Loss of imprinting at the 14q32 domain is associated with microRNA overexpression in acute promyelocytic leukemia by Floriana Manodoro, Jacek Marzec, Tracy.

Slides:



Advertisements
Similar presentations
K. Brennan, J.L. Koenig, A.J. Gentles, J.B. Sunwoo, O. Gevaert
Advertisements

DNA Methylation Regulates Gene Expression in Intracranial Aneurysms
The Cancer Genome Atlas Research Network
Arginine deprivation using pegylated arginine deiminase has activity against primary acute myeloid leukemia cells in vivo by Farideh Miraki-Moud, Essam.
Dynamic epigenetic enhancer signatures reveal key transcription factors associated with monocytic differentiation states by Thu-Hang Pham, Christopher.
Hypomethylation Status of CpG Sites at the Promoter Region and Overexpression of the Human MDR1 Gene in Acute Myeloid Leukemias by Masaharu Nakayama, Morimasa.
Tracking CD40 signaling during germinal center development
Two splice-factor mutant leukemia subgroups uncovered at the boundaries of MDS and AML using combined gene expression and DNA-methylation profiling by.
Molecular allelokaryotyping of pediatric acute lymphoblastic leukemias by high-resolution single nucleotide polymorphism oligonucleotide genomic microarray.
A leukemic stem cell with intrinsic drug efflux capacity in acute myeloid leukemia by Gerald G. Wulf, Rui-Yu Wang, Ingrid Kuehnle, Douglas Weidner, Frank.
Gene expression profiling of pediatric acute myelogenous leukemia
Lipopolysaccharide binding protein promoter variants influence the risk for Gram-negative bacteremia and mortality after allogeneic hematopoietic cell.
by Thomas A. Paul, Juraj Bies, Donald Small, and Linda Wolff
Genome-wide epigenetic analysis delineates a biologically distinct immature acute leukemia with myeloid/T-lymphoid features by Maria E. Figueroa, Bas J.
Expression profiling of snoRNAs in normal hematopoiesis and AML
by Giridharan Ramsingh, Meagan A. Jacoby, Jin Shao, Rigoberto E
Global approach to the diagnosis of leukemia using gene expression profiling by Torsten Haferlach, Alexander Kohlmann, Susanne Schnittger, Martin Dugas,
High-Resolution Profiling of Histone Methylations in the Human Genome
by Vladia Monsurrò, Ena Wang, Yoshisha Yamano, Stephen A
An intermediate-risk multiple myeloma subgroup is defined by sIL-6r: levels synergistically increase with incidence of SNP rs and 1q21 amplification.
by Holger Weishaupt, Mikael Sigvardsson, and Joanne L. Attema
Notch1 Pathway Activation Results from the Epigenetic Abrogation of Notch-Related MicroRNAs in Mycosis Fungoides  Fernando Gallardo, Juan Sandoval, Angel.
MicroRNA Expression Profiling and DNA Methylation Signature for Deregulated MicroRNA in Cutaneous T-Cell Lymphoma  Juan Sandoval, Angel Díaz-Lagares,
Qing Cheng, Cheng Cheng, Kristine R. Crews, Raul C
Robust Detection of DNA Hypermethylation of ZNF154 as a Pan-Cancer Locus with in Silico Modeling for Blood-Based Diagnostic Development  Gennady Margolin,
Shiran Bar, Maya Schachter, Talia Eldar-Geva, Nissim Benvenisty 
Volume 29, Issue 1, Pages (April 2014)
Chun Feng, M. D. , Shen Tian, Ph. D. , Yu Zhang, M. D. , Jing He, M. D
Severely impaired terminal erythroid differentiation as an independent prognostic marker in myelodysplastic syndromes by Abdullah Mahmood Ali, Yumin Huang,
Volume 15, Issue 5, Pages (November 2014)
Ying-Ying Yu, Ph. D. , Cui-Xiang Sun, Ph. D. , Yin-Kun Liu, Ph. D
Volume 17, Issue 2, Pages (October 2016)
Cell-lineage level–targeted sequencing to identify acute myeloid leukemia with myelodysplasia-related changes by Kazuaki Yokoyama, Eigo Shimizu, Nozomi.
