Identification of Novel High-Frequency DNA Methylation Changes in Breast Cancer
Publication Date
December 19, 2007
Journal
PLOS ONE
Authors
Jared M. Ordway, Muhammad A. Budiman, Yulia Korshunova, Rebecca K. Maloney, et al
Volume
2
Issue
12
Pages
e1314
DOI
https://dx.plos.org/10.1371/journal.pone.0001314
Publisher URL
http://journals.plos.org/plosone/article?id=10.1371%2Fjournal.pone.0001314
PubMed
http://www.ncbi.nlm.nih.gov/pubmed/18091988
PubMed Central
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC2117343
Europe PMC
http://europepmc.org/abstract/MED/18091988
Web of Science
000207459600002
Scopus
44449175595
Mendeley
http://www.mendeley.com/research/identification-novel-highfrequency-dna-methylation-changes-breast-cancer-2
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Mendeley | Further Information

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The inherent thermodynamic stability of cytosine methylation and the apparent high specificity of the alterations for disease may accelerate the development of powerful molecular diagnostics for cancer. We report a genome-wide analysis of DNA methylation alterations in breast cancer. The approach efficiently identified a large collection of novel differentially DNA methylated loci (approximately 200), a subset of which was independently validated across a panel of over 230 clinical samples. The differential cytosine methylation events were independent of patient age, tumor stage, estrogen receptor status or family history of breast cancer. The power of the global approach for discovery is underscored by the identification of a single differentially methylated locus, associated with the GHSR gene, capable of distinguishing infiltrating ductal breast carcinoma from normal and benign breast tissues with a sensitivity and specificity of 90% and 96%, respectively. Notably, the frequency of these molecular abnormalities in breast tumors substantially exceeds the frequency of any other single genetic or epigenetic change reported to date. The discovery of over 50 novel DNA methylation-based biomarkers of breast cancer may provide new routes for development of DNA methylation-based diagnostics and prognostics, as well as reveal epigenetically regulated mechanism involved in breast tumorigenesis.", "link"=>"http://www.mendeley.com/research/identification-novel-highfrequency-dna-methylation-changes-breast-cancer-2", "reader_count"=>57, "reader_count_by_academic_status"=>{"Professor > Associate Professor"=>1, "Researcher"=>20, "Student > Doctoral Student"=>2, "Student > Ph. D. 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CrossRef

Scopus | Further Information

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Figshare

  • {"files"=>["https://ndownloader.figshare.com/files/941388"], "description"=>"<p>(A) DNA methylation measurements for selected loci in normal blood, normal or benign breast tissue and breast tumors. Each data point represents the averaged delta Ct value for an independent clinical sample. (B) ROC curve analyses of the four loci shown in (A). Sensitivity (percentage of tumor samples scoring above a methylation threshold) and specificity (percentage of non-tumor samples scoring below that same threshold) were calculated for all observed delta Ct values. The minimum allowed threshold was set at 0.5 so that calculations could not be based on thresholds within the variability range of the qPCR platform.</p>", "links"=>[], "tags"=>["dna", "methylation"], "article_id"=>611789, "categories"=>["Genetics", "Plant Biology", "Molecular Biology"], "users"=>["Jared M. Ordway", "Muhammad A. Budiman", "Yulia Korshunova", "Rebecca K. Maloney", "Joseph A. Bedell", "Robert W. Citek", "Blaire Bacher", "Seth Peterson", "Tracy Rohlfing", "Jacqueline Hall", "Robert Brown", "Nathan Lakey", "Rebecca W. Doerge", "Robert A. Martienssen", "Jorge Leon", "John D. McPherson", "Jeffrey A. Jeddeloh"], "doi"=>"https://dx.doi.org/10.1371/journal.pone.0001314.g005", "stats"=>{"downloads"=>0, "page_views"=>4, "likes"=>0}, "figshare_url"=>"https://figshare.com/articles/_Differential_DNA_methylation_of_selected_loci_/611789", "title"=>"Differential DNA methylation of selected loci.", "pos_in_sequence"=>0, "defined_type"=>1, "published_date"=>"2007-12-19 00:29:49"}
