DESCRIPTION

FIELD This invention generally relates to methods and kits for the detection of and/or preemptive screening for colorectal cancer and/or advanced adenomas. In certain embodiments, the methods and kits described herein utilize identified differentially- methylated regions of the human genome as markers to determine the presence and/or risk of colorectal cancer and/or advanced adenomas in subjects.

BACKGROUND

Cancer screening is a critical component of cancer prevention, diagnosis, and treatment. Colorectal cancer (CRC) has been identified, according to some reports, as the third most common type of cancer and the second most frequent cause of cancer mortality in the world. According to some reports, there are over 1.8 million new cases of colorectal cancer per year and about 881,000 deaths from colorectal cancer, accounting for about 1 in 10 cancer deaths. Regular colorectal cancer screening is recommended, particular for individuals over age 50. Moreover, incidence of colorectal cancer in individuals below 50 has increased over time. Statistics suggest that current colorectal cancer screening techniques are insufficient. Despite improvements over time, only about 40-44% of colorectal cancers are currently detected by screening in an early, localized stage. This is at least in part due to insufficient sensitivity and/or specificity of current screening techniques. Currently recommended techniques include colonoscopy and/or fecal blood testing for those over age 50.

Most colorectal cancers originate from colon polyps that initially appeared, according to histology, to be benign. Accordingly, the advanced detection and removal of colon polyps are important parts of colon cancer screening. However, determining which polyps will develop into invasive cancers is difficult based on histopathological classifications alone. Histopathological classification of a polyp as an advanced adenoma, which has a tendency to progress to a malignant tumor, is routinely performed on samples resected from colon tissue during, for example, colonoscopies. Advanced adenomas are classified as having one or more of the following features: having a large size (i.e., the adenoma being greater than 1 cm); having high grade dysplasia; having a prominent villous component; and/or having serrated features. However, even when an adenoma is classified as an advanced adenomas according to the aforementioned classification, the adenoma may not progress to an invasive carcinoma.

Without wishing to be bound to any particular theory, adenomas or polyps that progress to an invasive carcinoma will acquire and accumulate genetic alterations that are distinct from normal tissue. Through the identification of these distinct alterations, a molecular fingerprint may be developed to help determine if an adenoma will progress to an invasive carcinoma. Developing tools and techniques to determine the molecular fingerprint of advanced carcinomas and colorectal cancers would aid in the identification of colorectal cancer at its earliest stages. Accordingly, there is a need for tools and screening techniques to accurately screen for colorectal cancer at its earliest stages.

SUMMARY OF THE INVENTION

The present disclosure provides, among other things, methods for colorectal cancer and/or advanced adenoma screening and compositions related thereto. In various embodiments as specifically disclosed herein, the present disclosure provides methods for colorectal cancer and/or advanced adenoma screening that include identification of the methylation status of at least one of one or more methylation sites found within a differentially methylated region (DMR) of DNA of a human subject. In various embodiments as specifically disclosed herein, the present disclosure provides methods for colorectal cancer and/or advanced adenoma screening that include screening methylation status of one or more methylation biomarkers in cfDNA (cell free DNA), e.g., in ctDNA (circulating tumor DNA). In various embodiments, the present disclosure provides methods for colorectal cancer and/or advanced adenoma screening that include screening methylation status of one or more methylation biomarkers in cfDNA, e.g., in ctDNA, using MSRE-qPCR. Various compositions and methods provided herein provide sensitivity and specificity sufficient for clinical application in colorectal cancer and/or advanced adenoma screening. Various compositions and methods provided herein are useful in colorectal cancer and/or advanced adenoma screening by analysis of an accessible tissue sample of a subject, e.g., a tissue sample that is blood or a blood component (e.g., cfDNA, e.g., ctDNA), colorectal tissue, or stool.

In certain embodiments, any of the methods as disclosed herein may be used in vitro.

In one aspect, the present disclosure provides a method of (i) screening for colorectal cancer or (ii) screening for advanced adenoma, or (iii) screening for the presence of either colorectal cancer or advanced adenoma (or both), the method comprising determining a methylation status of at least one methylation site found within a differentially methylated region (DMR) of DNA of a human subject as listed in Table 1 or Table 7.

In various embodiments as specifically referred to in the preceding paragraph, the method comprises, for each of one or more DMRs listed in Table 1 or Table 7, determining a methylation status of at least three methylation sites found within the DMR.

In various embodiments as specifically referred to in the preceding paragraphs, the method comprises, for each of one or more DMRs listed in Table 1 or Table 7, determining a methylation status of at least four methylation sites found within the DMR.

In various embodiments as specifically referred to in the preceding paragraphs, the method comprises, for each of one or more DMRs listed in Table 1 or Table 7, determining a methylation status of at least five methylation sites found within the DMR.

In various embodiments as specifically referred to in the preceding paragraphs, the method comprises, for each of three or more DMRs listed in Table 1 or Table 7, determining a methylation status of at least one methylation site found within the DMR In various embodiments as specifically referred to in the preceding paragraphs, the method comprises, for each of three or more DMRs listed in Table 1 or Table 7, determining a methylation status of at least three methylation sites found within the DMR.

In various embodiments as specifically referred to in the preceding paragraphs, the method comprises, for each of three or more DMRs listed in Table 1 or Table 7, determining a methylation status of at least four methylation sites found within the DMR.

In various embodiments as specifically referred to in the preceding paragraphs, the method comprises, for each of three or more DMRs listed in Table 1 or Table 7, determining a methylation status of at least five methylation sites found within the DMR.

In various embodiments as specifically referred to in the preceding paragraphs, the method comprises, for each of ten or more DMRs listed in Table 1 or Table 7, determining a methylation status of at least one methylation site found within the DMR. In various embodiments as specifically referred to in the preceding paragraphs, the method comprises, for each of ten or more DMRs listed in Table 1 or Table 7, determining a methylation status of at least three methylation sites found within the DMR.

In various embodiments as specifically referred to in the preceding paragraphs, the method comprises, for each of ten or more DMRs listed in Table 1 or Table 7, determining a methylation status of at least four methylation sites found within the DMR.

In various embodiments as specifically referred to in the preceding paragraphs, the method comprises, for each of ten or more DMRs listed in Table 1 or Table 7, determining a methylation status of at least five methylation sites found within the DMR In various embodiments as specifically referred to in the preceding paragraphs, the method comprises, for each of thirty-five or more DMRs listed in Table 1 , determining a methylation status of at least one methylation sites found within the DMR.

In various embodiments as specifically referred to in the preceding paragraphs, the method comprises, for each of thirty-five or more DMRs listed in Table 1 , determining a methylation status of at least three methylation sites found within the DMR.

In various embodiments as specifically referred to in the preceding paragraphs, the method comprises, for each of thirty-five or more DMRs listed in Table 1 , determining a methylation status of at least four methylation sites found within the DMR.

In various embodiments as specifically referred to in the preceding paragraphs, the method comprises, for each of thirty-five or more DMRs listed in Table 1 , determining a methylation status of at least five methylation sites found within the DMR.

In various embodiments as specifically referred to in the preceding paragraphs, the method comprises, for each of forty or more DMRs listed in Table 7, determining a methylation status of at least three methylation sites found within the DMR.

In various embodiments as specifically referred to in the preceding paragraphs, the method comprises, for each of forty or more DMRs listed in Table 7, determining a methylation status of at least four methylation sites found within the DMR.

In various embodiments as specifically referred to in the preceding paragraphs, the method comprises, for each of forty or more DMRs listed in Table 7, determining a methylation status of at least five methylation sites found within the DMR.

In various embodiments as specifically referred to in the preceding paragraphs, the DMR comprises at least 1 , at least 2, at least 3, at least 4, at least 5, at least 6, at least 7, at least 8, at least 9, at least 10, at least 11 , at least 12, at least 13, at least 14, at least 15, or more methylation sensitive restriction sites.

In various embodiments as specifically referred to in the preceding paragraphs, the method comprises determining whether the at least one methylation site is methylated as compared to a reference (e.g., wherein the reference is DNA from a population of one or more human subjects having been confirmed as not suffering from either advanced adenoma or colorectal cancer), wherein methylation is indicative of (i) colorectal cancer, (ii) advanced adenoma, or (iii) either colorectal cancer or advanced adenoma (or both).

In various embodiments as specifically referred to in the preceding paragraph, wherein the method comprises determining the methylation status of at least one methylation site found within each of the DMRs as listed in Table 2.

In various embodiments as specifically referred to in the preceding paragraphs, the method comprises determining the methylation status of at least one methylation site found within each of the DMRs as listed in Table 3.

In various embodiments as specifically referred to in the preceding paragraphs, the method comprises determining the methylation status of at least one methylation site found within each of the DMRs as listed in Table 4.

In various embodiments as specifically referred to in the preceding paragraphs, the one or more of the DMRs are amplified by oligonucleotide primer pairs as listed in Table 5.

In various embodiments as specifically referred to in the preceding paragraphs, the DNA of the human subject is isolated from a member selected from the group consisting of tissue (e.g., colorectal tissue, e.g., a polyp, an adenoma), blood, plasma, urine, saliva, and stool of the human subject.

In various embodiments as specifically referred to in the preceding paragraphs, the DNA is cell-free DNA of the human subject.

In various embodiments as specifically referred to in the preceding paragraphs, the subject was asymptomatic for either colorectal cancer or advanced adenomas (or both) at the time of screening.

In various embodiments as specifically referred to in the preceding paragraphs, the subject had been previously screened for either colorectal cancer or advanced adenomas (or both).

In various embodiments as specifically referred to in the preceding paragraphs, the subject had been screened for either colorectal cancer or advanced adenomas (or both) within the last 10 years, within the last 5 years, within the last 4 years, within the last 3 years, within the last 2 years, or within the last year.

In various embodiments as specifically referred to in the preceding paragraphs, a previous screen for either advanced adenomas or colorectal cancer (or both) in the subject had diagnosed the subject as not having (i) colorectal cancer, (ii) advanced adenoma, or (iii) advanced adenoma or colorectal cancer (or both). In various embodiments of this and specifically referred to in the preceding paragraphs, the previous screen for either advanced adenomas or colorectal cancer (or both) that had diagnosed the subject as not having (i) colorectal cancer, (ii) advanced adenoma, or (iii) advanced adenoma or colorectal cancer (or both) was within one year.

In various embodiments as specifically referred to in the preceding paragraphs, the previous screen for either advanced adenoma or colorectal cancer (or both) that had diagnosed the subject as not having either advanced adenomas or colorectal cancer (or both) was a colonoscopy.

In various embodiments as specifically referred to in the preceding paragraphs, the method includes diagnosis of early stage colorectal cancer (e.g., wherein the colorectal cancer is a stage 0, stage I, stage IIA, stage MB, or stage IIC colorectal cancer).

In various embodiments as specifically referred to in the preceding paragraphs, the method includes diagnosis of early stage colorectal cancer, wherein the cancer has not metastasized.

In various embodiments as specifically referred to in the preceding paragraphs, methylation status is determined using one or more members selected from the group consisting of methylation sensitive restriction enzyme quantitative polymerase chain reaction (MSRE-qPCR), Methylation-Specific PCR, Methylation Specific Nuclease- assisted Minor-allele Enrichment PCR, hybrid-capture targeted next-generation sequencing, and amplicon based targeted next-generation sequencing.

In various embodiments as specifically referred to in the preceding paragraphs, methylation status is determined using whole genome bisulfite sequencing.

In various embodiments as specifically referred to in the preceding paragraphs, the method is an in vitro method.

In another aspect, the present disclosure provides a method of methylation specific restriction enzyme quantitative polymerase chain reaction (MSRE-qPCR) for (i) screening for colorectal cancer or (ii) screening for advanced adenoma, or (iii) screening for the presence of either colorectal cancer or advanced adenoma (or both), the method comprising: (a) contacting DNA of a human subject with one or more methylation specific restriction enzymes; and (b) performing qPCR of enzyme-digested DNA, or amplicons thereof, to determine the methylation status of one or more regions of DNA, wherein each of the one or more regions of DNA comprises at least a portion of the one or more DMRs of Table 1 , each portion being at least 10, at least 15, at least 20, at least 24, at least 30, at least 40, at least 50, at least 100, at least 150, at least 200, at least 250, at least 300, at least 350, at least 400, at least 500, at least 1000 or more base pairs in length.

In various embodiments as specifically referred to in the preceding paragraph, wherein at least one of the one or more of the regions of DNA is amplified by a corresponding oligonucleotide primer pair (e.g., wherein the primer pair comprises a forward and a reverse primer).

In various embodiments as specifically referred to in the preceding paragraphs, each of the one or more regions of DNA comprises at least 1 , at least 2, at least 3, at least 4, at least 5, at least 6, at least 7, at least 8, at least 9, at least 10, at least 11 , at least 12, at least 13, at least 14, at least 15, or more methylation sensitive restriction sites.

In various embodiments as specifically referred to in the preceding paragraphs, a corresponding oligonucleotide primer pair is an oligonucleotide primer pair listed in Table 5. In various embodiments as specifically referred to herein and in the preceding paragraphs, a forward primer of the corresponding oligonucleotide primer pair is at least 80%, at least 85%, at least 90%, at least 95%, at least 99%, or at least 99.5% identical to a forward primer listed in Table 5.

In various embodiments as specifically referred to in the preceding paragraphs, a reverse primer of the corresponding oligonucleotide primer pair is at least 80%, at least 85%, at least 90%, at least 95%, at least 99%, or at least 99.5% identical to a reverse primer listed in Table 5.

In various embodiments as specifically referred to in the preceding paragraphs, the DNA is isolated from a member selected from the group consisting of tissue (e.g., colorectal tissue, e.g., a polyp, an adenoma), blood, plasma, urine, saliva, and stool of the human subject.

In various embodiments as specifically referred to in the preceding paragraphs, the DNA is cell-free DNA of the human subject.

In various embodiments as specifically referred to in the preceding paragraphs, the method provides a sensitivity for detecting colorectal cancer of at least 0.67. In various embodiments as specifically referred to in this and the preceding paragraphs, the method provides the sensitivity for detecting colorectal cancer of at least 0.78.

In various embodiments as specifically referred to in the preceding paragraphs, the method provides an overall sensitivity for detecting a combination of advanced adenoma and colorectal cancer of at least 0.48. In various embodiments as specifically referred to in this and the preceding paragraphs, the method provides an overall sensitivity for detecting the combination of advanced adenoma and colorectal cancer of at least 0.53.

In various embodiments as specifically referred to in the preceding paragraphs, the method provides a specificity of at least 0.9. In various embodiments as specifically referred to in this and the preceding paragraphs, the method provides a specificity of at least 0.93.

In various embodiments as specifically referred to in the preceding paragraphs, the one or more regions of DNA comprise each of the DMRs of Table 2.

In various embodiments as specifically referred to in the preceding paragraphs, each of the one or more regions of DNA is at least 80%, at least 85%, at least 90%, at least 95%, at least 99%, or at least 99.5% identical to, or comprises, a corresponding DMR of Table 2.

In various embodiments as specifically referred to in the preceding paragraphs, the one or more regions of DNA comprise each of the DMRs of Table 3.

In various embodiments as specifically referred to in the preceding paragraphs, each of the one or more regions of DNA is at least 80%, at least 85%, at least 90%, at least 95%, at least 99%, or at least 99.5% identical to, or comprises, a corresponding DMR of Table 3.

In various embodiments as specifically referred to in the preceding paragraphs, the one or more regions of DNA comprise each of the DMRs of Table 4.

In various embodiments as specifically referred to in the preceding paragraphs, each of the one or more regions of DNA is at least 80%, at least 85%, at least 90%, at least 95%, at least 99%, or at least 99.5% identical to, or comprises, a corresponding DMR of Table 4.

In various embodiments as specifically referred to in the preceding paragraphs, the method is an in vitro method.

In another aspect, the present disclosure provides a kit for use in (i) screening for colorectal cancer or (ii) screening for advanced adenoma, or (iii) screening for the presence of either colorectal cancer or advanced adenoma (or both), the kit comprising: (a) at least one oligonucleotide primer pair designed to amplify at least a portion of one or more DMRs of Table 1 , each portion being at least 10, at least 15, at least 20, at least 24, at least 30, at least 40, at least 50, at least 100, at least 150, at least 200, at least 250, at least 300, at least 350, at least 400, at least 500, at least 1000 or more base pairs in length; and (b) at least one methylation specific restriction enzyme and/or a bisulfite reagent.

In various embodiments as specifically referred to in the preceding paragraph, the portion of the one or more DMRs comprises at least 1 , at least 2, at least 3, at least 4, at least 5, at least 6, at least 7, at least 8, at least 9, at least 10, at least 11 , at least 12, at least 13, at least 14, at least 15, or more methylation sensitive restriction sites.

In various embodiments as specifically referred to in the preceding paragraphs, the oligonucleotide primer pairs include oligonucleotide primer pairs for amplification of each DMR of Table 2.

In various embodiments as specifically referred to in the preceding paragraphs, the oligonucleotide primer pairs include oligonucleotide primer pairs for amplification of each DMR of Table 3.

In various embodiments as specifically referred to in the preceding paragraphs, the oligonucleotide primer pairs include oligonucleotide primer pairs for amplification of each DMR of Table 4. In various embodiments as specifically referred to in the preceding paragraphs, the oligonucleotide primer pairs include at least one oligonucleotide primer pair of Table 5. In various embodiments as specifically referred to in the preceding paragraphs, at least one of the oligonucleotides of the oligonucleotide primer pair is at least 80%, at least 85%, at least 90%, at least 95%, at least 99%, or at least 99.5% identical to or comprises at least one forward primer of Table 5.

In various embodiments as specifically referred to in the preceding paragraphs, at least one of the oligonucleotides of the oligonucleotide primer pair is at least 80%, at least 85%, at least 90%, at least 95%, at least 99%, or at least 99.5% identical to or comprises at least one reverse primer of Table 5. In various embodiments as specifically referred to in the preceding paragraphs, the kit further comprises using the determined methylation status (e.g., the percent hypermethylation, the ratio of hypermethylation) of the one or more methylation sites to identify at least one of (i) to (iv) as follows: (i) a presence of colorectal cancer in the human subject; (ii) a predisposition for colorectal cancer in the human subject; (iii) an increased risk of colorectal cancer in the human subject, and (iv) a stage of colorectal cancer in the human subject.

In various embodiments as specifically referred to in the preceding paragraphs, the kit further comprises using the determined methylation status (e.g., the percent hypermethylation, the ratio of hypermethylation) of the one or more methylation sites to identify at least one of (i) to (iv) as follows: (i) a presence of one or more advanced adenomas in the human subject; (ii) a predisposition for advanced adenomas in the human subject; (iii) an increased risk of advanced adenomas in the human subject, and (iv) a type of adenoma in the human subject.

In various embodiments as specifically referred to in the preceding paragraphs, the kit further comprises using the determined methylation status (e.g., the percent hypermethylation, the ratio of hypermethylation) of the one or more methylation sites to identify at least one of (i) to (iv) as follows: (i) a presence of either colorectal cancer or advanced adenomas or both in the human subject; (ii) a predisposition for either colorectal cancer or advanced adenomas or both in the human subject; (iii) an increased risk of either colorectal cancer or advanced adenomas or both in the human subject, and (iv) a stage of either colorectal cancer or advanced adenomas or both in the human subject.

In various embodiments as specifically referred to in the preceding paragraphs, the kit is used in vitro.

In another aspect, the present disclosure provides a diagnostic qPCR reaction for (i) screening for colorectal cancer or (ii) screening for advanced adenoma, or (iii) screening for the presence of either colorectal cancer or advanced adenoma (or both), the diagnostic qPCR reaction including: (a) human DNA; (b) a polymerase; and (c) at least one oligonucleotide primer pair designed to amplify at least a portion of one or more DMRs of Table 1, each portion of the one or more DMRs being at least 10, at least 15, at least 20, at least 24, at least 30, at least 40, at least 50, at least 100, 150, 200, 250, 300, 350, 400, 500, 1000 or more base pairs in length, wherein the human DNA is bisulfite-treated human DNA or methylation specific restriction enzyme-digested human DNA.

In various embodiments as specifically referred to in the preceding paragraph, the portion of the one or more DMRs comprises at least 1 , at least 2, at least 3, at least 4, at least 5, at least 6, at least 7, at least 8, at least 9, at least 10, at least 11 , at least 12, at least 13, at least 14, at least 15, or more methylation sensitive restriction sites.

In various embodiments as specifically referred to in the preceding paragraphs, the oligonucleotide primer pairs include oligonucleotide primer pairs for amplification of each DMR of Table 2.

In various embodiments as specifically referred to in the preceding paragraphs, the oligonucleotide primer pairs include oligonucleotide primer pairs for amplification of each DMR of Table 3.

In various embodiments as specifically referred to in the preceding paragraphs, the oligonucleotide primer pairs include oligonucleotide primer pairs for amplification of each DMR of Table 4.

In various embodiments as specifically referred to in the preceding paragraphs, the oligonucleotide primer pairs include at least one oligonucleotide primer pair of Table 5. In various embodiments as specifically referred to in the preceding paragraphs, at least one of the oligonucleotides of the oligonucleotide primer pair is at least 80%, at least 85%, at least 90%, at least 95%, at least 99%, or at least 99.5% identical to or comprises at least one forward primer of Table 5.

In various embodiments as specifically referred to in the preceding paragraphs, at least one of the oligonucleotides of the oligonucleotide primer pair is at least 80%, at least 85%, at least 90%, at least 95%, at least 99%, or at least 99.5% identical to or comprises at least one reverse primer of Table 5.

In various embodiments as specifically referred to in the preceding paragraphs, the reaction further comprises using the determined methylation status (e.g., the percent hypermethylation, the ratio of hypermethylation) of the one or more methylation sites to identify at least one of (i) to (iv) as follows: (i) a presence of colorectal cancer in the human subject; (ii) a predisposition for colorectal cancer in the human subject; (iii) an increased risk of colorectal cancer in the human subject, and (iv) a stage of colorectal cancer in the human subject.

In various embodiments as specifically referred to in the preceding paragraphs, the reaction further comprises using the determined methylation status (e.g., the percent hypermethylation, the ratio of hypermethylation) of the one or more methylation sites to identify at least one of (i) to (iv) as follows: (i) a presence of one or more advanced adenomas in the human subject; (ii) a predisposition for advanced adenomas in the human subject; (iii) an increased risk of advanced adenomas in the human subject, and (iv) a type of adenoma in the human subject.

In various embodiments as specifically referred to in the preceding paragraphs, the reaction further comprises using the determined methylation status (e.g., the percent hypermethylation, the ratio of hypermethylation) of the one or more methylation sites to identify at least one of (i) to (iv) as follows: (i) a presence of either colorectal cancer or advanced adenomas or both in the human subject; (ii) a predisposition for either colorectal cancer or advanced adenomas or both in the human subject; (iii) an increased risk of either colorectal cancer or advanced adenomas or both in the human subject, and (iv) a stage of either colorectal cancer or advanced adenomas or both in the human subject. In various embodiments as specifically referred to in the preceding paragraphs, the reaction is performed in vitro.

In another aspect, the present disclosure provides a method of (i) screening for colorectal cancer or (ii) screening for advanced adenoma, or (iii) screening for the presence of either colorectal cancer or advanced adenoma (or both), the method comprising: determining a methylation status of one or more differentially methylated regions (DMRs), each of said one or more DMRs comprising or overlapping with one or more genes selected from the group consisting of PAX7, NTNG1 , SYT6, LINC01248, KCNK3, GALNT14, CHST10, THSD7B, UNC80, EPHA6, MED12L, ADGRL3, RNF150, SPOCK3, GPM6A, HELT, GFPT2, HSPA1L, HSPA1A, NKAIN2, TMEM178B, DPP6, MICU3, ALKALI , LOC401463, BHLHE22, RIMS2, LOC105375690, SLC25A32, DMRT1 , CDKN2A, CDKN2B-AS1 , PAX5, C1QL3, MY03A, LOC101929073, GAD2, MY03A, FOXI2, LOC105369438, AMOTL1 , LOC101928847, NCAM1 , DSCAML1 , PTPRO, RERG, DPY19L2, CUX2, PCDH9, MIR4500HG, SLITRK5, SLC8A3, LOC646548, GATM, PIF1 , RASGRF1 , VAC14, VAT 1 L, JPH3, SLFN13, ZACN, SRP68,

GALR2, ADCYAP1 , CDH2, DOK6, ZNF461 , ZNF829, ZNF568, ZNF540, ZNF571-AS1 , CIC, ZNF582-AS1 , ZNF582, ZNF471, ZNF264, ZNF671 , ZNF551, ZNF776, NKX2-2, ADAMTS1, TIAM1, and OLIG1 ; applying a classification model using as input the determined methylation status of each of said one or more DMRs; and outputting, from the model, a predicted status of colorectal cancer or a predicted status of advanced adenoma or a predicted status of either colorectal cancer or advanced adenoma (e.g., the latter meaning a status of having either or both colorectal cancer and advanced adenoma) of the human subject.

In various embodiments as specifically referred to in the preceding paragraph, the method comprises determining the methylation status of the one or more DMRs comprising or overlapping with at least each of the genes GAD2, MY03A, and ALKALI .

In various embodiments as specifically referred to in the preceding paragraphs, the method comprises determining the methylation status of the one or more DMRs comprising or overlapping with at least each of the genes GAD2, MY03A, ALKALI , RASGRF1, MICU3, RASGRF1 , FOXI2, C1QL3, CDKN2A, and CDKN2B-AS1.

In various embodiments as specifically referred to in the preceding paragraphs, the method comprises determining the methylation status of the one or more DMRs comprising or overlapping with at least each of the genes GAD2, MY03A, ALKALI , RASGRF1, MICU3, RASGRF1, FOXI2, C1QL3, CDKN2A, CDKN2B-AS1 , SYT6, SLFN13, GPM6A, THSD7B, ZBF582-AS1 , ZNF582, GATM, ZNF540, ZNF571-AS1 , OLIG1 , EPHA6, DPY19L2, SLC8A3, LOC646548, LOC101929073, UNC80, DPP6, ZNF568, JPH3, ZNF461 , NTNG1 , ADGRL3, AD AM ST 1 , CDH2, LINC01248, PTPRO, RERG, SLC8A3, LOC646548, PAX5, GFPT2.

In various embodiments as specifically referred to in the preceding paragraphs, the classification model is a support-vector machine (SVM) algorithm-based classification model.

In various embodiments as specifically referred to in the preceding paragraphs, the method is an in vitro method.

