Volume 17, Issue 2, Pages (October 2016)

Slides:



Advertisements
Similar presentations
DNA Methylation Regulates Gene Expression in Intracranial Aneurysms
Advertisements

Figure 1. Annotation and characterization of genomic target of p63 in mouse keratinocytes (MK) based on ChIP-Seq. (A) Scatterplot representing high degree.
Volume 8, Issue 4, Pages (April 2017)
Volume 20, Issue 12, Pages (September 2017)
Volume 41, Issue 5, Pages (November 2014)
Dynamic epigenetic enhancer signatures reveal key transcription factors associated with monocytic differentiation states by Thu-Hang Pham, Christopher.
Laila C. Schenkel, Charles Schwartz, Cindy Skinner, David I
Volume 20, Issue 13, Pages (September 2017)
Volume 3, Issue 4, Pages (April 2013)
High-Resolution Profiling of Histone Methylations in the Human Genome
Higher Nevus Count Exhibits a Distinct DNA Methylation Signature in Healthy Human Skin: Implications for Melanoma  Leonie Roos, Johanna K. Sandling, Christopher.
Roger B. Deal, Steven Henikoff  Developmental Cell 
Volume 44, Issue 3, Pages (November 2011)
Shiran Bar, Maya Schachter, Talia Eldar-Geva, Nissim Benvenisty 
Volume 29, Issue 1, Pages (April 2014)
Volume 9, Issue 3, Pages (September 2017)
Volume 23, Issue 11, Pages (June 2018)
Revealing Global Regulatory Perturbations across Human Cancers
Genome-wide DNA methylation profile implicates potential cartilage regeneration at the late stage of knee osteoarthritis  Y. Zhang, N. Fukui, M. Yahata,
Ying-Ying Yu, Ph. D. , Cui-Xiang Sun, Ph. D. , Yin-Kun Liu, Ph. D
Volume 44, Issue 1, Pages (October 2011)
Adrien Le Thomas, Georgi K. Marinov, Alexei A. Aravin  Cell Reports 
Volume 20, Issue 6, Pages (August 2017)
Volume 17, Issue 8, Pages (November 2016)
Volume 6, Issue 1, Pages (January 2016)
Mapping Global Histone Acetylation Patterns to Gene Expression
Volume 22, Issue 3, Pages (January 2018)
Volume 49, Issue 1, Pages (January 2013)
Volume 2, Issue 2, Pages (February 2008)
Volume 8, Issue 4, Pages (April 2017)
High-Resolution Profiling of Histone Methylations in the Human Genome
Volume 10, Issue 6, Pages (June 2018)
Volume 23, Issue 1, Pages 9-22 (January 2013)
Volume 11, Issue 3, Pages (April 2015)
Differential DNA Methylation Analysis without a Reference Genome
Volume 2, Issue 1, Pages (January 2014)
Revealing Global Regulatory Perturbations across Human Cancers
Volume 22, Issue 3, Pages (January 2018)
Molecular Convergence of Neurodevelopmental Disorders
Wei Jiang, Yuting Liu, Rui Liu, Kun Zhang, Yi Zhang  Cell Reports 
Volume 44, Issue 3, Pages (November 2011)
Shiran Bar, Maya Schachter, Talia Eldar-Geva, Nissim Benvenisty 
Volume 72, Issue 2, Pages e5 (October 2018)
Volume 13, Issue 3, Pages (September 2013)
Evolution of Alu Elements toward Enhancers
Volume 39, Issue 6, Pages (September 2010)
Volume 14, Issue 6, Pages (June 2014)
Volume 1, Issue 1, Pages (June 2013)
ADAR Regulates RNA Editing, Transcript Stability, and Gene Expression
Volume 55, Issue 2, Pages (July 2014)
Volume 122, Issue 6, Pages (September 2005)
Volume 35, Issue 2, Pages (August 2011)
Polycomb Protein Ezh1 Promotes RNA Polymerase II Elongation
Volume 14, Issue 6, Pages (June 2014)
Volume 12, Issue 12, Pages (September 2015)
Volume 20, Issue 12, Pages (September 2017)
Volume 7, Issue 2, Pages (August 2010)
Volume 9, Issue 3, Pages (November 2014)
Volume 32, Issue 6, Pages (June 2010)
Volume 56, Issue 6, Pages (December 2014)
Short Telomeres in ESCs Lead to Unstable Differentiation
Volume 26, Issue 12, Pages e5 (March 2019)
Volume 17, Issue 3, Pages (September 2009)
Volume 17, Issue 3, Pages (October 2016)
Symmetrical Dose-Dependent DNA-Methylation Profiles in Children with Deletion or Duplication of 7q11.23  Emma Strong, Darci T. Butcher, Rajat Singhania,
Volume 2, Issue 3, Pages (March 2016)
Rahul Karnik, Alexander Meissner  Cell Stem Cell 
Volume 13, Issue 10, Pages (December 2015)
Genome-wide Functional Analysis Reveals Factors Needed at the Transition Steps of Induced Reprogramming  Chao-Shun Yang, Kung-Yen Chang, Tariq M. Rana 
Volume 14, Issue 6, Pages (February 2016)
Presentation transcript:

