WO2010098862A2

WO2010098862A2 - Method of using an oligonucleotide microarray to detect cancer from serum nucleic acid

Info

Publication number: WO2010098862A2
Application number: PCT/US2010/000569
Authority: WO
Inventors: Michael J. Lodes; Dominic Suciu; Marcelo Caraballo; Andrew Antoniewicz
Original assignee: Combimatrix Corporation
Priority date: 2009-02-24
Filing date: 2010-02-24
Publication date: 2010-09-02
Also published as: WO2010098862A3

Abstract

Disclosed herein is a method of using an oligonucleotide microarray to detect cancer from serum micro RNA. The method provides a microarray of oligonucleotide probes. A serum miRNA sample is hybridized to the microarray of oligonucleotide probes. The oligonucleotide probes comprise complementary probes to the miRNAs in the serum miRNA sample and mismatch probes having mismatches from the complementary probes as well as control spike in probes.

Description

METHOD OF USING AN OLIGONUCLEOTIDE MICRO ARRAY TO DETECT CANCER FROM SERUM NUCLEIC ACID

Cross Reference to Related Applications

This nonpro visional application claims the benefit of provisional application Serial No. 61/208,555, filed February 29, 2009, provisional application Serial No. 61/216,105, filed May 12, 2009, provisional application Serial No. 61/216,376, filed May 14, 2009, and provisional application Serial No. 61/217,184, filed May 27, 2009, under 35 U.S.C §119(e); the disclosure of each provisional application is incorporated by reference herein for all purposes.

Technical Field

The disclosure herein relates to a method of using an oligonucleotide microarray to detect cancer from nucleic acids in serum. More specifically, the disclosure herein relates to capturing and labeling of nucleic acids from serum for hybridization to a microarray of oligonucleotide probes followed by analysis of the hybridization pattern to determine whether the serum contains nucleic acids that indicate the presence of cancer in the source of the serum.

Background

Within the field of biotechnology and diagnostics, microarrays have become important tools and essentially, are the standard for parallel analysis of biological samples. In general, microarrays are miniaturized arrays of locations on a solid surface, which is usually planar. As part of the preparation of a microarray, the locations may have presynthesized molecules, including biomolecules, attached thereto or may have molecules synthesized in situ such as a DNA molecule synthesized one monomer at a time. The attachment locations are usually in a column and row format; however, other formats may be used. Most often, microarrays, and in particular, microarrays of oligonucleotides, are silicon-based and most often are a glass microscope slide. The major advantage of microarrays is the ability to conduct hundreds, if not thousands, of experiments simultaneously. Simultaneous experimentation increases the efficiency of exploring relationships between molecular structure and biological function, wherein slight variations in chemical structure can have profound biochemical effects. As the name suggests, the attachment points on microarrays are of a micrometer scale, which is generally l-100μm.

Research using microarrays has focused mainly on deoxyribonucleic acid (DNA) and ribonucleic acid (RNA) related areas, which includes genomics, cellular gene expression, single nucleotide polymorphism (SNP) analysis, genomic DNA detection and validation, functional genomics, and proteomics as described in the following publications, wherein the disclosure of each publication is incorporated by reference herein for all purposes: Wilgenbus and Lichter, J. MoI. Med. 77:761, 1999; Ashfari et al., Cancer Res. 59:4759, 1999; Kurian et al., J. Pathol. 187:267, 1999; Hacia, Nature Genetics 21 suppl.:42, 1999; Hacia et al., MoI. Psychiatry 3:483, 1998; and Johnson, Curr. Biol. 26:R171, 1998). Additionally, microarrays can be used for research related to peptides (two or more linked natural or synthetic amino acids), small molecules (such as pharmaceutical compounds), oligomers, and polymers. There are numerous methods for preparing a microarray of DNA related molecules, which includes native or cloned DNA and synthetic DNA. Synthetic, relatively short single-stranded DNA or RNA strands are commonly referred to as oligonucleotides.

Microarray preparation methods include the following: (1) spotting a solution on a prepared flat surface using spotting robots; (2) in situ synthesis by printing reagents via ink jet or other printing technology and using regular phosphoramidite chemistry; (3) in situ parallel synthesis using electrochemically-generated acid for deprotection and using regular phosphoramidite chemistry; (4) maskless photo-generated acid (PGA) controlled in situ synthesis and using regular phosphoramidite chemistry; (5) mask-directed in situ parallel synthesis using photo-cleavage of photolabile protecting groups (PLPG); (6) maskless in situ parallel synthesis using PLPG and digital photolithography; and (7) electric field attraction/repulsion for depositing oligonucleotides. A review of oligonucleotide microarray synthesis is provided by: Gao et al., Biopolymers 73:579, 2004, the disclosure of which is incorporated by reference herein. Photolithographic techniques for in situ oligonucleotide synthesis are disclosed in Fodor et al. U.S. Patent No. 5,445,934 and the additional patents claiming priority thereto and Pirrung et al. U.S. Patent No. 5,405,783, the disclosure of each is incorporated by reference herein. Electric field attraction/repulsion microarrays are disclosed in Hollis et al. U.S. Patent No. 5,653,939, the disclosure of which is incorporated by reference herein, and Heller et al. U.S. Patent No. 5,929,208, the disclosure of which is incorporated by reference herein. Pin printing techniques (spotting) for mechanical deposition of macromolecules is disclosed in Martinsky U.S. Patent No. 6,101,946, the disclosure of which is incorporated by reference herein. Spotting by means of micropipettes is disclosed in Gordon, et al. U.S. Patent No. 5,601,980, the disclosure of which is incorporated by reference herein. Spotting by means of ink jet printing is disclosed in Papen, et al. U.S. Patent No. 5,927,547, the disclosure of which is incorporated by reference herein. An electrode microarray for in situ oligonucleotide synthesis using electrochemical deblocking is disclosed in Montgomery, U.S. Patent Nos. 6,093,302, 6,280,595, and 6,444,111 (Montgomery I, II, and III respectively), the disclosure of each is incorporated by reference herein.

The electrochemical synthesis microarray disclosed in Montgomery I, II, and III is based upon a semiconductor chip having a plurality of microelectrodes in a column and row format. This chip design uses Complementary Metal Oxide Semiconductor (CMOS) technology to create high-density arrays of microelectrodes with parallel addressing for selecting and controlling individual microelectrodes within the microarray. In order to provide appropriate reactive groups at each electrode, the microarray is coated with a porous reaction matrix material (layer.) The thickness and porosity of the matrix are controlled. Biomolecules, as well as other molecules, can be synthesized at locations on any of the electrodes on the porous matrix.

During synthesis at a location, the electrode is "turned on" by applying a voltage or current that generates electrochemical reagents (particularly acidic protons) that alter the pH in a small, defined "virtual flask" region or volume adjacent to the electrode and within the porous matrix. The electrochemically-generated reagents remove protective groups on the molecule being synthesized to allow continued synthesis of a DNA or other oligomeric or polymeric material. The pH decreases only in the vicinity of the electrode because the ability of the acidic reagent to travel away from an electrode is limited by natural diffusion and by buffering.

There are numerous methods for detection of cancer, and many of which have the problem of requiring the use of expensive equipment. Some examples of the methods for detecting cancer include Computerized Tomography, Magnetic Resonance Imaging, Conventional Mammography, Miraluma Breast Imaging, and Fluorescence Bronchoscopy. Additionally, many of the methods for detecting cancer are used after the cancer has progressed sufficiently such that a patient has developed symptoms. Since treatment for cancer, in general, is more successful when the cancer is diagnosed early, the ability to recover from cancer is reduced when treatment is started in the later stages of the cancer. To improve the chances of a cancer treatment being successful, there is a need in the art to diagnose cancer at an early stage. Additionally, to improve access to diagnosis, there is a need in the art for lower cost methods for early detection of cancer. The disclosure herein addresses these problems and provides inventive solutions for early detection of cancer using a method on a microarray having selected oligonucleotides sequences representative of specific micro RNA sequences that are indicative of the presence of a cancer.

Micro RNAs (miRNAs) are a class of small non-coding RNA species expressed in cells, and research indicates that they have an important role in regulation and development of cells. Research also indicates that the specific miRNAs expressed in a cell depend on the type of cell. In other words, miRNA taken from one type of tissue is different from that taken from another type of tissue. Thus, the miRNA itself can be an indication of the type of tissue from which the miRNA originated. In addition, research indicates that miRNA gene expression patterns have the potential to be used to identify or classify tumor cells, and that this classification can be more accurate than the classification achieved by using messenger RNA gene expression patterns. One aspect of miRNA biogenesis that makes them particularly attractive as a biomarker is the fact that they are maintained in a protected state in serum and plasma, thus allowing the detection of miRNA expression patterns directly from serum and plasma. Therefore, miRNA' s in serum could possibly be used as basis for determining whether particular miRNA's came from a certain type of tumor.

MicroRNAs (miRNA) are single-stranded RNA molecules of about 21-23 nucleotides in length, which function in the regulation of gene expression. miRNAs are expressed as part of primary transcripts in the form of hairpins with signals for dsRNA-specific nuclease cleavage by the ribonuclease Drosha in combination with an RNA-binding protein. After the precursor miRNA is released as an approximately 70 nt RNA, it is transported from the nucleus to the cytoplasm by Exportin-5, and then is cleaved by Dicer RNase III to form a double-stranded RNA. Dicer initiates the formation of the RNA-induced silencing complex (RISC), which is responsible for the gene silencing observed due to miRNA expression and RNA interference.

MicroRNAs have been found in tissues and also in serum and plasma, and other body fluids, in a stable form that is protected from endogenous RNase activity (in association with RISC, either free in blood or in exosomes (endosome-derived organelles)). Studies by researchers have demonstrated the feasibility and utility of monitoring the expression of miRNAs in human cancer tissue. They found a high level of diversity in miRNA expression across cancers, and found that approximately 200 miRNAs could be sufficient to classify human cancers. Some researchers found that because miRNAs function as managers in gene regulatory network, they are distinct from other biomarkers because they have a pathogenic role in the disease process and are not by-products of the disease state. Because miRNAs function by specific binding to their targets, polymorphisms within the sequence of miRNAs or their target mRNAs can lead to disease, including cancer. These miRNA-specific SNPs can influence the risk of disease and can also be used in the diagnosis of these diseases.

