Cell-free detection of methylated prostate tumour

[0001] This application is a continuation of U.S. application Ser. No. 16/098,455, which is a U.S. National Stage entry of PCT/CA2017/000111, filed May 4, 2017, which claims the benefit of U.S. Provisional App. No. 62/331,585, filed May 4, 2016. The disclosure of each of the above applications is herein incorporated by reference in its entirety.

[0002] The instant application contains a Sequence Listing which has been submitted electronically in XML file format and is hereby incorporated by reference in its entirety. Said XML copy, created on Apr. 1, 2024, is named “P70423_SL.xml” and is 891,948 bytes in size.

[0003] This disclosure relates generally to tumour detection. More particularly, this disclosure relates to tumour-specific DNA methylation detection.

[0004] Cancer screening and monitoring has helped to improve outcomes over the past few decades simply because early detection leads to a better outcome as the cancer can be eliminated before it has spread. In the case of breast cancer, for instance, physical breast exams, mammography, ultrasound and MRI (in high risk patients) have all played a role in improving early diagnosis. The cost/benefit of these modalities for general screening, particularly in relatively younger women, has been controversial.

[0005] A primary issue for any screening tool is the compromise between false positive and false negative results (or specificity and sensitivity) which lead to unnecessary investigations in the former case, and ineffectiveness in the latter case. An ideal test is one that has a high Positive Predictive Value (PPV), minimizing unnecessary investigations but detecting the vast majority of cancers. Another key factor is what is called “detection sensitivity”, to distinguish it from test sensitivity, and that is the lower limits of detection in terms of the size of the tumour. Screening mammography in breast cancer, for instance, is considered to have a sensitivity from 80 to 90% with a specificity of 90%. However the mean size of tumours detected by mammography remains in the range of 15 to 19 mm. It has been suggested that only 3-13% of women derive an improved treatment outcome from this screening suggesting that the detection of smaller tumours would provide increased benefit. For women at high risk of developing breast cancer the use of MRI has offered some benefit with sensitivities in the range of 75 to 97% and specificities in the area of 90 to 96% and in combination with mammography offering 93-94% sensitivity and 77 to 96% specificities. However, MRI is acknowledged to have a poor PPV, in the area of 10-20%, leading to a large number of false positives and as a consequence unnecessary invasive investigations. All of these screens have likely reached their limit of detection sensitivity (or size of the tumour) and in the case of mammography still involve exposure to radiation, which may be of particular concern in women with familial mutations which render them more sensitive to radiation damage. There are no effective blood based screens for breast cancer based on circulating analytes.

[0006] While the above discussion focusses on breast cancer as an example, many of the same challenges exist for other types of cancers as well.

[0007] The detection of circulating tumour DNA is increasingly acknowledged as a viable “liquid biopsy” allowing for the detection and informative investigation of tumours in a non-invasive manner. Typically using the identification of tumour specific mutations these techniques have been applied to colon, breast and prostate cancers. Due to the high background of normal DNA present in the circulation these techniques can be limited in sensitivity. As well, the variable nature of tumour mutations in terms of occurrence and location (such as p53 and KRAS mutations) has generally limited these approaches to detecting tumour DNA at 1% of the total DNA in serum. Advanced techniques such as BEAMing have increased sensitivity, but are still limited overall. Even with these limitations the detection of circulating tumour DNA has recently been shown to be useful for detecting metastasis in breast cancer patients.

[0008] The detection of tumour specific methylation in the blood has been proposed to offer distinct advantages over the detection of mutations^1-5. A number of single or multiple methylation biomarkers have been assessed in cancers including lung^6-10, colon^11,12 and breast^13-16. These have suffered from low sensitivities as they have tended to be insufficiently prevalent in the tumours. Several multi-gene assays have been developed with improved performance. A more advanced multi-gene system using a combination of 10 different genes has been reported and uses a multiplexed PCR based assay¹⁷. It offers combined sensitivity and specificity of 91% and 96% respectively, due to the better coverage offered and it has been validated in a small cohort of stage IV patients. However, it has a very high background in normal blood which will limit its detection sensitivity. Methylated markers have been used to monitor the response to neoadjuvant therapy^18,19, and recently a methylation gene signature associated with metastatic tumours has been identified²⁰.

[0009] There remains a need for more sensitive and specific screening tools, as well as for straightforward tests that allow for the assessment of tumour burden, chemotherapy response, detection of residual disease, relapse and primary screening in high risk populations.

[0010] It is an object of this disclosure to obviate or mitigate at least one disadvantage of previous approaches.

[0011] In a first aspect, this disclosure provides a method for detecting a tumour, comprising: extracting DNA from a cell-free sample obtained from a subject, bisulphite converting at least a portion of the DNA, amplifying regions methylated in cancer from the bisulphite converted DNA, generating sequencing reads from the amplified regions, and detecting tumour signals comprising at least two adjacent methylated sites within a single sequencing read, wherein the detection of at least one of the tumour signals is indicative of a tumour.

[0012] In another aspect, there is provided a use of the method for determining response to treatment.

[0013] In another aspect, there is provided a use of the method for monitoring tumour load.

[0014] In another aspect, there is provided a use of the method for detecting residual tumour post-surgery.

[0015] In another aspect, there is provided a use of the method for detecting relapse.

[0016] In another aspect, there is provided a use of the method as a secondary screen.

[0017] In another aspect, there is provided a use of the method as a primary screen.

[0018] In another aspect, there is provided a use of the method for monitoring cancer development.

[0019] In another aspect, there is provided a use of the method for monitoring cancer risk.

[0020] In another aspect, there is provided a kit for detecting a tumour comprising reagents for carrying out the method, and instructions for detecting the tumour signals.

[0021] Other aspects and features of this disclosure will become apparent to those ordinarily skilled in the art upon review of the following description of specific embodiments in conjunction with the accompanying figures.

[0053] Generally, this disclosure provides a method for detecting a tumour that can be applied to cell-free samples, e.g., to detect cell-free circulating tumour DNA. The method utilizes detection of adjacent methylation signals within a single sequencing read as the basic “positive” tumour signal.

[0054] In one aspect, there is provided a method for detecting a tumour, comprising: extracting DNA from a cell-free sample obtained from a subject, bisulphite converting at least a portion of the DNA, amplifying regions methylated in cancer from the bisulphite converted DNA, generating sequencing reads from the amplified regions, and detecting tumour signals comprising at least two adjacent methylated sites within a single sequencing read, wherein the detection of at least one of the tumour signals is indicative of a tumour.

[0055] By “cell-free DNA (cfDNA)” is meant DNA in a biological sample that is not contained in a cell. cfDNA may circulate freely in in a bodily fluid, such as in the bloodstream.

[0056] “Cell-free sample”, as used herein, is meant a biological sample that is substantially devoid of intact cells. This may be a derived from a biological sample that is itself substantially devoid of cells, or may be derived from a sample from which cells have been removed. Example cell-free samples include those derived from blood, such as serum or plasma; urine; or samples derived from other sources, such as semen, sputum, feces, ductal exudate, lymph, or recovered lavage.

[0057] “Circulating tumour DNA”, as used herein, accordingly refers to cfDNA originating from a tumour.

[0058] By “region methylated in cancer” is meant a segment of the genome containing methylation sites (CpG dinucleotides), methylation of which is associated with a malignant cellular state. Methylation of a region may be associated with more than one different type of cancer, or with one type of cancer specifically. Within this, methylation of a region may be associated with more than one subtype, or with one subtype specifically.

[0059] The terms cancer “type” and “subtype” are used relatively herein, such that one “type” of cancer, such as breast cancer, may be “subtypes” based on e.g., stage, morphology, histology, gene expression, receptor profile, mutation profile, aggressiveness, prognosis, malignant characteristics, etc. Likewise, “type” and “subtype” may be applied at a finer level, e.g., to differentiate one histological “type” into “subtypes”, e.g., defined according to mutation profile or gene expression.

[0060] By “adjacent methylated sites” is meant two methylated sites that are, sequentially, next to each other. It will be understood that this term does not necessarily require the sites to actually be directly beside each other in the physical DNA structure. Rather, in a sequence of DNA including spaced apart methylation sites A, B, and C in the context A-(n)_n-B-(n)_n-C, wherein (n)_n refers to the number of base pairs (bp) (e.g., up to 300 bp), sites A and B would be recognized as “adjacent” as would sites B and C. Sites A and C, however, would not be considered to be adjacent methylated sites.

[0061] In one embodiment, the regions methylated in cancer comprise CpG islands.

[0062] “CpG islands” are regions of the genome having a high frequency of CpG sites. CpG islands are usually 300-3000 bp in length and are found at or near promotors of approximately 40% of mammalian genes. They show a tendency to occur upstream of so-called “housekeeping genes”. A concrete definition is elusive, but CpG islands may be said to have an absolute GC content of at least 50%, and a CpG dinucleotide content of at least 60% of what would be statistically expected. Their occurrence at or upstream of the 5′ end of genes may reflect a role in the regulation of transcription, and methylation of CpG sites within the promoters of genes may lead to silencing. Silencing of tumour suppressors by methylation is, in turn, a hallmark of a number of human cancers.

[0063] In one embodiment, the regions methylated in cancer comprise CpG shores.

[0064] “CpG shores” are regions extending short distances from CpG islands in which methylation may also occur. CpG shores may be found in the region 0 to 2 kb upstream and downstream of a CpG island.

[0065] In one embodiment, the regions methylated in cancer comprise CpG shelves.

[0066] “CpG shelves” are regions extending short distances from CpG shores in which methylation may also occur. CpG shelves may generally be found in the region between 2 kb and 4 kb upstream and downstream of a CpG island (i.e., extending a further 2 kb out from a CpG shore).

[0067] In one embodiment, the regions methylated in cancer comprise CpG islands and CpG shores.

[0068] In one embodiment, the regions methylated in cancer comprise CpG islands, CpG shores, and CpG shelves.

[0069] In one embodiment, the regions methylated in cancer comprise CpG islands and sequences 0 to 4 kb upstream and downstream. The regions methylated in cancer may also comprise CpG islands and sequences 0 to 3 kb upstream and downstream, 0 to 2 kb upstream and downstream, 0 to 1 kb upstream and downstream, 0 to 500 bp upstream and downstream, 0 to 400 bp upstream and downstream, 0 to 300 bp upstream and downstream, 0 to 200 bp upstream and downstream, or 0 to 100 bp upstream and downstream.

[0070] In one embodiment, the step of amplifying is carried out with primers designed to anneal to bisulphite converted target sequences having at least one methylated site therein. Bisulphite conversion results in unmethylated cytosines being converted to uracil, while 5-methylcytosine is unaffected. “Bisulphite converted target sequences” are thus understood to be sequences in which cytosines known to be methylation sites are fixed as “C” (cytosine), while cytosines known to be unmethylated are fixed as “U” (uracil; which can be treated as “T” (thymine) for primer design purposes). Primers designed to target such sequences may exhibit a degree of bias towards converted methylated sequences. However, in one embodiment, the primers are designed without preference as to location of the at least one methylated site within target sequences. Often, to achieve optimal discrimination, it may be desirable to place a discriminatory base at the ultimate or penultimate 3′ position of an oligonucleotide PCR primer. In this embodiment, however, no preference is given to the location of the discriminatory sites of methylation, such that overall primer design is optimized based on sequence (not discrimination). This results in a degree of bias for some primer sets, but usually not complete specificity towards methylated sequences (some individual primer pairs, however, may be specific if a discriminatory site is fortuitously placed). As will be described herein, this permits some embodiments of the method to be quantitative or semi-quantitative.

[0071] In one embodiment, the PCR primers are designed to be methylation specific. This may allow for greater sensitivity in some applications. For instance, primers may be designed to include a discriminatory nucleotide (specific to a methylated sequence following bisulphite conversion) positioned to achieve optimal discrimination, e.g. in PCR applications. The discriminatory may be positioned at the 3′ ultimate or penultimate position.

[0072] In one embodiment, the primers are designed to amplify DNA fragments 75 to 150 bp in length. This is the general size range known for circulating DNA, and optimizing primer design to take into account target size may increase the sensitivity of the method according to this embodiment. The primers may be designed to amplify regions that are 50 to 200, 75 to 150, or 100 or 125 bp in length.

[0073] In some embodiments, concordant results provide additional confidence in a positive tumour signal. By “concordant” or “concordance”, as used herein, is meant methylation status that is consistent by location and/or by repeated observation. As has already been stated, the basic “tumour signal” defined herein comprises at least two adjacent methylated sites within a single sequencing read. However, additional layers of concordance can be used to increase confidence for tumour detection, in some embodiments, and not all of these need be derived from the same sequencing read. Layers of concordance that may provide confidence in tumor detection may include, for example:

• • [0074] (a) detection of methylation of at least two adjacent methylation sites;
  • [0075] (b) detection of methylation of more than two adjacent methylation sites;
  • [0076] (c) detection of methylation at adjacent sites within the same section of a target region amplified by one primer pair;
  • [0077] (d) detection of methylation at non-adjacent sites within the same section of a region amplified by one primer pair;
  • [0078] (e) detection of methylation at adjacent sites within the same target region;
  • [0079] (f) detection of methylation at non-adjacent sites within the same target region;
  • [0080] (g) any one of (a) to (f) in the same sequencing read;
  • [0081] (h) any one of (a) to (f) in at least two sequencing reads;
  • [0082] (i) any one of (a) to (f) in a plurality of sequencing reads;
  • [0083] (j) detection over methylation at sets of adjacent sites that overlap;
  • [0084] (k) repeated observation of any one of (a) to (j); or
  • [0085] (l) any combination or subset of the above.

[0086] In one embodiment, each of the regions is amplified in sections using multiple primer pairs. In one embodiment, these sections are non-overlapping. The sections may be immediately adjacent or spaced apart (e.g. spaced apart up to 10, 20, 30, 40, or 50 bp). Since target regions (including CpG islands, CpG shores, and/or CpG shelves) are usually Ionger than 75 to 150 bp, this embodiment permits the methylation status of sites across more (or all) of a given target region to be assessed.

[0087] A person of ordinary skill in the art would be well aware of how to design primers for target regions using available tools such as Primer3, Primer3Plus, Primer-BLAST, etc. As discussed, bisulphite conversion results in cytosine converting to uracil and 5′-methylcytosine converting to thymine. Thus, primer positioning or targeting may make use of bisulphite converted methylate sequences, depending on the degree of methylation specificity required.

[0088] Target regions for amplification are designed to have at least two CpG dinucleotide methylation sites. In some embodiments, however, it may be advantageous to amplify regions having more than one CpG methylation site. For instance, the amplified regions may have 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, or 15 CpG methylation sites. In one embodiment, the primers are designed to amplify DNA fragments comprising 3 to 12 CpG methylation sites. Overall this permits a larger number of adjacent methylation sites to be queried within a single sequencing read, and provides additional certainty (exclusion of false positives) because multiple concordant methylations can be detected within a single sequencing read. In one embodiment, the tumour signals comprise more than two adjacent methylation sites within the single sequencing read. Detecting more than two adjacent methylation sites provides additional concordance, and additional confidence that the tumour signal is not a false positive in this embodiment. For example, a tumour signal may be designated as 3, 4, 5, 6, 7, 8, 9, 10 or more adjacent detected methylation sites within a single sequencing read. In one embodiment, the detection of more than one of the tumour signals is indicative of a tumour. Detection of multiple tumour signals, in this embodiment, can increase confidence in tumour detection. Such signals can be at the same or at different sites. In one embodiment, the detection of more than one of the tumour signals at the same region is indicative of a tumour. Detection of multiple tumour signals indicative of methylation at the same site in the genome, in this embodiment, can increase confidence in tumour detection. So too can detection of methylation at adjacent sites in the genome, even if the signals are derived from different sequencing reads. This reflects another type of concordance. In one embodiment, the detection of adjacent or overlapping tumour signals across at least two different sequencing reads is indicative of a tumour. In one embodiment, the adjacent or overlapping tumour signals are within the same CpG island. In one embodiment, the detection of 5 to 25 adjacent methylated sites is indicative of a tumour.

[0089] Methylated regions can be selected according to the purpose of the intended assay. In one embodiment, the regions comprise at least one region listed Table 1 and/or Table 2. In one embodiment, the regions comprise all regions listed in Table 1 and/or Table 2. Likewise, primer pairs can be designed based on the intended target regions.

[0090] In one embodiment, the step of amplification is carried out with more than 100 primer pairs. The step of amplification may be carried out with 10, 20, 30, 40, 50, 60, 70, 80, 90, 100, 110, 120, 130, 140, 150, or more primer pairs. In one embodiment, the step of amplification is a multiplex amplification. Multiplex amplification permits large amount of methylation information to be gathered from many target regions in the genome in parallel, even from cfDNA samples in which DNA is generally not plentiful. The multiplexing may be scaled up to a platform such as ION AmpliSeq™, in which, e.g. up to 24,000 amplicons may be queried simultaneously. In one embodiment, the step of amplification is nested amplification. A nested amplification may improve sensitivity and specificity.

[0091] The nested reaction may be part of a next generation sequencing approach. Barcode and/or sequencing primers may be added in the second (nested) amplification. Alternatively, these may added in the first amplification.

[0092] In one embodiment, the method further comprises quantifying the tumour signals, wherein a number in excess of a threshold is indicative of a tumour. In one embodiment, the steps of quantifying and comparing are carried out independently for each of the sites methylated in cancer. Accordingly, a count of positive tumour signals may be established for each site. In one embodiment, the method further comprises determining a proportion of the sequencing reads containing tumour signals, wherein the proportion in excess of a threshold is indicative of a tumour. In one embodiment, the step of determining is carried out independently for each of the sites methylated in cancer.

[0093] By “threshold”, as used herein, is meant a value that is selected to discriminate between a disease (e.g., malignant) state, and a non-disease (e.g., healthy) state. Thresholds can be set according to the disease in question, and may be based on earlier analysis, e.g., of a training set. Thresholds may also be set for a site according to the predictive value of methylation at a particular site. Thresholds may be different for each methylation site, and data from multiple sites can be combined in the end analysis.

[0094] Various design parameters may be used to select the regions subject to amplification in some embodiments. In one embodiment, the regions are not methylated in healthy tissue. Healthy tissue would be understood to be non-malignant. Healthy tissue is often selected based on the origin of the corresponding tumour.

[0095] Regions may be selected based on desired aims or required specificity, in some embodiments. For instance, it may be desirable to screen for more than one cancer type. Thus, in one embodiment, the regions are collectively methylated in more than one tumour type. It may be desirable to include regions methylated generally in a group of cancers, and regions methylated in specific cancers in order to provide different tiers of information. Thus, in one embodiment, the regions comprise regions that are specifically methylated in specific tumours, and regions that are methylated in more than one tumour type. Likewise, it may be desirably to include a second tier of regions that can differentiate between tumour types. In one embodiment, the regions specifically methylated in specific tumours comprise a plurality of groups, each specific to one tumour type. However, it may be desirable in some contexts to have a test that is focused on one type of cancer. Thus, in one embodiment, the regions are methylated specifically in one tumour type. In one embodiment, the regions are selected from those listed in Table 3 and the tumour is one carrying a BRCA1 mutation.

[0096] More specifically, in some embodiments regions may be selected that are methylated in particular subtypes of a cancer exhibiting particular histology, karyotype, gene expression (or profile thereof), gene mutation (or profile thereof), staging, etc. Accordingly, the regions to be amplified may comprise one or more groups of regions, each being established to be methylated in one particular cancer subtype. In one embodiment the regions to be amplified may be methylated in a cancer subtype bearing particular mutations. With breast cancer in mind, one example subtype defined by mutation is cancer bearing BRCA1 mutations. Another subtype is cancer bearing BRCA2 mutations. Other breast cancer subtypes for which methylated regions may be determined include Basal, Luminal A, Luminal B, HER2 and Normal-like tumours. For uveal melanoma, for example, subtypes may include tumours that have retained or lost chromosome 3 (monosomy 3).

[0097] Within the context of such a test of some embodiments, information about not only the presence, but also the pattern and distribution of tumour signals both within specific regions and between different regions may help to detect or validate the presence of a form of cancer. In one embodiment, the method further comprises determining a distribution of tumour signals across the regions, and comparing the distribution to at least one pattern associated with a cancer, wherein similarity between the distribution and the pattern is indicative of the cancer.

[0098] “Distribution”, as used herein in this context, is meant to indicate the number and location of tumour signals across the regions. Statistical analysis may be used to compare the observed distribution with, e.g., pre-established patterns (data) associated with a form of cancer. In other embodiments, the distribution may be compared to multiple patterns. In one embodiment, the method further comprises determining a distribution of tumour signals across the regions, and comparing the distribution to a plurality of patterns, each one associated with a cancer type, wherein similarity between the distribution and one of the plurality of patterns is indicative of the associated cancer type.

[0099] In one embodiment, the step of generating sequencing reads is carried out by next generation sequencing. This permits a very high depth of reads to be achieved for a given region. These are high-throughput methods that include, for example, Ilumina (Solexa) sequencing, Roche 454 sequencing, Ion Torrent sequencing, and SOLID sequencing. The depth of sequencing reads may be adjusted depending on desired sensitivity.

[0100] In one embodiment, the step of generating sequencing reads is carried out simultaneously for samples obtained from multiple patients, wherein the amplified CpG islands from is barcoded for each patient. This permits parallel analysis of a plurality of patients in one sequencing run.

[0101] A number of design parameters may be considered in the selection of regions methylated in cancer, according to some embodiments. Data for this selection process may be from a variety of sources such as, e.g., The Cancer Genome Atlas (TCGA) (http://cancergenome.nih.gov/), derived by the use of, e.g., Illumina Infinium HumanMethylation450 BeadChip (http://www.illumina.com/products/methylation_450_beadchip kits.html) for a wide range of cancers, or from other sources based on, e.g., bisulphite whole genome sequencing, or other methodologies. For instance, “methylation value” (understood herein as derived from TCGA level 3 methylation data, which is in turn derived from the beta-value, which ranges from −0.5 to 0.5) may be used to select regions. In one embodiment, the step of amplification is carried out with primer sets designed to amplify at least one methylation site having a methylation value of below −0.3 in normal issue. This can be established in a plurality of normal tissue samples, for example 4. The methylation value may be at or below −0.1, −0.2, −0.3, −0.4, or −0.5. In one embodiment, the primer sets are designed to amplify at least one methylation site having a difference between the average methylation value in the cancer and the normal tissue of greater than 0.3. The difference may be greater than 0.1, 0.2, 0.3, 0.4, or 0.5. Proximity of other methylation sites that meet this requirement may also play a role in selecting regions, in some embodiments. In one embodiment, the primer sets include primer pairs amplifying at least one methylation site having at least one methylation site within 200 bp that also has a methylation value of below −0.3 in normal issue, and a difference between the average methylation value in the cancer and the normal tissue of greater than 0.3. In another embodiment the adjacent site having these features may be 300 bp. The adjacent site may be within 100, 200, 300, 400, or 500 bp.

[0102] In some embodiments, target regions may be selected for amplification based on the number of tumours in the validation set having methylation at that site. For example, a region may be selected if it is methylated in at least 50%, 55%, 60%, 65%, 70%, 75%, 80, 85%, 90, or 95% of tumours tested. For example, regions may be selected if they are methylated in at least 75% of tumours tested, including within specific subtypes. For some validations, it will be appreciated that tumour-derived cell lines may be used for the testing.

[0103] In another embodiment, the method further comprises oxidative bisulphite conversion. In addition to the analysis of methylation of CpG residues, additional information that may be of clinical significance may be derived from the analysis of hydroxymethylation. Bisulphite sequencing results in the conversion of unmethylated cytosine residues into uracil/thymidine residues, while both methylated and hydroxymethylated cytosines remain unconverted. However, oxidative bisulphite treatment allows for the conversion of hydroxymethylated cytosines to uracil/thymidine allowing for the differential analysis of both types of modifications. By comparison of bisulphite to oxidative bisulphite treatments the presence of hydroxymethylation can be deduced. This information may be of significance as its presence or absence may be correlated with clinical features of the tumor which may be clinically useful either as a predictive or prognostic factor. Accordingly, in some embodiments, information about hydroxymethylation could additionally be used in the above-described embodiments.

[0104] In one aspect, the presence of specific patterns of methylation is linked to underlying characteristics of particular tumours. In these cases, the methylation patterns detected by the method are indicative of clinically relevant aspects of the tumours such as aggressiveness, likelihood of recurrence, and response to various therapies. Detection of these patterns in the blood may thus provide both prognostic and predictive information related to a patient's tumor.

[0105] In another aspect, the forgoing method may be applied to clinical applications involving the detection or monitoring of cancer.

[0106] In one embodiment, the forgoing method may be applied to determine and/or predict response to treatment.

[0107] In one embodiment, the forgoing method may be applied to monitor and/or predict tumour load.

[0108] In one embodiment, the forgoing method may be applied to detect and/or predict residual tumour post-surgery.

[0109] In one embodiment, the forgoing method may be applied to detect and/or predict relapse.

[0110] In one aspect, the forgoing method may be applied as a secondary screen.

[0111] In one aspect, the forgoing method may be applied as a primary screen.

[0112] In one aspect, the forgoing method may be applied to monitor cancer development.

[0113] In one aspect, the forgoing method may be applied to monitor and/or predict cancer risk.

[0114] In another aspect, there is provided a kit for detecting a tumour comprising reagents for carrying out the aforementioned method, and instructions for detecting the tumour signals. Reagents may include, for example, primer sets, PCR reaction components, and/or sequencing reagents.

[0115] In one embodiment of the forgoing methods, the regions comprise C2CD4A, COL19A1, DCDC2, DHRS3, GALNT3, HES5, KILLIN, MUC21, NR2E1/OSTM1, PAMR1, SCRN1, and SEZ6, and the tumour is uveal melanoma. In one embodiment, the probes comprise C2C5F, COL2F, DCD5F, DGR2F, GAL1F, GAL3F, HES1F, HES3F, HES4F, KIL5F, KIL6F, MUC2F, OST3F, OST4F, PAM4F, SCR2F, SEZ3F, and SEZ5F.

