WO2006133866A2

WO2006133866A2 - Prognostic markers for prediction of treatment response and/or survival of breast cell proliferative disorder patients

Info

Publication number: WO2006133866A2
Application number: PCT/EP2006/005575
Authority: WO
Inventors: Dimo Dietrich; Ralf Lesche; Inko Nimmrich; Sabine Maier
Original assignee: Epigenomics Ag
Priority date: 2005-06-11
Filing date: 2006-06-09
Publication date: 2006-12-21
Also published as: WO2006133866A3

Abstract

The present invention relates to methods for prognosis and/or predicted outcome of treatment with estrogen treatment of breast cell proliferative disorder patients, in particular breast carcinoma. This is achieved by determining the expression level of PITX2 or the genetic or the epigenetic modifications of the genomic DNA associated with the gene PITX2. The invention also relates to sequences and oligonucleotides which can be used within the described methods.

Description

Prognostic markers for prediction of treatment response and/or survival of breast cell proliferative disorder patients.

The present invention relates to methods for predicting the survival and/or treatment response of a patient diagnosed with a cell proliferative disorder of the breast tissues, characterized in that the expression level of the gene PITX2 or the genetic or the epigenetic modifications of the genomic DNA associated with the gene PITX2 and/or regulatory or promoter regions thereof are determined. The invention also relates to nucleic acid sequences, oligonucleotides and antibodies which can be used in the described methods.

Field of the Invention

BREAST CANCER.

In European and American women breast cancer is the most frequently diagnosed cancer and the second leading cause of cancer death. In women aged 40-55, breast cancer is the leading cause of death (Greenlee et al., 2000). In 2002 there were 204,000 new cases of breast cancer in the US, and a comparable number in Europe.

Breast cancer is defined as the uncontrolled proliferation of cells within breast tissues. Breasts are comprised of 15 to 20 lobes joined together by ducts. Cancer arises most commonly in the duct, but is also found in the lobes with the rarest type of cancer termed inflammatory breast cancer. It will be appreciated by those skilled in the art that there exists a continuing need to improve methods of early detection, classification and treatment of breast cancers. In contrast to the detection of some other common cancers such as cervical and dermal there are inherent difficulties in classifying and detecting breast cancers.

BREAST CANCER TREATMENT.

The first step of any treatment is the assessment of the patient's condition comparative to defined classifications of the disease. However the value of such a system is inherently dependent upon the quality of the classification. Breast cancers are staged according to their size, location and occurrence of metastasis. Methods of treatment include the use of surgery, radiation therapy, chemotherapy and endocrine therapy, which are also used as adjuvant therapies to surgery. In general, more aggressive diseases should be treated with more aggressive therapies.

Although the vast majority of early cancers are operable, i.e. the tumor can be completely removed by surgery, about one third of the patients with lymph-node negative diseases and about 50-60% of patients with node-positive disease will develop metastases during follow- up.

Based on this observation, systemic adjuvant treatment has been introduced for both node- positive and node-negative breast cancers. Systemic adjuvant therapy is administered after surgical removal of the tumor, and has been shown to reduce the risk of recurrence significantly. Several types of adjuvant treatment are available: endocrine treatment, also called hormone treatment (for hormone receptor positive tumors), different chemotherapy regimens, and antibody treatments based on novel agents like Herceptin (an antibody to an epidermal growth factor receptor).

The growth of the majority of breast cancers (app. 70-80%) is dependent on the presence of estrogen. Therefore, one important target for adjuvant therapy is the removal of estrogen (e.g. by ovarian ablation) or the blocking of its synthesis or the blocking of its actions on the tumor cells either by blocking the receptor with competing substances (e.g. Tamoxifen) or by inhibiting the conversion of androgen into estrogen (e.g. aromatase inhibitors). This type of treatment is called "endocrine treatment". Endocrine treatment is thought to be efficient only in tumors that express hormone receptors (the estrogen receptor (ER) and/or the progesterone receptor (PR)). Currently, the vast majority of women with hormone receptor positive breast cancer receive some form of endocrine treatment, independent of their nodal status. The most frequently used drug in this scenario is Tamoxifen.

However, even in hormone receptor positive patients, not all patients benefit from endocrine treatment. Adjuvant endocrine therapy reduces mortality rates by 22% while response rates to endocrine treatment in the metastatic (advanced) setting are 50 to 60%.

Since Tamoxifen has relatively few side effects, treatment may be justified even for patients with low likelihood of benefit. However, these patients may require additional, more aggressive adjuvant treatment. Even in earliest and least aggressive tumors, such as node- negative, hormone receptor positive tumors, about 21 % of patients relapse within 10 years after initial diagnosis if they receive Tamoxifen monotherapy only, as adjuvant treatment (Lancet. 1998 May 16;351 (91 14): 1451-67. Tamoxifen for early breast cancer: an overview of the randomized trials. Early Breast Cancer Trialists' Collaborative Group.). Similarly, some patients with hormone receptor negative disease may be treated sufficiently with surgery and potentially radiotherapy alone, whereas others may require additional chemotherapy.

Several cytotoxic regimens have shown to be effective in reducing the risk of relapse in breast cancer (Mansour et al., 1998). According to current treatment guidelines, most node-positive patients receive adjuvant chemotherapy both in the US and Europe, since the risk of relapse is considerable. Nevertheless, not all patients do relapse, and there is a proportion of patients who would never have relapsed even without chemotherapy, but who nevertheless receive chemotherapy due to the currently used criteria. In hormone receptor positive patients, chemotherapy is usually given before endocrine treatment, whereas hormone receptor negative patients receive only chemotherapy.

The situation for node-negative patients is particularly complex. In the US, cytotoxic chemotherapy is recommended for node-negative patients, if the tumor is larger than 1 cm. In Europe, chemotherapy is considered for the node-negative cases if one or more risk factors such as tumor size larger than 2 cm, negative hormone receptor status, or tumor grading of three or age <35 is present. In general, there is a tendency to select premenopausal women for additional chemotherapy whereas for postmenopausal women, chemotherapy is often omitted. Compared to endocrine treatment, in particular Tamoxifen or aromatase inhibitors, chemotherapy is highly toxic, with short-term side effects such as nausea, vomiting, bone marrow depression, and long-term effects such as cardiotoxicity and an increased risk for secondary cancers.

LONGFELT NEED IN THE ART.

It is currently not clear which breast cancer patients should be selected for more aggressive therapy and which would do well without additional aggressive treatment, and clinicians agree that there is a need for improved selection of patients. The difficulty of selecting the right patients for adjuvant treatment and selecting the right adjuvant treatment, and the lack of suitable criteria is also reflected by a recent study which showed that chemotherapy is used much less frequently than recommended, based on data from the New Mexico Tumor registry (Du et al., 2003). This study provided substantial evidence that there is a need for better selection of patients for chemotherapy or other, more aggressive forms of breast cancer therapy.

PRIOR ART OF THE GENE PITX2

PITX2 (also known as PTX2, RS₅ RGS, ARPl , Brxl , IDG2, IGDS, IHG2, RIEG, IGDS2, IRID2, Otlx2, RIEGl , MGC20144) is known to belong to the PTX subfamily of PTXl , PTX2, and PTX3 genes which define a novel family of transcription factors, within the paired-like class of homeodomain factors. The gene PITX2 (according to NM l 53426) encodes the paired-like homeodomain transcription factor 2, which is known to be expressed during development of anterior structures such as the eye, teeth, and anterior pituitary.

Methylation of PITX2 has been previously associated with responsiveness to endocrine treatment (including Tamoxifen), as disclosed by the present applicant (in the US, "assignee") in PCT/EP03/ 10881. In this patent application, the methylation status of CpG positions within two sequences of the gene PITX2 (from the 3' and 5' regions of the gene respectively) were disclosed as being indicative of treatment response in breast cancer patients. Said document does not disclose two unexpected and highly important characteristics of the gene, namely, that the gene PITX2 has an alternative function as a general prognostic marker, and that the analysis of a wide variety of expression related methodologies (mRNA expression, protein expression, LOH) are suitable alternative analysis techniques to methylation analysis for determining said prognosis. These surprising effects enable the use of the marker PITX2 in a broader context in the treatment of breast cancer patients, by identifying which patients would most benefit from aggressive therapies such as chemotherapy and which patients would be suitable candidates for comparatively less aggressive treatment such as Tamoxifen monotherapy.

The correlation of PITX2 methylation with prognosis was recently disclosed by the applicant and others at the 41st Annual Meeting of the American Society of Clinical Oncology. In a study of 41 1 patients, PITX2 methylation was strongly correlated with outcome (Cox proportional hazard model, p=0.025). In the group with low PITX2 methylation (45% of the cohort), 98% of the patients were metastasis-free after 10 years, compared to only 85% in the group with high PITX2 methylation. In a multivariate model, PITX2 methylation added significant information to conventional factors such as grade and age. In this analysis, a quantitative methylation assay was used to measure the methylation levels of a bisulfite treated amplificate from the promoter region of the gene. This is the same region that was previously investigated with respect to treatment response.

The present invention discloses significant improvements to the state of the art, namely breast cancer prognosis by means of analysis of PITX2 methylation. It is herein disclosed that the combined methylation analysis of two specific regions of the PITX2 gene enable the prognosis of events and/or predicted outcome of treatment with estrogen treatment with a greater accuracy than the analysis of the single region heretofore investigate. Furthermore, this analysis may also be carried out by other alternative expression analysis techniques.

This marker thereby provides improved means for the characterization of breast carcinomas. Aberrant expression of the gene PITX2 is indicative of the relapse and/or survival of a breast carcinoma patient. The herein described invention is thereby particularly useful for making improved treatment decisions.

It is also indicative of the relapse and/or survival of said patients when treated with one or more treatments which target the estrogen receptor, synthesis or conversion pathways or are otherwise involved in estrogen metabolism, production or secretion.

The herein described invention is thereby particularly useful for the differentiation of individuals who may be appropriately treated with one or more treatments which target the estrogen receptor pathway or are involved in estrogen metabolism, production or secretion from those individuals who would be optimally treated with other treatments in addition to or instead of said treatment. Preferred Other treatments' include but are not limited to chemotherapy or radiotherapy.

Accordingly it is particularly preferred that said novel means of analysis of said marker be used in the treatment of breast cancer patients by enabling the classification of patients according to their likely treatment outcome wherein said patients are treated with an adjuvant therapy targeting the endocrine pathways. It is further preferred that patients with a poor treatment outcome are provided with a further adjuvant treatment instead of or in addition to said endocrine therapy, in particular but not limited to chemotherapy. A marker suitable for said purpose shall hereinafter also be referred to as an 'adjuvant marker'

PRIOR ART IN EXPRESSS1ON ANALYSIS

The expression of a gene, or the protein encoded by the gene, can be studied on four different levels. Firstly, protein expression levels can be determined directly, secondly, mRNA transcription levels can be determined, thirdly, epigenetic modifications, such as gene's DNA methylation profile or the gene's histone profile; can be analyzed, as methylation is often correlated with inhibited protein expression, and fourth, the gene itself may be analyzed for genetic modifications such as mutations, deletions, polymorphisms etc. influencing the expression of the gene product.

The levels of observation that have been studied by the methodological developments of recent years in molecular biology, are the genes themselves, the transcription of these genes into RNA, and the translation into the resulting proteins. However how the activation and inhibition of specific genes, in specific cells and tissues, at specific time points in the course of development of an individual are controlled, is correlatable to the degree and character of the methylation of the genes or respectively the genome. In this respect, pathogenic conditions may manifest themselves in a changed methylation pattern of individual genes or of the genome.

The four terms that apply to the fields of overall genome-wide analysis of all these biological processes are called: proteomics, transcriptomics, epigenomics (or methylomics) and genomics. Methods and techniques that can be used for studying expression or studying the modifications responsible for expression on all of these levels are well described in the literature and therefore known to a person skilled in the art. They are described in text books of molecular biology and in a large number of scientific journals.

Methods for the analysis of protein expression of individual genes is known in the art. It usually requires an antibody specific for the gene product of interest. Appropriate technologies would be ELISA or immunohistochemistry.

The analysis of the level of mRNA is also well known in the art, reverse transcriptase PCR being the current method of choice. A more detailed description of the prior art relating to current methodologies provided in the description of the invention.

US patent application 2003/0198970 by Gareth Roberts lists some of the technologies and methods for determining an individual's "genetic make up^", i.e. the genetic modifications, such as deletions, polymorphisms, mutations etc. that may vary between individuals and describes the potential role of this genetic sequence information in the individual's variability in disease, response to therapy and prognosis. Epigenetic differences however are not mentioned. The gene PITX2 is listed within this application as one gene name out of a long and comprehensive list of about 2.500 other gene names, suggesting its expression could play a role in some kind of treatment response. However, this is simply an assumption based on speculation only, as no experiments are disclosed, which demonstrate any kind of relation between genetic modifications of PITX2 and an individual^'s variation in treatment response.

A less established area in this context is the field of epi genomics or epigenetics, i.e. the field concerned with analysis of DNA methylation patterns.

PRIOR ART IN METHYLATION ANALYSIS

5-methylcytosine is the most frequent covalent base modification in the DNA of eukaryotic cells. Methylation of DNA can play an important role in the control of gene expression in mammalian cells. It plays a role, for example, in the regulation of the transcription, in genetic imprinting, and in tumorigenesis. DNA methyltransferases are involved in DNA methylation and catalyze the transfer of a methyl group from S-adenosylmethionine to cytosine residues to form 5-methylcytosine, a modified base that is found mostly at CpG sites in the genome. The presence of methylated CpG islands in the promoter region of genes can suppress their expression. This process may be due to the presence of 5-methylcytosine, which apparently interferes with the binding of transcription factors or other DNA-binding proteins to block transcription. In different types of tumors, aberrant or accidental methylation of CpG islands in the promoter region has been observed for many cancer-related genes, resulting in the silencing of their expression. Such genes include tumor suppressor genes, genes that suppress metastasis and angiogenesis, and genes that repair DNA (Momparler and Bovenzi (2000) J. Cell Physiol. 183:145-54). Therefore, the identification of 5-methylcytosine as a component of genetic information is of considerable interest. However, 5-methylcytosine positions cannot be identified by regular sequencing since 5-methylcytosine has the same base pairing behaviour as cytosine. Moreover, the epigenetic information carried by 5-methylcytosine is completely lost during PCR amplification.

DESCRIPTION

Characterization of a breast cancer in terms of prognosis and/or treatment outcome enables the physician to make an informed decision as to a therapeutic regimen with appropriate risk and benefit trade offs to the patient.

In the context of the present invention the terms "estrogen receptor positive" and/or "progesterone receptor positive" when used to describe a breast cell proliferative disorder are taken to mean that the proliferating cells express said hormone receptor.

In the context of the present invention the term 'aggressiveness' is taken to mean one or more of high likelihood of relapse post surgery; below average or below median patient survival; below average or below median disease free survival; below average or below median relapse- free survival; above average tumor-related complications; fast progression of tumor or metastases. According to the aggressiveness of the disease an appropriate treatment or treatments may be selected from the group consisting of chemotherapy, radiotherapy, surgery, biological therapy, immunotherapy, antibody treatments, treatments involving molecularly targeted drugs, estrogen receptor modulator treatments, estrogen receptor down-regulator treatments, aromatase inhibitors treatments, ovarian ablation, treatments providing LHRH analogues or other centrally acting drugs influencing estrogen production. Wherein a cancer is characterized as 'aggressive' it is particularly preferred that a treatment such as, but not limited to, chemotherapy is provided in addition to or instead of an endocrine targeting therapy.

Indicators of tumor aggressiveness that are standard in the art include but are not limited to, tumor stage, tumor grade, nodal status and survival.

Unless stated otherwise as used herein the term "survival" shall be taken to include all of the following: survival until mortality, also known as overall survival (wherein said mortality may be either irrespective of cause or breast tumor related); "recurrence- free survival" (wherein the term recurrence shall include both localized and distant recurrence) ; metastasis free survival; disease free survival (wherein the term disease shall include breast cancer and diseases associated therewith). The length of said survival may be calculated by reference to a defined start point (e.g. time of diagnosis or start of treatment) and end point (e.g. death, recurrence or metastasis).

As used herein the term ^"prognostic marker^" shall be taken to mean an indicator of the likelihood of progression of the disease, in particular aggressiveness and metastatic potential of a breast tumor.

As used herein the term 'predictive marker^" shall be taken to mean an indicator of response to therapy, said response is preferably defined according to patient survival. It is preferably used to define patients with high, low and intermediate length of survival or recurrence after treatment, that is the result of the inherent heterogeneity of the disease process.

As defined herein the term predictive marker may in some situations fall within the remit of a herein described 'prognostic marker', for example, wherein a prognostic marker differentiates between patients with different survival outcomes pursuant to a treatment, said marker is also a predictive marker for said treatment. Therefore, unless otherwise stated the two terms shall not be taken to be mutually exclusive.

As used herein the term 'expression' shall be taken to mean the transcription and translation of a gene, as well as the genetic or the epigenetic modifications of the genomic DNA associated with the marker gene and/or regulatory or promoter regions thereof. Genetic modifications include SNPs, point mutations, deletions, insertions, repeat length, rearrangements and other polymorphisms. The analysis of either the expression levels of protein, or mRNA or the analysis of the patient's individual genetic or epigenetic modification of the marker gene are herein summarized as the analysis of 'expression of the gene.

The level of expression of a gene may be determined by the analysis of any factors associated with or indicative of the level of transcription and translation of a gene including but not limited to methylation analysis, loss of heterozygosity (hereinafter also referred to as LOH), RNA expression levels and protein expression levels. Furthermore the activity of the transcribed gene may be affected by genetic variations such as but not limited to genetic modifications (including but not limited to SNPs, point mutations, deletions, insertions, repeat length, rearrangements and other polymorphisms).

The terms "endocrine therapy" or "endocrine treatment" are meant to comprise any therapy, treatment or treatments targeting the estrogen receptor pathway or estrogen synthesis pathway or estrogen conversion pathway, which is involved in estrogen metabolism, production or secretion. Said treatments include, but are not limited to estrogen receptor modulators, estrogen receptor down-regulators, aromatase inhibitors, ovarian ablation, LHRH analogues and other centrally acting drugs influencing estrogen production.

The term "monotherapy" shall be taken to mean the use of a single drug or other therapy.

In the context of the present invention the term "chemotherapy" is taken to mean the use of pharmaceutical or chemical substances to treat cancer. This definition excludes radiation therapy (treatment with high energy rays or particles), hormone therapy (treatment with hormones or hormone analogues) and surgical treatment.

In the context of the present invention the term "adjuvant treatment" is taken to mean a therapy of a cancer patient immediately following an initial non chemotherapeutical therapy, e.g. surgery. In general, the purpose of an adjuvant therapy is to decrease the risk of recurrence.

In the context of the present invention the term "determining a suitable treatment regimen for the subject" is taken to mean the determination of a treatment regimen (i.e. a single therapy or a combination of different therapies that are used for the prevention and/or treatment of the cancer in the patient) for a patient that is started, modified and/or ended based or essentially based or at least partially based on the results of the analysis according to the present invention. One example is starting an adjuvant endocrine therapy after surgery, another would be to modify the dosage of a particular chemotherapy. The determination can, in addition to the results of the analysis according to the present invention, be based on personal characteristics of the subject to be treated. In most cases, the actual determination of the suitable treatment regimen for the subject will be performed by the attending physician or doctor.

In the context of this invention the terms ^"obtaining a biological sample^"' or ^"'obtaining a sample from a subject^", shall not be taken to include the active retrieval of a sample from an individual, e.g. the performance of a biopsy. Said terms shall be taken to mean the obtainment of a sample previously isolated from an individual. Said samples may be isolated by any means standard in the art, including but not limited to biopsy, surgical removal, body fluids isolated by means of aspiration. Furthermore said samples may be provided by third parties including but not limited to clinicians, couriers, commercial sample providers and sample collections.

In the context of the present invention, the term "CpG island'^" refers to a contiguous region of genomic DNA that satisfies the criteria of (1) having a frequency of CpG dinucleotides corresponding to an "Observed/Expected Ratio" >0.6, and (2) having a "GC Content" >0.5. CpG islands are typically, but not always, between about 0.2 to about 1 kb in length.

In the context of the present invention the term "regulatory region" of a gene is taken to mean nucleotide sequences which affect the expression of a gene. Said regulatory regions may be located within, proximal or distal to said gene. Said regulatory regions include but are not limited to constitutive promoters, tissue-specific promoters, developmental-specific promoters, inducible promoters and the like. Promoter regulatory elements may also include certain enhancer sequence elements that control transcriptional or translational efficiency of the gene.

In the context of the present invention, the term "methylation" refers to the presence or absence of 5-methylcytosine ("5-mCyt") at one or a plurality of CpG dinucleotides within a DNA sequence.

In the context of the present invention the term "methylation state^"' is taken to mean the degree of methylation present in a nucleic acid of interest, this may be expressed in absolute or relative terms i.e. as a percentage or other numerical value or by comparison to another tissue and therein described as hypermethylated, hypomethylated or as having significantly similar or identical methylation status. In the context of the present invention, the term ^"hemi-methylation^"' or ^"'hemimethylation" refers to the methylation state of a CpG methylation site, where only a single cytosine in one of the two CpG dinucleotide sequences of the double stranded CpG methylation site is methylated (e.g., 5'-NNC^MGNN-3^" (top strand): 3^"-NNGCNN-5' (bottom strand)).

In the context of the present invention, the term ^"hypermethylation" refers to the average methylation state corresponding to an increased presence of 5-mCyt at one or a plurality of CpG dinucleotides within a DNA sequence of a test DNA sample, relative to the amount of 5- mCyt found at corresponding CpG dinucleotides within a normal control DNA sample.

In the context of the present invention, the term "hypomethylation'^" refers to the average methylation state corresponding to a decreased presence of 5-mCyt at one or a plurality of CpG dinucleotides within a DNA sequence of a test DNA sample, relative to the amount of 5- mCyt found at corresponding CpG dinucleotides within a normal control DNA sample.

In the context of the present invention, the term '^"microarray" refers broadly to both "DNA microarrays," and 'DNA chip(s),^' as recognized in the art, encompasses all art-recognized solid supports, and encompasses all methods for affixing nucleic acid molecules thereto or synthesis of nucleic acids thereon.

"Genetic parameters" are mutations and polymorphisms of genes and sequences further required for their regulation. To be designated as genetic modifications or mutations are, in particular, insertions, deletions, point mutations, inversions and polymorphisms and, particularly preferred, SNPs (single nucleotide polymorphisms).

"Epigenetic modifications" or '^"epigenetic parameters" are modifications of DNA bases of genomic DNA and sequences further required for their regulation, in particular, cytosine methylations thereof. Further epigenetic parameters include, for example, the acetylation of histones which, however, cannot be directly analyzed using the described method but which, in turn, correlate with the DNA methylation. In the context of the present invention, the term ^"bisulfite reagent" refers to a reagent comprising bisulfite, disulfite, hydrogen sulfite or combinations thereof, useful as disclosed herein to distinguish between methylated and unmethylated CpG dinucleotide sequences.

In the context of the present invention, the term ^"Methylation assay^"' refers to any assay for determining the methylation state of one or more CpG dinucleotide sequences within a sequence of DNA.

In the context of the present invention, the term "MS.AP-PCR^"' (Methylation-Sensitive Arbitrarily-Primed Polymerase Chain Reaction) refers to the art-recognized technology that allows for a global scan of the genome using CG-rich primers to focus on the regions most likely to contain CpG dinucleotides, and described by Gonzalgo et al., Cancer Research 57:594-599, 1997.

In the context of the present invention, the term '^"MethyLight" refers to the art-recognized fluorescence-based real-time PCR technique described by Eads et al., Cancer Res. 59:2302- 2306, 1999.

In the context of the present invention, the term ^"ΗeavyMethyl™" assay, in the embodiment thereof implemented herein, refers to a methylation assay comprising methylation specific blocking probes covering CpG positions between the amplification primers.

The term "Ms-SNuPE" (Methyl ation-sensitive Single Nucleotide Primer Extension) refers to the art-recognized assay described by Gonzalgo and Jones, Nucleic Acids Res. 25:2529-2531, 1997.

In the context of the present invention the term ^"'MSP" (Methylation-specific PCR) refers to the art-recognized methylation assay described by Herman et al. Proc. Natl. Acad. Sci. USA 93:9821-9826, 1996, and by US Patent No. 5,786,146.

In the context of the present invention the term "COBRA" (Combined Bisulfite Restriction Analysis) refers to the art-recognized methylation assay described by Xiong and Laird, Nucleic Acids Res. 25:2532-2534, 1997. In the context of the present invention the term ^"hybridization^" is to be understood as a bond of an oligonucleotide to a complementary sequence along the lines of the Watson-Crick base pairings in the sample DNA, forming a duplex structure.

"Stringent hybridization conditions," as defined herein, involve hybridizing at 68°C in 5x SSC/5x Denhardt's solution/1.0% SDS, and washing in 0.2x SSC/0.1 % SDS at room temperature, or involve the art-recognized equivalent thereof (e.g., conditions in which a hybridization is carried out at 60°C in 2.5 x SSC buffer, followed by several washing steps at 37°C in a low buffer concentration, and remains stable). Moderately stringent conditions, as defined herein, involve including washing in 3x SSC at 42⁰C, or the art-recognized equivalent thereof. The parameters of salt concentration and temperature can be varied to achieve the optimal level of identity between the probe and the target nucleic acid. Guidance regarding such conditions is available in the art, for example, by Sambrook et al., 1989, Molecular Cloning, A Laboratory Manual, Cold Spring Harbor Press, N. Y.; and Ausubel et al. (eds.), 1995, Current Protocols in Molecular Biology, (John Wiley and Sons, N.Y.) at Unit 2.10.

"Background DNA" as used herein refers to any nucleic acids which originate from sources other than breast cells.

Ina first aspect thereof, the present invention provides a method for providing a prognosis and/or predicting the outcome of endocrine treatment of a subject with a cell proliferative disorder of the breast tissue comprising the steps of a) obtaining a biological sample from the subject, b) determining the expression of at least two promoter/regulatory regions and/or transcripts of the gene PITX2 within said sample, and c) determining therefrom the prognosis and/or outcome of endocrine treatment of said subject.

