FIELD OF INVENTION

Provided herein is technology relating to detecting neoplasia and particularly, but not exclusively, to methods, compositions, and related uses for detecting premalignant and malignant neoplasms such as colorectal cancer.

BACKGROUND

Colorectal cancer remains the 2ndmost common cancer in U.S. men and women combined (Siegel R, et al., C A Cancer J Clin 2013; 63:11-30). The underlying biology of progression from precursor lesion to cancer lends itself favorably to screening (Vogelstein B, et al., Science 2013; 339:1546-58). Evidence supports and guidelines endorse any of several tests and strategies (Levin B, et al., Gastroenterology 2008; 134:1570-95; Rex D K, et al., Am J Gastroenterol 2009; 104:739-50; Karl J, et al., Clin Gastroenterol Hepatol 2008; 6:1122-8). From a societal perspective, screening is considered cost-effective (Karl J, et al., Clin Gastroenterol Hepatol 2008; 6:1122-8; Heitman S J, et al., PLoS Med 2010; 7:e1000370; Parekh M, et al., Aliment Pharmacol Ther 2008; 27:697-712; Sharaf R N, et al., Am J Gastroenterol 2013; 108:120-32).

Colorectal cancer arises from accumulated genetic and epigenetic alterations, providing a basis for analysis of stool for tumor-specific changes (Berger B M, et al., Pathology 2012; 44:80-8). Previous large-scale studies of early generation stool-based DNA tests in the screening setting demonstrated only fair sensitivity for colorectal cancer and low sensitivity for advanced adenomas (Ahlquist D A, et al., Ann Intern Med 2008; 149:441-50, W81; Imperiale T F, et al., N Engl J Med 2004; 351:2704-14). Important advances have since been incorporated, including a stabilizing buffer (Boynton K A, et al., Clin Chem 2003; 49:1058-65; Zou H, et al., Cancer Epidemiol Biomarkers Prev 2006; 15:1115-9), more discriminant markers (Ahlquist D A, et al., Gastroenterology 2012; 142:248-56; Bardan E, et al., Israel journal of medical sciences 1997; 33:777-80), platforms with higher analytic sensitivity (Ahlquist D A, et al., Gastroenterology 2012; 142:248-56; Aronchick C A, et al., Gastrointestinal endoscopy 2000; 52:346-52), result determination using a logistic regression analysis rather than individual marker values, and automation.

Although screening reduces colorectal cancer mortality (Mandel J S, et al., N Engl J Med. 1993, 328:1365-71; Hardcastle J D, et al., Lancet. 1996, 348:1472-7; Kronborg O, et al., Scand J Gastroenterol. 2004, 39:846-51; Winawer S J, et al., J Natl Cancer Inst. 1993, 85:1311-8; Singh H, et al., JAMA. 2006, 295:2366-73), observed reductions have been modest (Singh H, et al., JAMA. 2006; 295, 2366-73; Heresbach D, et al., Eur J Gastroenterol Hepatol. 2006, 18:427-33) and more than one half of adults in the United States have not received screening (Meissner H I, Cancer Epidemiol Biomarkers Prev. 2006, 15:389-94).

An emerging approach to cancer screening involves the assay of tumor-specific DNA alterations in bodily samples from cancer patients, such as stool, serum, and urine (Osborn N K, Ahlquist D A. Gastroenterology 2005; 128:192-206; Ahlquist D A, et al., Gastroenterology 2000; 119:1219-27; Ahlquist D A, et al., Gastroenterology 2002; 122:Suppl A40; Chen W D, et al., J Natl Cancer Inst 2005; 97:1124-32; Zou H, et al., Cancer Epidemiol Biomarkers Prev 2006; 15:1115-9; Zou H Z, Clin Cancer Res 2002; 8:188-91; Hoque M O, J Clin Oncol 2005; 23:6569-75; Belinsky S A, et al., Cancer Res 2006; 66:3338-44; Itzkowitz S H, et al., Clin Gastroenterol Hepatol 2007; 5:111-7′ Kann L, et al., Clin Chem 2006; 52:2299-302). It is important to select markers with high accuracy if efficiency and effectiveness are to be achieved in a cancer screening application. Due to the molecular heterogeneity of colorectal neoplasia, high detection rates often require a panel of markers.