[0116] In one embodiment, the regions comprise ADCY4, ALDH1L1, ALOX5, AMOTL2, ANXA2, CHST11, EFS, EPSTI1, EYA4, HAAO, HAPLN3, HCG4P6, HES5, HIF3A, HLA-F, HLA-J, HOXA7, HSF4, KLK4, LOC376693, LRRC4, NBR1, PAH, PON3, PPM1H, PTRF, RARA, RARB, RHCG, RND2, TMP4, TXNRD1, and ZSCAN12, and the tumour is prostate cancer. In one embodiment, the probes comprise ADCY4-F, ALDH1L1-F, ALOX5-F, AMOTL2-F, ANXA2-F, CHST11-F, EFS-F, EPSTI1-F, EYA4-F, HAAO-F, HAPLN3-F, HCG4P6-F, HES5-F, HIF3A-F, HLA-F-F, HLA-J-1-F, HLA-J-2-F, HOXA7-F, HSF4-F, KLK4-F, LOC376693-F, LRRC4-F, NBR1-F, PAH-F, PON3-F, PPM1H-F, PTRF-F, RARA-F, RARB-F, RHCG-F, RND2-F,TMP4-F, TXNRD1-F, and ZSCAN12-F. In one embodiment, the probes additionally include C1Dtrim, C1 Etrim, CHSAtrim, DMBCtrim, FOXAtrim, FOXEtrim, SFRAtrim, SFRCtrim, SFREtrim, TTBAtrim, VWCJtrim, and VWCKtrim.

[0117] In one embodiment, the regions comprise ASAP1, BC030768, C18orf62, C6orf141, CADPS2, CORO1C, CYP27A1, CYTH4, DMRTA2, EMX1, HFE, HIST1H3G/1H2BI, HMGCLL1, KCNK4, KJ904227, KRT78, LINC240, Me3, MIR1292, NBPF1, NHLH2, NRN1, PPM1H, PPP2R5C, PRSS3, SFRP2, SLCO4C1, SOX2OT, TUBB2B, USP44, Intergenic (Chr1), Intergenic (Chr2), Intergenic (Chr3), Intergenic (Chr4), Intergenic (Chr8), and Intergenic (Chr10), and the tumour is aggressive prostate cancer. In one embodiment, the aggressive prostate cancer has a Gleason Score greater than 6. In one embodiment, the aggressive prostate cancer has a Gleason Score of 9 or greater. In one embodiment, the probes comprise ASAP1/p, BC030768/p, C18orf62/p, C6orf141/p-1, C6orf141/p-2, CADPS2/p, CORO1C/p-1, CORO1C/p-2, CYP27A1/p, CYTH4/p, DMRTA2/p, EMX1/p, HFE/p-1, HFE/p-2, HIST1H3G/1H2BI/p, HMGCLL1/p, KCNK4/p, KJ904227/p, KRT78/p, LINC240/p-1, LINC240/p-2, Me3/p-1, Me3/p-2, MIR129, NBPF1/p, NHLH2/p, NRN1/p, PPM1H/p-1, PPM1H/p-2, PPP2R5C/p, PRSS3/p, SFRP2/p-1, SFRP2/p-2, SLCO4C1/p, SOX2OT/p, TUBB2B/p, USP44/p, Chr1/p-1, Chr2/p-1, Chr3/p-1, Chr4/p-1, Chr8/p-1, and Chr10/p-1.

[0118] In one embodiment, the regions comprise the regions depicted in FIGS. 26A, 26B, and 26C, and the tumour is breast cancer.

[0119] In one embodiment, the regions comprise ALX1, ACVRL1, BRCA1,C1orf114, CA9, CARD11, CCL28, CD38, CDKL2, CHST11, CRYM, DMBX1, DPP10, DRD4, ERNA4, EPSTI1, EVX1, FABP5, FOXA3, GALR3, GIPC2, HINF1B, HOXA9, HOXB13, Intergenic5, Intergenic 8, IRF8, ITPRIPL1, LEF1, LOC641518, MAST1, BARHL2, BOLL, C5orf39, DDAH2, DMRTA2, GABRA4, ID4, IRF4, NT5E, SIM1, TBX15, NFIC, NPHS2, NR5A2, OTX2, PAX6, GNG4, SCAND3, TAL1, PDX1, PHOX2B, POU4F1, PFIA3, PRDM13, PRKCB, PRSS27, PTGDR, PTPRN2, SALL3, SLC7A4, SOX2OT, SPAG6, TCTEX1D1, TMEM132C, TMEM90B, TNFRSF10D, TOP2P1, TSPAN33, TTBK1, UDB, and VWC2, and the tumour is triple negative breast cancer (TNBC). In one embodiment, the probes comprise ALX1, AVCRL1, BRCA1-A, C1Dtrim, C1Etrim, CA9-A, CARD11-B, CCL28-A, CD38, CDKL2-A, CHSAtrim, CRYM-A, DMBCtrim, DMRTA2exp-A, DPP10-A, DPP10-B, DPP10-C,DRD4-A, EFNA4-B, EPSTI1, EVX1, FABP5, FOXAtrim, FOXEtrim, GALR3-A, GIPC2-A, HINF C trim, HOXAAtrim, HOXACtrim, HOXB13-A, Int5, Int8, IRF8-A, ITRIPL1, LEF1-A, MAST1 A trim, mbBARHL2 Trim, mbBOLL Trim, mbC5orf Trim, mbDDAH Trim, mbDMRTA Trim, mbGABRA A Trim, mbGABRA B Trim, mbGNG Trim, mbID4 Trim, mbIRF Trim, mbNT5E Trim, mbSIM A Trim, mbTBX15 Trim, NFIC—B, NFIC-A, NPSH2-B, NR5A2-B, OTX2-A, PAX6-A, pbDMRTA Trim, pbGNG Trim, pbSCAND Trim, pbTAL Trim, PDX1exp-B, PHOX2B-A, POU4F1 A trim, PPFIA3-A, PRDM13, PRKCB-A, PRKCB-C, PRSS27-A, PTGDR, PTPRN2-A, PTPRN2-B, SALL3-A, SALL3-B, SLC7A4-A, SOX2OT-B, SPAG6 A trim, TCTEX1D1-A, TMEM-A, TMEM-B, TMEM90B-A, TNFRSF10D, TOP2P1-B, TSPAN33-A, TTBAtrim, UBD-A, VWCJtrim, and VWCKtrim.

[0120] In one embodiment, each region is amplified with primer pairs listed for the respective region in Table 15.

[0121] In one embodiment, the method further comprises administering a treatment for the tumour detected.

[0122] In one aspect, there is provided a method for identifying a methylation signature indicative of a biological characteristic, the method comprising: obtaining data for a population comprising a plurality of genomic methylation data sets, each of said genomic methylation data sets associated with biological information for a corresponding sample, segregating the methylation data sets into a first group corresponding to one tissue or cell type possessing the biological characteristic and a second group corresponding to a plurality of tissue or cell types not possessing the biological characteristic, matching methylation data from the first group to methylation data from the second group on a site-by-site basis across the genome, identifying a set of CpG sites that meet a predetermined threshold for establishing differential methylation between the first and second groups, identifying, using the set of CpG sites, target genomic regions comprising at least two differentially methylated CpGs with 300 bp that meet said predetermined criteria, extending the target genomic regions to encompass at least one adjacent differentially methylated CpG site that does not meet the predetermined criteria, wherein the extended target genomic regions provide the methylation signature indicative of the biological trait.

[0123] In one embodiment, the method further comprises validating the extended target genomic regions by testing for differential methylation within the extended target genomic regions using DNA from at least one independent sample possessing the biological trait and DNA from at least one independent sample not possessing the biological sample.

[0124] In one embodiment, the step of identifying further comprises limiting the set of CpG sites to CpG sites that further exhibit differential methylation with peripheral blood mononuclear cells from a control sample.

[0125] In one embodiment, the plurality of tissue or cell types of the second group comprises at least some tissue or cells of the same type as the first group.

[0126] In one embodiment, the plurality of tissue or cell types of the second group comprises a plurality of non-diseased tissue or cell types.

[0127] In one embodiment, the predetermined threshold is indicative of methylation in the first group and non-methylation in the second group.

[0128] In one embodiment, the predetermined threshold is at least 50% methylation in the first group.

[0129] In one embodiment, the predetermined threshold is a difference in average methylation between the first and second groups of 0.3 or greater.

[0130] In one embodiment, the biological trait comprises malignancy.

[0131] In one embodiment, the biological trait comprises a cancer type.

[0132] In one embodiment, the biological trait comprises a cancer classification.

[0133] In one embodiment, the cancer classification comprises a cancer grade.

[0134] In one embodiment, the cancer classification comprises a histological classification.

[0135] In one embodiment, the biological trait comprises a metabolic profile.

[0136] In one embodiment, the biological trait comprises a mutation.

[0137] In one embodiment, the mutation is a disease-associated mutation.

[0138] In one embodiment, the biological trait comprises a clinical outcome.

[0139] In one embodiment, the biological trait comprises a drug response.

[0140] In one embodiment, the method further comprises designing a plurality of PCR primers pairs to amplify portions of the extended target genomic regions, each of the portions comprising at least one differentially methylated CpG site.

[0141] In one embodiment, the step of designing the plurality of primer pairs comprising converting non-methylated cytosines uracil, to simulate bisulphite conversion, and designing the primer pairs using the converted sequence.

[0142] In one embodiment, the primer pairs are designed to have a methylation bias.

[0143] In one embodiment, the primer pairs are methylation-specific.

[0144] In one embodiment, the primer pairs have no CpG residues within them having no preference for methylation status.

[0145] In one aspect, there is provided a method for synthesizing primer pairs specific to a methylation signature, the method comprising: carrying out the forgoing method, and synthesizing the designed primer pairs.

[0146] In one aspect, there is provided a non-transitory computer-readable medium comprising instructions that direct a processor to carry out the forgoing method.

[0147] In one aspect, there is provided a computing device comprising the computer-readable medium.

Concept Summary

[0148] The embodiments detect circulating tumour DNA using a highly sensitive and specific methylation based assay with detection limits 100 times better than other techniques.

[0149] FIG. 1 depicts a schematic of the overall strategy. CpG dinucleotides are often clustered into concentrated regions in the genome referred to as CpG islands (grey box) and are often, but not always, associated with the promoter or enhancer regions of genes. These regions are known to become abnormally methylated in tumours (CmpG) as compared to normal tissue (CpG) which may be linked to the inactivation of tumour suppressor genes by this methylation event. Methylation of CpG islands and the boundary regions (CpG island shores) is extensive and co-ordinated such that most or all of the CpG residues in that region become methylated. The detection of this methylation typically involves bisulphite conversion, PCR amplification of the relevant region (arrows), and sequencing where un-methylated CpG residues are converted to TpG dinucleotides while methylated CpG residues are preserved as CpGs. Sequencing of these PCR-amplified “probes” (BISULFITE SEQUENCING) from tumour DNA (arrows) results in the detection of multiple CpG residues being methylated within the same DNA fragment (Dashed Box) which can easily be distinguished from DNA from normal tissue (Boxes). The co-ordinated/concordant nature of this methylation produces a strong signal which can be detected over random or background changes from DNA sequencing. This is accomplished by first identifying regions of tumour specific DNA methylation with multiple correlated CpG methylation sites within the same region.

[0150] FIG. 30 depicts a flowchart showing how a methylation signature for a biological trait may be determined. One or more steps of this method may be implemented on a computer. Accordingly, another aspect of this disclosure relates to a non-transitory computer-readable medium comprising instructions that direct a processor to carry out steps of this method.

[0151] Generally “probe” is used herein to refer to a target region for amplification and/or the ensuing amplified PCR product. It will be understood that each probe is amplified by a “primer set” or “primer pair”.

[0152] FIG. 2 depicts a schematic for amplification of target regions. Multiple regions from across the human genome have been identified as being differentially methylated in the DNA from various types of tumours compared to the normal DNA from a variety of different tissues. These regions can be fairly extensive spanning 100s to 1000s of base pairs of DNA. These target regions (black boxes, bottom) exhibit coordinated methylation where most or all of the CpG dinucleotides in these regions are methylated in tumour tissue with little or no methylation in normal tissues. As shown in FIG. 2, when sequencing across these regions (arrows) multiple CpG residues are seen to be methylated together in the tumour creating a concordant signal identifiable as being tumour specific. By targeting multiple PCR-amplified probes across individual regions (middle) and across the entire genome (top) large numbers of probes can be designed with the advantage that with more probes comes greater sensitivity due to the greater likelihood of detecting a tumour specific fragment in a given sample. Primers for these probes are designed to amplify regions from 75 to 150 bp in length, corresponding to the typical size of circulating tumour DNA. The primers may include CpG dinucleotides or not, which in the former case can make these primers biased towards the amplification of methylated DNA or exclusively amplify only methylated DNA.

[0153] Multiple methylation-biased PCR primer pairs can be created, which are able to preferentially amplify these regions. These multiple regions are sequenced using next generation sequencing (NGS) at a high read depth to detect multiple tumour specific methylation patterns in a single sample. As described herein, features have been incorporated into a blood based cancer detection system that provides advantages over other tests which have been developed, and provides an unprecedented level of sensitivity and specificity as well as enables the detection of minute quantities of DNA (detection sensitivity).

Probe and Primer Set Development

[0154] The detection of circulating tumour DNA is hampered by both the presence of large amounts of normal DNA as well as by the very low concentrations of tumour DNA in the blood. Compounding this issue, both PCR and sequencing based approaches suffer from the introduction of single nucleotide changes due to the error prone nature of these processes. To deal with these issues, regions of the genome have been identified that exhibit concerted tumour specific methylation over a significant expanse of DNA so that each CpG residue is concordant²¹. Methylation-biased PCR primer pairs were designed for multiple segments of DNA across these regions each containing multiple CpG residues. Sample protocols for selection of differentially methylated regions and design of region specific PCR primers are provided.

Protocol for the Selection of Differentially Methylated Regions

Use of TCGA DATA for identifying Breast Specific Probes

[0155] Level 3 (processed) Illumina Infinium HumanMethylation450 BeadChip array data (http://www.illumina.com/techniques/microarrays/methylation-arrays.html) was downloaded from The Tumour Genome Atlas (TCGA) site (https://tcga-data.nci.nih.gov/tcga/tcgaHome2.jsp) for the appropriate tumour types (e.g., breast, prostate, colon, lung, etc.). Tumour and normal samples were separated and the methylation values (from −0.5 to +0.5) for each group were averaged. The individual methylation probes were mapped to their respective genomic location. Probes that fulfilled the following example criteria were then identified:

• • [0156] 1. The average methylation values for the normal breast, prostate, colon and lung tissues all below −0.3;
  • [0157] 2. The difference between the average breast tumour and average breast normal values greater than 0.3, or at least 50% methylation in the tumour group; and
  • [0158] 3. Two probes within 300 bp of each other fulfill criteria 1 and 2.

[0159] These criteria establish that the particular probe is not methylated in normal tissue, that the difference between the tumour and normal is significant, and that multiple probes in a relatively small area are co-ordinately methylated. Regions which had multiple positive consecutive probes (i.e., 3 or more) were prioritized for further analysis. Average values for approximately 10 other probes to either side of the positive region were plotted for all tumour and normal tissue samples to define the region exhibiting differential methylation. Regions exhibiting concerted differential methylation between tumour and normal for single or multiple tumour types were identified.

[0160] A secondary screen for a lack of methylation of these regions in blood was carried out by examining the methylation status of the defined regions in multiple tissues using nucleotide level genome wide bisulphite sequencing data. Specifically the UCSC Genome Browser (https://genome.ucsc.edu/) was used to examine methylation data from multiple sources.

[0161] Data was processed by the method described in Song Q, et al., A reference methylome database and analysis pipeline to facilitate integrative and comparative epigenomics. PLOS ONE 2013 8(12): e81148 (http://journals.plos.org/plosone/article?id=10.1371/journal.pone.0081148) for use in the UCSC Browser and to identify hypo-methylated regions (above blue lines).

The following data sources were used:

[0162] Gertz J, et al., Analysis of DNA methylation in a three-generation family reveals widespread genetic influence on epigenetic regulation. PLOS Genet. 2011 7(8):e1002228 (http://journals.plos.org/plosgenetics/article?id=10.1371/journal.pgen.1002228).

[0163] Heyn H, et al., Distinct DNA methylomes of newborns and centenarians. Proc. Natl. Acad. Sci. U.S.A. 2012 109(26):10522−7 (http://www.pnas.org/content/109/26/10522).

[0164] Hon G C, et al., Global DNA hypomethylation coupled to repressive chromatin domain formation and gene silencing in breast cancer. Genome Res. 2012 22(2):246−58 (http://genome.cshlp.org/content/22/2/246).

[0165] Heyn H, et al., Whole-genome bisulfite DNA sequencing of a DNMT3B mutant patient. Epigenetics. 2012 7(6):542−50 (http://www.tandfonline.com/doi/abs/10.4161/epi.20523 #.VsS_gdIUVIw).

[0166] Hon G C, et al., Global DNA hypomethylation coupled to repressive chromatin domain formation and gene silencing in breast cancer. Genome Res. 2012 22(2):246−58 (http://genome.cshlp.org/content/22/2/246).

[0167] All of the regions identified exhibited hypo-methylation in normal blood cells including Peripheral Blood Mononuclear Cells (PBMC), the prime source of non-tissue DNA in plasma.

Protocol for the Design of Region Specific Primers for PCR Amplification and Next Generation Sequencing

[0168] For regions identified as being differentially methylated in tumours, PCR primers were designed that are able to recognize bisulphite converted DNA which is methylated. Using Methyprimer Express™ or PyroMark™, or other web based programs, the DNA sequence of the region was converted to the sequence obtained when fully methylated DNA is bisulphite converted (i.e., C residues in a CpG dinucleotide remain Cs, while all other C residues are converted to T residues). The converted DNA was then analysed using PrimerBlast™ (http://www.ncbi.nlm.nih.gov/tools/primer-blast/) to generate optimal primers. Primers were not expressly selected to contain CpG residues but due to the nature of the regions, generally CpG islands, most had 1 to 3 CpGs within them. This renders them biased towards the amplification of methylated DNA but in many cases they do recognize and amplify non-methylated DNA as well. The region between the primers includes 2 or more CpG residues. Primers were chosen to amplify regions from 75 to 150 base pairs in size with melting temperatures in the range of 52-68° C. Multiple primers were designed for each region to provide increased sensitivity by providing multiple opportunities to detect that region. Adapter sequences (CS1 and CS2) were included at the 5′ end of the primers to allow for barcoding and for sequencing on multiple sequencing platforms by the use of adaptor primers for secondary PCR.

[0169] Primers were characterized by PCR amplification of breast cancer cell line DNA and DNA from various primary tumours. PCR amplification was done with individual sets of primers and Next Generation Sequencing carried out to characterize the methylation status of specific regions. Primer sets exhibiting appropriate tumour specific methylation were then combined into a multiplex PCR reaction containing many primers.

Results

[0170] FIG. 3 lists the 47 CpG probes used to identify differentially methylated regions. These were analyzed by Receiver Operator Curve analysis (ROC). Normal and tumour samples from the entire TCGA breast cancer database were compared. The Area Under the Curve (AUC) analysis for each probe is shown with the standard error, 95% confidence interval and P-value. All of them where shown to have excellent discriminatory capabilities.

[0171] FIG. 4 depicts the results of analysis methylation level for each patient in the TCGA database for the 47 CpG. Those exceeding the threshold of −0.1 were considered to be positive for methylation in that patient. The number of probes exceeding this methylation threshold were calculated for each patient. Patients were divided into those with Luminal A and B subtypes (Luminal Tumours; FIG. 4, Panel A) and those with Basal cancers (Basal Tumours; FIG. 4, Panel B) or and the number of patients with a specific range of positive probes was calculated. The histogram shows the frequency of patents within each range of positive probes. While these probes give excellent coverage in both populations, there are more positive probes amongst the Luminal tumours than the Basal tumours. Additional probes specific to the different breast cancer subtypes have been identified and appropriate probe development and validation is underway.

Selection of Regions for Cancer and Cancer Types

[0172] For breast cancer, 52 regions in the genome were identified that are highly methylated in tumours but where multiple normal tissues do not exhibit methylation of these regions. These serve as highly specific markers for the presence of a tumour with little or no background signal.

[0173] Table 1 depicts regions selected for breast cancer screening.

[0174]

TABLE 1
Chromo-	Start	End	General
some	(hg18)	(hg18)	Location	Tumour	Size
2nd Generation
chr1	167663259	167663533	C1orf114	P/B	274
chr7	49783577	49784309	VWC2	P/B/C	732
chr14	23873519	23873993	ADCY4	P/B/C	474
chr11	43559012	43559541	MIR129-2	B/C	529
3rd Generation
chr6	43319186	43319213	TTBK1	P/B	27
chr1	46723905	46724176	DMBX1	P/B/C	271
chr7	27171684	27172029	HOXA9	B	345
chr8	120720175	120720579	ENPP2	P/B	404
chr10	99521635	99521924	SFRP5	P/B	289
chr12	103376281	103376485	CHST11	P/B/C	204
chr19	51071603	51072234	FOXA3	P/B	631
4th Generation
chr1	47470535	47470713	TAL1	B	178
chr1	50658998	50659557	DMRTA2	B	559
chr1	66030610	66030634	PDE4B	B	24
chr1	90967262	90967924	BARHL2	B	662
chr1	119331667	119332616	TBX15	B/C	949
chr1	153557070	153557585	RUSC1,	B	515
			C1orf104
chr1	233880632	233880962	GNG4	B	330
chr2	104836482	104837226	POU3F3	B	744
chr2	198359230	198359743	BOLL	B/C	513
chr3	32834103	32834562	TRIM71	B/C	459
chr3	172228723	172228985	SLC2A2	B	262
chr4	5071985	5072137	CYTL1	B	152
chr4	42094549	42094615	SHISA3	B	66
chr4	46690266	46690578	GABRA4	B	312
chr5	38293273	38293312	EGFLAM	B	39
chr5	43076195	43076642	C5orf39	B	447
chr5	115179918	115180393	CDO1	B	475
chr6	336189	337131	IRF4	B/C	942
chr6	19944994	19945298	ID4	B	304
chr6	28618285	28618318	SCAND3	B	33
chr6	31806197	31806205	DDAH2	B	8
chr6	33269254	33269355	COL11A2	B	101
chr6	86215822	86215929	NT5E	B	107
chr6	101018889	101019751	SIM1	B	862
5th Generation
chr6	153493505	153494425	RGS17	B	920
chr7	121743738	121744126	CAPDS2	B	388
chr8	72918338	72918895	MSC	B/C	557
chr10	22674438	22674584	SPAG6	B/C	146
chr10	105026601	105026737	INA	B	136
chr11	128068895	128069316	FLI1	B/C	421
chr12	52357158	52357378	ATP5G2	B	220
chr12	94466892	94467095	USP44	B/C	203
chr13	78075521	78075764	POU4F1	B	243
chr14	55656275	55656325	PELI2	B	50
chr17	33176853	33178091	HNF1B	B	1238
chr17	32368343	32368604	LHX1	B/C/L	261
chr17	44154844	44155027	PRAC,	B/C	183
			C17orf93
chr18	73090725	73091121	GALR1	B/C	396
chr19	12839383	12839805	MAST1	B	422
chr20	2729122	2729438	CPXM1	B/C	316
chr20	43952209	43952500	CTSA,	B	291
			NEURL2

[0175] In Table 1, ‘Start’ and ‘End’ designate the coordinates of the target regions in the hg18 build of the human genome reference sequence. The ‘General Location’ field gives the name of one or more gene or ORF in the vicinity of the target region. Examination of these sequences relative to nearby genes indicates that they were found, e.g., in upstream, in 5′ promoters, in 5′ enhancers, in introns, in exons, in distal promoters, in coding regions, or in intergenic regions. The ‘Tumour’ field indicates whether a region is methylated in prostate (P), breast (B), colon (C), and/or lung (L) cancers. The ‘Size’ field indicates the size of the target region.

[0176] In the discussion here, it should be recognized that reference to genes such as CHST11, FOXA, and NT5 are not intended to be indicative of the genes in question per se, but rather to the associated methylated regions described in Table 1.

[0177] In total, 52 regions were found to be methylated in association with breast cancer, 17 were found to be methylated in association with prostate cancer, 9 were found to be methylated in association with prostate cancer, and 1 region was found to be methylated in association with lung cancer. Thus, some regions appear to be generally indicative of the various types of cancers assessed. Other regions methylated in subgroups of these, while others are specific for cancers. In the context of this assay and the types of cancers examined, 25 regions may be described as being “specifically methylated in breast cancer”. However, it is noted that the same approach may be used to identify regions methylated specifically in other cancers.

[0178] Assays may be developed for cancer generally, or to detect groups of cancers or specific cancers. A multi-tiered assay may be developed using “general” regions (methylated in multiple cancers) and “specific” regions (methylated in only specific cancers). A multi-tiered test of this sort may be run together in one multiplex reaction, or may have its tiers executed separately.

Probes for Breast Cancer

[0179] Over 150 different PCR primer pairs were developed to the 52 different regions in the genome shown to exhibit extensive methylation in multiple breast cancer samples from the TCGA database but with no or minimal methylation in multiple normal tissues and in blood cells (Peripheral Blood Mononuclear Cells and others).

[0180] As proof of concept, these were then used to amplify bisulphite converted DNA from breast cancer cell lines MCF-7 (ER+, PR+), T47-D (ER+, PR+), SK-BR-3 (HER2+), MDA-MD-231 (Triple Negative) and normal breast lines MCF-10A and 184-hTERT. Sequencing adapters were added and Next Generation Sequencing carried out on an Ion Torrent sequencer. The sequencing reads were then separated by region and the sequence reads were analyzed using the BiqAnalyzer HT program.

Results

[0181] Example results of methylation analysis will be discussed herein. CHST11 is an example of a region methylated in prostate, breast, and colon cancer. FOXA is a region methylated in breast and prostate cancer. NT5 is a region methylated specifically in breast cancer.

[0182] FIG. 5 depicts sequencing results from a region from near the CHST11 gene (Probe C) is shown. For each cell line the results of a single sequencing read is depicted as a horizontal bar with each box representing a single CpG residue from between the PCR primers (in this case there being 6 CpG residues, Illustration at bottom right). Methylated bases are shown in dark grey while un-methylated bases are shown in light grey. Where a CpG could not be identified by the alignment program it is shown as a white box. Multiple sequence reads are shown for each cell line, stacked on top of each other. The numbers at the bottom of each stack indicates the number of sequence reads (Reads) and the overall methylation level determined from these reads (Meth).

