Breast cancer is the most frequent cause of death from cancer among women. Significant but slow progress in the reduction of mortality has been achieved due to earlier diagnosis and use of adjuvant treatment. These improvements, however, have been paid for by substantial overtreatment and undertreatment due to insufficient patient selection. The optimal value of new treatment options will only be revealed by improved patient and target selection based on a detailed and comprehensive molecular characterization of the tumor and the host. Furthermore, primary and secondary resistance against anti-cancer therapies are major negative factors impacting survival and quality of life. Within IG-CSG we aim (1) to identify and test diagnostic and predictive markers for patient stratification and improved therapy decision and (2) to better understand the physiological processes and mechanisms that are connected to drug resistance and breast cancer progression.
Along these lines, the central aims of the IG-CSG network are in two complementary themes, the first having a technical science focus and the latter a clear medical. The former is represented by resources, high-throughput as well as high-end small-scale technologies, strategies for functional gene analysis as well as concepts for data modeling and signaling network reconstruction. These technologies, resources, and strategies are made available also to other research networks within NGNF. The latter is represented by a strong clinical involvement. The different subprojects forming IG-CSG connect these themes in to generate synergies promoting scientific discoveries as well as clinical progress. This is achieved by formulating a common set of aims for the network:

• to apply qualitative and quantitative functional genomic, proteomic, and cell biological strategies, in order to analyze the dynamics and cross-talk of signaling pathways and networks in vitro and in vivo.
• to generate systems genomics models that predict and validate novel markers for diagnosis and prognosis as well as target molecules with potential for therapeutic intervention.
• to validate the gained knowledge in breast cancer, where drug resistance mechanisms shall be elucidated. Here we aim to define routes that shall prevent acquired drug resistance and lead to tumor remission.

Our successes are reported in scientific publications.

The Integrated Genome network IG-CSG is part of the National Program of Medical Genome Research (NGFN-Plus) and is funded by the German Federal Ministry of Education and Research (Bundesministerium für Bildung und Forschung - BMBF).