Computational Biology in Acute Myeloid Leukemia with CEBPA Abnormalities

Abstract

__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