Originally published as JCO Early Release 10.1200/JCO.2005.01.3516 on August 14 2006

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Detection of Aberrant Methylation of Four Genes in Plasma DNA for the Detection of Breast Cancer

Mohammad O. Hoque, Qinghua Feng, Papa Toure, Amadou Dem, Cathy W. Critchlow, Stephen E. Hawes, Troy Wood, Carmen Jeronimo, Eli Rosenbaum, Joshua Stern, Mujun Yu, Barry Trink, Nancy B. Kiviat, David Sidransky

From the Department of Otolaryngology-Head and Neck Surgery, Head and Neck Cancer Research Division, Johns Hopkins University School of Medicine, Baltimore, MD; Departments of Epidemiology, School of Public Health and Community Medicine, and Pathology, School of Medicine, University of Washington, Seattle, WA; and the Tumor Institute, University of Dakar, Senegal

Address reprint requests to Nancy B. Kiviat, MD, Department of Pathology, Harborview Medical Center, University of Washington, 325 9th Ave, Seattle, WA 98104 e-mail: nbk{at}u.washington.edu; or to David Sidransky, MD, Head and Neck Cancer Research Division, Johns Hopkins University School of Medicine, 818 Ross, 720 Rutland Avenue, Baltimore, MD 21205; e-mail: dsidrans{at}jhmi.edu

	ABSTRACT

TOP ABSTRACT INTRODUCTION PATIENTS AND METHODS RESULTS DISCUSSION Appendix Authors' Disclosures of... Author Contributions GLOSSARY REFERENCES

 
Purpose Novel approaches to breast cancer screening are necessary, especially in the developing world where mammography is not feasible. In this study, we explored the hypothesis that blood-based biomarkers have potential for biomarkers for breast cancer.

Patients and Methods We first determined the frequency of aberrant methylation of four candidate genes (APC, GSTP1, Rassf1A, and RARβ2) in primary breast cancer tissues from West African women with predominantly advanced cancers. We used a high-throughput DNA methylation assay (quantitative methylation-specific polymerase chain reaction) to examine plasma from 93 women with breast cancer and 76 controls for the presence of four methylated genes. Samples were randomly divided evenly into training and validation data sets. Cutoff values for gene positivity of the plasma-based assay and the gene panel were determined by receiver operating characteristic curves in the training data set and subsequently evaluated as a screening tool in the validation data set.

Results Methylation of at least one gene resulted in a sensitivity of 62% and a specificity of 87%. Moreover, the assay successfully detected 33% (eight of 24) of early-stage tumors.

Conclusion These data suggest that epigenetic markers in plasma may be of interest for detection of breast cancer. Identification of additional breast cancer specific methylated genes with higher prevalence in early stage cancers would improve this approach.

	INTRODUCTION

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Breast cancer is the second leading cause of cancer death among women after lung cancer. According to the WHO, more than 1.2 million women worldwide will be diagnosed with breast cancer this year. Although a recent significant decline in breast cancer mortality between 1992 and 1996 is believed to be due, in part, to early diagnosis by screening mammography, the limitations of mammography^1,2 are well recognized, especially for those women with premenopausal breast cancer. In developing countries, the extensive laboratory and clinical infrastructure required for mammographic screening, as well as the high cost of mammography precludes such an approach. Further, given the fact that the majority of women in many developing countries are under the age of 40 years, the problem of the detection of premenopausal breast cancer is of particular importance in such settings. Thus alternative approaches to breast cancer detection are clearly needed.

Detection of changes in DNA methylation, also termed epigenetic alterations, may offer an alternative approach to screening. Further, it may also be of interest in providing data for clinical long-term management of women treated for breast cancer. Epigenetic changes, such as DNA methylation are one of the most common molecular alterations in human neoplasia^3-6 including breast cancer.⁷ DNA hypermethylation refers to the addition of a methyl group to the cytosine ring of those cytosines that precede a guanosine (referred to as CpG dinucleotides) to form methyl cytosine (5-methylcytosine). CpG dinucleotides are found at increased frequency in the promoter region of many genes, and methylation in the promoter region is frequently associated with "gene silencing" (ie, the gene is expressed in the absence of methylation).⁸ Both global hypomethylation and gene-specific hypermethylation are associated with malignancy,^9-11 and studies in animals and in humans have demonstrated that these epigenetic changes are an early event in carcinogenesis and are present in the precursor lesions of a variety of cancers including breast,^12-14 lung,¹⁵ colon,¹⁶ and endometrium.¹⁷

