Project acronym ABC
Project Targeting Multidrug Resistant Cancer
Researcher (PI) Gergely Szakacs
Host Institution (HI) MAGYAR TUDOMANYOS AKADEMIA TERMESZETTUDOMANYI KUTATOKOZPONT
Call Details Starting Grant (StG), LS7, ERC-2010-StG_20091118
Summary Despite considerable advances in drug discovery, resistance to anticancer chemotherapy confounds the effective treatment of patients. Cancer cells can acquire broad cross-resistance to mechanistically and structurally unrelated drugs. P-glycoprotein (Pgp) actively extrudes many types of drugs from cancer cells, thereby conferring resistance to those agents. The central tenet of my work is that Pgp, a universally accepted biomarker of drug resistance, should in addition be considered as a molecular target of multidrug-resistant (MDR) cancer cells. Successful targeting of MDR cells would reduce the tumor burden and would also enable the elimination of ABC transporter-overexpressing cancer stem cells that are responsible for the replenishment of tumors. The proposed project is based on the following observations:
- First, by using a pharmacogenomic approach, I have revealed the hidden vulnerability of MDRcells (Szakács et al. 2004, Cancer Cell 6, 129-37);
- Second, I have identified a series of MDR-selective compounds with increased toxicity toPgp-expressing cells
(Turk et al.,Cancer Res, 2009. 69(21));
- Third, I have shown that MDR-selective compounds can be used to prevent theemergence of MDR (Ludwig, Szakács et al. 2006, Cancer Res 66, 4808-15);
- Fourth, we have generated initial pharmacophore models for cytotoxicity and MDR-selectivity (Hall et al. 2009, J Med Chem 52, 3191-3204).
I propose a comprehensive series of studies that will address thefollowing critical questions:
- First, what is the scope of MDR-selective compounds?
- Second, what is their mechanism of action?
- Third, what is the optimal therapeutic modality?
Extensive biological, pharmacological and bioinformatic analyses will be utilized to address four major specific aims. These aims address basic questions concerning the physiology of MDR ABC transporters in determining the mechanism of action of MDR-selective compounds, setting the stage for a fresh therapeutic approach that may eventually translate into improved patient care.
Summary
Despite considerable advances in drug discovery, resistance to anticancer chemotherapy confounds the effective treatment of patients. Cancer cells can acquire broad cross-resistance to mechanistically and structurally unrelated drugs. P-glycoprotein (Pgp) actively extrudes many types of drugs from cancer cells, thereby conferring resistance to those agents. The central tenet of my work is that Pgp, a universally accepted biomarker of drug resistance, should in addition be considered as a molecular target of multidrug-resistant (MDR) cancer cells. Successful targeting of MDR cells would reduce the tumor burden and would also enable the elimination of ABC transporter-overexpressing cancer stem cells that are responsible for the replenishment of tumors. The proposed project is based on the following observations:
- First, by using a pharmacogenomic approach, I have revealed the hidden vulnerability of MDRcells (Szakács et al. 2004, Cancer Cell 6, 129-37);
- Second, I have identified a series of MDR-selective compounds with increased toxicity toPgp-expressing cells
(Turk et al.,Cancer Res, 2009. 69(21));
- Third, I have shown that MDR-selective compounds can be used to prevent theemergence of MDR (Ludwig, Szakács et al. 2006, Cancer Res 66, 4808-15);
- Fourth, we have generated initial pharmacophore models for cytotoxicity and MDR-selectivity (Hall et al. 2009, J Med Chem 52, 3191-3204).
I propose a comprehensive series of studies that will address thefollowing critical questions:
- First, what is the scope of MDR-selective compounds?
- Second, what is their mechanism of action?
- Third, what is the optimal therapeutic modality?
Extensive biological, pharmacological and bioinformatic analyses will be utilized to address four major specific aims. These aims address basic questions concerning the physiology of MDR ABC transporters in determining the mechanism of action of MDR-selective compounds, setting the stage for a fresh therapeutic approach that may eventually translate into improved patient care.