Using the methods and nucleic acids described herein, statistically significant models of patient relapse, disease free survival, metastasis free survival, overall survival and/or disease progression can be developed and utilized in order to assist patients and clinicians in determining suitable treatment options to be included in the therapeutic regimen.

In another aspect the method according to the invention provides a prognostic marker for a cell proliferative disorder of the breast tissues. Preferably this prognosis is provided in terms of an outcome selected from the group consisting of likelihood of relapse; overall patient survival; metastasis free survival; disease free survival or disease progression.

In a further aspect of the invention said marker is used as a predictive marker of outcome of a treatment which targets the estrogen receptor pathway or is involved in estrogen metabolism, production or secretion as a therapy for patients suffering from a cell proliferative disorder of the breast tissues. This aspect of the method enables the physician to determine which treatments may be used in addition to or instead of said endocrine treatment. It is preferred that said additional treatment is a more aggressive therapy such as, but not limited to, chemotherapy. Thus, the present invention will be seen to reduce the problems associated with present breast cell proliferative disorder prognostic, predictive and treatment response prediction methods.

Using the methods and nucleic acids as described herein, patient survival can be evaluated before or during treatment for a cell proliferative disorder of the breast tissues, in order to provide critical information to the patient and clinician as to the likely progression of the disease. It will be appreciated, therefore, that the methods and nucleic acids exemplified herein can serve to improve a patient's quality of life and odds of treatment success by allowing both patient and clinician a more accurate assessment of the patient's treatment options. Preferred is a method according to the invention that further comprises the step of d) determining a suitable treatment regimen for the subject.

The herein disclosed method may be used for the improved treatment of all breast cell proliferative disorder patients, both pre- and post- menopausal and independent of their node or estrogen receptor status. However, it is particularly preferred that said patients are node- negative and estrogen receptor positive. Most preferred is a method according to the invention, wherein said subject or patient to be diagnosed is estrogen receptor positive.

The present invention makes available a method for the improved treatment of breast cell proliferative disorders, by enabling the improved prediction of a patient's survival, in particular by predicting the likelihood of relapse post-surgery both with or without adjuvant endocrine treatment. Furthermore, the present invention provides a means for the improved prediction of treatment outcome with endocrine therapy, wherein said therapy comprises one or more treatments which target the estrogen receptor pathway or are involved in estrogen metabolism, production, or secretion. Preferred suitable treatment suitable treatment regimen comprise one or more therapies selected from the group consisting of chemotherapy, radiotherapy, surgery, biological therapy, immunotherapy, antibodies, molecularly targeted drugs, estrogen receptor modulators, estrogen receptor down-regulators, aromatase inhibitors, ovarian ablation, LHRH analogues and other centrally acting drugs influencing estrogen production.

The method according to the invention may be used for the analysis of a wide variety of cell proliferative disorders of the breast tissues including, but not limited to, ductal carcinoma in situ, invasive ductal carcinoma, invasive lobular carcinoma, lobular carcinoma in situ, comedocarcinoma, inflammatory carcinoma, mucinous carcinoma, scirrhous carcinoma, colloid carcinoma, tubular carcinoma, medullary carcinoma, metaplastic carcinoma, and papillary carcinoma and papillary carcinoma in situ, undifferentiated or anaplastic carcinoma and Paget' s disease of the breast.

The method according to the invention may be used to provide a prognosis of breast cell proliferative disorder patients, furthermore said method may be used to provide a prediction of patient survival and/or relapse following treatment by endocrine therapy.

Wherein the herein disclosed markers, methods and nucleic acids are used as prognostic markers it is particularly preferred that said prognosis is defined in terms of patient survival and/or relapse. In this embodiment patients survival times and/or relapse are predicted according to their gene expression or genetic or epigenetic modifications thereof. In this aspect of the invention it is particularly preferred that said patients are tested prior to receiving any adjuvant endocrine treatment.

Wherein the herein disclosed markers, methods and nucleic acids are used as predictive markers it is particularly preferred that the method is applied to predict the outcome of patients who receive endocrine treatment as secondary treatment to an initial non chemotherapeutical therapy, e.g. surgery (hereinafter referred to as the 'adjuvant setting') as illustrated in Figure 1. Such a treatment is often prescribed to patients suffering from Stage 1 to 3 breast carcinomas. It is also preferred that said 'outcome' is defined in terms of patients survival and/or relapse. In this embodiment patients survival times and/or relapse are predicted according to their gene expression or genetic or epigenetic modifications thereof. By detecting patients with below average or below median metastasis free survival or disease free survival times and/or high likelihood of relapse the physician may choose to recommend the patient for further treatment, instead of or in addition to the endocrine targeting therapy(s), in particular but not limited to, chemotherapy.

The herein described invention provides a novel breast cell proliferative disorder prognostic and predictive biomarker.

It is herein described that aberrant expression of the gene PITX2 and/or regulatory or promoter regions thereof is correlated to prognosis and/or prediction of outcome of estrogen treatment of breast cell proliferative disorder patients, in particular breast carcinoma. This marker thereby provides a means for the characterization of breast cell proliferative disorders.

As described herein the determination of the expression of at least two promoter regions and/or transcripts of the gene PITX2 according to the invention enables the prediction of prognosis of a patient with a proliferative disorder of the breast tissues with a greater accuracy than was heretofore disclosed. In an alternative embodiment the expression of at least two promoter/regulatory regions and/or transcripts of the gene PITX2 enables the prediction of treatment response of a patient treated with one or more treatments which target the estrogen receptor, synthesis or conversion pathways or are otherwise involved in estrogen metabolism, production or secretion. Preferably, the expression is determined by analysis of at least one of mRNA expression, LOH, and/or protein expression according to standard methods as described herein. More preferred, mRNA expression is determined by analysis of the absence or presence of at least two different transcripts of the gene PITX2 or parts thereof. Most preferred is a method according to the present invention, wherein said expression is determined by determining the methylation state of one or more CpG positions of at least two sequences of the gene PITX2 and/or regulatory regions thereof as described herein.

In one preferred aspect thereof, it was found for the method according to the present invention, that the absence of at least one transcript of the gene PITX2 or parts thereof is indicative of a good prognosis. In another preferred aspect thereof, it was found for the method according to the present invention that the absence of all transcripts of the gene PITX2 or parts thereof is indicative of a bad prognosis. Nevertheless, these preferred examples reflect results of specific transcripts that have been compared (i.e. only a subselection of all possible transcripts has been analyzed), and therefore the correlations between the (physical) presence and/or absence of other transcripts and the outcome might be different, depending from the choice of the particular transcripts to be analyzed. Despite this, still it was surprisingly found that the determination of the expression of at least two promoter regions and/or transcripts of the gene PITX2 according to the invention enables the prediction of prognosis or the prediction of treatment response of a patient with a proliferative disorder of the breast tissues with a greater accuracy than was heretofore possible.

In one further preferred aspect thereof, it was found for the method according to the present invention, that hypermethylation in both of said two sequences within two different promoters and/or regulatory regions of PITX2 is indicative of a bad prognosis, whereas hypomethylation in at least one of said two sequences within two different promoters and/or regulatory regions of PITX2 is indicative of a good prognosis. More preferred, said sequences are selected from SEQ ID NO: 159 and SEQ ID NO: 160 or said sequences are selected from SEQ ID NO: 161 and SEQ ID NO: 162.

It was furthermore found in the context of the present invention that hypermethylation of PITX2, CDK6, ONECUT2, PLAU and/or sequences thereof as disclosed herein is associated with poor prognosis and/or outcome of endocrine treatment of breast cell proliferative disorders, most preferably breast carcinoma. Hypomethylation of the genes TFFl and ERBB2 and/or sequences thereof are associated with poor prognosis and/or outcome of endocrine treatment of breast cell proliferative disorders, most preferably breast carcinoma. Hypomethylation of the gene ABCA8 is correlated to poor disease free survival, however hypermethylation correlates to poor metastasis free survival.

The synergistic effects that result in the surprisingly improved accuracy of the combined analysis of the methylation patterns of both of the herein specified regions of the gene PITX2 (preferably SEQ ID NO: 159 to 162) have heretofore not been known and employed.

A further preferred aspect of the present invention relates to a method for providing a prognosis and/or predicting the outcome of endocrine treatment of a subject with a cell proliferative disorder of the breast tissue comprising the steps of a) isolating genomic DNA from a biological sample taken from said subject; b) treating the genomic DNA, or a fragment thereof, with one or more reagents to convert 5-position unmethylated cytosine bases to uracil or to another base that is detectably dissimilar to cytosine in terms of hybridization properties; c) contacting the treated genomic DNA, or the treated fragment thereof, with an amplification enzyme and at least two pairs of primers, wherein at least one pair of primers comprises in each case a contiguous sequence at least 18 nucleotides in length that is complementary to, or hybridizes under moderately stringent or stringent conditions to a sequence selected from the group consisting of SEQ ID NO: 163-164 and 171 to 172 and complements thereof and wherein at least one pair of primers comprises in each case a contiguous sequence at least 18 nucleotides in length that is complementary to, or hybridizes under moderately stringent or stringent conditions to a sequence selected from the group consisting of SEQ ID NO: 165-166 and 173-174 and complements thereof wherein the treated DNA or a fragment thereof is either amplified to produce one or more amplificates, or is not amplified; d) determining, based on the presence or absence of, or on the quantity or on a property of said amplificate, the methylation state of at least one CpG dinucleotide sequence of SEQ ID NO: 159 and 160, or an average, or a value reflecting an average methylation state of a plurality of CpG dinucleotide sequences of SEQ ID NO: 159 and 160, and e) determining from said methylation state the prognosis and/or outcome of endocrine treatment of said subject.

Preferred is a method according to the present invention which further comprises in step c) at least one primer pair comprising, in each case a contiguous sequence at least 18 nucleotides in length that is complementary to, or hybridizes under moderately stringent or, preferably, stringent conditions to a sequence selected from the group consisting of SEQ ID NO: 76 to 103 and SEQ ID NO: 153, 154, 157, and 158, and complements thereof. Preferably, said one or more reagents comprises a solution selected from the group consisting of bisulfite, hydrogen sulfite, disulfite, and combinations thereof. Still more preferred is a method according to the present invention wherein step d) is carried out by means of one or more methods taken from the group consisting of oligonucleotide hybridization analysis, Ms- SNuPE, sequencing, Real Time detection probes and oligonucleotide array analysis.

A still further preferred aspect of the present invention relates to a method for providing a prognosis and/or predicting the outcome of endocrine treatment of a subject with a cell proliferative disorder of the breast tissue, comprising a) isolating genomic DNA from a biological sample taken from said subject; b) treating the genomic DNA, or a fragment thereof, with one or more reagents to convert 5-position unmethylated cytosine bases to uracil or to another base that is detectably dissimilar to cytosine in terms of hybridization properties; c) contacting the treated genomic DNA, or the treated fragment thereof, with an amplification enzyme and at least two pairs of primers, wherein at least one pair of primers comprises a contiguous sequence at least 18 nucleotides in length that is complementary to, or hybridizes under moderately stringent or stringent conditions to a sequence selected from the group consisting of SEQ ID NO: 163-164 and 171-172 and complements thereof and wherein at least one pair of primers comprises a contiguous sequence at least 18 nucleotides in length that is complementary to, or hybridizes under moderately stringent or stringent conditions to a sequence selected from the group consisting of SEQ ID NO: 165-166 and 173-174 and complements thereof wherein the treated DNA or a fragment thereof is amplified to produce at least two amplificates, d) contacting each of said amplificates, either during or after amplification in step c) with a pair of labelled probes, comprising of a first and a second probe, said first probe being either complementary to, or hybridizing under moderately stringent or stringent conditions to a subsequence of the amplificate and comprising a CG dinucleotide, said second probe being either complementary to, or hybridizing under moderately stringent or stringent conditions to a subsequence of the amplificate comprising a TG dinucleotide; e) determining, based on the signal intensities generated by said labeled probes, the methylation rate of at least one CpG dinucleotide sequence of SEQ ID NO: 159 and 160, or an average, or a value reflecting an average methylation state of a plurality of CpG dinucleotide sequences of SEQ ID NO: 159, and 160, and f) determining from said methylation rate the prognosis and/or outcome of endocrine treatment of said subject.

Preferred is a method according to the present invention, wherein at least one primer pair is selected from the sequences according to SEQ ID NOS: 179 and 180. More preferred is a method according to the present invention, wherein at least one primer pair is selected from oligonucleotides with sequences according to SEQ ID NOS:6 and 7 or SEQ ID NOS:14 and 15; or SEQ ID NOS: 107 and 108; or SEQ ID NOS: 112 and 1 13. Most preferred is a method according to the present invention, wherein one pair of labeled probes is selected from oligonucleotides according to SEQ ID NOS:181 and 182; and a second pair of labeled probes is selected from oligonucleotides according to SEQ ID NOS:8 and 9; or SEQ ID NOS: 16 and 17; or SEQ ID NOS: 109 and 1 10; or SEQ ID NOS: 114 and 115. The herein described invention is thereby useful for the differentiation of individuals who may be appropriately treated with one or more treatments which target the estrogen receptor pathway or are involved in estrogen metabolism, production or secretion from those individuals, who would be optimally treated with other treatments in addition to said treatment. Preferred 'other treatments' include but are not limited to chemotherapy or radiotherapy. It is particularly preferred that said prognosis and/or treatment response is stated in terms of likelihood of relapse, survival or outcome.

In a further embodiment of the invention the aberrant expression of a plurality of genes comprising of at the aforementioned at least two promoter/regulatory regions and/or transcripts of the gene PITX2 is analyzed. Said plurality of genes is hereinafter also referred to as a 'gene panel'. The analysis of multiple genes increases the accuracy of a provided prognosis and/or prediction of estrogen treatment outcome. It is preferred that the gene panel consists of up to seven genes and/or their promoter regions associated with prognosis and/or prediction of treatment response of breast carcinoma patients. It is further preferred that said panel consists of at least two promoter regions and/or transcripts of the gene PITX2 and one or more genes selected from the group consisting of ABCA8, CDK6, ERBB2, ONECUT2, PLAU, TBC 1D3 and TFFl and/or regulatory regions thereof. It is particularly preferred that the gene panel is selected from the group of gene panels consisting of:

• PITX2, PLAU and TFF 1

• PITX2 and PLAU

• PITX2 and TFFl

It is particularly preferred that the gene panel consisting of at least two promoter regions and/or transcripts of the gene PITX2 and at least one promoter region and/or transcript of the gene TFFl is used to predict outcome of treatment of patients with an endocrine treatment. In an alternative embodiment it is also preferred that the gene panel consists of at least two promoter regions and/or transcripts of the gene PITX2 and at least one promoter region and/or transcript of the gene PLAU is used to provide a prognosis of patients. It is preferred that said patients are analyzed prior to receiving any endocrine treatment.

In further embodiments this invention relates to new methods and sequences for the prognosis of patients diagnosed with breast cell proliferative disease. In a further aspect the invention relates to new methods and sequences, which may be used as tools for the selection of suitable treatments of patients diagnosed with breast cell proliferative disease based on a prediction of likelihood of relapse, survival or outcome.

More specifically this invention provides new methods and sequences for patients diagnosed with breast cell proliferative disease, allowing the improved selection of suitable adjuvant therapy. Furthermore, it is preferred that patients with poor prognosis following endocrine monotherapy are provided with chemotherapy in addition to or instead of an endocrine therapy.

One additional aspect of the invention is the provision of methods for providing a prognosis and/or prediction of outcome of endocrine treatment of a patient with a cell proliferative disorder of the breast tissues. Preferably said prognosis and/or prediction is provided in terms of likelihood of relapse or the survival of said patient. It is further preferred that said survival is disease free survival or metastasis free survival. It is also preferred that said disease is breast cancer. These methods comprise the analysis of the expression levels of at least two promoter regions and/or transcripts of the gene PITX2.

In further embodiments the method comprises analysis of the expression of a 'gene panel' comprising of at least two promoter regions and/or transcripts of the gene PITX2 and at least one promoter region and/or transcript of one or more genes selected from the group consisting of ABCA8, CDK6, ERBB2, ONECUT2, PLAU, TBC 1D3 and TFFl and/or regulatory regions thereof. It is particularly preferred that said gene panels are selected from the group of gene panels consisting of:

• PITX2, PLAU and TFFl

• PITX2 and PLAU

• PITX2 and TFFl

It is particularly preferred that the expression of the gene panel consisting of at least two promoter regions and/or transcripts of the gene PITX2 and at least one promoter region and/or transcript of the gene TFFl is determined in order to predict outcome of treatment of patients with an endocrine treatment. It is also particularly preferred that the expression of the gene panel consisting of at least two promoter regions and/or transcripts of the gene PITX2 and at least one promoter region and/or transcript of the gene PLAU is determined in order to provide a prognosis of patients. It is preferred that said patients are analyzed prior to receiving any endocrine treatment.

Determination of expression may be achieved by any means standard in the art, however it is preferably achieved by analysis of LOH, methylation, protein expression, mRNA expression, genetic or other epigenetic modifications of the genomic sequences.

Especially preferred is the analysis of the DNA methylation profile of the genomic sequences of the gene PITX2 and/or regulatory or promoter regions thereof as given in SEQ ID NO: 159 and 160. Further preferred is the analysis of the DNA methylation profile of the genomic sequences of the gene PITX2 and/or regulatory or promoter regions thereof as given in SEQ ID NO: 161 and 162. SEQ ID NO: 159 and 160 comprise SEQ ID NO: 161 and 162, respectively.

Wherein the method comprises analysis of a gene panel it is further preferred that one or more genes selected from the group consisting ABCA8, CDK6, ERBB2, ONECUT2, PLAU, TBC 1D3 and TFFl and/or regulatory or promoter regions thereof are analyzed. It is preferred that the sequence of said genes is selected from the group consisting of SEQ ID NO: 69 to SEQ ID NO: 75 and SEQ ID NO: 150 according to Table 1.

This methodology presents further improvements over the state of the art in that the method may be applied to any subject, independent of the estrogen and/or progesterone receptor status. Therefore in a preferred embodiment, the subject is not required to have been tested for estrogen or progesterone receptor status.

In further aspects of the invention, the disclosed matter provides novel nucleic acid sequences useful for the analysis of methylation within said gene, other aspects provide novel uses of the gene and the gene product as well as methods, assays and kits directed to providing a prognosis and/or predicting outcome of endocrine treatment of a patient diagnosed with breast cell proliferative disease. Said novel nucleic acid sequences, in one preferred example, can constitute a composition comprising a solution of at least three nucleic acid compounds comprising the SEQ ID NOS: 179, 180 and one of SEQ ID NO: 181 or SEQ ID NO: 182, in water or suitable aqueous buffer, or a composition comprising a solution of at least four nucleic acid compounds comprising the SEQ ID NOS: 179 to 182 in water or suitable aqueous buffer.

In one embodiment the invention discloses a method for providing the prognosis and/or predicting outcome of endocrine treatment of a patient suffering from a breast cell proliferative disease, by analysis of expression of at least two mRNA transcripts and/or regulatory regions of the gene PITX2. Preferably said endocrine treatment is an adjuvant endocrine monotherapy. Said method may be enabled by means of any analysis of the expression of the gene, including but not limited to mRNA expression analysis or protein expression analysis or by analysis of its genetic modifications leading to an altered expression (including LOH). However, in the most preferred embodiment of the invention, said expression is determined by means of analysis of the methylation status of CpG sites within at least two promoter/regulatory regions of the gene PITX2.

In one embodiment of the method aberrant expression of the gene PITX2 and/or panels thereof may be detected by analysis of loss of heterozygosity of the gene. In a first step genomic DNA is isolated from a biological sample of the patient's tumor. The isolated DNA is then analyzed for LOH by any means standard in the art including but not limited to amplification of the gene locus or associated microsatellite markers. Said amplification may be carried out by any means standard in the art including polymerase chain reaction (PCR), strand displacement amplification (SDA)and isothermal amplification.

The level of amplificate is then detected by any means known in the art including but not limited to gel electrophoresis and detection by probes (including Real Time PCR). Furthermore the amplificates may be labeled in order to aid said detection. Suitable detectable labels include but are not limited to fluorescence label, radioactive labels and mass labels the suitable use of which shall be described herein.

The detection of a decreased amount of an amplificate corresponding to one of the amplified alleles in a test sample as relative to that of a heterozygous control sample is indicative of LOH.

To detect the levels of an mRNA transcript encoding PITX2 and/or panels comprising said gene in a detection system for breast cancer relapse, a sample is obtained from a patient. Said obtaining of a sample is preferably not meant to be retrieving of a sample, as in performing a biopsy, but rather directed to the availability of an isolated biological material representing a specific tissue, relevant for the intended use. The sample can be a rumor tissue sample from the surgically removed tumor, a biopsy sample as taken by a surgeon and provided to the analyst or a sample of blood, plasma, serum or the like. The sample may be treated to extract the nucleic acids contained therein. The resulting nucleic acid from the sample is subjected to gel electrophoresis or other separation techniques. Detection involves contacting the nucleic acids and in particular the mRNA of the sample with a DNA sequence serving as a probe to form hybrid duplexes. The stringency of hybridization is determined by a number of factors during hybridization and during the washing procedure, including temperature, ionic strength, length of time and concentration of formamide. These factors are outlined in, for example, Sambrook et al. (Molecular Cloning: A Laboratory Manual, 2nd ed., 1989). Detection of the resulting duplex is usually accomplished by the use of labeled probes. Alternatively, the probe may be unlabeled, but may be detectable by specific binding with a ligand which is labeled, either directly or indirectly. Suitable labels and methods for labeling probes and ligands are known in the art, and include, for example, radioactive labels which may be incorporated by known methods (e.g., nick translation or kinasing), biotin, fluorescent groups, chemiluminescent groups (e.g., dioxetanes, particularly triggered dioxetanes), enzymes, antibodies, and the like.

In order to increase the sensitivity of the detection in a sample of mRNA encoding PITX2 and/or panels comprising said gene, the technique of reverse transcription/polymerization chain reaction can be used to amplify cDNA transcribed from mRNA encoding PITX2 and/or panels comprising said gene. The method of reverse transcription/PCR is well known in the art (for example, see Watson and Fleming, supra).

The reverse transcription/PCR method can be performed as follows. Total cellular RNA is isolated by, for example, the standard guanidium isothiocyanate method and the total RNA is reverse transcribed. The reverse transcription method involves synthesis of DNA on a template of RNA using a reverse transcriptase enzyme and a 3' end primer. Typically, the primer contains an oligo(dT) sequence. The cDNA thus produced is then amplified using the PCR method and PITX2 and/or panels comprising said gene specific primers. (Belyavsky et al, Nucl Acid Res 17:2919-2932, 1989; Krug and Berger, Methods in Enzymology, Academic Press, N.Y., Vol.152, pp. 316-325, 1987 which are incorporated by reference) The present invention also in certain embodiments thereof constitutes a kit for use in predicting the likelihood of relapse and/or survival of a breast cancer patient before or after surgical tumor removal with or without adjuvant endocrine monotherapy state through testing of a biological sample. A representative kit may comprise one or more nucleic acid segments as described above that selectively hybridize to PITX2 mRNA and/or mRNA from genes of a panel comprising said PITX2 gene, and a container for each of the one or more nucleic acid segments. In certain embodiments the nucleic acid segments may be combined in a single tube. In further embodiments, the nucleic acid segments may also include a pair of primers for amplifying the target mRNA. Such kits may also include any buffers, solutions, solvents, enzymes, nucleotides, or other components for hybridization, amplification or detection reactions. Preferred kit components include reagents for reverse transcription-PCR, in situ hybridization, Northern analysis and/or RPA. Thus, the present invention in one further aspect thereof provides such a diagnostic kit, comprising at least one container and at least two pairs of primer oligonucleotides, wherein one pair is selected from sequences according to SEQ ID NOS: 179 and 180, optionally together with other suitable auxiliaries. Preferably, a second pair of primers is included that is selected from oligonucleotides according to SEQ ID NOS:6 and 7 or SEQ ID NOS:14 and 15; or SEQ ID NOS:107 and 108; or SEQ ID NOS:1 12 and 1 13. Furthermore, additional oligonucleotide are contained that are suitable for an analysis, and optionally suitable pairs of these oligonucleotide. Said additional oligonucleotide probes can be selected from oligonucleotides according to SEQ ID NOS: 181 and 182, and the said additional oligonucleotide probes are selected from oligonucleotides according to SEQ ID NOS:8 and 9; or SEQ ID NOS:16 and 17; or SEQ ID NOS:109 and 110; or SEQ ID NOS:114 and 115. Preferably, said probes are labeled probes.

Said kit may further comprise instructions for carrying out and evaluating the described method. In a further preferred embodiment, said kit may further comprise standard reagents for performing a CpG position-specific methylation analysis, wherein said analysis comprises one or more of the following techniques: MS-SNuPE, MSP, MethyLight®, HeavyMethyl®, COBRA, and nucleic acid sequencing. However, a kit along the lines of the present invention can also contain only part of the aforementioned components.

Typical reagents (e.g., as might be found in a typical COBRA-based kit) for COBRA analysis may include, but are not limited to: PCR primers for specific gene (or methylation-altered DNA sequence or CpG island); restriction enzyme and appropriate buffer; gene-hybridization oligo; control hybridization oligo; kinase labeling kit for oligonucleotide probe; and radioactive nucleotides. Additionally, bisulfite conversion reagents may include: DNA denaturation buffer; sulfonation buffer; DNA recovery reagents or kits (e.g., precipitation, ultrafiltration, affinity column); desulfonation buffer; and DNA recovery components.

Typical reagents (e.g., as might be found in a typical MethyLight®-based kit) for MethyLight® analysis may include, but are not limited to: PCR primers for specific gene (or methylation-altered DNA sequence or CpG island); TaqMan® probes; optimized PCR buffers and deoxynucleotides; and Taq polymerase.

Typical reagents (e.g., as might be found in a typical Ms-SNuPE-based kit) for Ms-SNuPE analysis may include, but are not limited to: PCR primers for specific gene (or methylation- altered DNA sequence or CpG island); optimized PCR buffers and deoxynucleotides; gel extraction kit; positive control primers; Ms-SNuPE primers for specific gene; reaction buffer (for the Ms-SNuPE reaction); and radioactive nucleotides. Additionally, bisulfite conversion reagents may include: DNA denaturation buffer; sulfonation buffer; DNA recovery regents or kit (e.g., precipitation, ultrafiltration, affinity column); desulfonation buffer; and DNA recovery components.

