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8 Projects

  • Canada
  • 2012-2021
  • 2015
  • 2021

  • Funder: EC Project Code: 634935
    Overall Budget: 6,460,000 EURFunder Contribution: 6,200,000 EUR

    Breast cancer affects more than 360,000 women per year in the EU and causes more than 90,000 deaths. Identification of women at high risk of the disease can lead to disease prevention through intensive screening, chemoprevention or prophylactic surgery. Breast cancer risk is determined by a combination of genetic and lifestyle risk factors. The advent of next generation sequencing has opened up the opportunity for testing in many disease genes, and diagnostic gene panel testing is being introduced in many EU countries. However, the cancer risks associated with most variants in most genes are unknown. This leads to a major problem in appropriate counselling and management of women undergoing panel testing. In this project, we aim to build a knowledge base that will allow identification of women at high-risk of breast cancer, in particular through comprehensive evaluation of DNA variants in known and suspected breast cancer genes. We will exploit the huge resources established through the Breast Cancer Association Consortium (BCAC) and ENIGMA (Evidence-based Network for the Interpretation of Germline Mutant Alleles). We will expand the existing datasets by sequencing all known breast cancer susceptibility genes in 20,000 breast cancer cases and 20,000 controls from population-based studies, and 10,000 cases from multiple case families. Sequence data will be integrated with in-silico and functional data, with data on other known risk factors, to generate a comprehensive risk model that can provide personalised risk estimates. We will develop online tools to aid the interpretation of gene variants and provide risk estimates in a user-friendly format, to help genetic counsellors and patients worldwide to make informed clinical decisions. We will evaluate the acceptability and utility of comprehensive gene panel testing in the clinical genetics context.

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  • Funder: EC Project Code: 643417
    Overall Budget: 30,953,000 EURFunder Contribution: 10,000,000 EUR

    Over 12 million people in Europe suffer from neurodegenerative diseases (ND), yet treatments that prevent or stop the progression of neurodegeneration are still lacking. Tackling this grand challenge requires enhanced coordination of national efforts to accelerate discovery. Such synergies have been created among 28 countries in the pilot EU JPI on Neurodegenerative Disease Research (JPND). JPND has a long standing experience in collaborative action with €75 million of additional national funds being successfully mobilized between 2011 and 2014 to support transnational research programs. The JPND Research Strategy is now ripe for further enhancement in tight coordination with the EC through an ERA-Net Cofund instrument JPco-fuND with an unprecedented commitment of €30 million of national funds associated to a highly incentivizing EC top-up fund. Among the most burning questions, three priority topics have emerged through a consultative process between researchers and JPND members in order to unlock several major issues within ND research: the identification of genetic, epigenetic and environmental risk and protective factors, the development and maintenance of longitudinal cohorts, the creation of advanced experimental models. These are key questions of equal priority to increase understanding of ND mechanisms that will be addressed through a common joint transnational call allowing a significant acceleration of the execution of the JPND research strategy. Moreover, to expand the impact of JPco-fuND, JPND will continue to implement other actions without EU co-funding such as aligning national research strategies, making databases more accessible and interoperable, developing enabling capacities such as supportive infrastructure and platforms, capacity building, education and training. These actions are required in parallel to achieve the highest impact for the patients, their carers and for society as whole and address this grand challenge in the coming years.

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  • Funder: UKRI Project Code: NE/M021025/1
    Funder Contribution: 1,473,360 GBP

    Concerns are growing about how much melting occurs on the surface of the Greenland Ice Sheet (GrIS), and how much this melting will contribute to sea level rise (1). It seems that the amount of melting is accelerating and that the impact on sea level rise is over 1 mm each year (2). This information is of concern to governmental policy makers around the world because of the risk to viability of populated coastal and low-lying areas. There is currently a great scientific need to predict the amount of melting that will occur on the surface of the GrIS over the coming decades (3), since the uncertainties are high. The current models which are used to predict the amount of melting in a warmer climate rely heavily on determining the albedo, the ratio of how reflective the snow cover and the ice surface are to incoming solar energy. Surfaces which are whiter are said to have higher albedo, reflect more sunlight and melt less. Surfaces which are darker adsorb more sunlight and so melt more. Just how the albedo varies over time depends on a number of factors, including how wet the snow and ice is. One important factor that has been missed to date is bio-albedo. Each drop of water in wet snow and ice contains thousands of tiny microorganisms, mostly algae and cyanobacteria, which are pigmented - they have a built in sunblock - to protect them from sunlight. These algae and cyanobacteria have a large impact on the albedo, lowering it significantly. They also glue together dust particles that are swept out of the air by the falling snow. These dust particles also contain soot from industrial activity and forest fires, and so the mix of pigmented microbes and dark dust at the surface produces a darker ice sheet. We urgently need to know more about the factors that lead to and limit the growth of the pigmented microbes. Recent work by our group in the darkest zone of the ice sheet surface in the SW of Greenland shows that the darkest areas have the highest numbers of cells. Were these algae to grow equally well in other areas of the ice sheet surface, then the rate of melting of the whole ice sheet would increase very quickly. A major concern is that there will be more wet ice surfaces for these microorganisms to grow in, and for longer, during a period of climate warming, and so the microorganisms will grow in greater numbers and over a larger area, lowering the albedo and increasing the amount of melt that occurs each year. The nutrient - plant food - that the microorganisms need comes from the ice crystals and dust on the ice sheet surface, and there are fears that increased N levels in snow and ice may contribute to the growth of the microorganisms. This project aims to be the first to examine the growth and spread of the microorganisms in a warming climate, and to incorporate biological darkening into models that predict the future melting of the GrIS. References 1. Sasgen I and 8 others. Timing and origin of recent regional ice-mass loss in Greenland. Earth and Planetary Science Letters, 333-334, 293-303(2012). 2. Rignot, E., Velicogna, I., van den Broeke, M. R., Monaghan, A. & Lenaerts, J. Acceleration of the contribution of the Greenland and Antarctic ice sheets to sea level rise. Geophys. Res. Lett. 38, L05503, doi:10.1029/2011gl046583 (2011). 3. Milne, G. A., Gehrels, W. R., Hughes, C. W. & Tamisiea, M. E. Identifying the causes of sea-level change. Nature Geosci 2, 471-478 (2009).

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  • Funder: EC Project Code: 638273
    Overall Budget: 1,436,290 EURFunder Contribution: 1,436,290 EUR

    Enhancers control the correct spatio-temporal activation of gene expression. A comprehensive characterization of the properties and regulatory activities of enhancers as well as their target genes is therefore crucial to understand the regulation and dysregulation of differentiation, homeostasis and cell type specificity. Genome-wide chromatin assays have provided insight into the properties and complex architectures by which enhancers regulate genes, but the understanding of their mechanisms is fragmented and their regulatory targets are mostly unknown. Several factors may confound the inference and interpretation of regulatory enhancer activity. There are likely many kinds of regulatory architectures with distinct levels of output and flexibility. Despite this, most state-of-the-art genome-wide studies only consider a single model. In addition, chromatin-based analysis alone does not provide clear insight into function or activity. This project aims to systematically characterize enhancer architectures and delineate what determines their: (1) restricted spatio-temporal activity; (2) robustness to regulatory genetic variation; and (3) dynamic activities over time. My work has shown enhancer transcription to be the most accurate classifier of enhancer activity to date. This data permits unprecedented modeling of regulatory architectures via enhancer-promoter co-expression linking. Careful computational analysis of such data from appropriate experimental systems has a great potential for distinguishing the different modes of regulation and their functional impact. The outcomes have great potential for providing us with new insights into mechanisms of transcriptional regulation. The results will be particularly relevant to interpretation of regulatory genetic variations. Ultimately, knowing the characteristics and conformations of enhancer architectures will increase our ability to link variation in non-coding DNA to phenotypic outcomes like disease susceptibility.

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  • Funder: UKRI Project Code: EP/M019918/1
    Funder Contribution: 4,991,610 GBP

