Patent Application
20100172880
Particular aspects relate generally to markers (e.g., diagnostic and/or prognostic DNA methylation markers) for cellular proliferative disorders and/or cancer and markers or for developmental lineages and/or stages, and to precursor cells (e.g., embryonic stem (ES) cells, somatic stem cells, cancer stem cells, etc), and more particularly to methods for identifying preferred DNA methylation markers for cellular proliferative disorders and/or cancer or markers for developmental lineages and/or stages, and for validating and/or monitoring of precursor cells (e.g., embryonic stem (ES) cells, somatic stem cells, cancer stem cells, cells of a particular developmental lineage and/or stage, etc), particularly of precursor cells to be used therapeutically. Additional aspects relate to method for diagnosis or prognosis of ovarian cancer comprising determining the methylation state of a HOX genomic DNA sequence. Yet further aspects relate to methods for predicting the response to neoadjuvant and/or adjuvant chemotherapy in a solid tumor.
Cancer and cancer stem cells. A long-standing question in cancer research has been whether cancer arises through mutations in stem cells, or whether transforming differentiated cells reacquire stem cell characteristics through a process of dedifferentiation (Houghton et al., Semin Cancer Biol 4, 4, 2006; Passegue, E. Nature 442:754-7555, 2006). Tumor heterogeneity and shared features of normal stem cells and cancer cells have recently given rise to the concept of cancer stem cells (Pardal et al., Nat Rev Cancer 3:895-902, 2003; Jordan et al., N Engl J Med 355:1253-1261, 2006). However, it has been challenging to obtain firm empirical evidence supporting a normal stem cell origin of cancer and this question remained open.
Epigenetic alterations in cancer and gene silencing. In the past decade, it has become clear that cancer arises, not only as a consequence of genetic alterations, such as mutations, deletions, amplifications and translocations, but also as a consequence of stable epigenetic changes in DNA methylation, histone modifications, and chromatin structure, with associated changes in gene expression (Jones & Laird, Nat Genet 21:163-167, 1999; Laird, P. W. Hum Mol Genet 14, R65-R76, 2005; Baylin & Ohm, Nat Rev Cancer 6:107-116, 2006; and Bird, A. Genes Dev 16, 6-21, 2002). In recent years, the disparate fields of chromatin structure, histone modification, DNA methylation, and transcription regulatory complexes have come together to provide an integrated view of epigenetics (Laird, P. W. Hum Mol Genet 14, R65-R76, 2005; Ordway & Curran, T. Cell Growth Differ 13:149-162, 2002; Freiman & Tjian Cell 112, 11-17, 2003; Felsenfeld & Groudine, Nature 421; 448-453, 2003; and Jaenisch & Bird, Nat Genet 33:245-254, 2003). This elaborate mechanism for regulating areas of the genome for transcriptional activity, repression, or silencing participates in mammalian development (Li et al., Cell 69:915-926, 1992), genomic imprinting (Li et al., Nature 366:362-5, 1993), X-inactivation in females (Zuccotti & Monk, Nat Genet 9:316-320, 1995; and Boumil et al., T. Mol Cell Biol 26:2109-2117, 2006), in silencing parasitic DNA elements (Walsh & Bestor, Genes Dev 13:26-34, 1999), and in coordinating cell-type specific gene expression (Futscher et al. Nat Genet 31:175-179. 2002).
Cancer cells contain extensive aberrant epigenetic alterations, including promoter CpG island DNA hypermethylation and associated alterations in histone modifications and chromatin structure. Aberrant epigenetic silencing of tumor-suppressor genes in cancer involves changes in gene expression, chromatin structure, histone modifications and cytosine-5 DNA methylation.
Epigenetic mechanisms in embryonic stem (ES) cell differentiation). Embryonic stem cells are unique in the ability to maintain pluripotency over significant periods in culture, making them leading candidates for use in cell therapy. Embryonic stem (ES) cell differentiation involves epigenetic mechanisms to control lineage-specific gene expression patterns. ES cells rely on Polycomb group (PcG) proteins to reversibly repress genes required for differentiation, promoting ES cell self-renewal potential. ES cell-based therapies hold great promise for the treatment of many currently intractable heritable, traumatic, and degenerative disorders. However, these therapeutic strategies inevitably involve the introduction of human cells that have been maintained, manipulated, and/or differentiated ex vivo to provide the desired precursor cells (e.g., somatic stem cells, etc.), raising the specter that aberrant or rogue cells (e.g., cancer cells or cells predisposed to cancer that may occur during such manipulations and differentiation protocols) may be administered along with desired cells.
Therefore, there is a pronounced need in the art for novel, effective and efficient methods for stem cell and/or precursor cell monitoring and validation, and for novel therapeutic methods, comprising monitoring and/or validating stem cells and/or precursor cells prior to therapeutic administration to preclude introduction of aberrant or rogue cells (e.g., cancer cells or cells predisposed to cancer).
Ovarian Cancer. In the US and Europe, epithelial ovarian cancer causes more deaths than cancer in any other female reproductive organ. It is estimated that there are about 20,180 new cases of ovarian cancer and 15,310 deaths in the US per year (1). Due to the current lack of early detection strategies, many ovarian cancer patients present with advanced stage disease, and the overall 5-year survival for these women is less than 30% (2). Despite the development of new therapeutic approaches, these survival statistics have remained largely unchanged for the past three decades. The most important prognostic parameters for this disease are age, stage, grade and optimal cytoreductive surgery (where all visible cancer in the peritoneal cavity is removed). Beside molecular genetic changes and expression profiling, studies have also begun addressing the epigenetic components of ovarian carcinogenesis (3-5). Changes in DNA methylation status (predominantly at CpG) are among the most common molecular alterations in human neoplasia (6). DNA methylation changes promise to be important screening markers for carcinogenesis.
Therefore, there is a pronounced need in the art for a better understanding of the molecular pathogenesis of ovarian cancer and identification of new drug targets or biomarkers that facilitate early detection.
Breast cancer. Breast cancer is the most frequent malignancy among women in the industrialized world. To date the presence or absence of metastatic involvement in the axillary lymph nodes is still the most powerful prognostic factor available for patients with primary breast cancer (1), although this is just an indirect measure reflecting the tendency of the tumor to spread. Chemotherapy can be an integral component of the adjuvant management strategy for women with early-stage breast cancer. Recently applicants showed that RASSF1A DNA methylation in serum is a poor prognostic marker in women with breast cancer (2) and that this cancer-specific DNA alteration allows monitoring of adjuvant Tamoxifen therapy, which is applied mainly in ER positive tumors (3). To date, however, no tool is available to sufficiently predict or monitor efficacy of neoadjuvant or adjuvant systemic chemotherapy which is frequently applied in ER negative breast cancer. Therefore, there is a pronounced need in the art for a better understanding of the molecular pathogenesis of breast cancer and identification of new biomarkers that facilitate early detection and treatment of breast cancer (e.g., ER negative breast cancer).
Stems cells rely on Polycomb group proteins (PcG) to reversibly repress genes encoding transcription factors required for differentiation (Ringrose & Paro, Annu Rev Genet 38:413-443, 2004; Lee et al. Cell 125:301-313, 2006, incorporated herein by reference, including supplemental materials thereof). While the present applicants and others have previously hypothesized that acquisition of promoter DNA methylation at these repressed genes may potentially lock in stem cell phenotypes and initiate abnormal clonal expansion and thereby predispose to cancer (for background, see also Schuebel, et al., Nat Genet 38:738-740, 2006), supporting empirical evidence for this idea has been lacking and this hypothesis has remained as mere speculation, until the instant disclosure herein. Moreover, recently, it has been reported that differentiating human ES cells acquire epigenetic abnormalities that are distinct from those observed in cancer (Shen et al., Hum Mol Genet 26:26, 2006).
Aspects of the present invention provide the first real evidence that stem-cell polycomb group (PcG) targets are substantially more likely to have cancer-specific promoter DNA hypermethylation than non-targets, thus providing, for the first time, effective and efficient methods for stem cell and/or precursor cell monitoring and validation, and for novel therapeutic methods, comprising monitoring and/or validating stem cells and/or precursor cells prior to therapeutic administration to preclude introduction of aberrant or rogue cells (e.g., cancer cells or cells predisposed to cancer). Specifically, according to particular aspects of the present invention, applicants report that stem-cell polycomb group (PcG) targets are up to twelve-fold more likely to have cancer-specific promoter DNA hypermethylation than non-targets, indicating a stem-cell origin of cancer, in which reversible gene repression is replaced by permanent silencing, locking the cell into a perpetual state of self-renewal and thereby predisposing to subsequent malignant transformation.
Exemplary aspects provide methods for identifying preferred DNA methylation markers for cellular proliferative disorders and/or cancer, based on identifying PcG protein or PcG repressive complex genomic target loci (collectively, PcG target loci) within a precursor cell (e.g., embryonic stem (ES) cells, somatic stem cells, cancer stem cells, progenitor cell, etc.) population, and determining, in cells of the cellular proliferative disorder and/or cancer (e.g., colorectal, breast, ovarian, hematopoietic, etc.), a characteristic (cancer-specific) methylation status of CpG sequences within loci corresponding to the precursor cell PcG target loci. Specific embodiments provide a method for identifying, screening, selecting or enriching for preferred DNA methylation markers for a cellular proliferative disorder and/or cancer, comprising: identifying, with respect to a precursor cell population, one or a plurality of genomic target loci for at least one polycomb group protein (PcG) or Polycomb repressive complex (collectively referred to herein as PcG target loci); obtaining a sample of genomic DNA from cells of a cellular proliferative disorder and/or cancer; and determining, by analyzing the genomic DNA from the cells of the cellular proliferative disorder and/or cancer using a suitable assay, a cancer-specific methylation status of at least one CpG dinucleotide sequence position within at least one region of at least one of the polycomb group protein (PcG) target loci, wherein the presence of said CpG methylation status identifies the at least one region of at least one of the polycomb group protein (PcG) target loci as a preferred DNA methylation marker for the cellular proliferative disorder and/or cancer.
