Thanks to early detection methods and innovative therapies, medical science controls cancer better than ever before. However, as the treatment modalities improved, the cancer incidence rose and scientists discovered more and more specific forms of cancer. This and the complex molecular nature of cancer create huge challenges for medical science.
Predicting the Characteristics of Complex Signaling Pathways
Scientists pull out all stops in their quest of untangling the complex regulatory networks in cancer cells. They refer to a variety of new research approaches among them new methods known as omics*. The name refers to methods such as exome and transcriptome sequencing as well as proteomics. The challenge is to integrate the tremendous amount of generated data to arrive at a coherent overall picture. Armed with these obtained data, the scientists want to demonstrate the impact of mutations and changes of expression levels. This may also help to understand not yet identified mechanisms or to predict cell activities using computational approaches.
The EU-funded research consortium CanPathPro should achieve significant progress regarding these challenges: Scientists from six nations come together to bundle the necessary expertise for the analysis of signaling pathways associated with cancer. The scientists use a combination of experimental cancer research and systems biology methods to formulate and test their hypotheses. The Horizon 2020 initiative promotes the research by providing 11 million Euros for the entire five-year project.
Dynamic Models for Big Data
The young investigator group of Dr. Jan Hasenauer at the Institute of Computational Biology (ICB) of the Helmholtz Zentrum München receives about one million Euros of the total funding. While the other involved scientists gather huge data volumes, the Helmholtz group of scientists will mainly work on making these data manageable. „Big Data is certainly an always present concern in modern cancer research“, explains Jan Hasenauer. „We will provide mechanistic dynamical models to organize and interpret the tremendous amounts of data provided by new experimental approaches“.
The data collected in the CanPathPro project will be used to predict the behavior of cancer-associated signaling pathways and to reconcile the predictions with patient data. This will assist in selecting optimal therapies and in discovering new drug targets. The developed models allow for the incorporation of patient-specific data. This may render the models also a valuable tool for the study of other diseases.
* The word ‚omics‘ refers to several technologies used mainly for the elucidation of biomedical processes. The names of these technologies all end in ‚omics‘. Therefore, the identical ending became the informal name for the entire group of biomedical technologies. The common characteristic of all these technologies is their purpose of describing a certain class of molecules in a sample in detail. For example, scientists use the methods of proteomics to detect all proteins in a sample. Thanks to technical improvements, this formerly challenging approach is now more feasible. Improved technologies paved the way toward more and more data gathering. In this project, the Helmholtz scientists want to make the data flood more manageable.
The project is coordinated by Alacris Theranostics GmbH (Germany) and carried out by leading European research institutions and SMEs: Alacris Theranostics GmbH (Germany); European Centre for Biological and Medical Research (France); Netherlands Cancer Institute (Netherlands); Leibniz Institute on Aging – Fritz-Lipmann Institute (Germany); Helmholtz Centre Munich (Germany); Spanish National Research Council (Spain); Biognosys AG (Switzerland); Simula Research Laboratory AS (Norway); Finovatis SAS (France).
As German Research Center for Environmental Health, Helmholtz Zentrum München pursues the goal of developing personalized medical approaches for the prevention and therapy of major common diseases such as diabetes mellitus and lung diseases. To achieve this, it investigates the interaction of genetics, environmental factors and lifestyle. The Helmholtz Zentrum München has about 2,300 staff members and is headquartered in Neuherberg in the north of Munich. Helmholtz Zentrum München is a member of the Helmholtz Association, a community of 18 scientific-technical and medical-biological research centers with a total of about 37,000 staff members.
The Institute of Computational Biology (ICB) develops and applies methods for the model-based description of biological systems, using a data-driven approach by integrating information on multiple scales ranging from single-cell time series to large-scale omics. Given the fast technological advances in molecular biology, the aim is to provide and collaboratively apply innovative tools with experimental groups in order to jointly advance the understanding and treatment of common human diseases.
Contact for the media:
Department of Communication, Helmholtz Zentrum München – German Research Center for Environmental Health (GmbH), Ingolstädter Landstr. 1, 85764 Neuherberg – Tel. +49 89 3187 2238 – Fax: +49 89 3187 3324 – E-mail:
Scientific contact at Helmholtz Zentrum München:
Dr. Jan Hasenauer, Helmholtz Zentrum München – Deutsches Forschungszentrum für Gesundheit und Umwelt (GmbH), Institute of Computational Biology (ICB), Ingolstädter Landstr. 1, 85764 Neuherberg- Tel. +49 89 3187 2788 – E-mail: