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The FDA approval of targeted therapy with BRAFV600E inhibitors like vemurafenib and dabrafenib in 2011 has been the first major breakthrough in the treatment of metastatic melanoma since almost three decades. Despite increased progression free survival and elevated overall survival rates, complete responses are scarce due to resistance development approximately six months after the initial drug treatment. It was previously shown in our group that melanoma cells under vemurafenib pressure in vitro and in vivo exhibit features of drug-induced senescence. It is known that some cell types, which undergo this cell cycle arrest, develop a so-called senescence associated secretome and it has been reported that melanoma cell lines also upregulate the expression of different factors after senescence induction. This work describes the effect of the vemurafenib-induced secretome on cells. Conditioned supernatants of vemurafenib-treated cells increased the viability of naive fibroblast and melanoma cell lines. RNA analysis of donor melanoma cells revealed elevated transcriptional levels of FGF1, MMP2 and CCL2 in the majority of tested cell lines under vemurafenib pressure, and I could confirm the secretion of functional proteins. Similar observations were also done after MEK inhibition as well as in a combined BRAF and MEK inhibitor treatment situation. Interestingly, the transcription of other FGF ligands (FGF7, FGF17) was also elevated after MEK/ERK1/2 inhibition. As FGF receptors are therapeutically relevant, I focused on the analysis of FGFR-dependent processes in response to BRAF inhibition. Recombinant FGF1 increased the survival rate of melanoma cells under vemurafenib pressure, while inhibition of the FGFR pathway diminished the viability of melanoma cells in combination with vemurafenib and blocked the stimulatory effect of vemurafenib conditioned medium. The BRAF inhibitor induced secretome is regulated by active PI3K/AKT signaling, and the joint inhibition of mTor and BRAFV600E led to decreased senescence induction and to a diminished induction of the secretome-associated genes. In parallel, combined inhibition of MEK and PI3K also drastically decreased mRNA levels of the relevant secretome components back to basal levels.
In summary, I could demonstrate that BRAF inhibitor treated melanoma cell lines acquire a specific PI3K/AKT dependent secretome, which is characterized by FGF1, CCL2 and MMP2. This secretome is able to stimulate other cells such as naive melanoma cells and fibroblasts and contributes to a better survival under drug pressure. These data are therapeutically highly relevant, as they imply the usage of novel drug combinations, especially specific FGFR inhibitors, with BRAF inhibitors in the clinic.
Since its first experimental implementation in 2005, single-molecule localization microscopy (SMLM) emerged as a versatile and powerful imaging tool for biological structures with nanometer resolution. By now, SMLM has compiled an extensive track-record of novel insights in sub- and inter- cellular organization.\\
Moreover, since all SMLM techniques rely on the analysis of emission patterns from isolated fluorophores, they inherently allocate molecular information $per$ $definitionem$.\\
Consequently, SMLM transitioned from its origin as pure high-resolution imaging instrument towards quantitative microscopy, where the key information medium is no longer the highly resolved image itself, but the raw localization data set.\\
The work presented in this thesis is part of the ongoing effort to translate those $per$ $se$ molecular information gained by SMLM imaging to insights into the structural organization of the targeted protein or even beyond. Although largely consistent in their objectives, the general distinction between global or segmentation clustering approaches on one side and particle averaging or meta-analyses techniques on the other is usually made.\\
During the course of my thesis, I designed, implemented and employed numerous quantitative approaches with varying degrees of complexity and fields of application.\\ \\
In my first major project, I analyzed the localization distribution of the integral protein gp210 of the nuclear pore complex (NPC) with an iterative \textit{k}-means algorithm. Relating the distinct localization statistics of separated gp210 domains to isolated fluorescent signals led, among others, to the conclusion that the anchoring ring of the NPC consists of 8 homo-dimers of gp210.\\
This is of particular significance, both because it answered a decades long standing question about the nature of the gp210 ring and it showcased the possibility to gain structural information well beyond the resolution capabilities of SMLM by crafty quantification approaches.\\ \\
The second major project reported comprises an extensive study of the synaptonemal complex (SNC) and linked cohesin complexes. Here, I employed a multi-level meta-analysis of the localization sets of various SNC proteins to facilitate the compilation of a novel model of the molecular organization of the major SNC components with so far unmatched extend and detail with isotropic three-dimensional resolution.\\
In a second venture, the two murine cohesin components SMC3 and STAG3 connected to the SNC were analyzed. Applying an adapted algorithm, considering the disperse nature of cohesins, led to the realization that there is an apparent polarization of those cohesin complexes in the SNC, as well as a possible sub-structure of STAG3 beyond the resolution capabilities of SMLM.\\ \\
Other minor projects connected to localization quantification included the study of plasma membrane glycans regarding their overall localization distribution and particular homogeneity as well as the investigation of two flotillin proteins in the membrane of bacteria, forming clusters of distinct shapes and sizes.\\ \\
Finally, a novel approach to three-dimensional SMLM is presented, employing the precise quantification of single molecule emitter intensities. This method, named TRABI, relies on the principles of aperture photometry which were improved for SMLM.\\
With TRABI it was shown, that widely used Gaussian fitting based localization software underestimates photon counts significantly. This mismatch was utilized as a $z$-dependent parameter, enabling the conversion of 2D SMLM data to a virtual 3D space. Furthermore it was demonstrated, that TRABI can be combined beneficially with a multi-plane detection scheme, resulting in superior performance regarding axial localization precision and resolution.\\
Additionally, TRABI has been subsequently employed to photometrically characterize a novel dye for SMLM, revealing superior photo-physical properties at the single-molecule level.\\
Following the conclusion of this thesis, the TRABI method and its applications remains subject of diverse ongoing research.
In this work models for molecular networks consisting of ordinary differential equations are extended by terms that include the interaction of the corresponding molecular network with the environment that the molecular network is embedded in. These terms model the effects of the external stimuli on the molecular network. The usability of this extension is demonstrated with a model of a circadian clock that is extended with certain terms and reproduces data from several experiments at the same time.
Once the model including external stimuli is set up, a framework is developed in order to calculate external stimuli that have a predefined desired effect on the molecular network. For this purpose the task of finding appropriate external stimuli is formulated as a mathematical optimal control problem for which in order to solve it a lot of mathematical methods are available. Several methods are discussed and worked out in order to calculate a solution for the corresponding optimal control problem. The application of the framework to find pharmacological intervention points or effective drug combinations is pointed out and discussed. Furthermore the framework is related to existing network analysis tools and their combination for network analysis in order to find dedicated external stimuli is discussed.
The total framework is verified with biological examples by comparing the calculated results with data from literature. For this purpose platelet aggregation is investigated based on a corresponding gene regulatory network and associated receptors are detected. Furthermore a transition from one to another type of T-helper cell is analyzed in a tumor setting where missing agents are calculated to induce the corresponding switch in vitro. Next a gene regulatory network of a myocardiocyte is investigated where it is shown how the presented framework can be used to compare different treatment strategies with respect to their beneficial effects and side effects quantitatively. Moreover a constitutively activated signaling pathway, which thus causes maleficent effects, is modeled and intervention points with corresponding treatment strategies are determined that steer the gene regulatory network from a pathological expression pattern to physiological one again.