Particular embodiments provide a method for identifying, screening, selecting or enriching for preferred DNA methylation markers for cells of a particular developmental lineage or stage, comprising: identifying, with respect to a precursor cell population, one or a plurality of genomic target loci for at least one polycomb group protein (PcG) or polycomb repressive complex (PcG target loci); obtaining a sample of genomic DNA from cells of a particular developmental lineage or stage; and determining, by analyzing the genomic DNA from the cells of the particular developmental lineage or stage using a suitable assay, a lineage-specific or stage-specific DNA methylation status of at least one CpG dinucleotide sequences within at least one region of at least one of the polycomb group protein (PcG) target loci, wherein the presence of said CpG methylation status identifies the at least one region of at least one of the polycomb group protein (PcG) target loci as a preferred DNA methylation marker for the particular developmental lineage or stage. In particular embodiments, determining the lineage-specific or stage-specific methylation status of the at least one CpG dinucleotide sequences within at least one region of at least one of the polycomb group protein (PcG) target loci, is determining the DNA methylation status of a locus that has a cancer-specific DNA methylation status.
Additional aspects provide methods for validating and/or monitoring a precursor cell (e.g., embryonic stem (ES) cells, somatic stem cells, cancer stem cells, progenitor cell, etc.) population, comprising screening or monitoring one or more PcG genomic target loci of a precursor cell population for the presence of absence of target loci methylation status that is characteristic of (disorders-specific, cancer-specific) the PcG target loci in one or more cellular proliferative disorders and/or cancers, or that, in certain further embodiments corresponds to (is specific for) a particular developmental status (e.g., lineage or stage). Specific embodiments provide a method for validating and/or monitoring a precursor cell population, comprising: identifying, with respect to a reference precursor cell population, one or a plurality of genomic target loci for at least one polycomb group protein (PcG) or polycomb repressive complex; identifying one or a plurality of said target loci having a characteristic (disorder-specific, cancer specific) DNA methylation status in a cellular proliferative disorder and/or cancer to provide a set of preferred disorder and/or cancer-related diagnostic/prognostic loci; obtaining genomic DNA from a first test therapeutic precursor cell population of interest; and determining, by analyzing the genomic DNA of the first test therapeutic precursor cell population using a suitable assay, the methylation status of at least one CpG dinucleotide sequence within at least one region of at least one of the polycomb group protein (PcG) preferred diagnostic/prognostic loci, wherein the first test therapeutic precursor cell population is validated and/or monitored with respect to the presence or absence of the characteristic (disorder-specific, cancer-specific) DNA methylation status of the one or a plurality of said target loci having a characteristic DNA methylation status in the cellular proliferative disorder and/or cancer, or with respect to the presence or absence of cells of the cellular proliferative disorder and/or cancer, or with respect to the presence or absence of cells or cells having a predispostion thereto.
Further aspects provide a method for validating and/or monitoring a precursor cell population, comprising: identifying, with respect to a reference precursor cell population, one or a plurality of genomic target loci for at least one polycomb group protein (PcG) or polycomb repressive complex; identifying one or a plurality of said target loci having a characteristic DNA methylation status (lineage-specific, stage specific, etc.) in a cell of a particular developmental lineage or stage to provide a set of preferred lineage or stage specific diagnostic/prognostic loci; obtaining genomic DNA from a first test therapeutic cell population of interest; and determining, by analyzing the genomic DNA of the first test therapeutic cell population using a suitable assay, the DNA methylation status of at least one CpG dinucleotide sequence within at least one region of at least one of the polycomb group protein (PcG) preferred diagnostic/prognostic loci, wherein the first test therapeutic cell population is validated and/or monitored with respect to the presence or absence of the characteristic methylation status (lineage-specific, stage-specific, etc.) of the one or a plurality of said target loci having a characteristic methylation status of cells of a particular developmental lineage or stage or with respect to the presence or absence of cells of the particular developmental lineage or stage, or with respect to the presence or absence of cells or cells having a developmental predispostion thereto. In particular embodiments, determining the lineage-specific or stage-specific methylation status of the at least one CpG dinucleotide sequences within at least one region of at least one of the polycomb group protein (PcG) target loci, is determining the methylation status of a locus that has a cancer-specific methylation status.
In yet additional embodiments, various stem or precursor cells are used to identify transcriptional repressor occupancy sites (e.g., by chromatin immunoprecipitation chip analysis) and status for not only polycomb repressive complex 2 (PRC2), but also for other repressors and repressor complexes (e.g., repressors of developmental genes) as well, and these ChIP-Chip targets are then used as a means of enrichment for cancer-specific DNA methylation markers as taught herein using the exemplary combination of embryonic stems cells and PRC2 targets. According to further aspects, therefore, the instant approach has substantial utility for various types of stem and precursor cells (ES cell, somatic stem cells, hematopoietic stem cells, leukemic stem cells, skin stem cells, intestinal stem cells, gonadal stem cells, brain stem cells, muscle stem cells (muscle myoblasts, etc.), mammary stem cells, neural stem cells (e.g., cerebellar granule neuron progenitors, etc.), etc), and for various stem- or precursor cell repressor complexes (e.g., such as those described in Table 1 of Sparmann & Lohuizen, Nature 6, 2006 (Nature Reviews Cancer, November 2006), incorporated herein by reference), and for various types of cancer, where the requirements are that the repressor occupancy sites/loci and corresponding occupancy status are defined/established, and a characteristic DNA methylation status (e.g., disorder-specific, cancer-specific, etc.) (e.g., DNA hypermethylation) is established at corresponding sites/loci in one or more cellular proliferative disorders or cancers of interest, or, in particular embodiments, characteristic lineage-specific, stage specific, etc., status in cells of a developmental lineage or stage of interest.
Yet additional aspects provide a method for the diagnosis or prognosis of ovarian cancer comprising: performing methylation analysis of genomic DNA of a subject tissue sample; and determining the methylation state of a HOX genomic DNA sequence relative to a control HOX genomic DNA sequence, wherein diagnosis or prognosis of ovarian cancer is provided. In particular embodiments, the HOX genomic DNA sequence is that of HOXA10 or HOXA11, and hypermethylation is used to provide the ovarian cancer related diagnosis or prognosis. In certain aspects, the HOX genomic DNA sequence is that of HOXA11, and hypermethylation is used to provide a ovarian cancer related prognosis of poor outcome. In particular embodiments, the diagnostic or prognosic marker is for at least one selected from the group consisting of: for stem cells that are unable to differentiate; for stem cell that are resistant to therapy; for residual tumor after cytoreductive surgery; for cancer stem cells; for mucinous cancer cases; for serous cancer cases; for endometrioid cancer cases; for clear cell cases; and for tumor distribution.
Further aspects provide a method for predicting the response to neoadjuvant and/or adjuvant chemotherapy in a solid tumor, comprising performing methylation analysis of genomic DNA of a subject tissue sample; and determining the methylation state of a NEUROD1 genomic DNA sequence relative to a control NEUROD1 genomic DNA sequence, wherein predicting the response to neoadjuvant and/or adjuvant chemotherapy in breast cancer is provided. Additional aspects provide a method for determining chemosensitivity in breast cancer, comprising: performing methylation analysis of genomic DNA of a subject tissue sample; and determining the methylation state of a NEUROD1 genomic DNA sequence relative to a control NEUROD1 genomic DNA sequence, wherein determining chemosensitivity in breast cancer is provided. In certain embodiments of these methods, NEUROD1 methylation is a chemosensitivity marker in estrogen receptor (ER) negative breast cancer. In particular aspects, methylation analysis is at least one of: methylation analysis in core breast cancer biopsies taken prior to preoperative chemotherapy with complete pathological response as the endpoint; and seroconversion of NEUROD1 methylation in serum DNA during adjuvant chemotherapy with survival as the endpoint. In particular implementations, the chemosensitivity is with respect to at least one of cyclophospamide, methotrexate, 5-fluorouracil, anthracycline, and combinations thereof.
Stems cells rely on Polycomb group proteins (PcG) to reversibly repress genes encoding transcription factors required for differentiation (Ringrose & Paro, Annu Rev Genet 38:413-443, 2004). Lee et al. have identified genes targeted for transcriptional repression in human embryonic stem (ES) cells by the PcG proteins SUZ12 and EED, which form the Polycomb Repressive Complex 2, PRC2, and which are associated with nucleosomes that are trimethylated at histone H3 lysine-27 (H3K27me3) (Lee, T. I. et al. Cell 125:301-313, 2006, incorporated herein by reference, including supplemental materials thereof). The present applicants have previously hypothesized that acquisition of promoter DNA methylation at these repressed genes could potentially lock in stem cell phenotypes and initiate abnormal clonal expansion and thereby predispose to cancer, but empirical evidence has been, until the instant disclosure herein, lacking to support such a hypothesis (for background, see also Schuebel, et al., Nat Genet 38:738-740, 2006). Moreover, recently, it has been reported that differentiating human ES cells acquire epigenetic abnormalities that are distinct from those observed in cancer (Shen et al., Hum Mol Genet 26:26, 2006).
