Classifications

• • C—CHEMISTRY; METALLURGY
  • C12—BIOCHEMISTRY; BEER; SPIRITS; WINE; VINEGAR; MICROBIOLOGY; ENZYMOLOGY; MUTATION OR GENETIC ENGINEERING
  • C12Q—MEASURING OR TESTING PROCESSES INVOLVING ENZYMES, NUCLEIC ACIDS OR MICROORGANISMS; COMPOSITIONS OR TEST PAPERS THEREFOR; PROCESSES OF PREPARING SUCH COMPOSITIONS; CONDITION-RESPONSIVE CONTROL IN MICROBIOLOGICAL OR ENZYMOLOGICAL PROCESSES
  • C12Q1/00—Measuring or testing processes involving enzymes, nucleic acids or microorganisms; Compositions therefor; Processes of preparing such compositions
  • C12Q1/68—Measuring or testing processes involving enzymes, nucleic acids or microorganisms; Compositions therefor; Processes of preparing such compositions involving nucleic acids
  • C12Q1/6876—Nucleic acid products used in the analysis of nucleic acids, e.g. primers or probes
  • C12Q1/6883—Nucleic acid products used in the analysis of nucleic acids, e.g. primers or probes for diseases caused by alterations of genetic material
  • C12Q1/6886—Nucleic acid products used in the analysis of nucleic acids, e.g. primers or probes for diseases caused by alterations of genetic material for cancer
• • C—CHEMISTRY; METALLURGY
  • C12—BIOCHEMISTRY; BEER; SPIRITS; WINE; VINEGAR; MICROBIOLOGY; ENZYMOLOGY; MUTATION OR GENETIC ENGINEERING
  • C12Q—MEASURING OR TESTING PROCESSES INVOLVING ENZYMES, NUCLEIC ACIDS OR MICROORGANISMS; COMPOSITIONS OR TEST PAPERS THEREFOR; PROCESSES OF PREPARING SUCH COMPOSITIONS; CONDITION-RESPONSIVE CONTROL IN MICROBIOLOGICAL OR ENZYMOLOGICAL PROCESSES
  • C12Q2600/00—Oligonucleotides characterized by their use
  • C12Q2600/154—Methylation markers

