DETECTING BREAST CANCER

Abstract
Provided herein is technology for breast cancer screening and particularly, but not exclusively, to methods, compositions, and related uses for detecting the presence of breast cancer.
Description
FIELD OF INVENTION

Provided herein is technology for breast cancer screening and particularly, but not exclusively, to methods, compositions, and related uses for detecting the presence of breast cancer.


BACKGROUND

Breast cancer affects approximately 230,000 US women per year and claims about 40,000 lives every year. Although carriers of germline mutations in BRCA1 and BRCA2 genes are known to be at high risk of breast cancer, most women who get breast cancer do not have a mutation in one of these genes and there is limited ability to accurately identify women at increased risk of breast cancer. Effective prevention therapies exist, but current risk prediction models do not accurately identify the majority of women at increased risk of breast cancer (see, e.g., Pankratz V S, et al., J Clin Oncol 2008 Nov. 20; 26(33):5374-9).


Improved methods for detecting breast cancer are needed.


The present invention addresses these needs.


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 other cancers like 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 Prey 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).


Epigenetic methylation of DNA at cytosine-phosphate-guanine (CpG) island sites by DNA methyltransferases has been studied as a potential class of biomarkers in the tissues of most tumor types. In a biologically attractive mechanism, acquired methylation events in promotor regions of tumor suppressor genes are thought to silence expression, contributing to oncogenesis. DNA methylation may be a more chemically and biologically stable diagnostic tool than RNA or protein expression. Furthermore, in other cancers like sporadic colon cancer, aberrant methylation markers are more broadly informative and sensitive than are individual DNA mutations and offer excellent specificity.


Several methods are available to search for novel methylation markers. While micro-array based interrogation of CpG methylation is a reasonable, high-throughput approach, this strategy is biased towards known regions of interest, mainly established tumor suppressor promotors. Alternative methods for genome-wide analysis of DNA methylation have been developed in the last decade. There are three basic approaches. The first employs digestion of DNA by restriction enzymes which recognize specific methylated sites, followed by several possible analytic techniques which provide methylation data limited to the enzyme recognition site or the primers used to amplify the DNA in quantification steps (such as methylation-specific PCR; MSP). A second approach enriches methylated fractions of genomic DNA using anti-bodies directed to methyl-cytosine or other methylation-specific binding domains followed by microarray analysis or sequencing to map the fragment to a reference genome. This approach does not provide single nucleotide resolution of all methylated sites within the fragment. A third approach begins with bisulfate treatment of the DNA to convert all unmethylated cytosines to uracil, followed by restriction enzyme digestion and complete sequencing of all fragments after coupling to an adapter ligand. The choice of restriction enzymes can enrich the fragments for CpG dense regions, reducing the number of redundant sequences which may map to multiple gene positions during analysis.


RRBS yields CpG methylation status data at single nucleotide resolution of 80-90% of all CpG islands and a majority of tumor suppressor promoters at medium to high read coverage. In cancer case—control studies, analysis of these reads results in the identification of differentially methylated regions (DMRs). In previous RRBS analysis of pancreatic cancer specimens, hundreds of DMRs were uncovered, many of which had never been associated with carcinogenesis and many of which were unannotated. Further validation studies on independent tissue samples sets confirmed marker CpGs which were 100% sensitive and specific in terms of performance.


Provided herein is technology for breast cancer screening and particularly, but not exclusively, to methods, compositions, and related uses for detecting the presence of breast cancer.


Indeed, as described in Examples I, II and III, experiments conducted during the course for identifying embodiments for the present invention identified a novel set of differentially methylated regions (DMRs) for discriminating cancer of the breast derived DNA from non-neoplastic control DNA.


Such experiments list and describe 375 novel DNA methylation markers distinguishing breast cancer tissue from benign breast tissue (see, Tables 2 and 5, Examples I, II and III).


From these 375 novel DNA methylation markers, further experiments identified the following markers and/or panels of markers capable of distinguishing breast cancer tissue from benign breast tissue:

    • ATP6V1B1, LMX1B_A, BANK1, OTX1, MAX.chr11.14926602-14927148, UBTF, PRKCB, TRH_A, MPZ, DNM3_A, TRIM67, MAX.chr12.4273906-4274012, CALN1_A, ITPRIPL1, MAX.chr12.4273906-4274012, GYPC_B, MAX.chr5.42994866-42994936, OSR2_A, SCRT2_B, MAX.chr5.145725410-145725459, MAX.chr11.68622869-68622968, MAX.chr8.124173030-124173395, MAX.chr20.1784209-1784461, LOC100132891, BHLHE23_D, MAX.chr19.46379903-46380197, CHST2_B, MAX.chr5.77268672-77268725, C17orf64, EMX1_A, DSCR6, ITPRIPL1, IGF2BP3_B, DLX4, and ABLIM1 (see, Table 4, Example II); and
    • ABLIM1_B, AJAP1_C, ALOX5_B, ASCL2_B, BANK1_B, BHLHE23_E, C10orf125_B, C17orf64_B, CALN1_1520, CALN1_B, CD1D_1058, CDH4_7890, CHST2_8128, CHST2_8384, CHST2_9316, CHST2_9470, CLIC6_B, CXCL12_B, DLX4_B, DNM3_D, EMX1_A, ESPN_B, FAM59B_7764, FOXP4_B, GP5, HOXA1_C, IGF2BP3_C, IPTRIPL1_1138, IPTRIPL1_1200, KCNK9_B, KCNK17_C, LAYN_B, LIME1_B, LMX1B_D, LOC100132891_B, MAST1_B, MAX.chr12.427.br, MAX.chr20.4422, MPZ_5742, MPZ_5554, MSX2P1_B, ODC1_B, OSR2_A, OTX1_B, PLXNC1_B, PRKCB_7570, SCRT2_C, SLC30A10, SPHK2_B, ST8SIA4_B, STX16_C, TRH_A, and TRIM67_B (see, Table 9, Example III).


From these 375 novel DNA methylation markers, further experiments identified the following markers and/or panels of markers for detecting breast cancer in blood samples (e.g., plasma samples, whole blood samples, serum samples):

    • CD1D, ITPRIPL1, FAM59B, C10orf125, TRIM67, SPHK2, CALN1_B, CHST2_B, MPZ, CXCL12_B, ODC1_B, OSR2_A, TRH_A, and C17orf64_B (see, Table 14, Example III).


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, or 8 markers) with high discrimination for breast cancer overall. 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 for purposes of breast 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 (e.g., breast tissue, plasma sample). These markers comprise one or more differentially methylated regions (DMR) as discussed herein, e.g., as provided in Tables 2 and 5. 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 or methylation-dependent 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. No. 8,361,720; and U.S. Pat. Appl. Pub. Nos. 2012/0122088 and 2012/0122106, incorporated herein by reference).


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.


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 contain a reagent capable of modifying DNA in a methylation-specific manner (e.g., a methylation-sensitive restriction enzyme, a methylation-dependent restriction enzyme, and a bisulfite reagent). 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., DMR 1-375 as provided in Tables 2 and 5); comparing methylation states (e.g., of one or more DMR, e.g., DMR 1-375 as provided in Tables 2 and 5); generating standard curves; determining a Ct value; calculating a fraction, frequency, or percentage of methylation (e.g., of one or more DMR, e.g., DMR 1-375 as provided in Tables 2 and 5); 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 microprocessor or computer uses methylation state data in an algorithm to predict a site of a cancer.


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 Tables 2 and 5). 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 Tables 2 and 5). 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 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 breast cancer in a sample obtained from a subject, the method comprising assaying a methylation state of a marker in a sample obtained from a subject (e.g., breast tissue) (e.g., plasma sample) and identifying the subject as having breast cancer when the methylation state of the marker is different than a methylation state of the marker assayed in a subject that does not have breast cancer, wherein the marker comprises a base in a differentially methylated region (DMR) selected from a group consisting of DMR 1-375 as provided in Tables 2 and 5.


In some embodiments wherein the sample obtained from the subject is breast tissue and the methylation state of one or more of the following markers is different than a methylation state of the one or more markers assayed in a subject that does not have breast cancer indicates the subject has breast cancer: ATP6V1B1, LMX1B_A, BANK1, OTX1, MAX.chr11.14926602-14927148, UBTF, PRKCB, TRH_A, MPZ, DNM3_A, TRIM67, MAX.chr12.4273906-4274012, CALN1_A, ITPRIPL1, MAX.chr12.4273906-4274012, GYPC_B, MAX.chr5.42994866-42994936, OSR2_A, SCRT2_B, MAX.chr5.145725410-145725459, MAX.chr11.68622869-68622968, MAX.chr8.124173030-124173395, MAX.chr20.1784209-1784461, LOC100132891, BHLHE23_D, MAX.chr19.46379903-46380197, CHST2_B, MAX.chr5.77268672-77268725, C17orf64, EMX1_A, DSCR6, ITPRIPL1, IGF2BP3_B, DLX4, and ABLIM1 (see, Table 4, Example II).


In some embodiments wherein the sample obtained from the subject is breast tissue and the methylation state of one or more of the following markers is different than a methylation state of the one or more markers assayed in a subject that does not have breast cancer indicates the subject has breast cancer: ABLIM1_B, AJAP1_C, ALOX5_B, ASCL2_B, BANK1_B, BHLHE23_E, C10orf125_B, C17orf64_B, CALN1_1520, CALN1_B, CD1D_1058, CDH4_7890, CHST2_8128, CHST2_8384, CHST2_9316, CHST2_9470, CLIC6_B, CXCL12_B, DLX4_B, DNM3_D, EMX1_A, ESPN_B, FAM59B_7764, FOXP4_B, GP5, HOXA1_C, IGF2BP3_C, IPTRIPL1_1138, IPTRIPL1_1200, KCNK9_B, KCNK17_C, LAYN_B, LIME1_B, LMX1B_D, LOC100132891_B, MAST1_B, MAX.chr12.427.br, MAX.chr20.4422, MPZ_5742, MPZ_5554, MSX2P1_B, ODC1_B, OSR2_A, OTX1_B, PLXNC1_B, PRKCB_7570, SCRT2_C, SLC30A10, SPHK2_B, ST8SIA4_B, STX16_C, TRH_A, and TRIM67_B (see, Table 9, Example III).


In some embodiments wherein the sample obtained from the subject is a blood sample (e.g., plasma, serum, whole blood) and the methylation state of one or more of the following markers is different than a methylation state of the one or more markers assayed in a subject that does not have breast cancer indicates the subject has breast cancer: CD1D, ITPRIPL1, FAM59B, C10orf125, TRIM67, SPHK2, CALN1_B, CHST2_B, MPZ, CXCL12_B, ODC1_B, OSR2_A, TRH_A, and C17orf64_B (see, Table 14, Example III).


The technology is related to identifying and discriminating breast cancer. Some embodiments provide methods comprising assaying a plurality of markers, e.g., comprising assaying 2 to 11 to 100 or 120 or 375 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 (e.g., breast 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 NO: 1-422 (see, Tables 3, 6, 7, 15 and 16). 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 use for identifying breast cancer, e.g., in some embodiments the marker comprises a chromosomal region having an annotation that is ATP6V1B1, LMX1B_A, BANK1, OTX1, MAX.chr11.14926602-14927148, UBTF, PRKCB, TRH_A, MPZ, DNM3_A, TRIM67, MAX.chr12.4273906-4274012, CALN1_A, ITPRIPL1, MAX.chr12.4273906-4274012, GYPC_B, MAX.chr5.42994866-42994936, OSR2_A, SCRT2_B, MAX.chr5.145725410-145725459, MAX.chr11.68622869-68622968, MAX.chr8.124173030-124173395, MAX.chr20.1784209-1784461, LOC100132891, BHLHE23_D, MAX.chr19.46379903-46380197, CHST2_B, MAX.chr5.77268672-77268725, C17orf64, EMX1_A, DSCR6, ITPRIPL1, IGF2BP3_B, DLX4, and ABLIM1 (see, Table 4, Example II).


The technology provides various panels of markers use for identifying breast cancer, e.g., in some embodiments the marker comprises a chromosomal region having an annotation that is ABLIM1_B, AJAP1_C, ALOX5_B, ASCL2_B, BANK1_B, BHLHE23_E, C10orf125_B, C17orf64_B, CALN1_1520, CALN1_B, CD1D_1058, CDH4_7890, CHST2_8128, CHST2_8384, CHST2_9316, CHST2_9470, CLIC6_B, CXCL12_B, DLX4_B, DNM3_D, EMX1_A, ESPN_B, FAM59B_7764, FOXP4_B, GP5, HOXA1_C, IGF2BP3_C, IPTRIPL1_1138, IPTRIPL1_1200, KCNK9_B, KCNK17_C, LAYN_B, LIME1_B, LMX1B_D, LOC100132891_B, MAST1_B, MAX.chr12.427.br, MAX.chr20.4422, MPZ_5742, MPZ_5554, MSX2P1_B, ODC1_B, OSR2_A, OTX1_B, PLXNC1_B, PRKCB_7570, SCRT2_C, SLC30A10, SPHK2_B, ST8SIA4_B, STX16_C, TRH_A, and TRIM67_B (see, Table 9, Example III).


The technology provides various panels of markers use for identifying breast cancer, e.g., in some embodiments the marker comprises a chromosomal region having an annotation that is CD1D, ITPRIPL1, FAM59B, C10orf125, TRIM67, SPHK2, CALN1_B, CHST2_B, MPZ, CXCL12_B, ODC1_B, OSR2_A, TRH_A, and C17orf64_B (see, Table 14, Example III).


Kit embodiments are provided, e.g., a kit comprising a reagent capable of modifying DNA in a methylation-specific manner (e.g., a methylation-sensitive restriction enzyme, a methylation-dependent restriction enzyme, and a bisulfite reagent); and a control nucleic acid comprising a sequence from a DMR selected from a group consisting of DMR 1-375 (from Tables 2 and 5) and having a methylation state associated with a subject who does not have breast cancer. In some embodiments, kits comprise a reagent capable of modifying DNA in a methylation-specific manner (e.g., a methylation-sensitive restriction enzyme, a methylation-dependent restriction enzyme, and a bisulfite reagent); and a control nucleic acid comprising a sequence from a DMR selected from a group consisting of DMR 1-375 (from Tables 2 and 5) and having a methylation state associated with a subject who has breast cancer. Some kit embodiments comprise a sample collector for obtaining a sample from a subject (e.g., a stool sample; breast tissue sample; plasma sample, serum sample, whole blood sample); a reagent capable of modifying DNA in a methylation-specific manner (e.g., a methylation-sensitive restriction enzyme, a methylation-dependent restriction enzyme, and 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 reagent capable of modifying DNA in a methylation-specific manner (e.g., a methylation-sensitive restriction enzyme, a methylation-dependent restriction enzyme, 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 breast cancer in a sample obtained from a subject (e.g., breast tissue sample; plasma sample; stool sample), e.g., a method comprising determining a methylation state of a marker in the sample comprising a base in a DMR that is one or more of DMR 1-375 (from Tables 2 and 5); 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 breast 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 reagent capable of modifying nucleic acid in a methylation-specific manner (e.g., a methylation-sensitive restriction enzyme, a methylation-dependent restriction enzyme, and a bisulfite reagent) to produce, for example, nucleic acid modified in a methylation-specific manner; sequencing the nucleic acid modified in a methylation-specific manner to provide a nucleotide sequence of the nucleic acid modified in a methylation-specific manner; comparing the nucleotide sequence of the nucleic acid modified in a methylation-specific manner with a nucleotide sequence of a nucleic acid comprising the DMR from a subject who does not have breast cancer and/or a form of breast cancer to identify differences in the two sequences; and identifying the subject as having breast cancer when a difference is present.


Systems for screening for breast cancer in a sample obtained from a subject are provided by the technology. Exemplary embodiments of systems include, e.g., a system for screening for breast cancer in a sample obtained from a subject (e.g., breast tissue sample; plasma sample; stool sample), 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 breast-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 Tables 2 and 5) 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 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 breast 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 breast cancer and/or specific types of breast 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 reagent capable of modifying DNA in a methylation-specific manner (e.g., a methylation-sensitive restriction enzyme, a methylation-dependent restriction enzyme, and a bisulfate reagent). And, some embodiments further comprise a nucleic acid sequencer.


In certain embodiments, methods for characterizing a sample (e.g., breast tissue sample; plasma sample; whole blood sample; serum sample; stool sample) from a human patient are provided. For example, in some embodiments such embodiments comprise obtaining DNA from a sample of a human patient; assaying a methylation state of a DNA methylation marker comprising a base in a differentially methylated region (DMR) selected from a group consisting of DMR 1-375 from Tables 2 and 5; and comparing the assayed methylation state of the one or more DNA methylation markers with methylation level references for the one or more DNA methylation markers for human patients not having breast cancer.


Such methods are not limited to a particular type of sample from a human patient. In some embodiments, the sample is a breast tissue sample. In some embodiments, the sample is a plasma sample. In some embodiments, the sample is a stool sample, a tissue sample, a breast tissue sample, a blood sample (e.g., plasma sample, whole blood sample, serum sample), or a urine sample.


In some embodiments, such methods comprise assaying a plurality of DNA methylation markers. In some embodiments, such methods comprise assaying 2 to 11 DNA methylation markers. In some embodiments, such methods comprise assaying 12 to 120 DNA methylation markers. In some embodiments, such methods comprise assaying 2 to 375 DNA methylation markers. In some embodiments, such methods comprise assaying the methylation state of the one or more DNA methylation markers in the sample comprises determining the methylation state of one base. In some embodiments, such methods comprise assaying the methylation state of the one or more DNA methylation markers in the sample comprises determining the extent of methylation at a plurality of bases. In some embodiments, such methods comprise assaying a methylation state of a forward strand or assaying a methylation state of a reverse strand.


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


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 methylation specific oligonucleotide is selected from the group consisting of SEQ ID NO: 1-422 (Tables 3, 6, 7, 15 and 16).


In some embodiments, a chromosomal region having an annotation selected from the group consisting of ATP6V1B1, LMX1B_A, BANK1, OTX1, MAX.chr11.14926602-14927148, UBTF, PRKCB, TRH_A, MPZ, DNM3_A, TRIM67, MAX.chr12.4273906-4274012, CALN1_A, ITPRIPL1, MAX.chr12.4273906-4274012, GYPC_B, MAX.chr5.42994866-42994936, OSR2_A, SCRT2_B, MAX.chr5.145725410-145725459, MAX.chr11.68622869-68622968, MAX.chr8.124173030-124173395, MAX.chr20.1784209-1784461, LOC100132891, BHLHE23_D, MAX.chr19.46379903-46380197, CHST2_B, MAX.chr5.77268672-77268725, C17orf64, EMX1_A, DSCR6, ITPRIPL1, IGF2BP3_B, DLX4, and ABLIM1 (see, Table 4, Example II) comprises the DNA methylation marker.


In some embodiments, a chromosomal region having an annotation selected from the group consisting of ABLIM1_B, AJAP1_C, ALOX5_B, ASCL2_B, BANK1_B, BHLHE23_E, C10orf125_B, C17orf64_B, CALN1_1520, CALN1_B, CD1D_1058, CDH4_7890, CHST2_8128, CHST2_8384, CHST2_9316, CHST2_9470, CLIC6_B, CXCL12_B, DLX4_B, DNM3_D, EMX1_A, ESPN_B, FAM59B_7764, FOXP4_B, GP5, HOXA1_C, IGF2BP3_C, IPTRIPL1_1138, IPTRIPL1_1200, KCNK9_B, KCNK17_C, LAYN_B, LIME1_B, LMX1B_D, LOC100132891_B, MAST1_B, MAX.chr12.427.br, MAX.chr20.4422, MPZ_5742, MPZ_5554, MSX2P1_B, ODC1_B, OSR2_A, OTX1_B, PLXNC1_B, PRKCB_7570, SCRT2_C, SLC30A10, SPHK2_B, ST8SIA4_B, STX16_C, TRH_A, and TRIM67_B (see, Table 9, Example III) comprises the DNA methylation marker.


In some embodiments, a chromosomal region having an annotation selected from the group consisting of CD1D, ITPRIPL1, FAM59B, C10orf125, TRIM67, SPHK2, CALN1_B, CHST2_B, MPZ, CXCL12_B, ODC1_B, OSR2_A, TRH_A, and C17orf64_B (see, Table 14, Example III) comprises the DNA methylation marker.


In some embodiments, such methods comprise determining the methylation state of two DNA methylation markers. In some embodiments, such methods comprise determining the methylation state of a pair of DNA methylation markers provided in a row of Tables 2 and 5.


In certain embodiments, the technology provides methods for characterizing a sample (e.g., breast tissue sample; plasma sample; whole blood sample; serum sample; stool sample) obtained from a human patient. In some embodiments, such methods comprise determining a methylation state of a DNA methylation marker in the sample comprising a base in a DMR selected from a group consisting of DMR 1-375 from Tables 2 and 5; comparing the methylation state of the DNA methylation marker from the patient sample to a methylation state of the DNA methylation marker from a normal control sample from a human subject who does not have a breast cancer; and determining a confidence interval and/or a p value of the difference in the methylation state of the human patient 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 thep value is 0.1, 0.05, 0.025, 0.02, 0.01, 0.005, 0.001, or 0.0001.


In certain embodiments, the technology provides methods for characterizing a sample obtained from a human subject (e.g., breast tissue sample; plasma sample; whole blood sample; serum sample; stool sample), the method comprising reacting a nucleic acid comprising a DMR with a reagent capable of modifying DNA in a methylation-specific manner (e.g., a methylation-sensitive restriction enzyme, a methylation-dependent restriction enzyme, and a bisulfate reagent) to produce nucleic acid modified in a methylation-specific manner; sequencing the nucleic acid modified in a methylation-specific manner to provide a nucleotide sequence of the nucleic acid modified in a methylation-specific manner; comparing the nucleotide sequence of the nucleic acid modified in a methylation-specific manner with a nucleotide sequence of a nucleic acid comprising the DMR from a subject who does not have breast cancer to identify differences in the two sequences.


In certain embodiments, the technology provides systems for characterizing a sample obtained from a human subject (e.g., breast tissue sample; plasma sample; stool sample), 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 determine a single value based on a combination of methylation states and alert a user of a breast cancer-associated methylation state. In some embodiments, the sample comprises a nucleic acid comprising a DMR.


In some embodiments, such systems further comprise a component for isolating a nucleic acid. In some embodiments, such systems further comprise a component for collecting a sample.


In some embodiments, the sample is a stool sample, a tissue sample, a breast tissue sample, a blood sample (e.g., plasma sample, whole blood sample, serum sample), or a urine sample.


In some embodiments, the database comprises nucleic acid sequences comprising a DMR. In some embodiments, the database comprises nucleic acid sequences from subjects who do not have a breast cancer.


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


Definitions

To facilitate an understanding of the present technology, a number of terms and phrases are defined below. Additional definitions are set forth throughout the detailed description.


Throughout the specification and claims, the following terms take the meanings explicitly associated herein, unless the context clearly dictates otherwise. The phrase “in one embodiment” as used herein does not necessarily refer to the same embodiment, though it may. Furthermore, the phrase “in another embodiment” as used herein does not necessarily refer to a different embodiment, although it may. Thus, as described below, various embodiments of the invention may be readily combined, without departing from the scope or spirit of the invention.


In addition, as used herein, the term “or” is an inclusive “or” operator and is equivalent to the term “and/or” unless the context clearly dictates otherwise. The term “based on” is not exclusive and allows for being based on additional factors not described, unless the context clearly dictates otherwise. In addition, throughout the specification, the meaning of “a”, “an”, and “the” include plural references. The meaning of “in” includes “in” and “on.”


The transitional phrase “consisting essentially of” as used in claims in the present application limits the scope of a claim to the specified materials or steps “and those that do not materially affect the basic and novel characteristic(s)” of the claimed invention, as discussed in In re Herz, 537 F2d 549, 551-52, 190 USPQ 461, 463 (CCPR 1976). For example, a composition “consisting essentially of” recited elements may contain an unrecited contaminant at a level such that, though present, the contaminant does not alter the function of the recited composition as compared to a pure composition, i.e., a composition “consisting of” the recited components.


As used herein, a “nucleic acid” or “nucleic acid molecule” generally refers to any ribonucleic acid or deoxyribonucleic acid, which may be unmodified or modified DNA or RNA. “Nucleic acids” include, without limitation, single- and double-stranded nucleic acids. As used herein, the term “nucleic acid” also includes DNA as described above that contains one or more modified bases. Thus, DNA with a backbone modified for stability or for other reasons is a “nucleic acid”. The term “nucleic acid” as it is used herein embraces such chemically, enzymatically, or metabolically modified forms of nucleic acids, as well as the chemical forms of DNA characteristic of viruses and cells, including for example, simple and complex cells.


The terms “oligonucleotide” or “polynucleotide” or “nucleotide” or “nucleic acid” refer to a molecule having two or more deoxyribonucleotides or ribonucleotides, preferably more than three, and usually more than ten. The exact size will depend on many factors, which in turn depends on the ultimate function or use of the oligonucleotide. The oligonucleotide may be generated in any manner, including chemical synthesis, DNA replication, reverse transcription, or a combination thereof. Typical deoxyribonucleotides for DNA are thymine, adenine, cytosine, and guanine. Typical ribonucleotides for RNA are uracil, adenine, cytosine, and guanine.


As used herein, the terms “locus” or “region” of a nucleic acid refer to a subregion of a nucleic acid, e.g., a gene on a chromosome, a single nucleotide, a CpG island, etc.


The terms “complementary” and “complementarity” refer to nucleotides (e.g., 1 nucleotide) or polynucleotides (e.g., a sequence of nucleotides) related by the base-pairing rules. For example, the sequence 5′-A-G-T-3′ is complementary to the sequence 3′-T-C-A-5′. Complementarity may be “partial,” in which only some of the nucleic acids' bases are matched according to the base pairing rules. Or, there may be “complete” or “total” complementarity between the nucleic acids. The degree of complementarity between nucleic acid strands effects the efficiency and strength of hybridization between nucleic acid strands. This is of particular importance in amplification reactions and in detection methods that depend upon binding between nucleic acids.


The term “gene” refers to a nucleic acid (e.g., DNA or RNA) sequence that comprises coding sequences necessary for the production of an RNA, or of a polypeptide or its precursor. A functional polypeptide can be encoded by a full length coding sequence or by any portion of the coding sequence as long as the desired activity or functional properties (e.g., enzymatic activity, ligand binding, signal transduction, etc.) of the polypeptide are retained. The term “portion” when used in reference to a gene refers to fragments of that gene. The fragments may range in size from a few nucleotides to the entire gene sequence minus one nucleotide. Thus, “a nucleotide comprising at least a portion of a gene” may comprise fragments of the gene or the entire gene.


The term “gene” also encompasses the coding regions of a structural gene and includes sequences located adjacent to the coding region on both the 5′ and 3′ ends, e.g., for a distance of about 1 kb on either end, such that the gene corresponds to the length of the full-length mRNA (e.g., comprising coding, regulatory, structural and other sequences). The sequences that are located 5′ of the coding region and that are present on the mRNA are referred to as 5′ non-translated or untranslated sequences. The sequences that are located 3′ or downstream of the coding region and that are present on the mRNA are referred to as 3′ non-translated or 3′ untranslated sequences. The term “gene” encompasses both cDNA and genomic forms of a gene. In some organisms (e.g., eukaryotes), a genomic form or clone of a gene contains the coding region interrupted with non-coding sequences termed “introns” or “intervening regions” or “intervening sequences.” Introns are segments of a gene that are transcribed into nuclear RNA (hnRNA); introns may contain regulatory elements such as enhancers. Introns are removed or “spliced out” from the nuclear or primary transcript; introns therefore are absent in the messenger RNA (mRNA) transcript. The mRNA functions during translation to specify the sequence or order of amino acids in a nascent polypeptide.


In addition to containing introns, genomic forms of a gene may also include sequences located on both the 5′ and 3′ ends of the sequences that are present on the RNA transcript. These sequences are referred to as “flanking” sequences or regions (these flanking sequences are located 5′ or 3′ to the non-translated sequences present on the mRNA transcript). The 5′ flanking region may contain regulatory sequences such as promoters and enhancers that control or influence the transcription of the gene. The 3′ flanking region may contain sequences that direct the termination of transcription, posttranscriptional cleavage, and polyadenylation.


The term “wild-type” when made in reference to a gene refers to a gene that has the characteristics of a gene isolated from a naturally occurring source. The term “wild-type” when made in reference to a gene product refers to a gene product that has the characteristics of a gene product isolated from a naturally occurring source. The term “naturally-occurring” as applied to an object refers to the fact that an object can be found in nature. For example, a polypeptide or polynucleotide sequence that is present in an organism (including viruses) that can be isolated from a source in nature and which has not been intentionally modified by the hand of a person in the laboratory is naturally-occurring. A wild-type gene is often that gene or allele that is most frequently observed in a population and is thus arbitrarily designated the “normal” or “wild-type” form of the gene. In contrast, the term “modified” or “mutant” when made in reference to a gene or to a gene product refers, respectively, to a gene or to a gene product that displays modifications in sequence and/or functional properties (e.g., altered characteristics) when compared to the wild-type gene or gene product. It is noted that naturally-occurring mutants can be isolated; these are identified by the fact that they have altered characteristics when compared to the wild-type gene or gene product.