Several methylated genes have been detected in the stool and serum/plasma samples from colorectal cancer patients (Ahlquist D A, Gastroenterology 2002; 122:Suppl A40; Chen W D, et al., J Natl Cancer Inst 2005; 97:1124-32; Zou H Z, et al., Clin Cancer Res 2002; 8:188-91; Itzkowitz S H, et al., Clin Gastroenterol Hepatol 2007; 5:111-7; Petko Z, et al., Clin Cancer Res 2005; 11:1203-9; Muller H M, et al., Lancet 2004; 363:1283-5; Leung W K, et al., Clin Chem 2004; 50:2179-82; Ebert M P, et al., Gastroenterology 2006; 131:1418-30; Grady W M, et al., Cancer Res 2001; 61:900-2). Whereas some methylated genes have been found in a majority of colorectal cancers, the yield of bodily fluid-based assays remains suboptimal (Ahlquist D A, et al., Gastroenterology 2002; 122. Suppl A40; Chen W D, et al., J Natl Cancer Inst 2005; 97:1124-32; Zou H, et al., Cancer Epidemiol Biomarkers Prev 2006; 15.1115-9; Zou H Z, Clin Cancer Res 2002; 8:188-91; Belinsky S A, et al., Cancer Res 2006; 66:3338-44; Itzkowitz S H, et al., Clin Gastroenterol Hepatol 2007; 5:111-7; Kann L, et al., Clin Chem 2006; 52:2299-302; Petko Z, et al., Clin Cancer Res 2005; 11:1203-9; Muller H M, et al., Lancet 2004; 363:1283-5; Leung W K, et al., Clin Chem 2004; 50:2179-82; Ebert M P, et al., Gastroenterology 2006; 131:1418-30; Grady W M, et al., Cancer Res 2001; 61:900-2).

More accurate, user-friendly, and widely distributable tools to improve screening effectiveness, acceptability, and access are needed.

SUMMARY

Methylated DNA has been studied as a potential class of biomarkers in the tissues of most tumor types. In many instances, DNA methyltransferases add a methyl group to DNA at cytosine-phosphate-guanine (CpG) island sites as an epigenetic control of gene expression. In a biologically attractive mechanism, acquired methylation events in promoter regions of tumor suppressor genes are thought to silence expression, thus contributing to oncogenesis. DNA methylation may be a more chemically and biologically stable diagnostic tool than RNA or protein expression (Laird (2010) Nat Rev Genet 11: 191-203). Furthermore, in cancers such as sporadic colon cancer, methylation markers offer excellent specificity and are more broadly informative and sensitive than are individual DNA mutations (Zou et al (2007) Cancer Epidemiol Biomarkers Prev 16: 2686-96).

Analysis of CpG islands has yielded important findings when applied to animal models and human cell lines. For example, Zhang and colleagues found that amplicons from different parts of the same CpG island may have different levels of methylation (Zhang et al. (2009) PLoS Genet 5: e1000438). Further, methylation levels were distributed bi-modally between highly methylated and unmethylated sequences, further supporting the binary switch-like pattern of DNA methyltransferase activity (Zhang et al. (2009) PLoS Genet 5: e1000438). Analysis of murine tissues in vivo and cell lines in vitro demonstrated that only about 0.3% of high CpG density promoters (HCP, defined as having >7% CpG sequence within a 300 base pair region) were methylated, whereas areas of low CpG density (LCP, defined as having <5% CpG sequence within a 300 base pair region) tended to be frequently methylated in a dynamic tissue-specific pattern (Meissner et al. (2008) Nature 454: 766-70). HCPs include promoters for ubiquitous housekeeping genes and highly regulated developmental genes. Among the HCP sites methylated at >50% were several established markers such as Wnt 2, NDRG2, SFRP2, and BMP3 (Meissner et al. (2008) Nature 454: 766-70).

Methylated genes have been detected in the blood and stool of patients with colorectal cancer and proposed as candidate screening markers (Ahlquist D A, et al., Gastroenterology 2002; 122. Suppl A40; Chen W D, et al., J Natl Cancer Inst 2005; 97:1124-32; Zou H Z, Clin Cancer Res 2002; 8:188-91; Itzkowitz S H, et al., Clin Gastroenterol Hepatol 2007; 5:111-7; Kann L, et al., Clin Chem 2006; 52:2299-302; Petko Z, et al., Clin Cancer Res 2005; 11:1203-9; Muller H M, et al., Lancet 2004; 363:1283-5; Leung W K, et al., Clin Chem 2004; 50:2179-82; Ebert M P, et al., Gastroenterology 2006; 131:1418-30; Grady W M, et al., Cancer Res 2001; 61:900-2).

