WO2007039291A2

WO2007039291A2 - Methods, apparatus and nomograms to determine prostate cancer progression

Info

Publication number: WO2007039291A2
Application number: PCT/EP2006/009606
Authority: WO
Inventors: Gunter Weiss; Christian Pipenbrock
Original assignee: Epigenomics Ag
Priority date: 2005-10-03
Filing date: 2006-10-04
Publication date: 2007-04-12
Also published as: WO2007039291A3

Abstract

The invention provides methods, apparatus and nomograms to predict the disease outcome of a prostate cancer patient comprising determining genomic methylation and further comprising determining clinical disease parameters.

Description

Methods, apparatus and nomograms to determine prostate cancer progression.

Background of the Invention

Prostate cancer. Prostate cancer is the most common malignancy among men in the United States (-200,000 new cases per year), and the sixth leading cause of male cancer-related deaths worldwide (~204,000 per year). Prostate cancer is primarily a disease of the elderly, with approximately 16% of men between the ages of 60 and 79 having the disease. According to some estimates at autopsy, 80% of all men over 80 years of age have some form of prostate disease (e.g., cancer, BPH, prostatitis, etc). Benign prostate hypertrophy is present in about 50% of men aged 50 or above, and in 95% of men aged 75 or above. Prostate cancer, based on these reports, is often not a disease that men die from, but more typically — with. Recent evidence suggests that the incidence of prostate cancer may in fact be declining, likely as result of better treatment, better surgery, and earlier detection.

Detection of prostate cancer; molecular approaches. Current guidelines for prostate cancer screening have been suggested by the American Cancer Society and are as follows: At 50 years of age, health care professionals should offer a blood test for prostate specific antigen (PSA) and perform a digital rectal exam (DRE). It is recommended that high risk populations, such as African Americans and those with a family history of prostate disease, should begin screening at 45 years of age. Men without abnormal prostate pathology generally have a PSA level in blood below 4ng/ml. PSA levels between 4ng/ml and 10ng/ml (called the 'Grey Zone') have a 25% chance of having prostate cancer. The result is that 75% of the time, men with an abnormal DRE and a PSA in this grey zone have a negative, or a seemingly unnecessary biopsy. Above the grey zone, the likelihood of having prostate cancer is significant (> 67%) and increases even further as PSA levels go up. Numerous methods exist for measuring PSA (percent-free PSA, PSA velocity, PSA density, etc.), and each has an associated accuracy for detecting the presence of cancer. Yet, even with the minor improvements in detection, and the reported drops in mortality associated with screening, the frequency of false positives remains high. Reduced specificity results in part from increased blood PSA associated with BPH, and prostatis. It has also been estimated that up to 45% of prostate biopsies under current guidelines are falsely negative, resulting in decreased sensitivity even with biopsy.

TRUS guided biopsy is considered the 'gold standard' for diagnosing prostate cancer. Recommendations for biopsy are based upon abnormal PSA levels and or an abnormal DREs. For PSA there is a grey zone where a high percentage of biopsies are perhaps not necessary. Yet the ability to detect cancer in this grey zone (PSA levels of 4.0 to 10 ng/ml) is difficult without biopsy. Due to this lack of specificity, 75% of men undergoing a biopsy do not have cancer. Yet without biopsy, those with cancer would be missed, resulting in increased morbidity and mortality. Unfortunately, the risks associated with an unnecessary biopsy are also high. Molecular markers would offer the advantage that they can be used to efficiently analyze even very small tissue samples, and samples whose tissue architecture has not been maintained. Within the last decade, numerous genes have been studied with respect to differential expression among benign hyperplasia of the prostate and different grades of prostate cancer. However, no single marker has as yet been shown to be sufficient for the prognostic classification of prostate tumors in a clinical setting.

Alternatively, high-dimensional mRNA-based approaches may, in particular instances, provide a means to distinguish between different tumor types and benign and malignant lesions. However, application of such approaches as a routine diagnostic tool in a clinical environment is impeded and substantially limited by the extreme instability of mRNA, the rapidly occurring expression changes following certain triggers (e.g., sample collection), and, most importantly, by the large amount of mRNA needed for analysis which often cannot be obtained from a routine biopsy (see, e.g., Lipshutz, R. J. et al., Nature Genetics 21 :20-24, 1999; Bowtell, D. D. L. Nature Genetics Suppl. 21 :25-32, 1999).

Aberrant genetic methylation in prostate cancer has been observed in several genes including GSTPi, AR, p16 (CDKN2a/INK4a), CD44, CDH1. Genome-wide hypomethylation for example of the LINE-1 repetitive element has also been associated with tumor progression (Santourlidis, S., et al., Prostate 39:166-74, 1999).

Prostate Cancer Treatment Options. There are many treatment strategies available to patients diagnosed with prostate cancer, and the decision for the patients and physicians is often unclear. Because prostate cancer can be a slowly developing disease, many men choose a treatment approach called watchful waiting, or conservative management. As the names imply, this approach does not include any radical therapy intended to cure the patient. Instead, the disease is carefully monitored using PSA tests and DREs. The ideal patient for this approach is one whose tumor is slow growing and non-invasive, and who is therefore likely to die of other causes before the prostate cancer becomes problematic.

For younger patients with localized disease, curative treatment is more appropriate. Radical prostatectomy is used to remove the prostate and hopefully all traces of the tumor. The surgical margins, seminal vesicles, and sometimes lymph nodes are tested for the presence of cancer, and in each case the presence of cancer correlates with reduced disease free survival Overall, about 70% of men remain free of disease ten years after surgery (Roehl, et al., 2004). Radical prostatectomy is a significant surgery, with side effects including blood loss, incontinence, and impotence. The rate of intraoperative and postoperative complications is estimated to be less than 2% (Lepor, et al., 2001).

Radiation therapy is also used to attempt to cure prostate cancer patients. Patients can choose either external beam radiation or brachytherapy (radioactive seed implants). The rates of survival and the side effects are similar to radical prostatectomy (D'amico, et al., 1998). For both radical prostatectomy and radiation therapy, the probability of survival is highly dependent on the stage and differentiation of the tumor. Localized indolent tumors are more likely to be cured. Hormonal therapy is often used for patients whose cancer has spread beyond the prostate or for patients whose cancer has recurred after prostatectomy or radiation therapy. In other words, hormonal therapy is used to control cancer but not to cure it. Hormonal therapy is sometimes used in conjunction with other therapies such as radiation or as a neo-adjuvant therapy prior to surgery. The goal of hormonal therapy is to reduce the stimulatory effect of androgens on the prostate tumor. The reduction in hormones is achieved through orchiectomy, lutenizing hormone-releasing hormone (LHRH) analogs, and antiandrogens. Side effects of hormonal therapy can include impotence, hot flashes, fatigue, and reduced libido. Eventually, prostate tumors become insensitive to androgens and hormonal therapy is no longer effective.

After the tumor has spread outside the capsule and hormonal therapy has failed, chemotherapy can be used to relieve pain or delay the progression of the disease. The response to chemotherapy is variable, and lives are extended for only a minority of patients. Bisphosphonates are used to reduce the osteolytic activity of tumors metastasised to the bones.

Prostate Cancer Prognosis Estimation. DRE₁ TRUS, biopsy, and PSA provide initial staging information on the tumor, but MRI, CT scans, ProstaScint scans and bone scans are used to determine the spread of the cancer beyond the prostatic capsule. These tests are not used on every prostate cancer patient, but only those with some likelihood of metastases. If metastases can be confirmed, the patient will receive treatment designed to slow the progression of the disease. If no metastases are detected, a patient is a candidate for potentially curative treatments such as prostatectomy and radiation therapy. Prior to the removal of the prostate, lymph nodes are sometimes dissected as a final test for metastases. If metastases are present in the dissected nodes, the surgery may be aborted. Analysis of the tissue surgically removed during prostatectomy is the final and gold standard staging technique for those patients who choose to undergo surgery. Frequently, analysis of the surgical specimens shows that the patient was originally understaged by the diagnostic tests (Bostwick, 1997).

An accurate estimation of prognosis is crucial for selection of the most appropriate treatment for each patient. Since organ confined prostate cancer cannot lead to death, estimation of prognosis is also an estimation of the presence or likelihood of development of metastases. A patient who is likely to develop cancer outside of the prostatic capsule will receive more extensive diagnostic work-up, including MRI and CT scans, and possibly more radical treatments, including surgery and radiation.

An initial prognostic assessment is made from the results of a PSA test, DRE, and biopsy analysis. The size, location, and method of detection of the tumor are combined to give a staging score on the TNM scale. Patients with higher stage tumors and high PSA values are more likely to have cancer that has spread or will spread outside of the prostate. A histological analysis of the biopsy allows a pathologist to determine the Gleason score. The Gleason score is a composite of the two most prevalent grades in the tissue sample, and the grades can range between one and five. A higher grade indicates more extreme dedifferentiation, and higher composite scores correlate with higher probability for metastasis and reduced disease free survival.

Prostate cancer nomograms have been developed and modified to predict the risk of cancer recurrence after primary therapy based on PSA levels, Gleason grading, and pre-operative staging information (Kattan et al 2003; Kattan et al 1998; Potter et al 2001). The data is derived from actual patient survival rates in cohorts of thousands of patients at multiple institutions. As with all prognostic measurements in prostate cancer, the estimate of recurrence risk by the nomogram is also an estimate of the likelihood of presence of cancer outside the prostatic capsule. Because the clinical characteristics of the cancers that patients are presenting with have changed with the widespread use of PSA, the nomograms are out of date and are not widely used. However, the general process of integrating Gleason, stage, and PSA information is still used.

Patients with cancer that has spread to lymph nodes or other metastatic sites are treated with systemic therapies such as hormonal therapies. Patients with localized disease (T1-T3) are candidates for definitive, curative treatments such as surgery or radiation. Those patients with localized disease who are thought to be low-risk are ideal candidates for watchful waiting. Those with intermediate risk are ideal for monotherapy such as surgery or radiation. Those with high risk localized disease should be considered for multimodal therapies or clinical trials.

After surgery, more prognostic information is available because the tumor spread can be directly analyzed. During some prostatectomies, the lymph nodes are directly dissected and the nodal status is confirmed. In all surgeries, the tumor spread to the seminal vesicles and the margin status are checked. Positive nodes, seminal vesicles, and margins all indicate an inferior prognosis and may suggest that the patient should receive adjuvant treatment.

Molecular prostate cancer prognostic markers; deficiencies of prior art approaches. As an alternative to current approaches to the prognostic classification of prostate carcinoma patients a variety of molecular approaches are currently being explored. It is anticipated that the development of suitable molecular markers will have significant advantages over current approaches in terms of accuracy, cost-effectiveness and/or patient invasiveness. A variety of molecular markers have been discovered including monoclonal antibodies. In a study by Xu et al (ICDB/95613763) 114 cases of prostate cancer showed that 57% of the bone marrow specimens had elevated OVX1 levels (greater than 7.2 U/ml). In other experiments, OVX1 levels were about 2-fold higher in serum samples from androgen- independent than from androgen-dependent prostate cancer patients (p less than 0.001 ), suggesting that serum OVX1 levels may be able to predict the progression of prostate cancer, since this disease when it progresses typically becomes androgen-independent. Expression of the PSCA protein and mRNA has been positively correlated with adverse tumor characteristics, such as increasing pathological grade (poor cell differentiation), worsening clinical stage and androgen-independence and speculatively with prostate carcinogenesis (Jpn J Clin Oncol, 4:414-9, 2004). Other prospective mRNA analysis markers include Hepsin. Expression of Hepsin showed significant difference between patients at lower risk (pT2, G2 and Gleason score less than 7) and higher risk (pT3/4, G3 and Gleason score 7 or greater) for relapse (J Urol, 171 :187-91 , 2004).

The GSTPi gene is the most well characterized prostate carcinoma diagnostic marker. Zhou et al. (J Urol, 171 :2195-8, 2004) recently correlated expression of the GSTPi gene with Gleason grade and cancer volume. Furthermore, use of the gene GSTPi as a marker for the detection of prostate carcinomas located in the peripheral zone (i.e., with a high likelihood of metastasis) has also been described in U.S. patent application serial number 10/350,763, which is hereby incorporated by reference in its entirety.

Another methylation marker which may be suitable for the prognostic classification of prostate carcinomas is uPA. Rabbani et al. (The FASEB Journal 17:1081-1088, 2003) have shown that the uPA promoter is hypermethylated in hormone-responsive PrEC and LNCaP cells and hypomethylated in hormone-insensitive PC-3 cells. De-methylation of the promoter in the LNCaP cell lines resulted in increase of mRNA analysis and resulted in an increase in the invasive capacity. Singal et al., analysed methylation of a gene panel consisting of glutathione s-transferase Pi1 (GSTP1), retinoic acid receptor beta (RARB), CD44, E-cadherin (ECAD) and RAS association domain family protein 1A (RASSF1 A) in prostate cancer. A methylation index (Ml) was calculated as the total number of genes methylated, higher Ml was noted in stage III as compared to stage Il disease, and in Gleason score 7 as compared to Gleason score 6 samples. Singal et al. thus concluded that the results suggest that the methylation of the gene panel in correlated with clinicopathological features of poor prognosis.

Pronounced need in the art. Significantly, however, none of the heretofore mentioned markers are sufficiently developed to provide a marker for the prognosis of prostate cell proliferative disorders that is sufficiently robust and/or accurate for effective use in a clinical setting.

While accurate diagnosis of prostate carcinoma is important, the most pressing need in prostate cancer treatment is for information to guide the treatment planning decisions.

Leaders in the field agree that many patients with clinically insignificant disease receive unnecessary radical treatments such as prostatectomy or radiation therapy. However, twenty percent of patients who do receive these curative treatments experience disease recurrence. A molecular test could help select patients for the optimal treatment choice and thereby reduce over and under treatment

Currently the therapy choice is made based on the likelihood of spread of the disease. Low-risk patients are candidates for watchful waiting. Medium and high risk patients should receive surgery or radiation, and the high risk patients are candidates for additional adjuvant treatments. Staging, Gleason, and PSA are currently used to estimate this risk, but the combined information from these tests is insufficient. Very few patients are recommended for watchful waiting because clinicians cannot be sure which cancers are indolent. Furthermore, many patients who receive monotherapy experience a recurrence. Gleason grading currently plays a primary role in prognostic assessment. Patients with localized disease and high Gleason scores (8-10) always undergo radical treatments. Patients with low Gleason scores (2-5) have the option of deferring curative treatment and opting for watchful waiting, however many chose to undergo curative therapy soon after diagnosis. For patients with mid-range Gleason scores, which is the majority of patients diagnosed today, clinicians must use other less-reliable prognostic indicators for further information.

Accordingly, there is a pronounced need in the art for a novel, effective prognostic test, and in particular one that would predict the probability that a cancer has or is likely to spread outside of the prostate based on the methylation patterns of biopsy samples. This type of information is highly valuable in the diagnostic and treatment planning processes. This information would initially be used in reaching the decision about whether imaging tests are necessary to check for metastasis for a complete diagnostic work-up. Surgery is unnecessary for any patient whose cancer has already spread, but if a patient is not selected for imaging the metastases will not be detected until surgery or later.

Furthermore there is a pronounced need in the art for a novel and effective prostate cell proliferative disorder molecular classification test, and in particular one that would be suitable for the analysis of biopsy samples to improve the stratification of patients into low, intermediate, and high risk categories so that optimal treatment plans can be selected for each patient. With accurate stratification, patients and doctors can choose watchful waiting with confidence that there is little risk for early recurrence. This test would therefore reduce the number of unnecessary surgeries and radiation treatments.

Additionally, with improved estimations of which patients are likely to recur with monotherapy, physicians can make better use of available adjuvant treatments. If a patient chooses to undergo surgery, the test can be repeated on prostatectomy samples to verify the assessment of his need for adjuvant therapy. The benefits of different adjuvant therapy approaches are still being worked out in clinical trials, and a molecular test could provide valuable information to stratify patients for this additional treatment or for clinical trials.

PITX2 (Paired-like homeodomain transcription factor 2), also known as PTX2, RIEG1 , or ARP1 , encodes a member of the RIEG/PITX homeobox family, which is in the bicoid class of homeodomain proteins. PITX2 encodes several alternative transcripts, and mutations in the gene lead to the autosomal-dominant disorder Rieger's syndrome, a developmental disorder predominantly affecting the eye (Semina et a/., 1996). The protein acts as a transcription factor and is involved in the development of several major organs. It is induced by the WNT pathway, and mediates cell-type specific proliferation by inducing growth-regulating genes (Kioussi et al. 2002). Toyota et al. (2001) found hypermethylation of the gene in a large proportion of acute myeloid leukemias. Several studies by the applicant (see WO 2005/059172) have demonstrated that hypermethylation of PITX2 is associated with poor prognosis for breast cancer patients.

The GSTP1 marker is located on Chromosome 11. Methylation of the regulatory and exonic regions this gene have been previously associated with prostate cancer prognosis. The gene ABHD9, abhydrolase domain containing 9, is located on Chromosome 9 and methylation of this genes has not been previously associated with prostate cancer. The gene CCN D2, is located on Chromosome 12 and is a cell-cycle regulatory gene. Methylation of Cyclin D2 in prostate cancers has been shown to correlate with poor prognosis. The GPR7 marker is located in a CpG island in the promoter region of an intronless gene on chromosome 10. GPR7, or G-protein receptor 7, is a receptor for neuropeptide W and neuropeptide B (Shimomura et al. 2002; Tanaka et al. 2003). The expression of GPR7 has been studied in the brain, and is expressed mainly in the cerebellum and frontal cortex (O'Dowd et al. 1995). lshii et al. (2003) studied the phenotype of mice lacking a functional copy of GPR7. The mice developed adult-onset obesity and metabolic defects such as decreased energy expenditure and increased blood levels of glucose and insulin. Interestingly, these phenotypes were only detected in male mice. The GPR7 ligands, neuropeptides W and B, have also been implicated in metabolism and obesity in separate studies (Samson et al. 2004; Levine et al. 2005). GPR7, which is similar in sequence to opioid receptors, may also have a role in pain signalling (Zaratin et al. 2005).

SEQ ID NO: 1 is located within the regulatory region of HIST2H2BF on chromosome 1 in a region with several histone genes. The histone content and status of chromatin can influence the expression of the encoded gene. Methylation and altered expression of a histone gene in prostate cancer could cause chromatin changes throughout the genome that alter gene expression in ways that result in more aggressive tumor properties. There are no published articles on the function of this particular histone.

The marker referred to as SEQ ID NO: 7 is located on chromosome 3 downstream of the FOXL2 (Forkhead transcription factor) gene and within or near predicted genes or ESTs. Although it is downstream, it is anticipated that methylation of this marker effects the expression of FOXL2, which is mutated in the blepharophimosis-ptosis epicanthus inversus syndrome (BPES). This syndrome is characterized by eye, craniofacial, and ovarian abnormalities. Methylation of the marker may also affect the expression of the EST, or the EST may be shown to be an alternative exon for the FOXL2 gene.

Summary of the Invention

The invention provides methods, apparatus and nomograms to predict the disease outcome of a prostate cancer patient comprising determining genomic methylation and further comprising determining clinical disease parameters. Brief description of the drawings

Figure 1 provides a nomogram for the prediction of overall patient survival time at 3, 5 and 7 years. Said nomogram comprises a PITX methylation value plot (A), to be correlated with a "predictor points" scale (B). This is then correlated with the total points scale (C), which is then in turn correlated with a linear predictor points scale (C). Patient survival probabilities can then be predicted by correlating said values on the outcome scales (D).

Figure 2 provides a nomogram for the prediction of overall patient survival time at 3, 5 and 7 years. Said nomogram comprises PITX methylation and Gleason sum (biopsy) value plots (A), each to be correlated with a "predictor points" scale (B). The sum of said values is then correlated with the total points scale (C), which is then in turn correlated with a linear predictor points scale (C). Patient survival probabilities can then be predicted by correlating said values on the outcome scales (D).

Figure 3 provides a nomogram for the prediction of overall patient survival time at 3, 5 and 7 years. Said nomogram comprises PITX methylation and Gleason sum (surgical) value plots (A), each to be correlated with a "predictor points" scale (B). The sum of said values is then correlated with the total points scale (C), which is then in turn correlated with a linear predictor points scale (C). Patient survival probabilities can then be predicted by correlating said values on the outcome scales (D).