Deregulated miRNAs have been described from numerous human cancers including breast, lung, colon, ovarian, and prostate cancer. Research has shown that miRNAs originating from prostate cancer tissue enter circulation and can be used to distinguish patients with prostate cancer from healthy controls and established a blood-based PCR approach for the detection of human prostate cancer. A similar approach was used to detect serum miRNA from ovarian cancer patients. Some researchers have investigated the use of circulating exosomes in the diagnosis of cancer, and found that the miRNA content of ovarian tumor cells and circulating exosome was similar and could be used to distinguish cancer patients from patients with benign ovarian disease and from normal controls. miRNA signatures from normal and cancerous tissues have been used to classify several types of cancer and may also allow clinicians to determine a treatment course based on the original tissue type. It may also be possible to use miRNA expression patterns as a biomarker to monitor the effect of therapy on cancer progression. Because miRNA expression profiles parallel the developmental origins of tissues, and because relatively few miRNAs can be used to effectively type tissues, they are potentially superior markers than messenger RNAs for cancer diagnosis. The potential for the use of serum miRNAs as biomarkers of disease and as targets of therapeutics is promising, since it would mean a non-invasive, accurate test for cancer. miRNA expression signatures have a potential role in the diagnosis, prognosis and therapy of human diseases, including cancer, heart disease, viral infections and inflammatory diseases]. Deregulation of miRNAs in cancer can be caused by chromosomal deletions, amplifications and translocations; by hypermethylation of CpG islands; and by regulation of transcription and post-transcriptional processing. Aberrant expression of miRNAs can influence cancer progression by affecting the expression of oncogenes or tumor suppressors, and miRNAs, such as the miR- 17-92 cluster, can function directly as oncogenes. miRNAs are also involved in cancer through their effect on the cell cycle, apoptosis, metastasis, and angiogenesis.

Several studies have detailed the miRNAs that are associated with cancers. Most of these studies have used biopsy samples, archival tissues or cancer cells, or have used miRNAs extracted from paraffin embedded or formalin fixed tissues. By comparing non-cancerous tissues surrounding cancerous tissues, or normal donors versus cancer patients, those miRNAs that are up or down regulated can be identified, often after PCR amplification. Many studies have been published describing the specificity of miRNAs for different types of cancers, cancer stages and cancer treatments and several reviews have been published that summarize the most recent information on the roles of miRNAs in cancer. These studies demonstrate the utility of miRNAs in both diagnosis and prognosis of several cancers and also differentiate between cancer and benign disorders. While numerous studies have led to an understanding of miRNAs at a tissue or cell level, there is a paucity of data in serum studies hampering their use in routine diagnosis.

Recently a series of studies have been performed on miRNAs present in serum. In a recent report, miRNAs were shown to be significantly elevated in pregnant versus nonpregnant women; and in another study, placental miRNAs were shown to be present in maternal plasma. In these studies, the miRNAs were found to be very stable to storage, and also to any RNAse degradation. miRNAs have recently been shown by Mitchell et al to circulate in serum of prostate cancer patients . In particular, miR-141 could differentiate prostate cancer patients from normal individuals. In a work by others, circulating tumor exosomes were isolated from serum of ovarian cancer patients using magnetic beads and an antiEpCAM antibody. miRNAs were then extracted, labeled and detected by microarray. This approach, using larger volumes of serum, indicated that eight diagnostic miRNAs were up- regulated in cancer exosomes: miR-21, miR-141, miR-200a, miR-200c, miR-200b, miR-203, miR-205, and miR-214. To date however, no routine assay is available for examining miRNA signatures in serum or in the plasma of cancer patients. Thus, there is a need in the art to develop a routine assay that uses serum or plasma for screening patients for cancer.

One issue that appears in research by others is the fact that the miRNA expression patterns seen in serum are not identical to those seen from miRNAs taken directly from cancer cell lines. The inventive disclosure herein shows that although both the prostate cancer serum sample and the prostate cancer cell line (22RvI) sample showed up-regulation compared to normal serum sample, they did not show much similarity to each other. This seeming discrepancy could be taking place for a number of reasons. The most obvious of which is the possibility that samples taken from the cell lines themselves are not representative of what appears in the serum. A source of miRNAs that appear in the serum could be a product of tumor cell lysis; however, it may also be possible that their appearance in the serum is the product of a form of active transport involving the formation of exosomes. This would confound a direct comparison between miRNA expression patters derived from cell-line and tumor with those that are serum-derived.

Information on the use of miRNAs as biomarkers is predominantly associated with studies on tissue samples or cancer cell lines. Distinct patterns of miRNA expression are able to distinguish between cell type and stage in various cancers. This bodes well for diagnostic and prognostic applications of miRNA profiles. It also indicates there is clearly a need to define the expression profiles of miRNAs in serum of cancer patients and compare these to profiles observed in the serum of individuals representing a range of diseased and healthy states. It is anticipated that miRNA profiles in serum have the potential to be early markers for cancer detection and will also play a role in the monitoring of disease status during chemotherapy. The disclosure herein describes a method that is based on this principle of conservation of miRNA's in serum to detect for the presence or absence of cancer in an organism by using microarray analysis of miRNA's in serum. The disclosure herein further relates to capturing nucleic acids from serum for hybridization to a microarray of oligonucleotide probes followed by an analysis method of the hybridization pattern to determine whether the serum contains nucleic acids that indicate presence of cancer cells in the serum. The methods disclosed herein provide a means to determine if cancer is present before symptoms arise using well established microarray technology and thus addresses the early detection problem.

Summary of the Invention

Disclosed herein is a method of using an oligonucleotide microarray to detect cancer in a patient from nucleic acid in serum from the patient. The method comprises: (a) extracting nucleic acids from a serum sample from a patient; (b) hybridizing the nucleic acids to a microarray having selected oligonucleotide probes to form hybridized nucleic acids, wherein the oligonucleotide probes are attached to separate and known locations on the microarray, wherein the oligonucleotide probes are synthetic DNA and are comprised of a set of miRNA probe complements, a set of mutated miRNA probe complements corresponding to the miRNA probe complements, and a set of probes that are complements to a set of spike-in control nucleic acids, wherein the set of spike-in control nucleic acids are selected from the group consisting of SEQ ID NO:1 - SEQ ID NO: 15 and the set of miRNA probe complements and the set of mutated miRNA probe complements are selected from the group consisting of SEQ ID NO: 16 - SEQ ID NO: 210; (c) labeling of the nucleic acids on the microarray; (d) scanning the microarray to determine a signal strength at each known location, wherein the signal strength is a measure of the amount of nucleic acid hybridized to the oligonucleotide probe at each separate and known location; (e) calculating an miRNA signal for each miRNA from a probe match signal, a probe mismatch signal, and a spike-in signal; and (f) determining a cancer score from the miRNA signal for each miRNA in a cancer calling model and comparing the cancer score to a threshold value of the cancer calling model, whereby the patient may have a cancer when the cancer score exceeds the threshold value. Preferably, the labeling step (c) further comprises: (ci) attaching biotin to the hybridized nucleic acids on the microarray to form biotinylated nucleic acids; and (c₂) labeling of the biotinylated nucleic acids on the microarray using streptavidin-Cy5.

Brief Description of the Drawings

Fig. 1 provides results of an assay sensitivity of miRNA on a microarray. RNA miRNA analog oligonucleotides at concentrations ranging from 0 to 40 million copies per microliter were spiked into 400 ul of serum after the addition of RLT buffer. RNA was then extracted from the serum using phenol/chloroform extractions and an ethanol precipitation. Samples were then labeled and hybridized on a microarray. Vertical bars indicate array signal intensities for specific miRNA probes representing the wild type sequence (Wild) and probes with two internal mutations (mut) for (A) oar|miR-431 and (B) oar|miR-127. Scales for the 4,000 and 0 copies data points (boxed in left panels) are expanded in the right panels: (C) oar|miR-431, and (D) oar|miR-127.

Fig. 2 provides results of up-regulation of cancer sera miRNAs over normal donor sera miRNAs. Log transformed normal donor serum miRNA signals (solid line) were compared to miRNA array signals from a prostate cancer cell line 22Rv (open squares) and from a prostate cancer patient (closed diamonds). In general, cancer and cell line miRNAs seem to be up- regulated when compared to normal donor serum miRNAs.

Fig. 3 displays an analysis of microRNA data for normal and prostate cancer sera. After data set normalization, the natural log of the ratio of the signal for a specific probe over the same probe from the normal serum sample was taken. 15 miRNAs showed up-regulation in all stage 3 and 4 prostate cancer samples when compared to sera from normal male donors. These miRNAs are listed below each data set. Five stage 3 and 4 prostate cancer sera, and 8 normal male donor sera were analyzed. Vertical lines indicate plus or minus one standard deviation of the mean.

Fig. 4 shows an analysis of the signal from perfect match (wild type) and miss-match (double mutant) miRNA probes (pm/mm ratio). (A) Analysis of signal from normal serum; (B) Analysis of signal from 22RvI cell culture; and (C) signal from prostate cancer patient serum. Z-scores (blue lines) were determined by subtracting the signal at each probe by the mean of the test probes from the entire hybridization, and then, by dividing the resulting value by the standard deviation of the signal across test probes, across the entire hybridization.

Fig. 5 shows hierarchical clustering of microarray data (Spearman). Cancer samples and normal donor samples (brackets) were clustered using a hierarchical clustering program to show sample-to-sample relationships. Sample labels include donor condition (cancer type or normal), sample lot number (last three digits), gender, and cancer stage (2 - 4, or 0 for normal). Labels marked with a or b indicate repeat testing of the same sample.

Fig. 6 shows an embodiment of a method disclosed herein.

Fig. 7 displays an analysis of microRNA data for female normal and ovarian cancer sera. After data set normalization, the natural log of the ratio of the signal for a specific probe over the same probe from the normal serum sample was taken. 14 miRNAs showed up- regulation in all ovarian cancer samples when compared to sera from normal male donors. These miRNAs are listed below each data set. Ten ovarian cancer sera and 10 normal female donor sera were analyzed. Vertical lines indicate plus or minus one standard deviation of the mean.

Fig. 8 displays an analysis of microRNA data for male normal and male colon cancer sera. After data set normalization, the natural log of the ratio of the signal for a specific probe over the same probe from the normal serum sample was taken. 13 miRNAs showed up- regulation in male prostate cancer samples when compared to sera from normal male donors. These miRNAs are listed below each data set. Two male colon cancer sera, and 5 normal male donor sera were analyzed. Vertical lines indicate plus or minus one standard deviation of the mean.