Definitions

• Human cancer cells typically contain somatically altered genomes, characterized by mutation, amplification, or deletion of critical genes.
• the DNA template from human cancer cells often displays somatic changes in DNA methylation. See, e.g., E. R. Fearon, et al, Cell 61:759 (1990); P. A. Jones, et al., Cancer Res. 46:461 (1986); R. Holliday, Science 238:163 (1987); A. De Bustros, et al., Proc. Natl. Acad. Sci. USA 85:5693 (1988); P. A. Jones, et al., Adv. Cancer Res. 54:1 (1990); S. B.
• DNA methylases transfer methyl groups from the universal methyl donor S-adenosyl methionine to specific sites on the DNA.
• Several biological functions have been attributed to the methylated bases in DNA. The most established biological function is the protection of the DNA from digestion by cognate restriction enzymes. This restriction modification phenomenon has, so far, been observed only in bacteria.
• Mammalian cells possess different methylases that exclusively methylate cytosine residues on the DNA that are 5′ neighbors of guanine (CpG). This methylation has been shown by several lines of evidence to play a role in gene activity, cell differentiation, tumorigenesis, X-chromosome inactivation, genomic imprinting and other major biological processes (Razin, A., H., and Riggs, R. D. eds. in DNA Methylation Biochemistry and Biological Significance , Springer-Verlag, N.Y., 1984).
• methylation of cytosine residues that are immediately 5′ to a guanosine occurs predominantly in CpG poor loci (Bird, A., Nature 321:209 (1986)).
• CpG islands discrete regions of CG dinucleotides called CpG islands (CGi) remain unmethylated in normal cells, except during X-chromosome inactivation and parental specific imprinting (Li, et al., Nature 366:362 (1993)) where methylation of 5′ regulatory regions can lead to transcriptional repression.
• de novo methylation of the Rb gene has been demonstrated in a small fraction of retinoblastomas (Sakai, et al., Am. J.
• VHL gene shows aberrant methylation in a subset of sporadic renal cell carcinomas (Herman, et al., Proc. Natl. Acad. Sci. U.S.A., 91:9700 (1994)).
• Expression of a tumor suppressor gene can also be abolished by de novo DNA methylation of a normally unmethylated 5′ CpG island. See, e.g., Issa, et al., Nature Genet. 7:536 (1994); Merlo, et al., Nature Med.
• the present invention provides methods for determining the methylation status of an individual.
• the methods comprise:
• the methods comprise determining the presence or absence of cancer, including but not limited to, bladder, breast, cervical, colon, endometrial, esophageal, head and neck, liver, lung, melanoma, ovarian, prostate, renal, and thyroid cancer, in an individual.
• cancer including but not limited to, bladder, breast, cervical, colon, endometrial, esophageal, head and neck, liver, lung, melanoma, ovarian, prostate, renal, and thyroid cancer, in an individual.
• the methods comprise:
• the methods comprise:
• the methods comprise:
• the methods comprise:
• the methods comprise:
• the methods comprise:
• the methods comprise:
• the methods comprise:
• the methods comprise:
• the methods comprise:
• the methods comprise:
• the methods comprise:
• the methods comprise:
• the methods comprise:
• the methods comprise:
• the determining step comprises determining the methylation status of at least one cytosine in the DNA region corresponding to a nucleotide in a biomarker, wherein the biomarker is at least 90%, 91%, 92%, 93%, 94%, 95%, 96%, 97%, 98%, or 99% identical to, or comprises, a sequence selected from the group consisting of SEQ ID NO: 292, 293, 294, 295, 296, 297, 298, 299, 300, 301, 302, 303, 304, 305, 306, 307, 308, 309, 310, 311, 312, 313, 314, 315, 316, 317, 318, 319, 320, 321, 322, 323, 324, 325, 326, 327, 328, 329, 330, 331, 332, 333, 334, 335, 336, 337, 338, 339, 340, 341, 342, 343, 344, 345, 346
• the determining step comprises determining the methylation status of the DNA region corresponding to a biomarker.
• the sample can be from any body fluid.
• the sample is selected from blood serum, blood plasma, fine needle aspirate of the breast, biopsy of the breast, ductal fluid, ductal lavage, feces, urine, sputum, saliva, semen, lavages, or tissue biopsy, such as biopsy of the lung, bronchial lavage or bronchial brushings in the case of lung cancer.
• the sample is from a tumor or polyp.
• the sample is a biopsy from lung, kidney, liver, ovarian, head, neck, thyroid, bladder, cervical, colon, endometrial, esophageal, prostate or skin tissue.
• the sample is from cell scrapes, washings, or resected tissues.
• the methylation status of at least one cytosine is compared to the methylation status of a control locus.
• the control locus is an endogenous control. In some embodiments, the control locus is an exogenous control.
• the determining step comprises determining the methylation status of at least one cytosine in at least two of the DNA regions.
• the invention provides computer implemented methods for determining the presence or absence of cancer (including but not limited to cancers of the bladder, breast, cervix, colon, endometrium, esophagus, head and neck, liver, lung(s), ovaries, prostate, rectum, and thyroid, and melanoma) in an individual.
• the methods comprise:
• the receiving step comprises receiving at least two methylation values, the two methylation values representing the methylation status of at least one cytosine biomarkers from two different DNA regions;
• the invention provides computer program products for determining the presence or absence of cancer (including but not limited to cancers of the bladder, breast, cervix, colon, endometrium, esophagus, head and neck, liver, lung(s), ovaries, prostate, rectum, and thyroid, and melanoma) in an individual.
• the computer readable products comprise:
• kits for determining the methylation status of at least one biomarker comprise:
• the pair of polynucleotides are capable of specifically amplifying a biomarker selected from the group consisting of one or more of SEQ ID NOs: 292, 293, 294, 295, 296, 297, 298, 299, 300, 301, 302, 303, 304, 305, 306, 307, 308, 309, 310, 311, 312, 313, 314, 315, 316, 317, 318, 319, 320, 321, 322, 323, 324, 325, 326, 327, 328, 329, 330, 331, 332, 333, 334, 335, 336, 337, 338, 339, 340, 341, 342, 343, 344, 345, 346, 347, 348, 349, 350, 351, 352, 353, 354, 355, 356, 357, 358, 359, 360, 361, 362, 363, 364, 365, 366, 367, 368, 369, 370, 371, 372, 373,
• kits comprise at least two pairs of polynucleotides, wherein each pair is capable of specifically amplifying at least a portion of a different DNA region.
• kits further comprise a detectably labeled polynucleotide probe that specifically detects the amplified biomarker in a real time amplification reaction.
• kits for determining the methylation status of at least one biomarker comprise:
• kits for determining the methylation status of at least one biomarker comprise:
• kits for determining the methylation status of at least one biomarker comprise:
• kits for determining the methylation status of at least one biomarker comprise:
• Methods refers to cytosine methylation at positions C5 or N4 of cytosine, the N6 position of adenine or other types of nucleic acid methylation.
• In vitro amplified DNA is unmethylated because in vitro DNA amplification methods do not retain the methylation pattern of the amplification template.
• unmethylated DNA or “methylated DNA” can also refer to amplified DNA whose original template was methylated or methylated, respectively.
• a “methylation profile” refers to a set of data representing the methylation states of one or more loci within a molecule of DNA from e.g., the genome of an individual or cells or tissues from an individual.
• the profile can indicate the methylation state of every base in an individual, can comprise information regarding a subset of the base pairs (e.g., the methylation state of specific restriction enzyme recognition sequence) in a genome, or can comprise information regarding regional methylation density of each locus.
• “Methylation status” refers to the presence, absence and/or quantity of methylation at a particular nucleotide, or nucleotides within a portion of DNA.
• the methylation status of a particular DNA sequence e.g., a DNA biomarker or DNA region as described herein
• the methylation status can optionally be represented or indicated by a “methylation value.”
• a methylation value can be generated, for example, by quantifying the amount of intact DNA present following restriction digestion with a methylation dependent restriction enzyme.
• a value i.e., a methylation value, for example from the above described example, represents the methylation status and can thus be used as a quantitative indicator of methylation status. This is of particular use when it is desirable to compare the methylation status of a sequence in a sample to a threshold value.
• a “methylation-dependent restriction enzyme” refers to a restriction enzyme that cleaves or digests DNA at or in proximity to a methylated recognition sequence, but does not cleave DNA at or near the same sequence when the recognition sequence is not methylated.
• Methylation-dependent restriction enzymes include those that cut at a methylated recognition sequence (e.g., DpnI) and enzymes that cut at a sequence near but not at the recognition sequence (e.g., McrBC).
• McrBC's recognition sequence is 5′ RmC (N40-3000) RmC 3′ where “R” is a purine and “mC” is a methylated cytosine and “N40-3000” indicates the distance between the two RmC half sites for which a restriction event has been observed.
• McrBC generally cuts close to one half-site or the other, but cleavage positions are typically distributed over several base pairs, approximately 30 base pairs from the methylated base. McrBC sometimes cuts 3′ of both half sites, sometimes 5′ of both half sites, and sometimes between the two sites.
• Exemplary methylation-dependent restriction enzymes include, e.g., McrBC (see, e.g., U.S. Pat. No.
• a “methylation-sensitive restriction enzyme” refers to a restriction enzyme that cleaves DNA at or in proximity to an unmethylated recognition sequence but does not cleave at or in proximity to the same sequence when the recognition sequence is methylated.
• Exemplary methylation-sensitive restriction enzymes are described in, e.g., McClelland et al., Nucleic Acids Res. 22(17):3640-59 (1994) and http://rebase.neb.com.
• Suitable methylation-sensitive restriction enzymes that do not cleave DNA at or near their recognition sequence when a cytosine within the recognition sequence is methylated at position C 5 include, e.g., Aat II, Aci I, Acl I, Age I, Alu I, Asc I, Ase I, AsiS I, Bbe I, BsaA I, BsaH I, BsiE I, BsiW I, BsrF I, BssH II, BssK I, BstB I, BstN I, BstU I, Cla I, Eae L, Eag L, Fau I, Fse I, Hha I, HinP1 I, HinC II, Hpa II, Hpy99 I, HpyCH4 IV, Kas I, Mbo I, Mlu I, MapAl I, Msp I, Nae I, Nar I, Not I, Pml I, Pst I, Pvu I, Rsr II, Sac II
• Suitable methylation-sensitive restriction enzymes that do not cleave DNA at or near their recognition sequence when an adenosine within the recognition sequence is methylated at position N 6 include, e.g., Mbo I.
• any methylation-sensitive restriction enzyme including homologs and orthologs of the restriction enzymes described herein, is also suitable for use in the present invention.
• a methylation-sensitive restriction enzyme that fails to cut in the presence of methylation of a cytosine at or near its recognition sequence may be insensitive to the presence of methylation of an adenosine at or near its recognition sequence.
• a methylation-sensitive restriction enzyme that fails to cut in the presence of methylation of an adenosine at or near its recognition sequence may be insensitive to the presence of methylation of a cytosine at or near its recognition sequence.
• Sau3AI is sensitive (i.e., fails to cut) to the presence of a methylated cytosine at or near its recognition sequence, but is insensitive (i.e., cuts) to the presence of a methylated adenosine at or near its recognition sequence.
• methylation-sensitive restriction enzymes are blocked by methylation of bases on one or both strands of DNA encompassing of their recognition sequence, while other methylation-sensitive restriction enzymes are blocked only by methylation on both strands, but can cut if a recognition site is hemi-methylated.
• a “threshold value that distinguishes between individuals with and without” a particular disease refers to a value or range of values of a particular measurement that can be used to distinguish between samples from individuals with the disease and samples without the disease.
