Biology subjects

DUPREZ, E.

Publications and source records attributed to DUPREZ, E..

4 recordsLinked to original sources

bioRxiv2024

Epigenenomic and transcriptomic characterization of NPM1-mutated CN-AML subtypes

Cytogenetic normal AML with NPM1 mutations forms a distinct AML entity, associated with an intermediate prognosis and a heterogeneous response to treatment. We previously described an epigenetic biomarker, defined by the level of H3K27me3 on 70kb of the HIST1 cluster in patient blast DNA. This epigenetic mark separates cytogenetically normal NPM1mut AML into two groups of patients differing in their survival rate following chemotherapy. To better characterize the influence of the biomarker on disease progression, we performed transcriptomic and histone mark profiling on patient blasts according to the level of H3K27me3 HIST1. Our integrated analysis revealed that the two groups of patients display differences in terms of transcriptomic, chromatin landscape and cell surface markers, which could explain the clinical difference. Our profiling revealed novel targets and therefore constitutes an (epi)transcriptomic resource for NPM1 AML. It also highlights the power of epigenetic profiling to dissect the heterogeneity of a single AML genetic entity.

genomics↗

bioRxiv2022

Logical modelling of myelofibrotic microenvironment predicts dysregulated progenitor stem cell crosstalk

Primary myelofibrosis is an untreatable age-related disorder of haematopoiesis in which a break in the crosstalk between progenitor Haematopoietic Stem Cells (HSCs) and neighbouring mesenchymal stem cells causes HSCs to rapidly proliferate and migrate out of the bone marrow. 90% of patients harbour mutations in driver genes that all converge to overactivate hematopoietic JAK-STAT signalling, which is thought to be critical for disease progression, as well as microenvironment modification induced by chronic inflammation. The trigger to the initial event is unknown but dysregulated thrombopoietin (TPO) and Toll-Like Receptor (TLR) signalling are hypothesised to initiate chronic inflammation which then disrupts stem cell crosstalk. Using a systems biology approach, we have constructed an inter and intracellular logical model that captures JAK-STAT signalling and key crosstalk channels between haematopoietic and mesenchymal stem cells. The aim of the model is to decipher how TPO and TLR stimulation can perturb the bone marrow microenvironment and dysregulate stem cell crosstalk. The model predicted conditions in which the disease was averted and established for both wildtype and ectopically JAK mutated simulations. The presence of TPO and TLR are both required to disturb stem cell crosstalk and result in the disease for wildtype. TLR signalling alone was sufficient to perturb the crosstalk and drive disease progression for JAK mutated simulations. Furthermore, the model predicts the probability of disease onset for wildtype simulations that matches clinical data. These predictions might explain why patients who test negative for the JAK mutation can still be diagnosed with PMF, in which continual exposure to TPO and TLR receptor activation may trigger the initial inflammatory event that perturbs the bone marrow microenvironment and induce disease onset.

systems biology↗

bioRxiv2022

SC-RNA-seq assisted synthesis of a Boolean network to model early haematopoiesis aging

Hematopoietic stem cell (HSC) aging is a multifactorial event that leads to changes in HSC properties and function. These changes are intrinsically coordinated and affect the early hematopoiesis, involving hematopoietic stem and progenitor cells (HSPCs). The objective of this work is to better understand the mechanisms and factors controlling these changes. We have therefore developed an original strategy to construct a Boolean network of genes explaining the priming and homeostasis of HSCs (graphical abstract). Based on our previous scRNA-seq data, we performed an exhaustive analysis of the transcriptional network and identified active transcription modules or regulons along the differentiation trajectory of selected HSPC states. This global view of transcriptional regulation led us to focus on 15 components, 13 selected TFs (Tal1, Fli1, Gata2, Gata1, Zfpm1, Egr1, Junb, Ikzf1, Myc, Cebpa, Bclaf1, Klf1, Spi1) and 2 complexes regulating the ability of HSC to cycle (CDK4/6 - Cyclin D and CIP/KIP). We then defined the connections controlling the differentiation dynamics of HSC states and constructed an influence graph between the TFs involved in the dynamics by mixing observations from our scRNA-seq data and knowledge from the literature. Then, using answer set programming (ASP) and in silico perturbation analysis, we obtained a Boolean model which is the solution of a Boolean satisfiability problem. Finally, perturbation of the model based on age-related changes revealed important regulations, such as the overactivation of Egr1 and Junb or the loss of Cebpa activation by Gata2, which were found to be relevant for the myeloid bias of aged HSC. Our work shows the efficiency of the combination of manual and systematic methods to elaborate a Boolean model. The developed strategy led to the proposal of new regulatory mechanisms underlying the differentiation bias of aged HSCs, explaining the decreased transcriptional priming of HSCs to all mature cell types except megakaryocytes. Graphical abstractFrom single cell RNA-seq (scRNA-seq) data and current knowledge in early hematopoiesis (literature and biological database investigation), 3 inputs were obtained to define the network synthesis as a Boolean Satisfiability Problem depending on observations of states in the differentiation process: O_LIInfluence graph between selected components. C_LIO_LIDiscretized component activity levels in the considered states (blue: 0/inactive, white: */unknown or free, red: 1/active). C_LIO_LIDynamic relations (stable states, (non) reachability) between the considered states. Then, these inputs were encoded as constraints in Answer Set Programing (ASP) thanks to the Bonesis tool. After the solving, a Boolean model of early hematopoiesis is obtained. This model is altered according to the characteristics of aging observed in our scRNA-seq data, in order to identify the main molecular actors and mechanisms of aging. C_LI O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=119 SRC="FIGDIR/small/479548v2_ufig1.gif" ALT="Figure 1"> View larger version (20K): org.highwire.dtl.DTLVardef@fbf1d1org.highwire.dtl.DTLVardef@c0ee97org.highwire.dtl.DTLVardef@70365corg.highwire.dtl.DTLVardef@100ff60_HPS_FORMAT_FIGEXP M_FIG O_FLOATNOGraphical abstract:C_FLOATNO Overview of the scRNA-seq assisted gene Boolean network synthesis strategy. C_FIG

systems biology↗

bioRxiv2020

Single-cell RNA-seq reveals a concomitant delay in differentiation and cell cycle of aged hematopoietic stem cell

Hematopoietic stem cells (HSCs) are the guarantor of the proper functioning of hematopoiesis due to their incredible diversity of potential. During aging the heterogeneity of mouse HSCs evolves, which contributes to the deterioration of the immune system. Here we address the transcriptional plasticity of HSC upon aging at the single-cell resolution. Through the analysis of 15,000 young and aged transcriptomes, we reveal 15 clusters of HSCs unveiling rare and specific HSC abilities that change with age. Pseudotime ordering complemented with regulon analysis showed that the consecutive differentiation states of HSC are delayed upon aging. By analysing cell cycle at the single cell level we highlight an imbalance of cell cycle regulators of very immature aged HSC that may contribute to their accumulation in an undifferentiated state. Our results therefore establish a reference map of young and old mouse HSC differentiation and reveal a potential mechanism that delay aged HSC differentiation.

genomics↗