In another aspect, the present disclosure provides a method of (i) screening for colorectal cancer or (ii) screening for advanced adenoma, or (iii) screening for the presence of either colorectal cancer or advanced adenoma (or both), the method comprising: determining a methylation status of one or more differentially methylated regions (DMRs), each of said one or more DMRs having at least 80%, at least 85%, at least 90%, at least 95%, at least 99%, or at least 99.5% sequence identity to or comprising at least one sequence selected from the group consisting of SEQ ID NO. 190, SEQ ID NO. 191 , SEQ ID NO. 192, SEQ ID NO. 193, SEQ ID NO. 194, SEQ ID NO. 195, SEQ ID NO. 196, SEQ ID NO. 197, SEQ ID NO. 198, SEQ ID NO. 199, SEQ ID NO. 200, SEQ ID NO. 201, SEQ ID NO. 202, SEQ ID NO. 203, SEQ ID NO. 204, SEQ ID NO. 205, SEQ ID NO. 206, SEQ ID NO. 207, SEQ ID NO. 208, SEQ ID NO. 209, SEQ ID NO. 210, SEQ ID NO. 211, SEQ ID NO. 212, SEQ ID NO. 213, SEQ ID NO. 214, SEQ ID NO. 215, SEQ ID NO. 216, SEQ ID NO. 217, SEQ ID NO. 218, SEQ ID NO. 219, SEQ ID NO. 220, SEQ ID NO. 221 , SEQ ID NO. 222, SEQ ID NO. 223, SEQ ID NO. 224, SEQ ID NO. 225, SEQ ID NO. 226, SEQ ID NO. 227, SEQ ID NO. 228, and SEQ ID NO. 229; applying a classification model using as input the determined methylation status of said one or more DMRs; and outputting, from the model, (i) a predicted status of colorectal cancer or (ii) a predicted status of advanced adenoma or (iii) a predicted status of either colorectal cancer or advanced adenoma (e.g., the latter meaning a status of having either or both colorectal cancer and advanced adenoma) of the human subject.

In various embodiments as specifically referred to in the preceding paragraph, the method comprises determining a methylation status of three or more differentially methylated regions (DMRs).

In various embodiments as specifically referred to in the preceding paragraphs, the method comprises determining a methylation status of ten or more differentially methylated regions (DMRs).

In various embodiments as specifically referred to in the preceding paragraphs, the method comprises determining a methylation status of forty differentially methylated regions (DMRs). In various embodiments as specifically referred to in the preceding paragraphs, the classification model is a support-vector machine (SVM) algorithm-based classification model.

In various embodiments as specifically referred to in the preceding paragraphs, the method is an in vitro method. In another aspect, the present disclosure provides a method of (i) screening for colorectal cancer or (ii) screening for advanced adenoma, or (iii) screening for the presence of either colorectal cancer or advanced adenoma (or both), the method comprising: determining a methylation status of at least one methylation site found within a differentially methylated region (DMR) of DNA of a human subject as listed in Table 1 or Table 7; determining, by a processor of a computing device, a methylation status of the differentially methylated region (DMR) of DNA of the human subject based on the methylation status of the at least one methylation site; and determining, by the processor, (i) a predicted status of colorectal cancer, (ii) a predicted status of advanced adenoma, or (iii) a predicted status of either colorectal cancer or advanced adenoma (e.g., the latter meaning a status of having either or both colorectal cancer and advanced adenoma) of the human subject using a classification model.

In various embodiments as specifically referred to in the preceding paragraph, the method comprises, for each of one or more DMRs listed in Table 1 or Table 7, determining a methylation status of at least three methylation sites found within the DMR.

In various embodiments as specifically referred to in the preceding paragraphs, the method comprises, for each of one or more DMRs listed in Table 1 or Table 7, determining a methylation status of at least four methylation sites found within the DMR. In various embodiments as specifically referred to in the preceding paragraphs, the method comprises, for each of one or more DMRs listed in Table 1 or Table 7, determining a methylation status of at least five methylation sites found within the DMR.

In various embodiments as specifically referred to in the preceding paragraphs, the method comprises, for each of three or more DMRs listed in Table 1 or Table 7, determining a methylation status of at least one methylation site found within the DMR. In various embodiments as specifically referred to in the preceding paragraphs, the method comprises, for each of three or more DMRs listed in Table 1 or Table 7, determining a methylation status of at least three methylation sites found within the DMR.

In various embodiments as specifically referred to in the preceding paragraphs, the method comprises, for each of three or more DMRs listed in Table 1 or Table 7, determining a methylation status of at least four methylation sites found within the DMR.

In various embodiments as specifically referred to in the preceding paragraphs, the method comprises, for each of three or more DMRs listed in Table 1 or Table 7, determining a methylation status of at least five methylation sites found within the DMR.

In various embodiments as specifically referred to in the preceding paragraphs, the method comprises, for each of ten or more DMRs listed in Table 1 or Table 7, determining a methylation status of at least one methylation site found within the DMR. In various embodiments as specifically referred to in the preceding paragraphs, the method comprises, for each of ten or more DMRs listed in Table 1 or Table 7, determining a methylation status of at least three methylation sites found within the DMR.

In various embodiments as specifically referred to in the preceding paragraphs, the method comprises, for each of ten or more DMRs listed in Table 1 or Table 7, determining a methylation status of at least four methylation sites found within the DMR.

In various embodiments as specifically referred to in the preceding paragraphs, the method comprises, for each of ten or more DMRs listed in Table 1 or Table 7, determining a methylation status of at least five methylation sites found within the DMR.

In various embodiments as specifically referred to in the preceding paragraphs, the method comprises, for each of thirty-five or more DMRs listed in Table 1 , determining a methylation status of at least one methylation sites found within the DMR.

In various embodiments as specifically referred to in the preceding paragraphs, the method comprises, for each of thirty-five or more DMRs listed in Table 1 , determining a methylation status of at least three methylation sites found within the DMR.

In various embodiments as specifically referred to in the preceding paragraphs, the method comprises, for each of thirty-five or more DMRs listed in Table 1 , determining a methylation status of at least four methylation sites found within the DMR.

In various embodiments as specifically referred to in the preceding paragraphs, the method comprises, for each of thirty-five or more DMRs listed in Table 1 , determining a methylation status of at least five methylation sites found within the DMR.

In various embodiments as specifically referred to in the preceding paragraphs, the method comprises, for each of forty or more DMRs listed in Table 7, determining a methylation status of at least three methylation sites found within the DMR.

In various embodiments as specifically referred to in the preceding paragraphs, the method comprises, for each of forty or more DMRs listed in Table 7, determining a methylation status of at least four methylation sites found within the DMR.

In various embodiments as specifically referred to in the preceding paragraphs, the method comprises, for each of forty or more DMRs listed in Table 7, determining a methylation status of at least five methylation sites found within the DMR.

In various embodiments as specifically referred to in the preceding paragraphs, the DMR comprises at least 1 , at least 2, at least 3, at least 4, at least 5, at least 6, at least 7, at least 8, at least 9, at least 10, at least 11 , at least 12, at least 13, at least 14, at least 15, or more methylation sensitive restriction sites.

In various embodiments as specifically referred to in the preceding paragraphs, the method comprises determining, by the processor, whether the at least one methylation site is methylated as compared to a reference (e.g., wherein the reference is DNA from a population of one or more human subjects having been confirmed as not suffering from either advanced adenoma or colorectal cancer), wherein methylation is indicative of (i) colorectal cancer, (ii) advanced adenoma, or (iii) either colorectal cancer or advanced adenoma (or both).

In various embodiments as specifically referred to in the preceding paragraphs, the method comprises determining the methylation status of at least one methylation site found within each of the DMRs as listed in Table 2.

In various embodiments as specifically referred to in the preceding paragraphs, the method comprises determining the methylation status of at least one methylation site found within each of the DMRs as listed in Table 3.

In various embodiments as specifically referred to in the preceding paragraphs, the method comprises determining, by the processor, the methylation status of at least one methylation site found within each of the DMRs as listed in Table 4.

In various embodiments as specifically referred to in the preceding paragraphs, the DMRs are amplified by oligonucleotide primer pairs as listed in Table 5.

In various embodiments as specifically referred to in the preceding paragraphs, the DNA of the human subject is isolated from a member selected from the group consisting of tissue (e.g., colorectal tissue, e.g., a polyp, an adenoma), blood, plasma, urine, saliva, and stool of the human subject.

In various embodiments as specifically referred to in the preceding paragraphs, the DNA is cell-free DNA of the human subject.

In various embodiments as specifically referred to in the preceding paragraphs, the subject was asymptomatic for either colorectal cancer or advanced adenomas (or both) at the time of screening.

In various embodiments as specifically referred to in the preceding paragraphs, the subject had been previously screened for either colorectal cancer or advanced adenomas (or both). In various embodiments as specifically referred to in the current or preceding paragraphs, the subject had been screened for either colorectal cancer or advanced adenomas (or both) within the last 10 years, within the last 5 years, within the last 4 years, within the last 3 years, within the last 2 years, or within the last year.

In various embodiments as specifically referred to in the preceding paragraphs, a previous screen for either advanced adenomas or colorectal cancer (or both) in the subject had diagnosed the subject as not having (i) colorectal cancer, (ii) advanced adenoma, or (iii) advanced adenoma or colorectal cancer (or both). In various embodiments as specifically referred to in the current or preceding paragraphs, the previous screen for either advanced adenomas or colorectal cancer (or both) that had diagnosed the subject as not having (i) colorectal cancer, (ii) advanced adenoma, or (iii) advanced adenoma or colorectal cancer (or both) was within one year.

In various embodiments as specifically referred to in the preceding paragraphs, the previous screen for either advanced adenoma or colorectal cancer (or both) that had diagnosed the subject as not having either advanced adenomas or colorectal cancer (or both) was a colonoscopy.

In various embodiments as specifically referred to in the preceding paragraphs, the method includes, by the processor, identifying the existence of early stage colorectal cancer (e.g., wherein the colorectal cancer is a stage 0, stage I, stage IIA, stage MB, or stage IIC colorectal cancer).

In various embodiments as specifically referred to in the preceding paragraphs, the method includes, by the processor, identifying the existence of early stage colorectal cancer, wherein the cancer has not metastasized. In various embodiments as specifically referred to in the preceding paragraphs, the methylation status is determined using one or more members selected from the group consisting of methylation sensitive restriction enzyme quantitative polymerase chain reaction (MSRE-qPCR), Methylation-Specific PCR, Methylation Specific Nuclease- assisted Minor-allele Enrichment PCR, hybrid-capture targeted next-generation sequencing, and amplicon based targeted next-generation sequencing.

In various embodiments as specifically referred to in the preceding paragraphs, the methylation status is determined using whole genome bisulfite sequencing.

In various embodiments as specifically referred to in the preceding paragraphs, the classification model is a support-vector machine (SVM) algorithm-based classification model.

In various embodiments as specifically referred to in the preceding paragraphs, the method is an in vitro method.

In another aspect, the present disclosure provides a method of methylation specific restriction enzyme quantitative polymerase chain reaction (MSRE-qPCR) for (i) screening for colorectal cancer or (ii) screening for advanced adenoma, or (iii) screening for the presence of either colorectal cancer or advanced adenoma (or both), the method comprising: (a) contacting DNA of a human subject with one or more methylation specific restriction enzymes; (b) performing qPCR of enzyme-digested DNA, or amplicons thereof, to determine the methylation status of one or more regions of DNA, wherein each of the one or more regions of DNA comprises at least a portion of the one or more DMRs of Table 1 , each portion being at least 10, at least 15, at least 20, at least 24, at least 30, at least 40, at least 50, at least 100, at least 150, at least 200, at least 250, at least 300, at least 350, at least 400, at least 500, at least 1000 or more base pairs in length; (c) applying, by a processor of a computing device, a classification model to the determined methylation status of the one or more regions of DNA; and (d) determining, by the processor, a predicted status of colorectal cancer, a predicted status of advanced adenoma, or a predicted status of either colorectal cancer or advanced adenoma (e.g., the latter meaning a status of having either or both colorectal cancer and advanced adenoma) of the human subject based on the applied classification model.

In various embodiments as specifically referred to in the preceding paragraph, at least one of the one or more of the regions of DNA is amplified by a corresponding oligonucleotide primer pair (e.g., wherein the primer pair comprises a forward and a reverse primer). In various embodiments as specifically referred to in the preceding paragraphs, each of the one or more regions of DNA comprises at least 1 , at least 2, at least 3, at least 4, at least 5, at least 6, at least 7, at least 8, at least 9, at least 10, at least 11 , at least 12, at least 13, at least 14, at least 15, or more methylation sensitive restriction sites.

In various embodiments as specifically referred to in the preceding paragraphs, the corresponding oligonucleotide primer pair is an oligonucleotide primer pair listed in Table 5.

In various embodiments as specifically referred to in the preceding paragraphs, a forward primer of the corresponding oligonucleotide primer pair is at least 80%, at least 85%, at least 90%, at least 95%, at least 99%, or at least 99.5% identical to a forward primer listed in Table 5.

In various embodiments as specifically referred to in the preceding paragraphs, a reverse primer of the corresponding oligonucleotide primer pair is at least 80%, at least 85%, at least 90%, at least 95%, at least 99%, or at least 99.5% identical to a reverse primer listed in Table 5.

In various embodiments as specifically referred to in the preceding paragraphs, the DNA is isolated from a member selected from the group consisting of tissue (e.g., colorectal tissue, e.g., a polyp, an adenoma), blood, plasma, urine, saliva, and stool of the human subject.

In various embodiments as specifically referred to in the preceding paragraphs, the DNA is cell-free DNA of the human subject.

In various embodiments as specifically referred to in the preceding paragraphs, the method provides a sensitivity for detecting colorectal cancer of at least 0.67. In various embodiments as specifically referred to in this or the preceding paragraphs, the method provides the sensitivity for detecting colorectal cancer of at least 0.78.

In various embodiments as specifically referred to in the preceding paragraphs, the method provides an overall sensitivity for detecting a combination of advanced adenoma and colorectal cancer of at least 0.48. In various embodiments as specifically referred to in this or the preceding paragraphs, the method provides an overall sensitivity for detecting the combination of advanced adenoma and colorectal cancer of at least 0.53.

In various embodiments as specifically referred to in the preceding paragraphs, the method provides a specificity of at least 0.9. In various embodiments as specifically referred to in this or the preceding paragraphs, the method provides a specificity of at least 0.93. In various embodiments as specifically referred to in the preceding paragraphs, the one or more regions of DNA comprise each DMR of Table 2.

In various embodiments as specifically referred to in the preceding paragraphs, each of the one or more regions of DNA are at least 80%, at least 85%, at least 90%, at least 95%, at least 99% or at least 99.5% identical to or comprises a corresponding DMR of

Table 2.

In various embodiments as specifically referred to in the preceding paragraphs, the one or more regions of DNA comprise each DMR of Table 3.

In various embodiments as specifically referred to in the preceding paragraphs, each of the one or more regions of DNA are at least 80%, at least 85%, at least 90%, at least 95%, at least 99% or at least 99.5% identical to, or comprises, a corresponding DMR of Table 2.

In various embodiments as specifically referred to in the preceding paragraphs, the one or more regions of DNA comprise each of DMR of Table 4. In various embodiments as specifically referred to in the preceding paragraphs, each of the one or more regions of DNA are at least 80%, at least 85%, at least 90%, at least 95%, at least 99% or at least 99.5% identical to, or comprises, a corresponding DMR of Table 4.

In various embodiments as specifically referred to in the preceding paragraphs, the classification model is a support-vector machine (SVM) algorithm-based classification model.

In various embodiments as specifically referred to in the preceding paragraphs, the method is an in vitro method.

In another aspect, the present disclosure provides a method of (i) screening for colorectal cancer or (ii) screening for advanced adenoma, or (iii) screening for the presence of either colorectal cancer or advanced adenoma (or both), the method comprising: determining (e.g., by a processor of a computing device) a methylation status of one or more differentially methylated regions (DMRs), each of said one or more DMRs comprising or overlapping with one or more genes selected from the group consisting of PAX7, NTNG1 , SYT6, LINC01248, KCNK3, GALNT14, CHST10, THSD7B, UNC80, EPHA6, MED12L, ADGRL3, RNF150, SPOCK3, GPM6A, HELT, GFPT2, HSPA1L, HSPA1A, NKAIN2, TMEM178B, DPP6, MICU3, ALKALI , LOC401463, BHLHE22, RIMS2, LOC105375690, SLC25A32, DMRT1 , CDKN2A, CDKN2B-AS1 , PAX5, C1QL3, MY03A, LOC101929073, GAD2, MY03A, FOXI2, LOC105369438, AMOTL1 , LOC101928847, NCAM1 , DSCAML1 , PTPRO, RERG, DPY19L2, CUX2, PCDH9, MIR4500HG, SLITRK5, SLC8A3, LOC646548, GATM, PIF1 , RASGRF1 , VAC14, VAT 1 L, JPH3, SLFN13, ZACN, SRP68, GALR2, ADCYAP1 , CDH2, DOK6, ZNF461 , ZNF829, ZNF568, ZNF540, ZNF571-AS1 , CIC, ZNF582-AS1 , ZNF582, ZNF471 , ZNF264, ZNF671 , ZNF551 , ZNF776, NKX2-2, ADAMTS1 , TIAM1 , and OLIG1 ; applying, by the processor, a classification model using as input the determined methylation status of each of said one or more DMRs; and outputting from the model, by the processor, (i) a predicted status of colorectal cancer, (ii) a predicted status of advanced adenoma, or (iii) a predicted status of either colorectal cancer or advanced adenoma (e.g., the latter meaning a status of having either or both colorectal cancer and advanced adenoma) of the human subject.

In various embodiments as specifically referred to in the preceding paragraph, the method comprises determining the methylation status of the one or more DMRs comprising or overlapping with at least each of the genes GAD2, MY03A, and ALKALI .

In various embodiments as specifically referred to in the preceding paragraphs, the method comprises determining the methylation status of the one or more DMRs comprising or overlapping with at least each of the genes at least each of the genes GAD2, MY03A, ALKALI , RASGRF1 , MICU3, RASGRF1 , FOXI2, C1QL3, CDKN2A, and CDKN2B-AS1.

In various embodiments as specifically referred to in the preceding paragraphs, the method comprises determining the methylation status of the one or more DMRs comprising or overlapping with at least each of the genes GAD2, MY03A, ALKALI , RASGRF1, MICU3, RASGRF1, FOXI2, C1QL3, CDKN2A, CDKN2B-AS1 , SYT6, SLFN13, GPM6A, THSD7B, ZBF582-AS1 , ZNF582, GATM, ZNF540, ZNF571-AS1 , OLIG1 , EPHA6, DPY19L2, SLC8A3, LOC646548, LOC101929073, UNC80, DPP6, ZNF568, JPH3, ZNF461 , NTNG1 , ADGRL3, AD AM ST 1 , CDH2, LINC01248, PTPRO, RERG, SLC8A3, LOC646548, PAX5, GFPT2.

In various embodiments as specifically referred to in the preceding paragraphs, the classification model is a support-vector machine (SVM) algorithm-based classification model.

In various embodiments as specifically referred to in the preceding paragraphs, the method is an in vitro method.

In another aspect, the present disclosure provides a method of (i) screening for colorectal cancer or (ii) screening for advanced adenoma, or (iii) screening for the presence of either colorectal cancer or advanced adenoma (or both), the method comprising: determining (e.g., by a processor of a computing device) a methylation status of one or more differentially methylated regions (DMRs), each of said one or more DMRs having at least 80%, at least 85%, at least 90%, at least 95%, at least 99% or at least 99.5% sequence identity with or comprises at least one sequence selected from the group consisting of SEQ ID NO. 190, SEQ ID NO. 191 , SEQ ID NO. 192, SEQ ID NO. 193, SEQ ID NO. 194, SEQ ID NO. 195, SEQ ID NO. 196, SEQ ID NO. 197, SEQ ID NO. 198, SEQ ID NO. 199, SEQ ID NO. 200, SEQ ID NO. 201 , SEQ ID NO. 202, SEQ ID NO. 203, SEQ ID NO. 204, SEQ ID NO. 205, SEQ ID NO. 206, SEQ ID NO. 207, SEQ ID NO. 208, SEQ ID NO. 209, SEQ ID NO. 210, SEQ ID NO. 211 , SEQ ID NO. 212, SEQ ID NO. 213, SEQ ID NO. 214, SEQ ID NO. 215, SEQ ID NO. 216, SEQ ID NO. 217, SEQ ID NO. 218, SEQ ID NO. 219, SEQ ID NO. 220, SEQ ID NO. 221 , SEQ ID NO. 222, SEQ ID NO. 223, SEQ ID NO. 224, SEQ ID NO. 225, SEQ ID NO. 226, SEQ ID NO. 227, SEQ ID NO. 228, and SEQ ID NO. 229; applying, by the processor, a classification model using as input the determined methylation status of said one or more DMRs; and outputting from the model, by the processor, (i) a predicted status of colorectal cancer, (ii) a predicted status of advanced adenoma, or (iii) a predicted status of either colorectal cancer or advanced adenoma (e.g., the latter meaning a status of having either or both colorectal cancer and advanced adenoma) of the human subject.

In various embodiments as specifically referred to in the preceding paragraphs, the method comprises determining the methylation status of each of three or more differentially methylated regions (DMRs).

In various embodiments as specifically referred to in the preceding paragraphs, the method comprises determining the methylation status of each of ten or more differentially methylated regions (DMRs).

In various embodiments as specifically referred to in the preceding paragraphs, the method comprises determining the methylation status of each of forty differentially methylated regions (DMRs).

In various embodiments as specifically referred to in the preceding paragraphs, the classification model is a support-vector machine (SVM) algorithm-based classification model.

In various embodiments as specifically referred to in the preceding paragraphs, the method is an in vitro method.

In various aspects, methods and compositions of the present invention can be used in combination with biomarkers known in the art, e.g., as disclosed in U.S. Patent No. 10,006,925, which is herein incorporated by reference in its entirety.

In another aspect, the invention is directed to a method of identifying one or more differentially methylated regions for the (i) screening for colorectal cancer or (ii) screening for advanced adenoma, or (iii) screening for the presence of either colorectal cancer or advanced adenoma (or both), wherein the method comprises: sequencing DNA of genomes of a first population (e.g., at least 10, at least 20, at least 50, at least 100, or more) of subjects diagnosed as having (i) colorectal cancer, (ii) advanced adenoma, or (iii) either colorectal cancer or advanced adenoma (or both) using whole genome bisulfiate sequencing; aligning each of the genomes of the first population with a reference genome (e.g., wherein the reference genome is GRCh38); identifying (e.g., using bioinformatics tools, e.g., MethylKit) a plurality of methylated colorectal cancer and/or advanced adenoma sites, wherein each of the plurality of methylated colorectal cancer and/or advanced adenoma sites is a differentially methylated site of the DNA of the first population relative to the corresponding site of a reference population (e.g., a population comprising healthy subjects)(e.g., wherein the difference in the percent methylation of the DNA of the first population with respect to the reference population is at least 5%, at least 10%, at least 15% or more); generating a list comprising a plurality of differentially methylated regions (DMRs), each of the plurality of the differentially methylated regions (DMRs) comprising one or more of the plurality of the identified methylated colorectal and/or advanced adenoma cancer sites (e.g., wherein the methylated colorectal and/or advanced adenoma cancer sites are or comprise methylated CpG regions) (e.g., wherein the DMRs comprise at least three methylated CpG regions having a maximum distance between the CpGs of 200 base pairs); determining a methylation status (e.g., a percent methylation, a number of methylated sites) of each of the plurality of DMRs of the first population; ranking the plurality of DMRs based, at least in part on, the methylation status of each of the plurality of DMRs; and filtering a set of candidate DMRs (e.g., filtering for DMRs comprising at least five CPG regions)(e.g., wherein the minimum methylation percent difference between the first subject group and the reference population is at least 5%, at least 6%, at least 7%, at least 8%, at least 9%, least 10%, at least 15% or more) from the plurality of the DMRs for the diagnosis of colorectal cancer and/or advanced adenoma. In various embodiments as specifically referred to in the preceding paragraph, the method comprises: identifying one or more CpG regions within each of the plurality of DMRs; determining the methylation status (e.g., a percent methylation, a number of methylated sites) of each of the identified CpG regions within each of the plurality of DMRs for the first population; and ranking the plurality of DMRs based, at least in part, on the determined methylation status of each of the one or more CpG regions of the DMR.

In certain embodiments as specifically referred to in the preceding paragraphs, the method further comprises: determining a methylation status of each of the plurality of DMRs for the reference population; comparing (e.g., comparing the percent methylation of) the determined methylation status of each of the plurality of DMRs of the reference population with a methylation status of a corresponding DMR of the first population; and ranking the plurality of DMRs based, at least in part, on the comparison.

In certain embodiments as specifically referred to in the preceding paragraphs, the DNA of the first population is isolated from a tissue (e.g., colorectal tissue, e.g., a polyp, an adenoma) of each human subject of the first population.

In certain embodiments as specifically referred to in the preceding paragraphs, the DNA of the first population is isolated from blood, plasma, urine, saliva, or stool of each human subject of the first population.

In other aspects, the invention is directed to a system for performing any of the methods referred to in the preceding paragraphs, the system comprising a processor; and a memory having instructions thereon, the instructions, when executed by the processor, causing the processor to perform one or more (up to all) steps of the method.

DEFINITIONS

A or An: The articles “a” and “an” are used herein to refer to one or to more than one (i.e., to at least one) of the grammatical object of the article. By way of example, “an element” refers to one element or more than one element.

About: The term “about”, when used herein in reference to a value, refers to a value that is similar, in context, to the referenced value. In general, those skilled in the art, familiar with the context, will appreciate the relevant degree of variance encompassed by “about” in that context. For example, in some embodiments, e.g., as set forth herein, the term “about” can encompass a range of values that within 25%, 20%, 19%, 18%, 17%, 16%, 15%, 14%, 13%, 12%, 11%, 10%, 9%, 8%, 7%, 6%, 5%, 4%, 3%, 2%, 1%, or with a fraction of a percent, of the referred value.

Advanced adenoma: As used herein, the term “advance adenoma” is used to refer to adenomatous polyps (adenomas) of the colon and rectum that are benign (noncancerous) cellular growths. Advanced adenomas are colonic adenomatous adenoma having at least one of the following features: 1 cm in size; tubulovillous or villous adenoma; high grade dysplasia; and serrated adenomas with dysplasia. In certain instances, e.g., as set forth herein, an advanced adenoma may also be classified as a “high risk” adenoma.