  • {"files"=>["https://ndownloader.figshare.com/files/941156"], "description"=>"<p>qPCR measurements of DNA methylation density were obtained for 53 loci across 16 IDC tumor samples and 25 normal or benign breast samples. An average delta Ct (Ct <sub>McrBC</sub>–Ct <sub>Mock</sub>) less than 1.0 was scored as sparsely methylated (green cells). A delta Ct of 1.0 indicates that approximately half of the DNA in the reaction was cleaved by McrBC within the amplified region and therefore contained a measurable density of DNA methylation. An average delta Ct greater than or equal to 1.0, but less than 2.0 was scored as intermediately methylated (yellow cells). Finally, an average delta Ct≥2.0 (≥75% of DNA molecules were cleaved by McrBC) was scored as densely methylated (red cells).</p>", "links"=>[], "tags"=>["dna", "methylation", "loci", "validation"], "article_id"=>611559, "categories"=>["Genetics", "Plant Biology", "Molecular Biology"], "users"=>["Jared M. Ordway", "Muhammad A. Budiman", "Yulia Korshunova", "Rebecca K. Maloney", "Joseph A. Bedell", "Robert W. Citek", "Blaire Bacher", "Seth Peterson", "Tracy Rohlfing", "Jacqueline Hall", "Robert Brown", "Nathan Lakey", "Rebecca W. Doerge", "Robert A. Martienssen", "Jorge Leon", "John D. McPherson", "Jeffrey A. Jeddeloh"], "doi"=>"https://dx.doi.org/10.1371/journal.pone.0001314.g003", "stats"=>{"downloads"=>1, "page_views"=>7, "likes"=>0}, "figshare_url"=>"https://figshare.com/articles/_Differential_DNA_methylation_of_identified_loci_within_an_initial_validation_panel_of_clinical_samples_/611559", "title"=>"Differential DNA methylation of identified loci within an initial validation panel of clinical samples.", "pos_in_sequence"=>0, "defined_type"=>1, "published_date"=>"2007-12-19 00:25:59"}
  • {"files"=>["https://ndownloader.figshare.com/files/941671"], "description"=>"a<p>Loci not within the vicinity of a known annotated gene (no description) are described by chromosome number and nucleotide position of the microarray feature (Ensembl 36).</p>b<p>Thresholds indicate the optimal average dCt value for distinction between tumor and non-tumor tissues.</p>", "links"=>[], "tags"=>["cancer", "biomarker"], "article_id"=>612072, "categories"=>["Genetics", "Plant Biology", "Molecular Biology"], "users"=>["Jared M. Ordway", "Muhammad A. Budiman", "Yulia Korshunova", "Rebecca K. Maloney", "Joseph A. Bedell", "Robert W. Citek", "Blaire Bacher", "Seth Peterson", "Tracy Rohlfing", "Jacqueline Hall", "Robert Brown", "Nathan Lakey", "Rebecca W. Doerge", "Robert A. Martienssen", "Jorge Leon", "John D. McPherson", "Jeffrey A. Jeddeloh"], "doi"=>"https://dx.doi.org/10.1371/journal.pone.0001314.t001", "stats"=>{"downloads"=>0, "page_views"=>1, "likes"=>0}, "figshare_url"=>"https://figshare.com/articles/_Breast_Cancer_Biomarker_Validation_/612072", "title"=>"Breast Cancer Biomarker Validation.", "pos_in_sequence"=>0, "defined_type"=>3, "published_date"=>"2007-12-19 00:34:32"}
  • {"files"=>["https://ndownloader.figshare.com/files/940903"], "description"=>"<p>(A) Hierarchical clustering of differentially methylated loci identified by microarray analysis. DNA methylation measurements of 220 loci identified to be significantly differentially methylated by statistical analysis of global DNA methylation profiles are shown. The color scale of the heatmap represents densely methylated loci (red) to sparsely methylated loci (green). Unsupervised clustering (top dendrogram) distinguishes adjacent histology normal breast tissues (green branches) from breast cancer tissues (red branches). Individual matched tumor/adjacent histology normal tissues pairs are indicated by a number assigned to each individual (Matched pair). (B) Differential DNA methylation in individual tumor and adjacent histology normal tissue pairs. Differences between log<sub>2</sub> ratios for individual tumor and adjacent histology normal pairs are shown for known and novel epigenetic targets. Because the experimental procedure compares total genome representations to those depleted for fragments containing DNA methylation, methylated sequences have a untreated:depleted ratio near or above 1.0 while unmethylated sequences have a ratio approaching zero due to mass normalization of target DNA <a href=\"http://www.plosone.org/article/info:doi/10.1371/journal.pone.0001314#pone.0001314-Ordway1\" target=\"_blank\">[27]</a>. Log<sub>2</sub> differences ≥0.7 (red), 0.5 to 0.6 (yellow) and ≤0.5 (green) are shown. The annotated genes associated with the differential DNA methylation events are indicated at the left.