[0183] When sequenced, these probes produced strong concordant signals that consisted of multiple methylated CpGs (5 to 25) where there is a strong correlation between individual sites being methylated in tumours. This eliminates false positive results due to PCR and sequencing errors. These tumour specific multiple methylated sites can be detected against a high background of normal DNA, being limited only by the read depth of the sequencing. Based on bioinformatic analysis of TCGA tumours, this essentially eliminates false positive signals.

[0184] FIG. 6 depicts results for CHST11 Probe A. Methylation in the region was characterized for a variety of breast cancer tumour samples (T) and in normal breast tissue samples (N) from the same patient. As in FIG. 5 the methylated bases are shown in dark grey while un-methylated bases are shown in light grey (illustration bottom left). Tumours of various subtypes were analysed including A02324 which is positive for HER2 amplification (HER2+), A02354 and B02275 which are Triple Negative Breast Cancer (TNBC), and D01333, D02291, D02610 which are all Estrogen and Progesterone Receptor positive tumours (ER+PR+). The values below each column refer to the number of sequence reads obtained by Next Generation Sequencing (Reads) and the overall level of methylation of all of the CpG residues (Meth) based on these reads. Where no sequence reads were obtained for a given sample and box is shown as for sample D01333 N (Normal).

[0185] FIG. 7 depicts results of similar analysis of FOXA Probe A in breast cancer cell lines.

[0186] FIG. 15 depicts a numerical summary generated methylation data for prostate cell lines. #Reads is indicative of the number of reads exported, and Mean Me is indicative of the mean methylation.

[0187] FIG. 8 depicts results of similar analysis of the CHST11 Probe A and CHST11 Probe B in prostate cancer cell lines. DU145 is an Androgen Receptor (AR−) negative cell line which is able to generate metastases in the mouse. PC3 is also AR- and also metastatic. LNCaP is an Androgen Receptor positive line (AR+) which does generate metastases in the mouse while RWPE cells are AR+ and non-metastatic.

[0188] FIG. 9 depicts results of similar analysis of FOXA Probe A in prostate cell lines.

[0189] FIG. 10 depicts sequencing results to assess methylation status NET5 Probe E in breast cancer cell lines.

[0190] These results exemplify probes of differing specificities that can be selected using the approach outlined herein.

Probes for Uveal Cancer

[0191] Using the above-described methodologies, regions were selected for uveal cancer screening. Table 2 depicts these regions.

[0192]

TABLE 2
Chromo-			General
some	Start	Stop	Location	Descriptor	Size
chr10	89611399	89611920	PTEN, KILLIN	Shore CGI	521
chr11	35503400	35504124	PAMR1	small CGI	724
chr11	1.18E+08	1.18E+08	MPZL2	Prox Prom	599
chr15	60146043	60147120	C2CD4A	Shore CGI	1077
chr17	24370858	24371386	SEZ6	small CGI	528
chr19	11060476	11060965	LDLR	Prox Prom	489
chr2	1.66E+08	1.66E+08	GALNT3	CGI	1465
chr2	2.23E+08	2.23E+08	ccdc140/pax3	Shore CGI	4724
chr6	21774638	21775386	FLI22536/casc15	small CGI	748
chr6	24465699	24466545	KAAG1, DCDC2	CGI	846
chr6	31031220	31031651	MUC21	CGI	431
chr6	70632889	70633262	COL19A1	Proc Prom	373
chr6	1.09E+08	1.09E+08	NR2E1/OSTM1	small CGI	1001
chr7	29996242	29996333	SCRN1	Shore CGI	91
chr1	2450725	2452224	HES5	CGI	1499
chr1	12601228	12601893	DHRS3	Shore CGI	665

Tests for Breast Cancer Subtypes

[0193] The screen that has been described above, which originally incorporated all breast tumours in the TCGA database, can also be done on subsets of the tumour database.

[0194] BRCA1 carriers were taken out of the dataset and analyzed individually to identify target methylated regions specific to this subgroup. Breast cancer can also be divided in other ways: e.g., into five subtypes, Basal, Luminal A., Luminal B, HER2 and Normal-like. Patients in each of these groups were identified and analyzed to identify target methylated regions for each subset.

[0195] The screen can also be changed to look at individual patients using the previously described criteria to see who are positive or negative. Target methylated regions can then be ranked based on how many individuals are positive. This can help to remove biasing due to amalgamation (averaging). Targets can then be selected, e.g., if they are present in greater than 75% of patients for each subtype, and then rationalize amongst these.

Test for BRCA Carriers

[0196] Current monitoring practices for women at high risk of developing breast cancer due to familial BRCA1 or 2 mutations involve yearly MRI, however the high false positive rates result in a large number of unnecessary biopsies. Using the methodology described herein, a test may be developed to serve as a secondary screen, e.g., to be employed after a positive MRI finding; or to be used for primary screening of high risk patients. The blood test is designed to detect all types of breast cancer but because ER+ breast cancer is the most frequent it is biased towards these cancers, though some of the constituent probes do recognize HER2+ and TNBC tumours. In order to provide optimal sensitivity for the monitoring of BRCA1 and 2 an assay optimized for these patients may be developed.

[0197] Both TNBC and BRCA1 and 2 patients were selected from the TOGA 450k methylation database. Generally, most BRCA1 and 2 tumours will present as TNBC but many non-familial cancers are also TNBC. These patients were analyzed using the above-described tumour specific methylation region protocol on both the overall TNBC population and on the BRCA1 and 2 patients. 85 tumour specific regions were identified for TNBC, 67 for BRCA1 and 13 for BRCA2 populations. Of these 39 were present in any two populations and they constitute the starting point for the development of this assay. Appropriate regions for a BRCA1 specific test were identified and assessed in individual patients with known mutations. This population is surprisingly uniform and most patients are recognized by a large number of probes. AUCs for individual probes are for the most part very high. Based on these results, an assay can be developed to detect all three, i.e., TNBC, BRCA1 and 2. If additional detection sensitivity is required, then individual tests can be constructed. For high risk women who are BRCA1 or 2 mutation carriers, their mutation status should be known so that the appropriate test can be applied.

Test for BRCA1 Carriers

[0198] Probes have been developed for the detection of cancer in carriers of the BRCA1 mutation. Methylation data from the TCGA Breast cancer cohort were selected from patients known to be carriers of pathogenic BRCA1 mutations. This data was then analyzed as described to identify regions of the genome specifically methylated in this sub-set of breast cancers. Table 3 lists appropriate regions identified and their genomic locations.

[0199]

TABLE 3
Target Region (hg18 reference)
chr	Nearest Gene	Start (nt)	End (nt)	Size
chr1	LOC105378683	43,023,840	43,023,487	353
chr1	NPHS2	177,811,942	177,811,671	271
chr1	NR5A2	198,278,599	198,278,409	190
chr11	PAX6	31,783,955	31,782,545	1,410
chr11	KCNE3	73,856,332	73,855,762	570
chr12	KCNA6	4,789,491	4,789,342	149
chr12	TMEM132C	127,318,539	127,317,001	1,538
chr13	PDX1	27,390,265	27,389,540	725
chr13	EPSTI1	42,464,618	42,463,901	717
chr16	A2BP1	6,009,930	6,009,020	910
chr16	CRYM	21,202,914	21,202,448	466
chr16	PRKCB	23,755,504	23,754,826	678
chr16	IRF8	84,490,354	84,490,167	187
chr18	SALL3	74,842,145	74,839,705	2,440
chr19	LYPD5	49,016,848	49,016,696	152
chr2:	DPP10	115,636,420	115,635,215	1,205
chr20	C20orf56	22,507,867	22,507,676	191
chr3	SOX2OT	182,919,993	182,919,839	154
chr4	CDKL2	76,774,880	76,774,658	222
chr5	March 11	16,233,072	16,232,633	439
chr5	CCL28	43,433,329	43,432,559	770
chr5	AP3B1	77,304,644	77,304,208	436
chr7	CARD11	3,050,299	3,049,859	440
chr7	BLACE	154,859,799	154,859,051	748
chr7	PTPRN2	157,176,806	157,176,096	710
chr8	RUNX1T1	93,183,481	93,183,326	155

[0200] 52 different probes were then developed to various parts of these regions and the methylation pattern in tumor cell lines was characterized, including MDA-MB-436 and HCC1937 which are known to carry BRCA1 mutations. These probes will be combined with previously characterized probes to other regions which are also methylated in tumours from BRCA1 patients. This would provide for a highly sensitive assay able to detect cancer in these high risk women at the earliest possible stage.

Tests for Other Subtypes

[0201] A number of breast cell lines from women with known BRCA1 mutations have been isolated such as MDA-MB-436, HCC1937 and HCC1395 (all available from ATCC). These may be used to validate the assay as was done for the general blood test. For BRCA2 mutant lines there is only one ATCC cell line at present, HCC1937. There are several BRCA2 mutant ovarian cancer lines that have been identified and they may be used if the bioinformatic analysis confirms that these methylation markers are also found in ovarian cancer. The development of a single assay that detects both breast and ovarian cancer in BRCA2 carriers represents a distinct advantage as it would simultaneously monitor the two primary cancer risks in these patients.

[0202] The development of these assays follows the same course the above-described general assay proceeding from TCGA data to cells lines to patient samples. Tumour banks (some of which have mutation data) can be used for this, and analysis of these tumours provides an indication of their likely BRCA mutation. These samples can also be sequenced to confirm the prediction.

Testing of Cell-Free Samples

[0203] Proof of concept testing was carried out using cell lines for ease of analysis. However, the assay can be applied to test for cell-free DNA, e.g., circulating cell-free tumour DNA in blood, and finds wide application in this context. A sample protocol for circulating tumour DNA is provided.

Sample Protocol: Test for Circulating Tumour DNA

DNA Preparation

[0204] The following example protocol may be used to detect circulating tumour DNA (tDNA).

• • [0205] Obtain DNA to be used for bisulfite conversion and downstream PCR amplification (i.e., cell line, tumour or normal DNA). Determine DNA purity on 0.8% agarose gel.
  • [0206] Determine genomic DNA (gDNA) for concentration in ug/uL by UV spectrophotometry.
  • [0207] Prepare a 1:100 dilution with TE buffer.
  • [0208] Remove RNA contaminates, if necessary, using the purification protocol for the GenElute Mammalian Genomic DNA Miniprep Kit, Sigma Aldrich, CAT #G1N350 (http://www.sigmaaldrich.com/technical-documents/protocols/biology/genelute-mammalian-genomic-dna-miniprep-kit.html). Follow purification protocol from steps A: 2a-3a, step 4−9.
  • [0209] OPTIONAL: For gDNA from a cell line, sonicate gDNA to approximately 90-120 bp (this represents general size of circulating tDNA). To do this, sonicate 5−10 ug of sample (50−100 ng/100 uL) using a sonicator. Use setting 4, and 15 pulses for 30 seconds with 30 seconds rest on ice in between. Determine sonicated DNA purity and bp size on 0.8% agarose gel.
  • [0210] Bisulfite convert DNA—EpiTect Fast Bisulfite Conversion Kit, QIAgen, CAT #59824 (https://www.qiagen.com/us/resources/resourcedetail?id=15863f2d-9d1c-4f12-b2e8-a0c6a82b2b1e&lang=en). Follow bisulfite conversion protocol on pages 1−18, 19−23. Refer to trouble shooting guide pages 30−32. Modifications to the protocol include: 1. Prepare reactions in 1.5 mL tubes, 2. High concentration samples at 2 ug, and low concentration samples at 500 ng-1 ug, 3. Perform the bisulfite conversion using 2 heat blocks set at 95° C. and 60° C., 4. Incubation at 60° C. extended to 20 minutes, to achieve complete bisulfite conversion, 5a Elute DNA in 10-20 uL of elution buffer for ˜50−100 ng/uL final concentration, and 5b Dilute DNA to 10 ng/uL for use in PCR.
  • [0211] Perform nested PCR with Hot Star Taq Plus DNA Polymerase, Qiagen, CAT #203605 (https://www.qiagen.com/ca/resources/resourcedetail?id=c505b538−7399−43b7-ad10-d27643013d10&lang=en).
    Singleplex PCR Amplification
  • [0212] For singleplex PCR amplification of individual probes, carry out a primary PCR reaction with methylation-biased primers (MBP), (primer forward and reverse).

[0213] Table 4 recites reaction components.

[0214]

	TABLE 4
	Component	1X (uL)
	10X PCR Buffer	2.5
	5 mM dNTP's	1
	5 U Hot Star Taq	0.1
	25 mM MgCl2	3
	PCR Grade H2O	17
	[10 ng/uL] DNA	1
	10 pmol FWD Primer	0.2
	10 pmol REV Primer	0.2
	Total	25

[0215] Table 5 lists thermocycler conditions.

[0216]

TABLE 5
Thermocycler Conditions
	Temp.		Time
	95° C.	15	min
	95° C.	30	sec
	58° C.	30	sec	{close oversize bracket}	X 40
	72° C.	30	sec
	72° C.	7	min
	4° C.	∞

• • [0217] Carry out a secondary PCR reaction with universal primers CS1 (Barcode) and CS2 (P1 Adapter). To do this, remove an aliquot from the primary reaction, use as template DNA, this method serves as a two-step dilution PCR reaction

[0218] Table 6 recites reaction components.

[0219]

	TABLE 6
	Component	1X (uL)
	10X PCR Buffer	5
	5 mM dNTP's	2
	5 U Hot Star Taq	0.2
	25 mM MgCl2	6
	PCR Grade H2O	34.4
	MBP PCR Template	2
	10 pmol CS1 Primer	0.2
	10 pmol CS2 Primer	0.2
	Total	50

[0220] Table 7 recites thermocycler conditions.

[0221]

TABLE 7
Thermocycler Conditions
	Temp.		Time
	95° C.	15	min
	95° C.	30	sec
	58° C.	30	sec	{close oversize bracket}	X 3
	72° C.	30	sec
	72° C.	7	min
	4° C.	∞

• • [0222] Determine PCR specificity on 2% agarose gel. Run the methylation-biased PCR product and the CS1 CS2 sequencing PCR product beside one another on the agarose to visualize the banding pattern and increase in bp size. PCR product should be between 200−300 bp

[0223] For Singleplex PCR products, pool 5−10 uL of each PCR reaction (CS1 CS2 Secondary RXN) into a single tube for each sample type. Purify the pooled PCR with Agencourt AMPure XP beads at a 1.2:1 ratio (90 uL beads+75 uL sample), e.g., as below.

Agencourt Ampure XP Bead Purification

[0224] Use freshly prepared 70% ethanol. Allow the beads and pooled DNA to equilibrate to room temperature.

• • [0225] 1. Add indicated volume of Agencourt AMPure XP beads to each sample: 90 uL beads+75 uL Pool (1.2:1)
  • [0226] 2. Pipet up and down 5 times to thoroughly mix the bead suspension with the DNA. Incubate the suspension at RT for 5 minutes.
  • [0227] 3. Place the tube on a magnet for 5 minutes or until the solution clears. Carefully remove the supernatant and store until purified library has been confirmed.
  • [0228] 4. Remove the tube from the magnet; add 200 uL of freshly prepared 70% EtOH. Place the tube back on the magnet and incubate for 30 seconds; turn the tube around twice in the magnet to move the beads through the EtOH solution. After the solution clears, remove and discard the supernatant without disturbing the pellet.
  • [0229] 5. Repeat step #4 for a second EtOH wash.
  • [0230] 6. To remove residual EtOH, pulse-spin the tube. Place the tube back on the magnet, and carefully remove any remaining EtOH with a 20 uL Pipette, without disturbing the pellet.
  • [0231] 7. Keeping the tube on the magnet, air-dry the beads at RT for ˜5 minutes.
  • [0232] 8. Remove the tube from the magnet; add 50 uL of TE directly to the pellet. Flick the tube to mix thoroughly. Incubate at RT for 5 minutes.
  • [0233] 9. Pulse-spin and place the tube back on the magnet for ˜2 minutes or until the solution clears. Transfer the supernatant containing the eluted DNA to a new 1.5 mL Eppendorf LoBind tube.
  • [0234] 10. Remove the tube from the magnet; add 50 uL of TE directly to the pellet. Flick the tube to mix thoroughly. Store the beads, along with the supernatant, at 4° C. until purified library has been confirmed.
  • [0235] 11. Visualize the sample pre- and post-purification on an 8% acrylamide gel (higher resolution). Pooled PCR product should be visualized as multiple bands (as each PCR product is a slightly different bp size). Purified sample should eliminate product beneath 150 bp.

[0236] FIG. 11 depicts a summary of BioAnalyzer electrophoresis summary for amplification product generated from various cell lines.

• • [0237] 12. Perform nested PCR with Multiplex PCR Plus Kit, Qiagen, CAT #206152 (https://www.qiagen.com/ca/resources/resourcedetail?id=beb1f99e-0580−42c5−85d4-ea5f37573c07&lang=en), e.g., as below.
    Multiplex PCR Amplification of up to 50 Probes in a Single Reaction
  • [0238] Create multiplex primer mix by aliquot 1 uL of each forward and reverse primer at 10pmol/uL into a single 1.5 mL tube. Calculate the final concentration of each primer by dividing the initial primer concentration by the final volume of primer mix in the tube, i.e., 15 probes to be multiplexed into a single reaction, would total 30 primers and at 1 uL each, 30 uL final volume. Thus ((10pmol)(1 uL))/30 uL=0.333pmol. Primer concentration requires optimization during PCR amplification, as the number of primers in a single reaction can influence the efficiency of the product, e.g.
  • [0239] 15 primer sets ˜2pmol final [ ] in PCR
  • [0240] 50 primer sets ˜0.5pmol final [ ] in PCR
  • [0241] Carry out primary PCR reaction with methylation-biased primers.

[0242] Table 8 lists reaction components for multiple amplifications of 15 probes, and Table 9 lists reaction components for multiple amplifications of 50 probes. Table 10 list reaction conditions.

[0243]

TABLE 8
15 primer pairs at 2 pmol
	Component	1X (uL)
	2X Multiplex MM	25
	PCR H2O	18
	Primer Mix	6
	[10 ng/uL] DNA	1
	Total	50

[0244]

TABLE 9
50 primer pairs at 0.5 pmol
	Component	1X (uL)
	2X Multiplex MM	25
	PCR H2O	19
	Primer Mix	5
	[10 ng/uL] DNA	1
	Total	50

[0245]

TABLE 10
Thermocycling Conditions
	Temp.		Time
	95° C.	5	min
	95° C.	30	sec
	58° C.	90	sec	{close oversize bracket}	X 35
	72° C.	90	sec
	68° C.	10	in

• • [0246] Determine PCR specificity on 2% agarose gel. Multiplex products should be visualized with multiple banding pattern between 100−300 bp.

[0247] Pooling is not required for multiplex products, as the probes have already been combined and amplified into a single tube/reaction.

• • [0248] Purify the pooled PCR with Agencourt AMPure XP beads at a 1.2:1 ratio (60 uL beads+50 uL sample) (refer within document for purification protocol).
  • [0249] After PCR amplification, along with pooling and purifying, the samples can be quantified by qPCR, e.g., Ion Library Quantification Kit, TaqMan assay quantification of Ion Torrent libraries, Thermo Fisher Scientific, CAT #4468802 (https://tools.thermofisher.com/content/sfs/manuals/4468986_lonLibraryQuantitationKit_UG.pdf)
  • [0250] 1. Create a standard curve of 6.8 pM, 0.68 pM, 0.068 pM, 0.0068 pM
  • [0251] 2. Dilute samples 1:1000, and run in duplicate
  • [0252] 3. Perform qPCR assay on the Step One Plus Real Time machine by Life Technologies
  • [0253] 4. Sample libraries quantified ≥100 pM can proceed to be sequenced on the Life Technologies Ion Torrent Sequencing platform
    Life Technologies Ion Torrent PGM Sequencing lon PGM Template OT2 200.
  • [0254] Perform template reaction with Ion PGM Template OT2 200 Kit, Thermo Fisher Scientific, CAT #4480974. Kit contents to be used on the One Touch 2 and Enrichment system (https://tools.thermofisher.com/content/sfs/manuals/MAN0007220_Ion_PGM_Template_OT2_2 00_Kit_UG.pdf
  • [0255] Utilizing library quant. obtained from qPCR, dilute libraries appropriately to 100 pM. Follow Life Technologies guide on how to further dilute libraries for input into final template reaction.
  • [0256] Follow reference guide to complete template reaction
    • [0257] Run the Ion One Touch 2 instrument
    • [0258] Recover the template positive ISPs
    • [0259] Enrich the template positive ISPs with the Ion One Touch ES
      Ion PGM Sequencing 200
  • [0260] Perform sequencing reaction with Ion PGM Sequencing 200 kit, Thermo Fisher Scientific, CAT #4482006. Kit contents to be used on the Ion PGM system (https://tools.thermofisher.com/content/sfs/manuals/MAN0007273_lonPGMSequenc_200 Kit_v2_UG.pdf).
  • [0261] Plan sequencing run
    • [0262] Select chip capacity (314, 316 or 318)
    • [0263] Determine sequencing flows and bp read length (i.e., 500 flows and 200 bp read length)
  • [0264] Follow reference guide to complete PGM sequencing
    • [0265] Prepare enriched template positive ISPs
    • [0266] Anneal the sequencing primer
    • [0267] Chip check
    • [0268] Bind sequencing polymerase to the ISPs
    • [0269] Load the chip
    • [0270] Select the planned run and perform sequencing analysis

[0271] Sequencing data analysis and work flow

• • [0272] Obtain run report generated by the PGM and Torrent Browser
  • [0273] Run report includes the following information
    • [0274] ISP Density and loading quality
    • [0275] Total reads generated and ISP summary
    • [0276] Read length distribution graph
    • [0277] Barcoded samples: reads generated per sample and mean read length
  • [0278] Obtain uBAM files generated by the PGM, available for download to an

[0279] external hard drive

• • [0280] Bioinformatics data analysis
    • [0281] Upload uBAM files to a web based bioinformatics platform, Galaxy GenAp
      • [0282] Perform quality control analysis (i.e., basic statistics and sequence quality check)
      • [0283] Convert data files: BAM SAM FastQ
      • [0284] Filter FastQ file: select bp size to trim (i.e., trim sequence <100 bp)
      • [0285] Convert data files: FastQ FastA
      • [0286] Download FastA file
    • [0287] Upload FastA files to BiqAnalyzer software platform
      • [0288] Create project
      • [0289] Add sample
      • [0290] Load reference sequence
      • [0291] Set gap extension penalty and minimal sequence identity
      • [0292] Link in FastA files to samples and reference sequences
      • [0293] Analyze and collect data files (pattern maps and pearl necklace diagrams)

Uveal Melanoma Test

[0294] The molecular biology of uveal melanoma (UM) is simpler than that of breast cancer, with minimal mutations and rearrangements, and only two major sub-types which correspond to the retention or loss of chromosome 3p. A test was developed for UM which is superior to current state of the art blood assays.

[0295] Analysis of 450k methylation TCGA data for 80 UMs allowed for the identification of regions of tumour specific methylation in both 3p- and 3pWT tumours using our algorithm. Table 11 shows 16 hypermethylated regions in both 3p- and 3pWT tumours used for probe development and testing, according to one embodiment.

[0296]

TABLE 11
Gene	Chr	start	stop	Size	CGI CpGs
PTEN, KILLIN	chr10	89611399	89611920	521 Shore CGI	171
PAMR1	chr11	35503400	35504124	724 small CGI	19
MPZL2	chr11	117640011	117640610	599 Prox Prom
C2CD4A	chr15	60146043	60147120	1077 Shore CGI	127
SEZ6	chr17	24370858	24371386	528 small CGI	34
LDLR	chr19	11060476	11060965	489 Prox Prom
GALNT3	chr2	166358156	166359621	1465 CGI	98
ccdc140/pax3	chr2	222881305	222886029	4724 Shore CGI	72
FLI22536/casc15	chr6	21774638	21775386	748 small CG	18
KAAG1, DCDC2	chr6	24465699	24466545	846 CGI	56
MUC21	chr6	31031220	31031651	431 CGI	46
COL19A1	chr6	70632889	70633262	373 Proc Prom
NR2E1/OSTM1	chr6	108542808	108543809	1001 small CG	34
SCRN1	chr7	29996242	29996333	91 Shore CGI	133
HES5	chr1	2450725	2452224	1499 CGI	111
DHRS3	chr1	12601228	12601893	665 Shore CGI	133

[0297] The top 14 of these common regions were carried forward for probe development and a total of 26 different probes were characterized, with several regions having up to three probes targeting them. Each of these probes was then validated using six different UM cell lines to assess their methylation status. As negative controls, DNA from peripheral blood mononuclear cells (PBMCs), which are the main source of contaminating DNA in blood samples, as well as a pool of cell free DNA (cfDNA) from 16 individuals, were also tested (FIG. 15). These results indicated that the majority of the probes tested showed tumour specific methylation with little or no methylation in the negative controls. A total of 18 probes from 12 different regions were combined into a multiplex PCR reaction and used to analyze cell free DNA from plasma for a previously characterized cohort of metastatic UM patients.

[0298] The validated regions were C2CD4A, COL19A1, DCDC2, DHRS3, GALNT3, HES5, KILLIN, MUC21, NR2E1/OSTM1, PAMR1, SCRN1, and SEZ6. The validated probes were C2C5F, COL2F, DCD5F, DGR2F, GAL1F, GAL3F, HES1F, HES3F, HES4F, KIL5F, KIL6F, MUC2F, OST3F, OST4F, PAM4F, SCR2F, SEZ3F, and SEZ5F.