Administration: As used herein, the term “administration” typically refers to the administration of a composition to a subject or system, for example to achieve delivery of an agent that is, is included in, or is otherwise delivered by, the composition.

Agent: As used herein, the term “agent” refers to an entity (e.g., for example, a small molecule, peptide, polypeptide, nucleic acid, lipid, polysaccharide, complex, combination, mixture, system, or phenomenon such as heat, electric current, electric field, magnetic force, magnetic field, etc.).

Amelioration: As used herein, the term “amelioration” refers to the prevention, reduction, palliation, or improvement of a state of a subject. Amelioration includes, but does not require, complete recovery or complete prevention of a disease, disorder or condition.

Amplicon or amplicon molecule: As used herein, the term “amplicon” or “amplicon molecule” refers to a nucleic acid molecule generated by transcription from a template nucleic acid molecule, or a nucleic acid molecule having a sequence complementary thereto, or a double-stranded nucleic acid including any such nucleic acid molecule. Transcription can be initiated from a primer.

Amplification: As used herein, the term “amplification” refers to the use of a template nucleic acid molecule in combination with various reagents to generate further nucleic acid molecules from the template nucleic acid molecule, which further nucleic acid molecules may be identical to or similar to (e.g., at least 70% identical, e.g., at least 75%, 80%, 85%, 90%, 91%, 92%, 93%, 94%, 95%, 96%, 97%, 98%, 99%, or 100% identical to) a segment of the template nucleic acid molecule and/or a sequence complementary thereto.

Amplification reaction mixture: As used herein, the terms “amplification reaction mixture” or “amplification reaction” refer to a template nucleic acid molecule together with reagents sufficient for amplification of the template nucleic acid molecule.

Biological Sample: As used herein, the term “biological sample” typically refers to a sample obtained or derived from a biological source (e.g., a tissue or organism or cell culture) of interest, as described herein. In some embodiments, e.g., as set forth herein, a biological source is or includes an organism, such as an animal or human. In some embodiments, e.g., as set forth herein, a biological sample is or include biological tissue or fluid. In some embodiments, e.g., as set forth herein, a biological sample can be or include cells, tissue, or bodily fluid. In some embodiments, e.g., as set forth herein, a biological sample can be or include blood, blood cells, cell-free DNA, free floating nucleic acids, ascites, biopsy samples, surgical specimens, cell-containing body fluids, sputum, saliva, feces, urine, cerebrospinal fluid, peritoneal fluid, pleural fluid, lymph, gynecological fluids, secretions, excretions, skin swabs, vaginal swabs, oral swabs, nasal swabs, washings or lavages such as a ductal lavages or broncheoalveolar lavages, aspirates, scrapings, bone marrow. In some embodiments, e.g., as set forth herein, a biological sample is or includes cells obtained from a single subject or from a plurality of subjects. A sample can be a “primary sample” obtained directly from a biological source, or can be a “processed sample.” A biological sample can also be referred to as a “sample.”

Biomarker: As used herein, the term “biomarker,” consistent with its use in the art, refers to a to an entity whose presence, level, or form, correlates with a particular biological event or state of interest, so that it is considered to be a “marker” of that event or state. Those of skill in the art will appreciate, for instance, in the context of a DNA biomarker, that a biomarker can be or include a locus (such as one or more methylation loci) and/or the status of a locus (e.g., the status of one or more methylation loci). To give but a few examples of biomarkers, in some embodiments, e.g., as set forth herein, a biomarker can be or include a marker for a particular disease, disorder or condition, or can be a marker for qualitative of quantitative probability that a particular disease, disorder or condition can develop, occur, or reoccur, e.g., in a subject. In some embodiments, e.g., as set forth herein, a biomarker can be or include a marker for a particular therapeutic outcome, or qualitative of quantitative probability thereof. Thus, in various embodiments, e.g., as set forth herein, a biomarker can be predictive, prognostic, and/or diagnostic, of the relevant biological event or state of interest. A biomarker can be an entity of any chemical class. For example, in some embodiments, e.g., as set forth herein, a biomarker can be or include a nucleic acid, a polypeptide, a lipid, a carbohydrate, a small molecule, an inorganic agent (e.g., a metal or ion), or a combination thereof. In some embodiments, e.g., as set forth herein, a biomarker is a cell surface marker. In some embodiments, e.g., as set forth herein, a biomarker is intracellular. In some embodiments, e.g., as set forth herein, a biomarker is found outside of cells (e.g., is secreted or is otherwise generated or present outside of cells, e.g., in a body fluid such as blood, urine, tears, saliva, cerebrospinal fluid, and the like). In some embodiments, e.g., as set forth herein, a biomarker is methylation status of a methylation locus. In some instances, e.g., as set forth herein, a biomarker may be referred to as a “marker.”

To give but one example of a biomarker, in some embodiments e.g., as set forth herein, the term refers to expression of a product encoded by a gene, expression of which is characteristic of a particular tumor, tumor subclass, stage of tumor, etc. Alternatively or additionally, in some embodiments, e.g., as set forth herein, presence or level of a particular marker can correlate with activity (or activity level) of a particular signaling pathway, for example, of a signaling pathway the activity of which is characteristic of a particular class of tumors.

Those of skill in the art will appreciate that a biomarker may be individually determinative of a particular biological event or state of interest, or may represent or contribute to a determination of the statistical probability of a particular biological event or state of interest. Those of skill in the art will appreciate that markers may differ in their specificity and/or sensitivity as related to a particular biological event or state of interest.

Blood component: As used herein, the term “blood component” refers to any component of whole blood, including red blood cells, white blood cells, plasma, platelets, endothelial cells, mesothelial cells, epithelial cells, and cell-free DNA. Blood components also include the components of plasma, including proteins, metabolites, lipids, nucleic acids, and carbohydrates, and any other cells that can be present in blood, e.g., due to pregnancy, organ transplant, infection, injury, or disease.

Cancer: As used herein, the terms “cancer,” “malignancy,” “neoplasm,” “tumor,” and “carcinoma,” are used interchangeably to refer to a disease, disorder, or condition in which cells exhibit or exhibited relatively abnormal, uncontrolled, and/or autonomous growth, so that they display or displayed an abnormally elevated proliferation rate and/or aberrant growth phenotype. In some embodiments, e.g., as set forth herein, a cancer can include one or more tumors. In some embodiments e.g., as set forth herein, a cancer can be or include cells that are precancerous (e.g., benign), malignant, pre-metastatic, metastatic, and/or non-metastatic. In some embodiments e.g., as set forth herein, a cancer can be or include a solid tumor. In some embodiments e.g., as set forth herein, a cancer can be or include a hematologic tumor. In general, examples of different types of cancers known in the art include, for example, colorectal cancer, hematopoietic cancers including leukemias, lymphomas (Hodgkin’s and non-Hodgkin’s), myelomas and myeloproliferative disorders; sarcomas, melanomas, adenomas, carcinomas of solid tissue, squamous cell carcinomas of the mouth, throat, larynx, and lung, liver cancer, genitourinary cancers such as prostate, cervical, bladder, uterine, and endometrial cancer and renal cell carcinomas, bone cancer, pancreatic cancer, skin cancer, cutaneous or intraocular melanoma, cancer of the endocrine system, cancer of the thyroid gland, cancer of the parathyroid gland, head and neck cancers, breast cancer, gastro-intestinal cancers and nervous system cancers, benign lesions such as papillomas, and the like.

Chemotherapeutic agent: As used herein, the term “chemotherapeutic agent,” consistent with its use in the art, refers to one or more agents known, or having characteristics known to, treat or contribute to the treatment of cancer. In particular, chemotherapeutic agents include pro-apoptotic, cytostatic, and/or cytotoxic agents. In some embodiments e.g., as set forth herein, a chemotherapeutic agent can be or include alkylating agents, anthracyclines, cytoskeletal disruptors (e.g., microtubule targeting moieties such as taxanes, maytansine, and analogs thereof, of), epothilones, histone deacetylase inhibitors HDACs), topoisomerase inhibitors (e.g., inhibitors of topoisomerase I and/or topoisomerase II), kinase inhibitors, nucleotide analogs or nucleotide precursor analogs, peptide antibiotics, platinum-based agents, retinoids, vinca alkaloids, and/or analogs that share a relevant anti-proliferative activity. In some particular embodiments e.g., as set forth herein, a chemotherapeutic agent can be or include of Actinomycin, All-trans retinoic acid, an Auiristatin, Azacitidine, Azathioprine, Bleomycin, Bortezomib, Carboplatin, Capecitabine, Cisplatin, Chlorambucil, Cyclophosphamide, Curcumin, Cytarabine, Daunorubicin, Docetaxel, Doxifluridine, Doxorubicin, Epirubicin, Epothilone, Etoposide, Fluorouracil, Gemcitabine, Hydroxyurea, Idarubicin, Imatinib, Irinotecan, Maytansine and/or analogs thereof (e.g., DM1) Mechlorethamine, Mercaptopurine, Methotrexate, Mitoxantrone, a Maytansinoid, Oxaliplatin, Paclitaxel, Pemetrexed, Teniposide, Tioguanine, Topotecan, Valrubicin, Vinblastine, Vincristine, Vindesine, Vinorelbine, or a combination thereof. In some embodiments e.g., as set forth herein, a chemotherapeutic agent can be utilized in the context of an antibody-drug conjugate. In some embodiments e.g., as set forth herein, a chemotherapeutic agent is one found in an antibody-drug conjugate selected from the group consisting of: hLU-doxorubicin, hRS7-SN-38, hMN-14-SN-38, hl_L2-SN-38, hA20-SN-38, hPAM4-SN-38, hl_L1-SN-38, hRS7-Pro-2-P-Dox, hMN-14-Pro-2-P-Dox, hl_L2-Pro-2-P-Dox, hA20-Pro-2-P-Dox, hPAM4-Pro-2-P-Dox, hl_L1-Pro-2-P-Dox, P4/D10-doxorubicin, gemtuzumab ozogamicin, brentuximab vedotin, trastuzumab emtansine, inotuzumab ozogamicin, glembatumomab vedotin, SAR3419, SAR566658, BIIB015, BT062, SGN-75, SGN-CD19A, AMG-172, AMG-595, BAY-94-9343, ASG- 5ME, ASG-22ME, ASG-16M8F, MDX-1203, MLN-0264, anti-PSMA ADC, RG-7450, RG-7458, RG-7593, RG-7596, RG-7598, RG-7599, RG-7600, RG-7636, ABT-414,

IMGN-853, IMGN-529, vorsetuzumab mafodotin, and lorvotuzumab mertansine. In some embodiments e.g., as set forth herein, a chemotherapeutic agent can be or comprise of farnesyl-thiosalicylic acid (FTS), 4-(4-Chloro-2-methylphenoxy)-N- hydroxybutanamide (CMH), estradiol (E2), tetramethoxystilbene (TMS), d-tocatrienol, salinomycin, or curcumin.

Comparable: As used herein, the term “comparable” refers to members within sets of two or more conditions, circumstances, agents, entities, populations, etc., that may not be identical to one another but that are sufficiently similar to permit comparison there between, such that one of skill in the art will appreciate that conclusions can reasonably be drawn based on differences or similarities observed. In some embodiments e.g., as set forth herein, comparable sets of conditions, circumstances, agents, entities, populations, etc. are typically characterized by a plurality of substantially identical features and zero, one, or a plurality of differing features. Those of ordinary skill in the art will understand, in context, what degree of identity is required to render members of a set comparable. For example, those of ordinary skill in the art will appreciate that members of sets of conditions, circumstances, agents, entities, populations, etc., are comparable to one another when characterized by a sufficient number and type of substantially identical features to warrant a reasonable conclusion that differences observed can be attributed in whole or part to non-identical features thereof.

Detectable moiety: The term “detectable moiety” as used herein refers to any element, molecule, functional group, compound, fragment, or other moiety that is detectable. In some embodiments e.g., as set forth herein, a detectable moiety is provided or utilized alone. In some embodiments e.g., as set forth herein, a detectable moiety is provided and/or utilized in association with (e.g., joined to) another agent. Examples of detectable moieties include, but are not limited to, various ligands, radionuclides (e.g., ³ H, ¹⁴ C, ¹⁸ F, ¹⁹ F, ³² P, ³⁵ S, ¹³⁵ l, ¹²⁵ l, ¹²³ i, ⁶⁴ Cu, ¹⁸⁷ Re, ¹¹¹ In, ⁹⁰ Y, ^99m Tc, ¹⁷⁷ Lu, ⁸⁹ Zr etc.), fluorescent dyes, chemiluminescent agents, bioluminescent agents, spectrally resolvable inorganic fluorescent semiconductors nanocrystals (i.e., quantum dots), metal nanoparticles, nanoclusters, paramagnetic metal ions, enzymes, colorimetric labels, biotin, dioxigenin, haptens, and proteins for which antisera or monoclonal antibodies are available. Diagnosis·. As used herein, the term “Diagnosis” refers to determining whether, and/or the qualitative of quantitative probability that, a subject has or will develop a disease, disorder, condition, or state. For example, in diagnosis of cancer, diagnosis can include a determination regarding the risk, type, stage, malignancy, or other classification of a cancer. In some instances, e.g., as set forth herein, a diagnosis can be or include a determination relating to prognosis and/or likely response to one or more general or particular therapeutic agents or regimens.

Diagnostic information: As used herein, the term “diagnostic information” refers to information useful in providing a diagnosis. Diagnostic information can include, without limitation, biomarker status information.

Differentially methylated: As used herein, the term “differentially methylated” describes a methylation site for which the methylation status differs between a first condition and a second condition. A methylation site that is differentially methylated can be referred to as a differentially methylated site. In some instances e.g., as set forth herein, a DMR is defined by the amplicon produced by amplification using oligonucleotide primers , e.g., a pair of oligonucleotide primers selected for amplification of the DMR or for amplification of a DNA region of interest present in the amplicon. In some instances e.g., as set forth herein, a DMR is defined as a DNA region amplified by a pair of oligonucleotide primers, including the region having the sequence of, or a sequence complementary to, the oligonucleotide primers. In some instances e.g., as set forth herein, a DMR is defined as a DNA region amplified by a pair of oligonucleotide primers, excluding the region having the sequence of, or a sequence complementary to, the oligonucleotide primers.

Differentially methylated region: As used herein, the term “differentially methylated region” (DMR) refers to a DNA region that includes one or more differentially methylated sites. A DMR that includes a greater number or frequency of methylated sites under a selected condition of interest, such as a cancerous state, can be referred to as a hypermethylated DMR. A DMR that includes a smaller number or frequency of methylated sites under a selected condition of interest, such as a cancerous state, can be referred to as a hypomethylated DMR. A DMR that is a methylation biomarker for colorectal cancer can be referred to as a colorectal cancer DMR. In some instances e.g., as set forth herein, a DMR that is a methylation biomarker for colorectal cancer may also be useful in identification of advanced adenoma. In some instances e.g., as set forth herein, a DMR that is a methylation biomarker for advanced adenoma can be referred to as an advanced adenoma DMR. In some instances e.g., as set forth herein, a DMR that is a methylation biomarker for advanced adenoma may also be useful in identification of colorectal cancer. In some instances e.g., as set forth herein, a DMR can be a single nucleotide, which single nucleotide is a methylation site. Preferably, a DMR has a length of at least about 10, 15, 20, 24, 50, 100, 150, 200, 250, 300, 350, 400, 500, 1000, 1500, 2000, 2225, 2500 or more base pairs.

DNA region: As used herein, “DNA region” refers to any contiguous portion of a larger DNA molecule. Those of skill in the art will be familiar with techniques for determining whether a first DNA region and a second DNA region correspond, based, e.g., on sequence similarity (e.g., sequence identity or homology) of the first and second DNA regions and/or context (e.g., the sequence identity or homology of nucleic acids upstream and/or downstream of the first and second DNA regions).

Except as otherwise specified herein, sequences found in or relating to humans (e.g., that hybridize to human DNA) are found in, based on, and/or derived from the example representative human genome sequence commonly referred to, and known to those of skill in the art, as Homo sapiens (human) genome assembly GRCh38, hg38, and/or Genome Reference Consortium Human Build 38. Those of skill in the art will further appreciate that DNA regions of hg38 can be referred to by a known system including identification of particular nucleotide positions or ranges thereof in accordance with assigned numbering.

Downstream: As used herein, the term” downstream” means that a first DNA region is closer, relative to a second DNA region, to the C-terminus of a nucleic acid that includes the first DNA region and the second DNA region.

Gene: As used herein, the term “gene” refers to a single DNA region, e.g., in a chromosome, that includes a coding sequence that encodes a product (e.g., an RNA product and/or a polypeptide product), together with all, some, or none of the DNA sequences that contribute to regulation of the expression of coding sequence. In some embodiments e.g., as set forth herein, a gene includes one or more non-coding sequences. In some particular embodiments e.g., as set forth herein, a gene includes exonic and intronic sequences. In some embodiments e.g., as set forth herein, a gene includes one or more regulatory elements that, for example, can control or impact one or more aspects of gene expression (e.g., cell-type-specific expression, inducible expression, etc.). In some embodiments e.g., as set forth herein a gene includes a promoter. In some embodiments e.g., as set forth herein, a gene includes one or both of a (i) DNA nucleotides extending a predetermined number of nucleotides upstream of the coding sequence and (ii) DNA nucleotides extending a predetermined number of nucleotides downstream of the coding sequence. In various embodiments e.g., as set forth herein, the predetermined number of nucleotides can be 500 bp, 1 kb, 2 kb, 3 kb, 4 kb, 5 kb, 10 kb, 20 kb, 30 kb, 40 kb, 50 kb, 75 kb, or 100 kb.

Hybridize: As used herein, “hybridize” refers to the association of a first nucleic acid with a second nucleic acid to form a double-stranded structure, which association occurs through complementary pairing of nucleotides. Those of skill in the art will recognize that complementary sequences, among others, can hybridize. In various embodiments e.g., as set forth herein, hybridization can occur, for example, between nucleotide sequences having at least 70% complementarity, e.g., at least 75%, 80%, 85%, 90%, 91%, 92%, 93%, 94%, 95%, 96%, 97%, 98%, 99%, or 100% complementarity. Those of skill in the art will further appreciate that whether hybridization of a first nucleic acid and a second nucleic acid does or does not occur can dependence upon various reaction conditions. Conditions under which hybridization can occur are known in the art.

Hypomethylation: As used herein, the term “hypomethylation” refers to the state of a methylation locus having at least one fewer methylated nucleotides in a state of interest as compared to a reference state (e.g., at least one fewer methylated nucleotides in colorectal cancer than in healthy control).

Hypermethylation: As used herein, the term “hypermethylation” refers to the state of a methylation locus having at least one more methylated nucleotide in a state of interest as compared to a reference state (e.g., at least one more methylated nucleotide in colorectal cancer than in healthy control).

Identity, identical: As used herein, the terms “identity” and “identical” refers to the overall relatedness between polymeric molecules, e.g., between nucleic acid molecules (e.g., DNA molecules and/or RNA molecules) and/or between polypeptide molecules. Methods for the calculation of a percent identity as between two provided sequences are known in the art. Calculation of the percent identity of two nucleic acid or polypeptide sequences, for example, can be performed by aligning the two sequences (or the complement of one or both sequences) for optimal comparison purposes (e.g., gaps can be introduced in one or both of a first and a second sequences for optimal alignment and non-identical sequences can be disregarded for comparison purposes). The nucleotides or amino acids at corresponding positions are then compared. When a position in the first sequence is occupied by the same residue (e.g., nucleotide or amino acid) as the corresponding position in the second sequence, then the molecules are identical at that position. The percent identity between the two sequences is a function of the number of identical positions shared by the sequences and, optionally, taking into account the number of gaps and the length of each gap, which may need to be introduced for optimal alignment of the two sequences. The comparison of sequences and determination of percent identity between two sequences can be accomplished using a computational algorithm, such as BLAST (basic local alignment search tool).

“Improved," “increased," or “reduced”: As used herein, these terms, or grammatically comparable comparative terms, indicate values that are relative to a comparable reference measurement. For example, in some embodiments e.g., as set forth herein, an assessed value achieved with an agent of interest may be “improved” relative to that obtained with a comparable reference agent or with no agent. Alternatively or additionally, in some embodiments e.g., as set forth herein, an assessed value in a subject or system of interest may be “improved” relative to that obtained in the same subject or system under different conditions or at a different point in time (e.g., prior to or after an event such as administration of an agent of interest), or in a different, comparable subject (e.g., in a comparable subject or system that differs from the subject or system of interest in presence of one or more indicators of a particular disease, disorder or condition of interest, or in prior exposure to a condition or agent, etc.). In some embodiments e.g., as set forth herein, comparative terms refer to statistically relevant differences (e.g., differences of a prevalence and/or magnitude sufficient to achieve statistical relevance). Those of skill in the art will be aware, or will readily be able to determine, in a given context, a degree and/or prevalence of difference that is required or sufficient to achieve such statistical significance. Methylation : As used herein, the term “methylation” includes methylation at any of (i) C5 position of cytosine; (ii) N4 position of cytosine; and (iii) the N6 position of adenine. Methylation also includes (iv) other types of nucleotide methylation. A nucleotide that is methylated can be referred to as a “methylated nucleotide” or “methylated nucleotide base.” In certain embodiments e.g., as set forth herein, methylation specifically refers to methylation of cytosine residues. In some instances e.g., as set forth herein, methylation specifically refers to methylation of cytosine residues present in CpG sites. Methylation assay: As used herein, the term “methylation assay” refers to any technique that can be used to determine the methylation status of a methylation locus or a methylation site.

Methylation biomarker: As used herein, the term “methylation biomarker” refers to a biomarker that is or includes at least one methylation site or locus and/or the methylation status of at least one methylation locus, e.g., a hypermethylated locus. In particular, a methylation biomarker is a biomarker characterized by a change between a first state and a second state (e.g., between a cancerous state and a non-cancerous state) in methylation status of one or more nucleic acid loci.

Methylation locus: As used herein, the term “methylation locus” refers to a DNA region that includes at least one differentially methylated region. A methylation locus that includes a greater number or frequency of methylated sites under a selected condition of interest, such as a cancerous state, can be referred to as a hypermethylated locus. A methylation locus that includes a smaller number or frequency of methylated sites under a selected condition of interest, such as a cancerous state, can be referred to as a hypomethylated locus.

Methylation site: As used herein, a methylation site refers to a nucleotide or nucleotide position that is methylated in at least one condition. In its methylated state, a methylation site can be referred to as a methylated site.

Methylation status: As used herein, “methylation status,” “methylation state,” or “methylation profile” refer to the number, frequency, or pattern of methylation at methylation sites within a methylation locus. Accordingly, a change in methylation status between a first state and a second state can be or include an increase in the number, frequency, or pattern of methylated sites, or can be or include a decrease in the number, frequency, or pattern of methylated sites. In various instances e.g., as set forth herein, a change in methylation status in a change in methylation value. In various instances e.g., as set forth herein, “methylation status” refers to the presence or absence of methylation at an individual methylation site.

Methylation value: As used herein, the term “methylation value” refers to a numerical representation of a methylation status, e.g., in the form of number that represents the frequency or ratio of methylation of a methylation locus. In some instances e.g., as set forth herein, a methylation value can be generated by a method that includes quantifying the amount of intact nucleic acid present in a sample following restriction digestion of the sample with a methylation dependent restriction enzyme. In some instances e.g., as set forth herein, a methylation value can be generated by a method that includes comparing amplification profiles after bisulfite reaction of a sample. In some instances e.g., as set forth herein, a methylation value can be generated by comparing sequences of bisulfite-treated and untreated nucleic acids. In some instances e.g., as set forth herein a methylation value is, includes, or is based on a quantitative PCR result. Nucleic acid. As used herein, in its broadest sense, the term “nucleic acid” refers to any compound and/or substance that is or can be incorporated into an oligonucleotide chain. In some embodiments e.g., as set forth herein, a nucleic acid is a compound and/or substance that is or can be incorporated into an oligonucleotide chain via a phosphodiester linkage. As will be clear from context, in some embodiments e.g., as set forth herein, the term nucleic acid refers to an individual nucleic acid residue (e.g., a nucleotide and/or nucleoside), and in some embodiments e.g., as set forth herein refers to an polynucleotide chain comprising a plurality of individual nucleic acid residues. A nucleic acid can be or include DNA, RNA, or a combinations thereof. A nucleic acid can include natural nucleic acid residues, nucleic acid analogs, and/or synthetic residues. In some embodiments e.g., as set forth herein, a nucleic acid includes natural nucleotides (e.g., adenosine, thymidine, guanosine, cytidine, uridine, deoxyadenosine, deoxythymidine, deoxy guanosine, and deoxycytidine). In some embodiments e.g., as set forth herein, a nucleic acid is or includes of one or more nucleotide analogs (e.g., 2-aminoadenosine, 2-thiothymidine, inosine, pyrrolo- pyrimidine, 3 -methyl adenosine, 5-methylcytidine, C-5 propynyl-cytidine, C-5 propynyl- uridine, 2-aminoadenosine, C5-bromouridine, C5-fluorouridine, C5-iodouridine, C5- propynyl-uridine, C5 -propynyl-cytidine, C5-methylcytidine, 2-aminoadenosine, 7- deazaadenosine, 7-deazaguanosine, 8-oxoadenosine, 8-oxoguanosine, 0(6)- methylguanine, 2-thiocytidine, methylated bases, intercalated bases, and combinations thereof).

In some embodiments e.g., as set forth herein, a nucleic acid has a nucleotide sequence that encodes a functional gene product such as an RNA or protein. In some embodiments e.g., as set forth herein, a nucleic acid includes one or more introns. In some embodiments e.g., as set forth herein, a nucleic acid includes one or more genes. In some embodiments e.g., as set forth herein, nucleic acids are prepared by one or more of isolation from a natural source, enzymatic synthesis by polymerization based on a complementary template (in vivo or in vitro), reproduction in a recombinant cell or system, and chemical synthesis.

In some embodiments e.g., as set forth herein, a nucleic acid analog differs from a nucleic acid in that it does not utilize a phosphodiester backbone. For example, in some embodiments e.g., as set forth herein, a nucleic acid can include one or more peptide nucleic acids, which are known in the art and have peptide bonds instead of phosphodiester bonds in the backbone. Alternatively or additionally, in some embodiments e.g., as set forth herein, a nucleic acid has one or more phosphorothioate and/or 5'-N-phosphoramidite linkages rather than phosphodiester bonds. In some embodiments e.g., as set forth herein, a nucleic acid comprises one or more modified sugars (e.g., 2'-fluororibose, ribose, 2'-deoxyribose, arabinose, and hexose) as compared with those in natural nucleic acids.

In some embodiments e.g., as set forth herein, a nucleic acid is or includes at least 3, 4, 5, 6, 7, 8, 9, 10, 15, 20, 25, 30, 35, 40, 45, 50, 55, 60, 65, 70, 75, 80, 85, 90, 95, 100, 1 10, 120, 130, 140, 150, 160, 170, 180, 190, 20, 225, 250, 275, 300, 325, 350, 375, 400, 425, 450, 475, 500, 600, 700, 800, 900, 1000, 1500, 2000, 2500, 3000, 3500, 4000, 4500, 5000 or more residues. In some embodiments e.g., as set forth herein, a nucleic acid is partly or wholly single stranded, or partly or wholly double stranded. Nucleic acid detection assay: As used herein, the term “nucleic acid detection assay” refers to any method of determining the nucleotide composition of a nucleic acid of interest. Nucleic acid detection assays include but are not limited to, DNA sequencing methods, polymerase chain reaction-based methods, probe hybridization methods, ligase chain reaction, etc.

Nucleotide: As used herein, the term “nucleotide” refers to a structural component, or building block, of polynucleotides, e.g., of DNA and/or RNA polymers. A nucleotide includes of a base (e.g., adenine, thymine, uracil, guanine, or cytosine) and a molecule of sugar and at least one phosphate group. As used herein, a nucleotide can be a methylated nucleotide or an un-methylated nucleotide. Those of skill in the art will appreciate that nucleic acid terminology, such as, as examples, “locus” or “nucleotide” can refer to both a locus or nucleotide of a single nucleic acid molecule and/or to the cumulative population of loci or nucleotides within a plurality of nucleic acids (e.g., a plurality of nucleic acids in a sample and/or representative of a subject) that are representative of the locus or nucleotide (e.g., having the same identical nucleic acid sequence and/or nucleic acid sequence context, or having a substantially identical nucleic acid sequence and/or nucleic acid context).

Oligonucleotide primer: As used herein, the term oligonucleotide primer, or primer, refers to a nucleic acid molecule used, capable of being used, or for use in, generating amplicons from a template nucleic acid molecule. Under transcription-permissive conditions (e.g., in the presence of nucleotides and a DNA polymerase, and at a suitable temperature and pH), an oligonucleotide primer can provide a point of initiation of transcription from a template to which the oligonucleotide primer hybridizes. Typically, an oligonucleotide primer is a single-stranded nucleic acid between 5 and 200 nucleotides in length. Those of skill in the art will appreciate that optimal primer length for generating amplicons from a template nucleic acid molecule can vary with conditions including temperature parameters, primer composition, and transcription or amplification method. A pair of oligonucleotide primers, as used herein, refers to a set of two oligonucleotide primers that are respectively complementary to a first strand and a second strand of a template double-stranded nucleic acid molecule. First and second members of a pair of oligonucleotide primers may be referred to as a “forward” oligonucleotide primer and a “reverse” oligonucleotide primer, respectively, with respect to a template nucleic acid strand, in that the forward oligonucleotide primer is capable of hybridizing with a nucleic acid strand complementary to the template nucleic acid strand, the reverse oligonucleotide primer is capable of hybridizing with the template nucleic acid strand, and the position of the forward oligonucleotide primer with respect to the template nucleic acid strand is 5' of the position of the reverse oligonucleotide primer sequence with respect to the template nucleic acid strand. It will be understood by those of skill in the art that the identification of a first and second oligonucleotide primer as forward and reverse oligonucleotide primers, respectively, is arbitrary inasmuch as these identifiers depend upon whether a given nucleic acid strand or its complement is utilized as a template nucleic acid molecule.

Overlapping: The term “overlapping” is used herein in reference to two regions of DNA, each of which contains a sub-sequence that is substantially identical to a subsequence of the same length in the other region (e.g., the two regions of DNA have a common sub-sequence). “Substantially identical” means that the two identically-long sub-sequences differ by fewer than a given number of base pairs. In certain instances e.g., as set forth herein, each sub-sequence has a length of at least 20 base pairs that differ by fewer than 4, 3, 2, or 1 base pairs from each other (e.g., the two subsequences having at least 80%, at least 85%, at least 90%, at least 95% similarity, at least 97% similarity, at least 98% similarity, at least 99% similarity, or at least 99.5% similarity). In certain instances e.g., as set forth herein, each sub-sequence has a length of at least 24 base pairs that differ by fewer than 5, 4, 3, 2, or 1 base pairs (e.g., the two sub-sequences having at least 80%, at least 85%, at least 90%, at least 95% similarity, at least 97% similarity, at least 98% similarity, at least 99% similarity, or at least 99.5% similarity). In certain instances e.g., as set forth herein, each subsequence has a length of at least 50 base pairs that differ by fewer than 10, 9, 8, 7, 6, 5, 4, 3, 2, or 1 base pairs (e.g., the two sub-sequences having at least 80%, at least 85%, at least 90%, at least 95% similarity, at least 97% similarity, at least 98% similarity, at least 99% similarity, or at least 99.5% similarity). In certain instances e.g., as set forth herein, each sub-sequence has a length of at least 100 base pairs that differ by fewer than 20, 15, 10, 9, 8, 7, 6, 5, 4, 3, 2, or 1 base pairs (e.g., the two subsequences having at least 80%, at least 85%, at least 90%, at least 95% similarity, at least 97% similarity, at least 98% similarity, at least 99% similarity, or at least 99.5% similarity). In certain instances e.g., as set forth herein, each sub-sequence has a length of at least 200 base pairs that differ by fewer than 40, 30, 20, 15, 10, 9, 8, 7, 6, 5, 4, 3, 2, or 1 base pairs (e.g., the two sub-sequences having at least 80%, at least 85%, at least 90%, at least 95% similarity, at least 97% similarity, at least 98% similarity, at least 99% similarity, or at least 99.5% similarity). In certain instances e.g., as set forth herein, each sub-sequence has a length of at least 250 base pairs that differ by fewer than 50, 40, 30, 20, 15, 10, 9, 8, 7, 6, 5, 4, 3, 2, or 1 base pairs (e.g., the two sub-sequences having at least 80%, at least 85%, at least 90%, at least 95% similarity, at least 97% similarity, at least 98% similarity, at least 99% similarity, or at least 99.5% similarity). In certain instances e.g., as set forth herein, each subsequence has a length of at least 300 base pairs that differ by fewer than 60, 50, 40, 30, 20, 15, 10, 9, 8, 7, 6, 5, 4, 3, 2, or 1 base pairs (e.g., the two sub-sequences having at least 80%, at least 85%, at least 90%, at least 95% similarity, at least 97% similarity, at least 98% similarity, at least 99% similarity, or at least 99.5% similarity). In certain instances e.g., as set forth herein, each sub-sequence has a length of at least 500 base pairs that differ by fewer than 100, 60, 50, 40, 30, 20, 15, 10, 9, 8, 7, 6, 5, 4, 3, 2, or 1 base pairs (e.g., the two sub-sequences having at least 80%, at least 85%, at least 90%, at least 95% similarity, at least 97% similarity, at least 98% similarity, at least 99% similarity, or at least 99.5% similarity). In certain instances e.g., as set forth herein, each sub-sequence has a length of at least 1000 base pairs that differ by fewer than 200, 100, 60, 50, 40, 30, 20, 15, 10, 9, 8, 7, 6, 5, 4, 3, 2, or 1 base pairs (e.g., the two sub-sequences having at least 80%, at least 85%, at least 90%, at least 95% similarity, at least 97% similarity, at least 98% similarity, at least 99% similarity, or at least 99.5% similarity). In certain instances e.g., as set forth herein, the subsequence of a first region of the two regions of DNA may comprise the entirety of the second region of the two regions of DNA (or vice versa) (e.g., the common sub-sequence may contain the whole of either or both regions).

Prevent or prevention: The terms “prevent” and “prevention,” as used herein in connection with the occurrence of a disease, disorder, or condition, refers to reducing the risk of developing the disease, disorder, or condition; delaying onset of the disease, disorder, or condition; delaying onset of one or more characteristics or symptoms of the disease, disorder, or condition; and/or to reducing the frequency and/or severity of one or more characteristics or symptoms of the disease, disorder, or condition. Prevention can refer to prevention in a particular subject or to a statistical impact on a population of subjects. Prevention can be considered complete when onset of a disease, disorder, or condition has been delayed for a predefined period of time.

Probe: As used herein, the term “probe” refers to a single- or double-stranded nucleic acid molecule that is capable of hybridizing with a complementary target and includes a detectable moiety. In certain embodiments e.g., as set forth herein, a probe is a restriction digest product or is a synthetically produced nucleic acid, e.g., a nucleic acid produced by recombination or amplification. In some instances e.g., as set forth herein, a probe is a capture probe useful in detection, identification, and/or isolation of a target sequence, such as a gene sequence. In various instances e.g., as set forth herein,, a detectable moiety of probe can be, e.g., an enzyme (e.g., ELISA, as well as enzyme-based histochemical assays), fluorescent moiety, radioactive moiety, or moiety associated with a luminescence signal.

Prognosis: As used herein, the term “prognosis” refers to determining the qualitative of quantitative probability of at least one possible future outcome or event. As used herein, a prognosis can be a determination of the likely course of a disease, disorder, or condition such as cancer in a subject, a determination regarding the life expectancy of a subject, or a determination regarding response to therapy, e.g., to a particular therapy.

Prognostic information: As used herein, the term “prognostic information” refers to information useful in providing a prognosis. Prognostic information can include, without limitation, biomarker status information.

Promoter: As used herein, a “promoter” can refer to a DNA regulatory region that directly or indirectly (e.g., through promoter-bound proteins or substances) associates with an RNA polymerase and participates in initiation of transcription of a coding sequence.

Reference: As used herein describes a standard or control relative to which a comparison is performed. For example, in some embodiments e.g., as set forth herein, an agent, subject, animal, individual, population, sample, sequence, or value of interest is compared with a reference or control agent, subject, animal, individual, population, sample, sequence, or value. In some embodiments e.g., as set forth herein, a reference or characteristic thereof is tested and/or determined substantially simultaneously with the testing or determination of the characteristic in a sample of interest. In some embodiments e.g., as set forth herein, a reference is a historical reference, optionally embodied in a tangible medium. Typically, as would be understood by those of skill in the art, a reference is determined or characterized under comparable conditions or circumstances to those under assessment, e.g., with regard to a sample. Those skilled in the art will appreciate when sufficient similarities are present to justify reliance on and/or comparison to a particular possible reference or control.

Risk: As used herein with respect to a disease, disorder, or condition, the term “risk” refers to the qualitative of quantitative probability (whether expressed as a percentage or otherwise) that a particular individual will develop the disease, disorder, or condition. In some embodiments e.g., as set forth herein, risk is expressed as a percentage. In some embodiments e.g., as set forth herein, a risk is a qualitative of quantitative probability that is equal to or greater than 0, 1 , 2, 3, 4, 5, 6, 7, 8, 9, 10, 20, 30, 40, 50, 60, 70, 80, 90, or 100%. In some embodiments e.g., as set forth herein risk is expressed as a qualitative of quantitative level of risk relative to a reference risk or level or the risk of the same outcome attributed to a reference. In some embodiments e.g., as set forth herein, relative risk is increased or decreased in comparison to the reference sample by a factor of 1.1 , 1.2, 1.3, 1.4, 1.5, 1.6, 1.7,. 1.8, 1.9, 2, 3, 4, 5, 6, 7, 8, 9, 10, or more.

Sample: As used herein, the term “sample” typically refers to an aliquot of material obtained or derived from a source of interest. In some embodiments e.g., as set forth herein, a source of interest is a biological or environmental source. In some embodiments e.g., as set forth herein, a sample is a “primary sample” obtained directly from a source of interest. In some embodiments e.g., as set forth herein, as will be clear from context, the term “sample” refers to a preparation that is obtained by processing of a primary sample (e.g., by removing one or more components of and/or by adding one or more agents to a primary sample). Such a “processed sample” can include, for example cells, nucleic acids, or proteins extracted from a sample or obtained by subjecting a primary sample to techniques such as amplification or reverse transcription of nucleic acids, isolation and/or purification of certain components, etc.

In certain instances e.g., as set forth herein, a processed sample can be a DNA sample that has been amplified (e.g., pre-amplified). Thus, in various instances, e.g., as set forth herein,, an identified sample can refer to a primary form of the sample or to a processed form of the sample. In some instances, a sample that is enzyme-digested DNA can refer to primary enzyme-digested DNA (the immediate product of enzyme digestion) or a further processed sample such as enzyme-digested DNA that has been subject to an amplification step (e.g., an intermediate amplification step, e.g., preamplification) and/or to a filtering step, purification step, or step that modifies the sample to facilitate a further step, e.g., in a process of determining methylation status (e.g., methylation status of a primary sample of DNA and/or of DNA as it existed in its original source context).

Screening: As used herein, the term “screening” refers to any method, technique, process, or undertaking intended to generate diagnostic information and/or prognostic information. Accordingly, those of skill in the art will appreciate that the term screening encompasses method, technique, process, or undertaking that determines whether an individual has, is likely to have or develop, or is at risk of having or developing a disease, disorder, or condition, e.g., colorectal cancer.

Specificity: As used herein, the “specificity” of a biomarker refers to the percentage of samples that are characterized by absence of the event or state of interest for which measurement of the biomarker accurately indicates absence of the event or state of interest (true negative rate). In various embodiments e.g., as set forth herein, characterization of the negative samples is independent of the biomarker, and can be achieved by any relevant measure, e.g., any relevant measure known to those of skill in the art. Thus, specificity reflects the probability that the biomarker would detect the absence of the event or state of interest when measured in a sample not characterized that event or state of interest. In particular embodiments e.g., as set forth herein in which the event or state of interest is colorectal cancer, specificity refers to the probability that a biomarker would detect the absence of colorectal cancer in a subject lacking colorectal cancer. Lack of colorectal cancer can be determined, e.g., by histology.

Sensitivity: As used herein, the “sensitivity” of a biomarker refers to the percentage of samples that are characterized by the presence of the event or state of interest for which measurement of the biomarker accurately indicates presence of the event or state of interest (true positive rate). In various embodiments e.g., as set forth herein, characterization of the positive samples is independent of the biomarker, and can be achieved by any relevant measure, e.g., any relevant measure known to those of skill in the art. Thus, sensitivity reflects the probability that a biomarker would detect the presence of the event or state of interest when measured in a sample characterized by presence of that event or state of interest. In particular embodiments e.g., as set forth herein in which the event or state of interest is colorectal cancer, sensitivity refers to the probability that a biomarker would detect the presence of colorectal cancer in a subject that has colorectal cancer. Presence of colorectal cancer can be determined, e.g., by histology.

Solid Tumor: As used herein, the term “solid tumor” refers to an abnormal mass of tissue including cancer cells. In various embodiments e.g., as set forth herein, a solid tumor is or includes an abnormal mass of tissue that does not contain cysts or liquid areas. In some embodiments e.g., as set forth herein, a solid tumor can be benign; in some embodiments e.g., as set forth herein, a solid tumor can be malignant. Examples of solid tumors include carcinomas, lymphomas, and sarcomas. In some embodiments e.g., as set forth herein, solid tumors can be or include adrenal, bile duct, bladder, bone, brain, breast, cervix, colon, endometrium, esophagum, eye, gall bladder, gastrointestinal tract, kidney, larynx, liver, lung, nasal cavity, nasopharynx, oral cavity, ovary, penis, pituitary, prostate, retina, salivary gland, skin, small intestine, stomach, testis, thymus, thyroid, uterine, vaginal, and/or vulval tumors.

Stage of cancer: As used herein, the term “stage of cancer” refers to a qualitative or quantitative assessment of the level of advancement of a cancer. In some embodiments e.g., as set forth herein, criteria used to determine the stage of a cancer can include, but are not limited to, one or more of where the cancer is located in a body, tumor size, whether the cancer has spread to lymph nodes, whether the cancer has spread to one or more different parts of the body, etc. In some embodiments e.g., as set forth herein, cancer can be staged using the so-called TNM System, according to which T refers to the size and extent of the main tumor, usually called the primary tumor; N refers to the number of nearby lymph nodes that have cancer; and M refers to whether the cancer has metastasized. In some embodiments e.g., as set forth herein, a cancer can be referred to as Stage 0 (abnormal cells are present but have not spread to nearby tissue, also called carcinoma in situ, or CIS; CIS is not cancer, but it can become cancer), Stage l-lll (cancer is present; the higher the number, the larger the tumor and the more it has spread into nearby tissues), or Stage IV (the cancer has spread to distant parts of the body). In some embodiments e.g., as set forth herein, a cancer can be assigned to a stage selected from the group consisting of: in situ (abnormal cells are present but have not spread to nearby tissue); localized (cancer is limited to the place where it started, with no sign that it has spread); regional (cancer has spread to nearby lymph nodes, tissues, or organs): distant (cancer has spread to distant parts of the body); and unknown (there is not enough information to identify cancer stage). Susceptible to: An individual who is “susceptible to” a disease, disorder, or condition is at risk for developing the disease, disorder, or condition. In some embodiments e.g., as set forth herein, an individual who is susceptible to a disease, disorder, or condition does not display any symptoms of the disease, disorder, or condition. In some embodiments e.g., as set forth herein, an individual who is susceptible to a disease, disorder, or condition has not been diagnosed with the disease, disorder, and/or condition. In some embodiments e.g., as set forth herein, an individual who is susceptible to a disease, disorder, or condition is an individual who has been exposed to conditions associated with, or presents a biomarker status (e.g., a methylation status) associated with, development of the disease, disorder, or condition. In some embodiments e.g., as set forth herein, a risk of developing a disease, disorder, and/or condition is a population-based risk (e.g., family members of individuals suffering from the disease, disorder, or condition).

Subject: As used herein, the term “subject” refers to an organism, typically a mammal (e.g., a human). In some embodiments e.g., as set forth herein, a subject is suffering from a disease, disorder or condition. In some embodiments e.g., as set forth herein, a subject is susceptible to a disease, disorder, or condition. In some embodiments e.g., as set forth herein, a subject displays one or more symptoms or characteristics of a disease, disorder or condition. In some embodiments e.g., as set forth herein, a subject is not suffering from a disease, disorder or condition. In some embodiments e.g., as set forth herein, a subject does not display any symptom or characteristic of a disease, disorder, or condition. In some embodiments e.g., as set forth herein, a subject is someone with one or more features characteristic of susceptibility to or risk of a disease, disorder, or condition. In some embodiments e.g., as set forth herein, a subject is a patient. In some embodiments e.g., as set forth herein, a subject is an individual to whom diagnosis has been performed and/or to whom therapy has been administered. In some instances e.g., as set forth herein,, a human subject can be interchangeably referred to as an “individual.”

Therapeutic agent: As used herein, the term “therapeutic agent” refers to any agent that elicits a desired pharmacological effect when administered to a subject. In some embodiments e.g., as set forth herein, an agent is considered to be a therapeutic agent if it demonstrates a statistically significant effect across an appropriate population. In some embodiments e.g., as set forth herein, the appropriate population can be a population of model organisms or a human population. In some embodiments e.g., as set forth herein, an appropriate population can be defined by various criteria, such as a certain age group, gender, genetic background, preexisting clinical conditions, etc. In some embodiments e.g., as set forth herein, a therapeutic agent is a substance that can be used for treatment of a disease, disorder, or condition. In some embodiments e.g., as set forth herein, a therapeutic agent is an agent that has been or is required to be approved by a government agency before it can be marketed for administration to humans. In some embodiments e.g., as set forth herein, a therapeutic agent is an agent for which a medical prescription is required for administration to humans. Treatment: As used herein, the term “treatment” (also “treat” or “treating”) refers to administration of a therapy that partially or completely alleviates, ameliorates, relieves, inhibits, delays onset of, reduces severity of, and/or reduces incidence of one or more symptoms, features, and/or causes of a particular disease, disorder, or condition, or is administered for the purpose of achieving any such result. In some embodiments e.g., as set forth herein, such treatment can be of a subject who does not exhibit signs of the relevant disease, disorder, or condition and/or of a subject who exhibits only early signs of the disease, disorder, or condition. Alternatively or additionally, such treatment can be of a subject who exhibits one or more established signs of the relevant disease, disorder and/or condition. In some embodiments e.g., as set forth herein, treatment can be of a subject who has been diagnosed as suffering from the relevant disease, disorder, and/or condition. In some embodiments e.g., as set forth herein, treatment can be of a subject known to have one or more susceptibility factors that are statistically correlated with increased risk of development of the relevant disease, disorder, or condition. In various examples, treatment is of a cancer.

Upstream: As used herein, the term “upstream” means a first DNA region is closer, relative to a second DNA region, to the N-terminus of a nucleic acid that includes the first DNA region and the second DNA region.

Unmethylated: As used herein, the terms “unmethylated” and “non-methylated” are used interchangeably and mean that an identified DNA region includes no methylated nucleotides.

Variant: As used herein, the term “variant” refers to an entity that shows significant structural identity with a reference entity but differs structurally from the reference entity in the presence, absence, or level of one or more chemical moieties as compared with the reference entity. In some embodiments e.g., as set forth herein, a variant also differs functionally from its reference entity. In general, whether a particular entity is properly considered to be a “variant” of a reference entity is based on its degree of structural identity with the reference entity. A variant can be a molecule comparable, but not identical to, a reference. For example, a variant nucleic acid can differ from a reference nucleic acid at one or more differences in nucleotide sequence. In some embodiments e.g., as set forth herein, a variant nucleic acid shows an overall sequence identity with a reference nucleic acid that is at least 80%, 85%, 86%, 87%, 88%, 89%, 90%, 91%, 92%, 93%, 94%, 95%, 96%, 97%, or 99%. In many embodiments e.g., as set forth herein, a nucleic acid of interest is considered to be a “variant” of a reference nucleic acid if the nucleic acid of interest has a sequence that is identical to that of the reference but for a small number of sequence alterations at particular positions. In some embodiments e.g., as set forth herein, a variant has 10, 9, 8, 7, 6, 5, 4, 3, 2, or 1 substituted residues as compared with a reference. In some embodiments e.g., as set forth herein, a variant has not more than 5, 4, 3, 2, or 1 residue additions, substitutions, or deletions as compared with the reference. In various embodiments e.g., as set forth herein, the number of additions, substitutions, or deletions is fewer than about 25, about 20, about 19, about 18, about 17, about 16, about 15, about 14, about 13, about 10, about 9, about 8, about 7, about 6, and commonly are fewer than about 5, about 4, about 3, or about 2 residues.

BRIEF DESCRIPTION OF THE DRAWINGS

The foregoing and other objects, aspects, features, and advantages of the present disclosure will become more apparent and better understood by referring to the following description taken in conjunction with the accompanying drawings, in which: FIG. 1 is a schematic showing an example MSRE-qPCR approach;

FIG. 2 is a table showing the characteristics of a training set of 166 subjects used to train the computational model for the development of the biomarker signature. The number of female subjects, the number of male subjects, and the average and range of ages of the subjects. The subjects were diagnosed as suffering with colorectal cancer (CRC), healthy control subjects (Control; having been diagnosed with hyperplastic polyps, patients diagnosed as having non-advanced adenomas (NAAs), and patients having no colonoscopy findings). FIG. 2 further distinguishes the location of the cancer of those suffering with CRC as proximal or distal based on a colonoscopy evaluation; FIG. 3 is a table showing the characteristics of a validation group of 535 human subjects which were used to validate the selected markers. FIG. 3 provides the number of female subjects, the number of male subjects, and the average and range of ages of the subjects. The subjects were diagnosed as suffering with colorectal cancer (CRC), healthy control subjects (Control; having been diagnosed with hyperplastic polyps, patients diagnosed as having non-advanced adenomas (NAAs), and patients having a no colonoscopy findings) and patients suffering with advanced adenomas (AA).

FIG. 4 shows a graph of an initial principle component analysis conducted on the validation set of subjects. The subjects were divided into three groups: patients suffering with advanced adenomas (AA), control patients (CNT), and patients suffering with colorectal cancer (CRC). Control (CNT) patients are defined as patients with no colonoscopy findings, patients with hyperplastic polyps, and patients with non- advanced adenomas (NAAs). Correlation circles have been drawn around each of the three groupings.

FIG. 5A is a graph showing performance of colorectal cancer screening using a 40 marker panel of DMRs on a 535 subject group. ROC and AUC for all subjects of the validation group are shown.

FIG. 5B is a chart showing accuracy values, including, from left to right, overall sensitivity of screening for advanced adenomas, overall sensitivity of screening for colorectal cancer, sensitivity of colorectal screening for localized colorectal cancer, sensitivity of colorectal screening for advanced colorectal cancer, and specificity of colorectal screening for control subjects (those with no colonoscopy findings, having hyperplastic polyps, and/or patients diagnosed as having non-advanced adenomas (NAAs)).

FIG. 6 shows a graph representing Ct (Cycle Threshold) values from MSRE-qPCR of the region identified as UDX_29_1 for subjects from the validation group with colorectal cancer (colorectal cancer and advanced adenoma) and control subjects (healthy subjects, patients with hyperplastic polyps and subjects with non-advanced adenoma). Data represent the second subject group (530 subjects) used for testing. For display purposes, Ct values are subtracted from 45 (45 - Ct). Higher 45 - Ct values correspond to higher methylation status, demonstrating hypermethylation in subjects with colorectal cancer.

FIG. 7 shows a graph representing Ct (Cycle Threshold) values from MSRE-qPCR of the region identified as UDX_272.3_2 for subjects from the validation group with colorectal cancer (colorectal cancer and advanced adenoma) and control subjects (healthy subjects, patients with hyperplastic polyps and subjects with non-advanced adenoma). Data represent the second subject group (530 subjects) used for testing. For display purposes, Ct values are subtracted from 45 (45- Ct). Higher 45 - Ct values correspond to higher methylation status, demonstrating hypermethylation in subjects with colorectal cancer.

