WO2014184684A2 - Methods and biomarkers for detection of hematological cancers - Google Patents

Abstract

The present invention relates to methods and biomarkers (e.g., epigenetic biomarkers) for detection of hematological cancers (e.g., lymphoma) in biological samples (e.g., tissue samples, blood samples, plasma samples, cell samples, serum samples).

Description

METHODS AND BIOMARKERS FOR DETECTION OF

HEMATOLOGICAL CANCERS

CROSS-REFERENCE TO RELATED APPLICATION

The present application claims priority to pending U.S. Provisional Patent Application

No. 61/824,278, filed May 16, 2013, the contents of which are incorporated by reference in its entirety.

FIELD OF THE INVENTION

The present invention relates to methods and biomarkers (e.g., epigenetic biomarkers) for detection of hematological cancers (e.g., lymphoma and leukemia) in biological samples (e.g., tissue samples, blood samples, plasma samples, cell samples, serum samples).

BACKGROUND OF THE INVENTION

B-cell-non-Hodgkin lymphoma (B-NHL) is a diverse group of different neoplasms of the lymphoid system and accounts for over 80% of all NHL types and includes numerous types, which are arrested at different developmental stages (Shaffer et al., Nat Rev Immunol 2002; 2:920-33). Chromosomal translocation involving the immunoglobulin (Ig) gene loci and oncogenes, e.g., MYC, BCL1 and BCL2, are common features in lymphoma. In addition, a broad pattern of other acquired genetic changes have been described in lymphoma, although considerable heterogeneity exists even within each lymphoma type. During the past decades it has become evident that alterations in the methylome can be found in nearly all cancer types (Esteller et al, Nat Rev Genet 2007; 8:286-98; Jones et al, Cell 2007; 128:683-92; Ting et al., Genes & Development 2006; 20:3215-31) and aberrant DNA methylation is considered to be a hallmark of cancer. The inactivation of tumor suppressor genes by DNA methylation has been described for several genes in different malignancies and represents an important mechanism for the loss of tumor suppressor gene activity (Herman et al., N Engl J Med 2003; 349:2042-54; Jones et al, Nat Rev Genet 2002; 3:415-28). Several tumor suppressor genes have been found to be inactivated in lymphoma, e.g. the cyclin-dependent kinase inhibitors CDKN2A and CDKN2B, the TP53 homologe TP75 and the death- associated protein kinase DAPK. Also genes which have not been described as tumor suppressor genes have been shown to be methylated in lymphoma at various frequencies. Furthermore, the discovery of novel methylated genes can in some cases predict the outcome of therapy (Daibata et al, Clin Cancer Res 2007; 13:3528-35). Thus, it was recently shown for the MGMT gene that DLBCL patients with methylation of the promoter of this gene had a favorable outcome (Uccella et al., Journal of Clinical Pathology 2009; 62:715-23).

Better, more effective non-invasive tests for early detection of lymphoma and other hematological cancers are needed to lower the morbidity and mortality associated with hematological cancers.

SUMMARY OF THE INVENTION

The present invention relates to kits, systems, uses, methods and biomarkers (e.g., epigenetic biomarkers) for detection of hematological cancers (e.g., lymphoma) in biological samples (e.g., tissue samples, blood samples, plasma samples, cell samples, serum samples).

For example, in some embodiments, the present invention provides a method for detecting a hematological cancer in a subject comprising: a) obtaining DNA from a biological sample of the subject; and b) determining the level, presence, or frequency of methylation of a nucleic acid polymer corresponding to one or more (e.g., 2, 3, 4, 5, or more or all of) genes selected, for example, BMPER, CDH1, DUSP4, LRP12, BCL2L10, CLU, CCL22, NPY1R, BMP7, DSP, FZD8, KCNH2, KLF9, MTSS1, NR4A2, PPP1R14A, BSPRY, ITGBL1, TRPM4, SGPP2, STAG3, UCHL1 or PTPRG. In some embodiments, the one or more genes are DSP, FZD8, KCNH2, NR4A2 and PPP1R14A. In some embodiments, the one or more genes are BMP7, BMPER, CDH1, DUSP4, and LRP12. In some embodiments, the one or more genes are one or more (e.g., all) of NPY1R, STAG3, BSPRY, ITGBL1, SGPP2, TRPM4, UCHL1, CLU and PTPRG. In some embodiments, the one or more genes are one or more (e.g., all) of LRP12, CDH1, PPP1R14A, FZD8, and BMPER; LRP12, PPP1R14A, FZD8, and BMPER; LRP12, CDH1, FZD8, and BMPER; LRP12, FZD8 and BMPER; or LRP12, FZD8, BMPER, and KCNH2. In some embodiments, the hematological cancer is a lymphoma (e.g., B-cell non-Hodgkins lymphoma). In some embodiments, the level or frequency of methylation of a nucleic acid polymer is compared to a reference level or frequency of methylations. In some embodiments, the method further comprises comparing the level, presence, or frequency of methylation of the nucleic acid polymer with a reference level, presence, or frequency of methylation, wherein an altered level, presence, or frequency of methylation for the patient relative to the reference provides an indication selected from, for example, an indication of a predisposition of the subject to a hematological cancer, an indication that the subject has a hematological cancer, or the response of a subject to treatment with a particular therapy. In some embodiments, the method comprises monitoring of a diagnosed patient for disease recurrence or progression. In some embodiments, the nucleic acid comprises a CpG island and/or CpG island shore. In some embodiments, the CpG island or shore is present in a coding region or a regulatory region (e.g., promoter). In some embodiments, determining of the level of altered methylation of a nucleic acid polymer comprises determining the methylation frequency of the CpG island or island shore. In some embodiments, determining of the level of a nucleic acid polymer with altered methylation is achieved by a technique selected from, for example methylation-specific PCR, quantitative methylation-specific PCR, methylation-sensitive DNA restriction enzyme analysis, methylation - insensitive DNA restriction enzyme analysis, quantitative bisulfite pyrosequencing, or bisulfite genomic sequencing PCR. In some embodiments, the method permits detection of a hematological cancer in the subject with a sensitivity of at least 85% at a specificity of at least 85%. In some embodiments, the method permits detection of hematological cancer in the subject with a sensitivity of at least 80% at a specificity of at least 90%. In some embodiments, the biological sample a tissue sample, a cell sample, or a blood sample. In some embodiments, the reagent is selected from, for example, a pair of amplification primers that specifically binds to said gene, one or more sequencing primers, a methylation specific restriction enzyme, or bisulfite. In some embodiments, the method further comprises administering a treatment (e.g., chemotherapy, radiation, etc.) for a hematological cancer to the subject. In some embodiments, testing is repeated after or during the treatment.

In further embodiments, the present invention provides the use of a methylation specific nucleic acid detection reagent for detection of one or more genes selected from, for example, BMPER, CDH1, DUSP4, LRP12, BCL2L10, CLU, CCL22, NPY1R, BMP7, DSP, FZD8, KCNH2, KLF9, MTSS1, NR4A2, PPP1R14A, BSPRY, ITGBL1, TRPM4, SGPP2, STAG3, UCHL1 and PTPRG for detecting a hematological cancer in a subject.

In yet other embodiments, the present invention provides a kit for detecting the presence of a hematological cancer in a mammal, the kit comprising reagents useful, sufficient, or necessary for detecting and/or characterizing level, presence, or frequency of methylation of one or more genes selected from, for example, BMPER, CDH1, DUSP4, LRP12, BCL2L10, CLU, CCL22, NPY1R, BMP7, DSP, FZD8, KCNH2, KLF9, MTSS1, NR4A2, PPP1R14A, BSPRY, ITGBL1, TRPM4, SGPP2, STAG3, UCHL1 or PTPRG.

The present invention also provides a system comprising a computer readable medium comprising instructions for utilizing information on the level, presence, or frequency of methylation of one or more genes selected from, for example, BMPER, CDH1, DUSP4, LRP12, BCL2L10, CLU, CCL22, NPY1R, BMP7, DSP, FZD8, KCNH2, KLF9, MTSS1, NR4A2, PPP1R14A, BSPRY, ITGBL1, TRPM4, SGPP2, STAG3, UCHL1 or PTPRG to provide an indication selected from an indication of a predisposition of the subject to a hematological cancer, an indication that the subject has a hematological cancer, or the response of a subject to treatment with a particular therapy.

In some embodiments, the present invention provides a reaction mixture comprising one or more methylation specific detection reagents complexed with one or more genes selected from for example, BMPER, CDH1, DUSP4, LRP12, BCL2L10, CLU, CCL22, NPY1R, BMP7, DSP, FZD8, KCNH2, KLF9, MTSS1, NR4A2, PPP1R14A, BSPRY, ITGBL1, TRPM4, SGPP2, STAG3, UCHL1 or PTPRG.

Further embodiments provide a method for detecting a hematological cancer in a subject comprising: a) providing reagents necessary for determining the level, presence, or frequency of methylation of a nucleic acid polymer corresponding to two or more biomarkers for a hematological cancer selected from, for example, BMPER, CDH1, DUSP4, LRP12, BCL2L10, CLU, NPY1R, BMP7, DSP, FZD8, KCNH2, KLF9, MTSS1, NR4A2, PPP1R14A, CCL22, BSPRY, ITGBL1, TRPM4, SGPP2, STAG3, UCHL1 or PTPRG, and an algorithm configured to receive information regarding the level, presence and/or frequency of methylation of the two or more biomarkers within a biological sample obtained from a subject, and configured to compare received information regarding the level, presence and/or frequency of methylation of the two or more biomarkers with established norms for methylation of the markers, and based upon such comparison, determine the presence, absence, or prognosis of hematological cancer for the subject; b) obtaining a biological sample from a subject; c) determining the level, presence, and/or frequency of methylation of the two or more biomarkers; d) inputting the determined level, presence, and/or frequency of methylation of the two or more biomarkers into the algorithm; and e) determine the presence, absence, or prognosis of hematological cancer for the subject using the algorithm. In some embodiments, the established norm for hematological cancer is one or more established norm selected from, for example, an established norm of methylation levels of said biomarkers in subjects not diagnosed with a hematological cancer for the received information regarding the level, presence and/or frequency of methylation of the two or more biomarkers, an established norm of methylation levels of said biomarkers in subjects diagnosed with a hematological cancer for the received information regarding the level, presence and/or frequency of methylation of the two or more biomarkers, or an established norm of methylation levels of the biomarkers in subjects neither diagnosed nor not diagnosed with a hematological cancer for the received information regarding the level, presence and/or frequency of methylation of the two or more biomarkers. Additional embodiments will be apparent to persons skilled in the relevant art based on the teachings contained herein.

DESCRIPTION OF THE DRAWINGS FIG. 1 shows the experimental setup for experiments described herein. Gene expression profiling was performed on 11 B-cell lymphoma cell lines, with or without epigenetic treatment.

FIG. 2 shows gene expression profiles of 30 candidate genes. Gene expression profiles of 11 B cell lymphoma cell lines treated (aza/TSA) and untreated (a), 638 B-cell lymphomas (b) and CD19⁺ B cells from five healthy donors (c) for 30 candidate genes.

FIG. 3 shows methylation status of individual CpG sites determined by bisulfite sequencing. The upper part of the figure is a schematic presentation of the area and the CpG sites covered by the bisulfite sequencing primers. The vertical bars represent individual CpG sites, the lower arrow marked by +1 indicates the transcription start site, and the two upper arrows marked by MSP-s, and MSP-as indicate the location of the quantitative methylation specific primers and probes. For the lower part of the figures, black circles represent methylated CpG sites (the ratio of C/(C+T)>0.8), grey circles represent partially methylated CpG sites (the ratio of C/(C+T) 0.8<0.20), and open circles represent unmethylated CpG sites (the ratio of C/(C+T)<0.20).

FIG. 4 shows the percent promoter methylation of the analyzed genes in the test and validation series.

FIG. 5 shows Receiver Operating Characteristics (ROC) curves for individual and combined markers in lymphoma patients versus healthy donors. The area under the ROC curve (AUC) represents how accurate the individual and combined biomarkers can discriminate between lymphomas and normal samples. A) Lymphoma samples versus healthy donors for individual genes. B) Lymphoma samples versus healthy donors for the combined gene panel.

FIG. 6 shows promoter methylation of BMPER, CDH1, DUSP4 and LRP12.

FIG. 7 shows promoter methylation of BMP7.

FIG. 8 shows receiver operating characteristics (ROC) curves. The genes of BMP7,

BMPER, CDH1, DUSP4 and LRP12 showed an individual area under the curve (AUC) of 0.70, 0.83, 0.99, 0.73 and 0.99 (Figure 8a, left). ROC of the panel (Figure 8b, right). DEFINITIONS

To facilitate an understanding of the present invention, a number of terms and phrases are defined below:

As used herein, the term "sensitivity" is defined as a statistical measure of

performance of an assay (e.g., method, test), calculated by dividing the number of true positives by the sum of the true positives and the false negatives.

As used herein, the term "specificity" is defined as a statistical measure of

performance of an assay (e.g., method, test), calculated by dividing the number of true negatives by the sum of true negatives and false positives.

As used herein, the term "informative" or "informativeness" refers to a quality of a marker or panel of markers, and specifically to the likelihood of finding a marker (or panel of markers) in a positive sample.

