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dna methylation analysis  (Zymo Research)
93
Zymo Research dna methylation analysis
Fig. 6 Construction and Evaluation of Prognostic RiskScoreEpi Model and Nomogram Integrating Clinical Information. A, B For TCGA Train Set (A) and ICGC Validation Set (B): Top panel: Distribution plot of RiskScoreEpi in high- and low-risk groups. Middle panel: Distribution plot of survival time and survival status in high- and low-risk groups; X-axis represents patients with increasing RiskScoreEpi, and Y-axis represents survival time. Bottom panel: Beta values of the six CpG sites in high- and low-risk groups. C ROC curves and AUC analyses for 1-, 3-, and 5-year overall survival prediction of the RiskScoreEpi model in TCGA dataset. D Sankey diagram illustrating similarities and differences in sample composition before and after grouping based on two different criteria: TCGA <t>DNAm</t> subgroups (left) and RiskScoreEpi model (right). E, F Univariate E and Multivariate F Cox regression analysis of RiskScoreEpi and clinical information in TCGA dataset. G Heatmap of six CpG sites’ <t>methylation</t> levels, corresponding RiskScoreEpi, survival time, survival status, and risk groups of the 8 PDAC patients we collected. Color bar = β-value. H Nomogram for predicting 1-, 2-, and 3-year overall survival of PDAC patients based on RiskScoreEpi and prognostic factors. I Calibration curves of the nomogram at 1, 3, and 5 years. J DCA curves of the nomogram, RiskScoreEpi, and other prognostic factors. TCGA, The Cancer Genome Atlas Program; ICGC, International Cancer Genome Consortium; ROC, receiver operating characteristic; AUC, area under the curve; PDAC, pancreatic ductal adenocarcinoma; DCA, decision curve analysis
Dna Methylation Analysis, supplied by Zymo Research, used in various techniques. Bioz Stars score: 93/100, based on 1 PubMed citations. ZERO BIAS - scores, article reviews, protocol conditions and more
https://www.bioz.com/result/dna methylation analysis/product/Zymo Research
Average 93 stars, based on 1 article reviews
dna methylation analysis - by Bioz Stars, 2026-03
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methylation analysis bisulfite sequencing genomic dna  (Thermo Fisher)
99
Thermo Fisher methylation analysis bisulfite sequencing genomic dna
Fig. 6 Construction and Evaluation of Prognostic RiskScoreEpi Model and Nomogram Integrating Clinical Information. A, B For TCGA Train Set (A) and ICGC Validation Set (B): Top panel: Distribution plot of RiskScoreEpi in high- and low-risk groups. Middle panel: Distribution plot of survival time and survival status in high- and low-risk groups; X-axis represents patients with increasing RiskScoreEpi, and Y-axis represents survival time. Bottom panel: Beta values of the six CpG sites in high- and low-risk groups. C ROC curves and AUC analyses for 1-, 3-, and 5-year overall survival prediction of the RiskScoreEpi model in TCGA dataset. D Sankey diagram illustrating similarities and differences in sample composition before and after grouping based on two different criteria: TCGA <t>DNAm</t> subgroups (left) and RiskScoreEpi model (right). E, F Univariate E and Multivariate F Cox regression analysis of RiskScoreEpi and clinical information in TCGA dataset. G Heatmap of six CpG sites’ <t>methylation</t> levels, corresponding RiskScoreEpi, survival time, survival status, and risk groups of the 8 PDAC patients we collected. Color bar = β-value. H Nomogram for predicting 1-, 2-, and 3-year overall survival of PDAC patients based on RiskScoreEpi and prognostic factors. I Calibration curves of the nomogram at 1, 3, and 5 years. J DCA curves of the nomogram, RiskScoreEpi, and other prognostic factors. TCGA, The Cancer Genome Atlas Program; ICGC, International Cancer Genome Consortium; ROC, receiver operating characteristic; AUC, area under the curve; PDAC, pancreatic ductal adenocarcinoma; DCA, decision curve analysis
Methylation Analysis Bisulfite Sequencing Genomic Dna, supplied by Thermo Fisher, used in various techniques. Bioz Stars score: 99/100, based on 1 PubMed citations. ZERO BIAS - scores, article reviews, protocol conditions and more
https://www.bioz.com/result/methylation analysis bisulfite sequencing genomic dna/product/Thermo Fisher
Average 99 stars, based on 1 article reviews
methylation analysis bisulfite sequencing genomic dna - by Bioz Stars, 2026-03