Volume 17, Issue 2, Pages 596-608 (October 2016) Insights into the Pathogenesis of Anaplastic Large-Cell Lymphoma through Genome- wide DNA Methylation Profiling  Melanie R. Hassler, Walter Pulverer, Ranjani Lakshminarasimhan, Elisa Redl, Julia Hacker, Gavin D. Garland, Olaf Merkel, Ana-Iris Schiefer, Ingrid Simonitsch-Klupp, Lukas Kenner, Daniel J. Weisenberger, Andreas Weinhaeusel, Suzanne D. Turner, Gerda Egger  Cell Reports  Volume 17, Issue 2, Pages 596-608 (October 2016) DOI: 10.1016/j.celrep.2016.09.018 Copyright © 2016 The Author(s) Terms and Conditions

Cell Reports 2016 17, 596-608DOI: (10.1016/j.celrep.2016.09.018) Copyright © 2016 The Author(s) Terms and Conditions

Figure 1 DNA Methylation of ALCL versus Normal CD3+ T Cells (A) Venn diagram showing significant MVPs (based on M values and adjusted p < 0.01) among indicated groups in comparisons of ALK+, ALK−, and normal CD3+. Numbers indicate unique MVPs of selected segments; numbers in parentheses indicate total number of MVPs of the three group comparisons: ALK+ versus CD3+, ALK− versus CD3+, and ALK+ versus ALK−. (B) Hierarchical clustering of the top 31,580 differentially methylated CpG sites detected between ALK+ and control T cells (color key indicates percentage of methylation, from red = 100% methylation to green = 0% methylation). Sample annotation: blue, tumor; yellow, normal CD3+; red, ALK+ ALCL; green, ALK− ALCL. (C) Hierarchical clustering of the top 5,453 MVPs detected in control T cells versus ALK− ALCL (color key and sample annotation as in B). (D) Number and distribution of MVPs between CD3+ T cells and ALK+ or ALK− ALCL found at specific genomic regions and regions around CpG islands. Hypomethylated MVPs are shown at the top; hypermethylated MVPs are at the bottom. Differentially methylated sites were obtained after filtering the data (filtering criteria: adjusted p value < 0.01 and β-value difference > |0.2|). See also Figures S1 and S2. Cell Reports 2016 17, 596-608DOI: (10.1016/j.celrep.2016.09.018) Copyright © 2016 The Author(s) Terms and Conditions

Figure 2 Comparison of Different Developmental Stages of Thymocytes with ALCL Tumor Cells (A) Left panel: principal-component analysis of thymic T cell subsets in comparison to ALK+ and ALK− tumor cells and peripheral CD3+ T cells (p < 9.4e−6, q value = 9.46e−4). Right panel: thymic developmental stages from ETPs (CD34+/CD1a−) to SP CD4+ or CD8+ cells. (B) Hierarchical clustering of the top 1% of all probes of thymic subsets, ALK+ and ALK− tumor cells, and peripheral CD3+ T cells (4,817 CpG sites) (p < 9.4e−6, q value = 9.46e−4). Data were normalized using Qlucore software, as described in the Supplemental Experimental Procedures. Global normalization was used to center the β values for each sample to a mean of 0 (variance = 1) to adjust for differences in signal intensities of the different Infinium BeadChips. Color key from green = −2 (0% methylation) to red = +2 (100% methylation). Cell Reports 2016 17, 596-608DOI: (10.1016/j.celrep.2016.09.018) Copyright © 2016 The Author(s) Terms and Conditions

