DNA METHYLATION BIOMARKERS FOR LUNG CANCER
The present invention relates to the identification of novel DNA biomarkers and the use of the aberrant methylation patterns of the biomarkers to diagnose a disease or a condition (e.g., a cancer) associated therewith. In particular, the present invention relates to the use of the novel DNA biomarkers to diagnose lung cancers, e.g., squamous cell carcinomas and adenocarcinomas.
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The present application is a continuation of U.S. application Ser. No. 12/231,337, filed Aug. 29, 2008, which claims priority to U.S. Provisional Application No. 60/969,157, filed Aug. 30, 2007, the disclosures of which are incorporated by reference herein in their entirety, including drawings.
GOVERNMENT SUPPORTThe present invention was made with government support under NIH Grant No. RO1 grant CA104967 awarded by the National Institutes of Health. The government has certain rights in the present invention.
FIELD OF THE INVENTIONThe present inventions relates to diagnosing a disease (e.g., tumor) through measuring methylation levels or patterns of nucleotide biomarkers in samples.
BACKGROUND OF THE INVENTION5-methylcytosine, present at 70-80% of all CpG dinucleotides, is the only normal modified base found in mammalian DNA. It has been known for more than two decades that the level of 5-methylcytosine bases is significantly reduced in tumor tissues relative to normal tissues (Feinberg and Vogelstein 1983; Gama-Sosa, Slagel et al. 1983; Riggs and Jones 1983). Later it was observed that gene-specific hypermethylation events at CpG-rich, so-called CpG-island sequences occur in cancer tissues (Baylin, Hoppener et al. 1986). In the 1990s researchers reported hypermethylation of CpG islands of several known and putative tumor suppressor genes and other genes involved in important genome defense pathways such as DNA repair (Gonzalez-Zulueta, Bender et al. 1995; Herman, Merlo et al. 1995; Merlo, Herman et al. 1995; Kane, Loda et al. 1997; Costello and Plass 2001; Esteller, Corn et al. 2001; Jones and Baylin 2007). Today, there are many reports that have documented methylation of CpG islands associated with a large number of different genes, including almost every type of human cancer. In lung cancer, several specific CpG islands are methylated including those associated with CDKN2A, RASSF1A, RARbeta, MGMT, GSTP1, CDH13, APC, DAPK, TIMP3, and several others (Dammann, Li et al. 2000; Zochbauer-Muller, Fong et al. 2001; Yanagawa, Tamura et al. 2003; Topaloglu, Hogue et al. 2004; Dammann, Strunnikova et al. 2005). The methylation frequency (i.e. the percentage of tumors analyzed that carry methylated alleles) in the published studies differs widely depending on the histological type of tumor, the study population, and/or the methodology used to assess methylation.
As aberrant methylation (e.g., hypermethylation) of CpG islands is a phenomenon commonly observed during the development and progression of human tumors, detection of methylated CpG islands in easily accessible biological materials or samples such as serum, urine or sputum has the potential to be useful for the early diagnosis of cancer including lung cancer (Laird 2003; Belinsky 2004; Ushijima 2005). Therefore, there is a need to identify CpG islands containing biomarkers that would have specificity in discriminating disease (e.g., tumor) from normal tissue and are aberrantly methylated during the onset or developing or remission stage of the disease.
SUMMARY OF THE INVENTIONOne aspect of the present invention relates to a method of diagnosing a condition associated with an aberrant methylation of DNA in a sample from a subject by measuring the methylation level of one or more DNA biomarkers from a test sample in comparison to that of a normal or standard sample, wherein the fold difference between the methylation level of the test sample in relation to that of the normal/standard sample indicate the likelihood of the test sample having the condition.
The aberrant methylation is referred as hypermethylation and/or hypomethylation (e.g., demethylation). In a preferred embodiment, the abnormal methylation is hypermethylation. In another preferred embodiment, the abnormal methylation is hypomethylation.
The methylation of DNA often occurs at genome regions known as CpG islands. The CpG islands are susceptible to aberrant methylation (e.g., hypermethylation) in stage- and tissue-specific manner during the development of a condition or disease (e.g., cancer). Thus the measurement of the level of methylation indicates the likelihood or the stage (e.g., onset, development, or remission stage) of the condition.
The methylation of DNA can be detected via methods known in the art. In a preferred embodiment, the level can be measured via a methylated-CpG island recovery assay (MIRA), combined bisulfite-restriction analysis (COBRA) or methylation-specific PCR (MSP). In another preferred embodiment, the methylation levels of a plurality DNA can be measured through MIRA-assisted DNA array.
The DNA biomarkers are fragments of genome DNA which contain a CpG island or CpG islands, or alternatively, are susceptible to aberrant methylation. Examples of the DNA markers associated with a condition are disclosed in Tables 2 and 4. Specifically, examples of the DNA markers include BARHL2, EVX2, IRX2, MEIS1, MSX1, NR2E1, OC2, PAX6, TFAP2A, ZNF577, CHAD, DLX4, GRIK2, KNCG3, NR2E1, OSR1, OTX1, OTX2, PROX1, RUNX1, and VAX1.
