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Recent advances in the field of cancer immunotherapy have enabled this therapeutic approach to enter the mainstream of modern cancer treatment. In particular, adoptive T cell therapy (ACT) is a potentially powerful immunotherapy approach that relies on the administration of tumor-specific T cells into the patient. There are several strategies to obtain tumor-reactive cytotoxic T lymphocytes (CTLs), which have already been shown to induce remarkable responses in the clinical setting. However, there are concerns and limitations regarding the conventional approaches to obtain tumor-reactive T cells, such as accuracy of the procedure and reproducibility. Therefore, we aimed to develop two approaches to improve the precision and efficacy of tumor-reactive T cells therapy. These two techniques could constitute effective, safe and broadly applicable alternatives to the conventional methods for obtaining tumor-specific CTLs.
The first approach of this study is the so called “Doublet Technology”. Here, we demonstrate that peptide-human leukocyte antigen-T cell receptor (pHLA-TCR) interactions that involve immune reactive peptides are stable and strong. Therefore, the CTLs that are bound by their TCR to tumor cells can be selected and isolated through FACS-based cell sorting taking advantage of this stable interaction between the CTLs and the target cells. The CTLs from acute myeloid leukemia (AML) patients obtained with this technique show cytolytic activity against blast cells suggesting a potential clinical use of these CTLs. “Doublet Technology” offers a personalized therapy in which there is no need for a priori knowledge of the exact tumor antigen.
The second approach of this study is the Chimeric Antigen Receptor (CAR) Technology. We design several CARs targeting the B-Cell Maturation Antigen (BCMA). BCMA CAR T cells show antigen-specific cytolytic activity, production of cytokines including IFN-γ and IL-2, as well as productive proliferation. Although we confirm the presence of soluble BCMA in serum of multiple myeloma (MM) patients, we demonstrate that the presence of soluble protein does not abrogate the efficacy of BCMA CAR T cells suggesting that BCMA CAR T cells can be used in the clinical setting to treat MM patients. The high antigen specificity of CAR T cells allows efficient tumor cell eradication and makes CAR Technology attractive for broadly applicable therapies.
Biological systems such as cells or whole organisms are governed by complex regulatory networks of transcription factors, hormones and other regulators which determine the behavior of the system depending on internal and external stimuli. In mathematical models of these networks, genes are represented by interacting “nodes” whose “value” represents the activity of the gene.
Control processes in these regulatory networks are challenging to elucidate and quantify. Previous control centrality metrics, which aim to mathematically capture the ability of individual nodes to control biological systems, have been found to suffer from problems regarding biological plausibility.
This thesis presents a new approach to control centrality in biological networks. Three types of network control are distinguished: Total control centrality quantifies the impact of gene mutations and identifies potential pharmacological targets such as genes involved in oncogenesis (e.g. zinc finger protein GLI2 or bone morphogenetic proteins in chondrocytes). Dynamic control centrality describes relaying functions as observed in signaling cascades (e.g control in mouse colon stem cells). Value control centrality measures the direct influence of the value of the node on the network (e.g. Indian hedgehog as an essential regulator of proliferation in chondrocytes). Well-defined network manipulations define all three centralities not only for nodes, but also for the interactions between them, enabling detailed insights into network pathways.
The calculation of the new metrics is made possible by substantial computational improvements in the simulation algorithms for several widely used mathematical modeling paradigms for genetic regulatory networks, which are implemented in the regulatory network simulation framework Jimena created for this thesis.
Applying the new metrics to biological networks and artificial random networks shows how these mathematical concepts correspond to experimentally verified gene functions and signaling pathways in immunity and cell differentiation. In contrast to controversial previous results even from the Barabási group, all results indicate that the ability to control biological networks resides in only few driver nodes characterized by a high number of connections to the rest of the network. Autoregulatory loops strongly increase the controllability of the network, i.e. its ability to control itself, and biological networks are characterized by high controllability in conjunction with high robustness against mutations, a combination that can be achieved best in sparsely connected networks with densities (i.e. connections to nodes ratios) around 2.0 - 3.0.
The new concepts are thus considerably narrowing the gap between network science and biology and can be used in various areas such as system modeling, plausibility trials and system analyses.
Medical applications discussed in this thesis include the search for oncogenes and pharmacological targets, as well their functional characterization.
Malignant melanoma is the most severe form of all skin cancers with a particular poor prognosis once metastases have developed. Angiogenesis, the formation of new blood vessels, is a prominent feature of human melanoma, which have angiogenic activity already early in development. This is at least partly ascribed to the action of MAPK- and PI3K pathways which are hyperactivated in most melanoma. Animal models which combine in depth in vivo examinations with the opportunity to perform small molecular screens are well suited to gain a more detailed insight into how this type of cancer modulates its angiogenic program. Here, a first transgenic melanoma angiogenesis model was established in the fish species Oryzias latipes (Japanese medaka). In this model, tumors are generated by the pigment cell-specific expression of the oncogenic receptor tyrosine kinase Xmrk. Xmrk is a mutated version of the fish Egfp. Furthermore, to get an angiogenesis model, a medaka line with endothelial cell specific GFP expression was used. By using crosses between these Xmrk- and GFP transgenic fishes, it was shown that angiogenesis occurs in a reactive oxygen species- and NF-κB-dependent manner, but was hypoxia-independent. It was observed that blood vessel sprouting and branch point formation was elevated in this model and furthermore that sprouting could even be induced by single transformed cells. The mouse melanocytes expressing the oncogenic receptor tyrosine kinase Xmrk as well human melanoma cells, which display various oncogenic alterations, produced pro-angiogenic factors, most prominently angiogenin, via NF-κB signaling. Furthermore, inhibiting NF-κB action prevented tumor angiogenesis and even led to the regression of existing tumor blood vessels. In summary, the present medaka melanoma angiogenesis model displays a high sensitivity for angiogenesis detection and is perfectly suited as in vivo model for the testing of anti-angiogenesis inhibitors, as exemplified by the NF-kappaB inhibitor.
