@article{DotterweichSchlegelmilchKelleretal.2016,
  author    = {Dotterweich, Julia and Schlegelmilch, Katrin and Keller, Alexander and Geyer, Beate and Schneider, Doris and Zeck, Sabine and Tower, Robert J. J. and Ebert, Regina and Jakob, Franz and Sch{\"u}tze, Norbert},
  title     = {Contact of myeloma cells induces a characteristic transcriptome signature in skeletal precursor cells-implications for myeloma bone disease},
  series = {Bone},
  volume    = {93},
  journal   = {Bone},
  doi       = {10.1016/j.bone.2016.08.006},
  url       = {http://nbn-resolving.de/urn:nbn:de:bvb:20-opus-186688},
  pages     = {155-166},
  year      = {2016},
  abstract  = {Physical interaction of skeletal precursors with multiple myeloma cells has been shown to suppress their osteogenic potential while favoring their tumor-promoting features. Although several transcriptome analyses of myeloma patient-derived mesenchymal stem cells have displayed differences compared to their healthy counterparts, these analyses insufficiently reflect the signatures mediated by tumor cell contact, vary due to different methodologies, and lack results in lineage-committed precursors. To determine tumor cell contact-mediated changes on skeletal precursors, we performed transcriptome analyses of mesenchymal stem cells and osteogenic precursor cells cultured in contact with the myeloma cell line INA-6. Comparative analyses confirmed dysregulation of genes which code for known disease-relevant factors and additionally revealed upregulation of genes that are associated with plasma cell homing, adhesion, osteoclastogenesis, and angiogenesis. Osteoclast-derived coupling factors, a dysregulated adipogenic potential, and an imbalance in favor of anti-anabolic factors may play a role in the hampered osteoblast differentiation potential of mesenchymal stem cells. Angiopoietin-Like 4 (ANGPTL4) was selected from a list of differentially expressed genes as a myeloma cell contact-dependent target in skeletal precursor cells which warranted further functional analyses. Adhesion assays with full-length ANGPTL4-coated plates revealed a potential role of this protein in INA6 cell attachment. This study expands knowledge of the myeloma cell contact-induced signature in the stromal compartment of myelomatous bones and thus offers potential targets that may allow detection and treatment of myeloma bone disease at an early stage.},
  language  = {en}
}
@article{MaichlKirnerBecketal.2023,
  author    = {Maichl, Daniela Simone and Kirner, Julius Arthur and Beck, Susanne and Cheng, Wen-Hui and Krug, Melanie and Kuric, Martin and Ade, Carsten Patrick and Bischler, Thorsten and Jakob, Franz and Hose, Dirk and Seckinger, Anja and Ebert, Regina and Jundt, Franziska},
  title     = {Identification of NOTCH-driven matrisome-associated genes as prognostic indicators of multiple myeloma patient survival},
  series = {Blood Cancer Journal},
  volume    = {13},
  journal   = {Blood Cancer Journal},
  doi       = {10.1038/s41408-023-00907-6},
  url       = {http://nbn-resolving.de/urn:nbn:de:bvb:20-opus-357598},
  year      = {2023},
  abstract  = {No abstract available.},
  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}
}