The present applicants have recently described the promoter DNA methylation analysis of 195 genes in ten primary human colorectal tumors and matched normal mucosa (Weisenberger, D. J. et al. Nat Genet 38:787-793, 2006, incorporated herein by reference, including supplementary materials thereof). As described in detail herein, the present applicants identified and correlated cancer-associated DNA methylation with the stem cell occupancy by SUZ12 and EED, and the H3K27Me3 status for 177 of the genes described by Lee et al (Supra). Of these 177 genes, an astonishing 77 displayed evidence of cancer-associated DNA methylation, when compared to matched normal colorectal mucosa (
Strikingly, approximately 44% of these 77 genes contain at least one of these ES cell repressive marks, while 32% of these genes contain all three marks (see working EXAMPLE 2 below and Table 1 thereof). Only about 5% of the 100 genes that are either constitutively methylated or unmethylated contain these marks, while only 3% contain all three marks, close to the average of 4% of the 16,710 gene promoters reported by Lee et al (Supra). The difference in ES cell repressive marks between cancer-specifically methylated genes and constitutively methylated or unmethylated genes is highly significant by Fisher Exact Test (P<0.0001; Odds Ratio: 12.1), whether the analysis is restricted to tumors with CpG island methylator phenotype (CIMP) (Weisenberger, D. J. et al., supra) or not.
This astonishing association was independently confirmed for both ovarian and breast cancer-specifically methylated genes (see working EXAMPLES 3 and 4, respectively, below). Hatada et al. (Oncogene 9:9, 2006) used a DNA methylation microarray to identify hypermethylated genes in lung cancer cells. According to additional aspects of the present invention, of the 273 hypermethylated loci with known gene names and PRC2 occupancy, an astonishing 96 (35%) had at least one PRC2 mark. This result contrasts to only one gene with a single mark among the 23 known genes showing DNA hypomethylation in this study (P=0.0019; Odds Ratio: 11.9).
According to additional aspects, the predisposition of ES-cell PRC2 targets to cancer-specific DNA hypermethylation indicates crosstalk between PRC2 and de novo DNA methyltransferases in an early precursor cell with a PRC2 distribution similar to that of ES cells. The precise developmental stage and type of cell in which such crosstalk occurs is unknown, and is not likely to be an embryonic stem cell. Other stem and embryonic cell types display a similar PRC2 preference for DNA-binding proteins and transcription factors (Squazzo et al. Genome Res 16:890-900, 2006; Bracken et al., Genes Dev 20:1123-1136, 2006, both incorporated herein by reference in their entireties). In contrast, colorectal and breast cancer cell lines display a markedly different set of PRC2 targets, enriched in genes encoding glycoproteins, receptors, and immunoglobulin-related genes (Squazzo et al. Genome Res 16:890-900, 2006), which are not frequent cancer-specific DNA hypermethylation targets. This indicates, according to particular aspects of the present invention, that the ‘crosstalk’ leading to DNA methylation predisposition likely occurred early in oncogenesis, at a time in which the PRC2 distribution resembled that of a stem cell (see, e.g., applicants' model of
According to further aspects, where such crosstalk occurs at low frequency in stem cells, this phenomenon is observable in enriched adult stem cell populations. In specific embodiments, the high sensitivity of the MethyLight™ assay allowed for the detection of low frequency dense promoter methylation in CD34-positive hematopoietic progenitor cells (see working EXAMPLE 5, respectively, below). Stem-cell repressed genes, containing at least two of the PRC2 marks demonstrated detectable DNA methylation in CD34-positive cells in twice the number of subjects compared to genes lacking these marks (Mean: 6.1 vs 3.2, respectively, P=0.02).
According to additional aspects, the first predisposing steps towards malignancy occur very early, and are consistent with reports of field changes in histologically normal tissues adjacent to malignant tumors (Feinberg et al., Nat Rev Genet 7:21-33, 2006; Eads et al., Cancer Res 60:5021-5026, 2000; Shen et al. J Natl Cancer Inst 97:1330-1338, 2005). The instant results provide a mechanistic basis for the predisposition of some (e.g., a subset), but not other promoter CpG islands to cancer-associated DNA hypermethylation. Indeed, since some of the PRC2 targets with tumor-specific promoter DNA methylation, such as MYOD1, NEUROD1 and NEUROG1, are not normally expressed in the epithelium, the instant teachings indicate a residual stem-cell memory, rather than selective pressure for silencing of these particular genes during the transformation process in epithelial cells.
According to certain aspects, aberrant PRC2-DNA methyltransferase ‘crosstalk’ occurs at low frequency in stem cells, and does not disrupt normal differentiation if the silencing affects a small number of PRC2 targets that are not crucial to differentiation. However, if a sufficient number of a particular subset is affected, then the resulting DNA methylation ‘seeds’ prevent proper differentiation, and predispose the cell to further malignant development.
Applicants note that not all cancer-specifically methylated genes are ES-cell PRC2 targets, and therefore, according to yet additional aspects, PRC2 targets in other stem or progenitor cells contribute to the diversity of DNA methylation targets observed among different types of cancer.
In further aspects, other, and more tissue-specific repressive complexes are capable of causing a similar predisposition to characteristic DNA methylation status (e.g., hypermethylation).
According to yet further aspects, screening for PRC2 target promoter DNA hypermethylation has substantial utility for therapeutic applications involving introduction of precursor cells derived from cloned or cultured ES cells (see, e.g., for background, Roy et al. Nat Med 12: 1259-1268, 2006).
In additional embodiments of the present invention, various stem or precursor cells are used to identify transcriptional repressor occupancy sites (e.g., by chromatin immunoprecipitation chip analysis) and status for not only PRC2, but also for other repressors and repressor complexes as well (e.g., such as those described in Table 1 of Sparmann & Lohuizen, Nature 6, 2006 (Nature Reviews Cancer, November 2006), incorporated herein by reference), and these ChIP-Chip targets as then used as a means of enrichment for cancer-specific DNA methylation markers as taught herein using the exemplary combination of embryonic stems cells and PRC2 targets.
Further embodiments provide a method for identifying, screening, selecting or enriching for preferred DNA methylation markers for a cellular proliferative disorder and/or cancer, or for selecting or enriching for preferred DNA methylation markers for a developmental cell lineage or stage (see, e.g., EXAMPLE 8).
Particular embodiments provide methods for validating and/or monitoring a precursor cell population, for example, with respect to the presence or absence of cells of a proliferative disorder or cancer, or cells having a development predisposition thereto, or cell of a particular development lineage or stage (see, e.g., EXAMPLE 9).
According to particular aspects, a preferred marker is a marker that is a developmental repressor locus (e.g., for PcGs, and PRC1, PRC2, etc.) and that further comprises at least one CpG dinucleotide sequence position having a DNA methylation state (e.g., DNA hypermethylation) that is cellular proliferative disorder-specific and/or cancer specific.
Particularly preferred is a marker that is a PRC1 or PRC2 developmental repressor locus with occupation by at least one of SUZ 12, EED, and H3K27me3, and that further comprises at least one CpG dinucleotide sequence position having a DNA methylation state (e.g., hypermethylation) that is cellular proliferative disorder-specific and/or cancer specific.
More preferred is a marker that is a PRC1 or PRC2 developmental repressor locus with occupation by at least two of SUZ 12, EED, and H3K27me3, and that further comprises at least one CpG dinucleotide sequence position having a methylation state (e.g., hypermethylation) that is cellular proliferative disorder-specific and/or cancer specific.
Especially preferred is a marker that is a PRC1 or PRC2 developmental repressor locus with occupation by all three of SUZ 12, EED, and H3K27me3, and that further comprises at least one CpG dinucleotide sequence position having a methylation state (e.g., hypermethylation) that is cellular proliferative disorder-specific and/or cancer specific.
Particularly preferred are subsets of any of the above preferred markers that also bind at least one of the transcription factors OCT4, SOX2, and Nanog.
In additional embodiments of the present invention, various stem or precursor cells are used to identify transcriptional repressor (e.g., transcription factor) occupancy sites (e.g., by chromatin immunoprecipitation chip analysis) and status for not only PRC2, but also for other repressors and repressor complexes as well (e.g., at least one transcription factor of the Dlx, Irx, Lhx and Pax gene families (neurogenesis, hematopoiesis and axial patterning), or the Fox, Sox, Gata and Tbx families (developmental processes)), and these ChIP-Chip targets as then used as a means of enrichment for cancer-specific DNA methylation markers as taught herein using the exemplary combination of embryonic stems cells and PRC2 targets.
Colorectal cancer DNA Methylation Data and PRC2 Occupancy. The full methods for the colorectal cancer data have been published previously (D. J. Weisenberger et al., Nat Genet. 38:7, 2006; incorporated by reference herein in its entirety).
Hematopoietic related Patients. CD34 pos. cells isolated from stem cell apheresis collections from nine women were analyzed. The samples were collected during treatment at the Division of Hematology and Oncology, Innsbruck Medical University, Austria. All patients signed informed consent prior to apheresis.
Ovarian and breast related patients. Ovarian tissues from 40 patients and breast specimens from 30 patients were collected during surgery at the Department of Obstetrics and Gynecology of the Innsbruck Medical University, Austria in compliance with and approved by the Institutional Review Board.
Apheresis samples. Peripheral blood progenitor cells (PBPC) were collected in these patients to perform high-dose chemotherapy followed by autologous stem cell transplantation to treat different diseases (n=9; age range: 20.1 to 49.4 yrs.; mean: 35.6 years; 3 breast cancer patients in a clinical trial setting, 2 patients with acute myeloid leukemia, 1 patient with B acute lymphoblastic leukemia, 1 patient with medulloblastoma, 1 patient with T non-Hodgkin's lymphoma and 1 patient with idiopathic thrombocytopenic purpura). Mobilization of PBPC was performed by administration of chemotherapy followed by G-CSF. The harvest of PBPC was performed as large-volume, continuous-flow collection using a COBE Spectra® blood cell separator (Gambro BCT, Colorado, USA) through bilateral peripheral venous accesses. During the first apheresis, the blood was processed at a rate of 50 to 120 ml/min. A second collection was optional and depended on the yield of CD34 pos. progenitors cells obtained during the first procedure. In addition, the CD34 pos. cells were isolated with CD34 conjugated magnetic beads (Miltenyi Biotec; Bergisch Gladbach, Germany) according the manufacturer's instructions. CD34 purity was controlled by flow cytometric analysis. Only cell fractions with >90% purity were further analyzed.