The presence of abnormally high DNA concentrations in the sera, plasma, and urine of patients with various malignant diseases has been described.^18-20 Several studies have also tested fine needle aspirate samples and corresponding sera from women with breast cancers for aberrant DNA hypermethylation at the time of diagnosis.^7,21 Overall, these studies have demonstrated a high concordance between the epigenetic alterations found in primary tumor specimens and in plasma, suggesting the potential utility of these alterations as surrogate tumor markers.^22-26 Thus far, however, there are only limited data available on the detection of these epigenetic alterations in primary breast cancer tissue and in corresponding blood samples. Therefore we undertook the current study among West African women presenting with untreated breast cancer to (1) determine the frequency in primary breast cancer tissue of methylation of four candidate genes, APC, GSTP1, RARβ2, and Rassf1A, which preliminary studies in other populations suggest are important in breast cancer, and (2) to determine whether detection of methylation changes of these four genes in plasma might have clinical utility.

	PATIENTS AND METHODS

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Study Population
Ninety-three consecutive women with breast cancer (cases) were recruited from patients presenting to the University of Dakar Tumor Institute (Senegal, West Africa) between August 2001 and April 2003 for initial diagnosis and treatment of their breast cancer and enrolled into this study before treatment. The blood samples for control women in this study (n = 76) were selected from available residual samples from a study evaluating the relationship between human papillomavirus and cervical neoplasia in Senegal.²⁷ Control patients in this study presented for gynecologic exams/symptoms (61%), routine follow-up (17%), HIV screening (8%), other infectious diseases including suspected malaria and tuberculosis (7%), and other reasons (7%).

After providing informed consent, all study participants were interviewed to elicit information regarding demographic characteristics, gynecologic history, use of cigarettes and alcohol, family history of cancer, and medical history. Approval for research on human subjects was obtained from the University of Washington (Seattle, WA) and the University of Dakar institutional review boards.

Collection and Processing of Samples and DNA Preparation
At the enrollment visit, 10 mL of peripheral blood was drawn into a purple-top blood collection tube (containing EDTA additive) before physical examination or biopsy. Two true-cut biopsies as well as fine needle aspiration were performed on all masses. One half of each sample was placed in formalin or Pap fixative (stored at room temperature; Cytyc Corp, Boxborough, MA) for routine histologic and cytologic examination and the other half, reserved for methylation studies, was placed in Specimen Transport Medium (STM; Digene Corporation, Gaithersburg, MD), transported at room temperature to the laboratory, and frozen at –80°C until they were shipped to University of Washington in liquid nitrogen. Plasma samples were left at room temperature for molecular assays, and all were transferred to the study laboratory within 4 hours of collection for processing. Biopsy findings were interpreted by a pathologist (N.B.K.) without knowledge of clinical or laboratory findings according to the WHO classification system.²⁸ Methylation samples were centrifuged at 2,200 rpm for 10 to 15 minutes, and approximately 5 mL supernatant (plasma) was collected and aliquoted into three 1.8 mL tubes. The plasma samples were stored at –80°C until they were shipped to University of Washington in liquid nitrogen. DNA was obtained from 1 mL of plasma by digestion with 50 µg/mL proteinase K (Boehringer Mannheim, Germany) in the presence of 1% sodium dodecyl sulfate (SDS) at 48°C for 2 days, followed by phenol/chloroform extraction and ethanol precipitation and finally dissolved in 30 µL of LoTE (2.5 mmol/L EDTA and 10 mmol/L Tris-HCL). Three microliter of DNA solution was used for the measurement of DNA concentration by quantitative polymerase chain reaction (PCR).