Figure 4 provides a nomogram for the prediction of overall patient survival time at 3, 5 and 7 years. Said nomogram comprises PITX methylation and nomogram scores (according to Han et al 2002) sum value plots (A), each to be correlated with a "predictor points" scale (B). The sum of said values is then correlated with the total points scale (C), which is then in turn correlated with a linear predictor points scale (C). Patient survival probabilities can then be predicted by correlating said values on the outcome scales (D).

Figure 5 provides a nomogram for the prediction of overall patient survival time at 3, 5 and 7 years. Said nomogram comprises PITX methylation, pre-surgery PSA, Gleason sum, surgical margins, seminal vesicle invasion and T stage value plots (A), each to be correlated with a "predictor points" scale (B). The sum of said values is then correlated with the total points scale (C), which is then in turn correlated with a linear predictor points scale (C). Patient survival probabilities can then be predicted by correlating said values on the outcome scales (D).

Figure 6 provides a nomogram for the prediction of overall patient survival time at 3, 5 and 7 years. Said nomogram comprises PITX methylation, pre-surgery PSA₁ Gleason sum (surgery), surgical margins, seminal vesicle invasion and T stage value plots (A), each to be correlated with a "predictor points" scale (B). The sum of said values is then correlated with the total points scale (C), which is then in turn correlated with a linear predictor points scale (C). Patient survival probabilities can then be predicted by correlating said values on the outcome scales (D). Figure 7 provides a nomogram for the prediction of overall patient survival time at 3, 5 and 7 years. Said nomogram comprises PITX methylation, first and second Gleason values, pre-surgery PSA and T stage plots (A), each to be correlated with a "predictor points" scale (B). The sum of said values is then correlated with the total points scale (C), which is then in turn correlated with a linear predictor points scale (C). Patient survival probabilities can then be predicted by correlating said values on the outcome scales (D).

Figure 8 shows the distribution of follow up times of patients as analysed in Example 1. The white bars represent the distribution of all censored (no PSA relapse) patients. The grey bars show the distribution of the PSA-free survival time for all of the relapse patients. Frequency is shown on the Y- axis and time (months) is shown on the X-axis.

Figure 9 shows Kaplan-Meier survival analysis of the PITX2 marker (A & B) and ROC curve analysis (C) of the marker PITX2 in differentiating between prostate cancer patients according to Example 1. Proportion of recurrence-free patients is shown on the Y-axis, time in years is shown on the x-axis. Figure 10 shows Kaplan-Meier survival analysis of PITX2 performance on sub-populations based on stage according to Example 1. Proportion of recurrence-free patients is shown on the Y-axis, time in years is shown on the x-axis. Figure A shows all T2 and T3 patients, wherein the dark grey plot shows clinical stage T3 patients, and light grey plot shows clinical stage T2 patients. Figure B shows all T3 patients, wherein the dark grey plot shows hypomethylated samples, and light grey plot shows hypomethylated samples. Figure C shows all T2 patients, wherein the dark grey plot shows hypomethylated samples, and light grey plot shows hypomethylated samples. Proportion of recurrence-free patients is shown on the Y-axis, time in years is shown on the x-axis.

Figure 11 shows Kaplan-Meier survival analysis of PITX2 performance on sub-populations based on Gleason score according to Example 1. Figure A shows the performance of Gleason score as a prognostic marker. Gleason 5 and 6 patients are in light grey, Gleason 7 patients are in dark-grey, and Gleason 8, 9, and 10 patients are in black. Figure C shows the performance of PITX2 on Gleason 5 and 6 patients. Figure B shows the performance of PITX2 on Gleason 7 patients. Figure D shows the performance of PITX2 on Gleason 8, 9, and 10 patients. In figures B to D light grey shows hypomethylated samples, black indicates hypermethylated samples. Proportion of recurrence-free patients is shown on the Y-axis, time in years is shown on the x-axis.

Figure 12 shows Kaplan-Meier survival analysis of PITX2 performance on sub-populations based on nomogram score according to Example 1. Figure A shows the performance of Nomogram score as a prognostic marker. High risk are in light grey, low risk patients are in black. Figure C shows the performance of PITX2 on high risk patients. Figure B shows the performance of PITX2 on low risk patients. Figure D shows the performance of PITX2 on Gleason 8, 9, and 10 patients. In figures B and C light grey shows hypomethylated samples, black indicates hypermethylated samples. Proportion of recurrence-free patients is shown on the Y-axis, time in years is shown on the x-axis. The terms "correlation," "correlate" and "correlating" shall be taken to include a statistical relationship between factors and outcome, and may or may not be equivalent to a calculation of a statistical correlation coefficient.

The term nomogram shall be taken to mean a graphic representation of numerical relations.

The term adjuvant treatment or adjuvant therapy shall be taken to mean a treatment given after the primary treatment to increase the chances of a cure. Adjuvant therapy may include chemotherapy, radiation therapy, hormone therapy, or biological 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 "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.

As used herein the term "prognosis" shall be taken to mean a prediction of the progression of the disease (for example but not limited to regression, stasis and metastasis), in particular aggressiveness and metastatic potential of a tumor.

As used herein the term "prognostic marker" shall be taken to mean an indicator of a prediction of the progression of the disease or disease outcome.

As used herein the term "prognostic classification" or "prognosis" shall be taken to mean the classification of a cell proliferative disorder, preferably cancer but not breast cancer according to a prediction of the progression of the disease or disease outcome.

It is preferably used to define patients with high, low and intermediate risks of metastasis, death or recurrence after treatment that result from the inherent heterogeneity of the disease process. As used herein the term "aggressive" as used with respect to a tumor shall be taken to mean a cell proliferative disorder that has the biological capability to rapidly spread outside of its primary location or organ. Indicators of tumor aggressiveness standard in the art include but are not limited to tumor stage, tumor grade, Gleason grade, nodal status and survival. As used herein the term "survival" shall not be limited to mean survival until mortality (wherein said mortality may be either irrespective of cause or cell proliferative disorder related) but may be used in combination with other terms to define clinical terms, for example but not limited to "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 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 a defined end point (e.g. death, recurrence or metastasis).

The term 'AUC as used herein is an abbreviation for the area under a curve. In particular it refers to the area under a Receiver Operating Characteristic (ROC) curve. The ROC curve is a plot of the true positive rate against the false positive rate for the different possible cutpoints of a diagnostic test. It shows the trade-off between sensitivity and specificity depending on the selected cutpoint (any increase in sensitivity will be accompanied by a decrease in specificity). The area under an ROC curve (AUC) is a measure for the accuracy of a diagnostic test (the larger the area the better, optimum is 1 , a random test would have a ROC curve lying on the diagonal with an area of 0.5; for reference: JP. Egan. Signal Detection Theory and ROC Analysis, Academic Press, New York, 1975).

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 a pre-determined cut-off, which is preferably between 0% and 4%.

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 a pre-determined cut-off, which is preferably between 0% and 4%.

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.

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.

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 DNA₁ 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 6O⁰C in 2.5 x SSC buffer, followed by several washing steps at 37⁰C in a low buffer concentration, and remains stable). Moderately stringent conditions, as defined herein, involve including washing in 3x SSC at 42°C, 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 & Sons, N. Y.) at Unit 2.10.

Detailed description of the invention.

The present invention provides methods, apparatus and nomograms to predict disease outcome in prostate cancer patients by means of CpG methylation status in combination with further clinical parameters. The subject matter of the invention thereby aids patients and clinicians in considering various treatment options, for example the use of radical prostatectomy, watchful waiting, radiation therapy, hormone therapy or other adjuvant treatments.

The subject matter of the present invention may be applied directly upon diagnosis of prostate cancer, during therapy or post-therapy as both a prognostic and monitoring means.

The invention provides methods, apparatus and nomograms of use in treatment of prostate cancer patients both prior to receiving a primary treatment (e.g. radical prostatectomy) and after receiving a primary treatment.

It is preferred that the clinical stage of the patient is selected from the group consisting of T3a, T3, T2c, T2b, T2a, T2, TIc, TIb, TIa and Tl.

In one embodiment, the methods, nomograms and apparatus of the invention may be used to determine the prognosis of a patient diagnosed as having prostate cancer.

In a further embodiment, the methods, nomograms and apparatus of the invention may be used to provide a prediction of the probability of disease recurrence, metastasis or patient survival time in a patient diagnosed with prostate cancer.

In yet another embodiment, the methods, nomograms and apparatus of the invention may be used for prediction of the probability of disease recurrence, metastasis or patient survival time in a patient to be treated with a primary treatment.

In a further embodiment, the methods, nomograms and apparatus of the invention may be used for the post-treatment prediction of the probability of disease recurrence; estimated patient survival time or metastasis in a patient treated with radical prostatectomy.

Furthermore, the present invention also provides nomograms and methods of use in determining disease outcome in patients prior to receiving a primary treatment, including, prostatectomy. Such a prognosis is of particular use in determining the suitability of adjuvant therapies in the treatment of a patient. In addition to assisting the patient and physician in selecting an appropriate course of therapy, the nomograms of the present invention are also useful in clinical trials to identify patients appropriate for a trial, to quantify the expected benefit relative to baseline risk, to verify the effectiveness of randomization, to reduce the sample size requirements, and to facilitate comparisons across studies.

Disease recurrence may be characterized as an increased serum PSA level, preferably greater than or equal to 0.2 ng/mL. Alternatively, disease recurrence may be characterized by positive biopsy, bone scan, x-rays, CT scans, MRIs, and PET scans or other imaging test or clinical parameter. Disease recurrence may alternatively be characterized as the need for or the application of further treatment for the cancer because of the high probability of recurrence of the cancer.

Disease metastasis may be characterized by positive biopsy, bone scan, x-rays, CT scans, MRIs, and PET scans or other imaging test or clinical parameter. Disease metastasis may alternatively be characterized as the need for or the application of further treatment for the cancer because of the high probability of metastasis of the cancer.

1. Prostate cancer prognosis.

One embodiment of the invention is directed to a method for providing a prognosis of prostate cancer in a patient.

The method preferably comprises the following steps: i) detecting or determining the methylation status of one or more genomic CpG positions; ii) detecting or determining at least one of the following: pre-treatment PSA; post-treatment PSA; primary Gleason grade in the biopsy specimen; secondary Gleason grade in the biopsy specimen;

Gleason sum in the biopsy specimen; pre- radical primary therapy; total length of cancer in biopsy cores; number of positive biopsy cores; percent of tumor biopsy in a multiple core biopsy set; primary

Gleason grade in the pathological specimen; secondary Gleason grade in the pathological specimen;

Gleason sum in the pathological specimen; pre-operativeTGF-ssl level; prostatic capsular invasion level (PCI); surgical margin status; seminal vesicle involvement; lymph node status; pre-operative

IL6sR level; prior therapy and/or clinical stage; iii) correlating i) and ii) with disease outcome.

Disease outcome may be defined according to at least one of: probability of disease recurrence or metastasis at one or a plurality of time points between one and twenty years e.g. five, ten or fifteen years following said primary treatment; estimated disease or metastasis free survival; organ confined disease; extracapsular extension; seminal vesical involvement and lymph node status in the patient following radical prostatectomy, for each person of the plurality of persons,

In one embodiment the method comprises correlating a selected set of factors determined for each of a plurality of persons previously diagnosed with prostatic cancer with disease outcome (hereinafter also referred to as the "reference dataset") so as to generate a functional representation of the correlation. The selected set of factors includes, but is not limited to, i) the methylation status of one or more genomic CpG positions. It is particularly preferred that said genes are selected from the group consisting of HIST2H2BF regulatory region (SEQ ID NO: 1); PITX2; ABHD9; GSTP1 ; GPR7; CCND2; SEQ ID NO: 7. It is further preferred that said CpG positions are located within the sequences thereof according to Table 1. It is further preferred that said gene is PITX2 and/or regulatory regions thereof. It is further preferred that said CpG positions are located within the sequences thereof according to Table 1.

The selected set of factors further includes, but is not limited to, ii) at least one of the following factors: pre-treatment PSA; post-treatment PSA; primary Gleason grade in the biopsy specimen; secondary Gleason grade in the biopsy specimen; Gleason sum in the biopsy specimen; pre- radical primary therapy; total length of cancer in biopsy cores; number of positive biopsy cores; percent of tumor biopsy in a multiple core biopsy set; primary Gleason grade in the pathological specimen; secondary Gleason grade in the pathological specimen; Gleason sum in the pathological specimen; pre-operative TGF-ssl level; prostatic capsular invasion level (PCI); surgical margin status; seminal vesicle involvement; lymph node status; pre-operative IL6sR level; prior therapy and/or clinical stage. In another embodiment, three or more, e.g., four, five, six or seven, factor values are employed. In a preferred embodiment only one ii) factor value is employed. In one embodiment of the method said factor is selected from the group consisting of primary Gleason grade in the biopsy specimen; secondary Gleason grade in the biopsy specimen; Gleason sum.

In a further embodiment of the method said selected set of factors comprises: i) the methylation status of one or more genomic CpG positions of at least one gene selected from the group consisting of HIST2H2BF regulatory region (SEQ ID NO: 1); PITX2; ABHD9; GSTP1 ; GPR7;

CCND2; SEQ ID NO: 7, wherein it is preferred that said CpG positions are located within the sequences thereof according to Table 1 , and ii) at least one factor selected from the group consisting of primary Gleason grade in the biopsy specimen; secondary Gleason grade in the biopsy specimen; Gleason sum in the biopsy specimen; primary Gleason grade in the pathological specimen; secondary Gleason grade in the pathological specimen and/or Gleason sum in the pathological specimen.

In a further embodiment of the method said selected set of factors comprises: i) the methylation status of one or more genomic CpG positions of the gene PITX2, wherein it is preferred that said CpG positions are located within the sequences thereof according to Table 1 , and ii) at least one selected from the group consisting of primary Gleason grade in the biopsy specimen; secondary Gleason grade in the biopsy specimen; Gleason sum in the biopsy specimen; primary Gleason grade in the pathological specimen; secondary Gleason grade in the pathological specimen and/or Gleason sum in the pathological specimen. The method further comprises determining an identical set of factors determined from the patient and comparing it to the functional representation so as to predict at least one of: probability of disease recurrence or metastasis at one or a plurality of time points between one and twenty years e.g. five, ten or fifteen years following said primary treatment; estimated disease or metastasis free survival; organ confined disease; extracapsular extension; seminal vesical involvement and lymph node status in the patient following radical prostatectomy.

The functional correlation may be generated by any means known in the art. Preferably it is generated by a means selected from the group consisting of a neural network, Cox proportional hazards regression model and support vector machine. Particularly preferred are the Cox proportional hazards regression model and support vector machine. In a preferred embodiment said correlation is generated by computer and/or software means.

In a further embodiment the invention provides an apparatus for predicting probability at least one of: probability of disease recurrence or metastasis at one or a plurality of time points between one and twenty years e.g. five, ten or fifteen years following said primary treatment; estimated disease or metastasis free survival; organ confined disease; extracapsular extension; seminal vesical involvement and lymph node status in the patient following radical prostatectomy.

The apparatus comprises a correlation of clinical factors determined for each of a plurality of persons previously diagnosed with prostatic cancer with disease outcome (at least one of: probability of disease recurrence or metastasis at one or a plurality of time points between one and twenty years e.g. five, ten or fifteen years following said primary treatment; estimated disease or metastasis free survival; organ confined disease; extracapsular extension; seminal vesical involvement and lymph node status in the patient following radical prostatectomy) for each person of said plurality of persons. The apparatus further comprises a means for comparing an identical set of factors determined from the patient diagnosed as having prostatic cancer to the correlation to predict disease outcome. It is particularly preferred that said means is a computer means or a graphical representation (e.g. a nomogram).

The selected set of factors includes, but is not limited to: i)the methylation status of one or more genomic CpG positions. It is particularly preferred that said genes are selected from the group consisting of HIST2H2BF regulatory region (SEQ ID NO: 1 ); PITX2; ABHD9; GSTP1 ; GPR7; CCND2; SEQ ID NO: 7. It is further preferred that said CpG positions are located within the sequences thereof according to Table 1. It is further preferred that said gene is PITX2 and/or regulatory regions thereof. It is particularly preferred that said CpG positions are located within the sequences thereof according to Table 1.

Said selected set of factors further includes, but is not limited to, ii) at least one factor selected from the group consisting of pre-treatment PSA; post-treatment PSA; primary Gleason grade in the biopsy specimen; secondary Gleason grade in the biopsy specimen; Gleason sum in the biopsy specimen; pre- radical primary therapy; total length of cancer in biopsy cores; number of positive biopsy cores; percent of tumor biopsy in a multiple core biopsy set; primary Gleason grade in the pathological specimen; secondary Gleason grade in the pathological specimen; Gleason sum in the pathological specimen; pre-operativeTGF-ssl level; prostatic capsular invasion level (PCI); surgical margin status; seminal vesicle involvement; lymph node status; pre-operative IL6sR level; prior therapy and/or clinical stage. In another embodiment, three or more, e.g., four, five, six or seven, factor values are employed. In one embodiment only one ii) factor value is employed. In one embodiment of the method said factor is selected from the group consisting of primary Gleason grade in the biopsy specimen; secondary Gleason grade in the biopsy specimen; Gleason sum in the biopsy specimen; primary Gleason grade in the pathological specimen; secondary Gleason grade in the pathological specimen and/or Gleason sum in the pathological specimen.

In a further embodiment said selected set of factors comprises: i) the methylation status of one or more genomic CpG positions of at least one gene selected from the group consisting of HIST2H2BF regulatory region (SEQ ID NO: 1 ); PITX2; ABHD9; GSTP1 ; GPR7;

In a further embodiment said selected set of factors comprises: i) the methylation status of one or more genomic CpG positions of the gene PITX2, wherein it is preferred that said CpG positions are located within the sequences thereof according to Table 1 , and ii) at least one factor selected from the group consisting of primary Gleason grade in the biopsy specimen; secondary Gleason grade in the biopsy specimen; Gleason sum in the biopsy specimen; primary Gleason grade in the pathological specimen; secondary Gleason grade in the pathological specimen and/or Gleason sum in the pathological specimen.

It is particularly preferred that the apparatus is stored on a computer accessible means (e.g. electronic database, CD-ROM, DVD-ROM, random access memory, read-only memory, disk, virtual memory or processor).

The apparatus further comprises a means for comparing an identical set of factors determined from the patient diagnosed as having prostatic cancer to the correlation to predict disease outcome (at least one of: probability of disease recurrence or metastasis at one or a plurality of time points between one and twenty years e.g. five, ten or fifteen years following said primary treatment; estimated disease or metastasis free survival; organ confined disease; extracapsular extension; seminal vesical involvement and lymph node status in the patient following radical prostatectomy) in the patient. Preferably said means is in the form of a nomogram or other graphical representation (e.g. tabular), however in an alternative embodiment said means may be a computer implemented means such as software or other computer code, which may be implemented and/or available on portable or other computing devices (e.g. PDA, internet accessible, available on a portable storage medium).

Accordingly, another embodiment of the invention is directed to a nomogram or other graphical representation for the prediction of at least one of: probability of disease recurrence or metastasis at one or a plurality of time points between one and twenty years e.g. five, ten or fifteen years following said primary treatment; estimated disease or metastasis free survival; organ confined disease; extracapsular extension; seminal vesical involvement and lymph node status in the patient following radical prostatectomy which incorporates the factors comprising of i) the methylation status of one or more genomic CpG positions. It is particularly preferred that said genes are selected from the group consisting of HIST2H2BF regulatory region (SEQ ID NO: 1); PITX2; ABHD9; GSTP1 ; GPR7; CCND2; SEQ ID NO: 7. It is further preferred that said gene is PITX2 and/or regulatory regions thereof. It is preferred that said CpG positions are located within the sequences thereof according to Table 1.

The selected set of factors further includes, but is not limited to, ii) at least one factor selected from the group consisting of pre-treatment PSA; post-treatment PSA; primary Gleason grade in the biopsy specimen; secondary Gleason grade in the biopsy specimen; Gleason sum in the biopsy specimen; pre- radical primary therapy; total length of cancer in biopsy cores; number of positive biopsy cores; percent of tumor biopsy in a multiple core biopsy set; primary Gleason grade in the pathological specimen; secondary Gleason grade in the pathological specimen; Gleason sum in the pathological specimen; pre-operativeTGF-ssl level; prostatic capsular invasion level (PCI); surgical margin status; seminal vesicle involvement; lymph node status; pre-operative IL6sR level; prior therapy and/or clinical stage. In another embodiment, three or more, e.g., four, five, six or seven, factor values are employed. In one embodiment only one ii) factor value is employed. In one embodiment of the method said factor is selected from the group consisting of primary Gleason grade in the biopsy specimen; secondary Gleason grade in the biopsy specimen; Gleason sum in the biopsy specimen; primary Gleason grade in the pathological specimen; secondary Gleason grade in the pathological specimen and/or Gleason sum in the pathological specimen.