FIG. 8 shows a graph representing Ct (Cycle Threshold) values from MSRE-qPCR of the region identified as UDX_277.7_2 for subjects from the validation group with colorectal cancer (colorectal cancer and advanced adenoma) and control subjects (healthy subjects, patients with hyperplastic polyps and subjects with non-advanced adenoma). Data represent the second subject group (530 subjects) used for testing. For display purposes, Ct values are subtracted from 45 (45 - Ct). Higher 45 - Ct values correspond to higher methylation status, demonstrating hypermethylation in subjects with colorectal cancer. FIG. 9 shows a graph representing Ct (Cycle Threshold) values from MSRE-qPCR of the region identified as UDX_272.4 for subjects from the validation group with colorectal cancer (colorectal cancer and advanced adenoma) and control subjects (healthy subjects, patients with hyperplastic polyps and subjects with non-advanced adenoma). Data represent the second subject group (530 subjects) used for testing. For display purposes, Ct values are subtracted from 45 (45- Ct). Higher 45 - Ct values correspond to higher methylation status, demonstrating hypermethylation in subjects with colorectal cancer.

FIG. 10 shows a graph representing Ct (Cycle Threshold) values from MSRE-qPCR of the region identified as UDX_174.3 for subjects from the validation group with colorectal cancer (colorectal cancer and advanced adenoma) and control subjects (healthy subjects, patients with hyperplastic polyps and subjects with non-advanced adenoma). Data represent the second subject group (530 subjects) used for testing. For display purposes, Ct values are subtracted from 45 (45- Ct). Higher 45 - Ct values correspond to higher methylation status, demonstrating hypermethylation in subjects with colorectal cancer.

FIG. 11 shows a graph representing Ct (Cycle Threshold) values from MSRE-qPCR of the region identified as UDX_260.2_1 for subjects from the validation group with colorectal cancer (colorectal cancer and advanced adenoma) and control subjects (healthy subjects, patients with hyperplastic polyps and subjects with non-advanced adenoma). Data represent the second subject group (530 subjects) used for testing. For display purposes, Ct values are subtracted from 45 (45- Ct). Higher 45 - Ct values correspond to higher methylation status, demonstrating hypermethylation in subjects with colorectal cancer.

FIG. 12 shows a graph representing Ct (Cycle Threshold) values from MSRE-qPCR of the region identified as UDX_260.1 for subjects from the validation group with colorectal cancer (colorectal cancer and advanced adenoma) and control subjects (healthy subjects, patients with hyperplastic polyps and subjects with non-advanced adenoma). Data represent the second subject group (530 subjects) used for testing. For display purposes, Ct values are subtracted from 45 (45- Ct). Higher 45 - Ct values correspond to higher methylation status, demonstrating hypermethylation in subjects with colorectal cancer.

FIG. 13 shows a graph representing Ct (Cycle Threshold) values from MSRE-qPCR of the region identified as UDX_137.1 for subjects from the validation group with colorectal cancer (colorectal cancer and advanced adenoma) and control subjects (healthy subjects, patients with hyperplastic polyps and subjects with non-advanced adenoma). Data represent the second subject group (530 subjects) used for testing. For display purposes, Ct values are subtracted from 45 (45- Ct). Higher 45 - Ct values correspond to higher methylation status, demonstrating hypermethylation in subjects with colorectal cancer.

FIG. 14 shows a graph representing Ct (Cycle Threshold) values from MSRE-qPCR of the region identified as UDX_17_2 for subjects from the validation group with colorectal cancer (colorectal cancer and advanced adenoma) and control subjects (healthy subjects, patients with hyperplastic polyps and subjects with non-advanced adenoma). Data represent the second subject group (530 subjects) used for testing. For display purposes, Ct values are subtracted from 45 (45- Ct). Higher 45 - Ct values correspond to higher methylation status, demonstrating hypermethylation in subjects with colorectal cancer.

FIG. 15 shows a graph representing Ct (Cycle Threshold) values from MSRE-qPCR of the region identified as UDX_230 for subjects from the validation group with colorectal cancer (colorectal cancer and advanced adenoma) and control subjects (healthy subjects, patients with hyperplastic polyps and subjects with non-advanced adenoma). Data represent the second subject group (530 subjects) used for testing. For display purposes, Ct values are subtracted from 45 (45- Ct). Higher 45 - Ct values correspond to higher methylation status, demonstrating hypermethylation in subjects with colorectal cancer.

FIG. 16 is a schematic showing example methylation changes in methylation status between normal and cancer cells, and further indicates how changes in methylation status can impact gene expression differences between normal and cancer cells.

FIG. 17 is a block diagram of an exemplary cloud computing environment, used in certain embodiments e.g., as set forth herein. FIG. 18 is a block diagram of an example computing device and an example mobile computing device used in certain embodiments e.g., as set forth herein.

The features and advantages of the present disclosure will become more apparent from the detailed description set forth below when taken in conjunction with the drawings.

DETAILED DESCRIPTION

It is contemplated that systems, architectures, devices, methods, and processes of the claimed invention encompass variations and adaptations developed using information from the embodiments described herein. Adaptation and/or modification of the systems, architectures, devices, methods, and processes described herein may be performed, as contemplated by this description.

Throughout the description, where articles, devices, systems, and architectures are described as having, including, or comprising specific components, or where processes and methods are described as having, including, or comprising specific steps, it is contemplated that, additionally, there are articles, devices, systems, and architectures of the present invention that consist essentially of, or consist of, the recited components, and that there are processes and methods according to the present invention that consist essentially of, or consist of, the recited processing steps.

It should be understood that the order of steps or order for performing certain action is immaterial so long as the invention remains operable. Moreover, two or more steps or actions may be conducted simultaneously.

The mention herein of any publication, for example, in the Background section, is not an admission that the publication serves as prior art with respect to any of the claims presented herein. The Background section is presented for purposes of clarity and is not meant as a description of prior art with respect to any claim.

Documents are incorporated herein by reference as noted. Where there is any discrepancy in the meaning of a particular term, the meaning provided in the Definition section above is controlling.

Headers are provided for the convenience of the reader - the presence and/or placement of a header is not intended to limit the scope of the subject matter described herein.

Screening for Colorectal Cancer

There is a need for improved methods of screening for colorectal cancer and/or advanced adenomas, including screening for early-stage colorectal cancer. Despite recommendations for screening of individuals, e.g., over age 50, colorectal cancer screening programs are often ineffective or unsatisfactory. Improved colorectal cancer and/or advanced adenoma screening improves diagnosis and reduces colorectal cancer mortality.

DNA methylation (e.g., hypermethylation or hypomethylation) can activate or inactivate genes, including genes that impact cancer development (see, e.g., FIG. 16). Thus, for example, hypermethylation can inactivate one or more genes that typically act to suppress cancer, causing or contributing to development of cancer in a sample or subject.

The present disclosure includes the discovery that determination of the methylation status of one or more methylation loci provided herein, and/or the methylation status of one or more DMRs provided herein, and/or the methylation status of one or more methylation sites provided herein, provides screening for colorectal cancer and/or advanced adenomas, e.g., with a high degree of sensitivity and/or specificity. The present disclosure provides compositions and methods including or relating to colorectal cancer and/or advanced adenoma methylation biomarkers that, individually or in various panels comprising two or more biomarkers, provide for screening of colorectal cancer and/or advanced adenomas, e.g., with a high degree of specificity and/or sensitivity.

In various embodiments e.g., as set forth herein, a colorectal cancer and/or advanced adenoma methylation biomarker of the present disclosure is selected from a methylation locus that is or includes a portion (e.g., at least 1 common base pair) of the sequence of the differentially methylated regions (DMRs) as identified in Table 1 below. The DMRs are identified by a chromosome number (Chr. No.) on which the DMR is located, the start position (start base pair) of the DMR on the chromosome, the end position of the DMR on the chromosome, the width of the DMR, the annotated names of the one or more genes (if available) overlapping with or contained within the DMR, and the Sequence ID Number of the DMR as presented in the Sequences section of the specification and in the sequence listing presented. The chromosome number and the start (start base pair) and end (end base pair) positions of the regions as identified are in reference to the human genome build identified as GRCh38.

Table 1. List of 69 DMRs of interest in screening for advanced adenomas and colorectal cancer.

For the avoidance of any doubt, any methylation biomarker provided herein can be, or be included in, among other things, a colorectal cancer methylation biomarker and/or an advanced adenoma methylation biomarker.

In some embodiments e.g., as set forth herein, a colorectal cancer and/or advanced adenoma methylation biomarker can be or include a single methylation locus. In some embodiments e.g., as set forth herein, the methylation biomarker can be or include two or more methylation loci. In some embodiments e.g., as set forth herein, the methylation biomarker can be or include a single differentially methylated region (DMR). In some embodiments e.g., as set forth herein, a methylation biomarker can be or include a single methylation site. In other embodiments e.g., as set forth herein, a methylation biomarker can be or include two or more methylation sites. In some embodiments e.g., as set forth herein, a methylation locus can include two or more DMRs and further include DNA regions adjacent to one or more of the included DMRs. In some instances e.g., as set forth herein, a methylation locus is or includes a gene, such as a gene provided in Table 1. In some instances e.g., as set forth herein a methylation locus is or includes a portion of a gene, e.g., a portion of a gene provided in Table 1. In some instances e.g., as set forth herein, a methylation locus includes but is not limited to identified nucleic acid boundaries of a gene. In some instances e.g., as set forth herein, a methylation locus is found outside of previously annotated genes, e.g., an unannotated region of a genetic sequence as provided in Table 1. In some instances e.g., as set forth herein, a methylation locus is or includes a portion of multiple genes, e.g., as provided in Table 1.

In some instances e.g., as set forth herein, a methylation locus is or includes a coding region of a gene, such as a coding region of a gene provided in Table 1. In some instances e.g., as set forth herein, a methylation locus is or includes a portion of the coding region of gene, e.g., a portion of the coding region a gene provided in Table 1. In some instances e.g., as set forth herein, a methylation locus includes but is not limited to identified nucleic acid boundaries of a coding region of gene.

In some instances e.g., as set forth herein, a methylation locus is or includes a promoter and/or other regulatory region of a gene, such as a promoter and/or other regulatory region of a gene provided in Table 1. In some instances e.g., as set forth herein, a methylation locus is or includes a portion of the promoter and/or regulatory region of gene, e.g., a portion of promoter and/or regulatory region a gene provided in Table 1. In some instances e.g., as set forth herein, a methylation locus includes but is not limited to identified nucleic acid boundaries of a promoter and/or other regulatory region of gene. In some embodiments e.g., as set forth herein a methylation locus is or includes a high CpG density promoter, or a portion thereof.

In some embodiments e.g., as set forth herein, a methylation locus is or includes noncoding sequence. In some embodiments e.g., as set forth herein, a methylation locus is or includes one or more exons, and/or one or more introns.

In some embodiments e.g., as set forth herein, a methylation locus includes a DNA region extending a predetermined number of nucleotides upstream of a coding sequence, and/or a DNA region extending a predetermined number of nucleotides downstream of a coding sequence. In various instances e.g., as set forth herein, a predetermined number of nucleotides upstream and/or downstream and be or include, e.g., 500 bp, 1 kb, 2 kb, 3 kb, 4 kb, 5 kb, 10 kb, 20 kb, 30 kb, 40 kb, 50 kb, 75 kb, or 100 kb. Those of skill in the art will appreciate that methylation biomarkers capable of impacting expression of a coding sequence may typically be within any of these distances of the coding sequence, upstream and/or downstream.

Those of skill in the art will appreciate that a methylation locus identified as a methylation biomarker need not necessarily be assayed in a single experiment, reaction, or amplicon. A single methylation locus identified as a colorectal cancer and/or advanced adenoma methylation biomarker can be assayed, e.g., in a method including separate amplification (or providing oligonucleotide primers and conditions sufficient for amplification of) of one or more distinct or overlapping DNA regions within a methylation locus, e.g., one or more distinct or overlapping DMRs. Those of skill in the art will further appreciate that a methylation locus identified as a methylation biomarker need not be analyzed for methylation status of each nucleotide, nor each CpG, present within the methylation locus. Rather, a methylation locus that is a methylation biomarker may be analyzed, e.g., by analysis of a single DNA region within the methylation locus, e.g., by analysis of a single DMR within the methylation locus. DMRs of the present disclosure can be a methylation locus or include a portion of a methylation locus. In some instances e.g., as set forth herein, a DMR is a DNA region with a methylation locus that is, e.g., 1 to 5,000 bp in length. In various embodiments e.g., as set forth herein, a DMR is a DNA region with a methylation locus that is equal to or less than 5000 bp, 4,000 bp, 3,000 bp, 2,000 bp, 1 ,000 bp, 950 bp, 900 bp, 850 bp, 800 bp, 750 bp, 700 bp, 650 bp, 600 bp, 550 bp, 500 bp, 450 bp, 400 bp, 350 bp, 300 bp, 250 bp, 200 bp, 150 bp, 100 bp, 50 bp, 40 bp, 30 bp, 20 bp, or 10 bp in length. In some embodiments e.g., as set forth herein, a DMR is 1 , 2, 3, 4, 5, 6, 7, 8 or 9 bp in length.

Methylation biomarkers, including without limitation methylation loci, methylation sites, and DMRs provided herein.

For clarity, those of skill in the art will appreciate that term methylation biomarker is used broadly, such that a methylation locus can be a methylation biomarker that includes one or more DMRs, each of which DMRs is also itself a methylation biomarker, and each of which DMRs can include one or more methylation sites, each of which methylation sites is also itself a methylation biomarker. Moreover, a methylation biomarker can include two or more methylation loci. Accordingly, status as a methylation biomarker does not turn on the contiguousness of nucleic acids included in a biomarker, but rather on the existence of a change in methylation status for included DNA region(s) between a first state and a second state, such as between colorectal cancer and controls and/or between advanced adenomas and controls.

As provided herein, a methylation locus can be any of one or more methylation loci each of which methylation loci is or includes a genetic region (e.g., a DMR) as identified in Table 1. In some particular embodiments e.g., as set forth herein, a colorectal cancer and/or advanced adenoma methylation biomarker includes a single methylation locus that is or includes (all or a portion of) a gene identified in Table 1.

In some particular embodiments e.g., as set forth herein, a colorectal cancer and/or advanced adenoma methylation biomarker includes two or more methylation loci, each of which is or includes a genetic region identified in Table 1. In some embodiments e.g., as set forth herein, the methylation biomarker includes 1 , 2, 3, 4, 5, 6, 7, 8, 9, 10, 11 , 12, 13, 14, 15, 16, 17, 18, 19, 20, 21 , 22, 23, 24, 25, 26, 27, 28, 29, 30, 31 , 32, 33,

34, 35, 36, 37, 38, 39, 40, 41 , 42, 43, 44, 45, 46, 47, 48, 49, 50, 51, 52, 53, 54, 55, 56,

57, 58, 59, 60, 61, 62, 63, 64, 65, 66, 67, 68, or 69 methylation loci, each of which includes (all or a portion of) a genetic region identified in Table 1.

The DMR sequences provided in Tables 2-4 are selected regions that consist of, overlap with, or contain portions of the DMRs of Table 1. That is, each identified region of DNA in Tables 2-4 encompasses a portion of, up to and including all of a DMRs identified in Table 1. To clarify, the evaluation of a DMR of Table 1 overlapping with a DMR of Tables 2-4 is made based on the sequence start and end positions and the chromosome number. If both DMRs are found on the same chromosome and a one of the two DMR sequence has a start and/or end point between the start and end points or at one of the start and end points of the second of the two DMR sequence, they are deemed to overlap. For instance, UDX_224.14 (SEQ ID No. 190) of Table 4 encompasses a selection of 111 contiguous base pairs on chromosome 21. All 111 contiguous base pairs are found within SEQ ID No. 67 of Table 1 , which is also found on chromosome 21. The start point of UDX_224.14 is 26844767 and the end point is at 26844877, while the start point of SEQ ID No. 67 is 26843133 and the end point is 26845357. As both the start and end points of UDX_224.14 are found between the start and end points of SEQ ID No. 67 and both are on the same chromosome, they overlap with one another and accordingly share an identical overlapping sequence.

In another instance, UDX_244_2 (SEQ ID No. 213) of Table 4 overlaps a portion of (i.e., does not encompass the entirety of) SEQ ID No. 2 of Table 1. UDX_244_2 is 213 base pairs long and shares a contiguous sequence of 73 base pairs in common with SEQ ID No. 2, which is 242 base pairs long. The start position of UDX_224_2 on chromosome 1 is 107140056 and the end position is 107140173. The start position of SEQ ID No. 2 is 107140100 and the end position is 107140341. Accordingly, as the start position of SEQ ID No. 2 is between the start and end positions of UDX_224.2 and both are located on chromosome 1 , these sequences are also said to be “overlapping” with one another. In some particular embodiments e.g., as set forth herein, a colorectal cancer and/or advanced adenoma methylation biomarker includes three or more methylation loci, each of three or more methylation loci is or includes a genetic region identified in any one of tables Table 1 to 4, including without limitation and combinations of three or more methylation loci that respectively are or include genetic regions identified in one of Tables 2 to 4.

In some particular embodiments e.g., as set forth herein, a colorectal cancer and/or advanced adenoma methylation biomarker includes three methylation loci, which three methylation loci include methylation loci that are or include the genetic regions identified in Table 2. In some particular embodiments e.g., as set forth herein, a colorectal cancer methylation biomarker includes ten methylation loci, which ten methylation loci include methylation loci that are or include the genetic regions identified in Table 3. In some particular embodiments e.g., as set forth herein, a colorectal cancer methylation biomarker includes forty methylation loci, which forty methylation loci include methylation loci that are or include the genetic regions identified in Table 4.

Table 2. Combination of 3 methylation loci ranked in order of importance to the

5 diagnosis of colorectal cancer and/or advanced adenoma.

Table 3. Combination of 10 methylation loci ranked in order of importance to the diagnosis of colorectal cancer and/or advanced adenoma.

10 Table 4. Combination of 40 methylation loci ranked in order of importance to the diagnosis of colorectal cancer and/or advanced adenoma.

As provided herein, a DMR can be any of one or more DMRs, each of which is present in a methylation locus that is or includes (all or a portion of) a genetic region identified in Table 1. In some particular embodiments e.g., as set forth herein, a colorectal cancer and/or advanced adenoma methylation biomarker is or includes a single DMR that is, includes all or a portion of, or is present in a genetic region identified in Table 1. In some particular embodiments e.g., as set forth herein, a colorectal cancer methylation biomarker includes three or more DMRs, each of which is, includes all or a portion of, or is present in a genetic region identified in Table 1. In some embodiments e.g., as set forth herein, a colorectal cancer methylation biomarker includes 1 , 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 21, 22, 23, 24, 25, 26, 27, 28, 29, 30, 31 , 32, 33, 34, 35, 36, 37, 38, 39, 40, 41 , 42, 43, 44, 45, 46, 47, 48, 49, 50, 51 , 52, 53, 54, 55, 56, 57, 58, 59, 60, 61 , 62, 63, 64, 65, 66, 67, 68, or 69 DMRs, each of which includes (all or a portion of) a genetic region identified in Table 1.

In some particular embodiments e.g., as set forth herein, a colorectal cancer and/or advanced adenoma methylation biomarker includes two or more DMRs, each of which two or more DMRs is, includes all or a portion of, or is present in a gene identified in any one of Tables 1-4. In some particular embodiments e.g., as set forth herein, a colorectal cancer methylation biomarker includes three DMRs, which three DMRs include DMRs that are, include all or a portion of, or are present in the genetic regions identified in Table 2. In some particular embodiments e.g., as set forth herein, a colorectal cancer and/or advanced adenoma methylation biomarker includes ten DMRs, which ten DMRs include DMRs that are, include all or a portion of, or are present in the genetic regions identified in Table 3. In some particular embodiments e.g., as set forth herein, a colorectal cancer methylation biomarker includes forty DMRs, which forty DMRs include DMRs that are, include all or a portion of, or are present in the genetic regions identified in Table 4.

In various embodiments e.g., as set forth herein, a methylation biomarker can be or include one or more individual nucleotides (e.g., a single individual cysteine residue in the context of CpG) or a plurality of individual cysteine residues (e.g., of a plurality of CpGs) present within one or more methylation loci (e.g, one or more DMRs) provided herein. Thus, in certain embodiments a methylation biomarker is or includes methylation status of a plurality of individual methylation sites.

In various embodiments e.g., as set forth herein, a methylation biomarker is, includes, or is characterized by change in methylation status that is a change in the methylation of one or more methylation sites within one or more methylation loci (e.g., one or more DMRs). In various embodiments e.g., as set forth herein, a methylation biomarker is or includes a change in methylation status that is a change in the number of methylated sites within a one or more methylation loci (e.g., one or more DMRs). In various embodiments e.g., as set forth herein, a methylation biomarker is or includes a change in methylation status that is a change in the frequency of methylation sites within one or more methylation loci (e.g., one or more DMRs). In various embodiments e.g., as set forth herein, a methylation biomarker is or includes a change in methylation status that is a change in the pattern of methylation sites within one or more methylation loci (e.g., one or more DMRs).

In various embodiments e.g., as set forth herein, methylation status of one or more methylation loci (e.g., one or more DMRs) is expressed as a fraction or percentage of the one or more methylation loci (e.g., the one or more DMRs) present in a sample that are methylated, e.g., as a fraction of the number of individual DNA strands of DNA in a sample that are methylated at a one or more particular methylation loci (e.g., one or more particular DMRs). Those of skill in the art will appreciate that, in some instances e.g., as set forth herein, the fraction or percentage of methylation can be calculated from the ratio of methylated DMRs to unmethylated DMRs for one or more analyzed DMRs, e.g., within a sample. In certain embodiments e.g., as set forth herein, the methylation status of one or more methylation loci (e.g., one or more DMRs) is expressed as a fraction or percentage of the one or more regions of CpG islands that are methylated.

In various embodiments e.g., as set forth herein, methylation status of one or more methylation loci (e.g., one or more DMRs) is compared to a reference methylation status value and/or to methylation status of the one or more methylation loci (e.g., one or more DMRs) in a reference sample. In certain instances e.g., as set forth herein e.g., as set forth herein, a reference is a non-contemporaneous sample from the same source, e.g., a prior sample from the same source, e.g., from the same subject. In certain instances e.g., as set forth herein e.g., as set forth herein, a reference for the methylation status of one or more methylation loci (e.g., one or more DMRs) is the methylation status of the one or more methylation loci (e.g., one or more DMRs) in a sample (e.g., a sample from a subject), or a plurality of samples, known to represent a particular state (e.g., a cancer state or a non-cancer state). Thus, a reference can be or include one or more predetermined thresholds, which thresholds can be quantitative (e.g., a methylation value) or qualitative. In certain instances e.g., as set forth herein e.g., as set forth herein, a reference for methylation status of a DMR is the methylation status of a nucleotide or plurality of nucleotides (e.g., a plurality of contiguous oligonucleotides) present in the same sample that does not include nucleotides of the DMR. Those of skill in the art will appreciate that a reference measurement is typically produced by measurement using a methodology identical to, similar to, or comparable to that by which the non-reference measurement was taken.

Without wishing to be bound by any particular scientific theory, FIG. 16 provides a schematic of one possible mechanism by which hypermethylation or hypomethylation of a regulatory sequence of gene can impact expression. As shown in FIG. 16, hypomethylation can result in increased expression and/or hypermethylation can result in suppression of expression. In various instances e.g., as set forth herein, increased methylation of express-regulatory regions, such as promoter regions and enhancer regions, as compared to a reference can reduce or silence expression of an operably linked gene, e.g., of an operably linked gene that typically acts to suppress cancer. In various embodiments e.g., as set forth herein, decreased methylation of expression- regulatory regions, such as promoter regions and enhancer regions, as compared to a reference can increase expression of an operably linked gene, e.g., of an operably linked gene having an activity that contributes to oncogenesis. Without wishing to be bound by any particular scientific theory, DNA methylation may provide a more chemically and biologically stable indicator of cancer status than RNA expression or protein expression perse.

Methylation is typically thought to be highly tissue-specific, providing a dimension of information not necessarily present in DNA sequence analysis.

Methylation events that substantially contribute to oncogenesis can occur, e.g., in expression-regulatory regions of DNA (e.g., at a promoter region, enhancer region, transcription factor binding site, CTCF-binding site, CpG island, or other sequence) operably linked with cancer-associated genes such as genes that typically act to suppress cancer. Accordingly, inactivation of genes that typically act to suppress cancer results in or contribute to oncogenesis.

Cancers Methods and compositions of the present disclosure are useful for screening for cancer, particularly colorectal cancer and precursor tumors to colorectal cancers (e.g., advanced adenomas). Colorectal cancers include, without limitation, colon cancer, rectal cancer, and combinations thereof. Colorectal cancers include metastatic colorectal cancers and non-metastatic colorectal cancers. Colorectal cancers include cancer located in the proximal part of the colon cancer and cancer located the distal part of the colon.

Colorectal cancers include colorectal cancers at any of the various possible stages known in the art, including, e.g., Stage I, Stage II, Stage III, and Stage IV colorectal cancers (e.g., stages 0, I, IIA, MB, IIC, IIIA, NIB, NIC, IVA, IVB, and IVC). Colorectal cancers include all stages of the Tumor/Node/Metastasis (TNM) staging system. With respect to colorectal cancer, T can refer to whether the tumor grown into the wall of the colon or rectum, and if so by how many layers; N can refer to whether the tumor has spread to lymph nodes, and if so how many lymph nodes and where they are located; and M can refer to whether the cancer has spread to other parts of the body, and if so which parts and to what extent. Particular stages of T, N, and M are known in the art. T stages can include TX, TO, Tis, T1 , T2, T3, T4a, and T4b; N stages can include NX, NO, N1a, N1b, N1c, N2a, and N2b; M stages can include M0, M1a, and M1b. Moreover, grades of colorectal cancer can include GX, G1 , G2, G3, and G4. Various means of staging cancer, and colorectal cancer in particular, are well known in the art summarized, e.g., on the world wide web at cancer.net/cancer-types/colorectal- cancer/stages.

In certain instances e.g., as set forth herein, the present disclosure includes screening of early stage colorectal cancer. Early stage colorectal cancers can include, e.g., colorectal cancers localized within a subject, e.g., in that they have not yet spread to lymph nodes of the subject, e.g., lymph nodes near to the cancer (stage NO), and have not spread to distant sites (stage MO). Early stage cancers include colorectal cancers corresponding to, e.g., Stages 0 to II C.

Thus, colorectal cancers of the present disclosure include, among other things, pre- malignant colorectal cancer (e.g., advanced adenomas) and malignant colorectal cancer. Methods and compositions of the present disclosure are useful for screening of colorectal cancer in all of its forms and stages, including without limitation those named herein or otherwise known in the art, as well as all subsets thereof. Accordingly, the person of skill in art will appreciate that all references to colorectal cancer provided here include, without limitation, colorectal cancer in all of its forms and stages, including without limitation those named herein or otherwise known in the art, as well as all subsets thereof.

