Data-Gouv-ML/pcri-erc-participations-et-projets-laureats huggingface dataset:
Projet ERC : Tamed Cancer (Horizon 2020, appel 2015, Starting grants)
Domaine scientifique : Physical Sciences and Engineering
Panel : Systems and communication engineering
Entité participante : Óbuda University — Pays : Hongrie — Rôle : PI
Type d'entité : Enseignement supérieur ou secondaire
Financement ERC de l'entité : 917925.0 €

Imagine if tumor growth would be reduced and then kept in a minimal and safe volume in an automated manner and in a personalized way, i.e. cancer drug would be injected using a continuous therapy improving the patient’s quality of life. By control engineering approaches it is possible to create model-based strategies for health problems. Artificial pancreas is an adequate example for this, where by continuous glucose measurement device and insulin pump it is possible to improve diabetes treatment. Gaining expertise from this problem, the current proposal focuses on taming the cancer by developing an engineering-based medical therapy. The interdisciplinary approach focuses on modern robust control algorithm development in order to stop the angiogenesis process (i.e. vascular system development) of the tumor; hence, to stop tumor growth, maintaining it in a minimal, “tamed” form. This breakthrough concept could revitalize cancer treatment. It is the right time to do it as some investigations regarding tumor growth modeling have been already done; now, it should be refined by model identification tools and validated on animal trials. The benefit of robust control was already demonstrated in artificial pancreas; hence, it could be adapted to cancer research. The result could end with a personalized healthcare approach for drug-delivery in cancer, improving quality of life, optimizing drug infusion and minimizing treatment costs. This interdisciplinary approach combines control engineering with mathematics, computer science and medical sciences. As a result, the model-based robust control approach envisage refining the currently existing tumor growth modeling aspects, design an optimal control algorithm and extend it by robust control theory to guarantee its general applicability. Based on our research background, validation will be done first in a manually controlled way, but then in an automatic mode to propose it for further human investigations.

Mots-clés : modern robust control,lpv model,model identification,targeted molecular therapy,antiangiogenic therapy
Projet ERC : CuHypMECH (Horizon 2020, appel 2017, Starting grants)
Domaine scientifique : Life Science
Panel : Prevention, Diagnosis and Treatment of Human Diseases
Entité participante : Bar-Ilan University — Pays : Israël — Rôle : PI
Acronyme de l'entité : BIU
Type d'entité : Enseignement supérieur ou secondaire
Financement ERC de l'entité : 1499345.0 €

Imaging of hypoxia is important in many disease states in oncology, cardiology, and neurology. Hypoxia is a common condition encountered within the tumour microenvironment that drives proliferation, angiogenesis, and resistance to therapy. Despite on-going efforts to identify hypoxia, until now there is no clinically approved imaging biomarker, due to both low tumour uptake, and a low signal to background (S/B) ratio that affects the imaging quality. Nuclear Medicine is using labelled radio-isotopes for PET/CT and SPECT imaging. These radio-tracers diagnose the metabolic processes in the body. Among these tracers, 18F-FDG is the most routinely used as a marker of glucose metabolism. However, not all tumours consume glucose, and glucose consumption is not specific only for malignant tumours, which limits its application. Copper is a nutritional metal, recently examined as a radiotracer for hypoxia, owing to its to the oxidising environment. Clinical and in-vivo studies on various 64Cu(II)-PET radiotracers resulted in controversial reports on the specificity of the current tracers for hypoxia imaging due to non-selective bio-distribution & low S/B ratio. This multidisciplinary proposal focuses on the discovery of comprehensive signal pathways of the cellular copper cycle using advanced biophysical methods and a proprietary design of 64Cu(II) radiotracer. This radiotracer will be incorporated in the cellular copper cycle, and will enable to selectively target the oxidising environment in tumours. The design of the new radiotracer is based on systematic structural & functional mapping of the copper binding sites to the various copper proteins and the visualisation of the transfer mechanism. This new copper tracer should increase the selectivity of tumour uptake, stability, and improve bio-distribution. This project assimilates cold and hot chemistry and biology, while emphasising the clinical unmet need in metal based radiotracer that form stable complexes.