Zou and colleagues, for example, evaluated genes frequently methylated in colorectal neoplasia to identify the most discriminant ones (Zou, et al., 2007 Cancer Epidemiol Biomarkers Prev. 16(12):2686-2696). Four genes specifically methylated in colorectal cancer (bone morphogenetic protein 3 (BMP3), EYA2, aristaless-like homeobox-4 (ALX4), and vimentin) were selected from 41 candidate genes and evaluated on 74 cancers, 62 adenomas, and 70 normal epithelia. Methylation status was analyzed qualitatively and quantitatively and confirmed by bisulfite genomic sequencing. Effect of methylation on gene expression was evaluated in five colon cancer cell lines. K-ras and BRAF mutations were detected by sequencing. Methylation of BMP3, EYA2, ALX4, or vimentin was detected respectively in 66%, 66%, 68%, and 72% of cancers; 74%, 48%, 89%, and 84% of adenomas; and 7%, 5%, 11%, and 11% of normal epithelia (P<0.01, cancer or adenoma versus normal). It was concluded that BMP3, EYA2, ALX4, and vimentin genes are methylated in most colorectal neoplasms but rarely in normal epithelia.

Cancer screening is in need of a marker or marker panel for colorectal cancer that is broadly informative and exhibits high specificity for colorectal cancer at the tissue level when interrogated in samples taken from a subject (e.g., a stool sample; a colorectal tissue sample).

Accordingly, provided herein is technology for colorectal cancer screening markers that provide a high signal-to-noise ratio and a low background level when detected from samples taken from a subject (e.g., a stool sample; a colorectal tissue sample; serum sample; blood or blood product).

In experiments conducted during the course of developing embodiments for the present invention, markers were identified in a case-control studies by comparing the methylation state of DNA markers from colorectal tissue of subjects with colorectal neoplasia, adenoma, and/or sessile serrated polyps (SSP) to the methylation state of the same DNA markers from control subjects (e.g., normal tissue such as normal colon) (see, Example 1, Table 1A and B).

For example, experiments conducted during the course of developing embodiments for the present invention demonstrated NDRG4, BMP3, OPLAH, FLI1, PDGFD, SFMBT2 (e.g., SFMBT2_895, SFMBT2_896, SFMBT2_897), CHST2 (e.g., CHST2_7889, and CHST2_7890), VAV3, and DTX1 as effective markers for detecting colorectal cancer within stool samples (see, Example 1 and Table 1A and B).

As described herein, the technology provides a number of methylated DNA markers and subsets thereof (e.g., sets of 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12 or more markers) with high discrimination for colorectal neoplasia (e.g., colorectal cancer, adenoma, SSP). Experiments applied a selection filter to candidate markers to identify markers that provide a high signal to noise ratio and a low background level to provide high specificity, e.g., when assaying distant media (e.g., stool, blood, urine, metastatic tissue, etc.) for purposes of colorectal cancer screening or diagnosis. As such, the technology provides for specific markers and marker combinations for purposes of colorectal cancer screening or diagnosis.

In some embodiments, the technology is related to assessing the presence of and methylation state of one or more of the markers identified herein in a biological sample. These markers comprise one or more differentially methylated regions (DMR) as discussed herein, e.g., as provided in Table 1A and B. Methylation state is assessed in embodiments of the technology. As such, the technology provided herein is not restricted in the method by which a gene's methylation state is measured. For example, in some embodiments the methylation state is measured by a genome scanning method. For example, one method involves restriction landmark genomic scanning (Kawai et al. (1994) Mol. Cell. Biol. 14: 7421-7427) and another example involves methylation-sensitive arbitrarily primed PCR (Gonzalgo et al. (1997) Cancer Res. 57: 594-599). In some embodiments, changes in methylation patterns at specific CpG sites are monitored by digestion of genomic DNA with methylation-sensitive restriction enzymes followed by Southern analysis of the regions of interest (digestion-Southern method). In some embodiments, analyzing changes in methylation patterns involves a PCR-based process that involves digestion of genomic DNA with methylation-sensitive restriction enzymes prior to PCR amplification (Singer-Sam et al. (1990) Nucl. Acids Res. 18: 687). In addition, other techniques have been reported that utilize bisulfite treatment of DNA as a starting point for methylation analysis. These include methylation-specific PCR (MSP) (Herman et al. (1992) Proc. Natl. Acad. Sci. USA 93: 9821-9826) and restriction enzyme digestion of PCR products amplified from bisulfite-converted DNA (Sadri and Hornsby (1996) Nucl. Acids Res. 24: 5058-5059; and Xiong and Laird (1997) Nucl. Acids Res. 25: 2532-2534). PCR techniques have been developed for detection of gene mutations (Kuppuswamy et al. (1991) Proc. Natl. Acad. Sci. USA 88: 1143-1147) and quantification of allelic-specific expression (Szabo and Mann (1995) Genes Dev. 9: 3097-3108; and Singer-Sam et al. (1992) PCR Methods Appl. 1: 160-163). Such techniques use internal primers, which anneal to a PCR-generated template and terminate immediately 5′ of the single nucleotide to be assayed. Methods using a “quantitative Ms-SNuPE assay” as described in U.S. Pat. No. 7,037,650 are used in some embodiments.