</p>", "links"=>[], "tags"=>["epigenetic", "targets"], "article_id"=>611311, "categories"=>["Genetics", "Plant Biology", "Molecular Biology"], "users"=>["Jared M. Ordway", "Muhammad A. Budiman", "Yulia Korshunova", "Rebecca K. Maloney", "Joseph A. Bedell", "Robert W. Citek", "Blaire Bacher", "Seth Peterson", "Tracy Rohlfing", "Jacqueline Hall", "Robert Brown", "Nathan Lakey", "Rebecca W. Doerge", "Robert A. Martienssen", "Jorge Leon", "John D. McPherson", "Jeffrey A. Jeddeloh"], "doi"=>"https://dx.doi.org/10.1371/journal.pone.0001314.g001", "stats"=>{"downloads"=>0, "page_views"=>1, "likes"=>0}, "figshare_url"=>"https://figshare.com/articles/_Comparison_of_previously_identified_and_novel_epigenetic_targets_in_breast_cancer_/611311", "title"=>"Comparison of previously identified and novel epigenetic targets in breast cancer.", "pos_in_sequence"=>0, "defined_type"=>1, "published_date"=>"2007-12-19 00:21:51"}
  • {"files"=>["https://ndownloader.figshare.com/files/463061", "https://ndownloader.figshare.com/files/463089", "https://ndownloader.figshare.com/files/463121", "https://ndownloader.figshare.com/files/463154", "https://ndownloader.figshare.com/files/463274", "https://ndownloader.figshare.com/files/463299", "https://ndownloader.figshare.com/files/463307", "https://ndownloader.figshare.com/files/463412"], "description"=>"<div><p>Recent data have revealed that epigenetic alterations, including DNA methylation and chromatin structure changes, are among the earliest molecular abnormalities to occur during tumorigenesis. The inherent thermodynamic stability of cytosine methylation and the apparent high specificity of the alterations for disease may accelerate the development of powerful molecular diagnostics for cancer. We report a genome-wide analysis of DNA methylation alterations in breast cancer. The approach efficiently identified a large collection of novel differentially DNA methylated loci (∼200), a subset of which was independently validated across a panel of over 230 clinical samples. The differential cytosine methylation events were independent of patient age, tumor stage, estrogen receptor status or family history of breast cancer. The power of the global approach for discovery is underscored by the identification of a single differentially methylated locus, associated with the <em>GHSR</em> gene, capable of distinguishing infiltrating ductal breast carcinoma from normal and benign breast tissues with a sensitivity and specificity of 90% and 96%, respectively. Notably, the frequency of these molecular abnormalities in breast tumors substantially exceeds the frequency of any other single genetic or epigenetic change reported to date. The discovery of over 50 novel DNA methylation-based biomarkers of breast cancer may provide new routes for development of DNA methylation-based diagnostics and prognostics, as well as reveal epigenetically regulated mechanism involved in breast tumorigenesis.</p></div>", "links"=>[], "tags"=>["high-frequency", "dna", "methylation", "changes", "cancer"], "article_id"=>151261, "categories"=>["Genetics", "Cell Biology", "Molecular Biology"], "users"=>["Jared M. Ordway", "Muhammad A. Budiman", "Yulia Korshunova", "Rebecca K. Maloney", "Joseph A. Bedell", "Robert W. Citek", "Blaire Bacher", "Seth Peterson", "Tracy Rohlfing", "Jacqueline Hall", "Robert Brown", "Nathan Lakey", "Rebecca W. Doerge", "Robert A. Martienssen", "Jorge Leon", "John D. McPherson", "Jeffrey A. Jeddeloh"], "doi"=>["https://dx.doi.org/10.1371/journal.pone.0001314.s001", "https://dx.doi.org/10.1371/journal.pone.0001314.s002", "https://dx.doi.org/10.1371/journal.pone.0001314.s003", "https://dx.doi.org/10.1371/journal.pone.0001314.s004", "https://dx.doi.org/10.1371/journal.pone.0001314.s005", "https://dx.doi.org/10.1371/journal.pone.0001314.s006", "https://dx.doi.org/10.1371/journal.pone.0001314.s007", "https://dx.doi.org/10.1371/journal.pone.0001314.s008"], "stats"=>{"downloads"=>16, "page_views"=>8, "likes"=>0}, "figshare_url"=>"https://figshare.com/articles/Identification_of_Novel_High_Frequency_DNA_Methylation_Changes_in_Breast_Cancer/151261", "title"=>"Identification of Novel High-Frequency DNA Methylation Changes in Breast Cancer", "pos_in_sequence"=>0, "defined_type"=>4, "published_date"=>"2007-12-19 00:21:01"}