Max ERC Funding
1 499 640 €
Duration
Start date: 2012-01-01, End date: 2016-12-31
Project acronym HIGHACCTC
Project High-accuracy models in theoretical chemistry
Researcher (PI) Mihály Kállay
Host Institution (HI) BUDAPESTI MUSZAKI ES GAZDASAGTUDOMANYI EGYETEM
Call Details Starting Grant (StG), PE4, ERC-2007-StG
Summary Even today, quantum chemical calculations with experimental accuracy are only feasible for small molecules. This statement is especially true if the considered molecule is far from the equilibrium structure, where the overwhelming majority of quantum chemical models break down. The main purpose of this proposal is to develop new quantum chemical methods that are applicable to at least medium-sized molecules and simultaneously provide results sufficiently close to the experimental data and are capable of describing entire potential energy surfaces. The accuracy goal will be achieved through the reduction of the computational cost of high-precision quantum chemical calculations, which are currently practical for molecules of up to 15 atoms. The cost reduction will be accomplished principally by decreasing the number of numerical parameters to be optimized without sacrificing accuracy. To this end, the negligible parameters will be identified and dropped by adopting the corresponding techniques of computer science. The correct behavior of the models for distorted structures will be ensured by developing new approaches that use a linear combination of functions rather than a single function as a starting point for the description of electronic states. Since the programming work associated with the implementation of the proposed schemes is very complex, the project will rely on the automated programming tools previously developed by the proposer. In addition to the outlined challenging tasks, the proposal aims to implement several more straightforward objectives. In particular, the high-accuracy calculations will be extended to molecular properties that are presently not available. Furthermore, the developed methods will be applied to real-life problems, especially in the field of spectroscopy and atmospheric chemistry.
Summary
Even today, quantum chemical calculations with experimental accuracy are only feasible for small molecules. This statement is especially true if the considered molecule is far from the equilibrium structure, where the overwhelming majority of quantum chemical models break down. The main purpose of this proposal is to develop new quantum chemical methods that are applicable to at least medium-sized molecules and simultaneously provide results sufficiently close to the experimental data and are capable of describing entire potential energy surfaces. The accuracy goal will be achieved through the reduction of the computational cost of high-precision quantum chemical calculations, which are currently practical for molecules of up to 15 atoms. The cost reduction will be accomplished principally by decreasing the number of numerical parameters to be optimized without sacrificing accuracy. To this end, the negligible parameters will be identified and dropped by adopting the corresponding techniques of computer science. The correct behavior of the models for distorted structures will be ensured by developing new approaches that use a linear combination of functions rather than a single function as a starting point for the description of electronic states. Since the programming work associated with the implementation of the proposed schemes is very complex, the project will rely on the automated programming tools previously developed by the proposer. In addition to the outlined challenging tasks, the proposal aims to implement several more straightforward objectives. In particular, the high-accuracy calculations will be extended to molecular properties that are presently not available. Furthermore, the developed methods will be applied to real-life problems, especially in the field of spectroscopy and atmospheric chemistry.
Max ERC Funding
500 000 €
Duration
Start date: 2008-07-01, End date: 2013-06-30
Project acronym INTERIMPACT
Project Impact of identified interneurons on cellular network mechanisms in the human and rodent neocortex
Researcher (PI) Gábor Tamás
Host Institution (HI) Szegedi Tudomanyegyetem - Hungarian-Netherlands School of Educational Management
Call Details Advanced Grant (AdG), LS5, ERC-2010-AdG_20100317
Summary This application addresses mechanisms linking the activity of single neurons with network events by defining the function of identified cell types in the cerebral cortex. The key hypotheses emerged from our experiments and propose that neurogliaform cells and axo-axonic cells achieve their function in the cortex through extreme forms of unspecificity and specificity, respectively. The project capitalizes on our discovery that neurogliaform cells reach GABAA and GABAB receptors on target cells through unitary volume transmission going beyond the classical theory which states that single cortical neurons act in or around synaptic junctions. We propose that the spatial unspecificity of neurotransmitter action leads to unprecedented functional capabilities for a single neuron simultaneously acting on neuronal, glial and vascular components of the surrounding area allowing neurogliaform cells to synchronize metabolic demand and supply in microcircuits. In contrast, axo-axonic cells represent extreme spatial specificity in the brain: terminals of axo-axonic cells exclusively target the axon initial segment of pyramidal neurons. Axo-axonic cells were considered as the most potent inhibitory neurons of the cortex. However, our experiments suggested that axo-axonic cells can be the most powerful excitatory neurons known to date by triggering complex network events. Our unprecedented recordings in the human cortex show that axo-axonic cells are crucial in activating functional assemblies which were implicated in higher order cognitive representations. We aim to define interactions between active cortical networks and axo-axonic cell triggered assemblies with an emphasis on mechanisms modulated by neurogliaform cells and commonly prescribed drugs.