    VISION: To create, run and exploit the world's leading research programme in mobile autonomy addressing fundamental technical issues which impede large scale commercial and societal adoption of mobile robotics. AMBITION: We need to build better robots - we need them to be cheap, work synergistically with people in large, complex and time-changing environments and do so for long periods of time. Moreover, it is essential that they are safe and trusted. We are compelled as researchers to produce the foundational technologies that will see robots work in economically and socially important domains. These motivations drive the science in this proposal. STRATEGY: Robotics is fast advancing to a point where autonomous systems can add real value to the public domain. The potential reach of mobile robotics in particular is vast, covering sectors as diverse as transport, logistics, space, defence, agriculture and infrastructure management. In order to realise this potential we need our robots to be cheap, work synergistically with people in large, complex and time-changing environments and do so robustly for long periods of time. Our aim, therefore, is to create a lasting, catalysing impact on UKPLC by growing a sustainable centre of excellence in mobile autonomy. A central tenet to this research is that the capability gap between the state of the art and what is needed is addressed by designing algorithms that leverage experiences gained through real and continued world use. Our machines will operate in support of humans and seamlessly integrate into complex cyber-physical systems with a variety of physical and computational elements. We must, therefore, be able to guarantee, and even certify, that the software that controls the robots is safe and trustworthy by design. We will engage in this via a range of flagship technology demonstrators in different domains (transport, logistics, space, etc.), which will mesh the research together, giving at once context, grounding, validation and impact.

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  • Funder: NSF Project Code: 1614036
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  • Funder: EC Project Code: 633190
    Overall Budget: 8,263,200 EURFunder Contribution: 5,998,990 EUR

    Parkinson’s disease (PD) is a major, chronic, non-communicable disease and the 2nd most frequent neurodegenerative disorder worldwide. Excess iron is primarily detected in the substantia nigra pars compacta, where dopaminergic neurons are exposed to high levels of oxidative stress produced by mitochondrial disorders and dopamine metabolism. Our previous preclinical, translational and pilot clinical studies demonstrated that novel iron chelation therapy with the prototypic drug deferiprone (DFP) (i) induces neuroprotection in cell models of PD via a powerful antioxidant effect, (ii) reduces regional siderosis of the brain, (iii) reduces motor handicap via inhibition of catechol-o-methyl transferase, and (iv) slows the progression of motor handicap in the 1-methyl-4-phenyl-1,2,3,6-tetrahydropyridine mouse model and in early PD patients. This project now seeks to demonstrate that conservative iron chelation therapy with moderate-dose DFP (30 mg/kg/day) slows the progression of handicap in de novo PD patients while not affecting systemic parameters. The 9-month, parallel-group, randomized, placebo-controlled, multicentre trial will be followed by a 1-month wash-out period. The primary efficacy criterion will be the change in motor and non-motor handicap scores on the Total Movement Disorders Society Unified Parkinson’s Disease Rating Scale to identify disease-modifying and symptomatic effects. The secondary efficacy criterion will be the change in score between baseline and 40 weeks (i.e. probing the disease-modifying effect only). Potential surrogate radiological and biological biomarkers, health economics and societal impacts will be assessed. 17 national, European and international research and innovation activities will be linked with the project. The study results should prompt academic and industrial research on iron chelation as a disease-modifying treatment in neurodegenerative diseases.

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  • Funder: EC Project Code: 633784
    Overall Budget: 6,120,860 EURFunder Contribution: 5,983,360 EUR

    Breast tumours are heterogeneous, and result from the complex interplay of multiple lifestyle/environmental and genetic risk factors. Through the EU-funded COGS project, we have identified a large number of germline variants that influence the risk of breast cancer. In combination, these variants can identify women at wide ranges of genetic risk, even in the absence of family history of breast cancer. Given that breast cancer is not one disease, it is now essential to better understand how risk factors act together to influence the development of pathologic-molecular subtypes of breast cancer. The aim of B-CAST is to identify women at moderate to high risk of breast cancer, the subtype of cancer that is most likely to develop and the prognosis of that particular subtype. This will be accomplished through large-scale pathologic-molecular analyses of over 20,000 breast tumours, and the integration of these data with unique resources from existing consortia, including germline, lifestyle/environmental, mammographic breast density, pathologic and clinical data. This information will inform the development of risk prediction and prognostication models that will be validated in longitudinal cohorts and clinical studies, and incorporated into online tools. We will also disseminate this knowledge to relevant stakeholders, and evaluate how to translate it into risk-stratified public health and clinical strategies. The current challenge for optimised prevention, early detection, and treatment decisions for breast cancer is understanding the genetic and lifestyle determinants of risk and prognosis of molecular subtypes. B-CAST will add to this understanding and will have immediate application with benefits to women by providing validated risk and prognostication tools. This will empower women and doctors with knowledge to tailor strategies for prevention and treatment. Ultimately, this work should result in reductions in the occurrence, morbidity and mortality of this disease.