Fig. 9 displays an analysis of microRNA data for female normal and female colon cancer sera. After data set normalization, the natural log of the ratio of the signal for a specific probe over the same probe from the normal serum sample was taken. 15 miRNAs showed up- regulation in female colon cancer samples when compared to sera from normal female donors. These miRNAs are listed below each data set. Two female colon cancer sera, and 5 normal female donor sera were analyzed. Vertical lines indicate plus or minus one standard deviation of the mean. Fig. 10 displays an analysis of microRNA data for female normal and female breast cancer sera. After data set normalization, the natural log of the ratio of the signal for a specific probe over the same probe from the normal serum sample was taken. 14 miRNAs showed up- regulation in female breast cancer samples when compared to sera from female male donors. These miRNAs are listed below each data set. Two female breast cancer sera, and 5 normal female donor sera were analyzed. Vertical lines indicate plus or minus one standard deviation of the mean.

Fig. 11 displays an analysis of microRNA data for female normal and female lung cancer sera. After data set normalization, the natural log of the ratio of the signal for a specific probe over the same probe from the normal serum sample was taken. 15 miRNAs showed up- regulation in female lung cancer samples when compared to sera from normal male donors. These miRNAs are listed below each data set. 2 female lung cancer sera, and 4 normal female donor sera were analyzed. Vertical lines indicate plus or minus one standard deviation of the mean.

Fig. 12 displays an analysis of microRNA data for female normal and female lung cancer sera. After data set normalization, the natural log of the ratio of the signal for a specific probe over the same probe from the normal serum sample was taken. 16 miRNAs showed up- regulation in female lung cancer samples when compared to sera from normal male donors. These miRNAs are listed below each data set. 2 female lung cancer sera, and 4 normal female donor sera were analyzed. Vertical lines indicate plus or minus one standard deviation of the mean.

Fig. 13 displays an analysis of microRNA data for female normal and female lung cancer sera. After data set normalization, the natural log of the ratio of the signal for a specific probe over the same probe from the normal serum sample was taken. 15 miRNAs showed up- regulation in female lung cancer samples when compared to sera from normal male donors. These miRNAs are listed below each data set. 2 female lung cancer sera, and 4 normal female donor sera were analyzed. Vertical lines indicate plus or minus one standard deviation of the mean.

Detailed Description Disclosed herein is a method on an oligonucleotide microarray that uses serum miRNAs to discriminate between cancer patient sera and normal donor sera, wherein no amplification step is required. Disclosed herein is a method of using miRNA expression patterns in human serum to determine whether human cancer is present in the source of the serum as compared to normal serum from a human not having cancer. Some of the human subjects having cancer had the following cancers: prostate, colon, ovarian, breast and lung. A high density microarray of oligonucleotide probes is used, wherein the probes are designed based on published miRNAs. This microarray platform allows the simultaneous analysis of all human microRNAs by either fluorescent or electrochemical signals and can be easily redesigned to include newly identified miRNAs. In an embodiment, a sufficient amount of miRNAs are present in one milliliter of serum to detect miRNA expression patterns, without the need for amplification techniques. In another embodiment, amplification is used. In an embodiment, miRNA expression patterns are used to correctly discriminate between normal and cancer patient samples.

In an embodiment, the following method is used to collect blood/plasma/serum from a patient for testing in the method disclosed herein.

(A) Collection Tubes: In an embodiment, the collection tubes are SST tubes selected from the group consisting of BD Vacutainer 8.5ml SST Ref 367988, Greiner Bio One - Vacuette 8ml Serum Separator Clot Activator 455071, BD Vacutainer 3.5ml SST Gold Top Ref 367983, and Corvac 12.5ml Serum Separator Ref 8881.

(B) Clotting: 30 minutes at room temperature.

(C) Centrifugation: The Spin time is 15 min. at 2500 rpm at room temperature and is the same for everyone.

(D) Serum Transfer 1 : Serum is poured off into 3.5 or 5 ml collection tubes and stored at 4°C for up to one week prior to freezing and shipping to the distribution center were serum is stored at -80⁰C until aliquots are ordered.

(E) Serum Transfer 2: The serum is then thawed and aliquoted into a cryogenic vials for shipment on dry ice to customers.

(F) Storage: Initially stored at 4°C for up to a week and then stored at -80⁰C until thawed for aliquoting. In an embodiment, the blood is drawn after a biopsy has been completed and confirmed to be cancer. The time between the biopsy and blood draw can vary significantly. In an embodiment, the blood is drawn without a biopsy being performed or before a biopsy is performed. Patients are not required to fast unless the doctor has asked them to. Patients could have been on antibiotics. All the samples collected are delinked, and there is no knowledge as to whether the patient was fasting or on antibiotics unless it was requested prior to the order.

In an embodiment, the collection tubes are as follows:

(A) BD Vacutainer 8.5ml SST Ref 367988; 16 x 100 mm x 8.5 mL BD Vacutainer® Plus plastic serum tube. Red / grey conventional closure. Paper label. Additive: Clot activator and gel for serum separation. (100/sp, 1000/ca)

(B) Greiner Bio One - Vacuette 8ml Serum Separator Clot Activator 455071 ; These tubes are coated with micronised silica particles which activate clotting when tubes are gently inverted (The clot activators main component is SiO₂) and also contain an inert olefinoligomer barrier gel. (PET plastic tubes)

(C) BD Vacutainer 3.5ml SST Gold Top Ref 367983; 367983 - 13 x 75 mm x 3.5 mL BD Vacutainer® Plus plastic serum tube. Gold BD Hemogard™ closure. Paper label. Additive: Clot activator and gel for serum separation and silicone-coated interior. (100/sp, 1000/ca)

(D) Corvac 12.5ml Serum Separator Ref 8881. Red/grey All Corvac™ tubes contain an inert acrylic gel. Glass powder activates the clotting of blood. Silicone coated tube indicates that the interior surface of the Corvac™ tube has been coated with water-soluble silicone material (glass or plastic).

(A) Collection Tubes: Greiner bio-one vacuette collection tubes Cat # 455071) to collect approximately 15 milliliters (total) of blood for serum. As with the serum tube, the inner wall of the serum gel tube is specially coated with microscopic silica particles, these particles activate the coagulation process. Serum / gel tubes contain a separation gel in the base of the tube. Sterile plastic tubes made from virtually unbreakable PET.

(B) Clotting: Invert the vacutainer tube five times, and then allow blood to clot at room temperature for a minimum of 30 minutes and a maximum of 2 hours. (C) Centrifugation: Centrifuge blood in vacutainer tube for 10 minutes at 130OxG- 150OxG at room temperature

(D) Transfer 1 :Transfer the serum to a 15 milliliter polypropylene conical centrifuge tube with a serological pipette and a 1000 microliter pipettor and Centrifuge the serum in the polypropylene tubes for 10 minutes at 130OxG-150OxG.

(E) Transfer 2: Transfer serum to labeled freezing vials (2 ml Self Standing CryoVial External Thread w/O Ring. BioExpress Cat #T-2871-2A) and store at -70 or -80 degrees.

(F) Storage: Process as soon as possible. Freezing of serum aliquots must occur no longer than 6 hours after blood collection.

In an embodiment, blood/plasma/serum is obtained from patients after diagnosis from biopsy. In an embodiment, blood is taken after this diagnosis, but before treatment. In an embodiment, if surgery occurs, then the pathology report's final diagnosis (stage and grade) is used.

In an embodiment, serum samples are collected after (2-6 weeks) biopsy for prostate cancer. In an embodiment, serum samples are collected prior to biopsy for ovarian cancer. In an embodiment, it is not known whether patients/donors used antibiotics or other drugs. In an embodiment, all ovarian cancer patients fasted prior to the sample being taken. In an embodiment, the patients/donors do not fast.

In an embodiment, the following method is used to collect blood from a patient for testing in the method disclosed herein.

Collection tubes: 30 - 40 mLs of whole blood is collected from the subject into a glass Corvac SST Tube with gel, powdered glass and coated with silicon.

(A) Clotting time: All specimens are allowed to clot at room temperature - Average time of 10 - 60 minutes

(B) Centrifugation: Specimens are centrifuged for at least 10 minutes at the following speeds: 3000 - 3500 RPM

(C) Transfer 1 : Following centrifugation, the separated serum is transferred into a polypropylene storage tube and placed at < -20 C within 6 hours from the time of collection.

(D) Transfer 2: The specimens are then shipped on dry ice where they are in turn thawed and aliquot into 1 ml volumes. (E) Storage: Following aliquoting, these specimens are stored at -80 C.

In an embodiment, the cancer samples are collected under a physician's diagnosis. Any detail on the cancer samples purchased is included on the Case Report Forms sent with the shipment. These reports disclose what the subject's current status is when the blood was drawn, dates and description of any procedures they have had to date, any medications they are taking, and other medical detail that was on their medical chart. In an embodiment, no any additional testing is performed after the sample is drawn, or any "follow-up" on their medical status after the sample is drawn; each subject's medical status and history will be different.

(A) Collection Tubes: 366430 - 16 x 100 mm x 10.0 mL BD Vacutainer® glass serum tube. Red conventional closure. Paper label. No additive, silicone coated (100/sp, 1000/ca)

(B) Clotting Procedure: Invert the tube gently no more than 5 times. Allow the blood to clot for at least 30 minutes but no longer than 1 hour

(C) Centrifugation: Centrifuge at 2200-2500 RPM for at least 15 minutes.

(D) Serum Transfer: Use a pipette to transfer the clear serum to a labeled plastic vial for storage and transportation (plastic 2ml cryogen vials - Fisher brand Cat N: 12- 567501).

(E) Storage: Place the vial in a freezer at -20⁰C to -70⁰C until shipping.

(F) Patient Diagnosis:

In an embodiment, the Blood is drawn from cancer patients based on clinical diagnoses prior to the surgery, and the diagnosis is confirmed pathologically and histologically after the biopsy and the surgery procedure except for custom collections. In an embodiment, standard in-stock blood samples are pre-operative with the complete pathological data that is retrieved upon the surgery after the blood draw.

