Big Data in Cancer: Curse or Cure?
Thursday 9 June - 16:00-16:20
photo intervenant Roland EILS
German Cancer Research Center (DKFZ), Heidelberg, Germany

Roland Eils received his PhD in Mathematics from the University of Heidelberg, Germany, in 1995. He is currently a Professor at the University of Heidelberg and holds a joint appointment as division head at the German Cancer Research Center (DKFZ) in Heidelberg. He is founding and managing Director of BioQuant, the Center for Quantitative Analysis of Molecular and Cellular Biosystems at the University of Heidelberg. His research focuses on the integration of tools from mathematical modeling, image analysis and informatics into life science research and he is a leading figure in systems biology and bioinformatics. In his research, he is applying various methods on issues related to human health such as viral infection, cellular death pathways and cancer genomics. He has published more than 280 papers in peer-reviewed journals over the past ten years and received a total of more than 10 000 citations from them. He is co-editor of the book Computational Systems Biology (Elsevier) and is the editor-in-Chief of, the magazine for systems biology research in germany. Professor eils is coordinating the several systems biology and systems medicine consortia and is the coordinator of HD-HUB, the Heidelberg Center for Human Bioinformatics. He is a member of the International Society for Systems Biology (ISSB). In 1999 he was awarded the BioFuture Prize, the most prestigious prize for young researchers in germany, and in 2014 he received the Heidelberg Molecular Life Sciences (HMLS) Investigator Award.


Recent developments in DNA sequencing technology now enable sequencing of the human genome for less than US$1,000 facilitating applications in basic and translational cancer research. These cost reductions have spurred initiatives such as the UK-based 100,000 Genomes Project, the International Cancer Genome Consortium to pursue sequencing and analysis of large numbers of patient genomes. Hundreds of thousands of patient genomes will become sequenced in the next few years, and in Germany alone we expect completion of >25,000 genomes by 2018. While those estimates are made on the basis that for each tumor only one sample is sequenced it has become very clear that averaging over millions of cells in a given tumor sample may hide subtle, but clinically important genomic alterations that are only present in a small fraction of cells. Sequencing of many individual cells per sample will lead to a further, massive explosion of genome sequencing data in the next few years. Thus, an unprecedentedly rich set of “big data” will emerge in cancer and other diseases with the promise to improve patient stratification, diagnostics and personalized medicine. These promises are, however, accompanied by significant threads and challenges: First of all, the fact that whole genome sequences are unequivocally connected to only one individual, ethical and legal considerations for generation, storage, analysis and distribution of genome sequences need to be taken into account. Further, no single institution has the necessary infrastructure to perform analyses of hundreds of thousands of genomes, to store and access them securely and to utilize these data for research and translation. Furthermore, the diversity of analysis pipelines renders data processed in different institutions largely non-comparable. I will present in my presentation recent advances in single cell genomics of patient derived cells. Further, I will discuss promises and challenges of big data in oncology and will outline potential avenues to overcome some of the most pressing hurdles in the field of personalized genomics.