Journal: Theranostics

Article Title: Genome-wide discovery and validation of diagnostic DNA methylation-based biomarkers for hepatocellular cancer detection in circulating cell free DNA

doi: 10.7150/thno.35573

Figure Lengend Snippet: Approach to identifying DNA methylation-based biomarkers for detection of early HCC in liver cirrhosis patients. We utilized two strategies to identify DNA methylation-based biomarkers. First, starting with primary tissue to discover markers and then examining their performance in cfDNA, and the converse, starting with cfDNA to discover markers then validating these markers in two independent primary tissue datasets. We then validated a 5-marker panel in 30 independent cfDNA samples by bisulfite pyrosequencing. A total of 586 patient-derived Infinium 450k profiles are assessed for this study.

Article Snippet: Demographic and clinical information on the cfDNA- and tissue-derived DNA samples used for Infinium 450k array-based DNA methylation analysis are summarized in Figure and Table .

Techniques: DNA Methylation Assay, Marker, Derivative Assay

Journal: Theranostics

Article Title: Genome-wide discovery and validation of diagnostic DNA methylation-based biomarkers for hepatocellular cancer detection in circulating cell free DNA

doi: 10.7150/thno.35573

Figure Lengend Snippet: Characterization of primary tissue- and cfDNA-derived DNA methylation landscapes. A ) Principal component analysis of differentially methylated CpGs in cfDNA (top, n=44; 22 cirrhosis in pink, 22 HCC in blue) and primary tissues (bottom, n=191; 82 cirrhosis in pink, 109 HCC in blue) using all CpGs on the array after QC filtering (including removal of X, Y, and SNP associated probes). B ) Overall methylation level bar charts (as beta values) for individual cirrhotic (green), average of all cirrhotic (dark green), individual HCC (red), and average of all HCC (dark red) patients derived from cfDNA (top) or primary liver tissues (bottom). C ) Volcano plots of 5mC changes plotted against -log P values between cirrhotic only and cirrhotic with concurrent HCC patients. Stepwise coloring of changes is based on delta beta values (0.05 increments) with black being below 0.05, dark red between 0.05-0.1, red between 0.1-0.15, orange between 0.15-0.20, and yellow greater than 0.20 in cfDNA (top) and primary tissue (bottom). D ) Bar charts representing the relative distribution of DNA methylation changes (Δβ > 0.1 tumor vs non-tumor) across the indicated features based on 450k data derived from cfDNA (top) and from primary tissue (bottom). Blue and orange bars represent hypermethylation and hypomethylation events, respectively.

Article Snippet: Demographic and clinical information on the cfDNA- and tissue-derived DNA samples used for Infinium 450k array-based DNA methylation analysis are summarized in Figure and Table .

Techniques: Derivative Assay, DNA Methylation Assay, Methylation

Journal: Theranostics

Article Title: Genome-wide discovery and validation of diagnostic DNA methylation-based biomarkers for hepatocellular cancer detection in circulating cell free DNA

doi: 10.7150/thno.35573

Figure Lengend Snippet: Discovery of DNA methylation biomarkers in primary liver tissues. A) Binned scatterplot of de novo DNA methylation events that significantly differ between cirrhotic only controls and HCC primary tissues (Δβ > 0.15, P < 0.05). A color bar representing density of CpGs is shown at the right. B) Area under the receiver operating characteristic curves for CpGs identified in (A). C) Heatmap of the 2,000 most differentially methylated CpGs between cirrhosis (green) and HCC (red) tissue. A color bar is shown with low methylation in red and high methylation in yellow. Red/green bar indicates tissue disease state. D) Binned scatterplot of AUROCs for CpGs identified in (A) in primary tissue set 1 analyzed using methylation values at the same CpG sites measured in cfDNA. E) Lasso regression analysis of CpGs identified in (A) presented as a dumbbell chart demarcated by the lower and upper 95% confidence interval of the coefficient (blue bar), with the original coefficient value shown as a black dot for 24 CpGs that reached the coefficient threshold of lower 95% CI > 0. F) A scatterplot of AUROCs from the 24 CpGs selected in (E) in cfDNA and primary tissue. The y-axis is the AUROC in cfDNA, the x-axis is the AUROC in primary tissue set 1.