The conditions or diseases associated with aberrant methylation (e.g., hypermethylation) include hematological disorders and cancers (e.g., breast cancer, lung cancer, liver cancer, ovarian cancer, and other tumors, carcinomas, and sarcomas). In a preferred embodiment, the condition is a lung cancer which includes squamous cell carcinoma and adenocarcinoma.
In one embodiment, the method of present invention is directed to a method of diagnosing a lung cancer (e.g., squamous cell carcinoma) in a test subject or a test sample through determining the methylation level of DNA markers from the test subject or test sample in relative to the level of the DNA markers from a normal subject or sample, wherein the DNA markers are one or more genes listed in Table 2, preferably, selected from the group consisting of BARHL2, EVX2, IRX2, MEIS1, MSX1, NR2E1, OC2, OSR1, OTX1, PAX6, TFAP2A, and ZNF577.
In another embodiment, the method of present invention is directed to a method of diagnosing a lung cancer (e.g., adenocarcinoma) in a test subject or a test sample through determining the methylation level of DNA markers from the test subject or test sample in relative to the level of the DNA markers from a normal subject or sample, wherein the DNA markers are one or more genes listed in Table 4, preferably, selected from the group consisting of CHAD, DLX4, GRIK2, KNCG3, NR2E1, OSR1, OTX1, OTX2, PROX1, RUNX1, and VAX1.
Another aspect of the present invention relates to a method of diagnosing a condition associated with an aberrant methylation of DNA in a sample from a subject by 1) obtaining test genome DNA from a test sample and control genome DNA from a control sample; 2) obtaining a first methylated region from the test genome DNA and a second methylated region from the control genome DNA, 3) hybridizing the first region and the second region to a DNA microarray wherein the microarray comprising at least one DNA biomarker associated with a disease or a condition, wherein the fold difference between the first region of test DNA hybridizing to the DNA biomarker relative to the second region hybridizing to the DNA biomarker indicates that the test sample has the disease or condition.
Another aspect of the present invention relates of a method of identifying one or more DNA biomarker susceptible to aberrant methylation by subjecting DNA fragments from a disease sample of a known condition or disease and a standard/normal/control sample (without the condition) to an MIRA-assisted DNA array wherein the array comprising a plurality of DNA probes, and analyzing the levels of the DNA fragments, specially the levels of methylated DNA fragments, which bind to a corresponding probe on the array, and detecting the fold difference between the levels of the DNA fragments from the disease sample and the normal sample, wherein the corresponding probe is a DNA biomarker if the fold difference is no less than 2.
One aspect of the present invention relates to the identification of novel DNA biomarkers and the use of the aberrant methylation patterns of the biomarkers to diagnose a disease or a condition (e.g., a cancer) associated therewith.
The DNA biomarkers according to the present invention are fragments of a polynucleotide (e.g., regions of genome polynucleotide or DNA) which likely contain CpG island(s), or fragments which are more susceptible to methylation or demethylation than other regions of genome DNA. The term “CpG islands” is a region of genome DNA which shows higher frequency of 5′-CG-3′ (CpG) dinucleotides than other regions of genome DNA. Methylation of DNA at CpG dinucleotides, in particularly, the addition of a methyl group to position 5 of the cytosine ring at CpG dinucleotides, is one of the epigenetic modifications in mammalian cells. CpG islands often harbor the promoters of genes and play a pivotal role in the control of gene expression. In normal tissues CpG islands are usually unmethylated, but a subset of islands becomes methylated during the development of a disease (e.g., tumor development). It is been reported that changes in DNA methylation patterns occur in a developmental stage and tissue specific manner and often accompany tumor development, most notably in the form of CpG island hypermethylation. During tumorigenesis, both alleles of a tumor suppressor gene need to be inactivated by genomic changes such as chromosomal deletions or loss-of-function mutations in the coding region of a gene. As an alternative mechanism, transcriptional silencing by hypermethylation of CpG islands spanning the promoter regions of tumor suppressor genes is a common and important process in carcinogenesis. Since hypermethylation generally leads to inactivation of gene expression, this epigenetic alteration is considered to be a key mechanism for long-term silencing of tumor suppressor genes. The importance of promoter methylation in functional inactivation of lung cancer suppressor genes is becoming increasingly recognized. It is estimated that between 0.5% and 3% of all genes carrying CpG islands may be silenced by DNA methylation in lung cancer (Costello et al., 2000). A schematic illustration of commonly observed DNA methylation differences between tumor cells and normal cells is depicted in
It is contemplated that the DNA markers for hypermethylation according to the present invention have the following criteria. First, the marker would preferably be unmethylated in normal sample (e.g., normal or control tissue without disease, or normal or control body fluid, blood, serum, urine, sputum), most importantly in the healthy tissue the tumor originates from and/or in healthy blood, serum, urine, sputum or other body fluid. Second, the marker should preferably be heavily methylated in a large fraction of the tumors, preferably at a methylation frequency of ≧about 50% or ≧about 60%, more preferably ≧about 70%, ≧about 75%, ≧about 80%, ≧about 85%, ≧about 90%, ≧about 95%, or about 100%. Third, markers that can preferably differentiate between different subtypes or tumor entities, or are of prognostic significance, would be of great value. Specific DNA methylation patterns may distinguish tumors with low and high metastatic potential making it possible to apply optimal treatment regimens early. In additional, methylation of certain DNA repair or damage response genes may be predictive of a positive therapeutic response.
The diseases or conditions associated with aberrant methylation (hypermethylation or hypomethylation) of DNA biomarkers include a wide variety of indications such as hematological disorders and cancers that are associated with hypermethylation, as well as for diagnosis and/or treatment of diseases or conditions associated with hypomethylation (also recognized, e.g., as a cause of oncogenesis; see, e.g., Das and Singal (2004)).
Examples of hematologic disorders include abnormal growth of blood cells which can lead to dysplastic changes in blood cells and hematological malignancies such as various leukemias. Examples of hematological disorders include but are not limited to acute myeloid leukemia, acute promyelocytic leukemia, acute lymphoblastic leukemia, chronic myelogenous leukemia, the myelodysplastic syndromes (MDS), thalassemia, and sickle cell anemia.
Examples of cancers include, but are not limited to, breast cancer, skin cancer, bone cancer, prostate cancer, liver cancer, lung cancer, brain cancer, cancer of the larynx, gallbladder, pancreas, rectum, parathyroid, thyroid, adrenal, neural tissue, head and neck, colon, stomach, bronchi, and kidneys, basal cell carcinoma, squamous cell carcinoma of both ulcerating and papillary type, metastatic skin carcinoma, osteo sarcoma, Ewing's sarcoma, veticulum cell sarcoma, myeloma, giant cell tumor, small-cell lung tumor, gallstones, islet cell tumor, primary brain tumor, acute and chronic lymphocytic and granulocytic tumors, hairy-cell tumor, adenoma, hyperplasia, medullary carcinoma, pheochromocytoma, mucosal neuromas, intestinal ganglloneuromas, hyperplastic corneal nerve tumor, marfanoid habitus tumor, Wilm's tumor, seminoma, ovarian tumor, leiomyomater tumor, cervical dysplasia and in situ carcinoma, neuroblastoma, retinoblastoma, soft tissue sarcoma, malignant carcinoid, topical skin lesion, mycosis fungoide, rhabdomyosarcoma, Kaposi's sarcoma, osteogenic and other sarcoma, malignant hypercalcemia, renal cell tumor, polycythemia vera, adenocarcinoma, glioblastoma multiforma, leukemias, lymphomas, malignant melanomas, epidermoid carcinomas, and other carcinomas and sarcomas. In one embodiment of the present invention, a disease or condition is a lung cancer. In a preferred embodiment, the lung cancer is squamous cell carcinoma (e.g., Stage I squamous cell carcinoma). In another preferred embodiment, the lung cancer is adenocarcinoma.
In another embodiment of the present invention, a test sample is an organ, a fragment of organ, a tissue, a fragment of a tissue, body fluid, blood, serum, urine, sputum, which may or may not have a condition or a disease. The test sample is subject to diagnosing methods according to the present invention to determine the methylation level of at least one DNA marker from the test sample in comparison to that of a normal or standard sample.
In another embodiment of the present invention, the DNA markers which are susceptible to aberrant methylation and associated with lung cancer include those disclosed in Tables 2 and 4. Further, examples of the DNA markers include BARHL2, EVX2, IRX2, MEIS1, MSX1, NR2E1, OC2, OSR1, OTX1, PAX6, TFAP2A, ZNF577, CHAD, DLX4, GRIK2, KNCG3, NR2E1, OSR1, OTX1, OTX2, PROX1, RUNX1, and VAX1. For another example, DNA biomarkers and their aberrant methylation including NR2E1, OSR1, and OTX1 are associated with both squamous cell carcinoma and/or adenocarcinoma, preferably, at frequency of over 95% of the both tumors (e.g., 100% of both tumors).
In another preferred embodiment, DNA markers associated with squamous cell carcinomas are one or more genes selected in Table 2, and preferably, selected from the group consisting of BARHL2, EVX2, IRX2, MEIS1, MSX1, NR2E1, OC2, OSR1, OTX1, PAX6, TFAP2A, and ZNF577. In another preferred embodiment, the DNA markers and their methylation occur at a frequency of over about 70%, preferably about 80-100%, of squamous cell carcinomas.
In another preferred embodiment, DNA markers associated with adenocarcinomas one or more genes selected in Table 4, and preferably, selected from the group consisting of CHAD, DLX4, GRIK2, KNCG3, NR2E1, OSR1, OTX1, OTX2, PROX1, RUNX1, and VAX1. In another preferred embodiment, the DNA markers and their methylation occur at frequency of over about 70%, preferably about 80%, of adenocarcinomas.
There are a number of methods that can be employed to determine, identify, and characterize methylation or aberrant methylation of a region/fragment of DNA or a region/fragment of genome DNA (e.g., CpG island-containing region/fragment) in the development of a disease (e.g., tumorigenesis) and thus diagnose the onset, presence or status of the disease.
In another embodiment, a methylation detection technique is based on restriction endonuclease cleavage. These techniques require the presence of methylated cytosine residues within the recognition sequence that affect the cleavage activity of restriction endonucleases (e.g., HpaII, HhaI) (Singer et al. (1979)). Southern blot hybridization and polymerase chain reaction (PCR)-based techniques can be used with along with this approach.