(A) Collection Tubes: Collect 10ml of blood in a red top tube (serum), a purple top tube (EDTA), and/or green top tube (glass plasma) according to your sites venipuncture Standard Operating Procedure (BD SST, #367988: 16 x 100 mm x 8.5 mL BD Vacutainer® Plus plastic serum tube. Red / grey conventional closure. Paper label. Additive: Clot activator and gel for serum separation. (100/sp, 1000/ca)).

(B) Clotting Procedure: Green top and/or purple top tubes should be will mixed by gently inverting a minimum of 10 times and Specimens will sit for 15-30 minutes at room temperature after collection.

(C) Centrifugation: Specimens will be spun at 3200 rpm for 15 minutes.

(D) Serum Transfer 1 : Plasma from green/purple top tubes will be transferred to a transfer tube using a transfer pipette. Serum from red top tubes will be transferred to a transfer tube. Avoid aspirating red blood cells into the transfer pipette. Specimens must be processed and removed from the cells within 6 hours of draw. Transfer tubes should be labeled serum or plasma.

(E) Serum Storage: Specimens will be stored at 2-6 degrees Celsius. Weekly, or as needed, specimens will be shipped on ice packs.

(F) Final Storage: Store at -80C and ship on Dry Ice.

(G) In an embodiment, the samples are drawn after diagnosis, which is biopsy confirmed. hi an embodiment, the following method is used to collect blood/plasma/serum from a patient for testing in the method disclosed herein.

(A) Tubes: Serum Collection Tubes: 367985 - 16 x 125 mm x 10.0 mL BD Vacutainer® Plus plastic serum tube (transport tube). Red / grey conventional closure. Paper label. Additive: Clot activator and double gel for transport. (100/sp, 1000/ca).

(B) ClottingThe whole blood is collected in each tube, inverted and allowed to clot over a period of approx thirty minutes.

(C) Centrifugation: Tubes are then spun down in an ambient centrifuge (Centrifuge speed (1300 x g) for 10 minutes).

(D) Transfer: aliquotted into 1.0 mL cryovials of serum.

In an embodiment, the nucleic acid (miRNA) from the serum/plasma is extracted and prepared for hybridization to a microarray as follows. Four hundred microliters of serum (or EDTA plasma) are added to each of two, 2-mililiter Axygen microtubes (MCT-200-L-C) containing 500 microliters of Qiagen RLT Lysis buffer (#79216) with 2-mercaptoethanol (following Qiagen protocol) and containing positive control spike-in, RNA oligonucleotides. Each tube is vortexed for 10 seconds and allowed to sit at room temperature for 2 minutes. Serum protein and DNA extraction is accomplished by the addition of 850 microliters of acid phenolichloroform (5:1) (Ambion AM9722) to each tube and vortexing each tube for 10 seconds. The two tubes are then centrifuged at 16000 xg for 30 minutes at room temperature (26⁰C) (Eppendorf Centrifuge 5415C), and if a white precipitate remains in the aqueous phase, the tubes are centrifuged for an additional 10 minutes. Seven hundred microliters of the upper aqueous phases are carefully removed from each tube and added to new, 2-ml tubes containing 800 microliters of acid phenolxhloroform each. These tubes are vortexed for 10 seconds and then centrifuged at 16000xg for 30 minutes at room temperature (26°C). Four hundred microliters of each aqueous phase are carefully pipetted from each tube and combined into a single 1.5 ml Axygen microrube (MCT- 150-L-C).

Precipitation of nucleic acids is accomplished by the addition of 75 micrograms of Ambion GlycoBlue (AM9515), 10 microliters of 5 M NaCl, and 900 microliters of 100% isopropanol. The tube is inverted 5 times to mix the solution and then incubated at minus 20⁰C for at least 2 hours. Sample tubes are then centrifuged for 30 minutes at 20,000 rcf, at 4⁰C. The resulting pellet is washed twice by the removal of liquid and the addition of cold 75% ethanol. After the second wash, the tube is air dried, but not to complete dryness of the pellet. The pellet is then resuspended in 9 microliters of molecular grade water and then 21 microliters of hybridization buffer are added and mixed by gently pipetting and briefly centrifuging to bring down contents. Hybridization buffer contains 9 microliters of 2OX SSPE (or 2OX SSC), 4.8 microliters of BSA at 50 mg/ml (Ambion AM2616), 3.6 microliters of deionized formamide (Ambion), and 3.75 microliters of 20% sodium dodecylsulfate (Ambion AM9820) (or 20% N-Lauroylsarcosine sodium salt (Sigma L9150)).

In an embodiment, the prepared nucleic acid is hybridized to a microarray as follows. Prior to hybridization to the microarray, the microarray is blocked with a prehybridization buffer and incubated at 45°C for 15 minutes. The prehybridization buffer contains 3 mis of 2OX SSPE (or 2OX SSC), 50 microliters of 10% tween-20, 280 microliters of 0.5 M EDTA, 750 microliters of 1% sodium dodecylsulfate (Ambion AM9820) (or 1% N-Lauroylsarcosine sodium salt (Sigma L9150)), 1.0 ml of 50X Denhardt's solution, and 4.92 ml of molecular grade water. After preblocking, the prehybridization buffer is removed from the microarray and replaced with the sample in hybridization buffer as described above. The array is then incubated at 45°C for 4 hours with rotation.

In an embodiment, the hybridized nucleic acid is labeled with biotin by the following method. After hybridization of sample, the array is washed 3 times with 2X SSC plus 0.1% sodium dodecylsulfate (or 0.1% N-Lauroylsarcosine sodium salt); 3 times with 2X SSC, 2 times with 0.2X SSC, and 2 times with IX Klenow polymerase buffer (New England Biolabs; NEB2). The hybridized target is then labeled by the addition of a labeling solution that contains 5 microliters of biotin- 1 1-dATP (PerkinElmer #NEL54000) and 2 microliters (100 Units) of Klenow fragment, exonuclease minus (New England Biolabs #M0212M) mixed with 193 microliters of IX NEB2 buffer (Klenow fragment, exonuclease plus can also be used for labeling). The array is incubated with labeling solution for 30 min at 37°C with rotation and then washed 2 times with IX Klenow polymerase buffer (New England Biolabs NEB2), 3 times with 2X SSC plus 0.1% sodium dodecylsulfate (or 0.1% N-Lauroylsarcosine sodium salt); 3 times with 2X SSC, and 2 times with 0.2X SSC.

In an embodiment, the hybridized nucleic acid is labeled with a dye by the following method. Prior to labeling hybridized target with a fluorescent dye, the array is blocked for 15 minutes at room temperature. Blocking is achieved by first washing the array one time with blocking buffer (5X phosphate buffered saline/casein (5X PBS/Casein) (BioFX #PBSC-1000- 01) and then replacing with fresh blocking solution. The blocking solution is next removed and replaced with Streptavidin-Cy5 (SA-Cy5; Zymed Laboratories #43-4316) labeling solution and the array is incubated in darkness for 30 minutes at room temperature. The SA- Cy5 labeling solution is prepared by adding 1 microliter of SA-Cy5 to 1000 microliters of the 5X PBS/Casein blocking solution. After labeling with SA-Cy5, the array is washed 3 times with 2X SSC plus 0.1% sodium dodecylsulfate (or 0.1% N-Lauroylsarcosine sodium salt) and 3 times with 2X SSC.

In an embodiment, the microarray is analyzed using a standard fluorescent scanner to determine the pattern of hybridization of the nucleic acid to the probes on the microarray. A cover slip with lifter strips is applied to the array while using 2X SSC as an imaging solution. The array is scanned at PMT 500.

In an embodiment, the hybridization pattern is analyzed by the following method to determine whether the source of the serum has cancer. An optical scanner is used to capture an optical image of hybridization pattern, as represented by the fluorescent dye, on a microarray. In a hybridization pattern, each separate location (feature) on the microarray where a specific probe (wild type or mutated wild type) is located has a level of fluorescence that depends upon how much of the fluorescent dye is at that location. The more hybridization of RNA (miRNA) from the serum sample, the more fluorescent dye will be at a location and hence the brightness is more. If there is no hybridization at a location, then the location will appear dark compared to other locations having some amount of hybridization.

In an embodiment, a software tool 'CombiMatrix MicroArray Imager' is used to extract a signal value for each feature from the optical scanner image. Any commercial software for analyzing microarray images can be used. Preferably, the microarray features have a regular size, spacing, and a circular shape. The software tool allows a technician to place an ideal set of circular templates over the image, which template describes the exact image pixel area that corresponds to a specific feature's hybridization signal. The tool extracts the pixels that fall inside each circular template and calculates the median signal value for each microarray feature. These median feature signal values are stored with information describing the corresponding microarray probe's name and sequence (wild type or mutated). Preferably, there are multiple features of the microarray that contain the same probe sequence. Preferably, there are two features having the same probe sequence. A probe's signal value is calculated as the median of its redundant feature's signal values. For example, if there are two features having the same probe, then the probe's signal value is the average of the two features. hi an embodiment, arrays for serum miRNA analysis are constructed based on 360 human miRNA sequences obtained from the Sanger database version 12.0. In an embodiment, arrays for serum miRNA analysis are constructed with the nucleic acid probes as provided in Table 1. In an embodiment, three synthetic DNA probes are used for each miRNA: an anti- sensed version of the probe, called the perfect match (PM) probe, and two distinct double- mutant control probes called mis-match (MMl and MM2) probes. The MM control mutations are made by generating a population of randomly mutated probes where two random base substitutions were made along the PM probe sequence. In an embodiment, the mutations are calculated to be disruptive (thermodynamically) to base pairing in hybridization of serum miRNA to the mutated probes. This population of MM is then screened for probes that had no differences in secondary structure, and that had the same notional melting temperature (Tm) as the PM probe. They are also designed to avoid perturbing or creating any secondary structure that may appear in the PM probe.

In an embodiment, also included in the microarray design are a set of five spike-in probe triplets (PM, MMl, MM2) designed in an identical form to the above miRNA probes. Each of these spike-in probe sets are designed to have a very low potential cross hybridization to the miRNA probes. A known, measured quantity of spike-in target is added to the patient sample at the beginning of the sample preparation, and the resulting spike-in signal is used for sample to sample signal normalization. The sample spike-in signal (SSS) is calculated as the mean signal of the five perfect match probes. SSS = mean( SpikePM(l), SpikePM(2) ... SpikePM(5))

In an embodiment, a signal for a specific miRNA is calculated from the combination of the miRNA's three specific probe signal values (PM, MMl, MM2) and the sample global spike-in signal value (SSS). For each miRNA, the mean of the MMl and MM2 probe signals are first combined and then subtracted from the PM probe signal. This value is then normalized to the sample's spike-in signal and if the result is less than zero then the final value is clamped to zero. So the i-th miRNA would have its signal calculated as miRNA(i) = MAX(O, ( PM(i) - mean( MMl(i), MM2(i)) ) * (10000/SSS) ).