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The following results are related to Canada. Are you interested to view more results? Visit OpenAIRE - Explore.
8 Projects
  • Funder: EC Project Code: 634935
    Overall Budget: 6,460,000 EURFunder Contribution: 6,200,000 EUR

    Breast cancer affects more than 360,000 women per year in the EU and causes more than 90,000 deaths. Identification of women at high risk of the disease can lead to disease prevention through intensive screening, chemoprevention or prophylactic surgery. Breast cancer risk is determined by a combination of genetic and lifestyle risk factors. The advent of next generation sequencing has opened up the opportunity for testing in many disease genes, and diagnostic gene panel testing is being introduced in many EU countries. However, the cancer risks associated with most variants in most genes are unknown. This leads to a major problem in appropriate counselling and management of women undergoing panel testing. In this project, we aim to build a knowledge base that will allow identification of women at high-risk of breast cancer, in particular through comprehensive evaluation of DNA variants in known and suspected breast cancer genes. We will exploit the huge resources established through the Breast Cancer Association Consortium (BCAC) and ENIGMA (Evidence-based Network for the Interpretation of Germline Mutant Alleles). We will expand the existing datasets by sequencing all known breast cancer susceptibility genes in 20,000 breast cancer cases and 20,000 controls from population-based studies, and 10,000 cases from multiple case families. Sequence data will be integrated with in-silico and functional data, with data on other known risk factors, to generate a comprehensive risk model that can provide personalised risk estimates. We will develop online tools to aid the interpretation of gene variants and provide risk estimates in a user-friendly format, to help genetic counsellors and patients worldwide to make informed clinical decisions. We will evaluate the acceptability and utility of comprehensive gene panel testing in the clinical genetics context.

    visibility4K
    visibilityviews3,905
    downloaddownloads8,876
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    more_vert
  • Funder: EC Project Code: 643417
    Overall Budget: 30,953,000 EURFunder Contribution: 10,000,000 EUR

    Over 12 million people in Europe suffer from neurodegenerative diseases (ND), yet treatments that prevent or stop the progression of neurodegeneration are still lacking. Tackling this grand challenge requires enhanced coordination of national efforts to accelerate discovery. Such synergies have been created among 28 countries in the pilot EU JPI on Neurodegenerative Disease Research (JPND). JPND has a long standing experience in collaborative action with €75 million of additional national funds being successfully mobilized between 2011 and 2014 to support transnational research programs. The JPND Research Strategy is now ripe for further enhancement in tight coordination with the EC through an ERA-Net Cofund instrument JPco-fuND with an unprecedented commitment of €30 million of national funds associated to a highly incentivizing EC top-up fund. Among the most burning questions, three priority topics have emerged through a consultative process between researchers and JPND members in order to unlock several major issues within ND research: the identification of genetic, epigenetic and environmental risk and protective factors, the development and maintenance of longitudinal cohorts, the creation of advanced experimental models. These are key questions of equal priority to increase understanding of ND mechanisms that will be addressed through a common joint transnational call allowing a significant acceleration of the execution of the JPND research strategy. Moreover, to expand the impact of JPco-fuND, JPND will continue to implement other actions without EU co-funding such as aligning national research strategies, making databases more accessible and interoperable, developing enabling capacities such as supportive infrastructure and platforms, capacity building, education and training. These actions are required in parallel to achieve the highest impact for the patients, their carers and for society as whole and address this grand challenge in the coming years.

    visibility4K
    visibilityviews3,710
    downloaddownloads6,252
    Powered by Usage counts
    more_vert
  • Funder: UKRI Project Code: NE/M021025/1
    Funder Contribution: 1,473,360 GBP

