Project acronym 3DBrainStrom
Project Brain metastases: Deciphering tumor-stroma interactions in three dimensions for the rational design of nanomedicines
Researcher (PI) Ronit Satchi Fainaro
Host Institution (HI) TEL AVIV UNIVERSITY
Call Details Advanced Grant (AdG), LS7, ERC-2018-ADG
Summary Brain metastases represent a major therapeutic challenge. Despite significant breakthroughs in targeted therapies, survival rates of patients with brain metastases remain poor. Nowadays, discovery, development and evaluation of new therapies are performed on human cancer cells grown in 2D on rigid plastic plates followed by in vivo testing in immunodeficient mice. These experimental settings are lacking and constitute a fundamental hurdle for the translation of preclinical discoveries into clinical practice. We propose to establish 3D-printed models of brain metastases (Aim 1), which include brain extracellular matrix, stroma and serum containing immune cells flowing in functional tumor vessels. Our unique models better capture the clinical physio-mechanical tissue properties, signaling pathways, hemodynamics and drug responsiveness. Using our 3D-printed models, we aim to develop two new fronts for identifying novel clinically-relevant molecular drivers (Aim 2) followed by the development of precision nanomedicines (Aim 3). We will exploit our vast experience in anticancer nanomedicines to design three therapeutic approaches that target various cellular compartments involved in brain metastases: 1) Prevention of brain metastatic colonization using targeted nano-vaccines, which elicit antitumor immune response; 2) Intervention of tumor-brain stroma cells crosstalk when brain micrometastases establish; 3) Regression of macrometastatic disease by selectively targeting tumor cells. These approaches will materialize using our libraries of polymeric nanocarriers that selectively accumulate in tumors.
This project will result in a paradigm shift by generating new preclinical cancer models that will bridge the translational gap in cancer therapeutics. The insights and tumor-stroma-targeted nanomedicines developed here will pave the way for prediction of patient outcome, revolutionizing our perception of tumor modelling and consequently the way we prevent and treat cancer.
Summary
Brain metastases represent a major therapeutic challenge. Despite significant breakthroughs in targeted therapies, survival rates of patients with brain metastases remain poor. Nowadays, discovery, development and evaluation of new therapies are performed on human cancer cells grown in 2D on rigid plastic plates followed by in vivo testing in immunodeficient mice. These experimental settings are lacking and constitute a fundamental hurdle for the translation of preclinical discoveries into clinical practice. We propose to establish 3D-printed models of brain metastases (Aim 1), which include brain extracellular matrix, stroma and serum containing immune cells flowing in functional tumor vessels. Our unique models better capture the clinical physio-mechanical tissue properties, signaling pathways, hemodynamics and drug responsiveness. Using our 3D-printed models, we aim to develop two new fronts for identifying novel clinically-relevant molecular drivers (Aim 2) followed by the development of precision nanomedicines (Aim 3). We will exploit our vast experience in anticancer nanomedicines to design three therapeutic approaches that target various cellular compartments involved in brain metastases: 1) Prevention of brain metastatic colonization using targeted nano-vaccines, which elicit antitumor immune response; 2) Intervention of tumor-brain stroma cells crosstalk when brain micrometastases establish; 3) Regression of macrometastatic disease by selectively targeting tumor cells. These approaches will materialize using our libraries of polymeric nanocarriers that selectively accumulate in tumors.
This project will result in a paradigm shift by generating new preclinical cancer models that will bridge the translational gap in cancer therapeutics. The insights and tumor-stroma-targeted nanomedicines developed here will pave the way for prediction of patient outcome, revolutionizing our perception of tumor modelling and consequently the way we prevent and treat cancer.