[0299] These patients were previously tested using the pyrophosphorolysis-activated polymerization (PAP) assay²⁶, which detects the frequent GNAQ or GNA11 mutations in UM27. In all cases the test detected cancer in these patients even when the PAP assay failed to register a signal (FIGS. 16 and 17). Most of the probes functioned like methylation specific PCR reactions, only giving product when there was tumour DNA present though with the additional validation that the specificity of each probe was guaranteed by the presence of multiple methylated CpG residues within each read. In two patients from which serial blood samples were obtained (FIGS. 18A and 18B) the test showed increased tumour levels over time even when the final tumour volume was 0.5 cm³ (FIG. 18A). The test was also generally correlated with the volume of tumour, though the nature of the metastatic tumour as either a solid mass or dispersed has not yet been accounted for (FIG. 19). The levels detected by the test were generally in line with those of the PAP assay and notably gave a signal where PAP failed due to the lack of a mutation (FIG. 16, UM32). Where no or limited amounts of tumour DNA were detected by PAP, the test still gave significant signals (FIG. 20). Even greater sensitivity is expected when the total number of reads analyzed per patient is increased, as this run had less than optimal overall reads due to the presence of large amounts of primer dimer, an issue that has now been resolved. The specificity of the test was demonstrated by the extremely low levels of methylation seen in the pool of 16 cfDNA controls. Overall, the test has been validated in a patient population, and it has been shown to be superior to a state of the art mutation based assay.

Prostate Cancer Test

[0300] An important aspect of any test is that it should be applicable to all patients. Based on our experience it is essential to consider specific subtypes of a given cancer to ensure that all patients are detected by the assay. The TCGA analysis of a large prostate cohort revealed sub-groups based on specific mutations and transcriptional profiles²⁸. Four subtypes were identified based on the overall pattern of methylation found in these tumours. In this example the TCGA prostate cohort was divided into groups based on the methylation pattern and subjected to methylation analysis.

[0301] Table 12 lists 40 regions associated with all sub-types of prostate cancer.

[0302]

	TABLE 12
	HES5	ANXA2	HLA-F	HAAO
	LOC376693	RHCG	PON3	RARB
	CSRP1	RARA	LRRC4	ALDH1L1
	ALOX5	PTRF	HLA-J	HIST1H3G
	PPM1H	RND2	PAH	ZSCAN12
	MON2	TMP4	EPSTI1	HCG4P6
	KIAA0984	HIF3A	ADCY4	EYA4
	TXNRD1	KLK5	HAPLN3	HOXA7
	CHST11	AMOTL2	AX747633	HSF4
	EFS	SCGB3A1	NBR1	TMEM106A

[0303] These regions common to all four methylation subtypes were identified and a total of 38 probes from 33 regions were selected and appropriate “biased” PCR probes were generated. These were characterized using four different prostate cancer lines. DU145 is an androgen receptor (AR−) negative cell line that is able to generate metastases in the mouse. PC3 is also AR- and also metastatic. LNCaP is an androgen receptor positive line (AR+) that is non-metastatic in the mouse while RWPE cells are AR+ and non-metastatic. DNA from PBMC was also tested as this represents the primary source of cell free DNA in the circulation.

[0304] A total of 34 probes from 33 regions were validated in that they showed little or no methylation in PBMCs while showing large scale methylation in one or more of the tumour cell lines (FIG. 21).

[0305] The validated regions were ADCY4, ALDH1L1, ALOX5, AMOTL2, ANXA2, CHST11, EFS, EPSTI1, EYA4, HAAO, HAPLN3, HCG4P6, HES5, HIF3A, HLA-F, HLA-J, HOXA7, HSF4, KLK4, LOC376693, LRRC4, NBR1, PAH, PON3, PPM1H, PTRF, RARA, RARB, RHCG, RND2, TMP4, TXNRD1, and ZSCAN12.

[0306] The validated probes were ADCY4-F, ALDH1L1-F, ALOX5-F, AMOTL2-F, ANXA2-F, CHST11-F, EFS-F, EPSTI1-F, EYA4-F, HAAO-F, HAPLN3-F, HCG4P6-F, HES5-F, HIF3A-F, HLA-F-F, HLA-J-1-F, HLA-J-2-F, HOXA7-F, HSF4-F, KLK4-F, LOC376693-F, LRRC4-F, NBR1-F, PAH-F, PON3-F, PPM1H-F, PTRF-F, RARA-F, RARB-F, RHCG-F, RND2-F, TMP4-F, TXNRD1-F, and ZSCAN12-F.

[0307] To these 34 probes an additional 12 probes (from 7 regions) were added that had previously been characterized in breast cancer, which were also able to detect prostate cancer, for a total of 46 probes.

[0308] The added probes were C1Dtrim, C1Etrim, CHSAtrim, DMBCtrim, FOXAtrim, FOXEtrim, SFRAtrim, SFRCtrim, SFREtrim, TTBAtrim, VWCJtrim, and VWCKtrim.

[0309] These probes were multiplexed together and were then used to analyze plasma samples from five patients before they had initiated androgen deprivation therapy (ADT) and 12 months after starting treatment. These patients were part of a small cohort (˜40 patients) being followed for depression and the plasma samples at 0.5 ml were much smaller than normally used for the assay (2 mls). All of the patients were MO with no sign of metastatic disease when placed on ADT.

[0310] A variety of probes were positive depending on the particular patient (FIG. 22). The total number of positive probes was in keeping with the total number of methylated reads, which were normalized for total reads for each sample (FIG. 23). In all cases significant ctDNA signals were observed with results that were notably different than PSA results (FIG. 24). Two of the patients, TM19 and RM26 were started on ADT due to their aggressive diseases (T3A and T3B) despite having low PSA levels. PSA levels for both remained low but methylation detection of circulating tumour DNA (mDETECT) either decreased slightly (TM19) or rose dramatically (RM26) suggesting their diseases did not express PSA but had stable or increasing disease. HS29 showed decreased PSA levels which mDETECT paralleled. Both GL20 and GP27 trended in opposite directions to PSA levels with mDETECT increasing even with dramatic drops in PSA levels. GL20 did develop a radiation induced secondary cancer which may be what is detected. Ongoing analysis of additional clinical data is expected to help explain these results.

[0311] Based on the literature, three of these regions appear to have prognostic significance as well. C1orf114 or CCDC1 has been shown to be correlated with biochemical relapse. HES5 is a transcription factor that is regulated by the Notch pathway and methylation of its promoter occurs early in prostate cancer development. KLK5 is part of the Kallikrein gene complex that includes KLK3 (the PSA gene). We can demonstrate that KLK5 expression is correlated with methylation and KLK5 expression has previously been shown to be increased in higher grade tumours. These results strongly suggest that the examination of a large number of methylation markers may yield significant insight into the specific processes involved in prostate cancer development and produce diagnostic and prognostic information that would be vital for management of the disease.

Predictive Prostate Cancer Methylation Biomarkers

[0312] The 50 region assay according to embodiments described herein is sufficiently sensitive to easily detect metastatic disease and to follow changes in tumour size over time and, as indicated, has predictive value in itself. As described above, at least three regions, KLK5, HER5, and C1orf114 have potential to predict progression. In order to develop additional probes that are able to predict outcome in this patient population, the prostate cancer TCGA data was reanalysed to divide the patients by Gleason score. An inter-cohort comparison was conducted to identify regions frequently methylated in higher score cancers. Initially, Gleason grades 6 and 9 were compared as these typically represent less and more aggressive tumours and both groups had sufficient numbers of patients to ensure significance of the results. Probe development was carried out under the same criteria as with the original probe sets so that they could be used with ctDNA. No single probe will be absolutely specific for a given grade but a number of the probes showed excellent division between Gleason scores with the proportion of the cohort positive for a given grade increasing with increasing grade (FIG. 25). One of these, PSS3, is a gene whose expression has previously been associated with prostate cancer and particularly metastasis. It should be noted that not all methylation is associated with gene repression. Forty-three new probes were developed based on selection criteria to target the 36 regions shown in Table 13, which are associated with aggressive prostate cancer.

[0313]

TABLE 13
ASAP1	EMX1	MIR1292	SOX2OT
BC030768	HFE	NBPF1	TUBB2B
C18orf62	HIST1H3G/1H2BI	NHLH2	USP44
C6orf141	HMGCLL1	NRN1	Intergenic (Chr1)
CADPS2	KCNK4	PPM1H	Intergenic (Chr8)
CORO1C	KJ904227	PPP2R5C	Intergenic (Chr2)
CYP27A1	KRT78	PRSS3	Intergenic (Chr3)
CYTH4	LINC240	SFRP2	Intergenic (Chr4)
DMRTA2	Me3	SLCO4C1	Intergenic (Chr10)

[0314] The probes were ASAP1/p, BC030768/p, C18orf62/p, C6orf141/p-1, C6orf141/p-2, CADPS2/p, CORO1C/p-1, CORO1C/p-2, CYP27A1/p, CYTH4/p, DMRTA2/p, EMX1/p, HFE/p-1, HFE/p-2, HIST1H3G/1H2BI/p, HMGCLL1/p, KCNK4/p, KJ904227/p, KRT78/p, LINC240/p-1, LINC240/p-2, Me3/p-1, Me3/p-2, MIR129, NBPF1/p, NHLH2/p, NRN1/p, PPM1H/p-1, PPM1H/p-2, PPP2R5C/p, PRSS3/p, SFRP2/p-1, SFRP2/p-2, SLCO4C1/p, SOX2OT/p, TUBB2B/p, USP44/p, Chr1/p-1, Chr2/p-1, Chr3/p-1, Chr4/p-1, Chr8/p-1, and Chr10/p-1.

[0315] It is expected that it will be an overall pattern of hypermethylation, rather than a single probe, that will have the greatest predictive power.

Breast Cancer Test

[0316] One approach described herein for identifying hypermethylated regions in breast cancer focused on the most frequently methylated regions within the TCGA database. Due to the large number of LumA and LumB patients in this dataset there was a significant under-detection particularly of the Basal class of tumours.

[0317] Accordingly, the data were reanalyzed based on the four molecular subtypes LumA, LumB, Her2 and Basal. The Normal-like subtype is not very frequent in the dataset and as expected is very close to normal tissue, however a small number of regions recognizing this subtype were also included. Overall, methods and probes were developed and tested for over 230 different regions (some with multiple probes), and these have been validated using a variety of breast cancer cell lines and tumour samples. Some regions are subtype-specific but most recognize multiple subtypes. These have been assembled into a single test incorporating 167 different probes which recognize all subtypes (FIGS. 26A, 26B, and 26C), with all patients being recognized by a significant number of probes. By looking at just the top 20 probes for each subtype this test has an area under the curve (AUC) per subgroup from 0.9078 to 0.9781, indicating that high detection rates have been achieved for all types of tumours (FIG. 27). This also means that the test is able to identify the subtype of tumour based on the distribution of probe methylation.

[0318] Another test specific for the triple negative breast cancer (TNBC) subtype was developed from the larger set of general regions identified as described above. This test incorporates 86 probes from 71 regions, listed in Table 14.

[0319]

TABLE 14
CCL28	PTPRN2	UDB	IRF4	HOXA9	HINF1B	POU4F1
PAX6	BARHL2	TMEM90B	SOX2OT	NT5E	TNFRSF10D	VWC2
PPFIA3	PRSS27	C1orf114	TSPAN33	DPP10	CD38	BRCA1
SPAG6	DMRTA2	ITPRIPL1	CA9	FOXA3	CHST11	HOXB13
TMEM132C	NR5A2	GIPC2	IRF8	C5orf39	FABP5	OTX2
DMBX1	BOLL	ERNA4	CRYM	PTGDR	Intergenic5
TAL1	SLC7A4	MAST1	GNG4	SALL3	EVX1
TOP2P1	LEF1	DRD4	DDAH2	ID4	ACVRL1
PRDM13	CARD11	Intergenic 8	EPSTI1	GABRA4	TBX15
GALR3	NFIC	TCTEX1D1	TTBK1	PRKCB	ALX1
CDKL2	PDX1	PHOX2B	SCAND3	NPHS2	SIM1

[0320] The probes were ALX1, AVCRL1, BRCA1-A, C1Dtrim, C1 Etrim, CA9-A, CARD11-B, CCL28-A, CD38, CDKL2-A, CHSAtrim, CRYM-A, DMBCtrim, DMRTA2exp-A, DPP10-A, DPP10-B, DPP10-C,DRD4-A, EFNA4-B, EPSTI1, EVX1, FABP5, FOXAtrim, FOXEtrim, GALR3-A, GIPC2-A, HINF C trim, HOXAAtrim, HOXACtrim, HOXB13-A, Int5, Int8, IRF8-A, ITRIPL1, LEF1-A, MAST1 A trim, mbBARHL2 Trim, mbBOLL Trim, mbC5orf Trim, mbDDAH Trim, mbDMRTA Trim, mbGABRA A Trim, mbGABRA B Trim, mbGNG Trim, mbID4 Trim, mbIRF Trim, mbNT5E Trim, mbSIM A Trim, mbTBX15 Trim, NFIC—B, NFIC-A, NPSH2-B, NR5A2-B, OTX2-A, PAX6-A, pbDMRTA Trim, pbGNG Trim, pbSCAND Trim, pbTAL Trim, PDX1exp-B, PHOX2B-A, POU4F1 A trim, PPFIA3-A, PRDM13, PRKCB-A, PRKCB-C, PRSS27-A, PTGDR, PTPRN2-A, PTPRN2-B, SALL3-A, SALL3-B, SLC7A4-A, SOX2OT-B, SPAG6 A trim, TCTEX1D1-A, TMEM-A, TMEM-B, TMEM90B-A, TNFRSF10D, TOP2P1-B, TSPAN33-A, TTBAtrim, UBD-A, VWCJtrim, and VWCKtrim.

[0321] The ability of this test to detect TNBC was validated by the analysis of 14 TNBC primary tumours as well as matched normal tissue from four of these patients. Large scale methylation was observed for the majority of probes and was distinctly different from the normal samples (FIG. 28).

Sensitivity of the Tests

[0322] The tests described herein are designed to detect less than one genome's worth of DNA in a sample through the use of multiple regions where a single probe out of many can signal the presence of a tumour. The more regions and probes incorporated into a test the greater is the sensitivity. This is in contrast to mutation detection where the presence of a single mutation per genome equivalent means that random sampling effects rapidly limit sensitivity when the concentration of the tumour DNA falls below one genome equivalent per sample. The presence of large amounts of normal DNA in fluid samples also creates problems for the detection of mutations through the relatively high error rates for PCR and sequencing. To assess the limits of methods and tests described herein, a dilution experiment was performed wherein DNA from a TNBC cell line (HCC1937 DNA) was diluted into a constant amount of PBMC DNA (10 ng) from a normal patient (FIG. 29). These samples were then tested using the TNBC test. A conclusive signal was obtained from the test even when as little as 0.0001 ng of TNBC DNA was present in 10 ng of PBMC DNA. This represents a detection of 0.03 genome equivalents of tumour DNA against a background of 100,000 times more normal DNA.

[0323] The sensitivity of mutation based detection tests is limited by their detection of single unknown mutations in genes, such as p53 or ras. As only a single mutation is present per genome equivalent, this dramatically limits the sensitivity of these assays. Once the concentration of tumour DNA in the blood decreases to less than one genome equivalent per volume of blood analysed, the probability of detecting a mutation decreases dramatically as that particular segment of DNA may not be present in the blood sample. The assay described herein incorporates multiple probes for multiple regions from across the genome to dramatically increase sensitivity. For example, up to 100 or more probes may be incorporated into the assay, making it up to 100 or more times more sensitive than mutation based tests.

[0324] Circulating tumour DNA may be produced by the apoptotic or necrotic lysis of tumour cells. This produces very small DNA fragments in the blood. With this in mind, PCR primer pairs were designed to detect DNA in the range of 75 to 150 bp in length, which is optimal for the detection of circulating tumour DNA.

[0325] The use of DNA methylation offers one more advantage over mutation based approaches. Mutated genes are typically expressed in the cells (such as p53). They are thus in loosely compacted euchromatin, in comparison to methylated DNA which is in tightly compacted heterochromatin. This methylated and compacted DNA may be protected from apoptotic nucleases, increasing its concentration in the blood in comparison to these less compacted genes.

[0326] Extensive analysis of the genome wide methylation patterns in breast, colon, prostate and lung cancers and normal tissue in each of these organs based on TCGA data was carried out. 52 regions were identified for breast cancer which fulfill design criteria, which looks for an optimal difference in methylation between tumour and normal breast tissue, and where there is no methylation in any of the other normal tissues. As well, there should optimally be at least 2 CpG residues within 200 basepairs of each other. This ensured that regions of coordinated tumour specific methylation have been identified.

[0327] Within these 52 regions, 17 were found in common with colon cancer, and 9 in common with prostate cancer. Interestingly there were few appropriate regions identified in lung cancer, with only 1 overlapping with breast cancer. Most of these regions are associated with specific genes, though several are distantly intergenic, and almost all were found in CpG islands of various sizes. Probes were first developed for those regions with some commonality between cancers and designed PCR primers which recognize the methylated DNA sequence. This provides a bias in the amplification process for tumour DNA, enriching the tumour signal. These primer pairs amplify regions of 75 to 150 bp in accordance with our design criteria. Typically these regions contain from 3 to 12 CpG residues each, ensuring a robust positive signal when these regions are sequenced. Multiple non-overlapping probes were used as the CpG islands are generally larger than 150 bp, allowing for multiple probes for each appropriate region, providing more power to detect these regions and increasing the detection sensitivity of the assay.

[0328] Six different breast cancer lines were used in this validation analysis that have been shown to generally retain tumour specific methylation patterns²². MCF-7 and T47D lines are classic ER+ positive cell lines representing the most frequent class of breast cancer. SK-BR-3 cells are a HER2+ line and MDA-MB-231 cells represent a Triple Negative Breast cancer (TNBC), thus the 3 main categories of breast cancer are represented covering 95% of all tumours. Two “normal” lines were also used, the MCF10A line, though this line has been shown to contain some genomic anomalies, and the karyotypically normal 184-hTERT line. DNA was bisulphite converted, and the probes were amplified individually, barcoded then pooled according to cell line and subject to Next Generation Sequencing on an Ion Torrent sequencer. Not all PCR primer pairs produced a product due to the methylation-based nature of the primers, but in general, where a signal was detected, around 1000 reads were obtained per probe for each cell line. These reads were processed through our NGS pipeline using Galaxy and then loaded into the NGS methylation program BiqAnalyzer^23,24. This program extracts probe specific reads, aligns them against the probe reference sequence, and calls methylated and unmethylated CpGs. It also carries out quality control measures related to bisulphite conversion and alignment criteria. In all of these probes there are several CpG residues within the primer sequence producing a bias towards amplifying methylated DNA. The analysis shown only includes CpGs outside of the primers which are solely representative of the methylation status of the sample being analysed.

[0329] FIGS. 5 and 6 depict results for the CHST11 gene, which is a good example where robust PCR primers are able to recognize tumour specific methylation. Four different primer pairs were assessed, three of which amplify probes that partially overlap. In all four cases these regions are completely methylated at all CpGs (not including CpGs in the primers) and are essentially completely unmethylated in the normal lines. CHST11 primers do not recognize the Her2 or TNBC lines, but other primers such as ADCY and MIRD do. The corresponding probes cover a small region of the CpG island and information about the status of the rest of the CpG island is limited due to the relatively coarse resolution of the 450K methylation data. Clearly the remaining part of the CpG island can be developed for additional probes that would increase the sensitivity of detection.

[0330] FIG. 7 shows that FOXA probe A had similar characteristics and recognized all but one TNBC tumour. This proves that the target and probe development pipeline moving from TCGA data to cell lines and then to patient normal and tumour tissue successfully identified primer pairs that are able to specifically recognize tumour DNA based on their methylation patterns.

[0331] Validation work continues to validate potential probe regions. A further 24 regions were characterized using 52 different probes in the cell lines as an initial screen for their suitability.

[0332] FIG. 4 shows the results of analysis of all of the potential CpGs identified in the TCGA cohort for individual patients indicates most patients are recognized by a large proportion of these probes.

[0333] FIG. 3 shows the results of ROC analysis²⁵ and indicates each of these probes has a very high AUC, suggesting excellent performance individually and presumably even better when combined.

[0334] It has been noted that there does appear to be a population of patients with relatively few positive probes. This is not subtype specific and other probes specific for this population have been identified. As appropriate, additional probes will be developed for all suitable regions and expanded to include other parts of the associated CpG islands. Overall it is expected that 100−150 separate probes in the assay will provide optimal sensitivity.

[0335] FIGS. 12A and 12B depict a numerical summary of validation data, wherein “#Reads” indicates the number of reads, and “Mean” Me indicates the mean methylation observed in results. Approximately half of the probes met the design criteria of having complete methylation of all CpG residues in the tumour samples and little or no methyation in the normal lines.

[0336] The next step in validating each of these probes was to examine their methylation patterns in actual patient tumour samples. A small cohort of patient samples was used to investigate GR methylation. From this group three ER+ tumours (one of which is positive for GR methylation), one HER2+ tumour and two TNBC tumours were chosen, as well as their corresponding normal controls. Taking the CHST11A probe as an example, FIG. 6 shows that all six of the normal breast tissue samples had either no reads due to the methylation biased amplification yielding no product or minimal methylation. In no case was there any concerted methylation signal where all CpGs were methylated. In contrast, in one TNBC and one ER+PR+ tumour a strong concordant methylation signal was seen at all six CpG sites. The other 2 ER+PR+ tumours also showed consistent methylation at four or five CpGs with their normal breast tissue controls having minimal reads with only one CpG showing any methylation.

[0337] FIGS. 13A and 13B depict a numerical summary of generated methylation data for tumour samples for all probes tested to date. #Reads is indicative of the number of reads exported, and Mean Me is indicative of the mean methylation.

[0338] Initial proof of concept work involved mixing experiments where non-methylated and methylated DNA was mixed in increasing ratios. This demonstrated that based in the presence of multiple CpG signatures methylated DNA could easily be detected in the presence of at least a 500 fold excess of unmethylated DNA. These probes were amplified with PCR primers that were not methylation specific or biased, and the probes developed to date do incorporate a bias towards methylated DNA, which further increases the detection sensitivity. However, they do amplify non-methylated DNA (in part because primers were designed with no preference as to the location of methylation sites within the primers). This was done intentionally as it provides for a potential quantitative aspect to this assay. Some of the circulating normal DNA in blood samples is likely from the lysis of nucleated blood cells, which is why serum is preferred over plasma as a source of DNA. However the ratio of tumour to normal DNA in blood may provide some quantitation of the actual concentration of tumour DNA present in the blood, which is thought to be correlated with tumour load. Since tumour can be distinguished from normal DNA reads, the ratio between them can be used as a proxy for the tumour DNA concentration. The number of tumour specific reads per volume of blood, regardless of the number of normal reads, may also prove to be closely linked to circulating tumour DNA levels.

[0339] Optimizing this test may include multiplexing to allow all of the probes the opportunity to amplify their targets in a given sample of DNA. Through the use of limited concentrations of primers and cycles, excellent amplification of all probes was obtained within a set of 17 primer pairs. Expanding this to include all of the optimized primers is not expected to be an issue.

[0340] The test may be implemented as a blood based breast cancer detection system in patient blood samples.

[0341] Based on development and validation work to date, the assay offers significant advantages other current and developing tests based on sensitivity, specificity, and detection sensitivity.

[0342] Some potential applications of the embodiments described herein are listed below by level of detection sensitivity:

• • [0343] Determining response to neo-adjuvant chemotherapy;
  • [0344] Monitoring tumour load in diagnosed patients;
  • [0345] Detecting residual disease post-surgery;
  • [0346] Detecting relapse;
  • [0347] Secondary screen after positive MRI in high risk patients;
  • [0348] Direct monitoring of high risk patients; and
  • [0349] Primary population screening.

[0350] The analysis of patients with active breast cancer offers the ability to assess a number of different aspects of this blood based test. Patients with locally advanced disease can be recruited preferentially, as these patients generally have larger tumours, receive neo-adjuvant therapy, are more likely to have residual disease and are at higher risk of relapse. By analysing blood samples from these patients upon diagnosis, after any neo-adjuvant treatments, pre-surgery, and at followup visits post-surgery it is possible to follow the relative tumour burden in these patients over the course of treatment. This will allow the tumour size and type to be correlated with the results of the test described herein.

[0351] Patients can be recruited in the clinic after a biopsy confirmed positive diagnosis. Blood can be drawn in conjunction with other routine blood work at diagnosis, after neo-adjuvant treatment, before surgery, within a month after surgery and every 3−6 months following that. Blood from 50 aged matched women without disease can also be collected from the community to provide control samples for the patient cohort. Relevant clinical data can be collected including radiological assessments and/or pathology reports. In particular, the receptor status of the tumours, the size of the tumour based on both radiological assessment and examination of the excised tumour, as well as treatments and response to therapy can be correlated with the circulating DNA analysis.

[0352] The assay described herein is expected to be quantitative at different levels. At very low levels of tumour DNA, the random presence of the tumour DNA in a sample will result in a subset of individual probes being positive, with the number of positive probes increasing with greater tumour DNA levels. At higher levels of tumour DNA the number of tumour specific reads will increase, either as an absolute number or in relation to the number of normal DNA reads. As a result methylation data can be treated in three ways:

• • [0353] (1) As a binary outcome where each probe will be considered to be positive if it has any tumour specific methylation pattern present;
  • [0354] (2) An individual threshold of methylation will be established for each probe based on the minimum number of reads required to call a tumour; or
  • [0355] (3) Tumour specific reads per number of normal reads for each probe (or, e.g., per 100,000 total reads).

[0356] Each of these approaches may be used to carry out logistic regression on the patient and control sets. Receiver Operating Characteristic (ROC) analysis may be used to define thresholds for each probe that maximizes the sensitivity and sensitivity of the assay. The performance of the entire assay may be characterized using Area Under the Curve (AUC) analysis for overall sensitivity, specificity, classification accuracy and likelihood ratio. Pearson or Spearman correlations may be used to compare patient parameters with the test outcomes.

[0357] Changes in methylation may be important drivers of breast cancer development and that these occur very early during the process of transformation. This may explain why many of the observed methylations are common amongst different breast cancer sub-types, while some are even common to other cancers. This may mean that these changes predate the development of full malignancy and suggests that they could also have value in assessing the risk of a women developing breast cancer. It is envisaged that the assay described herein can be used to track the accumulation of risk in the form of increasing gene specific methylation levels and could be used to develop a risk assessment tool. This would be useful for the development and assessment of risk mitigation and prevention strategies.