In an embodiment, a cancer calling model is a combination of a picked set of miRNA signal values and a threshold. Each cancer calling model set varies from 2-30 miRNA in size. The cancer score is calculated as the mean of the individual miRNA signal values that are part of the model set. This cancer score is then compared to the model threshold and a sample is called cancer if the cancer score is greater than the model threshold value. hi an embodiment, the cancer calling model used to determine whether the source of a serum has a cancer is selected from the group consisting of MC 19, BRH90, A1187, A1180, BI l, B25, B27, B36, B40, B41, B66, and T24, each of which model is further described below. For each model, specific miRNA's are identified for use in the model. The synthetic DNA oligonucleotide probes on the microarray for a specific model are comprised of the complement of each mi-RNA in the model, the complement but with one or more (preferably two) mutations, and the complement of each spike-in controls. The spike in controls are selected from the group consisting of SEQ ID NO:1 through SEQ ID NO: 15. In an embodiment, the model used is MC19, which has a threshold value of 71.0 and uses on a microarray synthetic DNA probes that are designed to detect and make a call on cancer based on the following serum miRNA's: miR-1180, miR-1183, miR-1224-5p, miR- 1250, miR-1290, miR-129-5p, miR-1307, miR-1825, miR-1910, miR-1972, miR-1975, miR- 486-5p, miR-512-5p, miR-574-5p, miR-638, miR-760, miR-765, miR-885-3p, and miR-939.

In an embodiment, the model used is BRH90, which has a threshold value of 169.4 and uses on a microarray synthetic DNA probes that are designed to detect and make a call on cancer based on the following serum miRNA's: miR-1183, miR-1246, miR-1307, miR-15a, miR-1972, and miR-574-5p.

In an embodiment, the model used is A1187, which has a threshold value of 121.0 and uses on a microarray synthetic DNA probes that are designed to detect and make a call on cancer based on the following serum miRNA's: miR-1182, miR-1183, miR-1246, miR-145, miR-1972, miR-574-5p, miR-638, miR-765, and miR-759. hi an embodiment, the model used is A1180, which has a threshold value of 108.2 and uses on a microarray synthetic DNA probes that are designed to detect and make a call on cancer based on the following serum miRNA's: miR-1246, miR-1323, miR-30a, miR-510, miR-574-5p, miR-602, miR-765, and miR-449c.

In an embodiment, the model used is Bl 1, which has a threshold value of 63.7 and uses on a microarray synthetic DNA probes that are designed to detect and make a call on cancer based on the following serum miRNA's: let-7b, miR-1249, miR-1281, miR-1290, miR-1471, miR-1825, miR-1910, miR-1973, miR-214, miR-296-5p, miR-297, miR-34b, miR-589, miR-634, miR-765, miR-886-5p, miR-759, and miR-670.

In an embodiment, the model used is B25, which has a threshold value of 151.8 and uses on a microarray synthetic DNA probes that are designed to detect and make a call on cancer based on the following serum miRNA's: miR-510, miR-548c-5p, rm^'R-574-5p, miR- 603, and miR-765.

In an embodiment, the model used is B27, which has a threshold value of 103.7 and uses on a microarray synthetic DNA probes that are designed to detect and make a call on cancer based on the following serum miRNA's: let-7b, miR-1182, miR-1249, miR-127-3p, miR-1290, miR-574-5p, miR-605, miR-640, and miR-2114. In an embodiment, the model used is B36, which has a threshold value of 203.3 and uses on a microarray synthetic DNA probes that are designed to detect and make a call on cancer based on the following serum miRNA's: let- 7b, miR-1183, miR-1972, miR-320b, miR-574-5p, and miR-765.

In an embodiment, the model used is B40, which has a threshold value of 166.2 and uses on a microarray synthetic DNA probes that are designed to detect and make a call on cancer based on the following serum miRNA's: miR-1972, miR-214, miR-510, miR-574-5p, and miR-765.

In an embodiment, the model used is B41, which has a threshold value of 66.2 and uses on a microarray synthetic DNA probes that are designed to detect and make a call on cancer based on the following serum miRNA's: let- 7b, miR-1290, miR-1307, miR-1972, miR-206, and miR-886-5p.

In an embodiment, the model used is B66, which has a threshold value of 170.6 and uses on a microarray synthetic DNA probes that are designed to detect and make a call on cancer based on the following serum miRNA's: let- 7b, miR-1183, miR-1307, miR-574-5p, and miR-765.

In an embodiment, the model used is T24, which has a threshold value of 82.8 and uses on a microarray synthetic DNA probes that are designed to detect and make a call on cancer based on the following serum miRNA's: miR-1181, miR-1201, miR-124, miR-1246, miR-129-5p, miR-1298, miR-130b, miR-1323, miR-1972, miR-1973, miR-206, miR-20b, miR-220b, miR-223, miR-29a, miR-320a, miR-331-5p, miR-483-5p, miR-510, miR-550, miR-605, miR-654-3p, miR-765, miR-885-5p, miR-670, and miR-2114.

Table 1. List of microarray probes: complement of serum miRNA's, complement of serum miRNA's with mutation(s), and complement of spiked in controls.

Example 1.

In this example, a sufficient quantity of miRNAs was found in less than one ml of human serum to produce a detectable signal on a microarray using fluorescence or electrochemical detection (ECD). Using a simple phenol/chloroform extraction protocol, approximately 1.3 μg of miRNAs was recovered from each 800 μl of serum (average of 18 samples; standard deviation 0.3). The resulting pattern of miRNA expression could be used to distinguish between cancer patients and normal donors. In a further sensitivity experiment, a sufficient quantity of miRNAs was found to be present in one ml of human serum to produce a detectable signal on a microarray using fluorescence or electrochemical detection. At the simplest level, this example has shown that serum miRNAs are up-regulated in cancer patients as compared to normal donors. In a comparison of stages 3 and 4 prostate cancer sera and normal donor serum miRNA levels, we found that 15 miRNAs (miR-16, -92a, -103, -107, -197, -34b, -328, -485-3p, -486-5p, -92b, -574-3p, -636, -640, -766, -885-5p) were up- regulated in serum from prostate cancer patients compared to normal donor sera.

The approximate size of the small RNAs recovered from plasma was determined by isolating large RNA fragments (low ethanol concentration) and small RNA fragments (high ethanol concentration) using an Invitrogen PureLink miRNA isolation kit, after phenol/chloroform extraction and precipitation. The two RNA size fractionations were labeled with biotin (obtained from Minis) and hybridized to a microarray. The results indicated that the vast majority of signal was from the small RNA fraction, which signal was similar to the signal from the un-fractionated sample. In an embodiment, the sensitivity of the miRNA assay was determined by adding dilutions of a synthetic RNA oligonucleotide to our assay during serum extraction. Approximately 4,000 copies of serum microRNAs were detected per microliter of serum as shown in Fig. 1.

Fig. 1 shows RNA miRNA analog oligonucleotides, at concentrations ranging from 0 to 40 million copies per microliter, were spiked into 400 ul of serum after the addition of RLT buffer. RNA was then extracted from the serum using phenol/chloroform extractions and an ethanol precipitation. Samples were then labeled and hybridized on a microarray. Vertical bars indicate array signal intensities for specific miRNA probes representing the wild-type sequence (Wild) and probes with two internal mutations (mut) for (A) oar|miR-431 and (B) oar|miR-127. Scales for the 4,000 and 0 copies data points (boxed in left panels) are expanded in the right panels: (C) oar|miR-431 and (D) oar|miR-127.

This detection level is similar to that reported in Mitchell et al (Mitchell PS, Parkin RK, Kroh EM, Fritz BR, Wyman SK et al. (2008) Circulating microRNAs as stable blood based markers for cancer detection. Proc Nat Acad Sci USA 105: 10513-10518) for the prostate cancer specific microRNA miR-141 using TaqMan assays. miRNA microarrays are relatively more sensitive than standard expression microarrays because small oligonucleotides tend to have better hybridization kinetics than larger RNA or DNA molecules. For miRNAs, both their protection from digestion by various cellular factors and their small size contribute to their detection in serum by microarrays at levels that are as low as those seen with methods that would otherwise be considered more sensitive.

Example 2.

In this example, data was collected from the same serum samples after being frozen at negative 8O⁰C for one week after the initial microRNA assays and was similar to the original data. miRNAs from aliquots of two serum samples from cancer patients (one prostate and one colon) were extracted, labeled, and hybridized to arrays, and after one freeze/thaw event, new aliquots were again extracted, labeled, and hybridized to a second array. Data sets from re- assayed prostate cancer sample 811 and colon sample 792 showed strong correlations when raw array data were compared (r² = 0.94 and 0.96 respectively). This result indicates that the assay is reproducible and stable over time.

Example 3.

In this example, several prostate, ovarian, colon, breast and lung cancer serum samples as well as normal male and female donor sera were analyzed on a pan-miRNA microarray to ascertain serum miRNA profiles and to confirm the specificity of the profiles for different cancers and normal donors. Several data analysis methods were tested to determine the most relevant method for the discrimination of cancer versus normal. For preliminary analysis, serum miRNA probe signals were Iog₂-transformed from a normal donor and compared to Iog₂-transformed probe data from a prostate cancer patient and from a prostate cancer cell line. Although both the prostate cancer serum sample and the prostate cancer cell line (22RvI) sample showed up-regulation compared to a normal serum sample, they did not show much similarity to each other. There is a relative up-regulation of serum miRNAs in cancer as compared to serum from normal donors as shown in Fig. 2. Fig. 2 shows Log transformed normal donor serum miRNA signals (solid line) as compared to miRNA array signals from a prostate cancer cell line 22Rv (open squares) and to a prostate cancer patient (closed diamonds). In general, cancer and cell line miRNAs seem to be up-regulated when compared to normal donor serum miRNAs. Example 4.

