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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.

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Presentation on theme: "SMBCa - Systems Medicine of Breast Cancer Metastasis and Drug Resistance Preparatory meeting for BMBF e:Med program Heidelberg, December 4, 2013."— Presentation transcript:

1 SMBCa - Systems Medicine of Breast Cancer Metastasis and Drug Resistance Preparatory meeting for BMBF e:Med program Heidelberg, December 4, 2013

2 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

3 background of e:Med Framework program Health Research 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

4 BMBF – Funding environment Deutsche Zentren der Gesundheitsforschung Research Infrastructures Neurodegenerative diseases Diabetes Cardiovascular diseases Infection diseases Translational cancer research (DKTK) Lung diseases Project Funding NGFN ( ), Systems Biology ( ) 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) International commitment of BMBF ICGC, IHEC, …

5 map of the BMBF

6 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

7 e:Med Key numbers Funding for years Evaluation after first 2 years mio EURO/year networks with mio EURO/year Deadline: January 15, 2013

8 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)

9 DC Koboldt et al. Nature 000, 1-10 (2012) doi: /nature11412 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).

10 WashU – Nature 2012

11 Massague Cell 2008 Tumor stroma interactions miR520/206

12 Evaluation criteria (the official ones) Wissenschaftlich-methodische Exzellenz und Erfolgsaussichten des Forschungsansatzes sowohl auf Verbund- wie auch auf Teilprojektebene, Bezug des Antrags zur Zielsetzung der Bekanntmachung: klarer Fokus auf eine alle Teilprojekte verbindende systemorientierte und krankheitsbezogene Forschungsfragestellung, Organisation und Steuerung des Verbundes: Funktionalität bezüglich der geplanten Zielsetzung, Angemessenheit von Größe und Struktur des Verbundes, Qualität und Stringenz von Zeit- und Meilensteinplanung, Einbindung aller notwendigen Disziplinen und Expertisen (siehe Mindestvoraussetzungen in 2.), arbeitsteilige und interdisziplinäre Qualität des Vorhabens; Konzept zur Koordination und Steuerung sowie zur Kommunikation und Kooperation, Erfolgsaussichten des Verbundes: nachgewiesene Verfügbarkeit adäquater Vorleistungen, Ressourcen und Kapazitäten, insbesondere relevantes und in ausreichender Qualität und Quantität vorhandenes, klinisch gut charakterisiertes Patienten- und Kontrollmaterial (Power-Kalkulationen) bzw. Datenmaterial, Angemessenheit des Budgets; Qualität der geplanten Maßnahmen für Datenmanagement sowie für Standardisierung bei der Gewinnung bzw. Generierung und dem Austausch von Verfahren, Proben und Daten, Verwertungspotential: Perspektive für Ansatzpunkte zur Entwicklung innovativer Verfahren und/ oder Produkte, die für das medizinische Handeln in Prävention, Diagnostik und Therapie nützlich werden können; ggf. Verwertungskonzept.

13 Growth factors/ligands/ shedding-products RPPA/MIA/ELISA Tumor-stroma interactions cytokines/chemokines e.g.Keklikoglou Oncogene 2012 Protein abundance and activation quantitative proteomics/cell-based assays e.g.Uhlmann Oncogene 2010 Henjes Oncogenesis 2012 Pathway interactions siRNA/miRNA screening e.g. Sahin PNAS 2007, Zhang PLoS One 2011 Uhlmann Mol Sys Biol 2012 Regulation of gene expression miRNA/transcription faktor interactions e.g. Ward Oncogene 2012 Burmeister Mol Cell Biol 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 3D-cultures co-cultures mouse models Signaling pathways: MAPK PI3K NF- B TGF- Division Molecular Genome Analysis mostly breast cancer (some GIST)

14 Aims – molecular mechanisms of disease Metastasis formation Drug resistance Tumor – stroma interactions miRNAs/TFs & signaling vs. molecular alterations Basic research – systems biological modeling – clinical translation

15 MetastasisDrug resistance Tumor Stroma interactions miRNA-signaling Networks Transcription factor Networks of metastasis Bioinformatics quantitative Modeling Epigenetic variation Genetic variation TF/molecular Variation Networks in cancer In vivo mouse models Pathology: Clinical validation Gynecology Clinical studies molecular Tools Data management

16 SMBCa Networking

17 How visualize relations within (and beyond) the consortium? Circos plot

18 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?)


20 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

21 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 exchange of information, methods, samples and data.

22 e:Med and our background/environment (BMBF funding) DHGP NGFN – cDNA platform -> Resources NGFN-2 – SMP-Cell -> cellular assays, protein localization NGFN-Plus – Integrated Genome Network Cellular Systems Genomics -> Breast cancer signaling NGFN-Plus – Integrated Genome Network Environmental Diseases (Stefan Schreiber) -> NF-KB signaling NGFN-Transfer Project Genome subfractionation for targeted sequencing (Hugo Katus) SysMed: Breast Sys – Identifying novel therapeutic strategies for breast cancer by data-driven modeling of tumor progression 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

23 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 !

24 ToDos Concept for commercial or clinical exploitation –Commercial –Clinical – small-scale studies? Ethical and legal considerations –Patient material –Patient data –Mouse models –Other?

25 3.8 key references from network members with relation to the e:Med project (max. 1 page) TopicCitationScience field Cancer genome sequencingNature 488: (2012)Genetic variation High-throughput cellular screeningNat Cell Biol 14: (2012)Phenotypic analysis Qualitative and quantitative miRNA- signaling network interactions Mol Syst Biol 8: 570. (2012)Molecular analysis/ Systems Biology miRNAs in breast cancer drug resistance Oncogene: doi: /onc (2012) Drug resistance International collaboration on minimum reporting guidelines & data exchange Nat Biotechnol 26: (2008), Nat Biotechnol 26: Reporting standards Quantitative protein network analysisPNAS 104: (2007)Molecular analysis TEXTEXTEXTEXTEXT [SW1] [SW1] Cancer epigenome … TEXTEXTEXTEXTEXT [SW1] Please insert up to three top-notch publications of yours (IF the higher the better) from within the last five years.[SW1]

26 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

27 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) draft by Dec 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

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