Mots-clés : hypoxia,64cu ii  radiotracer,radiopharmaceuticals,cancer,copper cycle,spect,biophysics,copper homeostasis,neurological disorders,structural biology,chemical physics of biological
Projet ERC : SpreadMRI (Horizon 2020, appel 2018, Advanced grants)
Domaine scientifique : Life Science
Panel : Prevention, Diagnosis and Treatment of Human Diseases
Entité participante : Max Planck Society — Pays : Allemagne — Rôle : PI
Acronyme de l'entité : MPG
Type d'entité : Recherche
Financement ERC de l'entité : 2278760.0 €

Imaging speed is a key factor to capture rapid changes at high spatial and temporal resolution. A major limitation of magnetic resonance (MR) imaging is its rather low speed compared to other modalities like ultra sound or computerized tomography. We aim to explore two novel concepts to boost MR imaging speed by another order of magnitude compared to existing techniques. SpreadMRI fundamentally steps beyond current concepts of image encoding by exploiting a spectral spin modulation that so far has not been utilized. SpreadMRI is based on the rapid and local modulation of magnetic fields produced by current loops and/or radiofrequency (RF) loops. Applied spectral modulations are in the MHz range bridging the low-frequency band of switched gradients (kHz) and the 100 MHz range of the Larmor frequency. SpreadMRI spreads the bandwidth of gradient-encoded spin frequencies using distinct carrier frequencies originating from a certain region of the object. This spatially unique information will then be used to disentangle parts of the object, and thus to drastically boost imaging speed. Approaching this intermediate frequency band requires to address several basic research questions related to image reconstruction, electromagnetic coupling, spin Physics and possible biological effects. Based on theoretical analysis and exhaustive electromagnetic simulations of dedicated current loop and RF coil arrangements, including variants of different modulation patterns, several types of SpreadMRI coils for human head imaging at 9.4T will be developed and applied for high temporal and spatial functional brain imaging. The specific approach of SpreadMRI will lead to major changes in the hard- and software environment of current MR-scanners. It will not only provide new insight within the areas covered by the proposal, but will definitely benefit conventional MR diagnostic by enabling new applications with a simultaneous reduction of motion artifacts and increased patient throughput.

Mots-clés : magnetic resonance imaging,parallel imaging,medical imaging,ultra high field 9 4 tesla,radiofrequency coils
Projet ERC : DyNAmecs (Horizon 2020, appel 2019, Starting grants)
Domaine scientifique : Life Science
Panel : Integrative Biology: from Genes and Genomes to Systems
Entité participante : Centre national de la recherche scientifique — Pays : France — Rôle : PI
Acronyme de l'entité : CNRS
Type d'entité : Recherche
Financement ERC de l'entité : 1495480.0 €

Immediately after fertilization, mammalian genomes undergo a dramatic reshaping of the epigenome as the embryo transitions from the zygote into the pluripotent cells primed for lineage commitment. This is best exemplified by DNA methylation reprogramming, as the gametic patterns are largely erased, and the embryonic genome undergoes a wave of de novo DNA methylation. Moreover, once DNA methylation patterns are established, mechanisms faithfully maintain the mark across cell division. Thus, there is latent potential for DNA methylation deposited in the early embryo to exhibit a lifelong effect. DNA methylation is a modification that is typically associated with gene repression at repetitive elements and at a minority of protein coding genes. I previously described the regulation of the Zdbf2 gene in mice, which is programmed during the de novo DNA methylation program. Challenging the paradigm, in this case DNA methylation is required for activation of a gene via antagonism of the polycomb-group of silencing proteins. If the DNA methylation fails to occur, the gene stays silent throughout life, resulting in a reduced growth phenotype. For my proposed research I will utilize both a cell-based system that recapitulates these early embryonic events as well as an in vivo mouse model to investigate the extent and mechanisms of non-canonical DNA methylation functions. I plan to use a combinatorial approach of genomics, genetics, and proteomics in order to ascertain novel insights into DNA methylation-based regulation. Furthermore, I plan to employ precision epigenome editing tools to address the locus-specific impact of DNA methylation. Ultimately, I strive to gain a clear understanding of the profound epigenetic consequences of DNA methylation on this window of development, which occurs in the first week of mouse embryogenesis, and the second of human, but the repercussions of which can ripple throughout life.