Genomic DNA was isolated from residual needle aspirate material collected in STM media (Digene Corporation) using the QIAamp DNA mini kit (Cat. No. 51,104; Qiagen, Hilden, Germany). Samples were first digested with protease K; DNA was extracted from 200 µL protease K digested samples, following the manufacturer's protocol; DNA concentration was measured using a fluorometer.

Conventional Methylation-Specific Analysis
The presence or absence of a specific promoter hypermethylation in tissues from primary breast cancers was determined using conventional methylation-specific (MSP) analysis. One microgram of genomic DNA was processed for bisulfite modification using the Intergen CpGenome DNA modification kit (Cat. No. S7820; Intergen, Purchase, NY). Briefly, genomic DNA was modified by sodium bisulfite, desulfonated with NaOH, then purified and resuspended in TE (10 mmol/L Tris/0.1 mmol/L EDTA, pH 7.5). Primers specific for methylated DNA were constructed for four genes examined (APC, RASSF1, GSTP1, and RARβ). "Hot start" PCR was performed with ampliTag Gold (Roche), using the following parameters: 95°C for 10 minutes; 95°C for 45 seconds, Ta°C for 45 seconds, 72°C for 1 minute, for 35 cycles; 72°C for 10 minutes. PCR products were analyzed on either 5% polyacrylamide gel or 2% agarose gel containing ethidium bromide. Human sperm DNA and in vitro methylated (using SssI CpG methylase; New England Biolabs, Beverly, MA) human sperm DNA were used as U and M DNA controls, respectively. Methylation of a specific gene was considered to be present if both the specimen and the M-control DNA, but not the U-control DNA, were amplified by M primers after modification. Similarly, methylation was considered absent if the M-control DNA, but neither the sample nor the U-control DNA, was amplified by M primers. For each gene, if the M-control or the U-control DNA did not amplify, then the test was considered invalid. The PCR results were read independently by two people without previous knowledge of histology results.

Quantitative MSP PCR Methylation Analysis
DNA from plasma (27 µL) samples was subjected to bisulfite treatment, as described previously.²⁹ Briefly, DNA was denatured in 0.2 M NaOH for 20 minutes at 50°C. The denatured DNA was diluted in 500 µL of a freshly prepared solution of 10 mmol/L hydroquinone and 3 M sodium bisulfite, and incubated for 3 hours at 70°C. After incubation, the DNA sample was desalted through a column (Wizard DNA Clean-Up System, Promega), treated with 0.3 M NaOH for 10 minutes at room temperature, and precipitated with ethanol. The bisulfite-modified genomic DNA was resuspended in 22 µL of LoTE (2.5 mmol/L EDTA, 10 mmol/L Tris-HCL) and stored at –80°C.

All plasma was examined using high throughput DNA methylation assay (quantitative MSP PCR [QMSP]). Bisulfite modified DNA was used as a template for fluorescence-based real-time PCR (Taqman) as previously described.³⁰ In brief, primers and probes were designed to specifically amplify the bisulfite-converted promoter of the gene of interest. The ratios between the values of the gene of interest and the internal reference gene, β-actin, obtained by Taqman analysis, were used as a measure for representing the relative level of methylation in the particular sample (target gene/β-actin x 1,000). Fluorogenic PCRs were carried out in a reaction volume of 20 µL consisting of 600 nmol/L of each primer; 200 nmol/L probe; 0.75 units of platinum Taq polymerase (Invitrogen, Carlsbad, CA); 200 µmol/L of each of dATP, dCTP, dGTP, and dTTP; 16.6 mmol/L ammonium sulfate; 67 mmol/L Trizma; and 6.7 mmol/L MgCl_2; 10 mmol/L mercaptoethanol; and 0.1% DMSO. Two microliters of treated DNA solution were used in each real-time MSP reaction. Amplifications were carried out in 384-well plates in a 7900 Sequence detector (Perkin-Elmer Applied Biosystems, Foster City, CA). Each plate consisted of patient samples and multiple water blanks, as well as positive and negative controls. Leukocytes from a healthy individual were methylated in vitro with excess SssI methyltransferase (New England Biolabs Inc, Beverly, MA) to generate completely methylated DNA, and serial dilutions of this DNA were used for constructing the calibration curves on each plate. A diagram to further explain the quantitative MSP is detailed in Figure A1.