Tissue samples; ovarian and breast. Applicants analyzed patients with ovarian cancer (n=22; age range: 30.1 to 80.9 yrs.; mean: 61.8 yrs.; 7 serous cystadeno, 6 mucinous, 6 endometrioid and 3 clear cell cancers) and patients with normal ovaries (n=18; age range: 24.1 to 76.9 yrs.; mean: 61.6 yrs.; 13, 4 and 1 had endometrial and cervical cancer and fibroids, respectively). In addition, patients with breast cancer (n=15; age range: 30.3 to 45.7 yrs.; mean: 38.0 yrs.; 13 invasive ductal, 1 invasive lobular and 1 tubular cancer) and patients with non-neoplastic breast tissue (n=15; age range: 19.8 to 46.2 yrs.; mean: 35.0 yrs; all of them had an open biopsy due to a benign breast lesion) were analyzed. Tissues were immediately snap-frozen in liquid nitrogen, pulverized in the frozen state, and stored at 80° C. until used.
Genomic DNA from cell and tissue samples was isolated using the DNeasy Tissue Kit (Qiagen, Hilden, Germany) according to the manufacturer's protocol.
Sodium bisulfite conversion, MethyLight™ analysis and nucleotide sequences for most MethyLight™ primers and probes has been described (Weisenberger et al., Nat Genet. 38:7, 2006; Muller et al., Cancer Res. 63:22, 2003; and Fiegl et al., Cancer Epidemiol Biomarkers Prey. 13:5, 2004; all of which are incorporated herein by reference in their entireties). The following primer and probe sequences were used for the ovarian, breast, and CD34 positive cell analyses, and differ from published reactions for these loci:
Descriptive analysis of obtained data was performed and median as well as interquartile range was given. Differences of PMR values between normal and cancer tissues were analyzed by means of Mann-Whitney U test. All statistical analyses were done applying SPSS Software 10.0.
Table 1 lists the 177 MethyLight™ reactions from Weisenberger et al. (2006) for which the PRC2 occupancy could be established from the data published in Lee et al. (2006). Of the 177 reactions, 164 (93%) are located within 1 kb of the transcription start site. Of the PRC2 targets, 95% are located within 1 kb of the transcription start site. See Table 5 herein below for primer and probe details.
Table 2 lists DNA methylation values (PMR) of 35 genes analyzed in 18 normal ovaries and 22 ovarian cancers. These genes were selected for their potential utility as cancer-specific DNA methylation markers without prior knowledge of their PRC2 occupancy status. P-values of genes that demonstrate significant higher DNA methylation levels (Mann Whitney U test) in cancer compared to normal ovaries are shaded and referred as to “cancer genes”. Applicants defined “Stem cell genes” as genes which are occupied with at least two of the three components (SUZ12, EED and H3K27me3) in human embryonic stem cells. Nine genes demonstrated higher frequencies of densely methylated alleles (as reflected in the listed values for PMR) in cancer tissues compared to normal ovaries. 56% ( 5/9) of these “cancer genes” were “stem cell genes”, whereas only 15% ( 4/26) of the “non-cancer genes” were “stem cell genes” (P=0.03). In addition, genes that are methylated in normal tissue are much more likely to show a quantitative increase in DNA methylation frequency in cancer (P=0.002) as opposed to genes that are not detectably methylated in normal tissues.
Table 3 lists DNA methylation values (PMR) of 61 genes (with known PRC2 component occupancy status in human embryonic stem cells) analyzed in 15 non-neoplastic breast and 15 breast cancers. P-values of genes that demonstrate significant higher DNA methylation levels (Mann Whitney U test) in cancer compared to non-neoplastic breast are shaded and referred as to “cancer genes”. Applicants defined “Stem cell genes” as genes which are occupied with at least two of the three components (SUZ12, EED and H3K27me3) in human embryonic stem cells. Eighteen genes demonstrated higher frequencies of densely methylated alleles in breast cancer tissues compared to non-neoplastic breast. 56% ( 10/18) of these “cancer genes” were “stem cell genes”, whereas only 23% ( 10/43) of the “non-cancer were “stem cell genes” (P=0.02).
Table 4 lists DNA methylation values (PMR) of 35 genes (with known PRC2 component occupancy status in human embryonic stem cells) analyzed in CD34 positive hematopoietic progenitor cells from nine patients. Applicants defined “Stem cell genes” as genes which are occupied with at least two of the three components (SUZ12, EED and H3K27me3) in human embryonic stem cells. Stem-cell repressed genes, containing at least two of the PRC2 marks demonstrated detectable DNA methylation in CD34-positive cells in twice the number of subjects compared to genes lacking these marks (Mean: 6.1 vs 3.2, respectively, P=0.02). Cancer genes (as identified in ovarian cancer; Table 2) are much more likely to be methylated in CD34 pos. cells (P=0.001).
Table 5 lists exemplary MethyLight™ primers and probes used in the analyses disclosed herein.
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Particular examples and embodiments disclosed herein provide an efficient way to identify/enrich for candidate cancer-specific DNA methylation markers, based on ES-cell PRC2 targets, and in certain aspects, based on a subset of ES-cell PRC2 targets that also bind at least one of the transcription factors: OCT4, SOX2, Nanog.
In additional embodiments of the present invention, various stem or precursor cells are used to identify transcriptional repressor (e.g., transcription factor) occupancy sites (e.g., by chromatin immunoprecipitation chip analysis) and status for not only PRC2, but also for other repressors and repressor complexes as well (e.g., at least one transcription factor of the Dlx, Irx, Lhx and Pax gene families (neurogenesis, hematopoiesis and axial patterning), or the Fox, Sox, Gata and Tbx families (developmental processes)), and these ChIP-Chip targets as then used as a means of enrichment for cancer-specific DNA methylation markers as taught herein using the exemplary combination of embryonic stems cells and PRC2 targets.
According to further aspects, therefore, the instant approach has substantial utility for various types of stem and precursor cells (ES cell, somatic stem cells, hematopoietic stem cells, leukemic stem cells, skin stem cells, intestinal stem cells, gonadal stem cells, brain stem cells, muscle stem cells (muscle myoblasts, etc.), mammary stem cells, neural stem cells (e.g., cerebellar granule neuron progenitors, etc.), etc) and for various stem- or precursor cell repressor complexes as discussed above, and for various types of cancer (e.g., as discussed herein above and further including basal carcinoma, pancreatic adenocarcinoma, small cell lung cancer and metastatic prostate cancer), where the requirements are that the repressor occupancy sites/loci and corresponding occupancy status are defined/established, and a characteristic methylation status (e.g., hypermethylation) is established at corresponding sites/loci in one or more cellular proliferative disorders or cancers of interest, or, in particular embodiments, in cells of a developmental stage of interest.
Particular embodiments provide a method for identifying, screening, selecting or enriching for preferred DNA methylation markers for a cellular proliferative disorder and/or cancer, comprising: identifying, within a precursor cell population, one or a plurality of genomic target loci for at least one polycomb group protein (PcG) or Polycomb repressive complex; obtaining a sample of genomic DNA from cells of a cellular proliferative disorder and/or cancer; and determining, by analyzing the genomic DNA from the cells of the cellular proliferative disorder and/or cancer using a suitable assay, the DNA methylation status of at least one CpG dinucleotide sequence within at least one region of at least one of the polycomb group protein (PcG) target loci, wherein the presence of said CpG methylation status identifies the at least one region of at least one of the polycomb group protein (PcG) target loci as a preferred DNA methylation marker for the cellular proliferative disorder and/or cancer.
In particular embodiments, identifying one or a plurality of polycomb group protein (PcG) target loci comprises identifying a plurality of said target loci using genomic DNA from stem cells. In certain embodiments, the stem cells consist of, or comprise embryonic stem (ES) cells. In particular preferred embodiments, the CpG methylation status is that of hypermethylation. In particular identifying comprises chromatin immunoprecipitation. In certain aspects, determining the methylation status comprises use of a high-throughput methylation assay. In particular aspects, the at least one region of at least one of the polycomb group protein (PcG) target loci comprises a CpG island or a portion thereof. In certain embodiments, the cellular proliferative disorder and/or cancer is at least one selected from the group consisting of human colorectal cancer, ovarian cancer, breast cancer, and proliferative disorders and/or cancers associated with haematopoietic stem cells.
Particular embodiments provide a method for identifying, screening, selecting or enriching for preferred DNA methylation markers for cells of a particular developmental lineage or stage, comprising: identifying, within a precursor cell population, one or a plurality of genomic target loci for at least one polycomb group protein (PcG) or polycomb repressive complex; obtaining a sample of genomic DNA from cells of a particular developmental lineage or stage; and determining, by analyzing the genomic DNA from the cells of the particular developmental lineage or stage using a suitable assay, the methylation status of at least one CpG dinucleotide sequences within at least one region of at least one of the polycomb group protein (PcG) target loci, wherein the presence of said CpG methylation status identifies the at least one region of at least one of the polycomb group protein (PcG) target loci as a preferred DNA methylation marker for the particular developmental lineage or stage. In particular aspects, identifying one or a plurality of polycomb group protein (PcG) target loci comprises identifying a plurality of said target loci using genomic DNA from stem cell-derived cells of a particular developmental lineage or stage. In certain embodiments, the stem cells comprise embryonic stem (ES) cells. In particular aspects, the CpG methylation status is that of hypermethylation.