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locus-specific dna methylation analysis by targeted deep bisulfite sequencing  (Epigenomics ag)
90
Epigenomics ag locus-specific dna methylation analysis by targeted deep bisulfite sequencing
Fig. 6 Construction and Evaluation of Prognostic RiskScoreEpi Model and Nomogram Integrating Clinical Information. A, B For TCGA Train Set (A) and ICGC Validation Set (B): Top panel: Distribution plot of RiskScoreEpi in high- and low-risk groups. Middle panel: Distribution plot of survival time and survival status in high- and low-risk groups; X-axis represents patients with increasing RiskScoreEpi, and Y-axis represents survival time. Bottom panel: Beta values of the six CpG sites in high- and low-risk groups. C ROC curves and AUC analyses for 1-, 3-, and 5-year overall survival prediction of the RiskScoreEpi model in TCGA dataset. D Sankey diagram illustrating similarities and differences in sample composition before and after grouping based on two different criteria: TCGA <t>DNAm</t> subgroups (left) and RiskScoreEpi model (right). E, F Univariate E and Multivariate F Cox regression analysis of RiskScoreEpi and clinical information in TCGA dataset. G Heatmap of six CpG sites’ <t>methylation</t> levels, corresponding RiskScoreEpi, survival time, survival status, and risk groups of the 8 PDAC patients we collected. Color bar = β-value. H Nomogram for predicting 1-, 2-, and 3-year overall survival of PDAC patients based on RiskScoreEpi and prognostic factors. I Calibration curves of the nomogram at 1, 3, and 5 years. J DCA curves of the nomogram, RiskScoreEpi, and other prognostic factors. TCGA, The Cancer Genome Atlas Program; ICGC, International Cancer Genome Consortium; ROC, receiver operating characteristic; AUC, area under the curve; PDAC, pancreatic ductal adenocarcinoma; DCA, decision curve analysis
Locus Specific Dna Methylation Analysis By Targeted Deep Bisulfite Sequencing, supplied by Epigenomics ag, used in various techniques. Bioz Stars score: 90/100, based on 1 PubMed citations. ZERO BIAS - scores, article reviews, protocol conditions and more
https://www.bioz.com/result/locus-specific dna methylation analysis by targeted deep bisulfite sequencing/product/Epigenomics ag
Average 90 stars, based on 1 article reviews
locus-specific dna methylation analysis by targeted deep bisulfite sequencing - by Bioz Stars, 2026-03
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dna quality control, bisulfite conversion, genome-wide methylation analysis, and initial methylation signal detection quality control  (Sinotech Engineering Consultants)
90
Sinotech Engineering Consultants dna quality control, bisulfite conversion, genome-wide methylation analysis, and initial methylation signal detection quality control
Fig. 6 Construction and Evaluation of Prognostic RiskScoreEpi Model and Nomogram Integrating Clinical Information. A, B For TCGA Train Set (A) and ICGC Validation Set (B): Top panel: Distribution plot of RiskScoreEpi in high- and low-risk groups. Middle panel: Distribution plot of survival time and survival status in high- and low-risk groups; X-axis represents patients with increasing RiskScoreEpi, and Y-axis represents survival time. Bottom panel: Beta values of the six CpG sites in high- and low-risk groups. C ROC curves and AUC analyses for 1-, 3-, and 5-year overall survival prediction of the RiskScoreEpi model in TCGA dataset. D Sankey diagram illustrating similarities and differences in sample composition before and after grouping based on two different criteria: TCGA <t>DNAm</t> subgroups (left) and RiskScoreEpi model (right). E, F Univariate E and Multivariate F Cox regression analysis of RiskScoreEpi and clinical information in TCGA dataset. G Heatmap of six CpG sites’ <t>methylation</t> levels, corresponding RiskScoreEpi, survival time, survival status, and risk groups of the 8 PDAC patients we collected. Color bar = β-value. H Nomogram for predicting 1-, 2-, and 3-year overall survival of PDAC patients based on RiskScoreEpi and prognostic factors. I Calibration curves of the nomogram at 1, 3, and 5 years. J DCA curves of the nomogram, RiskScoreEpi, and other prognostic factors. TCGA, The Cancer Genome Atlas Program; ICGC, International Cancer Genome Consortium; ROC, receiver operating characteristic; AUC, area under the curve; PDAC, pancreatic ductal adenocarcinoma; DCA, decision curve analysis