[0358] Table 15 lists the primers used herein for each probe.

[0359]

		SEQ			PCR
		ID	5′-3′Primer Sequence		Product
Gene	Probe	NO.	(Bisulfite)	Chr: Location	Length
C1orf114/	C1Df	1	TTGAGGTAAAGGAGATTTCGGT	chr1: 167663228-	134
CCDC18	C1Dr	2	ACATACGCCTACGCAAATTTTTA	167663361
	C1Ef	3	TTCGGTGTTTGCGAAGGGTTA	chr1: 167663398-	111
	+C1Er	4	TCACAACCAACACAACGACACTT	167663508
	C1Er	5	ACAACCAACACAACGACACTT
	C1Ff	6	TCGGTATTTGTTTTCGCGGT	chr1: 167663245-	112
	C1Fr	7	CGCCTACGCAAATTTTTATCGC	167663356
	C1Gf	8	CGAGAGCGATAAAAATTTGCGT	chr1: 167663330-	88
	C1Gr	9	ACCCTTCGCAAACACCGAAA	167663417
	C1 eAf	10	GGTAATAGCGTGTTTTTGC	chr1: 167663285-	82
	C1 eAr	11	ATATTACATACGCCTACGCAAA	167663366
	C1 eBf	12	TTTGTGTAAAATGCGGCGGT	chr1: 167663149-	118
	C1 eBr	13	CTACCGCGAAAACAAATACCGA	167663266
	C1 eCf	14	ATTTCGGTGTTTGCGAAGGG	chr1: 167663395-	112
	C1 eCr	15	ACAACCAACACAACGACACT	167663506
VWC2	VWCJf	16	TTTCGGTTGTCGGGTTTGGA
	+VWCJf	17	TATTTCGGTTGTCGGGTTTGGA	chr7: 49783871-	133
	VWCJr	18	CCCTCAATCGCTCATCCTCC	49784003
	VWCKf	19	TCGTCGGTCGGTTTAGGATG	chr7: 49784151-	129
	+VWCKr	20	AAAACCGACGCCAAACCTACAT	49784279
	VWCKr	21	AACCGACGCCAAACCTACAT
	VWCLf	22	CGGAGGATGAGCGATTGAGG	chr7: 49783983-	118
	VWCLr	23	TAACGCGCACACCGAACTAA	49784100
	VWCMf	24	CGAGTTGGGGTCGCGATTAT	chr7: 49784021-	150
	VWCMr	25	CATCCTAAACCGACCGACGA	49784170
	VWCNf	26	CGACGCGTTACGGTTGTTTA	chr7: 49783849-	125
	VWCNr	27	CCGCTTCTCCGAAACCAAAC	49783973
	VWC2 eAf	28	TAAGGCGGGGTTTTTAGAGC	chr7: 49783687-	106
	VWC2 eAr	29	TAAAAACTAACGCGCCCG	49783792
	VWC2 eBf	30	GGTTTCGGTGTTATTCGC	chr7: 49783797-	126
	VWC2 eBr	31	CTCCTCTCCGCGAAAAAAT	49783922
	VWC2 eCf	32	CGGAGGATGAGCGATTGAGG	chr7: 49783983-	118
	VWC2 eCr	33	TAACGCGCACACCGAACTAA	49784100
	VWC2 eDf	34	TCGTCGGTCGGTTTAGGATG	chr7: 49784151-	127
	VWC2 eDr	35	AACCGACGCCAAACCTACAT	49784277
	VWC2 eEf	36	GTCGGACGCGTTTTAGTTGG	chr7: 49784315-	110
	VWC2 eEr	37	TCCCTACCGACCTCAACACT	49784424
MIR129-2	MIRBf	38	TGGTTGGGGGATTTTGAGGG	chr11: 43559089-	141
	MIRBr	39	AAACCTCCCCGCCTACCTAT	43559229
	MIRCf	40	GCGGACGGTTTGGAGAAATG	chr11: 43559343-	82
	MIRCr	41	CGCGACTCAATCTCACCACT	43559424
	MIRDf	42	GGAGGTTGGGTTTCGGGATT	chr11: 43559257-	127
	MIRDr	43	GCGCCCCTAAACTCGTATCT	43559383
	MIREf	44	GCGGAGTGGTGAGATTGAGT	chr11: 43559401-	113
	MIREr	45	ACCGACTTCTTCGATTCGCC	43559513
	MIRFf	46	ATAGGTAGGCGGGGAGGTTT	chr11: 43559205-	139
	MIRFr	47	CGATCCCCCAACTCAACCC	43559343
	MIR eAf	48	TGAGTTGGCGGTTTCGTTTG	chr11: 43559004-	122
	MIR eAr	49	CCCGAATCCCCTCTTATCCC	43559125
	MIR eBf	50	CGCGATTTTGTAGTCGGGGT	chr11: 43559156-	96
	MIR eBr	51	TTTCCTATCGCCCCAACACC	43559251
	MIR eCf	52	GGAGGTTGGGTTTCGGGATT	chr11: 43559257-	127
	MIR eCr	53	GCGCCCCTAAACTCGTATCT	43559383
	MIR eDf	54	GATTGAGTCGCGATGGAACG	chr11: 43559413-	81
	MIR eDr	55	GCCGCCTTCAACCCAAAATA	43559494
ADCY4	ADCYFf	56	CGCGAGCGTATAGAGTACGA	chr14: 23873573	163
	ADCYFr	57	ACCCTAACCAACCCCGAAAC	23873735
	ADCYGf	58	TAGCGTCGCGAGCGTATAGA	chr14: 23873567-	188
	ADCYGr	59	AAAAATAACCCGACGCCCGA	23873754
	ADCYHf	60	GGTTTCGTAGAAGAGGTTTTC	chr14: 23873642-	174
	ADCYHr	61	CGCGAAATAATAACGACTTT	23873815
	ADCY4 eAf	62	AGAAGAGGTTTTCGTTGGGGG	chr14: 23873650-	80
	ADCY4 eAr	63	ACCAACCCCGAAACTCGAAA	23873729
	ADCY4 eBf	64	TAGGATTTGGGGTTGGTGCG	chr14: 23873975-	141
	ADCY4 eBr	65	AACGCAACGACGAACGTAAC	23874115
	ADCY4 eCf	66	TGGTAGTGGGGAGATCGAGG	chr14: 23874376-	99
	ADCY4 eCr	67	AAACGCCCCCAACTCTAACC	23874474
DMBX1	DMBAf	68	GTTGCGGACGGCGTAGAT	chr1: 46723984-	149
	DMBAr	69	ACGCTCCCCGAAACAATAACT	46724132
	DMBBf	70	TTGTTAGTTTTGTTAGCGCGG	chr1: 46723919-	75
	DMBBr	71	CGTCCGCAACGATTCATCATC	46723993
	DMBCf	72	TGTTTAGGAGATGGTTCGTGGT	chr1: 46723889-	115
	+DMBCr	73	GCATCTACGCCGTCCGCAAC	46724003
	DMBCr	74	ATCTACGCCGTCCGCAAC
	DMBX1 eAf	75	TGTTTAGACGTGGGTTGGGG	chr1: 46723237-	87
	DMBX1 eAr	76	TCAACTCCACTCACCCCGTA	46723323
	DMBX1 eBf	77	GAGGAGGGTGGAGAGGGTAG	chr1: 46723478-	133
	DMBX1 eBr	78	ATACCGCACGTACTCCCAAC	46723610
	DMBX1 eCf	79	GGAGTGGAGTAGGTAGCGGT	chr1: 46723635-	117
	DMBX1 eCr	80	TTCCTAACCCTCTCCGACCA	46723751
	DMBX1 eDf	81	TTTTTGAGCGGTGAAGGGGA	chr1: 46723764-	125
	DMBX1 eDr	82	AATTATTAACGCGACCGCCG	46723888
HOXA9	HOXAAf	83	GTAATAATTTGGTGGTATCGGGGG	chr7: 27171666-	100
	HOXAAr	84	TCTACTAAACGAACACGTAACGC	27171765
	HOXABf	85	ATAATTTGGTGGTATCGGGGG	chr7: 27171669-	109
	HOXABr	86	ACGCGTTATTATTCTACTAAACGAA	27171777
	HOXACf	87	TGGGGTTTGTTTTAATTGTGGTT	chr7: 27171878-	152
	+HOXACr	88	GCGAAACCCGCGCCTTCTTAAT	27172029
	HOXACr	89	GAAACCCGCGCCTTCTTAAT
	HOXADf	90	GGGGAAGTATAGTTATTTAATAAGTTG	chr7: 27171688-	128
	HOXADr	91	ACAAAACATCRAACCATTAATAA	27171815
	HOXA9 eAf	92	TTCGCGAAGGAGAGCGTATC	chr7: 27171234-	101
	HOXA9 eAr	93	CCCTACGTACACCCCCAAAC	27171334
	HOXA9 eBf	94	CGTTTGGGGGTGTACGTAGG	chr7: 27171314-	88
	HOXA9 eBr	95	AAACCCAATACACGCGACGA	27171401
	HOXA9 eCf	96	TTTGTCGGGGAGGTTGGTTT	chr7: 27171478-	82
	HOXA9 eCr	97	TTCCTACTAAACGCCGACGC	27171559
	HOXA9 eDf	98	TAGCGTTTGGTTCGTTCGGT	chr7: 27171611-	123
	HOXA9 eDr	99	ATAAAAACGCGAACGCCGAC	27171733
SFRP5	SFRAf	100	GCGGGCGTTTCGATTGATTT
	+SFRAf	101	TTGCGGGCGTTTCGATTGATTT	chr10: 99521730-	131
	SFRAr	102	TAAAAACCGCCCCCACTACC	99521860
	SFRBf	103	TGTTCGGCGGTTTAGGTGTT	chr10: 99521628-	124
	SFRBr	104	AAATCAATCGAAACGCCCGC	99521751
	SFRCf	105	TAGTTCGGGTTTCGTCGTGC	chr10: 99521776-	90
	+SFRCr	106	AAAACTAAAAACCGCCCCCACT	99521865
	SFRCr	107	AACTAAAAACCGCCCCCACT
	SFRDf	108	GTGGGTGGTAGTTTGCGTTG	chr10: 99521713-	135
	SFRDr	109	CACTACCTCCCCGCCTTAAA	99521847
	SFREf	110	GCGTGCGTTTTCGGTTTTGA
	+SFREf	111	CGGCGTGCGTTTTCGGTTTTGA	chr10: 99521649-	83
	SFREr	112	AACGCAAACTACCACCCACC	99521731
	SFRP5 eAf	113	GGACGTTGGGTTGAGTTAGGA	chr10: 99520910-	109
	SFRP5 eAr	114	ACGACCCTACAACTCCCCTA	99521018
	SFRP5 eBf	115	GGTGTTCGAATTGTACGGCG	chr10: 99521073-	107
	SFRP5 eBr	116	CTACGCGCCGCTCATAAAAA	99521179
	SFRP5 eCf	117	GCGCGTACGGTTTCGTATAG	chr10: 99521183-	75
	SFRP5 eCr	118	ATACTCGCTCTTTACGCCCG	99521257
	SFRP5 eDf	119	TAGAGCGGTAGGTCGGTAGG	chr10: 99521393-	79
	SFRP5 eDr	120	AACAAACCGAACCGCTACAC	99521471
CHST11	CHSAf	121	GCGGCGTGGGAATGAATTTT
	+CHSAf	122	GGGCGGCGTGGGAATGAATTTT	chr12: 103376278-	120
	CHSAr	123	CTTTCCCTCGCACCCCTAAA	103376397
	CHSBf	124	TGCGAGGGAAAGTTTGGGTT	chr12: 103376386-	123
	CHSBr	125	CCGCGTTACCCGAAAAACTT	103376508
	CHSCf	126	TTTTAGGGGTGCGAGGGAAA	chr12: 103376377-	86
	CHSCr	127	CGCAACCGAACTACTCACCC	103376462
	CHSDf	128	GTGCGAGGGAAAGTTTGGGT	chr12: 103376385-	126
	CHSDr	129	ACCCGCGTTACCCGAAAAA	103376510
	CHST11 eAf	130	TTTTTTTGGTTGTCGGGTC	chr12: 103375901-	109
	CHST11 eAr	131	CGAAACCCGAAACACGTA	103376009
	CHST11 eBf	132	AGAGTGGTCGGGTGTTTAGC	chr12: 103376031-	149
	CHST11 eBr	133	ACGTAACCCAAAAACTCGAAA	103376179
	CHST11 eCf	134	GTCGTTTTTTAGGGGTGC	chr12: 103376371-	99
	CHST11 eCr	135	TAAACTTCGCAACCGAACTA	103376469
	CHST11 eDf	136	TATTAAGTTTGCGTTTGGGTC	chr12: 103376781-	109
	CHST11 eDr	137	AAAACCGTCTATCCCTACGC	103376889
FOXA3	FOXAf	138	CGAGGTAGGAAGTTTTGCGG	chr19: 51071936-	103
	FOXAr	139	CGACTCCTCCCGCGAAATAA	51072038
	FOXBf	140	CGGGGTGTTGTTGTAGGGTT	chr19: 51072158-	93
	FOXBr	141	AATCACACCTACCCACGCC	51072250
	FOXCf	142	TAGGGCGGTTAGGTTTGGGG	chr19: 51072076-	128
	FOXCr	143	GACGAATAACCCCACCCTCC	51072203
	FOXDf	144	TTGTCGCGTTGGTTTTTCGT	chr19: 51071765-	103
	FOXDr	145	ACCTTTCTCTCGACCCCAAT	51071867
	FOXEf	146	CGTTTTGTCGGTTGCGTGTTA	chr19: 51071734-	91
	FOXEr	147	ATTCCCCGACCTACCCAAAAC	51071824
	FOXA3 eAf	148	GGTAGGTGATAACGTTAGTGGGTT	chr19: 51068615-	110
	FOXA3 eAr	149	ACCTCCATCCCCTACCCAAC	51068724
	FOXA3 eBf	150	AGTAGGGGGAGGTGGTTTTG	chr19: 51069110-	135
	FOXA3 eBr	151	TCCTCCTCCCCAACTTAACC	51069244
	FOXA3 eCf	152	AGTTTGGGTGTGGCGGTTTA	chr19: 51070046-	111
	FOXA3 eCr	153	ACCAACTTCGCCATATTAACCA	51070156
TTBK1	TTBAf	154	CGCGGTGTATTGTGGGTAGT	chr6: 43319189-	99
	TTBAr	155	CCTTCCGACCCGAATCATCC	43319287
	TTBBf	156	GGTCGTCGGAACGTGATGT	chr6: 43319101-	86
	TTBBr	157	GCCAACATCAACACCAACCC	43319186
	TTBCf	158	TCGTTTTGTCGTTGTCGTCG	chr6: 43319212-	107
	TTBCr	159	TTAAATAACCCGCTCCCTCCG	43319318
	TTBDf	160	GTCGTGATGTTAGAGCGGGC	chr6: 43319130-	126
	TTBDr	161	ACCCCGATCCTCCTTAAACG	43319255
	TTBK1 eAf	162	TTAAGGAGGATCGGGGTC	chr6: 43319239-	91
	TTBK1 eAr	163	TCAATACGACGTTAAATAACCC	43319329
	TTBK1 eBf	164	TGGAGTTAAGCGGGTGGTAG	chr6: 43319008-	141
	TTBK1 eBr	165	CCCGCTCTAACATCACGACTC	43319148
TAL1	pbTAL f	166	GTATTGTCGCGGGTTCGTTC	chr1: 47470631-	129
	pbTAL r	167	CTCAACCAATCCCCACTCCC	47470738
	mbTAL f	168	GTTTTAGGTTTCGTTAGTATGGG	chr1: 47470570-	129
	+mbTAL r	169	CAAATTAAAATAAATCATTTAACCCATAA	47470698
	mbTAL r	170	TTAAAATAAATCATTTAACCCATAA
DMRTA2	pbDMRTA f	171	CGAAGATTTCGTAGGCGGGT	chr1: 50659325-	145
	+pbDMRTA r	172	ACGACGCAAATAACGCTACGCA	50659469
	pbDMRTA r	173	GACGCAAATAACGCTACGCA
	mbDMRTA f	174	TGTTTTAGAAGCGGGAGAAAG
	mbDMRTA r	175	AAATAAAACCCCCGTATCCAAT
	+mbDMRTA f	176	AATGTTTTAGAAGCGGGAGAAAG	chr1: 50659041-	113
	+mbDMRTA r	177	AAAAATAAAACCCCCGTATCCAAT	50659153
	DMRTAexp Af	178	GCGGCGGTTAGCGTTAGTTTTTCGGTAG	chr1: 50659366-	124
	DMRTAexp Ar	179	CGAAACGCCAACGTATCATAACGACGCA	50659489
PDE4B	pbPDE f	180	ACGTTTTAGGGACGGCGAAT	chr1: 66030622-	77
	pbPDE r	181	AATCCCAACGACCGTCTACC	66030698
	mbPDE f	182	TTTCGTTTTGTATTTATGGTAGATGT	chr1: 66030580-	115
	mbPDE r	183	CCAACGACCGTCTACCACTA	66030694
BARHL2	pbBARHL f	184	CGTGGTATGGATTTCGGGGT	chr1: 90967266-	111
	pbBARHL r	185	ACTCCTAACCCTAAACGCGA	90967376
	mbBARHL f	186	GTTTTTTTCGGTTTTTGTTCGA
	mbBARHL r	187	TTTCTCCCAATTCCAATATCCA
	+mbBARHL f	188	TGGTTTTTTTCGGTTTTTGTTCGA	chr1: 90967815-	86
	+mbBARHL r	189	ACTTTCTCCCAATTCCAATATCCA	90967900
TBX15	pbTBX f	190	GCGATCGGCGATTGGTTTTT	chr1: 119331668-	100
	pbTBX r	191	GCGACGACACACGACCTAAA	119331767
	mbTBX f	192	TGAGGTTTTAGGTCGTGTGT
	+mbTBX f	193	GGTGAGGTTTTAGGTCGTGTGT	chr1: 119331740-	142
	mbTBX r	194	AAAACCTTAATCGACTCAAATAAAA	119331881
RUSC1,	pbRUSC f	195	GGGTGTAGTTGCGTAGCGTA	chr1: 153557280-	142
C1orf104	pbRUSC r	196	CCGAACCCTCCTCACCAAAA	153557421
	mbRUSC f	197	TAGTTGCGTAGCGTAGGGTA	chr1: 153557285-	126
	mbRUSC r	198	TCACCAAAATCCTCCTAAAAC	153557410
GNG4 B	pbGNG f	199	ACGTAGTGTTGGTAAGATTTGTAGA	chr1: 233880823-	149
	pbGNG r	200	ACAAAAACCGCTTATAAACGACGA	233880971
	mbGNG f	201	GTAGGTTTTTGCGTTGGAGATT	chr1: 233880677-	141
	mbGNG r	202	ATTTTCGTTACTTCTCTATTCCCAAA	233880817
POU3F3	pbPOU3F f	203	GGGGTTTCGCGTTTTGAGTT	chr2: 104836866-	79
	pbP0U3F r	204	AACACCAAAACCCCCGCTAA	104836944
	mbP0U3F f	205	AAAAGTAATTAATCGGAACGGT	chr2: 104836837-	134
	mbPOU3F r	206	ACACTTTCCCAAATACAAAAAAA	104836970
BOLL B/C	pbBOLL f	207	TTTCGAGTCGGGGCGTTTTA	chr2: 198359264-	138
	pbBOLL r	208	TACCTAACCGCTCGCTCTCT	198359401
	mbBOLL f	209	GTTCGGTTTTGGGATTTTT
	mbBOLL r	210	AATCCCAAAAACCGACTCT
	+mbBOLL f	211	GAGGGTTCGGTTTTGGGATTTTT	chr2: 198359331-	131
	+mbBOLL r	212	ACCAATCCCAAAAACCGACTCT	198359461
TRIM71	pbTRIM f	213	CGGAGGAATTTGTGTCGTCG	chr3: 32834331-	110
	pbTRIM r	214	CACCAAAACAACGCTACCCG	32834440
	mbTRIM Af	215	TTGGGAATTTTTTTCGTTTAT	chr3: 32834188-	150
	mbTRIM Ar	216	TCCTCCGAATAACTTAAAAACC	32834337
	mbTRIM Bf	217	TCGTTGGATAGTGGTATTTAATGT	chr3: 32834348-	150
	mbTRIM Br	218	AAAATCACCGACTCACTCAA	32834497
SLC2A2	pbSLC f	219	CGGAGTACGGCGGTAGGAA	chr3: 172228914-	80
	+pbSLC r	220	AATACCCCGAAAACCCGCTAATA	172228993
	pbSLC r	221	ACCCCGAAAACCCGCTAATA
	mbSLC f	222	ATGATATTTTGTAGGAAAGCGT	chr3: 172228748-	103
	mbSLC r	223	CAAATTCCGTTTCTAAAAAAAC	172228850
CYTL1	pbCYTL f	224	GGGTTCGTATGCGGGAGTAG	chr4: 5071974-	126
	pbCYTL r	225	ACGAAACTACACCAACGCCT	5072099
	mbCYTL f	226	GGGGGTTTTCGTTAGGAGTAG	chr4: 5072020-	123
	mbCYTL r	227	AAACCGCCCTAAACCACC	5072142
SHISA3	pbSHISA f	228	GAAGGGCGGTAGCGATAGTT	chr4: 42094543-	108
	+pbSHISA r	229	CTACGAATTCCGCAAACCGAAA	42094650
	pbSHISA r	230	ACGAATTCCGCAAACCGAAA
	mbSHISA f	231	ATTGTTTTTGTCGGCGTT	chr4: 42094569-	86
	mbSHISA r	232	TACACTACGAATTCCGCAA	42094654
GABRA4	pbGAB f	233	GCGTGCGTATATTCGCGTTT
	+pbGAB f	234	CGGCGTGCGTATATTCGCGTTT	chr4: 46690291-	95
	pbGAB r	235	AAATTCCGCCTCCCCTAACC	46690385
	mbGAB Af	236	TTTAGCGTTTAATGTGTATGTAGA	chr4: 46690411-	135
	+mbGAB Ar	237	CGAAATTACAATCGAAACAAACTTAC	46690545
	mbGAB Ar	238	AAATTACAATCGAAACAAACTTAC
	mbGAB Bf	239	GTTTTGAGTAGGGTGCGAG
	mbGAB Br	240	AAAAAAACAAATTCCGCCT
	+mbGAB Bf	241	GATGTTTTGAGTAGGGTGCGAG	chr4: 46690248-	151
	+mbGAB Br	242	AAACGAAAAAAACAAATTCCGCCT	46690398
EGFLAM	pbEGF f	243	TGGTAGCGTTGTAAGGTGGG	chr5: 38293231-	129
	pbEGF r	244	AAAAACAAACGCGACCCTCG	38293359
	mbEGF f	245	TCGAGTTTTGGTAGCGTTGTAA	chr5: 38293223-	84
	+mbEGF r	246	AATACCCCGCAAAAAAAATCTACA	38293306
	mbEGF r	247	CCCCGCAAAAAAAATCTACA
C5orf39	pbC5orf f	248	ACGAGAAATTGGCGCGTTGA	chr5: 43076304-	101
	pbC5orf r	249	AACAACACCCTTTACGACGC	43076404
	mbC5orf f	250	TGTTTGTTAGGGTTTTGTTTTAA
	mbC5orf r	251	CGCCAAAACGAATATTTATTTA
	+mbC5orf f	252	AATTGTTTGTTAGGGTTTTGTTTTAA	chr5: 43076267-	124
	+mbC5orf r	253	CGACGCCAAAACGAATATTTATTTA	43076390
CDO1 B	pbCDO f	254	GGTAGCGTAGTGGATTCGGG	chr5: 115180192-	142
	pbCDO r	255	CTCGTCCTCCCTCCGAAAAC	115180333
	mbCDO f	256	GTTTGTTTTATTTCGTGGGGAG	chr5: 115179983-	85
	mbCDO r	257	CCAACTCCTTAACTCGCTCAA	115180067
IRF4 B/C	pbIRF f	258	TCGCGGGAAACGGTTTTAGT
	pbIRF r	259	GCCCTTAACGACCCTCCG
	+pbIRF f	260	TTTTCGCGGGAAACGGTTTTAGT	chr6: 336451-	100
	+pbIRF r	261	GCGCCCTTAACGACCCTCCG	336550
	mbIRF f	262	CGTTTTGTAAAGCGAAGTTT
	+mbIRF f	263	GTTATACGTTTTGTAAAGCGAAGTTT	chr6: 336298-	108
	mbIRF r	264	AAACCAATCAATCACTAAACTACA	336405
ID4 B	pbID Af	265	GGTTTTTGGGCGTCGTGTTA	chr6: 19945064-	107
	pbID Ar	266	AAATTCACTCTCCACCGCCC	19945170
	pbID Bf	267	AGGCGAATAATGAAACGGAGGA	chr6: 19944950-	134
	pbID Br	268	TAACACGACGCCCAAAAACC	19945083
	mbID f	269	ATTTTACGGATGGAGTGATG
	+mbID f	270	GGAATTTTACGGATGGAGTGATG	chr6: 19945031-	118
	mbID r	271	CTTATCCCGACTAAACTACTAAAAAA	19945148
SCAND3,	pbSCAND f	272	AATTCGTTTCGCGACGTGAG
GPX5	+pbSCAND f	273	TTAATTCGTTTCGCGACGTGAG	chr6: 28618249-	111
	pbSCAND r	274	ACACGCCTTAAAACCTACTCAT	28618359
	mbSCAND f	275	CGTGAGGGAGAATTTAGGAG	chr6: 28618265-	104
	mbSCAND r	276	TAAAAAAACACACGCCTTAAAACCTA	28618368
DDAH2	pbDDAH f	277	TCGTTTAGCGAGCGTTGTTT	chr6: 31806112-	99
	pbDDAH r	278	GATCCGCCGTTACGCTATTC	31806210