The term “allele” refers to a variation of a gene; the variations include but are not limited to variants and mutants, polymorphic loci, and single nucleotide polymorphic loci, frameshift, and splice mutations. An allele may occur naturally in a population or it might arise during the lifetime of any particular individual of the population.


Thus, the terms “variant” and “mutant” when used in reference to a nucleotide sequence refer to a nucleic acid sequence that differs by one or more nucleotides from another, usually related, nucleotide acid sequence. A “variation” is a difference between two different nucleotide sequences; typically, one sequence is a reference sequence.


“Amplification” is a special case of nucleic acid replication involving template specificity. It is to be contrasted with non-specific template replication (e.g., replication that is template-dependent but not dependent on a specific template). Template specificity is here distinguished from fidelity of replication (e.g., synthesis of the proper polynucleotide sequence) and nucleotide (ribo- or deoxyribo-) specificity. Template specificity is frequently described in terms of “target” specificity. Target sequences are “targets” in the sense that they are sought to be sorted out from other nucleic acid. Amplification techniques have been designed primarily for this sorting out.


The term “amplifying” or “amplification” in the context of nucleic acids refers to the production of multiple copies of a polynucleotide, or a portion of the polynucleotide, typically starting from a small amount of the polynucleotide (e.g., a single polynucleotide molecule), where the amplification products or amplicons are generally detectable. Amplification of polynucleotides encompasses a variety of chemical and enzymatic processes. The generation of multiple DNA copies from one or a few copies of a target or template DNA molecule during a polymerase chain reaction (PCR) or a ligase chain reaction (LCR; see, e.g., U.S. Pat. No. 5,494,810; herein incorporated by reference in its entirety) are forms of amplification. Additional types of amplification include, but are not limited to, allele-specific PCR (see, e.g., U.S. Pat. No. 5,639,611; herein incorporated by reference in its entirety), assembly PCR (see, e.g., U.S. Pat. No. 5,965,408; herein incorporated by reference in its entirety), helicase-dependent amplification (see, e.g., U.S. Pat. No. 7,662,594; herein incorporated by reference in its entirety), hot-start PCR (see, e.g., U.S. Pat. Nos. 5,773,258 and 5,338,671; each herein incorporated by reference in their entireties), intersequence-specific PCR, inverse PCR (see, e.g., Triglia, et al. (1988) Nucleic Acids Res., 16:8186; herein incorporated by reference in its entirety), ligation-mediated PCR (see, e.g., Guilfoyle, R. et al., Nucleic Acids Research, 25:1854-1858 (1997); U.S. Pat. No. 5,508,169; each of which are herein incorporated by reference in their entireties), methylation-specific PCR (see, e.g., Herman, et al., (1996) PNAS 93(13) 9821-9826; herein incorporated by reference in its entirety), miniprimer PCR, multiplex ligation-dependent probe amplification (see, e.g., Schouten, et al., (2002) Nucleic Acids Research 30(12): e57; herein incorporated by reference in its entirety), multiplex PCR (see, e.g., Chamberlain, et al., (1988) Nucleic Acids Research 16(23) 11141-11156; Ballabio, et al., (1990) Human Genetics 84(6) 571-573; Hayden, et al., (2008) BMC Genetics 9:80; each of which are herein incorporated by reference in their entireties), nested PCR, overlap-extension PCR (see, e.g., Higuchi, et al., (1988) Nucleic Acids Research 16(15) 7351-7367; herein incorporated by reference in its entirety), real time PCR (see, e.g., Higuchi, et al., (1992) Biotechnology 10:413-417; Higuchi, et al., (1993) Biotechnology 11:1026-1030; each of which are herein incorporated by reference in their entireties), reverse transcription PCR (see, e.g., Bustin, S. A. (2000) J. Molecular Endocrinology 25:169-193; herein incorporated by reference in its entirety), solid phase PCR, thermal asymmetric interlaced PCR, and Touchdown PCR (see, e.g., Don, et al., Nucleic Acids Research (1991) 19(14) 4008; Roux, K. (1994) Biotechniques 16(5) 812-814; Hecker, et al., (1996) Biotechniques 20(3) 478-485; each of which are herein incorporated by reference in their entireties). Polynucleotide amplification also can be accomplished using digital PCR (see, e.g., Kalinina, et al., Nucleic Acids Research. 25; 1999-2004, (1997); Vogelstein and Kinzler, Proc Natl Acad Sci USA. 96; 9236-41, (1999); International Patent Publication No. WO05023091A2; US Patent Application Publication No. 20070202525; each of which are incorporated herein by reference in their entireties).


The term “polymerase chain reaction” (“PCR”) refers to the method of K. B. Mullis U.S. Pat. Nos. 4,683,195, 4,683,202, and 4,965,188, that describe a method for increasing the concentration of a segment of a target sequence in a mixture of genomic or other DNA or RNA, without cloning or purification. This process for amplifying the target sequence consists of introducing a large excess of two oligonucleotide primers to the DNA mixture containing the desired target sequence, followed by a precise sequence of thermal cycling in the presence of a DNA polymerase. The two primers are complementary to their respective strands of the double stranded target sequence. To effect amplification, the mixture is denatured and the primers then annealed to their complementary sequences within the target molecule. Following annealing, the primers are extended with a polymerase so as to form a new pair of complementary strands. The steps of denaturation, primer annealing, and polymerase extension can be repeated many times (i.e., denaturation, annealing and extension constitute one “cycle”; there can be numerous “cycles”) to obtain a high concentration of an amplified segment of the desired target sequence. The length of the amplified segment of the desired target sequence is determined by the relative positions of the primers with respect to each other, and therefore, this length is a controllable parameter. By virtue of the repeating aspect of the process, the method is referred to as the “polymerase chain reaction” (“PCR”). Because the desired amplified segments of the target sequence become the predominant sequences (in terms of concentration) in the mixture, they are said to be “PCR amplified” and are “PCR products” or “amplicons.” Those of skill in the art will understand the term “PCR” encompasses many variants of the originally described method using, e.g., real time PCR, nested PCR, reverse transcription PCR (RT-PCR), single primer and arbitrarily primed PCR, etc.


Template specificity is achieved in most amplification techniques by the choice of enzyme. Amplification enzymes are enzymes that, under conditions they are used, will process only specific sequences of nucleic acid in a heterogeneous mixture of nucleic acid. For example, in the case of Q-beta replicase, MDV-1 RNA is the specific template for the replicase (Kacian et al., Proc. Natl. Acad. Sci. USA, 69:3038 [1972]). Other nucleic acid will not be replicated by this amplification enzyme. Similarly, in the case of T7 RNA polymerase, this amplification enzyme has a stringent specificity for its own promoters (Chamberlin et al, Nature, 228:227 [1970]). In the case of T4 DNA ligase, the enzyme will not ligate the two oligonucleotides or polynucleotides, where there is a mismatch between the oligonucleotide or polynucleotide substrate and the template at the ligation junction (Wu and Wallace (1989) Genomics 4:560). Finally, thermostable template-dependant DNA polymerases (e.g., Taq and Pfu DNA polymerases), by virtue of their ability to function at high temperature, are found to display high specificity for the sequences bounded and thus defined by the primers; the high temperature results in thermodynamic conditions that favor primer hybridization with the target sequences and not hybridization with non-target sequences (H. A. Erlich (ed.), PCR Technology, Stockton Press [1989]).


As used herein, the term “nucleic acid detection assay” refers to any method of determining the nucleotide composition of a nucleic acid of interest. Nucleic acid detection assay include but are not limited to, DNA sequencing methods, probe hybridization methods, structure specific cleavage assays (e.g., the INVADER assay, (Hologic, Inc.) and are described, e.g., in U.S. Pat. Nos. 5,846,717, 5,985,557, 5,994,069, 6,001,567, 6,090,543, and 6,872,816; Lyamichev et al., Nat. Biotech., 17:292 (1999), Hall et al., PNAS, USA, 97:8272 (2000), and U.S. Pat. No. 9,096,893, each of which is herein incorporated by reference in its entirety for all purposes); enzyme mismatch cleavage methods (e.g., Variagenics, U.S. Pat. Nos. 6,110,684, 5,958,692, 5,851,770, herein incorporated by reference in their entireties); polymerase chain reaction (PCR), described above; branched hybridization methods (e.g., Chiron, U.S. Pat. Nos. 5,849,481, 5,710,264, 5,124,246, and 5,624,802, herein incorporated by reference in their entireties); rolling circle replication (e.g., U.S. Pat. Nos. 6,210,884, 6,183,960 and 6,235,502, herein incorporated by reference in their entireties); NASBA (e.g., U.S. Pat. No. 5,409,818, herein incorporated by reference in its entirety); molecular beacon technology (e.g., U.S. Pat. No. 6,150,097, herein incorporated by reference in its entirety); E-sensor technology (Motorola, U.S. Pat. Nos. 6,248,229, 6,221,583, 6,013,170, and 6,063,573, herein incorporated by reference in their entireties); cycling probe technology (e.g., U.S. Pat. Nos. 5,403,711, 5,011,769, and 5,660,988, herein incorporated by reference in their entireties); Dade Behring signal amplification methods (e.g., U.S. Pat. Nos. 6,121,001, 6,110,677, 5,914,230, 5,882,867, and 5,792,614, herein incorporated by reference in their entireties); ligase chain reaction (e.g., Baranay Proc. Natl. Acad. Sci USA 88, 189-93 (1991)); and sandwich hybridization methods (e.g., U.S. Pat. No. 5,288,609, herein incorporated by reference in its entirety).


The term “amplifiable nucleic acid” refers to a nucleic acid that may be amplified by any amplification method. It is contemplated that “amplifiable nucleic acid” will usually comprise “sample template.”


The term “sample template” refers to nucleic acid originating from a sample that is analyzed for the presence of “target” (defined below). In contrast, “background template” is used in reference to nucleic acid other than sample template that may or may not be present in a sample. Background template is most often inadvertent. It may be the result of carryover or it may be due to the presence of nucleic acid contaminants sought to be purified away from the sample. For example, nucleic acids from organisms other than those to be detected may be present as background in a test sample.


The term “primer” refers to an oligonucleotide, whether occurring naturally as, e.g., a nucleic acid fragment from a restriction digest, or produced synthetically, that is capable of acting as a point of initiation of synthesis when placed under conditions in which synthesis of a primer extension product that is complementary to a nucleic acid template strand is induced, (e.g., in the presence of nucleotides and an inducing agent such as a DNA polymerase, and at a suitable temperature and pH). The primer is preferably single stranded for maximum efficiency in amplification, but may alternatively be double stranded. If double stranded, the primer is first treated to separate its strands before being used to prepare extension products. Preferably, the primer is an oligodeoxyribonucleotide. The primer must be sufficiently long to prime the synthesis of extension products in the presence of the inducing agent. The exact lengths of the primers will depend on many factors, including temperature, source of primer, and the use of the method.


The term “probe” refers to an oligonucleotide (e.g., a sequence of nucleotides), whether occurring naturally as in a purified restriction digest or produced synthetically, recombinantly, or by PCR amplification, that is capable of hybridizing to another oligonucleotide of interest. A probe may be single-stranded or double-stranded. Probes are useful in the detection, identification, and isolation of particular gene sequences (e.g., a “capture probe”). It is contemplated that any probe used in the present invention may, in some embodiments, be labeled with any “reporter molecule,” so that is detectable in any detection system, including, but not limited to enzyme (e.g., ELISA, as well as enzyme-based histochemical assays), fluorescent, radioactive, and luminescent systems. It is not intended that the present invention be limited to any particular detection system or label.


The term “target,” as used herein refers to a nucleic acid sought to be sorted out from other nucleic acids, e.g., by probe binding, amplification, isolation, capture, etc. For example, when used in reference to the polymerase chain reaction, “target” refers to the region of nucleic acid bounded by the primers used for polymerase chain reaction, while when used in an assay in which target DNA is not amplified, e.g., in some embodiments of an invasive cleavage assay, a target comprises the site at which a probe and invasive oligonucleotides (e.g., INVADER oligonucleotide) bind to form an invasive cleavage structure, such that the presence of the target nucleic acid can be detected. A “segment” is defined as a region of nucleic acid within the target sequence.


As used herein, “methylation” refers to cytosine methylation at positions C5 or N4 of cytosine, the N6 position of adenine, or other types of nucleic acid methylation. In vitro amplified DNA is usually unmethylated because typical in vitro DNA amplification methods do not retain the methylation pattern of the amplification template. However, “unmethylated DNA” or “methylated DNA” can also refer to amplified DNA whose original template was unmethylated or methylated, respectively.


Accordingly, as used herein a “methylated nucleotide” or a “methylated nucleotide base” refers to the presence of a methyl moiety on a nucleotide base, where the methyl moiety is not present in a recognized typical nucleotide base. For example, cytosine does not contain a methyl moiety on its pyrimidine ring, but 5-methylcytosine contains a methyl moiety at position 5 of its pyrimidine ring. Therefore, cytosine is not a methylated nucleotide and 5-methylcytosine is a methylated nucleotide. In another example, thymine contains a methyl moiety at position 5 of its pyrimidine ring; however, for purposes herein, thymine is not considered a methylated nucleotide when present in DNA since thymine is a typical nucleotide base of DNA.


As used herein, a “methylated nucleic acid molecule” refers to a nucleic acid molecule that contains one or more methylated nucleotides.


As used herein, a “methylation state”, “methylation profile”, and “methylation status” of a nucleic acid molecule refers to the presence of absence of one or more methylated nucleotide bases in the nucleic acid molecule. For example, a nucleic acid molecule containing a methylated cytosine is considered methylated (e.g., the methylation state of the nucleic acid molecule is methylated). A nucleic acid molecule that does not contain any methylated nucleotides is considered unmethylated.


The methylation state of a particular nucleic acid sequence (e.g., a gene marker or DNA region as described herein) can indicate the methylation state of every base in the sequence or can indicate the methylation state of a subset of the bases (e.g., of one or more cytosines) within the sequence, or can indicate information regarding regional methylation density within the sequence with or without providing precise information of the locations within the sequence the methylation occurs.


The methylation state of a nucleotide locus in a nucleic acid molecule refers to the presence or absence of a methylated nucleotide at a particular locus in the nucleic acid molecule. For example, the methylation state of a cytosine at the 7th nucleotide in a nucleic acid molecule is methylated when the nucleotide present at the 7th nucleotide in the nucleic acid molecule is 5-methylcytosine. Similarly, the methylation state of a cytosine at the 7th nucleotide in a nucleic acid molecule is unmethylated when the nucleotide present at the 7th nucleotide in the nucleic acid molecule is cytosine (and not 5-methylcytosine).


The methylation status can optionally be represented or indicated by a “methylation value” (e.g., representing a methylation frequency, fraction, ratio, percent, etc.) A methylation value can be generated, for example, by quantifying the amount of intact nucleic acid present following restriction digestion with a methylation dependent restriction enzyme or by comparing amplification profiles after bisulfite reaction or by comparing sequences of bisulfite-treated and untreated nucleic acids. Accordingly, a value, e.g., a methylation value, represents the methylation status and can thus be used as a quantitative indicator of methylation status across multiple copies of a locus. This is of particular use when it is desirable to compare the methylation status of a sequence in a sample to a threshold or reference value.


As used herein, “methylation frequency” or “methylation percent (%)” refer to the number of instances in which a molecule or locus is methylated relative to the number of instances the molecule or locus is unmethylated.


As such, the methylation state describes the state of methylation of a nucleic acid (e.g., a genomic sequence). In addition, the methylation state refers to the characteristics of a nucleic acid segment at a particular genomic locus relevant to methylation. Such characteristics include, but are not limited to, whether any of the cytosine (C) residues within this DNA sequence are methylated, the location of methylated C residue(s), the frequency or percentage of methylated C throughout any particular region of a nucleic acid, and allelic differences in methylation due to, e.g., difference in the origin of the alleles. The terms “methylation state”, “methylation profile”, and “methylation status” also refer to the relative concentration, absolute concentration, or pattern of methylated C or unmethylated C throughout any particular region of a nucleic acid in a biological sample. For example, if the cytosine (C) residue(s) within a nucleic acid sequence are methylated it may be referred to as “hypermethylated” or having “increased methylation”, whereas if the cytosine (C) residue(s) within a DNA sequence are not methylated it may be referred to as “hypomethylated” or having “decreased methylation”. Likewise, if the cytosine (C) residue(s) within a nucleic acid sequence are methylated as compared to another nucleic acid sequence (e.g., from a different region or from a different individual, etc.) that sequence is considered hypermethylated or having increased methylation compared to the other nucleic acid sequence. Alternatively, if the cytosine (C) residue(s) within a DNA sequence are not methylated as compared to another nucleic acid sequence (e.g., from a different region or from a different individual, etc.) that sequence is considered hypomethylated or having decreased methylation compared to the other nucleic acid sequence. Additionally, the term “methylation pattern” as used herein refers to the collective sites of methylated and unmethylated nucleotides over a region of a nucleic acid. Two nucleic acids may have the same or similar methylation frequency or methylation percent but have different methylation patterns when the number of methylated and unmethylated nucleotides are the same or similar throughout the region but the locations of methylated and unmethylated nucleotides are different. Sequences are said to be “differentially methylated” or as having a “difference in methylation” or having a “different methylation state” when they differ in the extent (e.g., one has increased or decreased methylation relative to the other), frequency, or pattern of methylation. The term “differential methylation” refers to a difference in the level or pattern of nucleic acid methylation in a cancer positive sample as compared with the level or pattern of nucleic acid methylation in a cancer negative sample. It may also refer to the difference in levels or patterns between patients that have recurrence of cancer after surgery versus patients who not have recurrence. Differential methylation and specific levels or patterns of DNA methylation are prognostic and predictive biomarkers, e.g., once the correct cut-off or predictive characteristics have been defined.


Methylation state frequency can be used to describe a population of individuals or a sample from a single individual. For example, a nucleotide locus having a methylation state frequency of 50% is methylated in 50% of instances and unmethylated in 50% of instances. Such a frequency can be used, for example, to describe the degree to which a nucleotide locus or nucleic acid region is methylated in a population of individuals or a collection of nucleic acids. Thus, when methylation in a first population or pool of nucleic acid molecules is different from methylation in a second population or pool of nucleic acid molecules, the methylation state frequency of the first population or pool will be different from the methylation state frequency of the second population or pool. Such a frequency also can be used, for example, to describe the degree to which a nucleotide locus or nucleic acid region is methylated in a single individual. For example, such a frequency can be used to describe the degree to which a group of cells from a tissue sample are methylated or unmethylated at a nucleotide locus or nucleic acid region.


As used herein a “nucleotide locus” refers to the location of a nucleotide in a nucleic acid molecule. A nucleotide locus of a methylated nucleotide refers to the location of a methylated nucleotide in a nucleic acid molecule.


Typically, methylation of human DNA occurs on a dinucleotide sequence including an adjacent guanine and cytosine where the cytosine is located 5′ of the guanine (also termed CpG dinucleotide sequences). Most cytosines within the CpG dinucleotides are methylated in the human genome, however some remain unmethylated in specific CpG dinucleotide rich genomic regions, known as CpG islands (see, e.g, Antequera et al. (1990) Cell 62: 503-514).


As used herein, a “CpG island” refers to a G:C-rich region of genomic DNA containing an increased number of CpG dinucleotides relative to total genomic DNA. A CpG island can be at least 100, 200, or more base pairs in length, where the G:C content of the region is at least 50% and the ratio of observed CpG frequency over expected frequency is 0.6; in some instances, a CpG island can be at least 500 base pairs in length, where the G:C content of the region is at least 55%) and the ratio of observed CpG frequency over expected frequency is 0.65. The observed CpG frequency over expected frequency can be calculated according to the method provided in Gardiner-Garden et al (1987) J. Mol. Biol. 196: 261-281. For example, the observed CpG frequency over expected frequency can be calculated according to the formula R=(A×B)/(C×D), where R is the ratio of observed CpG frequency over expected frequency, A is the number of CpG dinucleotides in an analyzed sequence, B is the total number of nucleotides in the analyzed sequence, C is the total number of C nucleotides in the analyzed sequence, and D is the total number of G nucleotides in the analyzed sequence. Methylation state is typically determined in CpG islands, e.g., at promoter regions. It will be appreciated though that other sequences in the human genome are prone to DNA methylation such as CpA and CpT (see Ramsahoye (2000) Proc. Natl. Acad. Sci. USA 97: 5237-5242; Salmon and Kaye (1970) Biochim. Biophys. Acta. 204: 340-351; Grafstrom (1985) Nucleic Acids Res. 13: 2827-2842; Nyce (1986) Nucleic Acids Res. 14: 4353-4367; Woodcock (1987) Biochem. Biophys. Res. Commun. 145: 888-894).


As used herein, a “methylation-specific reagent” refers to a reagent that modifies a nucleotide of the nucleic acid molecule as a function of the methylation state of the nucleic acid molecule, or a methylation-specific reagent, refers to a compound or composition or other agent that can change the nucleotide sequence of a nucleic acid molecule in a manner that reflects the methylation state of the nucleic acid molecule. Methods of treating a nucleic acid molecule with such a reagent can include contacting the nucleic acid molecule with the reagent, coupled with additional steps, if desired, to accomplish the desired change of nucleotide sequence. Such methods can be applied in a manner in which unmethylated nucleotides (e.g., each unmethylated cytosine) is modified to a different nucleotide. For example, in some embodiments, such a reagent can deaminate unmethylated cytosine nucleotides to produce deoxy uracil residues. Examples of such reagents include, but are not limited to, a methylation-sensitive restriction enzyme, a methylation-dependent restriction enzyme, and a bisulfite reagent.


The term “bisulfite reagent” refers to a reagent comprising bisulfite, disulfite, hydrogen sulfite, or combinations thereof, useful as disclosed herein to distinguish between methylated and unmethylated CpG dinucleotide sequences. Methods of said treatment are known in the art (e.g., PCT/EP2004/011715 and WO 2013/116375, each of which is incorporated by reference in its entirety). In some embodiments, bisulfite treatment is conducted in the presence of denaturing solvents such as but not limited to n-alkyleneglycol or diethylene glycol dimethyl ether (DME), or in the presence of dioxane or dioxane derivatives. In some embodiments the denaturing solvents are used in concentrations between 1% and 35% (v/v). In some embodiments, the bisulfite reaction is carried out in the presence of scavengers such as but not limited to chromane derivatives, e.g., 6-hydroxy-2,5,7,8,-tetramethylchromane 2-carboxylic acid or trihydroxybenzone acid and derivates thereof, e.g., Gallic acid (see: PCT/EP2004/011715, which is incorporated by reference in its entirety). In certain preferred embodiments, the bisulfite reaction comprises treatment with ammonium hydrogen sulfite, e.g., as described in WO 2013/116375.


A change in the nucleic acid nucleotide sequence by a methylation-specific reagent can also result in a nucleic acid molecule in which each methylated nucleotide is modified to a different nucleotide.


The term “methylation assay” refers to any assay for determining the methylation state of one or more CpG dinucleotide sequences within a sequence of a nucleic acid.


The term “MS AP-PCR” (Methylation-Sensitive Arbitrarily-Primed Polymerase Chain Reaction) refers to the art-recognized technology that allows for a global scan of the genome using CG-rich primers to focus on the regions most likely to contain CpG dinucleotides, and described by Gonzalgo et al. (1997) Cancer Research 57: 594-599.


The term “MethyLight™” refers to the art-recognized fluorescence-based real-time PCR technique described by Eads et al. (1999) Cancer Res. 59: 2302-2306.


The term “HeavyMethyl™” refers to an assay wherein methylation specific blocking probes (also referred to herein as blockers) covering CpG positions between, or covered by, the amplification primers enable methylation-specific selective amplification of a nucleic acid sample.


The term “HeavyMethyl™ MethyLight™” assay refers to a HeavyMethyl™ MethyLight™ assay, which is a variation of the MethyLight™ assay, wherein the MethyLight™ assay is combined with methylation specific blocking probes covering CpG positions between the amplification primers.


The term “Ms-SNuPE” (Methylation-sensitive Single Nucleotide Primer Extension) refers to the art-recognized assay described by Gonzalgo & Jones (1997) Nucleic Acids Res. 25: 2529-2531.


The term “MSP” (Methylation-specific PCR) refers to the art-recognized methylation assay described by Herman et al. (1996) Proc. Natl. Acad. Sci. USA 93: 9821-9826, and by U.S. Pat. No. 5,786,146.


The term “COBRA” (Combined Bisulfite Restriction Analysis) refers to the art-recognized methylation assay described by Xiong & Laird (1997) Nucleic Acids Res. 25: 2532-2534.


The term “MCA” (Methylated CpG Island Amplification) refers to the methylation assay described by Toyota et al. (1999) Cancer Res. 59: 2307-12, and in WO 00/26401A1.


As used herein, a “selected nucleotide” refers to one nucleotide of the four typically occurring nucleotides in a nucleic acid molecule (C, G, T, and A for DNA and C, G, U, and A for RNA), and can include methylated derivatives of the typically occurring nucleotides (e.g., when C is the selected nucleotide, both methylated and unmethylated C are included within the meaning of a selected nucleotide), whereas a methylated selected nucleotide refers specifically to a methylated typically occurring nucleotide and an unmethylated selected nucleotides refers specifically to an unmethylated typically occurring nucleotide.


The term “methylation-specific restriction enzyme” refers to a restriction enzyme that selectively digests a nucleic acid dependent on the methylation state of its recognition site. In the case of a restriction enzyme that specifically cuts if the recognition site is not methylated or is hemi-methylated (a methylation-sensitive enzyme), the cut will not take place (or will take place with a significantly reduced efficiency) if the recognition site is methylated on one or both strands. In the case of a restriction enzyme that specifically cuts only if the recognition site is methylated (a methylation-dependent enzyme), the cut will not take place (or will take place with a significantly reduced efficiency) if the recognition site is not methylated. Preferred are methylation-specific restriction enzymes, the recognition sequence of which contains a CG dinucleotide (for instance a recognition sequence such as CGCG or CCCGGG). Further preferred for some embodiments are restriction enzymes that do not cut if the cytosine in this dinucleotide is methylated at the carbon atom C5.


As used herein, a “different nucleotide” refers to a nucleotide that is chemically different from a selected nucleotide, typically such that the different nucleotide has Watson-Crick base-pairing properties that differ from the selected nucleotide, whereby the typically occurring nucleotide that is complementary to the selected nucleotide is not the same as the typically occurring nucleotide that is complementary to the different nucleotide. For example, when C is the selected nucleotide, U or T can be the different nucleotide, which is exemplified by the complementarity of C to G and the complementarity of U or T to A. As used herein, a nucleotide that is complementary to the selected nucleotide or that is complementary to the different nucleotide refers to a nucleotide that base-pairs, under high stringency conditions, with the selected nucleotide or different nucleotide with higher affinity than the complementary nucleotide's base-paring with three of the four typically occurring nucleotides. An example of complementarity is Watson-Crick base pairing in DNA (e.g., A-T and C-G) and RNA (e.g., A-U and C-G). Thus, for example, G base-pairs, under high stringency conditions, with higher affinity to C than G base-pairs to G, A, or T and, therefore, when C is the selected nucleotide, G is a nucleotide complementary to the selected nucleotide.


As used herein, the “sensitivity” of a given marker (or set of markers used together) refers to the percentage of samples that report a DNA methylation value above a threshold value that distinguishes between neoplastic and non-neoplastic samples. In some embodiments, a positive is defined as a histology-confirmed neoplasia that reports a DNA methylation value above a threshold value (e.g., the range associated with disease), and a false negative is defined as a histology-confirmed neoplasia that reports a DNA methylation value below the threshold value (e.g., the range associated with no disease). The value of sensitivity, therefore, reflects the probability that a DNA methylation measurement for a given marker obtained from a known diseased sample will be in the range of disease-associated measurements. As defined here, the clinical relevance of the calculated sensitivity value represents an estimation of the probability that a given marker would detect the presence of a clinical condition when applied to a subject with that condition.


As used herein, the “specificity” of a given marker (or set of markers used together) refers to the percentage of non-neoplastic samples that report a DNA methylation value below a threshold value that distinguishes between neoplastic and non-neoplastic samples. In some embodiments, a negative is defined as a histology-confirmed non-neoplastic sample that reports a DNA methylation value below the threshold value (e.g., the range associated with no disease) and a false positive is defined as a histology-confirmed non-neoplastic sample that reports a DNA methylation value above the threshold value (e.g., the range associated with disease). The value of specificity, therefore, reflects the probability that a DNA methylation measurement for a given marker obtained from a known non-neoplastic sample will be in the range of non-disease associated measurements. As defined here, the clinical relevance of the calculated specificity value represents an estimation of the probability that a given marker would detect the absence of a clinical condition when applied to a patient without that condition.


The term “AUC” as used herein is an abbreviation for the “area under a curve”. In particular it refers to the area under a Receiver Operating Characteristic (ROC) curve. The ROC curve is a plot of the true positive rate against the false positive rate for the different possible cut points of a diagnostic test. It shows the trade-off between sensitivity and specificity depending on the selected cut point (any increase in sensitivity will be accompanied by a decrease in specificity). The area under an ROC curve (AUC) is a measure for the accuracy of a diagnostic test (the larger the area the better; the optimum is 1; a random test would have a ROC curve lying on the diagonal with an area of 0.5; for reference: J. P. Egan. (1975) Signal Detection Theory and ROC Analysis, Academic Press, New York).