Dna Quality Control, Bisulfite Conversion, Genome Wide Methylation Analysis, And Initial Methylation Signal Detection Quality Control, supplied by Sinotech Engineering Consultants, used in various techniques. Bioz Stars score: 90/100, based on 1 PubMed citations. ZERO BIAS - scores, article reviews, protocol conditions and more
https://www.bioz.com/result/dna quality control, bisulfite conversion, genome-wide methylation analysis, and initial methylation signal detection quality control/product/Sinotech Engineering Consultants
Average 90 stars, based on 1 article reviews
dna quality control, bisulfite conversion, genome-wide methylation analysis, and initial methylation signal detection quality control - by Bioz Stars, 2026-03
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bisulfite modification of genomic dna and methylation-specific pcr analysis  (tiangen biotech co)
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tiangen biotech co bisulfite modification of genomic dna and methylation-specific pcr analysis
Fig. 6 Construction and Evaluation of Prognostic RiskScoreEpi Model and Nomogram Integrating Clinical Information. A, B For TCGA Train Set (A) and ICGC Validation Set (B): Top panel: Distribution plot of RiskScoreEpi in high- and low-risk groups. Middle panel: Distribution plot of survival time and survival status in high- and low-risk groups; X-axis represents patients with increasing RiskScoreEpi, and Y-axis represents survival time. Bottom panel: Beta values of the six CpG sites in high- and low-risk groups. C ROC curves and AUC analyses for 1-, 3-, and 5-year overall survival prediction of the RiskScoreEpi model in TCGA dataset. D Sankey diagram illustrating similarities and differences in sample composition before and after grouping based on two different criteria: TCGA <t>DNAm</t> subgroups (left) and RiskScoreEpi model (right). E, F Univariate E and Multivariate F Cox regression analysis of RiskScoreEpi and clinical information in TCGA dataset. G Heatmap of six CpG sites’ <t>methylation</t> levels, corresponding RiskScoreEpi, survival time, survival status, and risk groups of the 8 PDAC patients we collected. Color bar = β-value. H Nomogram for predicting 1-, 2-, and 3-year overall survival of PDAC patients based on RiskScoreEpi and prognostic factors. I Calibration curves of the nomogram at 1, 3, and 5 years. J DCA curves of the nomogram, RiskScoreEpi, and other prognostic factors. TCGA, The Cancer Genome Atlas Program; ICGC, International Cancer Genome Consortium; ROC, receiver operating characteristic; AUC, area under the curve; PDAC, pancreatic ductal adenocarcinoma; DCA, decision curve analysis
Bisulfite Modification Of Genomic Dna And Methylation Specific Pcr Analysis, supplied by tiangen biotech co, used in various techniques. Bioz Stars score: 90/100, based on 1 PubMed citations. ZERO BIAS - scores, article reviews, protocol conditions and more
https://www.bioz.com/result/bisulfite modification of genomic dna and methylation-specific pcr analysis/product/tiangen biotech co
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bisulfite modification of genomic dna and methylation-specific pcr analysis - by Bioz Stars, 2026-03
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whole genome bisulfite sequencing for analysis of dna methylation  (Illumina Inc)
90
Illumina Inc whole genome bisulfite sequencing for analysis of dna methylation
Fig. 6 Construction and Evaluation of Prognostic RiskScoreEpi Model and Nomogram Integrating Clinical Information. A, B For TCGA Train Set (A) and ICGC Validation Set (B): Top panel: Distribution plot of RiskScoreEpi in high- and low-risk groups. Middle panel: Distribution plot of survival time and survival status in high- and low-risk groups; X-axis represents patients with increasing RiskScoreEpi, and Y-axis represents survival time. Bottom panel: Beta values of the six CpG sites in high- and low-risk groups. C ROC curves and AUC analyses for 1-, 3-, and 5-year overall survival prediction of the RiskScoreEpi model in TCGA dataset. D Sankey diagram illustrating similarities and differences in sample composition before and after grouping based on two different criteria: TCGA <t>DNAm</t> subgroups (left) and RiskScoreEpi model (right). E, F Univariate E and Multivariate F Cox