• a threshold value or values that absolutely distinguishes between the two groups i.e., values from the diseased group are always on one side (e.g., higher) of the threshold value and values from the healthy, non-diseased group are on the other side (e.g., lower) of the threshold value.
• threshold values do not absolutely distinguish between diseased and non-diseased samples (for example, when there is some overlap of values generated from diseased and non-diseased samples).
• corresponding to a nucleotide in a biomarker refers to a nucleotide in a DNA region that aligns with the same nucleotide (e.g. a cytosine) in a biomarker sequence.
• biomarker sequences are subsequences of (i.e., have 100% identity with) the DNA regions. Sequence comparisons can be performed using any BLAST including BLAST 2.2 algorithm with default parameters, described in Altschul et al., Nuc. Acids Res. 25:3389 3402 (1977) and Altschul et al., J. Mol. Biol. 215:403 410 (1990), respectively.
• “Sensitivity” of a given biomarker refers to the percentage of tumor samples that report a DNA methylation value above a threshold value that distinguishes between tumor and non-tumor samples. The percentage is calculated as follows:
• Sensitivity [ ( the ⁇ ⁇ number ⁇ ⁇ of ⁇ ⁇ tumor samples ⁇ ⁇ above ⁇ ⁇ the ⁇ ⁇ threshold ) ( the ⁇ ⁇ total ⁇ ⁇ number ⁇ ⁇ of ⁇ ⁇ tumor ⁇ ⁇ samples ⁇ ⁇ tested ) ] ⁇ 100
• Sensitivity [ ( the ⁇ ⁇ number ⁇ ⁇ of ⁇ ⁇ true ⁇ ⁇ positive ⁇ ⁇ samples ) ( the ⁇ ⁇ number ⁇ ⁇ of ⁇ ⁇ true ⁇ ⁇ positive ⁇ ⁇ samples ) + ( the ⁇ ⁇ number ⁇ ⁇ of ⁇ ⁇ false ⁇ ⁇ negative ⁇ ⁇ samples ) ] ⁇ 100
• true positive is defined as a histology-confirmed tumor sample that reports a DNA methylation value above the threshold value (i.e. the range associated with disease)
• false negative is defined as a histology-confirmed tumor sample that reports a DNA methylation value below the threshold value (i.e. the range associated with no disease).
• the value of sensitivity therefore, reflects the probability that a DNA methylation measurement for a given biomarker obtained from a known diseased sample will be in the range of disease-associated measurements.
• the clinical relevance of the calculated sensitivity value represents an estimation of the probability that a given biomarker would detect the presence of a clinical condition when applied to a patient with that condition.
• Specificity of a given biomarker refers to the percentage of non-tumor samples that report a DNA methylation value below a threshold value that distinguishes between tumor and non-tumor samples. The percentage is calculated as follows:
• true negative is defined as a histology-confirmed non-tumor sample that reports a DNA methylation value below the threshold value (i.e. the range associated with no disease)
• false positive is defined as a histology-confirmed non-tumor sample that reports DNA methylation value above the threshold value (i.e. the range associated with disease).
• the value of specificity therefore, reflects the probability that a DNA methylation measurement for a given biomarker obtained from a known non-diseased sample will be in the range of non-disease associated measurements.
• the clinical relevance of the calculated specificity value represents an estimation of the probability that a given biomarker would detect the absence of a clinical condition when applied to a patient without that condition.
• HSPs high scoring sequence pairs
• Cumulative scores are calculated using, for nucleotide sequences, the parameters M (reward score for a pair of matching residues; always >0) and N (penalty score for mismatching residues; always ⁇ 0).
• M forward score for a pair of matching residues; always >0
• N penalty score for mismatching residues; always ⁇ 0.
• a scoring matrix is used to calculate the cumulative score. Extension of the word hits in each direction are halted when: the cumulative alignment score falls off by the quantity X from its maximum achieved value; the cumulative score goes to zero or below, due to the accumulation of one or more negative-scoring residue alignments; or the end of either sequence is reached.
• the BLAST algorithm parameters W, T, and X determine the sensitivity and speed of the alignment.
• W wordlength
• E expectation
• nucleic acid refers to nucleic acid regions, nucleic acid segments, primers, probes, amplicons and oligomer fragments.
• the terms are not limited by length and are generic to linear polymers of polydeoxyribonucleotides (containing 2-deoxy-D-ribose), polyribonucleotides (containing D-ribose), and any other N-glycoside of a purine or pyrimidine base, or modified purine or pyrimidine bases. These terms include double- and single-stranded DNA, as well as double- and single-stranded RNA.
• a nucleic acid, polynucleotide or oligonucleotide can comprise, for example, phosphodiester linkages or modified linkages including, but not limited to phosphotriester, phosphoramidate, siloxane, carbonate, carboxymethylester, acetamidate, carbamate, thioether, bridged phosphoramidate, bridged methylene phosphonate, phosphorothioate, methylphosphonate, phosphorodithioate, bridged phosphorothioate or sulfone linkages, and combinations of such linkages.
• phosphodiester linkages or modified linkages including, but not limited to phosphotriester, phosphoramidate, siloxane, carbonate, carboxymethylester, acetamidate, carbamate, thioether, bridged phosphoramidate, bridged methylene phosphonate, phosphorothioate, methylphosphonate, phosphorodithioate, bridged phosphorothi
• a nucleic acid, polynucleotide or oligonucleotide can comprise the five biologically occurring bases (adenine, guanine, thymine, cytosine and uracil) and/or bases other than the five biologically occurring bases.
• a polynucleotide of the invention can contain one or more modified, non-standard, or derivatized base moieties, including, but not limited to, N 6 -methyl-adenine, N 6 -tert-butyl-benzyl-adenine, imidazole, substituted imidazoles, 5-fluorouracil, 5-bromouracil, 5-chlorouracil, 5-iodouracil, hypoxanthine, xanthine, 4-acetylcytosine, 5-(carboxyhydroxymethyl)uracil, 5-carboxymethylaminomethyl-2-thiouridine, 5-carboxymethylaminomethyluracil, dihydrouracil, beta-D-galactosylqueosine, inosine, N 6 -isopentenyladenine, 1-methylguanine, 1-methylinosine, 2,2-dimethylguanine, 2-methyladenine, 2-methylguanine, 3-methylcytosine, 5-methylcytosine, 5-
• modified, non-standard, or derivatized base moieties may be found in U.S. Pat. Nos. 6,001,611; 5,955,589; 5,844,106; 5,789,562; 5,750,343; 5,728,525; and 5,679,785.
• nucleic acid, polynucleotide or oligonucleotide can comprise one or more modified sugar moieties including, but not limited to, arabinose, 2-fluoroarabinose, xylulose, and a hexose.
• the present invention is based, in part, on the discovery that sequences in certain DNA regions are methylated in cancer cells, but not normal cells. Specifically, the inventors have found that methylation of biomarkers within the DNA regions described herein are associated with various types of cancer.
• the inventors have recognized that methods for detecting the biomarker sequences and DNA regions comprising the biomarker sequences as well as sequences adjacent to the biomarkers that contain a significant amount of CpG subsequences, methylation of the DNA regions, and/or expression of the genes regulated by the DNA regions can be used to detect cancer cells. Detecting cancer cells allows for diagnostic tests that detect disease, assess the risk of contracting disease, determining a predisposition to disease, stage disease, diagnose disease, monitor disease, and/or aid in the selection of treatment for a person with disease.
• the presence or absence or quantity of methylation of the chromosomal DNA within a DNA region or portion thereof is detected.
• a DNA region or portion thereof e.g., at least one cytosine selected from SEQ ID Nos: 389-485
• Portions of the DNA regions described herein will comprise at least one potential methylation site (i.e., a cytosine) and can in some embodiments generally comprise 2, 3, 4, 5, 10, or more potential methylation sites.
• the methylation status of all cytosines within at least 20, 50, 100, 200, 500 or more contiguous base pairs of the DNA region are determined.
• methylation can be detected for the purposes described herein to detect the methylation status of at least one cytosine in a sequence from:
• the methylation of more than one DNA region is detected.
• the methylation status of 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 21, 22, 23, 24, 25, 26, 27, 28, 29, 30, 31, 32, 33, 34, 35, 36, 37, 38, 39, 40, 41, 42, 43, 44, 45, 46, 47, 48, 49, 50, 51, 52, 53, 54, 55, 56, 57, 58, 59, 60, 61, 62, 63, 64, 65, 66, 67, 68, 69, 70, 71, 72, 73, 74, 75, 76, 77, 78, 79, 80, 81, 82, 83, 84, 85, 86, 87, 88, 89, 90, 91, 92, 93, 94, 95, 96, or 97 of the DNA regions is determined.
• the methylation of a DNA region or portion thereof is determined and then normalized (e.g., compared) to the methylation of a control locus.
• the control locus will have a known, relatively constant, methylation status.
• the control sequence can be previously determined to have no, some or a high amount of methylation, thereby providing a relative constant value to control for error in detection methods, etc., unrelated to the presence or absence of cancer.
• the control locus is endogenous, i.e., is part of the genome of the individual sampled.
• testes-specific histone 2B gene (hTH2B in human) gene is known to be methylated in all somatic tissues except testes.
• control locus can be an exogenous locus, i.e., a DNA sequence spiked into the sample in a known quantity and having a known methylation status.
• a DNA region comprises a nucleic acid including one or more methylation sites of interest (e.g., a cytosine, a “microarray feature,” or an amplicon amplified from select primers) and flanking nucleic acid sequences (i.e., “wingspan”) of up to 4 kilobases (kb) in either or both of the 3′ or 5′ direction from the amplicon.
• methylation sites of interest e.g., a cytosine, a “microarray feature,” or an amplicon amplified from select primers
• flanking nucleic acid sequences i.e., “wingspan”
• kb kilobases
• the wingspan of the one or more DNA regions is about 0.5 kb, 0.75 kb, 1.0 kb, 1.5 kb, 2.0 kb, 2.5 kb, 3.0 kb, 3.5 kb or 4.0 kb in both 3′ and 5′ directions relative to the sequence represented by the microarray feature.
• the methylation sites in a DNA region can reside in non-coding transcriptional control sequences (e.g. promoters, enhancers, etc.) or in coding sequences, including introns and exons of the designated genes listed in Tables 1 and 2 and in section “SEQUENCE LISTING.”
• the methods comprise detecting the methylation status in the promoter regions (e.g., comprising the nucleic acid sequence that is about 1.0 kb, 1.5 kb, 2.0 kb, 2.5 kb, 3.0 kb, 3.5 kb or 4.0 kb 5′ from the transcriptional start site through to the transcriptional start site) of one or more of the genes identified in Tables 1 and 2 and in section “SEQUENCE LISTING.”
• the DNA regions of the invention also include naturally occurring variants, including for example, variants occurring in different subject populations and variants arising from single nucleotide polymorphisms (SNPs).
• SNPs encompasses insertions and deletions of varying size and simple sequence repeats, such as dinucleotides and trinucleotide repeats.
• Variants include nucleic acid sequences from the same DNA region (e.g. as set forth in Tables 1 and 2 and in section “SEQUENCE LISTING”) sharing at least 90%, 95%, 98%, 99% sequence identity, i.e., having one or more deletions, additions, substitutions, inverted sequences, etc., relative to the DNA regions described herein.
• Any method for detecting DNA methylation can be used in the methods of the present invention.
• methods for detecting methylation include randomly shearing or randomly fragmenting the genomic DNA, cutting the DNA with a methylation-dependent or methylation-sensitive restriction enzyme and subsequently selectively identifying and/or analyzing the cut or uncut DNA.
• Selective identification can include, for example, separating cut and uncut DNA (e.g., by size) and quantifying a sequence of interest that was cut or, alternatively, that was not cut. See, e.g., U.S. Pat. No. 7,186,512.