As used herein, the term "CpG island" refers to a genomic DNA region that contains a high percentage of CpG sites relative to the average genomic CpG incidence (per same species, per same individual, or per subpopulation (e.g., strain, ethnic subpopulation, or the like). Various parameters and definitions for CpG islands exist; for example, in some embodiments, CpG islands are defined as having a GC percentage that is greater than 50% and with an observed/expected CpG ratio that is greater than 60% (Gardiner-Garden et al. (1987) J Mol. Biol. 196:261-282; Baylin et al. (2006) Nat. Rev. Cancer 6: 107-116; Irizarry et al. (2009) Nat. Genetics 41 : 178-186; each herein incorporated by reference in its entirety). In some embodiments, CpG islands may have a GC content >55%> and observed CpG/expected CpG of 0.65 (Takai et al. (2007) PNAS 99:3740-3745; herein incorporated by reference in its entirety). Various parameters also exist regarding the length of CpG islands. As used herein, CpG islands may be less than 100 bp; 100-200 bp, 200-300 bp, 300-500 bp, 500-750 bp; 750- 1000 bp; 100 or more bp in length. In some embodiments, CpG islands show altered methylation patterns relative to controls (e.g., altered methylation in cancer subjects relative to subjects without cancer; tissue-specific altered methylation patterns; altered methylation in biological samples (e.g., tissue, stool, blood, plasma, serum, cells, bile) from subjects with hematological neoplasia (e.g., lymphoma) relative to subjects without hematological neoplasia). In some embodiments, altered methylation involves hypermethylation. In some embodiments, altered methylation involves hypomethylation.

As used herein, the term "CpG shore" or "CpG island shore" refers to a genomic region external to a CpG island that is or that has potential to have altered methylation patterns (see, e.g., Irizarry et al. (2009) Nat. Genetics 41 : 178-186; herein incorporated by reference in its entirety). CpG island shores may show altered methylation patterns relative to controls (e.g., altered methylation in cancer subjects relative to subjects without cancer; tissue-specific altered methylation patterns; altered methylation in biological samples (e.g., tissue, blood, cells) from subjects with hematological cancers (e.g., lymphoma or leukemia) relative to subjects without such cancers). In some embodiments, altered methylation involves hypermethylation. In some embodiments, altered methylation involves

hypomethylation. CpG island shores may be located in various regions relative to CpG islands (see, e.g., Irizarry et al. (2009) Nat. Genetics 41;178-186; herein incorporated by reference in its entirety). Accordingly, in some embodiments, CpG island shores are located less than 100 bp; 100-250 bp; 250-500 bp; 500-1000 bp; 1000-1500 bp; 1500-2000 bp; 2000- 3000 bp; 3000 bp or more away from a CpG island.

As used herein, the term "epigenetic" refers to a non-sequence-based alteration that is inherited through cell division. For example, in some embodiments, epigenetic changes are altered methylation patters or levels (e.g. hypermethylation).

As used herein the term "methylation state" is a measure of the presence or absence of a methyl modification in one or more CpG sites in at least one nucleic acid sequence. It is to be understood that in some embodiments, the methylation state of one or more CpG sites is determined in multiple copies of a particular gene of interest.

As used herein, the term "methylation level" refers to the amount of methylation in one or more copies of a gene or nucleic acid sequence of interest. The methylation level may be calculated as an absolute measure of methylation within the gene or nucleic acid sequence of interest. Also a "relative methylation level" may be determined as the amount of methylated DNA, relative to the total amount DNA present or as the number of methylated copies of a gene or nucleic acid sequence of interest, relative to the total number of copies of the gene or nucleic acid sequence. Additionally, the "methylation level" can be determined as the percentage of methylated CpG sites within the DNA stretch of interest.

The term methylation level also encompasses the situation wherein one or more CpG site in e.g. the promoter region is methylated but where the amount of methylation is below amplification threshold. Thus methylation level may be an estimated value of the amount of methylation in a gene of interest.

In some embodiments, the methylation level of the gene of interest is 15% to 100%, such as 50%) to 100%, more preferably 60%>- 100 %, more preferably 70- 100 %, more preferably 80% to 100%, more preferably 90% to 100%. Thus in one embodiment of the present invention the methylation level of the genes according to the invention is 80%, 81%, 82%, 83%, 84%, 85%, 86%, 87%, 88%, 89%, 90%, 91%, 92%, 93%, 94%, 95%, 96%, 97%, 98%, 99% or 100%.

As used herein, the term "methylation specific nucleic acid detection sequence" refers to a probe, probes or primers or sets thereof that are used to specifically detect, determine or analyze the methylation status of a target nucleic acid sequence, e.g., the sequences encoding one or more of BMPER, CDH1, DUSP4, LRP12, BCL2L10, CLU, CCL22, NPY1R, BMP7, DSP, FZD8, KCNH2, KLF9, MTSSl, NR4A2, PPP1R14A, BSPRY, ITGBLl, TRPM4, SGPP2, STAG3, UCHL1 or PTPRG. The detection sequence may be a single probe or comprise multiple probes, such as would be the case for a set of PCR primers specific for the target sequence. Specific examples of "methylation specific nucleic acid detection sequences" include, but are not limited to, primer sets, probes, sequencing primers, etc..

As used herein, the term "metastasis" is meant to refer to the process in which cancer cells originating in one organ or part of the body relocate to another part of the body and continue to replicate. Metastasized cells subsequently form tumors which may further metastasize. Metastasis thus refers to the spread of cancer from the part of the body where it originally occurs to other parts of the body.

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

"neoplasm-specific marker" refers to any biological material that can be used to indicate the presence of a neoplasm. Examples of biological materials include, without limitation, nucleic acids, polypeptides, carbohydrates, fatty acids, cellular components (e.g., cell membranes and mitochondria), and whole cells. The term "hematological neoplasm-specific marker" refers to any biological material that can be used to indicate the presence of a hematological neoplasm (e.g., a leukemia or lymphoma). Examples of hematological cancer specific markers include, but are not limited to, BMPER, CDH1, DUSP4, LRP12, BCL2L10, CLU, CCL22, NPY1R, BMP7, DSP, FZD8, KCNH2, KLF9, MTSSl, NR4A2, PPP1R14A, BSPRY, ITGBLl, TRPM4, SGPP2, STAG3, UCHL1 or PTPRG.

As used herein, the term "amplicon" refers to a nucleic acid generated using primer pairs. The amplicon is typically single-stranded DNA (e.g., the result of asymmetric amplification), however, it may be R A or dsDNA.

The term "amplifying" or "amplification" in the context of nucleic acids refers to the production of multiple copies of a polynucleotide, or a portion of the polynucleotide, typically starting from a small amount of the polynucleotide (e.g., a single polynucleotide molecule), where the amplification products or amplicons are generally detectable. Amplification of polynucleotides encompasses a variety of chemical and enzymatic processes. The generation of multiple DNA copies from one or a few copies of a target or template DNA molecule during a polymerase chain reaction (PCR) or a ligase chain reaction (LCR; see, e.g., U.S. Patent No. 5,494,810; herein incorporated by reference in its entirety) are forms of amplification. Additional types of amplification include, but are not limited to, allele-specific PCR (see, e.g., U.S. Patent No. 5,639,611; herein incorporated by reference in its entirety), assembly PCR (see, e.g., U.S. Patent No. 5,965,408; herein incorporated by reference in its entirety), helicase-dependent amplification (see, e.g., U.S. Patent No.

7,662,594; herein incorporated by reference in its entirety), hot-start PCR (see, e.g., U.S. Patent Nos. 5,773,258 and 5,338,671; each herein incorporated by reference in their entireties), intersequence-specfic PCR, inverse PCR (see, e.g., Triglia, et al. (1988) Nucleic Acids Res., 16:8186; herein incorporated by reference in its entirety), ligation-mediated PCR (see, e.g., Guilfoyle, R. et al, Nucleic Acids Research, 25: 1854-1858 (1997); U.S. Patent No. 5,508,169; each of which are herein incorporated by reference in their entireties),

methylation-specific PCR (see, e.g., Herman, et al, (1996) PNAS 93(13) 9821-9826; herein incorporated by reference in its entirety), miniprimer PCR, multiplex ligation-dependent probe amplification (see, e.g., Schouten, et al, (2002) Nucleic Acids Research 30(12): e57; herein incorporated by reference in its entirety), multiplex PCR (see, e.g., Chamberlain, et al., (1988) Nucleic Acids Research 16(23) 11141-11156; Ballabio, et al, (1990) Human Genetics 84(6) 571-573; Hayden, et al, (2008) BMC Genetics 9:80; each of which are herein incorporated by reference in their entireties), nested PCR, overlap-extension PCR (see, e.g., Higuchi, et al, (1988) Nucleic Acids Research 16(15) 7351-7367; herein incorporated by reference in its entirety), real time PCR (see, e.g., Higuchi, etl al, (1992) Biotechnology 10:413-417; Higuchi, et al, (1993) Biotechnology 11 : 1026-1030; each of which are herein incorporated by reference in their entireties), reverse transcription PCR (see, e.g., Bustin,

S.A. (2000) J. Molecular Endocrinology 25: 169-193; herein incorporated by reference in its entirety), solid phase PCR, thermal asymmetric interlaced PCR, and Touchdown PCR (see, e.g., Don, et al, Nucleic Acids Research (1991) 19(14) 4008; Roux, K. (1994) Biotechniques 16(5) 812-814; Hecker, et al, (1996) Biotechniques 20(3) 478-485; each of which are herein incorporated by reference in their entireties). Polynucleotide amplification also can be accomplished using digital PCR (see, e.g., Kalinina, et al, Nucleic Acids Research. 25; 1999- 2004, (1997); Vogelstein and Kinzler, Proc Natl Acad Sci USA. 96; 9236-41, (1999);

International Patent Publication No. WO05023091 A2; US Patent Application Publication No. 20070202525; each of which are incorporated herein by reference in their entireties). As used herein, the terms "complementary" or "complementarity" are used in reference to polynucleotides (i.e., a sequence of nucleotides) related by the base-pairing rules. For example, the sequence "5'-A-G-T-3',^M is complementary to the sequence "3 -T-C-A-5'." Complementarity may be "partial," in which only some of the nucleic acids' bases are matched according to the base pairing rules. Or, there may be "complete" or "total" complementarity between the nucleic acids. The degree of complementarity between nucleic acid strands has significant effects on the efficiency and strength of hybridization between nucleic acid strands. This is of particular importance in amplification reactions, as well as detection methods that depend upon binding between nucleic acids.

As used herein, the term "primer" refers to an oligonucleotide, whether occurring naturally as in a purified restriction digest or produced synthetically, that is capable of acting as a point of initiation of synthesis when placed under conditions in which synthesis of a primer extension product that is complementary to a nucleic acid strand is induced (e.g. , in the presence of nucleotides and an inducing agent such as a biocatalyst (e.g., a DNA polymerase or the like) and at a suitable temperature and pH). The primer is typically single stranded for maximum efficiency in amplification, but may alternatively be double stranded. If double stranded, the primer is generally first treated to separate its strands before being used to prepare extension products. In some embodiments, the primer is an

oligodeoxyribonucleotide. The primer is sufficiently long to prime the synthesis of extension products in the presence of the inducing agent. The exact lengths of the primers will depend on many factors, including temperature, source of primer and the use of the method. In certain embodiments, the primer is a capture primer.

As used herein, the term "nucleic acid molecule" refers to any nucleic acid containing molecule, including but not limited to, DNA or RNA. The term encompasses sequences that include any of the known base analogs of DNA and RNA including, but not limited to, 4 acetylcytosine, 8-hydroxy-N6-methyladenosine, aziridinylcytosine, pseudoisocytosine, 5- (carboxyhydroxyl-methyl) uracil, 5-fluorouracil, 5-bromouracil, 5- carboxymethylaminomethyl-2-thiouracil, 5-carboxymethyl-aminomethyluracil,

dihydrouracil, inosine, N6-isopentenyladenine, 1-methyladenine, 1-methylpseudo-uracil, 1- methylguanine, 1-methylinosine, 2,2-dimethyl-guanine, 2-methyladenine, 2-methylguanine, 3-methyl-cytosine, 5-methylcytosine, N6-methyladenine, 7-methylguanine, 5- methylaminomethyluracil, 5-methoxy-amino-methyl-2-thiouracil, beta-D-mannosylqueosine, 5'-methoxycarbonylmethyluracil, 5-methoxyuracil, 2-methylthio-N- isopentenyladenine, uracil-5-oxyacetic acid methylester, uracil-5-oxyacetic acid, oxybutoxosine, pseudouracil, queosine, 2-thiocytosine, 5-methyl-2-thiouracil, 2-thiouracil, 4-thiouracil, 5-methyluracil, N- uracil-5-oxyacetic acid methylester, uracil-5-oxyacetic acid, pseudouracil, queosine, 2- thiocytosine, and 2,6-diaminopurine.

As used herein, the term "nucleobase" is synonymous with other terms in use in the art including "nucleotide," "deoxynucleotide," "nucleotide residue," "deoxynucleotide residue," "nucleotide triphosphate (NTP)," or deoxynucleotide triphosphate (dNTP).

An "oligonucleotide" refers to a nucleic acid that includes at least two nucleic acid monomer units (e.g. , nucleotides), typically more than three monomer units, and more typically greater than ten monomer units. The exact size of an oligonucleotide generally depends on various factors, including the ultimate function or use of the oligonucleotide. To further illustrate, oligonucleotides are typically less than 200 residues long (e.g., between 15 and 100), however, as used herein, the term is also intended to encompass longer

polynucleotide chains. Oligonucleotides are often referred to by their length. For example a 24 residue oligonucleotide is referred to as a "24-mer". Typically, the nucleoside monomers are linked by phosphodiester bonds or analogs thereof, including phosphorothioate, phosphorodithioate, phosphoroselenoate, phosphorodiselenoate, phosphoroanilothioate, phosphoranilidate, phosphoramidate, and the like, including associated counterions, e.g., H⁺, NH₄ ⁺, Na⁺, and the like, if such counterions are present. Further, oligonucleotides are typically single-stranded. Oligonucleotides are optionally prepared by any suitable method, including, but not limited to, isolation of an existing or natural sequence, DNA replication or amplification, reverse transcription, cloning and restriction digestion of appropriate sequences, or direct chemical synthesis by a method such as the phosphotriester method of Narang et al. (1979) Meth Enzymol. 68: 90-99; the phosphodiester method of Brown et al. (1979) Meth Enzymol. 68: 109-151 ; the diethylphosphoramidite method of Beaucage et al. (1981) Tetrahedron Lett. 22: 1859-1862; the triester method of Matteucci et al. (1981) J Am Chem Soc. 103 :3185-3191 ; automated synthesis methods; or the solid support method of U.S. Pat. No. 4,458,066, entitled "PROCESS FOR PREPARING POLYNUCLEOTIDES," issued Jul. 3, 1984 to Caruthers et al., or other methods known to those skilled in the art. All of these references are incorporated by reference.

