Epigenetic analysis reveals significant differential expression of miR‐378C and miR‐128‐2‐5p in a cohort of relapsed pediatric B‐acute lymphoblastic leukemia cases

Author(s):  
Prateek Bhatia ◽  
Minu Singh ◽  
Aditya Singh ◽  
Pankaj Sharma ◽  
Amita Trehan ◽  
...  
Epigenetics ◽  
2009 ◽  
Vol 4 (3) ◽  
pp. 185-193 ◽  
Author(s):  
Thomas L. Dunwell ◽  
Luke B. Hesson ◽  
Tatiana V. Pavlova ◽  
Veronika Zabarovska ◽  
Vladimir I. Kashuba ◽  
...  

2019 ◽  
Vol 110 (10) ◽  
pp. 3358-3367 ◽  
Author(s):  
Yasuo Kubota ◽  
Kumiko Uryu ◽  
Tatsuya Ito ◽  
Masafumi Seki ◽  
Tomoko Kawai ◽  
...  

Blood ◽  
2010 ◽  
Vol 116 (21) ◽  
pp. 2493-2493
Author(s):  
Vivek A Bhadri ◽  
Mark J Cowley ◽  
Warren Kaplan ◽  
Richard B Lock

Abstract Abstract 2493 Introduction. Glucocorticoids (GC) such as prednisolone (Pred) and dexamethasone (Dex) are critical drugs in multi-agent chemotherapy protocols used to treat acute lymphoblastic leukemia (ALL). The NOD/SCID ALL xenograft mouse model is a clinically relevant model in which the mice develop a systemic leukemia which retains the fundamental biological characteristics of the original disease. Here we report the results of a study evaluating the NOD/SCID xenograft model to investigate GC-induced gene expression. Methods. Cells from a GC-sensitive xenograft derived from a child with B-cell precursor ALL were inoculated into NOD/SCID mice. Engraftment, defined as the proportion of human vs mouse CD45+ cells in the peripheral blood, was monitored by serial weekly tail-vein sampling. When engraftment levels reached >50%, the mice were randomised and treated with either dexamethasone 15 mg/kg or vehicle control by intraperitoneal injection, and harvested at 0, 8, 24 or 48 h thereafter. The 48 hour groups received a second dose of vehicle or Dex at 24 hours. At the defined timepoints, the mice were euthanized and lymphoblasts harvested from the spleen. RNA was extracted, amplified and hybridised onto Illumina WG-6 V3 chips. The data was pre-processed using variance-stabilisation transformation, and quantile normalisation. Differential expression was determined using limma by comparing all treated groups to time 0, with the positive False Discovery Rate correction for multiple testing. Hierarchical clustering was used to compare groups to each other. The stability of results when reducing the number of replicates was assessed using the Recovery Score method. Functional analysis was performed using gene set enrichment analysis (GSEA) and comparison to publicly available microarray data using parametric GSEA. Results. The 8 hour Dex-treated timepoint had the most number of significantly differentially expressed genes (see Table), with fewer observed at the 24 and 48 hour Dex-treated timepoints. There was minimal significant differential gene expression across the time-matched controls. At the 8 hour timepoint, ZBTB16, a known GC-induced gene, was the most significantly upregulated gene. Other significantly differentially expressed genes included TSC22D3 and SOCS1, both downstream targets of the glucocorticoid receptor (upregulated), and BCL-2 and C-MYC (downregulated). GSEA at 8 hours revealed a significant upregulation of catabolic pathways and downregulation of pathways associated with cell proliferation, particularly C-MYC. GSEA at 24 hours revealed enrichment of pathways associated with NF-kB. Replicate analysis revealed that at the 8 hour Dex treated timepoint, a dataset with high signal and differential expression, using data from 3 replicates instead of 4 resulted in excellent recovery scores of >0.9. However at other timepoints with less signal very poor recovery scores were obtained using 3 replicates. We compared our data to publicly available datasets of GC-induced genes in ALL (Schmidt et al, Blood 2006; Rainer et al, Leukemia 2009) using parametric GSEA, which revealed that the 8 hour gene expression data obtained from the NOD/SCID xenograft model clustered with data from primary patient samples (Schmidt) rather than the cell line data (Rainer). The 24 and 48 hour datasets clustered separately from all other datasets by this method, reflecting fewer and predominantly downregulated gene expression at these timepoints. Conclusions: The NOD/SCID xenograft mouse model provides a reproducible experimental model system in which to investigate clinically-relevant mechanisms of GC-induced gene regulation in ALL; the 8 hour timepoint provides the highest number of significantly differentially expressed genes; time-matched controls are redundant and excellent recovery scores can be obtained with 3 replicates. Disclosures: No relevant conflicts of interest to declare.


2008 ◽  
Vol 30 (12) ◽  
pp. 941-944 ◽  
Author(s):  
Thomas Russell ◽  
Janet M. Oliver ◽  
Bridget S. Wilson ◽  
Christy A. Tarleton ◽  
Stuart S. Winter ◽  
...  