• the method can encompass amplifying intact DNA after restriction enzyme digestion, thereby only amplifying DNA that was not cleaved by the restriction enzyme in the area amplified. See, e.g., U.S. patent application Ser. Nos.
• amplification can be performed using primers that are gene specific.
• adaptors can be added to the ends of the randomly fragmented DNA, the DNA can be digested with a methylation-dependent or methylation-sensitive restriction enzyme, intact DNA can be amplified using primers that hybridize to the adaptor sequences.
• a second step can be performed to determine the presence, absence or quantity of a particular gene in an amplified pool of DNA.
• the DNA is amplified using real-time, quantitative PCR.
• the methods comprise quantifying the average methylation density in a target sequence within a population of genomic DNA.
• the method comprises contacting genomic DNA with a methylation-dependent restriction enzyme or methylation-sensitive restriction enzyme under conditions that allow for at least some copies of potential restriction enzyme cleavage sites in the locus to remain uncleaved; quantifying intact copies of the locus; and comparing the quantity of amplified product to a control value representing the quantity of methylation of control DNA, thereby quantifying the average methylation density in the locus compared to the methylation density of the control DNA.
• the quantity of methylation of a locus of DNA can be determined by providing a sample of genomic DNA comprising the locus, cleaving the DNA with a restriction enzyme that is either methylation-sensitive or methylation-dependent, and then quantifying the amount of intact DNA or quantifying the amount of cut DNA at the DNA locus of interest.
• the amount of intact or cut DNA will depend on the initial amount of genomic DNA containing the locus, the amount of methylation in the locus, and the number (i.e., the fraction) of nucleotides in the locus that are methylated in the genomic DNA.
• the amount of methylation in a DNA locus can be determined by comparing the quantity of intact DNA or cut DNA to a control value representing the quantity of intact DNA or cut DNA in a similarly-treated DNA sample.
• the control value can represent a known or predicted number of methylated nucleotides.
• the control value can represent the quantity of intact or cut DNA from the same locus in another (e.g., normal, non-diseased) cell or a second locus.
• methylation-sensitive or methylation-dependent restriction enzyme By using at least one methylation-sensitive or methylation-dependent restriction enzyme under conditions that allow for at least some copies of potential restriction enzyme cleavage sites in the locus to remain uncleaved and subsequently quantifying the remaining intact copies and comparing the quantity to a control, average methylation density of a locus can be determined. If the methylation-sensitive restriction enzyme is contacted to copies of a DNA locus under conditions that allow for at least some copies of potential restriction enzyme cleavage sites in the locus to remain uncleaved, then the remaining intact DNA will be directly proportional to the methylation density, and thus may be compared to a control to determine the relative methylation density of the locus in the sample.
• a methylation-dependent restriction enzyme is contacted to copies of a DNA locus under conditions that allow for at least some copies of potential restriction enzyme cleavage sites in the locus to remain uncleaved, then the remaining intact DNA will be inversely proportional to the methylation density, and thus may be compared to a control to determine the relative methylation density of the locus in the sample.
• assays are disclosed in, e.g., U.S. patent application Ser. No. 10/971,986.
• Kits for the above methods can include, e.g., one or more of methylation-dependent restriction enzymes, methylation-sensitive restriction enzymes, amplification (e.g., PCR) reagents, probes and/or primers.
• amplification e.g., PCR
• Quantitative amplification methods can be used to quantify the amount of intact DNA within a locus flanked by amplification primers following restriction digestion.
• Methods of quantitative amplification are disclosed in, e.g., U.S. Pat. Nos. 6,180,349; 6,033,854; and 5,972,602, as well as in, e.g., Gibson et al., Genome Research 6:995-1001 (1996); DeGraves, et al., Biotechniques 34(1):106-10, 112-5 (2003); Deiman B, et al., Mol Biotechnol. 20(2):163-79 (2002). Amplifications may be monitored in “real time.”
• Additional methods for detecting DNA methylation can involve genomic sequencing before and after treatment of the DNA with bisulfite. See, e.g., Frommer et al., Proc. Natl. Acad. Sci. USA 89:1827-1831 (1992). When sodium bisulfite is contacted to DNA, unmethylated cytosine is converted to uracil, while methylated cytosine is not modified.
• restriction enzyme digestion of PCR products amplified from bisulfite-converted DNA is used to detect DNA methylation. See, e.g., Sadri & Hornsby, Nucl. Acids Res. 24:5058-5059 (1996); Xiong & Laird, Nucleic Acids Res. 25:2532-2534 (1997).
• a MethyLight assay is used alone or in combination with other methods to detect DNA methylation (see, Eads et al., Cancer Res. 59:2302-2306 (1999)). Briefly, in the MethyLight process genomic DNA is converted in a sodium bisulfite reaction (the bisulfite process converts unmethylated cytosine residues to uracil). Amplification of a DNA sequence of interest is then performed using PCR primers that hybridize to CpG dinucleotides.
• amplification can indicate methylation status of sequences where the primers hybridize.
• the amplification product can be detected with a probe that specifically binds to a sequence resulting from bisulfite treatment of a unmethylated (or methylated) DNA. If desired, both primers and probes can be used to detect methylation status.
• kits for use with MethyLight can include sodium bisulfite as well as primers or detectably-labeled probes (including but not limited to Taqman or molecular beacon probes) that distinguish between methylated and unmethylated DNA that have been treated with bisulfite.
• kit components can include, e.g., reagents necessary for amplification of DNA including but not limited to, PCR buffers, deoxynucleotides; and a thermostable polymerase.
• a Ms-SNuPE Metal-sensitive Single Nucleotide Primer Extension reaction
• the Ms-SNuPE technique is a quantitative method for assessing methylation differences at specific CpG sites based on bisulfite treatment of DNA, followed by single-nucleotide primer extension (Gonzalgo & Jones, supra). Briefly, genomic DNA is reacted with sodium bisulfite to convert unmethylated cytosine to uracil while leaving 5-methylcytosine unchanged. Amplification of the desired target sequence is then performed using PCR primers specific for bisulfite-converted DNA, and the resulting product is isolated and used as a template for methylation analysis at the CpG site(s) of interest.
• Typical reagents for Ms-SNuPE analysis can include, but are not limited to: PCR primers for specific gene (or methylation-altered DNA sequence or CpG island); optimized PCR buffers and deoxynucleotides; gel extraction kit; positive control primers; Ms-SNuPE primers for a specific gene; reaction buffer (for the Ms-SNuPE reaction); and detectably-labeled nucleotides.
• bisulfite conversion reagents may include: DNA denaturation buffer; sulfonation buffer; DNA recovery regents or kit (e.g., precipitation, ultrafiltration, affinity column); desulfonation buffer; and DNA recovery components.
• a methylation-specific PCR (“MSP”) reaction is used alone or in combination with other methods to detect DNA methylation.
• An MSP assay entails initial modification of DNA by sodium bisulfite, converting all unmethylated, but not methylated, cytosines to uracil, and subsequent amplification with primers specific for methylated versus unmethylated DNA. See, Herman et al., Proc. Natl. Acad. Sci. USA 93:9821-9826, (1996); U.S. Pat. No. 5,786,146.
• Additional methylation detection methods include, but are not limited to, methylated CpG island amplification (see, Toyota et al., Cancer Res. 59:2307-12 (1999)) and those described in, e.g., U.S. Patent Publication 2005/0069879; Rein, et al. Nucleic Acids Res. 26 (10): 2255-64 (1998); Olek, et al. Nat. Genet. 17(3): 275-6 (1997); and PCT Publication No. WO 00/70090.
• the methods include the step of correlating the methylation status of at least one cytosine in a DNA region with the expression of nearby coding sequences, as described in Tables 1 and 2 and in section “SEQUENCE LISTING.” For example, expression of gene sequences within about 1.0 kb, 1.5 kb, 2.0 kb, 2.5 kb, 3.0 kb, 3.5 kb or 4.0 kb in either the 3′ or 5′ direction from the cytosine of interest in the DNA region can be detected. Methods for measuring transcription and/or translation of a particular gene sequence are well known in the art.
• the gene or protein expression of a gene in Tables 1 and 2 and in section “SEQUENCE LISTING” is compared to a control, for example, the methylation status in the DNA region and/or the expression of a nearby gene sequence from a sample from an individual known to be negative for cancer or known to be positive for cancer, or to an expression level that distinguishes between cancer and noncancer states.
• a control for example, the methylation status in the DNA region and/or the expression of a nearby gene sequence from a sample from an individual known to be negative for cancer or known to be positive for cancer, or to an expression level that distinguishes between cancer and noncancer states.
• Such methods like the methods of detecting methylation described herein, are useful in providing diagnosis, prognosis, etc., of cancer.
• the methods further comprise the step of correlating the methylation status and expression of one or more of the gene regions identified in Tables 1 and 2 and in section “SEQUENCE LISTING.”
• the present biomarkers and methods can be used in the diagnosis, prognosis, classification, prediction of disease risk, detection of recurrence of disease, and selection of treatment of a number of types of cancers.
• a cancer at any stage of progression can be detected, such as primary, metastatic, and recurrent cancers.
• Information regarding numerous types of cancer can be found, e.g., from the American Cancer Society (available on the worldwide web at cancer.org), or from, e.g., Harrison's Principles of Internal Medicine , Kaspar, et al., eds., 16th Edition, 2005, McGraw-Hill, Inc.
• Exemplary cancers that can be detected include lung, breast, renal, liver, ovarian, head and neck, thyroid, bladder, cervical, colon, endometrial, esophageal, prostate cancer or melanoma.
• the present invention provides methods for determining whether or not a mammal (e.g., a human) has cancer, whether or not a biological sample taken from a mammal contains cancerous cells, estimating the risk or likelihood of a mammal developing cancer, classifying cancer types and stages, monitoring the efficacy of anti-cancer treatment, or selecting the appropriate anti-cancer treatment in a mammal with cancer.
• a mammal e.g., a human
• a biological sample taken from a mammal contains cancerous cells
• estimating the risk or likelihood of a mammal developing cancer classifying cancer types and stages
• monitoring the efficacy of anti-cancer treatment or selecting the appropriate anti-cancer treatment in a mammal with cancer.
• Such methods are based on the discovery that cancer cells have a different methylation status than normal cells in the DNA regions described in the invention. Accordingly, by determining whether or not a cell contains differentially methylated sequences in the DNA regions as described herein, it is possible to determine whether
• the presence of methylated nucleotides in the diagnostic biomarker sequences of the invention is detected in a biological sample, thereby detecting the presence or absence of cancerous cells in the biological sample.
• the biological sample comprises a tissue sample from a tissue suspected of containing cancerous cells.
• tissue suspected of containing cancerous cells For example, in an individual suspected of having cancer, breast tissue, lymph tissue, lung tissue, brain tissue, or blood can be evaluated.
• the tissue or cells can be obtained by any method known in the art including, e.g., by surgery, biopsy, phlebotomy, swab, nipple discharge, stool, etc.
• a tissue sample known to contain cancerous cells e.g., from a tumor
• the methods will be used in conjunction with additional diagnostic methods, e.g., detection of other cancer biomarkers, etc.