Upon evaluating a methylation state, the methylation state is often expressed as the fraction or percentage of individual strands of DNA that is methylated at a particular site (e.g., at a single nucleotide, at a particular region or locus, at a longer sequence of interest, e.g., up to a˜100-bp, 200-bp, 500-bp, 1000-bp subsequence of a DNA or longer) relative to the total population of DNA in the sample comprising that particular site. Traditionally, the amount of the unmethylated nucleic acid is determined by PCR using calibrators. Then, a known amount of DNA is bisulfite treated and the resulting methylation-specific sequence is determined using either a real-time PCR or other exponential amplification, e.g., a QuARTS assay (e.g., as provided by U.S. Pat. Nos. 8,361,720, 8,916,344; and U.S. Pat. Appl. Pub. Nos. 2012/0122088 and 2012/0122106).

For example, in some embodiments methods comprise generating a standard curve for the unmethylated target by using external standards. The standard curve is constructed from at least two points and relates the real-time Ct value for unmethylated DNA to known quantitative standards. Then, a second standard curve for the methylated target is constructed from at least two points and external standards. This second standard curve relates the Ct for methylated DNA to known quantitative standards. Next, the test sample Ct values are determined for the methylated and unmethylated populations and the genomic equivalents of DNA are calculated from the standard curves produced by the first two steps. The percentage of methylation at the site of interest is calculated from the amount of methylated DNAs relative to the total amount of DNAs in the population, e.g., (number of methylated DNAs)/(the number of methylated DNAs+ number of unmethylated DNAs)×100.

According to another aspect of the present invention, neoplasia of a biological sample is indicated when a methylation ratio of one or more DNA methylation markers relative to a level of bisulfite-treated DNA copy number of a reference gene is different, wherein the one or more DNA methylation markers comprises a base in a differentially methylated region (DMR) as provided in Table 1A and B. The methylation ratio includes the ratio of the methylation level of the DNA methylation marker and the level of a region in a reference gene determined by the same means used for the determination of the methylation level of the biomarker. Usually, the methylation ratio is represented by the ratio of the methylation level of the DNA methylation marker and the level of a region in a reference gene determined by the same means used for the determination of the methylation level of the DNA methylation marker.

In some embodiments, the methylation ratio is the ratio of the methylation level of a DNA methylation marker and the level of a region of a reference gene, both of which are quantitatively measured using real-time polymerase chain reaction (PCR). For example, the methylation level of a DNA methylation marker from a sample of a subject can be quantitatively measured using a pair of primers and an oligonucleotide probe, where one primer, both primers, the oligonucleotide probe, or both primers and the oligonucleotide probe are capable of distinguishing between methylated and unmethylated nucleic acid, e.g., after the nucleic acid being modified by a modifying agent, e.g., bisulfite converting unmethylated cytosine to a converted nucleic acid.

The region of a reference gene of the present invention can be any region of a gene having one or more sites or regions that are devoid of methylation sites, e.g., devoid of CpG dinucleotides. For example, the region of a reference gene can be a region that having two primer binding sites for amplification such as PCR that are devoid of CpG dinucleotdies or a region having at least one specific oligonucleotide probe binding site for real-time PCR that is devoid of CpG dinucleotides. In one aspect, the region of a reference gene of the present invention is a region of MYOD gene. In another aspect, the region of a reference gene of the present invention is a region of ACTB gene. In yet another embodiment, the region of a reference gene of the present invention is a region that is not frequently subject to copy number alterations, such as gene amplification or deletion.

In general, according to the present invention the level of a region of a reference gene is quantitatively measured using real-time PCR with primers and specific probes that specifically bind to sites after bisulfite conversion but without discriminating directly or indirectly the methylation status of the sites.