Allele-Specific Methylome and Transcriptome Analysis Reveals Widespread Imprinting in the Human Placenta  Hirotaka Hamada, Hiroaki Okae, Hidehiro Toh,
Volume 17, Issue 2, Pages (February 2010)
Epigenetic regulation of miR-193b in liposarcomagenesis.
Integrative Multi-omic Analysis of Human Platelet eQTLs Reveals Alternative Start Site in Mitofusin 2  Lukas M. Simon, Edward S. Chen, Leonard C. Edelstein,
MicroRNA Methylation Profile Has Prognosis Impact in Acute Lymphoblastic Leukemia Patients Undergoing Stem Cell Transplantation  Vanesa Martín-Palanco,
High-Resolution Profiling of Histone Methylations in the Human Genome
Stable Ethnic Variations in DNA Methylation Patterns of Human Skin
Volume 23, Issue 1, Pages 9-22 (January 2013)
Bettina Heidecker et al. BTS 2016;1:
Cluster analysis and pathway-based characterization of differentially expressed genes and proteins from integrated proteomics. Cluster analysis and pathway-based.
Volume 128, Issue 6, Pages (March 2007)
Genome-wide promoter methylation of hairy cell leukemia
Epigenomic Profiling Reveals DNA-Methylation Changes Associated with Major Psychosis  Jonathan Mill, Thomas Tang, Zachary Kaminsky, Tarang Khare, Simin.
Shiran Bar, Maya Schachter, Talia Eldar-Geva, Nissim Benvenisty 
Shusuke Numata, Tianzhang Ye, Thomas M
Volume 13, Issue 3, Pages (September 2013)
Volume 1, Issue 1, Pages (June 2013)
AZA treatment induces a distinct gene-expression pattern in stromal cells. AZA treatment induces a distinct gene-expression pattern in stromal cells. (A-C)
Volume 10, Issue 3, Pages (March 2017)
Comparison ofMyc-induced zebrafish liver tumors with different stages of human HCC and seven mouse HCC models. Comparison ofMyc-induced zebrafish liver.
Relationship between blood cell and plasma miRNA expression among published circulating cancer biomarkers. Relationship between blood cell and plasma miRNA.
Profiling of the TCRB-MYB cases by large-scale gene expression analysis. Profiling of the TCRB-MYB cases by large-scale gene expression analysis. (A) Heat.
Symmetrical Dose-Dependent DNA-Methylation Profiles in Children with Deletion or Duplication of 7q11.23  Emma Strong, Darci T. Butcher, Rajat Singhania,
Promoter hypermethylation of the AE2/SLC4A2 gene in PBC
A, unsupervised hierarchical clustering of the expression of probe sets differentially expressed in the oral mucosa of smokers versus never smokers. A,
Unsupervised clustering heat map of genome-wide mRNA expression profiles, using skin samples from 49 MF/SS patients and 3 healthy individuals. Unsupervised.
Integrated mRNA and microRNA expression and DNA methylation clusters.
JAK2V617F leads to increased 5-hmC and genome-wide loss of cytosine methylation in primary patient samples. JAK2V617F leads to increased 5-hmC and genome-wide.
Specific DNA methylation and expression signatures associated with binding of E2A–PBX1 fusion protein. Specific DNA methylation and expression signatures.
Distinct subtypes of CAFs are detected in human PDAC
Gene expression heatmap of non–T-cell-inflamed, intermediate, and T-cell–inflamed testicular germ cell tumors from TCGA. Genes are on the row, and samples.
Qing Cheng, Cheng Cheng, Kristine R. Crews, Raul C
Driver pathways and key genes in OSCC
Integrated analysis of gene expression and copy number alterations.
K. Miura, M. Obama, K. Yun, H. Masuzaki, Y. Ikeda, S. Yoshimura, T
Genome-wide DNA hypomethylation associated with DNMT3A mutation in murine and human FLT3ITD AML. Human: A–C, volcano plot (A) representation of mean methylation.
Fig. 3 Gene expression analysis in 48-plex drug treatment experiments.
Presentation transcript:

