@article{FeiglStahringerPeindletal.2023,
  author    = {Feigl, Frederik Fabian and Stahringer, Anika and Peindl, Matthias and Dandekar, Gudrun and Koehl, Ulrike and Fricke, Stephan and Schmiedel, Dominik},
  title     = {Efficient redirection of NK cells by genetic modification with chemokine receptors CCR4 and CCR2B},
  series = {International Journal of Molecular Sciences},
  volume    = {24},
  journal   = {International Journal of Molecular Sciences},
  number    = {4},
  issn      = {1422-0067},
  doi       = {10.3390/ijms24043129},
  url       = {http://nbn-resolving.de/urn:nbn:de:bvb:20-opus-304049},
  year      = {2023},
  abstract  = {Natural killer (NK) cells are a subset of lymphocytes that offer great potential for cancer immunotherapy due to their natural anti-tumor activity and the possibility to safely transplant cells from healthy donors to patients in a clinical setting. However, the efficacy of cell-based immunotherapies using both T and NK cells is often limited by a poor infiltration of immune cells into solid tumors. Importantly, regulatory immune cell subsets are frequently recruited to tumor sites. In this study, we overexpressed two chemokine receptors, CCR4 and CCR2B, that are naturally found on T regulatory cells and tumor-resident monocytes, respectively, on NK cells. Using the NK cell line NK-92 as well as primary NK cells from peripheral blood, we show that genetically engineered NK cells can be efficiently redirected using chemokine receptors from different immune cell lineages and migrate towards chemokines such as CCL22 or CCL2, without impairing the natural effector functions. This approach has the potential to enhance the therapeutic effect of immunotherapies in solid tumors by directing genetically engineered donor NK cells to tumor sites. As a future therapeutic option, the natural anti-tumor activity of NK cells at the tumor sites can be increased by co-expression of chemokine receptors with chimeric antigen receptors (CAR) or T cell receptors (TCR) on NK cells can be performed in the future.},
  language  = {en}
}
@article{KaltdorfBreitenbachKarletal.2023,
  author    = {Kaltdorf, Martin and Breitenbach, Tim and Karl, Stefan and Fuchs, Maximilian and Kessie, David Komla and Psota, Eric and Prelog, Martina and Sarukhanyan, Edita and Ebert, Regina and Jakob, Franz and Dandekar, Gudrun and Naseem, Muhammad and Liang, Chunguang and Dandekar, Thomas},
  title     = {Software JimenaE allows efficient dynamic simulations of Boolean networks, centrality and system state analysis},
  series = {Scientific Reports},
  volume    = {13},
  journal   = {Scientific Reports},
  doi       = {10.1038/s41598-022-27098-7},
  url       = {http://nbn-resolving.de/urn:nbn:de:bvb:20-opus-313303},
  year      = {2023},
  abstract  = {The signal modelling framework JimenaE simulates dynamically Boolean networks. In contrast to SQUAD, there is systematic and not just heuristic calculation of all system states. These specific features are not present in CellNetAnalyzer and BoolNet. JimenaE is an expert extension of Jimena, with new optimized code, network conversion into different formats, rapid convergence both for system state calculation as well as for all three network centralities. It allows higher accuracy in determining network states and allows to dissect networks and identification of network control type and amount for each protein with high accuracy. Biological examples demonstrate this: (i) High plasticity of mesenchymal stromal cells for differentiation into chondrocytes, osteoblasts and adipocytes and differentiation-specific network control focusses on wnt-, TGF-beta and PPAR-gamma signaling. JimenaE allows to study individual proteins, removal or adding interactions (or autocrine loops) and accurately quantifies effects as well as number of system states. (ii) Dynamical modelling of cell-cell interactions of plant Arapidopsis thaliana against Pseudomonas syringae DC3000: We analyze for the first time the pathogen perspective and its interaction with the host. We next provide a detailed analysis on how plant hormonal regulation stimulates specific proteins and who and which protein has which type and amount of network control including a detailed heatmap of the A.thaliana response distinguishing between two states of the immune response. (iii) In an immune response network of dendritic cells confronted with Aspergillus fumigatus, JimenaE calculates now accurately the specific values for centralities and protein-specific network control including chemokine and pattern recognition receptors.},
  language  = {en}
}