In another embodiment, a methylation detection technique is based on the differential sensitivity of cytosine and 5-methylcytosine towards chemical modification (e.g., bisulfite dependent modification) and/or cleavage. This methodology allows single base resolution. In one example, hydrazine modification, as developed for Maxam-Gilbert chemical DNA sequencing, has been used to distinguish cytosines from methylcytosines with which it does not react (Pfeifer et al., 1989). The principle of bisulfite genomic sequencing is that methylated and unmethylated cytosine residues react in a different manner with sodium bisulfite (Clark et al. 1994). After bisulfite treatment of genomic DNA, the unmethylated cytosines are converted to uracils by hydrolytic deamination, while methylated cytosine residues can hardly react with sodium bisulfite and remain intact. After this chemical treatment resulting in cytosine deamination, the region of interest must be PCR amplified with primers complementary to the deaminated uracil-containing sequence, and in most cases the PCR products are cloned and then sequenced.
In another embodiment, a bisulfite dependent methylation assay is known as a combined bisulfite-restriction analysis (COBRA assay) whereas PCR products obtained from bisulfite-treated DNA can also be analyzed by using restriction enzymes that recognize sequences containing 5′CG, such as TaqI (5′TCGA) or BstUI (5′CGCG) such that methylated and unmethylated DNA can be distinguished (Xiong and Laird, 1997).
In another embodiment, another bisulfite dependent methylation assay is known as methylation-specific PCR assay (MSP) (Herman et al. 1996). Sodium bisulfite treated genomic DNA serves as the template for a subsequent PCR reaction. Specific sets of PCR primers are designed in such a way to discriminate between bisulfite modified and unmodified template DNA and between unmethylated (deaminated) and methylated (non-deaminated) cytosines at CpG sites.
In another embodiment, a methylation detection technique is based on the ability of the MBD domain of the MeCP2 protein to selectively bind to methylated DNA sequences (Frafa et al., 2003). The bacterially expressed and purified His-tagged methyl-CpG-binding domain is immobilized to a solid matrix and used for preparative column chromatography to isolate highly methylated DNA sequences. Restriction endonuclease-digested genomic DNA is loaded onto the affinity column and methylated-CpG island-enriched fractions are eluted by a linear gradient of sodium chloride. PCR or Southern hybridization techniques are used to detect specific sequences in these fractions.
In another embodiment, a methylation detection technique is known as methyl-CpG island recovery assay (MIRA) which is based on the fact that the MBD2b protein can specifically recognize methylated-CpG dinucleotides and this interaction is enhanced by the MBD3L1 protein. Matrix-assisted binding and simple PCR assays are used to detect methylated DNA sequences in the recovered fraction. MIRA does not depend on the use of sodium bisulfite but has similar sensitivity and specificity as bisulfite-based approaches (Rauch and Pfeifer, 2005).
An outline of MIRA is shown in
The efficiency of the MIRA pulldown depends on CpG density and the approach seems to be ideally suited for pulling down methylated CpG islands. In order to test how many methylated CpGs are required for efficient pull-down by MIRA, unmethylated DNA fragments derived from the human TBP gene promoter were used. The DNA was methylated with different prokaryotic DNA methylases to introduce different numbers of methylated CpGs. A MIRA assay was performed and the TBP promoter was amplified using quantitative real-time PCR. A fragment containing 13 methylated CpGs was amplified most efficiently, followed by one with two methylation sites. However, fragments containing zero or only one methylated CpG (such sequences may be found in areas flanking CpG islands) were amplified only at much higher PCR cycle numbers.
The MIRA assay has a high specificity to detect the methylated CpG island-containing fraction/region/fragment of the genome DNA. The MIRA procedure has been applied to isolate the methylated CpG island fraction from a tumor cell line. For example, DNA from the lung cancer cell line A549 was digested with MseI (5′-TTAA), which cuts outside of CpG islands. Linkers were ligated to the MseI digested DNA and enrichment of the methylated fraction was done by MIRA as described (Rauch & Pfeifer, 2005). The samples were then PCR-amplified using linker primers and PCR products were cloned into a plasmid vector. Individual plasmids were sequenced and the identity of the amplified fragments was assessed using BLAST searches. Of 54 sequenced plasmids, 24 contained sequences matching to CpG islands (defined as >60% G+C content; CpG frequency observed/expected >0.7; minimum length 200 bp) in Genbank. This data confirmed the specificity of the MIRA assay. The specificity was further confirmed by sodium bisulfite sequencing.
Methods have been developed to analyze DNA methylation patterns on a genome-wide scale. These methods include, for example, 1) restriction landmark genomic scanning, 2) methylation-sensitive representational difference analysis, 3) arbitrarily-primed PCR, 4) differential methylation hybridization in combination with a CpG island microarray (methods 1-4 use methylationsensitive restriction, 5) expression microarrays to look for genes reactivated by treatment with DNA methylation inhibitors, e.g. 5-aza-deoxycytidine, 6) genomic tiling and BAC microarrays, 7) immunoprecipitation using antibody against 5-methylcytosine combined with microarrays, 8) chromatin immunoprecipitation with antibodies against methyl-CpG binding proteins, 9) the use of the methylation-dependent restriction enzyme McrBC to cleave methylated DNA, and 10) direct sequencing of bisulfite-converted genomes (See Pfeifer at el., 2007, for review).