The term “neoplasm” as used herein refers to any new and abnormal growth of tissue. Thus, a neoplasm can be a premalignant neoplasm or a malignant neoplasm.


The term “neoplasm-specific marker,” as used herein, refers to any biological material or element that can be used to indicate the presence of a neoplasm. Examples of biological materials include, without limitation, nucleic acids, polypeptides, carbohydrates, fatty acids, cellular components (e.g., cell membranes and mitochondria), and whole cells. In some instances, markers are particular nucleic acid regions (e.g., genes, intragenic regions, specific loci, etc.). Regions of nucleic acid that are markers may be referred to, e.g., as “marker genes,” “marker regions,” “marker sequences,” “marker loci,” etc.


As used herein, the term “adenoma” refers to a benign tumor of glandular origin. Although these growths are benign, over time they may progress to become malignant.


The term “pre-cancerous” or “pre-neoplastic” and equivalents thereof refer to any cellular proliferative disorder that is undergoing malignant transformation.


A “site” of a neoplasm, adenoma, cancer, etc. is the tissue, organ, cell type, anatomical area, body part, etc. in a subject's body where the neoplasm, adenoma, cancer, etc. is located.


As used herein, a “diagnostic” test application includes the detection or identification of a disease state or condition of a subject, determining the likelihood that a subject will contract a given disease or condition, determining the likelihood that a subject with a disease or condition will respond to therapy, determining the prognosis of a subject with a disease or condition (or its likely progression or regression), and determining the effect of a treatment on a subject with a disease or condition. For example, a diagnostic can be used for detecting the presence or likelihood of a subject contracting a neoplasm or the likelihood that such a subject will respond favorably to a compound (e.g., a pharmaceutical, e.g., a drug) or other treatment.


The term “isolated” when used in relation to a nucleic acid, as in “an isolated oligonucleotide” refers to a nucleic acid sequence that is identified and separated from at least one contaminant nucleic acid with which it is ordinarily associated in its natural source. Isolated nucleic acid is present in a form or setting that is different from that in which it is found in nature. In contrast, non-isolated nucleic acids, such as DNA and RNA, are found in the state they exist in nature. Examples of non-isolated nucleic acids include: a given DNA sequence (e.g., a gene) found on the host cell chromosome in proximity to neighboring genes; RNA sequences, such as a specific mRNA sequence encoding a specific protein, found in the cell as a mixture with numerous other mRNAs which encode a multitude of proteins. However, isolated nucleic acid encoding a particular protein includes, by way of example, such nucleic acid in cells ordinarily expressing the protein, where the nucleic acid is in a chromosomal location different from that of natural cells, or is otherwise flanked by a different nucleic acid sequence than that found in nature. The isolated nucleic acid or oligonucleotide may be present in single-stranded or double-stranded form. When an isolated nucleic acid or oligonucleotide is to be utilized to express a protein, the oligonucleotide will contain at a minimum the sense or coding strand (i.e., the oligonucleotide may be single-stranded), but may contain both the sense and anti-sense strands (i.e., the oligonucleotide may be double-stranded). An isolated nucleic acid may, after isolation from its natural or typical environment, by be combined with other nucleic acids or molecules. For example, an isolated nucleic acid may be present in a host cell in which into which it has been placed, e.g., for heterologous expression.


The term “purified” refers to molecules, either nucleic acid or amino acid sequences that are removed from their natural environment, isolated, or separated. An “isolated nucleic acid sequence” may therefore be a purified nucleic acid sequence. “Substantially purified” molecules are at least 60% free, preferably at least 75% free, and more preferably at least 90% free from other components with which they are naturally associated. As used herein, the terms “purified” or “to purify” also refer to the removal of contaminants from a sample. The removal of contaminating proteins results in an increase in the percent of polypeptide or nucleic acid of interest in the sample. In another example, recombinant polypeptides are expressed in plant, bacterial, yeast, or mammalian host cells and the polypeptides are purified by the removal of host cell proteins; the percent of recombinant polypeptides is thereby increased in the sample.


The term “composition comprising” a given polynucleotide sequence or polypeptide refers broadly to any composition containing the given polynucleotide sequence or polypeptide. The composition may comprise an aqueous solution containing salts (e.g., NaCl), detergents (e.g., SDS), and other components (e.g., Denhardt's solution, dry milk, salmon sperm DNA, etc.).


The term “sample” is used in its broadest sense. In one sense it can refer to an animal cell or tissue. In another sense, it refers to a specimen or culture obtained from any source, as well as biological and environmental samples. Biological samples may be obtained from plants or animals (including humans) and encompass fluids, solids, tissues, and gases. Environmental samples include environmental material such as surface matter, soil, water, and industrial samples. These examples are not to be construed as limiting the sample types applicable to the present invention.


As used herein, a “remote sample” as used in some contexts relates to a sample indirectly collected from a site that is not the cell, tissue, or organ source of the sample. For instance, when sample material originating from the pancreas is assessed in a stool sample (e.g., not from a sample taken directly from a breast), the sample is a remote sample.


As used herein, the terms “patient” or “subject” refer to organisms to be subject to various tests provided by the technology. The term “subject” includes animals, preferably mammals, including humans. In a preferred embodiment, the subject is a primate. In an even more preferred embodiment, the subject is a human. Further with respect to diagnostic methods, a preferred subject is a vertebrate subject. A preferred vertebrate is warm-blooded; a preferred warm-blooded vertebrate is a mammal. A preferred mammal is most preferably a human. As used herein, the term “subject’ includes both human and animal subjects. Thus, veterinary therapeutic uses are provided herein. As such, the present technology provides for the diagnosis of mammals such as humans, as well as those mammals of importance due to being endangered, such as Siberian tigers; of economic importance, such as animals raised on farms for consumption by humans; and/or animals of social importance to humans, such as animals kept as pets or in zoos. Examples of such animals include but are not limited to: carnivores such as cats and dogs; swine, including pigs, hogs, and wild boars; ruminants and/or ungulates such as cattle, oxen, sheep, giraffes, deer, goats, bison, and camels; pinnipeds; and horses. Thus, also provided is the diagnosis and treatment of livestock, including, but not limited to, domesticated swine, ruminants, ungulates, horses (including race horses), and the like. The presently-disclosed subject matter further includes a system for diagnosing a lung cancer in a subject. The system can be provided, for example, as a commercial kit that can be used to screen for a risk of lung cancer or diagnose a lung cancer in a subject from whom a biological sample has been collected. An exemplary system provided in accordance with the present technology includes assessing the methylation state of a marker described herein.


As used herein, the term “kit” refers to any delivery system for delivering materials. In the context of reaction assays, such delivery systems include systems that allow for the storage, transport, or delivery of reaction reagents (e.g., oligonucleotides, enzymes, etc. in the appropriate containers) and/or supporting materials (e.g., buffers, written instructions for performing the assay etc.) from one location to another. For example, kits include one or more enclosures (e.g., boxes) containing the relevant reaction reagents and/or supporting materials. As used herein, the term “fragmented kit” refers to delivery systems comprising two or more separate containers that each contain a subportion of the total kit components. The containers may be delivered to the intended recipient together or separately. For example, a first container may contain an enzyme for use in an assay, while a second container contains oligonucleotides. The term “fragmented kit” is intended to encompass kits containing Analyte specific reagents (ASR's) regulated under section 520(e) of the Federal Food, Drug, and Cosmetic Act, but are not limited thereto. Indeed, any delivery system comprising two or more separate containers that each contains a subportion of the total kit components are included in the term “fragmented kit.” In contrast, a “combined kit” refers to a delivery system containing all of the components of a reaction assay in a single container (e.g., in a single box housing each of the desired components). The term “kit” includes both fragmented and combined kits.


As used herein, the term “breast cancer” refers generally to the uncontrolled growth of breast tissue and, more specifically, to a condition characterized by anomalous rapid proliferation of abnormal cells in one or both breasts of a subject. The abnormal cells often are referred to as malignant or “neoplastic cells,” which are transformed cells that can form a solid tumor. The term “tumor” refers to an abnormal mass or population of cells (i.e., two or more cells) that result from excessive or abnormal cell division, whether malignant or benign, and pre-cancerous and cancerous cells. Malignant tumors are distinguished from benign growths or tumors in that, in addition to uncontrolled cellular proliferation, they can invade surrounding tissues and can metastasize.


As used herein, the term “information” refers to any collection of facts or data. In reference to information stored or processed using a computer system(s), including but not limited to internets, the term refers to any data stored in any format (e.g., analog, digital, optical, etc.). As used herein, the term “information related to a subject” refers to facts or data pertaining to a subject (e.g., a human, plant, or animal). The term “genomic information” refers to information pertaining to a genome including, but not limited to, nucleic acid sequences, genes, percentage methylation, allele frequencies, RNA expression levels, protein expression, phenotypes correlating to genotypes, etc. “Allele frequency information” refers to facts or data pertaining to allele frequencies, including, but not limited to, allele identities, statistical correlations between the presence of an allele and a characteristic of a subject (e.g., a human subject), the presence or absence of an allele in an individual or population, the percentage likelihood of an allele being present in an individual having one or more particular characteristics, etc.







DETAILED DESCRIPTION

In this detailed description of the various embodiments, for purposes of explanation, numerous specific details are set forth to provide a thorough understanding of the embodiments disclosed. One skilled in the art will appreciate, however, that these various embodiments may be practiced with or without these specific details. In other instances, structures and devices are shown in block diagram form. Furthermore, one skilled in the art can readily appreciate that the specific sequences in which methods are presented and performed are illustrative and it is contemplated that the sequences can be varied and still remain within the spirit and scope of the various embodiments disclosed herein.


Provided herein is technology for breast cancer screening and particularly, but not exclusively, to methods, compositions, and related uses for detecting the presence of breast cancer. As the technology is described herein, the section headings used are for organizational purposes only and are not to be construed as limiting the subject matter in any way.


Indeed, as described in Examples I, II and III, experiments conducted during the course for identifying embodiments for the present invention identified a novel set of 375 differentially methylated regions (DMRs) for discriminating cancer of the breast derived DNA from non-neoplastic control DNA. In addition, DMRs were identified capable of plasma from subjects having breast cancer from plasma from subjects not having breast cancer.


Although the disclosure herein refers to certain illustrated embodiments, it is to be understood that these embodiments are presented by way of example and not by way of limitation.


In particular aspects, the present technology provides compositions and methods for identifying, determining, and/or classifying a cancer such as breast cancer. The methods comprise determining the methylation status of at least one methylation marker in a biological sample isolated from a subject (e.g., stool sample, breast tissue sample, plasma sample), wherein a change in the methylation state of the marker is indicative of the presence, class, or site of a breast cancer. Particular embodiments relate to markers comprising a differentially methylated region (DMR, e.g., DMR 1-375, see Tables 2 and 5) that are used for diagnosis (e.g., screening) of breast cancer.


In addition to embodiments wherein the methylation analysis of at least one marker, a region of a marker, or a base of a marker comprising a DMR (e.g., DMR, e.g., DMR 1-375) provided herein and listed in Tables 2 and 5 is analyzed, the technology also provides panels of markers comprising at least one marker, region of a marker, or base of a marker comprising a DMR with utility for the detection of cancers, in particular breast cancer.


Some embodiments of the technology are based upon the analysis of the CpG methylation status of at least one marker, region of a marker, or base of a marker comprising a DMR.


In some embodiments, the present technology provides for the use of a reagent that modifies DNA in a methylation-specific manner (e.g., a methylation-sensitive restriction enzyme, a methylation-dependent restriction enzyme, and a bisulfite reagent) in combination with one or more methylation assays to determine the methylation status of CpG dinucleotide sequences within at least one marker comprising a DMR (e.g., DMR 1-375, see Tables 2 and 5). Genomic CpG dinucleotides can be methylated or unmethylated (alternatively known as up- and down-methylated respectively). However the methods of the present invention are suitable for the analysis of biological samples of a heterogeneous nature, e.g., a low concentration of tumor cells, or biological materials therefrom, within a background of a remote sample (e.g., blood, organ effluent, or stool). Accordingly, when analyzing the methylation status of a CpG position within such a sample one may use a quantitative assay for determining the level (e.g., percent, fraction, ratio, proportion, or degree) of methylation at a particular CpG position.


According to the present technology, determination of the methylation status of CpG dinucleotide sequences in markers comprising a DMR has utility both in the diagnosis and characterization of cancers such as breast cancer.


Combinations of Markers

In some embodiments, the technology relates to assessing the methylation state of combinations of markers comprising a DMR from Tables 2 and 5 (e.g., DMR Nos. 1-375). In some embodiments, assessing the methylation state of more than one marker increases the specificity and/or sensitivity of a screen or diagnostic for identifying a neoplasm in a subject (e.g., breast cancer).


Various cancers are predicted by various combinations of markers, e.g., as identified by statistical techniques related to specificity and sensitivity of prediction. The technology provides methods for identifying predictive combinations and validated predictive combinations for some cancers.


Methods for Assaying Methylation State

In certain embodiments, methods for analyzing a nucleic acid for the presence of 5-methylcytosine involves treatment of DNA with a reagent that modifies DNA in a methylation-specific manner. Examples of such reagents include, but are not limited to, a methylation-sensitive restriction enzyme, a methylation-dependent restriction enzyme, and a bisulfite reagent.


A frequently used method for analyzing a nucleic acid for the presence of 5-methylcytosine is based upon the bisulfite method described by Frommer, et al. for the detection of 5-methylcytosines in DNA (Frommer et al. (1992) Proc. Natl. Acad. Sci. USA 89: 1827-31 explicitly incorporated herein by reference in its entirety for all purposes) or variations thereof. The bisulfite method of mapping 5-methylcytosines is based on the observation that cytosine, but not 5-methylcytosine, reacts with hydrogen sulfite ion (also known as bisulfite). The reaction is usually performed according to the following steps: first, cytosine reacts with hydrogen sulfite to form a sulfonated cytosine. Next, spontaneous deamination of the sulfonated reaction intermediate results in a sulfonated uracil. Finally, the sulfonated uracil is desulfonated under alkaline conditions to form uracil. Detection is possible because uracil base pairs with adenine (thus behaving like thymine), whereas 5-methylcytosine base pairs with guanine (thus behaving like cytosine). This makes the discrimination of methylated cytosines from non-methylated cytosines possible by, e.g., bisulfite genomic sequencing (Grigg G, & Clark S, Bioessays (1994) 16: 431-36; Grigg G, DNA Seq. (1996) 6: 189-98),methylation-specific PCR (MSP) as is disclosed, e.g., in U.S. Pat. No. 5,786,146, or using an assay comprising sequence-specific probe cleavage, e.g., a QuARTS flap endonuclease assay (see, e.g., Zou et al. (2010) “Sensitive quantification of methylated markers with a novel methylation specific technology” Clin Chem 56: A199; and in U.S. Pat. Nos. 8,361,720; 8,715,937; 8,916,344; and 9,212,392.


Some conventional technologies are related to methods comprising enclosing the DNA to be analyzed in an agarose matrix, thereby preventing the diffusion and renaturation of the DNA (bisulfite only reacts with single-stranded DNA), and replacing precipitation and purification steps with a fast dialysis (Olek A, et al. (1996) “A modified and improved method for bisulfite based cytosine methylation analysis” Nucleic Acids Res. 24: 5064-6). It is thus possible to analyze individual cells for methylation status, illustrating the utility and sensitivity of the method. An overview of conventional methods for detecting 5-methylcytosine is provided by Rein, T., et al. (1998) Nucleic Acids Res. 26: 2255.


The bisulfite technique typically involves amplifying short, specific fragments of a known nucleic acid subsequent to a bisulfite treatment, then either assaying the product by sequencing (Olek & Walter (1997) Nat. Genet. 17: 275-6) or a primer extension reaction (Gonzalgo & Jones (1997) Nucleic Acids Res. 25: 2529-31; WO 95/00669; U.S. Pat. No. 6,251,594) to analyze individual cytosine positions. Some methods use enzymatic digestion (Xiong & Laird (1997) Nucleic Acids Res. 25: 2532-4). Detection by hybridization has also been described in the art (Olek et al., WO 99/28498). Additionally, use of the bisulfite technique for methylation detection with respect to individual genes has been described (Grigg & Clark (1994) Bioessays 16: 431-6; Zeschnigk et al. (1997) Hum Mol Genet. 6: 387-95; Feil et al. (1994) Nucleic Acids Res. 22: 695; Martin et al. (1995) Gene 157: 261-4; WO 9746705; WO 9515373).


Various methylation assay procedures can be used in conjunction with bisulfite treatment according to the present technology. These assays allow for determination of the methylation state of one or a plurality of CpG dinucleotides (e.g., CpG islands) within a nucleic acid sequence. Such assays involve, among other techniques, sequencing of bisulfite-treated nucleic acid, PCR (for sequence-specific amplification), Southern blot analysis, and use of methylation-specific restriction enzymes, e.g., methylation-sensitive or methylation-dependent enzymes.


For example, genomic sequencing has been simplified for analysis of methylation patterns and 5-methylcytosine distributions by using bisulfite treatment (Frommer et al. (1992) Proc. Natl. Acad. Sci. USA 89: 1827-1831). Additionally, restriction enzyme digestion of PCR products amplified from bisulfite-converted DNA finds use in assessing methylation state, e.g., as described by Sadri & Hornsby (1997) Nucl. Acids Res. 24: 5058-5059 or as embodied in the method known as COBRA (Combined Bisulfite Restriction Analysis) (Xiong & Laird (1997) Nucleic Acids Res. 25: 2532-2534).


COBRA™ analysis is a quantitative methylation assay useful for determining DNA methylation levels at specific loci in small amounts of genomic DNA (Xiong & Laird, Nucleic Acids Res. 25:2532-2534, 1997). Briefly, restriction enzyme digestion is used to reveal methylation-dependent sequence differences in PCR products of sodium bisulfite-treated DNA. Methylation-dependent sequence differences are first introduced into the genomic DNA by standard bisulfite treatment according to the procedure described by Frommer et al. (Proc. Natl. Acad. Sci. USA 89:1827-1831, 1992). PCR amplification of the bisulfite converted DNA is then performed using primers specific for the CpG islands of interest, followed by restriction endonuclease digestion, gel electrophoresis, and detection using specific, labeled hybridization probes. Methylation levels in the original DNA sample are represented by the relative amounts of digested and undigested PCR product in a linearly quantitative fashion across a wide spectrum of DNA methylation levels. In addition, this technique can be reliably applied to DNA obtained from microdissected paraffin-embedded tissue samples.


Typical reagents (e.g., as might be found in a typical COBRA™-based kit) for COBRA™ analysis may include, but are not limited to: PCR primers for specific loci (e.g., specific genes, markers, DMR, regions of genes, regions of markers, bisulfite treated DNA sequence, CpG island, etc.); restriction enzyme and appropriate buffer; gene-hybridization oligonucleotide; control hybridization oligonucleotide; kinase labeling kit for oligonucleotide probe; and labeled nucleotides. Additionally, bisulfite conversion reagents may include: DNA denaturation buffer; sulfonation buffer; DNA recovery reagents or kits (e.g., precipitation, ultrafiltration, affinity column); desulfonation buffer; and DNA recovery components. Assays such as “MethyLight™” (a fluorescence-based real-time PCR technique) (Eads et al., Cancer Res. 59:2302-2306, 1999), Ms-SNuPE™ (Methylation-sensitive Single Nucleotide Primer Extension) reactions (Gonzalgo & Jones, Nucleic Acids Res. 25:2529-2531, 1997), methylation-specific PCR (“MSP”; Herman et al., Proc. Natl. Acad. Sci. USA 93:9821-9826, 1996; U.S. Pat. No. 5,786,146), and methylated CpG island amplification (“MCA”; Toyota et al., Cancer Res. 59:2307-12, 1999) are used alone or in combination with one or more of these methods.


The “HeavyMethyl™” assay, technique is a quantitative method for assessing methylation differences based on methylation-specific amplification of bisulfite-treated DNA. Methylation-specific blocking probes (“blockers”) covering CpG positions between, or covered by, the amplification primers enable methylation-specific selective amplification of a nucleic acid sample.


The term “HeavyMethyl™ MethyLight™” assay refers to a HeavyMethyl™ MethyLight™ assay, which is a variation of the MethyLight™ assay, wherein the MethyLight™ assay is combined with methylation specific blocking probes covering CpG positions between the amplification primers. The HeavyMethyl™ assay may also be used in combination with methylation specific amplification primers.


Typical reagents (e.g., as might be found in a typical MethyLight™-based kit) for HeavyMethyl™ analysis may include, but are not limited to: PCR primers for specific loci (e.g., specific genes, markers, regions of genes, regions of markers, bisulfite treated DNA sequence, CpG island, or bisulfite treated DNA sequence or CpG island, etc.); blocking oligonucleotides; optimized PCR buffers and deoxynucleotides; and Taq polymerase. MSP (methylation-specific PCR) allows for assessing the methylation status of virtually any group of CpG sites within a CpG island, independent of the use of methylation-sensitive restriction enzymes (Herman et al. Proc. Natl. Acad. Sci. USA 93:9821-9826, 1996; U.S. Pat. No. 5,786,146). Briefly, DNA is modified by sodium bisulfite, which converts unmethylated, but not methylated cytosines, to uracil, and the products are subsequently amplified with primers specific for methylated versus unmethylated DNA. MSP requires only small quantities of DNA, is sensitive to 0.1% methylated alleles of a given CpG island locus, and can be performed on DNA extracted from paraffin-embedded samples. Typical reagents (e.g., as might be found in a typical MSP-based kit) for MSP analysis may include, but are not limited to: methylated and unmethylated PCR primers for specific loci (e.g., specific genes, markers, regions of genes, regions of markers, bisulfite treated DNA sequence, CpG island, etc.); optimized PCR buffers and deoxynucleotides, and specific probes.


The MethyLight™ assay is a high-throughput quantitative methylation assay that utilizes fluorescence-based real-time PCR (e.g., TaqMan®) that requires no further manipulations after the PCR step (Eads et al., Cancer Res. 59:2302-2306, 1999). Briefly, the MethyLight™ process begins with a mixed sample of genomic DNA that is converted, in a sodium bisulfite reaction, to a mixed pool of methylation-dependent sequence differences according to standard procedures (the bisulfite process converts unmethylated cytosine residues to uracil). Fluorescence-based PCR is then performed in a “biased” reaction, e.g., with PCR primers that overlap known CpG dinucleotides. Sequence discrimination occurs both at the level of the amplification process and at the level of the fluorescence detection process.


The MethyLight™ assay is used as a quantitative test for methylation patterns in a nucleic acid, e.g., a genomic DNA sample, wherein sequence discrimination occurs at the level of probe hybridization. In a quantitative version, the PCR reaction provides for a methylation specific amplification in the presence of a fluorescent probe that overlaps a particular putative methylation site. An unbiased control for the amount of input DNA is provided by a reaction in which neither the primers, nor the probe, overlie any CpG dinucleotides. Alternatively, a qualitative test for genomic methylation is achieved by probing the biased PCR pool with either control oligonucleotides that do not cover known methylation sites (e.g., a fluorescence-based version of the HeavyMethyl™ and MSP techniques) or with oligonucleotides covering potential methylation sites.


The MethyLight™ process is used with any suitable probe (e.g. a “TaqMan®” probe, a Lightcycler® probe, etc.) For example, in some applications double-stranded genomic DNA is treated with sodium bisulfite and subjected to one of two sets of PCR reactions using TaqMan® probes, e.g., with MSP primers and/or HeavyMethyl blocker oligonucleotides and a TaqMan® probe. The TaqMan® probe is dual-labeled with fluorescent “reporter” and “quencher” molecules and is designed to be specific for a relatively high GC content region so that it melts at about a 10° C. higher temperature in the PCR cycle than the forward or reverse primers. This allows the TaqMan® probe to remain fully hybridized during the PCR annealing/extension step. As the Taq polymerase enzymatically synthesizes a new strand during PCR, it will eventually reach the annealed TaqMan® probe. The Taq polymerase 5′ to 3′ endonuclease activity will then displace the TaqMan® probe by digesting it to release the fluorescent reporter molecule for quantitative detection of its now unquenched signal using a real-time fluorescent detection system.


Typical reagents (e.g., as might be found in a typical MethyLight™-based kit) for MethyLight™ analysis may include, but are not limited to: PCR primers for specific loci (e.g., specific genes, markers, regions of genes, regions of markers, bisulfite treated DNA sequence, CpG island, etc.); TaqMan® or Lightcycler® probes; optimized PCR buffers and deoxynucleotides; and Taq polymerase.


The QM™ (quantitative methylation) assay is an alternative quantitative test for methylation patterns in genomic DNA samples, wherein sequence discrimination occurs at the level of probe hybridization. In this quantitative version, the PCR reaction provides for unbiased amplification in the presence of a fluorescent probe that overlaps a particular putative methylation site. An unbiased control for the amount of input DNA is provided by a reaction in which neither the primers, nor the probe, overlie any CpG dinucleotides. Alternatively, a qualitative test for genomic methylation is achieved by probing the biased PCR pool with either control oligonucleotides that do not cover known methylation sites (a fluorescence-based version of the HeavyMethyl™ and MSP techniques) or with oligonucleotides covering potential methylation sites.


The QM™ process can be used with any suitable probe, e.g., “TaqMan®” probes, Lightcycler® probes, in the amplification process. For example, double-stranded genomic DNA is treated with sodium bisulfite and subjected to unbiased primers and the TaqMan® probe. The TaqMan® probe is dual-labeled with fluorescent “reporter” and “quencher” molecules, and is designed to be specific for a relatively high GC content region so that it melts out at about a 10° C. higher temperature in the PCR cycle than the forward or reverse primers. This allows the TaqMan® probe to remain fully hybridized during the PCR annealing/extension step. As the Taq polymerase enzymatically synthesizes a new strand during PCR, it will eventually reach the annealed TaqMan® probe. The Taq polymerase 5′ to 3′ endonuclease activity will then displace the TaqMan® probe by digesting it to release the fluorescent reporter molecule for quantitative detection of its now unquenched signal using a real-time fluorescent detection system. Typical reagents (e.g., as might be found in a typical QM™-based kit) for QM™ analysis may include, but are not limited to: PCR primers for specific loci (e.g., specific genes, markers, regions of genes, regions of markers, bisulfite treated DNA sequence, CpG island, etc.); TaqMan® or Lightcycler® probes; optimized PCR buffers and deoxynucleotides; and Taq polymerase.


The Ms-SNuPE™ technique is a quantitative method for assessing methylation differences at specific CpG sites based on bisulfite treatment of DNA, followed by single-nucleotide primer extension (Gonzalgo & Jones, Nucleic Acids Res. 25:2529-2531, 1997). Briefly, genomic DNA is reacted with sodium bisulfite to convert unmethylated cytosine to uracil while leaving 5-methylcytosine unchanged. Amplification of the desired target sequence is then performed using PCR primers specific for bisulfite-converted DNA, and the resulting product is isolated and used as a template for methylation analysis at the CpG site of interest. Small amounts of DNA can be analyzed (e.g., microdissected pathology sections) and it avoids utilization of restriction enzymes for determining the methylation status at CpG sites.


Typical reagents (e.g., as might be found in a typical Ms-SNuPE™-based kit) for Ms-SNuPE™ analysis may include, but are not limited to: PCR primers for specific loci (e.g., specific genes, markers, regions of genes, regions of markers, bisulfite treated DNA sequence, CpG island, etc.); optimized PCR buffers and deoxynucleotides; gel extraction kit; positive control primers; Ms-SNuPE™ primers for specific loci; reaction buffer (for the Ms-SNuPE reaction); and labeled nucleotides. Additionally, bisulfite conversion reagents may include: DNA denaturation buffer; sulfonation buffer; DNA recovery reagents or kit (e.g., precipitation, ultrafiltration, affinity column); desulfonation buffer; and DNA recovery components.


Reduced Representation Bisulfite Sequencing (RRBS) begins with bisulfite treatment of nucleic acid to convert all unmethylated cytosines to uracil, followed by restriction enzyme digestion (e.g., by an enzyme that recognizes a site including a CG sequence such as Mspl) and complete sequencing of fragments after coupling to an adapter ligand. The choice of restriction enzyme enriches the fragments for CpG dense regions, reducing the number of redundant sequences that may map to multiple gene positions during analysis. As such, RRBS reduces the complexity of the nucleic acid sample by selecting a subset (e.g., by size selection using preparative gel electrophoresis) of restriction fragments for sequencing. As opposed to whole-genome bisulfite sequencing, every fragment produced by the restriction enzyme digestion contains DNA methylation information for at least one CpG dinucleotide. As such, RRBS enriches the sample for promoters, CpG islands, and other genomic features with a high frequency of restriction enzyme cut sites in these regions and thus provides an assay to assess the methylation state of one or more genomic loci.


A typical protocol for RRBS comprises the steps of digesting a nucleic acid sample with a restriction enzyme such as Mspl, filling in overhangs and A-tailing, ligating adaptors, bisulfite conversion, and PCR. See, e.g., et al. (2005) “Genome-scale DNA methylation mapping of clinical samples at single-nucleotide resolution” Nat Methods 7: 133-6; Meissner et al. (2005) “Reduced representation bisulfite sequencing for comparative high-resolution DNA methylation analysis” Nucleic Acids Res. 33: 5868-77.