	mbDDAH f	279	TGTTAGAAATCGGTATCGTTTA
	mbDDAH r	280	TCTACGAAACGTTTACAACC
	+mbDDAH f	281	TTTTTTGTTAGAAATCGGTATCGTTTA	chr6: 31806097-	97
	+mbDDAH r	282	AAAATCTACGAAACGTTTACAACC	31806189
COL11A2	pbCOL f	283	TTTAGGGATCGCGTTCGGAG	chr6: 33269259-	144
	pbCOL r	284	AAACTCCTTTCCCCTCTCATAC	33269402
	mbCOL f	285	CGGAGTTTTTAATCGGATAT	chr6: 33269274-	142
	mbCOL r	286	TCCCTTCTCTTTAAAACTCCT	33269415
NT5E B	mbNT5E f	287	GTCGGATTTTATTTTAATCGTG
	mbNT5E r	288	AAACAAAAAAATCTCAAAAACTAAAA
	+mbNT5E f	289	GTTGTCGGATTTTATTTTAATCGTG	chr6: 86215769-	144
	+mbNT5E r	290	CTTAAACAAAAAAATCTCAAAAACTAAAA	86215912
SIM1 B	pbSIM Af	291	GTTAGGGGCGAGGCGTTTAT	chr6: 101019614-	82
	pbSIM Ar	292	CGAAACCTAAACGCGCGAAA	101019695
	pbSIM Bf	293	AGGTTAATAGGTGGCGCGTT	chr6: 101019077-	95
	pbSIM Br	294	CCCGCAACTCCGCGATAATA	101019171
	pbSIM Cf	295	AGTCGTTTTTCGCGCGTTTA
	+pbSIM Cf	296	CGAGTCGTTTTTCGCGCGTTTA	chr6: 101019667-	90
	pbSIM Cr	297	GACCCGACACCCTAAACTCAT	101019756
	mbSIM Af	298	AGGCGTTTATTGGTTAATAGGG	chr6: 101019624-	134
	+mbSIM Ar	299	CGACCCGACACCCTAAACTCAT	101019757
	mbSIM Ar	300	ACCCGACACCCTAAACTCAT
	mbSIM Bf	301	TTTAATTTGGGTTTTAAGTTTGAGG	chr6: 101018944-	132
	mbSIM Br	302	ACGCTACTAAACCCCGCTTAT	101019075
RGS17	RGS17 Af	303	GCGTTTAGGTAGCGACGC	chr6: 153493700-	121
	RGS17 Ar	304	ATACCCCGACGAAAACGAC	153493820
	RGS17 Bf	305	TTTGGGATTTGGTCGAGC	chr6: 153493620-	111
	RGS17 Br	306	AAAATTAAATCCCGCGTCG	153493730
CAPDS2	CAPDS Af	307	CGTTTAGGTTTGTGGACGC	chr7: 121743823-	129
	CAPDS Ar	308	AAAAACGAAATCGCTAATACGC	121743951
MSC	MSC Af	309	TTTTTCGAATTTTTGCGC
	MSC Ar	310	AACACGCTCCGACTAACTTC
	+MSC Af	311	GGTTGTTTTTTCGAATTTTTGCGC	chr8: 72918397-	135
	+MSC Ar	312	TAAACACGCTCCGACTAACTTC	72918531
	MSC Bf	313	CGTTCGCGTTATTATTTGC
	MSC Br	314	CGCCCAATAACAACTCGT
	+MSC Bf	315	ATTATCGTTCGCGTTATTATTTGC	chr8: 72918698-	155
	+MSC Br	316	CCTCGCCCAATAACAACTCGT	72918852
SPAG6	SPAG6 Af	317	GTCGAGTCGTCGTTACGATC	chr10: 22674453-	77
	SPAG6 Ar	318	CTACCCTCCTCGAACTCTACG	22674529
INA	INA Af	319	GTTTTCGGATGGGAAATTTTAG
	INA Ar	320	AAACCATCTACATCGAAATCGC
	+INA Af	321	GTGGTTTTCGGATGGGAAATTTTAG	chr10: 105026593-	123
	+INA Ar	322	AACAAAACCATCTACATCGAAATCGC	105026715
FLI	FLI Af	323	TTTTTAGGAGTAAGTATTTTGTGTG	chr11: 128068870-	112
	FLI Ar	324	CCCTCTTCCTCCCCTACTAAT	128068981
ATP5G2	ATP5G2 Af	325	TAGGTATATTTCGGTCGGC	chr12: 52357363-	116
	ATP5G2 Ar	326	AACTCGAAACCTCATCCG	52357478
USP44	USP44 Af	327	ACGGGAGGGTAAATTTAGC	chr12: 94466977-	114
	USP44 Ar	328	TACCAAACAATTCGACGTTA	94467090
POU4F1	POU4F1 Af	329	GCGTACGTCGGTTTATTC
	POU4F1 Ar	330	ACGCTCTACGCGATCAAA
	+POU4F1 Af	331	AAGTGCGTACGTCGGTTTATTC	chr13: 78075512-	141
	+POU4F1 Ar	332	GCGACGCTCTACGCGATCAAA	78075652
LHX1	LHX Af	333	CGAGCGATTGTGGGGTTAGA	chr17: 32368543-	82
	LHX Ar	334	CAACTCGCGACCGCCTAAA	32368624
HINF1B	HINF Af	335	TTCGGGCGTTTATAGAGTTC	chr17: 33176898-	120
	HINF Ar	336	AAAATCAAAACGCGAACG	33177017
	HINF Bf	337	TAGCGTCGCGTTAGAAAGC
	HINF Br	338	ATCGCTCAAAACCTAACGAA
	+HINF Bf	339	TTTTAGCGTCGCGTTAGAAAGC	chr17: 33177225-	117
	+HINF Br	340	AAAAATCGCTCAAAACCTAACGAA	33177341
	HINF Cf	341	AGGTTTAGTTTCGAAATCGC
	HINF Cr	342	AACCGAACGATTCCCTAA
	+HINF Cf	343	GTTAAGGTTTAGTTTCGAAATCGC	chr17: 33177654-	120
	+HINF Cr	344	CTAAAAAACCGAACGATTCCCTAA	33177773
GALR1	GALR1 Af	345	GAATTTTTGGAAAAGTCGGGA
	GALR1 Ar	346	CTCCTACAAAAAAAACTCCC
	+GALR1 Af	347	TTCGGAATTTTTGGAAAAGTCGGGA	chr18: 73090886-	104
	+GALR1 Ar	348	CGACTCCTACAAAAAAAACTCCC	73090989
MAST1	MAST1 Af	349	AGAAGGTGGTCGGTAAGC
	MAST1 Ar	350	ACGTAATTATAAAAAACACGCC
	+MAST1 Af	351	GGAGAAGGTGGTCGGTAAGC	chr19: 12839386-	148
	+MAST1 Ar	352	AAAACGTAATTATAAAAAACACGCC	12839533
	MAST1 Bf	353	TAGTTTTTTGGAGGGAGAGG	chr19: 12839568-	103
	MAST1 Br	354	ATCCTCGTCCTCTTAAAAAAC	12839670
CPXM1	CPXM1 Af	355	GTCGAGTTTGGGATTTTGGT
	CPXM1 Ar	356	AAACTCCTACTCGCCCTAACC
	+CPXM1 Af	357	GGGGTCGAGTTTGGGATTTTGGT	chr20: 2729097-	118
	+CPXM1 Ar	358	AAAAACTCCTACTCGCCCTAACC	2729214
NEURL2	NEURL2 Af	359	TCGAGTTGGATAAGGCGTAC	chr20: 43952304-	142
	NEURL2 Ar	360	CCGATAACACGACCGACATA	43952445
	NEURL2 Bf	361	TGTATGTCGGTCGTGTTATC	chr20: 43952424-	82
	NEURL2 Br	362	TAAACGTACTACCTCCGACC	43952505
ACVRL1	ACVRL1f	363	GGATGTGGGAGGTTCGGTTCGGGTG	chr12:50587308-	136
	ACVRL1r	364	CCGCTCGCCCCTCGCTAAAACTACA	50587443
AFF3	AFF3f	365	GGCGCGAGGTAGTTTTAGTACGTAGTTTTT	chr2: 99542180-	78
	AFF3r	366	ATAACAACGTCGTCCTTTCCGCAAAACG	99542257
AKR1B1	AKR1B1f	367	GGGGATTTTGTAAGTTCGCGCGTGGTTT	chr7: 133794143-	108
	AKR1B1r	368	ACACTCTCCGCGCGACCTATATTAACGA	133794250
	AKR1B1R_f	369	GGAGACGGTTTGTTATGGTTGTTGCGTT	chr15: 43266838-	122
	AKR1B1R_r	370	ACGCCCTTTCTACCGACCTCACGAACTA	43266959
ALDOC	ALDOCf	371	TTTTTCGGGGGCGTGGTTTGTATGTTT	chr17: 23928071-	123
	ALDOCr	372	TACCTAACGAAACGCTCACTCCACCTCG	23928193
ALOX5	ALOX5f	373	TTTTGCGGTTAGGTGAAGGCGTAGAGGT	chr10: 45234654-	106
	ALOX5r	374	GACCGAATACCCCGCTTTCTCTCTCGAC	45234759
	ALOX5R_f	375	GAGGTCGAGAGAGAAAGCGGGGTATTCG	chr10: 45234729-	110
	ALOX5R_r	376	AACGCTCTCAACCCAACCCCTAAACTCA	45234838
ALX1	ALX1f	377	AGGATAGTAGCGGTGAGTCGTTAGCGTT	chr12: 84198385-	117
	ALX1r	378	CGCTCCCACTTTTCTCCTTTCTCCCTCC	84198501
ALX4	ALX4f	379	TTTTGATAAAGTGGGGAGGGCGTAGGGG	chr11: 44289270-	106
	ALX4r	380	ACACTCTCAAATACCCGTCGCGCTCTAT	44289375
C1orf230	C1orf230f	381	TTTTGATAAAGTGGGGAGGGCGTAGGGG	chr1: 149960830-	92
	C1orf230r	382	ACACTCTCAAATACCCGTCGCGCTCTAT	149960921
	C1orf230R_f	383	AGCGTAGCGTAGTTGGAGTAGTTGCGAA	chr1: 149960685-	121
	C1orf230R_r	384	CGACGACTCTCTTCCCAATCTAAAACCCCA	149960805
C6orf186	C6orf186f	385	CGGAGTTTAGAAGGGCGTTCGGTTACGG	chr6: 110785585-	116
	C6orf186r	386	CTCCACGAATCGCATCTTTCAATACCCA	110785700
C17orf64	C17orf64f	387	AAAGGTGGTTCGAGTGAGGAAATTGCGG	chr17: 55853711-	79
	C17orf64r	388	GCGTCCCTAAACGACACACGACGAAATC	55853789
	C17orf64R_f	389	GTCGACGGCGGTTTTATCGTATTGTCGC	chr17: 55853578-	112
	C17orf64R_r	390	CCTTCTCCCGAACCTTCCTTCGTATCCT	55853689
C19orf41	C19orf41f	391	TTAGAGGTATGGCGGGGTTTTTGTGACG	chr19: 55358254-	95
	C19orf41r	392	AATACTCCCTAAACCTCCTAACCGCGCC	55358348
CCDC67	CCDC67f	393	GAGGTTTAATTGTTTCGTTGGTCGC	chr11: 92703424-	123
	CCDC67r	394	ACGCAAAACCGCGTATATCACCT	92703546
CCDC8	CCDC8f	395	GGTTTTAGGGACGCGGTTGGAATTTGGG	chr19: 51608460-	89
	CCDC8r	396	CCCAACGCCTCGACCATATTAAATAACTT	51608548
CD38	CD38f	397	GCGATTAAGGCGTATCGGTGGGTATTGC	chr4: 15389377-	125
	CD38r	398	AACACCACCCGACGAACTCTCGACTAAC	15389501
CD8A	CD8Af	399	TAGGACGTTGTTTGGTTCGAAGTTCGGG	chr2: 86871471-	99
	CD8Ar	400	CTCCGAACCGACCGAAAAACGCAACTTT	86871569
CDH23	CDH23f	401	GGCGGGGTATTGTTTTGTTTC	chr10: 72826313-	111
	CDH23r	402	TCTACCGATATCATAACACCGACT	72826423
CDK5R2	CDK5R2f	403	AAAGGTAGAGGGAAGGAGAGTTGTTTTT	chr2: 219532251-	104
	CDK5R2r	404	ACTCCTACCTCCTCCGAATCCTAAAACCT	219532354
CHST2	CHST2f	405	CGGAATGAAGGTGTTTCGTAGGAAGGCG	chr3: 144322486-	151
	CHST2r	406	GCTACGACACCCAACGACCCATCGAAA	144322636
CLCN1	CLCN1f	407	AATGATTTTGTTGGGTTCGGTGGAGCGG	chr7: 142752740-	113
	CLCN1r	408	CCGACAACTTCCGCGCCATCTCTTAAAC	142752852
	CLCN1R_f	409	TTGTGTTTTGAGCGTAGGTTGCGCGTAG	chr7: 142752798-	77
	CLCN1R_r	410	GCCTTCCCGTCGTAAAACAACTCCGACA	142752874
COL16Af	COL16A1f	411	GTTTTAGGGGGTTGGGGGTTTGTTAGGGA	chr1: 31942237-	146
	COL16A1r	412	AACCCGAAACGAAACTATACACCCCGCA	31942382
CPNE8	CPNE8f	413	TCGATGTTCGTAGTGTTGTTGTAGCGGT	chr12: 37585569-	121
	CPNE8r	414	CCATCCCCGCCTAACGAAAACTAACCCT	37585689
DIO3	DIO3f	415	CGTTTCGAGAAGAAGTTTCGCGGTTGGT	chr14: 101095917-	89
	DIO3r	416	ATCTAAACCCAAATCGAAAACCGCCGCC	101096005
DNM3	DNM3f	417	TTGGAGTTGTCGTAGATCGTCGTGGTGG	chr1: 170077504-	123
	DNM3r	418	AAATCGCCCCACTACCGCATCCTTACTC	170077626
	DNM3R_f	419	GCGGTTAGGTGTGGTAAAGTAGTTGGCG	chr1: 170077283-	123
	DNM3R_r	420	GCGCACAACCAACCTATAAACTCCGACG	170077405
DUOX1	DUOX1f	421	GGGATTTGTGAAGGCGGATTTG	chr15: 43209229-	79
	DUOX1r	422	AATATTCCGTCGATACCGAAAACCCGA	43209307
EMX1	EMX1f	423	CGGTTGGAGCGCGTTTTCGAGAAGAAT	chr2: 73005041-	123
	EMX1r	424	AACGCAAAACAAACCGCGACCGAAAATA	73005163
EMX2OS	EMX2OSf	425	AGGAGAAGTCGTAGCGGGCGTC	chr10: 119291932-	101
	EMX2OSr	426	GACTAAACCTTCTACCGCCCACCG	119292032
ESPN	ESPNf	427	TAGTTGCGATGGGGTGGGAAGTTACGTT	chr1: 6430246-	112
	ESPNr	428	AAAACCATCGCCATCCACGAAAACGACA	6430357
EVX1	EVX1f	429	AGGAGGATGATAGTTTAGAAAGAAGAGGGT	chr7: 27248900-	120
	EVX1r	430	CGCGACCGCGACGATAACGATAAAAACT	27249019
FABP5	FABP5f	431	GAAACGTGTAGGCGTCGGCGTTTATGAG	chr8: 82355078-	80
	FABP5r	432	CGACCTCTCGAACGCCTCCTACAAACAA	82355157
FBRSL1	FBRSL1f	433	GTGGAGGAGGAAGTTCGTTTC	chr12: 131575948-	105
	FBRSL1r	434	AACTACTACCAAACACGAAACGCA	131576052
FLI41350	FLIf	435	GGTTAGAGTCGGTTGCGTAGTTT	chr10: 102979731-	125
	FLIr	436	TTTTTGTTAGGCGAAGTATAGAGAGCG	102979855
FOXG1	FOXG1f	437	TTTTTCGATTGGTCGACGGCGAGAGAG	chr14: 28305617-	124
	FOXG1r	438	TTTCCGAACTACAAACGCACACTAAAAC	28305740
FOXL2	FOXL2f	439	GATTCGTATGGGTTTTATCGAGTTTC	chr3: 140148670-	95
	FOXL2r	440	ACTTAAAAATAAACTCGCCCGTACG	140148764
FZD2	FZD2f	441	TCGTTGGTGAAGGTGTAGTGTTCGTTCG	chr17: 39990814-	125
	FZD2r	442	TAACGCGCGCGCTCACAAATAAAACGAC	39990938
	FZD2R_f	443	TTTTTAGTGGTTCGAGCGTTTGCGTTGC	chr17: 39990969-	91
	FZD2R_r	444	TCCGTCCTCGAAATAATTCTAACCGACGC	39991059
HIF3A	HIF3Af	445	CGTGGTATAGTTAATCGCGCGGCGT	chr19: 51492066-	125
	HIF3Ar	446	TACAACCCCAACGCCATAACTCGCCAAT	51492190
HIVEP3	HIVEP3f	447	TGTCGTCGTCGTCGGGGTTTTGTTATTT	chr1: 41901039-	76
	HIVEP3r	448	ACGACGATAAACTCCCGCTAAACCCGAA	41901114
	HIVEP3R_f	449	GAACGAGGATTTGCGTTTTTGGATCGC	chr1: 41901096-	80
	HIVEP3R_r	450	CCTAAACTCCTCTACATATTCCTCTACCT	41901175
HLA-F	HLA-Ff	451	GAATGGTTGCGATATGGGGTTCGACGG	chr6: 946778-	125
	HLA-Fr	452	CCACGATATCCGCCGCGATCCAAAAAC	946902
HOTAIR	HOTAIRf	453	TAAGGGTCGGTTGTTGTTTTTTTTC	chr12: 52645919-	116
	HOTAIRr	454	ACCGACGCCTTCCTTATAAAATACG	52646034
HOXA10	HOXA10f	455	TGTGGGATAATTTGGCGAAGGGAGTAGA	chr7: 27180403-	124
	HOXA10r	456	AACTCGAAATTAACTACGAACGCCCGCC	27180526
HOXD11	HOXD11f	457	GGCGGGGGTAGTTTTTGTATTAAGGCGA	chr2: 176680987-	125
	HOXD11r	458	CCTACGCTACTACTCTTCTCGACCCCCG	176681111
HOXD8	HOXD8f	459	CGTTTCGTTCGTCGGTCGTAGCGATTG	chr2: 176702636-	114
	HOXD8r	460	CCGACGAAACATTTTCGCACCACAACAC	176702749
	HOXD8R_f	461	CGCGGTTTCGGGGTATACGGAGTTTTTG	chr2: 176702549-	120
	HOXD8R_r	462	GCAATTCAATCGCTACGACCGACGAACG	176702668
HSPA12B	HSPA12Bf	463	CGTCGTAGCGGGTACGGTTAACGAGTTG	chr20: 3661361-	125
	HSPA12Br	464	TTTCTCCACTCGAAACGCCCGACAACC	3661485
ISL1	ISL1f	465	CGGGGGAGAACGGTTTGAGTTTCGAGTA	chr5: 50714776-	110
	ISL1r	466	TCATATTTCAACCTCGCCGCCGCTAAAC	50714885
Intergenic1	Int1f	467	AGTAGGGATGGTCGTTCGTTGTTCGGTG	chr11: 68379573-	107
	Int1r	468	GACAAACGACCGAAAATACTCGCGCAAC	68379679
	Int1R_f	469	TTTTACGGTCGGGGCGATAGTTGAAGGT	chr11: 68379395-	99
	Int1R_r	470	TCACGCCAATACCCGCTAATCCCTCCTA	68379493
Intergenic2	Int2f	471	GGGGATGGATAATTTTTAGGCGTTAAC	chr17: 69460223-	117
	Int2r	472	TAACCTCGTCTTTATCCCCGCG	69460339
Intergenic3	Int3f	473	AGTGTGTAGTCGTTTGTGGGTGAGGAGTT	chr8: 95315865-	130
	Int3r	474	CACCGCGAAAAACGCCCACAATCTTACC	95315994
	Int3R_f	475	CGCGGGGGAGTTTATTTTTGAGGATTCGG	chr8: 95315775-	118
	Int3R_r	476	ACTCCTCACCCACAAACGACTACACACT	95315892
Intergenic4	Int4f	477	TAGTATTTGTACGGAGTTTTTCGGCGGTC	chr5: 43054172-	92
	Int4r	478	TACGACGCAACCAACGATACTATCACCAA	43054263
Intergenic5	Int5f	479	TAGTGATTGGTTATTTGGGCGCGGGGC	chr10: 43138416-	115
	Int5r	480	AAACGACATCCATCATCTCCCTCGACCC	43138530
Intergenic6	Int6f	481	AGGTCGCGTTTTGGTCGTGC	chr3: 14827613-	76
	Int6r	482	ACTTAAAAATAAACTCGCCCGTACG	14827688
Intergenic7	Int7f	483	ATTTTACGTAGGGTGGGGTTGAGGGCGT	chr12: 52897799-	112
	Int7r	484	ATCCTAACCGTCCCGCCTCAAAACCGTA	52897910
Intergenic8	Int8f	485	CGTCGTAGTATTTGGCGGCGCGTTTC	chr2: 236737778-	106
	Int8r	486	AACGTACCTAATCCCCAAACCCACTCCT	236737883
Intergenic9	Int9f	487	TCGTTGTGCGCGTTTCGTTTGTTGGATTA	chr6: 778755-	92
	Int9r	488	TCGATAATATCTCCGTCGCCTCCGCAAA	778846
Intergenic10	Int10f	489	GCGCGTTTAATCGTGGGATTTTTGGGAG	chr2: 174899379-	116
	Int10r	490	CAAATTCGCGACACCCTACCCCAACAC	174899494
	Int10R_f	491	GGGTGTCGCGAATTTGGGGTA	chr2: 174899479-	124
	Int10R_r	492	CTAAACCTCTCCCCTCCCAAATTTACCT	174899602
Intergenic12	Int12f	493	ATCGAGTTTTTAGCGGTTTTTGGGGCGG	chr1: 119344866-	109
	Int12r	494	ACTAACATCGCGCACTTAAATCTTTCCG	119344974
Intergenic13	Int13f	495	GGTAGCGGCGGGTAAAAAGTC	chr7: 64675119-	107
	Int13r	496	TACAACTTTTTACCTCCGCCGC	64675225
Intergenic14	Int14f	497	CGTCGATTTGCGGAATTTCGTCGTCGTT	chr1: 238227938-	108
	Int14r	498	ACATCCGCGTAAACTCGCCCTTTAACAC	238228045
	Int14R_f	499	TTTCGGGATTAGGGTTTCGGAGGGTGTC	chr1: 238227822-	92
	Int14R_r	500	CGTATCGATCCGTCCCTCCCGCTTAAAA	238227913
Intergenic15	Int15f	501	CGGTTTTGGTGGTAGTTTTGGTAATC	chr19: 48895723-	80
	Int15r	502	AAAACCTCCCGAACGACGAAATAATCCA	48895802
	Int15R_f	503	GTAGGCGGTCGGAACGTGAAC	chr19: 48895536-	125
	Int15R_r	504	CGATAAAAACTACAATAACTCGACAACCA	48895660
Intergenic16	Int16f	505	GTTGTGAGGGTTTTCGGCGGTATC	chr1: 54713046-	120
	Int16r	506	CATAACAACGCGCGACCCCTA	54713165
Intergenic17	Int17f	507	TGATTATAAATTAGGGGGTTTGGTCGTCG	chr12: 61311832-	114
	Int17r	508	AAACCCTCCACCCTCGCAATACTACTCC	61311945
Intergenic18	Int18f	509	TGTAGGAGATAATGGGAGTGAAGAGGGA	chr6: 4971256-	83
	Int18r	510	TTCCACGAAACGCGCGACTTCCTAACTA	4971338
	Int18R_f	511	GTTGAGTTAGGAGAGGTCGATAGC	chr6: 4971467-	104
	Int18R_r	512	CCCGAAAACAACGACTATCGAAATCCAA	4971570
Intergenic19	Int19f	513	ATAAGGTTTGGTGGAAGCGTAGGAGCGT	chr6: 3177175-	115
	Int19r	514	ACGCCGAATAAAAATCCCGCAACCACAA	3177289
Intergenic20	Int20f	515	GGAGGGGAGGAGATAGCGTTATTTAGGG	chr10: 118912740-	103
	Int20r	516	AAACAAAACCCGAAACCCCACCTACACC	118912842
Intergenic21	Int21f	517	GCGTGGTAGTTGAGGATGTAGACGTGGT	chr16: 45381613-	124
	Int21r	518	TCCGAACTACTTAAAAATCCCCGCCGCC	45381736
Intergenic22	Int22f	519	TCGTTGGTTGTGATTTTTATGCGGGCGT	chr8: 68037259-	99
	Int22r	520	ACCTCTCCGATAAACCAAATCCTCCGCC	68037357
	Int22R_f	521	CGGGTGAGGTTTGTGGTTAATTTCGCGT	chr8: 68037556-	120
	Int22R_r	522	CTCAACCAAACTACAACGTTCCCGCCTC	68037675
Intergenic23	Int23f	523	AATGGAGGCGTAGATTAACGAGCGGTGT	chr5: 42987147-	108
	Int23r	524	ATCCTTAACAACCCCGCCGACTAACGTC	42987254
	Int23R_f	525	ACGGGTACGGAGAAACGTCGGATTTAGT	chr5: 42987852-	95
	Int23R_r	526	TCCCCGCGACACTCTACCTATAACGTCC	42987946
KCNH8	KCNH8f	527	CGTTTGGCGGGTATTGTTGTTC	chr3: 19164879-	93