Furthermore, results indicate that it might be a promising anti-tumor strategy to target signaling pathways such as the NF-κB pathway which are able to induce angiogenesis-dependent as well as -independent pro-tumorigenic effects.
The three closely related PUB proteins PUB22, PUB23 and PUB24 were described as important regulators for PTI signaling and plant immunity. To find cellular targets regulated by the action of the PUB triplet we performed a yeast two-hybrid screen to identify candidate target proteins of PUB22. We could identify Exo70B2 as a target protein of PUB22, which is ubiquitinated by the E3-ubiquitin ligase and consequently degraded in response to flg22 perception. The importance of Exo70B2 for immunity was shown by reverse genetics, demonstrating that exo70B2 mutants are impaired in PTI signaling and plant immunity.
Exo70B2 is one of 23 homologs of the yeast Exo70p in Arabidopsis thaliana, which is a subunit of an octameric protein complex, termed the exocyst. The exocyst complex is required for the tethering of post-Golgi vesicles to specific target membranes and thus an important component of intracellular vesicle trafficking. The elucidated function of Exo70B2 and its requirement for PTI signaling is a novel finding and similar functions had not yet been described for the exocyst complex or subunits thereof in plants. Additional target proteins of PUB22 are also predicted to be involved in vesicle trafficking processes, suggesting that PUB22 has specialized to regulate trafficking protein complexes required for PTI signaling.
Furthermore, the presented work suggests a mechanism for the regulation of Exo70B2 ubiquitination by PUB22. PUB22 was shown to be intrinsically instable due to its autocatalytic ubiquitination activity. Flg22 treatment induced the rapid post-translational stabilization of PUB22. This potentially enables the ligase to efficiently interact with Exo70B2, resulting in its polyubiquitination and 26S-proteasome-dependent turnover.
Staphylococcus aureus (SA) causes nosocomial infections including life threatening sepsis by multi-resistant strains (MRSA). It has the ability to form biofilms to protect it from the host immune system and from anti staphylococcal drugs. Biofilm and planctonic life style is regulated by a complex Quorum-Sensing (QS) system with agr as a central regulator. To study biofilm formation and QS mechanisms in SA a Boolean network was build (94 nodes, 184 edges) including two different component systems such as agr, sae and arl. Important proteins such as Sar, Rot and SigB were included as further nodes in the model. System analysis showed there are only two stable states biofilm forming versus planctonic with clearly different subnetworks turned on. Validation according to gene expression data confirmed this. Network consistency was tested first according to previous knowledge and literature. Furthermore, the predicted node activity of different in silico knock-out strains agreed well with corresponding micro array experiments and data sets. Additional validation included the expression of further nodes (Northern blots) and biofilm production compared in different knock-out strains in biofilm adherence assays. The model faithfully reproduces the behaviour of QS signalling mutants. The integrated model allows also prediction of various other network mutations and is supported by experimental data from different strains. Furthermore, the well connected hub proteins elucidate how integration of different inputs is achieved by the QS network. For in silico as well as in vitro experiments it was found that the sae-locus is also a central modulator of biofilm production. Sae knock-out strains showed stronger biofilms. Wild type phenotype was rescued by sae complementation. To elucidate the way in which sae takes influence on biofilm formation the network was used and Venn-diagrams were made, revealing nodes regulated by sae and changed in biofilms. In these Venn-diagrams nucleases and extracellular proteins were found to be promising nodes. The network revealed DNAse to be of great importance. Therefore qualitatively the DNAse amount, produced by different SA mutants was measured, it was tried to dissolve biofilms with according amounts of DNAse and the concentration of nucleic acids, proteins and polysaccharides were measured in biofilms of different SA mutants.
With its thorough validation the network model provides a powerful tool to study QS and biofilm formation in SA, including successful predictions for different knock-out mutant behaviour, QS signalling and biofilm formation. This includes implications for the behaviour of MRSA strains and mutants. Key regulatory mutation combinations (agr–, sae–, sae–/agr–, sigB+, sigB+/sae–) were directly tested in the model but also in experiments. High connectivity was a good guide to identify master regulators, whose detailed behaviour was studied both in vitro and in the model. Together, both lines of evidence support in particular a refined regulatory role for sae and agr with involvement in biofilm repression and/or SA dissemination. With examination of the composition of different mutant biofilms as well as with the examination of the reaction cascade that connects sae to the biofilm forming ability of SA and also by postulating that nucleases might play an important role in that, first steps were taken in proving and explaining regulatory links leading from sae to biofilms. Furthermore differences in biofilms of different mutant SA strains were found leading us in perspective towards a new understanding of biofilms including knowledge how to better regulate, fight and use its different properties.