In some embodiments, a quantitative allele-specific real-time target and signal amplification (QUARTS) assay is used to evaluate methylation state. Three reactions sequentially occur in each QUARTS assay, including amplification (reaction 1) and target probe cleavage (reaction 2) in the primary reaction; and FRET cleavage and fluorescent signal generation (reaction 3) in the secondary reaction. When target nucleic acid is amplified with specific primers, a specific detection probe with a flap sequence loosely binds to the amplicon. The presence of the specific invasive oligonucleotide at the target binding site causes a 5′ nuclease, e.g., a FEN-1 endonuclease, to release the flap sequence by cutting between the detection probe and the flap sequence. The flap sequence is complementary to a non-hairpin portion of a corresponding FRET cassette. Accordingly, the flap sequence functions as an invasive oligonucleotide on the FRET cassette and effects a cleavage between the FRET cassette fluorophore and a quencher, which produces a fluorescent signal. The cleavage reaction can cut multiple probes per target and thus release multiple fluorophore per flap, providing exponential signal amplification. QuARTS can detect multiple targets in a single reaction well by using FRET cassettes with different dyes. See, e.g., in Zou et al. (2010) “Sensitive quantification of methylated markers with a novel methylation specific technology” Clin Chem 56: A199), and U.S. Pat. Nos. 8,361,720; 8,715,937; 8,916,344; and 9,212,392, each of which is incorporated herein by reference for all purposes.


The term “bisulfite reagent” refers to a reagent comprising bisulfite, disulfite, hydrogen sulfite, or combinations thereof, useful as disclosed herein to distinguish between methylated and unmethylated CpG dinucleotide sequences. Methods of said treatment are known in the art (e.g., PCT/EP2004/011715 and WO 2013/116375, each of which is incorporated by reference in its entirety). In some embodiments, bisulfite treatment is conducted in the presence of denaturing solvents such as but not limited to n-alkyleneglycol or diethylene glycol dimethyl ether (DME), or in the presence of dioxane or dioxane derivatives. In some embodiments the denaturing solvents are used in concentrations between 1% and 35% (v/v). In some embodiments, the bisulfite reaction is carried out in the presence of scavengers such as but not limited to chromane derivatives, e.g., 6-hydroxy-2,5,7,8,-tetramethylchromane 2-carboxylic acid or trihydroxybenzone acid and derivates thereof, e.g., Gallic acid (see: PCT/EP2004/011715, which is incorporated by reference in its entirety). In certain preferred embodiments, the bisulfite reaction comprises treatment with ammonium hydrogen sulfite, e.g., as described in WO 2013/116375.


In some embodiments, fragments of the treated DNA are amplified using sets of primer oligonucleotides according to the present invention (e.g., see Tables 3, 6, 7, 15 and 16) and an amplification enzyme. The amplification of several DNA segments can be carried out simultaneously in one and the same reaction vessel. Typically, the amplification is carried out using a polymerase chain reaction (PCR). Amplicons are typically 100 to 2000 base pairs in length.


In another embodiment of the method, the methylation status of CpG positions within or near a marker comprising a DMR (e.g., DMR 1-375, Tables 2 and 5) may be detected by use of methylation-specific primer oligonucleotides. This technique (MSP) has been described in U.S. Pat. No. 6,265,171 to Herman. The use of methylation status specific primers for the amplification of bisulfite treated DNA allows the differentiation between methylated and unmethylated nucleic acids. MSP primer pairs contain at least one primer that hybridizes to a bisulfite treated CpG dinucleotide. Therefore, the sequence of said primers comprises at least one CpG dinucleotide. MSP primers specific for non-methylated DNA contain a “T” at the position of the C position in the CpG.


The fragments obtained by means of the amplification can carry a directly or indirectly detectable label. In some embodiments, the labels are fluorescent labels, radionuclides, or detachable molecule fragments having a typical mass that can be detected in a mass spectrometer. Where said labels are mass labels, some embodiments provide that the labeled amplicons have a single positive or negative net charge, allowing for better delectability in the mass spectrometer. The detection may be carried out and visualized by means of, e.g., matrix assisted laser desorption/ionization mass spectrometry (MALDI) or using electron spray mass spectrometry (ESI).


Methods for isolating DNA suitable for these assay technologies are known in the art. In particular, some embodiments comprise isolation of nucleic acids as described in U.S. patent application Ser. No. 13/470,251 (“Isolation of Nucleic Acids”), incorporated herein by reference in its entirety.


In some embodiments, the markers described herein find use in QUARTS assays performed on stool samples. In some embodiments, methods for producing DNA samples and, in particular, to methods for producing DNA samples that comprise highly purified, low-abundance nucleic acids in a small volume (e.g., less than 100, less than 60 microliters) and that are substantially and/or effectively free of substances that inhibit assays used to test the DNA samples (e.g., PCR, INVADER, QuARTS assays, etc.) are provided. Such DNA samples find use in diagnostic assays that qualitatively detect the presence of, or quantitatively measure the activity, expression, or amount of, a gene, a gene variant (e.g., an allele), or a gene modification (e.g., methylation) present in a sample taken from a patient. For example, some cancers are correlated with the presence of particular mutant alleles or particular methylation states, and thus detecting and/or quantifying such mutant alleles or methylation states has predictive value in the diagnosis and treatment of cancer.


Many valuable genetic markers are present in extremely low amounts in samples and many of the events that produce such markers are rare. Consequently, even sensitive detection methods such as PCR require a large amount of DNA to provide enough of a low-abundance target to meet or supersede the detection threshold of the assay. Moreover, the presence of even low amounts of inhibitory substances compromise the accuracy and precision of these assays directed to detecting such low amounts of a target. Accordingly, provided herein are methods providing the requisite management of volume and concentration to produce such DNA samples.


In some embodiments, the sample comprises blood, serum, plasma, or saliva. In some embodiments, the subject is human. Such samples can be obtained by any number of means known in the art, such as will be apparent to the skilled person. Cell free or substantially cell free samples can be obtained by subjecting the sample to various techniques known to those of skill in the art which include, but are not limited to, centrifugation and filtration. Although it is generally preferred that no invasive techniques are used to obtain the sample, it still may be preferable to obtain samples such as tissue homogenates, tissue sections, and biopsy specimens. The technology is not limited in the methods used to prepare the samples and provide a nucleic acid for testing. For example, in some embodiments, a DNA is isolated from a stool sample or from blood or from a plasma sample using direct gene capture, e.g., as detailed in U.S. Pat. Nos. 8,808,990 and 9,169,511, and in WO 2012/155072, or by a related method.


The analysis of markers can be carried out separately or simultaneously with additional markers within one test sample. For example, several markers can be combined into one test for efficient processing of multiple samples and for potentially providing greater diagnostic and/or prognostic accuracy. In addition, one skilled in the art would recognize the value of testing multiple samples (for example, at successive time points) from the same subject. Such testing of serial samples can allow the identification of changes in marker methylation states over time. Changes in methylation state, as well as the absence of change in methylation state, can provide useful information about the disease status that includes, but is not limited to, identifying the approximate time from onset of the event, the presence and amount of salvageable tissue, the appropriateness of drug therapies, the effectiveness of various therapies, and identification of the subject's outcome, including risk of future events. The analysis of biomarkers can be carried out in a variety of physical formats. For example, the use of microtiter plates or automation can be used to facilitate the processing of large numbers of test samples. Alternatively, single sample formats could be developed to facilitate immediate treatment and diagnosis in a timely fashion, for example, in ambulatory transport or emergency room settings.


It is contemplated that embodiments of the technology are provided in the form of a kit. The kits comprise embodiments of the compositions, devices, apparatuses, etc. described herein, and instructions for use of the kit. Such instructions describe appropriate methods for preparing an analyte from a sample, e.g., for collecting a sample and preparing a nucleic acid from the sample. Individual components of the kit are packaged in appropriate containers and packaging (e.g., vials, boxes, blister packs, ampules, jars, bottles, tubes, and the like) and the components are packaged together in an appropriate container (e.g., a box or boxes) for convenient storage, shipping, and/or use by the user of the kit. It is understood that liquid components (e.g., a buffer) may be provided in a lyophilized form to be reconstituted by the user. Kits may include a control or reference for assessing, validating, and/or assuring the performance of the kit. For example, a kit for assaying the amount of a nucleic acid present in a sample may include a control comprising a known concentration of the same or another nucleic acid for comparison and, in some embodiments, a detection reagent (e.g., a primer) specific for the control nucleic acid. The kits are appropriate for use in a clinical setting and, in some embodiments, for use in a user's home. The components of a kit, in some embodiments, provide the functionalities of a system for preparing a nucleic acid solution from a sample. In some embodiments, certain components of the system are provided by the user.


Methods

In some embodiments of the technology, methods are provided that comprise the following steps:

    • 1) contacting a nucleic acid (e.g., genomic DNA, e.g., isolated from body fluids such as blood or plasma or breast tissue) obtained from the subject with at least one reagent or series of reagents that distinguishes between methylated and non-methylated CpG dinucleotides within at least one marker comprising a DMR (e.g., DMR 1-375 e.g., as provided in Tables 2 and 5) and
    • 2) detecting breast cancer (e.g., afforded with a sensitivity of greater than or equal to 80% and a specificity of greater than or equal to 80%).


In some embodiments of the technology, methods are provided that comprise the following steps:

    • 1) contacting a nucleic acid (e.g., genomic DNA, e.g., isolated from body fluids such as blood or plasma or breast tissue) obtained from the subject with at least one reagent or series of reagents that distinguishes between methylated and non-methylated CpG dinucleotides within at least one marker selected from a chromosomal region having an annotation selected from the group consisting of ATP6V1B1, LMX1B_A, BANK1, OTX1, MAX.chr11.14926602-14927148, UBTF, PRKCB, TRH_A, MPZ, DNM3_A, TRIM67, MAX.chr12.4273906-4274012, CALN1_A, ITPRIPL1, MAX.chr12.4273906-4274012, GYPC_B, MAX.chr5.42994866-42994936, OSR2_A, SCRT2_B, MAX.chr5.145725410-145725459, MAX.chr11.68622869-68622968, MAX.chr8.124173030-124173395, MAX.chr20.1784209-1784461, LOC100132891, BHLHE23_D, MAX.chr19.46379903-46380197, CHST2_B, MAX.chr5.77268672-77268725, C17orf64, EMX1_A, DSCR6, ITPRIPL1, IGF2BP3_B, DLX4, and ABLIM1, and
    • 2) detecting breast cancer (e.g., afforded with a sensitivity of greater than or equal to 80% and a specificity of greater than or equal to 80%).


In some embodiments of the technology, methods are provided that comprise the following steps:

    • 1) contacting a nucleic acid (e.g., genomic DNA, e.g., isolated from body fluids such as blood or plasma or breast tissue) obtained from the subject with at least one reagent or series of reagents that distinguishes between methylated and non-methylated CpG dinucleotides within at least one marker selected from a chromosomal region having an annotation selected from the group consisting of ABLIM1_B, AJAP1_C, ALOX5_B, ASCL2_B, BANK1_B, BHLHE23_E, C10orf125_B, C17orf64_B, CALN1_1520, CALN1_B, CD1D_1058, CDH4_7890, CHST2_8128, CHST2_8384, CHST2_9316, CHST2_9470, CLIC6_B, CXCL12_B, DLX4_B, DNM3_D, EMX1_A, ESPN_B, FAM59B_7764, FOXP4_B, GP5, HOXA1_C, IGF2BP3_C, IPTRIPL1_1138, IPTRIPL1_1200, KCNK9_B, KCNK17_C, KLHDC7B_B, LAYN_B, LIME1_B, LMX1B_D, LOC100132891_B, MAST1_B, MAX.chr12.427.br, MAX.chr17.73073682-73073814, MAX.chr20.4422, MPZ_5742, MPZ_5554, MSX2P1_B, ODC1_B, OSR2_A, OTX1_B, PLXNC1_B, PRKCB_7570, SCRT2_C, SLC30A10, SPHK2_B, ST8SIA4_B, STX16_C, TBX1_B, TRH_A, and TRIM67_B, and
    • 2) detecting breast cancer (e.g., afforded with a sensitivity of greater than or equal to 80% and a specificity of greater than or equal to 80%).


In some embodiments of the technology, methods are provided that comprise the following steps:

    • 1) contacting a nucleic acid (e.g., genomic DNA, e.g., isolated from body fluids such as blood or plasma or breast tissue) obtained from the subject with at least one reagent or series of reagents that distinguishes between methylated and non-methylated CpG dinucleotides within at least one marker selected from a chromosomal region having an annotation selected from the group consisting of CD1D, ITPRIPL1, FAM59B, C10orf125, TRIM67, SPHK2, CALN1_B, CHST2_B, MPZ, CXCL12_B, ODC1_B, OSR2_A, TRH_A, and C17orf64_B, and
    • 2) detecting breast cancer (e.g., afforded with a sensitivity of greater than or equal to 80% and a specificity of greater than or equal to 80%).


In some embodiments of the technology, methods are provided that comprise the following steps:

    • 1) measuring a methylation level for one or more genes in a biological sample of a human individual through treating genomic DNA in the biological sample with a reagent that modifies DNA in a methylation-specific manner (e.g., wherein the reagent is a bisulfate reagent, a methylation-sensitive restriction enzyme, or a methylation-dependent restriction enzyme), wherein the one or more genes is selected from one of the following groups:
      • (i) ATP6V1B1, LMX1B_A, BANK1, OTX1, MAX.chr11.14926602-14927148, UBTF, PRKCB, TRH_A, MPZ, DNM3_A, TRIM67, MAX.chr12.4273906-4274012, CALN1_A, ITPRIPL1, MAX.chr12.4273906-4274012, GYPC_B, MAX.chr5.42994866-42994936, OSR2_A, SCRT2_B, MAX.chr5.145725410-145725459, MAX.chr11.68622869-68622968, MAX.chr8.124173030-124173395, MAX.chr20.1784209-1784461, LOC100132891, BHLHE23_D, MAX.chr19.46379903-46380197, CHST2_B, MAX.chr5.77268672-77268725, C17orf64, EMX1_A, DSCR6, ITPRIPL1, IGF2BP3_B, DLX4, and ABLIM1;
      • (ii) ABLIM1_B, AJAP1_C, ALOX5_B, ASCL2_B, BANK1_B, BHLHE23_E, C10orf125_B, C17orf64_B, CALN1_1520, CALN1_B, CD1D_1058, CDH4_7890, CHST2_8128, CHST2_8384, CHST2_9316, CHST2_9470, CLIC6_B, CXCL12_B, DLX4_B, DNM3_D, EMX1_A, ESPN_B, FAM59B_7764, FOXP4_B, GP5, HOXA1_C, IGF2BP3_C, IPTRIPL1_1138, IPTRIPL1_1200, KCNK9_B, KCNK17_C, LAYN_B, LIME1_B, LMX1B_D, LOC100132891_B, MAST1_B, MAX.chr12.427.br, MAX.chr20.4422, MPZ_5742, MPZ_5554, MSX2P1_B, ODC1_B, OSR2_A, OTX1_B, PLXNC1_B, PRKCB_7570, SCRT2_C, SLC30A10, SPHK2_B, ST8SIA4_B, STX16_C, TRH_A, and TRIM67_B; and
      • (iii) CD1D, ITPRIPL1, FAM59B, C10orf125, TRIM67, SPHK2, CALN1_B, CHST2_B, MPZ, CXCL12_B, ODC1_B, OSR2_A, TRH_A, and C17orf64_B;
    • 2) amplifying the treated genomic DNA using a set of primers for the selected one or more genes; and
    • 3) determining the methylation level of the one or more genes by polymerase chain reaction, nucleic acid sequencing, mass spectrometry, methylation-specific nuclease, mass-based separation, and target capture.


In some embodiments of the technology, methods are provided that comprise the following steps:

    • 1) measuring an amount of at least one methylated marker gene in DNA from the sample, wherein the one or more genes is selected from one of the following groups:
      • (i) ATP6V1B1, LMX1B_A, BANK1, OTX1, MAX.chr11.14926602-14927148, UBTF, PRKCB, TRH_A, MPZ, DNM3_A, TRIM67, MAX.chr12.4273906-4274012, CALN1_A, ITPRIPL1, MAX.chr12.4273906-4274012, GYPC_B, MAX.chr5.42994866-42994936, OSR2_A, SCRT2_B, MAX.chr5.145725410-145725459, MAX.chr11.68622869-68622968, MAX.chr8.124173030-124173395, MAX.chr20.1784209-1784461, LOC100132891, BHLHE23_D, MAX.chr19.46379903-46380197, CHST2_B, MAX.chr5.77268672-77268725, C17orf64, EMX1_A, DSCR6, ITPRIPL1, IGF2BP3_B, DLX4, and ABLIM1;
      • (ii) ABLIM1_B, AJAP1_C, ALOX5_B, ASCL2_B, BANK1_B, BHLHE23_E, C10orf125_B, C17orf64_B, CALN1_1520, CALN1_B, CD1D_1058, CDH4_7890, CHST2_8128, CHST2_8384, CHST2_9316, CHST2_9470, CLIC6_B, CXCL12_B, DLX4_B, DNM3_D, EMX1_A, ESPN_B, FAM59B_7764, FOXP4_B, GP5, HOXA1_C, IGF2BP3_C, IPTRIPL1_1138, IPTRIPL1_1200, KCNK9_B, KCNK17_C, LAYN_B, LIME1_B, LMX1B_D, LOC100132891_B, MAST1_B, MAX.chr12.427.br, MAX.chr20.4422, MPZ_5742, MPZ_5554, MSX2P1_B, ODC1_B, OSR2_A, OTX1_B, PLXNC1_B, PRKCB_7570, SCRT2_C, SLC30A10, SPHK2_B, ST8SIA4_B, STX16_C, TRH_A, and TRIM67_B; and
      • (iii) CD1D, ITPRIPL1, FAM59B, C10orf125, TRIM67, SPHK2, CALN1_B, CHST2_B, MPZ, CXCL12_B, ODC1_B, OSR2_A, TRH_A, and C17orf64_B;
    • 2) measuring the amount of at least one reference marker in the DNA; and
    • 3) calculating a value for the amount of the at least one methylated marker gene measured in the DNA as a percentage of the amount of the reference marker gene measured in the DNA, wherein the value indicates the amount of the at least one methylated marker DNA measured in the sample.


In some embodiments of the technology, methods are provided that comprise the following steps:

    • 1) measuring a methylation level of a CpG site for one or more genes in a biological sample of a human individual through treating genomic DNA in the biological sample with bisulfite a reagent capable of modifying DNA in a methylation-specific manner (e.g., a methylation-sensitive restriction enzyme, a methylation-dependent restriction enzyme, and a bisulfite reagent);
    • 2) amplifying the modified genomic DNA using a set of primers for the selected one or more genes; and
    • 3) determining the methylation level of the CpG site by methylation-specific PCR, quantitative methylation-specific PCR, methylation-sensitive DNA restriction enzyme analysis, quantitative bisulfite pyrosequencing, or bisulfite genomic sequencing PCR;
      • wherein the one or more genes is selected from one of the following groups:
        • (i) ATP6V1B1, LMX1B_A, BANK1, OTX1, MAX.chr11.14926602-14927148, UBTF, PRKCB, TRH_A, MPZ, DNM3_A, TRIM67, MAX.chr12.4273906-4274012, CALN1_A, ITPRIPL1, MAX.chr12.4273906-4274012, GYPC_B, MAX.chr5.42994866-42994936, OSR2_A, SCRT2_B, MAX.chr5.145725410-145725459, MAX.chr11.68622869-68622968, MAX.chr8.124173030-124173395, MAX.chr20.1784209-1784461, LOC100132891, BHLHE23_D, MAX.chr19.46379903-46380197, CHST2_B, MAX.chr5.77268672-77268725, C17orf64, EMX1_A, DSCR6, ITPRIPL1, IGF2BP3_B, DLX4, and ABLIM1;
        • (ii) ABLIM1_B, AJAP1_C, ALOX5_B, ASCL2_B, BANK1_B, BHLHE23_E, C10orf125_B, C17orf64_B, CALN1_1520, CALN1_B, CD1D_1058, CDH4_7890, CHST2_8128, CHST2_8384, CHST2_9316, CHST2_9470, CLIC6_B, CXCL12_B, DLX4_B, DNM3_D, EMX1_A, ESPN_B, FAM59B_7764, FOXP4_B, GP5, HOXA1_C, IGF2BP3_C, IPTRIPL1_1138, IPTRIPL1_1200, KCNK9_B, KCNK17_C, LAYN_B, LIME1_B, LMX1B_D, LOC100132891_B, MAST1_B, MAX.chr12.427.br, MAX.chr20.4422, MPZ_5742, MPZ_5554, MSX2P1_B, ODC1_B, OSR2_A, OTX1_B, PLXNC1_B, PRKCB_7570, SCRT2_C, SLC30A10, SPHK2_B, ST8SIA4_B, STX16_C, TRH_A, and TRIM67_B; and
        • (iii) CD1D, ITPRIPL1, FAM59B, C10orf125, TRIM67, SPHK2, CALN1_B, CHST2_B, MPZ, CXCL12_B, ODC1_B, OSR2_A, TRH_A, and C17orf64_B.


Preferably, the sensitivity for such methods is from about 70% to about 100%, or from about 80% to about 90%, or from about 80% to about 85%. Preferably, the specificity is from about 70% to about 100%, or from about 80% to about 90%, or from about 80% to about 85%.


Genomic DNA may be isolated by any means, including the use of commercially available kits. Briefly, wherein the DNA of interest is encapsulated in by a cellular membrane the biological sample must be disrupted and lysed by enzymatic, chemical or mechanical means. The DNA solution may then be cleared of proteins and other contaminants, e.g., by digestion with proteinase K. The genomic DNA is then recovered from the solution. This may be carried out by means of a variety of methods including salting out, organic extraction, or binding of the DNA to a solid phase support. The choice of method will be affected by several factors including time, expense, and required quantity of DNA. All clinical sample types comprising neoplastic matter or pre-neoplastic matter are suitable for use in the present method, e.g., cell lines, histological slides, biopsies, paraffin-embedded tissue, body fluids, stool, breast tissue, colonic effluent, urine, blood plasma, blood serum, whole blood, isolated blood cells, cells isolated from the blood, and combinations thereof.


The technology is not limited in the methods used to prepare the samples and provide a nucleic acid for testing. For example, in some embodiments, a DNA is isolated from a stool sample or from blood or from a plasma sample using direct gene capture, e.g., as detailed in U.S. Pat. Appl. Ser. No. 61/485,386 or by a related method.


The genomic DNA sample is then treated with at least one reagent, or series of reagents, that distinguishes between methylated and non-methylated CpG dinucleotides within at least one marker comprising a DMR (e.g., DMR 1-375, e.g., as provided by Tables 2 and 5).


In some embodiments, the reagent converts cytosine bases which are unmethylated at the 5′-position to uracil, thymine, or another base which is dissimilar to cytosine in terms of hybridization behavior. However in some embodiments, the reagent may be a methylation sensitive restriction enzyme.


In some embodiments, the genomic DNA sample is treated in such a manner that cytosine bases that are unmethylated at the 5′ position are converted to uracil, thymine, or another base that is dissimilar to cytosine in terms of hybridization behavior. In some embodiments, this treatment is carried out with bisulfite (hydrogen sulfite, disulfite) followed by alkaline hydrolysis.


The treated nucleic acid is then analyzed to determine the methylation state of the target gene sequences (at least one gene, genomic sequence, or nucleotide from a marker comprising a DMR, e.g., at least one DMR chosen from DMR 1-375, e.g., as provided in Tables 2 and 5). The method of analysis may be selected from those known in the art, including those listed herein, e.g., QuARTS and MSP as described herein.


Aberrant methylation, more specifically hypermethylation of a marker comprising a DMR (e.g., DMR 1-375, e.g., as provided by Tables 2 and 5) is associated with a breast cancer.


The technology relates to the analysis of any sample associated with a breast cancer. For example, in some embodiments the sample comprises a tissue and/or biological fluid obtained from a patient. In some embodiments, the sample comprises a secretion. In some embodiments, the sample comprises blood, serum, plasma, gastric secretions, pancreatic juice, a gastrointestinal biopsy sample, microdissected cells from a breast biopsy, and/or cells recovered from stool. In some embodiments, the sample comprises breast tissue. In some embodiments, the subject is human. The sample may include cells, secretions, or tissues from the breast, liver, bile ducts, pancreas, stomach, colon, rectum, esophagus, small intestine, appendix, duodenum, polyps, gall bladder, anus, and/or peritoneum. In some embodiments, the sample comprises cellular fluid, ascites, urine, feces, pancreatic fluid, fluid obtained during endoscopy, blood, mucus, or saliva. In some embodiments, the sample is a stool sample. In some embodiments, the sample is a breast tissue sample.


Such samples can be obtained by any number of means known in the art, such as will be apparent to the skilled person. For instance, urine and fecal samples are easily attainable, while blood, ascites, serum, or pancreatic fluid samples can be obtained parenterally by using a needle and syringe, for instance. Cell free or substantially cell free samples can be obtained by subjecting the sample to various techniques known to those of skill in the art which include, but are not limited to, centrifugation and filtration. Although it is generally preferred that no invasive techniques are used to obtain the sample, it still may be preferable to obtain samples such as tissue homogenates, tissue sections, and biopsy specimens


In some embodiments, the technology relates to a method for treating a patient (e.g., a patient with breast cancer, with early stage breast cancer, or who may develop breast cancer), the method comprising determining the methylation state of one or more DMR as provided herein and administering a treatment to the patient based on the results of determining the methylation state. The treatment may be administration of a pharmaceutical compound, a vaccine, performing a surgery, imaging the patient, performing another test. Preferably, said use is in a method of clinical screening, a method of prognosis assessment, a method of monitoring the results of therapy, a method to identify patients most likely to respond to a particular therapeutic treatment, a method of imaging a patient or subject, and a method for drug screening and development.


In some embodiments of the technology, a method for diagnosing a breast cancer in a subject is provided. The terms “diagnosing” and “diagnosis” as used herein refer to methods by which the skilled artisan can estimate and even determine whether or not a subject is suffering from a given disease or condition or may develop a given disease or condition in the future. The skilled artisan often makes a diagnosis on the basis of one or more diagnostic indicators, such as for example a biomarker (e.g., a DMR as disclosed herein), the methylation state of which is indicative of the presence, severity, or absence of the condition.


Along with diagnosis, clinical cancer prognosis relates to determining the aggressiveness of the cancer and the likelihood of tumor recurrence to plan the most effective therapy. If a more accurate prognosis can be made or even a potential risk for developing the cancer can be assessed, appropriate therapy, and in some instances less severe therapy for the patient can be chosen. Assessment (e.g., determining methylation state) of cancer biomarkers is useful to separate subjects with good prognosis and/or low risk of developing cancer who will need no therapy or limited therapy from those more likely to develop cancer or suffer a recurrence of cancer who might benefit from more intensive treatments.


As such, “making a diagnosis” or “diagnosing”, as used herein, is further inclusive of determining a risk of developing cancer or determining a prognosis, which can provide for predicting a clinical outcome (with or without medical treatment), selecting an appropriate treatment (or whether treatment would be effective), or monitoring a current treatment and potentially changing the treatment, based on the measure of the diagnostic biomarkers (e.g., DMR) disclosed herein. Further, in some embodiments of the presently disclosed subject matter, multiple determination of the biomarkers over time can be made to facilitate diagnosis and/or prognosis. A temporal change in the biomarker can be used to predict a clinical outcome, monitor the progression of breast cancer, and/or monitor the efficacy of appropriate therapies directed against the cancer. In such an embodiment for example, one might expect to see a change in the methylation state of one or more biomarkers (e.g., DMR) disclosed herein (and potentially one or more additional biomarker(s), if monitored) in a biological sample over time during the course of an effective therapy.


The presently disclosed subject matter further provides in some embodiments a method for determining whether to initiate or continue prophylaxis or treatment of a cancer in a subject. In some embodiments, the method comprises providing a series of biological samples over a time period from the subject; analyzing the series of biological samples to determine a methylation state of at least one biomarker disclosed herein in each of the biological samples; and comparing any measurable change in the methylation states of one or more of the biomarkers in each of the biological samples. Any changes in the methylation states of biomarkers over the time period can be used to predict risk of developing cancer, predict clinical outcome, determine whether to initiate or continue the prophylaxis or therapy of the cancer, and whether a current therapy is effectively treating the cancer. For example, a first time point can be selected prior to initiation of a treatment and a second time point can be selected at some time after initiation of the treatment. Methylation states can be measured in each of the samples taken from different time points and qualitative and/or quantitative differences noted. A change in the methylation states of the biomarker levels from the different samples can be correlated with breast cancer risk, prognosis, determining treatment efficacy, and/or progression of the cancer in the subject.


In preferred embodiments, the methods and compositions of the invention are for treatment or diagnosis of disease at an early stage, for example, before symptoms of the disease appear. In some embodiments, the methods and compositions of the invention are for treatment or diagnosis of disease at a clinical stage.


As noted, in some embodiments, multiple determinations of one or more diagnostic or prognostic biomarkers can be made, and a temporal change in the marker can be used to determine a diagnosis or prognosis. For example, a diagnostic marker can be determined at an initial time, and again at a second time. In such embodiments, an increase in the marker from the initial time to the second time can be diagnostic of a particular type or severity of cancer, or a given prognosis. Likewise, a decrease in the marker from the initial time to the second time can be indicative of a particular type or severity of cancer, or a given prognosis. Furthermore, the degree of change of one or more markers can be related to the severity of the cancer and future adverse events. The skilled artisan will understand that, while in certain embodiments comparative measurements can be made of the same biomarker at multiple time points, one can also measure a given biomarker at one time point, and a second biomarker at a second time point, and a comparison of these markers can provide diagnostic information.