regression analysis of RiskScoreEpi and clinical information in TCGA dataset. G Heatmap of six CpG sites’ <t>methylation</t> levels, corresponding RiskScoreEpi, survival time, survival status, and risk groups of the 8 PDAC patients we collected. Color bar = β-value. H Nomogram for predicting 1-, 2-, and 3-year overall survival of PDAC patients based on RiskScoreEpi and prognostic factors. I Calibration curves of the nomogram at 1, 3, and 5 years. J DCA curves of the nomogram, RiskScoreEpi, and other prognostic factors. TCGA, The Cancer Genome Atlas Program; ICGC, International Cancer Genome Consortium; ROC, receiver operating characteristic; AUC, area under the curve; PDAC, pancreatic ductal adenocarcinoma; DCA, decision curve analysis
Whole Genome Bisulfite Sequencing For Analysis Of Dna Methylation, supplied by Illumina Inc, used in various techniques. Bioz Stars score: 90/100, based on 1 PubMed citations. ZERO BIAS - scores, article reviews, protocol conditions and more
https://www.bioz.com/result/whole genome bisulfite sequencing for analysis of dna methylation/product/Illumina Inc
Average 90 stars, based on 1 article reviews
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dna methylation analysis bisulfite conversion  (Zymo Research)
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Zymo Research dna methylation analysis bisulfite conversion
Fig. 6 Construction and Evaluation of Prognostic RiskScoreEpi Model and Nomogram Integrating Clinical Information. A, B For TCGA Train Set (A) and ICGC Validation Set (B): Top panel: Distribution plot of RiskScoreEpi in high- and low-risk groups. Middle panel: Distribution plot of survival time and survival status in high- and low-risk groups; X-axis represents patients with increasing RiskScoreEpi, and Y-axis represents survival time. Bottom panel: Beta values of the six CpG sites in high- and low-risk groups. C ROC curves and AUC analyses for 1-, 3-, and 5-year overall survival prediction of the RiskScoreEpi model in TCGA dataset. D Sankey diagram illustrating similarities and differences in sample composition before and after grouping based on two different criteria: TCGA <t>DNAm</t> subgroups (left) and RiskScoreEpi model (right). E, F Univariate E and Multivariate F Cox regression analysis of RiskScoreEpi and clinical information in TCGA dataset. G Heatmap of six CpG sites’ <t>methylation</t> levels, corresponding RiskScoreEpi, survival time, survival status, and risk groups of the 8 PDAC patients we collected. Color bar = β-value. H Nomogram for predicting 1-, 2-, and 3-year overall survival of PDAC patients based on RiskScoreEpi and prognostic factors. I Calibration curves of the nomogram at 1, 3, and 5 years. J DCA curves of the nomogram, RiskScoreEpi, and other prognostic factors. TCGA, The Cancer Genome Atlas Program; ICGC, International Cancer Genome Consortium; ROC, receiver operating characteristic; AUC, area under the curve; PDAC, pancreatic ductal adenocarcinoma; DCA, decision curve analysis
Dna Methylation Analysis Bisulfite Conversion, supplied by Zymo Research, used in various techniques. Bioz Stars score: 95/100, based on 1 PubMed citations. ZERO BIAS - scores, article reviews, protocol conditions and more
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dna bisulfite-pyrosequencing methylation analysis  (Pyrosequencing Inc)
90
Pyrosequencing Inc dna bisulfite-pyrosequencing methylation analysis
Fig. 6 Construction and Evaluation of Prognostic RiskScoreEpi Model and Nomogram Integrating Clinical Information. A, B For TCGA Train Set (A) and ICGC Validation Set (B): Top panel: Distribution plot of RiskScoreEpi in high- and low-risk groups. Middle panel: Distribution plot of survival time and survival status in high- and low-risk groups; X-axis represents patients with increasing RiskScoreEpi, and Y-axis represents survival time. Bottom panel: Beta values of the six CpG sites in high- and low-risk groups. C ROC curves and AUC analyses for 1-, 3-, and 5-year overall survival prediction of the RiskScoreEpi model in TCGA dataset. D Sankey diagram illustrating similarities and differences in sample composition before and after grouping based on two different criteria: TCGA <t>DNAm</t> subgroups (left) and RiskScoreEpi model (right). E, F Univariate E and Multivariate F Cox regression analysis of RiskScoreEpi and clinical information in TCGA dataset. G