CCND2; SEQ ID NO: 7, wherein it is preferred that said CpG positions are located within the sequences thereof according to Table 1 , and ii) at least one factor selected from the group consisting of primary Gleason grade in the biopsy specimen; secondary Gleason grade in the biopsy specimen; Gleason sum.

In a further embodiment of the method said selected set of factors comprises: i) the methylation status of one or more genomic CpG positions of the gene PITX2, wherein it is preferred that said CpG positions are located within the sequences thereof according to Table 1 , and ii) at least one factor selected from the group consisting of primary Gleason grade in the biopsy specimen; secondary Gleason grade in the biopsy specimen; Gleason sum in the biopsy specimen; primary Gleason grade in the pathological specimen; secondary Gleason grade in the pathological specimen and/or Gleason sum in the pathological specimen.

Wherein a numeric or dichotomous value (e.g. 1/0; yes/no; positive/negative) is assigned to each of said factors.

The nomogram or other graphical representation of the correlation may be in any suitable format, e.g. in the form of pocket sized cards. Any suitable representation, picture, depiction or exemplification may be used.

It is particularly preferred that it is stored on a computer accessible means (e.g. electronic database, CD-ROM, DVD-ROM, random access memory, read-only memory, disk, virtual memory or processor). It is particularly preferred that the nomogram or other graphical representation of the correlation nomogram or other graphical representation of the correlation may be available as a computer program product which may be available on portable or other computing devices (e.g. PDA, internet accessible, available on a portable storage medium).

The apparatus (e.g. in graphical, nomogram or tabular form) may further comprise a storage mechanism, wherein the storage mechanism stores the correlation as deduced from the reference data set; an input device that inputs the identical set of factors determined from a patient into the apparatus; and a display mechanism, wherein the display mechanism displays a quantitative value for disease outcome (at least one of: probability of disease recurrence or metastasis at one or a plurality of time points between one and twenty years e.g. five, ten or fifteen years following said primary treatment; estimated disease or metastasis free survival; organ confined disease; extracapsular extension; seminal vesical involvement and lymph node status in the patient following radical prostatectomy). The storage mechanism may be random access memory, read-only memory, a disk, virtual memory, a database, and a processor. The input device may be a keypad, a keyboard, stored data, a touch screen, a voice activated system, a downloadable program, downloadable data, a digital interface, a hand-held device, or an infra- red signal device. The display mechanism may be a computer monitor, a cathode ray tub(CRI), a digital screen, a light-emitting diode (LED), a liquid crystal display (LCD), an X-ray, a compressed digitized image, a video image, or a hand-held device. The apparatus may further comprise a display that displays the quantitative value of disease outcome (at least one of: probability of disease recurrence or metastasis at one or a plurality of time points between one and twenty years e.g. five, ten or fifteen years following said primary treatment; estimated disease or metastasis free survival; organ confined disease; extracapsular extension; seminal vesical involvement and lymph node status in the patient following radical prostatectomy), e. g., the display is separated from the processor such that the display receives the quantitative probability. The apparatus may further comprise a database, wherein the database stores the correlation of factors and is accessible by the processor. The apparatus may further comprise an input device that inputs the identical set of factors determined from the patient diagnosed as having prostatic cancer into the apparatus. The input device stores the identical set of factors in a storage mechanism that is accessible by the processor. The apparatus may further comprise a transmission medium for transmitting the selected set of factors. The transmission medium is coupled to the processor and the correlation of factors. The apparatus may further comprise a transmission medium for transmitting the identical set of factors determined from the patient diagnosed as having prostatic cancer, preferably the transmission medium is coupled to the processor and the correlation of factors.

The processor may be a multi-purpose or a dedicated processor. The processor includes an object oriented program having libraries, said libraries storing said correlation of factors.

In one embodiment, the nomogram comprises a graphic representation of disease outcome (at least one of: probability of disease recurrence or metastasis at one or a plurality of time points between one and twenty years e.g. five, ten or fifteen years following said primary treatment; estimated disease or metastasis free survival; organ confined disease; extracapsular extension; seminal vesical involvement and lymph node status in the patient following radical prostatectomy) comprising a substrate or solid support, and a set of indicia on the substrate or solid support, the indicia comprising i)a plot indicating the methylation status of one or more genomic CpG positions. It is particularly preferred that said genes are selected from the group consisting of HIST2H2BF regulatory region (SEQ ID NO: 1 ); PITX2; ABHD9; GSTP1 ; GPR7; CCND2; SEQ ID NO: 7. It is further preferred that said gene is PITX2 and/or regulatory regions thereof.

The selected set of indicia further includes, but is not limited to, ii) at least one plot indicating a factor selected from the group consisting of pre-treatment PSA; post- treatment PSA; primary Gleason grade in the biopsy specimen; secondary Gleason grade in the biopsy specimen; Gleason sum in the biopsy specimen; pre- radical primary therapy; total length of cancer in biopsy cores; number of positive biopsy cores; percent of tumor biopsy in a multiple core biopsy set; primary Gleason grade in the pathological specimen; secondary Gleason grade in the pathological specimen; Gleason sum in the pathological specimen; pre-operativeTGF-ssl level; prostatic capsular invasion level (PCI); surgical margin status; seminal vesicle involvement; lymph node status; pre-operative IL6sR level; prior therapy and/or clinical stage); and/or clinical stage. In another embodiment, three or more, e.g., four, five, six or seven, of said ii) plots are employed. In one embodiment only one ii) plot is employed. In one embodiment of the method said indicia is selected from the group consisting of primary Gleason grade in the biopsy specimen; secondary Gleason grade in the biopsy specimen; Gleason sum in the biopsy specimen; primary Gleason grade in the pathological specimen; secondary Gleason grade in the pathological specimen and/or Gleason sum in the pathological specimen.

In a further embodiment said selected set of indicia comprises: i) a plot indicating the methylation status of one or more genomic CpG positions of at least one gene selected from the group consisting of HIST2H2BF regulatory region (SEQ ID NO: 1 ); PITX2; ABHD9; GSTP1 ; GPR7; CCND2; SEQ ID NO: 7, wherein it is preferred that said CpG positions are located within the sequences thereof according to Table 1 , and ii) at least one plot indicating a factor selected from the group consisting of primary Gleason grade in the biopsy specimen; secondary Gleason grade in the biopsy specimen; Gleason sum in the biopsy specimen; primary Gleason grade in the pathological specimen; secondary Gleason grade in the pathological specimen and/or Gleason sum in the pathological specimen.

In a further embodiment said selected set of factors comprises: i) a plot indicating the methylation status of one or more genomic CpG positions of the gene PITX2, wherein it is preferred that said CpG positions are located within the sequences thereof according to

Table 1 , and ii) at least one plot indicating a factor selected from the group consisting of primary Gleason grade in the biopsy specimen; secondary Gleason grade in the biopsy specimen; Gleason sum in the biopsy specimen; primary Gleason grade in the pathological specimen; secondary Gleason grade in the pathological specimen and/or Gleason sum in the pathological specimen.

In one embodiment the plurality of plots (A) is disposed on a solid support such that each factor has values on the said plots.

The invention further comprises a "predictor points" scale (B) which has values on the predictor points scale which are disposed on the solid support with respect to the values on the aforementioned plurality of plots (A) such that each value on said plots (A) may be assigned a points value.

The invention further comprises a total points scale (C) which has values on said scale wherein the sum of the points measured using (B) of the plurality of factors of (A) may be correlated to one of: probability of disease recurrence or metastasis at one or a plurality of time points between one and twenty years e.g. five, ten or fifteen years following said primary therapy; estimated disease or metastasis free survival. Said prostate cancer outcome may also be in the form of one or a plurality of outcome scales (D) which has values disposed on the solid support such that the values on the scale (C) may be correlated to the values on the scale (D). The invention may further optionally comprise a linear predictor points scale (C) which has values on said scale wherein the sum of the points measured using the total points scale (C) may be correlated to the outcome scale (D).

Figures 1 to 7 provide exemplary nomograms according to the invention.

The solid support is preferably a laminated card that can be easily carried on a person.

2. Prediction of disease recurrence, metastasis or patient survival time. One embodiment of the invention is directed to a method for providing a prediction of the probability of disease outcome (preferably disease recurrence, metastasis and/or patient survival time) in a patient diagnosed with prostate cancer.

The method preferably comprises the following steps: i) detecting or determining the methylation status of one or more genomic CpG positions; ii) detecting or determining at least one factor selected from the group consisting of: pre-treatment

PSA; primary Gleason grade in the biopsy specimen; secondary Gleason grade in the biopsy specimen; Gleason sum; previous therapy and/or clinical stage, iii) correlating i) and ii) with disease outcome.

It is further preferred that said gene is PITX2 and/or regulatory regions thereof. It is further preferred that said CpG positions are located within the sequence thereof according to Table 1.

It is further preferred that said at least one factor is selected from the group consisting of primary Gleason grade in the biopsy specimen; secondary Gleason grade in the biopsy specimen; Gleason sum.

In this embodiment disease outcome may be defined according to at least one of: probability of disease metastasis at one or a plurality of time points between one and twenty years e.g. five, ten or fifteen years; estimated patient survival time; estimated metastasis free survival for each person of the plurality of persons.

In one embodiment the method comprises correlating a selected set of factors determined for each of a plurality of persons previously diagnosed with prostatic cancer with disease outcome (hereinafter also referred to as the "reference dataset"), so as to generate a functional representation of the correlation.

The selected set of factors includes, but is not limited to, i) the methylation status of one or more genomic CpG positions. It is particularly preferred that said genes are selected from the group consisting of HIST2H2BF regulatory region (SEQ ID NO: 1); PITX2; ABHD9; GSTP1; GPR7; CCND2; SEQ ID NO: 7. It is further preferred that said CpG positions are located within the sequences thereof according to Table 1. It is further preferred that said gene is PITX2 and/or regulatory regions thereof. It is further preferred that said CpG positions are located within the sequences thereof according to Table 1.

The selected set of factors further includes, but is not limited to, ii) at least one of the following factors: pre-treatment PSA; primary Gleason grade in the biopsy specimen; secondary Gleason grade in the biopsy specimen; Gleason sum; previous therapy and/or clinical stage. In another embodiment, three or more, e.g., four, five, six or seven, factor values are employed. In a preferred embodiment only one ii) factor value is employed. In one embodiment of the method said factor is selected from the group consisting of primary Gleason grade in the biopsy specimen; secondary Gleason grade in the biopsy specimen; Gleason sum.

In a further embodiment of the method said selected set of factors comprises: i) the methylation status of one or more genomic CpG positions of at least one gene selected from the group consisting of HIST2H2BF regulatory region (SEQ ID NO: 1); PITX2; ABHD9; GSTP1; GPR7;

In a further embodiment of the method said selected set of factors comprises: i) the methylation status of one or more genomic CpG positions of the gene PITX2, wherein it is preferred that said CpG positions are located within the sequences thereof according to Table 1 , and ii) at least one selected from the group consisting of primary Gleason grade in the biopsy specimen; secondary Gleason grade in the biopsy specimen; Gleason sum.

The method further comprises determining an identical set of factors determined from the patient and comparing it to the functional representation so as to predict the probability of disease metastasis at one or a plurality of time points between one and twenty years e.g. five, ten or fifteen years ; estimated patient survival time or estimated metastasis free survival.

In this embodiment, the reference dataset comprises previously individuals diagnosed with prostatic cancer.

In a further embodiment the invention provides an apparatus for predicting probability of one of: probability of disease metastasis at one or a plurality of time points between one and twenty years e.g. five, ten or fifteen years; estimated patient survival time; estimated metastasis free survival in a patient with prostatic. The apparatus comprises a correlation of clinical factors determined for each of a plurality of persons previously diagnosed with prostatic cancer and treated by means of with disease outcome (probability of disease metastasis at one or a plurality of time points between one and twenty years e.g. five, ten or fifteen years; estimated patient survival time; estimated metastasis free survival) for each person of said plurality of persons. The apparatus further comprises a means for comparing an identical set of factors determined from the patient diagnosed as having prostatic cancer to the correlation to predict disease outcome. It is particularly preferred that said means is a computer means or a graphical representation (e.g. a nomogram).

The selected set of factors includes, but is not limited to: i) the methylation status of one or more genomic CpG positions. It is particularly preferred that said genes are selected from the group consisting of HIST2H2BF regulatory region (SEQ ID NO: 1); PITX2; ABHD9; GSTP1 ; GPR7; CCND2; SEQ ID NO: 7. It is further preferred that said CpG positions are located within the sequences thereof according to Table 1. It is further preferred that said gene is PITX2 and/or regulatory regions thereof. It is particularly preferred that said CpG positions are located within the sequences thereof according to Table t

Said selected set of factors further includes, but is not limited to, ii)at least one factor selected from the group consisting of pre-treatment PSA; primary Gleason grade in the biopsy specimen; secondary Gleason grade in the biopsy specimen; Gleason sum; previous therapy ; and/or clinical stage. In another embodiment, three or more, e.g., four, five, six or seven, factor values are employed. In one embodiment only one ii) factor value is employed. In one embodiment of the method said factor is selected from the group consisting primary Gleason grade in the biopsy specimen; secondary Gleason grade in the biopsy specimen; Gleason sum.

In a further embodiment said selected set of factors comprises: i) the methylation status of one or more genomic CpG positions of the gene PITX2, wherein it is preferred that said CpG positions are located within the sequences thereof according to Table 1 , and ii) at least one factor selected from the group consisting of primary Gleason grade in the biopsy specimen; secondary Gleason grade in the biopsy specimen; Gleason sum.

The apparatus further comprises a means for comparing an identical set of factors determined from the patient diagnosed as having prostatic cancer to the correlation to predict disease outcome (probability of disease metastasis at one or a plurality of time points between one and twenty years e.g. five, ten or fifteen years ; estimated patient survival time ; estimated metastasis free survival) in the patient. Preferably said means is in the form of a nomogram or other graphical representation (e.g. tabular), however in an alternative embodiment said means may be a computer implemented means such as software or other computer code, which may be implemented and/or available on portable or other computing devices (e.g. PDA, internet accessible, available on a portable storage medium).

Accordingly, another embodiment of the invention is directed to a nomogram or other graphical representation for the prediction of at least one of probability of disease metastasis at one or a plurality of time points between one and twenty years e.g. five, ten or fifteen years ; estimated patient survival time ; estimated metastasis free survival which incorporates the factors comprising of i) the methylation status of one or more genomic CpG positions. It is particularly preferred that said genes are selected from the group consisting of HIST2H2BF regulatory region (SEQ ID NO: 1); PITX2; ABHD9; GSTP1 ; GPR7; CCND2; SEQ ID NO: 7. It is further preferred that said gene is PITX2 and/or regulatory regions thereof. It is preferred that said CpG positions are located within the sequences thereof according to Table 1.

The selected set of factors further includes, but is not limited to, ii) at least one factor selected from the group consisting of pre-treatment PSA; primary Gleason grade in the biopsy specimen; secondary Gleason grade in the biopsy specimen; Gleason sum; previous therapy; and/or clinical stage. In another embodiment, three or more, e.g., four, five, six or seven, factor values are employed. In one embodiment only one ii) factor value is employed. In one embodiment of the method said factor is selected from the group consisting of primary Gleason grade in the biopsy specimen; secondary Gleason grade in the biopsy specimen; Gleason sum.

In a further embodiment said selected set of factors comprises: i) the methylation status of one or more genomic CpG positions of at least one gene selected from the group consisting of HIST2H2BF regulatory region (SEQ ID NO: 1); PITX2; ABHD9; GSTP1 ; GPR7; CCND2; SEQ ID NO: 7, wherein it is preferred that said CpG positions are located within the sequences thereof according to Table 1 , and ii) at least one factor selected from the group consisting of primary Gleason grade in the biopsy specimen; secondary Gleason grade in the biopsy specimen; Gleason sum.

In a further embodiment of the method said selected set of factors comprises: i) the methylation status of one or more genomic CpG positions of the gene PITX2, wherein it is preferred that said CpG positions are located within the sequences thereof according to Table 1 , and ii) at least one factor selected from the group consisting of primary Gleason grade in the biopsy specimen; secondary Gleason grade in the biopsy specimen; Gleason sum.

Wherein a numeric or dichotomous value (e.g. 1/0; yes/no; positive/negative) is assigned to each of said factors. The nomogram or other graphical representation of the correlation may be in any suitable format, e.g. in the form of pocket sized cards. Any suitable representation, picture, depiction or exemplification may be used.

The apparatus (e.g. in graphical, nomogram or tabular form) may further comprise a storage mechanism, wherein the storage mechanism stores the correlation as deduced from the reference data set; an input device that inputs the identical set of factors determined from a patient into the apparatus; and a display mechanism, wherein the display mechanism displays a quantitative value for disease outcome (probability of disease metastasis at one or a plurality of time points between one and twenty years e.g. five, ten or fifteen years ; estimated patient survival; estimated metastasis free survival). The storage mechanism may be random access memory, read-only memory, a disk, virtual memory, a database, and a processor. The input device may be a keypad, a keyboard, stored data, a touch screen, a voice activated system, a downloadable program, downloadable data, a digital interface, a hand-held device, or an infra- red signal device. The display mechanism may be a computer monitor, a cathode ray tub(CRI), a digital screen, a light-emitting diode (LED), a liquid crystal display (LCD), an X-ray, a compressed digitized image, a video image, or a hand-held device. The apparatus may further comprise a display that displays the quantitative value of disease outcome (probability of disease metastasis at one or a plurality of time points between one and twenty years e.g. five, ten or fifteen years ; estimated patient survival; estimated metastasis free survival), e. g., the display is separated from the processor such that the display receives the quantitative probability. The apparatus may further comprise a database, wherein the database stores the correlation of factors and is accessible by the processor. The apparatus may further comprise an input device that inputs the identical set of factors determined from the patient diagnosed as having prostatic cancer into the apparatus. The input device stores the identical set of factors in a storage mechanism that is accessible by the processor. The apparatus may further comprise a transmission medium for transmitting the selected set of factors. The transmission medium is coupled to the processor and the correlation of factors. The apparatus may further comprise a transmission medium for transmitting the identical set of factors determined from the patient diagnosed as having prostatic cancer, preferably the transmission medium is coupled to the processor and the correlation of factors.

The processor may be a multi-purpose or a dedicated processor. The processor includes an object oriented program having libraries, said libraries storing said correlation of factors. In one embodiment, the nomogram comprises a graphic representation of disease outcome (probability of disease metastasis at one or a plurality of time points between one and twenty years e.g. five, ten or fifteen years ; estimated patient survival time or estimated metastasis free survival) comprising a substrate or solid support, and a set of indicia on the substrate or solid support, the indicia comprising i) a plot indicating the methylation status of one or more genomic CpG positions. It is particularly preferred that said genes are selected from the group consisting of HIST2H2BF regulatory region (SEQ ID NO: 1); PITX2; ABHD9; GSTP1; GPR7; CCND2; SEQ ID NO: 7. It is further preferred that said gene is PITX2 and/or regulatory regions thereof.

The selected set of indicia further includes, but is not limited to, ii) at least one plot indicating a factor selected from the group consisting of pre-treatment PSA; primary Gleason grade in the biopsy specimen; secondary Gleason grade in the biopsy specimen; Gleason sum; previous therapy (e. g., hormone or radiation); and/or clinical stage. In another embodiment, three or more, e.g., four, five, six or seven, of said ii) plots are employed. In one embodiment only one ii) plot is employed. In one embodiment of the method said indicia is selected from the group consisting of primary Gleason grade in the biopsy specimen; secondary Gleason grade in the biopsy specimen; Gleason sum.

In a further embodiment said selected set of indicia comprises: i) a plot indicating the methylation status of one or more genomic CpG positions of at least one gene selected from the group consisting of HIST2H2BF regulatory region (SEQ ID NO: 1 ); PITX2; ABHD9;

GSTP1 ; GPR7; CCND2; SEQ ID NO: 7, wherein it is preferred that said CpG positions are located within the sequences thereof according to Table 1 , and ii) at least one plot indicating a factor selected from the group consisting of primary Gleason grade in the biopsy specimen; secondary Gleason grade in the biopsy specimen; Gleason sum.

Table 1, and ii) at least one plot indicating a factor selected from the group consisting of primary Gleason grade in the biopsy specimen; secondary Gleason grade in the biopsy specimen; Gleason sum.