As used herein, the phrase “determining the prognosis” refers to methods by which the skilled artisan can predict the course or outcome of a condition in a subject. The term “prognosis” does not refer to the ability to predict the course or outcome of a condition with 100% accuracy, or even that a given course or outcome is predictably more or less likely to occur based on the methylation state of a biomarker (e.g., a DMR). Instead, the skilled artisan will understand that the term “prognosis” refers to an increased probability that a certain course or outcome will occur; that is, that a course or outcome is more likely to occur in a subject exhibiting a given condition, when compared to those individuals not exhibiting the condition. For example, in individuals not exhibiting the condition (e.g., having a normal methylation state of one or more DMR), the chance of a given outcome (e.g., suffering from a breast cancer) may be very low.


In some embodiments, a statistical analysis associates a prognostic indicator with a predisposition to an adverse outcome. For example, in some embodiments, a methylation state different from that in a normal control sample obtained from a patient who does not have a cancer can signal that a subject is more likely to suffer from a cancer than subjects with a level that is more similar to the methylation state in the control sample, as determined by a level of statistical significance. Additionally, a change in methylation state from a baseline (e.g., “normal”) level can be reflective of subject prognosis, and the degree of change in methylation state can be related to the severity of adverse events. Statistical significance is often determined by comparing two or more populations and determining a confidence interval and/or a p value. See, e.g., Dowdy and Wearden, Statistics for Research, John Wiley & Sons, New York, 1983, incorporated herein by reference in its entirety. Exemplary confidence intervals of the present subject matter are 90%, 95%, 97.5%, 98%, 99%, 99.5%, 99.9% and 99.99%, while exemplary p values are 0.1, 0.05, 0.025, 0.02, 0.01, 0.005, 0.001, and 0.0001.


In other embodiments, a threshold degree of change in the methylation state of a prognostic or diagnostic biomarker disclosed herein (e.g., a DMR) can be established, and the degree of change in the methylation state of the biamarker in a biological sample is simply compared to the threshold degree of change in the methylation state. A preferred threshold change in the methylation state for biomarkers provided herein is about 5%, about 10%, about 15%, about 20%, about 25%, about 30%, about 50%, about 75%, about 100%, and about 150%. In yet other embodiments, a “nomogram” can be established, by which a methylation state of a prognostic or diagnostic indicator (biomarker or combination of biomarkers) is directly related to an associated disposition towards a given outcome. The skilled artisan is acquainted with the use of such nomograms to relate two numeric values with the understanding that the uncertainty in this measurement is the same as the uncertainty in the marker concentration because individual sample measurements are referenced, not population averages.


In some embodiments, a control sample is analyzed concurrently with the biological sample, such that the results obtained from the biological sample can be compared to the results obtained from the control sample. Additionally, it is contemplated that standard curves can be provided, with which assay results for the biological sample may be compared. Such standard curves present methylation states of a biomarker as a function of assay units, e.g., fluorescent signal intensity, if a fluorescent label is used. Using samples taken from multiple donors, standard curves can be provided for control methylation states of the one or more biomarkers in normal tissue, as well as for “at-risk” levels of the one or more biomarkers in tissue taken from donors with metaplasia or from donors with a breast cancer. In certain embodiments of the method, a subject is identified as having metaplasia upon identifying an aberrant methylation state of one or more DMR provided herein in a biological sample obtained from the subject. In other embodiments of the method, the detection of an aberrant methylation state of one or more of such biomarkers in a biological sample obtained from the subject results in the subject being identified as having cancer.


The analysis of markers can be carried out separately or simultaneously with additional markers within one test sample. For example, several markers can be combined into one test for efficient processing of a multiple of samples and for potentially providing greater diagnostic and/or prognostic accuracy. In addition, one skilled in the art would recognize the value of testing multiple samples (for example, at successive time points) from the same subject. Such testing of serial samples can allow the identification of changes in marker methylation states over time. Changes in methylation state, as well as the absence of change in methylation state, can provide useful information about the disease status that includes, but is not limited to, identifying the approximate time from onset of the event, the presence and amount of salvageable tissue, the appropriateness of drug therapies, the effectiveness of various therapies, and identification of the subject's outcome, including risk of future events.


The analysis of biomarkers can be carried out in a variety of physical formats. For example, the use of microtiter plates or automation can be used to facilitate the processing of large numbers of test samples. Alternatively, single sample formats could be developed to facilitate immediate treatment and diagnosis in a timely fashion, for example, in ambulatory transport or emergency room settings.


In some embodiments, the subject is diagnosed as having a breast cancer if, when compared to a control methylation state, there is a measurable difference in the methylation state of at least one biomarker in the sample. Conversely, when no change in methylation state is identified in the biological sample, the subject can be identified as not having breast cancer, not being at risk for the cancer, or as having a low risk of the cancer. In this regard, subjects having the cancer or risk thereof can be differentiated from subjects having low to substantially no cancer or risk thereof. Those subjects having a risk of developing a breast cancer can be placed on a more intensive and/or regular screening schedule, including endoscopic surveillance. On the other hand, those subjects having low to substantially no risk may avoid being subjected to additional testing for breast cancer (e.g., invasive procedure), until such time as a future screening, for example, a screening conducted in accordance with the present technology, indicates that a risk of breast cancer has appeared in those subjects.


As mentioned above, depending on the embodiment of the method of the present technology, detecting a change in methylation state of the one or more biomarkers can be a qualitative determination or it can be a quantitative determination. As such, the step of diagnosing a subject as having, or at risk of developing, a breast cancer indicates that certain threshold measurements are made, e.g., the methylation state of the one or more biomarkers in the biological sample varies from a predetermined control methylation state. In some embodiments of the method, the control methylation state is any detectable methylation state of the biomarker. In other embodiments of the method where a control sample is tested concurrently with the biological sample, the predetermined methylation state is the methylation state in the control sample. In other embodiments of the method, the predetermined methylation state is based upon and/or identified by a standard curve. In other embodiments of the method, the predetermined methylation state is a specifically state or range of state. As such, the predetermined methylation state can be chosen, within acceptable limits that will be apparent to those skilled in the art, based in part on the embodiment of the method being practiced and the desired specificity, etc.


Further with respect to diagnostic methods, a preferred subject is a vertebrate subject. A preferred vertebrate is warm-blooded; a preferred warm-blooded vertebrate is a mammal. A preferred mammal is most preferably a human. As used herein, the term “subject’ includes both human and animal subjects. Thus, veterinary therapeutic uses are provided herein. As such, the present technology provides for the diagnosis of mammals such as humans, as well as those mammals of importance due to being endangered, such as Siberian tigers; of economic importance, such as animals raised on farms for consumption by humans; and/or animals of social importance to humans, such as animals kept as pets or in zoos. Examples of such animals include but are not limited to: carnivores such as cats and dogs; swine, including pigs, hogs, and wild boars; ruminants and/or ungulates such as cattle, oxen, sheep, giraffes, deer, goats, bison, and camels; and horses. Thus, also provided is the diagnosis and treatment of livestock, including, but not limited to, domesticated swine, ruminants, ungulates, horses (including race horses), and the like.


The presently-disclosed subject matter further includes a system for diagnosing a breast cancer in a subject. The system can be provided, for example, as a commercial kit that can be used to screen for a risk of breast cancer or diagnose a breast cancer in a subject from whom a biological sample has been collected. An exemplary system provided in accordance with the present technology includes assessing the methylation state of a DMR as provided in Tables 2 and 5.


EXAMPLES
Example I

This example describes the discovery and tissue validation of breast-cancer specific markers.


Table 1 shows the number of tissue samples for each subtype of breast cancer used in the discovery of breast cancer specific markers.













TABLE 1








Number of




Breast Cancer Subtype
Subjects
Total




















Basal-like/Triple Negative
18
18



HER2+
18
18



Luminal A
18
18



Luminal B
18
18



BRCA 1
6
15



BRCA 2
9



Normal Breast
18
45



Normal Breast + BRCA
9



Normal Buffy Coat
18










For discovery of methylation markers by RRBS, frozen tissue samples were obtained from 72 invasive breast cancer cases (18 luminal A, 18 luminal B, 18 basal-like/triple negative, and 18 HER2+), 15 invasive breast cancer from BRCA germline mutation patients (6 BRCA1, 9 BRCA2), and 45 controls (18 normal breast (reduction mammoplasty or prophylactic mastectomy, 9 histologically normal breast in germline BRCA carriers (prophylactic mastectomy), and 18 normal buffy coat)). Tumor and breast tissue sections were reviewed by an expert GI pathologist to confirm diagnosis and estimate abnormal cellularity. Sections were then macro-dissected. Genomic DNA was purified using the QiaAmp Mini kit (Qiagen, Valencia Calif.). DNA (300 ng) was fragmented by digestion with 10 Units of Mspl. Digested fragments were end-repaired and A-tailed with 5 Units of Klenow fragment (3′-5′ exo-), and ligated overnight to methylated TruSeq adapters (Illumina, San Diego Calif.) containing barcode sequences (to link each fragment to its sample ID.) Reactions were purified using AMPure XP SPRI beads/buffer (Beckman Coulter, Brea Calif.).


Tissue samples then underwent bisulfite conversion (twice) using a modified EpiTect protocol (Qiagen). qPCR (LightCycler 480—Roche, Mannheim Germany) was used to determine the optimal enrichment Ct. The following conditions were used for final enrichment PCR: Each 50 uL reaction contained 5 uL of 10× buffer, 1.25 uL of 10 mM each deoxyribonucleotide triphosphate (dNTP), 5 uL primer cocktail (˜5 uM), 15 uL template (sample), 1 uL PfuTurbo Cx hotstart (Agilent, Santa Clara Calif.) and 22.75 water; temperatures and times were 95 C-5 min; 98 C-30 sec; 16 cycles of 98 C-10 sec, 65 C-30 sec, 72 C-30 sec, 72 C-5 min and 4 C hold, respectively. Samples were SPRI bead purified and then tested on the Bioanalyzer 2100 (Agilent) to assess the DNA size distribution of the enrichment. Size selection of 160-520 bp fragments (40-400 bp inserts) was performed using AMPure XP SPRI beads/buffer (Beckman Coulter, Brea Calif.). Buffer cutoffs were 0.7×-1.1× sample volumes. Samples were combined (equimolar) into 4-plex libraries based on the randomization scheme and tested with the bioanalyzer for final size and concentration verification, and with qPCR (KAPA Library Quantification Kit—KAPA Biosystems, Cape Town South Africa).


Tissue samples were loaded onto single read flow cells according to a randomized lane assignment and sequencing was performed by the Next Generation Sequencing Core at the Mayo Clinic Medical Genome Facility on the Illumina HiSeq 2000 platform. Reads were unidirectional for 101 cycles. The standard Illumina pipeline was run for the primary analysis. SAAP-RRBS (streamlined analysis and annotation pipeline for reduced representation bisulfate sequencing) was used for quality scoring, sequence alignment, annotation, and methylation extraction.


Breast cancer tissue yielded large numbers of discriminate DMRs, many of which had not been identified before. Comparing the methylation of breast cancer tissue samples to normal breast tissue, 327 methylated regions were identified (see, Table 2) that distinguished breast cancer tissue from normal breast tissue (the genomic coordinates for the regions shown in Table 2 are based on the Human Feb. 2009 (GRCh37/hg19) Assembly).









TABLE 2







Identified methylated regions distinguishing breast


cancer tissue from normal breast tissue.










Gene
Region on Chromosome


DMR No.
Annotation
(starting base-ending base)












1
ZSCAN23
chr6: 28411152-28411272


2
AADAT.R
chr4: 171010951-171010991


3
ABLIM1
chr10: 116391588-116391793


4
ACCN1
chr17: 31620207-31620314


5
AFAP1L1
chr5: 148651161-148651242


6
AJAP1_A
chr1: 4715535-4715646


7
AJAP1_B
chr1: 4715931-4716021


8
AKR1B1
chr7: 134143171-134143684


9
ALOX5
chr10: 45914840-45914949


10
AMN
chr14: 103394920-103395019


11
ANPEP
chr15: 90358420-90358514


12
ANTXR2
chr4: 80993475-80993634


13
ARL5C
chr17: 37321515-37321626


14
ASCL2
chr11: 2292240-2292361


15
ATP6V1B1
chr2: 71192354-71192453


16
B3GNT5
chr3: 182971589-182971825


17
BANK1
chr4: 102711871-102712076


18
BCAT1
chr12: 25055906-25055975


19
BEGAIN
chr14: 101033665-101033813


20
BEST4
chr1: 45251853-45252029


21
BHLHE23_A
chr20: 61637950-61637986


22
BHLHE23_B
chr20: 61638020-61638083


23
BHLHE23_C
chr20: 61638088-61638565


24
BHLHE23_D
chr20: 61638244-61638301


25
BMP4
chr14: 54421578-54421916


26
BMP6
chr6: 7727566-7727907


27
C10orf125
chr10: 135171410-135171504


28
C10orf93
chr10: 134756078-134756167


29
C17orf64
chr17: 58499095-58499190


30
C19orf35
chr19: 2282568-2282640


31
C19orf66
chr19: 10197688-10197823


32
C1QL2
chr2: 119916511-119916572


33
C20orf195_A
chr20: 62185293-62185364


34
C20orf195_B
chr20: 62185418-62185546


35
C7orf52
chr7: 100823483-100823514


36
CALN1_A
chr7: 71801486-71801594


37
CALN1_B
chr7: 71801741-71801800


38
CAMKV
chr3: 49907259-49907298


39
CAPN2.FR
chr1: 223900347-223900405


40
CAV2
chr7: 116140205-116140342


41
CBLN1_A
chr16: 49315588-49315691


42
CBLN1_B
chr16: 49316198-49316258


43
CCDC61
chr19: 46519467-46519536


44
CCND2_A
chr12: 4378317-4378375


45
CCND2_B
chr12: 4380560-4380681


46
CCND2_C
chr12: 4384096-4384146


47
CD1D
chr1: 158150864-158151129


48
CD8A
chr2: 87017780-87017917


49
CDH4_A
chr20: 59827230-59827285


50
CDH4_B
chr20: 59827762-59827776


51
CDH4_C
chr20: 59827794-59827868


52
CDH4_D
chr20: 59828193-59828258


53
CDH4_E
chr20: 59828479-59828729


54
CDH4_F
chr20: 59828778-59828814


55
CHRNA7
chr15: 32322830-32322897


56
CHST2_A
chr3: 142838025-142838494


57
CHST2_B
chr3: 142839223-142839568


58
CLIC6
chr21: 36042025-36042131


59
CLIP4
chr2: 29338109-29338339


60
COL23A1.R
chr5: 178017669-178017854


61
CR1
chr1: 207669481-207669639


62
CRHBP
chr5: 76249939-76249997


63
CXCL12.F
chr10: 44881210-44881300


64
DBNDD1.FR
chr16: 90085625-90085681


65
DLK1
chr14: 101193295-101193318


66
DLX4
chr17: 48042562-48042606


67
DLX6
chr7: 96635255-96635475


68
DNAJC6
chr1: 65731412-65731507


69
DNM3_A
chr1: 171810393-171810575


70
DNM3_B
chr1: 171810648-171810702


71
DNM3_C
chr1: 171810806-171810920


72
DSCR6
chr21: 38378540-38378601


73
DTX1
chr12: 113515535-113515637


74
EMX1_A
chr2: 73151498-73151578


75
EMX1_B
chr2: 73151663-73151756


76
EPHA4
chr2: 222436217-222436320


77
ESPN
chr1: 6508784-6509175


78
ESYT3
chr3: 138153979-138154071


79
ETS1_A
chr11: 128391809-128391908


80
ETS1_B
chr11: 128392062-128392309


81
FABP5
chr8: 82192605-82192921


82
FAIM2
chr12: 50297863-50297988


83
FAM126A
chr7: 23053941-23054066


84
FAM129C.F
chr19: 17650551-17650610


85
FAM150A
chr8: 53478266-53478416


86
FAM150B
chr2: 287868-287919


87
FAM171A1
chr10: 15412558-15412652


88
FAM189A1
chr15: 29862130-29862169


89
FAM20A
chr17: 66597237-66597326


90
FAM59B
chr2: 26407713-26407972


91
FBN1
chr15: 48937412-48937541


92
FLJ42875
chr1: 2987037-2987116


93
FLRT2
chr14: 85998469-85998535


94
FMN2
chr1: 240255171-240255253


95
FMNL2
chr2: 153192734-153192836


96
FOXP4
chr6: 41528816-41528958


97
FSCN1
chr7: 5633506-5633615


98
GAD2
chr10: 26505066-26505385


99
GAS7
chr17: 10101325-10101397


100
GCGR
chr17: 79761970-79762088


101
GLI3
chr7: 42267808-42267899


102
GLP1R
chr6: 39016381-39016421


103
GNG4
chr1: 235813658-235813798


104
GP5
chr3: 194118738-194118924


105
GRASP
chr12: 52400919-52401166


106
GRM7
chr3: 6902873-6902931


107
GSTP1
chr11: 67350986-67351055


108
GYPC_A
chr2: 127413505-127413678


109
GYPC_B
chr2: 127414096-127414189


110
HAND2
chr4: 174450452-174450478


111
HBM
chr16: 216426-216451


112
HES5
chr1: 2461823-2461915


113
HHEX.F
chr10: 94449486-94449597


114
HMGA2
chr12: 66219385-66219487


115
HNF1B_A
chr17: 36103713-36103793


116
HNF1B_B
chr17: 36105390-36105448


117
HOXA1_A
chr7: 27135603-27135889


118
HOXA1_B
chr7: 27136191-27136244


119
HOXA7_A
chr7: 27195742-27195895


120
HOXA7_B
chr7: 27196032-27196190


121
HOXA7_C
chr7: 27196441-27196531


122
HOXD9
chr2: 176987716-176987739


123
IGF2BP3_A
chr7: 23508901-23509225


124
IGF2BP3_B
chr7: 23513817-23514114


125
IGFBP5
chr2: 217559103-217559244


126
IGSF9B_A
chr11: 133825409-133825476


127
IGSF9B_B
chr11: 133825491-133825530


128
IL15RA
chr10: 6018610-6018848


129
IL17REL
chr22: 50453462-50453555


130
INSM1
chr20: 20348140-20348182


131
ITGA9
chr3: 37493895-37493994


132
ITPKA_A
chr15: 41787438-41787784


133
ITPKA_B
chr15: 41793928-41794003


134
ITPRIPL1
chr2: 96990968-96991328


135
JSRP1
chr19: 2253163-2253376


136
KCNA1
chr12: 5019401-5019633


137
KCNE3
chr11: 74178260-74178346


138
KCNH8
chr3: 19189837-19189897


139
KCNK17_A
chr6: 39281195-39281282


140
KCNK17_B
chr6: 39281408-39281478


141
KCNK9.FR
chr8: 140715096-140715164


142
KCNQ2
chr20: 62103558-62103625


143
KIAA1949
chr6: 30646976-30647084


144
KIRREL2
chr19: 36347825-36347863


145
KLF16
chr19: 1857330-1857476


146
KLHDC7B
chr22: 50987219-50987304


147
LAYN.R
chr11: 111412023-111412074


148
LIME1
chr20: 62369116-62369393


149
LMX1B_A
chr9: 129388175-129388223


150
LMX1B_B
chr9: 129388231-129388495


151
LMX1B_C
chr9: 129445588-129445603


152
LOC100131176
chr7: 151106986-151107060


153
LOC100132891
chr8: 72755897-72756295


154
LOC100302401.R
chr1: 178063509-178063567


155
LOC283999
chr17: 76227905-76227960


156
LRRC34
chr3: 169530006-169530139


157
LSS.F
chr21: 47649525-47649615


158
LY6H
chr8: 144241547-144241557


159
MAGI2
chr7: 79083359-79083600


160
MAST1
chr19: 12978399-12978642


161
MAX.chr1.158083198-
chr1: 158083198-158083476



158083476


162
MAX.chr1.228074764-
chr1: 228074764-228074977



228074977


163
MAX.chr1.239549742-
chr1: 239549742-239549886



239549886


164
MAX.chr1.46913931-
chr1: 46913931-46913950



46913950


165
MAX.chr1.8277285-
chr1: 8277285-8277316



8277316


166
MAX.chr1.8277479-
chr1: 8277479-8277527



8277527


167
MAX.chr10.130085265-
chr10: 130085265-130085312



130085312


168
MAX.chr11.14926602-
chr11: 14926602-14927148



14927148


169
MAX.chr11.68622869-
chr11: 68622869-68622968



68622968


170
MAX.chr12.4273906-
chr12: 4273906-4274012



4274012


171
MAX.chr12.59990591-
chr12: 59990591-59990895



59990895


172
MAX.chr14.101176106-
chr14: 101176106-101176260



101176260


173
MAX.chr15.96889013-
chr15: 96889013-96889128



96889128


174
MAX.chr17.73073682-
chr17: 73073682-73073814



73073814


175
MAX.chr17.8230197-
chr17: 8230197-8230314



8230314


176
MAX.chr18.5629721-
chr18: 5629721-5629791



5629791


177
MAX.chr18.76734362-
chr18: 76734362-76734476



76734476


178
MAX.chr19.30719261-
chr19: 30719261-30719354



30719354


179
MAX.chr19.46379903-
chr19: 46379903-46380197



46380197


180
MAX.chr2.223183057-
chr2: 223183057-223183114



223183114.FR


181
MAX.chr2.238864674-
chr2: 238864674-238864735



238864735


182
MAX.chr2.97193163-
chr2: 97193163-97193287



97193287


183
MAX.chr2.97193478-
chr2: 97193478-97193562



97193562


184
MAX.chr20.1783841-
chr20: 1783841-1784054



1784054


185
MAX.chr20.1784209-
chr20: 1784209-1784461



1784461


186
MAX.chr21.44782441-
chr21: 44782441-44782498



44782498


187
MAX.chr21.47063802-
chr21: 47063802-47063851



47063851


188
MAX.chr22.23908718-
chr22: 23908718-23908782



23908782


189
MAX.chr22.42679578-
chr22: 42679578-42679917



42679917


190
MAX.chr4.8859253-
chr4: 8859253-8859329



8859329


191
MAX.chr4.8859602-
chr4: 8859602-8859669



8859669


192
MAX.chr4.8860002-
chr4: 8860002-8860038



8860038


193
MAX.chr5.145725410-
chr5: 145725410-145725459



145725459


194
MAX.chr5.172234248-
chr5: 172234248-172234494



172234494


195
MAX.chr5.178957564-
chr5: 178957564-178957598



178957598


196
MAX.chr5.180101084-
chr5: 180101084-180101094



180101094


197
MAX.chr5.42952185-
chr5: 42952185-42952280



42952280


198
MAX.chr5.42994866-
chr5: 42994866-42994936



42994936


199
MAX.chr5.77268672-
chr5: 77268672-77268725



77268725


200
MAX.chr5.81148300-
chr5: 81148300-81148332



81148332


201
MAX.chr6.108440684-
chr6: 108440684-108440788



108440788


202
MAX.chr6.130686865-
chr6: 130686865-130686985



130686985


203
MAX.chr6.157556793-
chr6: 157556793-157556856



157556856


204
MAX.chr6.157557371-
chr6: 157557371-157557657



157557657


205
MAX.chr6.27064703-
chr6: 27064703-27064783



27064783


206
MAX.chr7.151145632-
chr7: 151145632-151145743



151145743


207
MAX.chr7.152622607-
chr7: 152622607-152622638



152622638


208
MAX.chr8.124173030-
chr8: 124173030-124173395



124173395


209
MAX.chr8.124173128-
chr8: 124173128-124173268



124173268


210
MAX.chr8.143533298-
chr8: 143533298-143533558



143533558


211
MAX.chr8.145104132-
chr8: 145104132-145104218



145104218


212
MAX.chr8.687688-
chr8: 687688-687736



687736


213
MAX.chr8.688863-
chr8: 688863-688924



688924


214
MAX.chr9.114010-
chr9: 114010-114207



114207


215
MAX.chr9.136474504-
chr9: 136474504-136474527



136474527


216
MCF2L2
chr3: 182896930-182897245


217
MERTK
chr2: 112656676-112656744


218
MGAT1
chr5: 180230434-180230767


219
MIB2
chr1: 1565891-1565987


220
MN1
chr22: 28197962-28198388


221
MPZ
chr1: 161275561-161275996


222
MSX2P1
chr17: 56234436-56234516


223
NACAD
chr7: 45128502-45128717


224
NID2_A
chr14: 52535260-52535353


225
NID2_B
chr14: 52535974-52536161


226
NID2_C
chr14: 52536192-52536328


227
NKX2-6
chr8: 23564115-23564146


228
NR2F6
chr19: 17346428-17346459


229
NTRK3
chr15: 88800287-88800414


230
NXPH4
chr12: 57618904-57618944


231
ODC1
chr2: 10589075-10589243


232
OLIG3_A
chr6: 137818896-137818917


233
OLIG3_B
chr6: 137818978-137818988


234
OSR2_A
chr8: 99952233-99952366


235
OSR2_B
chr8: 99952801-99952919


236
OSR2_C
chr8: 99960580-99960630


237
OTX1.R
chr2: 63281481-63281599


238
PAQR6
chr1: 156215470-156215739


239
PCDH8
chr13: 53421299-53421322


240
PDX1
chr13: 28498503-28498544


241
PDXK_A
chr21: 45148429-45148556


242
PDXK_B
chr21: 45148575-45148681


243
PEAR1
chr1: 156863318-156863493


244
PIF1
chr15: 65116285-65116597


245
PLXNC1_A
chr12: 94544327-94544503


246
PLXNC1_B
chr12: 94544333-94544426


247
POU4F1
chr13: 79177505-79177532


248
PPARA
chr22: 46545328-46545457


249
PPARG
chr3: 12330042-12330152


250
PPP1R16B_A
chr20: 37435507-37435716


251
PPP1R16B_B
chr20: 37435738-37435836


252
PPP2R5C
chr14: 102247681-102247929


253
PRDM13_A
chr6: 100061616-100061742


254
PRDM13_B
chr6: 100061748-100061792


255
PRHOXNB
chr13: 28552424-28552562


256
PRKCB
chr16: 23847575-23847699


257
PRMT1
chr19: 50179501-50179635


258
PROM1
chr4: 16084793-16085112


259
PTPRM
chr18: 7568565-7568808


260
PTPRN2
chr7: 157483341-157483429


261
RASGRF2
chr5: 80256117-80256162


262
RBFOX3_A
chr17: 77179579-77179752


263
RBFOX3_B
chr17: 77179778-77180064


264
RFX8
chr2: 102090934-102091130


265
RGS17
chr6: 153452120-153452393


266
RIC3.F
chr11: 8190622-8190711


267
RIPPLY2
chr6: 84563228-84563287


268
RYR2_A
chr1: 237205369-237205428


269
RYR2_B
chr1: 237205619-237205640


270
SALL3
chr18: 76739321-76739404


271
SBNO2
chr19: 1131795-1131992


272
SCRT2_A
chr20: 644533-644618


273
SCRT2_B
chr20: 644573-644618


274
SERPINB9_A
chr6: 2902941-2902998


275
SERPINB9_B
chr6: 2903031-2903143


276
SLC16A3.F
chr17: 80189895-80189962


277
SLC22A20.FR
chr11: 64993239-64993292


278
SLC2A2
chr3: 170746149-170746208


279
SLC30A10
chr1: 220101458-220101634


280
SLC7A4
chr22: 21386780-21386831


281
SLC8A3
chr14: 70654596-70654640


282
SLITRK5.R
chr13: 88329960-88330076


283
SNCA
chr4: 90758071-90758118


284
SPHK2
chr19: 49127580-49127683


285
ST8SIA4
chr5: 100240059-100240276


286
STAC2_A
chr17: 37381217-37381303


287
STAC2_B
chr17: 37381689-37381795


288
STX16_A
chr20: 57224798-57224975


289
STX16_B
chr20: 57225077-57225227


290
SYN2
chr3: 12045894-12045967


291
SYNJ2
chr6: 158402213-158402536


292
SYT5
chr19: 55690401-55690496


293
TAL1
chr1: 47697702-47697882


294
TBKBP1
chr17: 45772630-45772726


295
TBX1
chr22: 19754257-19754550


296
TEPP
chr16: 58018790-58018831


297
TIMP2
chr17: 76921762-76921779


298
TLX1NB
chr10: 102881178-102881198


299
TMEFF2
chr2: 193060012-193060126


300
TMEM176A
chr7: 150497411-150497535


301
TNFRSF10D
chr8: 23020896-23021114


302
TOX
chr8: 60030723-60030754


303
TRH_A
chr3: 129693484-129693575


304
TRH_B
chr3: 129694457-129694501


305
TRIM67
chr1: 231297047-231297159


306
TRIM71_A
chr3: 32858861-32858897


307
TRIM71_B
chr3: 32859445-32859559


308
TRIM71_C
chr3: 32860020-32860090


309
TSHZ3
chr19: 31839809-31840038


310
UBTF
chr17: 42287924-42288018


311
ULBP1
chr6: 150285563-150285661


312
USP44_A
chr12: 95942148-95942178


313
USP44_B
chr12: 95942519-95942558


314
UTF1
chr10: 135044125-135044171


315
UTS2R
chr17: 80329497-80329534


316
VIPR2
chr7: 158937370-158937481


317
VN1R2
chr19: 53758121-53758147


318
VSNL1
chr2: 17720216-17720257


319
VSTM2B_A
chr19: 30016283-30016357


320
VSTM2B_B
chr19: 30017789-30018165


321
ZBTB16
chr11: 113929882-113930166


322
ZFP64
chr20: 50721057-50721235


323
ZNF132
chr19: 58951402-58951775


324
ZNF486
chr19: 20278004-20278145


325
ZNF626
chr19: 20844070-20844199


326
ZNF671
chr19: 58238810-58238955


327
ZSCAN12
chr6: 28367128-28367509









Next, SYBR Green Methylation-specific PCR (qMSP) was performed on the discovery samples to confirm the accuracy and reproducibility of the candidate DMR's shown in Table 2.


qMSP primers were designed for each of the marker regions using Methprimer software (Li LC and Dahiya R. Bioinformatics. 2002 November; 18(11):1427-31) They were synthesized by IDT (Integrated DNA Technologies). Assays were tested and optimized (using the Roche LightCycler 480) on dilutions of bisulfite converted universally methylated DNA, along with converted unmethylated DNA and converted and unconverted leukocyte DNA negative controls (long/ea). Assays taken forward needed to demonstrate linear regression curves and negative control values less than 5-fold below the lowest standard (1.6 genomic copies). Some of the more promising DMRs which had assay or control failures were re-designed. Of the 127 total designs (Table 3 shows the forward and reverse primer sequence information for the 127 total designs), 80 high performing MSP assays met QC criteria and were applied to the samples. The MSP primer sequences, each of which include 2-8 CpGs, were designed to provide a quick means of assessing methylation in the samples, and as such, were biased for amplification efficiency over trying to target the most discriminate CpGs—which would have required lengthy optimization timeframes.


DNA was purified as described in the discovery RRBS section and quantified using picogreen absorbance (Tecan/Invitrogen). 2ug of sample DNA was then treated with sodium bisulfite and purified using the Zymo EZ-96 Methylation kit (Zymo Research). Eluted material was amplified on Roche 480 LightCyclers using 384-well blocks. Each plate was able to accommodate 2 markers (and standards and controls) for a total of 40 plates. The 80 MSP assays had differing optimal amplification profiles (Tm=60, 65, or 70° C.) and were grouped accordingly. The 20 uL reactions were run using LightCycler 480 SYBR I Master mix (Roche) and 0.5 umoles of primer for 50 cycles and analyzed, generally, by the Fit Point 18% absolute quantification method. All parameters (noise band, threshold, etc.) were pre-specified in an automated macro to avoid user subjectivity. The raw data, expressed in genomic copy number, was normalized to the amount of input DNA (β-actin). Results were analyzed logistically using JMP and displayed as AUC values. Twelve comparisons were run: each breast cancer subtype vs normal breast, and each subtype vs buffy coat. In addition, the methylation fold change ratio (mFCR) was calculated for each comparison using both average and median fractional methylation (FCR=cancer(methylated copies/β-actin copies)/normal(methylated copies/β-actin copies)). Both of these performance metrics were critical for assessing the potential of a marker in a clinical blood-based test.


>90% of the markers tested yielded superior performance in both AUC and FCR categories, with numerous AUCs in excess of 0.90, cancer vs normal tissue FCRs >10, and cancer vs buffy coat FCRs >50.














TABLE 3








SEQ

SEQ


Gene
DMR
Forward Primer
ID
Reverse Primer
ID


Annotation
No.
5′-3′
NO:
5′-3′
NO:







AADAT-RS
  2
GAG TTT CGG CGG
  1
CGC TAC GTC TAA
  2




CGT TTT TCG

CTT CCC GCG C






ABLIM1-FS
  3
TTT TCG ACG AGT
  3
GCG AAT CTA TCT
  4




AGG ATT GAA GAA

ACC GAA ACG CGC





GGA AC

T






AJAP1_A
  6
TTT TGA TTT GTA
  5
GTA TAA ACG CGT
  6




ATA TAG AGG AAA

AAA TAC CAA ACT





GCG TCG T

AAA CGA A






AJAP1_B
  7
GTT TCG AGA AAG
  7
ACT CCC AAC GAA
  8




GAG AAG GGG GAG

AAC TTC GCA AAC





C

G






ALOX5-RS
  9
GTT TTT TGT CGG
  9
CCA AAA ATT AAA
 10




GAG TTA TTC GT

TTA AAA ACG CTA







CGC A






ASCL2-RS
 14
GTT TTA GGA GGG
 11
AAC ACG ACT ATT
 12




TGG GGC GT

CGA AAA ACG CGC







A






ATP6V1B1-RS
 15
TTC GTA GTA TCG
 13
GAA ATA ATA AAA
 14




GGA GTC GA

ACG CCG CAC GCT






BANK1-FS
 17
GTC GTA GTT TTC
 15
CGA ACG CTA CCT
 16




GCG GGT GGT AAG

AAA CTC TCC CGA





C

C






BEST4-RS
 20
GGA ATC GCG AGT
 17
AAA TAC AAT TAC
 18




TTT GGG ATA GTC G

ACC CTC TAC CGC







C






BHLHE23_C
 23
GAG GCG TTC GGT
 19
CCC CGA CCT ATA
 20




GGG ATT TC

AAC CTA CGA CGC







T






BHLHE23_D
 24
GAG GAG GTA GCG
 21
CGC GTC GAT CTA
 22




GGC GTC GA

ACT TAC CTA CGA







A






C10orf125-FS
 27
TTG CGT TTA TCG
 23
GCA CTA CTA TCC
 24




ATT TCG TTT TCG T

CCC GAA CTA CTC







TAC GC






C17orf64-RS
 29
TTA TTA GGC GGG
 25
CTC GAA TCC CTA
 26




GAG TCG GGT GTC

AAA AAC TCG CGA







A






C19orf66-FS
 31
AGG AAA TTC GGT
 27
AAA CCC CTA CAA
 28




AGC GAT TAT ACG G

CCT CAC CGT ACA







CGA T






CALN1_A
 36
CGG AGT TAA TAG
 29
CAA ACC CCC GAA
 30




GTA CGG GAG GCG

CTA TCG CGA A





T








CAPN2-FS
 39
CGG GTA TCG CGG
 31
TAT CGT AAA AAC
 32




TTA AGT TGG C

CCA ACC CCT CGA







C






CD1D-FS
 47
GGG ATT GGT GAG
 33
CTC CCC GAA ACC
 34




ATT CGG GAC GT

AAA AAA CAA CGA







A






CDH4_E
 53
GTT TTA AAT CGT
 35
ACG AAC GAA AAC
 36




ATT CGT AGT TCG G

TTT CCT AAA CGA







A






CHST2_A
 56
GCG TTT TTT TAT
 37
ACC GAC ACT ACC
 38




CGT TTT AGG GCG T

AAC CTC TCC GAA






CHST2_B
 57
TGC GGG GAT TTT
 39
CCG ACG AAC TAT
 40




TAG CGG AAG C

CCG ACT ATC ACT







CGT T






CLIC6-FS
 58
GTA GTA GGT GGA
 41
CTC TCG AAA ACC
 42




GGG GGC GAG TTC

GCA AAA TCC TCG






CLIP4-FS
 59
GGT AAT ATT GCG
 43
AAC AAT CAA ATA
 44




ATA TTT CGT AGA

ATC GAA CGC ACG





CGT

C






COL23A1-RS
 60
GTC GTT TTT CGT
 45
AAA ACT AAA TAA
 46




TAC GAA GCG GC

ATC TAT CCT CGA







T






CXCL12-FS
 63
GCG TCG GCG GTT
 47
AAC GAA TCT CAT
 48




TTT AGT AAA AGC

TAA ATC TCC CGT







C






DBNDD1R-FS
 64
GAT TTT CGG GAG
 49
CTT CCC CGC AAC
 50




CGG CGA

GAA CCG






DLX4-FS
 66
TTC GTT GGT ATA
 51
CGA ATA CCG AAA
 52




TTC GCG TAG GTG

TCT ATA ACC CCG





C

AA






DLX6-FS
 67
ATT ATG ATT ACG
 53
CTC CAT AAA AAC
 54




ATG GTT GAC GG

GAA TTT AAA CGA







A






DNM3_A
 69
TTT GGT TAT AGA
 55
ATC GAA CCA CCA
 56




ACG TAG AGG TCG

AAC CAA ACG C





T








DSCR6-FS
 72
GGG AAG TTT AGT
 57
ACT AAA AAC GTT
 58




AGG TGA GCG T

TCC GTC GAA CGC







A






DTX1-RS
 73
GTT GGT AGG AGT
 59
ATC GCA ATC GTA
 60




AGG GTT GGT TCG

ACC CGT AAA CGC





A








EMX1_A
 74
ATT CGT ACG GTT
 61
GAC CAA CTA CTT
 62




TTT TCG TTT TCG T

CCG CTC GAC GC






ETS1_B
 80
CGG ATT TAG CGG
 63
TTT AAA ACG TTT
 64




TCG AGA CG

CTC GCG ACG CC






FAM126A-FS
 83
TCG TTA GGC GAT
 65
TAA AAA AAC CAT
 66




GAT AAT TAG CGA

AAA CCC TAA CGA







C






FAM129C-FS
 84
GTT GGA GAA GAC
 67
CCA AAA CCT CAC
 68




GAT TCG TTC GGA C

TCC TCA ACC GC






FBN1-FS
 91
CGC GAT GCG CGT
 69
GAC GCG ACT AAC
 70




TTT GAA C

TTC CAA CCT AAC







GAA






FMN2-RS
 94
TTT TCG TGG TTG
 71
GCC GCG CTC TAC
 72




TCG TCG TTG C

ACT AAA CAT ATT







CGC






FOXP4-FS
 96
CGG GGA AGT GGG
 73
AAA AAA ACT AAA
 74




AGT TTT TAG CG

TCA AAA CCG CGA







C






GAS7-FS
 99
GCG AGT TCG CGT
 75
ACC GAC GCT ACC
 76




TGT TTA CGT TTC

TAT AAC TCC ACG







CT






GP5-RS
104
TTA GGT TTG TTT
 77
TCT ACA AAA CGC
 78




ATT AAT TTT ACG T

CGC GAC






GRM7-FS
106
GTT AAT TCG AGA
 79
GAC CAA AAA AAA
 80




GCG CGA GGC GT

TAA AAA ATC CCG







CGA C






GYPC_B
109
TAA AGA AAT AGA
 81
CGA ACT AAA AAA
 82




AAG CGG GCG ATA

ACC GCC AAC CCG





CGT








HHEX-RS
113
GGG TTT TGC GGT
 83
AAT AAC AAA CGC
 84




TAA TGG CG

GTC CCG AAA ACG







A






HNF1B_B
116
TTA GTT TTT TTT
 85
AAC TTT TCC ACC
 86




GGT TTT TAT TTG

GAT TCT CAA TTC





AAT TTC GA

CG






HOXA1_A
117
ATT TAA ATT TTC
 87
ACA CTC CAA ATC
 88




GGC GTT TCG TCG

GAC CTT TAC AAT





T

CGC






HOXA7_A
119
AGT TTG GTT CGT
 89
AAC GCG ACT AAA
 90




TTA GCG ATT GCG T

ACC AAT TTC CGC







A






IGF2BP3_A
123
TTT ATT TGT TTT
 91
AAA TAT ATA CCC
 92




TAT CGT TCG TCG G

GAT TTC CCC GTT






IGF2BP3_B
124
TAA TCG GCG TCG
 93
CCG TCA ACC AAT
 94




AGA GAG ATA TCG T

CGA AAA CGA A






IL15RA-FS
128
TCG TTT ATT TCG
 95
AAC CAA CCT AAA
 96




TTT TTT TTG TCG A

ATC TAC ACT CGC







A






ITPRIPL1-FS
134
GGG TCG TAG GGG
 97
CAT ACT TAT CCG
 98




TTT ATC GC

AAC GTC TAA ACG







TC






ITPRIPL1-FS
134
GGT TTT AGC GAT
 99
CAC GAT CTT AAA
100




GAA TCG GAC GT

AAA ACA ACG CGA







C






KCNH8-RS
138
CGT ATT TTT AGG
101
ACA CTA TTA CCC
102




TTT AGT TCG GCG T

GCG AAA AAA CGA







T






KCNK17_B
140
GAG TTT GTT TGG
103
CCA AAT ATA ACG
104




GGG TTG GTC GTA

TTT AAC TCT TTA





TTC

CCA CGA A






KCNK9-FS
141
TTT TTT TTG ATT
105
CTA ATA AAC GCC
106




CGG ATT TTT TCG G

GCC GTA TTC GAC







G






KLF16-FS
145
TTT TCG CGT TGT
107
TAC ACA ACC ACC
108




TTT TAT TTA TCG T

CAA CTA CTC CGC







G






KLHDC7B-RS
146
TGT TGT TGG GTA
109
CGA AAA CCC AAC
110




AAG GTT AGT ACG T

TCC CGA A






LAYN-RS
147
TTT TTG CGG TCG
111
CTT ACC AAC TAA
112




TTT TTC GGA GC

CCC CCG CCT ACC







G






LIME1-RS
148
CGT TTT AGT AGG
113
CCC GAA AAC CAA
114




GAT TGG GGG CGA

AAT AAA ATC CGC







A






LMX1B_A
149
CGG AAT AGC GCG
115
TTT AAC CGT AAC
116




GTC GTT TTT TC

GCT CGC CTC GAC






LOC100132891-FS
153
GTC GGT TGT GTT
117
AAA AAA AAC CCC
118




TAG AGC GTA GCG

GAC GAC GAA





T








LOC100132891-FS
153
GTT GCG ATT GTT
119
ATA ATA ACA AAA
120




TGT ATT TTG CGG

AAC CCC TCC CGA







C






LSS-FS
157
AGT TTC GTT AGG
121
CAA CTA AAA CTC
122




GAA GGG TTG CGT

TAC CGC GCT CGA





C

T






MAGI2-RS
159
AGG AAG GGT TTC
123
AAA AAA ATC AAC
124




GAG TTT AGT GCG

GCG TCC TCC TCG





G

C






MAST1-RS
160
TTT CGA TTT CGT
125
AAA CTA AAC GAC
126




TTT TAA ATT TCG T

CTA ACC CTA CGT







A






MAX.chr1.8277479-
166
AAG TTT ACG CGC
127
CGA AAC GAC TTC
128


8277527-RS

GAG TTT GAT CGT C

TCT CCC CGC A






MAX.chr11.14926602-
168
TTT AGT TCG CGG
129
GAA AAC ACA ATA
130


14927148-FS

AAG TTA GGT TCG G

AAC CCC GCC GTC






MAX.chr11.68622869-
169
GTT AGA TTG TAG
131
AAA AAA CGA CTA
132


68622968-FS

GAG GGA TTA GCG

AAA AAT TCA CGC





G

C






MAX.chr12.4273906-
170
TTT GGA GTT TGG
133
CGA CGA AAC TAA
134


4274012-FS

GGG ATC GAT AGT

AAC CGC GTA CGT





C

A






MAX.chr12.4273906-
170
TTT GGA GTT TGG
135
CGA CGA AAC TAA
136


4274012-FS

GGG ATC GAT AGT

AAC CGC GTA CGT





C

A






MAX.chr12.59990671-
171
ATT ATA TTG GGG
137
AAC AAA CAA TTC
138


59990859-FS

GCG TTA GGT TCG

GCA CGT AAA CGA





G

A






MAX.chr15.96889013-
173
GGG CGG TTT ACG
139
GCG TCT CGA ACC
140


96889128-FS

TGG ATT TTT ATA

GTA CCC TAA CGT





GAT TTT C

A






MAX.chr17.73073682-
174
CGT CGT TGT TGA
141
CGC TTC CTA ACA
142


73073814-RS

TTA TGA TCG CGG

ACC TTC CTC GAA






MAX.chr18.76734362-
177
TTA ACG GTA TTT
143
AAA AAA AAC TCG
144


76734476-RS

TTT GTT TTT TCG T

TCC CCG CGC T






MAX.chr19.46379903-
179
TCG GTT AGT TCG
145
TAT TAA CCG AAA
146


46380197-FS

AGG TAG GAA GTT

AAC GAA AAC CAA





TTG C

ATC CGA






MAX.chr19.46379903-
179
AGT TTT GTT GTT
147
AAA AAC TAA AAA
148


46380197-FS

TTG GGT AGG TCG

CCT TTC TCT CGA





G

C






MAX.chr2.223183057-
180
GCG TTG AGA GTG
149
ACT ACC TAA ACT
150


223183114-RS

ACG GAT ATT TTT

CCG AAC ACG CCC





CGT C

G






MAX.chr20.1784209-
185
TTA GCG TAT CGG
151
GAA AAC GAA AAA
152


1784461-FS

GAA TTA GGG GGA

ACG ACG CGC A





C








MAX.chr20.1784209-
185
TCG TTT TTT AGG
153
GAA CCG TAT TTA
154


1784461-RS

TGG GGA AGA AGC

AAA CCA ATC CCC





G

GC






MAX.chr4.8859602-
191
AAT TGG GGT TCG
155
TTA CCC CTA CCC
156


8859669-RS

GGG TTC GGT AC

AAA AAA ATA CGC







T






MAX.chr5.145725410-
193
GGG GTT AGA GTT
157
CGC GTC TCC CGT
158


145725459-RS

TCG CGT TCG C

CCT ATC TAT ATA







CGT C






MAX.chr5.42994866-
198
TAG GAA TTT TTT
159
CAC AAA AAC TCG
160


42994936-FS

AAA TTC GTT TTA

ATA CAA TTA CCG





CGG

TT






MAX.chr5.77268672-
199
TAT TTT ATA GTC
161
GTC GAT AAA AAA
162


77268725-FS

GCG TTA AAA GCG T

CCT ACG CGA CGA







A






MAX.chr6.157557371-
204
GAT TTA GTT TTT
163
TAT TAA AAA CGA
164


157557657-FS

CGG GTT TAT AGC

CCA AAC CTC CGC





GG

A






MAX.chr8.124173030-
208
TGG TTG TAG GCG
165
AAA AAC GAC CCT
166


124173395-FS

TTT TGT TGG AGT

AAC CAC CCT CGT





TC

T






MCF2L2-FS
216
TTT TGC GTA GTT
167
CCC GCA TTC CCG
168




GGG TAG GGT TCG

AAA AAA ACG AT





G








MCF2L2-RS
216
TTA GGG TTT TTT
169
ATC CCC CGT ACG
170




TCG AGG AGT TCG

AAA CTA AAC GCG





A








MCF2L2-RS
216
GCG TTC GTA TTT
171
TCT ACG TAA CTA
172




TCG GGA GAG GC

AAC AAA ACC CGA







A






MIB2-FS
219
CGT TTT GTG TTT
173
AAA ACC CCA AAA
174




TAT AAA AAG AAA

ACG CCC GAT





GAT TTT CGG








MPZ-FS
221
GGG GCG TAT ATA
175
AAA AAA AAC CCT
176




TTA GTT ATC GAG

AAA AAC CGC CGA





CGA

A






MSX2P1-FS
222
TTC GTT TAA TGA
177
TAA AAC AAA CTA
178




GAA GGG GTT AGC

AAA ACC TTA ACG





GG

CGA CGC T






NACAD-RS
223
GGG GAG GGA GTT
179
GTA CGC GAA CTC
180




TTT TTT AC

GCC AAA CAC TAC







G






ODC1-FS
231
GTA GGG TTG GTA
181
AAC CCA TCT AAT
182




GTC GTT TTT ACG T

TAC AAA ATA CCT







CGA T






ODC1-RS
231
GGT TTT ATA GGG
183
AAA ACC TCG TCT
184




GAA ATT ATT TTC

TTA TAA CAT CGA





GT

A






ODC1-RS
231
TAG GAT ATT TCG
185
AAC AAA ACT AAC
186




ATG TTA TAA AGA

AAC CGC CTC CAC





CGA

G






OSR2_A
234
TTT GGA GTT ATC
187
GCA CGC CGA AAA
188




GGA AGG CGA AAG

AAT AAA AAC GAA





TAC








OTX1-RS
237
TTT TCG ATA TCG
189
ATA ACT TAA AAC
190




ATA TCG AAG GCG T

CCT AAA TTC CGC







C






PAQR6-FS
238
GCG GGT AGT AGG
191
CCG ACT TCC GTA
192




AAG ATT AGT AGC

CGA AAC CGT A





GG








PLXNC1_A
245
TAA TAG AGG TTT
193
AAC GCA CCC TAA
194




GCG TTG GAA TCG

ACA AAA CCA CGA





A

C






PLXNC1_B
246
TGA AGA GTT GTT
195
GCC AAA AAT TCG
196




AGT TCG TTT AGC

ATT CCA ACG CA





GT








PPARA-FS
248
TAG TGG TAG GTA
197
ATC AAA ACT CCC
198




TAG TTG GTA GCG

CTC CTC GAA AAC





G

G






PPARG-RS
249
GTT TTT AAG CGG
199
AAA AAA AAT CCC
200




CGG TCG T

GTT CGC T






PRKCB-RS
256
GCG CGC GTT TAT
201
AAA ATC AAA AAC
202




TAG ATG AAG TCG

CAC AAA TTC ACC







GCC






PRMT1-FS
257
CGG GGA GAG GAG
203
CAA CTT AAA CAC
204




GGG TAG GAT TTA C

CAC TTC CTC CGA







A






RBFOX3_A
262
TGT TTT TTT TGT
205
AAA TAA CTA ACT
206




TCG GGC GG

CCT ACT CTC GCC







CGC T






RFX8-FS
264
ATA GTT TTT TAA
207
AAA AAC AAC TCC
208




TTT TCG CGT TTC

AAC CCA CAC CGC





GTC GA








RIC3-RS
266
GCG GGA GGA GTA
209
AAA AAC AAA ATA
210




GGT TAA TTT TCG A

CGC GAA ACG CAC







G






SCRT2_B
273
CGA GAA GGT TTT
211
TAC GTA TCC ATA
212




GTC GTA GAC GTC

CCC GCG CTC G





GT








SLC16A3-FS
276
TTT GTT TGT ATA
213
CGC CTA ACT ACC
214




ATA GGG GTT GCG

GAA AAA TAC CGA





G

A






SLC22A20-FS
277
GGT GGG GTT ATT
215
CGA ACC AAA CCT
216




TTT TTA TGG AGT

ACG ATT CCC GAA





CGA TTC








SLC2A2-RS
278
GGG AGA AGA GAA
217
TCT TAT ACT CAA
218




TGG TTT TTT GTC

CCC CGA CCT ACC





GTC

GAC






SLC30A10-FS
279
GTT TTA TTC GGG
219
AAA AAA CCG CGT
220




GTT TTA GCG TTA

TAC TCA ACG CGC





TTT ACG G








SLC7A4-RS
280
GTT TAG AGC GGA
221
CGC CTA TTC TTA
222




GGT AGC GGT TGC

AAC CTA AAC CCG







TC






SLITRK5-FS
282
CGT AGA GGA TTA
223
TAC TAT AAC TAC
224




TAA AGA TTT GTA

TAC GAT AAC GAC





CGA

GAC GAC






SPHK2-RS
284
AGA TTT CGG TTT
225
ATT AAT ACT AAC
226




TTG TTT CGA TTT

TTA CGA AAC CGC





TCG T

C






ST8SIA4-RS
285
ATT ATT TTT GAG
227
AAA TTT CTC TCC
228




CGT GAA AAA TCG T

AAT TAA ATT CCG







TA






STAC2_B
287
GTG GGT TTG TCG
229
AAA TAA CCG CGT
230




TCG GAT TTC G

CAT CCG ATT CGT







T






STX16_A
288
TGG ATG TTT TAT
231
GTA CTT TTT CTC
232




ATT AAT TTT TAG

TCA CGA AAA ATA





TTG TAT AAC G

TTC CCG C






STX16_B
289
TGC GTG GAA TAA
233
GCT CAA CAC ACG
234




ATT TTA TAT ACG T

AAA AAC CCT CGA







A






STX16_B
289
CGG TGC GGG GTT
235
TCC ACG CAA AAA
236




TTA ATA AAG GAT C

CAA AAA ACG CGT







A






SYNJ2-FS
291
GGC GTA GTT ATG
237
ATC CTT TCG ACC
238




ATT TCG TTT TTT

CTA CGT ACC TCG





CGT

AT






TBX1-FS
295
TTT ACG ATT ATT
239
GAA CCC GAC GAA
240




GTT TTA GAT AAT

CTT CGA A





ACG G








TMEM176A-FS
300
GGG AAA TCG CGT
241
AAA ACG ACG AAA
242




AGT TTG GGC

AAA CGA AAA CGA







C






TNFRSF10D-FS
301
AGT TAT CGC GAT
243
AAA CGA TTA CCT
244




CGG TTT GGG TTA

CTT TCG TTC GTT





AC

CGT T






TRH_A
303
CGG CGG TTT ATT
245
CGA CAA ATC AAA
246




TGA AGA GGG TTC

AAT CTA CAA CGC







T






TRIM67-RS
305
TTT TAA CGT TAG
247
CGA ACA AAC CAA
248




TTA CGA GTT GCG

ACA ACC GAA





G








UBTF-RS
310
GTA GAT TAG GCG
249
GAA CAA AAA CAT
250




GGG GCG A

AAA CTA ATA CAA







ATA TCT CCC G






ZSCAN12-FS
327
GGA GGG AGA GTT
251
CTA AAC CCC TCA
252




TTT CGC GGA TTC

AAC CCT AAC CGA







T






GRASP
105
TGT TTT CGG ATA
253
ACG AAC GAA CTA
254




CGG CGA GC

TAC GCG ACG CT









Example II

This example describes the tissue validation of breast-cancer specific markers. Independent tissue samples (fresh frozen) were selected from institutional cancer registries at Mayo Clinic Rochester and were reviewed by an expert pathologist to confirm correct classification and to guide macro-dissection.


55 methylated DNA markers (MDMs) were chosen from the list of 80 MDMs (see, Example I) which were tested on the discovery samples.


Genomic DNA was prepared using QIAamp DNA Mini Kits (Qiagen, Valencia Calif.) and bisulfite converted using the EZ-96 DNA Methylation kit (Zymo Research, Irvine Calif.). Amplification primers were designed from marker sequences using Methprimer software (University of California, San Francisco Calif.) and synthesized commercially (IDT, Coralville Iowa). Assays were rigorously tested and optimized by SYBR Green qPCR (Roche) on bisulfite converted (methylated and unmethylated genomic DNA) and unconverted controls. Assays which cross reacted with negative controls were either redesigned or discarded. Melting curve analysis was utilized to ensure specific amplification was occurring.


qMSP was performed using the LightCycler 480 instrument on 2 uL of converted DNA in a total reaction volume of 25 uL. Standards were derived from serially diluted universal methylated DNA (Zymo Research). Raw marker copies were standardized to CpG-agnostic β-actin, a marker for total genomic DNA.


Results were analyzed logistically using JMP10 (SAS, Cary N.C.). Cases were compared separately to normal breast controls and normal buffy coat samples. Methylation ratios and absolute differentials were calculated for each of the MDMs.


MDM performance in the independent samples was excellent with many AUCs and methylation fold change ratios (FCs) greater than 0.90 and 50, respectively. Results are provided in Table 4 (Overall). Here, the MDMs are ranked by AUC (comparing overall cases to buffy coat samples). This is a critical metric for potential application in plasma as the majority of cell-free DNA (cfDNA) originates with leukocytes. Any MDM which does not highly discriminate epithelial-derived cancers from leukocyte DNA will fail in a blood test format, no matter its performance in tissues. 41 of 55 MDMs had cancer v buffy coat AUCs in excess of 0.9, with 3 achieving perfect discrimination (AUC=1). Table 4 also list AUCs, FCs, p-values, and % cancer methylation as other critical metrics in evaluating and demonstrating the excellence of these MDMs.














TABLE 4






Overall



DMR


Gene Annotation
AUC
p-value
% meth
FC
No.




