Statistical Methods
The 169 study samples were randomly divided evenly into training (n = 84) and validation (n = 85) data sets. Optimum cutoff values, maximizing the sum of sensitivity and specificity with respect to prediction of case-control status, for QMSP from blood samples for each individual gene were determined for each gene in the training data set. Predicted sensitivities and specificities of the individual gene cutoff values and determinations of gene panels as a potential screening tool were subsequently estimated in an independent validation sample. The sensitivity of QMSP and MSP-based detection of hypermethylation in plasma and breast tissue, respectively, for breast cancer was calculated as the number of positive tests among the cancer cases divided by the number of total cancer cases. The specificity was calculated as the number of negative tests among the controls divided by the total number of controls. Individual optimal operating point cutoff values for the four genes were separately determined in the training data set by simultaneously maximizing both sensitivity and specificity for detection of breast cancer for all values of QMSP which resulted in a false-positivite rate (FPR) below 15% (ie, for all values with a specificity above 85%).³¹ An assumption of equal cost/benefit for sensitivity compared with specificity was imposed. These potential cutoff values were subsequently confirmed as essentially the same as those determined by means of classification and regression tree analysis (QUEST version 1.9.2; http://www.stat.wisc.edu/~loh/quest.html).³²

Mantel-Haenszel ² tests were performed to assess univariate associations between groups (cases v controls) and categorical factors of interest, and associations with continuous factors such as age were tested with t tests. ² tests were performed to assess the associations between pairs of gene markers. A two-sided 0.05-level test determined statistical significance for analysis, except to account for multiple comparisons in the separate evaluation of the four genes and the multiple gene panel with respect to stage of disease, a two-sided 0.01-level test determined statistical significance. All data analyses were conducted with SAS 9.1 (SAS Institute Inc, Cary, NC).

	RESULTS

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The demographic and clinicopathologic characteristics of the participants at study entry are summarized in Table 1. Women with breast cancer (n = 93) as compared with control women (n = 76) were older on average (mean age, 44.9 v 37.3 years), less likely to be premenopausal (53% v 91%), and less likely to have received any formal education (19% v 68%). However, both women with breast cancer and control women were similar in regards to place of birth, previous history of pregnancy, and marital status. Lastly, only one study participant (a case) reported any history of hormone replacement therapy.

Cutoff values to distinguish cases from controls for the four genes were separately determined in the training data set (n = 84). There were no significant differences between the training and validation (n = 85) data sets with respect to any of the measured demographic or clinicopathologic characteristics and with respect to tumor stage among the cases. In the training data set, optimal cutoffs were determined by maximizing the sensitivity and specificity for detection of breast cancer for all values of QMSP, which resulted in an FPR below 15% (ie, for all values with a specificity above 85%; Fig 1). However, in effect, detection of any level of aberrant methylation (normalized values > 0) resulted in more than 85% specificity for all genes except APC (for which any level of detectable methylation resulted in a specificity of 79%). For GSTP1, the optimal QMSP value distinguishing cases from controls was found to be 0, and only a single control in the training set was found to have an extremely high value (346.3). For the other three genes, an optimal cutoff was determined (APC = 3.2; RARβ2 = 2.6 x 10^–8; RASSF1A = 6.5 x 10^–3). These potential cutoff values were subsequently confirmed by means of classification and regression tree analysis, with the only difference being that we chose the minimum value in the interval between the highest control and lowest case value, whereas classification and regression tree analysis produced the median value between the highest control and lowest case value.

View larger version (13K): [in this window] [in a new window] [PowerPoint Slide for Teaching]   Fig 1. Receiver-operator characteristic (ROC) curves considering all the samples from the training data set (46 cancer cases and 38 controls) for the four individual genes. The ROC curves plot sensitivity versus 1-specificity. The determined cutoff values for GSTP1, RARβ2, Rassf1A, and APC were 0, 2.6 x 10–8, 6.5 x 10–3, and 3.2, respectively.

