, when such a combination, including the set of extracellular vesicles and the detection probes, is maintained under conditions that allow the set of detection probes to bind to their respective targets on the extracellular vesicles, the detection probes can bind to the same extracellular vesicles to form a double-stranded complex. Such a double-stranded complex can be detected by contacting the double-stranded complex with a nucleic acid ligase to generate a ligated template; and by detecting the ligated template. The presence of such a ligated template indicates the presence of extracellular vesicles that are positive for the target biomarker signature of ovarian cancer.Such proximity ligation assays can be performed better than other existing proximity ligation assays, for example, with higher specificity and / or sensitivity; however, those skilled in the art will see, by reading this disclosure, that other forms of proximity ligation assays known in the art can also be used instead.

[0049] In some embodiments where the target biomarker is an intravesicular RNA (e.g., mRNA) marker, or includes such a marker, such a target biomarker can be detected by a nucleic acid detection assay. In some embodiments, the exemplary nucleic acid detection assay may be or include reverse transcription PCR.

[0050] In some embodiments in which the target biomarker is an intravesicular biomarker (e.g., an intravesicular protein biomarker and / or an intravesicular RNA (e.g., mRNA) biomarker), or includes such an intravesicular biomarker, such a target biomarker can be detected by processing the sample (e.g., immobilization and / or permeabilization) to expose the intravesicular biomarker(s) for subsequent detection, prior to a detection assay (e.g., a proximity ligation assay as described herein).

[0051] This disclosure particularly acknowledges that, unlike in the analysis of a single extracellular vesicle, the detection of a single ovarian cancer-associated serum protein or multiple ovarian cancer-associated biomarkers based on a bulk sample (e.g., a bulk sample of extracellular vesicles) typically does not provide sufficient specificity and / or sensitivity in determining whether the subject from which the sample was obtained is likely to have or be susceptible to ovarian cancer. This disclosure provides a system, composition, and / or method to solve such a problem, particularly including, for example, the specific requirement that individual extracellular vesicles for detection be characterized by the presence of a targeted biomarker signature comprising a combination of at least one extracellular vesicle-associated membrane-bound polypeptide and at least one target biomarker. In certain embodiments, the Disclosure teaches a technique that requires such individual extracellular vesicles to be characterized by the presence (e.g., expression) of such ovarian cancer target biomarker signatures, while extracellular vesicles that do not contain the target biomarker signatures do not generate a detectable signal (e.g., a level at least 10% above a reference level, where in some embodiments the reference level may be the level observed in a negative control sample, e.g., a sample in which no individual extracellular vesicles containing such target biomarker signatures are present).

[0052] Therefore, in some embodiments, the techniques provided herein may be useful for detecting the occurrence or recurrence of ovarian cancer in a subject and / or in a population of subjects. In some embodiments, a targeted biomarker signature can be selected for the detection of ovarian cancer. In some embodiments, the targeted biomarker signature can be selected for the detection of specific categories of ovarian cancer, including, for example, but not limited to, high-grade serous ovarian cancer, endometrial ovarian cancer, clear cell ovarian cancer, low-grade serous ovarian cancer, and / or mucinous ovarian cancer. In some embodiments, the techniques provided herein can be used periodically (e.g., annually) to screen a human subject or a population of human subjects for early-stage ovarian cancer or ovarian cancer recurrence.

[0053] In some embodiments, suitable subjects for the techniques provided herein to detect the onset or recurrence of ovarian cancer may be asymptomatic human subjects and / or entire asymptomatic populations. Such asymptomatic subjects may be subjects with a family history of ovarian cancer, a lifestyle that increases the risk of ovarian cancer, being postmenopausal, having been previously treated for ovarian cancer, being at risk of ovarian cancer recurrence after cancer treatment, being in remission after ovarian cancer treatment, and / or subjects who have been previously or periodically screened for the presence of at least one ovarian cancer biomarker, e.g., the CA-125 serum protein. In some embodiments, such asymptomatic subjects may be subjects determined to have normal serum CA-125 levels (e.g., serum CA-125 levels less than 35 U / mL). In some embodiments, such asymptomatic subjects may be subjects determined to have serum CA-125 levels equal to or greater than normal serum CA-125 levels. In alternative methods, in some embodiments, an asymptomatic subject may be a subject who has never been treated for ovarian cancer, has never been diagnosed with ovarian cancer, and / or has never received treatment for ovarian cancer.

[0054] In some embodiments, subjects or groups of subjects may be selected based on one or more characteristics, such as age, race, genetic history, personal history and / or medical history (e.g., smoking, alcohol, drugs, carcinogens, diet, obesity, diabetes, physical activity, sun exposure, radiation exposure, perineal talc use, hormone replacement therapy (HRT), infectious agents, such as exposure to viruses and / or occupational hazards).

[0055] In some embodiments, the techniques provided herein may be useful for selecting a treatment for subjects who have or are susceptible to ovarian cancer. In some embodiments, ovarian cancer treatment and / or adjuvant treatment can be selected in consideration of findings based on the techniques provided herein.

[0056] In some embodiments, the techniques provided herein may be useful for monitoring and / or evaluating the effectiveness of a treatment administered to a subject (e.g., a subject with ovarian cancer).

[0057] In some embodiments, the Disclosure provides techniques for managing patient care for, for example, one or more individual subjects and / or for an entire population of subjects. To provide just a few examples, in some embodiments, the Disclosure provides techniques that can be used in screening (e.g., temporarily or incidentally motivated screening and / or non-temporarily or non-incidentally motivated screening, e.g., periodic screening such as annually, semi-annually, every two years, or some other frequency). For example, in some embodiments, techniques provided for use in temporarily motivated screening may be useful for screening one or more individual subjects who are older than a certain age (e.g., over 50, 55, 60, 65, 70 or older) or for an entire population of subjects (e.g., asymptomatic subjects). In some embodiments, techniques provided for use in incidentally motivated screening may be useful for screening individual subjects who may have experienced an event or occurrence that motivates screening for ovarian cancer as described herein. For example, in some embodiments, incidental motivations related to the determination of one or more indicators of cancer or susceptibility may be, or include, events based on, for example, their family history (e.g., a close relative, e.g., a blood relative, has been previously diagnosed with ovarian cancer), the identification of one or more risk factors associated with ovarian cancer (e.g., lifestyle risk factors, including, but not limited to, smoking, alcohol, diet, obesity, occupational hazards, etc.) and / or prior incidental findings from genetic testing (e.g., genome sequencing), and / or imaging tests (e.g., ultrasound, computed tomography (CT), and / or magnetic resonance imaging (MRI) scans), or the occurrence of one or more signs or symptoms characteristic of ovarian cancer (e.g., abnormal menstrual bleeding that potentially indicates ovarian cancer).

[0058] In some embodiments, the technology provided for managing patient care may notify decisions and / or actions regarding treatment and / or payment (e.g., reimbursement of treatment costs). For example, in some embodiments, the technology provided may provide a determination of whether an individual subject has one or more indicators of ovarian cancer development or recurrence, thereby notifying the physician and / or patient of when to initiate treatment in consideration of such findings. In addition, or otherwise, in some embodiments, the technology provided may notify the physician and / or patient of treatment options based, for example, on findings of specific responsive biomarkers (e.g., ovarian cancer responsive biomarkers). In some embodiments, the technology provided may provide a determination of whether an individual subject is responsive to current treatment based, for example, on findings of changes in levels of one or more molecular targets associated with ovarian cancer, thereby notifying the physician and / or patient of the effectiveness of such treatment and / or decisions to maintain or modify treatment in consideration of such findings.

[0059] In some embodiments, the provided technology may notify a health insurer of a determination regarding whether to reimburse (or not reimburse) the screening itself (e.g., reimbursement valid only for periodic / regular screening, or only for temporary and / or incidentally motivated screening); and / or (2) the initiation, maintenance, and / or modification of treatment in consideration of findings obtained by the provided technology. For example, in some embodiments, the Disclosure provides methods for (a) receiving screening results as described herein, and likewise receiving requests for reimbursement of screening and / or a particular treatment regimen; (b) approving reimbursement of screening when performed in accordance with an appropriate schedule or response to relevant events, and / or approving reimbursement of a treatment regimen when it is an appropriate action in consideration of the received screening results; and (c) optionally providing notification of whether reimbursement is denied. In some embodiments, if the received screening results detect a biomarker that is an approved biomarker for the relevant treatment regimen, the treatment regimen is appropriate in light of the received screening results (for example, as noted on the instruction information label and / or by an approved companion diagnostic). Alternatively, or in addition, this disclosure envisions a reporting system (for example, performed by appropriate electronic devices and / or communication systems) that enables or facilitates the reporting and processing of screening results and / or reimbursement decisions as described herein.

[0060] Some embodiments provided herein relate to systems and kits for use in the provided technologies. In some embodiments, the system or kit may include a detection factor for a tumor biomarker signature of ovarian cancer (e.g., as described herein). In some embodiments, such a system or kit may include a capture factor for extracellular vesicle-associated membrane-bound polypeptides present in extracellular vesicles associated with ovarian cancer (e.g., as used and / or described herein); and (b) additional surface protein biomarkers (e.g., as used and / or described herein), intravesicle protein biomarkers (e.g., as used and / or described herein), and / or intravesic RNA (e.g., mRNA) biomarkers (e.g., as used and / or described herein), or may include, or be, additional surface protein biomarkers (e.g., as used and / or described herein), intravesicle protein biomarkers (e.g., as used and / or described herein), and / or intravesicle RNA (e.g., mRNA) biomarkers (e.g., as used and / or described herein).

[0061] In some embodiments, the capture factor included in the system and / or kit may include a binding moiety directed to an extracellular vesicle-associated membrane-binding polypeptide (e.g., as described herein). In some embodiments, such a binding moiety may be conjugated to a solid substrate, which in some embodiments may be or include a solid substrate. In some embodiments, such a solid substrate may be or include magnetic beads. In some embodiments, the exemplary capture factor included in the provided system and / or kit may be or include a solid substrate (e.g., magnetic beads) and an antibody factor directed to an extracellular vesicle-associated membrane-binding polypeptide conjugated thereto.

[0062] In some embodiments, the target biomarker includes a surface protein biomarker and / or an intravesicular protein biomarker, the system and / or kit may include a detection factor for performing a proximity ligation assay (e.g., as described herein). In some embodiments, such a detection factor for performing a proximity ligation assay may include a set of detection probes each directed to a target biomarker of the target biomarker signature, the set comprising at least two detection probes, each comprising (i) a polypeptide binding portion directed to the target biomarker; and (ii) an oligonucleotide domain coupled to the binding portion, wherein the oligonucleotide domain comprises a double-stranded portion and a single-stranded overhang portion extending from one end of the oligonucleotide domain, the single-stranded overhang portions of the detection probes being characterized in that they can hybridize with each other when the detection probes bind to the same extracellular vesicle.

[0063] In some embodiments, the provided system and / or kit may include multiple sets of detection probes (e.g., two, three, four, five or more), each set containing two or more detection probes (e.g., three, four, five, six, seven, eight, nine, ten, eleven, twelve, thirteen, fourteen, fifteen, sixteen, seventeen, eighteen, nineteen, twenty or more). In some embodiments, at least one set of detection probes may be directed towards the detection of ovarian cancer. For example, in some embodiments, the provided system and / or kit may include at least one set of detection probes for detecting ovarian cancer and at least one set of detection probes for detecting a different cancer (e.g., pancreatic cancer). In some embodiments, two or more detection probes may be directed towards different categories of ovarian cancer, such as high-grade serous ovarian cancer, endometrial ovarian cancer, clear cell ovarian cancer, low-grade serous ovarian cancer, or mucinous ovarian cancer. In some embodiments, two or more sets may be directed towards the detection of ovarian cancer at different stages. In some embodiments, two or more sets may be aimed at detecting ovarian cancer at the same stage.

[0064] In some embodiments, the detection probes in the provided kit can be provided as a single mixture in one container. In some embodiments, multiple sets of detection probes can be provided as individual mixtures in separate containers. In some embodiments, each detection probe is provided individually in a separate container.

[0065] In some embodiments, the target biomarker may include an intravesicular RNA (e.g., mRNA) biomarker, such a system and / or kit may include a detection factor for performing a nucleic acid detection assay. In some embodiments, such a system and / or kit may include a detection factor for performing quantitative reverse transcription PCR, which may include, for example, primers directed to an intravesicular RNA (e.g., mRNA) target(s).

[0066] In some embodiments, the provided system and / or kit may include, for example, at least one chemical reagent for processing a sample and / or extracellular vesicles therein. In some embodiments, the provided system and / or kit may include, for example, but not limited to, a fixative, a permeabilizer, and / or a blocker for processing extracellular vesicles in a sample. In some embodiments, the provided system and / or kit may include a nucleic acid ligase and / or nucleic acid polymerase. In some embodiments, the provided system and / or kit may include one or more primers and / or probes. In some embodiments, the provided system and / or kit may include, for example, one or more pairs of primers for PCR, e.g., quantitative PCR (qPCR) reactions. In some embodiments, the provided system and / or kit may include, for example, one or more probes, such as a hydrolysis probe which may be designed to increase the specificity of qPCR (e.g., a TaqMan probe). In some embodiments, the provided system and / or kit may include one or more multiplex probes, which may be useful, for example, when synchronous or parallel qPCR reactions are used (e.g., to facilitate or improve readout).

[0067] In some embodiments, the provided system and / or kit can be used for screening (e.g., routine screening) and / or other evaluation of individuals (e.g., asymptomatic or symptomatic subjects) to detect ovarian cancer (e.g., early detection). In some embodiments, the provided system and / or kit can be used for screening and / or other evaluation of individuals susceptible to ovarian cancer (e.g., individuals with known genetic, environmental, or experiential risk). In some embodiments, the provided system and / or kit can be used to monitor for recurrence of ovarian cancer in subjects that have been previously treated. In some embodiments, the provided system and / or kit can be used as a companion diagnostic in combination with treatment for subjects with ovarian cancer. In some embodiments, the provided system and / or kit can be used to monitor or evaluate the effectiveness of treatment administered to subjects with ovarian cancer. In some embodiments, the provided system and / or kit can be used to select treatment for subjects with ovarian cancer. In some embodiments, the provided system and / or kit can be used to determine and / or select a treatment for a subject having one or more symptoms associated with ovarian cancer (e.g., nonspecific symptoms).

[0068] Complexes formed by performing the methods described herein and / or using the systems and / or kits described herein are also within the scope of this disclosure. For example, in some embodiments, the complex comprises (a) an extracellular vesicle expressing a target biomarker signature, wherein at least two of the target biomarker signatures comprise at least one extracellular vesicle-associated membrane-bound polypeptide and at least one target biomarker selected from the group consisting of surface protein biomarkers, intravesicular protein biomarkers, and intravesicular RNA biomarkers, wherein the surface protein biomarkers are AQP5, CDH6, CHODL, CLDN3, CLDN6, CLDN16, EpCAM, FOLR1, HTR3A, LEMD1, LRRTM1, MUC16, SLC34A2, ALPL, BST2, CD24, MSLN, MU The extracellular vesicles are immobilized on a solid substrate containing binding moieties that point to such extracellular vesicle-associated membrane-bound polypeptides. Such a complex further comprises at least two detection probes directed to at least one target biomarker of the target biomarker signature present in the extracellular vesicle, wherein each detection probe binds to such target biomarker and each comprises (i) a binding domain directed to the target biomarker; and (ii) an oligonucleotide domain coupled to the binding portion, wherein the oligonucleotide domain comprises a double-stranded portion and a single-stranded overhang portion extending from one end of the oligonucleotide domain, and the single-stranded overhang portions of the detection probes hybridize with each other.

[0069] In some embodiments, extracellular vesicle-associated membrane-bound polypeptide biomarkers present in the extracellular vesicles forming the complex may include one or more of the following: AQP5, CDH6, CHODL, CLDN3, CLDN6, CLDN16, EpCAM, FOLR1, HTR3A, LEMD1, LRRTM1, MUC16, SLC34A2, ALPL, BST2, CD24, MSLN, MUC1, PTGS1, ST14, sTn, TACSTD2, BCAM, CD74, LY6E, SLC2A1, CXCR4, DDR1, EFNB1, NOTCH3, PLXNB1, SPINT2, TNFRSF12A, and combinations thereof. In some embodiments, such extracellular vesicle-associated membrane-bound polypeptides may be or include SLC34A2 polypeptides. In some embodiments, such extracellular vesicle-associated membrane-bound polypeptides may be or include MUC16 polypeptides. In some embodiments, such extracellular vesicle-associated membrane-binding polypeptides may be or include CLDN6 polypeptides. In some embodiments, such extracellular vesicle-associated membrane-binding polypeptides may be or include FOLR1 polypeptides. In some embodiments, such extracellular vesicle-associated membrane-binding polypeptides may be or include LRRTM1 polypeptides. In some embodiments, such extracellular vesicle-associated membrane-binding polypeptides may be or include TACSTD2 polypeptides. In some embodiments, such extracellular vesicle-associated membrane-binding polypeptides may be or include MUC1 polypeptides. In some embodiments, such extracellular vesicle-associated membrane-binding polypeptides may be or include sTn polypeptide glycosylation. In some embodiments, such extracellular vesicle-associated membrane-binding polypeptides may be or include MSLN polypeptides. In some embodiments, such extracellular vesicle-associated membrane-binding polypeptides may be or include ALPL polypeptides. In some embodiments, such extracellular vesicle-associated membrane-binding polypeptides may be or include BST2 polypeptides.In some embodiments, such extracellular vesicle-associated membrane-bound polypeptides may be or may include CLDN3 polypeptides.

