BIMSB boosts cancer research with new research group on “Evolutionary and Cancer Genomics” headed by Roland Schwarz
How do certain genetic predispositions cause diseases – and how can they be identified at the molecular level? “The relationship between genotypes and phenotypes is still one of the major topics in life sciences,” says Roland Schwarz. “Using large data sets and modern bioinformatics processes, we can now explore this relationship in detail.” The bioinformatician has been lead investigator of the new BIMSB junior research group on “Evolutionary and Cancer Genomics” since October 2016. Schwarz wants his work, particularly in the area of cancer research, to contribute towards ensuring that diseases are diagnosed earlier and treated more effectively.
Roland Schwarz obtained a doctorate at the University of Würzburg, where he conducted research on the evolution of bacterial microorganisms. He subsequently worked at the University of Cambridge branch of charitable organization Cancer Research UK, before moving to the European Molecular Biology Laboratory’s European Bioinformatics Institute (EMBL-EBI) in Hinxton, UK, where he focused on genome analyses of cancer patients and, in particular, addressed the question of how cancer evolves in the body of a patient. As part of a clinical study, he and his team developed methods to reconstruct the genealogy of cancer in patients and learn more about how structural changes in the genome affect the development of tumors. “We now have a fairly good idea about the mutations that are present in tumors. I would like my new working group to help us better understand their function,” says Schwarz.
To this end, the research group wants to sequence and analyze the primary tumor and metastases in each individual patient in order to understand how transcriptome, proteome and metabolome are modified in response to changes in the genome. External data such as patient behavior and environmental factors are also taken into consideration in the research. Schwarz is developing customized statistical methods and machine learning with a view to integrating a variety of heterogeneous data sets. A prototype study is currently underway and will run until February 2017. “We want to get a holistic picture of how cancer occurs and develops in the body,” he says. Together with his research group, Schwarz is keen to make a significant contribution towards achieving this goal.
Featured image: Keith Heppell