Subjects and Samples

A sample analyzed using methods and compositions provided herein can be any biological sample and/or any sample including nucleic acid. In various particular embodiments, a sample analyzed using methods and compositions provided herein can be a sample from a mammal. In various particular embodiments, a sample analyzed using methods and compositions provided herein can be a sample from a human subject. In various particular embodiments, a sample analyzed using methods and compositions provided herein can be a sample form a mouse, rat, pig, horse, chicken, or cow.

In various instances e.g., as set forth herein, a human subject is a subject diagnosed or seeking diagnosis as having, diagnosed as or seeking diagnosis as at risk of having, and/or diagnosed as or seeking diagnosis as at immediate risk of having, a cancer such as a colorectal cancer or a pre-cancerous tumor such as an advanced adenoma. In various instances e.g., as set forth herein, a human subject is a subjected identified as a subject in need of colorectal cancer and/or advanced adenoma screening. In certain instances e.g., as set forth herein, a human subject is a subjected identified as in need of colorectal cancer and/or advanced adenoma screening by a medical practitioner. In various instances e.g., as set forth herein, a human subject is identified as in need of screening due to age, e.g., due to an age equal to or greater than 50 years, e.g., an age equal to or greater than 50, 55, 60, 65, 70, 75, 80, 85, or 90 years. In various instances e.g., as set forth herein, a human subject is a subject not diagnosed as having, not at risk of having, not at immediate risk of having, not diagnosed as having, and/or not seeking diagnosis for a cancer such as a colorectal cancer or pre-cancerous tumor such as an advanced adenoma, or any combination thereof.

A sample from a subject, e.g., a human or other mammalian subject, can be a sample of, e.g., blood, blood component, cfDNA, ctDNA, stool, or colorectal tissue. In some particular embodiments, a sample is an excretion or bodily fluid of a subject (e.g., saliva, stool, blood, lymph, or urine of a subject), a colorectal cancer tissue sample, or an adenoma or polyp tissue sample. A sample from a subject can be a cell or tissue sample, e.g., a cell or tissue sample that is of a cancer or includes cancer cells, e.g., of a tumor or of a metastatic tissue. In various embodiments e.g., as set forth herein, a sample from a subject, e.g., a human or other mammalian subject, can be obtained by biopsy (e.g., fine needle aspiration or tissue biopsy) or surgery.

In various embodiments e.g., as set forth herein, a sample is a sample of cell-free DNA (cfDNA). cfDNA is typically found in human biofluids (e.g., plasma, serum, or urine) in short, double-stranded fragments. The concentration of cfDNA is typically low, but can significantly increase under particular conditions, including without limitation pregnancy, autoimmune disorder, myocardial infraction, and cancer. Circulating tumor DNA (ctDNA) is the component of circulating DNA specifically derived from cancer cells. ctDNA can be present in human biofluids bound to leukocytes and erythrocytes or not bound to leukocytes and erythrocytes. Various tests for detection of tumor-derived cfDNA are based on detection of genetic or epigenetic modifications that are characteristic of cancer (e.g., of a relevant cancer) or pre-cancerous tumor (e.g., an advanced adenoma). Genetic or epigenetic modifications characteristic of cancer can include, without limitation, oncogenic or cancer-associated mutations in tumor- suppressor genes, activated oncogenes, hypermethylation, and/or chromosomal disorders. Detection of genetic or epigenetic modifications characteristic of cancer can confirm that detected cfDNA is ctDNA. cfDNA and ctDNA provide a real-time or nearly real time metric of the methylation status of a source tissue. cfDNA and ctDNA demonstrate a half-life in blood of about 2 hours, such that a sample taken at a given time provides a relatively timely reflection of the status of a source tissue.

Various methods of isolating nucleic acids from a sample (e.g., of isolating cfDNA from blood or plasma) are known in the art. Nucleic acids can be isolated, e.g., without limitation, standard DNA purification techniques, by direct gene capture (e.g., by clarification of a sample to remove assay-inhibiting agents and capturing a target nucleic acid, if present, from the clarified sample with a capture agent to produce a capture complex, and isolating the capture complex to recover the target nucleic acid).

Methods of measuring methylation status

Methylation status can be measured by a variety of methods known in the art and/or by methods provided herein. Those of skill in the art will appreciate that a method for measuring methylation status can generally be applied to samples from any source and of any kind, and will further be aware of processing steps available to modify a sample into a form suitable for measurement by a given methodology. Methods of measuring methylation status include, without limitation, methods including methylation-status- specific polymerase chain reaction (PCR), methods including nucleic acid sequencing, methods including mass spectrometry, methods including methylation-sensitive nucleases, methods including mass-based separation, methods including target- specific capture, methods including methylation-specific oligonucleotide primers, methods including hybrid-capture targeted next-generation sequencing, methods including amplicon-based targeted next generation sequencing, and methods including whole genome bisulfite sequencing. Certain particular assays for methylation utilize a bisulfite reagent (e.g., hydrogen sulfite ions).

Bisulfite reagents can include, among other things, bisulfite, disulfite, hydrogen sulfite, or combinations thereof, which reagents can be useful in distinguishing methylated and unmethylated nucleic acids. Bisulfite interacts differently with cytosine and 5- methylcytosine. In typical bisulfite-based methods, contacting of DNA with bisulfite deaminates unmethylated cytosine to uracil, while methylated cytosine remains unaffected; methylated cytosines, but not unmethylated cytosines, are selectively retained. Thus, in a bisulfite processed sample, uracil residues stand in place of, and thus provide an identifying signal for, unmethylated cytosine residues, while remaining (methylated) cytosine residues thus provide an identifying signal for methylated cytosine residues. Bisulfite processed samples can be analyzed, e.g., by PCR or by whole genome bisulfite sequencing.

Various methylation assay procedures can be used in conjunction with bisulfite treatment to determine methylation status of a target sequence such as a DMR. Such assays can include, among others, Methylation-Specific Restriction Enzyme qPCR, Methylation-Sensitive Restriction Enzyme qPCR, sequencing of bisulfite-treated nucleic acids, PCR (e.g., with sequence-specific amplification), Methylation Specific Nuclease- assisted Minor-allele Enrichment PCR, Methylation-Sensitive High Resolution Melting, hybrid-capture targeted next-generation sequencing, and amplicon-based targeted next-generation sequencing. In some embodiments, DMRs are amplified from a bisulfite-treated DNA sample and a DNA sequencing library is prepared for sequencing according to, e.g., an lllumina protocol or transpose-based Nextera XT protocol. In certain embodiments, high-throughput and/or next-generation sequencing techniques are used to achieve base-pair level resolution of DNA sequence, permitting analysis of methylation status. When combined with bisulfite treatment and covering a significant portion (e.g., >50%) of the human genome, these whole genome sequencing technologies may be collectively referred to as Whole Genome Bisulfite Sequencing (WGBS).

In various embodiments e.g., as set forth herein, methylation status is detected by a method including PCR amplification with methylation-specific oligonucleotide primers (MSP methods), e.g., as applied to bisulfite-treated sample (see, e.g., Herman 1992 Proc. Natl. Acad. Sci. USA 93: 9821-9826, which is herein incorporated by reference with respect to methods of determining methylation status). Use of methylation-status- specific oligonucleotide primers for amplification of bisulfite-treated DNA allows differentiation between methylated and unmethylated nucleic acids. Oligonucleotide primer pairs for use in MSP methods include at least one oligonucleotide primer capable of hybridizing with sequence that includes a methylation site, e.g., a CpG. An oligonucleotide primer that includes a T residue at a position complementary to a cytosine residue will selectively hybridize to templates in which the cytosine was unmethylated prior to bisulfite treatment, while an oligonucleotide primer that includes a G residue at a position complementary to a cytosine residue will selectively hybridize to templates in which the cytosine was methylated cytosine prior to bisulfite treatment. MSP results can be obtained with or without sequencing amplicons, e.g., using gel electrophoresis. MSP (methylation-specific PCR) allows for highly sensitive detection (detection level of 0.1% of the alleles, with full specificity) of locus-specific DNA methylation, using PCR amplification of bisulfite-converted DNA.

Another method that can be used to determine methylation status after bisulfite treatment of a sample is Methylation-Sensitive High Resolution Melting (MS-HRM) PCR (see, e.g., Hussmann 2018 Methods Mol Biol. 1708:551-571 , which is herein incorporated by reference with respect to methods of determining methylation status). MS-HRM is an in-tube, PCR-based method to detect methylation levels at specific loci of interest based on hybridization melting. Bisulfite treatment of the DNA prior to performing MS-HRM ensures a different base composition between methylated and unmethylated DNA, which is used to separate the resulting amplicons by high resolution melting. A unique primer design facilitates a high sensitivity of the assays enabling detection of down to 0.1-1% methylated alleles in an unmethylated background. Oligonucleotide primers for MS-HRM assays are designed to be complementary to the methylated allele, and a specific annealing temperature enables these primers to anneal both to the methylated and the unmethylated alleles thereby increasing the sensitivity of the assays.

Another method that can be used to determine methylation status after bisulfite treatment of a sample is Quantitative Multiplex Methylation-Specific PCR (QM-MSP). QM-MSP uses methylation specific primers for sensitive quantification of DNA methylation (see, e.g., Fackler 2018 Methods Mol Biol. 1708:473-496, which is herein incorporated by reference with respect to methods of determining methylation status). QM-MSP is a two-step PCR approach, where in the first step, one pair of gene-specific primers (forward and reverse) amplifies the methylated and unmethylated copies of the same gene simultaneously and in multiplex, in one PCR reaction. This methylation- independent amplification step produces amplicons of up to 10 ⁹ copies per pl_ after 36 cycles of PCR. In the second step, the amplicons of the first reaction are quantified with a standard curve using real-time PCR and two independent fluorophores to detect methylated/unmethylated DNA of each gene in the same well (e.g., 6FAM and VIC). One methylated copy is detectable in 100,000 reference gene copies. Another method that can be used to determine methylation status after bisulfite treatment of a sample is Methylation Specific Nuclease-assisted Minor-allele Enrichment (MS-NaME) (see, e.g., Liu 2017 Nucleic Acids Res. 45(6):e39, which is herein incorporated by reference with respect to methods of determining methylation status). Ms-NaME is based on selective hybridization of probes to target sequences in the presence of DNA nuclease specific to double-stranded (ds) DNA (DSN), such that hybridization results in regions of double-stranded DNA that are subsequently digested by the DSN. Thus, oligonucleotide probes targeting unmethylated sequences generate local double stranded regions resulting to digestion of unmethylated targets; oligonucleotide probes capable of hybridizing to methylated sequences generate local double-stranded regions that result in digestion of methylated targets, leaving methylated targets intact. Moreover, oligonucleotide probes can direct DSN activity to multiple targets in bisulfite-treated DNA, simultaneously. Subsequent amplification can enrich non-digested sequences. Ms-NaME can be used, either independently or in combination with other techniques provided herein. Another method that can be used to determine methylation status after bisulfite treatment of a sample is Methylation-sensitive Single Nucleotide Primer Extension (Ms- SNuPE™) (see, e.g., Gonzalgo 2007 Nat Protoc. 2(8): 1931 -6, which is herein incorporated by reference with respect to methods of determining methylation status). In Ms-SNuPE, strand-specific PCR is performed to generate a DNA template for quantitative methylation analysis using Ms-SNuPE. SNuPE is then performed with oligonucleotide(s) designed to hybridize immediately upstream of the CpG site(s) being interrogated. Reaction products can be electrophoresed on polyacrylamide gels for visualization and quantitation by phosphor-image analysis. Amplicons can also carry a directly or indirectly detectable labels such as a fluorescent label, radionuclide, or a detachable molecule fragment or other entity having a mass that can be distinguished by mass spectrometry. Detection may be carried out and/or visualized by means of, e.g., matrix assisted laser desorption/ionization mass spectrometry (MALDI) or using electron spray mass spectrometry (ESI).

Certain methods that can be used to determine methylation status after bisulfite treatment of a sample utilize a first oligonucleotide primer, a second oligonucleotide primer, and an oligonucleotide probe in an amplification-based method. For instance, the oligonucleotide primers and probe can be used in a method of real-time polymerase chain reaction (PCR) or droplet digital PCR (ddPCR). In various instances e.g., as set forth herein, the first oligonucleotide primer, the second oligonucleotide primer, and/or the oligonucleotide probe selectively hybridize methylated DNA and/or unmethylated DNA, such that amplification or probe signal indicate methylation status of a sample.

Other bisulfite-based methods for detecting methylation status (e.g., the presence of level of 5-methylcytosine) are disclosed, e.g., in Frommer (1992 Proc Natl Acad Sci U S A. 1; 89(5): 1827-31 , which is herein incorporated by reference).

Bisulfite-based method for detecting methylation status may include amplicon-based targeted next generation sequencing, e.g., see Masser (2015 J Vis Exp, (96):52488, doi: 10.3791/52488, which is herein incorporated by reference). Generally, amplicon- based targeted next generation sequencing utilizes a bisulfite conversion and region- specific PCR amplification in combination with next-generation library construction to examine the methylation status of a targeted region of interest in a high-throughput manner.

Another bisulfite-based method for detecting methylation status may include hybrid- capture based targeted next generation sequencing, e.g., see Ivanov (2013, Nucleic Acids Res, doi: 10.1093/nar.gks1467, which is herein incorporated by reference). Generally, the method comprises treatment of the genomic DNA with bisulfite. Then, target regions are hybridized with DNA or RNA probes either in solution or bound to a solid support. Bound target regions are then enriched and sequenced according to known protocols, see Gasc (2016, Front. Microbiol., doi: 10.1093/nar/gkw309, which is incorporated herein by reference). Certain methods that can be used to determine methylation status do not include bisulfite treatment of a sample. For instance, changes in methylation status can be detected by a PCR-based process in which DNA is digested with one or more methylation-sensitive restriction enzymes (MSREs) prior to PCR amplification (e.g., by MSRE-qPCR). Typically, MSREs have recognition sites that include at least one CpG motif, such that activity of the MSRE is blocked from cleaving a possible recognition site if the site includes 5-methylcytosine. (see, e.g., Beikircher 2018 Methods Mol Biol. 1708:407-424, which is herein incorporated by reference). Thus, MSREs selectively digest nucleic acids based upon methylation status of the recognition site of the MSRE; they can digest DNA at MSRE recognition sites that are unmethylated, but not digest DNA in MSRE recognition sites that are methylated. In certain embodiments, an aliquot of sample can be digested with MSREs, generating a processed sample in which unmethylated DNA has been cleaved by the MSREs, such that, the proportion of uncleaved and/or amplifiable DNA with at least one methylated site within MSRE recognition sites (e.g., at least one methylated site within each MSRE recognition site of the DNA molecule) is increased relative to uncleaved and/or amplifiable DNA that did not include at least one methylated site within MSRE recognition sites (e.g., did not include at least one methylated site within each MSRE recognition site of the DNA molecule). Uncleaved sequences of a restriction-enzyme-digested sample can then be preamplified, e.g, in PCR, and quantified e.g. by qPCR, real-time PCR, or digital PCR. Oligonucleotide primers for MSRE-qPCR amplify regions that include one or more MSRE cleavage sites, and/or a plurality of MSRE cleavage sites. Amplicons including a plurality of MSRE cleavage sites are typically more likely to yield robust results. The number of cleavage sites within a DMR amplicon, and in some instances e.g., as set forth herein the resulting robustness of methylation status determination for the DMR, can be increased by design of DMRs that include a plurality of MSRE recognition sites (as opposed to a single recognition site) in a DMR amplicon. In various instances e.g., as set forth herein, a plurality of MSREs can be applied to the same sample, including, e.g., two or more of Acil, Hin6l, HpyCH4IV, and Hpall (e.g., including Acil, Hin6l, and HpyCH4IV) . A plurality of MSREs (e.g., the combination of Acil, Hin6l, HpyCH4IV, and Hpall, or the combination of Acil, Hin6l, and HpyCH4IV) can provide improved frequency of MSRE recognition sites within DMR amplicons.

MSRE-qPCR can also include a pre-amplification step following sample digestion by MSREs but before qPCR in order to improve the amount of available sample, given the low prevalence of cfDNA in blood. In certain MSRE-qPCR embodiments, e.g., as set forth herein, the amount of total DNA is measured in an aliquot of sample in native (e.g., undigested) form using, e.g., realtime PCR or digital PCR.

Various amplification technologies can be used alone or in conjunction with other techniques described herein for detection of methylation status. Those of skill in the art, having reviewed the present specification, will understand how to combine various amplification technologies known in the art and/or described herein together with various other technologies for methylation status determination known in the art and/or provided herein. Amplification technologies include, without limitation, PCR, e.g., quantitative PCR (qPCR), real-time PCR, and/or digital PCR. Those of skill in the art will appreciate that polymerase amplification can multiplex amplification of multiple targets in a single reaction. PCR amplicons are typically 100 to 2000 base pairs in length. In various instances e.g., as set forth herein, an amplification technology is sufficient to determine methylations status.

Digital PCR (dPCR) based methods involve dividing and distributing a sample across wells of a plate with 96-, 384-, or more wells, or in individual emulsion droplets (ddPCR) e.g., using a microfluidic device, such that some wells include one or more copies of template and others include no copies of template. Thus, the average number of template molecules per well is less than one prior to amplification. The number of wells in which amplification of template occurs provides a measure of template concentration. If the sample has been contacted with MSRE, the number of wells in which amplification of template occurs provides a measure of the concentration of methylated template.

In various embodiments e.g., as set forth herein, a fluorescence-based real-time PCR assay, such as MethyLight™, can be used to measure methylation status (see, e.g., Campan 2018 Methods Mol Biol. 1708:497-513, which is incorporated by reference). MethyLight is a quantitative, fluorescence-based, real-time PCR method to sensitively detect and quantify DNA methylation of candidate regions of the genome. MethyLight is uniquely suited for detecting low-frequency methylated DNA regions against a high background of unmethylated DNA, as it combines methylation-specific priming with methylation-specific fluorescent probing. Additionally, MethyLight can be combined with Digital PCR, for the highly sensitive detection of individual methylated molecules, with use in disease detection and screening.

Real-time PCR-based methods for use in determining methylation status typically include a step of generating a standard curve for unmethylated DNA based on analysis of external standards. A standard curve can be constructed from at least two points and can permit comparison of a real-time Ct value for digested DNA and/or a real-time Ct value for undigested DNA to known quantitative standards. In particular instances e.g., as set forth herein, sample Ct values can be determined for MSRE-digested and/or undigested samples or sample aliquots, and the genomic equivalents of DNA can be calculated from the standard curve. Ct values of MSRE-digested and undigested DNA can be evaluated to identify amplicons digested (e.g., efficiently digested; e.g., yielding a Ct value of 45). Amplicons not amplified under either digested or undigested conditions can also be identified. Corrected Ct values for amplicons of interest can then be directly compared across conditions to establish relative differences in methylation status between conditions. Alternatively or additionally, delta- difference between the Ct values of digested and undigested DNA can be used to establish relative differences in methylation status between conditions.

Methods of measuring methylation status can include, without limitation, massively parallel sequencing (e.g., next-generation sequencing) to determine methylation state, e.g., sequencing by- synthesis, real-time (e.g., single-molecule) sequencing, bead emulsion sequencing, nanopore sequencing, or other sequencing techniques known in the art. In some embodiments, e.g., as set forth herein, a method of measuring methylation status can include whole-genome sequencing, e.g., with base-pair resolution.

In certain particular embodiments e.g., as set forth herein, MSRE-qPCR, among other techniques, can be used to determine the methylation status of a colorectal cancer methylation biomarker that is or includes a single methylation locus. In certain particular embodiments e.g., as set forth herein, MSRE-qPCR, among other techniques, can be used to determine the methylation status of a colorectal cancer and/or advanced adenoma methylation biomarker that is or includes two or more methylation loci. In certain particular embodiments e.g., as set forth herein, MSRE- qPCR, among other techniques, can be used to determine the methylation status of a colorectal cancer and/or advanced adenoma methylation biomarker that is or includes a single differentially methylated region (DMR). In certain particular embodiments e.g., as set forth herein, MSRE-qPCR, among other techniques, can be used to determine the methylation status of a colorectal cancer and/or advanced adenoma methylation biomarker that is or includes two or more DMRs. In certain particular embodiments e.g., as set forth herein, MSRE-qPCR, among other techniques, can be used to determine the methylation status of a colorectal cancer and/or advanced adenoma methylation biomarker that is or includes a single methylation site. In certain particular embodiments e.g., as set forth herein, MSRE-qPCR, among other techniques, can be used to determine the methylation status of a colorectal cancer and/or advanced adenoma methylation biomarker that is or includes two or more methylation sites. In various embodiments e.g., as set forth herein, a colorectal cancer and/or advanced adenoma methylation biomarker can be any colorectal cancer and/or advanced adenoma methylation biomarker provided herein. The present disclosure includes, among other things, oligonucleotide primer pairs for amplification of DMRs, e.g., for amplification of DMRs identified in Table 5.

In certain particular embodiments e.g., as set forth herein,, a cfDNA sample is derived from subject plasma and contacted with MSREs (methylation sensitive restriction enzymes) that are or include one or more of Acil, Hin6l, HpyCH4IV, and Hpall (e.g., Acil, Hin6l, and HpyCH4IV). The digested sample can be amplified with oligonucleotide primer pairs of one or more DMRs, e.g., with one or more oligonucleotide primer pairs provided in Table 5 below. Table 5 identifies the chromosome number (Chr. No.), unique ID (UID), start position of the genetic region on the chromosome (start position), end position of the genetic region on the chromosome (end position), the width of the region (Seq. Width), the sequence ID numbers (SEQ ID NO.) of the forward primer (Fp) and the reverse primer (Rp) used in MSRE-qPCR, and the SEQ ID NO. of the DNA region amplified by the forward and reverse primer. Digested DNA, e.g., preamplified digested DNA, can be quantified with qPCR with oligonucleotide primer pairs of one or more DMRs, e.g., with one or more oligonucleotide primer pairs provided in Table 5 below. qPCR Ct values can then be determined and used to determine methylation status of each DMR amplicon. Lower Ct values (and thus higher 45 - Ct values) correspond to higher methylation status, demonstrating hypermethylation in subjects with colorectal cancer and/or advanced adenoma.

Table 5. 40 Highly Ranked DMRs identified with corresponding primer pairs.

It will be appreciated by those of skill in the art that oligonucleotide primer pairs provided in Table 5 can be used in accordance with any combination of colorectal cancer and/or advanced adenoma methylation biomarkers identified herein. The skilled artisan will be aware that the oligonucleotide primer pairs of Table 5 may be individually included or not included in a given analysis in order to analyze particularly desired combination of DRMs.

The person of skill in the art will further appreciate that while other oligonucleotide primer pairs may be used, selection and pairing of oligonucleotide primers to produce useful DMR amplicons is non-trivial and represents a substantial contribution.

Those of skill in the art will further appreciate that methods, reagents, and protocols for qPCR are well-known in the art. Unlike traditional PCR, qPCR is able to detect the production of amplicons over time in amplification (e.g., at the end of each amplification cycle), often by use of an amplification-responsive fluorescence system, e.g., in combination with a thermocycler with fluorescence-detection capability. Two common types of fluorescent reporters used in qPCR include (i) double-stranded DNA binding dyes that fluoresce substantially more brightly when bound than when unbound; and (ii) labeled oligonucleotides (e.g., labeled oligonucleotide primers or labeled oligonucleotide probes).

Those of skill in the art will appreciate that in embodiments in which a plurality of methylation loci (e.g., a plurality of DMRs) are analyzed for methylation status in a method of screening for colorectal cancer provided herein, methylation status of each methylation locus can be measured or represented in any of a variety of forms, and the methylation statuses of a plurality of methylation loci (preferably each measured and/or represented in a same, similar, or comparable manner) be together or cumulatively analyzed or represented in any of a variety of forms. In various embodiments e.g., as set forth herein, methylation status of each methylation locus can be measured as a Ct value. In various embodiments e.g., as set forth herein, methylation status of each methylation locus can be represented as the difference in Ct value between a measured sample and a reference. In various embodiments e.g., as set forth herein, methylation status of each methylation locus can be represented as a qualitative comparison to a reference, e.g., by identification of each methylation locus as hypermethylated or not hypermethyated.

In some embodiments e.g., as set forth herein in which a single methylation locus is analyzed, hypermethylation of the single methylation locus constitutes a diagnosis that a subject is suffering from or possibly suffering from colorectal cancer and/or advanced adenomas, while absence of hypermethylation of the single methylation locus constitutes a diagnosis that the subject is likely not suffering from colorectal cancer or advanced adenomas. In some embodiments e.g., as set forth herein, hypermethylation of a single methylation locus (e.g., a single DMR) of a plurality of analyzed methylation loci constitutes a diagnosis that a subject is suffering from or possibly suffering from colorectal cancer or an advanced adenoma, while the absence of hypermethylation at any methylation locus of a plurality of analyzed methylation loci constitutes a diagnosis that a subject is likely not suffering from either affliction. In some embodiments e.g., as set forth herein, hypermethylation of a determined percentage (e.g., a predetermined percentage) of methylation loci (e.g., at least 10% (e.g., at least 10%, at least 20%, at least 30%, at least 40%, at least 50%, at least 60%, at least 70%, at least 80%, at least 90%, or 100%)) of a plurality of analyzed methylation loci constitutes a diagnosis that a subject is suffering from or possibly suffering from colorectal cancer, while the absence of hypermethylation of a determined percentage (e.g., a predetermined percentage) of methylation loci (e.g., at least 10% (e.g., at least 10%, at least 20%, at least 30%, at least 40%, at least 50%, at least 60%, at least 70%, at least 80%, at least 90%, or 100%)) of a plurality of analyzed methylation loci constitutes a diagnosis that a subject is not likely suffering from colorectal cancer or advanced adenomas. In some embodiments e.g., as set forth herein, hypermethylation of a determined number (e.g., a predetermined number) of methylation loci (e.g., at least 1 , 2, 3, 4, 5, 6, 7, 8, 9, 10, 11 , 12, 13, 14, 15, 16, 17, 18, 19, 20, 21 , 22, 23, 24, 25, 26, 27, 28, 29, 30, 31 , 32, 33, 34, 35, 36, 37, 38, 39, or 40 DMRs) of a plurality of analyzed methylation loci (e.g., 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 21, 22, 23, 24, 25, 26, 27, 28, 29, 30, 31 , 32, 33, 34, 35, 36, 37, 38, 39, or 40 methylation loci DMRs) constitutes a diagnosis that a subject is suffering from or possibly suffering from colorectal cancer and/or advanced adenomas, while the absence of hypermethylation of a determined number (e.g., a predetermined number) of methylation loci (e.g., at least 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 21 , 22, 23, 24, 25, 26, 27, 28, 29, 30, 31 , 32, 33, 34, 35, 36, 37, 38, 39, or 40 DMRs) of a plurality of analyzed methylation loci (e.g., 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 21 , 22, 23, 24, 25, 26, 27, 28, 29, 30, 31 , 32, 33, 34, 35, 36, 37, 38, 39, or 40 DMRs) constitutes a diagnosis that a subject is not likely suffering from colorectal cancer or advanced adenoma.