Article Snippet: Demographic and clinical information on the cfDNA- and tissue-derived DNA samples used for Infinium 450k array-based DNA methylation analysis are summarized in Figure and Table .

Techniques: DNA Methylation Assay, Methylation

Journal: Theranostics

Article Title: Genome-wide discovery and validation of diagnostic DNA methylation-based biomarkers for hepatocellular cancer detection in circulating cell free DNA

doi: 10.7150/thno.35573

Figure Lengend Snippet: Discovery and validation of DNA methylation biomarkers derived from cfDNA. A) Schematic representation of the analytic process used to identify biomarkers directly from genome-wide cfDNA methylation data. B ) Heatmap of 443 CpGs showing differential methylation between cirrhotic only control and HCC patient-derived cfDNA (Δβ > 0.1, P < 0.05). A color bar is shown to indicate 5mC level. C ) Resultant 95% confidence intervals for positively-weighted coefficients identified by Lasso regression of CpGs from part (B). D ) Boxplot of the additive sum of coefficients multiplied by β values for the 13 CpGs identified in (C) in cirrhotic- and HCC-derived cfDNA samples. E ) List of the high performing CpGs identified from cfDNA along with their associated gene(s), genic features, and link to liver-specific enhancers. F ) Receiver operating characteristic curves for a 5 CpG panel in cfDNA (blue), and in two independent primary tissue sets (orange, set 1; black, set 2). CpGs used: cg04645914, cg06215569, cg23663760, cg13781744, and cg07610777.

Article Snippet: Demographic and clinical information on the cfDNA- and tissue-derived DNA samples used for Infinium 450k array-based DNA methylation analysis are summarized in Figure and Table .

Techniques: Biomarker Discovery, DNA Methylation Assay, Derivative Assay, Genome Wide, Methylation, Control

Journal: Theranostics

Article Title: Genome-wide discovery and validation of diagnostic DNA methylation-based biomarkers for hepatocellular cancer detection in circulating cell free DNA

doi: 10.7150/thno.35573

Figure Lengend Snippet: DNA hypomethylation based markers that distinguish between non-tumor and tumor disease states. A) Schematic representation of the analytic process used to identify hypomethylation biomarkers directly from genome-wide cfDNA 5mC datasets. B ) Heatmap of 63 CpGs showing differential methylation between cirrhotic only control and HCC patient-derived cfDNA (Δβ <- 0.15, P < 0.05). A color bar is shown to indicate 5mC level. C ) Resultant 95% confidence intervals for positively-weighted coefficients identified by Lasso regression of CpGs from part (B). D ) Boxplot of the additive sum of coefficients multiplied by β values for the 10 CpGs identified in (C) in cirrhotic- and HCC-derived cfDNA samples. E ) List of the high performing CpGs identified from cfDNA along with their associated gene(s), genic features, and link to liver-specific enhancers. F ) Receiver operating characteristic curves for a 4 CpG panel in cfDNA (blue), and in two independent primary tissue sets (orange, set 1; black, set 2). CpGs used: cg25026480, cg14774440, cg18054281, cg00638020.

Article Snippet: Demographic and clinical information on the cfDNA- and tissue-derived DNA samples used for Infinium 450k array-based DNA methylation analysis are summarized in Figure and Table .

Techniques: Genome Wide, Methylation, Control, Derivative Assay

Journal: Journal of immunology (Baltimore, Md. : 1950)

Article Title: Activation of murine CD4+ and CD8+ T lymphocytes leads to dramatic remodeling of N-linked glycans.

doi: 10.4049/jimmunol.177.4.2431

Figure Lengend Snippet: FIGURE 1. Purification of B cells and T cells from mixed splenocytes before and after activation. CD8 T cells, CD4 T cells, and B cells were purified from mixed splenocytes before or after activation using the MACS system with anti-CD8-, anti-CD4-, or anti-CD19-coated magnetic beads, respectively. Phenotypic analysis of purified fresh and activated cell populations was performed by flow cytometry and showed 90% purity of all cell preparations, as indicated. Purified cells were used either for RNA preparation for microarray analysis, or were processed to extract glycans for MALDI profiling and methylation analysis.