View larger version (15K): [in this window] [in a new window] [PowerPoint Slide for Teaching]   Fig 2. Methylation levels of RASSF1A, RAR-β2, GSTP1, and APC in plasma DNA of breast cancer patients (cases) and plasma from age-matched controls in validation data set. Calculation of the gene of interest: β-actin ratios were based on the fluorescence emission intensity values for both the gene of interest and β-actin obtained by quantitative real-time polymerase chain reaction analysis. Red horizontal bars indicate cutoff values. Values designated as 0.001 are zero values, which cannot be plotted correctly on a log scale.

When considering each gene as a dichotomous factor, with a cutoff as determined in training data set, methylation of multiple genes was present in 10 (21%) of 47 cases of breast cancer but was not detected in any of 38 controls in the validation data set. Although 19 cases (40%) of breast cancer had methylation of only one gene (Rassf1A, eight; RARβ2, four; GSTP1, four; APC, three), four cases (9%) had methylation of two genes, four cases (9%) had methylation of three genes, and two cases (4%) had methylation of all four genes of interest. Methylation of each gene was positively associated (but not necessarily significantly associated) with methylation of the other genes (data not shown), with odds ratios ranging from 1.8 (for the association between methylation of Rassf1A with methylation of RARβ2) to 4.8 (for the association between methylation of Rassf1A with methylation of APC). However, the use of combinations of methylated gene substantially increased the sensitivity for detecting breast cancer (from 32% for any single gene to 62% with all four genes), suggesting that the four genes, although somewhat associated with each other, were independently associated with detection of breast cancer. Small sample sizes prevented a formal multivariable analysis of the importance of each gene or gene combinations with respect to case-control status.

Detection of aberrant methylation was associated with increased tumor stage among all cases (Table 3). At least one of the four genes was detected by QMSP in eight (33%) of 24 plasma samples from women with stage I-II cancer and in 43 (65%) of 66 samples from women with stage III-IV cancer. RARβ2, Rassf1A, and APC were all somewhat more often detected in late- compared with early-stage breast cancer, whereas GSTP1 was not associated with stage. In early-stage disease, aberrant methylation of GSTP1 was present in six (25%) of 24 women with early-stage cancer. GSTP1, RARβ2, and Rassf1A were each aberrantly methylated in approximately 30% of stage III-IV tumors. Although there were no statistically significant differences in detection of aberrant methylation by age or menopausal status among cases, each gene was somewhat more likely to be aberrantly methylated in older compared with younger, and similarly in menopausal as compared to premenopausal participants with breast cancer (Tables 4 and 5).

	DISCUSSION

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Circulating plasma DNA, presumably shed from the original primary tumor, can be retrieved and tested for genetic and epigenetic alterations. Previous studies^33-39 have reported on detection of various genetic and epigenetic alterations in matched samples from tumor tissue and plasma in patients with cancer of the lung, head and neck, kidney, colon, and pancreas. However, thus far, little is known about the relationship between detection of epigenetic abnormalities in primary breast cancer tissue and detection of such abnormalities in plasma. Although knowledge of the underlying mechanism of this circulating DNA is still limited, there is some evidence that the DNA is released from the tumor as a glyconucleoprotein complex that may protect it from degradation by nucleases.⁴⁰ It remains unclear whether release of tumor DNA into plasma is associated with tumor necrosis, apoptotic cell death, or other selective cellular processes. However, these data provide strong, albeit indirect, evidence that the DNA containing the methylation of the specified gene originates from the primary breast cancer and is not an artifact in the plasma DNA from nonmalignant tissues. Thus, accumulating data on these methylation markers (APC, Rassf1A, GSTP1, and RARβ2) is of interest for the evaluation of such changes as potential plasma- or serum-based biomarkers for detection or monitoring of breast cancer patients.

Detection of methylation in circulating DNA depends on the ability of the assay to detect methylated DNA in a background of wild type DNA (estimated at > 1:1000). In our experience and that reported by others,⁴¹ QMSP is more sensitive than conventional MSP, and the identification of low levels of methylation in plasma DNA may be due to the higher sensitivity of QMSP compared with conventional MSP.

