Distinctive Patterns of MicroRNA Expression Associated with Karyotype in Acute Myeloid Leukaemia

Acute myeloid leukaemia (AML) is the most common acute leukaemia in adults; however, the genetic aetiology of the disease is not yet fully understood. A quantitative expression profile analysis of 157 mature miRNAs was performed on 100 AML patients representing the spectrum of known karyotypes common in AML. The principle observation reported here is that AMLs bearing a t(15;17) translocation had a distinctive signature throughout the whole set of genes, including the up regulation of a subset of miRNAs located in the human 14q32 imprinted domain. The set included miR-127, miR-154, miR-154*, miR-299, miR-323, miR-368, and miR-370. Furthermore, specific subsets of miRNAs were identified that provided molecular signatures characteristic of the major translocation-mediated gene fusion events in AML. Analysis of variance showed the significant deregulation of 33 miRNAs across the leukaemic set with respect to bone marrow from healthy donors. Fluorescent in situ hybridisation analysis using miRNA-specific locked nucleic acid (LNA) probes on cryopreserved patient cells confirmed the results obtained by real-time PCR. This study, conducted on about a fifth of the miRNAs currently reported in the Sanger database (microrna.sanger.ac.uk), demonstrates the potential for using miRNA expression to sub-classify cancer and suggests a role in the aetiology of leukaemia

Genome Wide Analysis of Acute Myeloid Leukemia Reveal Leukemia Specific Methylome and Subtype Specific Hypomethylation of Repeats

Methylated DNA immunoprecipitation followed by high-throughput sequencing (MeDIP-seq) has the potential to identify changes in DNA methylation important in cancer development. In order to understand the role of epigenetic modulation in the development of acute myeloid leukemia (AML) we have applied MeDIP-seq to the DNA of 12 AML patients and 4 normal bone marrows. This analysis revealed leukemia-associated differentially methylated regions that included gene promoters, gene bodies, CpG islands and CpG island shores. Two genes (SPHKAP and DPP6) with significantly methylated promoters were of interest and further analysis of their expression showed them to be repressed in AML. We also demonstrated considerable cytogenetic subtype specificity in the methylomes affecting different genomic features. Significantly distinct patterns of hypomethylation of certain interspersed repeat elements were associated with cytogenetic subtypes. The methylation patterns of members of the SINE family tightly clustered all leukemic patients with an enrichment of Alu repeats with a high CpG density (P<0.0001). We were able to demonstrate significant inverse correlation between intragenic interspersed repeat sequence methylation and gene expression with SINEs showing the strongest inverse correlation (R2 = 0.7). We conclude that the alterations in DNA methylation that accompany the development of AML affect not only the promoters, but also the non-promoter genomic features, with significant demethylation of certain interspersed repeat DNA elements being associated with AML cytogenetic subtypes. MeDIP-seq data were validated using bisulfite pyrosequencing and the Infinium array

Methylation of tumour suppressor gene promoters in the presence and absence of transcriptional silencing in high hyperdiploid acute lymphoblastic leukaemia

Promoter methylation is a common phenomenon in tumours, including haematological malignancies. In the present study, we investigated 36 cases of high hyperdiploid (&gt;50 chromosomes) acute lymphoblastic leukaemia (ALL) with methylation-specific multiplex ligase-dependent probe amplification to determine the extent of aberrant methylation in this subgroup. The analysis, which comprised the promoters of 35 known tumour suppressor genes, showed that 16 genes displayed abnormal methylation in at least one case each. The highest number of methylated gene promoters seen in a single case was thirteen, with all but one case displaying methylation for at least one gene. The most common targets were ESR1 (29/36 cases; 81%), CADM1 (IGSF4, TSLC1; 25/36 cases; 69%), FHIT (24/36 cases; 67%) and RARB (22/36 cases; 61%). Interestingly, quantitative reverse transcription-polymerase chain reaction showed that although methylation of the CADM1 and RARB promoters resulted in the expected pattern of downregulation of the respective genes, no difference could be detected in FHIT expression between methylation-positive and -negative cases. Furthermore, TIMP3 was not expressed regardless of methylation status, showing that aberrant methylation does not always lead to gene expression changes. Taken together, our findings suggest that aberrant methylation of tumour suppressor gene promoters is a common phenomenon in high hyperdiploid AL

<i>SPHKAP</i>, <i>DPP6</i> and <i>ID4</i> gene expression in AML.

<p>(A.1, B.1, C.1) Relative expression of <i>SPHKAP</i>, <i>DPP6</i>, <i>ID4</i> (respectively) in AML and normal tissues. The genes were down regulated in AML patients and in cancer cell lines, while the genes were up regulated in normal tissues. (A.2, B.2, C.2) Relative expression of <i>SPHKAP</i>, <i>DPP6</i> and <i>ID4</i> (respectively) in OCI-AML2 and CTS cell lines before and after treatment by DAC. Gene expression was restored in most of cell lines treated by DAC.</p

Hierarchical clustering of AML versus NBM in the interspersed repeats.

<p>In each figure, each column represents AML patient/NBM and each row represents a single DMR. First row represents cluster analysis of all AMLs versus all NBMs and the second row represents cluster analysis of AML subtypes in SINEs (A, D), LINEs (B, E) and LTRs (C, F). Distinctive hypomethylated SINEs, LINEs and LTRs clearly distinguished each AML subtype (second row).</p

Correlation between DNA methylation and gene expression.

<p>(A–F) For a single AML patient we categorized the gene methylation into 4 groups (>0.4, 0.4–0.6, 0.6–0.8, >0.8 Batman scores). We correlated the average of each methylation group to corresponding average of gene expression. (G) Box plots of DNA methylation levels of over- and under-expressed genes in each triplicate of t(8;21), t(15;17), NK and trisomy 8 AML subtypes. N refers to the number of genes in each set. Mann Whitney test of the two sets of genes demonstrated a significant methylation difference between the medians in t(8;21), NK and trisomy 8 AML subtypes.</p

Global DNA methylation display in AML and NBM.

<p>(A) DNA methylation of all AML patients and all NBMs were categorized into 5 groups of methylation. There was no significant difference in the global DNA methylation between AML and NBM. (B) DNA methylation scores of all AMLs (blue line) and all NBMs (green line) were plotted against their density (frequency). AML has less frequency of DNA methylation scores>0.8 in the comparison with NBM. (C–J) Percentages of different groups of DNA methylation in the average of each triplicate of AML subtype and in the average of 4 NBMs. SINEs showed the highest difference in the DNA methylation scores>0.8 between NBM and AML.</p

Hierarchical clustering of AML versus NBM in 4 genomic features.

<p>First row represents cluster analysis of all AMLs versus all NBMs and the second row represents cluster analysis of AML subtypes in promoters (A, E), gene bodies (B, F), CGIs (C, G) and CGI shores (D, H). In each figure, each column represents AML patient/NBM and each row represents a single DMR. AML patients were clustered more tightly in CGIs (first row). t(8;21) AML subtype was clustered separately from the other AML subtypes (second row).</p