The remarkable demonstration herein of a role for stem-cell PRC2 complexes in the genesis of oncogenic epigenetic abnormalities entails that it will be imperative to monitor not only the generalized epigenetic state of human ES cells in culture and upon differentiation, but also to apply highly sensitive screens for oncogenic epigenetic abnormalities in cells derived from human ES cells, intended for introduction into patients receiving stem-cell therapy.
Particular embodiments provide a method for validating and/or monitoring a precursor cell population, comprising: identifying, within a reference precursor cell population, one or a plurality of genomic target loci for at least one polycomb group protein (PcG) or polycomb repressive complex; identifying one or a plurality of said target loci having a characteristic (disorder-specific, cancer-specific, etc.) DNA methylation status (e.g., at one or more CpG dinucleotide sequence positions of said at least one loci) in a cellular proliferative disorder and/or cancer to provide a set of preferred disorder and/or cancer-related diagnostic/prognostic loci; obtaining genomic DNA from a first test therapeutic precursor cell population of interest; and determining, by analyzing the genomic DNA of the first test therapeutic precursor cell population using a suitable assay, the methylation status of at least one CpG dinucleotide sequence position within the at least one region of the at least one of the polycomb group protein (PcG) preferred diagnostic/prognostic loci, wherein the first test therapeutic precursor cell population is validated and/or monitored with respect to the presence or absence of the characteristic methylation status of the one or a plurality of said target loci having a disorder-specific and/or cancer-specific methylation status in the cellular proliferative disorder and/or cancer, or with respect to the presence or absence of cells of the cellular proliferative disorder and/or cancer, or with respect to the presence or absence of cells or cells having a predispostion thereto.
In particular embodiments, identifying one or a plurality of polycomb group protein (PcG) target loci within a reference precursor cell population comprises identifying a plurality of said target loci of genomic DNA of stem cells. In particular aspects, the stem cells consist of, or comprise embryonic stem (ES) cells. In certain embodiments, the CpG methylation status is that of DNA hypermethylation. In other embodiments the status is DNA hypomethylation. In certain aspects, identifying one or a plurality of said target loci having a characteristic (disorder-specific and/or cancer-specific, etc.) DNA methylation status in a cellular proliferative disorder and/or cancer comprises obtaining a sample of genomic DNA from cells of a cellular proliferative disorder and/or cancer, and determining, by analyzing the genomic DNA using a suitable assay, the methylation status of at least one CpG dinucleotide sequence within the at least one region of the at least one of the polycomb group protein (PcG) target locus. Preferably, determining the methylation status comprises use of a high-throughput DNA methylation assay. In particular embodiments, the at least one region of at least one of the polycomb group protein (PcG) target loci comprises a CpG island or a portion thereof. In certain aspects, the cellular proliferative disorder and/or cancer is at least one selected from the group consisting of human colorectal cancer, ovarian cancer, breast cancer, and cellular proliferative disorders and/or cancers associated with hematopoietic stem cells.
In particular embodiments, the methods further comprise: obtaining genomic DNA from a second test precursor cell population; applying the method steps to said second stem cell population; and comparing the methylation status of the first and second test precursor cell populations to provide for distinguishing or selecting a preferred precursor cell population. In certain aspects, the first and second test precursor cell populations consist of, or comprise stem cells, cultured stem cells, or cells derived from stem cells or cultured stem cells. In certain embodiments, the stem cells consist of, or comprise embryonic stem (ES) cells. In certain aspects, the CpG methylation status of the first and second test precursor cell populations is that of hypermethylation.
In certain embodiments, validating and/or monitoring is of the precursor cell population in culture, subjected to one or more differentiation protocols, or in storage, etc. In particular aspects, the precursor cell population consists of, or comprises stem cells. In certain embodiments, validating and/or monitoring (e.g., validation monitoring) is of the precursor cell population during or after differentiation of the precursor cell population. In certain aspects, the precursor cell population consists of, or comprises stem cells. In certain aspects, validating and/or monitoring comprises validating and/or monitoring during culture or differentiation of the stem cells population for a presence or absence of rogue cells of the cellular proliferative disorder and/or cancer, or of cells having a predisposition thereto, or for cells of a particular developmental lineage of stage.
Further aspects provide a method for validating and/or monitoring a precursor cell population, comprising: identifying, within a reference precursor cell population, one or a plurality of genomic target loci for at least one polycomb group protein (PcG) or polycomb repressive complex; identifying one or a plurality of said target loci having a characteristic (lineage-specific and/or stage-specific) DNA methylation status of at least one CpG dinucleotide sequence position within at least one region of the at least one of the polycomb group protein (PcG) target loci in a cell of a particular developmental lineage or stage, and wherein the one or the plurality of said target loci also has a cellular proliferative disorder-specific and/or cancer-specific methylation status, to provide a set of preferred diagnostic/prognostic loci for the lineage and/or stage; obtaining genomic DNA from a first test cell population of interest; and determining, by analyzing the genomic DNA of the first test cell population using a suitable assay, the DNA methylation status of the at least one CpG dinucleotide sequence within the at least one region of the at least one of the polycomb group protein (PcG) preferred diagnostic/prognostic loci, wherein the first test cell population is validated and/or monitored with respect to the presence or absence of the characteristic methylation status of the one or a plurality of said target loci having a lineage-specific and/or stage-specific methylation status of cells of a particular developmental lineage or stage or with respect to the presence or absence of cells of the particular developmental lineage or stage, or with respect to the presence or absence of cells or cells having a developmental predispostion thereto.
ES Cell maintenance and differentiation. Human ES cell lines are, for example, maintained according to the specific directions for each cell line.
For example, WA09 (H9) are cultured on MEFs in 80% DMEM/F12, 20% KSR, 1 mM L-glutamine, 1×NEAA, 4 ng/ml FGF-2. The cells are passaged by treatment with collagenase IV, 5-7 minutes at 37° C., and scraping to remove colonies, washed 1× in DMEM/F12 and plated on inactivated MEF feeder layer in 60 mm plates or 6-well plates every 5-7 days.
ES02 (HES-2) are, for example, cultured on MEFs in 80% DMEM, 20% FBS, 2 mM L glutamine, 1×NEAA, 50/50 Pen/Strep, 1×ITS, 0.1 mM 2-ME. The cells are cultured in 1 ml organ culture dishes, by carefully cutting undifferentiated pieces from hESC colonies placing them onto inactivated MEFs every 5-7 days. HUES cell lines will be cultured on MEFs in 80% KO-DMEM, 10% Plasmanate (Talecris Biotherapeutics, Inc. formerly Bayer Corporation), 10% KSR, 2 mM L-glutamine, 1×NEAA, 0.1 mM 2-ME, 10 ng/ml FGF-2. The cells are passaged by short treatment with 0.05% trypsin/EDTA and retitration every 4-5 days. The DNA methylation assays are species-specific, so the use of mouse embryonic fibroblasts will not interfere with the epigenetic analysis.
All cells are, for example, monitored daily for morphology and medium exchange. Additional analysis and validation is optionally performed for stem cell markers on a routine basis, including Alkaline Phosphatase every 5 passages, OCT4, NANOG, TRA-160, TRA-181, SEAA-4, CD30 and Karyotype by G-banding every 10-15 passages.
In additional aspects, culture conditions and differentiation protocols are analyzed for their tendency to predispose ES cells to the acquisition of aberrant epigenetic alterations. For example, undirected differentiation by maintenance in suboptimal culture conditions, such as the cultivation to high density for four to seven weeks without replacement of a feeder layer is analyzed as an exemplary condition having such a tendency. For this or other culture conditions and/or protocols, DNA samples are, for example, taken at regular intervals from parallel differentiation cultures to investigate progression of abnormal epigenetic alterations. Likewise, directed differentiation protocols, such as differentiation to neural lineages32,33 can be analyzed for their tendency to predispose ES cells to the acquisition of aberrant epigenetic alterations. pancreatic lineages (Segev et al., J. Stem Cells 22:265-274, 2004; and Xu, X. et al. Cloning Stem Cells 8:96-107, 2006, incorporated by reference herein) and/or cardiomyocytes (Yoon, B. S. et al. Differentiation 74:149-159, 2006; and Beqqali et al., Stem Cells 24:1956-1967, 2006, incorporated by reference herein).
Profiling technologies. A large number of different epigenetic profiling technologies have been developed (e.g., Laird, P. W. Hum Mol Genet 14, R65-R76, 2005; Laird, P. W. Nat Rev Cancer 3, 253-66, 2003; Squazzo, S. L. et al. Genome Res 16, 890-900, 2006; and Lieb, J. D. et al. Cytogenet Genome Res 114, 1-15, 2006, all incorporated by reference herein). These can be divided broadly into chromatin interrogation techniques, which rely primarily on chromatin immunoprecipitation with antibodies directed against specific chromatin components or histone modifications, and DNA methylation analysis techniques. Chromatin immunoprecipitation can be combined with hybridization to high-density genome tiling microarrays (ChIP-Chip) to obtain comprehensive genomic data. However, chromatin immunoprecipitation is not able to detect epigenetic abnormalities in a small percentage of cells, whereas DNA methylation analysis has been successfully applied to the highly sensitive detection of tumor-derived free DNA in the bloodstream of cancer patients (Laird, P. W. Nat Rev Cancer 3, 253-66, 2003). Prefereably, a sensitive, accurate, fluorescence-based methylation-specific PCR assay (e.g., MethyLight™) is used, which can detect abnormally methylated molecules in a 10.000-fold excess of unmethylated molecules (Eads, C. A. et al., Nucleic Acids Res 28, E32, 2000), or an even more sensitive variation of MethyLight™ that allows detection of a single abnormally methylated DNA molecule in a very large volume or excess of unmethylated molecules. In particular aspects, MethyLight™ analyses are performed as previously described by the present applicants (e.g., Weisenberger, D. J. et al. Nat Genet 38:787-793, 2006; Weisenberger et al., Nucleic Acids Res 33:6823-6836, 2005; Siegmund et al., Bioinformatics 25, 25, 2004; Eads et al., Nucleic Acids Res 28, E32, 2000; Virmani et al., Cancer Epidemiol Biomarkers Prey 11:291-297, 2002; Uhlmann et al., Int J Cancer 106:52-9, 2003; Ehrlich et al., Oncogene 25:2636-2645, 2006; Eads et al., Cancer Res 61:3410-3418, 2001; Ehrlich et al., Oncogene 21; 6694-6702, 2002; Marjoram et al., BMC Bioinformatics 7, 361, 2006; Eads et al., Cancer Res 60:5021-5026, 2000; Marchevsky et al., J Mol Diagn 6:28-36, 2004; Sarter et al., Hum Genet 117:402-403, 2005; Trinh et al., Methods 25:456-462, 2001; Ogino et al., Gut 55:1000-1006, 2006; Ogino et al., J Mol Diagn 8:209-217, 2006, and Woodson, K. et al. Cancer Epidemiol Biomarkers Prey 14:1219-1223, 2005).
