Computational Biology in Acute Myeloid Leukemia with CEBPA Abnormalities

__Abstract__ In the last decade, tiling-array and next-generation sequencing technologies allowed quantitative measurements of different cellular processes, such as mRNA expression, genomic changes including deletions or amplifications, DNA-methylation, chromatin modifications or Protein-DNA-binding interactions. Using these technologies, thousands of features can now be measured simultaneously in a patient cell sample. The use of for instance mRNA expression profiles or DNA-methylation profiles have already provided new insight into the molecular biology of patients with Acute Myeloid Leukemia (AML). AML is a blood cell malignancy, in which primitive myeloid cells have been transformed and accumulate in the bone marrow and blood. Different forms of AML exist with different molecular abnormalities that associate with distinct responses to therapy. Many subgroups with comparable mRNA expression or DNA-methylation patterns were identified. These studies also revealed the existence of novel previously undefined AML subtypes. Among those was a group of patients with a mutation in a gene called CEBPA. CEBPA is a gene that encodes the transcription factor CCAAT Enhancer Binding Protein Alpha (C/EBPα), which controls the expression of genes in myeloid progenitor cells. Mutated CEBPA encodes a dysfunctional C/EBPα-protein, which consequently results in aberrant control of “target genes”. In this thesis we focus particularly on the role of CEBPA. We studied the predictive and prognostic relevance of mutated CEBPA, and analyzed in a genome wide fashion the mRNA expression, DNA-methylation and the protein-DNA-binding levels corresponding to (mutated) CEBPA in AML. For the analysis of protein-DNA-binding, we developed a novel statistical methodology. With this statistical methodology we studied the fundamental role of (mutant) C/EBPα binding and the effect on gene expression levels. We also integrated gene expression with DNA-methylation profiles of hundreds of AML patients and revealed the existence of two previously unidentified AML subtypes

Genome-wide association meta-analysis of 78,308 individuals identifies new loci and genes influencing human intelligence

Intelligence is associated with important economic and health-related life outcomes1. Despite intelligence having substantial heritability2 (0.54) and a confirmed polygenic nature, initial genetic studies were mostly underpowered3,4,5. Here we report a meta-analysis for intelligence of 78,308 individuals. We identify 336 associated SNPs (METAL P < 5 × 10−8) in 18 genomic loci, of which 15 are new. Around half of the SNPs are located inside a gene, implicating 22 genes, of which 11 are new findings. Gene-based analyses identified an additional 30 genes (MAGMA P < 2.73 × 10−6), of which all but one had not been implicated previously. We show that the identified genes are predominantly expressed in brain tissue, and pathway analysis indicates the involvement of genes regulating cell development (MAGMA competitive P = 3.5 × 10−6). Despite the well-known difference in twin-based heritability2 for intelligence in childhood (0.45) and adulthood (0.80), we show substantial genetic correlation (rg = 0.89, LD score regression P = 5.4 × 10−29). These findings provide new insight into the genetic architecture of intelligence

EVI1 is critical for the pathogenesis of a subset of MLL-AF9-rearranged AMLs

The proto-oncogene EVI1 (ecotropic viral integration site-1), located on chromosome band 3q26, is aberrantly expressed in human acute myeloid leukemia (AML) with 3q26 rearrangements. In the current study, we showed, in a large AML cohort carrying 11q23 translocations, that similar to 43% of all mixed lineage leukemia (MLL)-rearranged leukemias are EVI1(pos). High EVI1 expression occurs in AMLs expressing the MLL-AF6, -AF9, -AF10, -ENL, or -ELL fusion genes. In addition, we present evidence that EVI1(pos) MLL-rearranged AMLs differ molecularly, morphologically, and immunophenotypically from EVI1(neg) MLL-rearranged leukemias. In mouse bone marrow cells transduced with MLL-AF9, we show that MLL-AF9 fusion protein maintains Evi1 expression on transformation of Evi1(pos) HSCs. MLL-AF9 does not activate Evi1 expression in MLL-AF9-transformed granulocyte macrophage progenitors (GMPs) that were initially Evi1(neg). Moreover, shRNA-mediated knockdown of Evi1 in an Evi1(pos) MLL-AF9 mouse model inhibits leukemia growth both in vitro and in vivo, suggesting that Evi1 provides a growth-promoting signal. Using the Evi1(pos) MLL-AF9 mouse leukemia model, we demonstrate increased sensitivity to chemotherapeutic agents on reduction of Evi1 expression. We conclude that EVI1 is a critical player in tumor growth in a subset of MLL-rearranged AMLs. (Blood. 2012; 119(24):5838-5849

EVI1 is critical for the pathogenesis of a subset of MLL-AF9-rearranged AMLs

The proto-oncogene EVI1 (ecotropic viral integration site-1), located on chromosome band 3q26, is aberrantly expressed in human acute myeloid leukemia (AML) with 3q26 rearrangements. In the current study, we showed, in a large AML cohort carrying 11q23 translocations, that ∼ 43% of all mixed lineage leukemia (MLL)-rearranged leukemias are EVI1pos. High EVI1 expression occurs in AMLs expressing the MLL-AF6, -AF9, -AF10, -ENL, or -ELL fusion genes. In addition, we present evidence that EVI1pos MLL-rearranged AMLs differ molecularly, morphologically, and immunophenotypically from EVI1neg MLL-rearranged leukemias. In mouse bone marrow cells transduced with MLL-AF9, we show that MLL-AF9 fusion protein maintains Evi1 expression on transformation of Evi1pos HSCs. MLL-AF9 does not activate Evi1 expression in MLLAF9- transformed granulocyte macrophage progenitors (GMPs) that were initially Evi1neg. Moreover, shRNA-mediated knockdown of Evi1 in an Evi1pos MLL-AF9 mouse model inhibits leukemia growth both in vitro and in vivo, suggesting that Evi1 provides a growth-promoting signal. Using the Evi1pos MLL-AF9 mouse leukemia model, we demonstrate increased sensitivity to chemotherapeutic agents on reduction of Evi1 expression. We conclude that EVI1 is a critical player in tumor growth in a subset of MLL-rearranged AMLs

Genome-wide association meta-analysis of 78,308 individuals identifies new loci and genes influencing human intelligence

Intelligence is associated with important economic and health-related life outcomes. Despite intelligence having substantial heritability (0.54) and a confirmed polygenic nature, initial genetic studies were mostly underpowered. Here we report a meta-analysis for intelligence of 78,308 individuals. We identify 336 associated SNPs (METAL P < 5 × 10-8) in 18 genomic loci, of which 15 are new. Around half of the SNPs are located inside a gene, implicating 22 genes, of which 11 are new findings. Gene-based analyses identified an additional 30 genes (MAGMA P < 2.73 × 10-6), of which all but one had not been implicated previously. We show that the identified genes are predominantly expressed in brain tissue, and pathway analysis indicates the involvement of genes regulating cell development (MAGMA competitive P = 3.5 × 10-6). Despite the well-known difference in twin-based heritability for intelligence in childhood (0.45) and adulthood (0.80), we show substantial genetic correlation (rg = 0.89, LD score regression P = 5.4 × 10-29). These findings provide new insight into the genetic architecture of intelligence