In certain embodiments, methods for detecting neoplasm in a subject are provided. Such methods comprise, for example, obtaining a sample comprising DNA from a subject; treating the obtained DNA with a reagent which selectively modifies unmethylated cytosine residues in the obtained DNA to produce modified residues but which does not modify methylated cytosine residues; determining the methylation level of one or more DNA methylation markers in the DNA having undergone the treating of step b), wherein one or more DNA methylation markers comprises a base in a differentially methylated region (DMR) as provided in Table 1A and B; comparing the determined methylation level of the one or more DNA methylation markers with methylation level references for the one or more DNA methylation markers for subjects not having neoplasm; and identifying the subject as having neoplasm when the methylation state of or more of the DNA methylation markers is different than a methylation state of the marker assayed in a subject that does not have a neoplasm.

In some embodiments, a determination of elevated methylation in one or more of the DNA methylation markers comprises a determination of altered methylation within a region selected from the group consisting of a CpG island and a CpG island shore.

In some embodiments, a determination of elevated methylation within said CpG island or CpG shore comprises elevated methylation within a coding region or a regulatory region of the DNA methylation marker.

In some embodiments, the determining the methylation level of one or more DNA methylation markers in the DNA having undergone the treating of step b) comprises determining the methylation score and/or the methylation frequency of the one or more DNA methylation markers.

In some embodiments, the treating of step b) is accomplished through bisulfite modification of the obtained DNA.

In some embodiments, the determining the methylation level of one or more DNA methylation markers in the DNA having undergone the treating of step b) is achieved by a technique selected from the group consisting of methylation-specific PCR, quantitative methylation-specific PCR, methylation-sensitive DNA restriction enzyme analysis, quantitative bisulfite pyrosequencing, and bisulfite genomic sequencing PCR.

In some embodiments, the neoplasm is colorectal cancer, a large colorectal adenoma, and/or a sessile serrated polyp.

In certain embodiments, methods for detecting neoplasm in a subject are provided. Such embodiments comprise, for example, determining a methylation ratio of a sample from a subject, wherein the methylation ratio is the level of methylation of a bisulfite-treated region of one or more DNA methylation markers relative to a level of bisulfite-treated DNA copy number of a reference gene, wherein the one or more DNA methylation markers comprises a base in a differentially methylated region (DMR) as provided in Table 1A and B, wherein the reference gene is MYOD or ACTB, identifying the subject as having neoplasm when the methylation ratio of one or more of the DNA methylation markers is different than the methylation ratio of the respective marker assayed in a subject that does not have a neoplasm.

In some embodiments, level of methylation is determined by using real-time polymerase chain reaction (PCR). In some embodiments, the level of methylation is determined by using real-time polymerase chain reaction (PCR), wherein at least one primer used in the PCR is capable of distinguishing between unmethylated and methylated nucleic acid. In some embodiments, the level of methylation is determined by using real-time polymerase chain reaction (PCR), wherein both primers used in the PCR are capable of distinguishing between unmethylated and methylated nucleic acid. In some embodiments, the level of methylation is determined by using real-time polymerase chain reaction (PCR), wherein a probe used in the PCR is capable of distinguishing between unmethylated and methylated nucleic acid. In some embodiments, the level of methylation is determined by using real-time polymerase chain reaction (PCR), wherein both primers and a probe used in the PCR are capable of distinguishing between unmethylated and methylated nucleic acid. In some embodiments, the level of the region in the reference gene is determined by using real-time polymerase chain reaction (PCR). In some embodiments, the level of the region in the reference gene is determined by using real-time polymerase chain reaction (PCR), wherein the region contains a first and second primer binding site and a probe binding site and wherein the first and second primer binding site and the probe binding site are devoid of CpG dinucleotides. In some embodiments, the region in the reference gene is devoid of CpG dinucleotides.

Also provided herein are compositions and kits for practicing the methods. For example, in some embodiments, reagents (e.g., primers, probes) specific for one or more markers are provided alone or in sets (e.g., sets of primers pairs for amplifying a plurality of markers). Additional reagents for conducting a detection assay may also be provided (e.g., enzymes, buffers, positive and negative controls for conducting QuARTS, PCR, sequencing, bisulfite, or other assays). In some embodiments, the kits containing one or more reagent necessary, sufficient, or useful for conducting a method are provided. Also provided are reactions mixtures containing the reagents. Further provided are master mix reagent sets containing a plurality of reagents that may be added to each other and/or to a test sample to complete a reaction mixture.