  • {"files"=>["https://ndownloader.figshare.com/files/941493"], "description"=>"<p>Analyzed loci included <i>GHSR</i> (A, B), the uncharacterized locus corresponding to chr7-8256880 (C, D), <i>MGA</i> (E, F) and <i>NFIX</i> (G, H). Bisulphite sequencing was performed by 454 Life Sciences technology as described in <a href=\"http://www.plosone.org/article/info:doi/10.1371/journal.pone.0001314#s4\" target=\"_blank\">Materials and Methods</a>. The average number of molecules sequenced for each locus within each sample was 587. The calculated DNA methylation density (number of methylated CpGs divided by the total number of CpGs sequenced) for each sample is plotted versus the qPCR DNA methylation measurement for the same sample (A, C, E, G). Analyzed samples included normal breast tissues (open circles), tumor-adjacent histology normal breast tissues (filled circles) and breast tumors (filled squares). The number of samples analyzed and the qPCR-based methylation score are as follows: <i>GHSR,</i> 6 tumor (5 densely and 1 intermediately methylated), 3 adjacent normal (sparsely methylated) and 5 normal (sparsely methylated); chr7-8256880, 6 tumor (3 densely and 3 intermediately methylated), 3 adjacent normal (sparsely methylated) and 7 normal (sparsely methylated); <i>MGA,</i> 6 tumor (2 densely and 4 intermediately methylated), 3 adjacent normal (2 sparsely and 1 intermediately methylated) and 5 normal (sparsely methylated); <i>NFIX</i>, 5 tumor (densely methylated), 3 adjacent normal (sparsely methylated) and 5 normal (sparsely methylated). In addition, the percent methylation occupancy at each analyzed CpG dinucleotide is shown (B, D, F, H).</p>", "links"=>[], "tags"=>["sequencing", "dna"], "article_id"=>611900, "categories"=>["Genetics", "Plant Biology", "Molecular Biology"], "users"=>["Jared M. Ordway", "Muhammad A. Budiman", "Yulia Korshunova", "Rebecca K. Maloney", "Joseph A. Bedell", "Robert W. Citek", "Blaire Bacher", "Seth Peterson", "Tracy Rohlfing", "Jacqueline Hall", "Robert Brown", "Nathan Lakey", "Rebecca W. Doerge", "Robert A. Martienssen", "Jorge Leon", "John D. McPherson", "Jeffrey A. Jeddeloh"], "doi"=>"https://dx.doi.org/10.1371/journal.pone.0001314.g006", "stats"=>{"downloads"=>0, "page_views"=>1, "likes"=>0}, "figshare_url"=>"https://figshare.com/articles/_Bisulphite_sequencing_analysis_of_DNA_methylation_/611900", "title"=>"Bisulphite sequencing analysis of DNA methylation.", "pos_in_sequence"=>0, "defined_type"=>1, "published_date"=>"2007-12-19 00:31:40"}
  • {"files"=>["https://ndownloader.figshare.com/files/941298"], "description"=>"<p>(A) Comparison of the frequency of differential DNA methylation of 16 loci in stage I breast tumors relative to stage II–III breast tumors. (B) DNA methylation density of 3 selected loci relative to tumor stage. The percent depletion by McrBC for each sample in which a given locus scored as methylated was calculated [1-(1/2̂delta Ct (McrBC digested – Mock treated)) * 100] to provide a measure of the load of methylated molecules within the sample. The % depletion is plotted (from left to right) for normal and benign samples, stage I tumors, stage IIA tumors, stage IIB tumors and stage III tumors.</p>", "links"=>[], "tags"=>["dna", "methylation"], "article_id"=>611704, "categories"=>["Genetics", "Plant Biology", "Molecular Biology"], "users"=>["Jared M. Ordway", "Muhammad A. Budiman", "Yulia Korshunova", "Rebecca K. Maloney", "Joseph A. Bedell", "Robert W. Citek", "Blaire Bacher", "Seth Peterson", "Tracy Rohlfing", "Jacqueline Hall", "Robert Brown", "Nathan Lakey", "Rebecca W. Doerge", "Robert A. Martienssen", "Jorge Leon", "John D. McPherson", "Jeffrey A. Jeddeloh"], "doi"=>"https://dx.doi.org/10.1371/journal.pone.0001314.g004", "stats"=>{"downloads"=>2, "page_views"=>3, "likes"=>0}, "figshare_url"=>"https://figshare.com/articles/_Differential_DNA_methylation_relative_to_tumor_stage_/611704", "title"=>"Differential DNA methylation relative to tumor stage.", "pos_in_sequence"=>0, "defined_type"=>1, "published_date"=>"2007-12-19 00:28:24"}