To determine the sensitivity of one embodiment of the inventive assay, RNA miRNA analog oligonucleotides (IDT) were purchased for spiking. The concentrations ranged from 0 to 40,000,000 copies per microliter and were spiked into 400 μl of normal human serum after the addition of RLT buffer. RNA was then extracted from the serum using acid phenol/chloroform extractions and an ethanol precipitation. Samples were then labeled with biotin and hybridized on a microarray.

The approximate size of the small RNAs recovered from serum was determined by isolating large RNA fragments (low ethanol concentration) and small RNA fragments (high ethanol concentration) using the Invitrogen PureLink miRNA isolation kit, after phenol/chloroform extraction and precipitation. The two RNA size fractionations were labeled with biotin (Mirus) and hybridized to a microarray as described above.

All human miRNA sequences were taken from the Sanger miRBase 12.0. Three probes were designed for each miRNA sequence: (1) antisense to wild type (has|let-71 |as|, SEQ ID NO. 214, AACTA TACAA CCTAC TACCT CA); (2) double-mutated antisense (has|let-7a|as|2mut|, SEQ ID NO. 215, AACTA TAGAA CCTAC TTCCT CA); and (3) sense negative control probes (has|let-7a|s|, SEQ ID NO. 216, TGAGG TAGTA GGTTG TATAG TT) (included if the corresponding sequence was not found in miRNA databases). The double-mutant control mutations were screened in order to maintain the same notional melting temperature (Tm) as the wild-type Tm. They were also designed to avoid perturbing or creating any secondary structure that may appear in the wild-type probe. In addition to the 547 human miRNAs, we also included as controls four sheep, three C. elegans, and two human sequences. These arrays were initially evaluated using a Cy5 fluorescence-detection system but can be converted to a more sensitive electrochemical system (ECD: ElectraSense®).

Example 5.

In this example, a minimal set of probes was obtained, wherein the probes would allow discrimination between prostate and normal serum samples. Signal from each miRNA probe was first background corrected using negative control probes. Subsequently, each miRNA probe was expressed as the natural log of the ratio between itself and the same probe in a normal human male serum sample. This gives a value of 0 for all the base serum sample probes and an up or down regulation with respect to that sample (normal) for all the other samples (normal and cancer). Fig. 3 shows the ratios of a subset of probes that passed multiple criteria. All prostate cancer probe data sets were filtered to remove all probes whose perfect match signal was not greater than its mutant signal. Fifteen miRNAs were found to be over-expressed in serum from all stage 3 and 4 prostate cancer patients (miR-16, -92a, -103, - 107, -197, -34b, -328, -485-3p, -486-5p, -92b, -574-3p, -636, -640, -766, -885-5p) with respect to 8 normal controls (Fig. 3). This analysis also showed a slightly elevated signal for miR-141 in stage 3 and 4 prostate cancer patient sera (mean = 829, STD = 201) over normal donor sera (mean = 555, STD = 64); as demonstrated by Mitchell et al [7] with RT-PCR.

Fig. 4 shows a plot of z-score-corrected signal intensities for three hybridizations. Z- score normalization was computed by subtracting the signal at each probe by the mean of the test probes from the entire hybridization, and then, by dividing that value by the standard deviation of the signal across test probes, across each hybridization. This normalization yields probe signals that are centered and normalized to a mean of 0 and a standard deviation of 1.0. For each plot, signal was sorted from highest to lowest intensity, and plotted as a solid line. Perfect match / mismatch (pm/mm) ratios were plotted as open triangles over the signal intensity line. Clearly, probes with higher intensities have significantly higher pm/mm ratios. For signal from a miRNA to be considered significant, its perfect match (wild-type anti-sense) probe signal must be greater than that of its double mutant negative control (mm) probe. Specifically, the pm/mm ratio must be greater than 1.5 (plotted on the right-hand side y-axis). By this metric, at least 34 probes were considered significant for the normal serum sample (Fig. 4A). For the prostate cancer cell line 22RvI sample and prostate cancer serum sample (Fig. 4 B and C), there were 57 and 62 significant probes respectively. At the simplest level, the fact that most of the probes that have high signal also have high pm/mm ratios, indicates that the signals we are reading are real. We also performed several non-miRNA negative control hybridizations. For these hybridizations, although some probes have a higher signal than others, this is not accompanied by a corresponding increase in the pm/mm ratios (not shown).

Hierarchical clustering was used to group samples from different disease and normal states (Fig. 5). The dataset used for clustering contained 35 serum samples that were a mixture of normal serum and cancer serum samples of diverse types and severity (stages) (see Tables 1 and 2). Since most of the miRNAs used on the microarray are not present at detectable levels in most serum samples, clustering was only performed on a subset of the miRNAs. This subset was drawn from the group of miRNAs that were judged to be significant. Only signal from miRNA probe sets that were found to have been significant in at least five hybridizations across the entire data set were taken and used for further analysis. Signal from test probes (wild-type anti-sense) was Iog₂-transformed. These probes were then normalized by conversion to Z-score. Only test probes, not any of the negative controls or spike-ins, were used for this calculation. Signal was then thresholded based on significance. Hierarchical clustering was performed using a program written in-house that uses the spearman rank correlation as the distance function. The output for this program is a dendrogram that was displayed using the program Treeview (Page RDM (1996) TREEVIEW: An application to display phylogenetic trees on personal computers. Comput Appl Biosci 12:357-358). Clustering indicates a clear demarcation between normal and most cancer samples (Fig. 5).

To further explore the miRNAs responsible for the clustering, Heat maps were used to look for similarities between miRNA expression patterns within each sample. This method is most effective when rows and columns are ordered to allow these patterns to be easily identified. Clustering was thus used to give this ordering (by identifying miRNAs that have similar expression patterns, and arranging them in close proximity). This data was ported to the open source program, Cluster. The raw data for both sample and miRNA signal were median centered and then clustered using average linkage, spearman rank coefficient as a distance function. Heatmaps were displayed using Treeview software. This method resulted in a clear ordering of the samples taken from our test-set. Samples were labeled with a unique identifier. Serum samples from patients with colon, prostate, ovarian, breast and lung cancer in various stages of disease and treatment were used in this dataset. This analysis resulted in two main branches: one major cluster of sequences containing most of the cancer samples, and a second branch containing the normal group along with a second cancer group. The set of miRNAs used for analysis was chosen based on significance in at least 5 hybridizations. A probe-set was judged significant if the ratio of perfect-match (PM) /mismatch (MM) probes was greater than 1.5. Signal for those miRNAs was extracted from each hybridization and was calculated as PM - MM. For each hybridization, signal was median normalized over the extracted probes and Average Linkage Clustering was performed using a Spearman Rank Correlation. Clustering was visualized using the program Tree View. K-means (K*, Cleary and Tn gg, 1995) clustering was tried using these selected (65) miRNA attributes. 3 cancer samples were misclassifϊed using these attributes, so other attributes needed to be selected.

Example 6.

Arrays for serum miRNA analysis were constructed with 547 human miRNA sequences obtained from the Sanger database version 12.0. Three probes were written for each miRNA: an anti-sensed wild-type version, a double-mutant control probe, and a sense control version. Antisense controls were not included if the corresponding antisense miRNA existed in the databases. The double mutant control mutations were screened in order to maintain the same notional melting temperature (Tm) as the wild-type Tm. They were also designed to avoid perturbing or creating any secondary structure that may appear in the wild- type probe. In addition to the 547 human miRNAs, we also included as controls, four sheep, three C. elegans, and two human sequences. These arrays have been initially evaluated using a Cy5 fluorescence detection system, but can be converted to a more sensitive electrochemical system (ECD: EIeCtTaSCnSe¹J. Additional microRNAs can be easily added to the array as they are identified in the Sanger database. Sequences for miRNA probes were extracted from the Sanger database version 12.0. Three probes were designed for each miRNA sequence: (1) antisense to wild type; (2) double mutated antisense ; and (3) sense negative control probes (included if the corresponding sequence was not found in miRNA databases). Hsa-let-7a is used here as an example of our approach to probe design.

22RvI human prostate cancer-derived cells were cultured in standard plastic tissue culture plates in RPMI medium 1640 (GIBCO) supplemented with 10% FBS and 1% penicillin-streptomycin at 37°C in a 5% CO₂ incubator. Cells were harvested in Qiagen RLT buffer and extracted with phenol/chloroform as described below.

Human serum samples were purchased from Bioreclamation, me, Hicksville, NY and include: stages 2 to 4 prostate, stages 1 to 4 colon, stage 4 ovarian, stage 4 breast, and stages 3 and 4 lung cancer sera (Table 1); and sera from normal male and female donors (Table 2). All cancer samples have associated patient data including age, race, gender, chemotherapy, and stage of disease. No information on treatment outcome or on radiation therapy was supplied with samples. Samples were stored at minus 80⁰C until use.

An aliquot of 400 μl of each serum sample was mixed with 500 μl lysis buffer (RLT, Qiagen, Valencia, CA) and 800 μl acid phenol: Chloroform (Ambion, Foster City, CA), vortexed for 30 seconds and centrifuged at 16000 rcf for 10 min at 25°C. The aqueous phase was extracted 2 x with an equal volume of acid phenol: chloroform and centrifuged at 16000 rcf for 10 min at 25°C. The resultant aqueous phase was then precipitated with 0.1 vol 5 M NaCl, 2 μl precipitation enhancer (Minis, Madison, WI), 2 μl GlycoBlue (Ambion) and 2.5 vol 100% ethanol at -20⁰C for at least 1 hr. After centrifugation at 4°C for 30 min, the resulting pellets were washed 2 * with 75% ethanol and the pellets air-dried. MicroRNA was resuspended in 50 μl molecular grade water (Ambion) and quantified with a NanoDrop ND- 1000 spectrophotometer (Thermo Scientific, Wilmington, DE).

Approximately one μg of isolated microRNA was labeled with a Mirus miRN A Biotin labeling kit (MIR8450) following manufacturers directions. Briefly, 1 μg microRNA was diluted to 86 μl with water and 10 μl 10 x buffer was added followed by 4 μl LabelIT biotin labeling reagent and incubation at 37°C for 1 hr. The reaction was stopped with 10 μl stop reagent and the sample precipitated as described above. The dried pellet was re-suspended in 5.1 μl water.