In some embodiments, the technology described herein is associated with a programmable machine designed to perform a sequence of arithmetic or logical operations as provided by the methods described herein. For example, some embodiments of the technology are associated with (e.g., implemented in) computer software and/or computer hardware. In one aspect, the technology relates to a computer comprising a form of memory, an element for performing arithmetic and logical operations, and a processing element (e.g., a microprocessor) for executing a series of instructions (e.g., a method as provided herein) to read, manipulate, and store data. In some embodiments, a microprocessor is part of a system for determining a methylation state (e.g., of one or more DMR, e.g. as provided in Table 1A and B); comparing methylation states (e.g., of one or more DMR, e.g. as provided in Table 1A and B); generating standard curves; determining a Ct value; calculating a fraction, frequency, or percentage of methylation (e.g., of one or more DMR, e.g. as provided in Table 1A and B); identifying a CpG island; determining a specificity and/or sensitivity of an assay or marker; calculating an ROC curve and an associated AUC; sequence analysis; all as described herein or is known in the art.

In some embodiments, a software or hardware component receives the results of multiple assays and determines a single value result to report to a user that indicates a cancer risk based on the results of the multiple assays (e.g., determining the methylation state of multiple DMR, e.g. as provided in Table 1A and B). Related embodiments calculate a risk factor based on a mathematical combination (e.g., a weighted combination, a linear combination) of the results from multiple assays, e.g., determining the methylation states of multiple markers (such as multiple DMR, e.g. as provided in Table 1A and B). In some embodiments, the methylation state of a DMR defines a dimension and may have values in a multidimensional space and the coordinate defined by the methylation states of multiple DMR is a result, e.g., to report to a user, e.g., related to a colorectal cancer risk.

Some embodiments comprise a storage medium and memory components. Memory components (e.g., volatile and/or nonvolatile memory) find use in storing instructions (e.g., an embodiment of a process as provided herein) and/or data (e.g., a work piece such as methylation measurements, sequences, and statistical descriptions associated therewith). Some embodiments relate to systems also comprising one or more of a CPU, a graphics card, and a user interface (e.g., comprising an output device such as display and an input device such as a keyboard).

Programmable machines associated with the technology comprise conventional extant technologies and technologies in development or yet to be developed (e.g., a quantum computer, a chemical computer, a DNA computer, an optical computer, a spintronics based computer, etc.).

In some embodiments, the technology comprises a wired (e.g., metallic cable, fiber optic) or wireless transmission medium for transmitting data. For example, some embodiments relate to data transmission over a network (e.g., a local area network (LAN), a wide area network (WAN), an ad-hoc network, the internet, etc.). In some embodiments, programmable machines are present on such a network as peers and in some embodiments the programmable machines have a client/server relationship.

In some embodiments, data are stored on a computer-readable storage medium such as a hard disk, flash memory, optical media, a floppy disk, etc.

In some embodiments, the technology provided herein is associated with a plurality of programmable devices that operate in concert to perform a method as described herein. For example, in some embodiments, a plurality of computers (e.g., connected by a network) may work in parallel to collect and process data, e.g., in an implementation of cluster computing or grid computing or some other distributed computer architecture that relies on complete computers (with onboard CPUs, storage, power supplies, network interfaces, etc.) connected to a network (private, public, or the internet) by a conventional network interface, such as Ethernet, fiber optic, or by a wireless network technology.

For example, some embodiments provide a computer that includes a computer-readable medium. The embodiment includes a random access memory (RAM) coupled to a processor. The processor executes computer-executable program instructions stored in memory. Such processors may include a microprocessor, an ASIC, a state machine, or other processor, and can be any of a number of computer processors, such as processors from Intel Corporation of Santa Clara, Calif. and Motorola Corporation of Schaumburg, Ill. Such processors include, or may be in communication with, media, for example computer-readable media, which stores instructions that, when executed by the processor, cause the processor to perform the steps described herein.

Embodiments of computer-readable media include, but are not limited to, an electronic, optical, magnetic, or other storage or transmission device capable of providing a processor with computer-readable instructions. Other examples of suitable media include, but are not limited to, a floppy disk, CD-ROM, DVD, magnetic disk, memory chip, ROM, RAM, an ASIC, a configured processor, all optical media, all magnetic tape or other magnetic media, or any other medium from which a computer processor can read instructions. Also, various other forms of computer-readable media may transmit or carry instructions to a computer, including a router, private or public network, or other transmission device or channel, both wired and wireless. The instructions may comprise code from any suitable computer-programming language, including, for example, C, C++, C#, Visual Basic, Java, Python, Perl, and JavaScript.