Loss of imprinting at the 14q32 domain is associated with microRNA overexpression in acute promyelocytic leukemia by Floriana Manodoro, Jacek Marzec, Tracy Chaplin, Farideh Miraki-Moud, Eva Moravcsik, Jelena V. Jovanovic, Jun Wang, Sameena Iqbal, David Taussig, David Grimwade, John G. Gribben, Bryan D. Young, and Silvana Debernardi Blood Volume 123(13):2066-2074 March 27, 2014 ©2014 by American Society of Hematology

Bar plots of the average methylation level for each CpG site per sample group. Bar plots of the average methylation level for each CpG site per sample group. The average DNA methylation level determined for the APL, remission (R), control (C), and AML sample groups is represented by blue columns. A black horizontal line indicates the 50% level of methylation. Amplicon names are indicated underneath the bar plots. Sample groups are labeled on the left of each panel. CpG islands and CTCF binding sites are indicated with green and red bars, respectively. Floriana Manodoro et al. Blood 2014;123:2066-2074 ©2014 by American Society of Hematology

Unsupervised hierarchical cluster analysis. Unsupervised hierarchical cluster analysis. The heat map represents the unsupervised hierarchical cluster analysis of the 4 sample groups based on the DNA methylation at the 202 CpG sites. Each row represents a CpG site, and each column a sample. The percentage of CpG methylation is depicted using color scales of red (CpG methylation >50%) and green (CpG methylation <50%). Sample group labels are also indicated at the top of the heat map. Floriana Manodoro et al. Blood 2014;123:2066-2074 ©2014 by American Society of Hematology

Allele-specific DNA methylation profiling. Allele-specific DNA methylation profiling. Unsupervised cluster analysis was performed on the CpG methylation pattern obtained for each sample and amplicon. When a heterozygous SNP was observed, sequence reads were separated accordingly to the SNP genotype, and the CpG methylation pattern of each allele was analyzed by cluster analysis. (A) Differential methylation between alleles at region 9 in the healthy donor C55. (i) Overall cluster analysis identified 2 clusters according to the methylation pattern; (ii) DNA methylation pattern for each allele. (B) Allele-specific DNA methylation differences at region 2 between diagnosis (i) and complete remission (ii) stages of patient P9 with APL; (iii) allele-specific DNA methylation at region 2 in the healthy donor C55. (C) Allele-specific DNA methylation differences at region 7 between diagnosis (i) and complete remission (ii) stages of patient P31 with APL; (iii) allele-specific DNA methylation at region 7 in the healthy donor C52. Heat maps show clustering results. Each column represents a CpG site, and each row the methylation pattern of a single sequence read. The color indicates the methylation status of each CpG: blue, methylated; yellow, not methylated. The bar plot at the top of each heat map shows the overall methylation level of each CpG site. Floriana Manodoro et al. Blood 2014;123:2066-2074 ©2014 by American Society of Hematology

Correlation between DNA methylation levels and gene expression profiles. Correlation between DNA methylation levels and gene expression profiles. The expression of 6 miRNAs included in the 14q32 cluster (miR-127, miR-136, miR-154, miR-337, miR-379, and miR-485) was correlated with DNA methylation data at the DMRs. The position of the CpG island, the CTCF binding sites, and the amplicon is labeled with green, red, and blue horizontal bars, respectively. The correlation is represented with red and green vertical bars indicating positive and negative values, respectively. Each column indicates a CpG site. The distance of each gene from the IG-DMR is indicated on the right. Floriana Manodoro et al. Blood 2014;123:2066-2074 ©2014 by American Society of Hematology

Comparison of the DNA methylation profiles in murine leukemic and nonleukemic control cells. Comparison of the DNA methylation profiles in murine leukemic and nonleukemic control cells. (A) Bar plots of the average methylation level for each CpG site (blue columns). The leukemic murine cells exhibited a distinctive hypermethylation at both regions compared with the nonleukemic counterpart. A black horizontal line indicates the 50% level of methylation. Amplicon names are indicated underneath the bar plots. Samples types are labeled on the left of each panel. The CpG island and the CTCF binding site positions are indicated with green and red bars, respectively. (B) Box plots of the methylation-level distribution in the murine samples showing hypermethylation at the CpG island and CTCF G in the leukemic cells. The P values indicate Kruskal-Wallis test results between the APL leukemic cells and the controls. Floriana Manodoro et al. Blood 2014;123:2066-2074 ©2014 by American Society of Hematology