In some embodiments e.g., as set forth herein, methylation status of a plurality of methylation loci (e.g., a plurality of DMRs) is measured qualitatively or quantitatively and the measurement for each of the plurality of methylation loci are combined to provide a diagnosis. In some embodiments e.g., as set forth herein, the quantitatively measured methylation status of each of a plurality of methylation loci is individually weighted, and weighted values are combined to provide a single value that can be comparative to a reference in order to provide a diagnosis. To provide but one example of such an approach, a support vector machine (SVM) algorithm can be used to analyze the methylation statuses of a plurality of methylation loci of the present disclosure to produce a diagnosis. At least one objective of the support vector machine algorithm is to identify a hyperplane in an N-dimensional space (N — the number of features) that distinctly classifies the data points with the objective to find a plane that has the maximum margin, i.e., the maximum distance between data points of both classes. As discussed in the present Examples, an SVM model is built on marker values (e.g., Ct values) derived from a training sample set (e.g., the training subject group) that are transformed to support vector values upon which a prediction is made. In application of the SVM model to new samples of a validation sample set, samples will be mapped onto vectoral space the model and categorized as having a probability of belonging to a first condition (e.g., the control group), a second condition (e.g., the group diagnosed with colorectal cancer), or a third group (e.g., the group diagnosed with advanced adenomas), e.g., based on each new sample’s location relative to the gap between the conditions. Those of skill in the art will appreciate that, once relevant compositions and methods have been identified, vector values can be used in conjunction with an SVM algorithm defined by predict () function of R-package (see Hypertext Transfer Protocol Secure (HTTPS) ://cran.r- project.org/web/packages/e1071/index.html, the SVM of which is hereby incorporated by reference) to easily generate a prediction on a new sample. Accordingly, with compositions and methods for colorectal cancer and/or advanced adenoma diagnosis disclosed herein in hand (and only then), generation of a predictive model utilizing algorithm input information in combination to predict () function of R-package (see Hypertext Transfer Protocol Secure (HTTPS) ://cran.r- project.org/web/packages/e1071/index.html, the SVM of which is hereby incorporated by reference) to provide colorectal cancer and/or advanced adenoma diagnosis would be straightforward. Those of skill in the art will appreciate that, with the present disclosure in hand, generation of SVM vectors can be accomplished according to methods provided herein and otherwise known in the art.

Applications

Methods and compositions of the present disclosure can be used in any of a variety of applications. For example, methods and compositions of the present disclosure can be used to screen, or aid in screening for, colorectal cancer or advanced adenomas. In various instances e.g., as set forth herein, screening using methods and compositions of the present disclosure can detect any stage of colorectal cancer, including without limitation early-stage colorectal cancer, and can detect advanced adenomas. In some embodiments e.g., as set forth herein, colorectal cancer and advanced adenoma screening using methods and compositions of the present disclosure is applied to individuals 50 years of age or older, e.g., 50, 55, 60, 65, 70, 75, 80, 85, or 90 years or older. In some embodiments e.g., as set forth herein, colorectal cancer and advanced adenoma screening using methods and compositions of the present disclosure is applied to individuals 20 years of age or older, e.g., 20, 25, 30, 35, 40, 45, 50, 55, 60, 65, 70, 75, 80, 85, or 90 years or older. In some embodiments e.g., as set forth herein, colorectal cancer and/or advanced adenoma screening using methods and compositions of the present disclosure is applied to individuals 20 to 50 years of age, e.g., 20 to 30 years of age, 20 to 40 years of age, 20 to 50 years of age, 30 to 40 years of age, 30 to 50 years of age, or 40 to 50 years of age. In various embodiments e.g., as set forth herein, colorectal cancer and/or advanced adenoma screening using methods and compositions of the present disclosure is applied to individuals experiencing abdominal pain or discomfort, e.g., experiencing undiagnosed or incompletely diagnosed abdominal pain or discomfort. In various embodiments e.g., as set forth herein, colorectal cancer and/or advanced adenoma screening using methods and compositions of the present disclosure is applied to individuals experiencing no symptoms likely to be associated with colorectal cancer. Thus, in certain embodiments e.g., as set forth herein, colorectal cancer screening using methods and compositions of the present disclosure is fully or partially preventative or prophylactic, at least with respect to later or non-early stages of colorectal cancer.

In various embodiments e.g., as set forth herein, colorectal cancer and/or advanced adenoma screening using methods and compositions of the present disclosure can be applied to an asymptomatic human subject. As used herein, a subject can be referred to as “asymptomatic” if the subject does not report, and/or demonstrate by non- invasively observable indicia (e.g., without one, several, or all of device-based probing, tissue sample analysis, bodily fluid analysis, surgery, or colorectal cancer screening), sufficient characteristics of colorectal cancer and/or advanced adenomas to support a medically reasonable suspicion that the subject is likely suffering from colorectal cancer and/or advanced adenomas. Detection of early stage colorectal cancer or the presence of advanced adenomas is particularly likely in asymptomatic individuals screened in accordance with methods and compositions of the present disclosure.

In various embodiments e.g., as set forth herein, colorectal cancer and/or screening using methods and compositions of the present disclosure can be applied to a symptomatic human subject. As used herein, a subject can be referred to as “symptomatic” if the subject report, and/or demonstrates by non-invasively observable indicia (e.g., without one, several, or all of device-based probing, tissue sample analysis, bodily fluid analysis, surgery, or colorectal cancer screening), sufficient characteristics of colorectal cancer and/or advanced adenomas to support a medically reasonable suspicion that the subject is likely suffering from colorectal cancer, advanced adenomas, and/or from cancer. Symptoms of colorectal cancer and advanced adenomas can include, without limitation, change in bowel habits (diarrhea, constipation, or narrowing of the stool) that are persistent (e.g., lasting more than 3 days), feeling of a need to have a bowel movement which feeling is not relieved upon bowel movement, rectal bleeding (e.g., with bright red blood), blood in stool (which can cause stool to appear dark), abdominal cramping, abdominal pain, weakness, fatigue, unintended weight loss, anemia, and combinations thereof. Those of skill in the art will appreciate that individual symptoms that would not alone indicate or raise a suspicion of colorectal cancer and/or advanced adenomas may do so when presented in combination, e.g., a combination of abdominal cramping and blood in stool, to provide but one non-limiting example.

Those of skill in the art will appreciate that regular, preventative, and/or prophylactic screening for colorectal cancer and advanced adenomas improves diagnosis of colorectal cancer, including and/or particularly early stage cancer. As noted above, early stage cancers include, according to at least one system of cancer staging, Stages 0 to II C of colorectal cancer. Thus, the present disclosure provides, among other things, methods and compositions particularly useful for the diagnosis and treatment of early stage colorectal cancer. Generally, and particularly in embodiments (e.g., as set forth herein) in which colorectal cancer screening in accordance with the present disclosure is carried out annually, and/or in which a subject is asymptomatic at time of screening, methods and compositions of the present invention are especially likely to detect early stage colorectal cancer and/or advanced adenomas.

In various embodiments e.g., as set forth herein, colorectal cancer or advanced adenoma screening in accordance with the present disclosure is performed once for a given subject or multiple times for a given subject. In various embodiments e.g., as set forth herein, screening in accordance with the present disclosure is performed on a regular basis, e.g., every six months, annually, every two years, every three years, every four years, every five years, or every ten years.

In various embodiments e.g., as set forth herein, screening for colorectal cancer and/or advanced adenomas using methods and compositions disclosed herein will provide a diagnosis of colorectal cancer and/or advanced adenomas. In other instances e.g., as set forth herein, screening for colorectal cancer and/or advanced adenomas using methods and compositions disclosed herein will be indicative of colorectal cancer diagnosis (e.g., through finding advanced adenomas) but not definitive for colorectal cancer and/or advanced adenoma diagnosis. In various instances e.g., as set forth herein in which methods and compositions of the present disclosure are used to screen for colorectal cancer and/or advanced adenomas, screening using methods and compositions of the present disclosure can be followed by a further diagnosis- confirmatory assay, which further assay can confirm, support, undermine, or reject a diagnosis resulting from prior screening, e.g., screening in accordance with the present disclosure. As used herein, a diagnosis-confirmatory assay can be a colorectal cancer and/or advanced adenoma assay that provides a diagnosis recognized as definitive by medical practitioners, e.g., a colonoscopy-based diagnosed, or a colorectal cancer and/or advanced adenoma assay that substantially increases or decreases the likelihood that a prior diagnosis was correct, e.g., a diagnosis resulting from screening in accordance with the present disclosure. Diagnosis-confirmatory assays could include existing screening technologies, which are generally in need of improvement with respect to one or more of sensitivity, specificity, and non-invasiveness, particularly in the detection of early stage colorectal cancers.

In some instances e.g., as set forth herein, a diagnosis-confirmatory assay is a test that is or includes a visual or structural inspection of subject tissues, e.g., by colonoscopy. In some embodiments e.g., as set forth herein, colonoscopy includes or is followed by histological analysis. Visual and/or structural assays for colorectal cancer can include inspection of the structure of the colon and/or rectum for any abnormal tissues and/or structures. Visual and/or structural inspection can be conducted, for example, by use of a scope via the rectum or by CT-scan. In some instances e.g., as set forth herein, a diagnosis-confirmatory assay is a colonoscopy, e.g., including or followed by histological analysis. According to some reports, colonoscopy is currently the predominant and/or most relied upon diagnosis-confirmatory assay.

Another visual and/or structural diagnosis confirmatory assay based on computer tomography (CT) is CT colonography, sometimes referred to as virtual colonoscopy. A CT scan utilizes numerous x-ray images of the colon and/or rectum to produce dimensional representations of the colon. Although useful as a diagnosis-confirmatory assay, some reports suggest that CT colonography is not sufficient for replacement of colonoscopy, at least in part because a medical practitioner has not physically accessed the subject’s colon to obtain tissue for histological analysis.

Another diagnosis-confirmatory assay can be a sigmoidoscopy. In sigmoidoscopy, a sigmoidoscope is used via the rectum to image portions of the colon and/or rectum. According to some reports, sigmoidoscopy is not widely used.

One particular screening technology is a stool-based screening test (Cologuard® (Exact Sciences Corporation, Madison, Wl, United States), which combines an FIT assay with analysis of DNA for abnormal modifications, such as mutation and methylation. The Cologuard® test demonstrates improved sensitivity as compared to FIT assay alone, but can be clinically impracticable or ineffective due to low compliance rates, which low compliance rates are at least in part due to subject dislike of using stool-based assays (see, e.g., doi: 10.1056/NEJMc1405215 (e.g., 2014 N Engl J Med. 371(2): 184- 188)). The Cologuard® test appears to leave almost half of the eligible population out of the screening programs (see, e.g., van der Vlugt 2017 Br J Cancer. 116(1):44-49). Use of screening as provided herein, e.g., by a blood-based analysis, would increase the number of individuals electing to screen for colorectal cancer (see, e.g., Adler 2014 BMC Gastroenterol. 14:183; Liles 2017 Cancer Treatment and Research Communications 10: 27-31). To present knowledge, only one existing screening technology for colorectal cancer, Epiprocolon, is FDA-approved and CE-IVD marked and is blood-based. Epiprocolon is based on hypermethylation of SEPT9 gene. The Epiprocolon test suffers from low accuracy for colorectal cancer detection with sensitivity of 68% and advanced adenoma sensitivity of only 22% (see, e.g., Potter 2014 Clin Chem. 60(9):1183-91). There is need in the art for, among other things, a non-invasive colorectal cancer and advanced adenoma screen that will likely achieve high subject adherence with high and/or improved specificity and/or sensitivity.

In various embodiments e.g., as set forth herein, screening in accordance with methods and compositions of the present disclosure reduces colorectal cancer mortality, e.g., by early colorectal cancer diagnosis, e.g., through the detection of advanced adenomas. Data supports that colorectal cancer screening reduces colorectal cancer mortality (see, e.g., Shaukat 2013 N Engl J Med. 369(12): 1106-14). Moreover, colorectal cancer is particularly difficult to treat at least in part because colorectal cancer, absent timely screening, may not be detected until cancer is past early stages. For at least this reason, treatment of colorectal cancer is often unsuccessful. To maximize population-wide improvement of colorectal cancer outcomes, utilization of screening in accordance with the present disclosure can be paired with, e.g., recruitment of eligible subjects to ensure widespread screening.

In various embodiments e.g., as set forth herein, screening for colorectal cancer and/or advanced adenomas including one or more methods and/or compositions disclosed herein is followed by treatment of colorectal cancer, e.g., treatment of early stage colorectal cancer. In various embodiments e.g., as set forth herein, treatment of colorectal cancer, e.g., early stage colorectal cancer, includes administration of a therapeutic regimen including one or more of surgery, radiation therapy, and chemotherapy. In various embodiments e.g., as set forth herein, treatment of colorectal cancer, e.g., early stage colorectal cancer, includes administration of a therapeutic regimen including one or more of treatments provided herein for treatment of stage 0 colorectal cancer, stage I colorectal cancer, and/or stage II colorectal cancer.

In various embodiments e.g., as set forth herein, screening for advanced adenomas and/or colorectal cancer is a stool-based assay. Typically, stool-based assays, when used in place of visual or structural inspection, are recommended to be utilized at a greater frequency than would be required if using visual or structural inspection. In some instances e.g., as set forth herein, a screening assay is a guiac-based fecal occult blood test or a fecal immunochemical test (gFOBTs/FITs) (see, e.g., Navarro 2017 World J Gastroenterol. 23(20):3632-3642, which is herein incorporated by reference with respect to colorectal cancer assays). FOBTs and FITs are sometimes used for diagnosis of colorectal cancer (see, e.g., Nakamura 2010 J Diabetes Investig. Oct 19; 1 (5):208-11 , which is herein incorporated by reference with respect to colorectal cancer assays). FIT is based on detection of occult blood in stool, the presence of which is often indicative of colorectal cancer or advanced adenoma but is often not in sufficient volume to permit identification by the unaided eye. For example, in a typical FIT, the test utilizes hemoglobin-specific reagent to test for occult blood in a stool sample. In various instances e.g., as set forth herein, FIT kits are suitable for use by individuals in their own homes. FIT may be recommended for use on an annual basis. FIT is generally not relied upon to provide sufficient diagnostic information for conclusive diagnosis of colorectal cancer or advanced adenomas.

In various embodiments e.g., as set forth herein, screening for advanced adenomas and/or colorectal cancer also includes gFOBT, which is designed to detect occult blood in stool by chemical reaction. Like FIT, gFOBT may be recommended for use on an annual basis. gFOBT is generally not relied upon to provide sufficient diagnostic information for conclusive diagnosis of colorectal cancer or advanced adenomas.

In some instances e.g., as set forth herein, a screening assay can also include stool DNA testing. Stool DNA testing for colorectal cancer or advanced adenomas can be designed to identify DNA sequences characteristic of colorectal cancer and/or advanced adenomas in stool samples. When used in the absence of other diagnosis- confirmatory assays, stool DNA testing may be recommended for use every three years. Stool DNA testing is generally not relied upon to provide sufficient diagnostic information for conclusive diagnosis of colorectal cancer and/or advanced adenomas.

In various embodiments e.g., as set forth herein, treatment of colorectal cancer includes treatment of early stage colorectal cancer, e.g., stage 0 colorectal cancer or stage I colorectal cancer, by one or more of surgical removal of cancerous tissue e.g., by local excision (e.g., by a colonoscope), partial colectomy, or complete colectomy.

In various embodiments e.g., as set forth herein, treatment of colorectal cancer includes treatment of early stage colorectal cancer, e.g., stage II colorectal cancer, by one or more of surgical removal of cancerous tissue (e.g., by local excision (e.g., by colonoscope), partial colectomy, or complete colectomy), surgery to remove lymph nodes near to identified colorectal cancer tissue, and chemotherapy (e.g., administration of one or more of 5-FU and leucovorin, oxaliplatin, or capecitabine).

In various embodiments e.g., as set forth herein, treatment of colorectal cancer includes treatment of stage III colorectal cancer, by one or more of surgical removal of cancerous tissue (e.g., by local excision (e.g., by colonoscopy-based excision), partial colectomy, or complete colectomy), surgical removal of lymph nodes near to identified colorectal cancer tissue, chemotherapy(e.g., administration of one or more of 5-FU, leucovorin, oxaliplatin, capecitabine, e.g., in a combination of (i) 5-FU and leucovorin, (ii) 5-FU, leucovorin, and oxaliplatin (e.g., FOLFOX), or (iii) capecitabine and oxaliplatin (e.g., CAPEOX)), and radiation therapy.

In various embodiments e.g., as set forth herein, treatment of colorectal cancer includes treatment of stage IV colorectal cancer, by one or more of surgical removal of cancerous tissue (e.g., by local excision (e.g., by colonoscope), partial colectomy, or complete colectomy), surgical removal of lymph nodes near to identified colorectal cancer tissue, surgical removal of metastases, chemotherapy (e.g., administration of one or more of 5-FU, leucovorin, oxaliplatin, capecitabine, irinotecan, VEGF- targeted therapeutic agent (e.g., bevacizumab, ziv-aflibercept, or ramucirumab), EGFR-targeted therapeutic agent (e.g., cetuximab or panitumumab), Regorafenib, trifluridine, and tipiracil, e.g., in a combination of or including (i) 5-FU and leucovorin, (ii) 5-FU, leucovorin, and oxaliplatin (e.g., FOLFOX), (iii) capecitabine and oxaliplatin (e.g., CAPEOX), (iv) leucovorin, 5-FU, oxaliplatin, and irinotecan (FOLFOXIRI), and (v) trifluridine and tipiracil (Lonsurf)), radiation therapy, hepatic artery infusion (e.g., if cancer has metastasized to liver), ablation of tumors, embolization of tumors, colon stent, colorectomy, colostomy (e.g., diverting colostomy), and immunotherapy (e.g., pembrolizumab).

Those of skill in the art that treatments of colorectal cancer provided herein can be utilized, e.g., as determined by a medical practitioner, alone or in any combination, in any order, regimen, and/or therapeutic program. Those of skill in the art will further appreciate that advanced treatment options may be appropriate for earlier stage cancers in subjects previously having suffered a cancer or colorectal cancer, e.g., subjects diagnosed as having a recurrent colorectal cancer.

In some embodiments e.g., as set forth herein, methods and compositions for colorectal cancer and advanced adenoma screening provided herein can inform treatment and/or payment ( e.g reimbursement for or reduction of cost of medical care, such as screening or treatment) decisions and/or actions, e.g., by individuals, healthcare facilities, healthcare practitioners, health insurance providers, governmental bodies, or other parties interested in healthcare cost.

In some embodiments e.g., as set forth herein, methods and compositions for colorectal cancer and advanced adenoma screening provided herein can inform decision making relating to whether health insurance providers reimburse a healthcare cost payer or recipient (or not), e.g., for (1) screening itself (e.g., reimbursement for screening otherwise unavailable, available only for periodic/regular screening, or available only for temporally- and/or incidentally- motivated screening); and/or for (2) treatment, including initiating, maintaining, and/or altering therapy, e.g., based on screening results. For example, in some embodiments e.g., as set forth herein, methods and compositions for colorectal cancer and advanced adenoma screening provided herein are used as the basis for, to contribute to, or support a determination as to whether a reimbursement or cost reduction will be provided to a healthcare cost payer or recipient. In some instances e.g., as set forth herein, a party seeking reimbursement or cost reduction can provide results of a screen conducted in accordance with the present specification together with a request for such reimbursement or cost reduction of a healthcare cost. In some instance e.g., as set forth herein s, a party making a determination as to whether or not to provide a reimbursement or cost reduction of a healthcare cost will reach a determination based in whole or in part upon receipt and/or review of results of a screen conducted in accordance with the present specification.

For the avoidance of any doubt, those of skill in the art will appreciate from the present disclosure that methods and compositions for colorectal cancer and/or advanced adenoma diagnosis of the present specification are at least for in vitro use. Accordingly, all aspects and embodiments of the present disclosure can be performed and/or used at least in vitro.

Kits

The present disclosure includes, among other things, kits including one or more compositions for use in colorectal cancer and/or advanced adenoma screening as provided herein, optionally in combination with instructions for use thereof in colorectal cancer screening. In various embodiments, e.g., as set forth herein, a kit for screening of colorectal cancer and/or advanced adenomas can include one or more of: one or more oligonucleotide primers (e.g., one or more oligonucleotide primer pairs, e.g., as found in Table 5), one or more MSREs, one or more reagents for qPCR (e.g., reagents sufficient for a complete qPCR reaction mixture, including without limitation dNTP and polymerase), and instructions for use of one or more components of the kit for colorectal cancer screening. In various embodiments, a kit for screening of colorectal cancer can include one or more of: one or more oligonucleotide primers (e.g., one or more oligonucleotide primer pairs, e.g., as found in Table 5), one or more bisulfite reagents, one or more reagents for qPCR (e.g., reagents sufficient for a complete qPCR reaction mixture, including without limitation dNTP and polymerase), and instructions for use of one or more components of the kit for colorectal cancer screening.

In certain embodiments, a kit of the present disclosure includes at least one oligonucleotide primer pair for amplification of a methylation locus and/or DMR as disclosed herein.

In some instances e.g., as set forth herein, a kit of the present disclosure includes one or more oligonucleotide primer pairs for amplification of one or more methylation regions of the present disclosure. In some instances e.g., as set forth herein, kit of the present disclosure includes one or more oligonucleotide primer pairs for amplification of one or more methylation regions that are or include all or a portion of one or more genetic regions provided in Table 1. In some particular instances e.g., as set forth herein, a kit of the present disclosure includes oligonucleotide primer pairs for a plurality of methylation regions that each include (all or a portion of) a genetic region identified in Table 1 , the plurality of methylation regions including (all or a portion of), e.g. 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 21 , 22, 23, 24, 25, 26, 27, 28, 29, 30, 31 , 32, 33, 34, 35, 36, 37, 38, 39, 40, 41, 42, 43, 44, 45, 46, 47, 48, 49, 50, 51, 52, 53, 54, 55, 56, 57, 58, 59, 60, 61, 62, 63, 64, 65, 66, 67, 68, or 69 of the methylation regions provided in any of Tables 1 to 4.

In some instances e.g., as set forth herein, a kit of the present disclosure includes one or more oligonucleotide primer pairs for amplification of one or more DMRs of the present disclosure. In some instances e.g., as set forth herein, kit of the present disclosure includes one or more oligonucleotide primer pairs for amplification of one or more DMRs that include (all or a portion of) a gene identified in Table 1. In some particular embodiments, a kit of the present disclosure includes oligonucleotide primer pairs for a plurality of DMRs, wherein each of the DMRs include (all or a portion of) a genetic region identified in Table 1 , e.g., 1 , 2, 3, 4, 5, 6, 7, 8, 9, 10, 11 , 12, 13, 14, 15, 16, 17, 18, 19, 20, 21 , 22, 23, 24, 25, 26, 27, 28, 29, 30, 31, 32, 33, 34, 35, 36, 37, 38,

39, 40, 41 , 42, 43, 44, 45, 46, 47, 48, 49, 50, 51, 52, 53, 54, 55, 56, 57, 58, 59, 60, 61,

62, 63, 64, 65, 66, 67, 68, or 69 DMRs, e.g., in accordance with any one of Tables 1 to 4.

In some instances e.g., as set forth herein, kit of the present disclosure includes one or more oligonucleotide primer pairs for amplification of one or more DMRs of Table 5. In some particular instances e.g., as set forth herein, a kit of the present disclosure includes oligonucleotide primer pairs for a plurality of DMRs of Table 5, the plurality of DMRs including (all or a portion of), e.g. 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16,

17, 18, 19, 20, 21 , 22, 23, 24, 25, 26, 27, 28, 29, 30, 31 , 32, 33, 34, 35, 36, 37, 38, 39, or 40 DMRs of Table 1 , e.g., as provided in any of Tables 2 to 4.

In various embodiments e.g., as set forth herein, a kit of the present disclosure includes one or more oligonucleotide primer pairs provided in Table 5. Those of skill in the art will appreciate that oligonucleotide primer pairs provided in Table 5 can be provided in any combination of one or more oligonucleotide primer pairs, e.g., in a combination as provided in any one of Tables 2-4.

A kit of the present disclosure can further include one or more MSREs individually or in a single solution. In various embodiments, one or more MSREs are selected from the set of MSREs including Acil, Hin6l, HpyCH4IV, and Hpall (e.g., such that the kit includes Acil, Hin6l, and HpyCH4IV, either individually or in a single solution). In certain embodiments, a kit of the present disclosure includes one or more reagents for qPCR (e.g., reagents sufficient for a complete qPCR reaction mixture, including without limitation dNTP and polymerase).

EXAMPLES

The present Examples confirm that the present disclosure provides methods and compositions for, among other things, screening for and treatment of colorectal cancer and/or advanced adenomas. The present Examples further demonstrate that compositions and methods provided herein provide a remarkably high degree of sensitivity and specificity in screening and/or treatment of colorectal cancer and/or advanced adenomas. Also provided are clinical studies comparing methylation of biomarkers in samples from subjects diagnosed as having colorectal cancer and methylation of biomarkers in samples from control subjects, further demonstrating screening for colorectal cancer including methods and/or compositions of the present disclosure. Samples of the present Examples are humans or of human origin. Example 1. Identification of methylation biomarkers associated with colorectal cancer The present Example includes identification of hypermethylation of CpG regions of DMRs in colorectal cancer and advanced adenoma as compared to healthy tissue. In particular, experiments of the present example examined colorectal tissue samples from a total of 150 subjects. The groupings of the subjects were as follows: (i) 52 subjects previously diagnosed as suffering with colorectal cancer, (ii) 33 subjects diagnosed as suffering with advanced adenomas, and (iii) 65 healthy colon tissue samples obtained from the subset of the 52 patients diagnosed as suffering with colorectal cancer and the 33 subjects diagnosed as suffering with advanced adenomas. Tissue samples were of fresh frozen tissue.