A "sequence" of a biopolymer refers to the order and identity of monomer units (e.g., nucleotides, etc.) in the biopolymer. The sequence (e.g., base sequence) of a nucleic acid is typically read in the 5' to 3' direction. A "subsequence" is any portion of an entire sequence. Thus, a subsequence refers to a consecutive sequence of amino acids or nucleic acids which is part of a longer sequence of nucleic acids (e.g. polynucleotide).

As used herein, the term "subject" refers to any animal (e.g., a mammal), including, but not limited to, humans, non-human primates, rodents, and the like, which is to be the recipient of a particular treatment. Typically, the terms "subject" and "patient" are used interchangeably herein in reference to a human subject.

As used herein, the term "non-human animals" refers to all non-human animals including, but are not limited to, vertebrates such as rodents, non-human primates, ovines, bovines, ruminants, lagomorphs, porcines, caprines, equines, canines, felines, aves, etc.

The term "gene" refers to a nucleic acid (e.g., DNA) sequence that comprises coding sequences necessary for the production of a polypeptide, RNA (e.g., including but not limited to, mRNA, tRNA and rRNA) or precursor. The polypeptide, RNA, or precursor can be encoded by a full length coding sequence or by any portion of the coding sequence so long as the desired activity or functional properties (e.g., enzymatic activity, ligand binding, signal transduction, etc.) of the full-length or fragment are retained. The term also encompasses the coding region of a structural gene and the including sequences located adjacent to the coding region on both the 5' and 3' ends for a distance of about 1 kb on either end such that the gene corresponds to the length of the full-length mRNA. The sequences that are located 5' of the coding region and which are present on the mRNA are referred to as 5' untranslated sequences. The sequences that are located 3' or downstream of the coding region and that are present on the mRNA are referred to as 3' untranslated sequences. The term "gene" encompasses both cDNA and genomic forms of a gene. A genomic form or clone of a gene contains the coding region interrupted with non-coding sequences termed "introns" or "intervening regions" or "intervening sequences". Introns are segments of a gene that are transcribed into nuclear RNA (hnRNA); introns may contain regulatory elements such as enhancers. Introns are removed or "spliced out" from the nuclear or primary transcript;

introns therefore are absent in the messenger RNA (mRNA) processed transcript. The mRNA functions during translation to specify the sequence or order of amino acids in a nascent polypeptide.

The term "locus" as used herein refers to a nucleic acid sequence on a chromosome or on a linkage map and includes the coding sequence as well as 5 ' and 3 ' sequences involved in regulation of the gene. DETAILED DESCRIPTION OF THE INVENTION

The present invention relates to methods and biomarkers (e.g., epigenetic biomarkers) for detection of hematological cancers (e.g., lymphoma and leukemia) in biological samples (e.g., tissue samples, blood samples, plasma samples, cell samples, serum samples).

Impaired epigenetic regulation is as common as gene mutations in human cancer.

These mechanisms lead to quantitative and qualitative gene expression changes causing a selective growth advantage, which may result in cancerous transformation. Aberrantly hypermethylated CpG islands in the gene promoter associated with transcriptional inactivation are among the most frequent epigenetic changes in cancer. Since early detection of disease can result in improved clinical outcome for most types of cancer, the identification of cancer-associated aberrant gene methylation represents promising novel biomarkers

In the present study, gene expression data from epigenetic treatment of a large panel of B cell lymphoma cell lines was combined with the gene expression in NHL patient samples to identify methylated genes in NHL. The study focused on major types of B-NHL (DLBCL (ABC and GCB subtypes), FL and BL) and compared data from cell lines and corresponding patient samples from the same lymphoma type. The gene promoters of BMPER, BMP7, CDH1, DUSP4 and LRP12 showed variable methylation frequencies with 58%, 24%, 92%o 32%o and 96%>, respectively in the analyzed lymphoma samples.

Furthermore, the methylation analysis of those genes combined could successfully discriminate all, except one, lymphoma samples from healthy controls, which includes FH samples) as shown by receiver operating characteristics with an AUC of 0.999.

Alterations of the TGF-β/ΒΜΡ signalling pathways are frequently found in human cancer. In epithelial cancers, TGF-β often acts as a tumour suppressor; during early stages of carcinogenesis, however, at later stages, it is often a tumour promoter. Resistance to TGFb and BMPS has been reported also in B cell lymphoma. Interestingly, three of these genes are related to TGFB/BMP signaling pathways. The LRP12 gene, which had the highest methylation frequency, encodes for a low density lipoprotein receptor-related protein. A role in signal transduction is projected, since the cytoplasmic c-terminus can interact among others with SARA (Smad anchor receptor activation), which also is reported to interact with the TGF-β and BMP pathways (Garnis et al, Oncogene 0 AD; 23 :2582-6). Moreover, the gene BMPER, which encodes for a BMP modulator, shows a high methylation frequency in the patient cohort. And further, BMP7, which is methylated in 30% of the analyzed lymphoma samples; as well as BMP6, which has been reported to be frequently methylated in lymphoma (Daibata et al., Clin Cancer Res 2007; 13:3528-35) are members of the TGFb superfamily of cytokines. Taken together, the data shows that resistance towards TGF-β and/or BMPs in lymphoma could be due to a downregulation of TGF-β/ΒΜΡ signaling pathway components, caused by methylation of those promoter regions.

In contrast to genetic aberrations, DNA methylation is a reversible modification. In vitro experiments and clinical trials have shown the therapeutic efficiency of demethylating agents in hematological malignencies (Esteller et al., J.Natl. Cancer Inst. 2002; 94:26-32). A specific marker for monitoring the dose-response of such agents in each patient would be of great importance. And further, since methylation occurs early in the development of cancer, the methylation status of those genes could be used to monitor relapses. Furthermore, usage of DNA methylation as a biomarker has been shown for many cancer types and different tissues (primary biopsy, serum, feces or sputum). A proof of principle for lymphoma, has been shown by Ying et al., and the analysis of the DLC1 methylation status in serum of HL patients (Tao Q and Ying. Tumor-specific methylation of the 8p22 tumor suppressor gene DLC1 is an epigenetic biomarker for Hodgkin, nasal NK/T-cell and other types of lymphomas).

An approach similar to that of (Lind et al., Molecular Cancer 2011; 10:85) was used a to combine gene expression data from a large panel of lymphoma cell lines treated with a demethylating agent with the expression in NHL patient biopsies and normal peripheral blood B cells from healthy controls. Using this approach, methylated genes in NHL were identified. Four genes, DSP, FZD8, KCNH2, and PPP1R14A were frequently methylated (80%) across the major NHL types. The combination of these four genes could successfully discriminate NHL samples from healthy controls (normal B lymphocytes isolated from blood, bone marrow samples, peripheral blood mononuclear cells, tonsils and follicular hyperplasia samples) as shown by Receiver Operating Characteristic analysis with a c-statistic (area under the curve) of 0.96.

Cancers generally harbor several hypermethylated promoter regions (Fernandez et al, Genome Research 2012; 22:407-19) and different methodological approaches are expected to identify various subsets of these. In spite of the numerous methylated genes identified so far only a limited number have high enough performance to qualify as biomarkers. In this study, several methylated genes were ifentifed in lymphoma and/or lymphoma cell lines. Several of these have previously been shown to be altered in other types of cancers. MTSS1 and DSP are known tumor suppressor genes and are together with PPP1R14A, also methylated in lung-, colorectal- and gastric cancer (Deeqa Ahmed Mohamed AIL, Carcinogenesis 2012; Utikal et al, Int.J.Cancer 2006; 119:2287-93; Yamashita et al, Cancer Science 2006; 97:64-71). However, this is first time DSP, FZD8, KCNH2, MTSSl, and PPP1R14A have been reported to be methylated in lymphoma. No cancer-relevant role has so far been reported for the PPP1R14A gene, which encodes a protein phosphatase, which is involved in regulation of contraction in smooth-muscle tissue. The gene KCNH2, also known as hERGl, encodes a potassium channel and has been shown to regulate cell proliferation, apoptosis, cell invasion and angiogenesis by modulating several biochemical pathways (Pillozzi et al., 674:55-67). These effects are mediated by KCNH2 recruitment into the plasma membrane as well as by an interaction with integrins and growth factors (Pillozzi et al., Blood 2011; 117:902-14). The gene with the second highest methylation frequency in the present study, Frizzled family receptor 8 (FZD8), is involved in the Wnt signaling pathway, which is frequently altered among several cancer types, including leukemia and CRC (GE X, et al., Journal of

Hematology & Oncology 2010; 3:33; White et al, Gastroenterology 2012; 142:219-32.). DSP has also been shown to be involved in the Wnt signaling pathway (Yang et al.,

Carcinogenesis 2012) and has been shown to be expressed in gastro-intestinal follicular lymphoma, a subtype with a favorable prognosis (Takata et al., Cancer Science 2011;

102: 1532-6).

In contrast to most other studies (Shaknovich et al., Blood 2010; blood-2010; Bennett et al., Genes Chromosom.Cancer 2009). Several genes which were methylated across NHL types were identified. This includes the primary mediastinal B-cell lymphomas, which in general showed less methylation than the other NHL types. Interestingly these lymphomas have a gene expression pattern that resembles that of Hodgkin's lymphoma (Rosenwald et al., The Journal of Experimental Medicine 2003; 198:851-62). Considering the significant molecular, phenotypical and clinical differences between the various lymphoma types, the "universal epi-markers" identified here are useful for the screening or monitoring of NHL patients.

Accordingly, in some embodiments, the present invention provides compositions, systems, and methods for molecular diagnosis and monitoring of various types of

hematological cancers (e.g., lymphoma and leukemia). In some embodiments, the technology involves a molecular diagnostic test for the methylation level of one or more or a panel of methylated genes associated with various lymphomas (e.g., B-cell Non-Hodgkin's

Lymphoma (NHL)).

In some embodiments, the markers are one or more of the following: BMPER, CDH1, DUSP4, LRP12, BCL2L10, CLU, CCL22, NPY1R, BMP7, DSP, FZD8, KCNH2, KLF9, MTSSl, NR4A2, PPP1R14A, BSPRY, ITGBLl, TRPM4, SGPP2, STAG3, UCHLl or PTPRG. While the present invention exemplifies several markers specific for detecting and/or monitoring hematological cancers, any marker that is correlated with the presence or absence or prognosis of hematological cancers may be used. A marker, as used herein, includes, for example, nucleic acid(s) whose production or mutation or lack of production is characteristic of a hematological neoplasm. Depending on the particular set of markers employed in a given analysis, the statistical analysis will vary. For example, where a particular combination of markers is highly specific for hematological cancer, the statistical significance of a positive result will be high. It may be, however, that such specificity is achieved at the cost of sensitivity (e.g., a negative result may occur even in the presence of cancer). By the same token, a different combination may be very sensitive (e.g., few false negatives, but has a lower specificity).

Particular combinations of markers may be used that show optimal function with different ethnic groups or sex, different geographic distributions, different stages of disease, different degrees of specificity or different degrees of sensitivity. Particular combinations may also be developed which are particularly sensitive to the effect of therapeutic regimens on disease progression. Subjects may be monitored after a therapy and/or course of action to determine the effectiveness of that specific therapy and/or course of action.

In some embodiments, the present invention provides combinations of markers in which one or more (e.g., 2, 3, 4, 5, or all of the members) are detected together to provide diagnostic, screening, or prognostic information for a hematological cancer such as lymphoma. In some embodiments, the markers are one or more of the following: BMPER, CDH1, DUSP4, LRP12, BCL2L10, CLU, CCL22, NPY1R, BMP7, DSP, FZD8, KCNH2, KLF9, MTSS1, NR4A2, PPP1R14A, BSPRY, ITGBL1, TRPM4, SGPP2, STAG3, UCHL1 or PTPRG.

The methods of the present invention are not limited to particular indicators of hematological neoplasm. In some embodiments, indicators of hematological neoplasm include, for example, epigenic alterations. Epigenetic alterations include but are not limited to DNA methylation (e.g., CpG methylation). In some embodiments, the level (e.g., frequency, score) of methylation (e.g., hypermethylation relative to a control, hypomethylation relative to a control) is determined without limitation to the technique used for such determining. Methods of the present invention are not limited to particular epigenetic alterations (e.g., DNA methylation) (e.g., CpG methylation) (e.g., CpG methylation in coding or regulatory regions). Altered methylation may occur in, for example, CpG islands; CpG island shores; or regions other than CpG islands or CpG island shores. In certain embodiments, methods, kits, and systems of the present invention involve determination of methylation state of a locus of interest (e.g., in human DNA) (e.g., in human DNA extracted from a blood sample, from a serum sample, from a plasma sample, from a cell sample, etc). Any appropriate method can be used to determine whether a particular DNA is hypermethylated or hypomethylated. Standard PCR techniques, for example, can be used to determine which residues are methylated, since unmethylated cytosines converted to uracil are replaced by thymidine residues during PCR. PCR reactions can contain, for example, 10 μΐ_^ of captured DNA that either has or has not been treated with sodium bisulfite, IX PCR buffer, 0.2 mM dNTPs, 0.5 μΜ sequence specific primers (e.g., primers flanking a CpG island or CpG shore within the captured DNA), and 5 units DNA polymerase (e.g., Amplitaq DNA polymerase from PE Applied Biosystems, Norwalk, CT) in a total volume of 50 μΐ. A typical PCR protocol can include, for example, an initial denaturation step at 94°C for 5 min, 40 amplification cycles consisting of 1 minute at 94°C, 1 minute at 60°C, and 1 minute at 72°C, and a final extension step at 72°C for 5 minutes.