Article Snippet: 6 The online version of this article contains supplemental material. at B row n U niversity on M ay 30, 2014 http://w w w .jim m unol.org/ D ow nloaded from Microarray analysis of the expression of cytokine and glycan transferase genes For gene expression analysis, mRNAs were extracted from purified cell populations of fresh and activated lymphocytes and subjected to analysis on a custom Affymetrix-based DNA microarray containing murine and human glycosyltransferase, sulfotransferase, and cytokine genes, made available by the Consortium for Functional Glycomics.

Techniques: Activation Assay, Magnetic Beads, Cytometry, Microarray, Methylation

Journal: Cold Spring Harbor Perspectives in Biology

Article Title: Chromatin Remodeling in Mammary Gland Differentiation and Breast Tumorigenesis

doi: 10.1101/cshperspect.a004515

Figure Lengend Snippet: Summary of candidate gene and genome-wide techniques for DNA methylation analysis a

Article Snippet: Microarray-based approaches , DMH (differential methylation hybridization): MTA (methylation tissue array); MSO (methylation-specific oligonucleotide); HELP ( Hpa II tiny fragment enrichment by ligation-mediated PCR); AIMS (amplification of intermethylated sites); MSNP (methylation single nucleotide polymorphism chip-based method); MMASS (microarray-based methylation assessment of single sample); PMAD (promoter-associated methylated DNA amplification); MSDK (methylation-specific digital karyotyping) MIAMI (microarray-based integrated analysis of methylation); MCAM (methylated CpG island amplification and microarray); MeDIP-chip (methylated DNA immunoprecipitation on microarray); MIRA-chip (methylated-CpG island recovery assay on microarray); Mcr BC ; MethylScope ; Pharmacologic unmasking analysis ; and Infinium BeadArray.

Techniques: Genome Wide, DNA Methylation Assay, Cloning, Methylation Sequencing, Methylation, Combined Bisulfite Restriction Analysis Assay, Microarray, Hybridization, Ligation, Amplification, DNA Amplification, Methylated DNA Immunoprecipitation, Immunoprecipitation, Next-Generation Sequencing, Methylated DNA Immunoprecipitation Sequencing

Journal: Epigenetics & Chromatin

Article Title: Losing DNA methylation at repetitive elements and breaking bad

doi: 10.1186/s13072-021-00400-z

Figure Lengend Snippet: Potential contributions of hypomethylated REs to carcinogenesis. As opposed to normal cells, cancer cells are characterized by cytosine methylation loss at repetitive DNA. This alteration can affect cell behaviour and contribute to cancer initiation/progression in several ways. The hypomethylated REs can be regulators of oncogenic lncRNAs and, thus, induce their abnormal transcription. TEs or satellite DNA, once hypomethylated, can be also transcribed potentially affecting several processes and leading to genomic and chromosome stability. Furthermore, hypomethylation of REs could affect chromosome structure making it more fragile and prone to breaks, recombination and even to the weakening of centromere function. By changing the compaction degree of the chromatin, hypomethylation of REs also affects nucleus size and organization which, we believe, could dangerously compromise cells, though this research field has not been well explored

Article Snippet: However, they have been clustered into two groups, through the analysis of the Infinium methylation array of 15 patients, based on the different methylation status of other genomic loci [ ].

Techniques: Methylation

Journal: Frontiers in Genetics

Article Title: Simultaneous Methylation-Level Assessment of Hundreds of CpG Sites by Targeted Bisulfite PCR Sequencing (TBPseq)