Although the sensitivity associated with any single gene was never greater than 32%, we achieved reasonable sensitivity with high specificity in breast cancer detection using only a small number of common epigenetic markers. However, one could envision an expansion of the current panel to other relevant and specific tumor suppressor genes to increase the sensitivity of the assay that might be of interest in both the developed and developing world. This expanded panel might be particularly useful for the diagnosis of early-stage breast cancer, assuming, as available data suggest, that most breast cancers carry epigenetic alterations.

In the present study, we amplified each gene individually by QMSP. This is clearly a research assay, and we used a purely statistical method to determine optimal QMSP cutoff values for each gene, which for one case (RARβ2) resulted in an extremely low (2.6 x 10^–8) cutoff value. For practical purposes, values of QMSP less than 0.01% indicate hypermethylation at extremely low levels, and the biologic relevance of such low values is unknown. However, development of multiplex PCR approaches based on QMSP along with hardware and software for automated signal enumeration and robotic pipeting currently under development will greatly facilitate the use of molecular diagnostics in the developed world. Other technological developments will be necessary if such an approach is to be used in resource-poor settings.

It is interesting that, in this study, methylation was detected not only in patients with breast cancer but also in a small proportion of control subjects (13%). Methylation of several genes has been reported previously in nonmalignant tissues and serum DNA of smokers. Detection of methylation in plasma DNA could be a marker of disease (an early neoplastic effect), exposure (a biologic effect of any environmental factor) or both. The presence of methylation in healthy subjects may reflect chronic exposure to still unidentified environmental carcinogenic factors. Longitudinal epidemiologic studies assessing the risk of developing precursor lesions associated with methylation of the tested genes will elucidate the basis of methylation related to environmental factors. Thus, detection of methylation may perhaps identify high-risk individuals who could benefit from more intensive standard evaluation that could eventually detect breast cancer earlier.

Because clinical outcomes in breast cancer often requires prolonged follow-up (still in progress for the current study), methylation markers were evaluated against known prognostic clinicopathologic factors. In univariate analysis, Rassf1A, RARβ2, and APC methylation were all marginally associated with advanced American Joint Committee on Cancer (AJCC) stage, as well as increasing age and post menopausal status. As additional markers improved assay detection sensitivity, statistical analysis of multimarker combinations with clinical and histopathologic factors was also performed. The combination of methylation of any of the four genes is significantly associated with increasing stage (P = .007), as is shown in Table 3. It must be noted that most AJCC stage IV patients generally receive chemotherapy (although these patients presented with stage IV and had not yet received therapy before blood draw), and its impact on tumor cell DNA presence in blood needs to be further examined in well-defined treatment protocols in more comprehensive studies. The detection of occult circulating tumor cells using a combination of epigenetic markers may not only enhance insight into the biologic behavior of a primary tumor of an individual, but may also provide valuable prognostic information that can be readily monitored throughout the disease course. Additionally, assessment of the functional role for these tumor markers in cancer progression may identify patients at high risk for relapse.

Authors' Note
Under a licensing agreement between Oncomethylome Sciences SA and the Johns Hopkins University, Dr Sidransky is entitled to a share of royalty received by the University on sales of products described in this article. Dr Sidransky owns Oncomethylome Sciences SA stock, which is subject to certain restrictions under University policy. Dr Sidransky is a paid consultant to Oncomethylome Sciences SA and is a paid member of the company's Scientific Advisory Board. The term of this arrangement is being managed by the Johns Hopkins University in accordance with its conflict of interest policies.

	Appendix

TOP ABSTRACT INTRODUCTION PATIENTS AND METHODS RESULTS DISCUSSION Appendix Authors' Disclosures of... Author Contributions GLOSSARY REFERENCES

 

View larger version (19K): [in this window] [in a new window] [PowerPoint Slide for Teaching]   Fig A1. (A) Sodium bisulfite modification of unmethylated cytosines. Unmethylated cytosine through a three-step process is converted into uracil during sodium bisulfite reaction. Conversion does not occur on methylated cytosine. (B) Overview of quantitative methylation-specific polymerase chain reaction (PCR); (C) TaqMan probes (Perkin-Elmore Applied Biosystems, Norwalk, CT) utilize the 5' exonuclease activity of the enzyme Taq Polymerase (Invitrogen, Carlsbad, CA) for measuring the amount of target sequences in the samples. Methylation-specific internal TaqMan probes consist on an approximately 30–base pair oligonucleotide probe labeled with a reporter (R) fluorophore at the 5' end and a quencher (Q) fluorophore at the 3' end.