High-throughput Illumina platforms, for example, can be used to screen PRC2 targets (or other targets) for aberrant DNA methylation in a large collection of human ES cell DNA samples (or other derivative and/or precursor cell populations), and then MethyLight™ and MethyLight™ variations can be used to sensitively detect abnormal DNA methylation at a limited number of loci (e.g., in a particular number of cell lines during cell culture and differentiation).
Illumina DNA Methylation Profiling. Illumina, Inc. (San Diego) has recently developed a flexible DNA methylation analysis technology based on their GoldenGate™ platform, which can interrogate 1,536 different loci for 96 different samples on a single plate (Bibikova, M. et al. Genome Res 16:383-393, 2006). Recently, Illumina reported that this platform can be used to identify unique epigenetic signatures in human embryonic stem cells (Bibikova, M. et al. Genome Res 16:1075-83, 200)). Therefore, Illumina analysis platforms are preferably used. High-throughput Illumina platforms, for example, can be used to screen PRC2 targets (or other targets) for aberrant DNA methylation in a large collection of human ES cell DNA samples (or other derivative and/or precursor cell populations), and then MethyLight™ and MethyLight™ variations can be used to sensitively detect abnormal DNA methylation at a limited number of loci (e.g., in a particular number of cell lines during cell culture and differentiation).
Cluster analysis and selection of markers. There is extensive experience in the analysis and clustering of DNA methylation data, and in DNA methylation marker selection that can be preferably used (e.g., Weisenberger, D. J. et al. Nat Genet 38:787-793, 2006; Siegmund et al., Bioinformatics 25, 25, 2004; Virmani et al. Cancer Epidemiol Biomarkers Prey 11:291-297, 2002; Marjoram et al., Bioinformatics 7, 361, 2006); Siegmund et al., Cancer Epidemiol Biomarkers Prey 15:567-572, 2006); and Siegmun & Laird, Methods 27:170-178, 2002, all incorporated herein by reference). For example, stepwise strategies (e.g., Weisenberger et al., Nat Genet 38:787-793, 2006, incorporated herein) are used as taught by the methods exemplified herein to provide DNA methylation markers that are targets for oncogenic epigenetic silencing in ES cells.
Particular embodiments provide methods for providing a validated cell population (e.g., precursor cell population) for therapeutic administration, comprising, prior to therapeutically administering a cell population, screening or monitoring the cell population using methods as described herein to validate the cells to be administered with respect to the presence or absence of cells of a cellular proliferative disorder and/or cancer (e.g., rogue cancer cells) or cells having a developmental predisposition thereto, or the presence or absence of cells of a particular development lineage or stage, or to validate that cells population to be delivered as being of a particular development lineage or stage, to provide for a validated precursor cell population.
For example, cell populations for therapeutic administration may be stem cells, or early progenitor cells, or typically may be cell populations derived from stem cells or from early progenitor cells. In particular embodiments, it is desired to know that the cell population to be administered is free of cancer cells, or cells having a predisposition to become cancer cells. In other embodiments, it is desired to know that the cell population to be administered is free of cells of a particular type, developmental lineage or stage, or cells having a predisposition to become cells of a particular type, developmental lineage or stage. In further embodiments, it is desired to know that the cell population to be administered is of cells of a particular type, developmental lineage or stage, or is of cells having a predisposition to become cells of a particular type, developmental lineage or stage. Generally, for purposes of determining the presence or absence of cells of a cellular proliferative disorder and/or cancer (e.g., rogue cancer cells) or cells having a developmental predisposition thereto, or the presence or absence of cells of a particular development lineage or stage, a sensitive DNA methylation assay is preferably used that is suitable to detect a characteristic DNA methylation pattern or status in one or fewer than one abnormal cells among about 1,000 or more normal cells, or among about 5,000 or more normal cells, and preferably that allows the detection of a single abnormally methylated promoter in a background of 10,000 cells without this epigenetic abnormality (e.g., MethyLight™ or suitable variations thereof).
Typically, stem cells (e.g., embryonic stem cells) are strategically differentiated to further developed cell types or lineages that suitable and appropriate for the particular therapeutic administration. Typically, it is such differentiated cell populations that will be screened or monitored or validated using methods of the present invention.
Example Overview. The present applicants have reported that stem cell Polycomb group targets (PGCTs) are up to 12-fold more likely to have cancer-specific promoter DNA hypermethylation than non-targets (see herein, and see also reference 7 below). This observation supports the idea of a stem cell origin of cancer where a reversible gene repression is replaced by an eternal silencing, forcing the cell into a never-ending state of self-renewal and so increasing the possibility for subsequent malignant transformation (7-10). A large number of PCGT genes have not yet been described to play a role in cancer and this could explain why non-tumor suppressor genes are found to be frequently hypermethylated in adult epithelial cancers.
In the present EXAMPLE, the methylation status of 71 genes in ovarian cancer and non-neoplastic ovarian tissues of 22 patients or 18 healthy controls, respectively, was analyzed. The methylation of 35 genes included in this study was recently described with regard to PCGT (7). After ranking the genes according to their strength to discriminate between non-neoplastic and cancer tissue the top ranked genes HOXA10 and HOXA11 both stem cell PCGT genes (7), were shown to be novel and useful discriminators between cancer and non-neoplastic tissue. An independent analysis of a set consisting of 92 ovarian cancer specimens further confirmed the utility of these genes as surrogate markers for cancer stem cells and as prognostic indicators, and demonstrated that HOXA11 DNA methylation is [1] strongly associated with the residual tumor after cytoreductive surgery and [2] a valuable prognostic marker (associated with a poor prognosis; HOXA11 DNA methylation was independently associated with poor outcome [relative risk for death 3.4 (95% CI 1.2-9.9; p=0.03)]). These findings support the view that the technical inability to optimally cytoreduce ovarian cancer is associated with particular molecular alterations in the tumor which per se define a subgroup of patients with poor outcome.
Patients and samples. All patients for this study were treated at the Department of Obstetrics and Gynaecology of the Innsbruck Medical University, Austria between 1989 and 2000 and staged according to the International Federation of Gynaecology and Obstetrics (FIGO) system. Ovarian cancer specimens had been prospectively collected from patients operated for gynaecological cancers in compliance with and approved by the Institutional Review Board. Specimens were brought to our pathologist, and a part of the tissue was pulverized under cooling with liquid nitrogen and stored at −70° C. Clinical, pathological and follow-up data were stored in a database in accordance with hospital privacy rules.
For the gene evaluation (TABLE 5), ovarian cancer specimens were analyzed from 22 patients (age range: 30.1 to 80.9 yrs.; mean: 61.8 yrs.; 7 serous cystadeno, 6 mucinous, 6 endometrioid and 3 clear cell cancers) and apparently normal ovaries from 18 patients (age range: 24.1 to 76.9 yrs.; mean: 61.6 yrs.; 13, 4 and 1 had endometrial and cervical cancer and fibroids, respectively). For HOXA10 and HOXA11 methylation analysis, 92 primary ovarian cancer cases were studied; details are provided in Supplementary TABLE 51 and TABLE 6. 77 patients received platinum-based chemotherapy.
After primary treatment, all patients were followed up at intervals increasing from three months to one year until death or the end of the study. Follow-up information was available for all patients.
DNA isolation and methylation analysis. Genomic DNA from lyophilized, quick-frozen specimens was isolated using the DNeasy™ tissue kit (Qiagen, Hilden, Germany). Sodium bisulfite conversion of genomic DNA and the MethyLight™ assay were performed as previously described, and PMR (Percentage of Methylated Reference) values were determined (11). For methylation analysis, ACTB was used as reference gene. Most of the primers and probes for the MethyLight™ reactions have been published (11-14, incorporated by reference herein; (HOXA10; AC004080. e.g., amplicon position 47850-47933); HOXA11; AC004080. e.g., amplicon position 59150-59249)). Primer and probes for the remaining genes analyzed by MethyLight™ are listed in Supplementary TABLE S2.
Statistical analysis. Differences of PMR values between non-neoplastic and cancer specimens or primary cancer were assessed using the Mann-Whitney U test. For further analysis in the frozen ovarian cancer specimens, applicants used the highest level of HOXA10 and HOXA11 methylation detected in non-neoplastic ovaries as a cut-off level (PMR >12) and dichotomized cases with methylation scores of <12 and >12. Associations of methylation and clinicopathological features were determined using the chi-square contingency test and Spearman rank coefficient. For univariate survival analysis, Kaplan-Meier curves and an univariate proportional Hazard model was used. Multivariate survival analysis was done using a time independent proportional Hazard model adjusted for age, grade, tumor stage and remaining tumor after surgery. All statistical calculations were performed using SPSS, version 10.0.