Max ERC Funding
2 353 125 €
Duration
Start date: 2019-04-01, End date: 2024-03-31
Project acronym ARTimmune
Project Programmable ARTificial immune systems to fight cancer
Researcher (PI) Carl FIGDOR
Host Institution (HI) STICHTING KATHOLIEKE UNIVERSITEIT
Call Details Advanced Grant (AdG), LS7, ERC-2018-ADG
Summary 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
Summary
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
Max ERC Funding
2 500 000 €
Duration
Start date: 2019-11-01, End date: 2024-10-31
Project acronym bECOMiNG
Project spontaneous Evolution and Clonal heterOgeneity in MoNoclonal Gammopathies: from mechanisms of progression to clinical management
Researcher (PI) Niccolo Bolli
Host Institution (HI) UNIVERSITA DEGLI STUDI DI MILANO
Call Details Consolidator Grant (CoG), LS7, ERC-2018-COG
Summary As an onco-hematologist with a strong expertise in genomics, I significantly contributed to the understanding of multiple myeloma (MM) heterogeneity and its evolution over time, driven by genotypic and phenotypic features carried by different subpopulations of cells. MM is preceded by prevalent, asymptomatic stages that may evolve with variable frequency, not accurately captured by current clinical prognostic scores. Supported by preliminary data, my hypothesis is that the same heterogeneity is present early on the disease course, and identification of the biological determinants of evolution at this stage will allow better prediction of its evolutionary trajectory, if not its control. In this proposal I will therefore make a sharp change from conventional approaches and move to early stages of MM using unique retrospective sample cohorts and ambitious prospective sampling. To identify clonal MM cells in the elderly before a monoclonal gammopathy can be detected, I will collect bone marrow (BM) from hundreds of hip replacement specimens, and analyze archive peripheral blood samples of thousands of healthy individuals with years of annotated clinical follow-up. This will identify early genomic alterations that are permissive to disease initiation/evolution and may serve as biomarkers for clinical screening. Through innovative, integrated single-cell genotyping and phenotyping of hundreds of asymptomatic MMs, I will functionally dissect heterogeneity and characterize the BM microenvironment to look for determinants of disease progression. Correlation with clinical outcome and mini-invasive serial sampling of circulating cell-free DNA will identify candidate biological markers to better predict evolution. Last, aggressive modelling of candidate early lesions and modifier screens will offer a list of vulnerabilities that could be exploited for rationale therapies. These methodologies will deliver a paradigm for the use of molecularly-driven precision medicine in cancer.
Summary
As an onco-hematologist with a strong expertise in genomics, I significantly contributed to the understanding of multiple myeloma (MM) heterogeneity and its evolution over time, driven by genotypic and phenotypic features carried by different subpopulations of cells. MM is preceded by prevalent, asymptomatic stages that may evolve with variable frequency, not accurately captured by current clinical prognostic scores. Supported by preliminary data, my hypothesis is that the same heterogeneity is present early on the disease course, and identification of the biological determinants of evolution at this stage will allow better prediction of its evolutionary trajectory, if not its control. In this proposal I will therefore make a sharp change from conventional approaches and move to early stages of MM using unique retrospective sample cohorts and ambitious prospective sampling. To identify clonal MM cells in the elderly before a monoclonal gammopathy can be detected, I will collect bone marrow (BM) from hundreds of hip replacement specimens, and analyze archive peripheral blood samples of thousands of healthy individuals with years of annotated clinical follow-up. This will identify early genomic alterations that are permissive to disease initiation/evolution and may serve as biomarkers for clinical screening. Through innovative, integrated single-cell genotyping and phenotyping of hundreds of asymptomatic MMs, I will functionally dissect heterogeneity and characterize the BM microenvironment to look for determinants of disease progression. Correlation with clinical outcome and mini-invasive serial sampling of circulating cell-free DNA will identify candidate biological markers to better predict evolution. Last, aggressive modelling of candidate early lesions and modifier screens will offer a list of vulnerabilities that could be exploited for rationale therapies. These methodologies will deliver a paradigm for the use of molecularly-driven precision medicine in cancer.