  • {"files"=>["https://ndownloader.figshare.com/files/941602"], "description"=>"<p>Transcription of <i>GHSR1a</i> was analyzed by RT-PCR. RT-PCR was performed using gene-specific primer pairs designed to flank intronic sequence so that the contribution of contaminating genomic DNA could be excluded. Analysis of <i>GAPDH</i> expression was performed as an internal control. Serial dilutions of first-strand cDNA preparations from tumor samples and a normal breast tissue sample were used as templates for PCR. The DNA methylation measurement (qPCR) for each locus in each tumor sample is indicated (- sparse, + intermediate and ++ dense methylation).</p>", "links"=>[], "tags"=>["dna", "hypermethylation"], "article_id"=>612001, "categories"=>["Genetics", "Plant Biology", "Molecular Biology"], "users"=>["Jared M. Ordway", "Muhammad A. Budiman", "Yulia Korshunova", "Rebecca K. Maloney", "Joseph A. Bedell", "Robert W. Citek", "Blaire Bacher", "Seth Peterson", "Tracy Rohlfing", "Jacqueline Hall", "Robert Brown", "Nathan Lakey", "Rebecca W. Doerge", "Robert A. Martienssen", "Jorge Leon", "John D. McPherson", "Jeffrey A. Jeddeloh"], "doi"=>"https://dx.doi.org/10.1371/journal.pone.0001314.g007", "stats"=>{"downloads"=>0, "page_views"=>4, "likes"=>0}, "figshare_url"=>"https://figshare.com/articles/_Correlation_between_DNA_hypermethylation_and_gene_expression_/612001", "title"=>"Correlation between DNA hypermethylation and gene expression.", "pos_in_sequence"=>0, "defined_type"=>1, "published_date"=>"2007-12-19 00:33:21"}
  • {"files"=>["https://ndownloader.figshare.com/files/941008"], "description"=>"<p>Log<sub>2</sub> (tumor-adjacent normal) microarray measurements of differential DNA methylation (y-axis) are plotted against qPCR (ddCt tumor-adjacent normal) measurements (x-axis). Primer pairs designed to amplify 116 of the 220 regions predicted to be significantly differentially methylated. Delta-delta Ct values (delta Ct <sub>tumor</sub>–delta Ct <sub>adjacent normal</sub>) and differential log<sub>2</sub> microarray values (Log<sub>2 tumor</sub>-Log<sub>2 adjacent normal</sub>) were compared for breast tumor/adjacent normal tissue pairs. Data for one representative tumor/adjacent normal pair are shown. Data points in the upper right and lower left quadrants represent hypermethylation and hypomethylation measurements that are concordant between the two independent methods, respectively. qPCR measurements within the 0.5 cycle range of variance of the qPCR platform (hatched lines) were considered discordant.</p>", "links"=>[], "tags"=>["differential", "dna", "methylation", "microarray", "qpcr"], "article_id"=>611410, "categories"=>["Genetics", "Plant Biology", "Molecular Biology"], "users"=>["Jared M. Ordway", "Muhammad A. Budiman", "Yulia Korshunova", "Rebecca K. Maloney", "Joseph A. Bedell", "Robert W. Citek", "Blaire Bacher", "Seth Peterson", "Tracy Rohlfing", "Jacqueline Hall", "Robert Brown", "Nathan Lakey", "Rebecca W. Doerge", "Robert A. Martienssen", "Jorge Leon", "John D. McPherson", "Jeffrey A. Jeddeloh"], "doi"=>"https://dx.doi.org/10.1371/journal.pone.0001314.g002", "stats"=>{"downloads"=>3, "page_views"=>18, "likes"=>0}, "figshare_url"=>"https://figshare.com/articles/_Correlation_between_differential_DNA_methylation_measured_by_microarray_and_independent_qPCR_analyses_/611410", "title"=>"Correlation between differential DNA methylation measured by microarray and independent qPCR analyses.", "pos_in_sequence"=>0, "defined_type"=>1, "published_date"=>"2007-12-19 00:23:30"}

PMC Usage Stats | Further Information

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Relative Metric

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