[0070] These and other aspects included in this disclosure are described in more detail below and in the claims. The present invention provides, for example, the following items: (Item 1) It is a method, (a) Preparing or obtaining blood-derived samples from the subject; (b) In the blood-derived sample, extracellular vesicles expressing the first target biomarker signature ("extracellular vesicles expressing the first target biomarker signature") are detected, and in this case, the first target biomarker signature is At least one extracellular vesicle-associated membrane-bound polypeptide biomarker and It includes at least one target biomarker selected from the group consisting of surface protein biomarkers, intravesicular protein biomarkers, and intravesicular RNA biomarkers, in which case, The aforementioned surface protein biomarkers are CLDN6, AQP5, CLDN16, and CLD Selected from N3, FOLR1, EpCAM, LEMD1, LRRTM1, MUC16, CHODL, CDH6, HTR3A, SLC34A2, ALPL, BST2, CD24, MSLN, MUC1, PTGS1, ST14, sTn, TACSTD2, BCAM, CD74, LY6E, SLC2A1, CXCR4, DDR1, EFNB1, NOTCH3, PLXNB1, SPINT2, TNFRSF12A, and combinations thereof; The intravesicular protein biomarkers are selected from CRABP2, KLK7, MIF, PRAME, and S100A1, and combinations thereof; The intravesicular RNA biomarker is selected from CRABP2, MIF, CLDN6, PRAME, S100A1, KLK7, and combinations thereof; (c) Comparing sample information indicating the level of extracellular vesicles expressing the first target biomarker signature in the blood-derived sample with reference information including a first reference threshold level; (d) Classifying the subject as having ovarian cancer or being susceptible to it if the blood-derived sample shows an elevated level of extracellular vesicles expressing the first target biomarker signature compared to a classification cutoff based on the first reference threshold level. The method, including the method described above. (Item 2) The method according to item 1, wherein, when the at least one target biomarker is selected from one or more of the surface protein biomarkers, the selected surface protein biomarker(s) and the at least one extracellular vesicle-associated membrane-bound polypeptide biomarker are different. (Item 3) The method according to item 1 or 2, wherein steps (b) and (c) are repeated for at least a second target biomarker signature, wherein the classification cutoff is based on the first reference threshold level and at least a second reference threshold level corresponding to the at least second target biomarker signature. (Item 4) The method according to any one of items 1 to 3, wherein the extracellular vesicle-associated membrane-bound polypeptide biomarker is CLDN3, CLDN6, AQP5, CLDN16, EpCAM, FOLR1, LEMD1, LRRTM1, MUC16, CHODL, CDH6, HTR3A, SLC34A2, ALPL, BST2, CD24, MSLN, MUC1, PTGS1, ST14, sTn, TACSTD2, BCAM, CD74, LY6E, SLC2A1, CXCR4, DDR1, EFNB1, NOTCH3, PLXNB1, SPINT2, TNFRSF12A, and combinations thereof, or comprising them. (Item 5) The method according to any one of items 1 to 4, wherein the extracellular vesicle-associated membrane-bound polypeptide biomarker is or comprises SLC34A2 polypeptide, FOLR1 polypeptide, MUC16 polypeptide, CLDN3 polypeptide, CLDN6 polypeptide, ALPL polypeptide, BST2 polypeptide, MSLN polypeptide, MUC1 polypeptide, PTGS1 polypeptide, sTn glycosylated polypeptide, TACSTD2 polypeptide, EpCAM polypeptide, and / or LRRTM1 polypeptide. (Item 6) The method according to any one of items 1 to 5, wherein the first and / or second target biomarker signature comprises (i) an extracellular vesicle-associated membrane-bound polypeptide biomarker which is or contains an SCL34A2 polypeptide and / or a CLDN6 polypeptide; and (ii) at least one target biomarker MUC16. (Item 7) The method according to any one of items 1 to 5, wherein the first and / or second target biomarker signature comprises (i) an extracellular vesicle-associated membrane-bound polypeptide biomarker which is or contains the SCL34A2 polypeptide, and (ii) at least one target biomarker FOLR1. (Item 8) The method according to any one of items 1 to 5, wherein the first and / or second target biomarker signature comprises (i) an extracellular vesicle-associated membrane-bound polypeptide biomarker which is or contains the SCL34A2 polypeptide, and (ii) at least two target biomarkers which are or contain MUC16 and FOLR1. (Item 9) The method according to any one of items 1 to 5, wherein the first and / or second target biomarker signature comprises (i) an extracellular vesicle-associated membrane-bound polypeptide biomarker comprising or containing a MUC16 polypeptide, and (ii) at least one target biomarker MUC16. (Item 10) The method according to any one of items 1 to 5, wherein the first and / or second target biomarker signature comprises (i) an extracellular vesicle-associated membrane-bound polypeptide biomarker which is or contains the MUC16 polypeptide, and (ii) at least two target biomarkers which are or contain MUC16 and CLDN6. (Item 11) The method according to any one of items 1 to 5, wherein the first and / or second target biomarker signature comprises (i) a FOLR1 polypeptide or at least one extracellular vesicle-associated membrane-bound polypeptide biomarker comprising the same, and (ii) at least two target biomarkers which are FOLR1 and CLDN6. (Item 12) The method according to any one of items 1 to 5, wherein the first and / or second target biomarker signature comprises (i) a FOLR1 polypeptide or at least one extracellular vesicle-associated membrane-bound polypeptide biomarker containing the same, and (ii) at least two target biomarkers, SLC34A2 and CLDN3. (Item 13) The method according to any one of items 1 to 5, wherein the first and / or second target biomarker signature comprises (i) an extracellular vesicle-associated membrane-bound polypeptide biomarker which is or contains the MUC16 polypeptide, and (ii) at least two target biomarkers which are SLC34A2 and MUC16. (Item 14) The method according to any one of items 1 to 5, wherein the first and / or second target biomarker signature comprises (i) an extracellular vesicle-associated membrane-bound polypeptide biomarker which is or contains the MUC16 polypeptide, and (ii) at least two target biomarkers which are SLC34A2 and FOLR1. (Item 15) The method according to any one of items 1 to 5, wherein the first and / or second target biomarker signature comprises (i) an extracellular vesicle-associated membrane-bound polypeptide biomarker which is or contains a MUC16 polypeptide, and (ii) at least two target biomarkers which are FOLR1 and MUC16. (Item 16) The method according to any one of items 1 to 5, wherein the first and / or second target biomarker signature comprises (i) an extracellular vesicle-associated membrane-bound polypeptide biomarker which is or contains the MUC16 polypeptide, and (ii) at least two target biomarkers which are CLDN3 and MUC16. (Item 17) The first and / or second target biomarker signature is (i) a MUC16 polypeptide or at least one extracellular vesicle-associated membrane-bound polypeptide biomarker comprising the same, and (ii) at least two target b The method described in any one of items 1 to 5, including an iomarker. (Item 18) The method according to any one of items 1 to 5, wherein the first and / or second target biomarker signature comprises (i) a CLDN3 polypeptide or at least one extracellular vesicle-associated membrane-bound polypeptide biomarker comprising the same, and (ii) at least one target biomarker FOLR1. (Item 19) The method according to any one of items 1 to 5, wherein the first and / or second target biomarker signature comprises (i) an LRRTM1 polypeptide or at least one extracellular vesicle-associated membrane-bound polypeptide biomarker containing the same, and (ii) at least one target biomarker MUC16. (Item 20) The method according to any one of items 1 to 5, wherein the first and / or second target biomarker signature comprises (i) an ALPL polypeptide or at least one extracellular vesicle-associated membrane-bound polypeptide biomarker containing the same, and (ii) at least one target biomarker FOLR1. (Item 21) The method according to any one of items 1 to 5, wherein the first and / or second target biomarker signature comprises (i) a BST2 polypeptide or at least one extracellular vesicle-associated membrane-bound polypeptide biomarker containing the same, and (ii) at least one target biomarker MUC16. (Item 22) The method according to any one of items 1 to 5, wherein the first and / or second target biomarker signature comprises (i) a FOLR1 polypeptide or at least one extracellular vesicle-associated membrane-bound polypeptide biomarker containing the same, and (ii) at least one target biomarker MSLN. (Item 23) The method according to any one of items 1 to 5, wherein the first and / or second target biomarker signature comprises (i) a FOLR1 polypeptide or at least one extracellular vesicle-associated membrane-bound polypeptide biomarker containing the same, and (ii) at least one target biomarker MUC16. (Item 24) The method according to any one of items 1 to 5, wherein the first and / or second target biomarker signature comprises (i) an MSLN polypeptide or at least one extracellular vesicle-associated membrane-bound polypeptide biomarker containing the same, and (ii) at least one target biomarker MUC16. (Item 25) The method according to any one of items 1 to 5, wherein the first and / or second target biomarker signature comprises (i) an MSLN polypeptide or at least one extracellular vesicle-associated membrane-bound polypeptide biomarker containing the same, and (ii) at least one target biomarker MUC1. (Item 26) The method according to any one of items 1 to 5, wherein the first and / or second target biomarker signature comprises (i) a MUC1 polypeptide or at least one extracellular vesicle-associated membrane-bound polypeptide biomarker containing the same, and (ii) at least one target biomarker sTn glycosylated polypeptide. (Item 27) The first and / or second target biomarker signature comprises (i) a MUC1 polypeptide or at least one extracellular vesicle-associated membrane-bound polypeptide biomarker containing the same, and (ii) at least one target biomarker MUC16. The method described in any one of items 1 to 5. (Item 28) The method according to any one of items 1 to 5, wherein the first and / or second target biomarker signature comprises (i) a MUC1 polypeptide or at least one extracellular vesicle-associated membrane-bound polypeptide biomarker containing the same, and (ii) at least one target biomarker FOLR1. (Item 29) The method according to any one of items 1 to 5, wherein the first and / or second target biomarker signature comprises (i) a MUC16 polypeptide or at least one extracellular vesicle-associated membrane-bound polypeptide biomarker comprising the same, and (ii) at least one target biomarker sTn glycosylated polypeptide. (Item 30) The method according to any one of items 1 to 5, wherein the first and / or second target biomarker signature comprises (i) a PTGS1 polypeptide or at least one extracellular vesicle-associated membrane-bound polypeptide biomarker containing the same, and (ii) at least one target biomarker MUC16. (Item 31) The method according to any one of items 1 to 5, wherein the first and / or second target biomarker signature comprises (i) an extracellular vesicle-associated membrane-bound polypeptide biomarker which is or contains the SLC34A2 polypeptide, and (ii) at least one target biomarker MUC16. (Item 32) The method according to any one of items 1 to 5, wherein the first and / or second target biomarker signature comprises (i) an sTn glycosylated polypeptide or at least one extracellular vesicle-associated membrane-bound polypeptide biomarker comprising the same, and (ii) at least one target biomarker FOLR1. (Item 33) The method according to any one of items 1 to 5, wherein the first and / or second target biomarker signature comprises (i) an sTn glycosylated polypeptide or at least one extracellular vesicle-associated membrane-bound polypeptide biomarker comprising the same, and (ii) at least one target biomarker MSLN. (Item 34) The method according to any one of items 1 to 5, wherein the first and / or second target biomarker signature comprises (i) a TACSTD2 polypeptide or at least one extracellular vesicle-associated membrane-bound polypeptide biomarker containing the same, and (ii) at least one target biomarker MUC16. (Item 35) The method according to any one of items 1 to 5, wherein the first and / or second target biomarker signature comprises (i) a TACSTD2 polypeptide or at least one extracellular vesicle-associated membrane-bound polypeptide biomarker containing the same, and (ii) at least one target biomarker sTn glycosylated polypeptide. (Item 36) The method according to any one of items 1 to 5, wherein the first and / or second target biomarker signature comprises (i) a TACSTD2 polypeptide or at least one extracellular vesicle-associated membrane-bound polypeptide biomarker containing the same, and (ii) at least two target biomarkers which are MUC16 and sTn glycosylated polypeptides. (Item 37) The first and / or second target biomarker signature is (i) a TACSTD2 polypeptide or at least one extracellular vesicle-associated membrane-bound polypeptide containing it. The method according to any one of items 1 to 5, comprising (ii) a ptide biomarker and at least two target biomarkers which are MUC16 and MUC1. (Item 38) The method according to any one of items 1 to 5, wherein the first and / or second target biomarker signature comprises (i) a TACSTD2 polypeptide or at least one extracellular vesicle-associated membrane-bound polypeptide biomarker containing the same, and (ii) at least two target biomarkers, MUC16 and MSLN. (Item 39) The method according to any one of items 1 to 5, wherein the first and / or second target biomarker signature comprises (i) a TACSTD2 polypeptide or at least one extracellular vesicle-associated membrane-bound polypeptide biomarker containing the same, and (ii) at least two target biomarkers, MUC16 and FOLR1. (Item 40) The method according to any one of items 1 to 5, wherein the first and / or second target biomarker signature comprises (i) a TACSTD2 polypeptide or at least one extracellular vesicle-associated membrane-bound polypeptide biomarker containing the same, and (ii) at least two target biomarkers which are an sTn glycosylated polypeptide and MUC1. (Item 41) The method according to any one of items 1 to 5, wherein the first and / or second target biomarker signature comprises (i) a TACSTD2 polypeptide or at least one extracellular vesicle-associated membrane-bound polypeptide biomarker containing the same, and (ii) at least two target biomarkers which are sTn glycosylated polypeptide and MSLN. (Item 42) The method according to any one of items 1 to 5, wherein the first and / or second target biomarker signature comprises (i) a TACSTD2 polypeptide or at least one extracellular vesicle-associated membrane-bound polypeptide biomarker containing the same, and (ii) at least two target biomarkers which are an sTn glycosylated polypeptide and FOLR1. (Item 43) The method according to any one of items 1 to 5, wherein the first and / or second target biomarker signature comprises (i) a TACSTD2 polypeptide or at least one extracellular vesicle-associated membrane-bound polypeptide biomarker containing the same, and (ii) at least two target biomarkers, MUC1 and MSLN. (Item 44) The method according to any one of items 1 to 5, wherein the first and / or second target biomarker signature comprises (i) an extracellular vesicle-associated membrane-bound polypeptide biomarker which is or contains a MUC1 polypeptide, and (ii) at least two target biomarkers which are MUC16 and an sTn glycosylated polypeptide. (Item 45) The method according to any one of items 1 to 5, wherein the first and / or second target biomarker signature comprises (i) an extracellular vesicle-associated membrane-bound polypeptide biomarker which is or contains the MUC1 polypeptide, and (ii) at least two target biomarkers which are MUC16 and MSLN. (Item 46) The method according to any one of items 1 to 5, wherein the first and / or second target biomarker signature comprises (i) an extracellular vesicle-associated membrane-bound polypeptide biomarker which is or contains the MUC1 polypeptide, and (ii) at least two target biomarkers which are MUC16 and FOLR1. (Item 47) The method according to any one of items 1 to 5, wherein the first and / or second target biomarker signature comprises (i) an extracellular vesicle-associated membrane-bound polypeptide biomarker which is or contains a MUC1 polypeptide, and (ii) at least two target biomarkers which are an sTn glycosylated polypeptide and MSLN. (Item 48) The method according to any one of items 1 to 5, wherein the first and / or second target biomarker signature comprises (i) an extracellular vesicle-associated membrane-bound polypeptide biomarker which is or contains a MUC1 polypeptide, and (ii) at least two target biomarkers which are an sTn glycosylated polypeptide and FOLR1. (Item 49) The method according to any one of items 1 to 5, wherein the first and / or second target biomarker signature comprises (i) an extracellular vesicle-associated membrane-bound polypeptide biomarker which is or contains a MUC1 polypeptide, and (ii) at least two target biomarkers which are MSLN and FOLR1. (Item 50) The method according to any one of items 1 to 5, wherein the first and / or second target biomarker signature comprises (i) an extracellular vesicle-associated membrane-bound polypeptide biomarker which is or contains a MUC16 polypeptide, and (ii) at least two target biomarkers which are an sTn glycosylated polypeptide and MUC1. (Item 51) The method according to any one of items 1 to 5, wherein the first and / or second target biomarker signature comprises (i) an extracellular vesicle-associated membrane-bound polypeptide biomarker which is or contains a MUC16 polypeptide, and (ii) at least two target biomarkers which are an sTn glycosylated polypeptide and MSLN. (Item 52) The method according to any one of items 1 to 5, wherein the first and / or second target biomarker signature comprises (i) an extracellular vesicle-associated membrane-bound polypeptide biomarker which is or contains a MUC16 polypeptide, and (ii) at least two target biomarkers which are an sTn glycosylated polypeptide and FOLR1. (Item 53) The method according to any one of items 1 to 5, wherein the first and / or second target biomarker signature comprises (i) an extracellular vesicle-associated membrane-bound polypeptide biomarker which is or contains the MUC16 polypeptide, and (ii) at least two target biomarkers which are MUC1 and MSLN. (Item 54) The method according to any one of items 1 to 5, wherein the first and / or second target biomarker signature comprises (i) an extracellular vesicle-associated membrane-bound polypeptide biomarker which is or contains the MUC16 polypeptide, and (ii) at least two target biomarkers which are MSLN and FOLR1. (Item 55) The method according to any one of items 1 to 5, wherein the first and / or second target biomarker signature comprises (i) an sTn glycosylated polypeptide or at least one extracellular vesicle-associated membrane-bound polypeptide biomarker comprising the same, and (ii) at least two target biomarkers which are MUC16 and MUC1. (Item 56) The method according to any one of items 1 to 5, wherein the first and / or second target biomarker signature comprises (i) an sTn glycosylated polypeptide or at least one extracellular vesicle-associated membrane-bound polypeptide biomarker comprising the same, and (ii) at least two target biomarkers which are MUC16 and MSLN. (Item 57) The method according to any one of items 1 to 5, wherein the first and / or second target biomarker signature comprises (i) an sTn glycosylated polypeptide or at least one extracellular vesicle-associated membrane-bound polypeptide biomarker comprising the same, and (ii) at least two target biomarkers which are MUC16 and FOLR1. (Item 58) The method according to any one of items 1 to 5, wherein the first and / or second target biomarker signature comprises (i) an sTn glycosylated polypeptide or at least one extracellular vesicle-associated membrane-bound polypeptide biomarker comprising the same, and (ii) at least two target biomarkers which are MUC1 and MSLN. (Item 59) The method according to any one of items 1 to 5, wherein the first and / or second target biomarker signature comprises (i) an sTn glycosylated polypeptide or at least one extracellular vesicle-associated membrane-bound polypeptide biomarker comprising the same, and (ii) at least two target biomarkers which are MUC1 and FOLR1. (Item 60) The method according to any one of items 1 to 5, wherein the first and / or second target biomarker signature comprises (i) an sTn glycosylated polypeptide or at least one extracellular vesicle-associated membrane-bound polypeptide biomarker comprising the same, and (ii) at least two target biomarkers which are MSLN and FOLR1. (Item 61) The method according to any one of items 1 to 5, wherein the first and / or second target biomarker signature comprises (i) an MSLN polypeptide or at least one extracellular vesicle-associated membrane-bound polypeptide biomarker containing the same, and (ii) at least two target biomarkers which are MUC16 and sTn glycosylated polypeptides. (Item 62) The method according to any one of items 1 to 5, wherein the first and / or second target biomarker signature comprises (i) an MSLN polypeptide or at least one extracellular vesicle-associated membrane-bound polypeptide biomarker containing the same, and (ii) at least two target biomarkers which are MUC16 and MUC1. (Item 63) The method according to any one of items 1 to 5, wherein the first and / or second target biomarker signature comprises (i) an MSLN polypeptide or at least one extracellular vesicle-associated membrane-bound polypeptide biomarker containing the same, and (ii) at least two target biomarkers, MUC16 and FOLR1. (Item 64) The method according to any one of items 1 to 5, wherein the first and / or second target biomarker signature comprises (i) an MSLN polypeptide or at least one extracellular vesicle-associated membrane-bound polypeptide biomarker containing the same, and (ii) at least two target biomarkers which are an sTn glycosylated polypeptide and MUC1. (Item 65) The method according to any one of items 1 to 5, wherein the first and / or second target biomarker signature comprises (i) an extracellular vesicle-associated membrane-bound polypeptide biomarker which is or contains an MSLN polypeptide, and (ii) at least two target biomarkers which are an sTn glycosylated polypeptide and FOLR1. (Item 66) The method according to any one of items 1 to 5, wherein the first and / or second target biomarker signature comprises (i) an MSLN polypeptide or at least one extracellular vesicle-associated membrane-bound polypeptide biomarker containing the same, and (ii) at least two target biomarkers which are MUC1 and FOLR1. (Item 67) The method according to any one of items 1 to 5, wherein the first and / or second target biomarker signature comprises (i) an extracellular vesicle-associated membrane-bound polypeptide biomarker which is or contains the SLC34A2 polypeptide, and (ii) at least two target biomarkers which are MUC16 and MSLN. (Item 68) The method according to any one of items 1 to 5, wherein the first and / or second target biomarker signature comprises (i) an extracellular vesicle-associated membrane-bound polypeptide biomarker which is or contains an SCL34A2 polypeptide, and (ii) at least two target biomarkers which are an sTn glycosylated polypeptide and MUC16. (Item 69) The method according to any one of items 1 to 5, wherein the first and / or second target biomarker signature comprises (i) an extracellular vesicle-associated membrane-bound polypeptide biomarker which is or contains an SCL34A2 polypeptide, and (ii) at least two target biomarkers which are an sTn glycosylated polypeptide and FOLR1. (Item 70) The method according to any one of items 1 to 69, wherein the first and / or second reference threshold levels are determined by the level of extracellular vesicles expressing a target biomarker signature observed in comparable samples from a population of non-cancer subjects. (Item 71) The method according to item 70, wherein the aforementioned population of non-cancer subjects includes one or more of the following subject populations: healthy women, women diagnosed with benign tumors, and women having non-ovarian related diseases, disorders, and / or conditions. (Item 72) The method according to any one of items 1 to 71, wherein the blood-derived sample is subjected to size exclusion chromatography in order to isolate nanoparticles having a desired size range, including extracellular vesicles, (for example, directly from the blood-derived sample). (Item 73) The method according to any one of items 1 to 72, wherein the detection step includes a capture assay. (Item 74) The method according to item 73, wherein the capture assay comprises contacting the blood-derived sample with a capture factor comprising a target capture moiety that binds to at least one extracellular vesicle-associated membrane-bound polypeptide biomarker. (Item 75) The method according to item 74, wherein the capture factor is a solid substrate containing the conjugated target capture portion, or contains the same. (Item 76) The method according to item 75, wherein the solid substrate includes magnetic beads. (Item 77) The method according to any one of items 74 to 76, wherein the target capture portion is an antibody factor or includes one. (Item 78) The method according to any one of items 1 to 77, wherein the detection step includes a detection assay. (Item 79) The method according to any one of items 1 to 78, wherein the detection step comprises a capture assay and a detection assay, the capture assay being performed before the detection assay. (Item 80) The first and / or second target biomarker signatures are at least one vesicle The method according to any one of items 78-79, wherein the detection assay includes reverse transcription qPCR if an internal RNA biomarker is present. (Item 81) The method according to any one of items 78-80, wherein the first and / or second target biomarker signature comprises at least one intravesicular protein biomarker, the extracellular vesicle expressing the target biomarker signature is treated, including immobilization and / or permeabilization, prior to the detection assay. (Item 82) The method according to any one of items 78 to 81, wherein the first and / or second target biomarker signature comprises at least one surface protein biomarker and / or intravesicular protein biomarker, the detection assay comprises an immunoassay (e.g., immuno-PCR and / or proximity ligation assay). (Item 83) The method according to item 82, wherein the detection assay includes a proximity ligation assay. (Item 84) The proximity ligation assay, (a) A step of bringing an extracellular vesicle expressing the target biomarker signature ("extracellular vesicle expressing the target biomarker") expressing at least one extracellular vesicle-associated membrane-bound polypeptide biomarker to contact a set of detection probes each directed to the target biomarker of the target biomarker signature, wherein the set includes at least two detection probes, so that a combination is made including the extracellular vesicle and the set of detection probes, Each of the aforementioned detection probes is: (i) the target binding portion of the target biomarker signature that directs to the target biomarker; (ii) an oligonucleotide domain coupled to the target binding portion, the oligonucleotide domain comprising a double-stranded portion and a single-stranded overhang portion extending from one end of the oligonucleotide domain. Includes, The step is characterized in that the single-stranded overhang portion of the detection probe can hybridize with each other when the detection probe binds to the same extracellular vesicle, (b) The step of maintaining the combination under conditions that enable the set of detection probes to bind to their respective targets on the extracellular vesicles, such that the at least two detection probes can bind to the same extracellular vesicle expressing the target biomarker signature to form a double-stranded complex; (c) The step of contacting the double-stranded complex with a nucleic acid ligase to generate a ligated template; (d) The step of detecting the lygated template, wherein the presence of the lygated template indicates the presence of the target biomarker signature-expressing extracellular vesicles in the blood-derived sample; (e) Optionally, repeat steps a through d for at least one additional target biomarker signature. The method described in item 83, including the method described in item 83. (Item 85) The method according to item 84, wherein the target binding portions of the at least two detection probes each point towards the MUC16. (Item 86) The method according to item 84, wherein the target binding portions of the at least two detection probes each point towards FOLR1. (Item 87) The method according to item 84, wherein the target binding portions of the at least two detection probes each point towards the MSLN. (Item 88) The method according to item 84, wherein the target binding portions of the at least two detection probes each point towards ALPL. (Item 89) The method according to item 84, wherein the target binding portions of the at least two detection probes each point towards MUC1. (Item 90) The method according to item 84, wherein the target binding portions of the at least two detection probes each point towards an sTn glycosylated polypeptide. (Item 91) The method according to item 84, wherein the target binding portions of the at least two detection probes each point towards BST2. (Item 92) The method according to item 84, wherein the target binding portions of the at least two detection probes each point towards the PTGS1. (Item 93) The method according to item 84, wherein the target binding portions of the at least two detection probes each point towards the SLC34A2. (Item 94) The method according to item 84, wherein the target binding portions of the at least two detection probes each point towards TACSTD2. (Item 95) The method according to item 84, wherein the target binding portions of the at least two detection probes are directed towards MUC16 and FOLR1, respectively. (Item 96) The method according to item 84, wherein the target binding portions of the at least two detection probes are directed towards MUC16 and CLDN6, respectively. (Item 97) The method according to item 84, wherein the target binding portions of the at least two detection probes are directed towards FOLR1 and CLDN6, respectively. (Item 98) The method according to item 84, wherein the target binding portions of the at least two detection probes are each directed toward SLC34A2 and CLDN3. (Item 99) The method according to item 84, wherein the target binding portions of the at least two detection probes are each directed toward SLC34A2 and MUC16. (Item 100) The method according to item 84, wherein the target binding portions of the at least two detection probes are directed towards CLDN3 and MUC16, respectively. (Item 101) The method according to item 84, wherein the target binding portions of the at least two detection probes are directed towards CLDN3 and FOLR1, respectively. (Item 102) The method according to item 84, wherein the target binding portions of the at least two detection probes are each directed towards ALPL and FOLR1. (Item 103) The target binding portions of the at least two detection probes are BST2 and MU, respectively. The method described in item 84, which is directed towards C16. (Item 104) The method according to item 84, wherein the target binding portions of the at least two detection probes are directed towards FOLR1 and MSLN, respectively. (Item 105) The method according to item 84, wherein the target binding portions of the at least two detection probes are directed towards FOLR1 and MUC16, respectively. (Item 106) The method according to item 84, wherein the target binding portions of the at least two detection probes are directed towards the MSLN and MUC16, respectively. (Item 107) The method according to item 84, wherein the target binding portions of the at least two detection probes are directed towards the MSLN and the MUC1, respectively. (Item 108) The method according to item 84, wherein the target binding portions of the at least two detection probes each point toward an sTn glycosylated polypeptide and MUC1. (Item 109) The method according to item 84, wherein the target binding portions of the at least two detection probes are directed towards MUC1 and MUC16, respectively. (Item 110) The method according to item 84, wherein the target binding portions of the at least two detection probes are directed towards MUC1 and FOLR1, respectively. (Item 111) The method according to item 84, wherein the target binding portions of the at least two detection probes each point toward an sTn glycosylated polypeptide and MUC16. (Item 112) The method according to item 84, wherein the target binding portions of the at least two detection probes are directed towards PTGS1 and MUC16, respectively. (Item 113) The method according to item 84, wherein the target binding portions of the at least two detection probes are each directed towards SLC34A2 and FOLR1. (Item 114) The method according to item 84, wherein the target binding portions of the at least two detection probes each point toward an sTn glycosylated polypeptide and FOLR1. (Item 115) The method according to item 84, wherein the target binding portions of the at least two detection probes each point toward an sTn glycosylated polypeptide and an MSLN. (Item 116) The method according to item 84, wherein the target binding portions of the at least two detection probes are directed towards TACSTD2 and MUC16, respectively. (Item 117) The method according to item 84, wherein the target binding portions of the at least two detection probes each point toward an sTn glycosylated polypeptide and TACSTD2. (Item 118) The method according to any one of items 85 to 117, wherein the oligonucleotide domains of at least two of the detection probes are different. (Item 119) The method according to any one of items 77 to 118, wherein the target capture portion of the capture assay is at least one antibody factor that targets the SLC34A2 polypeptide, or comprises such antibody factor. (Item 120) The method according to any one of items 77 to 118, wherein the target capture portion of the capture assay is at least one antibody factor that targets the MUC16 polypeptide, or includes such antibody factor. (Item 121) The method according to any one of items 77 to 118, wherein the target capture portion of the capture assay is at least one antibody factor that targets the FOLR1 polypeptide, or includes such antibody factor. (Item 122) The method according to any one of items 77 to 118, wherein the target capture portion of the capture assay is at least one antibody factor that points to an MSLN polypeptide, or includes such antibody factor. (Item 123) The method according to any one of items 77 to 118, wherein the target capture portion of the capture assay is or comprises at least one antibody factor that directs to an sTn glycosylated polypeptide. (Item 124) The method according to any one of items 77 to 118, wherein the target capture portion of the capture assay is at least one antibody factor that targets the MUC1 polypeptide, or includes such antibody factor. (Item 125) The method according to any one of items 77 to 118, wherein the target capture portion of the capture assay is at least one antibody factor that points to the TACSTD2 polypeptide, or includes such antibody factor. (Item 126) The method according to any one of items 77 to 118, wherein the target capture portion of the capture assay is at least one antibody factor that points to the PTGS1 polypeptide, or includes such antibody factor. (Item 127) The method according to any one of items 77 to 118, wherein the target capture portion of the capture assay is at least one antibody factor that points to a BST2 polypeptide, or includes such antibody factor. (Item 128) The method according to any one of items 77 to 118, wherein the target capture portion of the capture assay is at least one antibody factor that points to an ALPL polypeptide, or includes such antibody factor. (Item 129) The method according to any one of items 77 to 118, wherein the target capture portion of the capture assay is at least one antibody factor that targets the LRRTM1 polypeptide, or includes such antibody factor. (Item 130) The method according to any one of items 77 to 118, wherein the target capture portion of the capture assay is at least one antibody factor that points to the CLDN3 polypeptide, or includes such antibody factor. (Item 131) The method described in any one of items 1 to 130, which is performed to screen for early-stage ovarian cancer, late-stage ovarian cancer, or recurrent ovarian cancer in the aforementioned subjects. (Item 132) The aforementioned subjects have been determined to have normal serum CA-125 levels, items 1-13. The method described in any one of item 1. (Item 133) The method according to any one of items 1 to 132, wherein the subject is determined to have a serum CA-125 level equivalent to or higher than that of a normal serum CA-125 level. (Item 134) The aforementioned subject has the following characteristics: (i) Asymptomatic women (e.g., adult women) who are susceptible to ovarian cancer (e.g., those with an average population risk (i.e., no genetic risk) or those with a genetic risk for ovarian cancer); (ii) Postmenopausal women; (iii) Women with a family history of breast and / or ovarian cancer (e.g., adult women) (e.g., women with one or more first-degree relatives with a history of breast and / or ovarian cancer (e.g., adult women)); (iv) Women (e.g., adult women) who have been determined to have one or more germline mutations in ATM, BRCA1, BRCA2, CDKN2A, MSH2, MLH1, MSH2, EPCAM, PALB2, STK11, TP53, BARD, CHEK2, MRE11A, RAD50, RAD51C, RAD51D, and combinations thereof; (v) Women (e.g., adult women) with breast cancer that has been determined to have germline mutations in BRCA1, BRCA2 and / or PALB2; (vi) For example, an elderly woman aged 65 or older; (vii) Women (e.g., adult women) having one or more nonspecific symptoms of ovarian cancer, and optionally, at least one of the nonspecific symptoms being similar to one or more symptoms of irritable bowel syndrome; and (viii) Women for whom periodic screening of CA-125 / transvaginal ultrasound (TVUS) is recommended (e.g., adult women); (ix) A woman (e.g., an adult woman) diagnosed with an adnexal mass that is confirmed by imaging; (x) Women with a genetic risk (e.g., adult women) before undergoing bilateral salpingo-oophorectomy to reduce risk; (xi) A woman with a benign gynecological tumor (e.g., an adult woman); (xii) Women who have previously been treated for ovarian cancer (e.g., adult women); and (xiii) Women with a lifestyle-related risk for ovarian cancer (e.g., adult women) The method described in any one of items 1 to 133, comprising at least one or more of the following. (Item 135) The following diagnostic assay: (i) Annual physical examinations of the subject(s) (e.g., including HPV and / or Pap smear screening for cervical cancer and mammogram screening for breast cancer); (ii) Serum CA-125 and / or TVUS screening test; (iii) Genetic assays for screening plasma for gene mutations in circulating tumor DNA and / or protein biomarkers associated with cancer; (iv) Assays including immunofluorescence staining to identify cellular phenotype and marker expression, followed by amplification and analysis by next-generation sequencing; and (v) BRCA1 and / or BRCA2 germline and somatic mutation assays, or assays including cell-free tumor DNA, liquid biopsy, serum protein and cell-free DNA, OVA1 and OVERA testing, and / or circulating tumor cells. The method described in any one of items 1 through 134, used in combination with one or more of the above. (Item 136) The method according to any one of items 1 to 135, wherein the ovarian cancer is high-grade serous ovarian cancer, endometrial ovarian cancer, clear cell ovarian cancer, low-grade serous ovarian cancer, or mucinous ovarian cancer. (Item 137) The method according to any one of items 1 to 136, wherein the ovarian cancer is high-grade serous ovarian carcinoma. (Item 138) The method described in item 137, wherein the aforementioned high-grade serous ovarian cancer is in an early stage. (Item 139) The method described in any one of items 1 to 138, performed to monitor ovarian cancer patients for response to treatment with anti-ovarian cancer therapies (e.g., olaparib, cisplatin, lucaparib, niraparib, talazoparib) and / or for cancer recurrence / metastasis. (Item 140) A kit for detecting ovarian cancer: (a) a capture factor containing a target capture moiety directed towards an extracellular vesicle-associated membrane-bound polypeptide biomarker; and (b) A set of detection probes comprising at least two detection probes each directed to a target biomarker of a targeted biomarker signature for ovarian cancer. Includes, At that time, the detection probes each: (i) the target binding portion of the target biomarker signature for ovarian cancer that directs to the target biomarker; and (ii) an oligonucleotide domain coupled to the target binding portion, the oligonucleotide domain comprising a double-stranded portion and a single-stranded overhang portion extending from one end of the oligonucleotide domain. Includes, The single-stranded overhang portions of the at least two detection probes are characterized in that they can hybridize with each other when the at least two detection probes are bound to the same extracellular vesicle; The aforementioned targeted biomarker signature for ovarian cancer is: At least one extracellular vesicle-associated membrane-bound polypeptide biomarker, At least one target biomarker selected from the group consisting of surface protein biomarkers, intravesicular protein biomarkers, and intravesicular RNA biomarkers, Includes, The surface protein biomarkers are selected from CLDN6, CLDN3, AQP5, CLDN16, EpCAM, FOLR1, LEMD1, LRRTM1, MUC16, CHODL, CDH6, HTR3A, SLC34A2, ALPL, BST2, CD24, MSLN, MUC1, PTGS1, ST14, sTn, TACSTD2, BCAM, CD74, LY6E, SLC2A1, CXCR4, DDR1, EFNB1, NOTCH3, PLXNB1, SPINT2, TNFRSF12A, and combinations thereof; The intravesicular protein biomarkers are selected from CRABP2, KLK7, MIF, PRAME, and S100A1, and combinations thereof; The kit wherein the intravesicular RNA biomarker is selected from CRABP2, MIF, CLDN6, PRAME, S100A1, KLK7, and combinations thereof. (Item 141) The kit according to item 140, wherein, when the at least one target biomarker is selected from one or more of the surface protein biomarkers, the selected surface protein biomarker(s) and the at least one extracellular vesicle-associated membrane-bound polypeptide biomarker are different. (Item 142) The extracellular vesicle-associated membrane-bound polypeptide biomarkers are CLDN3, CLDN6, AQP5, CLDN16, EpCAM, FOLR1, LEMD1, LRRTM1, MUC16, CHODL, CDH6, HTR3A, SLC34A2, ALPL, BST2, CD24, MSLN, MUC1, PTGS1, ST14, sTn, TACSTD2, BCAM, CD74, LY6E, SLC2A1, CXCR4, DDR1, EFNB1, NOTCH3, PLXNB1, SPINT2, TNFRSF12A, and combinations thereof, as described in item 140 or 141. (Item 143) The kit according to any one of items 47-49, wherein the extracellular vesicle-associated membrane-bound polypeptide biomarker is or comprises SLC34A2 polypeptide, MUC16 polypeptide, EpCAM polypeptide, FOLR1 polypeptide, CLDN3 polypeptide, CLDN6 polypeptide, ALPL polypeptide, BST2 polypeptide, MSLN polypeptide, MUC1 polypeptide, PTGS1 polypeptide, sTn glycosylated polypeptide, TACSTD2 polypeptide, and / or LRRTM1 polypeptide. (Item 144) The kit according to any one of items 140 to 143, wherein each of the target-binding portions of the at least two detection probes points to the same target biomarker of the target biomarker signature. (Item 145) The kit described in item 144, wherein the same target biomarker is MUC16 or contains it. (Item 146) The kit described in item 144, wherein the same target biomarker is FOLR1 or contains it. (Item 148) The same target biomarker as described above is MSLN, or a kit containing it, as described in item 144. (Item 149) The kit described in item 144, wherein the same target biomarker is ALPL or contains it. (Item 150) The kit described in item 144, wherein the same target biomarker is MUC1 or contains it. (Item 151) The kit according to item 144, wherein the same target biomarker is or contains an sTn glycosylated polypeptide. (Item 152) The kit described in item 144, wherein the same target biomarker as described above is BST2, or contains it. (Item 153) The kit described in item 144, wherein the same target biomarker is PTGS1 or contains it. (Item 154) The kit described in item 144, wherein the same target biomarker is SLC34A2, or contains it. (Item 155) The kit described in item 144, wherein the same target biomarker is TACSTD2 or contains it. (Item 156) The oligonucleotide domains of the at least two detection probes are different, item A kit as described in any one of items 140-155. (Item 157) The kit according to any one of items 140 to 143, wherein each of the target-binding portions of the at least two detection probes points to a separate target biomarker of the target biomarker signature. (Item 158) The kit according to any one of items 140 to 143, wherein the target binding portions of the at least two detection probes are each directed toward MUC16 and FOLR1. (Item 159) The kit according to any one of items 140 to 143, wherein the target binding portions of the at least two detection probes are each directed toward MUC16 and CLDN6. (Item 160) The kit according to any one of items 140 to 143, wherein the target binding portions of the at least two detection probes are each directed towards FOLR1 and CLDN6. (Item 161) The kit according to any one of items 140 to 143, wherein the target binding portions of at least two detection probes are each directed toward SLC34A2 and CLDN3. (Item 162) The kit according to any one of items 140 to 143, wherein the target binding portions of the at least two detection probes are each directed toward SLC34A2 and MUC16. (Item 163) The kit according to any one of items 140 to 143, wherein the target binding portions of the at least two detection probes are each directed toward CLDN3 and MUC16. (Item 164) The kit according to any one of items 140 to 143, wherein the target binding portions of the at least two detection probes are each directed towards CLDN3 and FOLR1. (Item 165) The kit according to any one of items 140 to 143, wherein the target binding portions of at least two detection probes are each directed towards ALPL and FOLR1. (Item 166) The kit according to any one of items 140 to 143, wherein the target binding portions of at least two detection probes are each directed towards BST2 and MUC16. (Item 167) The kit according to any one of items 140 to 143, wherein the target binding portions of the at least two detection probes are each directed toward FOLR1 and MSLN. (Item 168) The kit according to any one of items 140 to 143, wherein the target binding portions of the at least two detection probes are each directed toward FOLR1 and MUC16. (Item 169) The kit according to any one of items 140 to 143, wherein the target binding portions of the at least two detection probes are each directed toward MSLN and MUC16. (Item 170) The kit according to any one of items 140 to 143, wherein the target binding portions of at least two detection probes each point towards MSLN and MUC1. (Item 171) The kit according to any one of items 140 to 143, wherein the target binding portions of at least two detection probes each point toward an sTn glycosylated polypeptide and MUC1. (Item 172) The target binding portions of the at least two detection probes are, respectively, MUC1 and MU A kit oriented towards C16, as described in any one of items 140-143. (Item 173) The kit according to any one of items 140 to 143, wherein the target binding portions of the at least two detection probes are each directed toward MUC1 and FOLR1. (Item 174) The kit according to any one of items 140 to 143, wherein the target binding portions of at least two detection probes each point towards an sTn glycosylated polypeptide and MUC16. (Item 175) The kit according to any one of items 140 to 143, wherein the target binding portions of the at least two detection probes are each directed toward PTGS1 and MUC16. (Item 176) The kit according to any one of items 140 to 143, wherein the target binding portions of the at least two detection probes are each directed toward SLC34A2 and FOLR1. (Item 177) The kit according to any one of items 140 to 143, wherein the target binding portions of at least two detection probes each point toward an sTn glycosylated polypeptide and FOLR1. (Item 178) The kit according to any one of items 140 to 143, wherein the target binding portions of at least two detection probes each point toward an sTn glycosylated polypeptide and an MSLN. (Item 179) The kit according to any one of items 140 to 143, wherein the target binding portions of at least two detection probes are each directed towards TACSTD2 and MUC16. (Item 180) The kit according to any one of items 140 to 143, wherein the target binding portions of at least two detection probes each point toward an sTn glycosylated polypeptide and TACSTD2. (Item 181) The method according to any one of items 140 to 180, wherein the capture factor, which includes a target capture moiety directed towards an extracellular vesicle-associated membrane-bound polypeptide biomarker, includes at least one antibody factor directed towards the SLC34A2 polypeptide. (Item 182) The method according to any one of items 140 to 180, wherein the capture factor, which includes a target capture moiety directed towards an extracellular vesicle-associated membrane-bound polypeptide biomarker, includes at least one antibody factor directed towards the MUC16 polypeptide. (Item 183) The method according to any one of items 140 to 180, wherein the capture factor, which includes a target capture moiety directed towards an extracellular vesicle-associated membrane-bound polypeptide biomarker, includes at least one antibody factor directed towards the FOLR1 polypeptide. (Item 184) The method according to any one of items 140 to 180, wherein the capture factor, which includes a target capture moiety directed towards an extracellular vesicle-associated membrane-bound polypeptide biomarker, includes at least one antibody factor directed towards an MSLN polypeptide. (Item 185) The method according to any one of items 140 to 180, wherein the capture factor, which includes a target capture moiety directed towards an extracellular vesicle-associated membrane-bound polypeptide biomarker, includes at least one antibody factor directed towards an sTn glycosylated polypeptide. (Item 186) The method according to any one of items 140 to 180, wherein the capture factor, which includes a target capture moiety directed towards an extracellular vesicle-associated membrane-bound polypeptide biomarker, includes at least one antibody factor directed towards a MUC1 polypeptide. (Item 187) The method according to any one of items 140 to 180, wherein the capture factor, which includes a target capture portion directed to an extracellular vesicle-associated membrane-bound polypeptide biomarker, includes at least one antibody factor directed to the TACSTD2 polypeptide. (Item 188) The method according to any one of items 140 to 180, wherein the capture factor, which includes a target capture moiety directed towards an extracellular vesicle-associated membrane-bound polypeptide biomarker, includes at least one antibody factor directed towards the PTGS1 polypeptide. (Item 189) The method according to any one of items 140 to 180, wherein the capture factor, which includes a target capture moiety directed towards an extracellular vesicle-associated membrane-bound polypeptide biomarker, includes at least one antibody factor directed towards a BST2 polypeptide. (Item 190) The method according to any one of items 140 to 180, wherein the capture factor, which includes a target capture moiety directed towards an extracellular vesicle-associated membrane-bound polypeptide biomarker, includes at least one antibody factor directed towards an ALPL polypeptide. (Item 191) The method according to any one of items 140 to 180, wherein the capture factor, which includes a target capture moiety directed to an extracellular vesicle-associated membrane-bound polypeptide biomarker, includes at least one antibody factor directed to the LRRTM1 polypeptide. (Item 192) The method according to any one of items 140 to 180, wherein the capture factor, which includes a target capture moiety directed to an extracellular vesicle-associated membrane-bound polypeptide biomarker, includes at least one antibody factor directed to a CLDN3 polypeptide. (Item 193) A kit as described in any one of items 140-192, further comprising at least one additional reagent (e.g., ligase, immobilizer, and / or permeabilizer). (Item 194) (a) A first capture factor containing a target capture moiety directed towards the SLC34A2 polypeptide; (b) A second capture factor containing a target capture moiety that targets the MUC16 polypeptide; (c) At least three sets of detection probes This includes, in which case the detection probes each: (i) Target binding sites that direct target surface protein biomarkers; and (ii) an oligonucleotide domain coupled to the target binding portion, the oligonucleotide domain comprising a double-stranded portion and a single-stranded overhang portion extending from one end of the oligonucleotide domain. Includes, The single-stranded overhang portions of the at least two detection probes are characterized in that they can hybridize with each other when the at least two detection probes bind to the same extracellular vesicle; At that time, At least two detection probes of the first set are directed towards the MUC16 target surface protein, respectively; At least two detection probes of the second set are directed towards the FOLR1 target surface protein, and At least two detection probes in the third set are directed towards the MUC16 polypeptide and the FOLR1 polypeptide, respectively. A kit as described in either item 140-146 or item 157-161. (Item 195) (a) A first capture factor including a target capture portion; (b) A second capture factor including a target capture portion; (c) at least two sets of detection probes This includes, in which case the detection probes each: (i) Target binding sites that direct target surface protein biomarkers; and (ii) an oligonucleotide domain coupled to the target binding portion, the oligonucleotide domain comprising a double-stranded portion and a single-stranded overhang portion extending from one end of the oligonucleotide domain. Includes, The kit according to any one of items 140 to 193, characterized in that the single-stranded overhang portions of the at least two detection probes can hybridize with each other when the at least two detection probes bind to the same extracellular vesicle. (Item 196) (a) A first capture factor including a target capture portion; (b) A second capture factor including a target capture portion; (c) A third capture factor including a target capture portion; (d) at least three sets of detection probes This includes, in which case the detection probes each: (i) Target binding sites that direct target surface protein biomarkers; and (ii) an oligonucleotide domain coupled to the target binding portion, the oligonucleotide domain comprising a double-stranded portion and a single-stranded overhang portion extending from one end of the oligonucleotide domain. Includes, The kit according to any one of items 140 to 193, characterized in that the single-stranded overhang portions of the at least two detection probes can hybridize with each other when the at least two detection probes bind to the same extracellular vesicle. (Item 197) It is a complex: (a) Extracellular vesicles expressing a target biomarker signature for ovarian cancer: At least one extracellular vesicle-associated membrane-bound polypeptide biomarker and It includes at least one target biomarker selected from the group consisting of surface protein biomarkers, intravesicular protein biomarkers, and intravesicular RNA biomarkers, in which case, The surface protein biomarkers are selected from CLDN3, CLDN6, AQP5, CLDN16, EpCAM, FOLR1, LEMD1, LRRTM1, MUC16, CHODL, CDH6, HTR3A, SLC34A2, ALPL, BST2, CD24, MSLN, MUC1, PTGS1, ST14, sTn, TACSTD2, BCAM, CD74, LY6E, SLC2A1, CXCR4, DDR1, EFNB1, NOTCH3, PLXNB1, SPINT2, TNFRSF12A, and combinations thereof; The intravesicular protein biomarkers are selected from CRABP2, KLK7, MIF, PRAME, and S100A1, and combinations thereof; The intravesicular RNA biomarkers are selected from CRABP2, MIF, CLDN6, PRAME, S100A1, KLK7, and combinations thereof; The extracellular vesicles are immobilized on a solid substrate containing a target capture portion that directs the extracellular vesicle-associated membrane-bound polypeptide; (b) A first detection probe and a second detection probe, wherein each detection probe is (i) A target binding portion of the tumor target biomarker signature that directs to one of the target biomarkers; and (ii) an oligonucleotide domain coupled to the target binding portion, the oligonucleotide domain comprising a double-stranded portion and a single-stranded overhang portion extending from one end of the oligonucleotide domain. Includes, The complex comprises the first detection probe and the second detection probe, each bound to the extracellular vesicle, wherein the single-stranded overhang portions of the first and second detection probes are hybridized with each other. (Item 198) The complex according to item 197, wherein, when the at least one target biomarker is selected from one or more of the surface protein biomarkers, the selected surface protein biomarker(s) and the at least one extracellular vesicle-associated membrane-bound protein biomarker are different. (Item 199) The complex described in item 196 or 197, wherein the extracellular vesicle-associated membrane-bound polypeptide biomarker is CLDN3, CLDN6, AQP5, CLDN16, EpCAM, FOLR1, LEMD1, LRRTM1, MUC16, CHODL, CDH6, HTR3A, SLC34A2, ALPL, BST2, CD24, MSLN, MUC1, PTGS1, ST14, sTn, TACSTD2, BCAM, CD74, LY6E, SLC2A1, CXCR4, DDR1, EFNB1, NOTCH3, PLXNB1, SPINT2, TNFRSF12A, and combinations thereof. (Item 200) The complex according to any one of items 197-199, wherein the extracellular vesicle-associated membrane-bound polypeptide biomarker is or comprises SLC34A2 polypeptide, FOLR1 polypeptide, MUC16 polypeptide, EpCAM polypeptide, CLDN3 polypeptide, CLDN6 polypeptide, ALPL polypeptide, BST2 polypeptide, MSLN polypeptide, MUC1 polypeptide, PTGS1 polypeptide, sTn glycosylated polypeptide, TACSTD2 polypeptide, and / or LRRTM1 polypeptide. (Item 201) The complex according to any one of items 197 to 200, wherein the target binding portions of at least two detection probes each point to the same target biomarker of the target biomarker signature. (Item 202) The complex described in item 201, wherein the same target biomarker is MUC16 or contains it. (Item 203) The complex described in item 201, wherein the same target biomarker is FOLR1 or contains it. (Item 204) The complex described in item 201, wherein the same target biomarker is MSLN or contains it. (Item 205) The complex described in item 201, wherein the same target biomarker is ALPL or contains it. (Item 206) The same target biomarker as described above is MUC1, or contains it, as described in item 201. A composite structure. (Item 207) The complex described in item 201, wherein the same target biomarker is or comprises an sTn glycosylated polypeptide. (Item 208) The complex described in item 201, wherein the same target biomarker is BST2 or contains it. (Item 209) The complex described in item 201, wherein the same target biomarker is PTGS1 or contains it. (Item 210) The complex described in item 201, wherein the same target biomarker is SLC34A2 or contains it. (Item 211) The complex described in item 201, wherein the same target biomarker is TACSTD2 or contains it. (Item 212) The complex according to any one of items 201 to 211, wherein the oligonucleotide domains of at least two of the detection probes are different. (Item 213) The complex according to any one of items 197 to 200, wherein each of the target-binding portions of the at least two detection probes points to a separate target biomarker of the target biomarker signature. (Item 214) The complex according to item 213, wherein the target binding portions of the at least two detection probes are directed towards MUC16 and FOLR1, respectively. (Item 215) The complex according to item 213, wherein the target binding portions of the at least two detection probes are directed towards MUC16 and CLDN6, respectively. (Item 216) The complex according to item 213, wherein the target binding portions of the at least two detection probes are each directed toward FOLR1 and CLDN6. (Item 217) The composite according to item 213, wherein the target binding portions of the at least two detection probes are each directed toward SLC34A2 and CLDN3. (Item 218) The composite according to item 213, wherein the target binding portions of the at least two detection probes are each directed toward SLC34A2 and MUC16. (Item 219) The complex according to item 213, wherein the target binding portions of the at least two detection probes are each directed toward CLDN3 and MUC16. (Item 220) The complex according to item 213, wherein the target binding portions of the at least two detection probes are each directed toward CLDN3 and FOLR1. (Item 221) The complex according to item 213, wherein the target binding portions of the at least two detection probes are each directed toward ALPL and FOLR1. (Item 222) The complex according to item 213, wherein the target binding portions of the at least two detection probes are each directed toward BST2 and MUC16. (Item 223) The complex according to item 213, wherein the target binding portions of the at least two detection probes are directed towards FOLR1 and MSLN, respectively. (Item 224) The complex according to item 213, wherein the target binding portions of the at least two detection probes are directed towards FOLR1 and MUC16, respectively. (Item 225) The complex according to item 213, wherein the target binding portions of the at least two detection probes are each directed toward MSLN and MUC16. (Item 226) The complex according to item 213, wherein the target binding portions of the at least two detection probes are directed toward MSLN and MUC1, respectively. (Item 227) The complex according to item 213, wherein the target binding portions of at least two detection probes each point toward an sTn glycosylated polypeptide and MUC1. (Item 228) The complex according to item 213, wherein the target binding portions of the at least two detection probes are each directed toward MUC1 and MUC16. (Item 229) The complex according to item 213, wherein the target binding portions of the at least two detection probes each point towards MUC1 and FOLR1. (Item 230) The complex according to item 213, wherein the target binding portions of at least two detection probes each point toward an sTn glycosylated polypeptide and MUC16. (Item 231) The complex according to item 213, wherein the target binding portions of the at least two detection probes are directed towards PTGS1 and MUC16, respectively. (Item 232) The composite according to item 213, wherein the target binding portions of the at least two detection probes are directed towards SLC34A2 and FOLR1, respectively. (Item 233) The complex according to item 213, wherein the target binding portions of at least two detection probes each point toward an sTn glycosylated polypeptide and FOLR1. (Item 234) The complex according to item 213, wherein the target binding portions of at least two detection probes each point toward an sTn glycosylated polypeptide and an MSLN. (Item 235) The complex according to item 213, wherein the target binding portions of the at least two detection probes are each directed toward TACSTD2 and MUC16. (Item 236) The complex according to item 213, wherein the target binding portions of at least two detection probes each point toward an sTn glycosylated polypeptide and TACSTD2. (Item 237) The composite according to any one of items 197 to 236, wherein the solid substrate comprises magnetic beads. (Item 238) The complex according to any one of items 197 to 236, wherein the target capture portion is an antibody factor or contains one. [Brief explanation of the drawing]