DNA methylation of 71 different genes in 18 non-neoplastic ovarian specimens and 22 ovarian cancer cases were analyzed and ranked according to their strength to discriminate between non-neoplastic and cancer tissue (TABLE 5). 21 genes (29%) demonstrated differences between cases and controls (p<0.05), whereas 9 genes still remained significant after adjustment for multiple testing (p<0.0007). HOXA10 and HOXA11 methylation showed the most significant differences between cancer and non-cancer specimens.
To further elucidate the role of HOXA10 and HOXA11 methylation and to evaluate the findings of the gene selection set, an independent set consisting of 92 ovarian cancer specimens was analyzed in more detail. HOXA11 demonstrated higher methylation levels in patients >60 years of age, whereas HOXA10 methylation was higher in poorly differentiated cancers (Supplementary TABLE S1). HOXA10 and HOXA11 methylation could be observed already in the normal frozen specimens (highest PMR value was 11.39 and 11.02 for HOXA10 and HOXA11, respectively). In light of applicants' previous data (herein and see reference 7 below), applicants reasoned that methylation of these genes is a marker for stem cells which are unable to differentiate and also resistant to therapy. A PMR of 12 was therefore taken as a cut-off to study whether patients whose tumors have higher methylation levels at these particular loci have a worse outcome compared to patients whose tumor methylation levels are comparable with the normal ovaries. This would indirectly confirm that HOXA10 and/or HOXA11 methylation is a marker for cancer stem cells. 26 (28.3%) and 27 (29.3%) of the cancer cases demonstrated PMR <12 for HOXA10 and HOXA11 methylation, respectively. 45.5% ( 15/33) of the mucinous cancer cases demonstrated low HOXA10 methylation whereas 80.5%, 78.6% and 100% of serous, endometrioid and clear cell cases showed PMR levels >12 (TABLE 6). Interestingly, 38.5% ( 25/65) of ovarian cancer cases with no or <2 cm residual tumor after surgery demonstrated low HOXA11 methylation whereas only 7% ( 2/27) of the tumors with more than 2 cm remaining after surgery had HOXA11 PMR values <12 (TABLE 6).
In an univariate analysis, age, grade, remaining tumor after debulking surgery and HOXA11 methylation were associated with overall survival (TABLE 7A,
In this EXAMPLE, applicants showed aberrant HOXA10 and HOXA11 DNA methylation in ovarian cancer patients. It has been demonstrated that HOX genes, which are known to be the key players in the development of the mullerian duct (15), are dysregulated in endometrial (16) and in ovarian cancer (17). Recently, using a genome-wide CHIP-chip approach, Lee et al. (10) demonstrated that in embryonic stem (ES) cells, genes which encode transcription factors with a role in development (e.g. HOXA family) are targets (and thereby silenced) by the Polycomb group proteins (PcG) SUZ12 and EED and associated with nucleosomes that are trimethylated at histone H3 lysine-27 (H3K27me3) for maintenance of transcriptional suppression in human embryonic stem cells. PcG control is critical for long term gene silencing essential for development and adult cell renewal. The observation that HOXA10 and HOXA11 are epigenetically silenced in embryonic stem cells in conjunction with our observation that both genes are already methylated at a low level in normal ovarian tissue and increasingly methylated in ovarian cancers, indicated to applicants that HOXA10 and HOXA11 methylation acts as a tag for ovarian cancer's cell of origin and as a marker for cancer stem cells.
aMann-Whitney U test
aCut-off for ovarian cancers (PMR >12<) has been chosen due to the fact that the highest PMR in normal ovaries was <12
bFisher exact test
cPearson Chi Quadrat test
aMann-Whitney U test
bKruskal Wallis test
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HOXA11 is a factor which is of paramount importance in Mullerian Duct biology (15) and is known to be occupied and thereby suppressed by PRC2 in human embryonic stem cells. The interesting finding that 93% of the tumors with more than 2 cm residual after surgery had HOXA11 PMR values >12 shows that HOXA11 may act also as a marker for the tumor distribution. This would support the view that the technical ability to cytoreduce the cancer simply identifies a biologically more favourable patient subgroup (18). Maurie Markman recently speculated that the multiple factors (both currently defined and still unknown) that likely determine the manner in which a cancer progresses throughout the peritoneal cavity and that might substantially influence a surgeon's ability to remove the majority of visible tumor may also define such critically important features as the presence of de novo, or development of acquired, cytotoxic drug resistance (18). In particular aspects of the present invention, therefore, HOXA11 provides a surrogate marker for cancer stem cells, and its methylation is a factor which determines cancer progression.
In the present EXAMPLE, applicants identified a steady increase of HOXA11 DNA methylation frequency from normal ovaries towards primary ovarian cancer—in particular those with suboptimal debulking surgery—as well as an independent association between high frequency of HOXA11 methylation and poor overall survival in ovarian cancer patients. Future research will need to elucidate whether epigenetic aberration of other HOX genes are also involved in ovarian carcinogenesis.
Example Overview. Applicants have reported that stem cell Polycomb group targets (PGCTs) are up to 12-fold more likely to have cancer-specific promoter DNA hypermethylation than non-targets (see herein and see also reference 4 below). This supports the idea of a stem cell origin of cancer whereby reversible gene repression is replaced by permanent silencing, forcing the cell into a perpetual state of self-renewal and so increasing the possibility for subsequent malignant transformation (4). A large number of PCGT genes have not yet been described to play a role in cancer and this could explain why non-tumor suppressor genes are found to be frequently hypermethylated in adult epithelial cancers. Applicants have analyzed the methylation status of 61 genes in breast cancer and non-neoplastic breast tissues of 15 patients and 15 healthy controls, respectively. NEUROD1 DNA methylation was the best discriminator between these different groups (4). In this EXAMPLE we focused on the role of NEUROD1 methylation in breast cancer biology, and analyzed tumor samples, pre-treatment core biopsies and pre- and post-therapeutic serum samples by means of MethyLight™, a sensitive fluorescence-based real-time PCR technique (5).
In this EXAMPLE, applicants used MethyLight™ and analyzed NEUROD1 methylation in [1] 74 breast cancer tissue samples, [2] two independent sets of pre-treatment core biopsies of 23 (training set) and 21 (test set) neoadjuvantly treated breast cancer patients and [3] pre- and post-therapeutic serum samples from 107 breast cancer patients treated with adjuvant chemotherapy. High grade tumors demonstrated higher NEUROD1 methylation levels. Estrogen receptor (ER) negative breast cancers with high NEUROD1 methylation were 10.8 fold more likely to respond with a complete pathological response following neoadjuvant chemotherapy. Patients with positive serum pretreatment NEUROD1 methylation, which persisted after chemotherapy indicated poor relapse-free and overall survival in uni- and multivariate analysis [relative risk for relapse 6.2 (95% CI 1.6-24; p=0.008), relative risk for death 14 (95% CI 1.6-120; p=0.02)]. Therefore, in particular aspects, NEUROD1 methylation is provided as a chemosensitivity marker in breast cancer (e.g., ER negative breast cancer).
Patients and samples. The following samples have been analyzed:
(1) Frozen breast tissue samples from 74 breast cancer patients. All samples were collected during surgery at the Department of Obstetrics and Gynecology of the Innsbruck Medical University, Austria in compliance with and approved by the Institutional Review Board. Breast cancer specimens were obtained immediately after resection of the breast or lumpectomy. Specimens were brought to our pathologist, and a part of the tissue was pulverized under cooling with liquid nitrogen and stored at −70° C. Patients were 35 to 90 years old (mean age at diagnosis, 62 years). Other clinicopathological features are shown in TABLE 8.
(2) Paraffin embedded pre-treatment core biopsies (formalin fixed 16 gauge cores) from breast cancer patients. Samples were obtained from the Department of Pathology, and Gynecology, General Hospital and Paracelsus University Salzburg (training set samples), the Department of Obstetrics and Gynecology, Medical University Innsbruck, Austria and the Royal Marsden Hospital, London, United Kingdom (test set samples). All samples were collected at diagnosis prior to chemotherapy in compliance with and approved by the Institutional Review Boards. In the training set applicants analyzed samples from 23 patients who received 6 cycles of anthracycline-based therapy. 21/23 samples yielded sufficient amount of DNA. 7/21 patients demonstrated a complete pathological response (CR; disappearance of the invasive cancer in the breast). Clinicopathological features are shown in TABLE 9A. For further evaluation applicants analysed samples from an independent test set from 21 patients. One patient received 3 cycles of a combination of cyclophospamide, methotrexate and 5-fluorouracil, 10 patients received 4 cycles, 9 patients 6 cycles and 1 patient 3 cycles of an anthracycline-based therapy. Clinicopathological features are shown in TABLE 9B.
(3) Pre- and post-therapeutic serum samples from 107 breast cancer patients, treated at the Department of Gynecology and Obstetrics, Medical University Innsbruck, Austria, with primary non-metastatic breast cancer. Serum samples were recruited from all patients diagnosed with breast cancer between September 1992 and February 2002 who met all the following criteria: (a) primary breast cancer without metastasis at diagnosis, (b) adjuvant treatment with chemotherapy (41 patients received an anthracycline-based therapy, 64 patients received a combination of cyclophospamide, methotrexate and 5-fluorouracil and 2 patients received another kind of chemotherapy), (c) availability of serum samples at diagnosis and 1 year after treatment (a time when the patient has completed her chemotherapy) and (d) no relapse after one year. Hormone receptor status was determined by either radioligand binding assay or immunohistochemistry. Clinicopathological features are shown TABLE 10. Patients' blood samples were drawn before or 1 year after therapeutic intervention. Blood was centrifuged at 2,000×g for 10 minutes at room temperature and 1 mL aliquots of serum samples were stored at ±30° C.