Max ERC Funding
1 998 781 €
Duration
Start date: 2019-03-01, End date: 2024-02-29
Project acronym BIOSENSORIMAGING
Project Hyperpolarized Biosensors in Molecular Imaging
Researcher (PI) Leif Schröder
Host Institution (HI) FORSCHUNGSVERBUND BERLIN EV
Call Details Starting Grant (StG), LS7, ERC-2009-StG
Summary Xenon biosensors have an outstanding potential to increase the significance of magnetic resonance imaging (MRI) in molecular imaging and to combine the advantages of MRI with the high sensitivity of hyperpolarized Xe-129 and the specificity of a functionalized contrast agent. Based on new detection schemes (Hyper-CEST method) in Xe MRI, this novel concept in molecular diagnostics will be made available for biomedical applications. The advancement focuses on high-sensitivity in vitro diagnostics for localization of tumour cells in cell cultures and first demonstrations on animal models based on a transferrin-functionalized biosensor. Such a sensor will enable detection of subcutaneous tumours at high sensitivity without any background signal. More detailed work on the different available Hyper-CEST contrast parameters focuses on an absolute quantification of new molecular markers that will improve non-invasive tumour diagnostics significantly. NMR detection of functionalized Xe biosensors have the potential to close the sensitivity gap between modalities of nuclear medicine like PET/SPECT and MRI without using ionizing radiation or making compromises in penetration depth like in optical methods.
Summary
Xenon biosensors have an outstanding potential to increase the significance of magnetic resonance imaging (MRI) in molecular imaging and to combine the advantages of MRI with the high sensitivity of hyperpolarized Xe-129 and the specificity of a functionalized contrast agent. Based on new detection schemes (Hyper-CEST method) in Xe MRI, this novel concept in molecular diagnostics will be made available for biomedical applications. The advancement focuses on high-sensitivity in vitro diagnostics for localization of tumour cells in cell cultures and first demonstrations on animal models based on a transferrin-functionalized biosensor. Such a sensor will enable detection of subcutaneous tumours at high sensitivity without any background signal. More detailed work on the different available Hyper-CEST contrast parameters focuses on an absolute quantification of new molecular markers that will improve non-invasive tumour diagnostics significantly. NMR detection of functionalized Xe biosensors have the potential to close the sensitivity gap between modalities of nuclear medicine like PET/SPECT and MRI without using ionizing radiation or making compromises in penetration depth like in optical methods.
Max ERC Funding
1 848 600 €
Duration
Start date: 2009-12-01, End date: 2014-11-30
Project acronym Brain Health Toolbox
Project The Brain Health Toolbox: Facilitating personalized decision-making for effective dementia prevention
Researcher (PI) Alina Gabriela SOLOMON
Host Institution (HI) ITA-SUOMEN YLIOPISTO
Call Details Starting Grant (StG), LS7, ERC-2018-STG
Summary Preventing dementia and Alzheimer disease (AD) is a global priority. Previous single-intervention failures stress the critical need for a new multimodal preventive approach in these complex multifactorial conditions. The Brain Health Toolbox is designed to create a seamless continuum from accurate dementia prediction to effective prevention by i) developing the missing disease models and prediction tools for multimodal prevention; ii) testing them in actual multimodal prevention trials; and iii) bridging the gap between non-pharmacological and pharmacological approaches by designing a combined multimodal prevention trial based on a new European adaptive trial platform. Disease models and prediction tools will be multi-dimensional, i.e. a broad range of risk factors and biomarker types, including novel markers. An innovative machine learning method will be used for pattern identification and risk profiling to highlight most important contributors to an individual’s overall risk level. This is crucial for early identification of individuals with high dementia risk and/or high likelihood of specific brain pathologies, quantifying an individual’s prevention potential, and longitudinal risk and disease monitoring, also beyond trial duration. Three Toolbox test scenarios are considered: use for selecting target populations, assessing heterogeneity of intervention effects, and use as trial outcome. The project is based on a unique set-up aligning several new multimodal lifestyle trials aiming to adapt and test non-pharmacological interventions to different geographic, economic and cultural settings, with two reference libraries (observational - large datasets; and interventional - four recently completed pioneering multimodal lifestyle prevention trials). The Brain Health Toolbox covers the entire continuum from general populations to patients with preclinical/prodromal disease stages, and will provide tools for personalized decision-making for dementia prevention.