The invention further comprises a "predictor points" scale (B) which has values on the predictor points scale which are disposed on the solid support with respect to the values on the aforementioned plurality of plots (A) such that each value on said plots (A) may be assigned a points value. The invention further comprises a total points scale (C) which has values on said scale wherein the sum of the points measured using (B) of the plurality of factors of (A) may be correlated to one of: probability of disease metastasis at one or a plurality of time points between one and twenty years e.g. five, ten or fifteen years ; estimated patient survival time; estimated metastasis free survival. Said prostate cancer outcome may also be in the form of one or a plurality of outcome scales (D) which has values disposed on the solid support such that the values on the scale (C) may be correlated to the values on the scale (D). The invention may further optionally comprise a linear predictor points scale (C) which has values on said scale wherein the sum of the points measured using the total points scale (C) may be correlated to the outcome scale (D).

Figures 1 to 7 provide exemplary nomograms according to the invention. The solid support is preferably a laminated card that can be easily carried on a person.

3. Prediction of disease progression after primary treatment using pre-operative factors. One embodiment of the invention is directed to a method for prediction of disease outcome (preferably disease recurrence, metastasis and/or patient survival time) in a patient to be treated with a primary treatment. Said primary treatment is preferably selected from the group consisting of surgical treatment, cryotherapy, radiation therapy, brachytherapy, and hormonal therapy. Said primary treatment is most preferably prostatectomy or radical prostatectomy.

PSA; primary Gleason grade in the biopsy specimen; secondary Gleason grade in the biopsy specimen; Gleason sum; previous therapy and/or clinical stage iii) correlating i) and ii) with disease outcome.

Disease outcome may be defined according to at least one of: probability of disease recurrence or metastasis at one or a plurality of time points between one and twenty years e.g. five, ten or fifteen years following said primary treatment; estimated patient survival time; estimated disease or metastasis free survival for each person of the plurality of persons.

In one embodiment the method comprises correlating a selected set of factors determined for each of a plurality of persons previously diagnosed with prostatic cancer and treated with said primary treatment, most preferably radical prostatectomy with disease outcome (hereinafter also referred to as the "reference dataset", so as to generate a functional representation of the correlation.

The selected set of factors includes, but is not limited to, i) the methylation status of one or more genomic CpG positions. It is particularly preferred that said genes are selected from the group consisting of HIST2H2BF regulatory region (SEQ ID NO: 1); PITX2; ABHD9; GSTP1 ; GPR7; CCND2; SEQ ID NO: 7. It is further preferred that said CpG positions are located within the sequences thereof according to Table 1. It is further preferred that said gene is PITX2 and/or regulatory regions thereof. It is further preferred that said CpG positions are located within the sequences thereof according to Table t

The method further comprises determining an identical set of factors determined from the patient and comparing it to the functional representation so as to predict the probability of disease recurrence or metastasis at one or a plurality of time points between one and twenty years e.g. five, ten or fifteen years following primary treatment estimated patient survival time or estimated disease or metastasis free survival to be treated with said primary therapy.

In this embodiment, the reference dataset comprises previously individuals diagnosed with prostatic cancer and treated with a primary therapy. It is preferred that said primary therapy is selected form the group consisting of surgical treatment, cryotherapy, radiation therapy, brachytherapy, and hormonal therapy.

In this embodiment, the reference dataset most preferably comprises previously individuals diagnosed with prostatic cancer and treated with radical prostatectomy.

In this embodiment, the reference dataset comprises previously individuals diagnosed with prostatic cancer and treated with a primary therapy but not with further adjuvant treatments (e.g. radiation therapy, chemotherapy, cryotherapy, ultrasound, targeted therapies and/or hormone therapy).

In a further preferred embodiment, the reference dataset comprises pre-operative factors of persons with clinically localized prostate cancer treated by means of radical prostatectomy but not with further adjuvant treatments (e.g. radiation therapy, chemotherapy, cryotherapy, ultrasound, targeted therapies and/or hormone therapy).

In a further embodiment the invention provides an apparatus for predicting probability of one of: probability of disease recurrence or metastasis at one or a plurality of time points between one and twenty years e.g. five, ten or fifteen years following said primary therapy; estimated patient survival time following said primary therapy; estimated disease or metastasis free survival in a patient with prostatic cancer treated with said primary therapy. The apparatus comprises a correlation of clinical factors determined for each of a plurality of persons previously diagnosed with prostatic cancer and treated by means of to be treated with said primary therapy with disease outcome (probability of disease recurrence or metastasis at one or a plurality of time points between one and twenty years e.g. five, ten or fifteen years following said primary therapy; estimated patient survival time following said primary therapy; estimated disease or metastasis free survival) for each person of said plurality of persons.

The apparatus further comprises a means for comparing an identical set of factors determined from the patient diagnosed as having prostatic cancer to the correlation to predict disease outcome. It is particularly preferred that said means is a computer means or a graphical representation (e.g. a nomogram).

The selected set of factors includes, but is not limited to: i)the methylation status of one or more genomic CpG positions. It is particularly preferred that said genes are selected from the group consisting of HIST2H2BF regulatory region (SEQ ID NO: 1); PITX2; ABHD9; GSTP1 ; GPR7; CCND2; SEQ ID NO: 7. It is further preferred that said CpG positions are located within the sequences thereof according to Table 1. It is further preferred that said gene is PITX2 and/or regulatory regions thereof. It is particularly preferred that said CpG positions are located within the sequences thereof according to Table t

In a further embodiment said selected set of factors comprises: i) the methylation status of one or more genomic CpG positions of at least one gene selected from the group consisting of HIST2H2BF regulatory region (SEQ ID NO: 1); PITX2; ABHD9; GSTP1 ; GPR7;

The apparatus further comprises a means for comparing an identical set of factors determined from the patient diagnosed as having prostatic cancer to the correlation to predict disease outcome (probability of disease recurrence or metastasis at one or a plurality of time points between one and twenty years e.g. five, ten or fifteen years following said primary therapy; estimated patient survival time following said primary therapy; estimated disease or metastasis free survival) in the patient. Preferably said means is in the form of a nomogram or other graphical representation (e.g. tabular), however in an alternative embodiment said means may be a computer implemented means such as software or other computer code, which may be implemented and/or available on portable or other computing devices (e.g. PDA, internet accessible, available on a portable storage medium). Accordingly, another embodiment of the invention is directed to a nomogram or other graphical representation for the prediction of at least one of probability of disease recurrence or metastasis at one or a plurality of time points between one and twenty years e.g. five, ten or fifteen years following said primary therapy; estimated patient survival time following said primary therapy; estimated disease or metastasis free survival which incorporates the factors comprising of i) the methylation status of one or more genomic CpG positions. It is particularly preferred that said genes are selected from the group consisting of HIST2H2BF regulatory region (SEQ ID NO: 1); PITX2; ABHD9; GSTP1 ; GPR7; CCND2; SEQ ID NO: 7. It is further preferred that said gene is PITX2 and/or regulatory regions thereof. It is preferred that said CpG positions are located within the sequences thereof according to Table 1.

The nomogram or other graphical representation of the correlation may be in any suitable format, e.g. in the form of pocket sized cards. Any suitable representation, picture, depiction or exemplification may be used. It is particularly preferred that it is stored on a computer accessible means (e.g. electronic database, CD-ROM, DVD-ROM, random access memory, read-only memory, disk, virtual memory or processor). It is particularly preferred that the nomogram or other graphical representation of the correlation nomogram or other graphical representation of the correlation may be available as a computer program product which may be available on portable or other computing devices (e.g. PDA, internet accessible, available on a portable storage medium).

The apparatus (e.g. in graphical, nomogram or tabular form) may further comprise a storage mechanism, wherein the storage mechanism stores the correlation as deduced from the reference data set; an input device that inputs the identical set of factors determined from a patient into the apparatus; and a display mechanism, wherein the display mechanism displays a quantitative value for disease outcome (probability of disease recurrence or metastasis at one or a plurality of time points between one and twenty years e.g. five, ten or fifteen years following said primary therapy; estimated patient survival; estimated disease or metastasis free survival). The storage mechanism may be random access memory, read-only memory, a disk, virtual memory, a database, and a processor. The input device may be a keypad, a keyboard, stored data, a touch screen, a voice activated system, a downloadable program, downloadable data, a digital interface, a hand-held device, or an infra- red signal device. The display mechanism may be a computer monitor, a cathode ray tub(CRI), a digital screen, a light-emitting diode (LED), a liquid crystal display (LCD), an X-ray, a compressed digitized image, a video image, or a hand-held device. The apparatus may further comprise a display that displays the quantitative value of disease outcome (probability of disease recurrence or metastasis at one or a plurality of time points between one and twenty years e.g. five, ten or fifteen years following said primary therapy; estimated patient survival; estimated disease or metastasis free survival), e. g., the display is separated from the processor such that the display receives the quantitative probability. The apparatus may further comprise a database, wherein the database stores the correlation of factors and is accessible by the processor. The apparatus may further comprise an input device that inputs the identical set of factors determined from the patient diagnosed as having prostatic cancer into the apparatus. The input device stores the identical set of factors in a storage mechanism that is accessible by the processor. The apparatus may further comprise a transmission medium for transmitting the selected set of factors. The transmission medium is coupled to the processor and the correlation of factors. The apparatus may further comprise a transmission medium for transmitting the identical set of factors determined from the patient diagnosed as having prostatic cancer, preferably the transmission medium is coupled to the processor and the correlation of factors.

In one embodiment, the nomogram comprises a graphic representation of disease outcome (probability of disease recurrence or metastasis at one or a plurality of time points between one and twenty years e.g. five, ten or fifteen years following said primary therapy; estimated patient survival time or estimated disease or metastasis free survival) comprising a substrate or solid support, and a set of indicia on the substrate or solid support, the indicia comprising i) a plot indicating the methylation status of one or more genomic CpG positions. It is particularly preferred that said genes are selected from the group consisting of HIST2H2BF regulatory region (SEQ ID NO: 1); PITX2; ABHD9; GSTP1 ; GPR7; CCND2; SEQ ID NO: 7. It is further preferred that said gene is PITX2 and/or regulatory regions thereof.

In a further embodiment said selected set of indicia comprises: i) a plot indicating the methylation status of one or more genomic CpG positions of at least one gene selected from the group consisting of HIST2H2BF regulatory region (SEQ ID NO: 1); PITX2; ABHD9;

Table 1 , and ii) at least one plot indicating a factor selected from the group consisting of primary Gleason grade in the biopsy specimen; secondary Gleason grade in the biopsy specimen; Gleason sum.

The invention further comprises a total points scale (C) which has values on said scale wherein the sum of the points measured using (B) of the plurality of factors of (A) may be correlated to one of: probability of disease recurrence or metastasis at one or a plurality of time points between one and twenty years e.g. five, ten or fifteen years following said primary therapy; estimated patient survival time; estimated disease or metastasis free survival. Said prostate cancer outcome may also be in the form of one or a plurality of outcome scales (D) which has values disposed on the solid support such that the values on the scale (C) may be correlated to the values on the scale (D). The invention may further optionally comprise a linear predictor points scale (C) which has values on said scale wherein the sum of the points measured using the total points scale (C) may be correlated to the outcome scale (D).

4. Prediction of disease progression after prostatectomy using pre-operative factors comprising biopsy.

One embodiment of the invention is directed to a method for prediction of the probability of disease recurrence, metastasis or patient survival time in a patient to be treated with a primary treatment. Said primary treatment is preferably selected from the group consisting of surgical treatment, cryotherapy, radiation therapy, brachytherapy, and hormonal therapy. Said primary treatment is most preferably prostatectomy or radical prostatectomy.

The method comprises the following steps: i) detecting or determining the methylation status of one or more genomic CpG positions; ii) detecting or determining at least one factor selected from the group consisting of: pre-treatment

PSA; primary Gleason grade in the biopsy specimen; secondary Gleason grade in the biopsy specimen; Gleason sum; previous therapy and/or clinical stage, iii) detecting or determining at least one factor selected from the group consisting of: total length of cancer in the biopsy cores; number of positive cores and percent of tumor in a multiple core biopsy set iii) correlating i), ii) and iii) with disease outcome.

Disease outcome may be defined according to at least one of: probability of disease recurrence or metastasis at one or a plurality of time points between one and twenty years e.g. five, ten or fifteen years following said primary treatment; estimated patient survival time; estimated disease or metastasis free survival for each person of the plurality of persons. In one embodiment the method comprises correlating a selected set of factors determined for each of a plurality of persons previously diagnosed with prostatic cancer and treated with said primary treatment, most preferably radical prostatectomy with disease outcome (hereinafter also referred to as the "reference dataset"), so as to generate a functional representation of the correlation.

The selected set of factors further includes, but is not limited to, ii) at least one of the following factors: pre-treatment PSA; primary Gleason grade in the biopsy specimen; secondary Gleason grade in the biopsy specimen; Gleason sum; previous therapy and/or clinical stage. In another embodiment, three or more, e.g., four, five, six or seven, factor values are employed. In a preferred embodiment only one ii) factor value is employed. In one embodiment of the method said factor is selected from the group consisting of primary Gleason grade in the biopsy specimen; secondary Gleason grade in the biopsy specimen; Gleason sum. The selected set of factors further includes, but is not limited to at least one of the following: iii) total length of cancer in the biopsy cores; number of positive cores and percent of tumor in a multiple core biopsy set.

CCND2; SEQ ID NO: 7, wherein it is preferred that said CpG positions are located within the sequences thereof according to Table 1 , and ii) at least one factor selected from the group consisting of primary Gleason grade in the biopsy specimen; secondary Gleason grade in the biopsy specimen; Gleason sum; the selected set of factors further includes, but is not limited to at least one of the following: iii) total length of cancer in the biopsy cores; number of positive cores and percent of tumor in a multiple core biopsy set.

In a further embodiment of the method said selected set of factors comprises: i) the methylation status of one or more genomic CpG positions of the gene PITX2, wherein it is preferred that said CpG positions are located within the sequences thereof according to Table 1 , ii) at least one factor selected from the group consisting of primary Gleason grade in the biopsy specimen; secondary Gleason grade in the biopsy specimen; Gleason sum.

The selected set of factors further includes, but is not limited to at least one of the following: iii) total length of cancer in the biopsy cores; number of positive cores and percent of tumor in a multiple core biopsy set.

The selected set of factors includes, but is not limited to: i) the methylation status of one or more genomic CpG positions. It is particularly preferred that said genes are selected from the group consisting of HIST2H2BF regulatory region (SEQ ID NO: 1); PITX2; ABHD9; GSTP1 ; GPR7; CCND2; SEQ ID NO: 7. It is further preferred that said CpG positions are located within the sequences thereof according to Table 1. It is further preferred that said gene is PITX2 and/or regulatory regions thereof. It is particularly preferred that said CpG positions are located within the sequences thereof according to Table 1.

Said selected set of factors further includes, but is not limited to, ii) at least one factor selected from the group consisting of pre-treatment PSA; primary Gleason grade in the biopsy specimen; secondary Gleason grade in the biopsy specimen; Gleason sum; previous therapy; and/or clinical stage. In another embodiment, three or more, e.g., four, five, six or seven, factor values are employed. In one embodiment only one ii) factor value is employed. In one embodiment of the method said factor is selected from the group consisting primary Gleason grade in the biopsy specimen; secondary Gleason grade in the biopsy specimen; Gleason sum.

CCND2; SEQ ID NO: 7, wherein it is preferred that said CpG positions are located within the sequences thereof according to Table 1 , ii) at least one factor selected from the group consisting of primary Gleason grade in the biopsy specimen; secondary Gleason grade in the biopsy specimen; Gleason sum; previous therapy; and/or clinical stage, and iii) total length of cancer in the biopsy cores; number of positive cores and percent of tumor in a multiple core biopsy set.

In a further embodiment said selected set of factors comprises: i) the methylation status of one or more genomic CpG positions of the gene PITX2, wherein it is preferred that said CpG positions are located within the sequences thereof according to Table 1 , and ii) at least one factor selected from the group consisting of primary Gleason grade in the biopsy specimen; secondary Gleason grade in the biopsy specimen; Gleason sum; the selected set of factors further includes, but is not limited to at least one of the following: iii) total length of cancer in the biopsy cores; number of positive cores and percent of tumor in a multiple core biopsy set.

The apparatus further comprises a means for comparing an identical set of factors determined from the patient diagnosed as having prostatic cancer to the correlation to predict disease outcome (probability of disease recurrence or metastasis at one or a plurality of time points between one and twenty years e.g. five, ten or fifteen years following said primary therapy; estimated patient survival time following said primary therapy; estimated disease or metastasis free survival) in the patient. Preferably said means is in the form of a nomogram or other graphical representation (e.g. tabular), however in an alternative embodiment said means may be a computer implemented means such as software or other computer code, which may be implemented and/or available on portable or other computing devices (e.g. PDA, internet accessible, available on a portable storage medium).

Accordingly, another embodiment of the invention is directed to a nomogram or other graphical representation for the prediction of at least one of probability of disease recurrence or metastasis at one or a plurality of time points between one and twenty years e.g. five, ten or fifteen years following said primary therapy; estimated patient survival time following said primary therapy; estimated disease or metastasis free survival which incorporates the factors comprising of i) the methylation status of one or more genomic CpG positions. It is particularly preferred that said genes are selected from the group consisting of HIST2H2BF regulatory region (SEQ ID NO: 1); PITX2; ABHD9; GSTP1 ; GPR7; CCND2; SEQ ID NO: 7. It is further preferred that said gene is PITX2 and/or regulatory regions thereof. It is preferred that said CpG positions are located within the sequences thereof according to Table 1.

The selected set of factors further includes, but is not limited to, ii) at least one factor selected from the group consisting of pre-treatment PSA; primary Gleason grade in the biopsy specimen; secondary Gleason grade in the biopsy specimen; Gleason sum; previous therapy; and/or clinical stage. In another embodiment, three or more, e.g., four, five, six or seven, factor values are employed. In one embodiment only one ii) factor value is employed. In one embodiment of the method said factor is selected from the group consisting of primary Gleason grade in the biopsy specimen; secondary Gleason grade in the biopsy specimen; Gleason sum. The selected set of factors further includes, but is not limited to at least one of the following: iii) total length of cancer in the biopsy cores; number of positive cores and percent of tumor in a multiple core biopsy set.

CCND2; SEQ ID NO: 7, wherein it is preferred that said CpG positions are located within the sequences thereof according to Table 1 , and ii) at least one factor selected from the group consisting of primary Gleason grade in the biopsy specimen; secondary Gleason grade in the biopsy specimen; Gleason sum, the selected set of factors further includes, but is not limited to at least one of the following: iii) total length of cancer in the biopsy cores; number of positive cores and percent of tumor in a multiple core biopsy set.

In a further embodiment of the method said selected set of factors comprises: i) the methylation status of one or more genomic CpG positions of the gene PITX2, wherein it is preferred that said CpG positions are located within the sequences thereof according to Table 1 , and ii) at least one factor selected from the group consisting of primary Gleason grade in the biopsy specimen; secondary Gleason grade in the biopsy specimen; Gleason sum, the selected set of factors further includes, but is not limited to at least one of the following: iii) total length of cancer in the biopsy cores; number of positive cores and percent of tumor in a multiple core biopsy set.