Array sectored chambers (four chambers per array) (CombiMatrix 4><2K arrays™) were filled with 30 μl of Pre-Hybridization Solution (CombiMatrix Corp) and incubated for 10 min at 45°C. MicroRNA was mixed with 9 μl 20^χ SSPE (Ambion), 4.8 μl BSA at 50 mg/ml (Ambion), 3.6 μl deionized formamide (Sigma) and 7.5 μl of 10% SDS (Ambion) and heated to 95°C for 3 min. 30 μl of each sample were added to sectored hybridization chambers, sealed with aluminum tape, and incubated at 45°C for 16 hr with rotation. After hybridization, arrays were washed 1 x with 6 x SSPET at room temperature (RT) for 10 sec (CombiMatrix Corp), 1 x with 3x SSPET at RT for 10 sec and then washed 2 x with 0.5 x SSPET at RT for 10 sec each.

Arrays were blocked with 5* PBS/Casein Blocking Buffer at RT for 10 min and then labeled with either Cy5 labeling solution for fluorescence scanning or HRP Biotin Labeling Solution (CombiMatrix) for ElectraSense reading (CombiMatrix) and incubated for 30 min at RT. Arrays were then washed 2 x with Biotin Wash Solution (2^χ PBST) for 30 sec each at room temp and again washed 2 * with 1 x PBS followed by scanning for fluorescence, or washed 2 x with TMB Rinse Solution (CombiMatrix), followed by one wash with TMB substrate (CombiMatrix) and scanning with an ElectraSense reader (CombiMatrix) after fresh TMB was added.

Example 7.

This example discloses a miRNA extraction and labeling protocol. Four hundred microliters of serum (or EDTA plasma) were added to each of two, 2-mililiter Axygen microtubes (MCT-200-L-C) containing 500 microliters of Qiagen RLT Lysis buffer (#79216) with 2-mercaptoethanol (following Qiagen protocol) and containing positive control spike-in, RNA oligonucleotides. Each tube was vortexed for 10 seconds and allowed to sit at room temperature for 2 minutes. Serum protein and DNA extraction was accomplished by the addition of 850 microliters of acid phenol: chloroform (5:1) (Ambion AM9722) to each tube and vortexing each tube for 10 seconds. The two tubes were then centrifuged at 16000 xg for 30 minutes at room temperature (26°C) (Eppendorf Centrifuge 5415C), and if a white precipitate remained in the aqueous phase, the tubes were centrifuged for an additional 10 minutes. Seven hundred microliters of the upper aqueous phases were carefully removed from each tube and added to new, 2-ml tubes containing 800 microliters of acid phenol: chloroform each. These tubes were vortexed for 10 seconds and then centrifuged at 16000xg for 30 minutes at room temperature (26°C). Four hundred microliters of each aqueous phase were carefully pipetted from each tube and combined into a single 1.5 ml Axygen microtube (MCT- 150-L-C).

Precipitation of nucleic acids was accomplished by the addition of 75 micrograms of Ambion GlycoBlue (AM9515), 10 microliters of 5 M NaCl, and 900 microliters of 100% isopropanol. The tube was inverted 5 times to mix the solution and then incubated at minus 20⁰C for at least 2 hours. Sample tubes were then centrifuged for 30 minutes at 20,000 rcf, at 4°C. The resulting pellet was washed twice by the removal of liquid and the addition of cold 75% ethanol. After the second wash, the tube was air dried, but not to complete dryness of the pellet. The pellet was then resuspended in 9 microliters of molecular grade water and then 21 microliters of hybridization buffer were added and mixed by gently pipetting and briefly centrifuging to bring down contents. Hybridization buffer contained 9 microliters of 2OX SSPE (or 2OX SSC), 4.8 microliters of BSA at 50 mg/ml (Ambion AM2616), 3.6 microliters of deionized formamide (Ambion), and 3.75 microliters of 20% sodium dodecylsulfate (Ambion AM9820) (or 20% N-Lauroylsarcosine sodium salt (Sigma L9150)).

Prior to hybridization to the microarray, the microarray was blocked with a prehybridization buffer and incubated at 45°C for 15 minutes. The prehybridization buffer contained 3 mis of 2OX SSPE (or 2OX SSC), 50 microliters of 10% tween-20, 280 microliters of 0.5 M EDTA, 750 microliters of 1% sodium dodecylsulfate (Ambion AM9820) (or 1% N- Lauroylsarcosine sodium salt (Sigma L9150)), 1.0 ml of 5OX Denhardt's solution, and 4.92 ml of molecular grade water. After preblocking, the prehybridization buffer was removed from the microarray and replaced with the sample in hybridization buffer as described above. The array was then incubated at 45°C for 4 hours with rotation.

After hybridization of sample, the array was washed 3 times with 2X SSC plus 0.1% sodium dodecylsulfate (or 0.1 % N-Lauroylsarcosine sodium salt); 3 times with 2X SSC, 2 times with 0.2X SSC, and 2 times with IX Klenow polymerase buffer (New England Biolabs; NEB2). The hybridized target was then labeled by the addition of a labeling solution that contained 5 microliters of biotin-11-dATP (PerkinElmer #NEL54000) and 2 microliters (100 Units) of Klenow fragment, exonuclease minus (New England Biolabs #M0212M) mixed with 193 microliters of IX NEB2 buffer (Klenow fragment, exonuclease plus can also be used for labeling). The array was incubated with labeling solution for 30 min at 37°C with rotation and then washed 2 times with IX Klenow polymerase buffer (New England Biolabs NEB2), 3 times with 2X SSC plus 0.1% sodium dodecylsulfate (or 0.1% N-Lauroylsarcosine sodium salt); 3 times with 2X SSC, and 2 times with 0.2X SSC.

Prior to labeling hybridized target with a fluorescent dye, the array was blocked for 15 minutes at room temperature. Blocking was achieved by first washing the array one time with blocking buffer (5X phosphate buffered saline/casein (5X PBS/Casein) (BioFX #PBSC-1000- 01) and then replacing with fresh blocking solution. The blocking solution was next removed and replaced with Streptavidin-Cy5 (SA-Cy5; Zymed Laboratories #43-4316) labeling solution and the array was incubated in darkness for 30 minutes at room temperature. The SA- Cy5 labeling solution was prepared by adding 1 microliter of SA-Cy5 to 1000 microliters of the 5X PBS/Casein blocking solution. After labeling with SA-Cy5, the array was washed 3 times with 2X SSC plus 0.1% sodium dodecylsulfate (or 0.1% N-Lauroylsarcosine sodium salt) and 3 times with 2X SSC. A cover slip with lifter strips was applied to the array while using 2X SSC as an imaging solution. The array is scanned at PMT 500.

Claims

What is claimed is:

1. A method of using an oligonucleotide microarray to detect cancer in a patient from nucleic acid in serum from the patient, comprising:

(a) extracting nucleic acids from a serum sample from a patient;

(b) hybridizing the nucleic acids to a microarray having selected oligonucleotide probes to form hybridized nucleic acids, wherein the oligonucleotide probes are attached to separate and known locations on the microarray, wherein the oligonucleotide probes are synthetic DNA and are comprised of a set of miRNA probe complements, a set of mutated miRNA probe complements corresponding to the miRNA probe complements, and a set of probes that are complements to a set of spike-in control nucleic acids, wherein the set of spike-in control nucleic acids are selected from the group consisting of SEQ ID NO:1 - SEQ ID NO: 15 and the set of miRNA probe complements and the set of mutated miRNA probe complements are selected from the group consisting of SEQ ID NO: 16 - SEQ ID NO: 210;

(c) labeling of the nucleic acids on the microarray;

(d) scanning the microarray to determine a signal strength at each known location, wherein the signal strength is a measure of the amount of nucleic acid hybridized to the oligonucleotide probe at each separate and known location;

(e) calculating an miRNA signal for each miRNA from a probe match signal, a probe mismatch signal, and a spike-in signal; and

(f) determining a cancer score from the miRNA signal for each miRNA in a cancer calling model and comparing the cancer score to a threshold value of the cancer calling model, whereby the patient may have a cancer when the cancer score exceeds the threshold value.

2. The method of claim 1, wherein labeling step (c) further comprises:

(ci) attaching biotin to the hybridized nucleic acids on the microarray to form biotinylated nucleic acids; and

(C₂) labeling of the biotinylated nucleic acids on the microarray using strep tavidin-Cy5.

3. The method of claim 1 , wherein the threshold value is 71 , wherein the set of spike-in control nucleic acids are SEQ ID NO:1, SEQ ID NO:4, SEQ ID NO:7, SEQ ID NO: 10, and SEQ ID NO: 13, wherein the set of miRNA probe complements is SEQ ID NO: 19, SEQ ID NO:28, SEQ ID NO:34, SEQ ID NO:46, SEQ ID NO:55, SEQ ID NO:58, SEQ ID NO:64, SEQ ID NO:82, SEQ ID NO:85, SEQ ID NO:88, SEQ ID NO:94, SEQ ID NO:139, SEQ ID NO:145, SEQ ID NO:154, SEQ ID NO:172, SEQ ID NO:181, SEQ ID NO: 184, SEQ ID NO: 187, and SEQ ID NO: 196, wherein the set of mutated miRNA probe complements is SEQ ID NO:20, SEQ ID NO:21, SEQ ID NO:29, SEQ ID NO:30, SEQ ID NO:35, SEQ ID NO:36, SEQ ID NO:47, SEQ ID NO:48, SEQ ID NO:56, SEQ ID NO:57, SEQ ID NO:59, SEQ ID NO:60, SEQ ID NO:65, SEQ ID NO:66, SEQ ID NO:83, SEQ ID NO:84, SEQ ID NO:86, SEQ ID NO:87, SEQ ID NO:89, SEQ ID NO:90, SEQ ID NO:95, SEQ ID NO:96, SEQ ID NO:140, SEQ ID NO:141, SEQ ID NO:146, SEQ ID NO:147, SEQ ID NO: 155, SEQ ID NO: 156, SEQ ID NO: 173, SEQ ID NO: 174, SEQ ID NO: 182, SEQ ID NO: 183, SEQ ID NO: 185, SEQ ID NO: 186, SEQ ID NO: 188, SEQ ID NO: 189, SEQ ID NO: 197 and SEQ ID NO: 198.