Mots-clés : dna methylation,polycomb,epigenetics,mammalian development,embryonic stem cells
Projet ERC : CL-IO (Horizon 2020, appel 2018, Proof of concept grants)
Domaine scientifique : Life Science
Panel : Prevention, Diagnosis and Treatment of Human Diseases
Entité participante : Maastricht University — Pays : Pays-Bas — Rôle : PI
Acronyme de l'entité : UM
Type d'entité : Enseignement supérieur ou secondaire
Financement ERC de l'entité : 150000.0 €

Immunotherapeutic strategies are powerful weapons in combating malignancies. However, only a minority of patients benefit from this therapeutic modality, as tumours develop mechanisms of immune escape and suppression and uptake of (antibody-based) agents in tumors is limited. The urgency of investigating novel strategic approaches is dictated by the high incidence and mortality rates of cancer worldwide. Lung cancer, in particular, is the leading cancer with respect to incidence and mortality (14% of new cancers). In the ERC Advanced “HYPOXIMMUNO”, Prof. Lambin and his team have investigated the trimodal therapy involving high precision Stereotactic Radiotherapy, hypoxia/necrosis targeting and tumour specific immunotherapy (immunocytokine L19-IL2 to “push the accelerator” with a checkpoint inhibitor to “release the break”). Despite promising results, the delivery of immunotherapeutics to the tumour site has proven to be challenging. Prof. Lambin and his team have sought to overcome this limitation with the inclusion of genetically-modified Clostridium bacteria as optimal delivery system capable of effectively delivering immunotherapeutics within the tumour. These Clostridium-bacteria selectively colonise the hypoxic/necrotic regions present in solid tumours and act as cellular factories capable of continuously producing tumour-specific immunotherapies within the tumour (watch https://vimeo.com/251022032 ). In this ERC PoC project, a team of technological and commercial experts will investigate the commercial feasibility of this innovative approach. We will prepare the first steps towards the start-up of a spin-off, by defining the exact business strategy, model and positioning for commercial success. We will develop the business strategy based on the technological aspects, the market needs and trends, and the IP-position. During CL-IO, we will gain technical and commercial proof-of-concept, providing the necessary information for potential commercialisation routes.

Mots-clés : hypoxia,necrosis,cancer immunotherapy,immunocytokines,lung cancer,clostridium mediated cancer immunotherapy
Projet ERC : ARTimmune (Horizon 2020, appel 2018, Advanced grants)
Domaine scientifique : Life Science
Panel : Prevention, Diagnosis and Treatment of Human Diseases
Entité participante : Radboud University Nijmegen — Pays : Pays-Bas — Rôle : Partner
Type d'entité : Enseignement supérieur ou secondaire
Financement ERC de l'entité : 0.0 €