    Concerns are growing about how much melting occurs on the surface of the Greenland Ice Sheet (GrIS), and how much this melting will contribute to sea level rise (1). It seems that the amount of melting is accelerating and that the impact on sea level rise is over 1 mm each year (2). This information is of concern to governmental policy makers around the world because of the risk to viability of populated coastal and low-lying areas. There is currently a great scientific need to predict the amount of melting that will occur on the surface of the GrIS over the coming decades (3), since the uncertainties are high. The current models which are used to predict the amount of melting in a warmer climate rely heavily on determining the albedo, the ratio of how reflective the snow cover and the ice surface are to incoming solar energy. Surfaces which are whiter are said to have higher albedo, reflect more sunlight and melt less. Surfaces which are darker adsorb more sunlight and so melt more. Just how the albedo varies over time depends on a number of factors, including how wet the snow and ice is. One important factor that has been missed to date is bio-albedo. Each drop of water in wet snow and ice contains thousands of tiny microorganisms, mostly algae and cyanobacteria, which are pigmented - they have a built in sunblock - to protect them from sunlight. These algae and cyanobacteria have a large impact on the albedo, lowering it significantly. They also glue together dust particles that are swept out of the air by the falling snow. These dust particles also contain soot from industrial activity and forest fires, and so the mix of pigmented microbes and dark dust at the surface produces a darker ice sheet. We urgently need to know more about the factors that lead to and limit the growth of the pigmented microbes. Recent work by our group in the darkest zone of the ice sheet surface in the SW of Greenland shows that the darkest areas have the highest numbers of cells. Were these algae to grow equally well in other areas of the ice sheet surface, then the rate of melting of the whole ice sheet would increase very quickly. A major concern is that there will be more wet ice surfaces for these microorganisms to grow in, and for longer, during a period of climate warming, and so the microorganisms will grow in greater numbers and over a larger area, lowering the albedo and increasing the amount of melt that occurs each year. The nutrient - plant food - that the microorganisms need comes from the ice crystals and dust on the ice sheet surface, and there are fears that increased N levels in snow and ice may contribute to the growth of the microorganisms. This project aims to be the first to examine the growth and spread of the microorganisms in a warming climate, and to incorporate biological darkening into models that predict the future melting of the GrIS. References 1. Sasgen I and 8 others. Timing and origin of recent regional ice-mass loss in Greenland. Earth and Planetary Science Letters, 333-334, 293-303(2012). 2. Rignot, E., Velicogna, I., van den Broeke, M. R., Monaghan, A. & Lenaerts, J. Acceleration of the contribution of the Greenland and Antarctic ice sheets to sea level rise. Geophys. Res. Lett. 38, L05503, doi:10.1029/2011gl046583 (2011). 3. Milne, G. A., Gehrels, W. R., Hughes, C. W. & Tamisiea, M. E. Identifying the causes of sea-level change. Nature Geosci 2, 471-478 (2009).

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  • Funder: EC Project Code: 638273
    Overall Budget: 1,436,290 EURFunder Contribution: 1,436,290 EUR

    Enhancers control the correct spatio-temporal activation of gene expression. A comprehensive characterization of the properties and regulatory activities of enhancers as well as their target genes is therefore crucial to understand the regulation and dysregulation of differentiation, homeostasis and cell type specificity. Genome-wide chromatin assays have provided insight into the properties and complex architectures by which enhancers regulate genes, but the understanding of their mechanisms is fragmented and their regulatory targets are mostly unknown. Several factors may confound the inference and interpretation of regulatory enhancer activity. There are likely many kinds of regulatory architectures with distinct levels of output and flexibility. Despite this, most state-of-the-art genome-wide studies only consider a single model. In addition, chromatin-based analysis alone does not provide clear insight into function or activity. This project aims to systematically characterize enhancer architectures and delineate what determines their: (1) restricted spatio-temporal activity; (2) robustness to regulatory genetic variation; and (3) dynamic activities over time. My work has shown enhancer transcription to be the most accurate classifier of enhancer activity to date. This data permits unprecedented modeling of regulatory architectures via enhancer-promoter co-expression linking. Careful computational analysis of such data from appropriate experimental systems has a great potential for distinguishing the different modes of regulation and their functional impact. The outcomes have great potential for providing us with new insights into mechanisms of transcriptional regulation. The results will be particularly relevant to interpretation of regulatory genetic variations. Ultimately, knowing the characteristics and conformations of enhancer architectures will increase our ability to link variation in non-coding DNA to phenotypic outcomes like disease susceptibility.

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  • Funder: UKRI Project Code: EP/M019918/1
    Funder Contribution: 4,991,610 GBP