Summary
Preventing dementia and Alzheimer disease (AD) is a global priority. Previous single-intervention failures stress the critical need for a new multimodal preventive approach in these complex multifactorial conditions. The Brain Health Toolbox is designed to create a seamless continuum from accurate dementia prediction to effective prevention by i) developing the missing disease models and prediction tools for multimodal prevention; ii) testing them in actual multimodal prevention trials; and iii) bridging the gap between non-pharmacological and pharmacological approaches by designing a combined multimodal prevention trial based on a new European adaptive trial platform. Disease models and prediction tools will be multi-dimensional, i.e. a broad range of risk factors and biomarker types, including novel markers. An innovative machine learning method will be used for pattern identification and risk profiling to highlight most important contributors to an individual’s overall risk level. This is crucial for early identification of individuals with high dementia risk and/or high likelihood of specific brain pathologies, quantifying an individual’s prevention potential, and longitudinal risk and disease monitoring, also beyond trial duration. Three Toolbox test scenarios are considered: use for selecting target populations, assessing heterogeneity of intervention effects, and use as trial outcome. The project is based on a unique set-up aligning several new multimodal lifestyle trials aiming to adapt and test non-pharmacological interventions to different geographic, economic and cultural settings, with two reference libraries (observational - large datasets; and interventional - four recently completed pioneering multimodal lifestyle prevention trials). The Brain Health Toolbox covers the entire continuum from general populations to patients with preclinical/prodromal disease stages, and will provide tools for personalized decision-making for dementia prevention.
Max ERC Funding
1 498 268 €
Duration
Start date: 2019-02-01, End date: 2024-01-31
Project acronym BRuSH
Project Oral bacteria as determinants for respiratory health
Researcher (PI) Randi BERTELSEN
Host Institution (HI) UNIVERSITETET I BERGEN
Call Details Starting Grant (StG), LS7, ERC-2018-STG
Summary The oral cavity is the gateway to the lower respiratory tract, and oral bacteria are likely to play a role in lung health. This may be the case for pathogens as well as commensal bacteria and the balance between species. The oral bacterial community of patients with periodontitis is dominated by gram-negative bacteria and a higher lipopolysaccharide (LPS) activity than in healthy microbiota. Furthermore, bacteria with especially potent pro-inflammatory LPS have been shown to be more common in the lungs of asthmatic than in healthy individuals. The working hypothesis of BRuSH is that microbiome communities dominated by LPS-producing bacteria which induce a particularly strong pro-inflammatory immune response in the host, will have a negative effect on respiratory health. I will test this hypothesis in two longitudinally designed population-based lung health studies. I aim to identify whether specific bacterial composition and types of LPS producing bacteria in oral and dust samples predict lung function and respiratory health over time; and if the different types of LPS-producing bacteria affect LPS in saliva saliva and dust. BRuSH will apply functional genome annotation that can assign biological significance to raw bacterial DNA sequences. With this bioinformatics tool I will cluster microbiome data into various LPS-producers: bacteria with LPS with strong inflammatory effects and others with weak- or antagonistic effects. The epidemiological studies will be supported by mice-models of asthma and cell assays of human bronchial epithelial cells, by exposing mice and bronchial cells to chemically synthesized Lipid A (the component that drive the LPS-induced immune responses) of various potency. The goal of BRuSH is to prove a causal relationship between oral microbiome and lung health, and gain knowledge that will enable us to make oral health a feasible target for intervention programs aimed at optimizing lung health and preventing respiratory disease.