Computers are connected in some embodiments to a network. Computers may also include a number of external or internal devices such as a mouse, a CD-ROM, DVD, a keyboard, a display, or other input or output devices. Examples of computers are personal computers, digital assistants, personal digital assistants, cellular phones, mobile phones, smart phones, pagers, digital tablets, laptop computers, internet appliances, and other processor-based devices. In general, the computers related to aspects of the technology provided herein may be any type of processor-based platform that operates on any operating system, such as Microsoft Windows, Linux, UNIX, Mac OS X, etc., capable of supporting one or more programs comprising the technology provided herein. Some embodiments comprise a personal computer executing other application programs (e.g., applications). The applications can be contained in memory and can include, for example, a word processing application, a spreadsheet application, an email application, an instant messenger application, a presentation application, an Internet browser application, a calendar/organizer application, and any other application capable of being executed by a client device.

All such components, computers, and systems described herein as associated with the technology may be logical or virtual.

Accordingly, provided herein is technology related to a method of screening for a colorectal neoplasm in a sample (e.g., stool sample, colorectal tissue sample; blood sample; blood product sample) obtained from a subject (e.g., a human subject), the method comprising assaying a methylation state of a marker in a sample obtained from a subject; and identifying the subject as having a colorectal neoplasm when the methylation state of the marker is different than a methylation state of the marker assayed in a subject that does not have a colorectal neoplasm, wherein the marker comprises a base in a differentially methylated region (DMR) selected from a group consisting of a DMR as provided in Table 1A and B. The technology also encompasses determining the state or stage of a colorectal cancer, e.g., in some embodiments the neoplasm is pre-cancerous. Some embodiments provide methods comprising assaying a plurality of markers, e.g., comprising assaying 2 to 10 markers.

The technology is not limited in the methylation state assessed. In some embodiments assessing the methylation state of the marker in the sample comprises determining the methylation state of one base. In some embodiments, assaying the methylation state of the marker in the sample comprises determining the extent of methylation at a plurality of bases. Moreover, in some embodiments the methylation state of the marker comprises an increased methylation of the marker relative to a normal methylation state of the marker. In some embodiments, the methylation state of the marker comprises a decreased methylation of the marker relative to a normal methylation state of the marker. In some embodiments the methylation state of the marker comprises a different pattern of methylation of the marker relative to a normal methylation state of the marker.

Furthermore, in some embodiments the marker is a region of 100 or fewer bases, the marker is a region of 500 or fewer bases, the marker is a region of 1000 or fewer bases, the marker is a region of 5000 or fewer bases, or, in some embodiments, the marker is one base. In some embodiments the marker is in a high CpG density promoter.

The technology is not limited by sample type. For example, in some embodiments the sample is a stool sample, a tissue sample, a colorectal tissue sample, a blood sample (e.g., plasma, serum, whole blood), an excretion, or a urine sample.

Furthermore, the technology is not limited in the method used to determine methylation state. In some embodiments the assaying comprises using methylation specific polymerase chain reaction, nucleic acid sequencing, mass spectrometry, methylation specific nuclease, mass-based separation, or target capture. In some embodiments, the assaying comprises use of a methylation specific oligonucleotide. In some embodiments, the technology uses massively parallel sequencing (e.g., next-generation sequencing) to determine methylation state, e.g., sequencing-by-synthesis, real-time (e.g., single-molecule) sequencing, bead emulsion sequencing, nanopore sequencing, etc.

The technology provides reagents for detecting a DMR, e.g., in some embodiments are provided a set of oligonucleotides comprising the sequences provided by SEQ ID NOs: 1-57. In some embodiments are provided an oligonucleotide comprising a sequence complementary to a chromosomal region having a base in a DMR, e.g., an oligonucleotide sensitive to methylation state of a DMR.

The technology provides various panels of markers, e.g., in some embodiments the marker comprises a chromosomal region having an annotation that is NDRG4, BMP3, OPLAH, FLI1, PDGFD, CHST_7889, SFMBT2_895, SFMBT2_896, SFMBT2_897, CHST2_7890, VAV3, and DTX1, and that comprises the marker (see, Table 1A and B).

In addition, embodiments provide a method of analyzing a DMR from Table 1A and B. Some embodiments provide determining the methylation state of a marker, wherein a chromosomal region having an annotation that is NDRG4, BMP3, OPLAH, FLI1, PDGFD, CHST_7889, SFMBT2_895, SFMBT2_896, SFMBT2_897, CHST2_7890, VAV3, and DTX1 comprises the marker.

Kit embodiments are provided, e.g., a kit comprising a bisulfite reagent; and a control nucleic acid comprising a sequence from a DMR selected from any of the chromosomal regions provided in Table 1A and B and having a methylation state associated with a subject who does not have a cancer. In some embodiments, kits comprise a bisulfite reagent and an oligonucleotide as described herein. In some embodiments, kits comprise a bisulfite reagent; and a control nucleic acid comprising a sequence from a DMR selected from any of the chromosomal regions provided in Table 1A and B and having a methylation state associated with a subject who has colorectal cancer, adenoma and/or SSP. Some kit embodiments comprise a sample collector for obtaining a sample from a subject (e.g., a stool sample); reagents for isolating a nucleic acid from the sample; a bisulfite reagent; and an oligonucleotide as described herein.