Heatmap of six CpG sites’ <t>methylation</t> levels, corresponding RiskScoreEpi, survival time, survival status, and risk groups of the 8 PDAC patients we collected. Color bar = β-value. H Nomogram for predicting 1-, 2-, and 3-year overall survival of PDAC patients based on RiskScoreEpi and prognostic factors. I Calibration curves of the nomogram at 1, 3, and 5 years. J DCA curves of the nomogram, RiskScoreEpi, and other prognostic factors. TCGA, The Cancer Genome Atlas Program; ICGC, International Cancer Genome Consortium; ROC, receiver operating characteristic; AUC, area under the curve; PDAC, pancreatic ductal adenocarcinoma; DCA, decision curve analysis
Dna Bisulfite Pyrosequencing Methylation Analysis, supplied by Pyrosequencing Inc, used in various techniques. Bioz Stars score: 90/100, based on 1 PubMed citations. ZERO BIAS - scores, article reviews, protocol conditions and more
https://www.bioz.com/result/dna bisulfite-pyrosequencing methylation analysis/product/Pyrosequencing Inc
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dna bisulfite-pyrosequencing methylation analysis - by Bioz Stars, 2026-03
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dna methylation analysis bisulfite/pyrosequencing  (Pyrosequencing Inc)
90
Pyrosequencing Inc dna methylation analysis bisulfite/pyrosequencing
Example of how some gene regions were chosen for examination in this study on the basis of available RRBS <t>DNA</t> <t>methylation</t> profiles for breast cancer cell lines and normal cell cultures and tissues visualized in the UCSC Genome Browser . a The EN1 gene structure with exons as heavy horizontal bars; b , the aligned CpG islands in the illustrated region.; c , DNA methylation (ENCODE/RRBS/HudsonAlpha) profiles for the indicated cell cultures and normal tissues using an 11-color, semi-continuous scale (see color key) to indicate the average DNA methylation levels at each monitored CpG site; d , aligned transcription results indicating that the non-transformed breast cancer cell line is not transcribing this gene irrespective of its lack of DNA methylation. Paradoxically, normal myoblasts are transcribing it despite some upstream DNA methylation. All data are from ENCODE
Dna Methylation Analysis Bisulfite/Pyrosequencing, supplied by Pyrosequencing Inc, used in various techniques. Bioz Stars score: 90/100, based on 1 PubMed citations. ZERO BIAS - scores, article reviews, protocol conditions and more
https://www.bioz.com/result/dna methylation analysis bisulfite/pyrosequencing/product/Pyrosequencing Inc
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dna methylation analysis bisulfite/pyrosequencing - by Bioz Stars, 2026-03
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genomic dna isolation and genome-wide methylation analysis by enhanced reduced representation bisulfite sequencing  (Qiagen)
90
Qiagen genomic dna isolation and genome-wide methylation analysis by enhanced reduced representation bisulfite sequencing
Example of how some gene regions were chosen for examination in this study on the basis of available RRBS <t>DNA</t> <t>methylation</t> profiles for breast cancer cell lines and normal cell cultures and tissues visualized in the UCSC Genome Browser . a The EN1 gene structure with exons as heavy horizontal bars; b , the aligned CpG islands in the illustrated region.; c , DNA methylation (ENCODE/RRBS/HudsonAlpha) profiles for the indicated cell cultures and normal tissues using an 11-color, semi-continuous scale (see color key) to indicate the average DNA methylation levels at each monitored CpG site; d , aligned transcription results indicating that the non-transformed breast cancer cell line is not transcribing this gene irrespective of its lack of DNA methylation. Paradoxically, normal myoblasts are transcribing it despite some upstream DNA methylation. All data are from ENCODE
Genomic Dna Isolation And Genome Wide Methylation Analysis By Enhanced Reduced Representation Bisulfite Sequencing, supplied by Qiagen, used in various techniques. Bioz Stars score: 90/100, based on 1 PubMed citations. ZERO BIAS - scores, article reviews, protocol conditions and more
https://www.bioz.com/result/genomic dna isolation and genome-wide methylation analysis by enhanced reduced representation bisulfite sequencing/product/Qiagen
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Image Search Results