Summary
The oral cavity is the gateway to the lower respiratory tract, and oral bacteria are likely to play a role in lung health. This may be the case for pathogens as well as commensal bacteria and the balance between species. The oral bacterial community of patients with periodontitis is dominated by gram-negative bacteria and a higher lipopolysaccharide (LPS) activity than in healthy microbiota. Furthermore, bacteria with especially potent pro-inflammatory LPS have been shown to be more common in the lungs of asthmatic than in healthy individuals. The working hypothesis of BRuSH is that microbiome communities dominated by LPS-producing bacteria which induce a particularly strong pro-inflammatory immune response in the host, will have a negative effect on respiratory health. I will test this hypothesis in two longitudinally designed population-based lung health studies. I aim to identify whether specific bacterial composition and types of LPS producing bacteria in oral and dust samples predict lung function and respiratory health over time; and if the different types of LPS-producing bacteria affect LPS in saliva saliva and dust. BRuSH will apply functional genome annotation that can assign biological significance to raw bacterial DNA sequences. With this bioinformatics tool I will cluster microbiome data into various LPS-producers: bacteria with LPS with strong inflammatory effects and others with weak- or antagonistic effects. The epidemiological studies will be supported by mice-models of asthma and cell assays of human bronchial epithelial cells, by exposing mice and bronchial cells to chemically synthesized Lipid A (the component that drive the LPS-induced immune responses) of various potency. The goal of BRuSH is to prove a causal relationship between oral microbiome and lung health, and gain knowledge that will enable us to make oral health a feasible target for intervention programs aimed at optimizing lung health and preventing respiratory disease.
Max ERC Funding
1 499 938 €
Duration
Start date: 2019-01-01, End date: 2023-12-31
Project acronym BUBBLE CURE
Project Targeted microbubble vibrations to accurately diagnose and treat cardiac device-related bacterial biofilm infections
Researcher (PI) Klazina KOOIMAN
Host Institution (HI) ERASMUS UNIVERSITAIR MEDISCH CENTRUM ROTTERDAM
Call Details Starting Grant (StG), LS7, ERC-2018-STG
Summary Due to an aging population, increasingly more cardiac devices are implanted (pacemaker/ICD/CRT/ prosthetic valve/LVAD; worldwide ~2 million yearly). Life-threatening bacterial infections (1-60% infection and 29-50% mortality rate) associated with these devices are a major healthcare burden and pose scientific challenges. Ultrasound imaging is currently the primary diagnostic modality. However, it lacks specificity and sensitivity because the signal from the bacteria is similar to the signal of healthy tissue or the cardiac device, thus making accurate diagnosis impossible. Recent developments in targeted ultrasound contrast agents (i.e. targeted microbubbles (tMB), 1-8 micron in size) allow ultrasound imaging of a specific tMB vibration signal resulting in exceptional sensitivity and specificity. Advancing tMB imaging to detect bacterial infections is needed to solve the challenges caused by the complex ultrasound field from these devices. I was the first to show that vibrating tMB induce vascular drug uptake, thereby showing the potential of tMB as a theranostic agent by combining imaging with drug delivery. Recently, my team and I were also the first to demonstrate which tMB vibrations kill vessel wall cells in vitro by developing analysis methods that link tMB vibrations to drug uptake patterns on a single cell layer. As this is the first time this technique will be applied to 3D bacterial biofilm infections on cardiac devices, I will go beyond the state-of-the-art in tMB-tissue interaction technology by developing novel detection, analysis, and modeling methods to accurately determine which tMB vibrations eradicate bacterial biofilm infections on devices.
The Bubble Cure project will result in a novel multidisciplinary technology that allows accurate diagnosis and treatment of cardiac device-related bacterial biofilm infections, thereby creating a whole new direction of tMB ultrasound imaging and therapy in the scientific field of cardiology and microbiology.