To analyze which residues within a captured DNA are methylated, the sequences of

PCR products corresponding to samples treated with and without sodium bisulfite can be compared. The sequence from the untreated DNA will reveal the positions of all cytosine residues within the PCR product. Cytosines that were unmethylated will be converted to thymidine residues in the sequence of the bisulfite-treated DNA, while residues that were methylated will be unaffected by bisulfite treatment.

Some embodiments of the present invention utilize next generation or high- throughput sequencing. A variety of nucleic acid sequencing methods are contemplated for use in the methods of the present disclosure including, for example, chain terminator (Sanger) sequencing, dye terminator sequencing, and high-throughput sequencing methods. Many of these sequencing methods are well known in the art. See, e.g., Sanger et al, Proc. Natl.

Acad. Sci. USA 74:5463-5467 (1997); Maxam et al, Proc. Natl. Acad. Sci. USA 74:560-564 (1977); Drmanac, et al, Nat. Biotechnol. 16:54-58 (1998); Kato, Int. J. Clin. Exp. Med. 2: 193-202 (2009); Ronaghi et al, Anal. Biochem. 242:84-89 (1996); Margulies et al, Nature 437:376-380 (2005); Ruparel et al, Proc. Natl. Acad. Sci. USA 102:5932-5937 (2005), and Harris et al, Science 320: 106-109 (2008); Levene et al, Science 299:682-686 (2003);

Korlach et al, Proc. Natl. Acad. Sci. USA 105: 1176-1181 (2008); Branton et al, Nat.

Biotechnol. 26(10): 1146-53 (2008); Eid et al, Science 323: 133-138 (2009); each of which is herein incorporated by reference in its entirety. Similarly, in some embodiments, methods of the present invention involve the determination (e.g., assessment, ascertaining, quantitation) of methylation level of an indicator of hematological neoplasm (e.g., the methylation level of a CpG island or CpG shore in the coding or regulatory region of a gene locus) in a sample (e.g., a DNA sample extracted from stool, bile or blood). A skilled artisan understands that an increased, decreased, informative, or otherwise distinguishably different methylation level is articulated with respect to a reference (e.g., a reference level, a control level, a threshold level, or the like). For example, the term "elevated methylation" as used herein with respect to the methylation status (e.g., CpG DNA methylation) of a gene locus (e.g.,) is any methylation level that is above a median methylation level in a sample from a random population of mammals (e.g., a random population of 10, 20, 30, 40, 50, 100, or 500 mammals) that do not have a hematological neoplasm (e.g., hematological cancer). Elevated levels of methylation can be any level provided that the level is greater than a corresponding reference level. For example, an elevated methylation level of a locus of interest (e.g.,) methylation can be 0.5, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, or more fold greater than the reference level methylation observed in a normal sample. It is noted that a reference level can be any amount. The term "elevated methylation score" as used herein with respect to detected methylation events in a matrix panel of particular nucleic acid markers is any methylation score that is above a median methylation score in a sample from a random population of mammals (e.g., a random population of 10, 20, 30, 40, 50, 100, or 500 mammals) that do not have a hematological neoplasm (e.g., leukemia or lymphoma). An elevated methylation score in a matrix panel of particular nucleic acid markers can be any score provided that the score is greater than a corresponding reference score. For example, an elevated score of methylation in a locus of interest (e.g.,) can be 0.5, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, or more fold greater than the reference methylation score observed in a normal sample. It is noted that a reference score can be any amount.

The methods are not limited to a particular type of mammal. In some embodiments, the mammal is a human. In some embodiments, the hematological cancer is premalignant. In some embodiments, the hematological cancer is malignant. In some embodiments, the hematological cancer is lymphoma without regard to stage of the cancer (e.g., stage I, II, III, or IV). In some embodiments, the lymphoma is B-cell-non-Hodgkin lymphoma (B-NHL).

The present invention also provides methods and materials to assist medical or research professionals in determining whether or not a mammal has a hematological cancer (e.g., lymphoma or leukemia). Medical professionals can be, for example, doctors, nurses, medical laboratory technologists, and pharmacists. Research professionals can be, for example, principle investigators, research technicians, postdoctoral trainees, and graduate students. A professional can be assisted by (1) determining the ratio of particular markers in a sample, and (2) communicating information about the ratio to that professional, for example.

After the level (score, frequency) of particular markers in a blood, serum, or plasma sample is reported, a medical professional can take one or more actions that can affect patient care. For example, a medical professional can record the results in a patient's medical record. In some cases, a medical professional can record a diagnosis of a hematological cancer, or otherwise transform the patient's medical record, to reflect the patient's medical condition. In some cases, a medical professional can review and evaluate a patient's entire medical record, and assess multiple treatment strategies, for clinical intervention of a patient's condition. In some cases, a medical professional can record a prediction of tumor occurrence with the reported indicators. In some cases, a medical professional can review and evaluate a patient's entire medical record and assess multiple treatment strategies, for clinical intervention of a patient's condition. In some embodiments, a diagnosed patient is monitored for disease recurrence or progression.

A medical professional can initiate or modify treatment of a hematological cancer after receiving information regarding the level (score, frequency) associated with markers in a patient's stool, blood, serum, bile or plasma sample. In some cases, a medical professional can compare previous reports and the recently communicated level (score, frequency) of markers, and recommend a change in therapy (e.g., due to remission, progression, or recurrence of disease). In some cases, a medical professional can enroll a patient in a clinical trial for novel therapeutic intervention of hematological neoplasm. In some cases, a medical professional can elect waiting to begin therapy until the patient's symptoms require clinical intervention.

A medical professional can communicate the assay results to a patient or a patient's family. In some cases, a medical professional can provide a patient and/or a patient's family with information regarding hematological neoplasia, including treatment options, prognosis, and referrals to specialists, e.g., oncologists and/or radiologists. In some cases, a medical professional can provide a copy of a patient's medical records to communicate assay results to a specialist. A research professional can apply information regarding a subject's assay results to advance hematological neoplasm research. For example, a researcher can compile data on the assay results, with information regarding the efficacy of a drug for treatment of a hematological cancer to identify an effective treatment. In some cases, a research professional can obtain assay results to evaluate a subject's enrollment, or continued participation in a research study or clinical trial. In some cases, a research professional can classify the severity of a subject's condition, based on assay results. In some cases, a research professional can communicate a subject's assay results to a medical professional. In some cases, a research professional can refer a subject to a medical professional for clinical assessment of hematological neoplasia, and treatment thereof. Any appropriate method can be used to communicate information to another person (e.g., a professional). For example, information can be given directly or indirectly to a professional. For example, a laboratory technician can input the assay results into a computer-based record. In some cases, information is communicated by making a physical alteration to medical or research records. For example, a medical professional can make a permanent notation or flag a medical record for

communicating a diagnosis to other medical professionals reviewing the record. In addition, any type of communication can be used to communicate the information. For example, mail, e-mail, telephone, and face-to-face interactions can be used. The information also can be communicated to a professional by making that information electronically available to the professional. For example, the information can be communicated to a professional by placing the information on a computer database such that the professional can access the information. In addition, the information can be communicated to a hospital, clinic, or research facility serving as an agent for the professional.

It is noted that a single sample can be analyzed for one hematological cancer-specific marker or for multiple hematological neoplasm- specific markers. In preferred embodiments, a single sample is analyzed for multiple hematological neoplasm-specific markers, for example, using multi-marker assays. In addition, multiple samples can be collected for a single mammal and analyzed as described herein. In some embodiments, a sample is split into first and second portions, where the first portion undergoes cytological analysis and the second portion undergoes further purification or processing (e.g., sequence-specific capture step(s) (e.g., for isolation of specific markers for analysis of methylation levels). In some embodiments, the sample undergoes one or more preprocessing steps before being split into portions. In some embodiments, the sample is treated, handled, or preserved in a manner that promotes DNA integrity and/or inhibits DNA degradation (e.g., through use of storage buffers with stabilizing agents (e.g., chelating agents, DNase inhibitors) or handling or processing techniques that promote DNA integrity (e.g., immediate processing or storage at low temperature (e.g., -80 degrees C)). Some embodiments of the invention provides a diagnostic kit for the diagnosis or screening of cancer comprising one or reagents for detection of methylation status of the genes selected from, for example one or more . For example, in some embodiments, the reagents comprise nucleic acids (e.g., oligonucleotides, primers, probes, etc.). In some embodiments, kits provide reagents useful, necessary or sufficient for detecting methylation status and/or providing a diagnosis or prognosis.

The diagnostic kits may further comprise any reagent or media necessary, sufficient or useful to perform analyses, such as PCR analyses, such as methylation specific polymerase chain reaction (MSP) sequence analyses, bisulphite treatment, bisulphite sequencing, electrophoresis, pyrosequencing, mass spectrometry and sequence analyses by restriction digestion, next generation sequencing, quantitative and/or qualitative methylation, pyrosequencing, Southern blotting, restriction landmark genome scanning (RLGS), single nucleotide primer extension, CpG island microarray, SNUPE, COBRA, mass spectrometry, by use of methylation specific restriction enzymes or by measuring the expression level of said genes. In particular, the kit may further comprise one or more components selected from the group consisting of: deoxyribonucleoside triphosphates, buffers, stabilizers, thermostable DNA polymerases, restriction endonucleases (including methylation specific endonucleases), and labels (including fluorescent, chemiluminescent and radioactive labels). The diagnostic assay according to the invention may further comprise one or more reagents required for isolation of DNA.

In some embodiments, the kits of the present invention include a means for containing the reagents in close confinement for commercial sale such as, e.g., injection or blow-molded plastic containers into which the desired reagent are retained. Other containers suitable for conducting certain steps of the disclosed methods also may be provided.

In some embodiments, the present disclosure provides compositions (e.g., reaction mixtures) comprising a methylation specific detection reagent complexed to one or more genes (e.g., those described herein).

In some embodiments, the methods disclosed herein are useful in monitoring the treatment of hematological cancers (e.g., lymphoma or leukemia). For example, in some embodiments, the methods may be performed immediately before, during and/or after a treatment to monitor treatment success. In some embodiments, the methods are performed at intervals on disease free patients to ensure treatment success.

The present invention also provides a variety of computer-related embodiments. Specifically, in some embodiments the invention provides computer programming for analyzing and comparing a pattern of hematological cancer-specific marker detection results in a sample obtained from a subject to, for example, a library of such marker patterns known to be indicative of the presence or absence of a hematological cancer, or a particular stage or prognosis of a hematological cancer.

In some embodiments, the present invention provides computer programming for analyzing and comparing a first and a second pattern of hematological cancer-specific marker detection results from a sample taken at least two different time points. In some

embodiments, the first pattern may be indicative of a pre-cancerous condition and/or low risk condition for a hematological cancer and/or progression from a pre-cancerous condition to a cancerous condition. In such embodiments, the comparing provides for monitoring of the progression of the condition from the first time point to the second time point.

In some embodiments, a processor (e.g., computer) uses an algorithm (e.g., software) specific for interpreting the level, presence, and/or frequency of methylation of biomarkers for a hematological cancer as determined with the methods of the present invention. In some embodiments, the biomarkers determined with the methods of the present invention are inputed into such an algorithm, and a report of the presence, absence, characterization, or prognosis of a hematological cancer is generated based upon a comparison of such input with established norms (e.g., established norm for hematological cancer or healthy individuals, established norm for various risk levels for developing a hematological cancer, established norm for subjects undergoing treatment or diagnosed with a hematological cancer. In some embodiments, the risk profile indicates a subject's risk for developing a hematological cancer or recurrence of a hematological cancer. In some embodiments, the risk profile indicates risk based on a population average at a desired level of specificity (e.g., 90%).

In yet another embodiment, the invention provides computer programming for analyzing and comparing a pattern of hematological cancer-specific marker detection results from a sample to a library of hematological cancer-specific marker patterns known to be indicative of the presence or absence of a hematological cancer, wherein the comparing provides, for example, a differential diagnosis between an aggressively malignant hematological cancer and a less aggressive hematological cancer (e.g., the marker pattern provides for staging and/or grading of the cancerous condition).

The methods and systems described herein can be implemented in numerous ways. In one embodiment, the methods involve use of a communications infrastructure, for example the internet. Several embodiments of the invention are discussed below. It is also to be understood that the present invention may be implemented in various forms of hardware, software, firmware, processors, distributed servers (e.g., as used in cloud computing) or a combination thereof. The methods and systems described herein can be implemented as a combination of hardware and software. The software can be implemented as an application program tangibly embodied on a program storage device, or different portions of the software implemented in the user's computing environment (e.g., as an applet) and on the reviewer's computing environment, where the reviewer may be located at a remote site (e.g., at a service provider's facility).

For example, during or after data input by the user, portions of the data processing can be performed in the user-side computing environment. For example, the user-side computing environment can be programmed to provide for defined test codes to denote platform, carrier/diagnostic test, or both; processing of data using defined flags, and/or generation of flag configurations, where the responses are transmitted as processed or partially processed responses to the reviewer's computing environment in the form of test code and flag configurations for subsequent execution of one or more algorithms to provide a results and/or generate a report in the reviewer's computing environment.

The application program for executing the algorithms described herein may be uploaded to, and executed by, a machine comprising any suitable architecture. In general, the machine involves a computer platform having hardware such as one or more central processing units (CPU), a random access memory (RAM), and input/output (I/O) interface(s). The computer platform also includes an operating system and microinstruction code. The various processes and functions described herein may either be part of the microinstruction code or part of the application program (or a combination thereof) which is executed via the operating system. In addition, various other peripheral devices may be connected to the computer platform such as an additional data storage device and a printing device.