	KCNH8r	528	CCCGACGCAAACTCCCTCTC	19164971
KCNJ2	KCNJ2f	529	GAAGTTGTTTTTTAGGGGTTTGCGC	chr17: 65676355-	86
	KCNJ2r	530	ACTCAAATCTACCCTCGCTTCAACG	65676440
KCKN4	KCNK4f	531	GCGCGGGGGTATTTTGGAGGGTTAGTTA	chr11: 63816449-	101
	KCNK4r	532	TCCCTACTCGCCCGCTACGACTATAACA	63816549
KCNK17	KCNK17f	533	CGGATTTTGTTTTCGGGAGTCGTTCGGG	chr6: 39390031-	120
	KCNK17r	534	AACTAAACGCCTAACCCTTCCCTCCCAC	39390150
KIAA1751	KIAAf	535	TTCGTTTTGTTTTTCGGTTGGAGCGGGT	chr1: 1925171-	118
	KIAAr	536	TATAACCTAACCCTTCAACCGCGCCTCG	1925288
	KIAA1751R_f	537	AGGCGGCGGTTTTTGGCGATTGTTTTTC	chr1: 1925065-	76
	KIAA1751R_r	538	TTCCGTTACCATAAAACTACCCGCCCC	1925140
LASS1	LASS1f	539	GATTTCGCGTATCGTCGTGTC	chr19: 18868171-	103
	LASS1r	540	TAATATCCCCCGTACCCCCCG	18868273
LOC255167	LOCf	541	TTTCGATAATAGCGTTTTTGCGGCGTGG	chr5: 6636474-	146
	LOCr	542	CAAAAACACGCGACCTACGCCCTCCTAA	6636619
LRRC4	LRRC4f	543	CGAGTCGGAGTGAGCGTTAAGTGAGGGG	chr7: 127459680-	101
	LRRC4r	544	CCTATCAACGACCACCCAACTACTCCCT	127459780
MIR155HG	MIR155HGf	545	TCGGGTTTAGCGTCGTTTGTAGTTTCGG	chr21: 25856335-	96
	MIR155HGr	546	AAAAACGTCTCCTTAATTCCCCGCGCTT	25856430
NEXN	NEXNf	547	GCGGTTGGAGTAGAAGTGTTAGCGGTTAGA	chr1: 78126913-	124
	NEXNr	548	TCACCCTACAAAAACCGATAACCGACGA	78127036
NKX2-1	NKX2-1f	549	AGTTGGTTATAGGCGGCGAATTGGGTTT	chr14: 36057307-	91
	NKX2-1r	550	TCAACACCCCCTCTCCTAACCTCTCCAA	36057397
NKX6-2	NXX6-2f	551	CGGGGAAGAGTTTCGGTTCGCGTTTTAG	chr10: 134449988-	123
	NXX6-2r	552	CCCTCCTATAACCCCGACCTACCCGAAA	134450110
	NKX6-2R_f	553	GCGCGGTAGGTGTTTTTCGGGTTGTAAA	chr10: 1344419796-	97
	NKX6-2R_r	554	ACCTTTACCTAACTACACTCCCATCCAA	134449892
NOTUM	NOTUMf	555	AGAGTAGGTCGTGGGGGATTC	chr17: 77512836-	87
	NOTUMr	556	CGCGCTAACCGCGATAAAAAC	77512922
NRN1	NRN1f	557	AGGAGCGGGAGAGGGAAAAATAGTTAAG	chr6: 5952635-	125
	NRN1r	558	ACTACGCCCAAAACTCAACTACTAAAT	5952759
PLTP	PLTPf	559	TGGGAACGGGATAGGGACGCGTTTTAAT	chr20: 43974093-	92
	PLTPr	560	GAATCCCCTAAACTACCCGCCATCCCAC	43974184
	PLTPR_f	561	TGTACGCGTATTTTTGGAGGGTGGTTTGC	chr20: 43973871-	80
	PLTPR_r	562	CGATCTAATCGACCACCTCCTCTCCTCC	43973950
PRDM13	PRDM13f	563	AAGTTTCGTCGAGTTGGGGTCGTTGGTT	chr6: 100168753-	92
	PRDM13r	564	GACCCTTCCCGACAACCATCTCGAACA	100168844
PRDM15	PRDM15f	565	GAAAATTGCGCGGTTGGGTTAGTAGGGG	chr21: 42110148-	112
	PRDM15r	566	ACCTACAAATACCGTCCCCACCCGAAAC	42110259
PTGDR	TGDRf	567	AAGAGGGGTGTGATTCGCGAGTTTAGAT	chr14: 51804089-	110
	TGDRr	568	CCGCGCGCGACTCGAACGAAAAA	51804198
RECK	RECKf	569	AAGGGTGCGATGTTTTCGTTTAGGATCG	chr9: 36027398-	88
	RECKr	570	TAACTAACTAAAACCGCGATAAAACGACT	36027485
RTN4RL1	RTN4f	571	TGGTAATCGCGTAGGTGTGTGATAGGGC	chr17: 1827825-	107
	RTN4r	572	AAAATACAAAATACGCCCCCGACCCCGA	1827931
	RTN4RL1R_f	573	TGAGGAGAGATTCGGAGTAGTTAGTAGA	chr17: 1827743-	109
	RTN4RL1R_r	574	CCCTATCACACACCTACGCGATTACCAA	1827851
SFRP5	SFRP5f	575	TTTCGAAAAGTTGGTAGTCGGCGGTTGG	chr4: 154929548-	123
	SFRP5r	576	CATTCTACTCCCCCGAATCGAAACCCCC	154929670
	SFRP5R_f	577	AAGAGGAAGAGTTCGCGCGTCGAGTTTA	chr4: 154929355-	100
	SFRP5R_r	578	GAAATCGCGCGCCCACGATACTACAAAA	154929454
SHF	SHFf	579	TTATTAGTAGGCGGCGTCGGGGGTT	chr15: 43266978-	150
	SHFr	580	CGAAAACCCCTACTCCGAAAAATCGTCCG	43267127
	SHFR_f	581	GTTGAGATATCGAGGGGTTCGGGTTAGG	chr15: 43266838-	122
	SHFR_r	582	CGCCAACAACGATAAAATAAATACCGCGCC	43266959
SHOX2	SHOX2f	583	CGTTTGTTCGATCGGGGTCGTACGAGTAT	chr3: 159304063-	100
	SHOX2r	584	TTTCCGCCTCCTACCTTCTAACCCGACT	159304162
SNCA	SNCAf	585	GGTTGGGGGAGTGGGAGGTAAATTCGTT	chr4: 90977105-	117
	SNCAr	586	CTAAACGCTCCCTCACGCCTTACCTTCA	90977221
SNX32	SNX32f	587	TTGAGGGAAACGCGGTGGGAATCGTTTT	chr11: 65357939-	119
	SNX32r	588	CCGTAACTCGCCCGAAAAACTAACCGAA	65358057
SP9	SP9f	589	TGATTGGTTGCGGGGTAGTTTC	chr2: 174907826-	86
	SP9r	590	ACACCCGCTTTAAAATACCGCTAA	174907911
STK33	STK33f	591	GCGTTTCGGGTCGTTCGTTTTATTTCGC	chr11: 8572140-	123
	STK33r	592	CGACAACCTACGCCGAATATACGCACCT	8572262
SYNGR3	SYNGR3f	593	GAAGGGATGAGGTTGAGGTTGGAGGTCG	chr16: 1981075-	121
	SYNGR3r	594	ACCTCCTACCCACCAATTCCGAAAAACAA	1981195
T	Tf	595	TTACGGAGTTTTAGGCGGCGTTAC	chr6: 166501979-	121
	Tr	596	CATTTCCCTCTCTACGCGCGAAC	166502099
THBS2	THBS2f	597	CGTAGGTTTTGTTGGAGCGAGAGATCGG	chr6: 169395805-	94
	THBS2r	598	ACATATAAAACCGCGCTACCCGAAAACCG	169395898
TLX1NB	TLX1NBf	599	TGAAAGGGGAGAGGGGAATGTTATTGTT	chr10: 102871413-	106
	TLX1NBr	600	AATATTCTCGCAAACCCACCGCCAAACC	102871518
TMEM22	TMEM22f	601	AAAGAGATTCGTGTTGCGGCGGATGAAG	chr3: 138021575-	117
	TMEM22r	602	GATCAACACTCGAACCCGAACTTTCCGC	138021691
TNFRSF10D	TNFRSf	603	AAGGGAGGAGGGTGGATCGAAAGCGTTA	chr8: 23077397-	79
	TNIFRSr	604	CGAAAACCTTTACACGCGCACAAACTACG	23077475
TXNRD1	TXNDR1f	605	TATGGGTTGCGTCGAGGGTAAGGTAGTG	chr12: 103133710-	79
	TXNDR1r	606	ACCATCGCCGTTCTTACCTTTCGTCTACA	103133788
VSTM2B	VSTM2Bf	607	TTTTTAATTCGGTTCGGCGTTGATTTGT	chr19: 34711435-	125
	VSTM2Br	608	ACAACCGCGCGCTCCCGATAC	34711559
ZFPM2	ZFPM2f	609	TAGCGCGGAAGTTGTGAGTTTAAGGCG	chr8: 106401146-	96
	ZFPM2r	610	TCCTCTAAACACCATCGAAACCCCCGAAC	106401241
ZNF280B	ZNF280Bf	611	AGTGGCGTTCGTTGAGATTAGGGAAGGG	chr22: 21192757-	121
	ZNF280Br	612	ACCGTACGCTACCGAAACGACCTTTACA	21192877
LOC105378683	LOC105 Af	613	GTTTGTAATTGGTATGAGCGGC	chr1: 43023566-	108
	LOC105 Ar	614	ATAACGAAACGACGCCTC	43023673
	LOC105 Bf	615	GTAATTGGTATGAGCGGCGT	chr1: 43023570-	91
	LOC105 Br	616	GCCTCCGCGAAATAAAACCAT	43023660
	LOC105 Cf	617	AGTTAGAGTGGGTTAGGGGAT	chr1: 43023464	150
	LOC105 Cr	618	ACGCGTAACACAAACACGAC	43023613
NPHS2	NPHS2 Af	619	GGGGGATTTTAAAGATCGTC	chr1: 177811721-	122
	NPHS2 Ar	620	GACGAACGCAATCCACAA	177811842
	NPHS2 Bf	621	TGGTGGAGTTGTGGATTGCG	chr1: 177811817-	75
	NPHS2 Br	622	TCCCACCCAAACCTCTCTCT	177811891
NR5A2	NR5A2 Af	623	GGTGCGTTTACGGGTTTC	chr1: 198278389-	150
	NR5A2 Ar	624	ACCTAATCCGATATTTCCCGA	198278538
	NR5A2 Bf	625	GGTAGGGTTTCGGTTGCGTA	chr1: 198278432-	139
	+NR5A2 Br	626	TATTTCCCGAAAACTCCACATCCA	198278527
	NR5A2 Br	627	TCCCGAAAACTCCACATCCA
PAX6	PAX6 Af	628	ATTTGGATGTTTCGCGTTTC
	PAX6 Ar	629	TATCGCTACGACCCGACTAA
	+PAX6 Af	630	GTTAATTTGGATGTTTCGCGTTTC	chr11: 31783206-	117
	+PAX6 Ar	631	GTTTATCGCTACGACCCGACTAA	31783322
	PAX6 Bf	632	AGGGGAGTCGCGTTTTTAGG	chr11: 31782520-	133
	PAX6 Br	633	TCCCGACCGAAACCCAAATC	31782652
KCNE3	KCNE3 Af	634	GAATAACGGCGTAAGTTTTTAC	chr11: 73855818-	98
	KCNE3 Ar	635	ATCCTCCCGAACGCAATA	73855915
	KCNE3 Bf	636	TTGTACGTTTGTGGGTGTGGA	chr11: 73855765-	150
	KCNE3 Br	637	TCCTCCCGAACGCAATAATCG	73855914
KCNA6	KCNA6 Af	638	TTAACGGTTAGGTTAGATCGC	chr12: 4789322-	100
	KCNA6 Ar	639	CAATCTCTAAAACGCGACAC	4789421
	KCNA6 Bf	640	CGGGTGTCGCGTTTTAGAGAT	chr12: 4789399-	84
	KCNA6 Br	641	TTCTCCGATCTCATACCCCCT	4789482
TMEM132C	TMEM Af	642	GAGAAAAGTTGTTTCGGTC
	TMEM Ar	643	GCTACGTCTCTACTATCCGA
	+TMEM Af	644	CGGGAGAAAAGTTGTTTCGGTC	chr12: 127317663-	124
	+TMEM Ar	645	CCGCTACGTCTCTACTATCCGA	127317786
	TMEM Bf	646	TTCGGGGTGAGGGTAGTC
	TMEM Br	647	CCGACGCCCAACTAAAAA
	+TMEM Bf	648	GAGTTCGGGGTGAGGGTAGTC	chr12: 127318043-	137
	+TMEM Br	649	GAATCCCGACGCCCAACTAAAAA	127318179
	TMEM Cf	650	TTTTCGGGTTACGGGTCGTT	chr12: 127317330-	95
	TMEM Cr	651	ACGACTCCTCCGAAAATCCG	127317424
PDX1	PDX1 Af	652	GTCGATTTTTGTTTTGAGC	chr13: 27390195-	86
	PDX1 Ar	653	TAAAAATAATCTACCGAATCGC	27390280
	PDX1 Bf	654	GGCGTTAGCGGGGATTTAGA	chr13: 27389563-	132
	PDX1 Br	655	CGCATCAAACGAAACCCTCC	27389694
	PDX1exp Af	656	CGGGAAGGTGTTCGTTTAATGGTTCGGT	chr13: 27389489-	102
	PDX1exp Ar	657	GTTTCCGCTCTAAATCCCCGCTAACGCC	27389590
	PDX1exp Bf	658	GGAAAAAGGAGGAGGATAAGAAGCGCGG	chr13: 27396588-	98
	PDX1exp Br	659	CTCGCCGAAAATCACGACGCAATCCTAC	27396685
EPSTI1	EPSTI1 Af	660	TAGGGGAGGCGTCGAGTTC	chr13: 42464253-	117
	EPSTI1 Ar	661	ACTCGCTAAACGTCCCAACC	42464369
A2BP1	A2BP1 Af	662	GAGTTTAGGGGTCGCGTC	chr16: 6009425-	140
	A2BP1 Ar	663	CAATACCGCCGCCTCTACTA	6009564
	A2BP1 Bf	664	GAGAGAGTAGGAGCGGATCG	chr16: 6009706-	137
	A2BP1 Br	665	ACAAATCAACCCCGCCCTAA	6009842
CRYM	CRYM Af	666	AGTGAGTGTTCGGGAGTTTC
	CRYM Ar	667	TCATTTATTAAAAACGCGCG
	+CRYM Af	668	GCAGTGAGTGCTCGGGAGCCCC	chr16: 21202786-	149
	+CRYM Ar	669	GGTTTTCATTTGTTAGAGGCGCGCG	21202934
	CRYM Bf	670	CGGGTTCGCGTAGGATTAGG	chr16: 21202650-	83
	CRYM Br	671	ACTCCTCATCCCAACACCCT	21202732
PRKCB	PRKCB Af	672	GTTCGTAGTTCGCGGTTTC
	PRKCB Ar	673	CGATACTCTCCTCGCCCT
	+PRKCB Af	674	TCGGTTCGTAGTTCGCGGTTTC	chr16: 23754928-	125
	+PRKCB Ar	675	GCACGATACTCTCCTCGCCCT	23755052
	PRKCB Bf	676	TTGGGCGAGTGATAGTTTC	chr16: 23754821-	89
	PRKCB Br	677	GACCGCTACTACACCCGA	23754909
	PRKCB Cf	678	CGGTAGAAGAACGTGTATGAGGT	chr16: 23755076-	141
	PRKCB Cr	679	GCTACCCTCGAAAACCCGAA	23755216
IRF8	IRF8 Af	680	GATTTTTTTTAAGGTCGCGC	chr16: 84490230-	112
	+IRF8 Af	681	TTACGATTTTTTTTAAGGTCGCGC	84490341
	IRF8 Ar	682	ACTATACCTACCTACCGCCGTC
	IRF8 Bf	683	ATTTCGAAGAAGGCGGGTCG	chr16: 84490149-	128
	IRF8 Br	684	CTCCAAACGATACGCCAACG	84490276
SALL3	SALL3 Af	685	TTTTGCGGGTAAGCGTTC
	SALL3 Ar	686	CCACAACTCTCTCGACGAC
	+SALL3 Af	687	TGTTTTTTGCGGGTAAGCGTTC	chr18: 74841456-	96
	+SALL3 Ar	688	GCCCACAACTCTCTCGACGAC	74841551
	SALL3 Bf	689	ATTTCGGGAAAGGGTGGGTC	chr18: 74840051-	113
	SALL3 Br	690	ACCCTAATCCCCCTTCACCA	74840163
	SALL3 Cf	691	TTTCGTTTCGTTTCGGTCGC	chr18: 74840452-	122
	SALL3 Cr	692	AACCCGCCCGAACTCAAATA	74840573
LYPD5	LYPD5 Af	693	ATTAGGAGCGTACGTTTATTC	chr19: 49016646-	143
	LYPD5 Ar	694	TACGCACTCGAAACACAA	49016788
	LYPD5 Bf	695	CGGCGCGTTTTAAGGGTTTT	chr19: 49016738-	126
	LYPD5 Br	696	ATTACTCTCACCTCCGCACG	49016863
DPP10	DPP10 Af	697	GATTGCGGGAAGAAGGTAC
	DPP10 Ar	698	AAACGAAACCAAACGACAA
	+DPP10 Af	699	CGGATTGCGGGAAGAAGGTAC	chr2: 115635638-	102
	+DPP10 Ar	700	GACGAAACGAAACCAAACGACAA	115635739
	DPP10 Bf	701	TTTTCGAGTTTGAAGCGTTC
	DPP10 Br	702	CGACTCTCACCTAATCCGC
	+DPP10 Bf	703	CGGTTTTCGAGTTTGAAGCGTTC	chr2: 115635947-	142
	+DPP10 Br	704	TACCGACTCTCACCTAATCCGC	115636088
	DPP10 Cf	705	TTACGACGGGGAGTTCGTTC	chr2: 115635821-	123
	+DPP10 Cr	706	CTTAACAACGTTCGCAAATCACGA	115635943
	DPP10 Cr	707	ACAACGTTCGCAAATCACGA
C20orf56	C20orf Af	708	GTTCGTTATTTCGGAATTC	chr20: 22507658-	147
	C20orf Ar	709	CCGACCGATAAAATATAATTC	22507804
	C20orf Bf	710	GGGAGGGATTTAAGCGGGAG	chr20: 22507684-	136
	C20orf Br	711	CCCCCTTCACTAATCCCGAC	22507819
SOX2OT	SOX2OT Af	712	AGTGTTGAGAGTCGACGC	chr3: 182919951-	92
	SOX2OT Ar	713	AATAAAATAACCCGAACCGC	182920042
	SOX2OT Bf	714	GGGTTACGGTTTCGGGTTGT	chr3: 182919884-	86
	SOX2OT Br	715	CGCGTCGACTCTCAACACTA	182919969
CDKL2	CDKL2 Af	716	GGTCGAGTCGAGTCGTTAC
	CDKL2 Ar	717	AAAACGCCTCCTAACGAA
	+CDKL2 Af	718	ATTGGTCGAGTCGAGTCGTTAC	chr4: 76774785-	151
	+CDKL2 Ar	719	ACAAAAAAACGCCTCCTAACGAA	76774935
	CDKL2 Bf	720	TATTTTTGGGCGAAGGCGTTG	chr4: 76774698-	109
	CDKL2 Br	721	GTAACGACTCGACTCGACCA	76774806
MARCH11	MARCH11 Af	722	TCGGCGTTTTCGTTTTTC	chr5: 16232623-	75
	MARCH11 Ar	723	CGACGACACAACCATAAACTTT	16232697
	MARCH11 Bf	724	AAGGTTTTGTAGTTGCGGCG	chr5: 16232839-	97
	MARCH11 Br	725	TCTCACGCGCAACCGAAT	16232935
CCL28	CCL28 Af	726	GTGGAGTTTTAGGTAGCGC
	CCL28 Ar	727	ACCCGCGATAAACTAAACC
	+CCL28 Af	728	AGGGTGGAGTTTTAGGTAGCGC	chr5: 43433001-	128
	+CCL28 Ar	729	AACAACCCGCGATAAACTAAACC	43433128
	CCL28 Bf	730	TGTAGTCGTGGTTGTCGTGG	chr5: 43432695-	140
	CCL28 Br	731	CCAAATAAACGACGTCCCGC	43432834
AP3B1	AP3B1 Af	732	ATTTTATAGTCGCGTTAAAAGC	chr5: 77304383-	137
	AP3B1 Ar	733	ACTTTTATTACTCGCGATCC	77304519
	AP3B1 Bf	734	GGTAGGGTGAGTTTGGTCGG	chr5: 77304339-	146
	AP3B1 Br	735	CGCCGAACCACGTAAAAACT	77304484
CARD11	CARD11 Af	736	ATTTGGGGCGTTTATGTTTC	chr7: 3049825-	120
	CARD11 Ar	737	CCCTCGAAAAACGACTCC	3049944
	CARD11 Bf	738	AGGGGTTGTAGGGTCGGG
	+CARD11 Bf	739	TTTAGGGGTTGTAGGGTCGGG	chr7: 3049955-	133
	CARD11 Br	740	ATTTTACATTTCCCTCCCCCGC	3050087
BLACE	BLACE Af	741	AGAATAAAAGTAGGCGGC	chr7: 154859246-	139
	BLACE Ar	742	TCTCGAAACCAAAATAAACG	154859384
	BLACE Bf	743	AGTAGGCGGCGGATTTGTAG	chr7: 154859254-	104
	BLACE Br	744	CCGAAAATACGCGAAATCAACC	154859357
PTPRN2	PTPRN2 Af	745	GAGGAGATAAAGGTGTCGC
	PTPRN2 Ar	746	AACGTACCTAACCCGAAAAC
	+PTPRN2 Af	747	TCGGAGGAGATAAAGGTGTCGC	chr7: 157176188-	155
	+PTPRN2 Ar	748	CCAACGTACCTAACCCGAAAAC	157176342
	PTPRN2 Bf	749	GACGGTTTCGGTAGGGTC
	PTPRN2 Br	750	CCGAACCGAATATAAAACGA
	+PTPRN2 Bf	751	CGGACGGTTTCGGTAGGGTC	chr7: 157176379-	85
	+PTPRN2 Br	752	GCGCCGAACCGAATATAAAACGA	157176463
RUNX1T1	RUNX1T1 Af	753	TTAGGTTCGTAAAGAGGGC	chr8: 93183286-	116
	RUNX1T1 Ar	754	TTAAAACCACGTCCGAATA	93183401
	RUNX1T1 Bf	755	TTTCGGGCGGGAGTTATAGG	chr8: 93183412-	118
	RUNX1T1 Br	756	ACGCGCTCTAAACTCAACCG	93183529
L1TD1	L1TD1 Af	757	GCGCGTGGGGYFCGTAGCGTTTTAAG	chr1: 62433357-	109
	L1TD1 Ar	758	TTACCCGAAACACCCCGCGCCCTTC	62433465
PPFIA3	PPFIA3 Af	759	AGATACGGAGATTTAGCGCGAGATCGGT	chr19: 54337953-	143
	PPFIA3 Ar	760	AAATTAACCGCCGAACACTCACAATACG	54338094
FILIP1L	FILIP1L Af	761	TTGTAGTGTCGCGTTGCGAGTCGATTGT	chr3: 101077651-	103
	FILIP1L Ar	762	ACAATAACGTAACGCCCATAAACCGAACG	101077753
NUDT16P	NUDT Af	763	GAGGACGGGTTGAATCGTGGTTTGTTGG	chr3: 132563775-	84
	NUDT Ar	764	ACTACGATAATCAAAACGCTCCACGCGA	132563858
TOP2P1	TOP Af	765	GTGCGCGTTTTAGTAGGGCGAGAATGG	chr6: 28283268-	150
	TOP Ar	766	CGAAAACCAAATCCGAACCACCGTCTCC	28283417
	TOP Bf	767	TGATTTGGGTGGATGTAGAGGTTGTGGT	chr6: 28283447-	122
	TOP Br	768	TTTCGAATAACGCTACTCCGAACCGCGA	28283568
UNKWN1	UNKWN1 Af	769	TTGAGAGTAGGGATTGTGGTGCGTCGTC	chr5: 72634694-	145
	UNKWN1 Ar	770	CTAACTCCCGAACGCTACATTCGCTCCA	72634838
GALR3	GALR3 Af	771	GGTTGTGGTGAGTTTGGTTTACGGGCG	chr22: 36550907-	143
	GALR3 Ar	772	CGTAAAACGCGACCACCGCCAACATA	36551049
PRSS27	PRSS Af	773	GGGAGGTTATTCGTAGGATTTGGCGCGG	chr16: 2705610-	139
	PRSS Ar	774	ATCCTAACGACTACGCACTACTTCCGCA	2705748
SLC7A4	SLC Af	775	GAGTTCGTTTAGTTCGTCGGCGTC	chr22: 19716858-	148
	SLC Ar	776	AACCCCGATAAACTCCGATAACGACCT	19717005
LEF1	LEF1 Af	777	AGAGTTGGGGGCGGTATAGTTAGGGTGT	chr4: 109307444-	104
	LEF1 Ar	778	TTCAATCCCTACGACCCCAACGCCTAAA	109307547
NFIC	NFIC Af	779	CGTGGATACGAGTTTTGGCGGCGATTAT	chr19: 3386117-	103
	NFIC Ar	780	GCCACCAACCCTACCTCCTTCCATATCC	3386219
	NFIC Bf	781	TTTTTCGGTTTGAGTTATCGTGGCGGGA	chr19: 3386234-	146
	NFIC Br	782	CGAACCGTACTTCCAACCAAACGCAACT	3386379
TMEM90B	TMEM90 Af	783	TAGGAAGGGGTCGATGTTGGTTTGGGTT	chr20: 24398648-	100
	TMEM90 Ar	784	TCTCACCAACTCCCATCGAATTCGCACA	24398747
	TMEM90 Bf	785	GTTTTGGTTTCGTTTCGGAGCGCGTAGA	chr20: 24398510-	133