[0071] [Figure 1] This diagram illustrates an exemplary workflow for profiling individual extracellular vesicles (EVs). The diagram shows the purification of EVs from plasma using size exclusion chromatography (SEC) and immunoaffinity capture of EVs that present specific membrane-bound protein markers (Panel A); and the detection of target markers (e.g., intravesicular proteins or surface proteins) co-localized on the captured EVs using target entity detection assays according to some embodiments described herein (Panel B).

[0072] [Figure 2] This is a schematic diagram illustrating a target entity detection assay according to some embodiments described herein. In some embodiments, a target entity detection assay is shown that uses a combination of detection probes that are specific to the detection of cancer. In some embodiments, a dual system comprising a first detection probe for target protein 1 (e.g., cancer marker 1) and a second detection probe for target protein 2 (e.g., cancer marker 2) is added to a sample containing a biological entity (e.g., an extracellular vesicle). In some embodiments, each detection probe comprises a target-binding portion (e.g., an antibody factor against the target protein) coupled to an oligonucleotide domain that includes a double-stranded portion and a single-stranded overhang extending from one end of its oligonucleotide domain. A detection signal is generated when the distinct target-binding portions of the first and second detection probes (e.g., antibody factors against target protein 1 and target protein 2, respectively) are localized in close proximity to the same biological entity (e.g., an extracellular vesicle) and the corresponding single-stranded overhangs hybridize with each other, thus allowing ligation of their oligonucleotide domains to occur. For example, a control entity (e.g., a biological entity from a healthy control sample) does not express either or both of target protein 1 (e.g., cancer marker 1) and target protein 2 (e.g., cancer marker 2), and therefore no signal can be detected. However, if a biological entity from a cancer sample (e.g., ovarian cancer) expresses target protein 1 and target protein 2, and these target proteins are located within a sufficiently short distance of each other in the same biological entity (e.g., an extracellular vesicle), a detection signal will occur.

[0073] [Figure 3]For example, Figure 1 or Figure 2 shows experimental data from qPCR detection of ligated samples in extracellular vesicle samples from various cell lines using the exemplary assays. In some embodiments, the target entity detection assay includes an action factor ("SLC34A2 capture") and an exemplary dual system for capturing extracellular vesicles based on the SLC34A2 marker, which includes, for example, at least two detection probes ("MUC16 + MUC16 antibody probe"), each containing a MUC16 binding moiety (e.g., an anti-MUC16 antibody) coupled to a separate oligonucleotide domain, each containing a double-stranded portion and a single-stranded overhang extending from one end of its oligonucleotide domain. Panel A shows a graph of qPCR data comparing the detection of ovarian cancer cell line EVs (positive cell lines) to non-ovarian cancer cell line EVs (negative cell lines). Panel B shows the corresponding mean delta Ct values, using a negative control cell line (e.g., a non-ovarian cancer cell line) as the baseline.

[0074] [Figure 4A] This is a set of graphs showing the demographics of patients included in the ovarian cystadenocarcinoma (OC) patient plasma sample study. (Panel A) Summary of age and cohort size in the female patient cohort as assessed by exemplary assays. [Figure 4B] This is a set of graphs showing the demographics of patients included in the study of plasma samples from patients with ovarian cystadenocarcinoma (OC). (Panel B) Summary of age and cohort size in female plasma samples from patients with benign tumors.

[0075] [Figure 5] This is a set of graphs showing the correlation between CA-125 levels and patient age in samples from ovarian cancer patients (Panel A) and patients with benign tumors (Panel B).

[0076] [Figure 6]This is a pie chart showing the prevalence of ovarian cancer by major ovarian carcinoma subtypes. "Other" refers to mixed or transitional cancers that cannot be classified into a single subtype. For example, see Gilks ​​et al., 2008, and Seidman et al., 2003, 2004, which are incorporated herein by reference in their entirety, for the purposes described herein and for additional information.

[0077] [Figure 7A] This is a set of graphs illustrating the performance of exemplary assays for detecting ovarian cancer, including a dual system (e.g., as shown in Figure 1 or 2) based on SLC34A2 capture and MUC16+MUC16 antibody probes. Panel A represents integrated data from various ovarian cancer subtypes. [Figure 7B] This is a set of graphs showing the performance of exemplary assays for detecting ovarian cancer, including a dual system (e.g., as shown in Figure 1 or 2) based on SLC34A2 capture and a MUC16+MUC16 antibody probe. Panel B shows excellent detection of high-grade serous ovarian cancer, the most common ovarian subtype, at two different cutoffs. Cutoff 1 is for 99.8% specificity, and cutoff 2 is for 98% specificity. Corresponding sensitivity for the noted ovarian cancer stage is shown at the specified cutoff.

[0078] [Figure 8] This graph shows the performance of an exemplary assay for detecting endometrial ovarian cancer, including a dual system (e.g., as shown in Figure 1 or 2) based on SLC34A2 capture and a MUC16+MUC16 antibody probe. Excellent detection of endometrial ovarian cancer, the second most common ovarian subtype, is shown at two different cutoffs. Cutoff 1 is for 99.8% specificity, and cutoff 2 is for 98% specificity.

[0079] [Figure 9]Graph showing the performance of an exemplary assay for detecting low-grade serous ovarian cancer, including a dual system based on SLC34A2 capture and MUC16+MUC16 antibody probe (e.g., as described in FIG. 1), at two different cutoffs. Cutoff 1 is for 99.8% specificity and cutoff 2 is for 98% specificity.

[0080] [Figure 10] Graph showing the performance of an exemplary assay for detecting clear cell ovarian cancer, including a dual system based on SLC34A2 capture and MUC16+MUC16 antibody probe (e.g., as described in FIG. 1 or 2), at two different cutoffs. Cutoff 1 is for 99.8% specificity and cutoff 2 is for 98% specificity.

[0081] [Figure 11] Graph showing the performance of an exemplary assay for detecting mucinous ovarian cancer, including a dual system based on SLC34A2 capture and MUC16+MUC16 antibody probe (e.g., as described in FIG. 1 or 2), at two different cutoffs. Cutoff 1 is for 99.8% specificity and cutoff 2 is for 98% specificity.

[0082] [Figure 12A] The readout of an exemplary assay for detecting ovarian cancer subtypes, including a dual system based on SLC34A2 capture and MUC16+MUC16 antibody probe (e.g., as described in FIG. 1 or 2), is shown against serum CA-125 levels. Panel A shows that no correlation is observed between the assay signal and serum CA-125 levels. Cutoff 1 was derived by fitting a log-normal distribution to the Ct values (obtained by the exemplary assay) in a population of healthy control patients and subtracting the mean of that distribution and 2.879 standard deviations, above which 99.8% of the Ct values of all healthy patients would lie. [Figure 12B]The readouts of an exemplary assay for detecting ovarian cancer subtypes, including a dual system based on SLC34A2 capture and MUC16+MUC16 antibody probes (e.g., as described in FIGS. 1 or 2), are shown against serum CA-125 levels. Panel B is a receiver operating characteristic (ROC) curve for discriminating patients with ovarian cancer from patients with benign gynecological tumors using Ct values determined from the exemplary assay shown in Panel A versus serum CA-125 values shown in Panel A (the patient cohort is described in FIG. 4A). Benign gynecological tumors include, for example, endometroid cysts, follicular cysts, mucinous cystadenomas, mature teratomas, leiomyomas, and serous cystadenomas. Further, several subtypes of ovarian cancer, including high-grade serous, low-grade serous, mucinous, endometroid, and clear cell, were evaluated.

[0083] [Figure 13] A set of data showing the performance of an exemplary assay for detecting stage I and II high-grade serous ovarian cancer (HGSOC) compared to the current standard of care: serum CA-125 and transvaginal ultrasound (TVUS). Specificity (Panels A and D), sensitivity (Panels B and E), and positive predictive value (Panels C and F) were compared for screening women with genetic risk (Panels A, B, and C), and average risk (Panels D, E, and F) for HGSOC. In some cases, the disease prevalence in women with genetic and average risk was 1% and 0.057%, respectively. The performance parameters of serum CA-125 and TVUS were obtained from Buys et al., 2011, which is incorporated herein by reference for the purposes described herein.

[0084] [Figure 14A] A set of graphs showing the detection of MIF mRNA in EVs from ovarian cancer cell lines versus negative control cell lines. (Panel A) Detection of MIF mRNA in bulk EVs using RT-qPCR. [Figure 14B]This is a set of graphs showing the detection of MIF mRNA in ovarian cancer cell lines versus EVs from negative control cell lines. (Panel B) Detection of MIF mRNA in EVs captured using anti-EpCAM functionalized beads compared to EVs in bulk.

[0085] [Figure 15] This is a schematic diagram illustrating a target entity detection assay according to some embodiments described herein. The diagram shows an exemplary triple target entity detection system, in which, in some embodiments, three or more detection probes for each target protein can be added to a sample containing a biological entity (e.g., an extracellular vesicle). In some embodiments, each detection probe includes a target binding portion (e.g., an antibody factor against the target protein) coupled to an oligonucleotide domain, which includes a double-stranded portion and a single-stranded overhang extending from one end of the oligonucleotide domain. A detection signal is generated when the corresponding single-stranded overhangs of all three or more detection probes hybridize to form a linear double-stranded complex, and ligation occurs of at least one strand of the double-stranded complex, making it possible to detect the resulting ligated product.

[0086] [Figure 16] This is a non-limiting example of a double-stranded complex containing four detection probes interconnected in a linear arrangement via hybridization of their respective single-stranded overhangs.

[0087] [Figure 17]This is a schematic diagram illustrating a target entity detection assay of an exemplary embodiment described herein. In some embodiments, multiple detection probes for distinct targets are added to a sample containing a biological entity (e.g., an extracellular vesicle). In some embodiments, each detection probe includes a target-binding moiety (e.g., an antibody factor) coupled to an oligonucleotide domain that includes a double-stranded portion and a single-stranded overhang extending from one end of its oligonucleotide domain. A detection signal is generated when all detection probes localize in close proximity to the same biological entity (e.g., an extracellular vesicle or analyte), the corresponding single-stranded overhangs hybridize to form a linear double-stranded complex, and ligation occurs of at least one strand of the resulting double-stranded complex, thereby making it possible to detect the ligated product.

[0088] [Figure 18A] Transcript expression in 442 ovarian cancer samples (stages I / II and III / IV) compared to a total of 17,382 healthy tissue samples is illustrated for four exemplary surface protein biomarkers, including (Panel A) SLC34A2, (Panel B) MUC16, (Panel C) FOLR1, and (Panel D) CLDN6. [Figure 18B] Transcript expression in 442 ovarian cancer samples (stages I / II and III / IV) compared to a total of 17,382 healthy tissue samples is illustrated for four exemplary surface protein biomarkers, including (Panel A) SLC34A2, (Panel B) MUC16, (Panel C) FOLR1, and (Panel D) CLDN6. [Figure 18C] Transcript expression in 442 ovarian cancer samples (stages I / II and III / IV) compared to a total of 17,382 healthy tissue samples is illustrated for four exemplary surface protein biomarkers, including (Panel A) SLC34A2, (Panel B) MUC16, (Panel C) FOLR1, and (Panel D) CLDN6. [Figure 18D]Transcript expression in 442 ovarian cancer samples (stages I / II and III / IV) compared to a total of 17,382 healthy tissue samples is illustrated for four exemplary surface protein biomarkers, including (Panel A) SLC34A2, (Panel B) MUC16, (Panel C) FOLR1, and (Panel D) CLDN6.

[0089] [Figure 19A] The performance of two exemplary orthogonal biomarker combinations is illustrated. When the transcript expression cutoff noted in Figure 18 was applied to (Panel A) SLC34A2+MUC16, 71% of ovarian cancer samples were identified from over 99.9% of healthy tissue samples. [Figure 19B] The performance of two exemplary orthogonal biomarker combinations is illustrated. When the transcript expression cutoff noted in Figure 18 was applied to (Panel B)FOLR1+CLDN6, it distinguished 75% of ovarian cancer samples from over 99.9% of healthy tissue samples, respectively. [Figure 19C] (Panel C) is a Venn diagram showing the percentage (91%) of ovarian cancer patients identified above the cutoff when both biomarker combinations shown in Panels A and B were used to characterize cancer patient samples. This indicates that using combinations of two or more biomarkers may increase the sensitivity of ovarian cancer detection assays (e.g., as described herein).

[0090] [Figure 20] The results of precedent biomarker combinations are illustrated. (Panel A) Results from precedent biomarker combination screening (112 combinations were screened) in pooled healthy plasma and pooled ovarian cancer plasma samples are illustrated. Each data point represents a unique biomarker combination, indicated by a red data point shown in Panel B. (Panel B) Differences in assay signals between pooled healthy plasma and pooled ovarian cancer plasma for seven exemplary biomarker combinations.

[0091] [Figure 21] The use of multiple orthogonal biomarker combinations and related improvements in assay sensitivity are illustrated. Combination 1 (SLC34A2 capture, MUC16 + MUC16 pliq - PCR detection probe readout) and Combination 2 (SLC34A2 capture, FOLR1 + FOLR1 pliq - PCR detection probe readout) can each distinguish an ovarian cancer population from healthy controls and a benign tumor cohort. Both cut - offs are set to achieve 99.5% specificity.

[0092] [Figure 22] The performance of the exemplary assays described herein using individual exemplary biomarker combinations to distinguish control subjects (e.g., healthy female subjects, and / or subjects with benign gynecological tumors and / or subjects with inflammatory conditions including, for example, Crohn's disease, ulcerative colitis, endometriosis, etc.) from ovarian cancer patients is illustrated. Exemplary individual biomarker combinations include the following:

Table A

[0093] [Figure 23]The performance of the exemplary assay described herein using exemplary biomarker combinations (e.g., a set of a capture factor directed to SLC34A2 and at least two detection probes directed to MUC16, respectively) is illustrated. The cutoff value was determined by selecting the less restrictive of either (i) a standard deviation of 2.93 away from the mean of healthy control subjects and subjects with inflammatory conditions (e.g., to exclude 99.83% of healthy subjects in the distribution) or (ii) the maximum assay signal from healthy control subjects. In some embodiments, benign ovarian tumor samples may be of less concern regarding off-target signals than healthy control subjects and / or subjects with inflammatory conditions (e.g., Crohn's disease, ulcerative colitis, endometriosis). Therefore, in some such embodiments, benign ovarian tumor samples may not be included in determining the cutoff value.

[0094] [Figure 24] The performance of the exemplary assay described herein using exemplary biomarker combinations (e.g., a capture factor targeting SLC34A2 and a set of at least one first detection probe targeting FOLR1 and a second detection probe targeting FOLR1) is illustrated. The cutoff values ​​were determined as shown in Figure 23.

[0095] [Figure 25] The performance of the exemplary assay described herein using exemplary biomarker combinations (e.g., a set of a capture factor targeting SLC34A2 and at least a first detection probe targeting MUC16 and a second detection probe targeting FOLR1) is illustrated. The cutoff values ​​were determined as shown in Figure 23.

[0096] [Figure 26]The performance of the exemplary assay described herein using exemplary biomarker combinations (e.g., a capture factor targeting MUC16 and a set of at least a first detection probe and a second detection probe targeting MUC16) is illustrated. The cutoff values ​​were determined as shown in Figure 23.

[0097] [Figure 27] The performance of the exemplary assay described herein using exemplary biomarker combinations (e.g., a capture factor targeting MUC16 and a set of at least one detection probe targeting MUC16 and a second detection probe targeting FOLR1) is illustrated. The cutoff values ​​were determined as shown in Figure 23.

[0098] [Figure 28] The performance of the exemplary assay described herein using exemplary biomarker combinations (e.g., a capture factor targeting MUC16 and a set of at least a first detection probe targeting FOLR1 and a second detection probe targeting FOLR1) is illustrated. The cutoff values ​​were determined as shown in Figure 23.

[0099] [Figure 29] The performance of exemplary assays described herein using each exemplary biomarker combination is illustrated: (Panel A) a set of a capture factor directed to SLC34A2 and at least a first detection probe directed to MUC16 and a second detection probe directed to MUC16; (Panel B) a set of a capture factor directed to SLC34A2 and at least a first detection probe directed to FOLR1 and a second detection probe directed to FOLR1; and (Panel C) a set of a capture factor directed to MUC16 and at least a first detection probe directed to MUC16 and a second detection probe directed to FOLR1.

[0100] [Figure 30]An exemplary assay using exemplary biomarker combinations (e.g., a capture factor targeting MUC16 and a set of at least one first detection probe targeting MUC16 and a second detection probe targeting FOLR1) is shown to be able to detect ovarian cancer patients with normal serum CA-125 (e.g., <35 U / mL) and to differentiate many non-ovarian cancer patients (e.g., patients with benign gynecological tumors) with elevated serum CA-125 from ovarian cancer patients.

[0101] [Figure 31] An exemplary assay using exemplary biomarker combinations (e.g., a capture factor targeting SLC34A2 and a set of at least a first detection probe targeting MUC16 and a second detection probe targeting MUC16) is shown to be able to detect ovarian cancer patients with normal serum CA-125 (e.g., <35 U / mL) and to differentiate many non-ovarian cancer patients (e.g., patients with benign gynecological tumors) with elevated serum CA-125 from ovarian cancer patients.

[0102] [Figure 32] An exemplary assay using exemplary biomarker combinations (e.g., a capture factor targeting SLC34A2 and a set of at least a first detection probe targeting FOLR1 and a second detection probe targeting FOLR1) is shown to be able to detect ovarian cancer patients with normal serum CA-125 (e.g., <35 U / mL) and to differentiate many non-ovarian cancer patients (e.g., patients with benign gynecological tumors) with elevated serum CA-125 from ovarian cancer patients.

[0103] [Figure 33] The performance of the exemplary assay described herein using exemplary biomarker combinations (e.g., a capture factor targeting MUC16 and a set of at least one detection probe targeting MUC16 and a second detection probe targeting CLDN3) is illustrated. The cutoff values ​​were determined as shown in Figure 23.

[0104] [Figure 34] The performance of the exemplary assay described herein using exemplary biomarker combinations (e.g., a capture factor targeting MUC16 and a set of at least one detection probe targeting MUC16 and a second detection probe targeting CLDN6) is illustrated. The cutoff values ​​were determined as shown in Figure 23.

[0105] [Figure 35] The performance of the exemplary assay described herein using exemplary biomarker combinations (e.g., a set of a capture factor targeting MUC16, at least a first detection probe targeting FOLR1, and a second detection probe targeting CLDN3) is illustrated. The cutoff values ​​were determined as shown in Figure 23.

[0106] [Figure 36] The performance of the exemplary assay described herein using exemplary biomarker combinations (e.g., a capture factor targeting LRRTM1 and a set of at least a first detection probe targeting MUC16 and a second detection probe targeting MUC16) is illustrated. The cutoff values ​​were determined as shown in Figure 23.

[0107] [Figure 37A] A series of receiver operating characteristic (ROC) curves for distinguishing patients with stage I–IV ovarian cancer from healthy patients are illustrated. The curves were generated using Ct values ​​determined from exemplary assays shown in Figures 23–28 and 33–36, respectively. Panel A illustrates exemplary ROC curves with an area under the curve (AUC) of 0.92 for the use of an SLC34A2 capture probe and a MUC16+MUC16 pliq-PCR detection probe. [Figure 37B]A series of receiver operating characteristic (ROC) curves for distinguishing patients with stage I–IV ovarian cancer from healthy patients are illustrated. The curves were generated using Ct values ​​determined from exemplary assays shown in Figures 23–28 and 33–36, respectively. Panel B illustrates exemplary ROC curves with an area under the curve (AUC) of 0.87 for the use of the SLC34A2 capture probe and the FOLR1+FOLR1 pliq-PCR detection probe. [Figure 37C] A series of receiver operating characteristic (ROC) curves for distinguishing patients with stage I–IV ovarian cancer from healthy patients are illustrated. The curves were generated using Ct values ​​determined from exemplary assays shown in Figures 23–28 and 33–36, respectively. Panel C illustrates exemplary ROC curves with area under the curve (AUC) of 0.90 for use with the SLC34A2 capture probe and the MUC16+FOLR1 pliq-PCR detection probe. [Figure 37D] A series of receiver operating characteristic (ROC) curves for distinguishing patients with stage I–IV ovarian cancer from healthy patients are illustrated. The curves were generated using Ct values ​​determined from exemplary assays shown in Figures 23–28 and 33–36, respectively. Panel D illustrates exemplary ROC curves with area under the curve (AUC) of 0.91 for the use of a MUC16 capture probe and a MUC16+MUC16 pliq-PCR detection probe. [Figure 37E] A series of receiver operating characteristic (ROC) curves for distinguishing patients with stage I–IV ovarian cancer from healthy patients are illustrated. The curves were generated using Ct values ​​determined from exemplary assays shown in Figures 23–28 and 33–36, respectively. Panel E illustrates exemplary ROC curves with area under the curve (AUC) of 0.91 for the use of the MUC16 capture probe and the MUC16+FOLR1 pliq-PCR detection probe. [Figure 37F]A series of receiver operating characteristic (ROC) curves for distinguishing patients with stage I–IV ovarian cancer from healthy patients are illustrated. The curves were generated using Ct values ​​determined from exemplary assays shown in Figures 23–28 and 33–36, respectively. Panel F illustrates exemplary ROC curves with area under the curve (AUC) of 0.84 for the use of a MUC16 capture probe and a MUC16+CLDN3 pliq-PCR detection probe. [Figure 37G] A series of receiver operating characteristic (ROC) curves for distinguishing patients with stage I–IV ovarian cancer from healthy patients are illustrated. The curves were generated using Ct values ​​determined from exemplary assays shown in Figures 23–28 and 33–36, respectively. Panel G illustrates exemplary ROC curves with area under the curve (AUC) of 0.90 for the use of a MUC16 capture probe and a MUC16+CLDN6 pliq-PCR detection probe. [Figure 37H] A series of receiver operating characteristic (ROC) curves for distinguishing patients with stage I–IV ovarian cancer from healthy patients are illustrated. The curves were generated using Ct values ​​determined from exemplary assays shown in Figures 23–28 and 33–36, respectively. Panel H illustrates exemplary ROC curves with area under the curve (AUC) of 0.90 for the use of the MUC16 capture probe and the FOLR1+FOLR1 pliq-PCR detection probe. [Figure 37I] A series of receiver operating characteristic (ROC) curves for distinguishing patients with stage I–IV ovarian cancer from healthy patients are illustrated. The curves were generated using Ct values ​​determined from exemplary assays shown in Figures 23–28 and 33–36, respectively. Panel I illustrates exemplary ROC curves with area under the curve (AUC) of 0.67 for the use of the MUC16 capture probe and the FOLR1+CLDN3 pliq-PCR detection probe. [Figure 37J]A series of receiver operating characteristic (ROC) curves for distinguishing patients with stage I–IV ovarian cancer from healthy patients are illustrated. The curves were generated using Ct values ​​determined from exemplary assays shown in Figures 23–28 and 33–36, respectively. Panel J illustrates exemplary ROC curves with area under the curve (AUC) of 0.78 for the use of the LRRTM1 capture probe and the MUC16+MUC16 pliq-PCR detection probe.

[0108] [Figure 38] The use of multiple orthogonal biomarker signature combinations and the associated improvements in assay sensitivity are illustrated. Combination 1 (SLC34A2 capture, MUC16 + MUC16 pliq-PCR detection probe) and Combination 2 (MUC16 capture probe, and MUC16 + FOLR1 pliq-PCR detection probe) can individually distinguish ovarian cancer populations from healthy control and benign tumor cohorts. Both cutoffs are set to achieve 99.5% specificity.

[0109] [Figure 39] The use of multiple orthogonal biomarker signature combinations and the associated improvements in assay sensitivity are illustrated. Combination 1 (SLC34A2 capture probe and FOLR1+FOLR1 pliq-PCR detection probe) and combination 2 (MUC16 capture probe and MUC16+FOLR1 pliq-PCR detection probe) can individually distinguish ovarian cancer populations from healthy control and benign tumor cohorts. Both cutoffs are set to achieve 99.5% specificity. [Modes for carrying out the invention]

[0110] A certain definition Administration: As used herein, the terms “administer” or “dosage” typically refer to administering a composition to a subject to deliver the composition, or any active ingredients contained in the composition, to a target site or site being treated. Those skilled in the art will understand the various routes that may be available for administration to a subject, e.g., a human, in appropriate circumstances. For example, in some embodiments, administration may be parenteral. In some embodiments, administration may be oral. In some embodiments, administration may consist of only a single dose. In some embodiments, administration may involve applying a fixed number of doses. In some embodiments, administration may include intermittent (e.g., multiple doses spaced apart) and / or cyclical (e.g., individual doses spaced apart) administrations. In some embodiments, administration may include continuous administration (e.g., perfusion) over at least a selected period of time.

[0111] Amplification: The terms “amplification” and “to amplify” refer to a template-dependent process that results in an increase in the quantity and / or level of a nucleic acid molecule compared to its initial quantity and / or level. A template-dependent process generally involves the template-dependent extension of a primer molecule, in which the sequence of the newly synthesized nucleic acid chain is determined by well-known rules of complementary base pairing (see, for example, Watson, J. Det. al., In: Molecular Biology of the Gene, 4th Ed., WABenjamin, Inc., Menlo Park, Calif. (1987), which is incorporated herein by reference for the purposes described herein).

[0112] Antibody Factor: As used herein, the term “antibody factor” refers to an action factor that specifically binds to a particular antigen. In some embodiments, the term also includes any polypeptide or polypeptide complex that contains sufficient immunoglobulin structural elements to confer specific binding. Exemplary antibody factors include, but are not limited to, monoclonal or polyclonal antibodies. In some embodiments, an antibody factor may comprise one or more constant region sequences characteristic of mouse, rabbit, primate, or human antibodies. In some embodiments, an antibody factor may comprise one or more sequence elements that are humanized, primated, chimeric, or otherwise known in the art. In many embodiments, the term “antibody factor” is used to refer to one or more constructs or formats known or developed in the art to utilize the structural and functional characteristics of an antibody in an alternative presentation.For example, embodiments of the present invention may utilize, but are not limited to, intact IgA, IgG, IgE, or IgM antibodies; bi- or multi-specific antibodies (e.g., Zybodies®); antibody fragments, e.g., Fab fragments, Fab' fragments, F(ab')2 fragments, Fd' fragments, Fd fragments, and isolated complementarity-determining regions (CDRs) or sets thereof; single-stranded Fv; polypeptide-Fc fusions; single-domain antibodies (e.g., shark single-domain antibodies, e.g., IgNAR or fragments thereof); camel antibodies; mask antibodies (e.g., Probodies®); small modular antibodies. ImmunoPharmaceuticals ("SMIP"); single-chain or tandem bispecific antibodies (TandAb®); VHH; Anticalin®; Nanobodies® minibodies; BiTE®; Ankyrin repeat protein or DARPIN®; Avimer®; DART; TCR-like antibodies; Adnectin®; Affilin®; Trans-bodies®; Affibodies®; TrimerX®; microproteins; and formats selected from Fynomers®, Centyrin®, KALBITOR®, and Affimer®. In some embodiments, antibodies may lack covalent modifications (e.g., glycan attachments) that they would have if naturally produced. In some embodiments, the antibody may include covalent modifications (e.g., glycans, payloads [e.g., detectable portions, therapeutic portions, catalytic portions, etc.]) or attachments of other pendant groups [e.g., polyethylene glycol, etc.]. In many embodiments, the antibody factor is a polypeptide comprising or including one or more structural elements whose amino acid sequence is recognized by those skilled in the art as a complementarity-determining region (CDR); in some embodiments, the antibody factor is a polypeptide comprising or including at least one CDR (e.g., at least one heavy-chain CDR and / or at least one light-chain CDR) whose amino acid sequence is substantially identical to that found in a reference antibody.In some embodiments, the included CDR is substantially identical to the reference CDR, in which case it has the same sequence or contains 1 to 5 amino acid substitutions compared to the reference CDR. In some embodiments, the included CDR is substantially identical to the reference CDR, in which case it exhibits at least 85%, 86%, 87%, 88%, 89%, 90%, 91%, 92%, 93%, 94%, 95%, 96%, 97%, 98%, 99%, or 100% sequence identity with the reference CDR. In some embodiments, the included CDR is substantially identical to the reference CDR, in which case it exhibits at least 95%, 96%, 97%, 98%, 99%, or 100% sequence identity with the reference CDR. In some embodiments, the included CDR is substantially identical to the reference CDR, in which case at least one amino acid in the included CDR is deleted, added, or substituted compared to the reference CDR, but the included CDR has an amino acid sequence that is otherwise identical to that of the reference CDR. In some embodiments, the included CDR is substantially identical to the reference CDR, in which case at least 1 to 5 amino acids in the included CDR are deleted, added, or substituted compared to the reference CDR, but the included CDR has an amino acid sequence that is otherwise identical to that of the reference CDR. In some embodiments, the included CDR is substantially identical to the reference CDR, in which case at least one amino acid in the included CDR is substituted compared to the reference CDR, but the included CDR has an amino acid sequence that is otherwise identical to that of the reference CDR. In some embodiments, the included CDR is substantially identical to the reference CDR, in which case 1 to 5 amino acids in the included CDR are deleted, added, or substituted compared to the reference CDR, but the included CDR has an amino acid sequence that is otherwise identical to the reference CDR. In some embodiments, the antibody factor is a polypeptide comprising, or including, a plurality of structural elements whose amino acid sequence is recognized by those skilled in the art as an immunoglobulin variable domain. In some embodiments, the antibody factor is a polypeptide protein having a binding domain homologous or broadly homologous to an immunoglobulin binding domain.

[0113] Those skilled in the art can prepare antibody factors using methods known in the art as well as commercially available services and kits. For example, methods for preparing monoclonal antibodies are well known in the art and include hybridoma techniques and phage display techniques. Further antibodies suitable for use in this disclosure are described, for example, in the following publication: Antibodies A Laboratory Manual, Second edition.Edward A.Greenfield.Cold Spring Harbor Laboratory Press(September 30,2013);Making and Using Antibodies:A Practical Handbook,Second Edition.Eds.Gary C.Howard and Matthew R.Kaser.CRC Press(July 29,2013);Antibody Engineering:Methods and Protocols,Second Edition(Methods in Molecular Biology).Patrick Chames.Humana Press(August 21,2012);Monoclonal Antibodies:Methods and Protocols(Methods in Molecular Biology).Eds.Vincent Ossipow and Nicolas Fischer.Humana Press(February 12, 2014); and Human Monoclonal Antibodies: Methods and Protocols (Methods in Molecular Biology). Michael Steinitz. Humana Press (September 30, 2013)).

[0114] Antibodies can be produced by standard techniques, for example, by immunization with a suitable polypeptide or part thereof, or by using a phage display library. If polyclonal antibodies are desired, selected host animals (e.g., mice, rabbits, goats, horses, chickens, etc.) are immunized with immunogenic polypeptides having the desired epitope(s) haptenized to another polypeptide, if optional. Depending on the host species, various adjuvants can be used to enhance the immune response. Such adjuvants include, but are not limited to, Freund's adjuvants, mineral gels, e.g., aluminum hydroxide, and surfactants, e.g., lysolecithin, pluronic polyols, polyanions, peptides, oil emulsions, keyhole limpet hemocyanins, and dinitrophenol. Serum is collected from the immunized animals and processed according to known procedures. If the serum containing polyclonal antibodies against the desired epitope also contains antibodies against other antigens, the polyclonal antibodies can be purified by immunoaffinity chromatography or any other method known in the art. Techniques for producing or processing polyclonal antiserums are well known in the art.

[0115] Approximately or about: As used herein, the terms “approximately” or “about” refer to a value that, when applied to one or more values ​​of interest, is similar to a defined baseline value. Generally, a person skilled in the art familiar with the context will understand the degree of related variance encompassed by “approximately” or “about” in that context. For example, in some embodiments, the terms “approximately” or “about” may encompass a range of values ​​that are 25%, 20%, 19%, 18%, 17%, 16%, 15%, 14%, 13%, 12%, 11%, 10%, 9%, 8%, 7%, 6%, 5%, 4%, 3%, 2%, 1%, or less than 25% of the related value.

[0116] Aptamer: As used herein, the term “aptamer” typically refers to a nucleic acid molecule or peptide molecule that binds to a specific target molecule (e.g., an epitope). In some embodiments, nucleic acid aptamers may be described by a nucleotide sequence and are typically about 15 to 60 nucleotides long. Nucleic acid aptamers may be or contain single-stranded and / or double-stranded structures. In some embodiments, nucleic acid aptamers may be or contain DNA. In some embodiments, nucleic acid aptamers may be or contain RNA. While we do not wish to be bound by any particular theory, it is intended that the nucleotide chains in the aptamer form intramolecular interactions that fold the molecule into a complex three-dimensional shape, and that this three-dimensional shape allows the aptamer to bind tightly to the surface of its target molecule. In some embodiments, peptide aptamers may be described as having one or more peptide loops of variable sequences presented by a protein scaffold. Peptide aptamers can be isolated from combinatorial libraries and, in many cases, subsequently improved by a round of targeted mutation or variable region mutagenesis and selection. Given the enormous diversity of molecular shapes present within the universe of all possible nucleotides and / or peptide sequences, aptamers can be obtained for a wide range of molecular targets, including proteins and small molecules. In addition to high specificity, aptamers typically exhibit very high affinity for their targets (e.g., affinity ranging from picomoles to low nanomoles for proteins or polypeptides). Since aptamers are typically synthetic molecules, they are well-suited for a variety of modifications that can optimize their function for specific applications.

[0117] Related to: When this term is used herein, two events or entities are “related” to each other if the presence, level and / or form of one correlates with those of the other. For example, a particular biological phenomenon (e.g., the expression of a specific biomarker) is considered related to ovarian cancer (e.g., a specific type and / or stage of ovarian cancer) if its presence correlates with the development and / or susceptibility to ovarian cancer (e.g., the entire relevant population).

[0118] Biological Entity: In appropriate circumstances, as will be apparent to those skilled in the art, the term “biological entity” may be used to refer to entities or components present in a biological sample derived from or obtained therefrom, for example, in some embodiments, which may be or include cells or living organisms, e.g., animals or humans, or in some embodiments, which may be or include biological tissues or fluids. In some embodiments, the biological entity is or includes cells or microorganisms, or fractions, extracts, or components thereof (e.g., including intracellular components and / or molecules secreted by cells or microorganisms). For example, in some embodiments, the biological entity is or includes cells. In some embodiments, the biological entity is or includes extracellular vesicles. In some embodiments, the biological entity is or includes biological analytes (e.g., metabolites, carbohydrates, proteins or polypeptides, enzymes, lipids, organelles, cytokines, receptors, ligands, and any combination thereof). In some embodiments, the biological entities present in the sample are in their native state (e.g., proteins or polypeptides maintained in their naturally occurring higher-order structures). In some embodiments, the biological entity is processed, for example, by isolating it from a sample or obtaining it from a naturally occurring biological entity. For example, the biological entity may be treated with one or more chemical agents to make it more desirable for detection using the techniques provided herein. For example, the biological entity may be a cell or extracellular vesicle that, upon contact with a fixative (e.g., methanol and / or formaldehyde), results in the formation of crosslinks of proteins and / or peptides present within the cell or extracellular vesicle. In some embodiments, the biological entity is in an isolated or pure form (e.g., isolated from a bodily fluid sample such as a blood, serum, or plasma sample). In some embodiments, the biological entity may be present in a composite matrix (e.g., a bodily fluid sample such as a blood, serum, or plasma sample).

[0119] Biomarkers: The term “biomarker” typically refers to entities, events, or characteristics whose presence, level, degree, type, and / or form correlate with a particular biological event or condition of interest, and which are therefore determined to be “markers” of that event or condition. To give some examples, in some embodiments, a biomarker may be, or may include, a marker for a particular pathological condition or the likelihood that a particular disease, disorder, or condition may occur, develop, or recur. In some embodiments, a biomarker may be, or may include, a marker for a particular disease or treatment outcome, or the likelihood thereof. In some embodiments, a biomarker may be, or may include, a marker for a particular tissue (e.g., but not limited to, the brain, breast, colon, ovaries and / or other tissues associated with the female reproductive system, pancreas, prostate and / or other tissues associated with the male reproductive system, liver, lungs, and skin). Such markers for a particular tissue may, in some embodiments, be specific to healthy tissue, specific to diseased tissue, or, in some embodiments, be present in normal, healthy tissue and diseased tissue (e.g., tumors); those skilled in the art will understand the appropriate context for each of such types of biomarkers by reading this disclosure. In some embodiments, a biomarker may be or include a cancer-specific marker (e.g., a marker specific to a particular cancer). In some embodiments, a biomarker may be or include a non-specific cancer marker (e.g., a marker present in at least two or more cancers). A non-specific cancer marker may, in some embodiments, be a general marker for cancer (e.g., a marker typically present in cancer regardless of tissue type), or in some embodiments, be a marker for cancer in a specific tissue (e.g., but not limited to, the brain, breast, colon, ovaries and / or other tissues associated with the female reproductive system, pancreas, prostate and / or other tissues associated with the male reproductive system, liver, lungs, and skin).Therefore, in some embodiments, biomarkers are predictive; in some embodiments, biomarkers are prognostic; and in some embodiments, biomarkers are diagnostic for relevant biological events or the situation of interest. A biomarker may be or may include entities of any chemical group, or combinations thereof. For example, in some embodiments, a biomarker may be or may include nucleic acids, polypeptides, lipids, carbohydrates, small molecules, inorganic factors (e.g., metals or ions), or combinations thereof. In some embodiments, a biomarker may be or may include a specific molecule, complex, or structure; for example, in some embodiments, a biomarker may be or may include an epitope. In some embodiments, a biomarker is a surface marker of an extracellular vesicle associated with ovarian cancer (e.g., a surface protein marker). In some embodiments, a biomarker is intravesicle (e.g., a protein or RNA marker present in an extracellular vesicle). In some embodiments, a biomarker may be or may include a genetic or epigenetic signature. In some embodiments, a biomarker may be or include a gene expression signature. In some embodiments, “biomarker” suitable for use in accordance with this disclosure may refer to the presence, level, and / or form of a molecular entity (e.g., an epitope) present at a target marker. For example, in some embodiments, two or more “biomarkers” (e.g., epitopes) as molecular entities may be present on the same target marker (e.g., a marker protein, e.g., a surface protein present in an extracellular vesicle).

[0120] Blood-derived samples: The term “blood-derived samples,” as used herein, refers to samples derived from the blood sample (i.e., whole blood sample) of the subject for which it is required. Examples of blood-derived samples include, but are not limited to, plasma (e.g., including fresh frozen plasma), serum, blood fractions, plasma fractions, serum fractions, blood fractions containing red blood cells (RBCs), platelets, white blood cells, etc., and cell lysates containing those fractions (e.g., cells, e.g., red blood cells, white blood cells, etc., can be collected and lysed to obtain cell lysates). In some embodiments, the blood-derived samples used in the methods, systems, and / or kits described herein are plasma samples.

[0121] Cancer: The term “cancer” is used herein to generally refer to a disease or condition in which cells of a tissue of interest exhibit relatively abnormal, uncontrolled, and / or autonomous growth, and thus they exhibit an abnormal growth phenotype characterized by a significant loss of control over cell proliferation. In some embodiments, cancer may include cells that are precancerous (e.g., benign), malignant, pre-metastatic, metastatic, and / or non-metastatic. This disclosure provides techniques for detecting ovarian cancer.

[0122] Classification Cutoff: As used herein, the term “classification cutoff” refers to a level, value, or score, or set of values, or index used to predict the risk of a subject for a disease or condition (e.g., lung cancer) by defining one or more boundaries within two or more subsets of a population (e.g., normal healthy subjects and subjects with an inflammatory condition versus lung cancer subjects). In some embodiments, the classification cutoff can optionally be determined based on at least one criterion threshold level (e.g., criterion cutoff) for the target biomarker signature described herein, in combination with other appropriate variables, e.g., age of the subject, life history-related risk factors, genetic factors, physical and / or medical condition. In some embodiments where the classification is based on a single target biomarker signature (e.g., as described herein), the classification cutoff may be the same as a predetermined criterion threshold (e.g., cutoff) for the single target biomarker signature. In some embodiments where the classification is based on two or more target biomarker signatures, the classification cutoff may optionally incorporate one or more appropriate variables, such as age of the subject, life history-related risk factors, genetic factors, physical and / or medical status, based on two or more pre-determined criterion thresholds (e.g., cutoffs) for each corresponding target biomarker signature. In some embodiments, the classification cutoff may optionally be determined by computer algorithm-mediated analysis based on at least one criterion threshold level (e.g., criterion cutoff) for the target biomarker signatures described herein, in combination with other appropriate variables, such as age of the subject, life history-related risk factors, genetic factors, physical and / or medical status.

[0123] Proximity: As used herein, “proximity” refers to the distance between two detection probes (e.g., two detection probes in a pair) that are close enough to likely occur to interact with each other (e.g., via their respective oligonucleotide domains). For example, in some embodiments, the probability that two detection probes will interact with each other (e.g., via their respective oligonucleotide domains) over a period of time when they are in sufficient proximity to each other under specified conditions (e.g., when the detection probes are bound to their respective targets in extracellular vesicles) is at least 50% or more, including, for example, at least 60%, at least 70%, at least 80%, at least 90%, or more. In some embodiments, the distance between two detection probes when they are in sufficient proximity to each other may be in the range of approximately 0.1–1000 nm, or 0.5–500 nm, or 1–250 nm. In some embodiments, the distance between two detection probes when they are in sufficient proximity to each other may be approximately 0.1–10 nm or approximately 0.5–5 nm. In some embodiments, the distance between two detection probes when they are sufficiently close to each other may be less than 100 nm or less, including, for example, less than 90 nm, less than 80 nm, less than 70 nm, less than 60 nm, less than 50 nm, less than 40 nm, less than 30 nm, less than 20 nm, less than 10 nm, less than 5 nm, less than 1 nm, or less. In some embodiments, the distance between two detection probes when they are sufficiently close to each other may be in the range of approximately 40 to 1000 nm or 40 nm to 500 nm.

[0124] Comparable: As used herein, the term “comparable” means two or more sets of actors, entities, situations, conditions, etc., that do not necessarily have to be identical to one another but are similar enough to allow comparison between them, and that a person skilled in the art would reasonably recognize that a conclusion can be drawn based on the differences or similarities observed. In some embodiments, a comparable set of conditions, situations, individuals, or groups is characterized by one or a few of several substantially identical features and various features. A person skilled in the art will understand, in context, what degree of identity is required for two or more such sets of actors, entities, situations, conditions, etc., to be determined to be comparable in any given situation. For example, a person skilled in the art will see that sets of situations, individuals, or groups are comparable to one another if they are characterized by a sufficient number and variety of substantially identical features to ensure a reasonable conclusion that differences in results obtained under different sets of situations, individuals, or groups, or in phenomena observed using them, are due to or indicate changes in the altered features.

