TY  - JOUR
A1  - Watzling, Martin
A1  - Klaus, Lorenz
A1  - Weidemeier, Tamara
A1  - Horder, Hannes
A1  - Ebert, Regina
A1  - Blunk, Torsten
A1  - Bauer-Kreisel, Petra
T1  - Three-dimensional breast cancer model to investigate CCL5/CCR1 expression mediated by direct contact between breast cancer cells and adipose-derived stromal cells or adipocytes
JF  - Cancers
N2  - The tumor microenvironment (TME) in breast cancer is determined by the complex crosstalk of cancer cells with adipose tissue-inherent cells such as adipose-derived stromal cells (ASCs) and adipocytes resulting from the local invasion of tumor cells in the mammary fat pad. This leads to heterotypic cellular contacts between these cell types. To adequately mimic the specific cell-to-cell interaction in an in vivo-like 3D environment, we developed a direct co-culture spheroid model using ASCs or differentiated adipocytes in combination with MDA-MB-231 or MCF-7 breast carcinoma cells. Co-spheroids were generated in a well-defined and reproducible manner in a high-throughput process. We compared the expression of the tumor-promoting chemokine CCL5 and its cognate receptors in these co-spheroids to indirect and direct standard 2D co-cultures. A marked up-regulation of CCL5 and in particular the receptor CCR1 with strict dependence on cell–cell contacts and culture dimensionality was evident. Furthermore, the impact of direct contacts between ASCs and tumor cells and the involvement of CCR1 in promoting tumor cell migration were demonstrated. Overall, these results show the importance of direct 3D co-culture models to better represent the complex tumor–stroma interaction in a tissue-like context. The unveiling of tumor-specific markers that are up-regulated upon direct cell–cell contact with neighboring stromal cells, as demonstrated in the 3D co-culture spheroids, may represent a promising strategy to find new targets for the diagnosis and treatment of invasive breast cancer.
KW  - 3D breast cancer model
KW  - adipose-derived stromal cells
KW  - adipocytes
KW  - adipose tissue
KW  - spheroids
KW  - co-culture
Y1  - 2023
U6  - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:bvb:20-opus-362502
SN  - 2072-6694
VL  - 15
IS  - 13
ER  - 
TY  - JOUR
A1  - Kaltdorf, Martin
A1  - Breitenbach, Tim
A1  - Karl, Stefan
A1  - Fuchs, Maximilian
A1  - Kessie, David Komla
A1  - Psota, Eric
A1  - Prelog, Martina
A1  - Sarukhanyan, Edita
A1  - Ebert, Regina
A1  - Jakob, Franz
A1  - Dandekar, Gudrun
A1  - Naseem, Muhammad
A1  - Liang, Chunguang
A1  - Dandekar, Thomas
T1  - Software JimenaE allows efficient dynamic simulations of Boolean networks, centrality and system state analysis
JF  - Scientific Reports
N2  - 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.
KW  - cellular signalling networks
KW  - computer modelling
Y1  - 2023
U6  - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:bvb:20-opus-313303
VL  - 13
ER  - 
TY  - JOUR
A1  - Maichl, Daniela Simone
A1  - Kirner, Julius Arthur
A1  - Beck, Susanne
A1  - Cheng, Wen-Hui
A1  - Krug, Melanie
A1  - Kuric, Martin
A1  - Ade, Carsten Patrick
A1  - Bischler, Thorsten
A1  - Jakob, Franz
A1  - Hose, Dirk
A1  - Seckinger, Anja
A1  - Ebert, Regina
A1  - Jundt, Franziska
T1  - Identification of NOTCH-driven matrisome-associated genes as prognostic indicators of multiple myeloma patient survival
JF  - Blood Cancer Journal
N2  - No abstract available.
KW  - cancer microenvironment
KW  - myeloma
Y1  - 2023
U6  - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:bvb:20-opus-357598
VL  - 13
ER  -