Summary
This application addresses mechanisms linking the activity of single neurons with network events by defining the function of identified cell types in the cerebral cortex. The key hypotheses emerged from our experiments and propose that neurogliaform cells and axo-axonic cells achieve their function in the cortex through extreme forms of unspecificity and specificity, respectively. The project capitalizes on our discovery that neurogliaform cells reach GABAA and GABAB receptors on target cells through unitary volume transmission going beyond the classical theory which states that single cortical neurons act in or around synaptic junctions. We propose that the spatial unspecificity of neurotransmitter action leads to unprecedented functional capabilities for a single neuron simultaneously acting on neuronal, glial and vascular components of the surrounding area allowing neurogliaform cells to synchronize metabolic demand and supply in microcircuits. In contrast, axo-axonic cells represent extreme spatial specificity in the brain: terminals of axo-axonic cells exclusively target the axon initial segment of pyramidal neurons. Axo-axonic cells were considered as the most potent inhibitory neurons of the cortex. However, our experiments suggested that axo-axonic cells can be the most powerful excitatory neurons known to date by triggering complex network events. Our unprecedented recordings in the human cortex show that axo-axonic cells are crucial in activating functional assemblies which were implicated in higher order cognitive representations. We aim to define interactions between active cortical networks and axo-axonic cell triggered assemblies with an emphasis on mechanisms modulated by neurogliaform cells and commonly prescribed drugs.
Max ERC Funding
2 391 695 €
Duration
Start date: 2011-06-01, End date: 2017-05-31
Project acronym NETWORK EVOLUTION
Project Integrated evolutionary analyses of genetic and drug interaction networks in yeast
Researcher (PI) Csaba Pal
Host Institution (HI) MAGYAR TUDOMANYOS AKADEMIA SZEGEDIBIOLOGIAI KUTATOKOZPONT
Call Details Starting Grant (StG), LS5, ERC-2007-StG
Summary The ability of cellular systems to adapt to genetic and environmental perturbations is a fundamental but poorly understood process both at the molecular and evolutionary level. There are both physiological and evolutionary reasonings why mutations often have limited impact on cellular growth. First, perturbations that hit one target often have no effect on the overall performance of a complex system (such as metabolic networks), as perturbations can be adjusted by reorganizing fluxes in metabolic networks, or changing regulation and expression of genes. Second, due to the fast evolvability of microbes, the effect of a perturbation can readily be alleviated by the evolution of compensatory mutations at other sites of the network. Understanding the extent of intrinsic and evolved robustness in cellular systems demands integrated analyses that combine functional genomics and computational systems biology with microbial evolutionary experiments. In collaboration with several leading research teams in the field, we plan to investigate the following issues. First, we will ask how accurately genome-scale metabolic network models can predict the impact of genetic deletions and other non-heritable perturbations. Second, to understand how the impact of genetic and drug perturbations can be mitigated during evolution, we will pursue a large-scale lab evolutionary protocol, and compare the results with predictions of computational models. Our work may suggest avenues of research on the general rules of acquired drug resistance in microbes.
Summary
The ability of cellular systems to adapt to genetic and environmental perturbations is a fundamental but poorly understood process both at the molecular and evolutionary level. There are both physiological and evolutionary reasonings why mutations often have limited impact on cellular growth. First, perturbations that hit one target often have no effect on the overall performance of a complex system (such as metabolic networks), as perturbations can be adjusted by reorganizing fluxes in metabolic networks, or changing regulation and expression of genes. Second, due to the fast evolvability of microbes, the effect of a perturbation can readily be alleviated by the evolution of compensatory mutations at other sites of the network. Understanding the extent of intrinsic and evolved robustness in cellular systems demands integrated analyses that combine functional genomics and computational systems biology with microbial evolutionary experiments. In collaboration with several leading research teams in the field, we plan to investigate the following issues. First, we will ask how accurately genome-scale metabolic network models can predict the impact of genetic deletions and other non-heritable perturbations. Second, to understand how the impact of genetic and drug perturbations can be mitigated during evolution, we will pursue a large-scale lab evolutionary protocol, and compare the results with predictions of computational models. Our work may suggest avenues of research on the general rules of acquired drug resistance in microbes.
Max ERC Funding
1 280 000 €
Duration
Start date: 2008-07-01, End date: 2013-06-30