• Genomic DNA samples can be obtained by any means known in the art. In cases where a particular phenotype or disease is to be detected, DNA samples should be prepared from a tissue of interest, or as appropriate, from blood. For example, DNA can be prepared from biopsy tissue to detect the methylation state of a particular locus associated with cancer.
• the nucleic acid-containing specimen used for detection of methylated loci may be from any source and may be extracted by a variety of techniques such as those described by Ausubel et al., Current Protocols in Molecular Biology (1995) or Sambrook et al., Molecular Cloning, A Laboratory Manual (3rd ed. 2001).
• the methods of the invention can be used to evaluate individuals known or suspected to have cancer or as a routine clinical test, i.e., in an individual not necessarily suspected to have cancer. Further diagnostic assays can be performed to confirm the status of cancer in the individual.
• the present methods may be used to assess the efficacy of a course of treatment.
• the efficacy of an anti-cancer treatment can be assessed by monitoring DNA methylation of the biomarker sequences described herein over time in a mammal having cancer.
• a reduction or absence of methylation in any of the diagnostic biomarkers of the invention in a biological sample taken from a mammal following a treatment, compared to a level in a sample taken from the mammal before, or earlier in, the treatment indicates efficacious treatment.
• the methods detecting cancer can comprise the detection of one or more other cancer-associated polynucleotide or polypeptides sequences. Accordingly, detection of methylation of any one or more of the diagnostic biomarkers of the invention can be used either alone, or in combination with other biomarkers, for the diagnosis or prognosis of cancer.
• the methods of the present invention can be used to determine the optimal course of treatment in a mammal with cancer.
• the presence of methylated DNA within any of the diagnostic biomarkers of the invention or an increased quantity of methylation within any of the diagnostic biomarkers of the invention can indicate a reduced survival expectancy of a mammal with cancer, thereby indicating a more aggressive treatment for the mammal.
• a correlation can be readily established between the presence, absence or quantity of methylation at a diagnostic biomarker, as described herein, and the relative efficacy of one or another anti-cancer agent.
• Such analyses can be performed, e.g., retrospectively, i.e., by detecting methylation in one or more of the diagnostic genes in samples taken previously from mammals that have subsequently undergone one or more types of anti-cancer therapy, and correlating the known efficacy of the treatment with the presence, absence or levels of methylation of one or more of the diagnostic biomarkers.
• the quantity of methylation may be compared to a threshold value that distinguishes between one diagnosis, prognosis, risk assessment, classification, etc., and another.
• a threshold value can represent the degree of methylation found at a particular DNA region that adequately distinguishes between cancer samples and normal samples with a desired level of sensitivity and specificity.
• a threshold value will likely vary depending on the assays used to measure methylation, but it is also understood that it is a relatively simple matter to determine a threshold value or range by measuring methylation of a DNA sequence in cancer samples and normal samples using the particular desired assay and then determining a value that distinguishes at least a majority of the cancer samples from a majority of non-cancer samples. If methylation of two or more DNA regions is detected, two or more different threshold values (one for each DNA region) will often, but not always, be used. Comparisons between a quantity of methylation of a sequence in a sample and a threshold value can be performed in any way known in the art.
• a manual comparison can be made or a computer can compare and analyze the values to detect disease, assess the risk of contracting disease, determining a predisposition to disease, stage disease, diagnose disease, monitor, or aid in the selection of treatment for a person with disease.
• threshold values provide at least a specified sensitivity and specificity for detection of a particular cancer type. In some embodiments, the threshold value allows for at least a 50%, 60%, 70%, or 80% sensitivity and specificity for detection of a specific cancer, e.g., breast, lung, renal, liver, ovarian, head and neck, thyroid, bladder, cervical, colon, endometrial, esophageal, prostate cancer or melanoma.
• a specific cancer e.g., breast, lung, renal, liver, ovarian, head and neck, thyroid, bladder, cervical, colon, endometrial, esophageal, prostate cancer or melanoma.
• the threshold value is set such that there is at least 10, 20, 30, 40, 50, 60, 70, 80% or more sensitivity and at least 70% specificity with regard to detecting cancer.
• the methods comprise recording a diagnosis, prognosis, risk assessment or classification, based on the methylation status determined from an individual. Any type of recordation is contemplated, including electronic recordation, e.g., by a computer.
• This invention also provides kits for the detection and/or quantification of the diagnostic biomarkers of the invention, or expression or methylation thereof using the methods described herein.
• kits for detection of methylation can comprise at least one polynucleotide that hybridizes to at least one of the diagnostic biomarker sequences of the invention and at least one reagent for detection of gene methylation.
• Reagents for detection of methylation include, e.g., sodium bisulfite, polynucleotides designed to hybridize to sequence that is the product of a biomarker sequence of the invention if the biomarker sequence is not methylated (e.g., containing at least one C ⁇ U conversion), and/or a methylation-sensitive or methylation-dependent restriction enzyme.
• the kits can provide solid supports in the form of an assay apparatus that is adapted to use in the assay.
• kits may further comprise detectable labels, optionally linked to a polynucleotide, e.g., a probe, in the kit.
• detectable labels optionally linked to a polynucleotide, e.g., a probe, in the kit.
• Other materials useful in the performance of the assays can also be included in the kits, including test tubes, transfer pipettes, and the like.
• the kits can also include written instructions for the use of one or more of these reagents in any of the assays described herein.
• kits of the invention comprise one or more (e.g., 1, 2, 3, 4, or more) different polynucleotides (e.g., primers and/or probes) capable of specifically amplifying at least a portion of a DNA region where the DNA region is a sequence selected from the group consisting of SEQ ID NOs: 389, 390, 391, 392, 393, 394, 395, 396, 397, 398, 399, 400, 401, 402, 403, 404, 405, 406, 407, 408, 409, 410, 411, 412, 413, 414, 415, 416, 417, 418, 419, 420, 421, 422, 423, 424, 425, 426, 427, 428, 429, 430, 431, 432, 433, 434, 435, 436, 437, 438, 439, 440, 441, 442, 443, 444, 445, 446, 447, 448, 449, 450
• kits comprise sufficient primers to amplify 2, 3, 4, 5, 6, 7, 8, 9, 10, or more different DNA regions or portions thereof, and optionally include detectably-labeled polynucleotides capable of hybridizing to each amplified DNA region or portion thereof.
• the kits further can comprise a methylation-dependent or methylation sensitive restriction enzyme and/or sodium bisulfite.
• kits comprise sodium bisulfite, primers and adapters (e.g., oligonucleotides that can be ligated or otherwise linked to genomic fragments) for whole genome amplification, and polynucleotides (e.g., detectably-labeled polynucleotoides) to quantify the presence of the converted methylated and or the converted unmethylated sequence of at least one cytosine from a DNA region that is selected from the group consisting of SEQ ID NOs: 389, 390, 391, 392, 393, 394, 395, 396, 397, 398, 399, 400, 401, 402, 403, 404, 405, 406, 407, 408, 409, 410, 411, 412, 413, 414, 415, 416, 417, 418, 419, 420, 421, 422, 423, 424, 425, 426, 427, 428, 429, 430, 431, 432, 433, 434, 435
• kits comprise a methylation sensing restriction enzymes (e.g., a methylation-dependent restriction enzyme and/or a methylation-sensitive restriction enzyme), primers and adapters for whole genome amplification, and polynucleotides to quantify the number of copies of at least a portion of a DNA region where the DNA region is selected from the group consisting of SEQ ID NOs: 389, 390, 391, 392, 393, 394, 395, 396, 397, 398, 399, 400, 401, 402, 403, 404, 405, 406, 407, 408, 409, 410, 411, 412, 413, 414, 415, 416, 417, 418, 419, 420, 421, 422, 423, 424, 425, 426, 427, 428, 429, 430, 431, 432, 433, 434, 435, 436, 437, 438, 439, 440, 441, 442, 443, 444, 445
• kits comprise a methylation binding moiety and one or more polynucleotides to quantify the number of copies of at least a portion of a DNA region where the DNA region is selected from the group consisting of SEQ ID NOs: 389, 390, 391, 392, 393, 394, 395, 396, 397, 398, 399, 400, 401, 402, 403, 404, 405, 406, 407, 408, 409, 410, 411, 412, 413, 414, 415, 416, 417, 418, 419, 420, 421, 422, 423, 424, 425, 426, 427, 428, 429, 430, 431, 432, 433, 434, 435, 436, 437, 438, 439, 440, 441, 442, 443, 444, 445, 446, 447, 448, 449, 450, 451, 452, 453, 454, 455, 456, 457, 458, 459, 460,
• a methylation binding moiety refers to a molecule (e.g., a polypeptide) that specifically binds to methyl-cytosine.
• a molecule e.g., a polypeptide
• restriction enzymes or fragments thereof that lack DNA cutting activity but retain the ability to bind methylated DNA, antibodies that specifically bind to methylated DNA, etc.).
• the calculations for the methods described herein can involve computer-based calculations and tools. For example, a methylation value for a DNA region or portion thereof can be compared by a computer to a threshold value, as described herein.
• the tools are advantageously provided in the form of computer programs that are executable by a general purpose computer system (referred to herein as a “host computer”) of conventional design.
• the host computer may be configured with many different hardware components and can be made in many dimensions and styles (e.g., desktop PC, laptop, tablet PC, handheld computer, server, workstation, mainframe). Standard components, such as monitors, keyboards, disk drives, CD and/or DVD drives, and the like, may be included.
• the connections may be provided via any suitable transport media (e.g., wired, optical, and/or wireless media) and any suitable communication protocol (e.g., TCP/IP); the host computer may include suitable networking hardware (e.g., modem, Ethernet card, WiFi card).
• suitable transport media e.g., wired, optical, and/or wireless media
• TCP/IP any suitable communication protocol
• the host computer may include suitable networking hardware (e.g., modem, Ethernet card, WiFi card).
• the host computer may implement any of a variety of operating systems, including UNIX, Linux, Microsoft Windows, MacOS, or any other operating system.
• Computer code for implementing aspects of the present invention may be written in a variety of languages, including PERL, C, C++, Java, JavaScript, VBScript, AWK, or any other scripting or programming language that can be executed on the host computer or that can be compiled to execute on the host computer. Code may also be written or distributed in low level languages such as assembler languages or machine languages.
• the host computer system advantageously provides an interface via which the user controls operation of the tools.
• software tools are implemented as scripts (e.g., using PERL), execution of which can be initiated by a user from a standard command line interface of an operating system such as Linux or UNIX.
• commands can be adapted to the operating system as appropriate.
• a graphical user interface may be provided, allowing the user to control operations using a pointing device.
• the present invention is not limited to any particular user interface.
• Scripts or programs incorporating various features of the present invention may be encoded on various computer readable media for storage and/or transmission.