The technology is related to embodiments of compositions (e.g., reaction mixtures). In some embodiments are provided a composition comprising a nucleic acid comprising a DMR and a bisulfite reagent. Some embodiments provide a composition comprising a nucleic acid comprising a DMR and an oligonucleotide as described herein. Some embodiments provide a composition comprising a nucleic acid comprising a DMR and a methylation-sensitive restriction enzyme. Some embodiments provide a composition comprising a nucleic acid comprising a DMR and a polymerase.

Additional related method embodiments are provided for screening for a colorectal neoplasm in a sample obtained from a subject, e.g., a method comprising determining a methylation state of a marker in the sample comprising a base in a DMR selected from any of the chromosomal regions provided in Table 1A and B; comparing the methylation state of the marker from the subject sample to a methylation state of the marker from a normal control sample from a subject who does not have a cancer; and determining a confidence interval and/or a p value of the difference in the methylation state of the subject sample and the normal control sample. In some embodiments, the confidence interval is 90%, 95%, 97.5%, 98%, 99%, 99.5%, 99.9% or 99.99% and the p value is 0.1, 0.05, 0.025, 0.02, 0.01, 0.005, 0.001, or 0.0001. Some embodiments of methods provide steps of reacting a nucleic acid comprising a DMR with a bisulfite reagent to produce a bisulfite-reacted nucleic acid; sequencing the bisulfite-reacted nucleic acid to provide a nucleotide sequence of the bisulfite-reacted nucleic acid; comparing the nucleotide sequence of the bisulfite-reacted nucleic acid with a nucleotide sequence of a nucleic acid comprising the DMR from a subject who does not have a cancer to identify differences in the two sequences; and identifying the subject as having a colorectal neoplasm when a difference is present.

Systems for screening for a colorectal neoplasm in a sample obtained from a subject are provided by the technology. Exemplary embodiments of systems include, e.g., a system for screening for a colorectal neoplasm in a sample obtained from a subject, the system comprising an analysis component configured to determine the methylation state of a sample, a software component configured to compare the methylation state of the sample with a control sample or a reference sample methylation state recorded in a database, and an alert component configured to alert a user of a cancer-associated methylation state. An alert is determined in some embodiments by a software component that receives the results from multiple assays (e.g., determining the methylation states of multiple markers, e.g., DMR, e.g., as provided in Table 1A and B) and calculating a value or result to report based on the multiple results. Some embodiments provide a database of weighted parameters associated with each DMR provided herein for use in calculating a value or result and/or an alert to report to a user (e.g., such as a physician, nurse, clinician, etc.). In some embodiments all results from multiple assays are reported and in some embodiments one or more results are used to provide a score, value, or result based on a composite of one or more results from multiple assays that is indicative of a colorectal cancer risk in a subject.

In some embodiments of systems, a sample comprises a nucleic acid comprising a DMR. In some embodiments the system further comprises a component for isolating a nucleic acid, a component for collecting a sample such as a component for collecting a stool sample. In some embodiments, the system comprises nucleic acid sequences comprising a DMR. In some embodiments the database comprises nucleic acid sequences from subjects who do not have a cancer. Also provided are nucleic acids, e.g., a set of nucleic acids, each nucleic acid having a sequence comprising a DMR. In some embodiments the set of nucleic acids wherein each nucleic acid has a sequence from a subject who does not have a cancer. Related system embodiments comprise a set of nucleic acids as described and a database of nucleic acid sequences associated with the set of nucleic acids. Some embodiments further comprise a bisulfite reagent. And, some embodiments further comprise a nucleic acid sequencer.

The technology is related to embodiments of compositions (e.g., reaction mixtures). In some embodiments are provided a composition comprising a nucleic acid comprising a DMR (e.g., a DMR as provided in Table 1A and B) and a bisulfite reagent. Some embodiments provide a composition comprising a nucleic acid comprising a DMR and an oligonucleotide as described herein. Some embodiments provide a composition comprising a nucleic acid comprising a DMR and a methylation-sensitive restriction enzyme. Some embodiments provide a composition comprising a nucleic acid comprising a DMR and a polymerase.

Additional embodiments will be apparent to persons skilled in the relevant art based on the teachings contained herein.

