Project Multi-Disciplinary Identification of Lineage-Specific Signaling Dependencies in Cancer (MILES)
During the past years, major collaborative efforts have enabled the mapping of virtually all genomic lesions that can contribute to the development of tumors in different tissues. However, each cancer lineage displays a unique signaling network that modulates the function of individual genomic lesions. Thus, it is not surprising that efficacy of cancer drugs that disrupt these signaling networks at the molecular level not only depend on the expression of the driving genomic lesion, but also on the origin of the tumor precursor tissue. The major goal of the junior group leader alliance "Multi-Disciplinary Identification of Lineage-Specific Signaling Dependencies in Cancer" (MILES) is to identify unique signaling networks within individual tumor lineages that mediate tumor growth. Emphasis will be placed on the integration of the individual life science and information science disciplines and the translation of the results into therapeutic strategies for the treatment of cancer patients. Therefore, our project aims to answer three major questions:
(1) How can we integrate genomic data to understand lineage-specific signaling dependencies of transcription regulators?
(2) How can we enable efficient and secure large-scale data handling to study these datasets in a multi-disciplinary environment?
(3) How can we dissect lineage-specific signaling dependencies of transcriptional regulators on a molecular level?
The MILES junior group leader alliance is a consortium funded by the German Federal Ministry of Education and Research (BMBF) within the e:Med call that promoted systems-oriented research into diseases and preventive measures by linking life sciences with information sciences. It consists of 5 sub-project leaders from the University of Cologne and the Karlsruhe Institute of Technology. Within the junior group leader alliance, the Critical Information Infrastructures Research Group is responsible for developing concepts to ensure privacy and integrity of sensitive medical information, which cannot be anonymized (e.g., genomic data), in cloud computing environments (sub-project 5 - Processing sensitive medical information in cloud computing environments while ensuring information security & privacy).