Summary
Due to an aging population, increasingly more cardiac devices are implanted (pacemaker/ICD/CRT/ prosthetic valve/LVAD; worldwide ~2 million yearly). Life-threatening bacterial infections (1-60% infection and 29-50% mortality rate) associated with these devices are a major healthcare burden and pose scientific challenges. Ultrasound imaging is currently the primary diagnostic modality. However, it lacks specificity and sensitivity because the signal from the bacteria is similar to the signal of healthy tissue or the cardiac device, thus making accurate diagnosis impossible. Recent developments in targeted ultrasound contrast agents (i.e. targeted microbubbles (tMB), 1-8 micron in size) allow ultrasound imaging of a specific tMB vibration signal resulting in exceptional sensitivity and specificity. Advancing tMB imaging to detect bacterial infections is needed to solve the challenges caused by the complex ultrasound field from these devices. I was the first to show that vibrating tMB induce vascular drug uptake, thereby showing the potential of tMB as a theranostic agent by combining imaging with drug delivery. Recently, my team and I were also the first to demonstrate which tMB vibrations kill vessel wall cells in vitro by developing analysis methods that link tMB vibrations to drug uptake patterns on a single cell layer. As this is the first time this technique will be applied to 3D bacterial biofilm infections on cardiac devices, I will go beyond the state-of-the-art in tMB-tissue interaction technology by developing novel detection, analysis, and modeling methods to accurately determine which tMB vibrations eradicate bacterial biofilm infections on devices.
The Bubble Cure project will result in a novel multidisciplinary technology that allows accurate diagnosis and treatment of cardiac device-related bacterial biofilm infections, thereby creating a whole new direction of tMB ultrasound imaging and therapy in the scientific field of cardiology and microbiology.
Max ERC Funding
1 878 000 €
Duration
Start date: 2019-01-01, End date: 2023-12-31
Project acronym C-MORPH
Project Noninvasive cell specific morphometry in neuroinflammation and degeneration
Researcher (PI) Henrik LUNDELL
Host Institution (HI) REGION HOVEDSTADEN
Call Details Starting Grant (StG), LS7, ERC-2018-STG
Summary Brain structure determines function. Disentangling regional microstructural properties and understanding how these properties constitute brain function is a central goal of neuroimaging of the human brain and a key prerequisite for a mechanistic understanding of brain diseases and their treatment. Using magnetic resonance (MR) imaging, previous research has established links between regional brain microstructure and inter-individual variation in brain function, but this line of research has been limited by the non-specificity of MR-derived markers. This hampers the application of MR imaging as a tool to identify specific fingerprints of the underlying disease process.
Exploiting state-of-the-art ultra-high field MR imaging techniques, I have recently developed two independent spectroscopic MR methods that have the potential to tackle this challenge: Powder averaged diffusion weighted spectroscopy (PADWS) can provide an unbiased marker for cell specific structural degeneration, and Spectrally tuned gradient trajectories (STGT) can isolate cell shape and size. In this project, I will harness these innovations for MR-based precision medicine. I will advance PADWS and STGT methodology on state-of-the-art MR hardware and harvest the synergy of these methods to realize Cell-specific in-vivo MORPHOMETRY (C-MORPH) of the intact human brain. I will establish novel MR read-outs and analyses to derive cell-type specific tissue properties in the healthy and diseased brain and validate them with the help of a strong translational experimental framework, including histological validation. Once validated, the experimental methods and analyses will be simplified and adapted to provide clinically applicable tools. This will push the frontiers of MR-based personalized medicine, guiding therapeutic decisions by providing sensitive probes of cell-specific microstructural changes caused by inflammation, neurodegeneration or treatment response.
Summary
Brain structure determines function. Disentangling regional microstructural properties and understanding how these properties constitute brain function is a central goal of neuroimaging of the human brain and a key prerequisite for a mechanistic understanding of brain diseases and their treatment. Using magnetic resonance (MR) imaging, previous research has established links between regional brain microstructure and inter-individual variation in brain function, but this line of research has been limited by the non-specificity of MR-derived markers. This hampers the application of MR imaging as a tool to identify specific fingerprints of the underlying disease process.