The apparatus (e.g. in graphical, nomogram or tabular form) may further comprise a storage mechanism, wherein the storage mechanism stores the correlation as deduced from the reference data set; an input device that inputs the identical set of factors determined from a patient into the apparatus, and a display mechanism, wherein the display mechanism displays a quantitative value for disease outcome (probability of disease recurrence or metastasis at one or a plurality of time points between one and twenty years e g five, ten or fifteen years following said primary therapy, estimated patient survival, estimated disease or metastasis free survival) The storage mechanism may be random access memory, read-only memory, a disk, virtual memory, a database, and a processor The input device may be a keypad, a keyboard, stored data, a touch screen, a voice activated system, a downloadable program, downloadable data, a digital interface, a hand-held device, or an infra- red signal device The display mechanism may be a computer monitor, a cathode ray tub(CRI), a digital screen, a light-emitting diode (LED), a liquid crystal display (LCD), an X-ray, a compressed digitized image, a video image, or a hand-held device The apparatus may further comprise a display that displays the quantitative value of disease outcome (probability of disease recurrence or metastasis at one or a plurality of time points between one and twenty years e g five, ten or fifteen years following said primary therapy, estimated patient survival, estimated disease or metastasis free survival), e g , the display is separated from the processor such that the display receives the quantitative probability The apparatus may further comprise a database, wherein the database stores the correlation of factors and is accessible by the processor The apparatus may further comprise an input device that inputs the identical set of factors determined from the patient diagnosed as having prostatic cancer into the apparatus The input device stores the identical set of factors in a storage mechanism that is accessible by the processor The apparatus may further comprise a transmission medium for transmitting the selected set of factors The transmission medium is coupled to the processor and the correlation of factors The apparatus may further comprise a transmission medium for transmitting the identical set of factors determined from the patient diagnosed as having prostatic cancer, preferably the transmission medium is coupled to the processor and the correlation of factors

The processor may be a multi-purpose or a dedicated processor The processor includes an object oriented program having libraries, said libraries storing said correlation of factors

In one embodiment, the nomogram comprises a graphic representation of disease outcome (probability of disease recurrence or metastasis at one or a plurality of time points between one and twenty years e g five, ten or fifteen years following said primary therapy, estimated patient survival time or estimated disease or metastasis free survival) comprising a substrate or solid support, and a set of indicia on the substrate or solid support, the indicia comprising ι) a plot indicating the methylation status of one or more genomic CpG positions It is particularly preferred that said genes are selected from the group consisting of HIST2H2BF regulatory region (SEQ ID NO 1), PITX2, ABHD9, GSTP1 , GPR7, CCND2, SEQ ID NO 7 It is further preferred that said gene is PITX2 and/or regulatory regions thereof

The selected set of indicia further includes, but is not limited to, n) at least one plot indicating a factor selected from the group consisting of pre-treatment PSA, primary Gleason grade in the biopsy specimen, secondary Gleason grade in the biopsy specimen, Gleason sum, previous therapy (e g , hormone or radiation), and/or clinical stage In another embodiment, three or more, e.g., four, five, six or seven, of said ii) plots are employed. In one embodiment only one ii) plot is employed. In one embodiment of the method said indicia is selected from the group consisting of primary Gleason grade in the biopsy specimen; secondary Gleason grade in the biopsy specimen; Gleason sum iii) at least one plot indicating a factor selected from the group consisting of total length of cancer in the biopsy cores; number of positive cores and percent of tumor in a multiple core biopsy set.

GSTP1 ; GPR7; CCND2; SEQ ID NO: 7, wherein it is preferred that said CpG positions are located within the sequences thereof according to Table 1 , and ii) at least one plot indicating a factor selected from the group consisting of primary Gleason grade in the biopsy specimen; secondary Gleason grade in the biopsy specimen; Gleason sum, iii) at least one plot indicating a factor selected from the group consisting of total length of cancer in the biopsy cores; number of positive cores and percent of tumor in a multiple core biopsy set.

Table 1, and ii) at least one plot indicating a factor selected from the group consisting of primary Gleason grade in the biopsy specimen; secondary Gleason grade in the biopsy specimen; Gleason sum iii) at least one plot indicating a factor selected from the group consisting of total length of cancer in the biopsy cores; number of positive cores and percent of tumor in a multiple core biopsy set.

5. Prediction of disease progression after primary treatment using pre-operative factors. One embodiment of the invention is directed to a method for the post-treatment prediction of the probability of disease recurrence; estimated patient survival time or metastasis in a patient treated with a primary treatment. Said primary treatment is preferably selected from the group consisting of surgical treatment, cryotherapy, radiation therapy, brachytherapy, and hormonal therapy.

PSA; primary Gleason grade in the pathological specimen; secondary Gleason grade in the pathological specimen; Gleason sum; pre-operativeTGF-ssl level; prostatic capsular invasion level

(PCI); surgical margin status; seminal vesicle involvement; lymph node status; pre-operative IL6sR level; prior therapy and/or clinical stage, and iii) correlating i) and ii) with disease outcome.

It is further preferred that said at least one factor is selected from the group consisting of primary Gleason grade in the pathological specimen; secondary Gleason grade in the pathological specimen; Gleason sum.

Disease outcome may be determined as any of probability of disease recurrence or metastasis at one or a plurality of time points between one and twenty years e.g. five, ten or fifteen years following said primary treatment; estimated patient survival time; estimated disease or metastasis free survival.

In one embodiment the method comprises correlating a selected set of factors determined for each of a plurality of persons previously diagnosed with prostatic cancer and treated with said primary treatment (hereinafter also referred to as the "reference dataset") with disease outcome, so as to generate a functional representation of the correlation. The selected set of factors includes, but is not limited to, i) the methylation status of one or more genomic CpG positions. It is particularly preferred that said genes are selected from the group consisting of HIST2H2BF regulatory region (SEQ ID NO: 1); PITX2; ABHD9; GSTP1 ; GPR7; CCND2; SEQ ID NO: 7. It is further preferred that said CpG positions are located within the sequences thereof according to Table 1. It is further preferred that said gene is PITX2 and/or regulatory regions thereof. It is further preferred that said CpG positions are located within the sequences thereof according to Table 1.

The selected set of factors further includes, but is not limited to, ii) at least one of the following factors: pre-treatment PSA; primary Gleason grade in the pathological specimen; secondary Gleason grade in the pathological specimen; Gleason sum; pre-operative TGF-ssl level; prostatic capsular invasion level (PCI); surgical margin status; seminal vesicle involvement; lymph node status; pre-operative IL6sR level; prior therapy and/or clinical stage. In another embodiment, three or more, e.g., four, five, six or seven, factor values are employed. In a preferred embodiment only one ii) factor value is employed. In one embodiment of the method said factor is selected from the group consisting of primary Gleason grade in the pathological specimen; secondary Gleason grade in the pathological specimen; Gleason sum.

CCND2; SEQ ID NO: 7, wherein it is preferred that said CpG positions are located within the sequences thereof according to Table 1 , and ii) at least one factor selected from the group consisting of primary Gleason grade in the pathological specimen; secondary Gleason grade in the pathological specimen; Gleason sum.

In a further embodiment of the method said selected set of factors comprises: i) the methylation status of one or more genomic CpG positions of the gene PITX2, wherein it is preferred that said CpG positions are located within the sequences thereof according to Table 1 , and ii) at least one selected from the group consisting of primary Gleason grade in the pathological specimen; secondary Gleason grade in the pathological specimen; Gleason sum.

The method further comprises determining an identical set of factors determined from the patient and comparing it to the functional representation so as to predict the probability of disease recurrence or metastasis at one or a plurality of time points between one and twenty years e.g. five, ten or fifteen years following said primary treatment; estimated patient survival time or estimated disease or metastasis free survival after treatment with said primary treatment.

In this embodiment, the reference dataset comprises patients previously diagnosed with prostatic cancer and treated with a primary treatment. Said primary treatment is preferably selected from the group consisting of surgical treatment, cryotherapy, radiation therapy, brachytherapy, and hormonal therapy.

In this embodiment, the reference dataset comprises previously individuals diagnosed with prostatic cancer and treated with said primary therapy but not with further adjuvant treatments (e.g. radiation therapy, chemotherapy, cryotherapy, ultrasound, targeted therapies and/or hormone therapy).

In a further embodiment the invention provides an apparatus for predicting probability of one of: probability of disease recurrence or metastasis at one or a plurality of time points between one and twenty years e.g. five, ten or fifteen years following said primary treatment; estimated patient survival time; estimated disease or metastasis free survival in a patient with prostatic cancer treated with said primary treatment. The apparatus comprises a correlation of clinical factors determined for each of a plurality of persons previously diagnosed with prostatic cancer and treated by means of said primary treatment with disease outcome (probability of disease recurrence or metastasis at one or a plurality of time points between one and twenty years e.g. five, ten or fifteen years following said primary treatment; estimated patient survival time; estimated disease or metastasis free survival) for each person of said plurality of persons.

Said selected set of factors further includes, but is not limited to, ii)at least one factor selected from the group consisting of pre-treatment PSA; primary Gleason grade in the pathological specimen; secondary Gleason grade in the pathological specimen; Gleason sum; pre-operative TGF-ssl level; prostatic capsular invasion level (PCI); surgical margin status; seminal vesicle involvement; lymph node status; pre-operative IL6sR level; prior therapy; and/or clinical stage. In another embodiment, three or more, e.g., four, five, six or seven, factor values are employed. In one embodiment only one ii) factor value is employed. In one embodiment of the method said factor is selected from the group consisting primary Gleason grade in the pathological specimen; secondary Gleason grade in the pathological specimen; Gleason sum.

In a further embodiment said selected set of factors comprises: i) the methylation status of one or more genomic CpG positions of the gene PITX2, wherein it is preferred that said CpG positions are located within the sequences thereof according to Table 1 , and ii) at least one factor selected from the group consisting of primary Gleason grade in the pathological specimen; secondary Gleason grade in the pathological specimen; Gleason sum.

The apparatus further comprises a means for comparing an identical set of factors determined from the patient diagnosed as having prostatic cancer to the correlation to predict disease outcome (probability of disease recurrence or metastasis at one or a plurality of time points between one and twenty years e.g. five, ten or fifteen years following said primary therapy; estimated patient survival time; estimated disease or metastasis free survival) in the patient. Preferably said means is in the form of a nomogram or other graphical representation (e.g. tabular), however in an alternative embodiment said means may be a computer implemented means such as software or other computer code, which may be implemented and/or available on portable or other computing devices (e.g. PDA, internet accessible, available on a portable storage medium).

The selected set of factors further includes, but is not limited to, ii) at least one factor selected from the group consisting of pre-treatment PSA; primary Gleason grade in the pathological specimen; secondary Gleason grade in the pathological specimen; Gleason sum; pre-operative TGF-ssl level; prostatic capsular invasion level (PCI); surgical margin status; seminal vesicle involvement; lymph node status; pre-operative IL6sR level; prior therapy and/or clinical stage. In another embodiment, three or more, e.g., four, five, six or seven, factor values are employed. In one embodiment only one ii) factor value is employed. In one embodiment of the method said factor is selected from the group consisting of primary Gleason grade in the pathological specimen; secondary Gleason grade in the pathological specimen; Gleason sum.

CCN D2; SEQ ID NO: 7, wherein it is preferred that said CpG positions are located within the sequences thereof according to Table 1 , and ii) at least one factor selected from the group consisting of primary Gleason grade in the pathological specimen; secondary Gleason grade in the pathological specimen; Gleason sum.

In a further embodiment of the method said selected set of factors comprises: i) the methylation status of one or more genomic CpG positions of the gene PITX2, wherein it is preferred that said CpG positions are located within the sequences thereof according to Table 1 , and ii) at least one factor selected from the group consisting of primary Gleason grade in the pathological specimen; secondary Gleason grade in the pathological specimen; Gleason sum.

It is particularly preferred that it is stored on a computer accessible means (e.g. electronic database, CD-ROM, DVD-ROM, random access memory, read-only memory, disk, virtual memory or processor). It is particularly preferred that the nomogram or other graphical representation of the correlation nomogram or other graphical representation of the correlation may be available as a computer program product which may be available on portable or other computing devices (e.g. PDA, internet accessible, available on a portable storage medium). The apparatus (e.g. in graphical, nomogram or tabular form) may further comprise a storage mechanism, wherein the storage mechanism stores the correlation as deduced from the reference data set; an input device that inputs the identical set of factors determined from a patient into the apparatus; and a display mechanism, wherein the display mechanism displays a quantitative value for disease outcome (probability of disease recurrence; or metastasis at one or a plurality of time points between one and twenty years e.g. five, ten or fifteen years following said primary therapy; estimated patient survival time; estimated disease or metastasis free survival). The storage mechanism may be random access memory, read-only memory, a disk, virtual memory, a database, and a processor. The input device may be a keypad, a keyboard, stored data, a touch screen, a voice activated system, a downloadable program, downloadable data, a digital interface, a hand-held device, or an infra- red signal device. The display mechanism may be a computer monitor, a cathode ray tub (CRI), a digital screen, a light-emitting diode (LED), a liquid crystal display (LCD), an X-ray, a compressed digitized image, a video image, or a hand-held device. The apparatus may further comprise a display that displays the quantitative value of disease outcome (probability of disease recurrence or metastasis at one or a piuraiity of time points between one and twenty years e.g. five, ten or fifteen years following said primary therapy; estimated patient survival time; estimated disease or metastasis free survival), e. g., the display is separated from the processor such that the display receives the quantitative probability. The apparatus may further comprise a database, wherein the database stores the correlation of factors and is accessible by the processor. The apparatus may further comprise an input device that inputs the identical set of factors determined from the patient diagnosed as having prostatic cancer into the apparatus. The input device stores the identical set of factors in a storage mechanism that is accessible by the processor. The apparatus may further comprise a transmission medium for transmitting the selected set of factors. The transmission medium is coupled to the processor and the correlation of factors. The apparatus may further comprise a transmission medium for transmitting the identical set of factors determined from the patient diagnosed as having prostatic cancer, preferably the transmission medium is coupled to the processor and the correlation of factors.

In one embodiment, the nomogram comprises a graphic representation of disease outcome (probability of disease recurrence or metastasis at one or a plurality of time points between one and twenty years e.g. five, ten or fifteen years following said primary therapy; estimated patient survival time; or estimated disease or metastasis free survival) comprising a substrate or solid support, and a set of indicia on the substrate or solid support, the indicia comprising i) a plot indicating the methylation status of one or more genomic CpG positions. It is particularly preferred that said genes are selected from the group consisting of HIST2H2BF regulatory region (SEQ ID NO: 1); PITX2; ABHD9; GSTP1 ; GPR7; CCND2; SEQ ID NO: 7. It is further preferred that said gene is PITX2 and/or regulatory regions thereof. The selected set of indicia further includes, but is not limited to, ii) at least one plot indicating a factor selected from the group consisting of pre-treatment PSA; primary Gleason grade in the pathological specimen; secondary Gleason grade in the pathological specimen; Gleason sum; pre-operativeTGF-ssl level; prostatic capsular invasion level (PCI); surgical margin status; seminal vesicle involvement; lymph node status; pre-operative IL6sR level; prior therapy and/or clinical stage. In another embodiment, three or more, e.g., four, five, six or seven, of said ii) plots are employed. In one embodiment only one ii) plot is employed. In one embodiment of the method said indicia is selected from the group consisting of primary Gleason grade in the pathological specimen; secondary Gleason grade in the pathological specimen; Gleason sum.

GSTP1 ; GPR7; CCND2; SEQ ID NO: 7, wherein it is preferred that said CpG positions are located within the sequences thereof according to Table 1 , and ii) at least one plot indicating a factor selected from the group consisting of primary Gleason grade in the pathological specimen; secondary Gleason grade in the pathological specimen; Gleason sum.

Table 1 , and ii) at least one plot indicating a factor selected from the group consisting of primary Gleason grade in the pathological specimen; secondary Gleason grade in the pathological specimen; Gleason sum.

The invention further comprises a total points scale (C) which has values on said scale wherein the sum of the points measured using (B) of the plurality of factors of (A) may be correlated to one of: probability of disease recurrence or metastasis at one or a plurality of time points between one and twenty years e.g. five, ten or fifteen years following said primary therapy; estimated patient survival time; estimated disease or metastasis free survival. Said prostate cancer outcome may also be in the form of an outcome scale (D) which has values disposed on the solid support such that the values on the scale (C) may be correlated to the values on the scale (D). The invention may further optionally comprise a linear predictor points scale (C) which has values on said scale wherein the sum of the points measured using the total points scale (C) may be correlated to the outcome scale (D).

6. Prediction of disease progression after prostatectomy using post-operative factors. One embodiment of the invention is directed to a method for the post-surgical prediction of the probability of disease recurrence; estimated patient survival time or metastasis in a patient treated with radical prostatectomy.

(PCI); surgical margin status; seminal vesicle involvement; lymph node status; pre-operative IL6sR level; prior therapy and/or clinical stage iii) correlating i) and ii) with disease outcome.

Disease outcome may be determined as any of: probability of disease recurrence or metastasis at one or a plurality of time points between one and twenty years e.g. five, ten or fifteen years following prostatectomy; estimated patient survival time; estimated disease or metastasis free survival.

In one embodiment the method comprises correlating a selected set of factors determined for each of a plurality of persons previously diagnosed with prostatic cancer and treated with radical prostatectomy (hereinafter also referred to as the "reference dataset") with disease outcome for each person of the plurality of persons, so as to generate a functional representation of the correlation. The selected set of factors includes, but is not limited to, i) the methylation status of one or more genomic CpG positions. It is particularly preferred that said genes are selected from the group consisting of HIST2H2BF regulatory region (SEQ ID NO: 1); PITX2; ABHD9; GSTP1 ; GPR7; CCND2; SEQ ID NO: 7. It is further preferred that said CpG positions are located within the sequences thereof according to Table 1. It is further preferred that said gene is PITX2 and/or regulatory regions thereof. It is further preferred that said CpG positions are located within the sequences thereof according to Table 1.

The method further comprises determining an identical set of factors determined from the patient and comparing it to the functional representation so as to predict the probability of disease recurrence or metastasis at one or a plurality of time points between one and twenty years e.g. five, ten or fifteen years following prostatectomy; estimated patient survival time or estimated disease or metastasis free survival to be treated with radical prostatectomy.

In this embodiment, the reference dataset comprises patients previously diagnosed with prostatic cancer and treated with radical prostatectomy. In this embodiment, the reference dataset comprises previously individuals diagnosed with prostatic cancer and treated with a primary therapy but not with further adjuvant treatments (e.g. radiation therapy, chemotherapy, cryotherapy, ultrasound, targeted therapies and/or hormone therapy).

In a further embodiment the invention provides an apparatus for predicting probability of one of: probability of disease recurrence or metastasis at one or a plurality of time points between one and twenty years e.g. five, ten or fifteen years following prostatectomy; estimated patient survival time; estimated disease or metastasis free survival in a patient with prostatic cancer treated with radical prostatectomy. The apparatus comprises a correlation of clinical factors determined for each of a plurality of persons previously diagnosed with prostatic cancer and treated by means of to be treated with radical prostatectomy with disease outcome (probability of disease recurrence or metastasis at one or a plurality of time points between one and twenty years e.g. five, ten or fifteen years following prostatectomy; estimated patient survival time; estimated disease or metastasis free survival) for each person of said plurality of persons.

The selected set of factors includes, but is not limited to: i)the methylation status of one or more genomic CpG positions. It is particularly preferred that said genes are selected from the group consisting of HIST2H2BF regulatory region (SEQ ID NO: 1 ); PITX2; ABHD9; GSTP1 ; GPR7; CCND2; SEQ ID NO: 7. It is further preferred that said CpG positions are located within the sequences thereof according to Table 1. It is further preferred that said gene is PITX2 and/or regulatory regions thereof. It is particularly preferred that said CpG positions are located within the sequences thereof according to Table t

The apparatus further comprises a means for comparing an identical set of factors determined from the patient diagnosed as having prostatic cancer to the correlation to predict disease outcome (probability of disease recurrence or metastasis at one or a plurality of time points between one and twenty years e.g. five, ten or fifteen years following prostatectomy; estimated patient survival time; estimated disease or metastasis free survival) in the patient. Preferably said means is in the form of a nomogram or other graphical representation (e.g. tabular), however in an alternative embodiment said means may be a computer implemented means such as software or other computer code, which may be implemented and/or available on portable or other computing devices (e.g. PDA, internet accessible, available on a portable storage medium).

The selected set of factors further includes, but is not limited to, ii) at least one factor selected from the group consisting of pre-treatment PSA; primary Gleason grade in the pathological specimen; secondary Gleason grade in the pathological specimen; Gleason sum; pre-operativeTGF-ssl level; prostatic capsular invasion level (PCI); surgical margin status; seminal vesicle involvement; lymph node status; pre-operative IL6sR level; prior therapy and/or clinical stage. In another embodiment, three or more, e.g., four, five, six or seven, factor values are employed. In one embodiment only one ii) factor value is employed. In one embodiment of the method said factor is selected from the group consisting of primary Gleason grade in the pathological specimen; secondary Gleason grade in the pathological specimen; Gleason sum.

It is particularly preferred that it is stored on a computer accessible means (e.g. electronic database, CD-ROM, DVD-ROM, random access memory, read-only memory, disk, virtual memory or processor). It is particularly preferred that the nomogram or other graphical representation of the correlation nomogram or other graphical representation of the correlation may be available as a computer program product which may be available on portable or other computing devices (e.g. PDA, internet accessible, available on a portable storage medium). The apparatus (e.g. in graphical, nomogram or tabular form) may further comprise a storage mechanism, wherein the storage mechanism stores the correlation as deduced from the reference data set; an input device that inputs the identical set of factors determined from a patient into the apparatus; and a display mechanism, wherein the display mechanism displays a quantitative value for disease outcome (probability of disease recurrence; or metastasis at one or a plurality of time points between one and twenty years e.g. five, ten or fifteen years following prostatectomy; estimated patient survival time; estimated disease or metastasis free survival). The storage mechanism may be random access memory, read-only memory, a disk, virtual memory, a database, and a processor. The input device may be a keypad, a keyboard, stored data, a touch screen, a voice activated system, a downloadable program, downloadable data, a digital interface, a hand-held device, or an infra- red signal device. The display mechanism may be a computer monitor, a cathode ray tub(CRI), a digital screen, a light-emitting diode (LED), a liquid crystal display (LCD), an X-ray, a compressed digitized image, a video image, or a hand-held device. The apparatus may further comprise a display that displays the quantitative value of disease outcome (probability of disease recurrence or metastasis at one or a plurality of time points between one and twenty years e.g. five, ten or fifteen years following prostatectomy; estimated patient survival time; estimated disease or metastasis free survival), e. g., the display is separated from the processor such that the display receives the quantitative probability. The apparatus may further comprise a database, wherein the database stores the correlation of factors and is accessible by the processor. The apparatus may further comprise an input device that inputs the identical set of factors determined from the patient diagnosed as having prostatic cancer into the apparatus. The input device stores the identical set of factors in a storage mechanism that is accessible by the processor. The apparatus may further comprise a transmission medium for transmitting the selected set of factors. The transmission medium is coupled to the processor and the correlation of factors. The apparatus may further comprise a transmission medium for transmitting the identical set of factors determined from the patient diagnosed as having prostatic cancer, preferably the transmission medium is coupled to the processor and the correlation of factors.

In one embodiment, the nomogram comprises a graphic representation of disease outcome (probability of disease recurrence or metastasis at one or a plurality of time points between one and twenty years e.g. five, ten or fifteen years following prostatectomy; estimated patient survival time; or estimated disease or metastasis free survival) comprising a substrate or solid support, and a set of indicia on the substrate or solid support, the indicia comprising i) a plot indicating the methylation status of one or more genomic CpG positions. It is particularly preferred that said genes are selected from the group consisting of HIST2H2BF regulatory region (SEQ ID NO: 1); PITX2; ABHD9; GSTP1; GPR7; CCND2; SEQ ID NO: 7. It is further preferred that said gene is PITX2 and/or regulatory regions thereof.

The selected set of indicia further includes, but is not limited to, ii) at least one plot indicating a factor selected from the group consisting of pre-treatment PSA; primary Gleason grade in the pathological specimen; secondary Gleason grade in the pathological specimen; Gleason sum; pre-operative TGF-ssl level; prostatic capsular invasion level (PCI); surgical margin status; seminal vesicle involvement; lymph node status; pre-operative IL6sR level; prior therapy and/or clinical stage. In another embodiment, three or more, e.g., four, five, six or seven, of said ii) plots are employed. In one embodiment only one ii) plot is employed. In one embodiment of the method said indicia is selected from the group consisting of primary Gleason grade in the pathological specimen; secondary Gleason grade in the pathological specimen; Gleason sum.

The invention further comprises a total points scale (C) which has values on said scale wherein the sum of the points measured using (B) of the plurality of factors of (A) may be correlated to one of: probability of disease recurrence or metastasis at one or a plurality of time points between one and twenty years e.g. five, ten or fifteen years following prostatectomy; estimated patient survival time; estimated disease or metastasis free survival. Said prostate cancer outcome may also be in the form of an outcome scale (D) which has values disposed on the solid support such that the values on the scale (C) may be correlated to the values on the scale (D). The invention may further optionally comprise a linear predictor points scale (C) which has values on said scale wherein the sum of the points measured using the total points scale (C) may be correlated to the outcome scale (D).

6. Determining the need for adjuvant treatment.

One embodiment of the invention is directed to a method for determining a need for an adjuvant therapy in a patient treated with radical prostatectomy. The method comprises correlating a selected set of factors determined for each of a plurality of persons previously diagnosed with prostatic cancer and treated with radical prostatectomy (hereinafter also referred to as the "reference dataset") with disease outcome according to at least one of: probability of disease recurrence or metastasis at one or a plurality of time points between one and twenty years e.g. five, ten or fifteen years following prostatectomy; estimated patient survival time; estimated patient survival time; estimated disease or metastasis free survival for each person of the plurality of persons, so as to generate a functional representation of the correlation.

The selected set of factors includes, but is not limited to, i) the methylation status of one or more genomic CpG positions. It is particularly preferred that said genes are selected from the group consisting of HIST2H2BF regulatory region (SEQ ID NO: 1); PITX2; ABHD9; GSTP1 ; GPR7; CCND2; SEQ ID NO: 7. It is further preferred that said CpG positions are located within the sequences thereof according to Table 1. It is further preferred that said gene is PITX2 and/or regulatory regions thereof. It is further preferred that said CpG positions are located within the sequences thereof according to Table !

In a further embodiment of the method said selected set of factors comprises: i) the methylation status of one or more genomic CpG positions of at least one gene selected from the group consisting of HIST2H2BF regulatory region (SEQ ID NO: 1); PITX2; ABHD9; GSTP1 ; GPR7; CCND2; SEQ ID NO: 7, wherein it is preferred that said CpG positions are located within the sequences thereof according to Table 1 , and ii) at least one factor selected from the group consisting of primary Gleason grade in the pathological specimen; secondary Gleason grade in the pathological specimen; Gleason sum.

In this embodiment, the reference dataset comprises previously individuals diagnosed with prostatic cancer and treated with radical prostatectomy.

The apparatus further comprises a means for comparing an identical set of factors determined from the patient diagnosed as having prostatic cancer to the correlation to predict disease outcome. It is particularly preferred that said means is a computer means or a graphical representation (e.g. a nomogram). The selected set of factors includes, but is not limited to: i)the methylation status of one or more genomic CpG positions. It is particularly preferred that said genes are selected from the group consisting of HIST2H2BF regulatory region (SEQ ID NO: 1); PITX2; ABHD9; GSTP1 ; GPR7; CCND2; SEQ ID NO: 7. It is further preferred that said CpG positions are located within the sequences thereof according to Table 1. It is further preferred that said gene is PITX2 and/or regulatory regions thereof. It is particularly preferred that said CpG positions are located within the sequences thereof according to Table 1.

In a further embodiment of the method said selected set of factors comprises: i) the methylation status of one or more genomic CpG positions of the gene PITX2, wherein it is preferred that said CpG positions are located within the sequences thereof according to Table 1 , and ii) at least one factor selected from the group consisting of primary Gleason grade in the pathological specimen; secondary Gleason grade in the pathological specimen; Gleason sum. Wherein a numeric or dichotomous value (e.g. 1/0; yes/no; positive/negative) is assigned to each of said factors.

The apparatus (e.g. in graphical, nomogram or tabular form) may further comprise a storage mechanism, wherein the storage mechanism stores the correlation as deduced from the reference data set; an input device that inputs the identical set of factors determined from a patient into the apparatus; and a display mechanism, wherein the display mechanism displays a quantitative value for disease outcome (probability of disease recurrence or metastasis at one or a plurality of time points between one and twenty years e.g. five, ten or fifteen years following prostatectomy; estimated patient survival time; estimated disease or metastasis free survival). The storage mechanism may be random access memory, read-only memory, a disk, virtual memory, a database, and a processor. The input device may be a keypad, a keyboard, stored data, a touch screen, a voice activated system, a downloadable program, downloadable data, a digital interface, a hand-held device, or an infra- red signal device. The display mechanism may be a computer monitor, a cathode ray tub(CRI), a digital screen, a light-emitting diode (LED), a liquid crystal display (LCD), an X-ray, a compressed digitized image, a video image, or a hand-held device. The apparatus may further comprise a display that displays the quantitative value of disease outcome (probability of disease recurrence or metastasis at one or a plurality of time points between one and twenty years e.g. five, ten or fifteen years following prostatectomy; estimated patient survival time; estimated disease or metastasis free survival), e. g., the display is separated from the processor such that the display receives the quantitative probability. The apparatus may further comprise a database, wherein the database stores the correlation of factors and is accessible by the processor. The apparatus may further comprise an input device that inputs the identical set of factors determined from the patient diagnosed as having prostatic cancer into the apparatus. The input device stores the identical set of factors in a storage mechanism that is accessible by the processor. The apparatus may further comprise a transmission medium for transmitting the selected set of factors. The transmission medium is coupled to the processor and the correlation of factors. The apparatus may further comprise a transmission medium for transmitting the identical set of factors determined from the patient diagnosed as having prostatic cancer, preferably the transmission medium is coupled to the processor and the correlation of factors. The processor may be a multi-purpose or a dedicated processor. The processor includes an object oriented program having libraries, said libraries storing said correlation of factors.

In one embodiment, the nomogram comprises a graphic representation of disease outcome (probability of disease recurrence or metastasis at one or a plurality of time points between one and twenty years e.g. five, ten or fifteen years following prostatectomy estimated patient survival time; or estimated disease or metastasis free survival) comprising a substrate or solid support, and a set of indicia on the substrate or solid support, the indicia comprising i) a plot indicating the methylation status of one or more genomic CpG positions. It is particularly preferred that said genes are selected from the group consisting of HIST2H2BF regulatory region (SEQ ID NO: 1); PITX2; ABHD9; GSTP1 ; GPR7; CCND2; SEQ ID NO: 7. It is further preferred that said gene is PITX2 and/or regulatory regions thereof.

The selected set of indicia further includes, but is not limited to, ii) at least one plot indicating a factor selected from the group consisting of pre-treatment PSA; primary Gleason grade in the pathological specimen; secondary Gleason grade in the pathological specimen; Gleason sum; pre-operativeTGF-ssl level; prostatic capsular invasion level (PCI); surgical margin status; seminal vesicle involvement; lymph node status; pre-operative IL6sR level; prior therapy and/or clinical stage. In another embodiment, three or more, e.g., four, five, six or seven, of said ii) plots are employed. In one embodiment only one ii) plot is employed. In one embodiment of the method said indicia is selected from the group consisting of primary Gleason grade in the pathological specimen; secondary Gleason grade in the pathological specimen; Gleason sum.

In one embodiment the plurality of plots (A) is disposed on a solid support such that each factor has values on the said plots. The invention further comprises a "predictor points" scale (B) which has values on the predictor points scale which are disposed on the solid support with respect to the values on the aforementioned plurality of plots (A) such that each value on said plots (A) may be assigned a points value.

The invention further comprises a total points scale (C) which has values on said scale wherein the sum of the points measured using (B) of the plurality of factors of (A) may be correlated to one of: probability of disease recurrence or metastasis at one or a plurality of time points between one and twenty years e.g. five, ten or fifteen years following prostatectomy; estimated patient survival time; estimated disease or metastasis free survival. Said prostate cancer outcome may also be in the form of an outcome scale (D) which has values disposed on the solid support such that the values on the scale (C) may be correlated to the values on the scale (D).

Methylation Assay Procedures.

Bisulfite modification of DNA is an art-recognized tool used to assess CpG methylation status. 5- methylcytosine is the most frequent covalent base modification in the DNA of eukaryotic cells. It plays a role, for example, in the regulation of the transcription, in genetic imprinting, and in tumorigenesis. Therefore, the identification of 5-methylcytosine as a component of genetic information is of considerable interest. However, 5-methylcytosine positions cannot be identified by sequencing, because 5-methylcytosine has the same base pairing behavior as cytosine. Moreover, the epigenetic information carried by 5-methylcytosine is completely lost during, e.g., PCR amplification.

The most frequently used method for analyzing DNA for the presence of 5-methylcytosine is based upon the specific reaction of bisulfite with cytosine whereby, upon subsequent alkaline hydrolysis, cytosine is converted to uracil, which corresponds to thymine in its base pairing behavior. Significantly, however, 5-methylcytosine remains unmodified under these conditions. Consequently, the original DNA is converted in such a manner that methylcytosine, which originally could not be distinguished from cytosine by its hybridization behavior, can now be detected as the only remaining cytosine using standard, art-recognized molecular biological techniques, for example, by amplification and hybridization, or by sequencing. All of these techniques are based on differential base pairing properties, which can now be fully exploited.

The present invention provides for the use of the bisulfite technique, in combination with one or more methylation assays, for determination of the methylation status of CpG dinucleotide sequences within genes, preferably those according to Table 1 and more preferably the gene PITX2. Accordingly the invention also provides the bisulfite converted sequences thereof.

Various methylation assay procedures are known in the art, and can be used in conjunction with the present invention. These assays allow for determination of the methylation state of one or a plurality of CpG dinucleotides (e.g., CpG islands) within a DNA sequence. Such assays involve, among other techniques, DNA sequencing of bisulfite-treated DNA, PCR (for sequence-specific amplification), Southern blot analysis, and use of methylation-sensitive restriction enzymes.

For example, genomic sequencing has been simplified for analysis of DNA methylation patterns and 5- methylcytosine distribution by using bisulfite treatment (Frommer et al., Proc. Natl. Acad. Sci. USA 89:1827-1831 , 1992). Additionally, restriction enzyme digestion of PCR products amplified from bisulfite-converted DNA is used, e.g., the method described by Sadri and Hornsby (Nucl. Acids Res. 24:5058-5059, 1996), or COBRA (Combined Bisulfite Restriction Analysis) (Xiong and Laird, Nucleic Acids Res. 25:2532-2534, 1997).

COBRA. COBRA analysis is a quantitative methylation assay useful for determining DNA methylation levels at specific gene loci in small amounts of genomic DNA (Xiong and Laird, Nucleic Acids Res. 25:2532-2534, 1997). Briefly, restriction enzyme digestion is used to reveal methylation-dependent sequence differences in PCR products of sodium bisulfite-treated DNA. Methylation-dependent sequence differences are first introduced into the genomic DNA by standard bisulfite treatment according to the procedure described by Frommer et al. {Proc. Natl. Acad. Sci. USA 89:1827-1831 , 1992). PCR amplification of the bisulfite converted DNA is then performed using primers specific for the CpG islands of interest, followed by restriction endonuclease digestion, gel electrophoresis, and detection using specific, labeled hybridization probes. Methylation levels in the original DNA sample are represented by the relative amounts of digested and undigested PCR product in a linearly quantitative fashion across a wide spectrum of DNA methylation levels. In addition, this technique can be reliably applied to DNA obtained from microdissected paraffin-embedded tissue samples. 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 bisulfite treated DNA sequence or CpG island); restriction enzyme and appropriate buffer; gene-hybridization oligo; control hybridization oligo; kinase labeling kit for oligo probe; and labelled 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.

Preferably, assays such as "MethyLight™" (a fluorescence-based real-time PCR technique) (Eads et al., Cancer Res. 59:2302-2306, 1999), Ms-SNuPE (Methylation-sensitive Single Nucleotide Primer Extension) reactions (Gonzalgo & Jones, Nucleic Acids Res. 25:2529-2531 , 1997), methylation- specific PCR ("MSP"; Herman et al., Proc. Natl. Acad. Sci. USA 93:9821-9826, 1996; US Patent No. 5,786,146), and methylated CpG island amplification ("MCA"; Toyota et al., Cancer Res. 59:2307-12, 1999) are used alone or in combination with other of these methods.

MethyLight™. The MethyLight™ assay is a high-throughput quantitative methylation assay that utilizes fluorescence-based real-time PCR (TaqMan™) technology that requires no further manipulations after the PCR step (Eads et al., Cancer Res. 59:2302-2306, 1999). Briefly, the MethyLight™ process begins with a mixed sample of genomic DNA that is converted, in a sodium bisulfite reaction, to a mixed pool of methylation-dependent sequence differences according to standard procedures (the bisulfite process converts unmethylated cytosine residues to uracil). Fluorescence-based PCR is then performed either in an "unbiased" (with primers that do not overlap known CpG methylation sites) PCR reaction, or in a "biased" (with PCR primers that overlap known CpG dinucleotides) reaction. Sequence discrimination can occur either at the level of the amplification process or at the level of the fluorescence detection process, or both.

The Methy Light™ assay may be used as a quantitative test for methylation patterns in the genomic DNA sample, wherein sequence discrimination occurs at the level of probe hybridization. In this quantitative version, the PCR reaction provides for unbiased amplification in the presence of a fluorescent probe that overlaps a particular putative methylation site. An unbiased control for the amount of input DNA is provided by a reaction in which neither the primers, nor the probe overlie any CpG dinucleotides. Alternatively, a qualitative test for genomic methylation is achieved by probing of the biased PCR pool with either control oligonucleotides that do not "cover" known methylation sites (a fluorescence-based version of the "MSP" technique), or with oligonucleotides covering potential methylation sites.

The MethyLight™ process can by used with a "TaqMan®" probe in the amplification process. For example, double-stranded genomic DNA is treated with sodium bisulfite and subjected to one of two sets of PCR reactions using TaqMan® probes; e.g., with either biased primers and TaqMan® probe, or unbiased primers and TaqMan® probe. The TaqMan® probe is dual-labeled with fluorescent "reporter" and "quencher" molecules, and is designed to be specific for a relatively high GC content region so that it melts out at about 10⁰C higher temperature in the PCR cycle than the forward or reverse primers. This allows the TaqMan® probe to remain fully hybridized during the PCR annealing/extension step. As the Taq polymerase enzymatically synthesizes a new strand during PCR, it will eventually reach the annealed TaqMan® probe. The Taq polymerase 5¹ to 3¹ endonuclease activity will then displace the TaqMan® probe by digesting it to release the fluorescent reporter molecule for quantitative detection of its now unquenched signal using a real-time fluorescent detection system.

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 bisulfite treated DNA sequence or CpG island); TaqMan® probes; optimized PCR buffers and deoxynucleotides; and Taq polymerase.

Ms-SNuPE. The Ms-SNuPE technique is a quantitative method for assessing methylation differences at specific CpG sites based on bisulfite treatment of DNA, followed by single-nucleotide primer extension (Gonzalgo & Jones, Nucleic Acids Res. 25:2529-2531 , 1997). Briefly, genomic DNA is reacted with sodium bisulfite to convert unmethylated cytosine to uracil while leaving 5-methylcytosine unchanged. Amplification of the desired target sequence is then performed using PCR primers specific for bisulfite-converted DNA, and the resulting product is isolated and used as a template for methylation analysis at the CpG site(s) of interest. Small amounts of DNA can be analyzed (e.g., microdissected pathology sections), and it avoids utilization of restriction enzymes for determining the methylation status at CpG sites.

In a preferred embodiment, the methylation analysis comprises the following steps: Preferably, said method comprises the following steps: In the first step, a sample of the tissue to be analysed is obtained. The source may be any suitable source, such as The DNA source may be any suitable source. Preferably, the source of the DNA sample is selected from the group consisting of cells or cell lines, histological slides, biopsies, paraffin-embedded tissue, bodily fluids, ejaculate, urine, blood, sputum. Preferably, the source is biopsies, bodily fluids, ejaculate, urine, or blood. The DNA is then isolated from the sample. Extraction may be by means that are standard to one skilled in the art, including the use of commercially available kits, detergent lysates, sonification and vortexing with glass beads. Briefly, wherein the DNA of interest is encapsulated 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. Once the nucleic acids have been extracted, the genomic double stranded DNA is used in the analysis.

In the second step of the method, the genomic DNA sample is 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 'pretreatmenf herein.

This is preferably achieved by means of treatment with a bisulfite reagent. 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. Methods of said treatment are known in the art (e.g. PCT/EP2004/011715, which is incorporated by reference in its entirety). It is preferred that the bisulfite treatment is conducted in the presence of denaturing solvents such as but not limited to n-alkylenglycol, particulary diethylene glycol dimethyl ether (DME), or in the presence of dioxane or dioxane derivatives. In a preferred embodiment the denaturing solvents are used in concentrations between 1% and 35% (v/v). It is also preferred that the bisulfite reaction is carried out in the presence of scavengers such as but not limited to chromane derivatives, e.g., 6-hydroxy-2,5,7,8,-tetramethylchromane 2-carboxylic acid (see: PCT/EP2004/011715 which is incorporated by reference in its entirety). The bisulfite conversion is preferably carried out at a reaction temperature between 30⁰C and 70°C, whereby the temperature is increased to over 85°C for short periods of times during the reaction (see: PCT/EP2004/011715 which is incorporated by reference in its entirety). The bisulfite treated DNA is preferably purified prior to the quantification. This may be conducted by any means known in the art, such as but not limited to ultrafiltration, preferably carried out by means of Microcon™ columns (manufactured by Millipore™). The purification is carried out according to a modified manufacturer's protocol (see: PCT/EP2004/011715 which is incorporated by reference in its entirety).

In the third step of the method, fragments of the pretreated DNA are amplified, using sets of primer oligonucleotides according to the present invention, and an amplification enzyme. The amplification of several DNA segments can be carried out simultaneously in one and the same reaction vessel. 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 to, identical to, or hybridize under stringent or highly stringent conditions to an at least 16-base-pair long segment of the bisulfite converted sequence of interest.

In an alternate embodiment of the method, the methylation status of preselected CpG positions, may be detected by use of methylation-specific primer oligonucleotides. 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 that hybridizes to a bisulfite treated CpG dinucleotide. Therefore, the sequence of said primers comprises at least one CpG or TpG 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 9 nucleotides which hybridizes to the bisulfite converted sequence of interest and sequences complementary thereto, wherein the base sequence of said oligomers comprises at least one CpG dinucleotide.

A further preferred embodiment of the method comprises the use of blocker oligonucleotides. The use of such blocker oligonucleotides has been described by Yu et al., BioTechniques 23:714-720, 1997. 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 'CpA' or 'TpG' at the position in question, as opposed to a 'CpG' if the suppression of amplification of methylated nucleic acids is desired.

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 derivatized 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. Preferably, therefore, the base sequence of said blocking oligonucleotides is required to comprise a sequence having a length of at least 9 nucleotides which hybridizes to the bisulfite converted sequence of interest, wherein the base sequence of said oligonucleotides comprises at least one CpG, TpG or CpA dinucleotide.

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 that 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 (ESI).

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 vapour 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 ionization process via the matrix is considerably less efficient. In MALDI-TOF spectrometry, the selection of the matrix plays an eminently important role. For 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 the fourth step of the method, the amplificates obtained during the third step of the method are analysed in order to ascertain the methylation status of the CpG dinucleotides prior to the treatment.

In embodiments where the amplificates were obtained by means of MSP amplification, the presence or absence of an amplificate is in itself indicative of the methylation state of the CpG positions covered by the primer, according to the base sequences of said primer.

Amplificates obtained by means of both standard and methylation specific PCR may be further analyzed 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 synthesised 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 present Sequence Listing; and the segment comprises at least one CpG, TpG or CpA dinucleotide.

Said oligonucleotides may also be present in the form of peptide nucleic acids. The non-hybridized amplificates are then removed. The hybridized amplificates are then detected. In this context, it is preferred that labels attached to the amplificates 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 hybridised 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) employing a dual-labelled fluorescent oligonucleotide probe (TaqMan™ PCR, using an ABI Prism 7700 Sequence Detection System, Perkin Elmer Applied Biosystems, Foster City, California). The TaqMan™ PCR reaction employs the use of a nonextendible interrogating oligonucleotide, called a TaqMan™ probe, which, in preferred embodiments, is designed to hybridize to a GpC-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. 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 MethylLight assay. Variations on the TaqMan™ detection methodology that are also suitable for use with the described invention include the use of dual-probe technology (Lightcycler) or fluorescent amplification primers (Sunrise technology). Both these techniques may be adapted in a manner suitable for use with bisulfite treated DNA, and moreover for methylation analysis within CpG dinucleotides.

A further suitable method for the use of probe oligonucleotides for the assessment of methylation by analysis of bisulfite treated nucleic acids In a further preferred embodiment of the method, the fifth 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 yet a further embodiment of the method, the fourth step of the method comprises sequencing and subsequent sequence analysis of the amplificate generated in the third step of the method (Sanger F., et al., Proc Natl Acad Sci USA 74:5463-5467, 1977).

Additional embodiments of the invention provide a method for the analysis of the methylation status of genomic DNA according to the invention (without the need for pretreatment.

In the first step of such additional embodiments, the genomic DNA sample is isolated from tissue or cellular sources. Preferably, such sources include cell lines, histological slides, paraffin embedded tissues, body fluids, or tissue embedded in paraffin.

In the second step, the genomic DNA is extracted. 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, in particular with methylation-sensitive restriction endonucleases. In the third 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 fourth 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, radionucleotides and mass labels.

In the fifth 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.

Detection, of PSA, IL6sR and TGF-ssl is preferably carried out in a blood sample isolated from the patient, or components thereof e.g. plasma. Methods for detection are known in the art. Such methods include, but are not limited to immunodiffusion, immunoelectrophoresis, immunochemical methods, binder-ligand assays, immunohistochemical techniques, agglutination and complement assays, (e.g., see Basic and Clinical Immunology, Sites and Terr, eds., Appleton & 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 and competitively displacing a labelled polypeptide or derivative thereof.

It is preferred that clinical stage is determined as one of:

TO-No evidence of prostatic tumor.

T1 -Clinically inapparent tumor, non-palpable nor visible by imaging.

TIa -tumor is incidental histologic finding with three of fewer microscopic foci. Non-palpable, with 5% or less of TURP chips (trans-urethral resected prostate tissue) positive for cancer.

Tib-Tumor is incidental histologic finding with more than three microscopic foci. Non-palpable, with greater than 5% of TURP chips (trans- urethra resected prostate tissue) positive for cancer.

Tic-Tumor is non-palpable, and is found in one or both lobes by needle biopsy diagnosis.

T2-Tumor is confined within the prostate.

T2a-Tumor present clinically or grossly, limited to the prostate, tumor

1.5 cm or less in greatest dimension, with normal tissue on at least three sides.

T2b-Tumor present clinically or grossly, limited to the prostate, tumor more than 1.5 cm in greatest dimension, or in only one lobe. Palpable, greater than half of 1 lobe but not both lobes.

T2c-Tumor present clinically or grossly, limited to the prostate, tumor more than 1.5 cm in greatest dimension, and in both lobes. Palpable, involves both lobes.

T3-Tumor extends through the prostatic capsule.

T3a-Palpable tumor extends unilaterally into or beyond the prostatic capsule, but with no seminal vesicle or lymph node involvement. Palpable, unilateral capsular penetration. T3b-Palpable tumor extends bilaterally into or beyond the prostatic capsule, but with no seminal vesicle or lymph node involvement. Palpable, bilateral capsular penetration.

T3c-Palpable tumor extends unilaterally and/or bilaterally beyond the prostatic capsule, with seminal vesicle and/or lymph node involvement.

T4-Tumor is fixed or invades adjacent structures other than the seminal vesicles or lymph nodes.

T4a-Tumor invades any of : bladder neck, external sphincter, rectum.

T4b-Tumor invades levator muscles and/or is fixed to pelvic wall.

Prior therapy shall be taken to include any prostate cancer primary or adjuvant therapy. Said primary treatment shall be taken to include, but is not limited to, cryotherapy, radiation therapy, brachytherapy, and hormonal therapy. Said adjuvant treatment shall be taken to include, but is not limited to, radiation therapy, chemotherapy, cryotherapy, ultrasound, targeted therapies and/or hormone therapy. It is preferred that surgical margin status, seminal vesicle involvement and lymph node status are provided as a dichotomous variable (for example but not limited to yes/no; positive/negative). Methods for the determination of prostatic capsular invasion are known in the art and may include the use of imaging techniques e.g. MRI.

Table 1 : Genes and sequences thereof according ot the present invention.

Table 2: Results of the Cox regression analysis for PITX2 according to Example 1. Using stepwise regression the marker remains in the model. P-values refer to the null-hypothesis "hazard ratio equals zero".

Table 3' Components for all QM assays according to Example 1

Table 4A. Optimized Reaction conditions for all QM assays according to Example 1

Table 4B: Cycle program for QM assays according to Example 1. For annealing temperatures see Table 4A.

Table 5: Clinical characteristics of the patient population according to Example 1. Age is given as the mean, and all other variables are given as the number of patients. Not all information was available for all patients

Table 6:Consensus Gleason score according to Example 3 lGleason Score [No. of samples

The invention will be further described by the following non-limiting examples.

Example 1

The aim of the investigation was to confirm the significance of the gene PITX as a prognostic marker and to optimize methylation cut-offs. The marker should be suitable to split patients who undergo prostatectomy into two groups: one with a high chance of PSA recurrence and one with a low chance of PSA recurrence. In addition, the markers should provide additional information to Gleason grade analysis. A marker meeting these criteria will have an important clinical role e.g. in selection of prostatectomy patients for adjuvant therapy. It was decided to undertake the analysis by means of methylation analysis on a real-time platform (QM Assay). 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 by measuring absolute fluorescence intensities (Fl) in the logarithmic phase of amplification.

The assay was used to analyze the methylation levels of 612 paraffin embedded prostatectomy samples from a cohort of node-negative patients from three institutions.

The primary aim of the invention was to provide a marker that can differentiate between patients with low chance for PSA recurrence after surgery and those with a high chance for PSA recurrence, suitable for use with other commonly used clinical parameters in a prognostic model (e.g. nomogram). Accordingly the performance of the marker was also compared to traditional prognostic indicators such as Gleason grading and stage information.

It is a further aim of the present invention to determine where the marker is most informative in relation to current clinical prognostic assessment and accordingly provide particularly preferred use embodiments of the present invention. It is particularly preferred that a molecular test according to the present invention is combined, either formally or informally, with information from Gleason grading.

Methods: QM Assay Description The QM-assay was developed to enhance performance without drastically altering standard conditions in order to allow future multiplexing. Primer and probe concentrations, MgCI₂ concentration and annealing temperature were optimized under fixed buffer and polymerase conditions. The assay was designed and optimized to ensure quantitative methylation analysis of between 10 and 100 percent methylation. The assay products were checked on an agarose gel and no undesired products were detected. The results of the optimization procedure are shown in Tables 3 and 4.

Oligonucleotide sequences:

Forward primer gtaggggagggaagtagatgtt

Reverse primer ttctaatcctcctttccacaataa

CG-probe agtcggagtcgggagagcga Label 5- FAM Label 3^'-TAMRA

TG-probe agttggagttgggagagtgaaaggaga Label 5- VIC Label 3^'-TAMRA

Sample Set

Paraffin-embedded prostatectomy tissue samples from 612 patients were analysed, see Table 5. The samples were provided by the Baylor College of Medicine SPORE, Stanford University Department of Urology, and Virginia Mason Hospital in Seattle. The samples from Stanford and Virginia Mason were prepared by first finding the surgical block with the highest percent tumor, then sectioning the block. Three tubes were prepared, each with three 10 micron thick sections. The procedure was slightly different at Baylor. A core of tissue was removed from the tumor within the prostatectomy block, and then this core was cut into 10 micron sections. Ten sections were included into each of three tubes.

An adjacent section was mounted on a slide and H&E stained for histological analysis. A pathologist reviewed these slides for an independent determination of Gleason grading and percent tumor. The Gleason results were used for all analyses in this report. The original provider Gleason values are available, but they were not used for analysis due to known and hypothetical biases among the providers. Stanford, for instance, uses a percentage Gleason 4/5 for reporting grade, while the other two providers use the traditional system. The measured Gleason values provided an independent and uniform measurement.

A few samples were found to have no tumor cells on the H&E slide, and these patients were omitted from the analysis. In addition, the inventors found a few patients that did not have a PSA nadir after surgery. These patients were also excluded from the study. In total, 612 patients were included in the data analysis.

Due to their coring technique, the percent tumor of the samples provided by Baylor were higher than the other providers.

All patients, aged 40-80, undergoing surgery at the three institutions during certain years were included in the study, with the exception of patients who received neo-adjuvant or adjuvant therapy (before PSA rise) and patients with positive nodes at the time of surgery. For Baylor, the time period was 1993-1998, for Virginia Mason it was 1996-2000, and for Stanford it was 1996-1999.

The overall cohort is similar to other prostatectomy cohorts described in the literature, such as the cohort collected by William Catalona and described in 2004 (Roehl et al.). The patient cohorts from each provider are similar for nearly all clinical parameters. One exception is the type of recurrence. While other institutions typically wait until the patient's PSA rises to 0.2ng/ml or higher after surgery, the Stanford Department of Urology treats many patients when their PSA rises to 0.05. Therefore, Stanford has a higher rate of recurrence based on the decision to treat criteria and a lower rate of recurrence based on the PSA level (0.2ng/ml) criteria.

Figure 8 provides a histogram of follow-up times for the patient cohort (all three providers included). The white bars consist of the patients who did not have a recurrence before they were censored, and the shaded bars consist of the patients who experienced recurrence. By selecting patients who received surgery from 1993-2000, the inventors have ensured that the median follow-up time of the cohort (66 months) is long enough to have a significant number of patients who have relapsed.

For deparaffination, the provided PET samples were processed directly in the tube in which they were delivered by the providers. One ml (Virginia Mason and Baylor) or 1.8 ml (Stanford) of limonene was added to each tube and incubated at room temperature for 10 minutes in a thermomixer with occasional vortexing. The samples were centrifuged at 16,000 x g for 5 minutes. The limonene supernatant was removed, and if no pellet was detected, centrifugation was repeated at higher speed and the remaining limonene was removed. For samples from Stanford, the deparaffination process was repeated once with 1.6 ml of limonene to get rid of residual paraffin.

For lysis of the tissue, 190 μl lysis buffer and 20 μl proteinase K was added to each deparaffinated sample. For Stanford samples, 570 μl lysis buffer and 60 μl proteinase K was used. After vortexing, samples were centrifuged briefly and incubated on a thermoshaker at 60⁰C for 40 hours. After the incubation, samples were checked to ensure that lysis was complete, and the proteinase was then inactivated at 95°C for 10 minutes. If the lysed samples were not directly used for DNA extraction, they were stored at -20°C.

The lysates were randomized based on the sample provider and PSA recurrence. The DNA was isolated using a QIAGEN DNeasy Tissue kit with a few modifications. 400 μl buffer AUE was distributed to collection tubes and 200 μl of lysate were added. The samples were mixed by shaking for 15 seconds. The lysate/buffer mixtures were applied to the 96-well DNeasy plate columns. The plate was sealed and centrifuged at 5790xg for 10 minutes. The columns were washed once with 500 μl of AW1 and then 500 μl AW2. The DNA was eluted with 120 μl buffer AE. Therefore, the final volume of extracted DNA was approximately 120μl. The DNA was stored at -2O⁰C.

Bisulfite Treatment The CFF real-time PCR assay was used to quantify the DNA concentration of the samples after extraction

CFF sequence

TAAGAGTAATAATGGATGGATGATGGATAGATGAATGGATGAAGAAAGAAAGGATGAGTGAGAG

AAAGGAAGGGAGATGGGAGG (84bp)

CFF-Forward primer TAAGAGTAATAATGGATGGATGATG

CFF-Reverse primer CCTCCCATCTCCCTTCC

CFF TaqMan probe ATGGATGAAGAAAGAAAGGATGAGT

The inventors adjusted the concentration of each genomic DNA sample so that 1 ug of CFF1 measured DNA was present in 44 μl The bisulfite treatment of genomic DNA derived from paraffin embedded tissue was performed using a 96 well protocol Forty-four μl genomic DNA (with approximately 1μg of amplifiable DNA), 83 μl 4 9 M bisulfite solution (pH 5 45-5 5), and 13 μl_ DME solution were pipetted into the wells of the plate The samples were thoroughly mixed then placed in a thermocycler with the following program

• 5 00 mm denaturation of DNA at 99⁰C

• 22 00 mm incubation at 60⁰C

• 3 00 mm denaturation of DNA at 99⁰C

• 1 27 00 hours incubation at 60°C

• 3 00 mm denaturation of DNA at 99°C

• 2 57 00 hours incubation at 60°C

• Cooling at 20°C

After the incubations, each sample was divided into two 70 μL ahquots Each aliquot was combined with 280 μL of prepared Buffer AVL/Carπer RNA and 280 μL ethanol The wells were sealed and the samples were mixed vigorously for 15 seconds The plate was incubated for 10 minutes at room temperature The first aliquot was applied to the QiAamp 96 plate and the plate was centrifuged for four minutes at 5790 x g The process was repeated with the second aliquot so that both ahquots were applied to the same binding column The columns were washed with 500 μL buffer AW1 , then 500 μL 0 2 M NaOH, and then twice with 500 μL buffer AW2 The DNA was eluted with 100 μL elution buffer (Qiagen) pre-heated to 70 deg C The bisDNAs were stored at -20⁰C

The bisulfite treated DNA samples were stored in 8 x 96 well plates (plate 01-08) The samples and controls were combined onto two 384-well PCR reaction plates for each QM assay Each QM assay plate contained the samples of 4 x 96 well plates (85 wells actually used per plate) and 1x96 well plate with standard DNA (7 mixtures of the calibration DNA and water for the no template control PCR reaction) The QM assay plates were run three times

The 384-well PCR plates were pipetted with the TECAN workstation The pipetting program transferred first 10 μl of the mastermix and then 10 μl of the respective DNA into the designated well The master mix was pipetted in a falcon tube and distributed to 8 x 500 μl screw cap vials for automatic pipetting with TECAN workstation.

All QM assays were run on an ABI TAQMAN 7900HT real-time device (SDS 2.2. software) with a reaction volume of 20 μl and 9600 emulation. An automatic sample setup was used to transfer the correct sample names and detector/reporter dyes to the TAQMAN software. The cycling conditions were manually adjusted and ROX was used as passive reference dye. All 384 well PCR plates the inventors analyzed with the SDS2.2 software using the manual analysis settings (baseline setting with start and stop values and manual threshold) to produce results files for each run individually.

Methods: Evaluation of Marker Performance Definition of Events

After a successful prostatectomy on a patient with non-metastatic disease, there should be no prostate cells left in his body and therefore his PSA levels should drop to zero. A patient's PSA levels are typically measured every 6-12 months after surgery to ensure that the patient remains free of prostate cancer. If PSA becomes detectable and rises to a certain level, the doctor and patient may decide on additional therapy. Therefore, the return and rise of PSA levels are the primary indication of disease recurrence.

A post-surgical PSA relapse is typically indicated by either a gradual or rapid rise in levels over a series of sequential tests. Depending on the clinical characteristics of the patient or the approach of the institution, patients may be treated as soon as PSA is detected, when it reaches a certain threshold, or when clinical symptoms accompany the PSA rise. Most institutions consider a PSA level of 0.2 ng/ml to be significant, and if a patient's PSA reaches this level and is confirmed to be rising in subsequent tests, he will be offered additional therapy. Stanford Department of Urology, one of the sample providers, considers 0.05 ng/ml to be a PSA recurrence, and considers treatment for patients when their PSA reaches this level.

An event in this study includes all PSA-based recurrences. A PSA level of 0.2ng/ml, confirmed in subsequent tests, has been demonstrated to provide the best sensitivity and specificity for detection of recurrence (Freedland et al. 2003). Rise of PSA to this level normally precedes any development of clinical recurrence; therefore, nearly all of the patients in this study are free of clinical recurrence at the time of PSA recurrence. Because Stanford often treats patients with PSA recurrence before they reach this cut-off of 0.2ng/ml, many of their recurrence patients would be censored in the present study if the PSA level of 0.2ng/ml was the only considered event. Therefore, patients from any of the three institutions who receive therapy due to PSA levels are also considered an event in this study.

To summarize, an event is defined in the present study as any rise in PSA to 0.2ng/ml (confirmed in subsequent test) OR a decision to treat the patient based on PSA criteria.

Raw QM Data Processing All analyses in this report are based on the CT evaluation. Assuming optimal real-time PCR conditions in the exponential amplification phase, the concentration of methylated DNA (C_meth) can be determined by

C ^{1 Q0} ran ^melh i ₊ 2^(CTcc-^CTro) where CT_CG denotes the threshold cycle of the CG reporter (FAM channel) and

CT_7υ denotes the threshold cycle of the TG reporter (VIC channel).

The thresholds for the cycles were determined by visual inspection of the amplification plots (ABI

PRISM 7900 HT Sequence Detection System User Guide). The values for the cycles ( CT_CG and

CT_j0 ) 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 e.g. 50.

The R software package, version 2.2. (Gentleman and lhaka 1997), was used for the statistical analysis.

In addition, the inventors used the "survival" package, version 2.11-5 (http://cran.at.r- project.org/src/contrib/Descriptions/survival.html), for survival analysis. Proprietary code was used for k-fold-cross validation, ROC analysis and plot functions. Each dataset is represented in a proprietary data object, called "Annotated Data Matrix" (ADM). This data object contains the measurements after quality control and averaging, as well as all necessary annotations for the samples and assays.