Typical reagents (e.g., as might be found in a typical MSP-based kit) for MSP analysis may include, but are not limited to: methylated and unmethylated PCR primers for specific gene (or methylation-altered DNA sequence or CpG island), optimized PCR buffers and deoxynucleotides, and specific probes.

The present invention further provides for methods to detect the presence of the polypeptide(s) of, PITX2 and/or panels comprising said protein, in a sample obtained from a patient. It is preferred that said sequence is essentially the same as the sequence as given in figure 10. Any method known in the art for detecting proteins can be used. Such methods include, but are not limited to immunodiffusion, immunoelectrophoresis, immunochemical methods, binder-ligand assays, immunohistochemical techniques, agglutination and complement assays, (for example see Basic and Clinical Immunology, Sites and Terr, eds., Appleton and Lange, Norwalk, Conn, pp 217-262, 1991 which is incorporated by reference). Preferred are binder-ligand immunoassay methods including reacting antibodies with an epitope or epitopes of PITX2 and/or panels thereof and competitively displacing a labeled PITX2 protein and/or panels thereof or derivatives thereof.

Certain embodiments of the present invention comprise the use of antibodies specific to the polypeptide encoded by the gene PITX2 and/or panels comprising said gene. Such antibodies may be useful for providing a prognosis of the likelihood of relapse and/or survival of a breast cancer patient preferably under adjuvant endocrine monotherapy by comparing a patient's levels of PITX2 marker expression and/or the expression of panels comprising PITX2 to expression of the same marker(s) in normal individuals. In certain embodiments the production of monoclonal or polyclonal antibodies can be induced by the use of the PITX2 and/or other polypeptides of the panels as antigene. Such antibodies may in turn be used to detect expressed proteins as markers for prognosis of relapse of a breast cancer patient under adjuvant endocrine monotherapy. The levels of such proteins present in the peripheral blood of a patient may be quantified by conventional methods. Antibody-protein binding may be detected and quantified by a variety of means known in the art, such as labeling with fluorescent or radioactive ligands. The invention further comprises kits for performing the above-mentioned procedures, wherein such kits contain antibodies specific for the PITX2 and/or panels thereof polypeptides.

Numerous competitive and non-competitive protein binding immunoassays are well known in the art. Antibodies employed in such assays may be unlabeled, for example as used in agglutination tests, or labeled for use a wide variety of assay methods. Labels that can be used include radionuclides, enzymes, fluorescers, chemiluminescers, enzyme substrates or co- factors, enzyme inhibitors, particles, dyes and the like for use in radioimmunoassay (RIA), enzyme immunoassays, e.g., enzyme-linked immunosorbent assay (ELISA), fluorescent immunoassays and the like. Polyclonal or monoclonal antibodies to PITX2 and/or panels thereof or an epitope thereof can be made for use in immunoassays by any of a number of methods known in the art. One approach for preparing antibodies to a protein is the selection and preparation of an amino acid sequence of all or part of the protein, chemically synthesizing the sequence and injecting it into an appropriate animal, usually a rabbit or a mouse (Milstein and Kohler Nature 256:495-497, 1975; Gulfre and Milstein, Methods in Enzymology: Immunochemical Techniques 73:1-46, Langone and Banatis eds., Academic Press, 1981 which are incorporated by reference). Methods for preparation of PITX2 and/or panels thereof or an epitope thereof include, but are not limited to chemical synthesis, recombinant DNA techniques or isolation from biological samples.

In one aspect the invention provides significant improvements over the state of the art in that it enables the prediction of the likelihood of relapse or of survival of a breast cancer patient under adjuvant endocrine monotherapy with a greater accuracy than the currently used method (analysis one CpG rich region only, at the promoter region of the gene).

In the most preferred embodiment of the invention the analysis of expression is carried out by means of methylation analysis. It is further preferred that the methylation state of at least two CpG dinucleotides at least one thereof selected from SEQ ID NO: 159 and at least one thereof selected from SEQ ID NO: 160 and sequences complementary thereto are analyzed. It is further preferred that the at least one CpG thereof selected from SEQ ID NO: 159 also comprises SEQ ID NO: 161 and that the at least one CpG selected from SEQ ID NO: 160 also comprises SEQ ID NO: 162.

Wherein the method comprises analysis of the expression of a 'gene panel' comprising at least two promoter/regulatory regions and/or transcripts of the gene PITX2 (including SEQ ID NO: 159 - 162 as described above) and one or more genes selected from the group consisting ABCA8, CDK6, ERBB2, ONECUT2, PLAU, TBC1D3 and TFFl it is most preferred that said analysis of expression is carried out by means of methylation analysis. It is particularly preferred that the CpG methylation of the gene panels selected from the group of gene panels consisting:

• PITX2, PLAU and TFFl

• PITX2 and PLAU

• PITX2 and TFFl is analyzed.

It is particularly preferred that the methylation of the gene panel consisting at least two promoter/regulatory regions of the genes PITX2 and at least one promoter/regulatory regions of the gene TFFl is determined in order to predict outcome of treatment of patients with an endocrine treatment. It is also particularly preferred that the methylation of the gene panel consisting at least two promoter/regulatory regions and/or transcripts of the genes PITX2 and at least one promoter/regulatory regions of the gene PLAU is determined in order to provide a prognosis of patients. It is preferred that said patients are analyzed prior to receiving any endocrine treatment.

Hypermethylation of PITX2 and selected other genes as herein and/or sequences thereof are associated with poor prognosis and/or outcome of endocrine treatment of breast cell proliferative disorders, most preferably breast carcinoma. Combined methylation analysis of two specific regions of the PITX2 gene enable the prognosis of events and/or predicted outcome of treatment with estrogen treatment with a greater accuracy than the analysis of the single region heretofore investigate.

It has heretofore not been recognized that the combined analysis of the methylation of the herein disclosed sequences of the gene PITX2 (SEQ ID NO: 159-162) enables the improved accuracy of prognosis or prediction of outcome of endocrine treatment of a patient diagnosed with a breast cell proliferative disorder. Due to the degeneracy of the genetic code, the sequences as identified in SEQ ID NO: 159-162 should be interpreted so as to include all substantially similar and equivalent sequences of the promoter region of a gene which encodes a polypeptide with the biological activity of that encoded by PITX2.

Most preferably the following method is used to detect methylation within the gene PITX2 and/or regulatory or promoter regions thereof wherein said methylated nucleic acids are present in an excess of background DNA, wherein the background DNA is present in 100 to 1000 times the concentration of the DNA to be detected.

The method for the analysis of methylation comprises contacting a nucleic acid sample obtained from a subject with at least one reagent or a series of reagents, wherein said reagent or series of reagents, distinguishes between methylated and non-methylated CpG dinucleotides within the target nucleic acid.

Preferably, said method comprises the following steps: In the first step, a sample of the tissue to be analyzed is obtained. The source may be any suitable source, preferably, the source of the sample is selected from the group consisting of histological slides, biopsies, paraffin- embedded tissue, bodily fluids, plasma, serum, stool, urine, blood, nipple aspirate and combinations thereof. Preferably, the source is tumor tissue, biopsies, serum, urine, blood or nipple aspirate. The most preferred source, is the tumor sample, surgically removed from the patient or a biopsy sample of said patient.

The DNA is then isolated from the sample. Genomic DNA may be isolated by any means standard in the art, including the use of commercially available kits. Briefly, wherein the DNA of interest is encapsulated in/by a cellular membrane the biological sample must be disrupted and lysed by enzymatic, chemical or mechanical means. The DNA solution may then be cleared of proteins and other contaminants e.g. by digestion with proteinase K. The genomic DNA is then recovered from the solution. This may be carried out by means of a variety of methods including salting out, organic extraction or binding of the DNA to a solid phase support. The choice of method will be affected by several factors including time, expense and required quantity of DNA.

The genomic DNA sample is then treated in such a manner that cytosine bases which are unmethylated at the 5'-position are converted to uracil, thymine, or another base which is dissimilar to cytosine in terms of hybridization behavior. This will be understood as "treatment" or "pre-treatment" herein.

The above described pre-treatment of genomic DNA is preferably carried out with bisulfite (hydrogen sulfite, disulfite) and subsequent alkaline hydrolysis which results in a conversion of non-methylated cytosine nucleobases to uracil or to another base which is dissimilar to cytosine in terms of base pairing behavior. Enclosing the DNA to be analyzed in an agarose matrix, thereby preventing the diffusion and renaturation of the DNA (bisulfite only reacts with single-stranded DNA), and replacing all precipitation and purification steps with fast dialysis (Olek A, et al., A modified and improved method for bisulfite based cytosine methylation analysis, Nucleic Acids Res. 24:5064-6, 1996) is one preferred example how to perform said pre-treatment . It is further preferred that the bisulfite treatment is carried out in the presence of a radical scavenger or DNA denaturing agent.

The treated DNA is then analyzed in order to determine the methylation state of at least two promoter/regulatory regions and/or transcripts of the gene PITX2 and/or regulatory regions thereof (prior to the treatment) associated with prognosis and/or outcome of endocrine treatment . In a further embodiment of the method the methylation state of at least two promoter/regulatory regions and/or transcripts of the gene PITX2 and/or regulatory regions thereof and the methylation state of one or more genes selected from the group consisting ABCA8, CDK6, ERBB2, ONECUT2, PLAU, TBC1D3 and TFFl and/or regulatory or promoter regions thereof is determined. It is particularly preferred that methylation status of a gene panel selected from the group of gene panels consisting at least two promoter/regulatory regions and/or transcripts of the gene PITX2, PLAU and TFFl ; at least two promoter/regulatory regions and/or transcripts of the gene PITX2 and PLAU; at least two promoter/regulatory regions and/or transcripts of the gene PITX2 and TFFl is determined.

Especially preferred is the analysis of the DNA methylation profile of the genomic sequences of the gene PITX2 and/or regulatory or promoter regions thereof as given in SEQ ID NO: 159 and 160. Further preferred is the analysis of the DNA methylation profile of the genomic sequences of the gene PITX2 and/or regulatory or promoter regions thereof as given in SEQ ID NO: 161 and 162. SEQ ID NO: 159 and 160 comprise SEQ ID NO: 161 and 162 respectively.

It is further preferred that the sequences of the genes ABCA8, CDK6, ERBB2, ONECUT2, PLAU, TBC 1D3, and TFFl as described in the accompanying sequence listing (see Table 1) are analyzed.

In the third step of the method, fragments of the pretreated DNA are amplified. Wherein the source of the DNA is free DNA from serum, or DNA extracted from paraffin it is particularly preferred that the size of the amplificate fragment is between 100 and 200 base pairs in length, and wherein said DNA source is extracted from cellular sources (e.g. tissues, biopsies, cell lines) it is preferred that the amplificate is between 100 and 350 base pairs in length. It is particularly preferred that said amplificates comprise at least one 20 base pair sequence comprising at least three CpG dinucleotides. Said amplification is carried out using sets of primer oligonucleotides according to the present invention, and a preferably heat-stable polymerase. The amplification of several DNA segments can be carried out simultaneously in one and the same reaction vessel, in one embodiment of the method preferably six or more fragments are amplified simultaneously. Typically, the amplification is carried out using a polymerase chain reaction (PCR). The set of primer oligonucleotides includes at least two oligonucleotides whose sequences are each reverse complementary, identical, or hybridize under stringent or highly stringent conditions to an at least 18-base-pair long segment of the base sequences of SEQ ID NO: 2-5, SEQ ID NO: 76 to SEQ ID NO: 103 and SEQ ID NO: 151 to SEQ ID NO: 158, SEQ ID NO: 163 to 178 and sequences complementary thereto.

However in the most preferred embodiment it is preferred that at least two sequences are amplified, at least one of which is complementary, reverse complementary or identical to SEQ ID NO: 159 and at least one of which is complementary, reverse complementary or identical to SEQ ID NO: 160. Accordingly in this embodiment it is preferred that the set of primers includes at least two oligonucleotides whose sequences are each reverse complementary, identical, or hybridize under stringent or highly stringent conditions to an at least 18-base-pair long segment of the base sequences of a sequence selected from the group consisting SEQ ID NO: 165, 166, 173 and 174 (and sequences complementary thereto) and at least two oligonucleotides whose sequences are each reverse complementary, identical, or hybridize under stringent or highly stringent conditions to an at least 18-base-pair long segment of the base sequences of a sequence selected from the group consisting SEQ ID NO: 165, 166, 173 and 174 and sequences complementary thereto.

In an alternate embodiment of the method, the methylation status of preselected CpG positions within the nucleic acid sequences comprising SEQ ID NO: 1, SEQ ID NO: 60 to SEQ ID NO: 75, SEQ ID NO: 149 and SEQ ID NO: 150 may be detected by use of methylation-specific primer oligonucleotides.

However in a more preferred embodiment the methylation status of preselected CpG positions within the nucleic acid sequences SEQ ID NO: 159 and SEQ ID NO: 160 may be detected by use of methylation-specific primer oligonucleotides. It is also preferred that the methylation status of preselected CpG positions within the nucleic acid sequences comprising SEQ ID NO: 161 and SEQ ID NO: 162 may be detected by use of methylation-specific primer oligonucleotides. SEQ ID NO: 159 and 160 comprise SEQ ID NO: 161, and SEQ ID NO: 162 respectively.

This technique (MSP) has been described in United States Patent No. 6,265,171 to Herman. The use of methylation status specific primers for the amplification of bisulfite treated DNA allows the differentiation between methylated and unmethylated nucleic acids. MSP primers pairs contain at least one primer which hybridizes to a bisulfite treated CpG dinucleotide. Therefore, the sequence of said primers comprises at least one CpG , TpG or CpA dinucleotide. MSP primers specific for non-methylated DNA contain a "T' at the 3' position of the C position in the CpG. Preferably, therefore, the base sequence of said primers is required to comprise a sequence having a length of at least 18 nucleotides which hybridizes to a pretreated nucleic acid sequence according to SEQ ID NO: 2 to SEQ ID NO: 5 and SEQ ID NO: 151 , 152, 155 and 156 and sequences complementary thereto, wherein the base sequence of said oligomers comprises at least one CpG, tpG or Cpa dinucleotide.

However in the most preferred embodiment it is preferred that at least two sequences are amplified, at least one of which is complementary, reverse complementary or identical to a sequence selected from the group consisting of SEQ ID NO: 163, 164, 171 and 172 and at least one of which is complementary, reverse complementary or identical to SEQ ID NO: 165, 166, 173 and 174. Accordingly, it is further preferred that at least two pairs of primers are used in the amplification. Wherein one pair of primers consists at least two oligonucleotides whose sequences are each reverse complementary, identical, or hybridize under stringent or highly stringent conditions to an at least 18-base-pair long segment of the base sequences of a sequence selected from the group consisting of SEQ ID NO: 163-166 and 171-174 (and sequences complementary thereto) and wherein one pair of primers consists at least two oligonucleotides whose sequences are each reverse complementary, identical, or hybridize under stringent or highly stringent conditions to an at least 18-base-pair long segment of the base sequences of a sequence selected from the group consisting of SEQ ID NO: 165, 166, 173 and 174 and sequences complementary thereto and further wherein the base sequence of said oligomers comprises at least one CpG, tpG or Cpa dinucleotide.

In this embodiment of the method according to the invention it is particularly preferred that the MSP primers comprise between 2 and 4 CpG , tpG or Cpa dinucleotides. It is further preferred that said dinucleotides are located within the 3' half of the primer e.g. wherein a primer is 18 bases in length the specified dinucleotides are located within the first 9 bases form the 3 'end of the molecule. In addition to the CpG , tpG or Cpa dinucleotides it is further preferred that said primers should further comprise several bisulfite converted bases (i.e. cytosine converted to thymine, or on the hybridizing strand, guanine converted to adenosine). In a further preferred embodiment said primers are designed so as to comprise no more than 2 cytosine or guanine bases.

The fragments obtained by means of the amplification can carry a directly or indirectly detectable label. Preferred are labels in the form of fluorescence labels, radionuclides, or detachable molecule fragments having a typical mass which can be detected in a mass spectrometer. Where said labels are mass labels, it is preferred that the labeled amplificates have a single positive or negative net charge, allowing for better detectability in the mass spectrometer. The detection may be carried out and visualized by means of, e.g., matrix assisted laser desorption/ionization mass spectrometry (MALDI) or using electron spray mass spectrometry (ESl).

Matrix Assisted Laser Desorption/ionization Mass Spectrometry (MALDI-TOF) is a very efficient development for the analysis of biomolecules (Karas and Hillenkamp, Anal Chem., 60:2299-301, 1988). An analyte is embedded in a light-absorbing matrix. The matrix is evaporated by a short laser pulse thus transporting the analyte molecule into the vapor phase in an unfragmented manner. The analyte is ionized by collisions with matrix molecules. An applied voltage accelerates the ions into a field-free flight tube. Due to their different masses, the ions are accelerated at different rates. Smaller ions reach the detector sooner than bigger ones. MALDI-TOF spectrometry is well suited to the analysis of peptides and proteins. The analysis of nucleic acids is somewhat more difficult (Gut and Beck, Current Innovations and Future Trends, 1 :147-57, 1995). The sensitivity with respect to nucleic acid analysis is approximately 100-times less than for peptides, and decreases disproportionally with increasing fragment size. Moreover, for nucleic acids having a multiply negatively charged backbone, the ionisation process via the matrix is considerably less efficient. In MALDI-TOF spectrometry, the selection of the matrix plays an eminently important role. For the desorption of peptides, several very efficient matrixes have been found which produce a very fine crystallisation. There are now several responsive matrixes for DNA, however, the difference in sensitivity between peptides and nucleic acids has not been reduced. This difference in sensitivity can be reduced, however, by chemically modifying the DNA in such a manner that it becomes more similar to a peptide. For example, phosphorothioate nucleic acids, in which the usual phosphates of the backbone are substituted with thiophosphates, can be converted into a charge-neutral DNA using simple alkylation chemistry (Gut and Beck, Nucleic Acids Res. 23: 1367-73, 1995). The coupling of a charge tag to this modified DNA results in an increase in MALDI-TOF sensitivity to the same level as that found for peptides. A further advantage of charge tagging is the increased stability of the analysis against impurities, which makes the detection of unmodified substrates considerably more difficult.

In a particularly preferred embodiment of the method the amplification of step three is carried out in the presence of at least one species of blocker oligonucleotides. The use of such blocker oligonucleotides has been described by Yu et al., BioTechniques 23:714-720, 1997. The use of blocking oligonucleotides enables the improved specificity of the amplification of a subpopulation of nucleic acids. Blocking probes hybridized to a nucleic acid suppress, or hinder the polymerase mediated amplification of said nucleic acid. In one embodiment of the method blocking oligonucleotides are designed so as to hybridize to background DNA. In a further embodiment of the method said oligonucleotides are designed so as to hinder or suppress the amplification of unmethylated nucleic acids as opposed to methylated nucleic acids or vice versa.

Blocking probe oligonucleotides are hybridized to the bisulfite treated nucleic acid concurrently with the PCR primers. PCR amplification of the nucleic acid is terminated at the 5' position of the blocking probe, such that amplification of a nucleic acid is suppressed where the complementary sequence to the blocking probe is present. The probes may be designed to hybridize to the bisulfite treated nucleic acid in a methylation status specific manner. For example, for detection of methylated nucleic acids within a population of unmethylated nucleic acids, suppression of the amplification of nucleic acids which are unmethylated at the position in question would be carried out by the use of blocking probes comprising a 'TpG' at the position in question, as opposed to a 'CpG.'

In one embodiment of the method the sequence of said blocking oligonucleotides should be identical or complementary to a sequence at least 18 base pairs in length selected from the group consisting of SEQ ID NOs: 2 to 5, 151, 152, 155 and 156 preferably comprising one or more CpG, TpG or CpA dinucleotides. In one embodiment of the method the sequence of said oligonucleotides is selected from the group consisting SEQ ID NO: 15 and SEQ ID NO: 16 and sequences complementary thereto.

However in the most preferred embodiment it is preferred that at least two sequences are amplified, at least one of which is complementary, reverse complementary or identical to a sequence selected from the group consisting SEQ ID NO: 163, 164, 171 and 172 and at least one of which is complementary, reverse complementary or identical to a sequence selected from the group SEQ ID NO: 165, 166, 173 and 174. Accordingly it is preferred that two species of blocking oligonucleotides are used. The sequence of said first species of blocking oligonucleotides should be identical or complementary to a sequence at least 18 base pairs in length selected from the group consisting of SEQ ID NOs: 163, 164, 171 and 172 comprising one or more CpG, TpG or CpA dinucleotides.

The sequence of said second species of blocking oligonucleotides should be identical or complementary to a sequence at least 18 base pairs in length selected from the group consisting of SEQ ID NOs: 165, 166, 173 and 174 comprising one or more CpG, TpG or CpA dinucleotides.

It is also preferred that the methylation status of preselected CpG positions within the nucleic acid sequences a sequence selected from the group consisting SEQ ID NO: 167, 168, 175 and 176 and SEQ ID NO: 169, 170, 177 and 178 may be analysed by means of blocker oligonucleotides. SEQ ID NO: 163-166 and 171-174 comprise SEQ ID NO: 167-170 and 175-178 respectively.

For PCR methods using blocker oligonucleotides, efficient disruption of polymerase-mediated amplification requires that blocker oligonucleotides not be elongated by the polymerase. Preferably, this is achieved through the use of blockers that are 3'-deoxyoligonucleotides, or oligonucleotides derivatised at the 3' position with other than a "free" hydroxyl group. For example, 3'-O-acetyl oligonucleotides are representative of a preferred class of blocker molecule.

Additionally, polymerase-mediated decomposition of the blocker oligonucleotides should be precluded. Preferably, such preclusion comprises either use of a polymerase lacking 5'-3' exonuclease activity, or use of modified blocker oligonucleotides having, for example, thioate bridges at the 5'-termini thereof that render the blocker molecule nuclease-resistant. Particular applications may not require such 5' modifications of the blocker. For example, if the blocker- and primer-binding sites overlap, thereby precluding binding of the primer (e.g., with excess blocker), degradation of the blocker oligonucleotide will be substantially precluded. This is because the polymerase will not extend the primer toward, and through (in the 5'-3' direction) the blocker - a process that normally results in degradation of the hybridized blocker oligonucleotide.

A particularly preferred blocker/PCR embodiment, for purposes of the present invention and as implemented herein, comprises the use of peptide nucleic acid (PNA) oligomers as blocking oligonucleotides. Such PNA blocker oligomers are ideally suited, because they are neither decomposed nor extended by the polymerase.

In one embodiment of the method, the binding site of the blocking oligonucleotide is identical to, or overlaps with that of the primer and thereby hinders the hybridization of the primer to its binding site. In a further preferred embodiment of the method, two or more such blocking oligonucleotides are used. In a particularly preferred embodiment, the hybridization of one of the blocking oligonucleotides hinders the hybridization of a forward primer, and the hybridization of another of the probe (blocker) oligonucleotides hinders the hybridization of a reverse primer that binds to the amplificate product of said forward primer.

In an alternative embodiment of the method, the blocking oligonucleotide hybridizes to a location between the reverse and forward primer positions of the treated background DNA, thereby hindering the elongation of the primer oligonucleotides.

It is particularly preferred that the blocking oligonucleotides are present in at least 5 times the concentration of the primers.

In the fourth step of the method, the amplificates obtained during the third step of the method are analyzed in order to ascertain the methylation status of the CpG dinucleotides prior to the treatment.

In embodiments where the amplificates are obtained by means of MSP amplification and/or blocking oligonucleotides, the presence or absence of an amplificate is in itself indicative of the methylation state of the CpG positions covered by the primers and or blocking oligonucleotide, according to the base sequences thereof. All possible known molecular biological methods may be used for this detection, including, but not limited to gel electrophoresis, sequencing, liquid chromatography, hybridizations, real time PCR analysis or combinations thereof. This step of the method further acts as a qualitative control of the preceding steps.

In the fourth step of the method amplificates obtained by means of both standard and methylation specific PCR are further analyzed in order to determine the CpG methylation status of the genomic DNA isolated in the first step of the method. This may be carried out by means of hybridization-based methods such as, but not limited to, array technology and probe based technologies as well as by means of techniques such as sequencing and template directed extension.

In one embodiment of the method, the amplificates synthesized in step three are subsequently hybridized to an array or a set of oligonucleotides and/or PNA probes. In this context, the hybridization takes place in the following manner: the set of probes used during the hybridization is preferably composed of at least 2 oligonucleotides or PNA-oligomers; in the process, the amplificates serve as probes which hybridize to oligonucleotides previously bonded to a solid phase; the non-hybridized fragments are subsequently removed; said oligonucleotides contain at least one base sequence having a length of at least 9 nucleotides which is reverse complementary or identical to a segment of the base sequences specified in the SEQ ID NO: 2 to SEQ ID NO: 5 and SEQ ID Nos: 151 , 152, 155 and 156 and the segment comprises at least one CpG , TpG or CpA dinucleotide. However it is further preferred that said sequences contain at least one base sequence having a length of at least 9 nucleotides which is reverse complementary or identical to a segment of the base sequences specified in the SEQ ID NO: 163-178 and the segment comprises at least one CpG, TpG or CpA dinucleotide.

In further embodiments said oligonucleotides further contain at least one base sequence having a length of at least 9 nucleotides which is reverse complementary or identical to a segment of the base sequences specified in the SEQ ID NO: 2-5, SEQ ID NO: 151 to SEQ ID NO: 158 and SEQ ID NO: 76 to SEQ ID NO: 103; and the segment comprises at least one CpG , TpG or CpA dinucleotide.

In a preferred embodiment, said dinucleotide is present in the central third of the oligomer. For example, wherein the oligomer comprises one CpG dinucleotide, said dinucleotide is preferably the fifth to ninth nucleotide from the 5'-end of a 13-mer. In a further embodiment one oligonucleotide exists for the analysis of each CpG dinucleotide within the sequence according to SEQ ID NO: 1 and 149, and the equivalent positions within SEQ ID NO: 2 to 5 and SEQ ID NO: 151 , 152, 155 and 156. One oligonucleotide exists for the analysis of each CpG dinucleotide within the sequence according to SEQ ID NO: 1, SEQ ID NOS. 149, 150, and SEQ ID NO: 60 to SEQ ID NO: 75, and the equivalent positions within SEQ ID NO: 2-5, SEQ ID NO: 151 to SEQ ID NO: 158, and SEQ ID NO: 76 to SEQ ID NO: 103. However it is most preferred that one oligonucleotide exists for the analysis of each CpG dinucleotide within the sequence according to SEQ ID NO: 163-166 and 171-174, and the equivalent positions within SEQ ID NO: 167-170 and 175-178.