Fig. 6 Construction and Evaluation of Prognostic RiskScoreEpi Model and Nomogram Integrating Clinical Information. A, B For TCGA Train Set (A) and ICGC Validation Set (B): Top panel: Distribution plot of RiskScoreEpi in high- and low-risk groups. Middle panel: Distribution plot of survival time and survival status in high- and low-risk groups; X-axis represents patients with increasing RiskScoreEpi, and Y-axis represents survival time. Bottom panel: Beta values of the six CpG sites in high- and low-risk groups. C ROC curves and AUC analyses for 1-, 3-, and 5-year overall survival prediction of the RiskScoreEpi model in TCGA dataset. D Sankey diagram illustrating similarities and differences in sample composition before and after grouping based on two different criteria: TCGA DNAm subgroups (left) and RiskScoreEpi model (right). E, F Univariate E and Multivariate F Cox regression analysis of RiskScoreEpi and clinical information in TCGA dataset. G Heatmap of six CpG sites’ methylation levels, corresponding RiskScoreEpi, survival time, survival status, and risk groups of the 8 PDAC patients we collected. Color bar = β-value. H Nomogram for predicting 1-, 2-, and 3-year overall survival of PDAC patients based on RiskScoreEpi and prognostic factors. I Calibration curves of the nomogram at 1, 3, and 5 years. J DCA curves of the nomogram, RiskScoreEpi, and other prognostic factors. TCGA, The Cancer Genome Atlas Program; ICGC, International Cancer Genome Consortium; ROC, receiver operating characteristic; AUC, area under the curve; PDAC, pancreatic ductal adenocarcinoma; DCA, decision curve analysis