In a preferred embodiment, MIRA-assisted microarray analysis is employed to determine DNA methylation patterns or diagnose a disease associated with aberrant methylation of DNA biomarkers or CpG containing regions/fragments (Rauch et al., 2006). This analysis is highly specific, sensitive (100 ng or less of genomic DNA are required), and relatively simple. Briefly, MIRA-enriched DNA and input DNA from control and tumor tissue can be labeled with tow different dyes (e.g., Cy3 and Cy5 dyes) respectively, and hybridized to commercially available CpG island or promoter arrays (see
Various types of microarrays can be used in analyzing DNA methylation patterns on a genome-wide scale. For example, MIRA is compatible with Affymetrix promoter arrays as well as with Agilent and NimbleGen arrays. On the NimbleGen platform, DNA methylation was measured across the sequences analyzed by the ENCODE project. In this analysis, MIRA-enriched DNA from a lymphoblastoid cell line was compared to input DNA. This process is basically analogous to chromatin immunoprecipitation applied to genome tiling arrays and displays the enrichment of methylated CpGs within genomic sequences at a resolution of ˜100 bp. The use of Agilent CpG island arrays has shown a genome-wide characterization of tumor-associated CpG island methylation (Rauch et al., 2007).
Another aspect of the present invention relates to the use of the demethylation/hypomethylation patterns of a DNA biomarker to diagnose a disease or a condition (e.g., a cancer) associated therewith. For example, the 3′ end of the C8orf72 gene is identified having CpG island sequences which is specifically demethylated in cancer cells or tissues. The detection of demethylation of the 3′ end of the C8orf72 gene in a test sample indicates that the sample is a cancerous sample (Rauch et al, 2008).
EXAMPLES Example 1 DNA Methylation Analysis of Lung CancerTo analyze tumor-associated DNA methylation changes, stage-I lung squamous cell carcinomas (SCCs) or adenocarcinomas (AC) are compared to normal matched lung tissues.
Lung squamous cell carcinoma samples and matching normal tissues removed with surgery were obtained from the frozen tumor bank of the City of Hope National Medical Center (Duarte, Calif.). Genomic DNA was purified from tissues by a standard procedure using phenol chloroform extraction and ethanol precipitation.
DNA obtained from normal tissues and from the lung cancer tissues was digested with MseI (5′-TTAA), which produces small (−200-300 bp) fragments and generally cuts outside of CpG islands. Linkers (upper strand 5′-AGCAACTGTGCTATCCGAGGGAT-3′ and lower strand 3′-TAATCCCTCGGA-5′) were ligated to the MseI digested DNA and enrichment of the methylated fraction was done by MIRA as described (Rauch, Wang et al. 2007). Human CpG island microarrays, which contain 237,000 oligonucleotide probes covering 27,800 CpG islands, were purchased from Agilent Technologies. Two micrograms each of the amplicons from MIRA-enriched tumor DNA and normal control samples were labeled with BioPrime Array CGH Genomic Labeling kit (Invitrogen; Carlsbad, Calif.) with either Cy5-dCTP (tumor) or Cy3-dCTP (control) in 87.5 μA reactions (both Cy3- and Cy5-dCTP were obtained from GE Healthcare). The purified labeled samples were then mixed and microarray hybridization was performed according to the Agilent ChIP-on-chip protocol (v.9.0). The hybridized arrays were scanned on an Axon 4000B microarray scanner and the images were analyzed with Axon GenePix software v.5.1. Image and data analysis were done as described (Rauch, Li et al. 2006). Individual CpG islands were considered methylation-positive when at least two adjacent probes within the CpG island scored a fold-difference factor of >3.0 when comparing tumor and normal tissue DNA.
As a result, five stage-I squamous cell carcinomas and eight stage-I adenocarcinomas were initially analyzed on these arrays. The number of methylated CpG islands ranged from 216 to 744 in the five individual squamous cell tumors (Table 1). For adenocarcinomas, between 219 and 908 CpG islands were methylated per tumor (Table 1).