[0125] Complementary: As used herein, the term “complementary” is used in reference to oligonucleotide hybridizations associated by base pairing rules. For example, the sequence “CAGT” is complementary to the sequence “GTCA”. Complementarity can be partial or complete. Therefore, any degree of partial complementarity is intended to fall within the scope of the term “complementary,” provided that such partial complementarity allows for oligonucleotide hybridization. Partial complementarity occurs when one or more nucleic acid bases do not match according to base pairing rules. Complete or complete complementarity occurs when all nucleic acid bases match with the bases of the other under base pairing rules.

[0126] Detection: The term “detection” is used herein to include appropriate means of determining the presence or absence of extracellular vesicles expressing a target biomarker signature of ovarian cancer or any form of measurement indicating such extracellular vesicles. Thus, “detection” may include determining, measuring, evaluating, or assaying the presence or absence, level, quantity, and / or location of an entity of interest corresponding to a portion of the target biomarker signature (e.g., a surface protein biomarker, an intravesical protein biomarker, or an intravesical RNA biomarker) in any way. In some embodiments, “detection” may include determining, measuring, evaluating, or quantifying a form of measurement indicating an entity of interest (e.g., a ligated template indicating a surface protein biomarker and / or an intravesical protein biomarker, or a PCR amplification product indicating intravesical mRNA). This includes quantitative and qualitative determination, measurement, or evaluation, including semi-quantitative. For example, if the entity of interest (e.g., a surface protein biomarker, an intravesical protein biomarker, or an intravesical RNA biomarker) or the form of measurement indicating it is detected in comparison to a control standard or an absolute, such determination, measurement, or evaluation may be relative. Therefore, when used in the context of quantifying the entity of interest (e.g., a surface protein biomarker, an intravesical protein biomarker, or an intravesical RNA biomarker) or the form of measurement indicating it, the term "quantifying" can refer to absolute or relative quantification. Absolute quantification can be achieved by correlating the detected level of the entity of interest (e.g., a surface protein biomarker, an intravesical protein biomarker, or an intravesical RNA biomarker) or the form of measurement indicating it to a known control standard (e.g., through the generation of a standard curve).Alternatively, relative quantification can be achieved by comparing the levels or amounts detected between two or more different target entities (e.g., different surface protein biomarkers, intracellular protein biomarkers, or intracellular RNA biomarkers) to obtain a relative quantification of each of the two or more different target entities, i.e., relative to each other.

[0127] Detection label: As used herein, the term "detection label" refers to any detectable element, molecule, functional group, compound, fragment or moiety. In some embodiments, the detection label is provided or utilized alone. In some embodiments, the detection label is provided and / or utilized in association with (e.g., conjugated to) another agent. Examples of detection labels include, but are not limited to: various ligands, radionuclides (e.g., H, 14 C, 18 F, 19 F, 32 P, 35 S, 135 I, 125 I, 123 I, 64 Cu, 187 Re, 111 In, 90 Y, 99m Tc, 177 Lu, 89 Zr, etc.), fluorescent dyes, chemiluminescent agents (e.g., acridinium esters, stabilized dioxetanes, etc.), bioluminescent agents, spectrally resolvable inorganic fluorescent semiconductor nanocrystals (i.e., quantum dots), metal nanoparticles (e.g., gold, silver, copper, platinum, etc.) nanoclusters, paramagnetic metal ions, enzymes, colorimetric labels (e.g., dyes, colloidal gold, etc.), biotin, dioxigenin, haptens, and proteins to which antisera or monoclonal antibodies can be utilized.

[0128] Detection Probe: The term “detection probe” typically refers to a probe oriented towards the detection and / or quantification of a specific target. In some embodiments, the detection probe is a quantification probe that provides an index representing the level of a specific target. In this disclosure, the detection probe refers to a composition comprising a target-binding entity directly or indirectly coupled to an oligonucleotide domain, wherein the target-binding entity specifically binds to its respective target (e.g., a molecular target), and at least a portion of the oligonucleotide domain is designed to allow hybridization with a portion of the oligonucleotide domain of another detection probe for a different target. In many embodiments, an oligonucleotide domain suitable for use by this disclosure comprises a double-stranded portion and at least one single-stranded overhang. In some embodiments, the oligonucleotide domain may comprise a double-stranded portion and single-stranded overhangs at each end of the double-stranded portion.

[0129] Double-stranded: As used herein, the term “double-stranded” in the context of the oligonucleotide domain is understood by those skilled in the art to mean a pair of oligonucleotides existing in a hydrogen-bonded helical arrangement, typically in association with a nucleic acid such as DNA. In addition to the 100% complementary form of double-stranded oligonucleotides, the term “double-stranded” is also intended, as used herein, to refer to forms that include mismatches (e.g., partial complementarity) and / or structural features such as bulges, loops, or hairpins.

[0130] Double-stranded complex: As used herein, the term “double-stranded complex” typically refers to a complex comprising at least two or more detection probes (e.g., including 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, or more) each directed to a target (which may be the same target or distinct targets) and linked or coupled to each other in a linear arrangement via hybridization of complementary single-stranded overhangs of the detection probes (e.g., as provided and / or utilized herein). In some embodiments, such a double-stranded complex may include extracellular vesicles, in which the target-binding portions of each detection probe are simultaneously bound to the extracellular vesicles.

[0131] Epitope: As used herein, the term “epitope” includes any portion that is specifically recognized by an immunoglobulin (e.g., antibody or receptor) binding component or aptamer. In some embodiments, the epitope consists of multiple chemical atoms or groups on an antigen. In some embodiments, if the antigen employs a relevant three-dimensional structure, such chemical atoms or groups are surface-exposed. In some embodiments, such chemical atoms or groups are spatially and physically close to each other if the antigen employs such a structure. In some embodiments, if the antigen employs an alternative structure (e.g., linearized), at least some of such chemical atoms that are groups are physically separated from each other.

[0132] Extracellular vesicles: As used herein, the term “extracellular vesicles” typically refers to vesicles outside a cell, such as those secreted by a cell. Examples of secreted vesicles include, but are not limited to, exosomes, microvesicles, microparticles, ectosomes, oncosomes, and apoptotic bodies. While we do not wish to be bound by theory, exosomes are intracellular nanometer-sized vesicles (e.g., 40 nm to 120 nm) that can be formed by inward budding of the boundary membrane of multivesicular endosomes (MVEs), while microvesicles typically budding from the cell surface, and their size can vary from 50 nm to 1000 nm. In some embodiments, extracellular vesicles are or include exosomes and / or microvesicles. In some embodiments, a sample containing extracellular vesicles is substantially free of apoptotic bodies. In some embodiments, a sample containing extracellular vesicles may include extracellular vesicles released from or originating from one or more tissues (e.g., cancerous tissue and / or non-cancerous or healthy tissue). In some embodiments, the extracellular vesicles in the sample may be released from or originate from an ovarian cancer tumor; in some embodiments, the extracellular vesicles in the sample are released from or originate from a non-ovarian cancer tumor. In some embodiments, the extracellular vesicles are released from or originate from healthy tissue. In some embodiments, the extracellular vesicles are released from or originate from a benign gynecological tumor. In some embodiments, the extracellular vesicles are released from or originate from the tissue of the subject having symptoms associated with ovarian cancer (e.g., nonspecific symptoms).

[0133] Extracellular vesicle-associated membrane-bound polypeptide: As used herein, such a term refers to a polypeptide present in the membrane of an extracellular vesicle. In some embodiments, such polypeptides may be tumor-specific. In some embodiments, such polypeptides may be tissue-specific (e.g., ovarian tissue-specific). In some embodiments, such polypeptides may be non-specific, for example, present in one or more non-target tumors and / or one or more non-target tissues.

[0134] As used herein, the terms “hybridize,” “hybridize,” “hybridization,” “annealing,” or “annealing” are used interchangeably when referring to the pairing of complementary nucleic acids using any process by which one strand of nucleic acid joins a complementary strand via base pairing to form a hybridize complex. Hybridization and the intensity of hybridization (e.g., the intensity of association between nucleic acids) are influenced by a variety of factors, including, for example, the degree of complementarity between nucleic acids, the stringency of the conditions involved, the melting temperature (T) of the hybridization complex formed, and the G:C ratio within the nucleic acid.

[0135] Intravesical protein biomarkers: As used herein, the term “intravesical protein biomarker” refers to a marker indicating the state (e.g., presence, level, and / or activity) of a polypeptide present within a biological entity (e.g., a cell or an extracellular vesicle). In many embodiments, intravesical protein biomarkers are associated with or present within extracellular vesicles.

[0136] Intravesical RNA Biomarkers: As used herein, the term “intravesical RNA biomarker” refers to a marker that indicates the state (e.g., presence and / or level) of RNA (e.g., mRNA) present within a biological entity (e.g., a cell or an extracellular vesicle). In many embodiments, intravesical RNA biomarkers are associated with or present within extracellular vesicles.

[0137] Ligase: As used herein, the terms “ligase” or “nucleic acid ligase” refer to an enzyme used for ligating nucleic acids. In some embodiments, the ligase is an enzyme used for ligating the 3' end of a polynucleotide to the 5' end of a polynucleotide. In some embodiments, the ligase is an enzyme used for performing adherent end ligation. In some embodiments, the ligase is an enzyme used for performing blunt end ligation. In some embodiments, the ligase is or includes a DNA ligase.

[0138] Lifestyle-related risk factors: As used herein, the term “lifestyle-related risk factors” refers to activities, experiences, medical history, and / or exposures in an individual’s life that may directly or indirectly increase the individual’s risk of a certain condition, such as ovarian cancer, compared to an individual who does not have such activities, experiences, medical history, and / or exposures in their life. In some embodiments, non-limiting examples of lifestyle-related risk factors include smoking, alcohol, drugs, carcinogens, diet, obesity, diabetes, polycystic ovary syndrome (PCOS), endometriosis, pelvic inflammatory disease (PID), nulliparous / infertile, no / short history of oral contraceptive use, physical activity, sun exposure, radiation exposure, perineal talc use, hormone replacement therapy (HRT), infectious agents, such as exposure to viruses, and / or occupational hazards (Reid et al., 2017; incorporated herein by reference for the purposes described herein). Those skilled in the art will understand that the above list of lifestyle-related risk factors contributing to cancer (e.g., ovarian cancer) incidence is not exhaustive and is constantly evolving.

[0139] Ligation: As used herein, the terms “ligate,” “ligate,” or “ligation” refer to methods or compositions known in the art for joining two oligonucleotides or polynucleotides. Ligation may be or include a sticky-end ligation or a blunt-end ligation. In some embodiments, the ligation included in the provided art is or includes a sticky-end ligation. In some embodiments, ligation refers to joining the 3' end of one polynucleotide to the 5' end of another polynucleotide. In some embodiments, ligation is facilitated by the use of a ligase.

[0140] Non-cancer subjects: As used herein, the term “non-cancer subjects” generally refers to female subjects who do not have non-benign ovarian cancer. For example, in some embodiments, non-cancer subjects are healthy female subjects (e.g., healthy adult female subjects). In some embodiments, non-cancer subjects are healthy female subjects under 55 years of age (e.g., healthy adult female subjects). In some embodiments, non-cancer subjects are healthy female subjects aged 55 years or older (e.g., healthy adult female subjects). In some embodiments, non-cancer subjects are female subjects with non-ovarian related health conditions, disorders, or conditions (e.g., adult female subjects). In some embodiments, non-cancer subjects are female subjects with benign ovarian tumors (e.g., benign masses observed in the fallopian tubes and / or on the ovaries) (e.g., adult female subjects).

[0141] Nucleic Acids / Oligononucleotides: As used herein, the term “nucleic acid” refers to a polymer consisting of at least 10 nucleotides or more. In some embodiments, the nucleic acid is or contains DNA. In some embodiments, the nucleic acid is or contains RNA. In some embodiments, the nucleic acid is or contains peptide nucleic acid (PNA). In some embodiments, the nucleic acid is or contains single-stranded nucleic acid. In some embodiments, the nucleic acid is or contains double-stranded nucleic acid. In some embodiments, the nucleic acid includes both single-stranded and double-stranded portions. In some embodiments, the nucleic acid includes a backbone comprising one or more phosphodiester bonds. In some embodiments, the nucleic acid includes a backbone comprising both phosphodiester and non-phosphodiester bonds. For example, in some embodiments, the nucleic acid may include a backbone comprising one or more phosphorothioate or 5'-N-phosphoramidite bonds and / or one or more peptide bonds, for example, in “peptide nucleic acid.” In some embodiments, the nucleic acid comprises one or more, or all, of the native residues (e.g., adenine, cytosine, deoxyadenosine, deoxycytidine, deoxyguanosine, deoxythymidine, guanine, thymine, uracil). In some embodiments, the nucleic acid comprises one or more, or all, of the non-native residues. In some embodiments, non-natural residues include nucleoside analogs (e.g., 2-aminoadenosine, 2-thiothymidine, inosine, pyrrolopyrimidine, 3-methyladenosine, 5-methylcytidine, C-5 propynylcytidine, C-5 propynyluridine, 2-aminoadenosine, C5-bromouridine, C5-fluorouridine, C5-iodouridine, C5-propynyluridine, C5-propynylcytidine, C5-methylcytidine, 2-aminoadenosine, 7-deazaadenosine, 7-deazaguanosine, 8-oxoadenosine, 8-oxoguanosine, 6-O-methylguanine, 2-thiocytidine, methylated bases, intercalated bases, and combinations thereof).In some embodiments, non-natural residues include one or more modified sugars (e.g., 2'-fluororibose, ribose, 2'-deoxyribose, arabinose, and hexose) compared to those in natural residues. In some embodiments, the nucleic acid has a nucleotide sequence encoding a functional gene product such as RNA or polypeptide. In some embodiments, the nucleic acid has a nucleotide sequence containing one or more introns. In some embodiments, the nucleic acid is isolated from a natural source, enzymatically synthesized (e.g., in vivo or in vivo). Nucleic acids can be prepared in vitro, for example, by polymerization based on a complementary template, reproduction in recombinant cells or systems, or chemosynthesis. In some embodiments, nucleic acids are at least 3, 4, 5, 6, 7, 8, 9, 10, 15, 20, 25, 30, 35, 40, 45, 50, 55, 60, 65, 70, 75, 80, 85, 90, 95, 100, 110, 120, 130, 140, 150, 160, 170, 180, 190, 20, 225, 250, 275, 300, 325, 350, 375, 400, 425, 450, 475, 500, 600, 700, 800, 900, 1000, 1500, 2000, 2500, 3000, 3500, 4000, 4500, 5000, 5500, 6000, 6500, 7000, 7500, 8000, 8500, 9000, 9500, 10,000, 10,500, 11,000, 11,500, 12,000, 12,500 The residue or nucleotide length is 13,000, 13,500, 14,000, 14,500, 15,000, 15,500, 16,000, 16,500, 17,000, 17,500, 18,000, 18,500, 19,000, 19,500, or 20,000 or more.

[0142] Nucleotides: As used herein, the term “nucleotide” means as it is understood in the art. When some nucleotides are used, for example, to indicate the size of an oligonucleotide, a certain number of nucleotides refers, for example, to the number of nucleotides on a single strand of an oligonucleotide.

[0143] Patient: As used herein, the term “patient” means any living organism that has or is at risk of having a disease or disorder or condition. Typical patients include animals (e.g., mammals, e.g., mice, rats, rabbits, non-human primates, and / or humans). In some embodiments, the patient is human. In some embodiments, the patient has or is susceptible to one or more diseases or disorders or conditions. In some embodiments, the patient exhibits one or more symptoms of a disease or disorder or condition. In some embodiments, the patient has been diagnosed with having one or more diseases or disorders or conditions. In some embodiments, the disease or disorder or condition suitable for the technology provided is or includes cancer, or the presence of one or more tumors. In some embodiments, the patient has been or is currently receiving certain treatments to diagnose and / or treat a disease, disorder, or condition.

[0144] Polypeptide: The term “polypeptide,” as used herein, typically has its art-accepted meaning of a polymer consisting of at least three amino acids or more. Those skilled in the art will see that the term “polypeptide” is intended to be sufficiently general to encompass not only polypeptides having the complete sequences listed herein, but also polypeptides representing functionally active or characteristic fragments, parts, or domains (e.g., fragments, parts, or domains retaining at least one activity) of such complete polypeptides. In some embodiments, the polypeptide may include L-amino acids, D-amino acids, or both, and / or any of the various amino acid modifications or analogs known in the art. Useful modifications include, for example, terminal acetylation, amidation, and methylation. In some embodiments, the polypeptide may include native amino acids, non-native amino acids, synthetic amino acids, and combinations thereof (e.g., it may be or may include peptide mimetic compounds).

[0145] To prevent or prevent: As used herein, “to prevent” or “prevention,” when used in connection with the occurrence of a disease, disorder, and / or condition, means to reduce the risk of the occurrence of that disease, disorder, and / or condition, and / or to delay the onset of one or more characteristics or symptoms of the disease, disorder, or condition. Prevention may be deemed complete if the onset of the disease, disorder, or condition is delayed over a predetermined period of time.

[0146] Primer: As used herein, the term "primer" refers to an oligonucleotide that can act as a synthesis initiation site when placed under conditions that induce the synthesis of a primer extension product complementary to the nucleic acid chain (e.g., in the presence of a nucleotide and an inducer, e.g., DNA polymerase, and at appropriate temperature and pH). Primers are preferably single-stranded for maximum amplification efficiency. Primers should be long enough to prime the synthesis of the extension product in the presence of an inducer. The exact length of the primer may depend on many factors, such as temperature.

[0147] Criteria: As used herein, “criteria” describes a standard or control against which comparison is made. For example, in some embodiments, a target agent, animal, individual, population, sample, sequence, or value is compared to a reference or control agent, animal, individual, population, sample, sequence, or value. In some embodiments, the reference or control is tested and / or determined substantially concurrently with the test or determination of interest. In some embodiments, the reference or control is a historical reference or control performed in a tangible medium, at the discretion of the user. In some embodiments, the reference or control in the context of a target baseline level refers to the target level in a normal, healthy subject or population of normal, healthy subjects. In some embodiments, the reference or control in the context of a target baseline level refers to the target level in a subject before treatment. Typically, as will be understood by those skilled in the art, a reference or control is determined or characterized against the one being evaluated under comparable conditions or circumstances. Those skilled in the art will see when there is sufficient similarity to justify reliability against a particular possible reference or control and / or to make a comparison against it.

[0148] Risk: As would be understood from the context, the “risk” of a disease, disorder, and / or condition refers to the likelihood that a particular individual will develop the disease, disorder, and / or condition. In some embodiments, the risk is expressed as a percentage. In some embodiments, the risk is from 0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 20, 30, 40, 50, 60, 70, 80, 90 up to 100%. In some embodiments, the risk is expressed as the risk relative to a reference sample or group of reference samples. In some embodiments, the reference sample or group of reference samples has a known risk of the disease, disorder, condition, and / or event. In some embodiments, the reference sample or group of reference samples is from individuals comparable to a particular individual. In some embodiments, the relative risk is 0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10 or higher.

[0149] Sample: As used herein, the term “sample” typically refers to a portion of a substance obtained from or derived from a source of interest. In some embodiments, the sample is obtained from or derived from a biological source of interest (e.g., tissue or living organism or cell culture). In some embodiments, the source of interest may be or include cells or living organisms, e.g., animals or humans. In some embodiments, the source of interest may be or include biological tissue or fluid. In some embodiments, biological tissues or fluids may be or include amniotic fluid, aqueous humor, ascites, bile, bone marrow, blood, breast milk, cerebrospinal fluid, earwax, chyle, chime, ejaculated semen, endolymph, exudate, feces, gastric acid, gastric juice, lymph, mucus, pericardial fluid, perilymph, peritoneal fluid, pleural fluid, pus, catarrhal secretions, saliva, sebum, semen, serum, smegma, sputum, synovial fluid, sweat, tears, urine, vaginal secretions, vitreous fluid, vomit, and / or combinations or components thereof. In some embodiments, biological fluids may be or include intracellular fluids, extracellular fluids, intravesical fluids (plasma), interstitial fluid, lymph, and / or cell permeable fluids. In some embodiments, biological tissue or specimens can be obtained, for example, by aspirate, biopsy (e.g., microneedle or tissue biopsy), swab (e.g., oral, nasal, skin, or vaginal swab), scraping, surgery, lavage, or irrigation (e.g., bronchoalveolar, tubal, nose, eye, oral cavity, uterus, vagina, or other lavage or irrigation). In some embodiments, the biological specimen is or includes a liquid biopsy. In some embodiments, the biological specimen is or includes cells obtained from an individual. In some embodiments, the specimen is a “primary specimen” obtained directly from the source of interest by any suitable means. In some embodiments, as will be evident from the context, the term “specimen” refers to a preparation obtained by processing a primary specimen (e.g., by removing one or more of its components and / or by adding one or more agents thereto). For example, the specimen is a preparation processed by using a semipermeable membrane or affinity-based method, such as an antibody-based method, to separate the biological entity of interest from other non-target entities.Such “processed samples” may, for example, include extracellular vesicles in some embodiments, while in other embodiments they may include nucleic acids and / or proteins extracted from the sample. In some embodiments, the processed sample can be obtained by subjecting the primary sample to one or more techniques, such as nucleic acid amplification or reverse transcription, isolation and / or purification of certain components, etc.

[0150] Selective or Specific: When the terms “selective” or “specific” are used herein in reference to an active activator, it will be understood by those skilled in the art that the activator identifies a potential target entity, state, or cell. For example, in some embodiments, an activator is described as binding “specifically” to its target if, in the presence of one or more competing alternative targets, it preferentially binds to that target. In many embodiments, specific interaction depends on the presence of specific structural features of the target entity (e.g., epitopes, clefts, binding sites). It should be understood that specificity does not have to be absolute. In some embodiments, specificity can be evaluated by comparing the specificity of the target binding moiety with respect to one or more other potential target entities (e.g., competing factors). In some embodiments, specificity is evaluated by comparing it with the specificity of a reference specific binding moiety. In some embodiments, specificity is evaluated by comparing it with the specificity of a reference nonspecific binding moiety. In some embodiments, the target binding moiety does not detectably bind to a competing alternative target under conditions that it binds to its target entity. In some embodiments, the target-binding moiety binds to its target entity with a higher on-rate, lower off-rate, increased affinity, decreased dissociation, and / or increased stability compared to the competing surrogate target(s).

[0151] Small molecules: As used herein, the term “small molecules” means low molecular weight organic and / or inorganic compounds. Generally, “small molecules” are molecules with a size of less than about 5 kilodaltons (kD). In some embodiments, small molecules are less than about 4 kD, 3 kD, 2 kD, or 1 kD. In some embodiments, small molecules are less than about 800 daltons (D), 600 D, 500 D, 400 D, 300 D, 200 D, or 100 D. In some embodiments, small molecules are less than about 2000 g / mol, 1500 g / mol, 1000 g / mol, 800 g / mol, or 500 g / mol. In some embodiments, small molecules are not polymers. In some embodiments, small molecules do not contain a polymer portion. In some embodiments, small molecules are not proteins or polypeptides (e.g., not oligopeptides or peptides). In some embodiments, the small molecule is not a polynucleotide (e.g., not an oligonucleotide). In some embodiments, the small molecule is not a polysaccharide. In some embodiments, the small molecule does not contain polysaccharides (e.g., not a glycoprotein, proteoglycan, glycolipid, etc.). In some embodiments, the small molecule is not a lipid. In some embodiments, the small molecule is biologically active. In some embodiments, a suitable small molecule is found through screening of a large library of compounds (Beck-Sickinger & Weber (2001) Combinational Strategies in Biology and Chemistry (John Wiley & Sons, Chichester, Sussex); structure-activity relationships by nuclear magnetic resonance (Shuker et al. (1996) "Discovering high-affinity ligands for proteins: SAR by NMR." Science 274:1531-1534); coded self-assembling chemical libraries (Melkko et al. (2004)). "Encoded self-assembling chemical libraries." Nature Biotechnol. 22:568-574); DNA-templated chemistry (Gartner et al. (2004) "DNA-templated organic synthesis and selection of They can be identified by methods such as a library of macrocycles (Science 305:1601-1605); dynamic combinatorial chemistry (Ramstrom & Lehn (2002) "Drug discovery by dynamic combinatorial libraries." Nature Rev. Drug Discov. 1:26-36); tethering (Arkin & Wells (2004) "Small-molecule inhibitors of protein-protein interactions: progressing towards the dream." Nature Rev. Drug Discov. 3:301-317); and speed screening (Muckenschnabel et al. (2004) "SpeedScreen: label-free liquid chromatography-mass spectrometry-based high-throughput screening for the discovery of orphan protein ligands." Anal. Biochem. 324:241-249). In some embodiments, small molecules may have dissociation constants in the nanomolar range with respect to their target.

[0152] Specific Binding: As used herein, the term “specific binding” refers to the ability to identify possible binding partners in an environment in which binding may occur. A target-binding moiety that interacts with a particular target in the presence of other potential targets may be described as “specifically binding” to the target with which it interacts. In some embodiments, specific binding is assessed by detecting or determining the degree of association between the target-binding moiety and its partner; in some embodiments, specific binding is assessed by detecting or determining the degree of dissociation of the target-binding moiety-partner complex; in some embodiments, specific binding is assessed by detecting or determining the ability of the target-binding moiety to compete with alternative interactions between its partner and another entity. In some embodiments, specific binding is assessed by performing such detection or determination over a range of concentrations.

[0153] Cancer Stage: As used herein, the term “cancer stage” refers to a qualitative or quantitative assessment of the level of progression of cancer (e.g., ovarian cancer). In some embodiments, the criteria used to determine the stage of cancer may include, but are not limited to, one or more of the following: whether the cancer is located in the body, tumor size, whether the cancer has spread to lymph nodes, and whether the cancer has spread to one or more different body parts. In some embodiments, cancer may be staged using the AJCC staging system, a classification system developed by the American Joint Committee on Cancer to describe the extent of disease progression in cancer patients, which in part utilizes the TNM scoring system: tumor size, affected lymph nodes, and metastasis. In some embodiments, cancer may be staged using a classification system which in part utilizes the TNM scoring system, according to which T refers to the size and scale of the primary tumor, usually called the primary tumor; N refers to the number of adjacent lymph nodes with cancer; and M refers to whether the cancer has metastasized. In some embodiments, cancer may be referred to as Stage 0 (abnormal cells are present but have not spread to adjacent tissues, also known as carcinoma in situ, or CIS; CIS is not cancer but can become cancerous), Stages I-III (cancer is present; the higher the number, the larger the tumor and the more widely it has spread to adjacent tissues), or Stage IV (cancer has spread to distal parts of the body). In some embodiments, cancer may be designated as a stage selected from the group consisting of in situ (abnormal cells are present but have not spread to adjacent tissues); localized (cancer is confined to the place of origin and shows no signs of spreading); focal (cancer has spread to adjacent lymph nodes, tissues, or organs); distal (cancer has spread to distal parts of the body); and unknown (there is not enough information to determine the stage).

[0154] Subject: As used herein, the term “subject” refers to a living organism from which a sample is taken for experimental, diagnostic, preventive, and / or therapeutic purposes, for example. Typical subjects include animals (e.g., mammals, e.g., mice, rats, rabbits, non-human primates, domestic pets, etc.) and humans. In some embodiments, the subject is a human female subject, e.g., a human adult female subject. In some embodiments, the subject has ovarian cancer. In some embodiments, the subject is susceptible to ovarian cancer. In some embodiments, the subject presents one or more symptoms or features of ovarian cancer. In some embodiments, the subject presents one or more nonspecific symptoms of ovarian cancer. In some embodiments, the subject does not present any symptoms or features of ovarian cancer. In some embodiments, the subject has one or more features characteristic of susceptibility to ovarian cancer or is at risk of ovarian cancer. In some embodiments, the subject is a patient. In some embodiments, the subject is an individual to be administered and / or has previously administered diagnostic and / or therapeutic treatment. In some embodiments, the subjects are female subjects (e.g., adult female subjects) determined to have an adnexal tumor. In some embodiments, the subjects are asymptomatic subjects. Such symptomatic subjects may be female subjects (e.g., adult female subjects) with average population risk or genetic risk. For example, such asymptomatic subjects may have a family history of cancer, have been previously treated for cancer, be at risk for cancer recurrence after cancer treatment, be in remission after cancer treatment, and / or have been previously or periodically screened for the presence of at least one cancer biomarker. Alternatively, in some embodiments, the asymptomatic subjects may be subjects who have never been previously screened for cancer, have never been diagnosed for cancer, and / or have never received cancer treatment. In some embodiments, subjects suitable for the technology provided are individuals selected based on one or more characteristics, e.g., age, race, genetic history, medical history, personal history (e.g., smoking, alcohol, drugs, oncologists, diet, obesity, physical activity, sun exposure, radiation exposure, infectious agents, e.g., exposure to viruses, and / or occupational hazards).