	Authors' Disclosures of Potential Conflicts of Interest

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Dollar Amount Codes (A) < $10,000 (B) $10,000-$99,999 (C) $100,000 (N/R) Not Required

	Author Contributions

TOP ABSTRACT INTRODUCTION PATIENTS AND METHODS RESULTS DISCUSSION Appendix Authors' Disclosures of... Author Contributions GLOSSARY REFERENCES

 

Conception and design: Mohammad O. Hoque, Nancy B. Kiviat, David Sidransky Financial support: Nancy B. Kiviat, David Sidransky Administrative support: Barry Trink, Nancy B. Kiviat, David Sidransky Provision of study materials or patients: Mohammad O. Hoque, Qinghua Feng, Papa Toure, Amadou Dem, Stephen E. Hawes, Troy Wood, Carmen Jeronimo, Eli Rosenbaum, Mujun Yu Collection and assembly of data: Mohammad O. Hoque Data analysis and interpretation: Mohammad O. Hoque, Cathy W. Critchlow, Joshua Stern, Nancy B. Kiviat, David Sidransky, Stephen E. Hawes Manuscript writing: Mohammad O. Hoque, Nancy B. Kiviat, David Sidransky, Stephen E. Hawes Final approval of manuscript: Nancy B. Kiviat, David Sidransky

 

	GLOSSARY

TOP ABSTRACT INTRODUCTION PATIENTS AND METHODS RESULTS DISCUSSION Appendix Authors' Disclosures of... Author Contributions GLOSSARY REFERENCES

 

APC (adenomatous polyptosis coli) gene:

A tumor suppressor gene. Mutations in the gene are responsible for familial adenomatous polyposis (germline mutations) or sporadic (somatic mutations) colorectal tumors. The gene product is known to interact with adherens junction proteins, a- and b-catenins, suggesting a role in cell adhesion.

GSTP1 (glutathione s-transferase p1):

Belongs to a family of enzymes that play an important role in detoxification, it catalyzes the conjugation of many compounds with reduced glutathione. Based on their biochemical, immunologic, and structural properties, GSTs are classified into four main classes: (alpha), µ (mu), (pi), and (theta).

Promoter hypermethylation:

Methylation of the promoter region of a gene can lead to DNA silencing as a consequence of the inability of activating transcriptional factors to bind to the promoter region, a process important in gene transcription. In addition, repressor complexes may be attracted to sites of promoter methylation, leading to the formation of inactive chromatin structures.

Rassf1A (Ras association domain family member 1A):

One of the most commonly epigenetically silenced tumor suppressor genes in human cancer that controls cell cycle and apoptosis.

RARβ2 (retinoic acid receptor beta) gene:

RARβ is expressed from two distinct promoters, both of which have distinct CpG islands. RARβ2 is expressed in adult tissues and hypermethylated in a number of cancer cells. Studies in cell lines indicate that sensitivity to the effects of retinoic acid is lost when RARβ expression is suppressed.

	NOTES

 
published online ahead of print at www.jco.org on August 14, 2006.

Supported by received grant support from the National Cancer Institute (National Institutes of Health, Bethesda, MD): 5U01CA 85050, N.B.K.; and U01-CA84986, D.S. Also supported by Oncomethylome Sciences SA.

Under a licensing agreement between Oncomethylome Sciences, SA and the Johns Hopkins University, Dr. Sidransky is entitled to a share of royalty received by the University on sales of products described in this article. Dr. Sidransky owns Oncomethylome Sciences, SA stock, which is subject to certain restrictions under University policy. The term of this arrangement is being managed by the Johns Hopkins University in accordance with its conflict of interest policies.

Terms in blue are defined in the glossary, found at the end of this article and online at www.jco.org.

Authors' disclosures of potential conflicts of interest and author contributions are found at the end of this article.

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Submitted January 24, 2005; accepted May 25, 2006.

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