Said oligonucleotides may also be present in the form of peptide nucleic acids. The non- hybridized amplifϊcates are then removed. The hybridized amplificates are detected. In this context, it is preferred that labels attached to the amplifϊcates are identifiable at each position of the solid phase at which an oligonucleotide sequence is located.

In yet a further embodiment of the method, the genomic methylation status of the CpG positions may be ascertained by means of oligonucleotide probes that are hybridized to the bisulfite treated DNA concurrently with the PCR amplification primers (wherein said primers may either be methylation specific or standard).

A particularly preferred embodiment of this method is the use of fluorescence-based Real Time Quantitative PCR (Heid et al., Genome Res. 6:986-994, 1996; also see United States Patent No. 6,331,393). There are two preferred embodiments of utilizing this method. One embodiment, known as the TaqMan™ assay employs a dual-labeled fluorescent oligonucleotide probe. The TaqMan™ PCR reaction employs the use of a non-extendible interrogating oligonucleotide, called a TaqMan™ probe, which is designed to hybridize to a CpG-rich sequence located between the forward and reverse amplification primers. The TaqMan™ probe further comprises a fluorescent "reporter moiety" and a "quencher moiety" covalently bound to linker moieties {e.g., phosphoramidites) attached to the nucleotides of the TaqMan™ oligonucleotide. Hybridized probes are displaced and broken down by the polymerase of the amplification reaction thereby leading to an increase in fluorescence. For analysis of methylation within nucleic acids subsequent to bisulfite treatment, it is required that the probe be methylation specific, as described in United States Patent No. 6,331,393, (hereby incorporated by reference in its entirety) also known as the MethyLight assay. The second preferred embodiment of this MethyLight technology is the use of dual-probe technology (Lightcycler®), each probe carrying donor or recipient fluorescent moieties, hybridization of two probes in proximity to each other is indicated by an increase or fluorescent amplification primers. Both these techniques may be adapted in a manner suitable for use with bisulfite treated DNA, and moreover for methylation analysis within CpG dinucleotides. Also any combination of these probes or combinations of these probes with other known probes may be used.

In a further preferred embodiment of the method, the fourth step of the method comprises the use of template-directed oligonucleotide extension, such as MS-SNuPE as described by Gonzalgo and Jones, Nucleic Acids Res. 25:2529-2531 , 1997. In said embodiment it is preferred that the methylation specific single nucleotide extension primer (MS-SNuPE primer) is identical or complementary to a sequence at least nine but preferably no more than twenty five nucleotides in length of one or more of the sequences taken from the group of SEQ ID NO: 2 to SEQ ID NO: 5 and SEQ ID NOS: 151, 152, 155 and 156. However in the most preferred embodiment it is preferred that at least two sequences are analysed, at least one of which is complementary, reverse complementary or identical to a sequence selected from the group consisting SEQ ID NO: 163, 164, 171 and 172, and at least one of which is complementary, reverse complementary or identical to a sequence selected from the group consisting SEQ ID NO: 165, 166, 173 and 174. Accordingly it is preferred that at least two methylation specific single nucleotide extension primers are used (MS-SNuPE primers). One of which is identical or complementary to a sequence at least nine but preferably no more than twenty five nucleotides in length of one or more of the sequences taken from the group of SEQ ID NO: 163, 164, 171 and 172 (more preferably SEQ ID NO: 167, 168, 175 and 176 which are part of said sequences respectively), and at least one of which is identical or complementary to a sequence at least nine but preferably no more than twenty five nucleotides in length of one or more of the sequences taken from the group of SEQ ID NO: 165, 166, 173 and 174 (more preferably SEQ ID NO: 169, 170, 177 and 178 which are part of said sequences respectively).

It is preferred to use fluorescently labeled nucleotides, as opposed to radioactively labeled nucleotides.

In yet a further embodiment of the method, the fourth step of the method comprises sequencing and subsequent sequence analysis of the amplificate(s) generated in the third step of the method (Sanger F., et al., Pr oc Natl Acad Sd USA 74:5463-5467, 1977). In the most preferred embodiment of the methylation analysis method the genomic nucleic acids are isolated and treated according to the first three steps of the method outlined above, namely: a) obtaining, from a subject, a biological sample having subject genomic DNA; b) extracting or otherwise isolating the genomic DNA; c) treating the genomic DNA of b), or a fragment thereof, with one or more reagents to convert cytosine bases that are unmethylated in the 5-position thereof to uracil or to another base that is detectably dissimilar to cytosine in terms of hybridization properties; and wherein d) amplifying subsequent to treatment in c) is carried out in a methylation specific manner, namely by use of methylation specific primers or blocking oligonucleotides, and further wherein e) detecting of the amplificates is carried out by means of a real-time detection probe, as described above.

Preferably, where the subsequent amplification of d) is carried out by means of methylation specific primers, as described above, said methylation specific primers comprise a sequence having a length of at least 9 nucleotides which hybridizes to a treated nucleic acid sequence according to one of SEQ ID NO: 2 to SEQ ID NO: 5 and SEQ ID Nos: 151, 152, 155 and 156 and sequences complementary thereto, wherein the base sequence of said oligomers comprises at least one CpG dinucleotide.

However in the most preferred embodiment it is preferred that at least two sequences are amplified, at least one of which is complementary, reverse complementary or identical to a sequence selected from the group consisting of SEQ ID NO: 163, 164, 171 and 172 and at least one of which is complementary, reverse complementary or identical to a sequence selected from the group consisting SEQ ID NO: 165, 166, 173 and 174. Accordingly, it is further preferred that at least two pairs of primers are used in the amplification. Wherein one pair of primers consists at least two oligonucleotides whose sequences are each reverse complementary, identical, or hybridize under stringent or highly stringent conditions to an at least 18-base-pair long segment of the base sequences of a sequence selected from the group consisting SEQ ID NO: 163, 164, 171 and 172 (and sequences complementary thereto) and wherein one pair of primers consists at least two oligonucleotides whose sequences are each reverse complementary, identical, or hybridize under stringent or highly stringent conditions to an at least 18-base-pair long segment of the base sequences of a sequence selected from the group consisting SEQ ID NO: 165, 166, 173 and 174 and sequences complementary thereto and further wherein the base sequence of said oligomers comprises at least one CpG, tpG or Cpa dinucleotide.

It is also preferred that the methylation status of preselected CpG positions within the nucleic acid sequences comprising SEQ ID NO: 161 and SEQ ID NO: 162 may be analysed by means of methylation specific primers. SEQ ID NO: 159 and 160 comprise SEQ ID NO: 161 and SEQ ID NO: 162 respectively.

Additionally, further methylation specific primers may also be used for the analysis of a gene panel as described above wherein said primers comprise a sequence having a length of at least 9 nucleotides which hybridizes to a treated nucleic acid sequence according to one of SEQ ID NO: 76 to SEQ ID NO: 103 and SEQ ID Nos: 153, 154, 157 and 158 and sequences complementary thereto, wherein the base sequence of said oligomers comprises at least one CpG dinucleotide.

In an alternative most preferred embodiment of the method, the subsequent amplification of d) is carried out in the presence of blocking oligonucleotides, as described above. It is particularly preferred that said blocking oligonucleotides comprise a sequence having a length of at least 9 nucleotides which hybridizes to a treated nucleic acid sequence according to one of SEQ ID NO: 2 to SEQ ID NO: 5 SEQ ID Nos: 151, 152, 155 and 156 and sequences complementary thereto, wherein the base sequence of said oligomers comprises at least one CpG, TpG or CpA dinucleotide.

However in the most preferred embodiment it is preferred that at least two sequences are amplified, at least one of which is complementary, reverse complementary or identical to a sequence selected from the group consisting SEQ ID NO: 163, 164, 171 and 172 and at least one of which is complementary, reverse complementary or identical to a sequence selected from the group consisting SEQ ID NO: 165, 166, 173 and 174. Accordingly it is preferred that the sequence of said blocking oligonucleotides should be identical or complementary to a sequence at least 18 base pairs in length selected from the group consisting of SEQ ID NOs: 163-166 and 171-174 preferably comprising one or more CpG, TpG or CpA dinucleotides. It is also preferred that the methylation status of preselected CpG positions within the nucleic acid sequences comprising SEQ ID NO: 167-170 and 175-178 may be analysed by means of blocker oligonucleotides. SEQ ID NO: 163-166 and 171-174 comprise SEQ ID NO: 167-170 and 175-178 respectively.

Additionally, further blocking oligonucleotides may also be used for the analysis of a gene panel as described above wherein said blocking oligonucleotides comprising a sequence having a length of at least 9 nucleotides which hybridizes to a treated nucleic acid sequence according to one of SEQ ID NO: 76 to SEQ ID NO: 103 and SEQ ID Nos: 153, 154, 157 and 158 and sequences complementary thereto, wherein the base sequence of said oligomers comprises at least one CpG, TpG or CpA dinucleotide.

Step e) of the method, namely the detection of the specific amplificates indicative of the methylation status of one or more CpG positions according to SEQ ID NO: 2-5, SEQ ID NO: 151 to SEQ ID NO: 158, and SEQ ID NO: 76 to SEQ ID NO: 103, and most preferably SEQ ID NO: 2 to SEQ ID NO: 5 and SEQ ID Nos: 151, 152, 155 and 156, or as is most preferred SEQ ID NO: 159 to 162, is carried out by means of real-time detection methods as described above.

Additional embodiments of the invention provide a method for the analysis of the methylation status of at least two promoter/regulatory regions of the gene PITX2 (most preferably SEQ ID NO: 159 and 160) without the need for pre-treatment. Furthermore said method may also be used for the methylation analysis of at least two promoter/regulatory regions of the gene PITX2 and/or regulatory regions thereof and the methylation state of one or more genes selected from the group consisting ABCA8, CDK6, ERBB2, ONECUT2, PLAU, TBC1D3, TFFl and/or regulatory or promoter regions thereof is determined. It is particularly preferred that methylation status of a gene panel selected from the group of gene panels consisting at least two promoter/regulatory regions and/or transcripts of the gene PITX2, PLAU and TFFl; at least two promoter/regulatory regions and/or transcripts of the gene PITX2 and PLAU; at least two promoter/regulatory regions and/or transcripts of the gene PITX2 and TFFl is determined.

In the βrst step of such additional embodiments, the genomic DNA sample is isolated from tissue or cellular sources. Preferably, such sources include cell lines, histological slides, biopsy tissue, body fluids, or breast tumor tissue embedded in paraffin. Extraction may be by means that are standard to one skilled in the art, including but not limited to the use of detergent lysates, sonification and vortexing with glass beads. Once the nucleic acids have been extracted, the genomic double-stranded DNA is used in the analysis.

In a preferred embodiment, the DNA may be cleaved prior to the treatment, and this may be by any means standard in the state of the art, but preferably with methylation-sensitive restriction endonucleases.

In the second step, the DNA is then digested with one or more methylation sensitive restriction enzymes. The digestion is carried out such that hydrolysis of the DNA at the restriction site is informative of the methylation status of a specific CpG dinucleotide.

In the third step, which is optional but a preferred embodiment, the restriction fragments are amplified. This is preferably carried out using a polymerase chain reaction, and said amplificates may carry suitable detectable labels as discussed above, namely fluorophore labels, radionuclides and mass labels.

In the fourth step the amplificates are detected. The detection may be by any means standard in the art, for example, but not limited to, gel electrophoresis analysis, hybridization analysis, incorporation of detectable tags within the PCR products, DNA array analysis, MALDI or ESI analysis.

In the final step of the method the prognosis and/or predicting outcome of endocrine treatment is determined. Preferably, the correlation of the expression level of the genes with the prognosis and/or predicting outcome of endocrine treatment is done substantially without human intervention. Poor prognosis and/or predicting outcome of endocrine treatment is determined by aberrant levels of mRNA and/or protein, and hypermethylation. It is particularly preferred that said hypermethylation is above average or above median of said disease in said specific setting.

It is particularly preferred that the classification of the sample is carried out by algorithmic means.

In one embodiment machine learning predictors are trained on the methylation patterns at the investigated CpG sites of the samples with known status. A selection of the CpG positions which are discriminative for the machine learning predictor are used in the panel. In a particularly preferred embodiment of the method, both methods are combined; that is, the machine learning classifier is trained only on the selected CpG positions that are significantly differentially methylated between the classes according to the statistical analysis.

The development of algorithmic methods for the classification of a sample based on the methylation status of the CpG positions within the panel are demonstrated in the examples.

The disclosed invention provides treated nucleic acids, derived from genomic SEQ ID NO: 1 , SEQ ID NO: 149, SEQ ID NO: 150, SEQ ID NO: 159 to 162 and SEQ ID NO: 60 to SEQ ID NO: 75, wherein the treatment is suitable to convert at least one unmethylated cytosine base of the genomic DNA sequence to uracil or another base that is detectably dissimilar to cytosine in terms of hybridization. The genomic sequences in question may comprise one, or more, consecutive or random methylated CpG positions. Said treatment preferably comprises use of a reagent selected from the group consisting of bisulfite, hydrogen sulfite, disulfite, and combinations thereof. In a preferred embodiment of the invention, the objective comprises analysis of a non-naturally occurring modified nucleic acid comprising a sequence of at least 16 contiguous nucleotide bases in length of a sequence selected from the group consisting of SEQ ID NO: 1 , SEQ ID NO: 149, SEQ ID NO: 150, SEQ ID NO: 159 to 162 and SEQ ID NO: 60 to SEQ ID NO: 75, wherein said sequence comprises at least one CpG, TpA or CpA dinucleotide and sequences complementary thereto. The sequences of SEQ ID NO: 2-5, SEQ ID NO: 151 to SEQ ID NO: 158 AND SEQ ID NO: 76 to SEQ ID NO: 103 provide non- naturally occurring modified versions of the nucleic acid according to SEQ ID NO: 1, SEQ ID NO: 149, SEQ ID NO: 150, SEQ ID NO: 159 to 162 and SEQ ID NO: 60 to SEQ ID NO: 75, wherein the modification of each genomic sequence results in the synthesis of a nucleic acid having a sequence that is unique and distinct from said genomic sequence as follows. For each sense strand genomic DNA, e.g., SEQ ID NO: 1 , four converted versions are disclosed. A first version wherein "C" to "T," but "CpG" remains "CpG" (i.e., corresponds to case where, for the genomic sequence, all "C" residues of CpG dinucleotide sequences are methylated and are thus not converted); a second version discloses the complement of the disclosed genomic DNA sequence (i.e. antisense strand), wherein "C" to "T," but "CpG" remains "CpG" (i.e., corresponds to case where, for all "C" residues of CpG dinucleotide sequences are methylated and are thus not converted). The 'upmethylated' converted sequences of SEQ ID NO: 1 , SEQ ID NO: 149, SEQ ID NO: 150, SEQ ID NO: 163-166 and 171-174 and SEQ ID NO: 60 to SEQ ID NO: 75 correspond to SEQ ID NO: 2-5, SEQ ID NO: 151 to SEQ ID NO: 158, SEQ ID NO: 163 to 170 and SEQ ID NO: 76 to SEQ ID NO: 103 . A third chemically converted version of each genomic sequences is provided, wherein "C" to "T" for all "C" residues, including those of "CpG" dinucleotide sequences (i.e., corresponds to case where, for the genomic sequences, all "C" residues of CpG dinucleotide sequences are unmethylated); a final chemically converted version of each sequence, discloses the complement of the disclosed genomic DNA sequence (i.e. antisense strand), wherein "C" to "T" for all "C" residues, including those of "CpG" dinucleotide sequences (i.e., corresponds to case where, for the complement (antisense strand) of each genomic sequence, all "C" residues of CpG dinucleotide sequences are unmethylated). The 'downmethylated' converted sequences of SEQ ID NO: 1, SEQ ID NO: 149, SEQ ID NO: 150, SEQ ID NO: 163 to 174 and SEQ ID NO: 60 to SEQ ID NO: 75 correspond to SEQ ID NO: 2-5, SEQ ID NO: 151 to SEQ ID NO: 158, SEQ ID NO: 171-178 and SEQ ID NO: 76 to SEQ ID NO: 103 .

The invention further discloses oligonucleotide or oligomer for detecting the cytosine methylation state within genomic or pre-treated DNA, according to SEQ ID NO: 1 , SEQ ID NO:149 to SEQ ID NO: 158, SEQ ID NO: 163-178 and SEQ ID NO: 60 to SEQ ID NO: 103. Said oligonucleotide or oligomer comprising a nucleic acid sequence having a length of at least nine (9) nucleotides which hybridizes, under moderately stringent or stringent conditions (as defined herein above), to a treated nucleic acid sequence according to SEQ ID NO: 2-5, SEQ ID NO: 151 to SEQ ID NO: 158, SEQ ID NO: 163-178 and SEQ ID NO: 76 to SEQ ID NO: 103 and/or sequences complementary thereto, or to a genomic sequence according to SEQ ID NO: 1, SEQ ID NO: 149, SEQ ID NO: 150, SEQ ID NO: 159-162 and SEQ ID NO: 60 to SEQ ID NO: 75 and/or sequences complementary thereto.

Thus, the present invention includes nucleic acid molecules (e.g., oligonucleotides and peptide nucleic acid (PNA) molecules (PNA-oligomers)) that hybridize under moderately stringent and/or stringent hybridization conditions to all or a portion of the sequences SEQ ID NO: 2-5, SEQ ID NO: 151 to SEQ ID NO: 158, SEQ ID NO: 163-178 and SEQ ID NO: 76 to SEQ ID NO: 103 , or to the complements thereof. The hybridizing portion of the hybridizing nucleic acids is typically at least 9, 15, 20, 25, 30 or 35 nucleotides in length. However, longer molecules have inventive utility, and are thus within the scope of the present invention. Preferably, the hybridizing portion of the inventive hybridizing nucleic acids is at least 95%, or at least 98%, or 100% identical to the sequence, or to a portion thereof of SEQ ID NO: 2-5, SEQ ID NO: 151 to SEQ ID NO: 158, SEQ ID NO: 163-178 and SEQ ID NO: 76 to SEQ ID NO: 103 , or to the complements thereof.

Hybridizing nucleic acids of the type described herein can be used, for example, as a primer (e.g., a PCR primer), or a diagnostic and/or prognostic probe or primer. Preferably, hybridization of the oligonucleotide probe to a nucleic acid sample is performed under stringent conditions and the probe is 100% identical to the target sequence. Nucleic acid duplex or hybrid stability is expressed as the melting temperature or Tm, which is the temperature at which a probe dissociates from a target DNA. This melting temperature is used to define the required stringency conditions.

For target sequences that are related and substantially identical to the corresponding sequence of SEQ ID NO: 1, SEQ ID NO: 149, SEQ ID NO: 150, SEQ ID NO: 159-162 and SEQ ID NO: 60 to SEQ ID NO: 75 (such as allelic variants and SNPs), rather than identical, it is useful to first establish the lowest temperature at which only homologous hybridization occurs with a particular concentration of salt (e.g., SSC or SSPE). Then, assuming that 1% mismatching results in a 1 °C decrease in the Tm, the temperature of the final wash in the hybridisation reaction is reduced accordingly (for example, if sequences having > 95% identity with the probe are sought, the final wash temperature is decreased by 5°C). In practice, the change in Tm can be between 0.5°C and 1.5°C per 1% mismatch.

Examples of inventive oligonucleotides of length X (in nucleotides), as indicated by polynucleotide positions with reference to, e.g., SEQ ID NO:1, include those corresponding to sets (sense and antisense sets) of consecutively overlapping oligonucleotides of length X, where the oligonucleotides within each consecutively overlapping set (corresponding to a given X value) are defined as the finite set of Z oligonucleotides from nucleotide positions:

n to (n + (X-I)); where n=l , 2, 3,...(Y-(X-I)); where Y equals the length (nucleotides or base pairs) of SEQ ID NO: 1 (9001); where X equals the common length (in nucleotides) of each oligonucleotide in the set (e.g.,

X=20 for a set of consecutively overlapping 20-mers); and where the number (Z) of consecutively overlapping oligomers of length X for a given SEQ ID NO of length Y is equal to Y-(X-I). For example Z= 9001-19= 8,982 for either sense or antisense sets of SEQ ID NO: 1, where X=20.

Preferably, the set is limited to those oligomers that comprise at least one CpG, TpG or CpA dinucleotide.

Examples of inventive 20-mer oligonucleotides include the following set of oligomers (and the antisense set complementary thereto), indicated by polynucleotide positions with reference to SEQ ID NO: 1 : 1-20, 2-21, 3-22, 4-23, 5-24, and 8,982 -9,001.

Likewise, examples of inventive 25-mer oligonucleotides include the following set of oligomers (and the antisense set complementary thereto), indicated by polynucleotide positions with reference to SEQ ID NO: 1 : 1-25, 2-26, 3-27, 4-28, 5-29, and 8,977-

9,001.

The present invention encompasses, for each of SEQ ID NO: 1-5, SEQ ID NO: 149 to SEQ ID NO: 158, SEQ ID NO: 163-178 and SEQ ID NO: 60 to SEQ ID NO: 103 (sense and antisense), multiple consecutively overlapping sets of oligonucleotides or modified oligonucleotides of length X, where, e.g., X= 9, 10, 17, 20, 22, 23, 25, 27, 30 or 35 nucleotides.

The oligonucleotides or oligomers according to the present invention constitute effective tools useful to ascertain genetic and epi genetic parameters of the genomic sequence corresponding to SEQ ID NO: 1, SEQ ID NO: 149, SEQ ID NO: 150, SEQ ID NO: 159-162 and SEQ ID NO: 60 to SEQ ID NO: 75. Preferred sets of such oligonucleotides or modified oligonucleotides of length X are those consecutively overlapping sets of oligomers corresponding to SEQ ID NO: 1-5, SEQ ID NO: 149 to SEQ ID NO: 158, SEQ ID NO: 163- 178 and SEQ ID NO: 60 to SEQ ID NO: 103 (and to the complements thereof). Preferably, said oligomers comprise at least one CpG, TpG or CpA dinucleotide.

Particularly preferred oligonucleotides or oligomers according to the present invention are those in which the cytosine of the CpG dinucleotide (or of the corresponding converted TpG or CpA dinculeotide) sequences is within the middle third of the oligonucleotide; that is, where the oligonucleotide is, for example, 13 bases in length, the CpG, TpG or CpA dinucleotide is positioned within the fifth to ninth nucleotide from the 5'-end.

The oligonucleotides of the invention can also be modified by chemically linking the oligonucleotide to one or more moieties or conjugates to enhance the activity, stability or detection of the oligonucleotide. Such moieties or conjugates include chromophores, fluorophores, lipids such as cholesterol, cholic acid, thioether, aliphatic chains, phospholipids, polyamines, polyethylene glycol (PEG), palmityl moieties, and others as disclosed in, for example, United States Patent Numbers 5,514,758, 5,574,142, 5,585,481, 5,587,371, 5,597,696 and 5,958,773. The probes may also exist in the form of a PNA (peptide nucleic acid) which has particularly preferred pairing properties. Thus, the oligonucleotide may include other appended groups such as peptides, and may include hybridization-triggered cleavage agents (Krol et al., BioTechniques 6:958-976, 1988) or intercalating agents (Zon, Pharm. Res. 5:539-549, 1988). To this end, the oligonucleotide may be conjugated to another molecule, e.g., a chromophore, fluorophor, peptide, hybridization-triggered cross-linking agent, transport agent, hybridisation-triggered cleavage agent, etc.

The oligonucleotide may also comprise at least one art-recognized modified sugar and/or base moiety, or may comprise a modified backbone or non-natural internucleoside linkage.

The oligonucleotides or oligomers according to particular embodiments of the present invention are typically used in 'sets,' which contain at least one oligomer for analysis of each of the CpG dinucleotides of genomic sequences SEQ ID NO: 1, SEQ ID NO: 149, SEQ ID NO: 150, SEQ ID NO: 163-178 and SEQ ID NO: 60 to SEQ ID NO: 75 and sequences complementary thereto, or to the corresponding CpG, TpG or CpA dinucleotide within a sequence of the treated nucleic acids according to SEQ ID NO: 2-5, SEQ ID NO: 151 to SEQ ID NO: 158, SEQ ID NO: 163-178 and SEQ ID NO: 76 to SEQ ID NO: 103 and sequences complementary thereto. However, it is anticipated that for economic or other factors it may be preferable to analyze a limited selection of the CpG dinucleotides within said sequences, and the content of the set of oligonucleotides is altered accordingly.

Therefore, in particular embodiments, the present invention provides a set of at least two (2) (oligonucleotides and/or PNA-oligomers) useful for detecting the cytosine methylation state of treated genomic DNA (SEQ ID NO: 2-5, SEQ ID NO: 151 to SEQ ID NO: 158, SEQ ID NO: 163-178 and SEQ ID NO: 76 to SEQ ID NO: 103 ), or in genomic DNA (SEQ ID NO: 1, SEQ ID NO: 149, SEQ ID NO: 150, SEQ ID NO: 159-162 and SEQ ID NO: 60 to SEQ ID NO: 75 and sequences complementary thereto). These probes enable diagnosis, and/or classification of genetic and epigenetic parameters of breast cell proliferative disorders. The set of oligomers may also be used for detecting single nucleotide polymorphisms (SNPs) in treated genomic DNA (SEQ ID NO: 2-5, SEQ ID NO: 151 to SEQ ID NO: 158, SEQ ID NO: 163-178 and SEQ ID NO: 76 to SEQ ID NO: 103 ), or in genomic DNA (SEQ ID NO: 1, SEQ ID NO: 149, SEQ ID NO: 150, SEQ ID NO: 159-162 and SEQ ID NO: 60 to SEQ ID NO: 75 and sequences complementary thereto).

In preferred embodiments, at least one, and more preferably all members of a set of oligonucleotides is bound to a solid phase.