[0155] A person suffering from a disease, disorder, and / or condition is diagnosed with and / or presents with one or more symptoms of the disease, disorder, and / or condition.

[0156] Surface polypeptide or surface protein: As used interchangeably herein, the terms “surface polypeptide,” “surface protein,” and “membrane-bound polypeptide” refer to polypeptides or proteins having one or more domains or regions present on and / or on the surface of the membrane of a biological entity (e.g., a cell, an extracellular vesicle, etc.). In some embodiments, a surface protein may include one or more domains or regions that penetrate and / or associate with the plasma membrane of a biological entity (e.g., a cell, an extracellular vesicle, etc.). In some embodiments, a surface protein may include one or more domains or regions that penetrate and / or associate with the plasma membrane of a biological entity (e.g., a cell, an extracellular vesicle, etc.) and also project into the intracellular and / or intravesicular space. In some embodiments, a surface protein may include one or more domains or regions that associate with the plasma membrane of a biological entity (e.g., a cell, an extracellular vesicle, etc.) via, for example, one or more non-peptide bonds. In some embodiments, a surface protein may include one or more domains or regions anchored to both sides of the plasma membrane of a biological entity (e.g., a cell, an extracellular vesicle, etc.). In some embodiments, surface proteins are associated with or present within extracellular vesicles. In some embodiments, surface polypeptides or membrane-bound polypeptides may be associated with or present within ovarian cancer-associated extracellular vesicles (e.g., extracellular vesicles obtained from or derived from blood or blood-derived samples of subjects who have or are susceptible to ovarian cancer). As will be understood by those skilled in the art, detection of the presence of at least a portion of surface polypeptides or surface proteins on / within extracellular vesicles can facilitate the separation and / or isolation of ovarian cancer-associated extracellular vesicles from biological samples (e.g., blood or blood-derived samples) of subjects. In some embodiments, detection of the presence of surface polypeptides or surface proteins may be or include detection of intravesicular portions (e.g., intravesicular epitopes) of such surface polypeptides or surface proteins.In some embodiments, the detection of the presence of a surface polypeptide or surface protein may be, or include, the detection of a transmembrane portion of such a surface polypeptide or surface protein. In some embodiments, the detection of the presence of a surface polypeptide or surface protein may be, or include, the detection of an extravesicular portion of such a surface polypeptide or surface protein.

[0157] Surface Protein Biomarkers: As used herein, the term “surface protein biomarker” refers to a marker indicating the state (e.g., presence, level, and / or activity) of a surface protein (e.g., as described herein) of a biological entity (e.g., a cell or extracellular vesicle). In some embodiments, a surface protein refers to a polypeptide or protein having one or more domains or regions located on or on the surface of the membrane of a biological entity (e.g., a cell or extracellular vesicle). In some embodiments, a surface protein biomarker may be or include an epitope located on or outside (extracellular) of the membrane. In some embodiments, a surface protein biomarker may be associated with or present within an extracellular vesicle.

[0158] Susceptible to: An individual who is "suspended to" a disease, disorder, and / or condition is an individual whose risk of developing a disease, disorder, and / or condition is higher than that of the general population. In some embodiments, an individual susceptible to a disease, disorder, and / or condition may not have been diagnosed with the disease, disorder, and / or condition. In some embodiments, an individual susceptible to a disease, disorder, and / or condition may exhibit symptoms of the disease, disorder, and / or condition. In some embodiments, an individual susceptible to a disease, disorder, and / or condition may not exhibit symptoms of the disease, disorder, and / or condition. In some embodiments, an individual susceptible to a disease, disorder, and / or condition will develop the disease, disorder, and / or condition. In some embodiments, an individual susceptible to a disease, disorder, and / or condition will not develop the disease, disorder, and / or condition.

[0159] Target-binding moiety: Generally, the terms “target-binding moiety” and “binding moiety” are used interchangeably herein to refer to any entity or portion that binds to a target of interest (e.g., a molecular target of interest, e.g., a biomarker or epitope). In many embodiments, the target-binding moiety of interest specifically binds to its target (e.g., a target biomarker) to distinguish that target from other potential binding partners in a particular interaction context. Generally, the target-binding moiety may be or include an entity or portion of any chemical group (e.g., polymers, nonpolymers, small molecules, polypeptides, carbohydrates, lipids, nucleic acids, etc.). In some embodiments, the target-binding moiety is a single chemical entity. In some embodiments, the target-binding moiety is a complex of two or more distinct chemical entities that associate with each other by non-covalent interactions under relevant conditions. For example, those skilled in the art will see that in some embodiments, the target binding moiety may include a “general” binding moiety that binds to a general binding moiety partner (e.g., a biotin / avidin / streptavidin and / or class-specific antibody portion) and a “specific” binding moiety (e.g., an antibody or aptamer with a specific molecular target). In some embodiments, such an approach may enable a modular assembly of multiple target binding moieties through the binding of various specific binding moieties to general binding moiety partners.

[0160] Targeted Biomarker Signature: The term “targeted biomarker signature,” as used herein, refers to a combination of biomarkers (e.g., at least two or more, including at least three, at least four, at least five, at least six, at least seven, at least eight, at least nine, at least ten, at least 11, at least 12, at least 13, at least four, at least 15, at least 16, at least 17, at least 18, at least 19, at least 20, at least 25, at least 30, or more) that correlate with a particular biological event or condition of interest, and a person skilled in the art will find that this can be appropriately determined to be the “signature” of that event or condition. In some embodiments, a targeted biomarker signature may correlate with a particular disease or condition and / or the likelihood that a particular disease, disorder or condition may occur, be likely to occur, or recur. In some embodiments, a targeted biomarker signature may correlate with a particular disease or treatment outcome, or the likelihood thereof. In some embodiments, the targeted biomarker signature may correlate with a specific cancer and / or its stage. In some embodiments, the targeted biomarker signature may correlate with ovarian cancer and / or its stage and / or subtype. In some embodiments, the targeted biomarker signature includes a combination of biomarkers that together are specific to ovarian cancer or its subtype and / or disease stage (e.g., including at least 3, at least 4, at least 5, at least 6, at least 7, at least 8, at least 9, at least 10, at least 11, at least 12, at least 13, at least 14, at least 15, at least 16, at least 17, at least 18, at least 19, at least 20, at least 25, at least 30, or more, e.g., at least two or more), but one or more biomarkers in such a combination may be directed to targets that are not specific to ovarian cancer (e.g., surface protein biomarkers, intravesical protein biomarkers, and / or intravesical RNA).For example, in some embodiments, the target biomarker signature may include at least one biomarker specific to ovarian cancer or its stage and / or subtype (i.e., an ovarian cancer-specific target), and may further include biomarkers that are not necessarily, or not at all, specific to ovarian cancer (e.g., those found in some or all biological entities, e.g., cells, extracellular vesicles, etc., that are not cancerous, not of the related cancer, and / or not of the specific stage and / or subtype of the target). That is, as those skilled in the art will see by reading this specification, a combination of biomarkers used in a target biomarker signature is a useful target biomarker signature according to certain embodiments of this disclosure, insofar as the combination of biomarkers used together is specific to the target biological entity of interest (e.g., the ovarian cancer cell of interest or extracellular vesicles secreted by the ovarian cancer cell of interest) (i.e., adequately distinguishes the target biological entity for detection (e.g., the ovarian cancer cell of interest or extracellular vesicles secreted by the ovarian cancer cell of interest) from other biological entities that are not the target of detection).

[0161] Therapeutic Agent: As used interchangeably herein, the terms “therapeutic agent” or “treatment” refer to a substance or intervention that, when administered to a subject or patient, has a therapeutic effect and / or induces a desired biological and / or pharmacological effect. In some embodiments, a therapeutic agent or treatment is any substance that can be used to alleviate, remit, reduce, inhibit, prevent, delay the onset of, reduce the severity of, and / or reduce the incidence of one or more symptoms or characteristics of a disease, disorder, and / or condition. In some embodiments, a therapeutic agent or treatment is a medical intervention (e.g., surgery, radiation, phototherapy) that can be performed to alleviate, reduce, inhibit, present, delay the onset of, reduce the severity of, and / or reduce the incidence of one or more symptoms or characteristics of a disease, disorder, and / or condition.

[0162] Threshold Level (e.g., Cutoff): As used herein, the term “threshold level” refers to a level used as a criterion for obtaining information about the results of a measurement, e.g., the measurement results obtained in an assay, and / or for classification. For example, in some embodiments, the threshold level (e.g., cutoff) means a value measured in an assay that defines a boundary between two subsets of a population (e.g., normal and / or non-ovarian cancer versus ovarian cancer). Thus, a value greater than or equal to the threshold level defines one subset of the population, and a value less than the threshold level defines the other subset of the population. The threshold level can be determined based on one or more control samples, or across a population of control samples. The threshold level can be determined before, simultaneously with, or after performing the measurement of interest. In some embodiments, the threshold level may be a range of values.

[0163] To treat: As used herein, the terms “to treat,” “treatment,” or “to treat” refer to any method used to partially or completely alleviate, remit, reduce, inhibit, prevent, delay the onset of, reduce the severity of, and / or reduce the incidence of one or more symptoms or features of a disease, disorder, and / or condition. Treatment may be administered to subjects who are not showing signs of a disease, disorder, and / or condition. In some embodiments, treatment may be administered to subjects showing only early signs of a disease, disorder, and / or condition, for example, to reduce the risk of developing a condition associated with the disease, disorder, and / or condition. In some embodiments, treatment may be administered to subjects in a later stage of a disease, disorder, and / or condition.

[0164] Standard techniques can be used for recombinant DNA, oligonucleotide synthesis, and tissue culture and transformation (e.g., electroporation, lipofection). Enzymatic reactions and purification techniques can be carried out according to the manufacturer's specifications, as commonly achieved in the art, or as described herein. The techniques and procedures described above can generally be carried out according to conventional methods well known in the art and as described in various general and more specific references cited and discussed herein. For example, see Sambrook et al., Molecular Cloning: A Laboratory Manual (2nd ed., Cold Spring Harbor Laboratory Press, Cold Spring Harbor, NY (1989)), which is incorporated herein by reference for the purposes described herein.

[0165] Ovarian cancer was the cause of an estimated 14,070 deaths in the United States in 2018 (Torre et al., 2018; incorporated herein by reference for the purposes described herein). The majority of these deaths can be attributed to delayed diagnosis; ovarian cancer has an estimated 93% 5-year survival rate if detected at its earliest stage, compared to 26% if detected at its latest stage (Torre et al., 2018; incorporated herein by reference for the purposes described herein). Detection of high-grade serous ovarian cancer (HGSOC) is particularly important, given that HGSOC accounts for 70%–80% of all ovarian cancer deaths, while other subtypes grow more slowly and are prone to overdiagnosis with current technology (Temkin et al., 2017; incorporated herein by reference for the purposes described herein). Unfortunately, despite being the fifth leading cause of death among women from all cancers (Howlader et al., 2019; incorporated herein by reference for the purposes described herein), there is no recommended screening test for women at average risk of ovarian cancer. Many women who have a genetic risk and / or may be experiencing one or more symptoms of ovarian cancer (e.g., intraperitoneal fluid (ascites), general gastrointestinal dysfunction, constipation, bowel obstruction, nausea, vomiting, diarrhea, gastrointestinal reflux, increased waist circumference, urinary symptoms, abdominal distension, abdominal and / or pelvic pain, fatigue, and / or shortness of breath) are currently screened by serum CA-125 and / or transvaginal ultrasonography (TVUS), but these tests are suboptimal for screening because they have low sensitivity (about 20%) and insufficient specificity for stage I and II disease. For example, randomized screening trials for prostate, lung, colorectal, and ovarian cancer have identified serum CA-125, and TVUS increases the number of unnecessary surgeries and does not provide a mortality benefit for women at average risk (Buys et al., 2011; incorporated herein by reference for the purposes described herein).Despite these shortcomings, serum CA-125 and TVUS are currently common screening tools for postmenopausal women with nonspecific pelvic pain that may potentially indicate ovarian cancer.

[0166] This disclosure particularly identifies the causes of problems in several prior art, including, for example, several conventional approaches for detecting and diagnosing ovarian cancer. For example, this disclosure recognizes that many conventional diagnostic assays based on bulk analysis of, for example, cell-non-cellular nucleic acids, serum proteins (e.g., CA-125), and / or extracellular vesicles can be time-consuming, costly, and / or may not have sufficient sensitivity and / or specificity to obtain a reliable and comprehensive diagnostic assessment. In some embodiments, this disclosure provides techniques (including systems, compositions, and methods) to solve such problems by identifying biomarker combinations that are predicted to show high sensitivity and specificity for ovarian cancer, particularly based on bioinformatics analysis. In some embodiments, the Disclosure provides techniques (including systems, compositions, and methods) to solve such problems by detecting the colocalization of ovarian cancer target biomarker signatures (e.g., those identified by bioinformatics analysis) in individual extracellular vesicles, comprising at least one extracellular vesicle-associated membrane-bound polypeptide and at least one target biomarker selected from the group consisting of surface protein biomarkers, internal protein biomarkers, and RNA biomarkers present in extracellular vesicles associated with ovarian cancer. In some embodiments, the Disclosure provides techniques (including systems, compositions, and methods) to solve such problems by detecting such target biomarker signatures of ovarian cancer using target entity detection approaches developed by the Applicant and filed both February 28, 2020, in U.S. Patent Application No. 16 / 805,637 and International Application PCT / US2020 / 020529, both titled “Systems, Compositions, and Methods for Detecting Target Entities,” particularly based on the interaction and / or colocalization of target biomarker signatures in individual extracellular vesicles. The contents of each of the above disclosures are incorporated herein by reference in their entirety.

[0167] This disclosure provides insights and techniques, in particular, for achieving effective ovarian cancer screening, for example, for early detection of ovarian cancer. In some embodiments, this disclosure provides techniques for early detection of ovarian cancer in women who may be experiencing one or more symptoms associated with ovarian cancer. In some embodiments, this disclosure provides techniques for early detection of ovarian cancer in women who have a genetic risk for ovarian cancer. In some embodiments, this disclosure provides techniques for early detection of ovarian cancer in postmenopausal women who may have a genetic risk and / or may be experiencing one or more symptoms associated with ovarian cancer. In some embodiments, this disclosure provides techniques for screening women who have a genetic or average risk for early-stage high-grade serous ovarian cancer (HGSOC). HGSOC is the most common and deadly subtype of ovarian cancer, in which 84% of cases are detected at an advanced stage (Torre et al., 2018, incorporated herein by reference for the purposes described herein). In some embodiments, the techniques provided are effective for the detection of early-stage ovarian cancer. In some embodiments, the provided technology is effective even when applied to a population that includes or consists of asymptomatic or symptomatic individuals (e.g., with sufficiently high sensitivity and / or a low probability of false positive and / or false negative results). In some embodiments, the provided technology is effective when applied to a population that includes or consists of individuals that do not have a genetic risk of developing ovarian cancer (e.g., asymptomatic or symptomatic individuals). In some embodiments, the provided technology is effective when applied to a population that includes or consists of individuals that have a genetic risk of developing ovarian cancer (e.g., asymptomatic or symptomatic individuals). In some embodiments, the provided technology is effective when applied to a population that includes or consists of individuals that are susceptible to ovarian cancer (e.g., individuals with known genetic, environmental, or empirical risks).In some embodiments, as will be obvious to those skilled in the art by reading the disclosures provided herein, the provided technology may be or may include one or more compositions (e.g., molecular complexes, systems, collections, combinations, kits, etc.) and / or methods (e.g., methods for manufacturing, using, evaluating, etc.).

[0168] In some embodiments, the provided technology achieves detection of one or more features of ovarian cancer (e.g., onset, progression, response to treatment, recurrence, etc.) (e.g., early detection in asymptomatic individuals and / or populations) with appropriate sensitivity and / or specificity (e.g., rate of false positives and / or false negatives) that allows for useful application of the provided technology to single and / or periodic (e.g., periodic) evaluations of the provided technology. In some embodiments, the provided technology is useful in conjunction with periodic physical examinations of women, such as mammography, HPV, and / or Pap smear screening. In some embodiments, the provided technology is useful in conjunction with one or more screening methods (e.g., for ovarian cancer), such as CA-125 measurement (e.g., CA-125 serum level measurement) and / or TVUS. In some embodiments, the provided technology is useful in conjunction with treatment regimens; in some embodiments, the provided technology may improve one or more features (e.g., success rate by acceptable parameters) of such treatment regimens.

[0169] In some embodiments, the disclosure provides insight that screening of asymptomatic individuals before the onset of symptoms, or otherwise in the absence of symptoms, e.g., routine screening, may be advantageous and may also be important for the effective management of ovarian cancer (e.g., successful treatment). In some embodiments, the disclosure provides an ovarian cancer screening system that can be implemented to detect ovarian cancer, including early-stage cancer, in asymptomatic individuals (e.g., those without a genetic risk for ovarian cancer). In some embodiments, the provided technology is implemented to achieve routine screening of asymptomatic individuals (e.g., those with or without a genetic risk for ovarian cancer). In some embodiments, the provided technology is implemented to achieve routine screening of symptomatic individuals (e.g., those with or without a genetic risk for ovarian cancer). The disclosure provides, for example, compositions (e.g., reagents, kits, components, etc.) and methods for providing and / or using them, including strategies that involve routine examination of one or more individuals (e.g., asymptomatic individuals). This disclosure defines the usefulness of such systems and provides compositions and methods for implementing them.

[0170] I. Detection of ovarian cancer Currently, there are no FDA-approved ovarian cancer screening tests for asymptomatic women at average risk. However, in the United States, the average lifetime risk of developing ovarian cancer is 1.3%, or 1 in 78 women. The overall ovarian cancer prevalence in the United States was 5.7 per 10,000 women aged 55–74 years (Buys et al., 2011; incorporated herein by reference for the purposes described herein). In 2018, there were approximately 22,240 new cases of ovarian cancer diagnosed and 14,070 deaths from ovarian cancer in the United States (Torre et al., 2018; incorporated herein by reference for the purposes described herein). In particular, age and menopausal status have been identified as risk factors for ovarian cancer, with an average age of initial manifestation of approximately 68 years.

[0171] Epithelial ovarian cancer subtypes account for 90% of all ovarian cancers. Epithelial carcinomas are classified as serous (52%), endometrioid (10%), mucinous (6%), or clear cell (6%) (Torre et al., 2018; incorporated herein by reference for the purposes described herein). Many serous carcinomas are diagnosed at stage III (51%) or stage IV (29%), at which point the 5-year survival rates are 42% and 26%, respectively, highlighting the need for early staging screening. Germ cell and sex cord-stromal tumors constitute the majority of non-epithelial carcinomas, but account for only 3% and 2% of all ovarian cancers, respectively. Ovarian cancer affects women of all ethnicities.

[0172] A more significant risk factor for ovarian cancer is a family history of breast or ovarian cancer. The risk of developing invasive epithelial ovarian cancer is approximately 50% higher in women with a first-degree relative with a history of ovarian cancer, and 10% higher in women with a first-degree relative with breast cancer. Approximately 18% of epithelial ovarian cancer cases, particularly high-grade serous carcinoma, are estimated to be due to hereditary mutations that increase the risk. BRCA1 and BRCA2 mutations account for approximately 40% of ovarian cancer cases in women with a family history of the disease. Women with BRCA1 or BRCA2 mutations have a 44% and 17% risk, respectively, of developing ovarian cancer by age 80. For example, as described in Matulonis et al., 2016 (incorporated herein by reference for the purposes described herein), rare moderate penetrant gene mutations in epithelial ovarian cancer include genes involved in the Fanconi anemia / BRCA pathway, such as PALB2, BARD1, BRIP1, RAD51C, and RAD51D. Families with Lynch syndrome are characterized by germline mutations in DNA mismatch repair genes (e.g., MLH1, MSH2, MSH6, or PMS2). Women with Lynch syndrome have approximately 8% risk of developing ovarian cancer (usually non-serous epithelial tumors) by age 70, compared to 0.7% in the general population (Torre, et al., 2018; incorporated herein by reference for the purposes described herein). Hereditary mutations in other genes involved in DNA repair, such as CHEK2, MRE11A, RAD50, ATM, and TP53, may also increase the risk of developing ovarian cancer. As suggested by genome-wide association studies, additional common low-penetration alleles may also be associated with epithelial ovarian cancer susceptibility.Such genes and loci include WNT4, RSPO1, BCL2L11, HOXD3, HAGLR, TIPARP, SYNPO2, TERT, GPX6, CHMP4C, LINC00824, COL15A1, SMC2-AS1, MLLT10, INCENP, RCCD1, ATAD5, HNF1B, PLEKHM1, SKAP1, ANKLE1, GATAD2A, Cytobands, and SNPs 2q13 rs752590, 4q32.3 rs4691139, 9p22 rs3814113, 9q34.2 rs635634, 10p11.21 rs1192691, and / or 19q13.2 rs688187 (Reid et al., 2017; incorporated herein by reference for the purposes described herein).

[0173] The number of relatively young women identified as having a genetic risk is projected to increase year by year. The NCCN guidelines for pancreatic cancer were updated in December 2019 to include a recommendation to test all patients for germline mutations in ATM, BRCA1, BRCA2, CDKN2A, MSH2, MLH1, MSH2, EPCAM, PALB2, STK11, and TP53. Given that this gene list overlaps with the genes that carry a genetic risk for ovarian cancer, it is likely that more daughters of pancreatic cancer patients will become aware of their own genetic risk for both pancreatic and ovarian cancer, and they will move from a general risk category to a genetic risk category. In addition, recent cost-effectiveness studies in breast cancer patients have concluded that screening all breast cancer patients in the United States and the United Kingdom for germline mutations in BRCA1 and / or BRCA2 and PALB2 is cost-effective (Sun, et al., 2019; incorporated herein by reference for the purposes described herein). Introducing germline genetic testing into guidelines for all women with breast cancer would identify additional risk mutation carriers whose daughters also carry a genetic risk for breast and ovarian cancer. Currently, there are no recommended screening tests for ovarian cancer in women (e.g., those without genetic risk). In particular, in certain embodiments, this disclosure provides the insight that there is a need for the development of an ovarian cancer liquid biopsy assay (e.g., as described herein) that can be used to obtain an ovarian cancer risk assessment. In certain embodiments, the assay and / or techniques described herein may provide a score with respect to a reference threshold (e.g., as described herein). In certain embodiments, such a score may be or include an ovarian cancer risk score. In some embodiments, such a score may be used in conjunction with other ovarian cancer screening assessments (may include, but are not limited to, CA-125 measurement (e.g., CA-125 serum level measurement and / or TVUS) and / or ovarian cancer-related risk factors) to obtain an overall assessment.

[0174] The Prostate, Lung, Colorectal, and Ovarian Cancer Screening Trial (PLCO), which evaluated the use of transvaginal ultrasonography (TVUS) and a fixed cutpoint (≥35 U / mL) for the tumor marker CA-125 for early detection, did not observe a reduction in ovarian cancer mortality after 19 years of follow-up. The UK Collaborative Trial of Ovarian Cancer Screening evaluated TVUS in combination with a risk algorithm incorporating changes in CA-125 levels and found a reduction in mortality in women at average risk after 15 years. Contrary to this, the US Preventive Services Task Force (USPSTF) continues to recommend against screening for ovarian cancer in the general population, concluding that there is sufficient evidence that annual screening does not reduce ovarian cancer mortality and can lead to significant harm, primarily surgical intervention in women without ovarian cancer.

[0175] In particular, in certain embodiments, the disclosure provides the insight that there is a need for the development of ovarian cancer liquid biopsy assays to screen women who have a genetic risk for ovarian cancer and / or who may be experiencing one or more symptoms associated with ovarian cancer. In certain embodiments, the disclosure provides the insight that there is a need for the development of ovarian cancer liquid biopsy assays to screen symptomatic or asymptomatic women, for example, before other screening methods, such as TVUS. In certain embodiments, the disclosure provides the insight that there is a need for the development of ovarian cancer liquid biopsy assays to screen asymptomatic women, for example, before other screening methods, such as TVUS. In certain embodiments, the disclosure provides the insight that there is a need for the development of ovarian cancer liquid biopsy assays to screen women who have an average risk for ovarian cancer. In certain embodiments, the disclosure provides the insight that there is a need for the development of ovarian cancer liquid biopsy assays to screen women who have a lifestyle-related risk for ovarian cancer. In certain embodiments, this disclosure provides insight that there is a need for the development of an ovarian cancer liquid biopsy assay to screen postmenopausal women, for example, postmenopausal women who may be experiencing one or more symptoms associated with ovarian cancer. Despite being the fifth leading cause of death among women from all cancers (Howlader et al., 2019; incorporated herein by reference for the purposes described herein), there is currently no recommended screening tool for women at average risk, and current standard treatment screening assays for stage 1 and II disease in women with genetic risk and / or who may be experiencing symptoms of ovarian cancer (e.g., TVUS and serum marker CA-125 levels) exhibit low sensitivity (approximately 20%) and low specificity (NCCN, 2019; Buys et al., 2011; incorporated herein by reference for the purposes described herein). These low rates of sensitivity and specificity pose a barrier to efficient and timely diagnosis.Given the incidence of ovarian cancer in women at average risk, insufficient test specificity (e.g., <99.5%) results in false positives far exceeding the number of true positives by more than an order of magnitude. This places a considerable burden on healthcare systems and on women screened for false positives, leading to additional tests, unnecessary surgery, and emotional / physical distress (Buys et al., 2011; incorporated herein by reference for the purposes described herein).

[0176] In some embodiments, this disclosure provides the insight that particularly useful ovarian cancer screening tests may be characterized by (1) extremely high specificity (>98%) that minimizes the number of false positives and (2) high sensitivity (>40%) for stage I and II ovarian cancer (i.e., when the prognosis is most favorable). For example, in some embodiments, a particularly useful ovarian cancer screening test may be characterized by, for example, >98% specificity and >50% sensitivity for stage I and II ovarian cancer. In some embodiments, a particularly useful ovarian cancer screening test may be characterized by, for example, >98% specificity and >60% sensitivity for stage I and II ovarian cancer. In some embodiments, a particularly useful ovarian cancer screening test may be characterized by, for example, >98% specificity and >70% sensitivity for stage I and II ovarian cancer. In some embodiments, a particularly useful ovarian cancer screening test may be characterized by, for example, >99.5% specificity and >65% sensitivity for stage I and II ovarian cancer. In some embodiments, particularly useful ovarian cancer screening tests may be characterized, for example, by >99.5% specificity and >60% sensitivity for stage I and II ovarian cancer.

[0177] In some embodiments, this disclosure provides the insight that an ovarian cancer screening test comprising more than one set of biomarker combinations (e.g., at least two orthogonal biomarker combinations as described herein) may increase the sensitivity of such assays compared to the sensitivity achieved by one set of biomarker combinations. For example, in some embodiments, an ovarian cancer screening test comprising at least two orthogonal biomarker combinations may achieve at least 98% specificity and at least 50% sensitivity. In some embodiments, an ovarian cancer screening test comprising at least two orthogonal biomarker combinations may achieve at least 98% specificity and at least 60% sensitivity.

[0178] In some embodiments, this disclosure provides the insight that particularly useful ovarian cancer screening tests may be characterized by a positive predictive value (PPV) that is acceptable at an economically justifiable cost. PPV is the likelihood that a patient will have the disease after a positive test and is influenced by susceptibility, specificity, and / or disease prevalence. One clinician consensus on the minimum PPV required to screen for ovarian cancer is 10% (Nossov). (Buys et al., 2008; incorporated herein by reference for the purposes described herein). In a 10% PPV, there would be nine false positives for every one true positive. These false positives pose a considerable burden to the healthcare system and to both the false positive results and the screened women, as they lead to additional tests, unnecessary surgery, and emotional and physical distress (Buys et al., 2011; incorporated herein by reference for the purposes described herein). In some embodiments, the assays described herein are particularly useful for early ovarian cancer detection, achieving PPVs of 10% or higher, including, for example, greater than 15%, greater than 20%, or 25% or higher, with a specificity cutoff of at least 98% in women with a genetic risk for ovarian cancer, or at least 99.5% in women experiencing one or more symptoms associated with ovarian cancer.

[0179] In some embodiments, the assays described herein may be useful for early ovarian cancer detection achieving PPV of more than 2% or more, including, for example, more than 3%, more than 4%, more than 5%, more than 6%, more than 7%, more than 8%, more than 9%, more than 10%, more than 15%, more than 20%, or more than 25% or more. In some such embodiments, the assays described herein may achieve a specificity cutoff of at least 95% or more (for example, at least a specificity cutoff of 98% in women with a genetic risk for ovarian cancer, or at least a specificity cutoff of 99.5% in women experiencing one or more symptoms associated with ovarian cancer).

