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SMBCa - Systems Medicine of Breast Cancer Metastasis and Drug Resistance. Preparatory meeting for BMBF e:Med program Heidelberg, December 4, 2013. agenda. Welcome Introduction of partners and participating groups Introduction into the BMBF e:Med program Why breast cancer?
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SMBCa-Systems Medicine of Breast CancerMetastasis and Drug Resistance Preparatory meeting for BMBF e:Med program Heidelberg, December 4, 2013
agenda • Welcome • Introduction of partners and participating groups • Introduction into the BMBF e:Med program • Why breast cancer? • Presentation and discussion of individual subprojects • Open questions • Timeline • Miscellaneous • close
background of e:Med • Framework program ‘Health Research 2010-2018’ of the Federal Government • Key-words: • Aging population -> cancer, cardiovascular, diabetes… • New routes for prevention and treatment • Individualized medicine • Molecular mechanisms of disease • Innovation: diagnosis, therapy, early detection, prevention • Basic research >>> clinical application (“from bench to bedside”) • Systems Biology – high throughput technologies, disease models, biobanking, • Integration of key competences in Germany • Global networking: research infrastructures competitiveness
BMBF – Funding environment • Deutsche Zentren der Gesundheitsforschung • Research Infrastructures • Neurodegenerative diseases • Diabetes • Cardiovascular diseases • Infection diseases • Translational cancer research (DKTK) • Lung diseases International commitmentof BMBF ICGC, IHEC, … Project Funding NGFN (2001-2013), Systems Biology (2008-2013) e:Bio – on-going -> small Systems Biology related projects->SysmetBC – ‘Systems biology of metabolic transformation in breast Cancer’ -> Metastasys – ‘Analysis of Molecular Markers and Pathways in Cancer Cells and Microenviroment that determine the Fate and Localization of Tumor Metastases’ e:Med – NEW – Maßnahmen zur Etablierung der Systemmedizin e:??? – more to come (this year – “demonstrator” projects towards commercialization)
e:Med Keywords • Systems Medicine – personalized treatment • Improvement of the quality of medicine • OMICs technologies – - - -> clinics • Molecular networks and their roles in pathophysiological processes • Preexisting data and materials (no large-scale gathering of new data and biomaterials/clinical studies) • Data management strategies (collection, archiving, processing, analysis, visualization, exchange) • International standards for collection and management of materials and data -> integration of data into existing collections • Systems biological modeling of pathophysiological mechanisms combined with in vivo testing • Some technology development (e.g., in vitro functional assays and animal models) • International networking – international visibility
e:Med Key numbers • Funding for 3 + 2 years • Evaluation after first 2 years • 12-15 mio EURO/year • 10-20 networks with 0.5-2 mio EURO/year • Deadline: January 15, 2013
Targeted Systems Medicine into the clinics • Targeted therapies – benefits and challenges • Combination of large-scale molecular data (sequencing, gene expression), in vitro cell biology models (large- and fine-scale), quantitative proteomics, in vivo mouse models & in vivo imaging, clinics, systems biological modeling • Breast cancer subtypes – molecular subtypes (expression profiling -> sequencing)
Significantly mutated genes and correlations with genomic and clinical features. Tumour samples are grouped by mRNA subtype: luminal A (n = 225), luminal B (n = 126), HER2E (n = 57) and basal-like (n = 93). The left panel shows non-silent somatic mutation patterns and frequencies for significantly mutated genes. The middle panel shows clinical features: dark grey, positive or T2–4; white, negative or T1; light grey, N/A or equivocal. N, node status; T, tumour size. The right panel shows significantly mutated genes with frequent copy number amplifications (red) or deletions (blue). The far-right panel shows non-silent mutation rate per tumour (mutations per megabase, adjusted for coverage). The average mutation rate for each expression subtype is indicated. Hypermutated: mutation rates >3 s.d. above the mean (>4.688, indicated by grey line). DC Koboldt et al. Nature000, 1-10 (2012) doi:10.1038/nature11412
Tumor stroma interactions miR520/206 Massague Cell 2008