Exploiting state-of-the-art ultra-high field MR imaging techniques, I have recently developed two independent spectroscopic MR methods that have the potential to tackle this challenge: Powder averaged diffusion weighted spectroscopy (PADWS) can provide an unbiased marker for cell specific structural degeneration, and Spectrally tuned gradient trajectories (STGT) can isolate cell shape and size. In this project, I will harness these innovations for MR-based precision medicine. I will advance PADWS and STGT methodology on state-of-the-art MR hardware and harvest the synergy of these methods to realize Cell-specific in-vivo MORPHOMETRY (C-MORPH) of the intact human brain. I will establish novel MR read-outs and analyses to derive cell-type specific tissue properties in the healthy and diseased brain and validate them with the help of a strong translational experimental framework, including histological validation. Once validated, the experimental methods and analyses will be simplified and adapted to provide clinically applicable tools. This will push the frontiers of MR-based personalized medicine, guiding therapeutic decisions by providing sensitive probes of cell-specific microstructural changes caused by inflammation, neurodegeneration or treatment response.
Max ERC Funding
1 498 811 €
Duration
Start date: 2018-12-01, End date: 2023-11-30
Project acronym CANCEREVO
Project Deciphering and predicting the evolution of cancer cell populations
Researcher (PI) Marco Helmut GERLINGER
Host Institution (HI) THE INSTITUTE OF CANCER RESEARCH: ROYAL CANCER HOSPITAL
Call Details Consolidator Grant (CoG), LS7, ERC-2018-COG
Summary The fundamental evolutionary nature of cancer is well recognized but an understanding of the dynamic evolutionary changes occurring throughout a tumour’s lifetime and their clinical implications is in its infancy. Current approaches to reveal cancer evolution by sequencing of multiple biopsies remain of limited use in the clinic due to sample access problems in multi-metastatic disease. Circulating tumour DNA (ctDNA) is thought to comprehensively sample subclones across metastatic sites. However, available technologies either have high sensitivity but are restricted to the analysis of small gene panels or they allow sequencing of large target regions such as exomes but with too limited sensitivity to detect rare subclones. We developed a novel error corrected sequencing technology that will be applied to perform deep exome sequencing on longitudinal ctDNA samples from highly heterogeneous metastatic gastro-oesophageal carcinomas. This will track the evolution of the entire cancer population over the lifetime of these tumours, from metastatic disease over drug therapy to end-stage disease and enable ground breaking insights into cancer population evolution rules and mechanisms. Specifically, we will: 1. Define the genomic landscape and drivers of metastatic and end stage disease. 2. Understand the rules of cancer evolutionary dynamics of entire cancer cell populations. 3. Predict cancer evolution and define the limits of predictability. 4. Rapidly identify drug resistance mechanisms to chemo- and immunotherapy based on signals of Darwinian selection such as parallel and convergent evolution. Our sequencing technology and analysis framework will also transform the way cancer evolution metrics can be accessed and interpreted in the clinic which will have major impacts, ranging from better biomarkers to predict cancer evolution to the identification of drug targets that drive disease progression and therapy resistance.
Summary
The fundamental evolutionary nature of cancer is well recognized but an understanding of the dynamic evolutionary changes occurring throughout a tumour’s lifetime and their clinical implications is in its infancy. Current approaches to reveal cancer evolution by sequencing of multiple biopsies remain of limited use in the clinic due to sample access problems in multi-metastatic disease. Circulating tumour DNA (ctDNA) is thought to comprehensively sample subclones across metastatic sites. However, available technologies either have high sensitivity but are restricted to the analysis of small gene panels or they allow sequencing of large target regions such as exomes but with too limited sensitivity to detect rare subclones. We developed a novel error corrected sequencing technology that will be applied to perform deep exome sequencing on longitudinal ctDNA samples from highly heterogeneous metastatic gastro-oesophageal carcinomas. This will track the evolution of the entire cancer population over the lifetime of these tumours, from metastatic disease over drug therapy to end-stage disease and enable ground breaking insights into cancer population evolution rules and mechanisms. Specifically, we will: 1. Define the genomic landscape and drivers of metastatic and end stage disease. 2. Understand the rules of cancer evolutionary dynamics of entire cancer cell populations. 3. Predict cancer evolution and define the limits of predictability. 4. Rapidly identify drug resistance mechanisms to chemo- and immunotherapy based on signals of Darwinian selection such as parallel and convergent evolution. Our sequencing technology and analysis framework will also transform the way cancer evolution metrics can be accessed and interpreted in the clinic which will have major impacts, ranging from better biomarkers to predict cancer evolution to the identification of drug targets that drive disease progression and therapy resistance.
Max ERC Funding
2 000 000 €
Duration
Start date: 2019-03-01, End date: 2024-02-29
Project acronym CHILIC
Project Child health intervention interactions in low-income countries
Researcher (PI) Christine Benn
Host Institution (HI) STATENS SERUM INSTITUT
Call Details Starting Grant (StG), LS7, ERC-2009-StG
Summary Vitamin A supplementation (VAS) and vaccines are the most powerful tools to reduce child mortality in low-income countries. However, we may not use these interventions optimally because we disregard that the interventions may have immunomodulatory effects which differ for boys and girls and which may interact with the effects of other interventions. I have proposed the hypothesis that VAS and vaccines interact. This hypothesis is supported by randomised and observational studies showing that the combination of VAS and DTP may be harmful. I have furthermore proposed that VAS has sex-differential effects. VAS seems beneficial for boys but may not carry any benefits for girls. These findings challenge the current understanding that VAS and vaccines have only targeted effects and can be given together without considering interactions. This is of outmost importance for policy makers. The global trend is to combine health interventions for logistic reasons. My research suggests that this may not always be a good idea. Furthermore, the concept of sex-differential response to our common health interventions opens up for a completely new understanding of the immunology of the two sexes and may imply that we need to treat the two sexes differently in order to treat them optimally possibly also in high-income countries. In the present proposal I outline a series of inter-disciplinary epidemiological and immunological studies, which will serve to determine the overall and sex-differential effects of VAS and vaccines, the mechanisms behind these effects, and the basis for the immunological difference between boys and girls. If my hypotheses are true we can use the existing tools in a more optimal way to reduce child mortality without increasing costs. Thus, the results could lead to shifts in policy as well as paradigms.
Summary
Vitamin A supplementation (VAS) and vaccines are the most powerful tools to reduce child mortality in low-income countries. However, we may not use these interventions optimally because we disregard that the interventions may have immunomodulatory effects which differ for boys and girls and which may interact with the effects of other interventions. I have proposed the hypothesis that VAS and vaccines interact. This hypothesis is supported by randomised and observational studies showing that the combination of VAS and DTP may be harmful. I have furthermore proposed that VAS has sex-differential effects. VAS seems beneficial for boys but may not carry any benefits for girls. These findings challenge the current understanding that VAS and vaccines have only targeted effects and can be given together without considering interactions. This is of outmost importance for policy makers. The global trend is to combine health interventions for logistic reasons. My research suggests that this may not always be a good idea. Furthermore, the concept of sex-differential response to our common health interventions opens up for a completely new understanding of the immunology of the two sexes and may imply that we need to treat the two sexes differently in order to treat them optimally possibly also in high-income countries. In the present proposal I outline a series of inter-disciplinary epidemiological and immunological studies, which will serve to determine the overall and sex-differential effects of VAS and vaccines, the mechanisms behind these effects, and the basis for the immunological difference between boys and girls. If my hypotheses are true we can use the existing tools in a more optimal way to reduce child mortality without increasing costs. Thus, the results could lead to shifts in policy as well as paradigms.
Max ERC Funding
1 686 043 €
Duration
Start date: 2010-01-01, End date: 2014-12-31
