Title: Biomarker Prediction from Genomic Sequencing Data

Duration: 01.08.2023 – 31.07.2027

Research Area: Bioinformatics

Our cross-disciplinary project involves different concepts of Systems Biology, Bioinformatics, and Data science, in which we integrate different omics data levels (e.g., DNA, RNA). In particular, we investigate various aspects at the molecular level like the response of cancer cells to ionizing radiation (IR) or the role of the immune system due to cardiac regeneration, among many others. By this means, we analyze heterogeneous data (e.g., DNA-seq and RNA-seq) from databases like TCGA, GEO, and data obtained from experimental partners to understand the impact of different molecular profiles for guiding more personalized treatment strategies.

Problem and Aims

Different AI approaches will analyze large-scale genomic data to identify key molecular pathways affected by different treatments like IR or stem cell transplantation, discern patterns in genetic or regulatory changes, and predict the effectiveness of IR therapy based on specific tumor profiles. By integrating AI into this research, the project can achieve more precise and comprehensive insights into personalized cancer treatment strategies.

Technology

This project will combine current sequencing technologies with Systems Biology approaches and predictive AI approaches, such as AI-guided diffusion network prediction and topology network predictions that might be instrumental in understanding complex cellular responses.

Outlook

Our work is embedded around the BMBF-funded project OLCIR, in which we will contribute towards the more in-depth investigation of the molecular genetic mechanisms of lung cancer cells and analyze the current AI capabilities to predict established and novel diagnostic markers leading to more personalized therapies.

Publications

• Limitations in next-generation sequencing-based genotyping of breast cancer polygenic risk score loci. Alexandra Baumann, Christian Ruckert, Christoph Meier, Tim Hutschenreiter, Robert Remy et al. (Pre-print 2023) https://www.medrxiv.org/content/10.1101/2023.12.15.23298835v1
• NaviCenta – The disease map for placental research. Julia Scheel, Matti Hoch, Markus Wolfien, Shailendra Gupta (Placenta 2023)https://doi.org/10.1016/j.placenta.2023.09.007
• CCR2 macrophage response determines the functional outcome following cardiomyocyte transplantation. Praveen Vasudevan, Markus Wolfien, Heiko Lemcke, Cajetan Immanuel Lang, Anna Skorska, Ralf Gaebel, Anne-Marie Galow, Dirk Koczan, Tobias Lindner, Wendy Bergmann, Brigitte Mueller-Hilke, Brigitte Vollmar, Bernd Joachim Krause, Olaf Wolkenhauer, Gustav Steinhoff, Robert David (Genome Medicine 2023)https://genomemedicine.biomedcentral.com/articles/10.1186/s13073-023-01213-3
• In silico investigation of molecular networks linking gastrointestinal diseases, malnutrition, and sarcopenia. Matti Hoch, Luise Ehlers, Karen Bannert, Christina Stanke, David Brauer, Vanessa Caton, Georg Lamprecht, Olaf Wolkenhauer, Robert Jaster, Markus Wolfien (Frontiers in Nutrition 2022) https://doi.org/10.3389/fnut.2022.989453

Team

Lead

• Dr. Markus Wolfien

Team Members

• Alexandra Baumann

Partner

• University of Rostock, Dept. of Systems Biology and Bioinformatics