[0180] Several different biomarker classes, including circulating tumor DNA (ctDNA), circulating tumor cells (CTCs), bulk proteins, and extracellular vesicles (EVs), have been studied for ovarian cancer liquid biopsy assays. EVs are particularly promising compared to ctDNA and CTCs due to their abundance and stability in the bloodstream, suggesting improved sensitivity for early-stage cancers. Furthermore, EVs contain cargo (e.g., proteins, RNA, metabolites) derived from the same cells, resulting in superior specificity compared to bulk protein measurements. While the diagnostic utility of EVs has been studied, much of this research concerns bulk EV measurement or low-throughput single EV analysis.

[0181] II. Biomarkers and / or targeted biomarker signatures provided for the detection of ovarian cancer This disclosure provides, in particular, various target biomarkers or combinations thereof for ovarian cancer (e.g., target biomarker signatures). Such target biomarker signatures, which are predicted to show high sensitivity and specificity for ovarian cancer, have been discovered by multidirectional bioinformatics analysis and biological approaches, which, for example, in some embodiments, include computational analysis of a diverse set of data, including, for example, sequencing data, expression data, mass spectrometry, histology, post-translational modification data, and / or in vitro and / or in vivo experimental data, via machine learning and / or computational modeling.

[0182] In some embodiments, the ovarian cancer target biomarker signature comprises at least one (e.g., 1, 2, 3, 4, 5, 6, 7, 8, or more) extracellular vesicle-associated membrane-bound polypeptides (e.g., surface polypeptides present in extracellular vesicles associated with ovarian cancer) and at least one (e.g., 1, 2, 3, 4, 5, 6, 7, 8, or more) selected from the group consisting of surface protein biomarkers, intravesicular protein biomarkers, and intravesicular RNA biomarkers. The combination of such extracellular vesicle-associated membrane-bound polypeptides (plural) and such target biomarkers (plural) is thus designed to represent a target biomarker signature for ovarian cancer that results in (a) high specificity (e.g., greater than 98% or higher, such as greater than 99% or greater than 99.5%) to minimize the number of false positives, and (b) high sensitivity (e.g., greater than 40%, greater than 50%, greater than 60%, greater than 70%, greater than 80%) for stage I and II ovarian cancer, when the prognosis is most favorable. In some embodiments, the ovarian cancer target biomarker signature comprises at least one extracellular vesicle-associated membrane-bound polypeptide (e.g., a surface polypeptide present in extracellular vesicles associated with ovarian cancer) and at least one target biomarker selected from the group consisting of surface protein biomarkers, intravesicular protein biomarkers, and intravesicular RNA biomarkers, such that the combination of such extracellular vesicle-associated membrane-bound polypeptides and such target biomarkers represents the ovarian cancer target biomarker signature that provides a positive predictive value (PPV) of at least 15% or more, at least 20% or more, at least 25% or more, and / or at least 30% or more.In some embodiments, the ovarian cancer target biomarker signature comprises at least one extracellular vesicle-associated membrane-bound polypeptide (e.g., a surface polypeptide present in extracellular vesicles associated with ovarian cancer) and at least one target biomarker selected from the group consisting of surface protein biomarkers, intravesicular protein biomarkers, and intravesicular RNA biomarkers, such that the combination of such extracellular vesicle-associated membrane-bound polypeptides and such target biomarkers results in a 2% or greater positive predictive value (PPV), including, for example, greater than 3%, greater than 5%, greater than 7%, greater than 10%, greater than 15% or more, greater than 20% or more, greater than 25% or more, and / or greater than 30% or more.

[0183] In some embodiments, this disclosure acknowledges that in certain embodiments, sensitivity and specificity in women with varying ovarian risk levels may vary depending on the risk tolerance guidelines outlined by the attending physician and / or the medical association. In certain embodiments, women with a genetic risk of ovarian cancer may be best managed with 99.5% specificity and 70% sensitivity, or with 98% specificity and 80% sensitivity. In certain embodiments, postmenopausal non-symptomatic women may be best managed with 99.5% specificity and 70% sensitivity, or with 98% specificity and 80% sensitivity. In certain embodiments, postmenopausal symptomatic women may be best managed with 99.5% specificity and 70% sensitivity, or with 98% specificity and 80% sensitivity. In certain embodiments, women with a lifestyle risk may be best managed with 99.5% specificity and 70% sensitivity, or with 98% specificity and 80% sensitivity. In some embodiments, the techniques and / or assays described herein for detecting ovarian cancer in symptomatic women may have lower sensitivity and / or specificity requirements than the techniques and / or assays described herein for detecting ovarian cancer in asymptomatic women. In some embodiments, the assays described herein for detecting ovarian cancer in symptomatic women may have a set specificity of less than 99.5%, including, for example, a sensitivity of less than 99%, a specificity of less than 95%, a specificity of less than 90%, or a specificity of less than 85%. In some embodiments, the assays described herein for detecting ovarian cancer in symptomatic women may have a set sensitivity of less than 80%, including, for example, a sensitivity of less than 70% or a sensitivity of less than 60%.

[0184] In some embodiments, the extracellular vesicle-associated membrane-bound polypeptide(SPC)(or polypeptides) included in the ovarian cancer target biomarker signature may be aquaporin-5 (AQP5) polypeptide, cadherin-6 (CDH6) polypeptide, chondrolectin (CHODL) polypeptide, claudin-3 (CLDN3) polypeptide, claudin-6 (CLDN6) polypeptide, claudin-16 (CLDN16) polypeptide, epithelial cell adhesion molecule (EpCAM), folate receptor alpha (FOLR1) polypeptide, and 5-hydroxytryptamine receptor 3A (HTR3A) polypeptide, LEM domain-containing 1 (LEMD1) polypeptide, leucine-rich repeat transmembrane neuron protein 1 (LRRTM1) polypeptide, mucin-16 (MUC16) polypeptide, sodium-dependent phosphate transport protein 2B (SLC34A2) polypeptide, alkaline phosphatase (ALPL) polypeptide, bone marrow stromal cell antigen 2 (BST2) polypeptide, small cell lung cancer cluster 4 antigen (CD24) polypeptide, mesothelin (MSLN) polypeptide, mucin-1 (MUC1) polypeptide, pros Taglandin-endoperoxide synthase 1 (PTGS1) polypeptide, ST14 transmembrane serine protease matryptase (ST14) polypeptide, cancer-related sialyl-Thompsen-nouvelle (Tn)(sTn) polypeptide glycosylation, tumor-related calcium signaling transducer 2 (TACSTD2) polypeptide, basal cell adhesion molecule (BCAM) polypeptide, CD74 antigen (CD74) polypeptide, lymphocyte antigen 6 family member E (LY6E) polypeptide, solute transporter family 2 member 1 (SLC2A1) polypeptide, CXC motif chemokine receptor 4 (CXCR4) polypeptide, discoidin domain receptor tyrosine kinase 1 (DDR1) polypeptide, ephrin B1 (EFNB1) polypeptide, Notch receptor 3 (NOTCH3) polypeptide, plexin B1 (PLXNB1) polypeptide, serine peptidase inhibitor Knitz type 2 (SPINT2) polypeptide, TNF receptor superfamily member 12A (TNFRSF12A) polypeptide, or a combination thereof, or comprising the above.

[0185] In some embodiments, the target biomarkers included in the ovarian cancer target biomarker signature are aquaporin-5 (AQP5) polypeptide, cadherin-6 (CDH6) polypeptide, chondrolectin (CHODL) polypeptide, claudin-3 (CLDN3) polypeptide, claudin-6 (CLDN6) polypeptide, claudin-16 (CLDN16) polypeptide, epithelial cell adhesion molecule (EpCAM), folate receptor 1 (FOLR1) polypeptide, and 5-hydroxytryptamine receptor 3A (HTR3A) polypeptide. LEM domain-containing 1 (LEMD1) polypeptide, leucine-rich repeat transmembrane neuron protein 1 (LRRTM1) polypeptide, mucin-16 (MUC16) polypeptide, sodium-dependent phosphate transport protein 2B (SLC34A2) polypeptide, alkaline phosphatase (ALPL) polypeptide, bone marrow stromal cell antigen 2 (BST2) polypeptide, small cell lung cancer cluster 4 antigen (CD24) polypeptide, mesothelin (MSLN) polypeptide, mucin-1 (MUC1) polypeptide, prostaglandin-endothelial polypeptide Luoxide synthase 1 (PTGS1) polypeptide, ST14 transmembrane serine protease matryptase (ST14) polypeptide, cancer-related sialyl-Tn (sTn) polypeptide glycosylation, tumor-related calcium signaling transducer 2 (TACSTD2) polypeptide, basal cell adhesion molecule (BCAM) polypeptide, CD74 antigen (CD74) polypeptide, lymphocyte antigen 6 family member E (LY6E) polypeptide, solute transporter family 2 member 1 (SLC2A1) polypeptide, CXC motif chemokine receptor A surface protein biomarker selected from the group consisting of CXCR4 polypeptide, discoidin domain receptor tyrosine kinase 1 (DDR1) polypeptide, ephrin B1 (EFNB1) polypeptide, Notch receptor 3 (NOTCH3) polypeptide, plexin B1 (PLXNB1) polypeptide, serine peptidase inhibitor Knitz type 2 (SPINT2) polypeptide, TNF receptor superfamily member 12A (TNFRSF12A) polypeptide, or a combination thereof, or comprising such a biomarker.

[0186] In some embodiments, the extracellular vesicle-associated membrane-bound polypeptide(PPC) included in the ovarian cancer target biomarker signature may be aquaporin-5 (AQP5) polypeptide, cadherin-6 (CDH6) polypeptide, chondrolectin (CHODL) polypeptide, claudin-3 (CLDN3) polypeptide, claudin-6 (CLDN6) polypeptide, claudin-16 (CLDN16) polypeptide, epithelial cell adhesion molecule (EpCAM), folate receptor alpha (FOLR1) polypeptide, 5-hydroxytryptamine receptor 3A (HTR3A) polypeptide, LEM domain-containing 1 (LEMD1) polypeptide, leucine-rich repeat transmembrane neuron protein 1 (LRRTM1) polypeptide, mucin-16 (MUC16) polypeptide, sodium-dependent phosphate transport protein 2B (SLC34A2) polypeptide, or a combination thereof, or including such polypeptide.

[0187] In some embodiments, the target biomarker signature may include combinations of targets as listed in Table 1, in which case the targets can be used with the capture probe and / or detection probe. In some embodiments, the target biomarker signature may include the capture probe targets as listed in Table 1 and at least one or more (e.g., at least two or more) targets of the detection probe (e.g., detection probe 1 and / or detection probe 2). For example, in some embodiments, the target biomarker signature may include ALPL (the capture probe target listed in Table 1), sTn (the detection probe 1 or 2 target listed in Table 1), and FOLR1 (the detection probe 1 or 2 target listed in Table 1). In some embodiments, the target biomarker signature may include combinations of targets for the capture and detection probes as listed in Table 1. [Table 1-1] [Table 1-2] [Table 1-3] [Table 1-4] [Table 1-5] [Table 1-6]

[0188] In some embodiments, certain biomarker combinations, as shown in Table 1, which may be particularly useful for detecting ovarian cancer (e.g., with higher sensitivity, specificity, and / or PPV), can be applied to the initial round of screening using a pool of advanced-stage (e.g., late-stage, e.g., stage III and / or IV) ovarian cancer samples and a pool of healthy control samples as a baseline. In some embodiments, the selected combinations can be further tested using a pool of early-stage ovarian cancer samples (e.g., optionally, stage I and / or II identified by low or high CA-125 content), a pool of benign gynecological tumor plasma samples (e.g., as described herein), a pool of non-ovarian cancer samples (e.g., as described herein), and / or any combination thereof. In some embodiments, the performance of the biomarker combination can be determined by calculating the difference in assay signals (e.g., on a Ct basis) between the healthy sample pool and the ovarian cancer sample pool.

[0189] In some embodiments, certain biomarker combinations for ovarian cancer detection can be selected based on a delta Ct higher than the inter-assay variability. For example, in some embodiments, biomarker combinations with a delta Ct higher than 2.0 (corresponding to a 4-fold difference) or 1.0 (corresponding to a 2-fold difference) are deemed to provide particularly effective diagnostic utility (e.g., a signal higher than the inter-assay variability). See, for example, Example 7, which provides an exemplary analysis of a particular combination described herein.

[0190] In some embodiments, the target biomarker included in the ovarian cancer target biomarker signature is an intravesical protein biomarker selected from the group consisting of intracellular retinoic acid-binding protein 2 (CRABP2) polypeptide, kallikrein-7 (KLK7) polypeptide, macrophage migration inhibitory factor (MIF) polypeptide, melanoma preferential expression antigen (PRAME) polypeptide, S100 calcium-binding protein A1 (S100A1) polypeptide, and combinations thereof, or includes such biomarkers.

[0191] In some embodiments, the target biomarker included in the ovarian cancer target biomarker signature is an intravesicular RNA (e.g., mRNA) biomarker selected from the group consisting of CLDN6 RNA, CRABP2 RNA, KLK7 RNA, MIF RNA, PRAME RNA, S100A1 RNA, and combinations thereof, or includes such biomarker.

[0192] In some embodiments, the targeted biomarker signature for ovarian cancer comprises at least one (e.g., 1, 2, 3, 4, 5, 6, 7, 8, or more) extracellular vesicle-associated membrane-binding polypeptides (e.g., those described herein) and at least one (e.g., 1, 2, 3, 4, 5, 6, 7, 8, or more) surface protein biomarkers (e.g., those described herein). In some such embodiments, the extracellular vesicle-associated membrane-binding polypeptides and the at least one surface protein biomarker are the same. For example, in some embodiments, the targeted biomarker signature for ovarian cancer comprises at least one extracellular vesicle-associated membrane-binding polypeptide that is a MUC16 polypeptide and at least one surface protein biomarker that is a MUC16 polypeptide. In some embodiments, the targeted biomarker signature for ovarian cancer comprises at least one extracellular vesicle-associated membrane-binding polypeptide that is a FOLR1 polypeptide and at least one surface protein biomarker that is a FOLR1 polypeptide.

[0193] In some embodiments, the target biomarker signature for ovarian cancer is distinct from at least one extracellular vesicle-associated membrane-bound polypeptide and at least one surface protein biomarker. For example, in some embodiments, the target biomarker signature for ovarian cancer comprises at least one extracellular vesicle-associated membrane-bound polypeptide that is or contains FOLR1 polypeptide, and at least one surface protein biomarker that is or contains CLDN3 polypeptide, CLDN6 polypeptide, and / or SLC34A2 polypeptide. In some embodiments, the target biomarker signature for ovarian cancer comprises at least one extracellular vesicle-associated membrane-bound polypeptide that is or contains MUC16 polypeptide, and at least one surface protein biomarker that is or contains CLDN3 polypeptide, CLDN6 polypeptide, and / or FOLR1 polypeptide. In some embodiments, the target biomarker signature for ovarian cancer comprises the SLC34A2 polypeptide or at least one extracellular vesicle-associated membrane-binding polypeptide containing it, and the MUC16 polypeptide and / or the FOLR1 polypeptide or at least one surface protein biomarker containing it. In some embodiments, the target biomarker signature for ovarian cancer comprises the LRRTM1 polypeptide or at least one extracellular vesicle-associated membrane-binding polypeptide containing it, and the MUC16 polypeptide or at least one surface protein biomarker containing it.

[0194] In some embodiments, a targeted biomarker signature for ovarian cancer comprises at least one (e.g., 1, 2, 3, 4, 5, 6, 7, 8, or more) extracellular vesicle-associated membrane-binding polypeptides (e.g., those described herein) and at least one (e.g., 1, 2, 3, 4, 5, 6, 7, 8, or more) intravesicular protein biomarkers (e.g., those described herein). In some such embodiments, the extracellular vesicle-associated membrane-binding polypeptides and the intravesicular protein biomarkers may be encoded by the same gene, while the former is expressed on the membrane of the extracellular vesicle and the latter is expressed within the extracellular vesicle. In some such embodiments, the extracellular vesicle-associated membrane-binding polypeptides and the intravesicular protein biomarkers may be encoded by different genes.

[0195] In some embodiments, a targeted biomarker signature for ovarian cancer comprises at least one (e.g., 1, 2, 3, 4, 5, 6, 7, 8, or more) extracellular vesicle-associated membrane-binding polypeptides (e.g., those described herein) and at least one (e.g., 1, 2, 3, 4, 5, 6, 7, 8, or more) intravesicular RNA (e.g., mRNA) biomarkers (e.g., those described herein). In some such embodiments, the extracellular vesicle-associated membrane-binding polypeptides and the intravesicular RNA (e.g., mRNA) biomarkers may be encoded by the same gene. In some such embodiments, the extracellular vesicle-associated membrane-binding polypeptides and the intravesicular RNA (e.g., mRNA) biomarkers may be encoded by different genes.

[0196] In some embodiments, the targeted biomarker signature for ovarian cancer may be or include combinations of targets as shown in Tables 3-5. In certain embodiments, the targeted biomarker signature for ovarian cancer distinguishes late-stage ovarian cancer samples from control samples (e.g., compared to healthy samples, compared to benign gynecological tumor samples, and / or other cancer samples; see, for example, Tables 3-5). In certain embodiments, the targeted biomarker signature for ovarian cancer distinguishes early-stage ovarian cancer samples (e.g., having low and / or high serum CA-125) from control samples (e.g., compared to healthy samples, compared to benign gynecological tumor samples, and / or other cancer samples; see, for example, Tables 3-5). In some embodiments, assays directed to detect the targeted biomarker signature for ovarian cancer may include combinations of capture and detection probes as shown in Tables 3-5.

[0197] In some embodiments, the targeted biomarker signature for ovarian cancer includes at least the SLC34A2 polypeptide (as an extracellular vesicle-associated membrane-bound polypeptide) and the MUC16 polypeptide (as a targeted surface protein biomarker).

[0198] In some embodiments, the targeted biomarker signature for ovarian cancer includes at least the SLC34A2 polypeptide (as an extracellular vesicle-associated membrane-bound polypeptide) and the FOLR1 polypeptide (as a targeted surface protein biomarker).

[0199] In some embodiments, the targeted biomarker signature for ovarian cancer includes at least the SLC34A2 polypeptide (as an extracellular vesicle-associated membrane-bound polypeptide) and at least two targeted surface protein biomarkers, which may be or may include the MUC16 polypeptide and the FOLR1 polypeptide.

[0200] In some embodiments, the targeted biomarker signature for ovarian cancer includes at least the MUC16 polypeptide (as an extracellular vesicle-associated membrane-bound polypeptide) and the MUC16 polypeptide (as a targeted surface protein biomarker).

[0201] In some embodiments, the targeted biomarker signature for ovarian cancer includes at least the MUC16 polypeptide (as an extracellular vesicle-associated membrane-bound polypeptide) and at least two targeted surface protein biomarkers that may be, or may contain, the MUC16 polypeptide and the CLDN6 polypeptide.

[0202] In some embodiments, the targeted biomarker signature for ovarian cancer includes at least the MUC16 polypeptide (as an extracellular vesicle-associated membrane-bound polypeptide) and at least two targeted surface protein biomarkers, which may be or may include the SLC34A2 polypeptide and the FOLR1 polypeptide.

[0203] In some embodiments, the targeted biomarker signature for ovarian cancer includes at least the MUC16 polypeptide (as an extracellular vesicle-associated membrane-bound polypeptide) and at least two targeted surface protein biomarkers that may be or may contain the MUC16 polypeptide and the CLDN3 polypeptide.

[0204] In some embodiments, the targeted biomarker signature for ovarian cancer includes at least the MUC16 polypeptide (as an extracellular vesicle-associated membrane-bound polypeptide) and at least two targeted surface protein biomarkers, which may be or may include the FOLR1 polypeptide and the CLDN3 polypeptide.

[0205] In some embodiments, the targeted biomarker signature for ovarian cancer includes at least the MUC16 polypeptide (as an extracellular vesicle-associated membrane-bound polypeptide) and at least one targeted surface protein biomarker which may be or may contain the FOLR1 polypeptide.

[0206] In some embodiments, the targeted biomarker signature for ovarian cancer includes at least the MUC16 polypeptide (as an extracellular vesicle-associated membrane-bound polypeptide) and at least one targeted surface protein biomarker which may be or may contain the AQP5 polypeptide.

[0207] In some embodiments, the targeted biomarker signature for ovarian cancer includes at least the MUC16 polypeptide (as an extracellular vesicle-associated membrane-bound polypeptide) and at least two targeted surface protein biomarkers, which may be or may include the FOLR1 polypeptide and the AQP5 polypeptide.

[0208] In some embodiments, the targeted biomarker signature for ovarian cancer includes at least the FOLR1 polypeptide (as an extracellular vesicle-associated membrane-bound polypeptide) and at least two targeted surface protein biomarkers that may be, or may contain, the FOLR1 polypeptide and the CLDN6 polypeptide.

[0209] In some embodiments, the targeted biomarker signature for ovarian cancer includes at least the FOLR1 polypeptide (as an extracellular vesicle-associated membrane-bound polypeptide) and at least two targeted surface protein biomarkers, which may be or may include the SLC34A2 polypeptide and the CLDN3 polypeptide.

[0210] In some embodiments, the targeted biomarker signature for ovarian cancer includes at least the FOLR1 polypeptide (as an extracellular vesicle-associated membrane-bound polypeptide) and at least two targeted surface protein biomarkers, which may be or may include the SLC34A2 polypeptide and the MUC16 polypeptide.

[0211] In some embodiments, the targeted biomarker signature for ovarian cancer includes at least a FOLR1 polypeptide (as an extracellular vesicle-associated membrane-bound polypeptide) and at least one targeted surface protein biomarker which may be or may contain a MUC16 polypeptide.

[0212] In some embodiments, the targeted biomarker signature for ovarian cancer includes at least a FOLR1 polypeptide (as an extracellular vesicle-associated membrane-bound polypeptide) and at least one targeted surface protein biomarker that may be or may contain a FOLR1 polypeptide.

[0213] In some embodiments, the targeted biomarker signature for ovarian cancer includes at least the FOLR1 polypeptide (as an extracellular vesicle-associated membrane-bound polypeptide) and at least two targeted surface protein biomarkers that may be, or may contain, the FOLR1 polypeptide and the CLDN3 polypeptide.

[0214] In some embodiments, the targeted biomarker signature for ovarian cancer includes at least the FOLR1 polypeptide (as an extracellular vesicle-associated membrane-bound polypeptide) and at least two targeted surface protein biomarkers that may be, or contain, the FOLR1 polypeptide and the AQP5 polypeptide.

[0215] In some embodiments, the targeted biomarker signature for ovarian cancer includes at least a FOLR1 polypeptide (as an extracellular vesicle-associated membrane-bound polypeptide) and at least one targeted surface protein biomarker which may be or may contain a CLDN6 polypeptide.

[0216] In some embodiments, the targeted biomarker signature for ovarian cancer includes at least the FOLR1 polypeptide (as an extracellular vesicle-associated membrane-bound polypeptide) and at least two targeted surface protein biomarkers, which may be or may contain both the MUC16 polypeptide and the FOLR1 polypeptide.

[0217] In some embodiments, the targeted biomarker signature for ovarian cancer includes at least the FOLR1 polypeptide (as an extracellular vesicle-associated membrane-bound polypeptide) and at least two targeted surface protein biomarkers, which may be the MUC16 polypeptide and the CLDN3 polypeptide, or may include them.

[0218] In some embodiments, the targeted biomarker signature for ovarian cancer includes at least the LRRTM1 polypeptide (as an extracellular vesicle-associated membrane-bound polypeptide) and at least one targeted surface protein biomarker which may be or may contain the MUC16 polypeptide.

[0219] In some embodiments, the targeted biomarker signature for ovarian cancer comprises at least a CLDN3 polypeptide (as an extracellular vesicle-associated membrane-bound polypeptide) and at least one targeted surface protein biomarker which may be a FOLR1 polypeptide or may contain them.

[0220] In some embodiments, the targeted biomarker signature for ovarian cancer includes at least the CLDN3 polypeptide (as an extracellular vesicle-associated membrane-bound polypeptide) and at least two targeted surface protein biomarkers, which may be or may include the SLC34A2 polypeptide and the MUC16 polypeptide.

[0221] In some embodiments, the targeted biomarker signature for ovarian cancer includes at least the CLDN3 polypeptide (as an extracellular vesicle-associated membrane-bound polypeptide) and at least two targeted surface protein biomarkers, which may be or may contain the MUC16 polypeptide and the CLDN3 polypeptide.

[0222] In some embodiments, the targeted biomarker signature for ovarian cancer includes at least a CLDN3 polypeptide (as an extracellular vesicle-associated membrane-bound polypeptide) and at least one targeted surface protein biomarker which may be or may contain a MUC16 polypeptide.

[0223] In some embodiments, the target biomarker signature for ovarian cancer includes at least the CLDN3 polypeptide (as an extracellular vesicle-associated membrane-bound polypeptide) and at least two target surface protein biomarkers, which may be or may include the MUC16 polypeptide and the FOLR1 polypeptide.

[0224] In some embodiments, the targeted biomarker signature for ovarian cancer includes at least the CLDN3 polypeptide (as an extracellular vesicle-associated membrane-bound polypeptide) and at least two targeted surface protein biomarkers, which may be or may contain the MUC16 polypeptide and the CLDN3 polypeptide.

[0225] In some embodiments, the targeted biomarker signature for ovarian cancer includes at least the CLDN3 polypeptide (as an extracellular vesicle-associated membrane-bound polypeptide) and at least two targeted surface protein biomarkers, which may be or may include the MUC16 polypeptide and the CLDN6 polypeptide.

[0226] In some embodiments, the targeted biomarker signature for ovarian cancer includes at least a CLDN6 polypeptide (as an extracellular vesicle-associated membrane-bound polypeptide) and at least one targeted surface protein biomarker which may be or may contain a MUC16 polypeptide.

[0227] In some embodiments, the targeted biomarker signature for ovarian cancer includes at least an ALPL polypeptide (as an extracellular vesicle-associated membrane-bound polypeptide) and at least one targeted surface protein biomarker which may be or may contain a FOLR1 polypeptide.

[0228] In some embodiments, the targeted biomarker signature for ovarian cancer includes at least a BST2 polypeptide (as an extracellular vesicle-associated membrane-bound polypeptide) and at least one targeted surface protein biomarker which may be or may contain a MUC16 polypeptide.

[0229] In some embodiments, the targeted biomarker signature for ovarian cancer includes at least a FOLR1 polypeptide (as an extracellular vesicle-associated membrane-bound polypeptide) and at least one targeted surface protein biomarker which may be or may contain an MSLN polypeptide.

[0230] In some embodiments, the targeted biomarker signature for ovarian cancer includes at least a FOLR1 polypeptide (as an extracellular vesicle-associated membrane-bound polypeptide) and at least one targeted surface protein biomarker which may be or may contain a MUC16 polypeptide.

[0231] In some embodiments, the targeted biomarker signature for ovarian cancer includes at least an MSLN polypeptide (as an extracellular vesicle-associated membrane-bound polypeptide) and at least one targeted surface protein biomarker which may be or may contain a MUC16 polypeptide.

[0232] In some embodiments, the targeted biomarker signature for ovarian cancer includes at least an MSLN polypeptide (as an extracellular vesicle-associated membrane-bound polypeptide) and at least one targeted surface protein biomarker which may be or may contain a MUC1 polypeptide.

[0233] In some embodiments, the targeted biomarker signature for ovarian cancer includes at least an MSLN polypeptide (as an extracellular vesicle-associated membrane-bound polypeptide) and at least one targeted surface protein biomarker which may be or may contain an SLC2A1 polypeptide.

[0234] In some embodiments, the targeted biomarker signature for ovarian cancer includes at least a MUC1 polypeptide (as an extracellular vesicle-associated membrane-bound polypeptide) and at least one targeted surface protein biomarker which may be or may contain an sTn glycosylated polypeptide.

[0235] In some embodiments, the targeted biomarker signature for ovarian cancer includes at least a MUC1 polypeptide (as an extracellular vesicle-associated membrane-bound polypeptide) and at least one targeted surface protein biomarker which may be or may contain a MUC16 polypeptide.

[0236] In some embodiments, the targeted biomarker signature for ovarian cancer includes at least a MUC1 polypeptide (as an extracellular vesicle-associated membrane-bound polypeptide) and at least one targeted surface protein biomarker which may be a FOLR1 polypeptide or may contain them.

[0237] In some embodiments, the targeted biomarker signature for ovarian cancer comprises at least a MUC16 polypeptide (as an extracellular vesicle-associated membrane-bound polypeptide) and at least one targeted surface protein biomarker which may be or may contain an sTn glycosylated polypeptide.

[0238] In some embodiments, the targeted biomarker signature for ovarian cancer includes at least a PTGS1 polypeptide (as an extracellular vesicle-associated membrane-bound polypeptide) and at least one targeted surface protein biomarker which may be or may contain a MUC16 polypeptide.