In further embodiments, the present invention provides a set of at least two (2) oligonucleotides that are used as 'primer' oligonucleotides for amplifying DNA sequences of one of SEQ ID NO: 2-5, SEQ ID NO: 151 to SEQ ID NO: 158, SEQ ID NO: 163-178 and SEQ ID NO: 76 to SEQ ID NO: 103 and sequences complementary thereto, or segments thereof.

It is anticipated that the oligonucleotides may constitute all or part of an "array" or "DNA chip" (i.e., an arrangement of different oligonucleotides and/or PNA-oligomers bound to a solid phase). Such an array of different oligonucleotide- and/or PNA-oligomer sequences can be characterized, for example, in that it is arranged on the solid phase in the form of a rectangular or hexagonal lattice. The solid-phase surface may be composed of silicon, glass, polystyrene, aluminium, steel, iron, copper, nickel, silver, or gold. Nitrocellulose as well as plastics such as nylon, which can exist in the form of pellets or also as resin matrices, may also be used. An overview of the prior art in oligomer array manufacturing can be gathered from a special edition of Nature Genetics (Nature Genetics Supplement, Volume 21, January 1999, and from the literature cited therein). Fluorescently labeled probes are often used for the scanning of immobilized DNA arrays. The simple attachment of Cy3 and Cy5 dyes to the 5'- OH of the specific probe are particularly suitable for fluorescence labels. The detection of the fluorescence of the hybridized probes may be carried out, for example, via a confocal microscope. Cy3 and Cy5 dyes, besides many others, are commercially available.

It is also anticipated that the oligonucleotides, or particular sequences thereof, may constitute all or part of an "virtual array" wherein the oligonucleotides, or particular sequences thereof, are used, for example, as 'specifiers' as part of, or in combination with a diverse population of unique labeled probes to analyze a complex mixture of analytes. Such a method, for example is described in US 2003/0013091 (United States serial number 09/898,743, published 16 January 2003). In such methods, enough labels are generated so that each nucleic acid in the complex mixture (i.e., each analyte) can be uniquely bound by a unique label and thus detected (each label is directly counted, resulting in a digital read-out of each molecular species in the mixture).

Moreover, an additional aspect of the present invention is a kit comprising, for example: a bisulfite-containing reagent as well as at least at least one oligonucleotide whose sequences are each reverse complementary, identical, or hybridize under stringent or highly stringent conditions to an at least 18-base-pair long segment of the base sequences of a sequence selected from the group consisting SEQ ID NO: 163, 164, 171 and 172 (and sequences complementary thereto) and at least one oligonucleotide whose sequences are each reverse complementary, identical, or hybridize under stringent or highly stringent conditions to an at least 18-base-pair long segment of the base sequences of a sequence selected from the group consisting SEQ ID NO: 165, 166, 173 and 174. Said kit may further comprise at least one oligonucleotide whose sequences in each case correspond, are complementary, or hybridize under stringent or highly stringent conditions to a 18-base long segment of the sequences SEQ ID NO: 2-5, SEQ ID NO: 151-158 and SEQ ID NO: 76 to 103. Said kit may further comprise instructions for carrying out and evaluating the described method. In a further preferred embodiment, said kit may further comprise standard reagents for performing a CpG position- specific methylation analysis, wherein said analysis comprises one or more of the following techniques: MS-SNuPE, MSP, MethyLight®, HeavyMethyl®, COBRA, and nucleic acid sequencing. However, a kit along the lines of the present invention can also contain only part of the aforementioned components. Typical reagents (e.g., as might be found in a typical COBRA-based kit) for COBRA analysis may include, but are not limited to: PCR primers for specific gene (or methylation-altered DNA sequence or CpG island); restriction enzyme and appropriate buffer; gene-hybridization oligo; control hybridization oligo; kinase labeling kit for oligonucleotide probe; and radioactive nucleotides. Additionally, bisulfite conversion reagents may include: DNA denaturation buffer; sulfonation buffer; DNA recovery reagents or kits (e.g., precipitation, ultrafiltration, affinity column); desulfonation buffer; and DNA recovery components.

A last aspect of the present invention is then related to the use of the method according to the present invention, the composition according to the present invention, or the kit according to the present invention for providing a prognosis and/or predicting the outcome of endocrine treatment of a subject with a cell proliferative disorder of the breast tissue.

While the present invention has been described with specificity in accordance with certain of its preferred embodiments, the following examples and figures serve only to illustrate the invention and is not intended to limit the invention within the principles and scope of the broadest interpretations and equivalent configurations thereof.

SEQ ID NO: 6 to 9 provide the nucleic acid sequences of those primers and probes useful to predict the survival of breast cancer patients according to the invention as described in Example 4.

SEQ ID NO: 10 to 12 provide the nucleic acid sequences of primers and probes according to a control gene used in the example 4 and 5.

SEQ ID NO: 13 provides a sub-sequence of SEQ ID NO: 1 , which represents the nucleic acid sequence of the human gene PITX2.

SEQ ID NO: 14 to 17 provide the nucleic acid sequences of those primers and probes useful to predict the survival of breast cancer patients according to the invention as described in example 5.

SEQ ID NO: 21 provides an amino acid sequence of the polypeptide encoded by the gene PITX2. The amino acid sequence of the polypeptide encoded by the gene PITX2 is also illustrated in figure 10.

BRIEF DESCRIPTION OF THE DRAWINGS

Figure 1 illustrates a simplified model of a Stage 1-3 breast tumor wherein primary treatment was surgery (at point 1), followed by adjuvant therapy with Tamoxifen, as an example for an endocrine treatment. The Y axis represents tumor(s) mass (or size), wherein the line '3' indicates the limit of detectability of said tumor mass. The X axis represents time. In a first scenario a patient without relapse during endocrine treatment (4) is shown as remaining below the limit of detectability for the duration of the observation. A patient with relapse of the cancer (5) has a period of disease free survival (2) followed by relapse when the carcinoma mass reaches the level of detectability. Figure 2 shows the result of the assay (QM assay) as described in Example 4: A Kaplan- Meier estimated metastasis-free survival curve for three CpG sites of the PITX2 gene by means of Real-Time methylation specific probe analysis (QM assay). The lower curve shows the proportion of metastasis free patients in the population with above median methylation levels, the upper curve shows the proportion of metastasis free patients in the population with below median methylation levels. The X axis shows the metastasis free survival times of the patients in months, and the Y axis shows the proportion of metastasis free survival patients.

Figure 3 shows the result of the chip hybridization experiment as described in Example 2. A Kaplan-Meier estimated metastasis-free survival curves for two CpG positions of the PITX2 gene by means of methylation specific detection oligonucleotide hybridization analysis. The lower curve shows the proportion of metastasis free patients in the population with above median methylation levels, the upper curve shows the proportion of metastasis free patients in the population with below median methylation levels. The X axis shows the metastasis free survival times of the patients in months, and the Y axis shows the proportion of metastasis free survival patients.

Figure 4 shows the Kaplan-Meier estimated metastasis-free survival curves for two CpG positions of the PITX2 gene by means of methylation specific detection oligonucleotide hybridization analysis. The lower line shows the proportion of metastasis free patients in the population of 55 patients with above median methylation levels, the upper curve shows the proportion of metastasis free patients in the population of 54 patients with below median methylation levels. The X axis shows the metastasis free survival times of the patients in years, and the Y axis shows the proportion of metastasis free survival patients in %. This resulted from a first data set that was achieved in a first study.

Figure 5 shows the Kaplan-Meier estimated metastasis-free survival curves for six different CpG positions located within the preferred region of the PITX2 gene (SEQ ID NO: 13) by means of methylation specific detection oligonucleotide hybridization analysis. The lower line shows the proportion of metastasis free patients in the population of 1 18 patients with above median methylation levels, the upper curve shows the proportion of metastasis free patients in the population of 118 patients with below median methylation levels. The X axis shows the metastasis free survival times of the patients in years, and the Y axis shows the proportion of metastasis free survival patients in %. This resulted from a second data set that was achieved in a second study.

Figure 6 shows the Kaplan-Meier estimated metastasis-free survival curves for 6 different CpG positions located within the preferred region of the PITX2 gene (SEQ ID NO: 13) by means of methylation specific detection oligonucleotide hybridization analysis. This time only a sub-population of 148 patients, characterized by a tumor at grade Gl or G2, was analyzed: The lower curve shows the proportion of metastasis free patients in the population of 74 patients with above median methylation levels, the upper curve shows the proportion of metastasis free patients in the population of 74 patients with below median methylation levels. The X axis shows the metastasis free survival times of the patients in years, and the Y axis shows the proportion of metastasis free survival patients in %. This resulted from a second data set as shown in the Example 2.

Figure 7 shows the Kaplan-Meier estimated metastasis-free survival curves for 4 different CpG positions located within the preferred region of the PITX2 gene (SEQ ID NO: 13) by means of methylation specific detection oligonucleotide hybridization analysis. This time a sub-population of 224 patients, characterized by a tumor of stage 1 or 2 (Tl or T2), was analyzed: The lower curve shows the proportion of metastasis free patients in the population of 112 patients with above median methylation levels, the upper curve shows the proportion of metastasis free patients in the population of 1 12 patients with below median methylation levels. The X axis shows the metastasis free survival times of the patients in years, and the Y axis shows the proportion of metastasis free survival patients in %. This resulted from the second data set that was achieved in the second example.

Figure 8 shows the disease-free survival curves of a combination of two oligonucleotides each from the genes TBCl D3 and CDK6, and one oligonucleotide from the gene PITX2 covering two CpG sites. The black curve shows the proportion of disease free patients in the population with above median methylation scores, the gray curve shows the proportion of disease free patients in the population with below median methylation scores.

Figure 9 shows the plot according to Figure 8 and the classification of the sample set by means of the St. Gallen method. The unbroken lines represent the methylation analysis wherein the black curve shows the proportion of disease free patients in the population with above median methylation scores, the gray curve shows the proportion of disease free patients in the population with below median methylation scores. The broken lines represent the St. Gallen classification of the sample set wherein the black curve shows the disease free survival time of the high risk group and the gray curve shows the disease free survival of the low risk group.

Figure 10 illustrates the amino acid sequence of the polypeptide encoded by the gene PITX2.

Figure 1 1 illustrates the positions of the amplificates sequenced in Example 7. 'A' shows an illustration of the gene with the major exons annotated, 'B' shows annotated mRNA transcript variants and 'C shows CpG rich regions of the gene. The positions of amplificates 1 to 1 1 are shown to the right of the illustrations.

Figure 12 shows the sequencing data of 1 1 amplificates of the gene PITX2 according to Example 7. Each column of the matrices of columns 'A' and 'B' represent the sequencing data for one amplificate. The amplificate number is shown to the left of the matrices. Each row of a matrix represents a single CpG site within the fragment and each column represents an individual DNA sample. The matrices in the column marked 'A' showed below median methylation as measured by QM assays, the matrices in the column marked 'B' showed below median methylation as measured by QM assays. The bar on the left represents a scale of the percent methylation, with the degree of methylation represented by the shade of each position within the column from black representing 100% methylation to light gray representing 0% methylation. White positions represented a measurement for which no data was available.

Figure 13 shows a schematic view of mRNA transcript variants of PITX2, as annotated in the on-line Ensembl database.

Figure 14 shows the Kaplan-Meier estimated disease- free survival curves for a CpG position of the ERBB2 gene by means of Real-Time methylation specific probe analysis according to Example 8. The X axis shows the disease free survival times of the patients in years, and the Y- axis shows the proportion of patients with disease free survival. The black plot shows the proportion of disease free patients in the population with above an optimized cut off point's methylation levels, the gray plot shows the proportion of disease free patients in the population with below an optimized cut off point's methylation levels. Figure 15 shows the Kaplan-Meier estimated metastasis-free survival curves for a CpG position of the ERBB2 gene by means of Real-Time methylation specific probe analysis according to Example 8. The X axis shows the disease free survival times of the patients in years, and the Y- axis shows the proportion of patients with disease free survival. The black plot shows the proportion of disease free patients in the population with above an optimized cut off point's methylation levels, the gray plot shows the proportion of disease free patients in the population with below an optimized cut off point's methylation levels.

Figure 16 shows the Kaplan-Meier estimated disease-free survival curves for a CpG position of the TFFl gene by means of Real-Time methylation specific probe analysis according to Example 8. The X axis shows the disease free survival times of the patients in years, and the Y- axis shows the proportion of patients with disease free survival. The black plot shows the proportion of disease free patients in the population with above an optimized cut off point's methylation levels, the gray plot shows the proportion of disease free patients in the population with below an optimized cut off point's methylation levels.

Figure 17 shows the Kaplan-Meier estimated metastasis-free survival curves for a CpG position of the TFFl gene by means of Real-Time methylation specific probe analysis according to Example 8. The X axis shows the metastasis free survival times of the patients in years, and the Y- axis shows the proportion of patients with metastasis free survival. The black plot shows the proportion of metastasis free patients in the population with above an optimized cut off point's methylation levels, the gray plot shows the proportion of metastasis free patients in the population with below an optimized cut off point's methylation levels.

Figure 18 shows the Kaplan-Meier estimated disease-free survival curves for a CpG position of the PLAU gene by means of Real-Time methylation specific probe analysis according to Example 8. The X axis shows the disease free survival times of the patients in years, and the Y- axis shows the proportion of patients with disease free survival. The black plot shows the proportion of disease free patients in the population with above an optimized cut off point's methylation levels, the gray plot shows the proportion of disease free patients in the population with below an optimized cut off point's methylation levels. Figure 19 shows the Kaplan-Meier estimated metastasis-free survival curves for a CpG position of the PLAU gene by means of Real-Time methylation specific probe analysis according to Example 8. The X axis shows the metastasis free survival times of the patients in years, and the Y- axis shows the proportion of patients with metastasis free survival. The black plot shows the proportion of metastasis free patients in the population with above an optimized cut off point's methylation levels, the gray plot shows the proportion of metastasis free patients in the population with below an optimized cut off point's methylation levels.

Figure 20 shows the Kaplan-Meier estimated disease-free survival curves for a CpG position of the PITX2 gene by means of Real-Time methylation specific probe analysis according to Example 8. The X axis shows the disease free survival times of the patients in years, and the Y- axis shows the proportion of patients with disease free survival. The black plot shows the proportion of disease free patients in the population with above an optimized cut off point's methylation levels, the gray plot shows the proportion of disease free patients in the population with below an optimized cut off point's methylation levels.

Figure 21 shows the Kaplan-Meier estimated metastasis-free survival curves for a CpG position of the PITX2 gene by means of Real-Time methylation specific probe analysis according to Example 8. The X axis shows the metastasis free survival times of the patients in years, and the Y- axis shows the proportion of patients with metastasis free survival. The black plot shows the proportion of metastasis free patients in the population with above an optimized cut off point's methylation levels, the gray plot shows the proportion of metastasis free patients in the population with below an optimized cut off point's methylation levels.

Figure 22 shows the Kaplan-Meier estimated disease-free survival curves for a CpG position of the TBC 1D3 gene by means of Real-Time methylation specific probe analysis according to Example 8. The X axis shows the disease free survival times of the patients in years, and the Y- axis shows the proportion of patients with disease free survival. The black plot shows the proportion of disease free patients in the population with above an optimized cut off point's methylation levels, the gray plot shows the proportion of disease free patients in the population with below an optimized cut off point's methylation levels.

Figure 23 shows the Kaplan-Meier estimated metastasis-free survival curves for a CpG position of the TBCl D3 gene by means of Real-Time methylation specific probe analysis according to Example 8. The X axis shows the metastasis free survival times of the patients in years, and the Y- axis shows the proportion of patients with metastasis free survival. The black plot shows the proportion of metastasis free patients in the population with above an optimized cut off point^'s methylation levels, the gray plot shows the proportion of metastasis free patients in the population with below an optimized cut off point's methylation levels.

Figure 24 shows the Kaplan-Meier estimated disease-free survival curves for a CpG position of the ERBB2 gene by means of Real-Time methylation specific probe analysis according to Example 8. The X axis shows the disease free survival times of the patients in years, and the Y- axis shows the proportion of patients with disease free survival. The black plot shows the proportion of disease free patients in the population with above an optimized cut off point's methylation levels, the gray plot shows the proportion of disease free patients in the population with below an optimized cut off point's methylation levels.

Figure 25 shows the Kaplan-Meier estimated metastasis-free survival curves for a CpG position of the ERBB2 gene by means of Real-Time methylation specific probe analysis according to Example 8. The X axis shows the metastasis free survival times of the patients in years, and the Y- axis shows the proportion of patients with metastasis free survival. The black plot shows the proportion of metastasis free patients in the population with above an optimized cut off point's methylation levels, the gray plot shows the proportion of metastasis free patients in the population with below an optimized cut off point's methylation levels.

Figure 26 shows the Kaplan-Meier estimated disease-free survival curves for a CpG position of the TFFl gene by means of Real-Time methylation specific probe analysis according to Example 8. The X axis shows the disease free survival times of the patients in years, and the Y- axis shows the proportion of patients with disease free survival. The black plot shows the proportion of disease free patients in the population with above an optimized cut off point's methylation levels, the gray plot shows the proportion of disease free patients in the population with below an optimized cut off point's methylation levels.

Figure 27 shows the Kaplan-Meier estimated metastasis- free survival curves for a CpG position of the TFFl gene by means of Real-Time methylation specific probe analysis according to Example 8. The X axis shows the metastasis free survival times of the patients in years, and the Y- axis shows the proportion of patients with metastasis free survival. The black plot shows the proportion of metastasis free patients in the population with above an optimized cut off point's methylation levels, the gray plot shows the proportion of metastasis free patients in the population with below an optimized cut off point's methylation levels.

Figure 28 shows the Kaplan-Meier estimated disease-free survival curves for a CpG position of the PLAU gene by means of Real-Time methylation specific probe analysis according to Example 8. The X axis shows the disease free survival times of the patients in years, and the Y- axis shows the proportion of patients with disease free survival. The black plot shows the proportion of disease free patients in the population with above an optimized cut off point's methylation levels, the gray plot shows the proportion of disease free patients in the population with below an optimized cut off point's methylation levels.

Figure 29 shows the Kaplan-Meier estimated metastasis-free survival curves for a CpG position of the PLAU gene by means of Real-Time methylation specific probe analysis according to Example 8. The X axis shows the metastasis free survival times of the patients in years, and the Y- axis shows the proportion of patients with metastasis free survival. The black plot shows the proportion of metastasis free patients in the population with above an optimized cut off point's methylation levels, the gray plot shows the proportion of metastasis free patients in the population with below an optimized cut off point's methylation levels.

Figure 30 shows the Kaplan-Meier estimated disease-free survival curves for a CpG position of the PITX2 gene by means of Real-Time methylation specific probe analysis according to Example 8. The X axis shows the disease free survival times of the patients in years, and the Y- axis shows the proportion of patients with disease free survival. The black plot shows the proportion of disease free patients in the population with above an optimized cut off point's methylation levels, the gray plot shows the proportion of disease free patients in the population with below an optimized cut off point's methylation levels.

Figure 31 shows the Kaplan-Meier estimated metastasis-free survival curves for a CpG position of the PITX2 gene by means of Real-Time methylation specific probe analysis according to Example 8. The X axis shows the metastasis free survival times of the patients in years, and the Y- axis shows the proportion of patients with metastasis free survival. The black plot shows the proportion of metastasis free patients in the population with above an optimized cut off point's methylation levels, the gray plot shows the proportion of metastasis free patients in the population with below an optimized cut off point's methylation levels.

Figure 32 shows the Kaplan-Meier estimated disease-free survival curves for a CpG position of the PITX2 gene by means of Real-Time methylation specific probe analysis according to Example 8. The X axis shows the disease free survival times of the patients in years, and the Y- axis shows the proportion of patients with disease free survival. The black plot shows the proportion of disease free patients in the population with above an optimized cut off point's methylation levels, the gray plot shows the proportion of disease free patients in the population with below an optimized cut off point's methylation levels.

Figure 33 shows the Kaplan-Meier estimated metastasis-free survival curves for a CpG position of the PITX2 gene by means of Real-Time methylation specific probe analysis according to Example 8. The X axis shows the metastasis free survival times of the patients in years, and the Y- axis shows the proportion of patients with metastasis free survival. The black plot shows the proportion of metastasis free patients in the population with above an optimized cut off point's methylation levels, the gray plot shows the proportion of metastasis free patients in the population with below an optimized cut off point's methylation levels.

Figure 34 shows the Kaplan-Meier estimated disease-free survival curves for a CpG position of the ONECUT gene by means of Real-Time methylation specific probe analysis according to Example 8. The X axis shows the disease free survival times of the patients in years, and the Y- axis shows the proportion of patients with disease free survival. The black plot shows the proportion of disease free patients in the population with above an optimized cut off point's methylation levels, the gray plot shows the proportion of disease free patients in the population with below an optimized cut off point's methylation levels.

Figure 35 shows the Kaplan-Meier estimated metastasis-free survival curves for a CpG position of the ONECUT gene by means of Real-Time methylation specific probe analysis according to Example 8. The X axis shows the metastasis free survival times of the patients in years, and the Y- axis shows the proportion of patients with metastasis free survival. The black plot shows the proportion of metastasis free patients in the population with above an optimized cut off point's methylation levels, the gray plot shows the proportion of metastasis free patients in the population with below an optimized cut off point's methylation levels. Figure 36 shows the Kaplan-Meier estimated disease-free survival curves for a CpG position of the TBCl D3 gene by means of Real-Time methylation specific probe analysis according to Example 8. The X axis shows the disease free survival times of the patients in years, and the Y- axis shows the proportion of patients with disease free survival. The black plot shows the proportion of disease free patients in the population with above an optimized cut off point's methylation levels, the gray plot shows the proportion of disease free patients in the population with below an optimized cut off point's methylation levels.

Figure 37 shows the Kaplan-Meier estimated metastasis-free survival curves for a CpG position of the TBC1D3 gene by means of Real-Time methylation specific probe analysis according to Example 8. The X axis shows the metastasis free survival times of the patients in years, and the Y- axis shows the proportion of patients with metastasis free survival. The black plot shows the proportion of metastasis free patients in the population with above an optimized cut off point's methylation levels, the gray plot shows the proportion of metastasis free patients in the population with below an optimized cut off point's methylation levels.

Figure 38 shows the Kaplan-Meier estimated disease-free survival curves for a CpG position of the ABCA8 gene by means of Real-Time methylation specific probe analysis according to Example 8. The X axis shows the disease free survival times of the patients in years, and the Y- axis shows the proportion of patients with disease free survival. The black plot shows the proportion of disease free patients in the population with above an optimized cut off point's methylation levels, the gray plot shows the proportion of disease free patients in the population with below an optimized cut off point's methylation levels.

Figure 39 shows the Kaplan-Meier estimated metastasis-free survival curves for a CpG position of the ABCA8 gene by means of Real-Time methylation specific probe analysis according to Example 8. The X axis shows the metastasis free survival times of the patients in years, and the Y- axis shows the proportion of patients with metastasis free survival. The black plot shows the proportion of metastasis free patients in the population with above an optimized cut off point's methylation levels, the gray plot shows the proportion of metastasis free patients in the population with below an optimized cut off point's methylation levels. Figure 40 shows the Kaplan-Meier estimated disease-free survival curves for a CpG position of a combination of the TFFl and PLAU genes by means of Real-Time methylation specific probe analysis according to Example 8.The X axis shows the disease free survival times of the patients in years, and the Y- axis shows the proportion of patients with disease free survival. The black plot shows the proportion of disease free patients in the population with above an optimized cut off point's methylation levels, the gray plot shows the proportion of disease free patients in the population with below an optimized cut off point's methylation levels.

Figure 41 shows the Kaplan-Meier estimated metastasis-free survival curves for a CpG position of a combination of the TFFl and PLAU genes by means of Real-Time methylation specific probe analysis according to Example 8. The X axis shows the metastasis free survival times of the patients in years, and the Y- axis shows the proportion of patients with metastasis free survival. The black plot shows the proportion of metastasis free patients in the population with above an optimized cut off point's methylation levels, the gray plot shows the proportion of metastasis free patients in the population with below an optimized cut off point's methylation levels.

Figure 42 shows the Kaplan-Meier estimated disease-free survival curves for a CpG position of a combination of the TFFl and PLAU and PITX2 genes by means of Real-Time methylation specific probe analysis according to Example 8. The X axis shows the disease free survival times of the patients in years, and the Y- axis shows the proportion of patients with disease free survival. The black plot shows the proportion of disease free patients in the population with above an optimized cut off point's methylation levels, the gray plot shows the proportion of disease free patients in the population with below an optimized cut off point's methylation levels.

Figure 43 shows the Kaplan-Meier estimated metastasis-free survival curves for a CpG position of a combination of the TFFl and PLAU and PITX2 genes by means of Real-Time methylation specific probe analysis according to Example 8. The X axis shows the metastasis free survival times of the patients in years, and the Y- axis shows the proportion of patients with metastasis free survival. The black plot shows the proportion of metastasis free patients in the population with above an optimized cut off point's methylation levels, the gray plot shows the proportion of metastasis free patients in the population with below an optimized cut off point's methylation levels. Figure 44 shows the Kaplan-Meier estimated disease-free survival curves for a CpG position of a combination of the PITX2 and TFFl genes by means of Real-Time methylation specific probe analysis according to Example 8. The X axis shows the disease free survival times of the patients in years, and the Y- axis shows the proportion of patients with disease free survival. The black plot shows the proportion of disease free patients in the population with above an optimized cut off point's methylation levels, the gray plot shows the proportion of disease free patients in the population with below an optimized cut off point's methylation levels.

Figure 45 shows the Kaplan-Meier estimated metastasis-free survival curves for a CpG position a combination of the PITX2 and TFFl genes by means of Real-Time methylation specific probe analysis according to Example 8. The X axis shows the metastasis free survival times of the patients in years, and the Y- axis shows the proportion of patients with metastasis free survival. The black plot shows the proportion of metastasis free patients in the population with above an optimized cut off point's methylation levels, the gray plot shows the proportion of metastasis free patients in the population with below an optimized cut off point's methylation levels.