ATP6V1B1
0.88731
<.0001
26.75
3.17
15


FOXP4
0.62969
0.0032
47.95
1.39
96


LMX1B_A
0.86181
<.0001
26.52
3.35
149


BANK1
0.81125
<.0001
28.59
2.25
17


OTX1
0.84786
<.0001
28.23
3.84
237


ST8SIA4
0.61072
0.0054
19.51
1.59
285


MAX.chr11.14926602-
0.93745
<.0001
18.72
33.52
168


14927148


UBTF
0.81517
<.0001
42.18
3.07
310


STX16_B
0.66565
<.0001
38.93
2.61
289


KLHDC7B
0.67241
0.0005
29.94
1.58
146


PRKCB
0.92153
<.0001
19.52
43.21
256


TBX1
0.36127
0.9266
13.81
1.02
295


TRH_A
0.94355
<.0001
29.05
11.02
303


MPZ
0.93396
<.0001
18.93
65.72
221


GP5
0.79294
<.0001
30.09
4.08
104


DNM3_A
0.85418
<.0001
24.75
30.48
69


MAX.chr17.73073682-
0.53095
0.1372
21.71
1.31
174


73073814


TRIM67
0.91391
<.0001
10.80
41.41
305


PLXNC1_A
0.76983
<.0001
10.49
16.29
245


MAX.chr12.4273906-
0.9017
<.0001
12.09
55.76
170


4274012


CALN1_A
0.87271
<.0001
11.47
27.59
36


ITPRIPL1
0.88928
<.0001
17.19
37.21
134


MAX.chr12.4273906-
0.9029
<.0001
6.69
197.30
170


4274012


GYPC_B
0.87925
<.0001
15.78
16.22
109


MAX.chr5.42994866-
0.8932
<.0001
11.11
16.19
198


42994936


OSR2_A
0.80667
<.0001
18.56
44.40
234


SCRT2
0.841
<.0001
7.84
59.82
273


MAX.chr5.145725410-
0.91303
<.0001
10.12
52.12
193


145725459


MAX.chr11.68622869-
0.87947
<.0001
20.07
23.21
169


68622968


MAX.chr8.124173030-
0.85636
<.0001
21.94
3.08
208


124173395


CXCL12
0.60615
<.0001
41.39
6.66
63


MAX.chr20.1784209-
0.85113
<.0001
12.03
36.91
185


1784461


LOC100132891
0.89124
<.0001
19.91
64.60
153


BHLHE23_D
0.82149
<.0001
5.60
86.71
24


ALOX5
0.79948
<.0001
15.96
14.97
9


MAX.chr19.46379903-
0.84416
<.0001
12.85
31.77
179


46380197


ODC1
0.76024
<.0001
7.77
16.38
231


CHST2_B
0.84154
<.0001
12.15
226.06
57


MAX.chr5.77268672-
0.90519
<.0001
12.13
46.85
199


77268725


C17orf64
0.87293
<.0001
28.03
31.07
29


EMX1_A
0.88056
<.0001
11.01
83.60
74


CHST2_A
0.77114
<.0001
8.00
97.42
56


DSCR6
0.86595
<.0001
7.14
73.34
72


ITPRIPL1
0.88165
<.0001
15.26
36.79
134


IGF2BP3_B
0.81822
<.0001
27.51
69.74
124


CDH4_E
0.78073
<.0001
6.67
12.81
53


NACAD
0.75207
<.0001
4.29
38.67
223


DLX4
0.86399
<.0001
22.31
9.58
66


ABLIM1
0.83054
<.0001
5.25
265.54
3


BHLHE23_C
0.79174
<.0001
7.40
66.61
23


MAST1
0.73627
<.0001
9.73
32.31
160


ZSCAN12
0.75774
<.0001
7.79
139.40
327


SLC30A10
0.78182
<.0001
8.75
55.48
279


GRASP
0.77114
<.0001
7.10
43.44
105


C10orf125
0.72646
<.0001
11.36
9.94
27









Example III

This example describes identification of breast tissue markers and plasma markers for detecting breast cancer.


Candidate methylation markers for the detection of breast cancer were identified by RRBS of breast cancer and normal breast tissue samples. Originally 58 markers were identified and target enrichment long-probe quantitative amplified signal assays were designed and ordered (see, e.g., WO2017/075061 and U.S. patent application Ser. No. 15/841,006 for general techniques) (Table 5 shows the methylated regions distinguishing breast cancer tissue from normal breast tissue) (Tables 6 and 7 show the primer and probe sequences for the markers shown in Table 5). After design screening and redesign, 56 markers (see, Table 8) were chosen and assays made, triplexed and tested on tissue. Assays were equally split between FAM and HEX reporting and triplexed with the reference assay, B3GALT6 which reports to Quasar670.









TABLE 5







Methylated regions distinguishing breast


cancer tissue from normal breast tissue










Gene
Region on Chromosome


DMR No.
Annotation
(starting base-ending base)












329
ABLIM1_B
chr10: 116391634-116391781


330
AJAP1_C
chr1: 4715533-4715652


331
ALOX5_B
chr10: 45914740-45914889


332
ASCL2_B
chr11: 2292232-2292371


333
BANK1_B
chr4: 102711861-102712082


334
BHLHE23_E
chr20: 61638334-61638574


335
C10orf125_B
chr10: 135171404-135171514


336
C17orf64_B
chr17: 58499085-58499196


337
CALN1_1520
chr7: 71801485-71801604


37
CALN1_B
chr7: 71801741-71801800


339
CD1D_1058
chr1: 158150861-158151139


340
CDH4_7890
chr20: 59827763-59828158


341
CHST2_8128
chr3: 142838015-142838501


342
CHST2_8384
chr3: 142838015-142838501


343
CHST2_9316
chr3: 142839218-142839575


344
CHST2_9470
chr3: 142839218-142839575


345
CLIC6_B
chr21: 36042020-36042140


346
CXCL12_B
chr10: 44881200-44881315


347
DLX4_B
chr17: 48042552-48042616


348
DNM3_D
chr1: 171810425-171810575


74
EMX1_A
chr2: 73151498-73151578


349
ESPN_B
chr1: 6507924-6508087


350
FAM59B_7764
chr2: 26407703-26407976


351
FOXP4_B
chr6: 41528816-41528912


104
GP5
chr3: 194118738-194118924


352
HOXA1_C
chr7: 27135593-27135895


353
IGF2BP3_C
chr7: 23513861-23514064


354
IPTRIPL1_1138
chr2: 96990958-96991338


355
IPTRIPL1_1200
chr2: 96990958-96991338


356
KCNK9_B
chr8: 140715096-140715177


357
KCNK17_C
chr6: 39281887-39281994


358
KLHDC7B_B
chr22: 50987209-50987311


359
LAYN_B
chr11: 111412023-111412090


360
LIME1_B
chr20: 62369173-62369342


361
LMX1B_D
chr9: 129388170-129388223


362
LOC100132891_B
chr8: 72755986-72756299


375
MAST1_B
chr19: 12978496-12978642


338
MAX.chr12.427.br
chr12: 4273906-4274012


174
MAX.chr17.73073682-
chr17: 73073682-73073814



73073814


363
MAX.chr20.4422
chr20: 1784207-1784471


364
MPZ_5742
chr1: 161275554-161276006


365
MPZ_5554
chr1: 161275554-161276006


366
MSX2P1_B
chr17: 56234426-56234520


367
ODC1_B
chr2: 10589075-10589225


234
OSR2_A
chr8: 99952233-99952366


368
OTX1_B
chr2: 63281460-63281599


246
PLXNC1_B
chr12: 94544333-94544426


369
PRKCB_7570
chr16: 23847569-23847705


370
SCRT2_C
chr20: 644563-644631


279
SLC30A10
chr1: 220101458-220101634


371
SPHK2_B
chr19: 49127571-49127685


372
ST8SIA4_B
chr5: 100240049-100240286


373
STX16_C
chr20: 57225077-57225237


374
TBX1_B
chr22: 19754226-19754419


303
TRH_A
chr3: 129693484-129693575


328
TRIM67_B
chr1: 231297039-231297163





















TABLE 6








SEQ

SEQ


Gene
DMR
Forward Primer
ID
Reverse Primer
ID


Annotation
No.
5′-3′
NO:
5′-3′
NO:







ABLIM1_B
329
TGGTAATCGGGTTTTT
255
CCGCGAATCTATCTACC
256




CGACG

GAAAC






AJAP1_C
330
GTGTTAGGTTGGGCGG
257
GTTACCCGCTTACGAAA
258




AAG

AACGA






ALOX5_B
331
TTCGTTTTTTGTCGGG
259
TCCAAAAATTAAATTAAA
260




AGTTATTC

AACGCTACGC






ASCL2_B
332
ATAATACGGTTGTTCG
261
GTAAATATAAACTACGCG
262




GGAGG

ACGCGTA






BANK1_B
333
GAGAGTTTAGGTAGCG
263
CCTAACGCTACTAACAAC
264




TTCGG

ATTATAACGA






BHLHE23_E
334
CGCGGTTTTGGAGCGT
265
CCGAAACGACCGAAAAC
266




TAG

GAC






C10orf125_B
335
CGGTTCGTTGCGTTTA
267
CCCCCGAACTACTCTAC
268




TCGA

GCG






C17orf64_B
336
GATTATATTCGGATTTT
269
GACTCTTCCTACCCGCG
270




GTTTATCGCGT

A






CALN1_1520
337
GCGGTTTTTAGTTCGC
271
AACAAATAATTAACAAAC
272




GGG

AACGCCTCC






CALN1_B
 37
TCGTTCGGCGTATTTA
273
CGCGAAAAACTTCCTCC
274




TTTCGTAT

GA






CD1D_1058
339
GGATTGGTGAGATTCG
275
CCCGAAACCAAAAAACA
276




GGAC

ACGA






CDH4_7890
340
CGGGGAGTTTCGTTTG
277
CGAATAACGACTACGAA
278




TATCG

CTTTAAACG






CHST2_8128
341
CGTAGTTATAGATTTAT
279
CTAAAACGATAAAAAAAC
280




TAGAGAGGGCG

GCGAAACG






CHST2_8384
342
TGGTAGTTTTCGGTAT
281
TAACTCTACGCGCAAAA
282




CGACGAG

CGC






CHST2_9316
343
GGGATTTTTAGCGGAA
283
CGACGAACTATCCGACT
284




GCGA

ATCACT






CHST2_9470
344
CGGAGGAATCGGGTA
285
ACTCTCCCATAACAACGA
286




GAATCG

CTCC






CLIC6_B
345
CGCGTAGGGCGAGTTT
287
GCCTCCTCCTACCTCTC
288




C

G






CXCL12_B
346
TCGGCGGTTTTTAGTA
289
AAATCTCCCGTCCCACT
290




AAAGCG

CC






DLX4_B
347
GGTATATTCGCGTAGG
291
AACCGAATACCGAAATCT
292




TGCG

ATAACCC






DNM3_D
348
GTAGTTGGGTTGTAGT
293
CCCGAACTTCCCATCGA
294




GCGTG

AC






EMX1_A
 74
TTCGTACGGTTTTTTCG
295
CCACCACGTAATAATTCT
296




TTTTCG

TCTCGAAA






ESPN_B
349
CGGTTTGATATTATTCG
297
AATTAACGCCCCCTATAA
298




GGGTTCG

CATCC






FAM59B_7764
350
CGCGATAGCGTTTTTT
299
CGCACGACCGTAAAATA
300




ATTGTCGCG

CTCG






FOXP4_B
351
CGGTTCGTAGATTGTT
301
CAAATACCGTCGAAAAAA
302




TTAGAGCG

AACTAAATCAAAAC






GP5
104
CGTTGTAGGACGGTTA
303
CATCCTACTCTTCGAAAT
304




TGTCG

AAACCGC






HOXA1_C
352
AGTCGTTTTTTTAGGTA
305
CGACCTTTACAATCGCC
306




GTTTAGGCG

GC






IGF2BP3_C
353
AGATTGGCGCGTAAAA
307
ACCGACCCCGAAAAACG
308




GCG








IPTRIPL1_1138
354
CGTTTTCGGAGTCGCG
309
AACCATACTTATCCGAAC
310




TG

GTCTAAAC






IPTRIPL1_1200
355
GAGTAGGGTTATTTTC
311
CTACTTTTTTCCCGACAA
312




GCGGG

AATAAAAACGT






KCNK9_B
356
TTTTCGCGTATTTCGTG
313
AACGCCGCCGTATTCG
314




GTTC








KCNK17_C
357
TCGCGTTGGAAGTTGC
315
CGTATTCTAAACGCTAAA
316




G

AAACCGC






KLHDC7B_B
358
CGGCGGTAGTTTTGCG
317
CTACTAAACAAAAACCAA
318




G

CACGTCC






LAYN_B
359
GGTAGGTTTGTTAGTT
319
CGCTATCTCTACGACCG
320




GGTTTTCG

CCT






LIME1_B
360
CGGAGGTAGCGGGCG
321
CACTCACCGCTTCCGCC
322




AG








LMX1B_D
361
GGCGTTCGTTTCGGCG
323
CGCTTCTCCGACGCCC
324





LOC100132891_B
362
GCGGTTGAGTTTTTGG
325
CCCCGTATAACTAAAAAC
326




TCGG

GACGAC






MAST1_B
375
CGTTTTTTTTATGTAGT
327
AAACGACGACGAACGCC
328




AAGCGATTTTTCGC








MAX.chr12.427.br
338
GCGTTTTGGTTTTTTCG
329
GAACGACGAAACTAAAA
330




TTTCGAG

CCGC






MAX.chr17.73073
174
CGTTTTTTGGTAGTTTT
331
GCTTAAACGTAACCGAA
332




682-73073814

TTTCGAGTCGACGCC






MAX.chr20.4422
363
GGTTGCGCGTCGTTTT
333
CCCGACGCGTTTAAATC
334




TTC

GT






MPZ_5742
364
GGATGGGAATAGTTAA
335
TCCAACATTACATACAAC
336




GTTTTAGTCGTT

ACTAACGTC






MPZ_5554
365
GGTTAGGGGTGGAGTT
337
ACTCCGAACTCTACTCAT
338




CGTTA

CCTTTC






MSX2P1_B
366
TAGGTTGGAGATTTTG
339
CGAAACCTAAAAACGCC
340




ACGCG

GAAAC






ODC1_B
367
GGTTGGTAGTCGTTTT
341
CAAAACCCATCTAATTAC
342




TACGTTTTC

AAAATACCTCGA






OSR2_A
234
TGGAGTTATCGGAAGG
343
CGAACTCCCGAAACGAC
344




CGA

G






OTX1_B
368
GGAAATGGTTTAGAGT
345
TTCTAAAAAATACTTTCG
346




TTTGGATTTCG

ATACCGACA






PLXNC1_B
246
GTGGTTTGAAGAGTTG
347
GCCAAAAATTCGATTCCA
348




TTAGTTCGTTTAG

ACGCA






PRKCB_7570
369
AAGGTGGGTTGTTTGA
349
ACCCTCCGACAAAAAAA
350




AGAAGC

CGTAC






SCRT2_C
370
GCGAGAAGGTTTTGTC
351
ACCTACTCACGCACAAC
352




GTAGA

CT






SLC30A10
279
CGCGGTGAGGAAGAT
353
ACGCCACCTACGACTAC
354




CG

G






SPHK2_B
371
GTACGGTTATTGGTTG
355
CCGAATCCTCCTCCAAA
356




AGCGG

CG






ST8SIA4_B
372
GGAATTTAATTGGAGA
357
CCAAAATTTCCCTCATCT
358




GAAATTTTGGCG

ATATACGCC






STX16_C
373
GTTGCGGGTCGGGTT
359
GCAAAAACAAAAAACGC
360




GC

GTAAAAACC






TBX1_B
374
GTCGTCGTTGTCGTAG
361
CGTAAAAACCGAACGAC
362




TTGTC

GCG






TRH_A
303
TTTTCGTTGATTTTATT
363
GAACCCTCTTCAAATAAA
364




CGAGTCGTC

CCGC






TRIM67_B
328
GATTAAATAGTCGGGG
365
ATTCTCCAACGCCAACC
366




TCGCG

AC



















TABLE 7








SEQ


Gene
DMR

ID


Annotation
No.
Probe Sequence
NO:







ABLIM1_B
329
CGCGCCGAGG CGCGCTTCCACTCC/
367




3C6/






AJAP1_C
330
AGGCCACGGACG
368




GCGGCGTTTTTTTTTATGTTG/3C6/






ALOX5_B
331
AGGCCACGGACG
369




CAACCGAACTAAAAAAAAAAACTAACG/





3C6/






ASCL2_B
332
CGCGCCGAGG 
370




GCGCGTAAGATTTTCGG/3C6/






BANK1_B
333
CGCGCCGAGG GCGGGTAGTAGTGCG/
371




3C6/






BHLHE23_E
334
CGCGCCGAGG
372




CGACCGAAAAATCGAAAAACA/3C6/






C10orf125_B
335
CGCGCCGAGG
373




GCTAACGCGAATAAAACACG/3C6/






C17orf64_B
336
CGCGCCGAGG
374




TTTTCGTTTTCGGTTTCGG/3C6/






CALN1_1520
337
CGCGCCGAGG
375




CCGTACCTATTAACTCCG/3C6/






CALN1_B
 37
AGGCCACGGACG
376




TCGTTTTTTTTTTGCGGGT/3C6/






CD1D_1058
339
AGGCCACGGACG
377




CGTATTGGCGCGATTTAG/3C6/






CDH4_7890
340
AGGCCACGGACG
378




GTTCGAAAAAAACTCGACGAA/3C6/






CHST2_8128
341
AGGCCACGGACG
379




GCCGTTCTCTAACTTCCG/3C6/






CHST2_8384
342
AGGCCACGGACG
380




CCGAAATACGAACGCGA/3C6/






CHST2_9316
343
AGGCCACGGACG
381




TCGTTCCTCGATTTCGC/3C6/






CHST2_9470
344
AGGCCACGGACG
382




CGAATAAAACCTACGAAAAAAAACG/





3C6/






CLIC6_B
345
AGGCCACGGACG
383




GAAAACCGCAAAATCCTCG/3C6/






CXCL12_B
346
AGGCCACGGACG
384




CGCGAAATAAACCTATAATTAACTCA/





3C6/






DLX4_B
347
CGCGCCGAGG
385




CCGAACCAACACTCAAAAC/3C6/






DNM3_D
348
CGCGCCGAGG GCGCGTTTGGTTTGGT/
386




3C6/






EMX1_A
 74
AGGCCACGGACG AACGCGCTCCAACC/
387




3C6/






ESPN_B
349
CGCGCCGAGG
388




CGCGACGACTAAAAAAATTCA/3C6/






FAM59B_7764
350
AGGCCACGGACG
389




GTCGAAATCGAAACGCTC/3C6/






FOXP4_B
351
CGCGCCGAGG CCGCGACTACCTCTTC/
390




3C6/






GP5
104
AGGCCACGGACG
391




CGACGTCCTACAAAACCA/3C6/






HOXA1_C
352
CGCGCCGAGG GGCGGTAGTTGTTGC/
392




3C6/






IGF2BP3_C
353
CGCGCCGAGG GCGAAAACCCCGCC/
393




3C6/






IPTRIPL1_1138
354
CGCGCCGAGG
394




CGTCTAACTAAACGCGATAAAC/3C6/






IPTRIPL1_1200
355
CGCGCCGAGG
395




GCGGTTTTAGCGATGAATC/3C6/






KCNK9_B
356
CGCGCCGAGG CGATTCGAGGGCGT/
396




3C6/






KCNK17_C
357
AGGCCACGGACG 
397




CGCGACGCAAAACTC/3C6/






KLHDC7B_B
358
AGGCCACGGACG GCGGCGGTTGGATT/
398




3C6/






LAYN_B
359
AGGCCACGGACG
399




TCCCGAAACGAACGATAAA/3C6/






LIME1_B
360
CGCGCCGAGG CGCCGTCGCACTAC/
400




3C6/






LMX1B_D
361
AGGCCACGGACG CGCGACTCCCCACT/
401




3C6/






LOC100132891_
362
AGGCCACGGACG
402


B

CGCAAATAATAACGCGAACG/3C6/






MAST1_B
375
AGGCCACGGACG
403




CGTTCGAGGTTAGTTTTTTGG/3C6/






MAX.chr12.427.b
338
AGGCCACGGACG 
404


r

CGTACGTAACCCGCG/3C6/






MAX.chr17.7307
174
CGCGCCGAGG
405


3682-73073814

CGCTACTAACCATAACCGC/3C6/






MAX.chr20.4422
363
CGCGCCGAGG
406




CGTTTTCGTTTGATTCGGTT/3C6/






MPZ_5742
364
CGCGCCGAGG
407




TCGGTGATTGATGTGTGCG/3C6/






MPZ_5554
365
CGCGCCGAGG
408




CGTAACTCCATCTCGATAACC/3C6/






MSX2P1_B
366
CGCGCCGAGG CGACCGCGAAAAAACG/
409




3C6/






ODC1_B
367
AGGCCACGGACG
410




CGCGTTGGAAGTTTCG/3C6/






OSR2_A
234
CGCGCCGAGG GCGCGAACACAAAACG/
411




3C6/






OTX1_B
368
CGCGCCGAGG 
412




ACCGAAAACGCCCTAAA/3C6/






PLXNC1_B
246
CGCGCCGAGG
413




GCGTGGAGAAATGTTAGTTTG/3C6/






PRKCB_7570
369
AGGCCACGGACG
414




CGGGCGGTGAATTTGT/3C6/






SCRT2_C
370
AGGCCACGGACG
415




ACGTCGTATTTGTGGCG/3C6/






SLC30A10
279
AGGCCACGGACG 
416




GCGTTGTTTAGCGCG/3C6/






SPHK2_B
371
AGGCCACGGACG
417




GATCCCGCAAATCAACAC/3C6/






ST8SIA4_B
372
CGCGCCGAGG CGATCCCCAACTCCC/
418




3C6/






STX16_C
373
CGCGCCGAGG
419




CGCTTCTAAAACCTCGATCC/3C6/






TBX1_B
374
CGCGCCGAGG
420




CGCGGTCGTTAATATGTATTC/3C6/






TRH_A
303
AGGCCACGGACG
421




CGTTTGGCGTAGATATAAGC/3C6/






TRIM67_B
328
AGGCCACGGACG
422




CGAACTACGAAAACAACCTC/3C6/



















TABLE 8





Marker
DMR
Marker
DMR


















AJAP1_C
330
CHST2_9316
343


C10orf125_B
335
ASCL2_B
332


CALN1_B
37
ESPN_B
349


BHLHE23_E
334
DLX4_B
347


CD1D_1058
339
KCNK17_C
357


HOXA1_C
352
EMX1_A
74


LOC100132891_B
362
MPZ_5742
364


MSX2P1_B
366
LAYN_B
359


PRKCB_7570
369
KCNK9_B
356


ITPRIPL1_1200
355
ABLIM1_B
329


SPHK2_B
371
MAX.chr12.427.br
338


C17orf64_B
336
SCRT2_C
370


TRIM67_B
328
IGF2BP3_C
353


MAX.chr20.4422
363
MAST1_B
375


DNM3_D
348
MAX.chr17.73073682-73073814
174


ODC1_B
367
OTX1_B
368


OSR2_A
234
ST8SIA4_B
372


SLC30A10
279
CXCL12_B
346


TRH_A
303
LIME1_B
360


ALOX5_B
331
TBX1_B
374


PLXNC1_B
246
STX16_C
373


CDH4_7890
340
FOXP4_B
351


CLIC6_B
345
CALN1_1520
337


LMX1B_D
361
ITPRIPL1_1138
354


FAM59B_7764
350
CHST2_8128
341


GP5
104
CHST2_8384
342


BANK1_B
333
CHST2_9470
344


KLHDC7B_B
358
MPZ_5554
365









A collection of 38 normal breast cancer samples were tested for presence of the 56 methylation markers. The 56 markers displayed a range of sensitivities from ˜15% to 92% at 95% specificity. Table 9 shows the markers demonstrating sensitivity at or above 25% at 95% specificity. A 5 marker panel (SPHK2, c17orf64_B, DLX4_B, MPZ_5742, ITPRIPL1_1138) showed 96% sensitivity at 100% specificity. The resulting ROC curve had an AUC of 0.995.













TABLE 9







Marker
DMR No.
Sensitivity




















AJAP1_C
330
66.30%



C10orf125_B
335
58.40%



CALN1_B
37
69.70%



BHLHE23_E
334
43.80%



CD1D_1058
339
68.50%



HOXA1_C
352
62.90%



LOC100132891_B
362
79.80%



MSX2P1_B
366
79.80%



PRKCB_7570
369
86.50%



ITPRIPL1_1200
355
79.80%



SPHK2_B
371
65.20%



C17orf64_B
336
77.50%



TRIM67_B
328
79.80%



MAX.chr20.4422
363
71.90%



CHST2_9316
343
73.00%



ASCL2_B
332
53.90%



ESPN_B
349
67.40%



DLX4_B
347
83.10%



KCNK17_C
357
55.10%



EMX1_A
74
77.50%



MPZ_5742
364
91.00%



LAYN_B
359
57.30%



KCNK9_B
356
62.90%



ABLIM1_B
329
44.90%



MAX.chr12.427.br
338
79.80%



SCRT2_C
370
78.70%



IGF2BP3_C
353
70.80%



MAST1_B
375
77.50%



DNM3 _D
348
74.20%



ODC1_B
367
65.20%



OSR2_A
234
70.80%



SLC30A10
279
60.70%



TRH_A
303
85.40%



ALOX5_B
331
59.60%



PLXNC1_B
246
61.80%



CDH4_7890
340
71.90%



CLIC6_B
345
48.30%



LMX1B_D
361
56.20%



FAM59B_7764
350
66.30%



GP5
104
61.80%



BANK1_B
333
43.80%



OTX1_B
368
70.80%



ST8SIA4_B
372
40.40%



CXCL12_B
346
56.20%



LIME1_B
360
47.20%



STX16_C
373
52.80%



FOXP4_B
351
36.00%



CALN1_1520
337
66.30%



ITPRIPL1_1138
354
83.10%



CHST2_8128
341
62.90%



CHST2_8384
342
60.70%



CHST2_9470
344
66.30%



MPZ_5554
365
92.10%










Based on the results of the tissue testing, a set of 28 markers were selected to test on a set of plasma samples collected from breast cancer patients and normal controls. The 28 markers were split into two pools of 14 due to the high number of markers to be tested. The markers in the two pools are shown in Tables 10 and 11 below.









TABLE 10





Pool 7 Breast Cancer Plasma Markers


















AJAP1
C10orf125



CALN1_B
BHLHE23



LOC100132891
MSX2P1



SPHK2
C17orf64



MAST1
DNM3



MAX.chr.12.427.br
OTX1



SCRT2
ALOX5

















TABLE 11





Pool 8 Breast Cancer Plasma Markers


















FAM59B
ITPRIPL1_B



ODC1_B
OSR2_A



CD1D_B
DLX4_2591



PRKCB_7570
MAX.chr20.4422



TRIM67
MPZ



TRH_A
CXCL12_B



EMX1_br
CHST2_B










The testing of Pool 7 markers was done on a collection of EDTA plasma samples comprised of 85 breast cancer samples (33 stage I, 33 stage II, 18 stage III, and 1 stage IV) and 100 healthy normal controls. The testing of Pool 8 markers was done on a similar collection of EDTA plasma samples comprised of 85 breast cancer samples (34 stage I, 32 stage II, 18 stage III and 1 stage IV) and 100 healthy normal controls. Based on the results of the Pool 7 and Pool 8 testing, a collection of 14 assays were selected for further testing (shown in Table 12).









TABLE 12





Pool 9 Breast Cancer Plasma Markers


















SPHK2
C17orf64



FAM59B
ITPRIPL1_B



ODC1_B
OSR2_A



TRIM67
MPZ



TRH_A
CXCL12_B



CD1D_B
C10orf125



CALN1_B
CHST2_B










The testing of Pool 9 markers was done on a collection of LBgard (Biomatrica, San Diego, Calif.) plasma samples comprised of 42 breast cancer samples (1 stage I, 16 stage II, 14 stage III, and 11 stage IV) and 84 healthy normal controls. Table 13 shows the identified methylated region for the Pool 9 markers. Table 14 shows the exhibited sensitivity and 90% specificity for the Pool 9 markers. Tables 15 and 16 show the primer information, and probe information for the Pool 9 markers. A collection of 4 markers (FAM59B, ITPRIPL1, TRH_A, and C17orf64_B) exhibited a sensitivity of 74% at 90% specificity. The resulting ROC curve exhibited an AUC of 0.884.











TABLE 13






Gene
Region on Chromosome


DMR No.
Annotation
(starting base-ending base)

















47
CD1D
chr1: 158150864-158151129


134
ITPRIPL1
chr2: 96990968-96991328


90
FAM59B
chr2: 26407713-26407972


27
C10orf125
chr10: 135171410-135171504


305
TRIM67
chr1: 231297047-231297159


284
SPHK2
chr19: 49127580-49127683


37
CALN1_B
chr7: 71801741-71801800


57
CHST2_B
chr3: 142839223-142839568


221
MPZ
chr1: 161275561-161275996


346
CXCL12_B
chr10: 44881200-44881315


367
ODC1_B
chr2: 10589075-10589225


234
OSR2_A
chr8: 99952233-99952366


303
TRH_A
chr3: 129693484-129693575


336
C17orf64_B
chr17: 58499085-58499196





















TABLE 14







Marker Name
AUC
Sens @ 90% sp
DMR No.





