[0239] In some embodiments, the targeted biomarker signature for ovarian cancer includes at least an sTn glycosylated polypeptide (as an extracellular vesicle-associated membrane-bound polypeptide) and at least one targeted surface protein biomarker which may be or may contain a FOLR1 polypeptide.

[0240] In some embodiments, the targeted biomarker signature for ovarian cancer comprises at least an sTn glycosylated polypeptide (as an extracellular vesicle-associated membrane-bound polypeptide) and at least one targeted surface protein biomarker which may be or may contain an MSLN polypeptide.

[0241] In some embodiments, the targeted biomarker signature for ovarian cancer includes at least the TACSTD2 polypeptide (as an extracellular vesicle-associated membrane-bound polypeptide) and at least one targeted surface protein biomarker which may be or may contain the MUC16 polypeptide.

[0242] In some embodiments, the targeted biomarker signature for ovarian cancer comprises at least the TACSTD2 polypeptide (as an extracellular vesicle-associated membrane-bound polypeptide) and at least one targeted surface protein biomarker which may be or may contain an sTn glycosylated polypeptide.

[0243] In some embodiments, the targeted biomarker signature for ovarian cancer includes at least a TACSTD polypeptide (as an extracellular vesicle-associated membrane-bound polypeptide) and at least two targeted surface protein biomarkers, which may be or may include MUC16 polypeptide and sTn glycosylated polypeptide.

[0244] In some embodiments, the targeted biomarker signature for ovarian cancer includes at least a TACSTD polypeptide (as an extracellular vesicle-associated membrane-bound polypeptide) and at least two targeted surface protein biomarkers, which may be or may include MUC1 polypeptide and sTn glycosylated polypeptide.

[0245] In some embodiments, the targeted biomarker signature for ovarian cancer includes at least a TACSTD polypeptide (as an extracellular vesicle-associated membrane-bound polypeptide) and at least two targeted surface protein biomarkers, which may be or may include MSLN polypeptides and sTn glycosylated polypeptides.

[0246] In some embodiments, the targeted biomarker signature for ovarian cancer includes at least a TACSTD polypeptide (as an extracellular vesicle-associated membrane-bound polypeptide) and at least two targeted surface protein biomarkers, which may be or may include a FOLR1 polypeptide and an sTn glycosylated polypeptide.

[0247] In some embodiments, the targeted biomarker signature for ovarian cancer includes at least a TACSTD polypeptide (as an extracellular vesicle-associated membrane-bound polypeptide) and at least two targeted surface protein biomarkers, which may be or may include MUC16 polypeptide and MUC1 polypeptide.

[0248] In some embodiments, the targeted biomarker signature for ovarian cancer includes at least the TACSTD polypeptide (as an extracellular vesicle-associated membrane-bound polypeptide) and at least two targeted surface protein biomarkers, which may be or may include the MUC16 polypeptide and the MSLN polypeptide.

[0249] In some embodiments, the targeted biomarker signature for ovarian cancer includes at least the TACSTD polypeptide (as an extracellular vesicle-associated membrane-bound polypeptide) and at least two targeted surface protein biomarkers, which may be the MUC16 polypeptide and the FOLR1 polypeptide, or may include them.

[0250] In some embodiments, the targeted biomarker signature for ovarian cancer includes at least a TACSTD polypeptide (as an extracellular vesicle-associated membrane-bound polypeptide) and at least two targeted surface protein biomarkers, which may be or may include MUC1 polypeptide and MSLN polypeptide.

[0251] In some embodiments, the targeted biomarker signature for ovarian cancer includes at least a TACSTD polypeptide (as an extracellular vesicle-associated membrane-bound polypeptide) and at least two targeted surface protein biomarkers, which may be or may include MUC1 polypeptide and FOLR1 polypeptide.

[0252] In some embodiments, the targeted biomarker signature for ovarian cancer includes at least a TACSTD polypeptide (as an extracellular vesicle-associated membrane-bound polypeptide) and at least two targeted surface protein biomarkers, which may be or may include MSLN polypeptide and FOLR1 polypeptide.

[0253] In some embodiments, the targeted biomarker signature for ovarian cancer includes at least the MUC1 polypeptide (as an extracellular vesicle-associated membrane-bound polypeptide) and at least two targeted surface protein biomarkers, which may be the MUC16 polypeptide and the sTn glycosylated polypeptide, or may contain them.

[0254] In some embodiments, the targeted biomarker signature for ovarian cancer includes at least the MUC1 polypeptide (as an extracellular vesicle-associated membrane-bound polypeptide) and at least two targeted surface protein biomarkers, which may be or may include the MUC16 polypeptide and the MSLN polypeptide.

[0255] In some embodiments, the targeted biomarker signature for ovarian cancer includes at least the MUC1 polypeptide (as an extracellular vesicle-associated membrane-bound polypeptide) and at least two targeted surface protein biomarkers, which may be the MUC16 polypeptide and the FOLR1 polypeptide, or may include them.

[0256] In some embodiments, the targeted biomarker signature for ovarian cancer includes at least a MUC1 polypeptide (as an extracellular vesicle-associated membrane-bound polypeptide) and at least two targeted surface protein biomarkers, which may be or may include an MSLN polypeptide and an sTn glycosylated polypeptide.

[0257] In some embodiments, the targeted biomarker signature for ovarian cancer includes at least the MUC1 polypeptide (as an extracellular vesicle-associated membrane-bound polypeptide) and at least two targeted surface protein biomarkers, which may be or may include the FOLR1 polypeptide and the sTn glycosylated polypeptide.

[0258] In some embodiments, the targeted biomarker signature for ovarian cancer includes at least the MUC1 polypeptide (as an extracellular vesicle-associated membrane-bound polypeptide) and at least two targeted surface protein biomarkers, which may be or may include the MSLN polypeptide and the FOLR1 polypeptide.

[0259] In some embodiments, the targeted biomarker signature for ovarian cancer includes at least the MUC16 polypeptide (as an extracellular vesicle-associated membrane-bound polypeptide) and at least two targeted surface protein biomarkers, which may be or may include the MUC1 polypeptide and the sTn glycosylated polypeptide.

[0260] In some embodiments, the targeted biomarker signature for ovarian cancer includes at least the MUC16 polypeptide (as an extracellular vesicle-associated membrane-bound polypeptide) and at least two targeted surface protein biomarkers, which may be or may include MSLN polypeptide and sTn glycosylated polypeptide.

[0261] In some embodiments, the targeted biomarker signature for ovarian cancer includes at least the MUC16 polypeptide (as an extracellular vesicle-associated membrane-bound polypeptide) and at least two targeted surface protein biomarkers, which may be or may include the FOLR1 polypeptide and the sTn glycosylated polypeptide.

[0262] In some embodiments, the targeted biomarker signature for ovarian cancer includes at least the MUC16 polypeptide (as an extracellular vesicle-associated membrane-bound polypeptide) and at least two targeted surface protein biomarkers, which may be or may include the MUC1 polypeptide and the MSLN polypeptide.

[0263] In some embodiments, the targeted biomarker signature for ovarian cancer includes at least the MUC16 polypeptide (as an extracellular vesicle-associated membrane-bound polypeptide) and at least two targeted surface protein biomarkers, which may be or may include the MUC1 polypeptide and the FOLR1 polypeptide.

[0264] In some embodiments, the targeted biomarker signature for ovarian cancer includes at least the MUC16 polypeptide (as an extracellular vesicle-associated membrane-bound polypeptide) and at least two targeted surface protein biomarkers, which may be or may include the MSLN polypeptide and the FOLR1 polypeptide.

[0265] In some embodiments, the targeted biomarker signature for ovarian cancer includes at least an sTn glycosylated polypeptide (as an extracellular vesicle-associated membrane-bound polypeptide) and at least two targeted surface protein biomarkers, which may be MUC16 polypeptide and MUC1 polypeptide, or may contain them.

[0266] In some embodiments, the targeted biomarker signature for ovarian cancer includes at least an sTn glycosylated polypeptide (as an extracellular vesicle-associated membrane-bound polypeptide) and at least two targeted surface protein biomarkers, which may be or may include MUC16 polypeptide and MSLN polypeptide.

[0267] In some embodiments, the targeted biomarker signature for ovarian cancer includes at least an sTn glycosylated polypeptide (as an extracellular vesicle-associated membrane-bound polypeptide) and at least two targeted surface protein biomarkers, which may be or may include MUC16 polypeptide and FOLR1 polypeptide.

[0268] In some embodiments, the targeted biomarker signature for ovarian cancer includes at least an sTn glycosylated polypeptide (as an extracellular vesicle-associated membrane-bound polypeptide) and at least two targeted surface protein biomarkers, which may be or may include MUC1 polypeptide and MSLN polypeptide.

[0269] In some embodiments, the targeted biomarker signature for ovarian cancer includes at least an sTn glycosylated polypeptide (as an extracellular vesicle-associated membrane-bound polypeptide) and at least two targeted surface protein biomarkers, which may be or may include MUC1 polypeptide and FOLR1 polypeptide.

[0270] In some embodiments, the targeted biomarker signature for ovarian cancer includes at least an sTn glycosylated polypeptide (as an extracellular vesicle-associated membrane-bound polypeptide) and at least two targeted surface protein biomarkers, which may be or may include MSLN polypeptide and FOLR1 polypeptide.

[0271] In some embodiments, the targeted biomarker signature for ovarian cancer includes at least an MSLN polypeptide (as an extracellular vesicle-associated membrane-bound polypeptide) and at least two targeted surface protein biomarkers, which may be or may include MUC16 polypeptide and sTn glycosylated polypeptide.

[0272] In some embodiments, the targeted biomarker signature for ovarian cancer includes at least an MSLN polypeptide (as an extracellular vesicle-associated membrane-bound polypeptide) and at least two targeted surface protein biomarkers, which may be or may include MUC16 polypeptide and MUC1 polypeptide.

[0273] In some embodiments, the targeted biomarker signature for ovarian cancer includes at least an MSLN polypeptide (as an extracellular vesicle-associated membrane-bound polypeptide) and at least two targeted surface protein biomarkers, which may be or may include MUC16 polypeptide and FOLR1 polypeptide.

[0274] In some embodiments, the targeted biomarker signature for ovarian cancer includes at least an MSLN polypeptide (as an extracellular vesicle-associated membrane-bound polypeptide) and at least two targeted surface protein biomarkers that may be or may contain a MUC1 polypeptide and an sTn glycosylated polypeptide.

[0275] In some embodiments, the targeted biomarker signature for ovarian cancer includes at least an MSLN polypeptide (as an extracellular vesicle-associated membrane-bound polypeptide) and at least two targeted surface protein biomarkers, which may be or may include a FOLR1 polypeptide and an sTn glycosylated polypeptide.

[0276] In some embodiments, the targeted biomarker signature for ovarian cancer includes at least an MSLN polypeptide (as an extracellular vesicle-associated membrane-bound polypeptide) and at least two targeted surface protein biomarkers, which may be or may include MUC1 polypeptide and FOLR1 polypeptide.

[0277] In some embodiments, the targeted biomarker signature for ovarian cancer includes at least the SLC34A2 polypeptide (as an extracellular vesicle-associated membrane-bound polypeptide) and at least two targeted surface protein biomarkers, which may be or may include the MUC16 polypeptide and the MSLN polypeptide.

[0278] In some embodiments, the targeted biomarker signature for ovarian cancer includes at least the SLC34A2 polypeptide (as an extracellular vesicle-associated membrane-bound polypeptide) and at least two targeted surface protein biomarkers, which may be the MUC16 polypeptide and the sTn glycosylated polypeptide, or may contain them.

[0279] In some embodiments, the targeted biomarker signature for ovarian cancer includes at least the SLC34A2 polypeptide (as an extracellular vesicle-associated membrane-bound polypeptide) and at least two targeted surface protein biomarkers, which may be or may include the FOLR1 polypeptide and the sTn glycosylated polypeptide.

[0280] In some embodiments, one of the provided biomarkers can be detected and / or measured by the expression level of wild-type protein and / or RNA (e.g., mRNA).

[0281] In some embodiments, any one of the provided biomarkers can be detected and / or measured by the expression level of a mutant form of protein and / or RNA (e.g., mRNA). Thus, in some embodiments, mutant-specific detection of the provided biomarkers (e.g., protein and / or RNA, e.g., mRNA) may also be included.

[0282] As noted herein, in some embodiments, the biomarker is or includes a specific form of one or more polypeptides or proteins (e.g., pro-forms, truncated forms, modified forms, e.g., glycosylated, phosphorylated, lipidized forms). In some embodiments, detection of such a form involves detecting multiple (and, in some embodiments, substantially all) polypeptides present in that form (e.g., including specific modifications, e.g., specific glycosylations, e.g., sialyl-Tn(sTn) glycosylation, e.g., truncated O-glycans containing sialic acid α-2,6 bound to GalNAc α-O-Ser / Thr).

[0283] Therefore, in some embodiments, the surface protein biomarker may be or include a glycosylated moiety (e.g., an sTn moiety). The Thompsen-nouvelle (Tn) antigen is an O-linked glycan thought to be associated with a wide range of tumors. Tn is a single alpha-linked GalNAc that is added to Ser or Thr as the first step in the major O-linked glycosylation pathway. In some embodiments, the surface protein biomarker may be or include tumor-associated post-translational modifications. In some embodiments, such post-translational modifications may be or include tumor-specific glycosylation patterns, such as mucins, that initially contain abnormally shortened glycans in GalNAc (e.g., Tn), or combinations thereof.

[0284] In some embodiments, the biomarker is or includes a shortened form of a polypeptide. For example, in some embodiments, the MUC16 biomarker is a shortened form of the MUC16 protein.

[0285] III. Exemplary methods for detecting markers and / or target biomarker signatures provided for ovarian cancer Generally, this disclosure provides techniques for analyzing and / or evaluating target biomarker signatures in blood-derived samples containing extracellular vesicles from subjects requiring such analysis and / or evaluation; in some embodiments, diagnostic or therapeutic decisions are made based on such analysis and / or evaluation.

[0286] In some embodiments, a method for detecting a target biomarker signature includes a method for detecting one or more provided markers of the target biomarker signature as a protein. Exemplary protein-based methods for detecting one or more provided markers include, but are not limited to, proximity ligation assays, immunoassays such as mass spectrometry (MS) and immunoprecipitation; Western blotting; ELISA; immunohistochemistry; immunocytochemistry; flow cytometry; and immunoPCR. In some embodiments, the immunoassay may be a chemiluminescent immunoassay. In some embodiments, the immunoassay may be a high-throughput and / or automated immunoassay platform.

[0287] In some embodiments, a method for detecting one or more provided markers as proteins in a sample includes contacting the sample with one or more antibody factors that are directed to the desired provided marker. In some embodiments, such a method also includes contacting the sample with one or more detection labels. In some embodiments, the antibody factors are labeled with one or more detection labels.

[0288] In some embodiments, the detection of binding between a biomarker of interest and an antibody factor for that biomarker of interest includes determining the absorbance or emission value of one or more detection factors. For example, the absorbance or emission value indicates the amount and / or concentration of the biomarker of interest expressed by extracellular vesicles (e.g., higher absorbance indicates a higher level of the biomarker of interest expressed by extracellular vesicles). In some embodiments, the absorbance or emission value of the detection factor exceeds a threshold. In some embodiments, the absorbance or emission value of the detection factor is at least 1.3, at least 1.4, at least 1.5, at least 1.6, at least 1.7, at least 1.8, at least 1.9, at least 2.0, at least 2.5, at least 3.0, at least 3.5 times or more higher than the threshold. In some embodiments, the threshold is determined across a control or reference population (e.g., non-cancer subjects).

[0289] In some embodiments, a method for detecting one or more provided markers includes a method for detecting one or more provided markers as nucleic acids. Exemplary nucleic acid-based methods for detecting one or more provided markers include, but are not limited to, performing nucleic acid amplification methods, such as polymerase chain reaction (PCR), reverse transcription polymerase chain reaction (RT-PCR), transcription-mediated amplification (TMA), ligase chain reaction (LCR), strand substitution amplification (SDA), and nucleic acid sequence-based amplification (NASBA). In some embodiments, a nucleic acid-based method for detecting one or more provided markers includes detecting hybridization between one or more nucleic acid probes and one or more nucleotides encoding a biomarker of interest. In some embodiments, the nucleic acid probes are each complementary to at least a portion of one of the one or more nucleotides encoding the biomarker of interest. In some embodiments, the nucleotides encoding the biomarker of interest include DNA (e.g., cDNA). In some embodiments, the nucleotides encoding the biomarker of interest include RNA (e.g., mRNA).

[0290] In some embodiments, a method for detecting one or more provided markers may include proximity-ligation-immunoquantitative polymerase chain reaction (pliq-PCR). pliq-PCR may have certain advantages over other techniques for profiling EVs. For example, pliq-PCR may have sensitivity three orders of magnitude higher than other standard immunoassays, e.g., ELISA (Darmanis et al., 2010; incorporated herein by reference for the purposes described herein). In some embodiments, the pliq-PCR reaction may be designed to have an extremely low LOD, enabling the detection of trace levels of tumor-derived EVs, e.g., up to 1000 EVs per mL.

[0291] In some embodiments, a method for detecting one or more provided markers is, for example, about 10 each. 3 and about 10 4 LOD for EVs has been reported (Shao et al.) Other techniques for detecting EVs may include Im et al., 2018 (incorporated herein by reference for the purposes described herein), Nanoplasmic Exosome (nPLEX) Sensor (Im et al., 2014 (incorporated herein by reference for the purposes described herein)), and Integrated Magnetic-Electrochemical Exosome (iMEX) Sensor (Jeong et al., 2016 (incorporated herein by reference for the purposes described herein)).

[0292] In some embodiments, a method for detecting one or more provided biomarkers in extracellular vesicles may be based on bulk EV sample analysis.

[0293] In some embodiments, a method for detecting one or more provided biomarkers in extracellular vesicles is obtained based on profiling individual EVs (e.g., a single EV profiling assay), which is further discussed in the section below titled “Exemplary Methods for Profiling Individual Extracellular Vesicles (EVs)”.

[0294] In some embodiments, extracellular vesicles in a sample can be captured or immobilized on a solid substrate before detection of one or more biomarkers provided in accordance with this disclosure. In some embodiments, extracellular vesicles can be captured on the surface of a solid substrate by nonspecific interactions, including, for example, adsorption. In some embodiments, extracellular vesicles can be selectively captured on the surface of a solid substrate. For example, in some embodiments, the surface of a solid substrate can be coated with an action factor that specifically binds to extracellular vesicles (e.g., an antibody factor that specifically targets extracellular vesicles, such as those associated with ovarian cancer). In some embodiments, the surface of a solid substrate can be coated with a film of affinity-binding pairs, and the entity of interest to be captured (e.g., extracellular vesicles) can be conjugated to a complementary member of the affinity-binding pair. In some embodiments, exemplary affinity-binding pairs include, for example, biotin and avidin-like molecules, such as streptavidin, but are not limited to these. As will be understood by those skilled in the art, other suitable affinity-binding pairs can also be used to facilitate the capture of the entity of interest on the surface of a solid substrate. In some embodiments, for example, as described in Ibsen et al. ACS Nano., 11:6641-6651 (2017) and Lewis et al. ACS Nano., 12:3311-3320 (2018), both of which are incorporated herein by reference for the purposes described herein and both describe the use of AC electrokinetic microarray chip devices for isolating extracellular vesicles from undiluted human blood or plasma samples, the entities of interest can be captured on the surface of a solid substrate by the application of an electric current.

[0295] The solid substrate can be obtained in a form suitable for capturing extracellular vesicles and that does not interfere with downstream handling, processing, and / or detection. For example, in some embodiments, the solid substrate may be or include beads (e.g., magnetic beads). In some embodiments, the solid substrate may be or include a surface. For example, in some embodiments, such a surface may be a capture surface of an assay chamber (e.g., including tubes, wells, microwells, plates, filters, membranes, matrices, etc.). Thus, in some embodiments, the method described herein includes capturing or immobilizing extracellular vesicles on a solid substrate before detecting biomarkers obtained in a sample.

[0296] In some embodiments, before capturing extracellular vesicles on a solid substrate surface, the sample may be treated to remove, for example, undesirable entities, such as cell debris or cells. For example, in some embodiments, such a sample may be subjected to centrifugation to remove, for example, cell debris, cells, and / or other fine particles. In addition, or alternatively, in some embodiments, such a sample may be subjected to size exclusion-based purification or filtration. Various size exclusion-based purifications or filtrations are known in the art, and those skilled in the art will see that, in some cases, the sample may be subjected to spin column purification based on a specific molecular weight or particle size cutoff. Those skilled in the art will also see that an appropriate molecular weight or particle size cutoff for purification purposes can be selected, for example, based on the size of the extracellular vesicles. For example, in some embodiments, a size exclusion separation method may be applied to a sample containing extracellular vesicles to isolate a fraction of extracellular vesicles of a certain size (e.g., greater than 30 nm and less than or equal to 1000 nm, or greater than 70 nm and less than or equal to 200 nm). Typically, extracellular vesicles may range in diameter from 30 nm to several micrometers. For example, see Chuo et al., “Imaging extracellular vesicles: current and emerging methods,” Journal of Biomedical Sciences 25:91 (2018), which is incorporated herein by reference for the purposes described herein, providing information on the sizes of various extracellular vesicle (EV) subtypes: migrasomes (0.5–3 μm), microendoplasmic reticulum (0.1–1 μm), oncosomes (1–10 μm), exomers (<50 nm), small exosomes (60–80 nm), and large exosomes (90–120 nm). In some embodiments, nanoparticles having a size range of approximately 30 nm to 1000 nm can be isolated for detection assays, for example, by one or more size exclusion separation methods in some embodiments. In some embodiments, specific EV subtypes can be isolated for detection assays, for example, by one or more size exclusion separation methods in some embodiments.

[0297] In some embodiments, extracellular vesicles in a sample can be treated before detecting one or more provided biomarkers of a targeted biomarker signature for ovarian cancer. For example, various sample treatments and / or preparations can be performed to stabilize the target (e.g., a targeted biomarker) in the extracellular vesicle to be detected, and / or to facilitate the exposure of the target (e.g., intravesicular proteins and / or RNA, e.g., mRNA) to a detection assay (e.g., as described herein), and / or to reduce nonspecific binding. Examples of such sample treatments and / or preparations are known in the Art and include, but are not limited to, crosslinking (e.g., immobilization) of molecular targets, permeabilization of biological entities (e.g., cells or extracellular vesicles), and / or blocking of nonspecific binding sites.

[0298] In one embodiment, the disclosure provides a method for detecting whether or not a targeted biomarker signature for ovarian cancer is present in a biological sample from a subject requiring it, which may in some embodiments be a blood-derived sample containing extracellular vesicles. In some embodiments, such a method includes (a) detecting a biological entity of interest (e.g., including extracellular vesicles) expressing the targeted biomarker signature for ovarian cancer in a biological sample from a subject, e.g., a blood-derived sample (e.g., a plasma sample); and (b) comparing sample information indicating the level of the biological entity expressing the target biomarker signature of interest (e.g., extracellular vesicles) in the biological sample (e.g., a blood-derived sample) with reference information including a reference threshold level. In some embodiments, the reference threshold level corresponds to the level of the biological entity of interest expressing such a targeted biomarker signature (e.g., extracellular vesicles) in a comparable sample from a reference subject, e.g., a population of non-cancer subjects. In some embodiments, exemplary non-cancer subjects include healthy women (e.g., healthy women within a specified age range, such as under or over 55 years of age), women with non-ovarian related health conditions, disorders, or states (e.g., women with non-ovarian cancers such as lung cancer or colorectal cancer, or women with symptoms of inflammatory bowel disease or disorder), women with benign ovarian tumors (e.g., benign lumps observed in the fallopian tubes and / or on the ovaries), and combinations thereof.

[0299] In some embodiments, samples are pre-screened for certain characteristics before being used in the assays described herein. In some embodiments, samples that meet certain pre-screening criteria are more suitable for diagnostic application than samples that do not meet the pre-screening criteria. For example, in some embodiments, samples are visually examined for appearance using known standards, such as normal, hemolytic (red), jaundice (yellow), and / or fatty (turbid). In some embodiments, samples can then be rated on a known standard scale (e.g., 1, 2, 3, 4, 5) and the results recorded. In some embodiments, samples are visually examined for hemolysis (e.g., heme) and rated on a scale of 1 to 5, where the visual examination correlates with known concentrations, for example, 1 represents approximately 0 mg / dL, 2 represents approximately 50 mg / dL, 3 represents approximately 150 mg / dL, 4 represents approximately 250 mg / dL, and 5 represents approximately 525 mg / dL. In some embodiments, the sample is visually inspected for jaundice levels (e.g., bilirubin) and rated on a scale of 1 to 5, where the visual inspection correlates with known concentrations, for example, 1 represents approximately 0 mg / dL, 2 represents approximately 1.7 mg / dL, 3 represents approximately 6.6 mg / dL, 4 represents approximately 16 mg / dL, and 5 represents approximately 30 mg / dL. In some embodiments, the sample is visually inspected for turbidity (e.g., lipids) and rated on a scale of 1 to 5, where the visual inspection correlates with known concentrations, for example, 1 represents approximately 0 mg / dL, 2 represents approximately 125 mg / dL, 3 represents approximately 250 mg / dL, 4 represents approximately 500 mg / dL, and 5 represents approximately 1000 mg / dL.

[0300] In some embodiments, samples with a score below a certain level for one or more metrics, for example, a score of 4 or less, can be used in the assay as described herein. In some embodiments, samples with a score below a certain level for one or more metrics, for example, a score of 3 or less, can be used in the assay as described herein. In some embodiments, samples with a score below a certain level for one or more metrics, for example, a score of 2 or less, can be used in the assay as described herein. In some embodiments, samples with a score below a certain level for all three metrics (e.g., hemolysis, jaundice, and lipids), for example, a score of 2 or less, can be used in the assay as described herein. In some embodiments, a low visual examination score (e.g., a score of 2 or less) on pre-screening criteria such as hemolysis, bilirubin, and / or hyperlipidemia may not have a clear effect on (e.g., may not correlate with) the diagnostic characteristics (e.g., Ct values) produced in the assay as described herein.

[0301] In some embodiments, a sample is determined to have extracellular vesicles expressing a target biomarker signature (e.g., as described herein) if the sample exhibits extracellular vesicles expressing a target biomarker signature at a level elevated compared to a reference threshold level (e.g., as described herein). In some embodiments, a sample is determined to be positive for extracellular vesicles expressing a target biomarker signature if the level is at least 30% or higher compared to the reference threshold level, including, for example, at least 40%, at least 50%, at least 60%, at least 70%, at least 80%, at least 90%, at least 95%, or higher. In some embodiments, a sample is determined to be positive for target biomarker signature-expressing extracellular vesicles if the level is at least twice or more higher than a reference threshold level, including, for example, at least 3 times, at least 4 times, at least 5 times, at least 6 times, at least 7 times, at least 8 times, at least 9 times, at least 10 times, at least 50 times, at least 10 times, at least 100 times, at least 250 times, at least 500 times, at least 750 times, at least 1000 times, at least 2500 times, at least 5000 times, or more.

[0302] In some embodiments, a binary classification system can be used to determine whether a sample is positive for extracellular vesicles expressing a target biomarker signature. For example, in some embodiments, a sample is determined to be positive for extracellular vesicles expressing a target biomarker signature if its level is at or above a reference threshold level, e.g., a cutoff value. In some embodiments, such a reference threshold level (e.g., a cutoff value) can be determined by selecting a certain number of standard deviations away from the mean value obtained from a control, so that the desired sensitivity and / or specificity of the ovarian cancer detection assay (e.g., one described herein) can be achieved. In some embodiments, such a reference threshold level (e.g., a cutoff value) can be determined by selecting a certain number of standard deviations away from the maximum assay signal obtained from a control, so that the desired sensitivity and / or specificity of the ovarian cancer detection assay (e.g., one described herein) can be achieved. In some embodiments, such a reference threshold level (e.g., cutoff value) can be determined by selecting whichever is less restrictive: (i) a certain number of standard deviations away from the mean obtained from control subjects, or (ii) a certain number of standard deviations away from the maximum assay signal obtained from control subjects. In some embodiments, the control subjects for determining the reference threshold level (e.g., cutoff value) may include, but are not limited to, healthy subjects, subjects with inflammatory conditions (e.g., Crohn's disease, ulcerative colitis, endometriosis, etc.), subjects with benign gynecological tumors, and combinations thereof. In some embodiments, healthy subjects and subjects with inflammatory conditions (e.g., Crohn's disease, ulcerative colitis, endometriosis, etc.) are included in the determination of the reference threshold level (e.g., cutoff value). In some embodiments, subjects with benign gynecological tumors are not included in the determination of the reference threshold level (e.g., cutoff value).In some embodiments, a reference threshold level (e.g., cutoff value) can be determined by selecting (i) the mean value obtained from control subjects, or (ii) at least 1.5 or more standard deviations (SD) awa...

Claims

[Claim 1] The invention described in the specification.

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