• suitable media include magnetic disk or tape, optical storage media such as compact disk (CD) or DVD (digital versatile disk), flash memory, and carrier signals adapted for transmission via wired, optical, and/or wireless networks conforming to a variety of protocols, including the Internet.
• Loci that are differentially methylated in tumors relative to matched adjacent histologically normal tissue were identified using a DNA microarray-based technology platform that utilizes the methylation-dependent restriction enzyme McrBC. See, e.g. U.S. Pat. No. 7,186,512.
• McrBC methylation-dependent restriction enzyme
• Gels were visualized with long-wave UV, and gel slices including DNA within the modal size range of the untreated fraction (approximately 1-4 kb) were excised with a clean razor blade. DNA was extracted from gel slices using gel extraction kits (Qiagen).
• Untreated and Treated portions were resolved by agarose gel electrophoresis, and DNA within the modal size range of the Untreated portions were excised and gel extracted, the Untreated portions represent the entire fragmented genome of the sample while the Treated portions are depleted of DNA fragments including Pu m C. Fractions were analyzed using a duplicated dye swap microarray hybridization paradigm. For example, equal mass (200 ng) of Untreated 1 and Treated 1 fraction DNA were used as template for labeling with Cy3 and Cy5, respectively, and hybridized to a microarray (described below).
• Equal mass (200 ng) of the same Untreated 1 and Treated 1 fraction DNA were used as template for labeling with Cy5 and Cy3, respectively, and hybridized to a second microarray (these two hybridizations represent a dye swap of Untreated 1/Treated 1 fractions).
• Equal mass (200 ng) of Untreated 2 and Treated 2 fraction DNA were used as template for labeling with Cy3 and Cy5, respectively, and hybridized to a third microarray.
• equal mass (200 ng) of Untreated 2 and Treated 2 fraction DNA were used as template for labeling with Cy5 and Cy3, respectively, and hybridized to a fourth microarray (the final two hybridizations represent a technical replicate of the first dye swap). All DNA samples (e.g., tumor samples and adjacent normal samples) were analyzed in this way.
• the microarray described in this Example consists of 380,727 features. Each 50mer oligonucleotide feature is represented by three replicates per microarray slide, yielding a total of 124,877 unique feature probes, and 2412 control probes. Each probe was selected to represent a 1 Kb interval of the human genome. Because of the natural intersection of epigenetically interesting loci (i.e. promoters, CpG Islands, etc) there are multiple probes per genomic interval providing the capacity of supporting measurements with adjacent feature's data. The genomic content represented by the features represents the majority of ENSEMBL recognized human transcriptional start sites (TSS) with two probes per TSS (>55,000 probes).
• TSS human transcriptional start sites
• loci that were predicted to be differentially methylated in at least 70% of tumors relative to normal tissues were identified.
• differential DNA methylation of a collection of loci identified by a microarray discovery experiment was verified within the discovery panel of tumor and normal samples, as well as validated in larger panels of independent cancer tissue DNA, normal DNA tissue samples, and normal peripheral blood samples.
• Tables 1 and 2 and the section “SEQUENCE LISTING” list the unique microarray feature identifier (Feature name) for each of these loci.
• the genomic region in which a given microarray feature can report DNA methylation status is dependent upon the molecular size of the DNA fragments that were labeled for the microarray hybridizations.
• DNA in the size range of 1 to 4 kb was purified by agarose gel extraction and used as template for cyanogen dye labeling. Therefore, a conservative estimate for the genomic region interrogated by each microarray feature is 1 kb (i.e., 500 bp upstream and 500 bp downstream of the sequence represented by the microarray feature).
• Some features represent loci in which there is no Ensembl gene ID and no annotated transcribed gene within this 1 kb “wingspan” (e.g., CHR01P063154999, CHR03P027740753, CHR10P118975684, CHR11P021861414, CHR14P093230340, ha1p — 12601 — 150, ha1p — 42350 — 150, and ha1p — 44897 — 150) and some features have Ensembl gene IDs but no gene description (e.g., CHR01P043164342, CHR01P225608458, CHR02P223364582, CHR03P052525960, CHR16P000373719, CHR19P018622408).
• wingspan e.g., CHR01P063154999, CHR03P027740753, CHR10P118975684, CHR11P021861414, CHR14P093230340, ha
• CDK4I Cyclin-dependent kinase 4 inhibitor A
• p16-INK4a Multiple tumor suppressor 1
• MTS1 Multiple tumor suppressor 1
• AQP-1 Aquaporin-1
• Amporin-CHIP Water channel protein for red blood cells and kidney proximal tubule
• PCR primers that interrogated the loci predicted to be differentially methylated between tumor and histologically normal tissue were designed. Due to the functional properties of the enzyme, DNA methylation-dependent depletion of DNA fragments by McrBC is capable of monitoring the DNA methylation status of sequences neighboring the genomic sequences represented by the features on the microarray described in Example 1 (wingspan). Since the size of DNA fragments analyzed as described in Example 1 was approximately 1-4 kb, we selected a 1 kb region spanning the sequence represented by the microarray feature as a conservative estimate of the predicted region of differential methylation.
• PCR primers were selected within this approximately 1 kb region flanking the genomic sequence represented on the DNA microarray (approximately 500 bp upstream and 500 bp downstream). Selection of primer sequences was guided by uniqueness of the primer sequence across the genome, as well as the distribution of purine-CG sequences within the 1 kb region. PCR primer pairs were selected to amplify an approximately 400-600 bp sequence within each 1 kb region. Optimal PCR cycling conditions for the primer pairs were empirically determined, and amplification of a specific PCR amplicon of the correct size was verified. The sequences of the microarray features, primer pairs and amplicons are indicated in Table 2, and in section “SEQUENCE LISTING.”
• DNA methylation state of the loci was independently assayed in 10 ovarian carcinoma samples and the 10 histologically normal samples described above (i.e. the discovery tissue panel used for microarray experiments). DNA methylation was assayed by a quantitative PCR approach utilizing digestion by the McrBC restriction enzyme to monitor DNA methylation status. Genomic DNA purified from each sample was split into two equal portions of 9.6 ⁇ g.
• One 9.6 ⁇ g portion was digested with McrBC in a total volume of 120 ⁇ L including 1 ⁇ NEB2 buffer (New England Biolabs), 0.1 mg/mL bovine serum albumin (New England Biolabs), 2 mM GTP (Roche) and 80 units of McrBC enzyme (New England Biolabs).
• the second 9.6 ⁇ g portion was treated exactly the same as the Treated Portion, except that 8 ⁇ L of sterile 50% glycerol was added instead of McrBC enzyme. Reactions were incubated at 37° C. for approximately 12 hours, followed by incubation at 60° C. for 20 minutes to inactivate McrBC.
• McrBC cleavage at each locus was monitored by quantitative real-time PCR (qPCR). For each assayed locus, qPCR was performed using 20 ng of the Untreated Portion DNA as template and, separately, using 20 ng of the Treated Portion DNA as template. Each reaction was performed in 10 ⁇ L total volume including 1 ⁇ LightCycler 480 SYBR Green I Master mix (Roche) and 625 nM of each primer. Reactions were run in a Roche LightCycler 480 instrument. Optimal annealing temperatures varied depending on the primer pair. Primer sequences (Left Primer; Right Primer) and appropriate annealing temperatures (Annealing Temp.) are shown in Table 2. Cycling conditions were: 95° C.
• the differential DNA methylation status of the loci was further validated by analyzing an independent panel of 26 ovarian carcinoma samples (17 Stage 1 and 9 Stage II), 27 normal ovarian tissue samples, and 23 normal blood samples.
• the normal ovarian tissues included in this panel were obtained from mastectomies unrelated to ovarian cancer. Each sample was split into two equal portions of 4 ⁇ g. One portion was digested with McrBC (Treated Portion) in a total volume of 200 ⁇ L including 1 ⁇ NEB2 buffer (New England Biolabs), 0.1 mg/mL bovine serum albumin (New England Biolabs), 2 mM GTP (Roche) and 32 units McrBC (New England Biolabs).
• the second portion was mock treated under identical conditions, except that 3.2 ⁇ L sterile 50% glycerol was added instead of McrBC enzyme (Untreated Portion). Samples were incubated at 37° C. for approximately 12 hours, followed by incubation at 60° C. to inactivate the McrBC enzyme. qPCR reactions and data analysis were performed as described in Example 3.
• Gain biomarkers are biomarkers that show more methylation in tumor samples than normal samples and loss biomarkers show conversely.
• sensitivity reflects the frequency of scoring a known tumor sample as positive for DNA methylation at each locus while specificity reflects the frequency of scoring a known normal sample as negative for DNA methylation at each locus.
• loss biomarkers sensitivity reflects the frequency of scoring a known tumor sample as negative for DNA methylation at each locus while specificity reflects the frequency of scoring a known normal sample as positive for DNA methylation at each locus.
• an average delta Ct>1.0 (Treated Portion—Untreated Portion) was used as a threshold to score a sample as positive for DNA methylation at each locus (representing >50% depletion of amplifiable molecules in the DNA methylation-dependent restricted population relative to the untreated population).
• Percent sensitivity of gain biomarkers was calculated as the number of tumor samples with an average delta Ct>1.0 divided by the total number of tumor samples analyzed for that locus (i.e. excluding any measurements with a standard deviation between qPCR replicates>1 cycle) ⁇ 100.
• Percent specificity of gain biomarkers was calculated as (1 ⁇ (the number of normal samples with an average delta Ct>1.0 divided by the total number of normal samples analyzed for that locus)) ⁇ 100.
• the loci have sensitivities>8% and specificities relative to normal ovarian samples>40%. Notably, at least 9 of the loci have 100% specificity relative to normal ovarian and relative to normal blood samples. It is important to point out that the sensitivity and specificity of the differential DNA methylation status of any given locus may be increased by further optimization of the precise local genetic region interrogated by a DNA methylation-sensing assay.
• the differential DNA methylation status of the 49 loci was validated by analyzing an independent panel of 4 lung non-small adenocarcinoma samples (1 Stage I, 1 Stage II, 1 Stage III, 1 Stage 1V) and 4 matched adjacent histologically normal as well as in 23 samples of peripheral blood of normal individuals. Each sample was split into two equal portions of 4 ⁇ g. One portion was digested with McrBC (Treated Portion) in a total volume of 200 ⁇ L including 1 ⁇ NEB2 buffer (New England Biolabs), 0.1 mg/mL bovine serum albumin (New England Biolabs), 2 mM GTP (Roche) and 32 units McrBC (New England Biolabs).
• the second portion was mock treated under identical conditions, except that 3.2 ⁇ L sterile 50% glycerol was added instead of McrBC enzyme (Untreated Portion). Samples were incubated at 37° C. for approximately 12 hours, followed by incubation at 60° C. to inactivate the McrBC enzyme. qPCR reactions and data analysis were performed as described in these Examples.
• Gain biomarkers are biomarkers that show more methylation in tumor samples than normal samples and loss biomarkers show conversely.
• sensitivity reflects the frequency of scoring a known tumor sample as positive for DNA methylation at each locus while specificity reflects the frequency of scoring a known normal sample as negative for DNA methylation at each locus.
• loss biomarkers sensitivity reflects the frequency of scoring a known tumor sample as negative for DNA methylation at each locus while specificity reflects the frequency of scoring a known normal sample as positive for DNA methylation at each locus.
• an average delta Ct>1.0 (Treated Portion—Untreated Portion) was used as a threshold to score a sample as positive for DNA methylation at each locus (representing >50% depletion of amplifiable molecules in the DNA methylation-dependent restricted population relative to the untreated population).