Using MIRA-assisted microarray analysis in Example 1, 59 CpG islands were identified that were methylated in five out of five SCC tumors (
Since these 59 loci (e.g., chromosome 18, chr18: 53254153-53259851, marker OC2) had excellent potential to be specific and sensitive methylation biomarkers for SCC, twelve of these markers (BARHL2, EVX2, IRX2, MEIS1, MSX1, NR2E1, OC2, OSR1, OTX1, PAX6, TFAP2A, and ZNF577) were analyzed in a larger series of 20 SCCs by bisulfite-based COBRA assays (
The methylation frequency of the individual markers ranged from 14/20 (70%) to 20/20 (=100%) of the tumors (Table 3) (e.g., 14/20 (70%) for OC2, 16/20 (80%) for EVX2, 17/20 (85%) for BARHL2, PAX6, or MEIS1, 18/20 (90%) for TFAP2A or ZNF577, 19/20 (90%) for MSX1 or IRX2, and 20/20 (95%) for OTX1, OSR1, or NR2E1). The OTX1, OSR1 and NR2E1 associated CpG islands were methylated in all SCC tumors tested (=100%). Several of these SCC markers were highly specific for tumor-associated methylation, i.e. no methylation was observed in tumor-adjacent normal lung tissue. These included the CpG islands of the OTX1, BARHL2, MEIS1, PAX6, IRX2, OC2, TFAP2A, and EVX2 genes (
Using MIRA-assisted microarray analysis of Example 1, 52 CpG islands (e.g., chromosome 14, chr14: 56344361-56346593, marker OTX2) were identified that were methylated in at least 6 out of 8 adenocarcinomas (Table 4). Several of these adenocarcinoma methylation markers (CHAD, DLX4, GRIK2, KCNG3, NR2E1, OSR1, OTX1, OTX2, PROX1, RUNX1, and VAX1) were chosen for verification by bisulfite-based COBRA assays. These selected adenocarcinoma markers were methylated in more than 80% of the ACs (
A comprehensive analysis of CpG islands in human lung cancer was conducted using MIRA-assisted microarrays. The methylation levels at over 27,000 CpG islands were directly measured and between approximately 200 and 900 of these islands were found to be methylated in individual lung SCC and AC samples. These numbers are compatible with earlier estimates derived from analysis of only a subset of CpG islands methylated in cancer (Costello, Fruhwald et al. 2000). It is clear that not all of these genes can be tumor suppressor genes. For example, consistent with earlier observations, a substantial subset of the methylated genes (20-40% depending on the tumor) was homeobox genes (Rauch, Wang et al. 2007). Homeobox gene associated CpG islands were among the DNA methylation markers identified. The CpG islands of the OTX1, BARHL2, MEIS1, PAX6, IRX2, OC2, TFAP2A, and EVX2 genes were tumor-specifically methylated with no detectable methylation seen in normal lung tissue or in blood DNA. Methylation of these genes (in particular, OTX1, IRX2, OC2 and EVX2), except for TFAP2A in breast cancer (Douglas, Akiyama et al. 2004), has not yet been reported in human cancers. Also, importantly, the methylation frequency of these markers (70 to 100% of the tumors were methylated) is much higher than methylation frequencies of other lung cancer DNA methylation markers reported previously. For example, OTX1 was tumor specifically methylated in 20/20 (=100%) of the tumors, so were NR2E1 and OSR1. These markers present candidates for clinical or diagnostic applications aimed at either detection of early disease in body fluids such as blood or sputum or at disease management and follow-up by using molecular diagnostic testing or methods provided in the instant application.
For adenocarcinomas, several DNA markers have been identified including CHAD, DLX4, GRIK2, KCNG3, NR2E1, OSR1, OTX1, OTX2, PROX1, RUNX1, and VAX1. Methylation of these genes in lung cancer has not yet been reported. The CpG islands associated with the NR2E1, OSR1, and OTX1 genes were methylated in both adenocarcinomas and squamous cell carcinomas at a frequency of over 95%. These markers are excellent candidates for clinical or diagnostic applications aimed at either detection of early disease (e.g., lung cancer) in body fluids such as blood or sputum, or at disease management and follow-up using molecular diagnostic testing.
In sum, changes in DNA methylation patterns are an important characteristic of human cancer. In particular, hypermethylation of CpG islands is a marker of malignant progression. Methylated CpG islands are promising diagnostic markers for the early detection of cancer. In the present invention, a methylated-CpG island recovery assay (MIRA) assisted high-resolution microarray screening approach was used to find hypermethylated CpG islands in squamous cell carcinomas (SCC) and adenocarcinomas (AC) of the lung. Each tumor contained several hundred hypermethylated CpG islands. In an initial microarray screen, 59 CpG islands were methylated in 5/5 (=100%) of the SCC tumors tested and 52 CpG islands were methylated in >75% of the adenocarcinomas tested (n=8). Using sodium-bisulfite based approaches, 12 CpG islands (associated with the BARHL2, EVX2, IRX2, MEIS1, MSX1, NR2E1, OC2, OSR1, OTX1, PAX6, TFAP2A, and ZNF577 genes) were confirmed to be methylated in 70 to 100% of the squamous cell carcinomas (80-100% of the tumors were methylated for 11 of 12 markers tested, 70% for OC2; see Table 3) and 11 CpG islands (associated with the CHAD, DLX4, GRIK2, KCNG3, NR2E1, OSR1, OTX1, OTX2, PROX1, RUNX1, and VAX1 genes) were methylated in >80% of the adenocarcinomas. Many of these newly discovered methylated CpG islands make them specific biomarkers for the early detection of lung cancer.