Figure 46 shows the Kaplan-Meier estimated disease-free survival curves for a CpG position of a combination of the PITX2 and PLAU genes by means of Real-Time methylation specific probe analysis according to Example 8. The X axis shows the disease free survival times of the patients in years, and the Y- axis shows the proportion of patients with disease free survival. The black plot shows the proportion of disease free patients in the population with above an optimized cut off point's methylation levels, the gray plot shows the proportion of disease free patients in the population with below an optimized cut off point's methylation levels.

Figure 47 shows the Kaplan-Meier estimated metastasis-free survival curves for a CpG position of a combination of the PITX2 and PLAU genes by means of Real-Time methylation specific probe analysis according to Example 8. The X axis shows the metastasis free survival times of the patients in years, and the Y- axis shows the proportion of patients with metastasis free survival. The black plot shows the proportion of metastasis free patients in the population with above an optimized cut off point's methylation levels, the gray plot shows the proportion of metastasis free patients in the population with below an optimized cut off point's methylation levels.

Figure 48 shows the Kaplan-Meier estimated disease-free survival curves for a CpG position of a combination of the TFFl and PLAU genes by means of Real-Time methylation specific probe analysis according to Example 8. The X axis shows the disease free survival times of the patients in years, and the Y- axis shows the proportion of patients with disease free survival. The black plot shows the proportion of disease free patients in the population with above an optimized cut off point's methylation levels, the gray plot shows the proportion of disease free patients in the population with below an optimized cut off point's methylation levels.

Figure 49 shows the Kaplan-Meier estimated metastasis-free survival curves for a CpG position of a combination of the TFFl and PLAU genes by means of Real-Time methylation specific probe analysis according to Example 8. The X axis shows the metastasis free survival times of the patients in years, and the Y- axis shows the proportion of patients with metastasis free survival. The black plot shows the proportion of metastasis free patients in the population with above an optimized cut off point's methylation levels, the gray plot shows the proportion of metastasis free patients in the population with below an optimized cut off point's methylation levels.

Figure 50 shows the Kaplan-Meier estimated disease-free survival curves for a CpG position of a combination of the TFFl and PLAU and PITX2 genes by means of Real-Time methylation specific probe analysis according to Example 8. The X axis shows the disease free survival times of the patients in years, and the Y- axis shows the proportion of patients with disease free survival. The black plot shows the proportion of disease free patients in the population with above an optimized cut off point's methylation levels, the gray plot shows the proportion of disease free patients in the population with below an optimized cut off point's methylation levels.

Figure 51 shows the Kaplan-Meier estimated metastasis-free survival curves for a CpG position of a combination of the TFFl and PLAU and PITX2 genes by means of Real-Time methylation specific probe analysis according to Example 8. The X axis shows the metastasis free survival times of the patients in years, and the Y- axis shows the proportion of patients with metastasis free survival. The black plot shows the proportion of metastasis free patients in the population with above an optimized cut off point's methylation levels, the gray plot shows the proportion of metastasis free patients in the population with below an optimized cut off point's methylation levels.

Figure 52 shows the Kaplan-Meier estimated disease-free survival curves for a CpG position of a combination of the PITX2 and TFFl genes by means of Real-Time methylation specific probe analysis according to Example 8. The X axis shows the disease free survival times of the patients in years, and the Y- axis shows the proportion of patients with disease free survival. The black plot shows the proportion of disease free patients in the population with above an optimized cut off point's methylation levels, the gray plot shows the proportion of disease free patients in the population with below an optimized cut off point's methylation levels.

Figure 53 shows the Kaplan-Meier estimated metastasis-free survival curves for a CpG position of a combination of the PITX2 and TFFl genes by means of Real-Time methylation specific probe analysis according to Example 8. The X axis shows the metastasis free survival times of the patients in years, and the Y- axis shows the proportion of patients with metastasis free survival. The black plot shows the proportion of metastasis free patients in the population with above an optimized cut off point's methylation levels, the gray plot shows the proportion of metastasis free patients in the population with below an optimized cut off point's methylation levels.

Figure 54 shows the Kaplan-Meier estimated disease-free survival curves for a CpG position of a combination of the PITX2 and PLAU genes by means of Real-Time methylation specific probe analysis according to Example 8. The X axis shows the disease free survival times of the patients in years, and the Y- axis shows the proportion of patients with disease free survival. The black plot shows the proportion of disease free patients in the population with above an optimized cut off point's methylation levels, the gray plot shows the proportion of disease free patients in the population with below an optimized cut off point's methylation levels.

Figure 55 shows the Kaplan-Meier estimated metastasis-free survival curves for a CpG position of a combination of the PITX2 and PLAU genes by means of Real-Time methylation specific probe analysis according to Example 8. The X axis shows the metastasis free survival times of the patients in years, and the Y- axis shows the proportion of patients with metastasis free survival. The black plot shows the proportion of metastasis free patients in the population with above an optimized cut off point's methylation levels, the gray plot shows the proportion of metastasis free patients in the population with below an optimized cut off point's methylation levels.

Figure 56 shows a scatter plot of matched pair PET and fresh frozen tissues analyzed using PITX2 gene assay 1 according to Example 8. Quantitative methylation CT scores of PET samples are shown on the Y-axis, and quantitative methylation CT scores of fresh frozen samples are shown on the X-axis. The association between the paired samples is 0.81 (Spearman's rho). This analysis is based on n=89 samples.

Figure 57 shows the Disease free survival (DFS) of randomly selected ER+, NO, untreated patient population in Kaplan-Meier survival plot according to Example 8. Proportion of disease free patients is shown on the Y-axis and time in years is shown on the X-axis. 139 events were observed (observed event rate=33%). Disease free survival after 5 years: 74.5% [70.3%, 78.9%], after 10 years 59.8% [54.2%, 66%]. 95% confidence intervals are plotted.

Figure 58 shows the distribution of follow-up times in ER+, NO, untreated population according to Example 8. Frequency is shown on the Y-axis and time in months is shown on the X-axis. The figure on the left shows patients with event (all kinds of relapses). Mean follow-up time 45.8 months (standard deviation=31), median=38 (range=[2, 123]). The figure on the right shows censored patients. Mean follow up time 93 months (standard deviation=35.6), median=94 (range=[l, 190]).

Figure 59 shows the Disease free survival (DFS) of ER+, NO, TAM treated population in Kaplan-Meier plot according to Example 8. Proportion of disease free patients is shown on the Y-axis and time in years is shown on the X-axis. 56 events were observed (observed event rate=10 %). DFS after 5 years: 92.4% [90%, 94.9%], after 10 years: 82.1% [77.3%,87.2%]. 95% confidence intervals are plotted.

Figure 60 shows the distribution of follow-up times in ER+, NO, untreated population according to Example 8. Frequency is shown on the Y-axis and time in months is shown on the X-axis. The figure on the left shows patients with all events (all kinds of relapses). Mean follow-up time 47.9 months (standard deviation=24.4), median=45 (range=[2, 98]). The figure on the right shows censored patients. Mean follow up time 65.3 months (standard deviation=31.6), median=64 (range=[0, 158]).

Figure 61 shows the ROC plot at different times for marker model 3522 (Assay 1 ) and 2265 on ER+NO TAM treated population according to Example 8. Figure A shows the plot at 60 months, figure B shows the plot at 72 months, figure C shows the plot at 84 months and figure D shows the plot at 96 months. Only distant metastasis are defined as events. Sensitivity (proportion of all relapsed patients in poor prognostic group) shown on the X-axis and specificity (proportion of all relapse free patients in good prognostic group) shown on the Y- axis are calculated from KM estimates, and the estimated area under the curve (AUC) is calculated. Values for median cut off (triangle) and best cut off (diamond, 0.32 quantile) are plotted.

Figure 62 shows the ROC plot at different times for marker model 3522 (Assay 1) alone on ER+NO TAM treated population according to Example 8. Figure A shows the plot at 60 months, figure B shows the plot at 72 months, figure C shows the plot at 84 months and figure D shows the plot at 96 months. Only distant metastasis are defined as events. Sensitivity (proportion of all relapsed patients in poor prognostic group) shown on the X-axis and specificity (proportion of all relapse free patients in good prognostic group) shown on the Y- axis are calculated from KM estimates, and the estimated area under the curve (AUC) is calculated. Values for median cut off (triangle) and best cut off (diamond, 0.42 quantile) are plotted.

Figure 63 shows the ROC plot at different times for marker model 2265 on ER+NO TAM treated population according to Example 8. Figure A shows the plot at 60 months, figure B shows the plot at 72 months, figure C shows the plot at 84 months and figure D shows the plot at 96 months. Only distant metastasis are defined as events. Sensitivity (proportion of all relapsed patients in poor prognostic group) shown on the X-axis and specificity (proportion of all relapse free patients in good prognostic group) shown on the Y-axis are calculated from KM estimates for different thresholds (= 5, 6, 7 , 8 years) and the estimated area under the curve (AUC) is calculated. Values for median cut off (triangle) and best cut off (diamond, 0.78 quantile) are plotted. Figure 64 shows the ROC plot at different times for marker model 2395 on ER+NO TAM treated population according to Example 8. Figure A shows the plot at 60 months, figure B shows the plot at 72 months, figure C shows the plot at 84 months and figure D shows the plot at 96 months. Only distant metastasis are defined as events. Sensitivity (proportion of all relapsed patients in poor prognostic group) shown on the X-axis and specificity (proportion of all relapse free patients in good prognostic group) shown on the Y-axis are calculated from KM estimates for different thresholds (= 5, 6, 7 , 8 years), and the estimated area under the curve (AUC) is calculated. Values for median cut off (triangle) and best cut off (diamond, 0.77 quantile) are plotted.

Figure 65 shows the stability of the assignment of one certain patient to the bad or good outcome group, the left hand figure shows model marker panel PITX2 (Assay 1) plus TFFl and the right hand figure shows model marker panel PITX2 (Assay 1) alone. The plot illustrates in how many crossvalidation replicates each patient get's assigned to group 1 (light gray) or group 2 (dark gray).

Figure 66 shows the validation of a second promoter region of the gene PITX2 that was analyzed in more detail according to Example 9.

Figure 67 shows a genetic map of the gene PITX2 (see example 9)

Table 1 : Genomic sequences and treated variants thereof according to the invention

* SEQ ID NO 159 comprises all of SEQ ID NO 161, SEQ ID NO: 160 comprises all of SEQ ID NO: 162, this also applies to the converted sequences.

EXAMPLES

EXAMPLE l : Study 1

The first study was based on a population of 109 patients, comprising patients of both nodal statuses NO and N+. All patients were ER+ (estrogen receptor positive). All patients received Tamoxifen monotherapy immediately after surgery or diagnosis. The samples were analyzed using the applicant's chip technology with two chip panels representing 1 17 candidate genes. For further details see examples in the published patent applications WO 04/035803 and EP 03 090 432.0, which are hereby incorporated by reference. In this study one of the most significant marker gene was PITX2. The methylation status of PITX2, coding for a transcription factor, was statistically significantly correlated with disease-free survival of patients undergoing adjuvant Tamoxifen treatment. This was calculated using the Cox regression model taking into account the nodal status of the patient at the time of diagnosis.

The result from this study - with respect to PITX2 - is illustrated in Figure 4. The X axis shows the metastasis free survival times of the patients in years, and the Y axis shows the proportion of metastasis free survival patients in %. Amongst the 54 patients (upper line) with below median methylation levels have a significantly longer metastasis free survival time than the 55 patients with above median methylation levels (lower line). To illustrate the result, at 10 years after surgery combined with Tamoxifen monotherapy, more than 75% of the patients with below median methylation in PITX2 were still metastasis free, as compared to less than 60% of the patients with above median methylation in PITX2.

As the survival of a breast cancer patient is known to also be correlated to the patient's nodal status, the differentiating power of the marker in this mixed population is expected to be less than in a homogenous population. Another study was performed to analyze whether the same marker can be identified independently, in a completely different set of patient samples and also to characterize the differential power towards predicting survival for a sub-group of patients, all being NO.

EXAMPLE 2 : Study 2

The second study was based on samples from 236 patients from 5 different sample providers, wherein all patients were NO (nodal status negative), and older than 35 years. In all cases surgery was performed before 1998. All patients were ER+ (estrogen receptor positive), and the tumors were graded to be Tl-3, Gl -3. In this study all patients received Tamoxifen directly after surgery, and the outcome was assessed according to the length of disease-free survival. In order to be as representative as possible for the final target group, the patients and their tumor samples had to fulfill the following criteria:

The range and median follow-up of patients were the following:

Median: 64.5 months

Range: 3 months to 142 months

(calculated based on patients who were disease-free at end of observation time).

Analysis of the methylation patterns of patient samples treated with Tamoxifen as an adjuvant therapy immediately following surgery (see Figure 1) is shown in the plots according to

Figures 5 to 7. For the amplifϊcate, the mean methylation over 4 oligo-pairs for that amplifϊcate was calculated and the population split into groups according to their mean methylation values, wherein one group was composed of individuals with a methylation score higher than the median and a second group composed of individuals with a methylation score lower than the median.

The primer oligonucleotides used to generate the amplifϊcate, that was analyzed in the array experiment were:

Array Primer PITX2 Q21 : GTAGGGGAGGGAAGTAGATGT (SEQ ID NO: 22)

Array Primer PITX2 R23: TCCTCAACTCTACAAACCTAAAA (SEQ ID NO: 23)

The corresponding genomic region of said amplifϊcate is given in SEQ ID NO: 13.

The sequences of the oligonucleotides used in this array experiment were the following: SEQ ID NO 24: AGTCGGGAGAGCGAAA SEQ ID NO 25: AGTTGGGAGAGTGAAA SEQ ID NO 26: AAGAGTCGGGAGTCGGA SEQ ID NO 27: AAGAGTTGGGAGTTGGA SEQ ID NO 28: GGTCGAAGAGTCGGGA SEQ ID NO 29: GGTTGAAGAGTTGGGA SEQ ID NO 30: ATGTTAGCGGGTCGAA SEQ ID NO 31: TAGTGGGTTGAAGAGT

When the data derived from analyzing 6 different CpG sites, located within the preferred amplified region of the PITX2 gene by means of methylation specific detection oligonucleotide hybridization analysis were plotted as Kaplan-Meier estimated metastasis-free survival curves, it can be seen that the differential power of the marker PITX2 increased with selecting for NO patients. This is shown in figures 5 to 7. The X axis shows the metastasis free survival times of the patients in years, and the Y axis shows the proportion of metastasis free survival patients in %. The lower curve shows the proportion of metastasis free patients in the population with above median methylation levels, and the upper curve shows the proportion of metastasis free patients in the population with below median methylation levels.

For example, as illustrated in figure 5, 10 years after surgery only about 65% of the patients of the 118 patients with the higher methylation status are metastasis free, whereas about 90% of the 118 patients with lower methylation status are metastasis free.

As illustrated in Figure 6, the analogous Kaplan-Meier analysis for a sub-population of 148 patients, characterized by a tumor at stage Gl or G2 this differential power increases again: 10 years after surgery only about 60% of the 74 patients with the higher methylation status are metastasis free, whereas about 95% of the 74 patients with lower methylation status are metastasis free.

Figure 7 illustrates how the survival is also correlated to the tumor stage at surgery by showing the analogous Kaplan-Meier analysis for a sub-population of 150 patients, characterized by a tumor stage of Tl or T2: The number of patients with 10 years MFS is about 68% of patients of the 1 12 with the higher methylation status, whereas about 95% of the 112 patients with lower methylation status are metastasis free.

EXAMPLE 3: The accuracy of the differentiation between the different groups was further increased by combining multiple oligonucleotides from different genes. As described in the text it was recognized that adding additional informative markers to the analysis could potentially increase the prognostic power of a survival test. Therefore it was calculated how a combination of two methylation specific oligonucleotides each from the genes TBC 1D3 and CDK6, and one oligonucleotide from the gene PITX2 would differentiate the groups of good or bad prognosis. The result is shown in figure 8 as the according Kaplan-Meier curve.

Figure 9 shows -on top of Figure 8- the classification of the patients from the sample set by means of the St. Gallen method (the current method of choice for estimating disease free survival), thereby showing the improved effectiveness of methylation analysis over current methods, in particular post 80 months.

EXAMPLE 4: Real time quantitative methylation analysis

Genomic DNA was analyzed using the Real Time PCR technique after bisulfite conversion. In this analysis four oligonucleotides were used in each reaction. Two non methylation specific PCR primers were used to amplify a segment of the treated genomic DNA containing a methylation variable oligonucleotide probe binding site. Two oligonucleotide probes competitively hybridize to the binding site, one specific for the methylated version of the binding site, the other specific to the unmethlyated version of the binding site. Accordingly, one of the probes comprises a CpG at the methylation variable position (i.e. anneals to methylated bisulphite treated sites) and the other comprises a TpG at said position (i.e. anneals to unmethylated bisulphite treated sites). Each species of probe is labeled with a 5' fluorescent reporter dye and a 3' quencher dye wherein the CpG and TpG oligonucleotides are labeled with different dyes.

The reactions are calibrated by reference to DNA standards of known methylation levels in order to quantify the levels of methylation within the sample. The DNA standards were composed of bisulfite treated phi29 amplified genomic DNA (i.e. unmethlyated), and/or phi29 amplified genomic DNA treated with Sssl methylase enzyme (thereby methylating each CpG position in the sample), which is then treated with bisulfite solution. Seven different reference standards were used with 0%, (i.e. phi29 amplified genomic DNA only), 5%, 10%, 25%, 50%, 75% and 100% (i.e. phi29 Sssl treated genomic only). The amount of sample DNA amplified is quantified by reference to the gene (β-actin (ACTB)) to normalize for input DNA. For standardization the primers and the probe for analysis of the ACTB gene lack CpG dinucleotides so that amplification is possible regardless of methylation levels. As there are no methylation variable positions, only one probe oligonucleotide is required.

The following oligonucleotides were used in the reaction to amplify the control amplificate:

Control Primerl : TGGTGATGGAGGAGGTTTAGTAAGT (SEQ ID NO: 10)

Control Primer2: AACCAATAAAACCTACTCCTCCCTTAA (SEQ ID NO: 11)

Control Probe: 6FAM-ACCACCACCCAACACACAATAACAAACACA-TAMRA or

Dabcyl (SEQ ID NO: 12)

The nucleic acid sequence of the gene PITX2 is given in (SEQ ID NO: 1), after treatment with bisulfite two different strands are generated, and each of the strands is represented twice, once in a prior to treatment methylated version (SEQ ID NO: 2 and 3) and once in the prior to treatment unmethylated form (SEQ ID NO: 4 and 5), which are characterized as containing no cytosine bases (despite of those 5' adjacent to a guanine and methylated before treatment). The following primers are used to generate an amplificate within the PITX2 sequence comprising the CpG sites of interest:

Primers for PITX2 bisulfite amplificate length: 144 bp PITX2: GTAGGGGAGGGAAGTAGATGTT (SEQ ID NO: 6) PITX2: TTCTAATCCTCCTTTCCACAATAA (SEQ ID NO: 7)

The genomic region according to the generated amplificate of 144 bp in length is given in

SEQ ID NO: 18.

Probes:

PITX2cgl : FAM-AGTCGGAGTCGGGAGAGCGA-Darquencher (SEQ ID NO: 8)

As an alternative quencher TAMRA was also used in additional experiments:

FAM-AGTCGGAGTCGGGAGAGCGA-TAMRA

PITX2tgl : YAKIMA YELLOW-AGTTGGAGTTGGGAGAGTGAAAGGAGA-

Darquencher (SEQ ID NO: 9)

In additional experiments we also used :

VIC- AGTTGGAGTTGGGAGAGTGAAAGGAGA -TAMRA The extent of methylation at a specific locus was determined by the following formula: methylation rate = 100 * I (CG) / (I(CG) + 1(TG))

(I = Intensity of the fluorescence of CG-probe or TG-probe)

PCR components were ordered from Eurogentec:

3 mM MgC12 buffer, 10x buffer, Hotstart TAQ

Program (45 cycles): 95 °C, 10 min; 95 °C, 15 sec; 62 °C, 1 min

This assay was performed on 236 samples identical to those used in Example 2. The result is shown in Figure 2. Figure 2 shows the Kaplan-Meier estimated disease-free survival curves for 3 CpG positions of the PITX2 gene by means of Real-Time methylation specific probe analysis, as described above. The lower curve shows the proportion of disease free patients in the population with above median methylation levels, the upper curve shows the proportion of disease free patients in the population with below median methylation levels. The X axis shows the disease free survival times of the patients in months, and the Y- axis shows the proportion of disease free survival patients. The p-value (probability that the observed distribution occurred by chance) was calculated as 0.0031, thereby confirming the data obtained by means of array analysis.

For comparison, figure 3 illustrates the result from the array analysis of said gene, according to the chip hybridization experiment described in Example 2, wherein detection oligos were used (for details see EP 03 090 432.0, which is incorporated by reference). The p-value (probability that the observed distribution occurred by chance) was calculated as 0.001 1.

EXAMPLE 5

Another QM assay was developed, which also performed very well. The following PITX2 specific oligonucleotides were employed to generate an amplificate of 164 bp. The oligonucleotides are specific for three co-methylated CpG positions:

Primers for PITX2 bisulfite amplificate with a length of 162 bp :

PITX2: AACATCTACTTCCCTCCCCTAC (SEQ ID NO: 14)

PITX2: GTTAGTAGAGATTTTATTAAATTTTATTGTAT (SEQ ID NO: 15)

The genomic region according to the generated amplificate of 162 bp in length is given in

SEQ ID NO: 19. Probes (from ABI):

PITX2-IIcgl : FAM-TTCGGTTGCGCGGT-MGBNQF (SEQ ID NO: 16)

PITX2-IItgl : VIC-TTTGGTTGTGTGGTTG- MGBNQF (SEQ ID NO: 17)

The extent of methylation at a specific locus was determined by the following formula: methylation rate = 100 * I (CG) / (I(CG) + 1(TG))

(I = Intensity of the fluorescence of CG-probe or TG-probe)

PCR components were ordered from Eurogentec : 2,5 mM MgC12 buffer, 1 Ox buffer, Hotstart

TAQ

Program (45 cycles): 95 °C, 10 min; 95 °C, 15 sec; 60 °C, 1 min

EXAMPLE 6: LOH analysis Patient material

The material to be used in this study, consists of fresh frozen healthy breast tissue, fresh frozen breast tumor tissue from untreated breast cancer patients (follow up over >10 years) and samples from tamoxifen treated patients (follow up over >10 years from Tamoxifen treatment). Aliquots of DNA from these micro-dissected lesions are used as the source template for PCR-based LOH (Loss of heterozygosity) analysis. All tumor samples were derived from ER+ node negative patients.

LOH analysis

DNA from all tissue samples is subjected to PCR-based LOH analysis using two 4q25-26 markers (D4S1284 and D4S406). These markers define a region on chromosome 4 comprising the gene PITX2 gene said region but being more than 8.5 kbp distant of a region previously shown to undergo LOH in breast carcinomas [Cancer Research 59, 3576-3580, August 1, 1999].

DNA Extraction

Extract DNA from samples using the Wizzard Kit (Promega).

PCR reaction

See Clin. Cancer Res., 5: 17-23, 1999 for further details.

Analyze each sample by means of single-plex PCR using the following primers: D4S406

Forward primer: GAAAGGCAGAGTCATAACAGGAAG (SEQ ID NO: 32)

Reverse primer: TAAGGATAGAGTGATTTCCAAGAAAG (SEQ ID NO: 33)

PCR product size:205 (bp)

GenBank Accession: Zl 6728

D4S1284

Forward primer: CTTATCTGACAACAAGCGAGTATG (SEQ ID NO: 34)

Reverse primer: CAATTATTGTATTGTAGCATCGGAG (SEQ ID NO: 35)

PCR product size: 172 (bp)

GenBank Accession: L14168

Synthesize forward primers with either a fluorescent FAM tag (D4S1284) or a fluorescent

TET tag (D4S406) at the 5' end.

Prepare a suitable quantity of nucleotide mixture according to Table 2.

Aliquot 1 μl of each DNA sample into separate PCR tubes, add 9 μl reaction mixture according to Table 3 and thermal cycle according to the following conditions.

Thermal cycling conditions:

95°C for 15 min; 39 cycles: 95°C for 1 min; 55°C for 0:45; 72°C for 1 :15; and 72°C for 10 min

Gel electrophoresis

Horizontal ultrathin, high throughput fluorescence-based DNA fragment gel electrophoresis is the preferred technique to separate and analyze the PCR-generated alleles. Combine one microliter of amplified material with 2 μl formamide loading dye (APB) prior to electrophoresis. Add ROX 350 fluorescent size markers (0.7 μl; ABI) to amplified tumor DNA to allow sizing of alleles. Heat samples to 95°C, load on 70 μm, 5% horizontal polyacrylamide gel and electrophorese for 1 h and 15 min at 30 W in 1 x TBE.

Data may be collected as commonly known in the art (see for example Clin. Cancer Res., 5: 17-23, 1999).

To determine whether allelic deletion had occurred at individual markers, calculate allelic ratios and express as a percentage of loss of intensity for the treated and untreated tumor samples compared with the corresponding normal samples (D-value) after normalization. When the allelic ratio in the tumor DNA is reduced by greater than 40% (DO.40) from that found in the normal DNA, the sample is denoted as having LOH at that locus.

Table 2: Nucleotide Mix

10 μi dATP, 10 mM

10 μl dGTP, 10 mM

10 μi dTTP, 10 mM

2.0 μi dCTP, 10 mM

288 μl DEPC-treated H₂O

Table 3: Reaction mixture

1.0 μl Taq Buffer

0.8 μi Reduced nucleotide mixture

0.2 μl Forward primer, 20 μM

0.2 μl Reverse primer, 20 μM

6.6 μl DEPC treated H₂O

0.1 μl alpha-³²P dCTP

0.1 μl AmpliTaq Gold

Polymerase

Total volume = 9 μl

Example 7: Sequencing of gene PITX2

Sequencing of the gene PITX2 was carried out in order to confirm that co-methylation of CpG positions correlated across all exons. For bisulfite sequencing amplification primers were designed to cover 11 sequences within the gene PITX2, see Figure 1 1 for further details. Sixteen samples analyzed in Example 4 were utilized for amplicon production. Each sample was treated with sodium bisulfite and sequenced. Sequence data was obtained using ABI 3700 sequencing technology. Obtained sequence traces were normalized and percentage methylation calculated using the Applicant's proprietary bisulphite sequence sequencing trace analysis program (See WO 2004/000463 for further information). Samples

Eight samples displayed hypermethylation and eight samples displayed hypomethylation in analysis using the QM assay as described in Example 4.