Immunotherapy has entered centre stage as a novel treatment modality for cancer. Notwithstanding this major step forward, toxicity and immunosuppression remain major obstacles, and illustrate the pressing need for more powerful and specific immunotherapies against cancer. To overcome these roadblocks, in ARTimmune, I propose to follow a radically different approach by developing local rather than systemic immunotherapies. Taking advantage of the architecture of a lymph node (LN), I aim to design fully synthetic immune niches to locally instruct immune cell function. I hypothesize that programmable synthetic immune niches, when injected next to a tumour, will act as local powerhouses to generate bursts of cytotoxic T cells for tumour destruction, without toxic side effects. Single cell transcriptomics on LN, obtained from patients that are vaccinated against cancer, will provide unique insight in communication within immune cell clusters and provide a blueprint for the intelligent design of synthetic immune niches. Chemical tools will be used to build branched polymeric structures decorated with immunomodulating molecules to mimic LN architecture. These will be injected, mixed with sponge-like scaffolds to provide porosity needed for immune cell infiltration. Programming of immune cell function will be accomplished by in vivo targeting- and proteolytic activation- of immunomodulators for fine-tuning, and to extend the life span of these local powerhouses. The innovative character of ARTimmune comes from: 1) novel fundamental immunological insight in complex communication within LN cell clusters, 2) a revolutionary new approach in immunotherapy, by the development of 3) injectable- and 4) programmable- synthetic immune niches by state-of-the-art chemical technology. When successful, it will revolutionize cancer immunotherapy, moving from maximal tolerable dose systemic treatment with significant toxicity to local low dose treatment in the direct vicinity of a tumour

Mots-clés : cancer immunotherapy,chemical engineering,artificial immune sytem,single cell,transcriptomics,3d polymer scaffolds
Projet ERC : STIMUNITY (Horizon 2020, appel 2016, Proof of concept grants)
Entité participante : Institut Curie — Pays : France — Rôle : PI
Type d'entité : Recherche
Financement ERC de l'entité : 150000.0 €

Immunotherapy is a promising approach to treat cancer and infectious diseases, but innovative approaches are required. The cGAS-cGAMP-STING pathway can induce a potent immune response against viruses. It is also implicated in antitumoral immune responses that are effective. We have recently discovered that the small second messenger cGAMP can be packaged by viruses to stimulate immunity in target cells. We have developed methods to produce non-infectious virus-like particles containing cGAMP (cGAMP-VLPs) that strongly stimulate this innovative immune pathway. We will test the idea that cGAMP-VLPs are potent activators of anti-tumoral and anti-viral immunity. To reach this proof-of-concept, we propose pre-clinical development plan in translational mouse models.

Mots-clés : innate immunity,immunotherapy,vaccine,virus like particles
Projet ERC : BoneImplant (Horizon 2020, appel 2015, Consolidator grants)
Domaine scientifique : Physical Sciences and Engineering
Panel : Products and processes engineering
Entité participante : Centre national de la recherche scientifique — Pays : France — Rôle : PI
Acronyme de l'entité : CNRS
Type d'entité : Recherche
Financement ERC de l'entité : 1992154.0 €

Implants are often employed in orthopaedic and dental surgeries. However, risks of failure, which are difficult to anticipate, are still experienced and may have dramatic consequences. Failures are due to degraded bone remodeling at the bone-implant interface, a multiscale phenomenon of an interdisciplinary nature which remains poorly understood. The objective of BoneImplant is to provide a better understanding of the multiscale and multitime mechanisms at work at the bone-implant interface. To do so, BoneImplant aims at studying the evolution of the biomechanical properties of bone tissue around an implant during the remodeling process. A methodology involving combined in vivo, in vitro and in silico approaches is proposed. New modeling approaches will be developed in close synergy with the experiments. Molecular dynamic computations will be used to understand fluid flow in nanoscopic cavities, a phenomenon determining bone healing process. Generalized continuum theories will be necessary to model bone tissue due to the important strain field around implants. Isogeometric mortar formulation will allow to simulate the bone-implant interface in a stable and efficient manner. In vivo experiments realized under standardized conditions will be realized on the basis of feasibility studies. A multimodality and multi-physical experimental approach will be carried out to assess the biomechanical properties of newly formed bone tissue as a function of the implant environment. The experimental approach aims at estimating the effective adhesion energy and the potentiality of quantitative ultrasound imaging to assess different biomechanical properties of the interface. Results will be used to design effective loading clinical procedures of implants and to optimize implant conception, leading to the development of therapeutic and diagnostic techniques. The development of quantitative ultrasonic techniques to monitor implant stability has a potential for industrial transfer.
Projet ERC : PANEDA (Horizon 2020, appel 2018, Consolidator grants)
Domaine scientifique : Social Sciences and Humanities
Panel : Individuals, Markets and Organisations
Entité participante : University of London — Pays : Royaume-Uni — Rôle : Partner
Acronyme de l'entité : U. London
Type d'entité : Enseignement supérieur ou secondaire
Financement ERC de l'entité : 442778.24 €