Example 5 Hypomethylation of CpG Islands in TumorsIn addition to hypermethylation, the MIRA method in combination with CpG island and genomic tiling arrays provided information on the extent and sequence specificity of DNA hypomethylation (Rauch et al., 2008). Short interspersed nuclear elements (SINEs) and long interspersed nuclear elements (LINEs), together with human endogenous retroviruses (HERVs), make up >45% of the human genome. Transposable elements are highly methylated and mostly silenced in normal cells. Although repetitive sequences are not directly represented as probes on the tiling arrays, information on the methylation status of SINE elements was obtained due to hybridization of flanking single copy DNA to adjacent probes after MseI digestion. In the MIRA technique, the highly methylated elements are captured by the MBD2b/MBD3L1 protein complex. After comparing the DNA methylation profiles of normal lung tissues and the matched SCC samples, several thousand tumor associated demethylation events of genomic regions carrying SINE elements (examples are shown
Next, all of the CpG islands on chromosome 8p in tumor SCC2 and its corresponding normal tissue were surveyed. As expected, >98% (159/162) of the promoter-associated CpG islands were unmethylated in normal lung. In addition, there were 78 unmethylated iatrogenic and intergenic CpGislands. Further, 159 mostly short (<0.6 kb) methylated CpG islands were found in normal lung. Sixty-four of these methylated CpG islands were intragenic, and they generally did not become hypomethylated in the tumor. However, the majority of the methylated islands (a total of 95) were located between 0 and 2 Mb away from the chromosome end, overlapping the subtelomeric region, and these were not associated with a known gene. Almost all of the methylated subtelomeric CpG islands were composed of short direct or indirect repeat sequences. Fifty-four of the 95 subtelomeric methylated islands underwent demethylation in the tumor. Their demethylation is consistent with a specific defect of repetitive DNA methylation in cancer tissue. The repeat-rich subtelomeric region of chromosome 8, even outside of CpG islands, was substantially hypomethylated in the tumor (example shown in
The UNC5D gene is another interesting example, because cancer-specific hyper- and hypomethylation events occurred in the same gene. Its promoter was hypermethylated, whereas SINE sequences downstream in the intragenic region were all hypomethylated (
To get a more complete picture of the DNA methylation changes in other repetitive sequences, the analysis was extended to LINE- and HERV-containing loci. A modified COBRA method (Yang et al. 2004) was used to explore methylation changes in LINE and HERV elements. This approach can give an estimate for the global changes in methylation status of these elements. 20 normal lung tissues and matching SCC samples were analyzed (
Another class of repeat sequences are segmental duplications that can be several kilobases in size. Chromosome 8p23 contains an area of a direct genomic duplication (30.5 kb direct repeat) that is also found on several other chromosomes. It was observed that these duplicated sequences underwent extensive demethylation in the tumor sample.
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Claims
1. A method of diagnosing lung cancer comprising:
- obtaining a lung tissue test sample from a subject;
- measuring a methylation level of one or a combination of DNA biomarkers selected from the group consisting of SEQ ID NOS. 1-21 and 23-111 in the lung tissue test sample;
- comparing the methylation level of the one or a combination of DNA biomarkers with the methylation level of a corresponding one or combination of DNA biomarkers in a normal lung tissue sample or lung standard sample; and
- predicting that an increase in the methylation level of the lung tissue test sample in relation to that of the normal lung tissue sample or lung standard sample indicates that the subject is likely to have lung cancer.
2. The method of claim 1 wherein the aberrant methylation is hypermethylation or hypomethylation.
3. The method of claim 2 wherein the condition is a lung cancer.
4. The method of claim 1 wherein the lung cancer is squamous cell carcinoma.
5. The method of claim 4 wherein the one or a combination of DNA biomarkers are selected from one or more genes listed in Table 2 (SEQ ID NOS. 1-59).
6. The method of claim 4 wherein the one or a combination of DNA biomarkers are selected from the group consisting of BARHL2 (SEQ ID NO. 3), EVX2 (SEQ ID NO. 14), IRX2 (SEQ ID NO. 24), MEIS1 (SEQ ID NO. 11), MSX1 (SEQ ID NO. 22), NR2E1 (SEQ ID NO. 33), OC2 (SEQ ID NO. 55), OSR1 (SEQ ID NO. 7), OTX1 (SEQ ID NO. 10), PAX6 (SEQ ID NO. 44), TFAP2A (SEQ ID NO. 30), and ZNF577 (SEQ ID NO. 56).
7. The method of claim 4 wherein the lung cancer is adenocarcinoma.
8. The method claim 7 wherein the one or combination of DNA biomarkers are selected from one or more genes listed in Table 4 (SEQ ID NOS. 60-111).
9. The method of claim 7 wherein the one or combination of DNA biomarkers are selected from the group consisting of CHAD (SEQ ID NO. 63), DLX4 (SEQ ID NO. 64), GRIK2 (SEQ ID NO. 68), KNCG3 (SEQ ID NO. 74), NR2E1 (SEQ ID NO. 78), OSR1 (SEQ ID NO. 79), OTX1 (SEQ ID NO. 80), OTX2 (SEQ ID NO. 83), PROX1 (SEQ ID NO. 88), RUNX1 (SEQ ID NO. 90), and VAX1 (SEQ ID NO. 98).
10. The method of claim 1 wherein the one or a combination of DNA biomarkers are selected from the group consisting of BARHL2 (SEQ ID NO. 3), EVX2 (SEQ ID NO. 14), IRX2 (SEQ ID NO. 24), MEIS1 (SEQ ID NO. 11), MSX1 (SEQ ID NO. 22), NR2E1 (SEQ ID NO. 33), OC2 (SEQ ID NO. 55), OSR1 (SEQ ID NO. 7), OTX1 (SEQ ID NO. 10), PAX6 (SEQ ID NO. 44), TFAP2A (SEQ ID NO. 30), ZNF577 (SEQ ID NO. 56), CHAD (SEQ ID NO. 63), DLX4 (SEQ ID NO. 64), GRIK2 (SEQ ID NO. 68), KNCG3 (SEQ ID NO. 74), NR2E1 (SEQ ID NO. 78), OSR1 (SEQ ID NO. 79), OTX1 (SEQ ID NO. 80), OTX2 (SEQ ID NO. 83), PROX1 (SEQ ID NO. 88), RUNX1 (SEQ ID NO. 90), and VAX1 (SEQ ID NO. 98).
11. The method of claim 1 wherein the methylation level is measured by a methylated-CpG island recovery assay (MIRA), a combined bisulfite-restriction analysis (COBRA), or a methylation-specific PCR (MSP).
12. The method of claim 11 wherein the methylation levels of the one or a combination of DNA biomarkers are measured by an MIRA-assisted microarray analysis.
13. The method of claim 1 wherein the one or combination of DNA biomarkers are selected from the group consisting of OTX1 (SEQ ID NO. 10), IRX2 (SEQ ID NO. 24), OC2 (SEQ ID NO. 55), and EVX2 (SEQ ID NO. 14).
14. The method of claim 1 wherein the increase is more than 2 fold.
15. The method of claim 14 wherein the increase is more than 3 fold.
16. A method of diagnosing lung cancer comprising:
- 1) obtaining a lung tissue test sample from a subject;
- 2) obtaining a genome DNA from the lung tissue test sample from the subject;
- 3) obtaining methylated regions from the genome DNA;
- 4) hybridizing the methylated regions to a DNA microarray comprising one or a combination of DNA biomarkers selected from the group consisting of SEQ ID NOS. 1-21 and 23-111;
- 5) comparing the hybridization of the methylated regions from the genome DNA with the hybridization of the corresponding methylated regions of a normal lung tissue sample or lung standard sample genome DNA; and
- 6) predicting that an increase in the methylated regions of the genome DNA hybridizing to the DNA biomarker relative to the methylated regions of the normal lung tissue sample or lung standard sample genome DNA hybridizing to the one or a combination of DNA biomarkers indicates that the subject is likely to have lung cancer.
17. The method of claim 16 wherein the lung cancer is squamous cell carcinoma and the one or combination of DNA biomarkers are selected from is one or more genes listed in Table 2 (SEQ ID NOS. 1-59).
18. The method of claim 17 wherein the one or a combination of DNA biomarkers are selected from the group consisting of BARHL2 (SEQ ID NO. 3), EVX2 (SEQ ID NO. 14), IRX2 (SEQ ID NO. 24), MEIS1 (SEQ ID NO. 11), MSX1 (SEQ ID NO. 22), NR2E1 (SEQ ID NO. 33), OC2 (SEQ ID NO. 55), OSR1 (SEQ ID NO. 7), OTX1 (SEQ ID NO. 10), PAX6 (SEQ ID NO. 44), TFAP2A (SEQ ID NO. 30), and ZNF577 (SEQ ID NO. 56).
19. The method of claim 16 wherein the condition is adenocarcinoma and the one or combination of DNA biomarkers are selected from one or more genes listed in Table 4 (SEQ ID NOS. 60-111).
20. The method of claim 19 wherein the one or combination of DNA biomarkers are selected from the group consisting of CHAD (SEQ ID NO. 63), DLX4 (SEQ ID NO. 64), GRIK2 (SEQ ID NO. 68), KNCG3 (SEQ ID NO. 74), NR2E1 (SEQ ID NO. 78), OSR1 (SEQ ID NO. 79), OTX1 (SEQ ID NO. 80), OTX2 (SEQ ID NO. 83), PROX1 (SEQ ID NO. 88), RUNX1 (SEQ ID NO. 90), and VAX1 (SEQ ID NO. 98).
21. A method of diagnosing a tumor from a test sample in a subject comprising the step of:
- measuring the methylation level of one or a combination of DNA biomarkers from the test sample and a standard sample:
- wherein the fold difference between the methylation level of the test sample in relation to the methylation level of the standard sample indicates the likelihood of the test sample having the condition; and
- wherein the one or combination of DNA biomarkers are selected from the group consisting of OTX1 (SEQ ID NO. 10), IRX2 (SEQ ID NO. 24), OC2 (SEQ ID NO. 55), EVX2 (SEQ ID NO. 14).
22. The method of claim 21 wherein the methylation level is measured by a methylated-CpG island recovery assay (MIRA), a combined bisulfite-restriction analysis (COBRA), or a methylation-specific PCR (MSP).
23. A method of diagnosing a tumor from a test sample in a subject comprising the step of:
- measuring the methylation level of one or a combination of DNA biomarkers from the test sample and a standard sample:
- wherein the fold difference between the methylation level of the test sample in relation to that of the standard sample indicates the likelihood of the test sample having the condition; and
- wherein the DNA biomarker is the 3′ end of C8orf72 gene.
Type: Application
Filed: Jan 10, 2013
Publication Date: May 9, 2013
Applicant: CITY OF HOPE (Duarte, CA)
Inventor: CITY OF HOPE (Duarte, CA)
Application Number: 13/738,869
International Classification: C12Q 1/68 (20060101);