• Percent sensitivity of gain biomarkers was calculated as the number of tumor samples with an average delta Ct>1.0 divided by the total number of tumor samples analyzed for that locus (i.e. excluding any measurements with a standard deviation between qPCR replicates>1 cycle) ⁇ 100.
• Percent specificity of gain biomarkers was calculated as (1 ⁇ (the number of normal samples with an average delta Ct>1.0 divided by the total number of normal samples analyzed for that locus)) ⁇ 100.
• the 49 loci have sensitivities>32% up to 100% and specificities in range 8-100% in tissues and in range 0-100% specificity in peripheral blood. Notably, 33 of the 49 loci have 100% specificity in tissues, and 19 of the 49 loci have 100% specificity in blood. It is important to point out that the sensitivity and specificity of the differential DNA methylation status of any given locus may be increased by further optimization of the precise local genetic region interrogated by a DNA methylation-sensing assay.
• a panel of 37 loci were selected for further validation in a panel of 25 additional lung carcinoma samples as well as 25 additional matched adjacent histologically normal samples, bringing the total number of tumor and normal samples analyzed to 38.
• the panel also included 22 lung samples from individuals who died from reasons other than cancer (i.e., benign samples). Samples were treated and analyzed as described in these Examples. As shown in Table 5, these loci display greater than 19% sensitivity, and all of them showed greater than 70% specificity relative to normal lung tissue, and 30 showed greater than 90% specificity relative to normal peripheral blood.
• ROC Receiver Operating Characteristic
• sensitivity refers to the percentage of tumor samples that report a value above (for a gain of DNA methylation event in tumor) or below (for a loss of DNA methylation event in tumor) a threshold value determined by ROC analysis.
• Specificity refers to the percentage of normal samples that report a value below (for a gain of DNA methylation event in tumor) or above (for a loss of DNA methylation event in tumor) a threshold value determined by ROC analysis.
• the models developed on the training set were validated on a test dataset of twenty-six tumor samples and twenty-seven normal samples. Error rates of 0% and 1.92% were achieved when classifying tumor vs. normal using each of the two models (see Table 9 and 10).
• the loci identified as differentially methylated were originally discovered based on DNA methylation-dependent microarray analyses.
• the sequences of the microarray features reporting this differential methylation are indicated in Table 2 and in section “SEQUENCE LISTING.”
• the “wingspan” of genomic interrogation by each array feature is proportional to the size of the sheared target at the beginning of the experiment (e.g., 1 to 4 Kbp), therefore regions of the genome comprising the probe participated the interrogation for differential methylation. Because the DNA was randomly sheared the effective genomic region scanned is roughly twice the size of the average molecular weight. The smallest fragments in the molecular population were 1 Kb, this suggests the minimum region size.
• PCR primers that amplify an amplicon within a 1 kb region surrounding the sequence represented by each microarray feature were selected and used for independent verification and validation experiments. Primer sequences and amplicon sequences are indicated in Table 2 and in section “SEQUENCE LISTING.” To optimize successful PCR amplification, these amplicons were designed to be less than the entire 1 kb region represented by the wingspan of the microarray feature. However, it should be noted that differential methylation may be detectable anywhere within this 1-8 Kb sequence window adjacent to the probe.
• CG density was expressed as the ratio of CG dinucleotides per kb.
• a region anywhere within the ⁇ 4 kb peak of CG density associated with the promoter region of the gene could be monitored for DNA methylation and could be important in development of a clinical diagnostic assay.
• the sequences indicated in Table 2 (DNA Region sequences) and in section “SEQUENCE LISTING” were selected using an 8 Kb criteria.
• CHR01P043164342 is a DNA methylation loss marker, and this sequence is less methylated in tumor sample relative to the normal sample.
• two other loci were analyzed by bisulfite genomic sequencing as described above. Between 10 and 24 independent clones were sequenced per amplicon per sample. The sequencing results were in line with the qPCR results (see Table 11). Note that the CG Position column in Table 11 refers to the CG position in the amplicons used for bisulfite sequencing.
• Sensitivity % of positive (i.e., methylation score above Threshold for gain of methylation markers or below Threshold for loss of methylation markers) tumors.
• Pos. of Total Number of positive tumors relative to the total number of tumors analyzed.
• Specificity % of negative (i.e., methylation score below Threshold for gain of methylation markers or above Threshold for loss of methylation markers) adjacent normal samples.
• Neg. of Total Number of negative adjacent normal samples relative to the total number of adjacent normal samples analyzed.
• Sensitivity % of positive (i.e., methylation score above Threshold for gain of methylation markers or below Threshold for loss of methylation markers) tumors.
• Pos. of Total Number of positive tumors relative to the total number of tumors analyzed.
• Specificity % of negative (i.e., methylation score below Threshold for gain of methylation markers or above Threshold for loss of methylation markers) adjacent normal samples.
• Neg. of Total Number of negative adjacent normal samples relative to the total number of adjacent normal samples analyzed.
• Sensitivity % of positive (i.e., methylation score above Threshold for gain of methylation markers or below Threshold for loss of methylation markers) tumors.
• Pos. of Total Number of positive tumors relative to the total number of tumors analyzed.
• Specificity % of negative (i.e., methylation score below Threshold for gain of methylation markers or above Threshold for loss of methylation markers) adjacent normal samples.
• Neg. of Total Number of negative adjacent normal samples relative to the total number of adjacent normal samples analyzed.
• Sensitivity % of positive (i.e., methylation score above Threshold for gain of methylation markers or below Threshold for loss of methylation markers) tumors.
• Pos. of Total Number of positive tumors relative to the total number of tumors analyzed.
• Specificity % of negative (i.e., methylation score below Threshold for gain of methylation markers or above Threshold for loss of methylation markers) adjacent normal samples.
• Neg. of Total Number of negative adjacent normal samples relative to the total number of adjacent normal samples analyzed.
• Sensitivity % of positive (i.e., methylation score above Threshold for gain of methylation markers or below Threshold for loss of methylation markers) tumors.
• Pos. of Total Number of positive tumors relative to the total number of tumors analyzed.
• Specificity % of negative (i.e., methylation score below Threshold for gain of methylation markers or above Threshold for loss of methylation markers) adjacent normal samples.
• Neg. of Total Number of negative adjacent normal samples relative to the total number of adjacent normal samples analyzed.
• Sensitivity % of positive (i.e., methylation score above Threshold for gain of methylation markers or below Threshold for loss of methylation markers) tumors.
• Pos. of Total Number of positive tumors relative to the total number of tumors analyzed.
• Specificity % of negative (i.e., methylation score below Threshold for gain of methylation markers or above Threshold for loss of methylation markers) adjacent normal samples.
• Neg. of Total Number of negative adjacent normal samples relative to the total number of adjacent normal samples analyzed.
• Sensitivity % of positive (i.e., methylation score above Threshold for gain of methylation markers or below Threshold for loss of methylation markers) tumors.
• Pos. of Total Number of positive tumors relative to the total number of tumors analyzed.
• Specificity % of negative (i.e., methylation score below Threshold for gain of methylation markers or above Threshold for loss of methylation markers) adjacent normal samples.
• Neg. of Total Number of negative adjacent normal samples relative to the total number of adjacent normal samples analyzed.
• Sensitivity % of positive (i.e., methylation score above Threshold for gain of methylation markers or below Threshold for loss of methylation markers) tumors.
• Pos. of Total Number of positive tumors relative to the total number of tumors analyzed.
• Specificity % of negative (i.e., methylation score below Threshold for gain of methylation markers or above Threshold for loss of methylation markers) adjacent normal samples.
• Neg. of Total Number of negative adjacent normal samples relative to the total number of adjacent normal samples analyzed.
• Sensitivity % of positive (i.e., methylation score above Threshold for gain of methylation markers or below Threshold for loss of methylation markers) tumors.
• Pos. of Total Number of positive tumors relative to the total number of tumors analyzed.
• Specificity % of negative (i.e., methylation score below Threshold for gain of methylation markers or above Threshold for loss of methylation markers) adjacent normal samples.
• Neg. of Total Number of negative adjacent normal samples relative to the total number of adjacent normal samples analyzed.
• Sensitivity % of positive (i.e., methylation score above Threshold for gain of methylation markers or below Threshold for loss of methylation markers) tumors.
• Pos. of Total Number of positive tumors relative to the total number of tumors analyzed.
• Specificity % of negative (i.e., methylation score below Threshold for gain of methylation markers or above Threshold for loss of methylation markers) benign normal samples.
• Neg. of Total Number of negative benign normal samples relative to the total number of adjacent normal samples analyzed.
• Sensitivity % of positive (i.e. methylation score above Threshold for gain of methylation markers or below Threshold for loss of methylation markers) tumors.
• Pos. of Total Number of positive tumors relative to the total number of tumors analyzed.
• Specificity % of negative (i.e. methylation score below Threshold for gain of methylation markers or above Threshold for loss of methylation markers) adjacent normal samples.
• Neg. of Total Number of negative adjacent normal samples relative to the total number of adjacent normal samples analyzed.
• Sensitivity % of positive (i.e., methylation score above Threshold for gain of methylation markers or below Threshold for loss of methylation markers) tumors.
• Pos. of Total Number of positive tumors relative to the total number of tumors analyzed.
• Specificity % of negative (i.e., methylation score below Threshold for gain of methylation markers or above Threshold for loss of methylation markers) adjacent normal samples.
• Neg. of Total Number of negative adjacent normal samples relative to the total number of adjacent normal samples analyzed.
• Sensitivity % of positive (i.e., methylation score above Threshold for gain of methylation markers or below Threshold for loss of methylation markers) tumors.
• Pos. of Total Number of positive tumors relative to the total number of tumors analyzed.
• Specificity % of negative (i.e., methylation score below Threshold for gain of methylation markers or above Threshold for loss of methylation markers) adjacent normal samples.
• Neg. of Total Number of negative adjacent normal samples relative to the total number of adjacent normal samples analyzed.
• Sensitivity % of positive (i.e., methylation score above Threshold for gain of methylation markers or below Threshold for loss of methylation markers) tumors.
• Pos. of Total Number of positive tumors relative to the total number of tumors analyzed.
• Specificity % of negative (i.e., methylation score below Threshold for gain of methylation markers or above Threshold for loss of methylation markers) adjacent normal samples.
• Neg. of Total Number of negative adjacent normal samples relative to the total number of adjacent normal samples analyzed.