DNA of the samples were analyzed with whole genome bisulfite sequencing using the NovaSeq™ 6000 Sequencing system from lllumina. Whole genome bisulfite sequencing has been described previously herein. In general, whole genome bisulfite sequencing involves treatment of the DNA samples with a bisulfite (e.g., sodium bisulfite) prior to sequencing the genome using any one of a number of next generation technologies as previously discussed.

The samples had an average sequencing coverage of 37.5x, meaning that, a given region of the sequenced genome had been uniquely sequenced approximately 37-38 times. Having an average coverage greater than 30x indicates that the sequencing has been conducted with clinical grade (i.e., high) reliability.

The raw sequencing files obtained from the samples were then processed to determine the differentially methylated regions (DMRs) as compared to the control tissue samples. First, the raw sequences were aligned with the reference genome of GRCh38 (Genome Research Consortium human build 38) and deduplicated using Bismark Bisulfite Mapper. Bismark output the methylation call files for each of the samples. These methylation call files contain a percent methylation score per base output. The methylation call output files were then further analyzed using MethylKit. MethylKit was used to compare the output files from colorectal cancer tissues to control tissues and the output files from the advanced adenoma tissues to control tissues. These comparisons resulted in the identification of DMRs for both colorectal cancer and advanced adenoma samples. The identified DMRs output from MethylKit were considered to be a region where at least 3 CpGs are present with maximum distance between the CpGs being 200 bp. The minimum methylation percentage difference between control and case was set to 10%. The DMRs were then filtered for regions of hypermethylation in the advanced adenoma and colorectal cancer samples with respect to the control samples. The DMRs were again filtered to select for a higher number of methylated CpGs per region length. A minimum of 5 CpGs with maximum of 200 bp between two adjacent methylated CpGs was considered. Additionally, a highest average methylation percent difference between the condition (e.g., colorectal cancer or advanced adenoma) and the control was used by excluding regions where the difference between the methylation of the condition and the control was less than 25%.

The processing of the resulted in a list of 69 DMRs (i.e., as seen in Table 6 below), which were selected for further, targeted assay development. As can be seen below in Table 6, each of the DMRs are identified by their sequence ID (SEQ ID NO) corresponding to their sequence as provided herein, the chromosome number the DMR is on, the start and end base pairs of the DMR on the chromosome, the width of the DMR region (region width), and the annotated name of the one (or more) genes falling within the DMR region (if available). The start and end base pairs and chromosome number of the DMRs correspond to locations on the reference genome of GRCh38. The annotations of the gene names are according to Ensemble genome browser 98. Table 6. 69 DMRs identified for targeted assay development.

Example 2: Development of cell-free DNA assay for methylation biomarkers by MSRE- qPCR

The present Example develops an assay for determining the methylation status of colorectal cancer and advanced adenoma methylation biomarkers based on circulating cell free DNA (cfDNA). cfDNA is incomplete and fragmented, and the mechanism by which the cfDNA is transmitted from cancer cells to blood (as a portion called circulating tumor DNA) is unknown. At least because the 69 methylation biomarkers of Example 1 were identified from tissue samples, it was not known prior to the experiments of the present Example whether identified colorectal cancer methylation biomarkers could be sufficiently analyzed from cfDNA to successfully capture the ctDNA portion that allows for identifying subjects or samples of subjects corresponding to a diagnosis of colorectal cancer and/or advanced adenoma.

As a critical step toward determining whether the colorectal cancer and advanced adenoma methylation biomarkers identified in Example 1 could be sufficiently analyzed from cfDNA to successfully capture the ctDNA portion that allows for identification of subjects or samples for colorectal cancer, a sensitive assay was developed for screening of these biomarkers. In particular, a Methylation-Sensitive Restriction Enzyme (MSRE)-qPCR methodology was developed. The MSRE-qPCR methodology was developed to measure methylation of DMRs covering identified CpG sites in blood samples, in particular in cell-free DNA (cfDNA) of tumors present in blood.

Development of the MSRE-qPCR methodology was significant at least in part because analyzing CpG methylation biomarkers derived from tumor tissue by analysis of cfDNA is challenging due to the low concentration of tumor-derived DNA circulating in blood (0.1 - 1%) as compared to the non-tumor DNA background of the sample. Thus, while it is generally preferred to develop biomarker analyses that rely on readily obtainable samples such as blood, urine, or stool, use of blood for analysis of tumor derived methylation biomarkers is challenging. Thus, even after identification of methylation biomarkers characteristic of colorectal cancer and advanced adenoma in tissue, as discussed above, it cannot be predicted whether the fragmented and poorly understood nature of ctDNA will permit successful screening using methylation biomarkers identified in tissue.

MSRE-qPCR requires design of oligonucleotide primers (MSRE-qPCR oligonucleotide primer pairs) that amplify regions of DNA that each include at least one MSRE cleavage site (i.e., an MSRE cleavage site that covers at least one methylation biomarker site, such that cleavage of the MSRE cleavage site is permitted in nucleic acid molecules where all of the least one of the methylation biomarker sites are unmethylated and blocked in nucleic acid molecules where at least one of the methylation biomarker sites is methylated). MSRE-qPCR assays can utilize multiple restriction enzymes to enhance the range of methylation biomarker sites that can be assayed by a single MSRE-qPCR reaction, as a single MSRE is unlikely to cleave sites that together include all methylation biomarker sites of interest. MSRE-qPCR assays of the present Examples utilize the MSREs Acil, Hin6l, and HpyCH4IV, which together were found to provide sufficient coverage.

An exemplary schematic work flow for MSRE-qPCR is provided in FIG. 1. As performed in the present Examples, circulating cell-free tumor DNA was extracted from subject blood (typically a plasma sample of approximately 10 mL) by QIAamp MinElute ccfDNA Kit in accordance with manufacturer protocol (QIAamp MinElute ccfDNA Handbook 08/2018, Qiagene). As shown in FIG. 1 , isolated cfDNA was divided into two aliquots, a first of which aliquots is utilized in a qPCR quality control analysis, and a second of which aliquots is used in MSRE-qPCR.

For MSRE-qPCR, 2/3 of eluted cfDNA by volume was digested with MSREs. Because non-methylated DNA is selectively cleaved, contacting the cfDNA with the MSREs enriches the sample for methylation-derived signal; methylated DNA remains intact and quantifiable. The remaining 1/3 of eluted cfDNA by volume was used for qPCR using the MSRE-qPCR oligonucleotide primers to confirm that amplicons were successfully amplified from cfDNA, which amplification confirms that template is present, hence providing technical quality control.

As applied herein, MSRE-qPCR oligonucleotide primer pairs were successfully developed for amplification of DMRs, thus yielding 88 different target DMRs from the methylation biomarker regions identified in the DMRs of Example 1. The 88 different target DMRs are listed in Table 7 below. The identified regions have significantly higher hypermethylation in colorectal cancer and advanced adenoma as compared to matching control tissue. Gene annotation has been added for genes that have annotation according to Ensembl genome browser 98. As some of the DMRs overlap different genes, all overlapping genes in the regions are listed. Table 7 below contains the unique identifier (UID) of the DMR, the chromosome number (Chr) the DMR is found on, the start and end positions of the DMR, the length/number of base pairs of the DMR, the name of an annotated gene (or multiple genes) found within the DMR, and the SEQ ID NO of the identified DMR. The genomic region parameters listed, including chromosome number and DMR start and end location, correspond to the reference genome of GRCh38. DMRs typically included 1 to 15 MSRE cleavage sites, which MSRE cleavage sites together covered each of the 88 methylation biomarker regions. As applied herein, methylation status of four genes (JUB, H19, SNRPN, IRF4) provided a methylation control, which permitted monitoring of assay robustness and reproducibility. Table 7. 88 Candidate DMRs Identified For MSRE-qPCR.

Example 3: MSRE-qPCR of cfDNA Successfully Distinguishes Subjects by Colorectal Cancer Status To probe clinical diagnostic and prognostic power of identified methylation biomarkers, the DMRs amplified by the MSRE-qPCR oligonucleotide primer pairs covering the 88 methylation biomarker regions, and appropriate controls, were assayed in cfDNA extracted from plasma of human subjects. In particular, cfDNA was sampled from individuals seeking, or in the process of obtaining, a diagnosis regarding possible colorectal cancer at screening centers and oncology clinics in Spain, the United Kingdom, and the United States between 2017 and 2018. A first subject group (the “training set”) included 166 such individuals (see description of the first subject group in FIG. 2), and a second subject group (the “validation set”) included 535 such individuals (see description of second subject group in FIG. 3).

To verify the predictive power of methylation biomarker DMRs for colorectal cancer, data derived from MSRE-qPCR analysis of samples from the training set of subjects were further analyzed to perform an initial feature selection based on the 88 methylation biomarker sites of Table 7. Monte-Carlo cross-validation was used over 50 runs and random forest algorithm was used for feature ranking and markers with VIP >2 were used for building a support-vector machine (SVM) algorithm-based classification model. This analysis identified several subsets of markers (3, 10, and 40 as described in Tables 2-4) that in the SVM-model gave a good prediction. Oligonucleotide primer pairs (Table 5) for amplification of the 40 DRMs in MSRE-qPCR cover at least one MSRE cleavage site. However, typically 3 to 15 MSRE cleavage sites are covered. MSRE-qPCR was carried out according to the methodology described in Example 2.

Initial principal component analysis based on the 40 marker panel revealed a good separation between colorectal cancer patients (i.e., those who are suffering colorectal cancer) and control patients (i.e., patients having no colonoscopy findings, hyperplastic polyps, and/or non-advanced adenomas) in 535 subjects tested as can be seen in FIG. 4. In the tested subject group, only some of the patients diagnosed with having advanced adenomas showed good separation from the control group. Without wishing to be bound to any particular theory, the similarity of the characteristics of the results to colorectal cancer in certain subjects may indicate that the advanced adenomas are further along in their path in progressing to a malignant, colorectal carcinoma.

Statistical analysis of the SVM algorithm based results are shown in FIGs. 5A and 5B. The 40 marker panel allowed identification of control patients from those suffering with colorectal cancer with a sensitivity of 78%. The sensitivity of determining patients suffering with advanced adenomas from control patients was 14%. The sensitivity of early localized cancer detection was 78%. A ROC curve analysis of the data based on the 40-marker panel of Table 4 as identified by the SVM model is provided in FIG. 5A. Table 8, shown below, shows additional studies of panels having less than 40 DMRs. The list of DMRs utilized for the 3 DMR combination study is shown in Table 2. The list of DMRs utilized for the 10 DMR combination study is shown in Table 3. The list of DMRs utilized for the 40 DMR combination study is shown in Table 4. “SensitivityALL” refers to the sensitivity when detecting if a subject is suffering from either colorectal cancer or advanced adenomas. “SensitivityCRC” refers to the sensitivity of detecting a subject suffering from colorectal cancer. “SensitivityAA” refers to the sensitivity of detecting a subject suffering from advanced adenomas. To highlight one particular example, the 3 marker panel indicates an especially good separation of colorectal cancer and advanced adenomas from the control subjects with overall sensitivity of 48% and specificity of 93%. At 93% specificity, advanced adenomas were detected with a sensitivity of 14% and colorectal cancer was detected with a sensitivity of 67%. Table 8. Accuracy metrics for application of 40 colorectal cancer DMR panel and subsets thereof to the verification group.

Example 4. Various Individual Methylation Biomarkers are Each Highly Informative Evaluation of the performance of individual colorectal cancer and advanced adenoma DMRs from among the 40 colorectal cancer DMR panel reveal that various individual colorectal cancer DMRs are sufficient for screening of colorectal cancer and advanced adenomas (See FIGs 6-15). FIGs. 6 - 15, respectively, show graphs representing Ct (Cycle Threshold) values from MSRE-qPCR of the DMRs identified as UDX_29_1 (FIG. 6), UDX_272.3_2 (FIG. 7), UDX_277.7_2 (FIG. 8), UDX_272.4 (FIG. 9). UDX_174.3 (FIG. 10), UDX_260.2_1 (FIG. 11), UDX_260.1 (FIG. 12), UDX_137.1 (FIG. 13), UDX_17_2 (FIG. 14), and UDX_230 (FIG. 15). For selected colorectal cancer and advance adenoma DMRs, FIGs 6-15 show methylation status of the indicated DMR in colorectal cancer and advanced adenoma samples (collectively denoted as “CRC”) and control samples (denoted as “CNT”; healthy subjects, patients with hyperplastic polyps and subjects with non-advanced adenoma). Results are displayed as the MSRE-qPCR Ct (“cycle threshold”) value subtracted from 45 (i.e., 45 - Ct value) for display purposes. The higher the 45-Ct value is, the higher the degree of methylation in the sample. Data provided in this Example, as well as data provided by the present Examples, cumulatively (including, e.g., FIGs. 4-9) demonstrate that for each individual DMR identified, the methylation status signal is sufficiently stable across subject groups to permit clinical screening for the combination of colorectal cancer and advanced adenomas. Results presented in FIGs. 4-15 therefore confirm that methylation markers of colorectal cancer and advanced adenoma provided herein can provide an overall, robust signal for screening of colorectal cancer and advanced adenomas. Moreover, those of skill in the art will appreciate that the present disclosure provides methylation biomarkers that are individually independently useful in screening for the combination of colorectal cancer and advanced adenomas, and specifically that methylation biomarkers provided herein are useful both individually or in combination with one another.

Computer System and Network Environment

As shown in FIG. 17, an implementation of a network environment 1700 for use in providing systems, methods, and architectures for retrieving, managing, and analyzing data from a plurality of sources as described herein is shown and described. In brief overview, referring now to FIG. 17, a block diagram of an exemplary cloud computing environment 1700 is shown and described. The cloud computing environment 1700 may include one or more resource providers 1702a, 1702b, 1702c (collectively, 1702). Each resource provider 1702 may include computing resources. In some implementations, computing resources may include any hardware and/or software used to process data. For example, computing resources may include hardware and/or software capable of executing algorithms, computer programs, and/or computer applications. In some implementations, exemplary computing resources may include application servers and/or databases with storage and retrieval capabilities. Each resource provider 1702 may be connected to any other resource provider 1702 in the cloud computing environment 1700. In some implementations, the resource providers 1702 may be connected over a computer network 1708. Each resource provider 1702 may be connected to one or more computing device 1704a, 1704b, 1704c (collectively, 1704), over the computer network 1708.

The cloud computing environment 1700 may include a resource manager 1706. The resource manager 1706 may be connected to the resource providers 1702 and the computing devices 1704 over the computer network 1708. In some implementations, the resource manager 1706 may facilitate the provision of computing resources by one or more resource providers 1702 to one or more computing devices 1704. The resource manager 1706 may receive a request for a computing resource from a particular computing device 1704. The resource manager 1706 may identify one or more resource providers 1702 capable of providing the computing resource requested by the computing device 1704. The resource manager 1706 may select a resource provider 1702 to provide the computing resource. The resource manager 1706 may facilitate a connection between the resource provider 1702 and a particular computing device 1704. In some implementations, the resource manager 1706 may establish a connection between a particular resource provider 1702 and a particular computing device 1704. In some implementations, the resource manager 1706 may redirect a particular computing device 1704 to a particular resource provider 1702 with the requested computing resource.

FIG. 18 shows an example of a computing device 1800 and a mobile computing device 1850 that can be used to implement the techniques described in this disclosure. The computing device 1800 is intended to represent various forms of digital computers, such as laptops, desktops, workstations, personal digital assistants, servers, blade servers, mainframes, and other appropriate computers. The mobile computing device 1850 is intended to represent various forms of mobile devices, such as personal digital assistants, cellular telephones, smart-phones, and other similar computing devices. The components shown here, their connections and relationships, and their functions, are meant to be examples only, and are not meant to be limiting.

The computing device 1800 includes a processor 1802, a memory 1804, a storage device 1806, a high-speed interface 1808 connecting to the memory 1804 and multiple high-speed expansion ports 1810, and a low-speed interface 1812 connecting to a low- speed expansion port 1814 and the storage device 1806. Each of the processor 1802, the memory 1804, the storage device 1806, the high-speed interface 1808, the highspeed expansion ports 1810, and the low-speed interface 1812, are interconnected using various busses, and may be mounted on a common motherboard or in other manners as appropriate. The processor 1802 can process instructions for execution within the computing device 1800, including instructions stored in the memory 1804 or on the storage device 1806 to display graphical information for a GUI on an external input/output device, such as a display 1816 coupled to the high-speed interface 1808. In other implementations, multiple processors and/or multiple buses may be used, as appropriate, along with multiple memories and types of memory. The memory 1804 stores information within the computing device 1800. In some implementations, the memory 1804 is a volatile memory unit or units. In some implementations, the memory 1804 is a non-volatile memory unit or units. The memory 1804 may also be another form of computer-readable medium, such as a magnetic or optical disk.

The storage device 1806 is capable of providing mass storage for the computing device 1800. In some implementations, the storage device 1806 may be or contain a computer-readable medium, such as a floppy disk device, a hard disk device, an optical disk device, or a tape device, a flash memory or other similar solid state memory device, or an array of devices, including devices in a storage area network or other configurations. Instructions can be stored in an information carrier. The instructions, when executed by one or more processing devices (for example, processor 1802), perform one or more methods, such as those described above. The instructions can also be stored by one or more storage devices such as computer- or machine-readable mediums (for example, the memory 1804, the storage device 1806, or memory on the processor 1802).

The high-speed interface 1808 manages bandwidth-intensive operations for the computing device 1800, while the low-speed interface 1812 manages lower bandwidth intensive operations. Such allocation of functions is an example only. In some implementations, the high-speed interface 1808 is coupled to the memory 1804, the display 1816 (e.g., through a graphics processor or accelerator), and to the high-speed expansion ports 1810, which may accept various expansion cards (not shown). In the implementation, the low-speed interface 1812 is coupled to the storage device 1806 and the low-speed expansion port 1814. The low-speed expansion port 1814, which may include various communication ports (e.g., USB, Bluetooth®, Ethernet, wireless Ethernet) may be coupled to one or more input/output devices, such as a keyboard, a pointing device, a scanner, or a networking device such as a switch or router, e.g., through a network adapter.

The computing device 1800 may be implemented in a number of different forms, as shown in the figure. For example, it may be implemented as a standard server 1820, or multiple times in a group of such servers. In addition, it may be implemented in a personal computer such as a laptop computer 1822. It may also be implemented as part of a rack server system 1824. Alternatively, components from the computing device 1800 may be combined with other components in a mobile device (not shown), such as a mobile computing device 1850. Each of such devices may contain one or more of the computing device 1800 and the mobile computing device 1850, and an entire system may be made up of multiple computing devices communicating with each other.

The mobile computing device 1850 includes a processor 1852, a memory 1864, an input/output device such as a display 1854, a communication interface 1866, and a transceiver 1868, among other components. The mobile computing device 1850 may also be provided with a storage device, such as a micro-drive or other device, to provide additional storage. Each of the processor 1852, the memory 1864, the display 1854, the communication interface 1866, and the transceiver 1868, are interconnected using various buses, and several of the components may be mounted on a common motherboard or in other manners as appropriate.

The processor 1852 can execute instructions within the mobile computing device 1850, including instructions stored in the memory 1864. The processor 1852 may be implemented as a chipset of chips that include separate and multiple analog and digital processors. The processor 1852 may provide, for example, for coordination of the other components of the mobile computing device 1850, such as control of user interfaces, applications run by the mobile computing device 1850, and wireless communication by the mobile computing device 1850.

The processor 1852 may communicate with a user through a control interface 1858 and a display interface 1856 coupled to the display 1854. The display 1854 may be, for example, a TFT (Thin-Film-Transistor Liquid Crystal Display) display or an OLED (Organic Light Emitting Diode) display, or other appropriate display technology. The display interface 1856 may comprise appropriate circuitry for driving the display 1854 to present graphical and other information to a user. The control interface 1858 may receive commands from a user and convert them for submission to the processor 1852. In addition, an external interface 1862 may provide communication with the processor 1852, so as to enable near area communication of the mobile computing device 1850 with other devices. The external interface 1862 may provide, for example, for wired communication in some implementations, or for wireless communication in other implementations, and multiple interfaces may also be used.

The memory 1864 stores information within the mobile computing device 1850. The memory 1864 can be implemented as one or more of a computer-readable medium or media, a volatile memory unit or units, or a non-volatile memory unit or units. An expansion memory 1874 may also be provided and connected to the mobile computing device 1850 through an expansion interface 1872, which may include, for example, a SIMM (Single In Line Memory Module) card interface. The expansion memory 1874 may provide extra storage space for the mobile computing device 1850, or may also store applications or other information for the mobile computing device 1850. Specifically, the expansion memory 1874 may include instructions to carry out or supplement the processes described above, and may include secure information also. Thus, for example, the expansion memory 1874 may be provide as a security module for the mobile computing device 1850, and may be programmed with instructions that permit secure use of the mobile computing device 1850. In addition, secure applications may be provided via the SIMM cards, along with additional information, such as placing identifying information on the SIMM card in a non-hackable manner. The memory may include, for example, flash memory and/or NVRAM memory (nonvolatile random access memory), as discussed below. In some implementations, instructions are stored in an information carrier that the instructions, when executed by one or more processing devices (for example, processor 1852), perform one or more methods, such as those described above. The instructions can also be stored by one or more storage devices, such as one or more computer- or machine-readable mediums (for example, the memory 1864, the expansion memory 1874, or memory on the processor 1852). In some implementations, the instructions can be received in a propagated signal, for example, over the transceiver 1868 or the external interface 1862.

The mobile computing device 1850 may communicate wirelessly through the communication interface 1866, which may include digital signal processing circuitry where necessary. The communication interface 1866 may provide for communications under various modes or protocols, such as GSM voice calls (Global System for Mobile communications), SMS (Short Message Service), EMS (Enhanced Messaging Service), or MMS messaging (Multimedia Messaging Service), CDMA (code division multiple access), TDMA (time division multiple access), PDC (Personal Digital Cellular), WCDMA (Wideband Code Division Multiple Access), CDMA2000, or GPRS (General Packet Radio Service), among others. Such communication may occur, for example, through the transceiver 1868 using a radio-frequency. In addition, short- range communication may occur, such as using a Bluetooth®, Wi-Fi™, or other such transceiver (not shown). In addition, a GPS (Global Positioning System) receiver module 1870 may provide additional navigation- and location-related wireless data to the mobile computing device 1850, which may be used as appropriate by applications running on the mobile computing device 1850. The mobile computing device 1850 may also communicate audibly using an audio codec 1860, which may receive spoken information from a user and convert it to usable digital information. The audio codec 1860 may likewise generate audible sound for a user, such as through a speaker, e.g., in a handset of the mobile computing device 1850. Such sound may include sound from voice telephone calls, may include recorded sound (e.g., voice messages, music files, etc.) and may also include sound generated by applications operating on the mobile computing device 1850.

The mobile computing device 1850 may be implemented in a number of different forms, as shown in the figure. For example, it may be implemented as a cellular telephone 1880. It may also be implemented as part of a smart-phone 1882, personal digital assistant, or other similar mobile device.

Various implementations of the systems and techniques described here can be realized in digital electronic circuitry, integrated circuitry, specially designed ASICs (application specific integrated circuits), computer hardware, firmware, software, and/or combinations thereof. These various implementations can include implementation in one or more computer programs that are executable and/or interpretable on a programmable system including at least one programmable processor, which may be special or general purpose, coupled to receive data and instructions from, and to transmit data and instructions to, a storage system, at least one input device, and at least one output device.

These computer programs (also known as programs, software, software applications or code) include machine instructions for a programmable processor, and can be implemented in a high-level procedural and/or object-oriented programming language, and/or in assembly/machine language. As used herein, the terms machine-readable medium and computer-readable medium refer to any computer program product, apparatus and/or device (e.g., magnetic discs, optical disks, memory, Programmable Logic Devices (PLDs)) used to provide machine instructions and/or data to a programmable processor, including a machine-readable medium that receives machine instructions as a machine-readable signal. The term machine-readable signal refers to any signal used to provide machine instructions and/or data to a programmable processor.

To provide for interaction with a user, the systems and techniques described here can be implemented on a computer having a display device (e.g., a CRT (cathode ray tube) or LCD (liquid crystal display) monitor) for displaying information to the user and a keyboard and a pointing device (e.g., a mouse or a trackball) by which the user can provide input to the computer. Other kinds of devices can be used to provide for interaction with a user as well; for example, feedback provided to the user can be any form of sensory feedback (e.g., visual feedback, auditory feedback, or tactile feedback); and input from the user can be received in any form, including acoustic, speech, or tactile input.

The systems and techniques described here can be implemented in a computing system that includes a back end component (e.g., as a data server), or that includes a middleware component (e.g., an application server), or that includes a front end component (e.g., a client computer having a graphical user interface or a Web browser through which a user can interact with an implementation of the systems and techniques described here), or any combination of such back end, middleware, or front end components. The components of the system can be interconnected by any form or medium of digital data communication (e.g., a communication network). Examples of communication networks include a local area network (LAN), a wide area network (WAN), and the Internet.

The computing system can include clients and servers. A client and server are generally remote from each other and typically interact through a communication network. The relationship of client and server arises by virtue of computer programs running on the respective computers and having a client-server relationship to each other.

In some implementations, the modules (e.g. data aggregation module 1830, mapping module 1850, specifications module 1870) described herein can be separated, combined or incorporated into single or combined modules. The modules depicted in the figures are not intended to limit the systems described herein to the software architectures shown therein.

Elements of different implementations described herein may be combined to form other implementations not specifically set forth above. Elements may be left out of the processes, computer programs, databases, etc. described herein without adversely affecting their operation. In addition, the logic flows depicted in the figures do not require the particular order shown, or sequential order, to achieve desirable results. Various separate elements may be combined into one or more individual elements to perform the functions described herein.

Throughout the description, where apparatus and systems are described as having, including, or comprising specific components, or where processes and methods are described as having, including, or comprising specific steps, it is contemplated that, additionally, there are apparatus, and systems of the present invention that consist essentially of, or consist of, the recited components, and that there are processes and methods according to the present invention that consist essentially of, or consist of, the recited processing steps. It should be understood that the order of steps or order for performing certain action is immaterial so long as the invention remains operable. Moreover, two or more steps or actions may be conducted simultaneously.

While the invention has been particularly shown and described with reference to specific preferred embodiments, it should be understood by those skilled in the art that various changes in form and detail may be made therein without departing from the spirit and scope of the invention as defined by the appended claims.