As a computer system, the system generally includes a processor unit. The processor unit operates to receive information, which generally includes test data (e.g., specific gene products assayed), and test result data (e.g., the pattern of hematological neoplasm-specific marker detection results from a sample). This information received can be stored at least temporarily in a database, and data analyzed in comparison to a library of marker patterns known to be indicative of the presence or absence of a pre-cancerous condition, or known to be indicative of a stage and/or grade of hematological cancer.

Part or all of the input and output data can also be sent electronically; certain output data (e.g., reports) can be sent electronically or telephonically (e.g., by facsimile, e.g., using devices such as fax back). Exemplary output receiving devices can include a display element, a printer, a facsimile device and the like. Electronic forms of transmission and/or display can include email, interactive television, and the like. In some embodiments, all or a portion of the input data and/or all or a portion of the output data (e.g., usually at least the library of the pattern of hematological neoplasm-specific marker detection results known to be indicative of the presence or absence of a pre-cancerous condition) are maintained on a server for access, e.g., confidential access. The results may be accessed or sent to professionals as desired.

A system for use in the methods described herein generally includes at least one computer processor (e.g., where the method is carried out in its entirety at a single site) or at least two networked computer processors (e.g., where detected marker data for a sample obtained from a subject is to be input by a user (e.g., a technician or someone performing the assays)) and transmitted to a remote site to a second computer processor for analysis (e.g., where the pattern of hematological cancer-specific marker) detection results is compared to a library of patterns known to be indicative of the presence or absence of a pre-cancerous condition), where the first and second computer processors are connected by a network, e.g., via an intranet or internet). The system can also include a user component(s) for input; and a reviewer component(s) for review of data, and generation of reports, including detection of a pre-cancerous condition, staging and/or grading of a hematological cancer, or monitoring the progression of a pre-cancerous condition or a hematological cancer. Additional components of the system can include a server component(s); and a database(s) for storing data (e.g., as in a database of report elements, e.g., a library of marker patterns known to be indicative of the presence or absence of a pre-cancerous condition and/or known to be indicative of a grade and/or a stage of a hematological cancer, or a relational database (RDB) which can include data input by the user and data output. The computer processors can be processors that are typically found in personal desktop computers (e.g., IBM, Dell, Macintosh), portable computers, mainframes, minicomputers, tablet computer, smart phone, or other computing devices.

The input components can be complete, stand-alone personal computers offering a full range of power and features to run applications. The user component usually operates under any desired operating system and includes a communication element (e.g., a modem or other hardware for connecting to a network using a cellular phone network, Wi-Fi, Bluetooth, Ethernet, etc.), one or more input devices (e.g., a keyboard, mouse, keypad, or other device used to transfer information or commands), a storage element (e.g., a hard drive or other computer-readable, computer-writable storage medium), and a display element (e.g., a monitor, television, LCD, LED, or other display device that conveys information to the user). The user enters input commands into the computer processor through an input device.

Generally, the user interface is a graphical user interface (GUI) written for web browser applications.

The server component(s) can be a personal computer, a minicomputer, or a mainframe, or distributed across multiple servers (e.g., as in cloud computing applications) and offers data management, information sharing between clients, network administration and security. The application and any databases used can be on the same or different servers. Other computing arrangements for the user and server(s), including processing on a single machine such as a mainframe, a collection of machines, or other suitable configuration are contemplated. In general, the user and server machines work together to accomplish the processing of the present invention.

Where used, the database(s) is usually connected to the database server component and can be any device which will hold data. For example, the database can be any magnetic or optical storing device for a computer (e.g., CDROM, internal hard drive, tape drive). The database can be located remote to the server component (with access via a network, modem, etc.) or locally to the server component.

Where used in the system and methods, the database can be a relational database that is organized and accessed according to relationships between data items. The relational database is generally composed of a plurality of tables (entities). The rows of a table represent records (collections of information about separate items) and the columns represent fields (particular attributes of a record). In its simplest conception, the relational database is a collection of data entries that "relate" to each other through at least one common field.

Additional workstations equipped with computers and printers may be used at point of service to enter data and, in some embodiments, generate appropriate reports, if desired. The computer(s) can have a shortcut (e.g., on the desktop) to launch the application to facilitate initiation of data entry, transmission, analysis, report receipt, etc. as desired.

In certain embodiments, the present invention provides methods for obtaining a subject's risk profile for developing hematological cancer (e.g., leukemia or lymphoma). In some embodiments, such methods involve obtaining a blood or blood product sample from a subject (e.g., a human at risk for developing hematological cancer; a human undergoing a routine physical examination), detecting the presence, absence, or level (e.g., methylation frequency or score) of one or more markers specific for a hematological cancer in or associated with the blood or blood product sample (e.g., specific for a hematological cancer) in the sample, and generating a risk profile for developing hematological cancer (e.g., leukemia or lymphoma based upon the detected level (score, frequency) or presence or absence of the indicators of hematological cancer. For example, in some embodiments, a generated risk profile will change depending upon specific markers and detected as present or absent or at defined threshold levels. The present invention is not limited to a particular manner of generating the risk profile. In some embodiments, a processor (e.g., computer) is used to generate such a risk profile. In some embodiments, the processor uses an algorithm (e.g., software) specific for interpreting the presence and absence of specific exfoliated epithelial markers as determined with the methods of the present invention. In some embodiments, the presence and absence of specific markers as determined with the methods of the present invention are imputed into such an algorithm, and the risk profile is reported based upon a comparison of such input with established norms (e.g., established norm for pre-cancerous condition, established norm for various risk levels for developing

hematological cancer, established norm for subjects diagnosed with various stages of hematological cancer). In some embodiments, the risk profile indicates a subject's risk for developing hematological cancer or a subject's risk for re-developing hematological cancer. In some embodiments, the risk profile indicates a subject to be, for example, a very low, a low, a moderate, a high, and a very high chance of developing or re-developing

hematological cancer or having a poor prognosis (e.g., likelihood of long term survival) from hematological cancer. In some embodiments, a health care provider (e.g., an oncologist) will use such a risk profile in determining a course of treatment or intervention (e.g., biopsy, wait and see, referral to an oncologist, referral to a surgeon, etc.).

EXPERIMENTAL

The following examples are provided in order to demonstrate and further illustrate certain preferred embodiments and aspects of the present invention and are not to be construed as limiting the scope thereof.

Example 1

Material and Methods

Patients and cell lines

In the present study DNA from 62 fresh-frozen biopsies of patients diagnosed with B- cell lymphoma was utilized (activated B cell like diffuse large B-cell lymphoma (DLBCL ABC); n = 17, germinal centre cell like diffuse large B-cell lymphoma (DLBCL GCB); n = 18, primary mediastinal B-cell lymphoma (PMBL); n = 6, follicular lymphoma (FL); n = 14 and Burkit s lymphoma (BL), η = Ί) and 43 various healthy donors (CD19 B cells isolated from buffy coat with CD19⁺ Dynebeads (Invitogen) as previously described (Rasmussen et al., Journal of Immunological Methods 1992; 146: 195-202); n = 20, follicular hyperplasia samples; n = 9, peripheral blood mononuclear cells; n = 10, bone marrow, n = three and tonsils; n = 10). The patients included in this study had a median observation time of 36 months, and during this time eight out of 62 patients (13%) died. Additional information about the patients can be found in Table 1. Patients with BL were treated according to an intensified chemotherapy regimen with rituximab and FL patients, if in need of therapy, with rituximab monotherapy, cyclophosphamide, Vincristine, Predisolone (CVP) plus rituximab or cyclophospamide, doxorubicine, vincristine, prednisolone (CHOP) plus rituximab. DLBCL patients were treated with CHOP-like therapy plus rituximab.

Nineteen B-cell lymphoma cell lines were examined: (BL: BL41 (purchased from DSMZ, Germany), Namwalwa (J. Delabie), Raji and Ramos (DSMZ); DLBCL ABC: HLY-1 (kindly provided by Talal Al Saati, Department of Oncogenesis and Signaling in

Hematopoietic Cells, Inserm, France), OciLy3, OciLylO, and U2932 (kindly provided by L. Staudt, Metabolism Branch, Center for Cancer research, National Cancer Institute, National Institutes of Health, Bethesda, MD); DLBCL GCB: HS445, NUDHL1, OciLy2, OciLy7, OciLyl9, SUDHL4, and SUDHL10 (L. Staudt), SUDHL6 (DSMZ); and FL: K422 (J.

Delabie), SC-1 and ROS50 (DSMZ)). OciLy2, -3, -7, -10, and -19 were cultured in IMDM medium (Invitrogen) supplemented with 20% human plasma (SeraCare Life Sciences, Inc.; California, USA), 55 μΜ β-mercaptoethanol (Invitrogen), 100 Units/ml penicillin and 0.1 mg/ml streptomycin (PAA Laboratories) at 37°C with 5% C0₂. The remaining lymphoma cell lines were cultured in RPMI 1640 (PAA Laboratories, Austria), supplemented with 10% fetal calf serum (PAA Laboratories), 100 Units/ml penicillin and 0.1 mg/ml streptomycin

(PAA Laboratories) at 37°C with 5% C0₂. All cell lines have been authenticated by STR-loci analysis, which has been compared to the database of DMZG. The STR results of non- commercially available cell lines are listed in Table 2.

Nucleic acid isolation

The AllPrep DNA/RNA/protein Kit from Qiagen was used to isolate DNA and total RNA; the concentrations were measured using the ND-1000 Nanodrop. RNA quality was measured with the 2100 Bioanalyzer. Epigenetic treatment of lymphoma cell lines

The B-cell lymphoma cell lines Raji, BL41, Ramos, HLY-1, OciLy3, OciLylO, SUDHL4, SUDHL6, K422, SC-1, ROS50 were treated with a combination of the demethylating reagent 5-aza-2'deoxycytidine (aza; 1 μΜ for 72 h) and the histone deacetylase inhibitor trichostatin A (TSA; 0.5 μΜ added the last 12 h). Cell lines cultured in parallel without treatment were used as a control.

Gene expression microarray analysis

Epigenetically treated cell lines and their untreated counterparts were analyzed with the Applied Biosystems Human Genome Survey Microarray following manufacturer's protocol. In brief, 1.5 μg of total RNA was labeled using the Chemiluminiescent RT-IVT Labeling Kit from Applied Biosystems. Hybridization was performed at 55°C for 16h using 10 μg of the labeled cRNA. Chemiluminescence detection and image analysis were performed using Applied Biosystems Chemiluminescence Detection Kit and Applied Biosystems 1700 Chemiluminescent Microarray Analyzer according to the manufacturer's protocol. Post-processing and normalization was done with the R-script "ABarray" and Bioconductor. Only array elements that were at least 2-fold up-regulated after the epigenetic treatment in at least 6 out of the 11 analyzed cell lines, were considered to be methylated candidate genes in B-cell lymphoma cell lines.

Gene expression data from 480 B-cell lymphomas (BL n = 24, GSE 4732 (Amara et al, Ann Oncol 2008; 19: 1774-86.); DLBCL ABC n = 168 (Bennett et al, Genes

Chromosom.Cancer 2009), GSE 10846; DLBCL GC n = 97 (Bennett et al, Genes

Chromosom.Cancer 2009), GSE10846; FL n = 191) were accessible for the project from the Leukemia Lymphoma Molecular Profiling Project (LLMPP). To compare the tumor gene expression to healthy donors, RNA from CD19 -B cells (n = 5) was analyzed on the same Affymetrix HG-U133 Plus 2.0 arrays and were normalized with the same protocol as the tumor samples in a LLMPP facility.

Experimental strategy for identifying methylated candidate genes

To increase the likelihood of selecting appropriate candidates for DNA methylation in

B-cell lymphomas, a multistep strategy focusing on genes that in addition to being upregulated by epigenetic treatment in cell lines were also downregulated in lymphomas compared to normal CD19 -B cells was utilzed. The candidate genes were subject to further analyses in cancer cell lines (MSP) and finally in patient material (qMSP) (Figure 1). Methylation specific polymerase chain reaction (MSP)

All DNA methylation candidates from the array approach mentioned above were analyzed using the RefSeqs from the UCSC Genome browser database and default settings in the CpG Island Searcher Software (Takai D, Proceedings of the National Academy of

Sciences of the United States of America 2002; 99:3740-5) in order to see if they had a CpG island present in their promoter. The input sequence included 1000 bp upstream and 500 bp downstream of the transcription start site.

Genes containing a promoter CpG-Island were analyzed by MSP in all cell lines (n = 19) and in CD19 -B cells. Primers were designed using the Methyl Primer Express 1.0

Applied Biosystems, their sequences are provided in Table 3. DNA from normal blood and in vitro Sssl methyltransferase (New England Biolabs Inc.) treated methylated DNA (Human placenta DNA (Sigma), was used as an unmethylated and methylated positive control, respectively, and dH₂0 replacing the bisulfite template was the negative control in both reactions.

For each sample, 1.3 μg DNA was bisulfite treated with the EpiTect bisulfite kit (Qiagen), according to the manufacturer's protocol. For the MSP reaction the HotStarTaq polymerase (0.6 units) was used along with lOx PCR buffer containing MgCl₂ (all Qiagen), dNTP mix (ΙΟηΜ each; Roche), and 20pmol of each primer (Euro fins MWG operon, Germany). Approximately 32.5ng bisulfite-converted DNA was used as template and the total volume of the PCR reactions was 25 μΐ. The following PCR program was used: 15 min at 95°C to activate the enzyme; followed by 35 cycles: 95°C for 30 sec (denaturation), annealing for 30 sec, and 72°C for 30 sec (elongation). A final elongation at 72°C for 7 min completed the PCR reaction. PCR products were loaded on a 2% agarose gel, stained with SYBR Safe (Invitrogen), and visualized by UV irradiation using a Geldoc (Biorad). For all samples and all genes two independent PCR reactions were performed.

