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HUJI

Hebrew University of Jerusalem
Country: Israel
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522 Projects, page 1 of 105
  • Funder: EC Project Code: 247471
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  • Funder: EC Project Code: 758735
    Overall Budget: 1,500,000 EURFunder Contribution: 1,500,000 EUR

    Recent advances have shown that therapeutic manipulations of key cell-cell interactions can have dramatic clinical outcomes. Most notable are several early successes in cancer immunotherapy that target the tumor-T cell interface. However, these successes were only partial. This is likely because the few known interactions are just a few pieces of a much larger puzzle, involving additional signaling molecules and cell types. Dendritic cells (DCs), play critical roles in the induction/suppression of T cells. At early cancer stages, DCs capture tumor antigens and present them to T cells. However, in advanced cancers, the tumor microenvironment (TME) disrupts the crosstalk between DCs and T cells. We will take a multi-step approach to explore how the TME imposes a suppressive effect on DCs and how to reverse this hazardous effect. First, we will use single cell RNA-seq to search for genes in aggressive human and mouse ovarian tumors that are highly expressed in advanced tumors compared to early tumors and that encode molecules that suppress DC activity. Second, we will design a set of CRISPR screens to find genes that are expressed in DCs and regulate the transfer of the suppressive signals. The screens will be performed in the presence of suppressive molecules to mimic the TME and are expected to uncover many key genes in DCs biology. We will develop a new strategy to find synergistic combinations of genes to target (named Perturb-comb), thereby reversing the effect of local tumor immunosuppressive signals. Lastly, we will examine the effect of modified DCs on T cell activation and proliferation in-vivo, and on tumor growth. We expect to find: (1) Signaling molecules in the TME that affect the immune system. (2) New cytokines and cell surface receptors that are expressed in DCs and signal to T cells. (3) New key regulators in DC biology and their mechanisms. (4) Combinations of genes to target in DCs that reverse the TME’s hazardous effects.

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  • Funder: EC Project Code: 101039914
    Overall Budget: 1,439,410 EURFunder Contribution: 1,439,410 EUR

    Modern data analysis and optimization rely on our ability to process rapidly evolving dynamic datasets, often involving matrix operations in very high dimensions. Dynamic data structures enable fast information-retrieval on these huge databases by maintain- ing implicit information on the underlying data. As such, understanding the power and limitations of dynamic (matrix) data structures is a fundamental question in theory and practice. Despite decades of research, there are still very basic dynamic problems whose complexity is (exponen- tially) far from understood – Bridging this gap is one of the centerpieces of this proposal. The second theme of this proposal is advancing the nascent role of dynamic data structures in continuous optimization. For over a century, the traditional focus of optimization research was on minimizing the rate of convergence of local-search methods. The last ∼3 years have witnessed the dramatic potential of dynamic data structures in reducing the cost-per-iteration of (Newton type) optimization algorithms, proclaiming that the bottleneck to accelerating literally thousands of algorithms, is efficient maintenance of dynamic matrix functions. This new framework is only at its early stages, but already led to breakthroughs on decade-old problems in computer science. This proposal will substantially develop this interdisciplinary theory, and identifies the mathematical machinery which would lead to ultra-fast first and second-order convex optimization. In the non-convex setting, this proposal demonstrates the game-changing potential of dynamic data structures and algebraic sketching techniques in achieving scalable training and inference of deep neural networks, a major challenge of modern AI. Our program is based on a novel connection of Kernel methods and compressed sensing techniques for approximate matrix multiplication.

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  • Funder: EC Project Code: 629304
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  • Funder: EC Project Code: 863809
    Overall Budget: 1,998,750 EURFunder Contribution: 1,998,750 EUR

    Viruses are absolute parasites as their replication depends on biochemical systems of their host. Because viral infections reduce the fitness of the host organism, hosts and viruses have been tangled in an evolutionary arms race for survival from the very beginning of life. As the immune system allows organisms to identify and eliminate viral infections, it is of pivotal importance for host fitness. In vertebrates, the antiviral immunity is heavily based on the interferon pathway that enables infected cells to alert neighbouring cells against incoming infection and recruits cells of the immune system to battle the virus. However, in the case of invertebrates, which lack interferons, the antiviral immunity is believed to be based mostly on an RNA interference (RNAi) that cleaves viral RNA. Until now, the recognition mechanism and mode of action of such systems were studied mostly in vertebrates, insects and nematodes. From this limited phyletic sampling, it is impossible to deduce what was the original mode of action of these systems in their last common ancestor and how antiviral immunity was triggered in early animals. To attain novel insights into the early evolution of this crucial system, I propose to study it in an outgroup: the sea anemone Nematostella vectensis, a representative model species of Cnidaria, a phylum that diverged approximately 600 million years ago from the rest of animals. Beyond its key phyletic position, Nematostella is a tractable lab model with available advanced molecular and gene manipulation tools making it an excellent comparative model. I will harness these tools to decipher the cnidarian system for battling RNA viruses and answer the outstanding questions regarding the evolution of antiviral immunity and its ancestral state in animals. My preliminary results put in question the textbook dichotomy between the antiviral immune systems of vertebrates and invertebrates as I find active components of both systems in Nematostella.

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