Figure 3 Silencing of T-Cell-Specific TFs in ALCL (A) Serial stages of thymic T cell development are driven by specific TFs. DN, double negative. (B) Gene expression differences of indicated TFs between ALK+ and ALK− ALCL compared to CD3+ T cells. (C) DNA methylation levels of promoter regions of indicated genes as determined by quantitative methylation ms-qPCR in 28 ALK+ ALCL, 3 ALK− ALCL, 15 AITL, and 18 PTCL-NOS tumor samples, with 6 healthy CD3+ samples as controls. Samples were analyzed by one-way ANOVA (p < 0.05) followed by pairwise comparisons to the control group using unpaired t tests. Values are shown as mean ± SEM. See also Figure S3. Cell Reports 2016 17, 596-608DOI: (10.1016/j.celrep.2016.09.018) Copyright © 2016 The Author(s) Terms and Conditions

Figure 4 Genomic and Epigenomic Features of Differentially Methylated CpG Sites (A) Epiexplorer analysis using indicated genomic features of hypermethylated (red) and hypomethylated (green) CpG sites for ALK+ and ALK− ALCL compared to CD3+ T cells in relation to all CpG sites on the Illumina 450k array (black). (B) Epigenetic switching is detected at the HOXD cluster in ALK+ and ALK− ALCL at regions that show H3K27me3 and EZH2 occupancy by ChIP-seq in ESCs and in GM12878 lymphoblastoid cells. Top tracks (blue): differential methylation of ALK+/ALK− ALCL versus CD3+ T cells. Middle tracks: University of California Santa Cruz (UCSC) gene annotation track, where green boxes are CpG islands. Lower tracks: enrichment of EZH2 and H3K27me3 in lymphoblastoid cells (red) and ESCs (green). (C) ChIP interrogating repressive histone marks (H3K9me3, H3K27me3) and active histone marks (H3K4me3) at HOXA9 and HOXD3 gene promoters in ALK+ SU-DHL-1 cells. GAPDH is shown as control for an active region, SAT2 is control for a heterochromatic region, NCR is control for a negative control region, and PLAU is control positive control for H3K27me3 occupancy. H3global indicates a control ChIP for global H3 occupancy. Values are means ± SD. Each value is the mean of three replicates. See also Figure S4. Cell Reports 2016 17, 596-608DOI: (10.1016/j.celrep.2016.09.018) Copyright © 2016 The Author(s) Terms and Conditions

Figure 5 Characterization of DMRs (A) Identification of DMRs, calculated from mean β values of all CpGs annotated to a distinct genomic region, between ALK+ (left) and ALK− (right) versus CD3+ T cells (p value < 0.05; β-value difference ≥ 0.15). TSS includes CpGs within either 200 or 1,500 bp of the TSS. Hypermethylated DMRs are depicted in red; hypomethylated DMRs are in green. (B) GO term analysis using the DAVID web-based tool. Significant GO terms (adjusted p < 0.05) are highly similar in ALK+ and ALK− tumors. (C) Correlation of genes with differentially methylated promoters with gene expression profiles of ALK+ and ALK− ALCL and T cells. Blue, genes downregulated in ALCL versus T cells; red, genes upregulated in ALCL versus T cells. Hypermethylated TSS, genes showing higher methylation in both groups within their promoters; hypomethylated TSS, genes with lower methylation in their promoters in both groups. See also Tables S1, S2, and S3. Cell Reports 2016 17, 596-608DOI: (10.1016/j.celrep.2016.09.018) Copyright © 2016 The Author(s) Terms and Conditions

Figure 6 Canonical Pathways Are Affected by Differentially Methylated Genes (A) Multiple genes of the TCR pathway are hypermethylated in ALK+ and ALK− ALCL (red, significantly hypermethylated genes; green, significantly hypomethylated genes; adjusted p value < 0.05; β-value difference ≥ 0.15). The pathway was generated through the use of QIAGEN’s IPA. (B) DNA sequence motif identified by unbiased motif search in regions adjacent to hypomethylated CpGs in ALK+ and ALK− ALCL (top) compared to the AP1 consensus motif (bottom). (C) ChIP for JUNB occupancy at hypomethylated ALCL promoters with putative AP1 binding sites. PDGFRβ, positive control. ChIP was normalized to a negative control region in the 3′ end of the PDGFRβ gene containing no AP1 motif. Values are means ± SEM. Each value is the mean of three replicates. See also Figures S5–S8. Cell Reports 2016 17, 596-608DOI: (10.1016/j.celrep.2016.09.018) Copyright © 2016 The Author(s) Terms and Conditions