Journal: Clinical epigenetics

Article Title: Single-cell transcriptomics reveal the prognostic roles of epithelial and T cells and DNA methylation-based prognostic models in pancreatic cancer.

doi: 10.1186/s13148-024-01800-0

Figure Lengend Snippet: Fig. 6 Construction and Evaluation of Prognostic RiskScoreEpi Model and Nomogram Integrating Clinical Information. A, B For TCGA Train Set (A) and ICGC Validation Set (B): Top panel: Distribution plot of RiskScoreEpi in high- and low-risk groups. Middle panel: Distribution plot of survival time and survival status in high- and low-risk groups; X-axis represents patients with increasing RiskScoreEpi, and Y-axis represents survival time. Bottom panel: Beta values of the six CpG sites in high- and low-risk groups. C ROC curves and AUC analyses for 1-, 3-, and 5-year overall survival prediction of the RiskScoreEpi model in TCGA dataset. D Sankey diagram illustrating similarities and differences in sample composition before and after grouping based on two different criteria: TCGA DNAm subgroups (left) and RiskScoreEpi model (right). E, F Univariate E and Multivariate F Cox regression analysis of RiskScoreEpi and clinical information in TCGA dataset. G Heatmap of six CpG sites’ methylation levels, corresponding RiskScoreEpi, survival time, survival status, and risk groups of the 8 PDAC patients we collected. Color bar = β-value. H Nomogram for predicting 1-, 2-, and 3-year overall survival of PDAC patients based on RiskScoreEpi and prognostic factors. I Calibration curves of the nomogram at 1, 3, and 5 years. J DCA curves of the nomogram, RiskScoreEpi, and other prognostic factors. TCGA, The Cancer Genome Atlas Program; ICGC, International Cancer Genome Consortium; ROC, receiver operating characteristic; AUC, area under the curve; PDAC, pancreatic ductal adenocarcinoma; DCA, decision curve analysis

Article Snippet: DNA methylation analysis was performed on ≥ 0.5 μg of bisulfite-converted DNA using the EZ methylation Kit (Zymo Research), followed by amplification, and hybridization to Infinium Human MethylationEPIC BeadChip (850 K, Illumina).

Techniques: Biomarker Discovery, Methylation

Example of how some gene regions were chosen for examination in this study on the basis of available RRBS DNA methylation profiles for breast cancer cell lines and normal cell cultures and tissues visualized in the UCSC Genome Browser . a The EN1 gene structure with exons as heavy horizontal bars; b , the aligned CpG islands in the illustrated region.; c , DNA methylation (ENCODE/RRBS/HudsonAlpha) profiles for the indicated cell cultures and normal tissues using an 11-color, semi-continuous scale (see color key) to indicate the average DNA methylation levels at each monitored CpG site; d , aligned transcription results indicating that the non-transformed breast cancer cell line is not transcribing this gene irrespective of its lack of DNA methylation. Paradoxically, normal myoblasts are transcribing it despite some upstream DNA methylation. All data are from ENCODE

Journal: BMC Cancer

Article Title: Exploring DNA methylation changes in promoter, intragenic, and intergenic regions as early and late events in breast cancer formation

doi: 10.1186/s12885-015-1777-9

Figure Lengend Snippet: Example of how some gene regions were chosen for examination in this study on the basis of available RRBS DNA methylation profiles for breast cancer cell lines and normal cell cultures and tissues visualized in the UCSC Genome Browser . a The EN1 gene structure with exons as heavy horizontal bars; b , the aligned CpG islands in the illustrated region.; c , DNA methylation (ENCODE/RRBS/HudsonAlpha) profiles for the indicated cell cultures and normal tissues using an 11-color, semi-continuous scale (see color key) to indicate the average DNA methylation levels at each monitored CpG site; d , aligned transcription results indicating that the non-transformed breast cancer cell line is not transcribing this gene irrespective of its lack of DNA methylation. Paradoxically, normal myoblasts are transcribing it despite some upstream DNA methylation. All data are from ENCODE

Article Snippet: Using a candidate gene approach on a large, ethnically diverse set of subjects, we compared not only invasive breast cancer and adjacent histologically normal tissue (as in the TCGA Illumina HumanMethylation450 database [ ]), but also control samples of reductive mammoplasty tissue from non-cancer patients using a quantitative, gold-standard method for DNA methylation analysis (bisulfite/pyrosequencing) amenable to archival FFPE samples.