doi: 10.3389/fgene.2017.00097

Figure Lengend Snippet: Validation of the LIFR promoter methylation for cancer specificity and its relationship with the expression of associated genes. (A) DNA methylation levels of target CpGs in public cancer methylome data (Infinium 450K BeadChip array) of four cancer types: colorectal ( n = 313 for cancer samples and n = 38 for normal samples), liver (377 and 50), lung (843 and 74), and stomach (395 and 2) cancers. Infinium CpG identification numbers (IDs) together with the associated gene names are shown; the Infinium IDs cg03723506 and cg11291081 indicate chr5:38557143 and chr3:37033894, respectively, in the Figure . Statistical significance was calculated using Wilcoxon rank sum test. T: tumor samples, N: normal samples. (B) Schematic drawing of COBRA region at the LIFR promoter. Blue arrows, primers. CGI, CpG island (green line). (C) COBRA analysis. Genomic DNA was extracted from each colon cancer cell lines along with a normal control colon cell line (CCD-18co) and subjected to COBRA using the Taq I enzyme to examine the methylation state at the LIFR gene promoter. Arrowhead and arrow indicate the positions of intact and Taq I-digested DNA fragments, respectively. The fraction (% meth) of methylated DNA was measured by band intensity analysis and noted under each cell line. (D) RT-PCR. The same cancer cell lines used in COBRA (C) were subjected to RT-PCR to measure the transcript levels of the LIFR and LIFR-AS genes.

Article Snippet: The panel composition is highly flexible and can accommodate a variety of experimental designs, a big advantage over other methylation analysis platforms such as the array-based Infinium BeadChip.

Techniques: Biomarker Discovery, Methylation, Expressing, DNA Methylation Assay, Combined Bisulfite Restriction Analysis Assay, Control, Reverse Transcription Polymerase Chain Reaction

Journal: Cold Spring Harbor Perspectives in Biology

Article Title: Chromatin Remodeling in Mammary Gland Differentiation and Breast Tumorigenesis

doi: 10.1101/cshperspect.a004515

Figure Lengend Snippet: Summary of candidate gene and genome-wide techniques for DNA methylation analysis a

Article Snippet: Microarray-based approaches , DMH (differential methylation hybridization): MTA (methylation tissue array); MSO (methylation-specific oligonucleotide); HELP ( Hpa II tiny fragment enrichment by ligation-mediated PCR); AIMS (amplification of intermethylated sites); MSNP (methylation single nucleotide polymorphism chip-based method); MMASS (microarray-based methylation assessment of single sample); PMAD (promoter-associated methylated DNA amplification); MSDK (methylation-specific digital karyotyping) MIAMI (microarray-based integrated analysis of methylation); MCAM (methylated CpG island amplification and microarray); MeDIP-chip (methylated DNA immunoprecipitation on microarray); MIRA-chip (methylated-CpG island recovery assay on microarray); Mcr BC ; MethylScope ; Pharmacologic unmasking analysis ; and Infinium BeadArray.

Techniques: Genome Wide, DNA Methylation Assay, Cloning, Methylation Sequencing, Methylation, Combined Bisulfite Restriction Analysis Assay, Microarray, Hybridization, Ligation, Amplification, DNA Amplification, Methylated DNA Immunoprecipitation, Immunoprecipitation, Next-Generation Sequencing, Methylated DNA Immunoprecipitation Sequencing

Journal: Cold Spring Harbor Perspectives in Biology

Article Title: Chromatin Remodeling in Mammary Gland Differentiation and Breast Tumorigenesis

doi: 10.1101/cshperspect.a004515

Figure Lengend Snippet: Summary of candidate gene and genome-wide techniques for DNA methylation analysis a

Article Snippet: Microarray-based approaches , DMH (differential methylation hybridization): MTA (methylation tissue array); MSO (methylation-specific oligonucleotide); HELP ( Hpa II tiny fragment enrichment by ligation-mediated PCR); AIMS (amplification of intermethylated sites); MSNP (methylation single nucleotide polymorphism chip-based method); MMASS (microarray-based methylation assessment of single sample); PMAD (promoter-associated methylated DNA amplification); MSDK (methylation-specific digital karyotyping) MIAMI (microarray-based integrated analysis of methylation); MCAM (methylated CpG island amplification and microarray); MeDIP-chip (methylated DNA immunoprecipitation on microarray); MIRA-chip (methylated-CpG island recovery assay on microarray); Mcr BC ; MethylScope ; Pharmacologic unmasking analysis ; and Infinium BeadArray.

Techniques: Genome Wide, DNA Methylation Assay, Cloning, Methylation Sequencing, Methylation, Combined Bisulfite Restriction Analysis Assay, Microarray, Hybridization, Ligation, Amplification, DNA Amplification, Methylated DNA Immunoprecipitation, Immunoprecipitation, Next-Generation Sequencing, Methylated DNA Immunoprecipitation Sequencing