4. The method of claim 1 , wherein the serum sample is drawn by a serum sample drawing method, comprising:

(a) collecting a blood sample in a SST tube selected from the group consisting of BD Vacutainer 8.5ml SST Ref 367988, Greiner Bio One - Vacuette 8ml Serum Separator Clot Activator 455071, BD Vacutainer 3.5ml SST Gold Top Ref 367983, and Corvac 12.5ml Serum Separator Ref 8881;

(b) clotting the blood for approximately 30 minutes at room temperature;

(c) centrifuging the blood for approximately 15 minutes at 2500 rpm at room temperature;

(d) pouring off a serum is into 3.5 or 5 ml collection tubes;

(e) storing the serum at approximately 4°C for up to approximately one week;

(f) freezing and storing the serum at approximately -80⁰C;

(g) thawing the serum and aliquoting into a cryogenic vial and storing on dry ice; and

(h) storing at approximately 4⁰C for up to a week and then storing at -8O⁰C until thawing for aliquoting.

5. The method of claim 1, wherein the threshold value is 121, wherein the set of spike-in control nucleic acids are SEQ ID NO:1, SEQ ID NO:4, SEQ ID NO:7, SEQ ID NO:10, and SEQ ID NO:13, wherein the set of miRNA probe complements is SEQ ID NO:25, SEQ ID NO:28, SEQ ID NO:40, SEQ ID NO:73, SEQ ID NO:88, SEQ ID NO: 154, SEQ ID NO:172, SEQ ID NO:184, and SEQ ID NO:199, wherein the set of mutated miRNA probe complements is SEQ ID NO:26, SEQ ID NO:27, SEQ ID NO:29, SEQ ID NO:30, SEQ ID NO:41, SEQ ID NO:42, SEQ ID NO:74, SEQ ID NO:75, SEQ ID NO:89, SEQ ID NO:90, SEQ ID NO: 155, SEQ ID NO: 156, SEQ ID NO: 173, SEQ ID NO: 174, SEQ ID NO: 185, SEQ ID NO: 186, SEQ ID NO:200, and SEQ ID NO:201.

6. The method of claim 1, wherein the threshold value is 169.4, wherein the set of spike-in control nucleic acids are SEQ ID NO:1, SEQ ID NO:4, SEQ ID NO:7, SEQ ID NO-.10, and SEQ ID NO:13, wherein the set of miRNA probe complements is SEQ ID NO:28, SEQ ID NO:40, SEQ ID NO:64, SEQ ID NO:79, and SEQ ID NO: 154, wherein the set of mutated miRNA probe complements is SEQ ID NO:29, SEQ ID NO:30, SEQ ID NO:41, SEQ ID NO:42, SEQ ID NO:65, SEQ ID NO:66, SEQ ID NO:80, SEQ ID NO:81, SEQ ID NO: 146, and SEQ ID NO: 147.

7. The method of claim 1 , wherein the threshold value is 108.2, wherein the set of spike-in control nucleic acids are SEQ ID NO:1, SEQ ID NO:4, SEQ ID NO:7, SEQ ID NO:10, and SEQ ID NO:13, wherein the set of miRNA probe complements is SEQ ID NO:40, SEQ ID NO:70, SEQ ID NO: 121, SEQ ID NO: 142, SEQ ID NO: 154, SEQ ID NO:160, SEQ ID NO:184, and SEQ ID NO:205, wherein the set of mutated miRNA probe complements is SEQ ID NO:41, SEQ ID NO:3420, SEQ ID NO:71, SEQ ID NO:72, SEQ ID NO:122, SEQ ID NO:123, SEQ ID NO:143, SEQ ID NO:144, SEQ ID NO:155, SEQ ID NO:156, SEQ ID NO:161, SEQ ID NO:162, SEQ ID NO:185, SEQ ID NO:186, SEQ ID NO:206, SEQ ID NO:207.

8. The method of claim 1, wherein the threshold value is 63.7, wherein the set of spike-in control nucleic acids are SEQ ID NO:1, SEQ ID NO:4, SEQ ID NO:7, SEQ ID NO: 10, and SEQ ID NO: 13, wherein the set of miRNA probe complements is SEQ ID NO:16, SEQ ID NO:43, SEQ ID NO:52, SEQ ID NO:55, SEQ ID NO:76, SEQ ID NO:82, SEQ ID NO:85, SEQ ID NO:91, SEQ ID NO:103, SEQ ID NO:112, SEQ ID NO:115, SEQ ID NO: 133, SEQ ID NO: 157, SEQ ID NO: 169, SEQ ID NO: 184, SEQ ID NO: 193, SEQ ID NO: 199, and SEQ ID NO:202, wherein the set of mutated miRNA probe complements is SEQ ID NO: 17, SEQ ID NO: 18, SEQ ID NO:44, SEQ ID NO:45, SEQ ID NO:53, SEQ ID NO:54, SEQ ID NO:56, SEQ ID NO:57, SEQ ID NO:77, SEQ ID NO:78, SEQ ID NO:83, SEQ ID NO:84 SEQ ID NO:86, SEQ ID NO:87, SEQ ID NO:92, SEQ ID NO:93, SEQ ID NO: 104, SEQ ID NO: 105, SEQ ID NO:1 13, SEQ ID NO: 114, SEQ ID NO:116, SEQ ID NO: 117, SEQ ID NO: 134, SEQ ID NO: 135, SEQ ID NO: 158, SEQ ID NO: 159, SEQ ID NO: 170, SEQ ID NO:171, SEQ ID NO:185, SEQ ID NO.186, SEQ ID NO:194, SEQ ID NO:195, SEQ ID NO:200, SEQ ID NO:201, SEQ ID NO:203, and SEQ ID NO:204.

9. The method of claim 1 , wherein the threshold value is 151.8, wherein the set of spike-in control nucleic acids are SEQ ID NO:1, SEQ ID NO:4, SEQ ID NO:7, SEQ ID NO: 10, and SEQ ID NO: 13, wherein the set of miRNA probe complements is SEQ ID NO:142, SEQ ID NO:148, SEQ ID NO:154, SEQ ID NO:163, and SEQ ID NO:184, wherein the set of mutated miRNA probe complements is SEQ ID NO:143, SEQ ID NO:144, SEQ ID NO: 149, SEQ ID NO: 150, SEQ ID NO: 155, SEQ ID NO: 156, SEQ ID NO: 164, SEQ ID NO: 165, SEQ ID NO: 185, and SEQ ID NO: 186.

10. The method of claim 1, wherein the threshold value is 103.7, wherein the set of spike-in control nucleic acids are SEQ ID NO:1, SEQ ID NO:4, SEQ ID NO:7, SEQ ID NO:10, and SEQ ID NO:13, wherein the set of miRNA probe complements is SEQ ID NO:16, SEQ ID NO:25, SEQ ID NO:43, SEQ ID NO:49, SEQ ID NO:55, SEQ ID NO:154, SEQ ID NO:166, and SEQ ID NO:175, wherein the set of mutated miRNA probe complements is SEQ ID NO: 17, SEQ ID NO: 18, SEQ ID NO:26, SEQ ID NO:27, SEQ ID NO:44, SEQ ID NO:45, SEQ ID NO:50, SEQ ID NO:51, SEQ ID NO:56, SEQ ID NO:57, SEQ ID NO: 155, SEQ ID NO: 156, SEQ ID NO: 167, SEQ ID NO: 168, SEQ ID NO: 176, and SEQ ID NO: 177.

11. The method of claim 1, wherein the threshold value is 203.3, wherein the set of spike-in control nucleic acids are SEQ ID NO:1, SEQ ID NO:4, SEQ ID NO:7, SEQ ID NO:10, and SEQ ID NO:13, wherein the set of miRNA probe complements is SEQ ID

NO: 16, SEQ ID NO:28, SEQ ID NO:88, SEQ ID NO: 127, SEQ ID NO: 154, and SEQ ID NO: 184, wherein the set of mutated miRNA probe complements is SEQ ID NO: 17, SEQ ID NO: 18, SEQ ID NO:29, SEQ ID NO:30, SEQ ID NO:89, SEQ ID NO:90, SEQ ID NO: 128, SEQ ID NO: 129, SEQ ID NO: 155, SEQ ID NO: 156, SEQ ID NO: 185, and SEQ ID NO: 186.

12. The method of claim 1, wherein the threshold value is 166.2, wherein the set of spike-in control nucleic acids are SEQ ID NO:1, SEQ ID NO:4, SEQ ID NO:7, SEQ ID NO: 10, and SEQ ID NO: 13, wherein the set of miRNA probe complements is SEQ ID NO:88, SEQ ID NO: 103, SEQ ID NO: 142, SEQ ID NO: 154, and SEQ ID NO: 184, wherein the set of mutated miRNA probe complements is SEQ ID NO:89, SEQ ID NO:90, SEQ ID NO:104, SEQ ID NO:103, SEQ ID NO:143, SEQ ID NO:144, SEQ ID NO:155, SEQ ID NO: 156, SEQ ID NO: 185, and SEQ ID NO: 186.

13. The method of claim 1, wherein the threshold value is 66.2, wherein the set of spike-in control nucleic acids are SEQ ID NO:1, SEQ ID NO:4, SEQ ID NO:7, SEQ ID NO:10, and SEQ ID NO:13, wherein the set of miRNA probe complements is SEQ ID

NO: 16, SEQ ID NO:55, SEQ ID NO:64, SEQ ID NO:88, SEQ ID NO:97, and SEQ ID NO:193, wherein the set of mutated miRNA probe complements is SEQ ID NO:17, SEQ ID NO: 18, SEQ ID NO:56, SEQ ID NO:57, SEQ ID NO:65, SEQ ID NO:66, SEQ ID NO:89, SEQ ID NO:90, SEQ ID NO:98, SEQ ID NO:99, SEQ ID NO: 194, and SEQ ID NO: 195.

14. The method of claim 1 , wherein the threshold value is 170.6, wherein the set of spike-in control nucleic acids are SEQ ID NO:1, SEQ ID NO:4, SEQ ID NO:7, SEQ ID NO: 10, and SEQ ID NO: 13, wherein the set of miRNA probe complements is SEQ ID

NO: 16, SEQ ID NO:28, SEQ ID NO:64, SEQ ID NO: 154, and SEQ ID NO: 184, wherein the set of mutated miRNA probe complements is SEQ ID NO: 17, SEQ ID NO: 18, SEQ ID NO:29, SEQ ID NO:30, SEQ ID NO:65, SEQ ID NO:66, SEQ ID NO: 155, SEQ ID NO: 156, SEQ ID NO: 185, and SEQ ID NO: 186.