Bisulfite sequencing

Bisulfite sequencing primers were designed using Methyl Primer Express 1.0

(Applied Biosystems) to flank the MSP primer binding sites in the respective gene promoter. Primer sequences and annealing temperatures are provided in Table 3. The same initial PCR conditions as for the MSP was applied. PCR products were cleaned from excess primer and nucleotides with ExoSAP-IT (GE Healthcare) following the manufactures instructions. The purified products were sequenced using the Big Dye sequencing kit 1.1 in an ABI Prism 3700 Genetic Analyzer (Applied Biosystems). The approximate amount of methyl cytosine of each CpG site was calculated by comparing the peak height of the cytosine signal with the sum of the cytosine and thymine peak height signals. Unmethylated CpG sites included ratios between 0 and 0.20, partially methylated included ratios from 0.21 to 0.80, and a ratio from 0.81 to 1.0 was considered to be fully methylated.

Quantitative methylation-specific polymerase chain reaction (qMSP)

Primers and probes for qMSP were designed with Applied Biosystems Primer Express 3.0 Software to anneal to bisulfite treated and fully methylated DNA (sequences are provided in Table 3). In a 20 μΐ reaction approximately 32.5 ng bisulfite treated DNA was used as template in addition to 10 μΐ 2xTaqMan Universal PCR Master Mix No AmpErase UNG (Applied Biosystems), 100 μΜ of forward and reverse primer and 10 μΜ probe. The PCR program started with an incubation step at 95°C for 10 min, followed by 45 cycles of 95°C for 15 sec and 60°C for 1 min. The samples were run in triplicates on a ABI Prism 7900 HT Sequence detection system and analyzed with the sequence detector system 2.3 (Applied Biosystems). The analyzed genes were normalized for DNA input using ALU-C4 as a reference gene (Weisenberger et al, Nucl. Acids Res. 33:6823-36). A standard curve of bisulfite treated universal methylated DNA (Chemicon, Millipore) was used to determine the quantity of methylated DNA in each sample.

For all samples, amplification after cycle 35 was censored. The percent of methylated reference (PMR) was calculated by using the median GENE: ALU ratio of a sample and divided it by the median GENE: ALU ratio of the positive control (CpGenome Universally Methylated DNA) and multiplied it by 100. The highest PMR value across the healthy controls was used as a threshold for scoring samples as methylation positive (Table 4).

Results

Identification of methylated candidate genes in B-cell lymphoma

The epigenetic treatment of B-cell lymphoma cell lines (BL: Raji, BL41, Ramos; DLBCL ABC: HLY-1, OciLy3, OciLylO; DLBCL GC: SUDHL4, SUDHL6; FL: K422, SC- 1, ROS50) with 5-aza-2'deoxycytidine (aza) and Trichostatin A (TSA) and a subsequent genome-wide expression analysis revealed that 2027 array elements were upregulated a minimum of two fold in at least 6 out of the 11 analyzed cell lines (Figure 2a). From a dataset of 638 B-cell lymphomas (Figure 2b) and normal peripherial blood CD19 -B cells (Figure 2c), 5736 downregulated array elements were identified and ranked according to their degree of downregulation. The overlap between the two microarray datasets consisted of 233 genes, which were considered to be potential epigenetically downregulated genes in B-cell lymphoma. Analysis of methylation candidates in cell lines using methylation specific PCR

(MSP)

The promoter regions of the top 30 of 233 genes from the combined methylation candidate gene list were analyzed for the presence of CpG-islands. With the exception of CD69 and SLC2A3, all candidate genes had a promoter CpG-island. The majority of the analyzed genes displayed variable promoter methylation frequencies among the 19 B-cell lymphoma cell lines, and were unmethylated in normal B cells (Table 5). Seven of the candidates (25%) were unmethylated in all cell lines and may represent genes lacking histone acetylation, reactivated by the combined treatment with aza and TSA. Eight genes

(COMMD6, DSP, FZD8, KCNH2, KLF9, MTSSI, NR4A2, and PPP1R14A) were individually methylated in more than 70% of the cell lines, and were further subjected to quantitative methylation analysis in patient and normal samples.

Bisulfite sequencing of promoter CpG sites

Prior to designing qMSP primers and probes, the methylation status of the individual CpG sites in parts of the promoter of the candidates (DSP, FZD8, KLF9, MTSSI, and NR4A2) was analyzed by bisulfite sequencing. The gene PPP1R14A has previously been sequenced and was therefore not included in the bisulfite sequencing. In addition to validating the methylation status as assessed by the MSP analysis (Figure 3), the bisulfite sequencing results confirmed that all non-methylated cytosines were converted to thymines.

Quantitative methylation analysis of patients and healthy donors

By qMSP the promoter methylation status of COMMD6, KLF9, MTSSI, NR4A2, KCNH2, DSP, FZD8, and PPP1R14A was analyzed in 37 NHL patients and CD19⁺-B cells from 10 healthy donors. The overall promoter methylation across all analyzed NHL types was 0%, 3%, 19%, 22%, 22%, 28%, 67%, and 78%, respectively. All genes were

unmethylated (PMR = 0) in CD19 -B-cells from healthy donors, with the exception of the gene MTSSI and KCNH2, which showed some methylation among the healthy controls (PMR = 0-4%) (Figure 4 and Table 6). The four best-performing candidates from the test series (DSP, FZD8, KCNH2, and PPP1R14A) were further subjected to promoter methylation analyses in a validation series, which included additional NHL samples (n = 25) and healthy controls (bone marrow, tonsils, peripheral blood mononuclear cells and follicular hyperplasia samples, n = 42). The threshold for scoring methylation-positive samples from the test series was applied and it was possible to differentiate 80% (sensitivity) of the patients from healthy donors. The individual promoter-methylation frequencies of DSP, FZD8, KCNH2, and PPP1R14A across the different NHL types in the validation series was 40%, 60%>, 40%>, and 60%>, respectively (Figure 4 and Table 6). All genes were unmethylated in the analyzed healthy controls (100% specificity).

Receiver Operating Characteristics curves

The PMR values from the qMSP analysis were used to generate receiver operating characteristics (ROC) curves. Due to low methylation frequencies the genes KLF9, MTSS1, and NR4A2 were only analyzed in the test series, resulting in an area under the ROC curve (AUC) of 0.17, 0.34, and 0.44, respectively. The remaining genes DSP, FZD8, KCNH2, and PPP1R14A were analyzed in both the test and validation series and showed an individual AUC of 0.55, 0.85, 0.59 and 0.89, respectively across both series (Figure 5a, left panel). The combined panel of DSP, FZD8, KCNH2, and PPP1R14A, based on the sum of the PMR values, generated an AUC of 0.96 (Figure 5b, right panel).

Table 1 : Patient characteristics

The international prognostic index (IPI) and follicular lymphoma IPI (FLIPI) status or stage could not be obtained from every patient. Aberrations: Burkit s lymphoma (BL), diffuse large B-cell lymphoma (DLBCL) activated B-cell type (ABC), germinal center B-cell type (GCB), follicular lymphoma (FL) and primary mediastinal B-cell lymphoma (PMBL).

test serie

Numfeer of BL 7 0

Number of DLBC L GCf

Staoe 3-4

FtJP tow ii

btaae 1

Number of P BL

Sta e :J-4

Medi n age, year (m«¾«) ii (34-73) S6 ( -81

Table 2. Data from STR locus analysis of non-commercially available cell lines.

Table 3. Primer sequences and amplicon lengths for qMSP analysis.

qMSP SEQ SEQ SEQ

ID ID ID Amplicon

Sense primer No. Antisense primer No. Probe No. length

COMMD6 GCGTTAGGTCGTTAGGGGTAGG 119 ACTTAACATCCAACGACGACTCG 126 GACGTTGTTTATGGAGGCG 133 128

DSP GGAGGAGATTCGTTTCGTCG 120 AATCGCTACTCGCTACCTAAACCC 127 1 1 I CGACG IAG I 1 1 1 1 1 I GCG I 1 134 170

FZD8 GAAGTGATTTCGTTGTTGGTCG 121 GATACCCTTACACAACGACACGATAAT 128 GGCGTTGTTGTAGCGTT 135 117

KCNH2 GTATTGGATCGGTTGGGCG 122 GCAACCCGCCCAAACTC 129 ATAGGTTCGGTTGTTGGC 136 124

KLF9 CGTGAGTTAGGAGGTTCGGATC 123 CGTTTCGCTACCTCGTACTA 130 GTTACGGGATCGCGAGGT 137 139

MTSS1 CGTTAGGTAGGGTGTCGATACGT 124 GCCTCCCTCTCCAAAGCCA 131 TTTCGCGTTGCGACGG 138 99

NR4A2 TAAAATCGGTTTTGTTCGTGACG 125 ATTTATATAACTT ACG CTACCG CT A 132 TAGGTCGGAAATATATTAAAGCGA 139 168

Table 4. PMR-threshold for methylated genes. The highest PMR value across the healthy controls was used as a threshold for scoring samples as methylation positive.

5

Table 5: Methylation status of candidate genes in 19 B-cell lymphoma cell lines as well as CD19⁺-B-cells. MSP analysis of 28 gene promoters in 19 B-cell lymphoma cell lines. A methylated promoter region is represented by M and an unmethylated by an U. Genes have been sorted by their methyl

Table 6: Methylation frequencies and range of PMR values (brackets) assessed by qMSP in the clinical test and validation sets. The various healthy controls were unmethylated in all analyzed markers. Aberrations: Burkitf s lymphoma (BL), diffuse large B-cell lymphoma (DLBCL) activated B-cell type (ABC), germinal center B-cell type (GCB), follicular lymphoma (FL), primary mediastinal B-cell lymphoma (PMBL) and non-Hodgkin lymphoma (NHL).

Test series BL DLBCL DLBCL FL NHL

ABC GCB

0/6 (0%) 0/10 (0%) 0/10 (0%) 0/10 (0%) 0/36 (0%)

COMMD6

[0] [0] [0] [0] [0]

1/6 (17%) 4/10 (40%) 4/10 (40%) 1/10 (10%) 10/36 (28%)

DSP

[16] [7-24] [1 1-34] [3] [3-34]

6/6 (100%) 7/10 (70%) 4/10 (40%) 7/10 (70%) 24/36 (67%)

FZD8

[2-92] [4-68] [3-47] [5-45] [2-92]

3/6 (50%) 1/10 (10%) 1/10 (10%) 3/10 (30%) 8/36 (22%)

KCNH2

[6-22] [19] [5] [7-47] [5-47]

0/7 (0%) 0/10 (0%) 1/10 (10%) 0/10 (0%) 1/37 (3%)

KLF9

[0] [1] [25] [0] [1-25]

2/7 (28%) 3/10 (30%) 1/10 (10%) 1/10 (30%) 7/37 (19%)

MTSS1

[8-48] [8-25] [29] [12] [8-48]

1/7 (14%) 3/10 (30%) 4/10 (40%) 0/10 (0%) 8/37 (22%)

NR4A2

[10] [13-28] [2-47] [0] [2-47]

4/6 (57%) 9/10 (90%) 8/10 (80%) 7/10 (70%) 28/36 (78%)

PPP1R14A

[2-24] [2-52] [4-39] [2-42] [2-52]

combined panel 100 % 100 % 80 % 100 % 95 %

Validation series DLBCL DLBCL FL PMBL NHL

ABC GCB

3/8 (38%) 3/7 (43%) 1/4 (25%) 3/6 (50%) 10/25 (40%)

DSP

[18-28] [23-70] [44] [24-67] [18-70]

6/8 (75%) 3/7 (43%) 2/4 (50%) 4/6 (67%) 15/25 (60%)

FZD8

[2-65] [6-54] [14-24] [3-63] [2-65]

2/8 (25%) 5/7 (72%) 1/4 (25%) 2/6 (34%) 10/25 (40%)

KCNH2

[5-6] [10-23] [16] [25-50] [5-50]

6/8 (75%) 5/7 (72%) 3/4 (75%) 1/6 (17%) 15/25 (60%)

PPP1R14A

[9-54] [15-84] [9-30] [39] [9-84]

combined panel 88 % 100 % 75 % 67 % 83 %

Example 2 Materials and Methods

Patients and cell lines

DNA from 60 patients diagnosed with B-cell lymphoma (germinal center B cell-like (GCB) (n = 17) and activated B cell-like (ABC) (n = 18) subtypes of diffuse large B cell lymphoma (DLBCL), primary mediastinal B-cell lymphoma (n = 6), follicular lymphoma (FL) (n=12) and Burkitt's lymphoma (BL, n=7)) was utilzed. Further, several healthy controls (n = 49) were included; e.g. CD19⁺ B cells isolated from buffy coat with CD19⁺ Dynebeads (Invitogen) as previously described (Rasmussen et al, Journal of Immunological Methods 1992; 146: 195-202); n = 20, follicular hyperplasia samples; n = 9, peripheral blood mononuclear cells; n = 10; and tonsils; n = 10. The patients included in this study had a median observation time of 36 months, and during this time eight out of 60 patients (13%) died. Additional information about the patients can be found in Table 7. Patients with BL were treated according to an intensified chemotherapy regimen with rituximab (GMALL 2002) and FL patients, if in need of therapy, with rituximab monotherapy, cyclophosphamide, Vincristine, Predisolone (CVP) plus rituximab or cyclophospamide, doxorubicine, vincristine, prednisolone (CHOP) plus rituximab. DLBCL patients were treated with CHOP- like therapy plus rituximab.