    VISION: To create, run and exploit the world's leading research programme in mobile autonomy addressing fundamental technical issues which impede large scale commercial and societal adoption of mobile robotics. AMBITION: We need to build better robots - we need them to be cheap, work synergistically with people in large, complex and time-changing environments and do so for long periods of time. Moreover, it is essential that they are safe and trusted. We are compelled as researchers to produce the foundational technologies that will see robots work in economically and socially important domains. These motivations drive the science in this proposal. STRATEGY: Robotics is fast advancing to a point where autonomous systems can add real value to the public domain. The potential reach of mobile robotics in particular is vast, covering sectors as diverse as transport, logistics, space, defence, agriculture and infrastructure management. In order to realise this potential we need our robots to be cheap, work synergistically with people in large, complex and time-changing environments and do so robustly for long periods of time. Our aim, therefore, is to create a lasting, catalysing impact on UKPLC by growing a sustainable centre of excellence in mobile autonomy. A central tenet to this research is that the capability gap between the state of the art and what is needed is addressed by designing algorithms that leverage experiences gained through real and continued world use. Our machines will operate in support of humans and seamlessly integrate into complex cyber-physical systems with a variety of physical and computational elements. We must, therefore, be able to guarantee, and even certify, that the software that controls the robots is safe and trustworthy by design. We will engage in this via a range of flagship technology demonstrators in different domains (transport, logistics, space, etc.), which will mesh the research together, giving at once context, grounding, validation and impact.

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  • Funder: NSF Project Code: 1614036
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  • Funder: EC Project Code: 633190
    Overall Budget: 8,263,200 EURFunder Contribution: 5,998,990 EUR

    Parkinson’s disease (PD) is a major, chronic, non-communicable disease and the 2nd most frequent neurodegenerative disorder worldwide. Excess iron is primarily detected in the substantia nigra pars compacta, where dopaminergic neurons are exposed to high levels of oxidative stress produced by mitochondrial disorders and dopamine metabolism. Our previous preclinical, translational and pilot clinical studies demonstrated that novel iron chelation therapy with the prototypic drug deferiprone (DFP) (i) induces neuroprotection in cell models of PD via a powerful antioxidant effect, (ii) reduces regional siderosis of the brain, (iii) reduces motor handicap via inhibition of catechol-o-methyl transferase, and (iv) slows the progression of motor handicap in the 1-methyl-4-phenyl-1,2,3,6-tetrahydropyridine mouse model and in early PD patients. This project now seeks to demonstrate that conservative iron chelation therapy with moderate-dose DFP (30 mg/kg/day) slows the progression of handicap in de novo PD patients while not affecting systemic parameters. The 9-month, parallel-group, randomized, placebo-controlled, multicentre trial will be followed by a 1-month wash-out period. The primary efficacy criterion will be the change in motor and non-motor handicap scores on the Total Movement Disorders Society Unified Parkinson’s Disease Rating Scale to identify disease-modifying and symptomatic effects. The secondary efficacy criterion will be the change in score between baseline and 40 weeks (i.e. probing the disease-modifying effect only). Potential surrogate radiological and biological biomarkers, health economics and societal impacts will be assessed. 17 national, European and international research and innovation activities will be linked with the project. The study results should prompt academic and industrial research on iron chelation as a disease-modifying treatment in neurodegenerative diseases.

    visibility559
    visibilityviews559
    downloaddownloads1,046
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  • Funder: EC Project Code: 633784
    Overall Budget: 6,120,860 EURFunder Contribution: 5,983,360 EUR

    Breast tumours are heterogeneous, and result from the complex interplay of multiple lifestyle/environmental and genetic risk factors. Through the EU-funded COGS project, we have identified a large number of germline variants that influence the risk of breast cancer. In combination, these variants can identify women at wide ranges of genetic risk, even in the absence of family history of breast cancer. Given that breast cancer is not one disease, it is now essential to better understand how risk factors act together to influence the development of pathologic-molecular subtypes of breast cancer. The aim of B-CAST is to identify women at moderate to high risk of breast cancer, the subtype of cancer that is most likely to develop and the prognosis of that particular subtype. This will be accomplished through large-scale pathologic-molecular analyses of over 20,000 breast tumours, and the integration of these data with unique resources from existing consortia, including germline, lifestyle/environmental, mammographic breast density, pathologic and clinical data. This information will inform the development of risk prediction and prognostication models that will be validated in longitudinal cohorts and clinical studies, and incorporated into online tools. We will also disseminate this knowledge to relevant stakeholders, and evaluate how to translate it into risk-stratified public health and clinical strategies. The current challenge for optimised prevention, early detection, and treatment decisions for breast cancer is understanding the genetic and lifestyle determinants of risk and prognosis of molecular subtypes. B-CAST will add to this understanding and will have immediate application with benefits to women by providing validated risk and prognostication tools. This will empower women and doctors with knowledge to tailor strategies for prevention and treatment. Ultimately, this work should result in reductions in the occurrence, morbidity and mortality of this disease.

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    downloaddownloads6,801
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