Amplification

Fragments of interest were amplified using the following conditions

PCR Reaction solution :

Taq 5U/μl 0,2 dNTPs 25mM each 0,2

10x buffer 2,5 water 10,1 primer (6,25μM) 2

DNA (WuI) 10

Cycling conditions:

15min 95°C; 30s 95°C; 30s 58°C; l :30min 72°C (40 cycles)

Table 4: Primers and Amplificates

Sequencing

Only one primer was used for sequencing with one exception: Amplificate Number 2 was sequenced using both forward and reverse primer.

ExoSAP-IT Reaction solution: 4μl PCR product + 2μl ExoSAP-IT 45min/37°C and 15min/95°C

Cycle sequencing: 1 μl BigDye v.1.1 1 μl water 4 μl Sanger buffer

4 μl dNTP mix (0,025 mM each)

lOμl +

5 μl Primer (2pmol/μl) +

6μl ExoSAP-IT product

Cycling

2 min 96°C, 26 cycles a (30 s/96°C, 15s/55°C, 4 min/60°C)

Purification

A 96 well MultiScreen (Millipore) plate was filled with Sephadex G50 (Amersham) using an appropriate admeasure device. 300μl water were added to each well and incubated 3h at 4°C.

Water was removed by spinning for 5minutes at 91Og. Cycle sequencing product was loaded to the plate and purified by spinning for 5min at 91Og. lOμl of formamide was added to each eluate.

Results:

All PCRs yielded a product.

Figure 12 provides matrices produced from bisulfite sequencing data analyzed by the applicant's proprietary software (See WO 2004/000463 for further information). Each column of the matrices of columns 'A' and 'B' represent the sequencing data for one amplificate. The amplificate number is shown to the left of the matrices. Each row of a matrix represents a single CpG site within the fragment and each column represents an individual DNA sample.

The matrices in the column marked 'A' showed below median methylation as measured by QM assays (see example 4), the matrices in the column marked 'B' showed below median methylation as measured by QM assays.

The bar on the left represents a scale of the percent methylation, with the degree of methylation represented by the shade of each position within the column from black representing 100% methylation to light gray representing 0% methylation. White positions represented a measurement for which no data was available.

Bisulfite sequencing indicated differential methylation of CpG sites between the two selected classes of samples, furthermore co-methylation was observed across the gene. In particular amplificates 4 to 7 showed a high level of differential methylation between the two analyzed groups.

EXAMPLE 8

To validate the most promising marker panels from the set of ERBB2, TFFl, PLAU, PITX2, ONECUT, TBCl D3, and ABCA8 Real-Time assays were designed and optimized in order to provide assays of optimum accuracy. The assays were run on a combination of paraffin embedded tissue (hereinafter also referred to as PET) and fresh frozen tissue samples. DNA derived from PET is often of 'lower quality' (e.g., higher degree of DNA fragmentation and low DNA yield from samples), thus confirmation of assay results on PET demonstrates the robustness of the assay and increased utility of the marker.

Quantitative methylation assays were designed for the genes ERBB2, TFFl, PLAU, PITX2, ONECUT, TBC 1D3, and ABCA8 and tested using a sample set of 415 estrogen receptor positive node negative samples untreated breast cancer patients and 541 estrogen receptor positive node negative samples tamoxifen treated samples. Approximately 100 of these samples were previously analyzed in the microarray study.

The QM assay (= Quantitative Methylation Assay) is a Real-time PCR based method for quantitative DNA methylation detection. The assay principle is based on non-methylation specific amplification of the target region and a methylation specific detection by competitive hybridization of two different probes specific for the CG or the TG status, respectively. For the present study, TaqMan probes were used that were labeled with two different fluorescence dyes ("FAM" for CG specific probes, "VIC" for TG specific probes) and were further modified by a quencher molecule ("TAMRA" or "Minor Groove Binder/non-fluorescent quencher").

Evaluation of the QM assay raw data is possible with two different methods:

1. Measuring absolute fluorescence intensities (FI) in the logarithmic phase of amplification

2. Difference in threshold cycles (Ct) of CG and TG specific probe. Results of this study were generated by using the Ct method.

In the following series of quantitative methylation assays the amount of sample DNA amplified is quantified by reference to the gene GSTPl to normalize for input DNA. For standardization, the primers and the probe for analysis of the GSTPl gene lack CpG dinucleotides so that amplification is possible regardless of methylation levels. As there are no methylation variable positions, only one probe oligonucleotide is required.

Sample Sets

ER+ NO Untreated Population

To demonstrate that the markers identified have a strong prognostic component, ER+ NO tumor samples from patients not treated with any adjuvant therapy were analyzed. Markers that are able to show a significant survival difference in this population are considered to be prognostic. All 508 samples of this set were obtained from an academic collaborator as cell nuclei pellets (fresh frozen samples). The sample population can be divided into two subsets:

One with 415 randomly selected samples (from both censored and relapsing patients), representing a population with a natural distribution of relapses, and additional 93 samples from relapsing patients only. The latter samples were used for sensitivity/specificity analyses only.

FIGURE 57 shows the disease-free survival of the randomly selected population in a Kaplan- Meier plot and FIGURE 58 the distribution of follow-up times for the relapsed and censored patients in histograms. TABLE 6 lists the number of events broken down by different kinds of relapse. In summary, the survival of this population is comparable to the expected one from the literature. ER+ NO TAM treated Population

One intended target population of the invention is patients with ER+ NO tumors that are treated with hormone therapy. To check the performance of the marker candidates in this population, 589 samples from ER+ NO tumors from patients treated with Tamoxifen were analyzed. All samples were received as Paraffin-embedded tissues (PET). Three to ten 10 μm sections were provided.

In addition, for 89 PET patient samples matching fresh frozen samples from the same tumor were included into the study as controls. As these samples were already used in phase 1 , they allowed for two kinds of concordance studies :

• Chip versus QM assay

• Fresh frozen versus PET samples

Samples of the ER+, NO, TAM treated population were received from eight different providers. Altogether 589 samples were processed, 48 of which had to be excluded from the study due to various reasons (e.g., two samples from same tumor, samples from patients that did not fulfill inclusion criteria etc.).

FIGURE 59 shows the disease-free survival of the total population in a Kaplan-Meier plot and FIGURE 60 the distribution of follow-up times for the relapsed and censored patients in histograms. TABLE 5 lists the number of events broken down by different kinds of relapse. In summary, the survival of this population (82.1 % after 10 years) is comparable to the expected one from the literature (79.2 %).

DNA Extraction

DNA extraction from Fresh Frozen Samples. From a total of 508 fresh frozen samples available as cell nuclei pellets, genomic DNA was isolated using the QIAamp Kit (Qiagen, Hilden, Germany). The extraction was done according to the Cell Culture protocol using Proteinase K with few modifications.

DNA extraction from PET Samples. 589 provided PET samples were deparaffinated directly in the tube in which they were delivered by the providers. The tissue was then lysed and DNA extracted using the QIAGEN DNeasy Tissue kit. Bisulfite treatment

Bisulfite treatment was carried out based on the method disclosed by Olek et al. Nucleic

Acids Res. 1996 Dec 15;24(24):5064-6, and optimized to the applicant's laboratory workflow.

Quantification Standards. The reactions are calibrated by reference to DNA standards of known methylation levels in order to quantify the levels of methylation within the sample. The DNA standards were composed of bisulfite treated phi29 amplified human genomic DNA (Promega) (i.e. unmethlyated), and/or phi29 amplified genomic DNA treated with Sssl Methylase enzyme (thereby methylating each CpG position in the sample), which is then treated with bisulfite solution. Seven different reference standards were used with 0%, {i.e., phi29 amplified genomic DNA only), 5%, 10%, 25%, 50%, 75% and 100% (i.e. phi29 Sssl treated genomic only). 2000 ng batches of human genomic DNA (Promega) were treated with bisulfite. To generate methylated MDA DNA, 13 tubes of 4.5 μg MDA-DNA (700ng/μl) were treated with Sssl.

Control assay. The GSTP 1-C3 assay design makes it suitable for quantitating DNAs from different sources, including fresh/frozen samples, remote samples such as plasma or serum, and DNA obtained from archival specimen such as paraffin embedded material. The following oligonucleotides were used in the reaction to amplify the control amplificate:

Control Primerl : GGAGTGGAGGAAATTGAGAT (SEQ ID NO: 104)

Control Primer2: CCACACAACAAAT ACTCAAAAC (SEQ ID NO: 105)

Control Probe: FAM-TGGGTGTTTGTAATTTTTGTTTTGTGTTAGGTT-TAMRA (SEQ

ID NO: 106)

Cycle program (40 cycles): 95 °C, 10 min

95 °C, 15 sec

58 °C, 1 min

Assay design and reaction conditions

Two assays were developed for the analysis of the gene PITX2(SEQ ID NO:1) Assay 1 :

Primers: GTAGGGGAGGGAAGTAGATGTT (SEQ ID NO: 107)

TTCTAATCCTCCTTTCCACAATAA (SEQ ID NO: 108) Probes: FAM-AGTCGGAGTCGGGAGAGCGA-TAMRA (SEQ ID NO: 109)

VIC-AGTTGGAGTTGGGAGAGTGAAAGGAGA -TAMRA (SEQ ID NO: 110)

Amplicon (SEQ ID NO:l l l):

GtAGGGGAGGGAAGtAGATGttAGCGGGtCGAAGAGTCGGGΛ GtCGGA GtCGGGA GA GCGΛAAGGAGAGGGGAttTGGCGGGGtAtTTAGGAGttAAtCGAGGAGtAGGAGtACG GAtTtttAtTGTGGAAAGGAGGAttAGAA Length of fragment: 143 bp

Positions of primers and probes are highlighted.

PCR components (supplied by Eurogentec) : 3 mM MgC12 buffer, 1 Ox buffer, Hotstart TAQ,

200 μM dNTP, 625 nM each primer, 200 nM each probe

Cycle program (45 cycles): 95 °C, 10 min

95 °C, 15 sec 62 °C, 1 min

Assay 2 :

Primers: AACATCTACTTCCCTCCCCTAC (SEQ ID NO: 112)

GTTAGTAGAGATTTTATTAAATTTTATTGTAT (SEQ ID NO: 1 13) Probes: FAM-TTCGGTTGCGCGGT-MGBNQF (SEQ ID NO:114)

VIC-TTTGGTTGTGTGGTTG- MGBNQF (SEQ ID NO: 115) Amplicon (SEQ ID NO:1 16):

GTtAGtAGAGATTttAttAAAtTttAtTGtAtAGTGGCGCGCGGGCGGtCGGtCGAGttCGGtr GCGCGG/TGGCGATttAGGAGCGAGtAtAGCGttCGGGCGAGCGtCGGGGGGAGCGAG tAGGGGCGACGAGAAACGAGGtAGGGGAGGGAAGtAGATGtt Length of fragment: 164 bp The positions of probes and primers are indicated. The probes cover three co-methylated CpG positions.

PCR components (supplied by Eurogentec): 2,5 mM MgC12 buffer, 1Ox buffer, Hotstart TAQ, 200 μM dNTP, 625 nM each primer, 200 nM each probe

Program (45 cycles): 95 °C, 10 min 95 °C, 15 sec 60 °C, 1 min

The extent of methylation at a specific locus was determined by the following formulas: Using absolute fluorescence intensity: methylation rate= 100 * I (CG) / (I(CG) + 1(TG)) (I = Intensity of the fluorescence of CG-probe or TG-probe)

Using threshold cycle Ct: methylation rate= 100*CG/(CG+TG)= 100/(l+TG/CG)= 100/(l+2^Λdelta(ct))

(assuming PCR efficiency E=2; delta (Ct)= Ct (methylated) - Ct (unmethylated) )

Gene PLAU

Primer: GTTAGGTGTATGGGAGGAAGTA (SEQ ID NO: 1 17)

TCCCTCCCCTATCTTACAA (SEQ ID NO: 118) Probes: FAM-ACCCGAACCCCGCGTACTTC-TAMRA (SEQ ID NO: 119)

VIC-ACCCAAACCCCACATACTTCCACA-TAMRA (SEQ ID NO: 120) Amplicon (SEQ ID NO: 121):

GttAGGTGtATGGGAGGAAGtACGGAGAATTTAtAAGttTtTCGATTttTtAGTttAGACGtT GTTGGGTttttTtCGtTGGAGATCGCGtTTtttttAAATtTTTGTGAGCGTTGCGGAAGtACG CGGGGTtCGGGTCGtTGAGCGtTGtAAGAtAGGGGAGGGA Length of fragment: 166 bp

PCR components were supplied by Eurogentec : 2,5 mM MgC12 buffer, 1Ox buffer, Hotstart TAQ, 200 μM dNTP, 625 nM each primer, 200 nM each probe

Program (45 cycles): 95 °C, 10 min 95 ⁰C, 15 sec 60 °C, 1 min

Gene ONECUT2

Primer: GTAGGAAGAGGTGTTGAGAAATTAA (SEQ ID NO: 122)

CCACACAAAAAATTTCTATACTCCT (SEQ ID NO: 123) Probes: FAM- ACGGGTAGAGGCGCGGGT -TAMRA (SEQ ID NO: 124) VIC- ATGGGTAGAGGTGTGGGTTATATTGTTTTG-TAMRA (SEQ ID NO:125)

Amplicon (SEQ ID NO: 126):

GtAGGAAGAGGTGtTGAGAAATTAAAAATTtAGGTTAGTTAATGtATmTGtCGtCGGt TGtAGGtTtCGttTTTGtATTAAGCGGGCGtTGATTGTGCGCGttTGGCGAtCGCGGGGA GGAtTGGCGGttCGCGGGAGGGGACGGGTAGAGGCGCGGGTTAtATTGTTtTGGAGt CGGtTCGGtTtTTTGTGttTttTtTAGCGGttAAGtTGCGAGGTAtAGtttTtTATTGTTtTAGG AGtAtAGAAAttTttTGTGTGG Length of fragment: 266 bp

PCR components were supplied by Eurogentec : 3 mM MgC12 buffer, 1Ox buffer, Hotstart TAQ, 200 μM dNTP, 625 nM each primer, 200 nM each probe

Program (45 cycles): 95 °C, 10 min 95 °C, 15 sec 60 °C, 1 min

Gene ABCA8

Primer: GTGAGGTATTGGATTTAGTTTATTTG (SEQ ID NO: 127)

CCCTAAATCTCATCCTAAAAACAC (SEQ ID NO: 128) Probes: FAM- TG AGGTTTCGGTTTTT AACGGTGG -TAMRA (SEQ ID NO: 129)

VIC- TGAGGTTTTGGTTTTTAATGGTGGGAT -TAMRA (SEQ ID NO: 130)

Amplicon (SEQ ID NO: 131):

GTGAGGTAtTGGATTtAGtttATTTGGtttCGAAGttTtTGTTtTCGGAATtCGGGTGtTGTG GGTTGAGGTttCGGTTttTAACGGTGGGAtTGGTGTttTCGAGATGAAATTTGGGGTTTt tTCGGGGtTTTGGTGGGATCGGTGTttTtAGGATGAGATTTAGGG Length of fragment: 168 bp

PCR components were supplied by Eurogentec : 3 mM MgC12 buffer, 10x buffer, Hotstart TAQ, 200 μM dNTP, 625 nM each primer, 200 nM each probe

Program (45 cycles): 95 ⁰C, 10 min

95 °C, 15 sec 62 °C, 1 min

Gene ERBB2

Primer: GGAGGGGGTAGAGTTATTAGTTTT (SEQ ID NO: 134)

ACTCCCAACTTCACTTTCTCC (SEQ ID NO: 135) Probes: FAM- TAATTTAGGCGTTTCGGCGTTAGG -TAMRA (SEQ ID NO: 136)

VIC- TAATTTAGGTGTTTTGGTGTTAGGAGGGA -TAMRA (SEQ ID NO:137)

Amplicon (SEQ ID NO: 138):

GGAGGGGGTAGAGTTATTAGTTTTTGTATTTAGGGATTTTTCGAGGAAAAGTGTG AGAACGGTTGTAGGTAATTTAGGCGTTTCGGCGTTAGGAGGGACGTATTTAGGTT TGCGCGAAGAGAGGGAGAAAGTGAAGTTGGGAGT Length of fragment: 144 bp

PCR components were supplied by Eurogentec: 2,5 mM MgC12 buffer, 1Ox buffer, Hotstart TAQ, 200 μM dNTP, 625 nM each primer, 200 nM each probe

Program (45 cycles): 95 °C, 10 min 95 °C, 15 sec 62 °C, 1 min

Gene TFFl

Primer: AGTTGGTGATGTTGATTAGAGTT (SEQ ID NO: 139)

CCCTCCCAATATACAAATAAAAACTA (SEQ ID NO: 140) Probes: FAM- ACACCGTTCGTAAAA-MGBNFQ (SEQ ID NO: 141)

VIC- ACACCATTCATAAAAT-MGBNFQ (SEQ ID NO: 142) Amplicon (SEQ ID NO: 143):

AGTTGGTGATGTTGATTAGAGTTTTTGTAGTTTΓAAATGATTTTTTTAATTAATTTT AAATTTTTAGAATTTATCGTATAAAAAGGTTATATTTTTTGGAGGGACGTCGATG

GTATTAGGATAGAAGTATTAGGGGATTTTACGAACGGTGTCGTCGAAATAGTAGT TTTTATTTGTATATTGGGAGGG

Length of fragment: 189 bp PCR components were supplied by Eurogentec: 2,5 mM MgC12 buffer, 10x buffer, Hotstart TAQ, 200 μM dNTP, 625 nM each primer, 200 nM each probe

Program (45 cycles): 95 °C, 10 min 95 °C, 15 sec 60 °C, 1 min

Gene TBC 1D3

Primer: TTTTTAGTTGGTTTTTATTAGGGTTTT (SEQ ID NO: 144)

CCAACATATCCACCCACTTACT (SEQ ID NO: 145) Probes: FAM- TTTCGACTAATCTCCCGCCGA-TAMRA (SEQ ID NO: 146)

VIC- TTTCAACTAATCTCCCACCAAATTTACTATCA-TAMRA (SEQ ID NO: 147) Amplicon(SEQ ID NO: 148): tTTttAGtTGGtTtttAttAGGGtTttAGAGtttAAGAtttAGtATtCGCGGGCGGtTtTGGGAAGttT GGtAGtTtCGtTAAtTttAAtATGttTtATTTGAtAGtAAATTCGGCGGGAGATtAGtCGAAA GAGtAAGTGGGTGGATATGtTGG Length of fragment: 142 bp

PCR components were supplied by Eurogentec: 4,5 mM MgC12 buffer, 10x buffer, Hotstart TAQ, 200 μM dNTP, 625 nM each primer, 200 nM each probe

Program (45 cycles): 95 °C, 10 min; 95 °C, 15 sec; 60 °C, 1 min

Each of the designed assays was tested on the following sets of samples:

• Tamoxifen treated patients who relapsed during treatment (all relapses).

• Tamoxifen treated patients who relapsed during treatment with distant metastases only.

• Non-Tamoxifen treated patients who relapsed during treatment (all relapses).

• Non-Tamoxifen treated patients who relapsed during treatment with distant metastases only.

Raw Data Processing All analyses were based on CT evaluation (evaluation using fluorescence intensities are available upon request). Assuming optimal real-time PCR conditions in the exponential amplification phase, the concentration of methylated DNA (C_meth) can be determined by c ^mah .= j ₊ 2« ¹~⁰7^" ₍,°;-rr₇,_; ) rl.%^/0iJ > where

CT _CG denotes the threshold cycle of the CG reporter (FAM channel); and

CT_TG denotes the threshold cycle of the TG reporter (VIC channel).

The thresholds for the cycles were determined by human experts after a visual inspection of the Amplification Plots [ABI PRISM 7900 HT Sequence Detection System User Guide]. The values for the cycles (CT_CG and CT_TG) were calculated with these thresholds by the ABI 7900 software. Whenever the amplification curve did not exceed the threshold, the value of the cycle was set to the maximum cycle (i.e., 50).

Statistical Methods

Cox Regression. The relation between disease-free survival times (DFS) (or metastasis free survival, MFS) and covariates are modeled using Cox Proportional Hazard models (Cox and Oates, 1984; Harrel, 2001). The hazard, i.e. the instantaneous risk of a relapse, is modeled as h(t \ x) = h_ϋ (t)-exp(βx) (3) and h(t \ x_h... _Λ) - ho (t)-exp(β_λx_x + ... + β_kx_k) (4) for univariate and multiple regression analyses, respectively, where t is the time measured in months after surgery, ho(t) is the baseline hazard, x is the vector of covariates (e.g., measurements of the assays) and β is the vector of regression coefficients (parameters of the model), β will be estimated by maximizing the partial likelihood of the Cox proportional hazard model.

Likelihood ratio tests are performed to test whether methylation is related to the hazard. The difference between -2 Log (Likelihood) of full model and null-model is approximately χ¹- distributed with k degrees of freedom under the null hypotheses βi = ... = β* = 0. The assumption of proportional hazards were checked by scaled Schoenfeld residuals (Thernau et al., 2000). For the calculation, analysis and diagnostic of the Cox Proportional Hazard Model the R functions coxph, coxph.zph of the "survival" package were used.

Stepwise Regression Analysis

For multivariate Cox regression models a stepwise procedure (Venables et al., 1999; Harrel, 2001) may be used in order to find sub-models including only relevant variables. Two effects are Usually achieved by these procedures:

• Variables (methylation rates) that are basically unrelated to the dependent variable (DFS/MFS) are excluded as they do not add relevant information to the model.

• Out of a set of highly correlated variables, only the one with the best relation to the dependent variable is retained.

Inclusion of both types of variables can lead to numerical instabilities and a loss of power. Moreover, the predictory performance can be low due to overfitting.

The following algorithm aims at minimizing the Akaike information criterion (AIC) which is defined as

AIC = -2 maximized log-likelihood + 2 #parameters.

The AIC is related to the predictory performance of a model, smaller values promise better performance. Whereas the inclusion of additional variables always improves the model fit and thus increases the likelihood, the second term penalizes the estimation of additional parameters. The best model will present a compromise model with good fit and usually a small or moderate number of variables.

Stepwise regression calculation with AIC may be done with the R function "step".

Kaplan-Meier Survival Curves and Log-Rank Tests

Survival curves are estimated from DFS/MFS data using the Kaplan-Meier method (Kaplan and Meier, 1958). Log-rank tests were used to test for differences of two survival curves, e.g. survival in hyper- vs. hypomethylated groups. For a description of this test see (Cox and Oates, 1984). For the Kaplan Meier Analysis the functions "survfit" and "survdiff' of the "survival" package were used.

Independence of markers from other covariates

To check whether our marker panel gives additional and independent information, other relevant clinical factors were included in the cox proportional hazard model and the p-values for the weights for every factor were calculated (Wald-Test) (Thernau et al., 2000). For the analysis of additional factors in the Cox Proportional Hazard model, the R function "coxph" was used.

Correlation Analysis

Pearson and Spearman correlation coefficients are calculated to estimate the concordance between measurements (e.g., methylation in matched fresh frozen and PET samples).

Density Estimation

For numerical variables, kernel density estimation was performed with a gaussian kernel and variable bandwidth. The bandwidth is determined using Silverman's "rule-of-thumb" (Silverman, 1986). For the calculation of the densities the R function "density" was used.

Analysis of Sensitivity and Specificity

For the analysis of sensitivity and specificity of single assays and marker panels time dependent ROCs were calculated. The calculation of the ROCs was done with two methods: The first method is to calculate sensitivity and specificity for a given threshold for the time T_nreshold . With that threshold, true positives, false positives, true negatives and false negatives were defined and the values for sensitivity and specificity were calculated for different cutoffs of the model. Patients censored before T_nreshold were excluded. The ROCs were calculated for different times T_nreshold (3 year, 4 years, ... , 10 years). The second method is to calculate sensitivity and specificity by using the Bayes-formula based on the Kaplan- Meier estimates (Heagerty et al., 2000) for the survival probabilities in the marker positive and marker negative groups for a given time T_nreshold . The ROCs were calculated for different times T_nreslwld (3 year, 4 years, ... , 10 years). k-fold Crossvalidation

For the analysis of model selection and model robustness k-fold crossvalidation (Hastie et ah, 2001) was used. The set of observation was split in k chunks by random. In turn, every chunk was used as a test set and the remaining k-1 chunks were used as training set. This procedure was repeated n times.

Population Charts

For the description of the relation between censoring and a covariate Population Charts (Mocks et al, 2002) were used. The baseline of the covariate was calculated including all observations with event. For a given time t, the mean (in case of real variables like age) or the fraction (in case of categorical variables) for all censored patients in the risk set at time t was calculated and added to the baseline value.

Technical Performance

Comparison of Assay Replicates

Each marker was measured in at least three replicates, variability between assay replicates was observed to be higher for PET than for fresh frozen samples.

Concordance Study Fresh Frozen versus PET Samples

Markers analyzed in this study (Example 2)were initially identified on a chip platform

(EXAMPLE 1) using fresh frozen samples. The ER+ NO untreated population was also analyzed on fresh frozen samples in EXAMPLE 2. A concordance study should demonstrate that measured methylation ratios are comparable for fresh frozen and PET samples. For this purpose, 89 fresh frozen samples from three different providers already used in the chip study were processed again in parallel with a matching PET sample originating from the same tumor.

FIGURE 15 shows such a concordance study for marker candidate PITX2 assay 1 as a scatter plot between fresh frozen and PET samples (using the QM assay). The association between the paired samples is 0.81 (Spearman's rho). This analysis is based on n=89 samples.

Results

Evaluation of Single Markers. Each of the eight established QM assays was used to measure the 508 samples from the NO, ER+ untreated patient population (random selection and additional relapses) in three replicates. After filtering of measuring points not fulfilling quality criteria and performing a Cox analyses, Kaplan-Meier survival curves and ROC curves for each single marker were generated.

Two different clinical endpoints were used for analyses:

• Disease-free survival, i.e. using all kinds of relapses (distant metastasis, loco-regional relapses, relapses at contralateral breast) as event.