	TMEM90 Br	786	TTTCTCTACCGACTCAACTCCCCCTCCC	24398642
UBD	UBD Af	787	TCGGTTGCGTAAATCGCGTTTTTGGTTG	chr6: 29629437-	128
	UBD Ar	788	TTCTCGATAATATCTCCGTCGCCTCCGC	29629564
GIPC2	GIPC Af	789	GTTTAGGGGTGGAGGTCGGGGTTTTGA	chr1: 78284199-	91
	GIPC Ar	790	CCGAACCCCGCGCAAATAAAAACAACCT	78284289
EFNA4	ERNA Af	791	GGGGCGCGTTTTTATGGAAAGTTAGGGT	chr1: 153310423-	127
ERNA4	ERNA Ar	792	CTACGCCCTAAAACACGCCTCGACTTCT	153310549
	ERNA Bf	793	TGTGCGAAAGAGACGCGGGGTTTAGTTA	chr1: 153310139-	150
	ERNA Br	794	CCCGTAATCGCTAAAACATCCGCCCTTA	153310288
DRD4	DRD4 Af	795	CGTCGGGCGATGTTGGTTTGTTCGTG	chr11: 627035-	141
	DRD4 Ar	796	GCGACGCTCCACCGTAAACCCAATATTTA	627175
TCTEX1D1	TCTEX Af	797	CGGGGAGGGTCGAGGGTTTTGTTTGAG	chr1: 66990668-	101
	TCTEX Ar	798	GCGTCCCAAACTTCATTCAACCGACGAC	66990782
PHOX2B	PHOX Af	799	GCGGACGTAGTAATGGATTAAACGGGGA	chr4: 41447111-	145
	PHOX Ar	800	AAATCCGACTCCCTACACTCCCGACTTT	41447255
TSPAN33	TSPAN Af	801	GGGGGTTGTGTTAGTTGTTTGTTTAGCGA	chr7: 128596487-	107
	TSPAN Ar	802	CGAAACTATTTCCCGCCAAACCGAACCC	128596593
CA9	CA9 Af	803	TTTCGGGCGGGAGTATCGGGTTTTGTAG	chr9: 35666101-	139
	CA9 Ar	804	GCTCCTTTACCCCTTCTCGACCAACTCC	35666239
UNKWN2	UNKWN2 Af	805	TTACGGATTTTATTTGTATTCGGAATCGTA	chr10: 102409232-	104
	UNKWN2 Ar	806	ACGCATCAAACTCGACACAAAATTTCATC	102409335
WT1	WT1 Af	807	GGTGTTTTCGTAAGACGGGGTAGTGGGT	chr11: 32406776-	94
	WT1 Ar	808	TTCTCCTCCGCTAAAAATCCGAATACGA	32406869
OTX2	OTX2 Af	809	AGGGATTGTATTTCGAGGTGGTCGAGGT	chr14: 56331673-	109
	OTX2 Ar	810	CCGACAAATCGAAACCTTCGCCCGAAAC	56331781
HOXB13	HOXB13 Af	811	TCGCGGGTTATAAATATTTGGTTGCGGC	chr17: 44157793-	93
	HOXB13 Ar	812	GACCGCCACTACCTCGAAAACATTTCCC	44157885
BRCA1	BRCA1 Af	813	GGTAACGGAAAAGCGCGGGAATTATAGA	chr17: 38530874-	95
	BRCA1 Ar	814	CCCACAACCTATCCCCCGTCCAAAAA	38530968
ITPRIPL1	ITPRIPL1f	815	TTTTGTACGTTGGGTTACGGGGGTTTGG	chr2: 96354715-	143
	ITPRIPL1r	816	TAAACGCGATAAACCCCTACGACCCCCA	96354857
HES5	HES5-F	817	TATCGGTTTTCGTAGTTGCGGGAGGAGG	Chr1: 2451323-	118
	HES5-R	818	CCGAATAAATACCAAACTCGCCCGACGC	2451386
CSRP1/	CSRP1/	819	CGGGTAGAGGGGAGGTAGGAATTGGAGA	Chr1: 199775889-	80
LOC376693	LOC376693-F			199775914
	CSRP1/	820	CCGAATAAACGTCACCCCTACACACCGC
	LOC376693-R
ALOX5	ALOX5-F	821	TTTTGCGGTTAGGTGAAGGCGTAGAGGT	Chr10: 45234681-	106
	ALOX5-R	822	GACCGAATACCCCGCTTTCTCTCTCGAC	45234732
PPM1H/	PPM1H/MON2-	823	AGGAGTAGTATTGCGAGGGTGGAGGGT	Chr12: 61311943-	112
MON2	PPM1H/MON2-	824	TAAACCCGAAAAACAACGCCAATCCCGC	61312001
KIAA0984	KIAA0984-F	825	GGGGATTTGTTGTAGAGTCGTAGGAGAA	Chr12: 63515983-	62
	KIAA0984-R	826	CCGCATCCCACCCTTTAAAACTCTA	63516043
TXNRD1	TXNRD1-F	827	TATGGGTTGCGTCGAGGGTAAGGTAGTG	Chr12: 103133737-	86
	TXNRD1-R	828	TACGACGACCATCGCCGTTCTTACCTTT	103133768
CHST11	CHST11-F	829	AAATTTGGATTGGGGGAGGGACGAGGTT	Chr12: 103376469-	124
	CHST11-R	830	CTTCGCAACCGAACTACTCACCCCCGAC	103376538
EFS	EFS-F	831	GGTCGTTGGAGTGGTCGTTTCGGTTTAG	Chr14: 22904743-	98
	EFS-R	832	CCTCAAACCCCCGAACGCGCTAAATAAA	22904785
ANXA2	ANXA2-F	833	GTTCGGGGAGGGAGGGAGATTCGTTTTG	Chr15: 58478046-	107
	ANXA2-R	834	AACTCCCGACTTTAACCTCCCAACCCAA	58478098
RHCG	RHCG-F	835	GTTGTAGGGGTGTTTGGTCGGGTTGGTA	Chr15: 87840807-	118
	RHCG-R	836	ATCAACTACTCCGTACCCCACGTAACCG	87840869
RARA	RARA-F	837	AGTCGGGGTTGGTTGGTGGAAGAGG	Chr17: 35718896-	137
	RARA-R	838	CCCTCTCAACTCGATTCAAAATTCCCCC	35718981
PTRF	PTRF-F	839	AAAGTAATAAGTGGTTTCGGGCGGAGTC	Chr17: 37827277-	104
	PTRF-R	840	ACCCCGCATACCTACGAAAACGAAAACC	37827326
RND2	RND2-F	841	CGGGATTATGGAGGGGTAGAGCGGTCG	Chr17: 38430910-	99
	RND2-R	842	ACGTCCTTAACGAACACCTACAACAACG	38430955
TMP4	TMP4-F	843	AGGTTTTGTAGTAGTAGGCGGACGAGGC	Chr19: 16048446-	121
	TMP4-R	844	ACGAATACGAAACCCGAAACCGAAACGC	16048512
HIF3A	HIF3A-F	845	CGTGGTATAGTTAATCGCGCGGCGT	Chr19: 51492259-	118
	HIF3A-R	846	TACAACCCCAACGCCATAACTCGCCAAT	51492376
KLK5	KLK4-F	847	TAGCGGGGATTTATTAGGGGAGAGGTGG	Chr19: 56107959-	123
	KLK4-R	848	ATCACCTACGAACACTATCCCTCACCCG	56108027
AMOTL2	AMOTL2-F	849	GCGGAATAGTTCGCGGTTTTGGAATGTT	Chr3: 135565786-	125
	AMOTL2-R	850	AAACGTTTCCGCTCCCCGAAAAACGAAT	135565856
SCGB3A1	SCGB3A1-F	851	GGAGATAGTTTTGAGAGGGGGAGGTCGC	Chr5: 179950858-	120
	SCGB3A1-R	852	CGCTACCTACGCCGATCGTAAATCCCAA	179950923
HLA-F	HLA-F-F	853	GAATGGTTGCGATATGGGGTTCGACGGA	Chr6: 29799978-	112
	HLA-F-R	854	CGCGATCCAAAAACGCAAATCCTCGTTC	29800035
HLA-J-1	HLA-J,	855	GGTTTTGGTCGAGATTTGGGCGGGTGAG	Chr6: 30082430-	101
	NCRNA00171-1-F			30082476
	HLA-J,	856	CCCGAATCCTACGCCCCAACCAAATAAA
	NCRNA0017101-R
HLA-J-3	HLA-J,	857	TGAGTGATTTCGGTTCGGGGCGTAGATT	Chr6: 30083115-	125
HLA0J	NCRNA00171-2-F			30083168
	HLA-J,	858	CGAAAATCTCTACAAATCCCGCAACCTCG
	NCRNA00171-2-R
PON3	PON3-F	859	ATGGTTTCGGGGTGTTTAGCGGCGATTG	Chr7: 94863624-	105
	PON3-R	860	AACGAAACCGAACGAACCCCAATCCGTA	94863674
LRRC4/SND1	LRRC4-F	861	GAGTCGGAGTGAGCGTTAAGTGAGGGG	Chr7: 127459707-	77
	LRRC4-R	862	TCCCTCCGACCGACCCAAAATAACTACG	127459730
PAH	PAH-F	863	TTCGTTGTTCGTTTTGGGTAAAGGGAAG	Chr12: 101835348-	116
	PAH-R	864	AAACTCGCTTCCCAAACTTCTAAAAATC	101835409
EPSTI1	EPSTI1-F	865	GGGGAGGCGTCGAGTTCGGAGTTTATTA	Chr13: 42464282-	117
	EPSTI1-R	866	AAAACTCGCTAAACGTCCCAACCGCATC	42464345
ADCY4	ADCY4-F	867	CGGGTATTGTTGGTTTAGGTTGTAGTAGGT	Chr14: 23873644-	123
	ADCY4-R	868	CGACCCTAACCAACCCCGAAACTCGAAA	23873710
HAPLN3	HAPLN3-F	869	AGGGTAGAAAGGAAGCGGTAGTAGAAAA	Chr15: 87239811-	116
	HAPLN3-R	870	ACAACAACTCCTCCCTTCGAACCCAACC	87239872
HSF4	HSF4-F	871	TGTGGGAGGGAAGGGAAATCGAGATTGG	Chr16: 65762053-	113
	HSF4-R	872	ACGACAAAACGAAACCCACAATCCTACCC	65762164
NBR1/	NBR1/TMEM106A-F	873	ATTCGGATTGGTTAGTTTTTGCGGAAGT	Chr17: 38719260-	91
TMEM106A	NBR1/TMEM106A-R	874	TTCGCCACGCAACAACCTAAAACGCTAC	38719296
HAAO	HAAO-F	875	GGTTGCGGCGTTTATTTAGCGGGAAGTC	Chr2: 42873761-	114
	HAAO-R	876	CTCGCCGAACCCGCGACGAAATCTAC	42873822
RARB	RARB-F	877	TAGAGGAATTTAAAGTGTGGGTTGGGGG	Chr3: 25444371-	125
	RARB-R	878	ACCAACTTCTCTCCCTTTACGCCTTTTT	25444441
ALDH1L1	ALDH1L1-F	879	TGGGTTAAGTATTTGTTATGTGTTACGGA	Chr3: 127382511-	121
	ALDH1L1-R	880	CGCTATCCACCCGAATACGCAACT	127382580
HIST1H3G	HIST1H3G-F	881	GCGCGGCGTTTTGTTATCGGTGGATT	Chr6: 26379588-	60
	HIST1H3G-R	882	TCTAAAATAACCCGCACCAAACAAACTACA	26379647
ZSCAN12	ZSCAN12-F	883	TTATAAAGGTCGGAAGCGGTTACGGGGG	Chr6: 28475534-	93
	ZSCAN12-R	884	AACCCCTTTCGCTCCCTTCCTAAAACGA	28475572
HCG4P6	HCG4P6-F	885	GTATGGTTGCGATTTGGGGTTGGAAGGG	Chr6: 30002983-	114
	HCG4P6-R	886	GCCGCGATCCAAAAACGCAAATCCTAAT	30003042
HLA-J-3	HLA-J,	887	TAGGGAATGTTTGGTTGCGATTTGGGG	Chr6: 30083115-	80
	NCRNA00171-3-F			30083168
	HLA-J,	888	TCCTTACCGTCGTAAACATACTACTCAT
	NCRNA00171-3-R
EYA4	EYA4-F	889	GCGTAAGTGCGAGGTTGTCGGTAGC	Chr6: 133604154-	125
	EYA4-R	890	TTTCCCGCAACTCTTTCCCCCTCTCT	133604229
HOXA7	HOXA7-F	891	TGCGGTTAAAGAATTCGTTCGCGTTCGG	Chr7: 27162955-	82
	HOXA7-R	892	CTAAACGCTCCCGCGAAACCTCCAAATC	27162982
USP44	USP44/p-F	893	TTCGGGTATTTTGAGGTTGTCGTCGGGA	Chr12: 94466379-	103
	USP44/p-R	894	GACGACGACGCGTCCGACGAATTTTA	94466481
CYP27A1	CYP27A1/p-F	895	GTTTTGGTCGGGGCGTCGTGGATATTTT	Chr2: 219354932-	111
	CYP27A1/p-R	896	AAAAACCAACTAAACCCCTTCCCGCTCG	219355042
PRSS3	PRSS3/p-F	897	GTGTGGAAAGGGTTTGGCGGTTGTTAGG	Chr9: 33740574-	113
	PRSS3/p-R	898	CTCGCCAAATACGTCCACCCAAAAACGA	33740686
C18orf62	C18orf62/p-F	899	TAGGAGGGGACGTAGAGTTTACGGCGAA	Chr18: 71296729-	105
	C18orf62/p-R	900	GAATACCCGACCCGACCCATCCATCAC	71296833
SFRP2	SFRP2/p-1-F	901	TGCGTTTGTAGGAGAAGTCGGGTTGGTT	Chr4: 154929326-	83
	SFRP2/p-1-R	902	ACTCTTCCTCGCCTCGCACTACTACCTA	154929408
	SFRP2/p-2-F	903	GTGCGATTCGGGGTTTCGAAAAGTTGGT	Chr4: 154929535-	107
	SFRP2/p-2-R	904	GAAACTACGCGCGAACTTACAACGCCTC	154929641
SLCO4C1	SLCO4C1/p-F	905	GAGCGTAGAGCGTTGAGCGGGG	Chr5: 101660047-	123
	SLCO4C1/p-R	906	CGCCGCCGAATAACACGCCCAC	101660169
CORO1C	CORO1C/p-1-F	907	AGCGGGGATTTTCGGAGTTGGAGAGTTT	Chr12: 107686622-	112
	CORO1C/p-1-R	908	CTCCATCCGCCCGACCTAACCCTAAAAA	107686733
	CORO1C/p-2-F	909	GGGAAGTGGCGTAGTGGGCGTTTGTATC	Chr12: 107686752-	97
	CORO1C/p-2-R	910	TACCTCCAACGACCACGCCCACAAAATA	107686848
KJ904227	KJ904227/p-F	911	TGGAGCGTTGAGTCGAAGTTTTGATTTT	Chr3: 127489474-	109
	KJ904227/p-R	912	TCTTACCCGAACTTTAACCCCAACCGCT	127489582
C6orf141	C6orf141/	913	GGTTGGGAGTTCGGAGTTGTAGTAGAGG	Chr6: 49626357-	99
	p-1-F			49626455
	C6orf141/	914	CTTTAACCGATTCAAACAACAAACGCCT
	p-1-R
	C6orf141/	915	GTAGGGCGCGGGGTTTCGTTAGTTTC	Chr6: 49626570-	99
	p-2-F			49626668
	C6orf141/	916	ATCTACCGTTCTATCCTCGTAACCGCCG
	p-2-R
BC030768	BC030768/p-F	917	TCGTTTGGGAGGGATCGTTTTTGGGAGA	Chr1: 26424688-	80
	BC030768/p-R	918	AACCCGAATACTATCCAACTACCGCCGC	26424767
DMRTA2	DMRTA2/p-F	919	CGAGCGTGGGTATTAAGTCGGTAGTGGA	Chr1: 50657067-	103
	DMRTA2/p-R	920	GACCTCAACCCCCTACGCCTAACCTACT	50657169
HFE	HFE/p-1-F	921	GTAGATCGCGGTTTTGTAGGGGCGTTTG	Chr6: 26195692-	92
	HFE/p-1-R	922	CTAATTTCGATTTTTCCACCCCCGCCGC	26195783
	HFE/p-2-F	923	GAGTGTTTGTCGAGAAGGTTGAGTAAAT	Chr6: 26196140-	82
	HFE/p-2-R	924	CACCGCCCAACGCATTCGTTCTAAAATA	26196221
CADPS2	CADPS2/p-F	925	ATAAAAGTGGGGTGGGTGGCGGAGGG	Chr7: 121744063-	104
	CADPS2/p-R	926	GCGCCGAAATAACAACCCAACCTACCAA	121744166
CYTH4	CYTH4/p-F	927	TTTATCGGGGAAGTTTTCGAGGGTGGGC	Chr22: 36050993-	120
	CYTH4/p-R	928	TCCCAACTACCTCCTACGCACGAACGAT	36051112
Intergenic	Chr4/p-1-F	929	ATGAAATGTGGTTCGTGGAAGGTGTTTGT	Chr4: 186174475-	75
(Chr4)	Chr4/p-1-R	930	ACGACCCGAACGTTAATCCTCTTACTAC	186174549
NHLH2	NHLH2/p-F	931	ACGTAGTTTTCGAGTTAGTGTCGTTAGAA	Chr1: 116172677-	117
	NHLH2/p-R	932	GACAAACGCCTCAAACCCGACCG	116172793
NRN1	NRN1/p-F	933	AGGAGCGGGAGAGGGAAAAATAGTTAAG	Chr6: 5952635-	133
	NRN1/p-R	934	CGCTCCAAACTACGCCCAAAACTCAA	5952767
HMGCLL1	HMGCLL1/p-F	935	ATTAGAGTTGTTTTGCGTATTGCGGCGG	Chr6: 55551934-	97
	HMGCLL1/p-R	936	CAAATACCCCGTACACCCGCTACCCCAA	55552030
Me3	Me3/p-1-F	937	GGGAGTTGAGGTTTACGCGGTTTCGTTG	Chr11: 86061026-	99
	Me3/p-1-R	938	GACCGCCAACGCGATCCACCCATTAAC	86061124
	Me3/p-2-F	939	AGTTTTGGAAGTAGATTCGGTGCGGGTG	Chr11: 86060867-	82
	Me3/p-2-R	940	GCCGCGCAATCGCCTCTTTTTCAC	86060948
Intergenic	Chr3/p-1-F	941	AGACGATAGATGGCGGGTAGGAAGGGAG	Chr3: 135608250-	125
(Chr3)	Chr3/p-1-R	942	GCCGCCTACAACCGACGAACTACAAATC	135608374
Intergenic	Chr8/p-1-F	943	TCGCGGGTGAGGTTTGTGGTTAATTTCG	Chr8: 68037553-	124
(Chr8)	Chr8/p-1-R	944	GCTCAACCAAACTACAACGTTCCCGCCT	68037676
NBPF1	NBPF1/p-F	945	TGAGAGGCGTATTTTGTTGGTTACGGTT	Chr1: 146219493-	82
	NBPF1/p-R	946	CGAAAACCATTCCGCTACCCTTCCAACT	146219574
Intergenic	Chr10/p-1-F	947	GGGGCGTTGGGTTATGGAGATTACGTTTT	Chr10: 42748953-	101
(Chr10)	Chr10/p-1-R	948	GTCCCGCGCTTAACGAATTCTACGAACG	42749053
ASAP1	ASAP1/p-F	949	GTTCGGGTAGGGGTCGGGGGTC	Chr8: 131524437-	110
	ASAP1/p-R	950	CCCGAAACGACGTACTTAACGACCCGAA	131524546
Intergenic	Chr1/p-1-F	951	GGGAGGTTTGAGCGTCGAAGTTTTCGTT	Chr1: 119352428-	122
(Chr1)	Chr1/p-1-R	952	GCCCACTACCCCGCGAAACCTTATCAAC	119352549
PPP2R5C	PPP2R5C/p-F	953	AGTCGTTAGGTTGTTAAGGCGCGTTGTG	Chr14: 101317476-	59
	PPP2R5C/p-R	954	ACAAAAATAAAATCGAACCTAACCCCACG	101317534
Intergenic	Chr2/p-1-F	955	CGTATTAAGGGTTAAGCGGCGCGGT	Chr22: 44883312-	93
(Chr2)	Chr2/p-1-R	956	AACTTTCTCGAACGACTCGATAAACCTAA	44883404
KRT78	KRT78/p-F	957	AGGTTTTGGGAATTTGGAAGTTCGCGGG	Chr12: 51554274-	97
	KRT78/p-R	958	AAAAACGCTCGAACCCAACCAATCGACG	51554370
LINC240	LINC240/	959	AAAGGAAGATCGTGGGTAGTTCGTGCG	Chr6: 27167780-	80
	p-1-F			27167859
	LINC240/	960	ACTACAACTCACGTTTCCCCTCCAACAC
	p-1-R
	LINC240/	961	AGGTTTATTTGACGTTTTAGGTCGATAGT	Chr6: 27172709-	122
	p-2-F			27172830
	LINC240/	962	CGATCTCTCCCTTTCTTCCGCTTCCTAA
	p-2-R
Intergenic	Chr16/p-1-F	963	GGCGTCGGTTGCGGTTTTAGAT	Chr16: 53648145-	125
(Chr16)	Chr16/p-1-R	964	ACGCGAAAATCTACCTTTTAATTACGAACC	53648269
HIST1H3G/	HIST1H3G/	965	TCGTCGGTGGTCGGCGCGTTTTT	Chr6: 26379488-	102
1H2BI	1H2BI/p-F			26379589
	HIST1H3G/	966	AACCCGCACCAAACAAACTACACGCAAA
	1H2BI/p-R
PPM1H	PPM1H/p-1-F	967	GAATGGTAGCGAGAGGTTGCGGGTTAGG	Chr12: 61312222-	89
	PPM1H/p-1-R	968	CTCTACCCTCAAAATCGCGACGCAAACG	61312310
	PPM1H/p-2-F	969	AGGAGTAGTATTGCGAGGGTGGAGGGTT	Chr12: 61311917-	96
	PPM1H/p-2-R	970	CGCCAATCCCGCTCCGACACTATAACAA	61312012
TUBB2B	TUBB2B/p-F	971	ATAAGGTTTGGTGGAAGCGTAGGAGCGT	Chr12: 3177175-	88
	TUBB2B/p-R	972	ACGATATTCTAACCTCCGCCGCGAAACT	3177262
C2CD4A	C2C5F	973	GGTAGAGGGATAGGGAAGAGTTTGGCGT	Chr15: 60146378-	150
	C2C5R	974	ATTCAAAACGCGCGCGACGAAATTCAAC	60146528
COL19A1	COL2F	975	GCGGAGTGGGAGGGTTATATTGGGAGAG	Chr6: 70633134-	106
	COL2R	976	CCGAACAAAACTACGACACCGCCGAAAA	70633240
DCDC2	DCD5F	977	ACGACGGGTTGAGATAGGTGGTTGGATT	Chr6: 24465938-	90
	DCD5R	978	CCCGACGCGAAACAACGAACTAAAACGA	24466027
DHRS3	DGR2F	979	TTTTTGTACGTTTTCGGGGTCGGAGGAG	Chr1: 12601840-	102
	DHR2R	980	AATCGCCGTCTAAACAAATCGCGAACTA	12601942
GALNT3	GAL1F	981	CGGCGGTCGCGGTTTGTAGTTTAGAATTG	Chr2: 166358281-	150
	GAL1R	982	ACGCGCTTCCACTCCGACTAACAAATTA	166358431
	GAL3F	983	GGCGTCGTTCGGGTTAAGTTTGGTTGT	Chr2: 166359152-	78
	GAL3R	984	CACAACTTACGCGAAACAACAACCTCGC	166359230
HES5	HES1F	985	TGGGTTGGTGTCGCGCGAATTTTTGTTT	Chr1: 2451234-	116
	HES1R	986	CCTCCTCCCGCAACTACGAAAACCGATA	2451350
	HES3F	987	GTTGGGGGTTATGTTTGGCGCGGAATAG	Chr1: 2451478-	144
	HES3R	988	CGCCTATATAAAACGTCGACGCGCGAAA	2451622
	HES4F	989	GTTCGGGCGTCGCGGTCGTTTTTATATT	Chr1: 2453144-	122
	HES4R	990	AAAACGCCCATTATACCCGCGCCAATTC	2453266
KILLIN	KIL5F	991	TAAGAATCGGCGGTAGTTAGTAGGCGGG	Chr10: 89611638-	145
	KIL5R	992	TCCTACGCCGCGACGAAAACAAAAACTC	89611783
	KIL6F	993	AGGTGGGGCGCGTTTATTAGTTTAGGGG	Chr10: 89611428-	150
	KIL6R	994	ACCTCTCCATCGCTAATACCCTACCGCT	89611578
MUC21	MUC2F	995	GAGTGTTTCGAGGGTAGGAGGTTGTCGG	Chr6: 31031426-	133
	MUC2R	996	CAAAAACCGCCCGCAAAACGAAACCTAA	31031559
NR2E1/	OST3F	997	ACGGATCGATCGCGGTTTTGGTAAGGAT	Chr6: 108542828-	87
OSTM1	OST3R	998	CGCAAAAACGAAAAACTACGTACGCGCT	108542915
	OST4F	999	GTTGTTTGAGGACGGGTCGTTTAGCGG	Chr6: 108543090-	99
	OST4R	1000	ACCCCTATCCTACAACCCTACGAACGCA	108543189
PAMR1	PAM4F	1001	TTTCGGGAGGTGTGGTTACGTTTGGAGA	Chr11: 35503958-	119
	PAM4R	1002	CCCCTCCTCCCAACACCCAACACTAAAA	35504077
SCRN1	SCR2F	1003	GGTTGTGGTTTTTAAAAGGGAAAATTCGGG	Chr7: 29996282-	106
	SCR2R	1004	TAAACGCCGAAACCCGAACGTAACAACC	29996388
SEZ6	SEZ3F	1005	AGGTGATTAGAAGGGAGAGGGGGAGGTT	Chr17: 24371083-	97
	SEZ3R	1006	TCATTATACACGACGCGCCCCTCCAAAT	24371180
	SEZ5F	1007	TACGTGGGTGTAGGTTAGGTCGGGTTGA	Chr17: 24371224-	121
	SEZ5R	1008	ACCACGCGACTACCGTATAAACAACCGAA	24371345