Deutsches Krebsforschungszentrum Stifung Des Oeffe, Universitaetsklinikum Heidelberg and University of Heidelberg | Date: 2011-04-29
Described is a diagnostic method for predicting the response of a patient to chemovirotherapy or radiovirotherapy, comprising exposing primary tumor cells from a patient, e.g., tumor cells obtained from a brain tumor or pancreatic cancer, to (i) a parvovirus and/or (ii) a chemotherapeutic agent or radiotherapy, and determining the reduction of the expression or concentration of ISG15.
Deutsches Krebsforschungszentrum Stiftung Des Oeffentlichen Rechts and Universitaetsklinikum Heidelberg | Date: 2015-04-30
The present invention relates to methods for treating an individual with high grade glioblastoma multiforme by preventing or disrupting the binding of CD95 to its ligand, CD95L, in vivo, whereupon that neutralization of CD95 activity reduces undesirable glial cell migration and invasion into body tissue.
Agency: Cordis | Branch: H2020 | Program: RIA | Phase: PHC-32-2014 | Award Amount: 3.66M | Year: 2015
Bioinformatic analysis is the biggest bottleneck in many genomic medicine projects. Our objective is to enable researchers to dramatically increase statistically informed use of personal multi-omic data in medicine. Soon, multiple types of omic technologies will be applied to 100,000s of patient-derived samples, with the three-stage goal of better understanding disease biology, discovery of new interventions, and personalizing the choice of treatment options. Our interdisciplinary team of biostatisticians, bioinformaticians, software developers and physician-scientists will address the analysis bottleneck with statistically and computationally sound methods. The SOUND consortium will (i) develop widely used and excellent bioinformatic and statistical methods and open source software for common but challenging tasks, including data pre-processing, data integration, statistical inference, visual presentation, and publication-quality reporting; (ii) introduce novel approaches to ground breaking multi-omics applications in oncology and medical genetics; (iii) develop interoperable data structures and software interfaces that enable seamless combination of tools; (iv) support a collaborative international academic and industry developer community; (v) enable rapid development and execution of high-quality software; (vi) lower the barrier to entry into this transdisciplinary field by providing simple, robust, easy-to-use solutions; and (vii) develop a training programme with regular courses and comprehensive online tutorials. Our aim is to create the de facto standard toolkit used in every clinical research lab for statistically informed analysis of personal multi-omic data. SOUND will increase research and innovation opportunities by reducing barriers of entry to genomic medicine across academic, healthcare and commercial sectors by translating in a rapid and efficient manner complex and innovative analytical approaches into modular, interoperable, reusable applications.
Agency: Cordis | Branch: H2020 | Program: RIA | Phase: PHC-03-2015 | Award Amount: 6.19M | Year: 2016
Understanding mechanisms underlying comorbid disorders poses a challenge for developing precision medicine tools. Psychiatric disorders are highly comorbid, and are among the last areas of medicine, where classification is driven by phenomenology rather than pathophysiology. We will study comorbidity between the most frequent psychiatric conditions, ADHD, mood/anxiety, and substance use disorders, and a highly prevalent somatic disease, obesity. ADHD, a childhood-onset disorder, forms the entry into a lifelong negative trajectory characterized by these comorbidities. Common mechanisms underlying this course are unknown, despite their relevance for early detection, prevention, and treatment. Our interdisciplinary team of experts will integrate epidemiologic/genetic approaches with experimental designs to address those issues. We will determine disease burden of comorbidity, calculate its socioeconomic impact, and reveal risk factors. We will study biological pathways of comorbidity and derive biomarkers, prioritizing two candidate mechanisms (circadian rhythm and dopaminergic neurotransmission), but also leveraging large existing data sets to identify new ones. A pilot clinical trial to study non-pharmacologic, dopamine-based and chronobiological treatments will be performed, employing innovative mHealth to monitor and support patients daily life. Integration of findings will lead to prediction algorithms enhancing early diagnosis and prevention of comorbidity. Finally, we will screen to repurpose existing pharmacological compounds. Integrating complementary approaches based on large-scale, existing data and innovative data collection, we maximize value for money in this project, leading to insight into the mechanisms underlying this comorbidity triad with its huge burden for healthcare, economy, and society. This will facilitate early detection and non-invasive, scalable, and low-cost treatment, creating opportunities for substantial and immediate societal impact.
Agency: Cordis | Branch: H2020 | Program: MSCA-IF-EF-RI | Phase: MSCA-IF-2015-EF | Award Amount: 159.46K | Year: 2016
The formation of episodic (unique event) memories is based on the interaction between the hippocampus and the cortical regions that receive its output. The major hippocampal output cells are pyramidal cells (PCs) in area CA1. In rodents, populations of CA1 PCs are known to represent a wide range of aspects associated with an episodic memory: Some cells participate in the formation of a map-like representation of space, while others additionally or exclusively encode items within the environment, represent meaningful locations, or participate in the representation of emotional and behavioural contexts. It is not known so far how heterogeneous CA1 firing patterns are organized and affect memory formation. While CA1 PCs have been traditionally considered a homogeneous cell population, we now have clear evidence for the presence of at least two distinct CA1 PC cell types that differ in their local and long-range connectivity, in their morphology, their molecular makeup and their basic firing patterns. This strongly argues for a functional specialization within the CA1 area. However, a link between the heterogeneous representation of mnemonic information and the presence of anatomically distinct PC types remains to be established. In this proposal I aim to determine whether heterogeneous response properties of CA1 PCs are based on computations in distinct anatomical microcircuits in deep and superficial layers by combining optogenetic and chemogenetic techniques with in vivo recordings in behaving mice. Furthermore, I will seek to obtain detailed knowledge about the functional connectivity between different CA1 PC populations and their target areas. Knowledge about the function of individual CA1 microcircuits and their anatomical connections is the prerequisite to subsequently develop an independent research plan aiming to determine how intra-hippocampal processing affects memory formation in their downstream targets.