Techniques: DNA Methylation Assay, Transformation Assay

Mean percent methylation by gene and tissue type from the Breast Cancer Care in Chicago study

Journal: BMC Cancer

Article Title: Exploring DNA methylation changes in promoter, intragenic, and intergenic regions as early and late events in breast cancer formation

doi: 10.1186/s12885-015-1777-9

Figure Lengend Snippet: Mean percent methylation by gene and tissue type from the Breast Cancer Care in Chicago study

Article Snippet: Using a candidate gene approach on a large, ethnically diverse set of subjects, we compared not only invasive breast cancer and adjacent histologically normal tissue (as in the TCGA Illumina HumanMethylation450 database [ ]), but also control samples of reductive mammoplasty tissue from non-cancer patients using a quantitative, gold-standard method for DNA methylation analysis (bisulfite/pyrosequencing) amenable to archival FFPE samples.

Techniques: Methylation, Control

Mean percent methylation and 95 % error bars by gene and tissue type for the DNA regions listed in Table . a DNA methylation analysis of samples from the Breast Cancer Care in Chicago study (2005-2008) as determined by our bisulfite pyrosequencing. Control samples (reduction mammoplasty) from unaffected women are represented by green bars, cancer-adjacent, histologically normal samples by blue bars and cancer samples by red bars. b Bioinformatic analysis of DNA methylation of breast cancer samples and paired non-cancerous adjacent samples from The Cancer Genome Atlas (TCGA). Paired non-cancerous adjacent samples are represented by blue bars and cancer samples by red bars. In both panels, promoter sequences are displayed first, followed by upstream sequences, then introns and lastly, DNA repeats

Journal: BMC Cancer

Article Title: Exploring DNA methylation changes in promoter, intragenic, and intergenic regions as early and late events in breast cancer formation

doi: 10.1186/s12885-015-1777-9

Figure Lengend Snippet: Mean percent methylation and 95 % error bars by gene and tissue type for the DNA regions listed in Table . a DNA methylation analysis of samples from the Breast Cancer Care in Chicago study (2005-2008) as determined by our bisulfite pyrosequencing. Control samples (reduction mammoplasty) from unaffected women are represented by green bars, cancer-adjacent, histologically normal samples by blue bars and cancer samples by red bars. b Bioinformatic analysis of DNA methylation of breast cancer samples and paired non-cancerous adjacent samples from The Cancer Genome Atlas (TCGA). Paired non-cancerous adjacent samples are represented by blue bars and cancer samples by red bars. In both panels, promoter sequences are displayed first, followed by upstream sequences, then introns and lastly, DNA repeats

Article Snippet: Using a candidate gene approach on a large, ethnically diverse set of subjects, we compared not only invasive breast cancer and adjacent histologically normal tissue (as in the TCGA Illumina HumanMethylation450 database [ ]), but also control samples of reductive mammoplasty tissue from non-cancer patients using a quantitative, gold-standard method for DNA methylation analysis (bisulfite/pyrosequencing) amenable to archival FFPE samples.

Techniques: Methylation, DNA Methylation Assay, Control

Adjusted differences in mean % methylation comparing adjacent (referent) to cancer tissue, overall and stratified by ER/PR status

Journal: BMC Cancer

Article Title: Exploring DNA methylation changes in promoter, intragenic, and intergenic regions as early and late events in breast cancer formation

doi: 10.1186/s12885-015-1777-9

Figure Lengend Snippet: Adjusted differences in mean % methylation comparing adjacent (referent) to cancer tissue, overall and stratified by ER/PR status

Article Snippet: Using a candidate gene approach on a large, ethnically diverse set of subjects, we compared not only invasive breast cancer and adjacent histologically normal tissue (as in the TCGA Illumina HumanMethylation450 database [ ]), but also control samples of reductive mammoplasty tissue from non-cancer patients using a quantitative, gold-standard method for DNA methylation analysis (bisulfite/pyrosequencing) amenable to archival FFPE samples.

Techniques: Methylation