Epigenetic changes in human model KMT2A leukemias highlight early events during leukemogenesis.

Chromosomal translocations involving KMT2A gene are one of the most common genetic alterations found in pediatric acute myeloid leukemias (AML) although the molecular mechanisms that initiate the disease remain incompletely defined. To elucidate these initiating events we have used a human model system of AML driven by the KMT2A-MLLT3 (KM3) fusion. More specifically, we investigated changes in DNA methylation, histone modifications, and chromatin accessibility at each stage of our model system and correlated these with expression changes.

Modeling human MLL-AF9 translocated acute myeloid leukemia from single donors reveals RET as a potential therapeutic target.

Acute myeloid leukemias (AMLs) result from a series of genetic events occurring in a stem or progenitor hematopoietic cell that gives rise to their clonal expansion and an impaired capacity to differentiate. To circumvent the genetic heterogeneity of AML patient cohorts, we have developed a model system, driven by the MLL-AF9 (MA9) oncogene, to generate multiple human leukemias using progenitor cells from a single healthy donor. Through stepwise RNA-sequencing data generated using this model and AML patients, we have identified consistent changes associated with MA9-driven leukemogenesis and demonstrate that no recurrent secondary mutations are required.

Whole genome and transcriptome analysis of a novel AML cell line with a normal karyotype.

Acute myeloid leukemia (AML) occurs when hematopoietic progenitor cells acquire genetic defects blocking the regulation of normal growth and differentiation. Although recurrent translocations have been identified in AML, almost half of adult AML patients present with a normal karyotype (NK-AML). While cell line models exist to study AML, they frequently have abnormal/unstable karyotypes, while primary cells from NK-AML patients are difficult to maintain in vitro.

Epigenetic regulation of GATA2 and its impact on normal karyotype acute myeloid leukemia.

The GATA2 gene encodes a zinc-finger transcription factor that acts as a master regulator of normal hematopoiesis. Mutations in GATA2 have been implicated in the development of myelodysplastic syndrome and acute myeloid leukemia (AML). Using RNA sequencing we now report that GATA2 is either mutated with a functional consequence, or expressed at low levels in the majority of normal karyotype AML (NK-AML).

A comparative transcriptomic, fluxomic and metabolomic analysis of the response of Saccharomyces cerevisiae to increases in NADPH oxidation.

Background: Redox homeostasis is essential to sustain metabolism and growth. We recently reported that yeast cells meet a gradual increase in imposed NADPH demand by progressively increasing flux through the pentose phosphate (PP) and acetate pathways and by exchanging NADH for NADPH in the cytosol, via a transhydrogenase-like cycle. Here, we studied the mechanisms underlying this metabolic response, through a combination of gene expression profiling and analyses of extracellular and intracellular metabolites and 13 C-flux analysis.

A constraint-based model analysis of the metabolic consequences of increased NADPH oxidation in Saccharomyces cerevisiae.

Controlling the amounts of redox cofactors to manipulate metabolic fluxes is emerging as a useful approach to optimizing byproduct yields in yeast biotechnological processes. Redox cofactors are extensively interconnected metabolites, so predicting metabolite patterns is challenging and requires in-depth knowledge of how the metabolic network responds to a redox perturbation. Our aim was to analyze comprehensively the metabolic consequences of increased cytosolic NADPH oxidation during yeast fermentation.

Comparative analysis of missing value imputation methods to improve clustering and interpretation of microarray experiments.

Background: Microarray technologies produced large amount of data. In a previous study, we have shown the interest of k-Nearest Neighbour approach for restoring the missing gene expression values, and its positive impact of the gene clustering by hierarchical algorithm. Since, numerous replacement methods have been proposed to impute missing values (MVs) for microarray data.