• Metastasis-free survival, i.e. treating only distant metastasis as an event.

For analyzing the ER+, NO, TAM treated population, five marker candidates were analyzed on 541 samples from the NO, ER+ untreated patient population. Assays were measured in three replicates. Three assays that were measured on the untreated population (PITX2, ONECUT, and ABCA8) were not measured due to the limited material that was available for the TAM treated population. These assays were rejected either because they performed bad in the untreated population (ONECUT and ABCA8) or in case of PITX2-II it performed significantly worse than the other assay of this marker (P1TX2-I). After filtering of measuring points not fulfilling quality criteria Kaplan-Meier survival curves and ROC curves for each single marker were generated.

Two different clinical endpoints were used:

• Disease-free survival, i.e., using all kinds of relapses (distant metastasis, locoregional relapses, relapses at contralateral breast) as event.

The Kaplan-Meier estimated disease-free survival or metastasis-free survival curves of each single assay are shown in Figures 14 to 39, and combinations of assays are shown in Figures 40 to 55. The X axis shows the disease free survival times of the patients in years, and the Y- axis shows the proportion of patients with disease free survival. The black plot shows the proportion of disease free patients in the population with above an optimized cut off point's methylation levels (hypermethylation), the gray plot shows the proportion of disease free patients in the population with below an optimized cut off point's methylation levels (hypomethylation). The following p-values (probability that the observed distribution occurred by chance) were calculated for an optimized cut off. For cut-off optimization, the methylation rate/score (if multiple markers are evaluated) is chosen to minimize the log-rank p-value, with the constrain that both groups contain at least 20% of all samples. Percentage values refer to the methylation ratios at the cut-off point, in some plots these are alternatively expressed in terms of cox score.

Single gene assays Tamoxifen treated

TAM treated (all relapses) ERBB2 (Figure 14) : p-value 0.089; cut off: 0 TAM treated (distant only) ERBB2 (Figure 15): p-value 0.084; cut off: 0 TAM treated (all relapses) TFFl (Figure 16): p-value 0.037; cut off: 0.36 TAM treated (distant only) TFFl (Figure 17): p-value 0.029; cut off: 0.88 TAM treated (all relapses) PLAU (Figure 18): p-value 0.056; cut off point: 4.8% TAM treated (distant only) PLAU (Figure 19): p-value 0.065; cut off point: 4.8% TAM treated (all relapses) PITX2 (Figure 20): p-value 0.01; cut off point: 13.1% TAM treated (distant only) PITX2 (Figure 21): p-value 0.0012; cut off point: 14.3% TAM treated (all relapses) TBC1D3 (assay II) (Figure 22): p-value 0.28; cut off point: 94.6% TAM treated (distant only) TBC1D3 (assay H) (Figure 23): p-value 0.078; cut off point: 97%

FIGURE 62 shows the ROC (Heagerty et ai, 2000) plot at different times for marker model PITX2 (Assay 1) alone on ER+N0 TAM treated population. Panel A shows the plot at 60 months, panel B shows the plot at 72 months, Panel C shows the plot at 84 months, and Panel D shows the plot at 96 months. Only distant metastasis are defined as events. Sensitivity (proportion of all relapsed patients in poor prognostic group) shown on the X-axis and specificity (proportion of all relapse free patients in good prognostic group) shown on the Y- axis are calculated from KM estimates, and the area under the curve (AUC) is calculated. Values for median cut off (triangle) and best cut off (diamond, 0.42 quantile) are plotted.

AUC 60 months: 0.6 AUC 72 months: 0.69 AUC 84 months: 0.69 AUC 96 months: 0.67 FIGURE 63 shows the ROC (Heagerty et al, 2000) plot at different times for marker model TFFl on ER+N0 TAM treated population. Panel A shows the plot at 60 months, panel B shows the plot at 72 months, panel C shows the plot at 84 months and panel D shows the plot at 96 months. Only distant metastasis are defined as events. Sensitivity (proportion of all relapsed patients in poor prognostic group) shown on the X-axis and specificity (proportion of all relapse free patients in good prognostic group) shown on the Y-axis are calculated from KM estimates for different thresholds (= 5, 6, 7 , 8 years) and the area under the curve (AUC) is calculated. Values for median cut off (triangle) and best cut off (diamond, 0.78 quantile) are plotted.

AUC 60 months: 0.7 AUC 72 months: 0.65 AUC 84 months: 0.61 AUC 96 months: 0.64

FIGURE 64 shows the ROC (Heagerty et al, 2000) plot at different times for marker model PLAU on ER+N0 TAM treated population. Panel A shows the plot at 60 months, panel B shows the plot at 72 months, panel C shows the plot at 84 months and panel D shows the plot at 96 months. Only distant metastasis are defined as events. Sensitivity (proportion of all relapsed patients in poor prognostic group) shown on the X-axis and specificity (proportion of all relapse free patients in good prognostic group) shown on the Y-axis are calculated from KM estimates for different thresholds (= 5, 6, 7 , 8 years), and the area under the curve (AUC) is calculated. Values for median cut off (triangle) and best cut off (diamond, 0.77 quantile) are plotted.

AUC 60 months: 0.6 AUC 72 months: 0.63 AUC 84 months: 0.57 AUC 96 months: 0.6

Non Tamoxifen treated

Non Tamoxifen treated (all relapses) ERBB2 (Figure 24): p-value 0.21 ; cut off: 0.05 Non Tamoxifen treated (distant only) ERBB2 (Figure 25): p-value 0.23; cut off: 0 Non Tamoxifen treated (all relapses) TFFl (Figure 26) : p-value 0.012; cut off: 0.66 Non Tamoxifen treated (distant only) TFFl (Figure 27): p-value 0.016; cut off: 0.71

Non Tamoxifen treated (all relapses) PLAU (Figure 28): p-value 0.01 1 ; cut off point: 3.2%;

Non Tamoxifen treated (distant only) PLAU (Figure 29): p-value 0.0082; cut off point: 5.5%;

Non Tamoxifen treated (all relapses) PITX2 (I) (Figure 30): p-value 1.4e-06; cut off point:

35.4%;

Non Tamoxifen treated (distant only) PITX2 (I) (Figure 31): p-value 1.7 e-05; cut off point:

41.2%;

Non Tamoxifen treated (all relapses) PITX2 (II) (Figure 32): p-value 0.00026; cut off point:

56.1%;

Non Tamoxifen treated (distant only) PITX2 (II) (Figure 33): p-value 0.0026; cut off point:

61.9%;

Non Tamoxifen treated (all relapses) ONECUT (Figure 34): p-value 0.26; cut off point: 0%;

Non Tamoxifen treated (distant only) ONECUT (Figure 35): p-value 0.77; cut off point: 0%;

Non Tamoxifen treated (all relapses) TBC 1D3 (Figure 36): p-value 0.004; cut off point:

98.6%;

Non Tamoxifen treated (distant only) TBC1D3 (Figure 37): p-value 0.00022; cut off point:

98.6%;

Non Tamoxifen treated (all relapses) ABCA8 (Figure 38): p-value 0.0065; cut off: 0.41

Non Tamoxifen treated (distant only) ABCA8 (Figure 39): p-value 0.15; cut off point: 49.2%

Panels

Based on the results of the single marker evaluations, it was decided to build models using the marker candidates PITX2 -Assay I, TFFl, and PLAU. All possible combinations of these markers were evaluated. To combine methylation rates from multiple markers, Cox Proportional Hazard models are applied. Markers in a marker panel are combined by calculating the score from the Cox model: score = β\x\ + ... + β_kx_k, where β_\ and X_J determine the weight (regression coefficient) and the methylation rate for marker /, respectively. Weights for all markers in a model and the cut off (as score and quantile of sample population) used to determine the good and bad prognosis group are reported. Note that weights and optimal cut off are highly technology/assay component dependent and will most likely need to be adjusted individually for each lab. Reported p- values are from the log-rank test. See the statistical methods section for details. Tamoxifen treated

TAM treated (all relapses) TFFl and PLAU (Figure 40): p-value 0.023; cut off point: 0.7 quantile/ -0.26 score; weights: -0.0093 (TFFl), 0.0091 (PLAU);

TAM treated (distant only) TFFl and PLAU (Figure 41): p-value 0.00084; cut off point: 0.72 quantile/ -0.72 score; weights: -0.0253 (TFFl), 0.0132 (PLAU);

TAM treated (all relapses) TFFl and PLAU and PITX2 (Figure 42): p-value 0.037; cut off point: 0.72 quantile/ -0.1 score; weights: -0.0085 (TFFl), 0.0073 (PLAU), 0.0036 (PITX2);

TAM treated (distant only) TFFl and PLAU and PITX2 (Figure 43): p-value 0.0014; cut off point: 0.4 quantile/ -0.73 score; weights: -0.0232 (TFFl), 0.0071 (PLAU), 0.0129 (PITX2);

TAM treated (all relapses) PITX2 and TFFl (Figure 44): p-value 0.17; cut off point: 0.78 quantile/ -0.12 score; weights: 0.0047 (PITX2), -0.0103 (TFFl);

TAM treated (distant only) PITX2 and TFFl (Figure 45): p-value 0.0048; cut off point: 0.32 quantile/ -0.95 score; weights: 0.0142 (PITX2), -0.0256 (TFFl);

TAM treated (all relapses) PITX2 and PLAU (Figure 46): p-value 0.1 ; cut off point: 0.74 quantile/ 0.31 score; weights: 0.0063 (PITX2), 0.0076 (PLAU);

TAM treated (distant only) PITX2 and PLAU (Figure 47): p-value 0.0081 ; cut off point: 0.44 quantile/ 0.26 score; weights: 0.0154 (PITX2), 0.0106 (PLAU).

Figure 61 shows the ROC (Heagerty et al., 2000) plot at different times for marker model PITX2 (Assay 1) and TFFl on ER+N0 TAM treated population. Panel A shows the plot at 60 months, panel B shows the plot at 72 months, panel C shows the plot at 84 months and panel D shows the plot at 96 months. Only distant metastasis are defined as events. Sensitivity (proportion of all relapsed patients in poor prognostic group) shown on the X-axis and specificity (proportion of all relapse free patients in good prognostic group) shown on the Y- axis are calculated from KM estimates, and the area under the curve (AUC) is calculated. Values for median cut off (triangle) and best cut off (diamond, 0.32 quantile) are plotted.

AUC 60 months: 0.62 AUC 72 months: 0.67 AUC 84 months: 0.63 AUC 96 months: 0.65

Non Tamoxifen treated Non Tamoxifen treated (all relapses) TFFl and PLAU (Figure 48): p-value 0.0015; cut off point: 0.78 quantile/ -0.2 score; weights: -0.0075 (TFFl), 0.0176 (PLAU);

Non Tamoxifen treated (distant only) TFFl and PLAU (Figure 49): p-value 0.003; cut off point: 0.8 quantile/ -0.04 score; weights: -0.0044 (TFFl), 0.0219 (PLAU);

Non Tamoxifen treated (all relapses) TFFl and PLAU and PITX2 (Figure 50): p-value 8.9e-

07; cut off point: 0.64 quantile/ 0.59 score; weights: 0.0018 (TFFl), 0.01 17 (PLAU), 0.0140

(PITX2);

Non Tamoxifen treated (distant only) TFFl and PLAU and PITX2 (Figure 51): p-value 5.4e-

05; cut off point: 0.66 quantile/ 0.87 score; weights: 0.0054 (TFFl), 0.0147 (PLAU), 0.0160

(PITX2);

Non Tamoxifen treated (all relapses) PITX2 and TFFl (Figure 52): p-value 1.9e-06; cut off point: 0.72 quantile/ 0.57 score; weights: 0.0164 (PITX2), -0.0015 (TFFl);

Non Tamoxifen treated (distant only) PITX2 and TFFl (Figure 53): p-value 3.5e-05; cut off point: 0.76 quantile/ 0.87 score; weights: 0.0192 (PITX2), 0.0008 (TFFl);

Non Tamoxifen treated (all relapses) PITX2 and PLAU (Figure 54): p-value l .le-06; cut off point: 0.68 quantile/ 0.57 score; weights: 0.0142 (PITX2), 0.01 1 1 (PLAU);

Non Tamoxifen treated (distant only) P1TX2 and PLAU (Figure 55): p-value 1.5e-05; cut off point: 0.64 quantile/ 0.59 score; weights: 0.0163 (PITX2), 0.0130 (PLAU).

Robustness of marker models

To evaluate the robustness of the models, a crossvalidation was performed on model marker panel PITX2 (Assay 1) plus TFFl and marker panel PITX2 (Assay 1) alone, with 200 replicates. The stability of the assignment of one certain patient to the bad or good outcome group is illustrated in Figure 65, the left hand figure shows model marker panel PITX2 (Assay 1) plus TFFl and the right hand figure shows model marker panel PITX2 (Assay 1) alone. The plot illustrates in how many crossvalidation replicates each patient get's assigned to group 1 (light gray) or group 2 (dark gray).

Table 4: Numbers of censored and relapsed patients in randomly selected sample set of ER+, NO, untreated population.

Table 5: Numbers of censored and relapsed patients in ER+, NO, TAM treated population.

EXAMPLE 9:

To validate the most promising marker panels a second promoter region of the gene PITX2 was analyzed in more detail. This promoter region may also be called C-Promoter. To analyze the methylation rates of CpG positions within this region of interest a QM Real-Time-assay was designed and optimized in order to provide assays of optimum accuracy.

The assay was run on a set of fresh frozen tissue samples from untreated patients, i.e. not treated with Tamoxifen or any other hormone or chemotherapy. 94 samples from ER+ NO tumors from untreated patients were analyzed.

These 94 samples were chosen based on a previous analysis. 62 of these samples were previously "misclassified" as showing a low risk of relapse) by analyzing the AB-promoter of the gene PITX2 alone. These misclassified samples either showed high methylation levels at the AB promoter region- thereby indicating a high risk of relapse without having a recurrence (31) or showed a low methylation level at the AB promoter region indicating a low risk of relapse when a relapse or recurrence occurred within the observed time period (31). In addition 32 properly classified samples were chosen, of which 16 had a recurrence and were correctly classified as high risk because they showed high methylation rates at the AB- Promoter and 16 which showed low methylation rates at the AB promoter indicating a low risk of relapse and no recurrence occurred, and were therefore. From a total of 94 fresh frozen samples available as cell nuclei pellets, genomic DNA was isolated using the QIAamp Kit (Qiagen, Hilden, Germany). The extraction was done according to the Cell Culture protocol using Proteinase K with few modifications.

Bisulfite treatment was carried out based on the method disclosed by Olek et al. Nucleic Acids Res. 1996 Dec 15;24(24):5064-6, and optimized to the applicant's laboratory workflow.

The reactions are calibrated by reference to DNA standards of known methylation levels in order to quantify the levels of methylation within the sample. The DNA standards were composed of bisulfite treated phi29 amplified human genomic DNA (Promega) (i.e. unmethlyated), and/or phi29 amplified genomic DNA treated with Sssl Methylase enzyme (thereby methylating each CpG position in the sample), which is then treated with bisulfite solution. To generate methylated MDA DNA, 5 μg MDA-DNA (700ng/μl) was treated with Sssl . Seven different reference standards were used with 0%, (i.e., phi29 amplified genomic DNA only), 5%, 10%, 25%, 50%, 75% and 100% (i.e. phi29 Sssl treated MDA DNA only).

Assay design and reaction conditions:

A new assay was developed for the analysis of the C-promoter of the gene PITX2 (SEQ ID

NO: 1)

Primers: GATAGGTAGGTGATATT AGATTTT (SEQ ID NO: 179)

CCTAAATACCTAAAACTAAACTAC (SEQ ID NO: 180)

Probes: FAM-ACTCCTATTCGACCGCCCGAAAA-TAMRA (SEQ ID NO: 181 )

VIC-ACTCCTATTCAACCACCCAAAAAATATAC-TAMRA (SEQ ID NO: 182)

Amplicon (SEQ ID NO: 183):

GATAGGTAGGTGATATTAGATTTTTTGTGGTGGTAGTAGTTGTTGTAGTTATGATG TGGTTTTTTGAGTGTATTTTTTGTAATGTGTATATGTATATTTTTTGGGTGGTTGAA TAGGAGTTGGGTTTTGTTGTAGTTTAGTTTTAGGTATTTAGG

Length of fragment: 155 bp

PCR components (final concentrations) supplied by Eurogentec : Ix PCR buffer, 1 U Hotstart

Taq polymerase, 200 μM dNTP, 625 nM each primer, 200 nM each probe, 3 mM MgC12 Cycle program: 95 °C, 10 min (initial polymerase activation) and 45 cycles with

95 °C, 15 sec 62 °C, 1 min

The results are shown in Figure 66. In general, both promoters the AB promoter and the C- promoter show a significant degree of co-methylation - both promoters are methylated to a similar extend. A subgroup of 12 patients however shows a significant lower methylation level within promoter C I l patients (labeled with asterisks) in this subgroup (92%) have no recurrence. An analysis of promoter AB alone led to a bad prognosis for these patients. The combined analysis of both promoters significantly improved the prognosis accuracy, if a low methylation rate of promoter C is interpreted as indicating a good prognosis, even though the promoter AB is hypermethylated.

Claims

1. A method for providing a prognosis and/or predicting the outcome of endocrine treatment of a subject with a cell proliferative disorder of the breast tissue comprising a) obtaining a biological sample from the subject, b) determining the expression of at least two promoter/regulatory regions and/or transcripts of the gene PITX2 within said sample, and c) determining therefrom the prognosis and/or outcome of endocrine treatment of said subject.

2. The method according to claim 1 , wherein said subject is estrogen receptor positive.

3. The method according to claim 1 , further comprising the step of d) determining a suitable treatment regimen for the subject.

4. The method according to claim 3, wherein said suitable treatment regimen comprises one or more therapies selected from the group consisting of chemotherapy, radiotherapy, surgery, biological therapy, immunotherapy, antibodies, molecularly targeted drugs, estrogen receptor modulators, estrogen receptor down-regulators, aromatase inhibitors, ovarian ablation, LHRH analogues and other centrally acting drugs influencing estrogen production.

5. The method according to any of claim 1 to 4, wherein said cell proliferative disorder of the breast tissue is selected from the group consisting of ductal carcinoma in situ, invasive ductal carcinoma, invasive lobular carcinoma, lobular carcinoma in situ, comedocarcinoma, inflammatory carcinoma, mucinous carcinoma, scirrhous carcinoma, colloid carcinoma, tubular carcinoma, medullary carcinoma, metaplastic carcinoma, and papillary carcinoma and papillary carcinoma in situ, undifferentiated or anaplastic carcinoma and Paget' s disease of the breast.

6. The method according to any of claim 1 to 5, wherein said expression is determined by analysis of at least one of mRNA expression, LOH, and/or protein expression.

7. The method according to claim 6, wherein said mRNA expression is determined by analysis of the absence or presence of at least two different transcripts of the gene PITX2 or parts thereof.

8. The method according to claim 7, wherein the absence of at least one transcript is indicative of a good prognosis.

9. The method according to claim 7, wherein the absence of all transcripts is indicative of a bad prognosis.

10. The method according to any of claim 1 to 5, wherein said expression is determined by determining the methylation state of one or more CpG positions of at least two sequences of the gene PITX2 and/or regulatory regions thereof.

11. The method according to claim 10, wherein said at least two sequences are located within two different promoters and/or regulatory regions of PITX2.

12. The method according to claim 11, wherein hypermethylation in both of said two sequences is indicative of a bad prognosis.

13. The method according to claim 11 , wherein hypomethylation in at least one of said two sequences is indicative of a good prognosis.

14. The method according to any of claim 10 to 13, wherein said sequences are selected from SEQ ID NO: 159 and SEQ ID NO: 160.

15. The method according to any of claim 10 to 13, wherein said sequences are selected from SEQ ID NO: 161 and SEQ ID NO: 162.

16. A method for providing a prognosis and/or predicting the outcome of endocrine treatment of a subject with a cell proliferative disorder of the breast tissue comprising, a. isolating genomic DNA from a biological sample taken from said subject; b. treating the genomic DNA, or a fragment thereof, with one or more reagents to convert 5-position unmethylated cytosine bases to uracil or to another base that is detectably dissimilar to cytosine in terms of hybridization properties; c. contacting the treated genomic DNA, or the treated fragment thereof, with an amplification enzyme and at least two pairs of primers, wherein at least one pair of primers comprises in each case a contiguous sequence at least 18 nucleotides in length that is complementary to, or hybridizes under moderately stringent or stringent conditions to a sequence selected from the group consisting of SEQ ID NO: 163-164 and 171 to 172 and complements thereof and wherein at least one pair of primers comprises in each case a contiguous sequence at least 18 nucleotides in length that is complementary to, or hybridizes under moderately stringent or stringent conditions to a sequence selected from the group consisting of SEQ ID NO: 165-166 and 173-174 and complements thereof wherein the treated DNA or a fragment thereof is either amplified to produce one or more amplificates, or is not amplified; d. determining, based on the presence or absence of, or on the quantity or on a property of said amplifϊcate, the methylation state of at least one CpG dinucleotide sequence of SEQ ID NO: 159 and 160, or an average, or a value reflecting an average methylation state of a plurality of CpG dinucleotide sequences of SEQ ID NO: 159 and 160, and e. determining from said methylation state the prognosis and/or outcome of endocrine treatment of said subject.

17. The method according to claim 16, further comprising in step c) at least one primer pair comprising, in each case a contiguous sequence at least 18 nucleotides in length that is complementary to, or hybridizes under moderately stringent or stringent conditions to a sequence selected from the group consisting of SEQ ID NO: 76 to 103 and SEQ ID NO: 153, 154, 157, and 158, and complements thereof.

18. The method according to claim 16 or 17, wherein said one or more reagents comprises a solution selected from the group consisting of bisulfite, hydrogen sulfite, disulfite, and combinations thereof.

19. The method according to any of claims 16 to 18, wherein step d) is carried out by means of one or more methods taken from the group consisting of oligonucleotide hybridization analysis, Ms-SNuPE, sequencing, Real Time detection probes and oligonucleotide array analysis.

20. A method for providing a prognosis and/or predicting the outcome of endocrine treatment of a subject with a cell proliferative disorder of the breast tissue, comprising a. isolating genomic DNA from a biological sample taken from said subject; b. treating the genomic DNA, or a fragment thereof, with one or more reagents to convert 5-position unmethylated cytosine bases to uracil or to another base that is detectably dissimilar to cytosine in terms of hybridization properties; c. contacting the treated genomic DNA, or the treated fragment thereof, with an amplification enzyme and at least two pairs of primers, wherein at least one pair of primers comprises a contiguous sequence at least 18 nucleotides in length that is complementary to, or hybridizes under moderately stringent or stringent conditions to a sequence selected from the group consisting of SEQ ID NO: 163-164 and 171-172 and complements thereof and wherein at least one pair of primers comprises a contiguous sequence at least 18 nucleotides in length that is complementary to, or hybridizes under moderately stringent or stringent conditions to a sequence selected from the group consisting of SEQ ID NO: 165-166 and 173-174 and complements thereof wherein the treated DNA or a fragment thereof is amplified to produce at least two amplifϊcates, d. contacting each of said amplificates, either during or after amplification in step c) with a pair of labelled probes, comprising of a first and a second probe, said first probe being either complementary to, or hybridizing under moderately stringent or stringent conditions to a subsequence of the amplificate and comprising a CG dinucleotide, said second probe being either complementary to, or hybridizing under moderately stringent or stringent conditions to a subsequence of the amplificate comprising a TG dinucleotide; e. determining, based on the signal intensities generated by said labeled probes, the methylation rate of at least one CpG dinucleotide sequence of SEQ ID NO: 159 and 160, or an average, or a value reflecting an average methylation state of a plurality of CpG dinucleotide sequences of SEQ ID NO: 159, and 160, and f. determining from said methylation rate the prognosis and/or outcome of endocrine treatment of said subject.

21. The method of claim 20, wherein at least one primer pair is selected from the sequences according to SEQ ID NOS: 179 and 180.

22. The method of claim 20, wherein at least one primer pair is selected from oligonucleotides with sequences according to SEQ ID NOS:6 and 7 or SEQ ID NOS:14 and 15; or SEQ ID NOS: 107 and 108; or SEQ ID NOS:1 12 and 1 13.

23. The method of claim 20, wherein one pair of labeled probes is selected from oligonucleotides according to SEQ ID NOS: 181 and 182; and a second pair of labeled probes is selected from oligonucleotides according to SEQ ID NOS:8 and 9; or SEQ ID NOS: 16 and 17; or SEQ ID NOS: 109 and 1 10; or SEQ ID NOS:1 14 and 1 15.

24. A composition comprising a solution of at least three nucleic acid compounds comprising the SEQ ID NOS: 179, 180 and one of SEQ ID NO: 181 or SEQ ID NO: 182, in water.

25. A composition comprising a solution of at least four nucleic acid compounds comprising the SEQ ID NOS: 179 to 182 in water.

26. A diagnostic kit comprising at least one container and at least two pairs of primer oligonucleotides, wherein one pair is selected from sequences according to SEQ ID NOS: 179 and 180, optionally together with other suitable auxiliaries.

27. The kit according to claim 26, wherein a second pair of primers is included that is selected from oligonucleotides according to SEQ ID NOS:6 and 7 or SEQ ID NOS:14 and 15; or SEQ ID NOS:107 and 108; or SEQ ID NOS:1 12 and 1 13.

28. The kit according to claim 26, wherein additional oligonucleotide probes are contained that are suitable for an analysis, and optionally pairs thereof.

29. The kit according to claim 26, wherein additional oligonucleotide probes are contained, and wherein one pair of said probes is selected from oligonucleotides according to SEQ ID NOS:181 and 182.

30. The kit according to claim 29, wherein said additional oligonucleotide probes are selected from oligonucleotides according to SEQ ID NOS:8 and 9; or SEQ ID NOS: 16 and 17; or SEQ ID NOS: 109 and 1 10; or SEQ ID NOS:1 14 and 1 15.

31. The kit according to any of claims 28 to 30, wherein said probes are labeled probes.

32. Use of the method according to any of claims 1 to 23, the composition according to claim 24 or 25, and the kit according to any of claims 26 to 31 for providing a prognosis and/or predicting the outcome of endocrine treatment of a subject with a cell proliferative disorder of the breast tissue.