QM Assay calibration curves

A series of mixtures of methylated MDA-DNA and unmethylated MDA-DNA₁ ranging from 0 to 100 percent methylated, were included in triplicate on each QM PCR plate. These DNAs were used to ensure uniform QM assay performance on all PCR plates. All assays showed strong quantitative abilities between 10 and 100%, and some assays were able to consistently distinguish 5% methylated DNA from unmethylated DNA.

Statistical Methods

After quality control, each assay was statistically analyzed.

Cox Regression

The relation between recurrence-free survival times (RFS) and covariates were analyzed 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 I x) = ho (t) exp(βx) (3) and h(t I X₁,... , x_k) = ho (t) exp(β_iXi + ... + β_kx_k) (4) for univariate and multiple regression analyses, respectively, where t is the time measured in months after surgery, h_o(t) is the (unspecified) baseline hazard, Xj are the covariates (e.g. measurements of the assays) and βi are the regression coefficients (parameters of the model), βj 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^" 2Log(Likelihood) of the full model and the null-model is approximately undistributed with k degrees of freedom under the null hypotheses Di = ... = D_k = 0.

The assumption of proportional hazards were evaluated by scaled Schoenfeld residuals (Thernau and Grambsch 2000). For the calculation, analysis and diagnostics of the Cox Proportional Hazard Model the R functions "coxph" and "coxph.zph" of the "survival" package are used.

Stepwise Regression Analysis

For multiple Cox regression models a stepwise procedure (Venables and Ripley 1999; Harrel 2001 ) was 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 predictor's performance can be low due to over-fitting.

The applied algorithm aims at minimizing the Akaike information criterion (AIC), which is defined as AIC = 2 D maximized log-likelihood + 20#parameters.

The AIC is related to the 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 are done with the R function "step".

Kaplan-Meier Survival Curves and Log-Rank Tests

Survival curves were estimated from RFS data using Kaplan-Meier estimator for survival (Kaplan and Meier, 1958). Log-rank tests (Cox and Oates 1984) are used to test for differences of two survival curves, e.g. survival in hyper- vs. hypomethylated groups. In addition, a variant of the Log-rank test usually referred to as the Generalized Wilcoxon test was applied (for description see Hosmer and Lemeshow 1999). For the Kaplan-Meier analysis the functions "survfit" and "survdiff" of the "survival" package are used. Independence of single markers and marker panels from other covariates

To check whether the present markers give 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" is used.

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" is used.

Analysis of Sensitivity and Specificity

The method of calculating sensitivity and specificity using the Bayes-formula was 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_n^₀₁₁, . The ROCs were calculated for different reference times T_Threshold (3 year, 4 years, 5 years, 6 years).

k-fold Crossvalidation

For the analysis of model selection and model robustness k-fold crossvalidation (Hastie et al. 2001 ) was used. The set of observations is randomly split into k chunks. In turn, every chunk was used as a test set, whereas the remaining k-1 chunks constitute the training set. This procedure is repeated m times.

Results

The 605 samples were processed as described above. All samples were analyzed by the QM assays with three replicates. The data was filtered for quality control, and analyzed as described in the methods section. The clinical performance of each marker is summarized below and the Kaplan-Meier survival curves and ROC curves according to figure 9. P-values for comparison of survival curves reported in the graphs are based on the ordinary Log-rank test. The results of using the Generalized Wilcoxon test are essentially the same (data not shown).

The performance of the marker was first examined using the median methylation level as a cut-off. Since this cut-off was fixed before looking at the data, the p values can be used to judge the performance of the markers. A marker with a significant p value using the median methylation as a cut-off is considered to be validated. The median methylation level might not be the best cut-off as the prognostic separation can be further optimized by choosing the methylation cut-off that results in the lowest p value. Since the cut-off is optimized specifically for p value, the p value no longer can be used to indicate statistical significance. For judging the significance of the marker performance using the median methylation as a cut-off, the inventors used a p value of 0.005 (assuming correction for 10 markers and panels). Based on p-value and event separation, PITX2 is a strong candidate.

Figure 9 A shows the Kaplan-Meier survival analysis of the PITX2 marker of the 585 patient samples that passed the quality control filter using the optimized methylation cut-off value (13.5%). Figure 9B shows the Kaplan-Meier survival analysis of the PITX2 marker using the predefined median methylation value as a cut-off, the p-value was 0.000017. Figure 9C shows the ROC curve analysis of the PITX2 marker after 5 years of follow-up. The median methylation cut-off is marked as a triangle, and the optimized methylation cut-off is shown as a diamond. The AUC was 0.64.

Example 2

Several clinical prognostic factors are commonly used for assessing prostate cancer. Histological analysis of the tumor with quantification of the tumor differentiation state using the Gleason grading system is a particularly important prognostic indicator in current clinical practice. In order to provide a preliminary assessment of whether PITX2 methylation could add further prognostic information the analysis was continued by determining whether the marker could improve Gleason analysis by subdividing patients within a Gleason category. The inventors also investigated whether the markers could add information to other prognostic indicators, such as nomogram risk estimation (Han et al. 2003) and disease stage.

For these analyses, the inventors used Kaplan-Meier analysis to determine whether PITX2 is still informative on population sub-groups, and Cox regression analysis to determine whether the markers provide information independent of the prognostic clinical variables. Gleason score was divided into three groups (6 or lower, 7, and 8 through 10), stage was divided into two groups (T2/organ-confined and T3/non-organ confined), PSA was divided into four groups (0 to 4 ng/ml, 4 to 10 ng/ml, 10 to 20 ng/ml, and greater than 20 ng/ml), and nomogram estimation of 5 year PSA-free survival was divided into two groups (90 to 100% also referred to as "high" and 0 to 89% also referred to as "low").

With Cox regression modeling, PITX2 is a valuable prognostic marker independent of other clinical prognostic information (Table 2). In other words, PITX2 methylation adds more information to Gleason than either PSA or disease stage. The hazard ratio for PITX2 is 2.2. In the survival analysis of subgroups, PITX2 has the potential to be a significant marker for all prostate cancer patients.

It is particularly interesting to see strong separation within the patient sub-group with organ-confined disease (Figure 10). Patients with organ-confined disease (T2) should be cured by surgery. Those that are not cured by surgery must have had some cells leave the prostate before surgery, and therefore had tumor cells with aggressive characteristics early in the development. PITX2 can separate the T2 group into a hypomethylated group with a very small chance for recurrence (-5%) and a hyper- methylated group with a prognosis more like T3 patients. Figure 10 shows the survival analysis of PITX2 performance on sub-populations based on stage. The upper left plot shows the performance of disease stage as a prognostic marker. The upper right plot shows the performance of PITX2 on pT2 patients. The lower left plot shows the performance of PITX2 on T3 patients.

PITX2 is also capable of stratifying patients within Gleason sub-categories. Figure 11 shows that survival analysis on low Gleason patients (Score 5 or 6) and high Gleason patients (Score 8, 9, or 10) results in low p values. Patients with high Gleason scores are currently candidates for clinical trials on post-surgical adjuvant therapies. However, the PITX2 values suggest that this is not a uniform group. PITX2 hypomethylated, high Gleason patients have 85% probability of disease free survival at ten years, while hypermethylated high Gleason patients have a very low chance (~35%). These patients with high likelihood for disease recurrence are the patients who should be selected for adjuvant therapy or clinical trials.

Figure 11 shows the survival analysis of PITX2 performance on sub-populations based on Gleason score categories. The upper left plot shows the performance of Gleason score as a prognostic marker. Gleason 5 and 6 patients are in light grey, Gleason 7 patients are in dark-grey, and Gleason 8, 9, and 10 patients are in black. The upper right plot shows the performance of PITX2 on Gleason 5 and 6 patients. The lower left plot shows the performance of PITX2 on Gleason 7 patients. The lower right plot shows the performance of PITX2 on Gleason 8, 9, and 10 patients.

Prostate cancer nomograms are created based on large cohorts of patients. They mathematically combine information from stage, Gleason, and pre-operative PSA levels into one prognostic indicator. As Figure 12 shows, the nomogram by itself is very strong. But PITX2 is capable of further subdividing the patients.

Figure 12 shows the survival analysis of PITX2 performance on sub-populations based on nomogram risk estimation. The upper left plot shows the performance of the nomogram as a prognostic marker. The upper right plot shows the performance of PITX2 on patients with a 90% chance of 5-year PSA- free survival according to the nomogram. The lower left plot shows the performance of PITX2 on patients with less than 90% chance of 5-year PSA-free survival according to the nomogram.

Discussion

PITX2 shows significant prognostic information when the median methylation level is used as a cut-off. Setting the methylation cut-off even higher than the median improves the performance. This has the effect of decreasing the marker positive group and increasing the specificity of the test.

The patients whose samples were analyzed in this study are representative of the population who would be targeted for a prostatectomy test. Therefore, it is possible to speculate on the information these markers could provide for future patients. PITX2, for example, has a sensitivity of around 60% and a specificity of 70%. In the Kaplan-Meier analysis in Figure 9, the marker positive group has approximately three times the risk of recurrence after ten years as the marker negative group has. In Figure 11 , Gleason 8-10 patients that are positive for PITX2 have a 65% chance for PSA recurrence in 10 years. In contrast, the Gleason 8-10 patients who were marker negative had only a 15% chance of PSA relapse. The addition of the methylation marker information to the Gleason stratification will allow clinicians to identify a poor prognosis sub-group who can most benefit from adjuvant therapy. If the marker is incorporated into the patient selection procedure for adjuvant therapy clinical trials, clinicians may begin to see a clear benefit to the addition of early adjuvant treatments for poor prognosis patients.

In addition to adding information to Gleason, PITX2 can also stratify patients with organ-confined disease. Patients with disease that is truly confined to the organ will be cured by complete removal of the organ. Patients with disease that appears to be confined to the organ, but have undetected micrometastases, will not be cured by surgery. These two groups of patients, both with small operable lesions, have tumors with very different capacities for metastases. PITX2 seems to be detecting these underlying differences in basic tumor aggressiveness.

The ability of PITX2 to add information to currently used markers is essential. Gleason and staging already provide significant prognostic information, a new test that would not replace but complement these traditional sources of information is both more valuable and more likely to be easily adopted in clinical practice.

In the analysis on sub-groups of patients, the marker often seemed strongest on patients with poor prognosis based on traditional clinical variables. Gleason 8-10 patients and patients with low nomogram probability for PSA free survival are well stratified by the present marker into good and poor prognosis groups. For a prostatectomy test, these are the ideal patients to target, since the test would be used to select a group of poor prognosis patients who can most benefit from adjuvant therapy. Overall, this analysis demonstrates that the PITX2 marker is especially well suited for identifying poor prognosis patients.

Based on the samples and data of Example 1 above, the next aim was to construct and assess prognostic models combining PITX2 methylation and commonly used clinical parameters.

The following factors were considered:

• PITX2 methylation measurements

• Pre-surgery PSA levels (log transformed)

• Gleason scores (see Table 6 for consensus Gleason scores)

• Tumor cell content (continuous variable reported within range from 5% to 95%)

• Han nomogram scores (predicated at 5 year recurrence free survival probability)

• T stage: T2 (organ confined) and T3 (non-organ confined) only (a, b& c were not considered)

• Extracapsular invasion (reported as dichotome "yes" or "no")

• Seminal vesicle involvement (reported as dichotome "yes" or "no") • Surgical margins (reported as dichotome "negative" or "positive")

Clinical endpoint and events were determined as above in Example 1. Accordingly the following nomograms were determined as having prognostic value in patient treatment:

Figure 1 : PITX2 methylation only.

Figure 2 : PITX2 methylation; Gleason sum (biopsy)

Figure 3: PITX2 methylation; Gleason sum (surgical)

Figure 4: PITX2 methylation; Nomogram scores (according to Han et al 2002)

Figure 5: PITX2 methylation; Pre-surgery PSA; Gleason sum (consensus); Surgical margins; Seminal vesicle invasion; T stage

Figure 6: PITX2 methylation; Pre-surgery PSA; Gleason sum (surgery); Surgical margins; Seminal vesicle invasion; T stage

Figure 7: PITX2 methylation; Pre-surgery PSA; Gleason (first value); Gleason (second value); T stage

Claims

1. A method for providing a prognosis of prostate cancer in a patient comprising: i) detecting or determining the methylation status of one or more genomic CpG positions; ii) detecting or determining at least one of the following: pre-treatment PSA; post-treatment PSA; primary Gleason grade in the biopsy specimen; secondary Gleason grade in the biopsy specimen; Gleason sum in the biopsy specimen; pre- radical primary therapy; total length of cancer in biopsy cores; number of positive biopsy cores; percent of tumor biopsy in a multiple core biopsy set; primary Gleason grade in the pathological specimen; secondary Gleason grade in the pathological specimen; Gleason sum in the pathological specimen; pre-operative TGF-ssl level; prostatic capsular invasion level (PCI); surgical margin status; seminal vesicle involvement; lymph node status; pre-operative ILδsR level; prior therapy and/or clinical stage; and iii) correlating i) and ii) with disease outcome.

2. A method for providing a pre-therapy prognosis of prostate cancer in a patient comprising: i) detecting or determining the methylation status of one or more genomic CpG positions; ii) detecting or determining at least one factor selected from the group consisting of: pre- treatment PSA; primary Gleason grade in the biopsy specimen; secondary Gleason grade in the biopsy specimen; Gleason sum; previous therapy and/or clinical stage, and iii) correlating i) and ii) with disease outcome.

3. A method for providing a prognosis of prostate cancer in a patient comprising: i) detecting or determining the methylation status of one or more genomic CpG positions; ii) detecting or determining at least one factor selected from the group consisting of: pre- treatment PSA; primary Gleason grade in the biopsy specimen; secondary Gleason grade in the biopsy specimen; Gleason sum; previous therapy and/or clinical stage iii) detecting or determining at least one factor selected from the group consisting of: total length of cancer in the biopsy cores; number of positive cores and percent of tumor in a multiple core biopsy set, and iv) correlating i) ii) and iii) with disease outcome.

4. A method for providing a post-therapy prognosis of prostate cancer in a patient comprising: i) detecting or determining the methylation status of one or more genomic CpG positions; ii) detecting or determining at least one factor selected from the group consisting of: pre- treatment PSA; primary Gleason grade in the pathological specimen; secondary Gleason grade in the pathological specimen; Gleason sum; pre-operative TGF-ssl level; prostatic capsular invasion level (PCI); surgical margin status; seminal vesicle involvement; lymph node status; pre-operative ILΘsR level; prior therapy and/or clinical stage, and iii) correlating i) and ii) with disease outcome.

5. A method according to any of claims 1 to 4 where in i) said CpG positions are located within the gene PITX2 and/or regulatory regions thereof.

6. A method according to any of claims 1 to 4 where in ii) said factor is selected from the group consisting of primary Gleason grade; secondary Gleason grade; Gleason sum.

7. A method according to any of claims 1 to 4 wherein said clinical stage is T3a, T3, T2c, T2b, T2a, T2, TIc, TIb, TIa or Tl.

8. A method according to any of claims 3 to 4 wherein the therapy is primary therapy.

9. A method according to any of claims 3 to 4 wherein the therapy is prostatectomy.

10. A method according to any of claims 3 to 4 wherein the patient has not been subject to adjuvant therapy.

11. A method according to any of claims 1 to 10 wherein detecting or determining the methylation status of one or more genomic CpG positions is carried out by means of a bisulfite reagent.

12 The method according to claim 11 further comprising the use of at least one method selected from the group consisting of MSP; Methylight; QM, Heavymethyl.

13. A method according to any of claims 1 to 10 where in iii) said correlating is conducted by computer means.

14. An apparatus for predicting disease outcome in a patient with prostate cancer comprising:

- a correlation of: i) the methylation status of one or more genomic CpG positions and ii) at least one of the following: pre-treatment PSA; post-treatment PSA; primary Gleason grade in the biopsy specimen; secondary Gleason grade in the biopsy specimen; Gleason sum in the biopsy specimen; pre- radical primary therapy; total length of cancer in biopsy cores; number of positive biopsy cores; percent of tumor biopsy in a multiple core biopsy set; primary Gleason grade in the pathological specimen; secondary Gleason grade in the pathological specimen; Gleason sum in the pathological specimen; pre-operative TGF-ssl level; prostatic capsular invasion level (PCI); surgical margin status; seminal vesicle involvement; lymph node status; pre-operative IL6sR level; prior therapy and/or clinical stage with disease outcome, and

- a means for comparing an identical set of factors i) and ii) determined from said patient to the correlation to predict disease outcome.

15. An apparatus for predicting disease outcome in a patient with prostate cancer comprising:

- a correlation of: i) the methylation status of one or more genomic CpG positions and ii) at least one of the following: pre-treatment PSA; primary Gleason grade in the biopsy specimen; secondary Gleason grade in the biopsy specimen; Gleason sum; previous therapy and/or clinical stage with disease outcome, and

16. An apparatus for predicting disease outcome in a patient with prostate cancer comprising:

17. An apparatus for predicting disease outcome in a patient with prostate cancer comprising:

- a correlation of: i) the methylation status of one or more genomic CpG positions, ii) at least one of the following: pre-treatment PSA; primary Gleason grade in the biopsy specimen; secondary Gleason grade in the biopsy specimen; Gleason sum; previous therapy and/or clinical stage with disease outcome, and iii) at least one of the following: total length of cancer in the biopsy cores; number of positive cores and percent of tumor in a multiple core biopsy set,

18. An apparatus for predicting disease outcome in a patient with prostate cancer comprising:

- a correlation of: i) the methylation status of one or more genomic CpG positions and ii) at least one of the following: pre-treatment PSA; primary Gleason grade in the pathological specimen; secondary Gleason grade in the pathological specimen; Gleason sum; pre-operative TGF-ssl level; prostatic capsular invasion level (PCI); surgical margin status; seminal vesicle involvement; lymph node status; pre-operative IL6sR level; prior therapy and/or clinical stage, and

19. A nomogram for predicting disease outcome in a patient with prostate cancer comprising: - a plurality of scales and a solid support, the plurality of scales being disposed on said support and comprising a scale for each of: i) the methylation status of one or more genomic CpG positions, and ii) at least one of the following: pre-treatment PSA; post-treatment PSA; primary Gleason grade in the biopsy specimen; secondary Gleason grade in the biopsy specimen; Gleason sum in the biopsy specimen; pre- radical primary therapy; total length of cancer in biopsy cores; number of positive biopsy cores; percent of tumor biopsy in a multiple core biopsy set; primary Gleason grade in the pathological specimen; secondary Gleason grade in the pathological specimen; Gleason sum in the pathological specimen; pre-operative TGF-ssl level; prostatic capsular invasion level (PCI); surgical margin status; seminal vesicle involvement; lymph node status; pre-operative IL6sR level; prior therapy and/or clinical stage.

20. A nomogram for predicting disease outcome in a patient with prostate cancer comprising:

- a plurality of scales disposed on a solid support, and comprising at least one scale for each of: i) the methylation status of one or more genomic CpG positions, and ii) at least one of the following: pre-treatment PSA; primary Gleason grade in the biopsy specimen; secondary Gleason grade in the biopsy specimen; Gleason sum; previous therapy and/or clinical stage.

21. A nomogram for predicting disease outcome in a patient with prostate cancer comprising:

- a plurality of scales disposed on a solid support, and comprising at least one scale for each of: i) the methylation status of one or more genomic CpG positions, and ii) at least one of the following: pre-treatment PSA; primary Gleason grade in the biopsy specimen; secondary Gleason grade in the biopsy specimen; Gleason sum; previous therapy and/or clinical stage, iii) at least one of the following: total length of cancer in the biopsy cores; number of positive cores and percent of tumor in a multiple core biopsy set.

22. A nomogram for predicting disease outcome in a patient with prostate cancer comprising:

- a plurality of scales disposed on a solid support, and comprising at least one scale for each of: i) the methylation status of one or more genomic CpG positions, and ii) at least one of the following: pre-treatment PSA; primary Gleason grade in the pathological specimen; secondary Gleason grade in the pathological specimen; Gleason sum; pre-operative TGF-ssl level; prostatic capsular invasion level (PCI); surgical margin status; seminal vesicle involvement; lymph node status; pre-operative IL6sR level; prior therapy and/or clinical stage.

23. An apparatus or nomogram according to any of claims 14 to 22 where in i) said CpG positions are located within the gene PITX2 and/or regulatory regions thereof.

24. An apparatus or nomogram according to any of claims 14 to 23 where in ii) said factor is selected from the group consisting of primary Gleason grade; secondary Gleason grade; Gleason sum.

25. An apparatus according to any of claims 14 to 24 wherein said means is a computing or software means.

26. An apparatus according to any of claims 14 to 24 wherein said means is a nomogram or graphical representation.