Improved data availability in Economics provides access to richer datasets with increased complexity. There is regularly a network aspect to the data, whenever outcomes are observed for matches of different economic units (e.g. households, individuals, firms, products, markets). Such observations include, e.g., wages for workers in firms, academic achievement for students taught by teachers in schools, and purchasing decisions for consumers in stores. The underlying network structure is often sparse, because we only observe a small subset of all possible matches, say between workers and firms. In addition, we aim to estimate models with many parameters, for example to control for and to estimate unobserved heterogeneity of economic units by including (e.g. worker and firm specific) fixed effects. The combination of sparsity of the underlying network structure and a large number of parameters in the model creates challenging Econometric problems. In particular, there is a serious gap between empirical practice, where applied researchers regularly use such sparse network datasets, and the theoretical justifications for those inference methods that are based on classic data structures (cross-sectional, time-series, and panel data) that do not account for the sparsity aspect of the data. The goal of this research project is to develop robust inference methods for such sparse panel and network datasets. This requires to establish a mathematical representation of the network that allows to formalize asymptotic inference results for sequences of growing networks. Subsequently, new bias correction and robust standard error estimation methods will be developed that account for the sparsity structure of the data. I will also advance more parsimonious modeling and estimation approaches (e.g. grouped heterogeneity or empirical Bayes) for situations where the data are otherwise uninformative for the parameters of interest.

Mots-clés : panel data,social networks,graph theory
Projet ERC : CrispSCNAs (Horizon 2020, appel 2020, Starting grants)
Domaine scientifique : Life Science
Panel : Physiology in Health, Disease and Ageing
Entité participante : University Hospital Heidelberg — Pays : Allemagne — Rôle : PI
Type d'entité : Enseignement supérieur ou secondaire
Financement ERC de l'entité : 1400000.0 €

In 1914 Theodor Boveri described abnormal chromosome counts in cancer cells and speculated that these alterations are the driving force of cancer. Almost 100 years later it became clear that somatic copy number alterations (SCNAs) are one of the most striking characteristics of cancer genomes. SCNAs comprise deletions and amplifications of whole chromosome arms and therefore alter the expression patterns of several hundred genes simultaneously. These alterations show defined patterns suggesting selective pressure, and thus likely contain multiple driver genes, which can shape several tumorigenic properties. Therefore, studying how these events contribute to tumor development will be fundamental to understand cancer biology and develop targeted cancer therapies. However, whereas the function of recurrently mutated driver genes can be readily assessed, studying SCNAs remains challenging so far. This project will overcome these limitations by combining our unique ability to model liver cancer in vivo and in vitro with innovative CRISPR-based genomic engineering technologies. First, we will generate large chromosomal deletions in murine livers and human-derived liver organoids by CRISPR technologies and assess their functional role in cancer development. Furthermore, synthetic lethal interactions generated by these deletions will be evaluated on their therapeutic potential. Additionally, driver genes and driver gene-combinations of amplified chromosomal regions will be investigated using a novel CRISPR/Cas9-based mouse model for endogenous gene activation and chromosome engineering. Finally, we will exploit a novel concept for targeting cancer cells with specific amplifications. Our unique approach will for the first time systematically investigate the functional role of SCNAs in tumor pathobiology, identify new therapeutic strategies specifically tailored for individual SCNAs, and will therefore have high impact for future efforts to understand and combat cancer.

Mots-clés : liver cancer,mouse models,somatic copy number alterations,pathology,crispr,cas9,functional genomics