Project Details
Mathematical modeling of homeostasis and oncogenesis in mature T-cells
Applicant
Professor Dr. Ingo Röder
Subject Area
Pathology
Hematology, Oncology
Immunology
Hematology, Oncology
Immunology
Term
from 2013 to 2020
Project identifier
Deutsche Forschungsgemeinschaft (DFG) - Project number 225165194
The maintenance of life-long T-cell diversity, i.e. the abundance of different T-cell receptors (TCR), is a central feature of the adaptive immune defense. Understanding the mechanisms that lead to a robust, polyclonal T-cell repertoire is a basic biological question. However, it is also clinically relevant, because there is evidence that the polyclonal nature of T-cell homeostasis prevents the outgrowth of mature T-cell leukemia/lymphoma (MTCL). Although several T-cell transforming oncogenes (e.g. ALK, TCL1) and effected downstream events (e.g. IL-2 signaling) have been identified, it is currently not resolved how these are related to the control of a healthy, polyclonal T-cell population. Another feature that might have an important regulatory impact is the heterogeneity of TCR-mediated stimuli in lymph nodes and the circulation of T-cells between different stimulatory regions. To address these and other open questions, RP4 will provide an explanatory mathematical modeling framework of mature T-cell organization, which will be applied to the homeostatic and the malignant situation. Specifically, we will combine different modeling techniques, with the aim to arrive at a quantitative, multiscale description of physiological and malignant T-cell clonality. In an iterative process of formulating biologically meaningful model assumptions, providing testable predictions, and experimental validation/falsification of the theoretical results, RP4 will play a central role within the CONTROL-T consortium, by integrating the different experimental insights. The modeling will substantially contribute to a deeper systemic understanding of T-cell organization and, therefore, also fostering the design of new therapeutic strategies for MTCL.
DFG Programme
Research Units