Systems View on the Regulation of Cellular State
Cells represent the fundamental unit of life. Within tissues, cells are in constant interaction with their environment. Our goal is to elucidate disease mechanisms that are related to aberrant regulation of cell states. We develop computational models based on systems biology and data analysis tools with bioinformatics and machine learning methods suitable for integrating different types of genomics data or combining datasets across studies. We apply them in our own research that utilizes large omics datasets and collect new genomics data from cell models and human studies.
Childhood acute lymphoblastic leukemia The most common type of cancer in children develops as a consequence of arrested cell differentiation of early lymphoid precursor cells. We study changes in the gene regulatory network across different leukemia subtypes. To translate genomics into clinical practice, we also develop data analysis tools that allow determining at unprecedented resolution the alterations in cancer cells.
Cell-cell interaction in disease development In addition to regulatory networks that operate inside cells, we study how these interactions extend to tissue level. Inflammation and cellular stress influence cell states within a tissue. We are addressing the question what role changes in cell-cell-interactions have in this process. By characterizing such tissue-level regulatory circuits, we can discover new therapy targets that would enable reverting the changes in cell states at early stage during disease progression. Later at advanced disease state it would be more challenging to repair tissue damage. We are focusing on the role of endothelial cells and macrophages in context of coronary artery disease development. Cell-cell interactions have an important role also in cancer.
A central future goal in our research is to connect the molecular and cell-interaction levels together, in order to better model the dynamics of cell state changes.