DNA Isolation, Bisulfite modification and MethyLight Analysis. Genomic DNA from fresh frozen tissue samples or paraffin embedded tissue sample respectively was isolated using the DNeasy Tissue Kit (Qiagen, Hilden, Germany) according to the manufacturer's protocol. DNA isolation from serum samples, bisulfite modification, and MethyLight analysis was done as described previously (2). Primers and Probe for NEUROD1 (AC013733; e.g., amplicon position 78576-78657) have been described recently (6, incorporated by reference herein).
RNA Isolation and RT-PCR. Total cellular RNA was extracted from the tumor specimens as previously described by the acid guanidium thiocyanate-phenol-chlorophorm method.
Reverse Transcription of RNA was performed as previously described. The following primers were used for COX-2 expression analysis: Forward: 5′-TGCTGCTGTGCGCGG-3′ (SEQ ID NO: 607), Reverse: 5′-GGTTTTGACATGGGTGGGAAC-3′ (SEQ ID NO: 608), Probe: 5′FAM-CCTGGCGCTCAGCCATACAG CAAA-3′TAMRA (SEQ ID NO 609). Primers and probes for the TATA box-binding protein (TBP) were used according to Bieche et al (7).
Real-time PCR was performed using an ABI Prism 7900HT Detection System (Applied Biosystems, Foster City, Calif.) as recently described. The standard curves were generated using serially diluted solutions of standard cDNA derived from the HBL-100 breast carcinoma cell-line.
Statistics. Descriptive analysis of obtained data was performed and median as well as interquartile ranges were given. Data of parametric distributed variables were shown as mean and standard deviation. Differences of PMR (Percentage of Methylated Reference) values between groups were analyzed by means of a two-sided Mann-Whitney-U-test. Survival analysis was done by using univariate Kaplan-Meier curves and Cox Regression Models. All statistical analyses were done applying SPSS Software 10.0.
Based on our recent study, NEUROD1 methylation is the best discriminator between breast cancer and non-neoplastic tissue samples (4; Supplementary TABLE S4). To further explore the role of NEUROD1 methylation in primary breast cancer, in this EXAMPLE, applicants first analyzed NEUROD1 methylation in 74 frozen primary breast cancer specimens. High grade tumors demonstrated higher NEUROD1 methylation levels (p=0.03), whereas no other clinicopathological feature was associated with NEUROD1 methylation (TABLE 8). The promoter of NEUROD1 is occupied by repressive regulators in human embryonic stem cells (8) which would be consistent with NEUROD1 DNA methylation marking cancer stem cells in the tumor. Although there is a highly significant increase in NEUROD1 methylation from non-neoplastic to breast cancer tissue (Supplementary Table S1) with higher levels in high grade tumors (TABLE 8), surprisingly NEUROD1 methylation in breast cancer is not an indicator of tumor aggressiveness which is demonstrated in a lack of association of NEUROD1 methylation and lymphnode metastasis (TABLE 8) or survival (TABLE 11). This rather surprising finding led applicants to the conclusion that NEUROD1 methylation is associated with other tumor features like responsiveness to systemic treatment in breast cancer.
To confirm this aspect, applicants used two in vivo experiments: NEUROD1 methylation analysis in core breast cancer biopsies taken prior to preoperative chemotherapy with complete pathological response as the endpoint (model 1) and seroconversion of NEUROD1 methylation in serum DNA during adjuvant chemotherapy with survival as the endpoint (model 2). For model 1, applicants first analyzed DNA from pretreatment core biopsies from 23 breast cancer patients (training set). 21/23 samples yielded sufficient DNA and 7/21 patients demonstrated a CR (TABLE 9A). Patients with a CR demonstrated significantly higher NEUROD1 methylation levels in their pretreatment cancer cores (
As ER-negative tumors are more likely to respond to neoadjuvant chemotherapy (9-11), applicants analyzed the association of CR and NEUROD1 methylation separately, in ER negative and ER positive tumor samples. Although the numbers are small, the association between NEUROD1 methylation and response to neoadjuvant chemotherapy was retained in ER negative cancers (Mann-Whitney-U-test; p=0.02;
In order to further validate these findings and to calculate the predictive potential of NEUROD1 methylation, applicants analyzed an independent test set of 21 core biopsies taken prior to the start of neoadjuvant chemotherapy from ER negative breast cancer patients (TABLE 9B). NEUROD1 methylation was classified as low (n=11) and high (n=10) using the median PMR value (PMR=2.18) as the cut-off. 8/10 (80%) women with high and 3/11 (27%) women with low NEUROD1 methylation in their core biopsy had a CR. Using a logistic regression model and adjusting for age and HER2 status, high NEUROD1 methylation in ER negative pretreatment breast cancer biopsies was associated with a 10.8-fold increased likelihood for a CR following neoadjuvant chemotherapy (95% CI 1.1-106.4; p=0.042). This means that NEUROD1 methylation had a sensitivity of 80% (44.0, 96.0) and a specificity of 72% (39.0, 92.0) to predict complete pathological response in women treated with neoadjuvant chemotherapy. In applicants' second model, applicants assessed whether serum NEUROD1 methylation is able to predict the response to adjuvant chemotherapy in patients with primary breast cancer. Applicants have previously demonstrated that DNA methylation of specific genes in circulating serum DNA is a marker for poor prognosis (2) and a tool to monitor adjuvant tamoxifen treatment (3). For confirming that NEUROD1 methylation is a marker for chemosensitivity in breast cancer, we would expect that women whose serum NEUROD1 methylation is positive before, but not detectable after adjuvant chemotherapy have an improved relapse-free and overall survival as their chemosensitive tumor cells have been eliminated. 107 patients were identified who received adjuvant chemotherapy due to primary non-metastatic breast cancer and from whom both pretreatment and post-chemotherapy serum samples have been stored. Characteristics of these patients are shown in TABLE 10A. Pretreatment NEUROD1 serum DNA methylation was more prevalent in postmenopausal women, whereas no difference in any of the other clinicopathological features could be observed. In the group of 21 ER negative patients with positive pretreatment NEUROD1 methylation in their serum, persistence of NEUROD1 DNA methylation after chemotherapy indicated poor overall and relapse-free survival in the univariate analysis (
aMann-Whitney U Test
indicates data missing or illegible when filed
Neoadjuvant chemotherapy has been widely used prior to surgery for locally advanced breast cancer (12, 13). Response to this kind of therapy has been shown to be a valid surrogate marker of survival and facilitates breast conserving surgery (14-16). But current clinical and pathological markers poorly predict response to neoadjuvant chemotherapy. In applicants EXAMPLE study, ER negative breast cancers with high NEUROD1 methylation are more likely to respond with a complete pathological response following neoadjuvant chemotherapy.
Predictive factors in adjuvant breast cancer therapy are limited to ER, progesterone receptor, and HER-2/neu. These markers are used to predict response to hormonal treatment and herceptin, respectively (17, 18). Recently HER-2/neu in serum was shown to be a significant predictor of response to neoadjuvant anthracycline-based chemotherapy for breast cancer, whereas the HER-2/neu status of tumor tissue did not correlate with response to treatment (19). Furthermore HER-2/neu overexpression was identified as a major prognostic factor in stage II and III breast cancer patients treated with a neoadjuvant docetaxel and epirubicin combination (20). Despite these findings a more extensive range of predictive markers is highly needed in order to extend the range of individualized therapies for breast cancer patients.
The biological characteristics of circulating tumor cells are poorly understood despite their potential contribution towards the formation of distant metastases. Up until recently, only a limited number of reports examined the occurrence of circulating tumor cells in the context of systemic therapy for primary or metastatic breast cancer. It has been demonstrated that circulating tumor cells are present in a substantial fraction of patients with breast cancer undergoing systemic therapy (21). These circulating tumor cells are usually non-proliferative, and a fraction of these cells seem to be resistant to chemotherapy (21). Only very limited data is available regarding specific characterization of these circulating tumor cells. In our EXAMPLE study applicants described NEUROD1 methylation as a marker for breast cancer cells which are responsive to chemotherapy. Expression of cyclooxygenase-2 (COX-2) has recently been demonstrated to be a marker of doxorubicin-resistant breast cancer (22). In addition, inhibitors of COX-2 increase doxorubicin-induced cytotoxicity (23) and this is at least in part due to COX-2 mediated upregulation of MDR1/P-glycoprotein (MDR1/P-gp) (24, 25), an energy-dependent pump that participates in multidrug resistance. In addition COX-2 derived Prostaglandin E2 protects embryonic stem cells from apoptosis (26). Interestingly, applicants observed a strong inverse correlation of COX-2 expression and NEUROD1 methylation in ER negative breast cancer specimens (correlation coefficient r=−0.4; p=0.03; Supplementary
In particular aspects, this is the first study describing a DNA based marker which is able to predict the response to neoadjuvant as well as adjuvant chemotherapy in a solid tumor independent of gene transcription and the source of DNA analyzed.
This application claims the benefit of priority to U.S. Provisional Patent Application Ser. Nos. 60/877,530, filed 27 Dec. 2006 and entitled “DNA METHYLATION MARKERS BASED ON EPIGENETIC STEM CELL SIGNATURE IN CANCER,” and 60/882,948, filed 31 Dec. 2006 and of same title, both of which are incorporated herein by reference in their entirety.
Particular aspects of this inventive subject matter were supported by National Institutes of Health (NIH) grant R01 CA075090, and the Untied States government may, therefore, have certain rights to these aspects of the invention.
| Filing Document | Filing Date | Country | Kind | 371c Date |
|---|---|---|---|---|
| PCT/US07/88994 | 12/27/2007 | WO | 00 | 1/14/2010 |
| Number | Date | Country | |
|---|---|---|---|
| 60882948 | Dec 2006 | US | |
| 60877530 | Dec 2006 | US |