Landscapes

• Chemical & Material Sciences (AREA)
• Life Sciences & Earth Sciences (AREA)
• Health & Medical Sciences (AREA)
• Organic Chemistry (AREA)
• Proteomics, Peptides & Aminoacids (AREA)
• Engineering & Computer Science (AREA)
• Immunology (AREA)
• Pathology (AREA)
• Analytical Chemistry (AREA)
• Zoology (AREA)
• Genetics & Genomics (AREA)
• Wood Science & Technology (AREA)
• Physics & Mathematics (AREA)
• Biotechnology (AREA)
• Microbiology (AREA)
• Molecular Biology (AREA)
• Hospice & Palliative Care (AREA)
• Biophysics (AREA)
• Oncology (AREA)
• Biochemistry (AREA)
• Bioinformatics & Cheminformatics (AREA)
• General Engineering & Computer Science (AREA)
• General Health & Medical Sciences (AREA)
• Measuring Or Testing Involving Enzymes Or Micro-Organisms (AREA)

Priority Applications (1)

Applications Claiming Priority (6)

Publications (1)

Family

ID=39682307

Family Applications (16)

Family Applications Before (4)

Family Applications After (11)

Country Status (5)

Cited By (1)

Families Citing this family (47)

Family Cites Families (6)

• 2008
  • 2008-02-01 WO PCT/US2008/001510 patent/WO2008097543A2/fr active Application Filing
  • 2008-02-01 US US12/024,589 patent/US20090170085A1/en not_active Abandoned
  • 2008-02-01 US US12/024,566 patent/US20090170084A1/en not_active Abandoned
  • 2008-02-01 US US12/024,672 patent/US20090075264A1/en not_active Abandoned
  • 2008-02-01 US US12/024,767 patent/US20090170087A1/en not_active Abandoned
  • 2008-02-01 US US12/024,583 patent/US20090176215A1/en not_active Abandoned
  • 2008-02-01 US US12/024,477 patent/US20090098542A1/en not_active Abandoned
  • 2008-02-01 US US12/024,461 patent/US20090170082A1/en not_active Abandoned
  • 2008-02-01 CA CA002677085A patent/CA2677085A1/fr not_active Abandoned
  • 2008-02-01 US US12/024,803 patent/US7960112B2/en active Active
  • 2008-02-01 US US12/024,417 patent/US20090170081A1/en not_active Abandoned
  • 2008-02-01 US US12/024,701 patent/US20090098543A1/en not_active Abandoned
  • 2008-02-01 US US12/024,498 patent/US20090170083A1/en not_active Abandoned
  • 2008-02-01 EP EP08725181A patent/EP2115161A4/fr not_active Withdrawn
  • 2008-02-01 US US12/024,621 patent/US20090170086A1/en not_active Abandoned
  • 2008-02-01 US US12/024,534 patent/US20090075263A1/en not_active Abandoned
  • 2008-02-01 US US12/024,769 patent/US20090075265A1/en not_active Abandoned
  • 2008-02-01 US US12/024,458 patent/US20090075262A1/en not_active Abandoned
  • 2008-02-01 AU AU2008214377A patent/AU2008214377A1/en not_active Abandoned
• 2011
  • 2011-05-05 US US13/101,992 patent/US20120122090A1/en not_active Abandoned

Also Published As

Similar Documents

Legal Events