Genetic and Microenvironmental Pathway Regulation in CLL

Chronic lymphocytic leukemia (CLL) is a cancerous disease affecting mature B-cells which accumulate in the peripheral blood and in the lymphoid organs. CLL is a very heterogeneous disease with some patients experience a very indolent course of disease without therapy indication, while others show a very aggressive course of disease, require early treatment and eventually relapse afterwards. The reason for this heterogeneity is that CLL tumor cells use very different strategies to 1. avoid anti-tumor immune attacks and programmed cells death and 2. to increase the growth rate of tumor cells as compared to normal cells, often in absence of external activation signals. Independent of whether these strategies are caused by genetic defects or a general miscommunication of CLL tumor cells with the direct cellular surrounding (the microenvironment), they eventually contribute to a deregulation of a variety of different signalling pathways, which affects disease progression, therapy success and relapse. The definition of individual markers that accurately predict disease progression, therapy response and/or a potential disease relapse is however challenging, as different patients show a very diverse pattern of individual genetic and microenvironmental defects in a number of different critical regulators along different signalling pathways. While the number of these markers is very high and diverse, these markers line up with a much more restricted set of signalling pathways. In this project we thus suggest to first determine the impact of individual genetic and microenvironmental defects on signalling pathway regulation. In the second step patients with a similar pathway regulation network (which consists of a set of predefined signalling pathways) shall be summarized to so-called CLL Signalotypes. We hypothesize that these CLL Signalotypes show a lower degree of heterogeneity as compared to the classical approach using individual genetic and microenvironmental markers and are thus better suited to predict disease progression and therapy response. To evaluate this novel Signalotype concept we will apply the following experimental design. 1. Analysis of genetic defects using DNA sequencing, 2. Analysis of microenvironmental defects using RNA sequencing and pathway ac tivation using mass cytometry (CyTOF), 3. Definition of Signalotypes using Bioinformatics and 4. Application of the defined and validated Signalotypes for the prediction of CLL disease progression and therapy response in untreated and treated CLL patients, respectively. In addition we will use our validated CLL mouse model to verify the CLL Signalotype concept also in the murine disease. This will be the first approach in CLL aiming to address the effect of genetic and microenvironmental defects on pathway regulation networks, pathway collaboration and the clinical relevance of our novel Signalotype definitions.

Chronic lymphocytic leukemia (CLL) is a cancerous disease affecting mature B-cells which accumulate in the peripheral blood and in the lymphoid organs. CLL is a very heterogeneous disease with some patients experience a very indolent course of disease without therapy indication, while others show a very aggressive course of disease. The reason for this heterogeneity is the cellular surrounding (the so-called microenvironment) in which CLL cells develop, proliferate and reside and the genetic architecture which includes chromosomal aberrations and/or mutations in different genes. Moreover, an inferior CLL disease progression is often associated with immune defects that allow CLL cells to evade potential anti-tumor immune attacks from specific immune cells e.g. T-cells by deregulated expression of surface markers on tumor cells and/or the corresponding receptors on immune cells. The heterogeneity of the disease is not only reflected in disease progression but also affects therapy strategies and may be associated with disease relapse. The heterogeneity and the complexity of CLL makes it challenging to select biologic Biomarkers which are sufficient to predict CLL outcome or therapy success. In this project we thus aimed to develop a novel strategy that does not focus on a small set of defined Biomarkers but instead characterizes CLL pathway expression patterns. We followed our initial theory that a large amount of genetic, microenvironmental and immune system associated aspects accumulate on a limited number of deregulated signalling pathways which creates a very specific pathway activation pattern that characterizes CLL subgroups and is related to CLL disease progression. CLL subgroups (so-called Signalotypes) were first defined by gene expression analysis and later characterized for their signalling pathway activity profile. We could demonstrate that the activity of a defined set of signalling pathways is indeed related to CLL disease progression. Moreover, we observed that specific genetic aberrations and mutations accumulate in specific CLL Signalotypes. Our concept is thus important for a better prediction of CLL disease progression and can potentially be applied for the selection of optimal treatment strategies.