Division Molecular Genome Analysismostly breast cancer(some GIST) Tumor-stroma interactions cytokines/chemokinese.g. Keklikoglou Oncogene 2012 Growth factors/ligands/ shedding-products RPPA/MIA/ELISA 3D-cultures co-cultures mouse models Signaling pathways: MAPK PI3K NF-KB TGF-b Pathway interactions siRNA/miRNA screeninge.g. Sahin PNAS 2007, Zhang PLoS One 2011 Uhlmann Mol Sys Biol 2012 Protein abundance and activation quantitative proteomics/cell-based assayse.g. Uhlmann Oncogene 2010 Henjes Oncogenesis 2012 • Gene-activation and feedback control • mutations / miRNA interactions • e.g. Haller J Pathol 2010 • Epigenetics – promoter methylation • e.g. Haller J Pathol in review Regulation of gene expression miRNA/transcription faktor interactionse.g. Ward Oncogene 2012 Burmeister Mol Cell Biol 2012
Aims – molecular mechanisms of disease Metastasis formation miRNAs/TFs & signaling vs. molecular alterations Tumor – stroma interactions Drug resistance Basic research – systems biological modeling – clinical translation
Gynecology Clinical studies Pathology: Clinical validation Genetic variation Epigenetic variation Metastasis Drug resistance TF/molecular Variation Networks in cancer quantitative Modeling Bioinformatics Transcription factor Networks of metastasis molecular Tools miRNA-signaling Networks Data management In vivo mouse models Tumor Stroma interactions
How visualize relations within (and beyond) the consortium? Circos plot
e:Med prerequisites (call for proposals) • Systems biology concept - quantitative, dynamic data – Stefan Legewie/Jens Timmer/ (?) • Clear disease focus - breast cancer metastasis & drug resistance & environment • Interdisciplinary research problem to be tackled - big and small data -> “systems medicine of BCa” • Coverage of all necessary disciplines - basic research … clinics • Willingness for cooperation with other research consortia - successful (joint publications) collaborations in the past • Highest quality of methods and the planned science - depends on you ! • Proven expertise of applicants - i.e. you ! • Relevance of aims for medicine and industry - no. of cases, mortality, targeted drugs • access to relevant patient- and controll collections and –materials, and clinical data in sufficient quality and quantity - Erlangen – primary tumor, metastases(?), Bavarian cancer registry w/ long-term follow-up • Equipment to carry out high-throughput analyses (sequencing, arrays, …) and internal as well as external data from high-throughput projects DKFZ facilities and ICGC, TCGA, … (IHEC?)
ToDos • Outlines of individual subprojects • What can you provide? • What can others provide to you – your needs? • Connections between subprojects (internal and external) • National and international networking
ToDos • expertise and previous work of the consortium partners in the research area addressed. • Proof that all necessary expertises and capacities are included. • existing resources within the consortium (e.g. established methods, phenotyped patient- and control-collectives, equipment, material- or data libraries, HT-capacities for genotyping or sequencing etc.). • availability and access to data and/or biomaterials for the consortium. • Planned measures for quality assurance, standardisation and exchangeof information, methods, samples and data.
e:Med and ‘our’ background/environment (BMBF funding) 1996-2004 DHGP 2001-2004 NGFN – cDNA platform -> Resources 2004-2008 NGFN-2 – SMP-Cell -> cellular assays, protein localization 2008-2011 NGFN-Plus – Integrated Genome Network Cellular Systems Genomics -> Breast cancer signaling 2008-2013 NGFN-Plus – Integrated Genome Network Environmental Diseases (Stefan Schreiber) -> NF-KB signaling 2008-2011 NGFN-Transfer Project Genome subfractionation for targeted sequencing (Hugo Katus) 2009-2013 SysMed: Breast Sys – Identifying novel therapeutic strategies for breast cancer by data-driven modeling of tumor progression 2013-2015 e:Bio small Systems Biology related projects -> SysmetBC – ‘Systems biology of metabolic transformation in breast Cancer’ -> Metastasys – ‘Analysis of Molecular Markers and Pathways in Cancer Cells and Microenviroment that determine the Fate and Localization of Tumor Metastases’ Plus some international collaborations
Your background/environment ? • To be added to the proposal: • large funding programs and grants • previous projects… • ICGC • ... ? • … national and international • … with relation to e:Med !
ToDos • Concept for commercial or clinical exploitation • Commercial • Clinical – small-scale studies? • Ethical and legal considerations • Patient material • Patient data • Mouse models • Other?
This is a 5-year program • longer time visions • Deliverables and milestones – for 2 years, 3 years and 5 years -> measurable!! Time of review End of first period End of program
Timeline • SW will distribute templates for subproject descriptions (today) • SW will distribute first draft of global description (end of next week) • Everyone will submit first (advanced) draftbyDec 12 • return for revision by Dec 18 • submit of second draft by Dec 28 • distribution of proposal by Jan 9 for last revisions • finalization of proposal by Jan 14 • submission on Jan 15