In addition 12 B-cell lymphoma cell lines (BL: BL41 (purchased from DSMZ, Germany), Raji and Ramos (DSMZ); DLBCL ABC: HLY-1 (gift from Talal Al Saati, Department of Oncogenesis and Signaling in Hematopoietic Cells, Inserm, France), OciLy3, and OciLylO (kindly provided by L. Staudt, Metabolism Branch, Center for Cancer research, National Cancer Institute, National Institutes of Health, Bethesda, MD); DLBCL GCB:

OciLy7 and SUDHL4 (L. Staudt), SUDHL6 (DSMZ); and FL: K422 (J. Delabie), SC-1 and ROS50 (DSMZ) were included. The culturing conditions were as followed: OciLy-3, -7 and - 10 were cultured in IMDM medium (Invitrogen) supplemented with 20% human plasma

(SeraCare Life Sciences, Inc. (California, USA)), 55 μΜ β-mercaptoethanol (Invitrogen), 100 Units/ml penicillin and 0.1 mg/ml streptomycin (PAA Laboratories) at 37°C with 5% C0₂. The remaining lymphoma cell lines were cultured in RPMI 1640 (PAA Laboratories, Austria), supplemented with 10% fetal calf serum (PAA Laboratories, Austria), 100 Units/ml penicillin and 0.1 mg/ml streptomycin (PAA Laboratories, Austria) at 37°C with 5% C0₂. Nucleic acid isolation

The AllPrep DNA/RNA/protein Kit from Qiagen was used to isolate DNA and total RNA; the concentrations were measured using the ND-1000 Nanodrop. RNA quality was measured with the 2100 Bioanalyzer.

Epigenetic treatment of lymphoma cell lines

The B-cell lymphoma cell lines BL41, Raji, Ramos, HLY-1, OciLy3, OciLy7, OciLylO, SUDHL4, SUDHL6, K422, SC-1, ROS50 were treated with a combination of the demethylating reagent 5-aza-2'deoxycytidine (aza; 1 μΜ for 72 h) and the histone deacetylase inhibitor trichostatin A (TSA; 0.5 μΜ added the last 12 h). Cell lines cultured in parallel without treatment were used as a control.

Gene expression microarray analysis

Epigenetically treated cell lines and their untreated counterparts were analyzed with the Applied Biosystems Human Genome Survey Microarray following manufacturer's protocol. In brief, 1.5 μg of total RNA was labeled using the Chemiluminiescent RT-IVT Labeling Kit from Applied Biosystems. Hybridization was performed at 55°C for 16h using 10 μg of the labeled cRNA. Chemiluminescence detection and image analysis were performed using Applied Biosystems Chemiluminescence Detection Kit and Applied Biosystems 1700 Chemiluminescent Microarray Analyzer according to the manufacturer's protocol. Post-processing and normalization was done with the R-script "ABarray" and Bioconductor. Only array elements that were at least 2-fold up-regulated after the epigenetic treatment in at least 6 out of the 11 analyzed cell lines, were considered to be methylated candidate genes in B-cell lymphoma cell lines.

Gene expression data from 480 B-cell lymphomas (BL n = 24, GSE 4732 (Dave SS,

Fu K, Wright GW, Lam LT, Kluin P, Boerma EJ et al. Molecular Diagnosis of Burkitt's Lymphoma. N Engl J Med 2006; 354:2431-42)); DLBCL ABC n = 168 (Alizadeh AA, Eisen MB, Davis RE, Ma C, Lossos IS, Rosenwald A et al. Distinct types of diffuse large B-cell lymphoma identified by gene expression profiling. Nature 2000; 403:503-11), GSE10846; DLBCL GC n = 97 (Alizadeh et al, supra), GSE10846; FL n = 191, unpublished) were accessible for the project from the Leukemia Lymphoma Molecular Profiling Project (LLMPP). To compare the tumor gene expression to healthy donors, RNA from CD19 -B cells (n = 5) was analyzed on the same Affymetrix HG-U133 Plus 2.0 arrays and were normalized with the same protocol as the tumor samples in a LLMPP facility. Bisulphite Treatment and Methylation specific polymerase chain reaction (MSP)

The default settings in the CpG Island Searcher Software (Takai D, Jones PA.

Comprehensive analysis of CpG islands in human chromosomes 21 and 22. Proceedings of the National Academy of Sciences of the United States of America 2002; 99:3740-5) and the RefSeqs from the UCSC Genome browser database was used to analyze for the presence of promoter CpG islands. The input sequence included 1000 bp upstream and 500 bp downstream of the transcription start site. Genes containing a promoter CpG-Island were analyzed by MSP in B-cell lymphoma cell lines and CD19⁺ B-cells.

Primers were designed using the Methyl Primer Express 1.0 Applied Biosystems.

DNA from normal blood and in vitro methylated DNA (Human placenta DNA (Sigma), Sssl methyltransferase (New England Biolabs Inc.)) was used as an unmethylated and methylated positive control, respectively. H₂0 replaced the bisulphite template in the negative control for both reactions. For each sample, 1.3 μg DNA was bisulphite treated with the EpiTect bisulphite kit (Qiagen). The HotStarTaq polymerase (0.6 units) along with lOx PCR buffer and MgCl₂ (all Qiagen), dNTP mix (ΙΟηΜ each (Roche)) and 20pmol of each primer (Euro fins MWG operon, Germany) were used for a 25 μΐ volume PCR reaction. The following PCR conditions were used: 15 min, 95°C incubation; followed by 35 cycles: 95°C for 30 seconds, annealing temperature for 30 seconds and 72°C for 30 seconds; elongation with 72°C for 7 minutes finished the PCR reaction. PCR products were loaded on a 2% agarose gel, stained with SYBR Safe (Invitrogen). To validate each result, an independent run of each PCR reaction was performed.

Bisulfite sequencing

Primers for the bisulfite sequencing were designed using Methyl Primer Express 1.0

Applied Biosystems to amplify the respective MSP primer binding sites. The same PCR conditions as for the MSP were applied. Further, the PCR products were cleaned from excess primer and nucleotides with ExoSAP-IT following the manufactures instructions. Using Big Dye sequencing kit in an ABI Prism 3700 Genetic Analyzer (Applied Biosystems) the purified products were sequenced. By comparing the peak height of the cytosine signal with the sum of the cytosine and thymine peak height signals, the approximate amount of methyl cytosine of each CpG site was calculated. Unmethylated CpG sites had a ratio between 0 and 0.20, partially methylated a ratio from 0.21 to 0.80, and a ratio from 0.81 to 1.0 was considered to be fully methylated. Quantitative methylation-specific polymerase chain reaction (qMSP)

Primers and probes for qMSP (Table 8), which bind bisulfite treated and methylated DNA, were designed with Applied Biosystems Primer Express 3.0 Software. In a 20 μΐ reaction, 32.5 ng bisulphite treated DNA was used as a template in addition to 10 μΐ

2xTaqMan Universal PCR Master Mix No AmpErase UNG (Applied Biosystems), 100 μΜ of forward and reverse primer and 10 μΜ probe. The PCR program started with an incubation step at 95°C for 10 minutes, followed by 45 cycles of 95°C for 15 seconds and 60°C for 1 minute. All samples were run in triplicates on a ABI Prism 7000 Sequence detection system and analyzed with the sequence detector system 2.3 (Applied Biosystems). By using ALU-C4 as a reference gene, the analyzed genes were normalized for DNA input (Weisenberger DJ, Campan M, Long TI, Kim M, Woods C, Fiala E et al. Analysis of repetitive element DNA methylation by MethyLight. Nucl.Acids Res. 33:6823-36). To determine the quantity of methylated DNA in each sample, a standard curve of bisulfate treated universal methylated DNA (Chemicon, Millipore) was used.

Results

Identification of genes which are upregulated after epigenetic treatment of B cell lines and are expressed at a low level in lymphoma patients

The top 24 candidate genes, which were upregulated after epigenetic treatment of cell lines and simultaneously expressed at low levels in lymphoma samples of the corresponding type were analyzed. These candidates were analyzed by MSP in 12 B-cell lymphoma cell lines and CD 19+ peripheral blood B cells from healthy donors. The gene promoters of BMPER, CDH1 and LRP12 were methylated in all analyzed B-cell lymphoma cell lines across all subtypes (Table 9). In addition, the following genes had a high promoter methylation frequency (CLU, DUSP4 andNPYlR (92%); BCL2L10 and CCL22 (83%)). Of note, BMP7 was methylated in all three ABC DLBCL cell lines and in two of three FL cell lines, but not in cell lines derived from BL or GCB DLBCL. It was the only gene showing a subype-specific methylation pattern in DLBCL cell lines. As can be expected from the combined treatment of aza and TSA, genes that were unmethylated in all cell lines tested, were also identified. Bisulfite sequencing of the BMP7-, BMPER-, CDHI- and LR /2-promoter

Before designing qMSP primers and probes, the promoter methylation of BMP7, BMPER, CDHI, DUSP4 and LRP12 was analyzed further by bisulfite sequencing. With this method one can determine the methylation status of single CpG-sites within the CpG-island promoter thereby validating the results obtained from the initial MSP. In general, the bisulphite sequencing revealed that all non-methylated cytosines were converted to thymines. All cell lines, which showed partial or complete methylation in MSP, revealed a partially or fully methylated CpG-site in the MSP-primer covering CpG-sites. Furthermore all cell lines being negative for promoter CpG-island methylation, were confirmed negative by bisulphite sequencing.

Investigation of the promoter methylation status from patients and healthy donors

BMPER, CDHI, DUSP4 and LRP12 promoter methylation in clinical samples was analyzed by qMSP in two series; the test series contained 30 NHL patients (ABC DLBCL, GCB DLBCL and FL; n = 10 each) and CD19⁺ peripheral blood B cells from healthy donors (n = 10). For the NHL patients in the test series, the methylation frequencies were 94%, 94% and 60% for LRP12, CDHI and BMPER, respectively (Figure 6). Due to a limited access to patient material, DUSP4 was only analyzed in the validation series. The analyzed control samples showed low PMR values, ranging from 0-3.7%. All, except one lymphoma sample, had a higher PMR value compared to the healthy samples. The highest PMR value obtained from the analyzed healthy samples were used to set a threshold (4%) for scoring. The validation series contained healthy donors (CD19⁺ B cells, tonsils and PBMC, n = 10 each; and follicular hyperplasia samples, n = 9), as well as the following patient material (DLBCL ABC, n = 8; DLBCL GCB, n = l; FL, n = 2; and PMBL, n = 6). The promoter methylation of LRP12, CDHI, BMPER and DUSP4 was 100%, 91%, 55%, and 32% across all analyzed subtypes in the validation series, respectively (Figure 6). Overall promoter methylation for all clinical samples from both series is shown in Table 10.

The 5 P7-promoter methylation status was analyzed by qMSP in 37 NHL patients and CD19⁺ B cells from 10 healthy donors. The promoter methylation of BMP7 was 0%, 40%, 30% and 50% in BL, FL, DLBCL ABC and DLBCL GCB, respectively. Thus, the subtype specific methylation pattern seen in DLBCL cell lines could not be confirmed in patient samples. The promoter of BMP7 showed no methylation in healthy donors (Figure 7 and Table 10). DUSP4 was methylated in 50% of DLBCL ABC and showed no methylation in DLBCL GCB.

Receiver Operating Characteristics (ROC) curves

The PMR values obtained from the qMSP analysis were used to generate receiver operating characteristics (ROC) curves. The genes of BMP7, BMPER, CDHl, DUSP4 and LRP12 showed an individual area under the curve (AUC) of 0.70, 0.83, 0.99, 0.73 and 0.99 (Figure 8a, left panel). By combining the panel one could discriminate all, except one, lymphoma samples (BL, DLBCL ABC, DLBCL GCB, FL, PMBL) from the various healthy controls (B cells, PBMC, tonsils, follicular hyperplasia) as showed by an AUC of 0.999 (Figure 8b, right panel).

Table 7: Patient characteristics. The international prognostic index (IPI) and follicular lymphoma IPI (FLIPI) status or stage could not be obtained from every patient. Aberrations: Burkit s lymphoma (BL), diffuse large B-cell lymphoma (DLBCL) activated B-cell type (ABC), germinal center B-cell type (GCB), follicular lymphoma (FL) and primary mediastinal B-cell lymphoma (PMBL).

BSP BMP7 TTTAGAGGGAATGAATGAATTT 190 CAACAAACCTAAAAATCCAAA 245

BSP LRP12 GATTGGYGTTGTTTTGTT 191 CRACCCTCCTAAAAACAA 246

BSP BMPER GTTGGGGAATTGGAAGTT 192 T AC R AC AACC R AA AATA AACTAA 247

BSP DUSP4 GGAGAA I GA I I A I 1 1 1 1 I G I 1 1 AG 193 AATCTAAACTACCTACCRAACTC 248

BSP CDH1 TTTGGGTGAAAGAGTGAGATT 194 CAAACTCACAAATACTTTACAATTC 249

qMSP BMPER AGAGTTTTCGTTGTAGTTATCGCGTA 250 TCGAAATAGTAGCGGTAGTTCGG 255 CGAGCGCGTTTCG 260 qMSP DUSP4 TGGAGGGATTTGGCGTTC 251 CGCGCGGGTAGGGTTT 256 TTCGCGGTTTTCGGGT 261 qMSP LRP12 GTTTTGTTATCGATTGGCGTTG 252 GTACGATCGACAATCCCCTAACC 257 TGGGTTTTCGTCGCGTGG 262 qMSP CDH1 AATTTTAGGTTAGAGGGTTATCGCGT 253 TCCCCAAAACGAAACTAACGAC 258 CGCCCACCCGACCTCGAT 263 qMSP BMP7 GAGGGG 1 1 1 1 1 GAAG 1 1 G 1 254 TCCCAACCTTATACGCCCTAAAT 259 CGCGTATTATTTTGGCGTT 264

Table 8. Primer and probe sequences for qMSP.