FAM59B
0.814
50.0%
90



ITPRIPL1
0.804
61.9%
134



ODC1_B
0.809
59.5%
367



OSR2_A
0.749
42.9%
234



TRIM67
0.669
30.9%
305



MPZ
0.698
47.6%
221



TRH_A
0.83
50.0%
303



CXCL12_B
0.71
28.6%
346



SPHK2
0.585
31.0%
284



C17orf64_B
0.763
59.5%
336



CD1D
0.613
33.3%
47



C10orf125
0.775
45.2%
27



CALN1_B
0.622
26.2%
37



CHST2_B
0.687
38.1%
57






















TABLE 15







Forward
SEQ
Reverse
SEQ


Gene
DMR
Primer
ID
Primer
ID


Annotation
No.
5′-3′
NO:
5′-3′
NO:







CD1D
 47
GGATTGGTGA
423
CCCGAAACCAAA
424




GATTCGGGAC

AAACAACGA






ITPRIPL1
134
GAGTAGGGTT
425
CTACTTTTTTCC
426




ATTTTCGCGG

CGACAAAATAAA





G

AACGT






FAM59B
 90
CGCGATAGCG
427
CGCACGACCGT
428




TTTTTTATTGT

AAAATACTCG





CGCG








C10orf125
 27
CGGTTCGTTG
429
CCCCCGAACTAC
430




CGTTTATCGA

TCTACGCG






TRIM67
305
GATTAAATAGT
431
ATTCTCCAACGC
432




CGGGGTCGC

CAACCAC





G








SPHK2
284
GTACGGTTAT
433
CCGAATCCTCCT
434




TGGTTGAGCG

CCAAACG





G








CALN1_B
 37
TCGTTCGGCG
273
CGCGAAAAACTT
274




TATTTATTTCG

CCTCCGA





TAT








CHST2_B
 57
GGGATTTTTA
437
CGACGAACTATC
438




GCGGAAGCGA

CGACTATCACT






MPZ
221
GGTTAGGGGT
439
ACTCCGAACTCT
440




GGAGTTCGTT

ACTCATCCTTTC





A








CXCL12_B
346
TCGGCGGTTT
441
AAATCTCCCGTC
442




TTAGTAAAAG

CCACTCC





CG








ODC1_B
367
GGTTGGTAGT
443
CAAAACCCATCT
444




CGTTTTTACGT

AATTACAAAATA





TTTC

CCTCGA






OSR2_A
234
TGGAGTTATC
445
CGAACTCCCGAA
446




GGAAGGCGA

ACGACG






TRH_A
303
TTTTCGTTGAT
447
GAACCCTCTTCA
448




TTTATTCGAGT

AATAAACCGC





CGTC








C17orf64_B
336
GATTATATTCG
449
GACTCTTCCTAC
450




GATTTTGTTTA

CCGCGA





TCGCGT



















TABLE 16








SEQ


Gene
DMR

ID


Annotation
No.
Probe Sequence
NO:







CD1D
 47
AGGCCACGGACG
451




CGTATTGGCGCGATTTAG/3C6/






ITPRIPL1
134
CGCGCCGAGG
452




GCGGTTTTAGCGATGAATC/3C6/






FAM59B
 90
AGGCCACGGACG
453




GTCGAAATCGAAACGCTC/3C6/






C10orf125
 27
CGCGCCGAGG
454




GCTAACGCGAATAAAACACG/3C6/






TRIM67
305
AGGCCACGGACG
455




CGAACTACGAAAACAACCTC/3C6/






SPHK2
284
AGGCCACGGACG
456




GATCCCGCAAATCAACAC/3C6/






CALN1_B
 37
AGGCCACGGACG
376




TCGTTTTTTTTTTGCGGGT/3C6/






CHST2_B
 57
CGCGCCGAGG
458




TCGTTCCTCGATTTCGC/3C6/






MPZ
221
CGCGCCGAGG
459




CGTAACTCCATCTCGATAACC/3C6/






CXCL12_B
346
CGCGCCGAGG
460




CGCGAAATAAACCTATAATTAACTCA/





3C6/






ODC1_B
367
AGGCCACGGACG
461




CGCGTTGGAAGTTTCG/3C6/






OSR2_A
234
CGCGCCGAGG
462




GCGCGAACACAAAACG/3C6/






TRH_A
303
AGGCCACGGACG
463




CGTTTGGCGTAGATATAAGC/3C6/






C17orf64_B
336
CGCGCCGAGG
464




TTTTCGTTTTCGGTTTCGG/3C6/









Having now fully described the invention, it will be understood by those of skill in the art that the same can be performed within a wide and equivalent range of conditions, formulations, and other parameters without affecting the scope of the invention or any embodiment thereof. All patents, patent applications and publications cited herein are fully incorporated by reference herein in their entirety.


INCORPORATION BY REFERENCE

The entire disclosure of each of the patent documents and scientific articles referred to herein is incorporated by reference for all purposes.


Equivalents

The invention may be embodied in other specific forms without departing from the spirit or essential characteristics thereof. The foregoing embodiments are therefore to be considered in all respects illustrative rather than limiting the invention described herein. Scope of the invention is thus indicated by the appended claims rather than by the foregoing description, and all changes that come within the meaning and range of equivalency of the claims are intended to be embraced therein.

Claims
  • 1. A method, comprising: measuring a methylation level for one or more genes in a biological sample of a human individual through treating genomic DNA in the biological sample with a reagent that modifies DNA in a methylation-specific manner;amplifying the treated genomic DNA using a set of primers for the selected one or more genes; anddetermining the methylation level of the one or more genes by polymerase chain reaction, nucleic acid sequencing, mass spectrometry, methylation-specific nuclease, mass-based separation, and target capture; wherein the one or more genes comprises a chromosomal region having an annotation that is selected from one of the following groups:(i) ATP6V1B1, LMX1B_A, BANK1, OTX1, MAX.chr11.14926602-14927148, UBTF, PRKCB, TRH_A, MPZ, DNM3_A, TRIM67, MAX.chr12.4273906-4274012, CALN1_A, ITPRIPL1, MAX.chr12.4273906-4274012, GYPC_B, MAX.chr5.42994866-42994936, OSR2_A, SCRT2_B, MAX.chr5.145725410-145725459, MAX.chr11.68622869-68622968, MAX.chr8.124173030-124173395, MAX.chr20.1784209-1784461, LOC100132891, BHLHE23_D, MAX.chr19.46379903-46380197, CHST2_B, MAX.chr5.77268672-77268725, C17orf64, EMX1_A, DSCR6, ITPRIPL1, IGF2BP3_B, DLX4, and ABLIM1;(ii) ABLIM1_B, AJAP1_C, ALOX5_B, ASCL2_B, BANK1_B, BHLHE23_E, C10orf125_B, C17orf64_B, CALN1_1520, CALN1_B, CD1D_1058, CDH4_7890, CHST2_8128, CHST2_8384, CHST2_9316, CHST2_9470, CLIC6_B, CXCL12_B, DLX4_B, DNM3_D, EMX1_A, ESPN_B, FAM59B_7764, FOXP4_B, GP5, HOXA1_C, IGF2BP3_C, IPTRIPL1_1138, IPTRIPL1_1200, KCNK9_B, KCNK17_C, LAYN_B, LIME1_B, LMX1B_D, LOC100132891_B, MAST1_B, MAX.chr12.427.br, MAX.chr20.4422, MPZ_5742, MPZ_5554, MSX2P1_B, ODC1_B, OSR2_A, OTX1_B, PLXNC1_B, PRKCB_7570, SCRT2_C, SLC30A10, SPHK2_B, ST8SIA4_B, STX16_C, TRH_A, and TRIM67_B; and(iii) CD1D, ITPRIPL1, FAM59B, C10orf125, TRIM67, SPHK2, CALN1_B, CHST2_B, MPZ, CXCL12_B, ODC1_B, OSR2_A, TRH_A, and C17orf64_B.
  • 2. The method of claim 1, wherein the DNA is treated with a reagent that modifies DNA in a methylation-specific manner.
  • 3. The method of claim 2, wherein the reagent comprises one or more of a methylation-sensitive restriction enzyme, a methylation-dependent restriction enzyme, and a bisulfite reagent.
  • 4. The method of claim 3, wherein the DNA is treated with a bisulfite reagent to produce bisulfite-treated DNA.
  • 5. The method of claim 1, wherein the measuring comprises multiplex amplification.
  • 6. The method of claim 1, wherein measuring the amount of at least one methylated marker gene comprises using one or more methods selected from the group consisting of methylation-specific PCR, quantitative methylation-specific PCR, methylation-specific DNA restriction enzyme analysis, quantitative bisulfite pyrosequencing, flap endonuclease assay, PCR-flap assay, and bisulfite genomic sequencing PCR.
  • 7. The method of claim 1, wherein the sample comprises one or more of a plasma sample, a blood sample, or a tissue sample (e.g., breast tissue).
  • 8. The method of claim 1, wherein the set of primers for the selected one or more genes is selected from the group consisting of:for ATP6V1B1 a set of primers consisting of SEQ ID NOS: 13 and 14for LMX1B_A a set of primers consisting of SEQ ID NOS: 115 and 116,for BANK1 a set of primers consisting of SEQ ID NOS: 15 and 16for OTX1 a set of primers consisting of SEQ ID NOS: 189 and 190for MAX.chr11.14926602-14927148 a set of primers consisting of SEQ ID NOS: 129 and 130for UBTF a set of primers consisting of SEQ ID NOS: 249 and 250for PRKCB a set of primers consisting of SEQ ID NOS: 201 and 202,for TRH_A a set of primers consisting of SEQ ID NOS: 245 and 246,for MPZ a set of primers selected from the group consisting of SEQ ID NOS: 175 and 176 and SEQ ID NOS: 439 and 440,for DNM3_A a set of primers consisting of SEQ ID NOS: 55 and 56,for TRIM67 a set of primers consisting of SEQ ID NOS: 247 and 248,for MAX.chr12.4273906-4274012 a set of primers selected from the group consisting of SEQ ID NOS: 133 and 134 and SEQ ID NOS: 135 and 136,for CALN1_A a set of primers consisting of SEQ ID NOS: 29 and 30,for ITPRIPL1 a set of primers selected from the group consisting of from SEQ ID NOS: 97 and 98, SEQ ID NOS: 99 and 100 and SEQ ID NOS: 425 and 426,for GYPC_B a set of primers consisting of SEQ ID NOS: 81 and 82,for MAX.chr5.42994866-42994936 a set of primers consisting of SEQ ID NOS: 159 and 160,for OSR2_A a set of primers consisting of SEQ ID NOS: 187 and 188,for SCRT2_B a set of primers consisting of SEQ ID NOS: 211 and 212,for MAX.chr5.145725410-145725459 a set of primers consisting of SEQ ID NOS: 157 and 158,for MAX.chr11.68622869-68622968 a set of primers consisting of SEQ ID NOS: 131 and 132,for MAX.chr8.124173030-124173395 a set of primers consisting of SEQ ID NOS: 165 and 166,for MAX.chr20.1784209-1784461 a set of primers selected from the group consisting of SEQ ID NOS: 151 and 152 and SEQ ID NOS: 153 and 154,for LOC100132891 a set of primers selected from the group consisting of SEQ ID NOS: 117 and 118 or SEQ ID NOS: 119 and 120,for BHLHE23_D a set of primers consisting of SEQ ID NOS:SEQ ID NOS: 21 and 22,for MAX.chr19.46379903-46380197 a set of primers selected from the group consisting of SEQ ID NOS: 145 and 146 and SEQ ID NOS: 147 and 148,for CHST2_B a set of primers consisting of and SEQ ID NOS: 39 and 40, for MAX.chr5.77268672-77268725 a set of primers consisting of SEQ ID NOS: 161 and 162,for C17orf64 a set of primers consisting of SEQ ID NOS: 25 and 26,for EMX1_A a set of primers consisting of SEQ ID NOS: 61 and 62,for DSCR6 a set of primers consisting of SEQ ID NOS: 57 and 58,for IGF2BP3_B a set of primers consisting of SEQ ID NOS: 93 and 94,for DLX4 a set of primers consisting of SEQ ID NOS: 51 and 52,for ABLIM1 a set of primers consisting of SEQ ID NOS: 3 and 4,ABLIM1_B a set of primers consisting of SEQ ID NOS: 255 and 256,AJAP1_C a set of primers consisting of SEQ ID NOS: 257 and 258,ALOX5_B a set of primers consisting of SEQ ID NOS: 259 and 260,ASCL2_B a set of primers consisting of SEQ ID NOS: 261 and 262,BANK1_B a set of primers consisting of SEQ ID NOS: 263 and 264,BHLHE23_E a set of primers consisting of SEQ ID NOS: 265 and 266,C10orf125_B a set of primers consisting of SEQ ID NOS: 267 and 268,C17orf64_B a set of primers selected from the group consisting of SEQ ID NOS: 269 and 270 and SEQ ID NOS: 449 and 450,CALN1_1520 a set of primers consisting of SEQ ID NOS: 271 and 272,CALN1_B a set of primers consisting of SEQ ID NOS: 273 and 274,CD1D_1058 a set of primers consisting of SEQ ID NOS: 275 and 276,CDH4_7890 a set of primers consisting of SEQ ID NOS: 277 and 278,CHST2_8128 a set of primers consisting of SEQ ID NOS: 279 and 280,CHST2_8384 a set of primers consisting of SEQ ID NOS: 281 and 282,CHST2_9316 a set of primers consisting of SEQ ID NOS: 283 and 284,CHST2_9470 a set of primers consisting of SEQ ID NOS: 285 and 286,CLIC6_B a set of primers consisting of SEQ ID NOS: 287 and 288,CXCL12_B a set of primers selected from the group consisting of SEQ ID NOS: 289 and 290 and SEQ ID NOS: 441 and 442,for DLX4_B a set of primers consisting of SEQ ID NOS: 291 and 292,for DNM3_D a set of primers consisting of SEQ ID NOS: 293 and 294,for EMX1_A a set of primers consisting of SEQ ID NOS: 295 and 296,for ESPN_B a set of primers consisting of SEQ ID NOS: 277 and 298,for FAM59B_7764 a set of primers consisting of SEQ ID NOS: 299 and 300,for FOXP4_B a set of primers consisting of SEQ ID NOS: 301 and 302,for GP5 a set of primers consisting of SEQ ID NOS: 303 and 304,for HOXA1_C a set of primers consisting of SEQ ID NOS: 305 and 306,for IGF2BP3_C a set of primers consisting of SEQ ID NOS: 307 and 308,for IPTRIPL1_1138 a set of primers consisting of SEQ ID NOS: 309 and 310,for IPTRIPL1_1200 a set of primers consisting of SEQ ID NOS: 311 and 312,for KCNK9_B a set of primers consisting of SEQ ID NOS: 313 and 314,for KCNK17_C a set of primers consisting of SEQ ID NOS: 315 and 316,for LAYN_B a set of primers consisting of SEQ ID NOS: 319 and 320,for LIME1_B a set of primers consisting of SEQ ID NOS: 321 and 322,for LMX1B_D a set of primers consisting of SEQ ID NOS: 323 and 324,for LOC100132891_B a set of primers consisting of SEQ ID NOS: 325 and 326,for MAST1_B a set of primers consisting of SEQ ID NOS: 327 and 328,for MAX.chr12.427.br a set of primers consisting of SEQ ID NOS: 329 and 330,for MAX.chr20.4422 a set of primers consisting of SEQ ID NOS: 333 and 334,for MPZ_5742 a set of primers consisting of SEQ ID NOS: 335 and 336,for MPZ_5554 a set of primers consisting of SEQ ID NOS: 337 and 338,for MSX2P1_B a set of primers consisting of SEQ ID NOS: 339 and 340,for ODC1_B a set of primers selected from the group consisting of SEQ ID NOS: 341 and 342 and SEQ ID NOS: 443 and 444,for OSR2_A a set of primers selected from the group consisting of SEQ ID NOS: 343 and 344 and SEQ ID NOS: 445 and 446,for OTX1_B a set of primers consisting of SEQ ID NOS: 345 and 346,for PLXNC1_B a set of primers consisting of SEQ ID NOS: 347 and 348,for PRKCB_7570 a set of primers consisting of SEQ ID NOS: 349 and 350,for SCRT2_C a set of primers consisting of SEQ ID NOS: 351 and 352,for SLC30A10 a set of primers consisting of SEQ ID NOS: 353 and 354,for SPHK2_B a set of primers consisting of SEQ ID NOS: 355 and 356,for ST8SIA4_B a set of primers consisting of SEQ ID NOS: 357 and 358,for STX16_C a set of primers consisting of SEQ ID NOS: 359 and 360,for TRH_A a set of primers selected from the group consisting of SEQ ID NOS: 363 and 364 and SEQ ID NOS: 47 and 448,for TRIM67_B a set of primers consisting of SEQ ID NOS: 365 and 366,for CD1D a set of primers consisting of SEQ ID NOS: 423 and 424,for FAM59B a set of primers consisting of SEQ ID NOS: 427 and 428,for C10orf125 a set of primers consisting of SEQ ID NOS: 429 and 430,for TRIM67 a set of primers consisting of SEQ ID NOS: 431 and 432,for SPHK2 a set of primers consisting of SEQ ID NOS: 433 and 434,for CALN1_B a set of primers consisting of SEQ ID NOS: 273 and 274, andfor CHST2_B a set of primers consisting of SEQ ID NOS: 437 and 438.
  • 9. A method of characterizing a sample, comprising: a) measuring an amount of at least one methylated marker gene in DNA extracted from the sample, wherein the one or more genes comprises a chromosomal region having an annotation that is selected from one of the following groups: (i) ATP6V1B1, LMX1B_A, BANK1, OTX1, MAX.chr11.14926602-14927148, UBTF, PRKCB, TRH_A, MPZ, DNM3_A, TRIM67, MAX.chr12.4273906-4274012, CALN1_A, ITPRIPL1, MAX.chr12.4273906-4274012, GYPC_B, MAX.chr5.42994866-42994936, OSR2_A, SCRT2_B, MAX.chr5.145725410-145725459, MAX.chr11.68622869-68622968, MAX.chr8.124173030-124173395, MAX.chr20.1784209-1784461, LOC100132891, BHLHE23_D, MAX.chr19.46379903-46380197, CHST2_B, MAX.chr5.77268672-77268725, C17orf64, EMX1_A, DSCR6, ITPRIPL1, IGF2BP3_B, DLX4, and ABLIM1;(ii) ABLIM1_B, AJAP1_C, ALOX5_B, ASCL2_B, BANK1_B, BHLHE23_E, C10orf125_B, C17orf64_B, CALN1_1520, CALN1_B, CD1D_1058, CDH4_7890, CHST2_8128, CHST2_8384, CHST2_9316, CHST2_9470, CLIC6_B, CXCL12_B, DLX4_B, DNM3_D, EMX1_A, ESPN_B, FAM59B_7764, FOXP4_B, GP5, HOXA1_C, IGF2BP3_C, IPTRIPL1_1138, IPTRIPL1_1200, KCNK9_B, KCNK17_C, LAYN_B, LIME1_B, LMX1B_D, LOC100132891_B, MAST1_B, MAX.chr12.427.br, MAX.chr20.4422, MPZ_5742, MPZ_5554, MSX2P1_B, ODC1_B, OSR2_A, OTX1_B, PLXNC1_B, PRKCB_7570, SCRT2_C, SLC30A10, SPHK2_B, ST8SIA4_B, STX16_C, TRH_A, and TRIM67_B; and(iii) CD1D, ITPRIPL1, FAM59B, C10orf125, TRIM67, SPHK2, CALN1_B, CHST2_B, MPZ, CXCL12_B, ODC1_B, OSR2_A, TRH_A, and C17orf64_B;b) measuring the amount of at least one reference marker in the DNA; andc) calculating a value for the amount of the at least one methylated marker gene measured in the DNA as a percentage of the amount of the reference marker gene measured in the DNA, wherein the value indicates the amount of the at least one methylated marker DNA measured in the sample.
  • 10. The method of claim 9, wherein the at least one reference marker comprises one or more reference marker selected from B3GALT6 DNA and β-actin DNA.
  • 11. The method of claim 9, wherein the sample comprises one or more of a plasma sample, a blood sample, or a tissue sample (e.g., breast tissue).
  • 12. The method of claim 9, wherein the one or more genes comprises a base in a differentially methylated region (DMR) selected from a group consisting of DMR 1-375 from Tables 2 and 5.
  • 13. The method of claim 9, wherein the DNA is treated with a reagent that modifies DNA in a methylation-specific manner.
  • 14. The method of claim 13, wherein the reagent comprises one or more of a methylation-sensitive restriction enzyme, a methylation-dependent restriction enzyme, and a bisulfite reagent.
  • 15. The method of claim 14, wherein the DNA is treated with a bisulfite reagent to produce bisulfite-treated DNA.
  • 16. The method of claim 14, wherein the modified DNA is amplified using a set of primers for the selected one or more genes.
  • 17. The method of claim 16, wherein the set of primers for the selected one or more genes is selected from the group consisting of:for ATP6V1B1 a set of primers consisting of SEQ ID NOS: 13 and 14for LMX1B_A a set of primers consisting of SEQ ID NOS: 115 and 116,for BANK1 a set of primers consisting of SEQ ID NOS: 15 and 16for OTX1 a set of primers consisting of SEQ ID NOS: 189 and πfor MAX.chr11.14926602-14927148 a set of primers consisting of SEQ ID NOS: 29 and 130for UBTF a set of primers consisting of SEQ ID NOS: 249 and 250for PRKCB a set of primers consisting of SEQ ID NOS: 201 and 202,for TRH_A a set of primers consisting of SEQ ID NOS: 245 and 246,for MPZ a set of primers selected from the group consisting of SEQ ID NOS: 175 and 176 and SEQ ID NOS: 439 and 440,for DNM3_A a set of primers consisting of SEQ ID NOS: 55 and 56,for TRIM67 a set of primers consisting of SEQ ID NOS: 247 and 248,for MAX.chr12.4273906-4274012 a set of primers selected from the group consisting of SEQ ID NOS: 133 and 134 and SEQ ID NOS: 135 and 136,for CALN1_A a set of primers consisting of SEQ ID NOS: 29 and 30,for ITPRIPL1 a set of primers selected from the group consisting of from SEQ ID NOS: 97 and 98, SEQ ID NOS: 99 and 100 and SEQ ID NOS: 425 and 426,for GYPC_B a set of primers consisting of SEQ ID NOS: 81 and 82,for MAX.chr5.42994866-42994936 a set of primers consisting of SEQ ID NOS: 159 and 160,for OSR2_A a set of primers consisting of SEQ ID NOS: 187 and 188,for SCRT2_B a set of primers consisting of SEQ ID NOS: 211 and 212,for MAX.chr5.145725410-145725459 a set of primers consisting of SEQ ID NOS: 157 and 158,for MAX.chr11.68622869-68622968 a set of primers consisting of SEQ ID NOS: 131 and 132,for MAX.chr8.124173030-124173395 a set of primers consisting of SEQ ID NOS: 165 and 166,for MAX.chr20.1784209-1784461 a set of primers selected from the group consisting of SEQ ID NOS: 151 and 152 and SEQ ID NOS: 153 and 154,for LOC100132891 a set of primers selected from the group consisting of SEQ ID NOS: 117 and 118 or SEQ ID NOS: 119 and 120,for BHLHE23_D a set of primers consisting of SEQ ID NOS:SEQ ID NOS: 21 and 22,for MAX.chr19.46379903-46380197 a set of primers selected from the group consisting of SEQ ID NOS: 145 and 146 and SEQ ID NOS: 147 and 148,for CHST2_B a set of primers consisting of and SEQ ID NOS: 39 and 40, for MAX.chr5.77268672-77268725 a set of primers consisting of SEQ ID NOS: 161 and 162,for C17orf64 a set of primers consisting of SEQ ID NOS: 25 and 26,for EMX1_A a set of primers consisting of SEQ ID NOS: 61 and 62,for DSCR6 a set of primers consisting of SEQ ID NOS: 57 and 58,for IGF2BP3_B a set of primers consisting of SEQ ID NOS: 93 and 94,for DLX4 a set of primers consisting of SEQ ID NOS: 51 and 52,for ABLIM1 a set of primers consisting of SEQ ID NOS: 3 and 4,ABLIM1_B a set of primers consisting of SEQ ID NOS: 255 and 256,AJAP1_C a set of primers consisting of SEQ ID NOS: 257 and 258,ALOX5_B a set of primers consisting of SEQ ID NOS: 259 and 260,ASCL2_B a set of primers consisting of SEQ ID NOS: 261 and 262,BANK1_B a set of primers consisting of SEQ ID NOS: 263 and 264,BHLHE23_E a set of primers consisting of SEQ ID NOS: 265 and 266,C10orf125_B a set of primers consisting of SEQ ID NOS: 267 and 268,C17orf64_B a set of primers selected from the group consisting of SEQ ID NOS: 269 and 270 and SEQ ID NOS: 449 and 450,CALN1_1520 a set of primers consisting of SEQ ID NOS: 271 and 272,CALN1_B a set of primers consisting of SEQ ID NOS: 273 and 274,CD1D_1058 a set of primers consisting of SEQ ID NOS: 275 and 276,CDH4_7890 a set of primers consisting of SEQ ID NOS: 277 and 278,CHST2_8128 a set of primers consisting of SEQ ID NOS: 279 and 280,CHST2_8384 a set of primers consisting of SEQ ID NOS: 281 and 282,CHST2_9316 a set of primers consisting of SEQ ID NOS: 283 and 284,CHST2_9470 a set of primers consisting of SEQ ID NOS: 285 and 286,CLIC6_B a set of primers consisting of SEQ ID NOS: 287 and 288,CXCL12_B a set of primers selected from the group consisting of SEQ ID NOS: 289 and 290 and SEQ ID NOS: 441 and 442,for DLX4_B a set of primers consisting of SEQ ID NOS: 291 and 292,for DNM3_D a set of primers consisting of SEQ ID NOS: 293 and 294,for EMX1_A a set of primers consisting of SEQ ID NOS: 295 and 296,for ESPN_B a set of primers consisting of SEQ ID NOS: 277 and 298,for FAM59B_7764 a set of primers consisting of SEQ ID NOS: 299 and 300,for FOXP4_B a set of primers consisting of SEQ ID NOS: 301 and 302,for GP5 a set of primers consisting of SEQ ID NOS: 303 and 304,for HOXA1_C a set of primers consisting of SEQ ID NOS: 305 and 306,for IGF2BP3_C a set of primers consisting of SEQ ID NOS: 307 and 308,for IPTRIPL1_1138 a set of primers consisting of SEQ ID NOS: 309 and 310,for IPTRIPL1_1200 a set of primers consisting of SEQ ID NOS: 311 and 312,for KCNK9_B a set of primers consisting of SEQ ID NOS: 313 and 314,for KCNK17_C a set of primers consisting of SEQ ID NOS: 315 and 316,for LAYN_B a set of primers consisting of SEQ ID NOS: 319 and 320,for LIME1_B a set of primers consisting of SEQ ID NOS: 321 and 322,for LMX1B_D a set of primers consisting of SEQ ID NOS: 323 and 324,for LOC100132891_B a set of primers consisting of SEQ ID NOS: 325 and 326,for MAST1_B a set of primers consisting of SEQ ID NOS: 327 and 328,for MAX.chr12.427.br a set of primers consisting of SEQ ID NOS: 329 and 330,for MAX.chr20.4422 a set of primers consisting of SEQ ID NOS: 333 and 334,for MPZ_5742 a set of primers consisting of SEQ ID NOS: 335 and 336,for MPZ_5554 a set of primers consisting of SEQ ID NOS: 337 and 338,for MSX2P1_B a set of primers consisting of SEQ ID NOS: 339 and 340,for ODC1_B a set of primers selected from the group consisting of SEQ ID NOS: 341 and 342 and SEQ ID NOS: 443 and 444,for OSR2_A a set of primers selected from the group consisting of SEQ ID NOS: 343 and 344 and SEQ ID NOS: 445 and 446,for OTX1_B a set of primers consisting of SEQ ID NOS: 345 and 346,for PLXNC1_B a set of primers consisting of SEQ ID NOS: 347 and 348,for PRKCB_7570 a set of primers consisting of SEQ ID NOS: 349 and 350,for SCRT2_C a set of primers consisting of SEQ ID NOS: 351 and 352,for SLC30A10 a set of primers consisting of SEQ ID NOS: 353 and 354,for SPHK2_B a set of primers consisting of SEQ ID NOS: 355 and 356,for ST8SIA4_B a set of primers consisting of SEQ ID NOS: 357 and 358,for STX16_C a set of primers consisting of SEQ ID NOS: 359 and 360,for TRH_A a set of primers selected from the group consisting of SEQ ID NOS: 363 and 364 and SEQ ID NOS: 47 and 448,for TRIM67_B a set of primers consisting of SEQ ID NOS: 365 and 366,for CD1D a set of primers consisting of SEQ ID NOS: 423 and 424,for FAM59B a set of primers consisting of SEQ ID NOS: 427 and 428,for C10orf125 a set of primers consisting of SEQ ID NOS: 429 and 430,for TRIM67 a set of primers consisting of SEQ ID NOS: 431 and 432,for SPHK2 a set of primers consisting of SEQ ID NOS: 433 and 434,for CALN1_B a set of primers consisting of SEQ ID NOS: 273 and 274, andfor CHST2_B a set of primers consisting of SEQ ID NOS: 437 and 438.
  • 18. The method of claim 1 wherein measuring amounts of a methylated marker gene comprises using one or more of polymerase chain reaction, nucleic acid sequencing, mass spectrometry, methylation-specific nuclease, mass-based separation, and target capture.
  • 19. The method of claim 18, wherein the measuring comprises multiplex amplification.
  • 20. The method of claim 18, wherein measuring the amount of at least one methylated marker gene comprises using one or more methods selected from the group consisting of methylation-specific PCR, quantitative methylation-specific PCR, methylation-specific DNA restriction enzyme analysis, quantitative bisulfite pyrosequencing, flap endonuclease assay, PCR-flap assay, and bisulfite genomic sequencing PCR.
CROSS REFERENCE TO RELATED APPLICATION

This application claims priority to and the benefit of U.S. Provisional Application No. 62/592,828, filed Nov. 30, 2017, the content of which is hereby incorporated by reference in its entirety.

Provisional Applications (1)
Number Date Country
62592828 Nov 2017 US