ERC FUNDED PROJECTS

Acute Myeloid Leukemia (AML), the most common leukemia diagnosed in adults, represents the paradigm of resistance to front-line therapies in hematology. Indeed, AML is so genetically complex that only few targeted therapies are currently tested in this disease and chemotherapy remains the only standard treatment for AML since the past four decades. Despite an initial sustained remission achieved by chemotherapeutic agents, almost all patients relapse with a chemoresistant minimal residual disease (MRD). The goal of my proposal is to characterize the still poorly understood biological mechanisms underlying persistence and emergence of MRD. MRD is the consequence of the re-expansion of leukemia-initiating cells that are intrinsically more resistant to chemotherapy. This cell fraction may be stochastically more prone to survive front-line therapy regardless of their mutational status (the stochastic model), or genetically predetermined to resist by virtue of a collection of chemoprotective mutations (the mutational model). I have already generated in mice, by consecutive rounds of chemotherapy, a stochastic MLL-AF9-driven chemoresistance model that I examined by RNA-sequencing. I will pursue the comprehensive cell autonomous and cell non-autonomous characterization of this chemoresistant AML disease using whole-exome and ChIP-sequencing. To establish a mutationally-induced chemoresistant mouse model, I will conduct an innovative in vivo screen using pooled mutant open reading frame and shRNA libraries in order to predict which combinations of mutations, among those already known in AML, actively promote chemoresistance. Finally, by combining genomic profiling and in vivo shRNA screening experiments, I will decipher the molecular mechanisms and identify the functional effectors of these two modes of resistance. Ultimately, I will then be able to firmly establish the fundamental relevance of the stochastic and/or the mutational model of chemoresistance for MRD genesis.

1 500 000 €

Start date: 2018-03-01, End date: 2023-02-28

Our research interests lie in breaking new ground in studying mechanism-based functions of AP-1 (Fos/Jun) in vivo with the aim of obtaining a more global perspective on AP-1 in human physiology and disease/cancer. The unresolved issues regarding the AP-1 subunit composition will be tackled biochemically and genetically in various cell types including bone, liver and skin, the primary organs affected by altered AP-1 activity. I plan to utilize the knowledge gained on AP-1 functions in the mouse and transfer it to human disease. The opportunities here lie in exploiting the knowledge of AP-1 target genes and utilizing this information to interfere with pathways involved in normal physiology and disease/cancer. The past investigations revealed that the functions of AP-1 are an essential node at the crossroads between life and death in different cellular systems. I plan to further exploit our findings and concentrate on utilising better mouse models to define these connections. The emphasis will be on identifying molecular signatures and potential treatments in models for cancer, inflammatory and fibrotic diseases. Exploring genetically modified stem cell-based therapies in murine and human cells is an ongoing challenge I would like to meet in the forthcoming years at the CNIO. In addition, the mouse models will be used for mechanism-driven therapeutic strategies and these studies will be undertaken in collaboration with the Experimental Therapeutics Division and the service units such as the tumor bank. The project proposal is divided into 6 Goals (see also Figure 1): Some are a logical continuation based on previous work with completely new aspects (Goal 1-2), some focussing on in depth molecular analyses of disease models with innovative and unconventional concepts, such as for inflammation and cancer, psoriasis and fibrosis (Goal 3-5). A final section is devoted to mouse and human ES cells and their impact for regenerative medicine in bone diseases and cancer.

2 500 000 €

Start date: 2009-11-01, End date: 2015-10-31

Diabetes has become one of the most widespread metabolic disorders with epidemic dimensions affecting almost 6% of the world’s population. Despite modern treatments, the life expectancy of patients with Type 1 diabetes remains reduced as compared to healthy subjects. There is therefore a need for alternative therapies. Towards this aim, using the mouse, we recently demonstrated that the in vivo forced expression of a single factor in pancreatic alpha-cells is sufficient to induce a continuous regeneration of alpha-cells and their subsequent conversion into beta-like cells, such converted cells being capable of reversing the consequences of chemically-induced diabetes in vivo (Collombat et al. Cell, 2009). The PI and his team therefore propose to further decipher the mechanisms involved in this alpha-cell-mediated beta-cell regeneration process and determine whether this approach may be applied to adult animals and whether it would efficiently reverse Type 1 diabetes. Furthermore, a major effort will be made to verify whether our findings could be translated to human. Specifically, we will use a tri-partite approach to address the following issues: (1) Can the in vivo alpha-cell-mediated beta-cell regeneration be induced in adults mice? What would be the genetic determinants involved? (2) Can alpha-cell-mediated beta-cell regeneration reverse diabetes in the NOD Type 1 diabetes mouse model? (3) Can adult human alpha-cells be converted into beta-like cells? Together, these ambitious objectives will most certainly allow us to gain new insight into the mechanisms defining the identity and the reprogramming capabilities of mouse and human endocrine cells and may thereby open new avenues for the treatment of diabetes. Similarly, the determination of the molecular triggers implicated in the beta-cell regeneration observed in our diabetic mice may lead to exciting new findings, including the identification of “drugable” targets of importance for human diabetic patients.

1 500 000 €

Start date: 2012-01-01, End date: 2016-12-31

The composition and molecular features of tumours vary during the course of the disease, and the selection pressure imposed by the environment is a central component in this process. Evolutionary principles have been exploited to explain the genomic aberrations in cancer. However, the phenotypic changes underlying disease progression remain poorly understood. In the past years, I have contributed to identify and characterise the therapeutic implications underlying metabolic alterations that are intrinsic to primary tumours or metastasis. In CancerADAPT I postulate that cancer cells rely on adaptive transcriptional & metabolic mechanisms [converging on a Metabolic Phenotype] in order to rapidly succeed in their establishment in new microenvironments along disease progression. I aim to predict the molecular cues that govern the adaptive properties in prostate cancer (PCa), one of the most commonly diagnosed cancers in men and an important source of cancer-related deaths. I will exploit single cell RNASeq, spatial transcriptomics and multiregional OMICs in order to identify the transcriptional and metabolic diversity within tumours and along disease progression. I will complement experimental strategies with computational analyses that identify and classify the predicted adaptation strategies of PCa cells in response to variations in the tumour microenvironment. Metabolic phenotypes postulated to sustain PCa adaptability will be functionally and mechanistically deconstructed. We will identify therapeutic strategies emanating from these results through in silico methodologies and small molecule high-throughput screening, and evaluate their potential to hamper the adaptability of tumour cells in vitro and in vivo, in two specific aspects: metastasis and therapy response. CancerADAPT will generate fundamental understanding on how cancer cells adapt in our organism, in turn leading to therapeutic strategies that increase the efficacy of current treatments.

1 999 882 €

Start date: 2019-11-01, End date: 2024-10-31