Table 9: Methylation status of candidate genes in 12 B-cell lymphoma cell lines. Only candidate genes which have a CpG island in their promoter region have been analyzed by MSP. Candidate genes for each lymphoma type (represented by gray color) have been analyzed in 12 B-cell lymphoma cell lines (three cell lines per type). Genes have been sorted by the combined methylation frequency (brackets) across all lymphoma cell lines (NHL). DLBCL DLBCL All NHL

BL FL PMBL ABC GCB Subtypes

CDH1 n.a. 16/18 (89%) 15/16 (94%) 12/12 (100%) 5/6 (84%) 48/52 (92%)

LRP12 n.a. 18/18 (100%) 14/16 (88%) 12/12 (100%) 6/6 (100%) 50/52 (96%)

BMPER n.a. 11/18 (62%) 11/16 (69%) 5/12 (42%) 3/6 (50%) 30/52 (58%)

DUSP4 n.a. 4/8 (50%) 0/6 (0%) 2/2 (100%) 1/6 (17%) 7/22 (32%)

BMP7 0/7 (0%) 3/10 (30%) 4/10 (40%) 2/10 (20%) n.a. 9/37 (24%)

Table 10: Methylation frequency of the analyzed lymphoma patients. Gene promoters have been analyzed by qMSP in five different lymphoma types. The methylation frequency is given in brackets for each lymphoma type and in the NHL column as a combination of all lymphoma types.

Example 3

Table 11 includes ROC curve results (Areas under the curve) for the clinically validated biomarkers in Examples 1 and 2, both individually and for selected combinations. The ROC curves are, with the exception of DUSP4 and BMP7, based on a combination of both test and validation series. All analyzed lymphomas are included in the analysis, in addition to the various controls.

Four additional genes have been identified as biomarkers based on their uniformly high methylation frequency across a wide range of lymphoma cell lines (Table 12).

Genes AUC Std. error Asympt. sign. 95% CI

LRP12 0.987 0.012 9.6E-16 0.964-1.000

CDH1 0.986 0.013 1.0E-15 0.961-1.000

PPP1R14A 0.887 0.032 2.0E-11 0.825-0.950

FZD8 0.852 0.039 1.1E-9 0.777-0.928

BMPR 0.828 0.044 6.3E-8 0.742-0.913

DUSP4 0.742 0.075 0.003 0.595-0.889

KCNH2 0.727 0.049 8.5E-5 0.631-0.823

DSP 0.719 0.049 1.5E-4 0.623-0.815

BMP7 0.700 0.083 0.061 0.537-0.862

LRP 12 CDH1 PPP 1 Rl 4A FZD8 BMPER 0.999 0.001 1.8E-16 0.997-1.000

LRP 12 PPP 1 Rl 4A FZD8 BMPER 0.982 0.015 1.9E-15 0.952-1.000

LRP 12 CDH 1 FZD8 BMPER 0.999 0.001 1.8E-16 0.997-1.000

LRP 12 FZD 8 BMPER 0.984 0.014 1.5E-15 0.956-1.000

LRP12 FZD8 0.984 0.014 1.4E-15 0.956-1.000

LRP12 BMPER 0.986 0.012 1.0E-15 0.964-1.000

LRP 12 FZD8 BMPER KCNH2 0.989 0.008 7.0E-16 0.973-1.000 Table 11. ROC curve analysis of individual and selected combinations of clinically tested markers.

Table 12. Methylation analysis of candidate genes in various lymphoma cell lines.

All publications and patents mentioned in the above specification are herein incorporated by reference. Various modifications and variations of the described method and system of the invention will be apparent to those skilled in the art without departing from the scope and spirit of the invention. Although the invention has been described in connection with specific preferred embodiments, it should be understood that the invention as claimed should not be unduly limited to such specific embodiments. Indeed, various modifications of the described modes for carrying out the invention that are obvious to those skilled in the medical sciences are intended to be within the scope of the following claims.

Claims

1. A method for detecting a hematological cancer in a subject comprising:

a) obtaining DNA from a biological sample of said subject; and

b) determining the level, presence, or frequency of methylation of a nucleic acid polymer corresponding to one or more genes selected from the group consisting of LRP12, FZD8, BMPER, PPP1R14A, CDHl, DSP, DUSP4, KCNH2, BMP7, BCL2L10, CLU, NPYIR, KLF9, MTSSl, NR4A2, CCL22, BSPRY, ITGBLl, TRPM4, SGPP2, STAG3, UCHLl and PTPRG using a reagent that specifically binds to said one or more genes.

2. The method of claim 1, wherein said one or more genes is two or more genes.

3. The method of claim 1, wherein said one or more genes is three or more genes.

4. The method of claim 1, wherein said one or more genes is four or more genes.

5. The method of claim 1, wherein said one or more genes is five or more genes.

6. The method of claim 1, wherein said one or more genes are selected from the group consisting oiLRP12, CDHl, PPP1R14A, FZD8, and BMPER.

7. The method of claim 1, wherein said one or more genes are selected from the group consisting oiLRP12, PPP1R14A, FZD8, and BMPER.

8. The method of claim 1, wherein said one or more genes are selected from the group consisting oiLRP12, CDHl, FZD8, and BMPER.

9. The method of claim 1, wherein said one or more genes are selected from the group consisting ofLRP12, FZD8 and BMPER.

10. The method of claim 1, wherein said one or more genes are selected from the group consisting oiLRP12, FZD8, BMPER, BMP7 and KCNH2.

11. The method of claim 1 , wherein said hematological cancer is a lymphoma.

12. The method of claim 11, wherein said lymphoma is B-cell non-Hodgkins lymphoma.

13. The method of any of Claims 1 to 12, wherein the level or frequency of methylation of a nucleic acid polymer is compared to a reference level or frequency of methylations.

14. The method of any of Claims 1 to 13, further comprising comparing the level, presence, or frequency of methylation of said nucleic acid polymer with a reference level, presence, or frequency of methylation, wherein an altered level, presence, or frequency of methylation for said patient relative to said reference provides an indication selected from the group consisting of an indication of a predisposition of the subject to a hematological cancer, an indication that the subject has a hematological cancer, an indication of prognosis, and the response of a subject to treatment with a particular therapy.

15. The method of any of Claims 1 to 14, wherein said nucleic acid comprises a region selected from the group consisting of a CpG island and a CpG island shore.

16. The method of claim 15, wherein said CpG island or shore is present in a coding region or a regulatory region.

17. The method of claim 16, wherein said regulatory region is a promoter.

18. The method of claim 14, wherein said determining of the level of altered methylation of a nucleic acid polymer comprises determining the methylation frequency of said CpG island or island shore.

19. The method of any of Claims 1 to 18, wherein said determining of the level of a nucleic acid polymer with altered methylation is achieved by a technique selected from the group consisting of methylation-specific PCR, quantitative methylation-specific PCR, methylation-sensitive DNA restriction enzyme analysis, methylation - insensitive DNA restriction enzyme analysis, quantitative bisulfite pyrosequencing, and bisulfite genomic sequencing PCR.

20. The method of any of Claims 1 to 19, wherein said method permits detection of a hematological cancer in said subject with a sensitivity of at least 85% at a specificity of at least 85%.

21. The method of any of Claims 1 to 20, wherein said method permits detection of hematological cancer in said subject with a sensitivity of at least 80% at a specificity of at least 90%.

22. The method of any of Claims 1 to 21, wherein said biological sample is selected from the group consisting of a tissue sample, a cell sample, and a blood sample.

23. The method of any of Claims 1 to 22, wherein said reagent is selected from a pair of amplification primers that specifically binds to said gene, one or more sequencing primers, a methylation specific restriction enzyme, and bisulfite.

24. The method of any one of claims 1 to 23, further comprising administering a treatment for a hematological cancer to said subject.

25. The method of any one of claims 1 to 23, further comprising monitoring of disease recurrence or progression for a hematological cancer to said subject.

26. The method of any one of claims 1 to 24, further comprising monitoring response of a treatment for a hematological cancer to said subject.

27. Use of a methylation specific nucleic acid detection reagent that specifically detects the methylation status of two or more genes selected from the group consisting of BMPER, CDH1, DUSP4, LRP12, BCL2L10, CLU, NPY1R, BMP7, DSP, FZD8, KCNH2, KLF9, MTSSl, NR4A2, PPP1R14A, CCL22, BSPRY, ITGBLl, TRPM4, SGPP2, STAG3, UCHLl and PTPRG for detecting a hematological cancer in a subject.

28. The use of claim 27, wherein aid hematological cancer is B-cell non-Hodgkins lymphoma.

29. The use of claim 27 or 28, wherein said one or more genes are selected from the group consisting of LRP12, CDHl, PPP1R14A, FZD8, and BMPER.

30. The use of claim 27 or 28, wherein said one or more genes are selected from the group consisting of LRP12, PPP1R14A, FZD8, and BMPER.

31. The use of claim 27 or 28, wherein said one or more genes are selected from the group consisting of LRP12, CDHl, FZD8, and BMPER.

32. The use of claim 27 or 28, wherein said one or more genes are selected from the group consisting of LRP 12, FZD8 and BMPER.

33. The use of claim 27 or 28, wherein said one or more genes are selected from the group consisting of LRP12, FZD8, BMPER, BMP7 and KCNH2.

34. Use of any one of Claims 27 to 33, wherein an altered level, presence, or frequency of methylation for a patient relative to a reference provides an indication selected from the group consisting of an indication of a predisposition of the subject to a hematological cancer, an indication that the subject has a hematological cancer, an indication of prognosis, and the response of a subject to treatment with a particular therapy.

35. The method of any of Claims 27 to 34, wherein said reagent is selected from a pair of amplification primers that specifically binds to said gene, one or more sequencing primers, a methylation specific restriction enzyme, and bisulfite.

36. A kit for detecting the presence of a hematological cancer in a mammal, said kit comprising reagents useful, sufficient, or necessary for detecting and/or characterizing level, presence, or frequency of methylation of one or more genes selected from the group consisting of BMPER, CDHl, DUSP4, LRP12, BCL2L10, CLU, NPYIR, BMP7, DSP, FZD8, KCNH2, KLF9, MTSS1, NR4A2, PPP1R14A, CCL22, BSPRY, ITGBL1, TRPM4, SGPP2, STAG3, UCHL1 and PTPRG.

37. The kit of claim 36, wherein said one or more genes are from the group consisting of LRP12, CDHl, PPP1R14A, FZD8, and BMPER.

38. The kit of claim 36, wherein said one or more genes are from the group consisting of LRP12, PPP1R14A, FZD8, and BMPER.

39. The kit of claim 36, wherein said one or more genes are from the group consisting of LRP12, CDH1, FZD8, and BMPER.

40. The kit of claim 36, wherein said one or more genes are from the group consisting of LRP12, FZD8 and BMPER.

41. The kit of claim 36, wherein said one or more genes are from the group consisting of LRP12, FZD8, BMPER, BMP7 and KCNH2.

42. The kit of any of Claims 36 to 41, wherein said reagent is selected from a pair of amplification primers that specifically binds to said gene, one or more sequencing primers, a methylation specific restriction enzyme, and bisulfite.

43. A system comprising a computer readable medium comprising instructions for utilizing information on the level, presence, or frequency of methylation of one or more genes selected from the group consisting of BMPER, CDH1, DUSP4, LRP12, BCL2L10, CLU,

NPYIR, BMP7, DSP, FZD8, KCNH2, KLF9, MTSSl, NR4A2, PPP1R14A, CCL22, BSPRY, ITGBL1, TRPM4, SGPP2, STAG3, UCHL1 and PTPRG to provide an indication selected from the group consisting of an indication of a predisposition of the subject to a

hematological cancer, an indication that the subject has a hematological cancer, and the response of a subject to treatment with a particular therapy.

44. The system of claim 43, wherein said one or more genes are selected from the group consisting oiLRPU, CDH1, PPP1R14A, FZD8, and BMPER.

45. The system of claim 43, wherein said one or more genes are selected from the group consisting oiLRPU, PPP1R14A, FZD8, and BMPER.

46. The system of claim 43, wherein said one or more genes are selected from the group consisting oiLRPU, CDH1, FZD8, and BMPER.

47. The system of claim 43, wherein said one or more genes are selected from the group consisting ofLRP12, FZD8 and BMPER.

48. The system of claim 43, wherein said one or more genes are selected from the group consisting oiLRPU, FZD8, BMPER, and KCNH2.

49. A method for detecting a hematological cancer in a subject comprising:

a) providing

reagents necessary for determining the level, presence, or frequency of methylation of a nucleic acid polymer corresponding to two or more biomarkers for a hematological cancer selected from the group consisting of LRP12, FZD8, BMPER, PPP1R14A, CDH1, DSP, DUSP4, KCNH2, BMP7, BCL2L10, CLU, NPY1R, KLF9, MTSS1, NR4A2, CCL22, BSPRY, ITGBL1, TRPM4, SGPP2, STAG3, UCHL1 and PTPRG, and

an algorithm

configured to receive information regarding the level, presence and/or frequency of methylation of said two or more biomarkers within a biological sample obtained from a subject, and

configured to compare received information regarding the level, presence and/or frequency of methylation two or more biomarkers with established norms for methylation of said markers, and based upon such comparison, determine the presence, absence, or prognosis of hematological cancer for the subject;

b) obtaining a biological sample from a subject;

c) determining the level, presence, and/or frequency of methylation of said two or more biomarkers;

d) inputting the determined level, presence, and/or frequency of methylation of the two or more biomarkers into the algorithm; and

e) determine the presence, absence, or prognosis of hematological cancer for the subject using the algorithm.

50. The method of Claim 49, wherein the established norm for hematological cancer is one or more established norm selected from the group consisting of an established norm of methylation levels of said biomarkers in subjects not diagnosed with a hematological cancer for the received information regarding the level, presence and/or frequency of methylation of said two or more biomarkers, an established norm of methylation levels of said biomarkers in subjects diagnosed with a hematological cancer for the received information regarding the level, presence and/or frequency of methylation of said two or more biomarkers, an established norm of methylation levels of said biomarkers in subjects neither diagnosed nor not diagnosed with a hematological cancer for the received information regarding the level, presence and/or frequency of methylation of said two or more biomarkers.