Blood ◽  
2010 ◽  
Vol 116 (21) ◽  
pp. 537-537
Author(s):  
Maria E. Figueroa ◽  
Shann-Ching Chen ◽  
Anna K. Andersson ◽  
Wei Liu ◽  
Cheng Cheng ◽  
...  

Abstract Abstract 537 Acute lymphoblastic leukemia (ALL), the commonest childhood malignancy, is characterized by recurring gross and submicroscopic structural genetic alterations that contribute to leukemogenesis. Disordered epigenetic regulation is a hallmark of many tumors, and while analysis of DNA methylation of limited numbers of genes or ALL samples suggests epigenetic alterations may also be important, a large-scale integrative genome-wide analysis evaluating DNA methylation in ALL has not been performed. Here, we report an integrated epigenomic, transcriptional and genetic analysis of 167 childhood ALL cases, comprising B-progenitor ALL with hyperdiploidy (N=26), ETV6-RUNX1 (N=27), TCF3-PBX1 (N=9), BCR-ABL1 (N=19), rearrangement of MLL (MLLr) (N=20), rearrangement of CRLF2 (N=11, CRLF2r), deletion of ERG (N=11), miscellaneous or normal karyotype (N=14), and T-lineage ALL (N=30), including 4 MLLr cases and 8 cases with early T-cell precursor immunophenotype. Genome-wide profiling of structural DNA alterations was performed for all cases using Affymetrix 500K and SNP 6.0 arrays. Affymetrix U133A gene expression profiling data was available for 154 cases. Genome-wide methylation profiling was performed using the HELP microarray assay, which measures methylation at approximately 50,000 CpGs distributed among 22,722 Refseq promoters. Methylation data was compared to that of normal pro-B (CD34+CD19+sIg-), pre-B (CD34-CD19+sIg-) and mature B (CD34-CD19+sIg+) cells FACS-sorted from bone marrow of 6 healthy individuals. Unsupervised hierarchical clustering of the top 4043 most variable methylation probesets identified 9 B-ALL clusters with significant correlation to specific genetic lesions including ETV6-RUNX1, MLLr, BCR-ABL1, CRLF2r, TCF3-PBX1 and ERG deletion. T-ALLs and hyperdiploid B-ALLs also defined specific DNA methylation clusters. Supervised analysis including limma and ANOVA identified distinct DNA methylation signatures for each subtype. Notably, the strength of these signatures was subtype dependent, with more differentially methylated genes observed in ALL cases with genetic alterations targeting transcriptional regulators (e.g. ETV6-RUNX1 and MLLr) and fewer genes in cases with alterations deregulating cytokine receptor signaling (e.g. CRLF2r). Aberrant DNA methylation affected specific and distinct biological processes in the various leukemia subtypes implicating epigenetic regulation of these pathways in the pathogenesis of these different forms of ALL (e.g. TGFB and TNF in ERG deleted leukemias; telomere and centriole regulation in BCR-ABL1 ALL). Aberrantly methylated genes were also enriched for binding sites of known or suspected oncogenic transcription factors that might represent cooperative influences in establishing the phenotype of the various B-ALL subtypes. Most importantly, an integrated analysis of methylation and gene expression of these ALL subtypes demonstrated striking inversely correlated expression of the corresponding gene transcripts. The methylation signatures of each subtype exhibited only partial overlap with those of normal B cells, indicating that the signatures do not simply reflect stage of lymphoid maturation. In a separate approach, we discovered that 81 genes showed consistent aberrant methylation across all ALL subtypes, including the tumor suppressor PDZD2, HOXA5, HOXA6 and MSH2. Inverse correlation with expression was confirmed in 66% of these genes. These data suggest the existence of a common epigenetic pathway underlying the malignant transformation of lymphoid precursor cells. Integrative genetic and epigenetic analysis revealed hypermethylation of genes on trisomic chromosomes that do not show increased expression, suggesting that epigenetic silencing may control genes within amplified regions and explain why only selected genes are overexpressed. Finally, analysis of individual genes targeted by recurring copy number alterations in ALL revealed a subset of genes also targeted by abnormal methylation, with corresponding changes in gene expression (e.g. ERG, GAB1), suggesting that such genes are inactivated far more frequently than suggested by genetic analyses alone. Collectively, the data support a key role of epigenetic gene regulation in the pathogenesis of ALL, and point towards a scenario where genetic and epigenetic lesions cooperatively determine disease phenotype. Disclosures: No relevant conflicts of interest to declare.


2017 ◽  
Vol 408 ◽  
pp. 92-101 ◽  
Author(s):  
Teresa Sadras ◽  
Susan L. Heatley ◽  
Chung H. Kok ◽  
Phuong Dang ◽  
Kate M. Galbraith ◽  
...  

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