@article{BaurNietzerKunzetal.2020, author = {Baur, Florentin and Nietzer, Sarah L. and Kunz, Meik and Saal, Fabian and Jeromin, Julian and Matschos, Stephanie and Linnebacher, Michael and Walles, Heike and Dandekar, Thomas and Dandekar, Gudrun}, title = {Connecting cancer pathways to tumor engines: a stratification tool for colorectal cancer combining human in vitro tissue models with boolean in silico models}, series = {Cancers}, volume = {12}, journal = {Cancers}, number = {1}, issn = {2072-6694}, doi = {10.3390/cancers12010028}, url = {http://nbn-resolving.de/urn:nbn:de:bvb:20-opus-193798}, pages = {28}, year = {2020}, abstract = {To improve and focus preclinical testing, we combine tumor models based on a decellularized tissue matrix with bioinformatics to stratify tumors according to stage-specific mutations that are linked to central cancer pathways. We generated tissue models with BRAF-mutant colorectal cancer (CRC) cells (HROC24 and HROC87) and compared treatment responses to two-dimensional (2D) cultures and xenografts. As the BRAF inhibitor vemurafenib is—in contrast to melanoma—not effective in CRC, we combined it with the EGFR inhibitor gefitinib. In general, our 3D models showed higher chemoresistance and in contrast to 2D a more active HGFR after gefitinib and combination-therapy. In xenograft models murine HGF could not activate the human HGFR, stressing the importance of the human microenvironment. In order to stratify patient groups for targeted treatment options in CRC, an in silico topology with different stages including mutations and changes in common signaling pathways was developed. We applied the established topology for in silico simulations to predict new therapeutic options for BRAF-mutated CRC patients in advanced stages. Our in silico tool connects genome information with a deeper understanding of tumor engines in clinically relevant signaling networks which goes beyond the consideration of single drivers to improve CRC patient stratification.}, language = {en} } @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{PeindlGoettlichCrouchetal.2022, author = {Peindl, Matthias and G{\"o}ttlich, Claudia and Crouch, Samantha and Hoff, Niklas and L{\"u}ttgens, Tamara and Schmitt, Franziska and Pereira, Jes{\´u}s Guillermo Nieves and May, Celina and Schliermann, Anna and Kronenthaler, Corinna and Cheufou, Danjouma and Reu-Hofer, Simone and Rosenwald, Andreas and Weigl, Elena and Walles, Thorsten and Sch{\"u}ler, Julia and Dandekar, Thomas and Nietzer, Sarah and Dandekar, Gudrun}, title = {EMT, stemness, and drug resistance in biological context: a 3D tumor tissue/in silico platform for analysis of combinatorial treatment in NSCLC with aggressive KRAS-biomarker signatures}, series = {Cancers}, volume = {14}, journal = {Cancers}, number = {9}, issn = {2072-6694}, doi = {10.3390/cancers14092176}, url = {http://nbn-resolving.de/urn:nbn:de:bvb:20-opus-270744}, year = {2022}, abstract = {Epithelial-to-mesenchymal transition (EMT) is discussed to be centrally involved in invasion, stemness, and drug resistance. Experimental models to evaluate this process in its biological complexity are limited. To shed light on EMT impact and test drug response more reliably, we use a lung tumor test system based on a decellularized intestinal matrix showing more in vivo-like proliferation levels and enhanced expression of clinical markers and carcinogenesis-related genes. In our models, we found evidence for a correlation of EMT with drug resistance in primary and secondary resistant cells harboring KRAS\(^{G12C}\) or EGFR mutations, which was simulated in silico based on an optimized signaling network topology. Notably, drug resistance did not correlate with EMT status in KRAS-mutated patient-derived xenograft (PDX) cell lines, and drug efficacy was not affected by EMT induction via TGF-β. To investigate further determinants of drug response, we tested several drugs in combination with a KRAS\(^{G12C}\) inhibitor in KRAS\(^{G12C}\) mutant HCC44 models, which, besides EMT, display mutations in P53, LKB1, KEAP1, and high c-MYC expression. We identified an aurora-kinase A (AURKA) inhibitor as the most promising candidate. In our network, AURKA is a centrally linked hub to EMT, proliferation, apoptosis, LKB1, and c-MYC. This exemplifies our systemic analysis approach for clinical translation of biomarker signatures.}, language = {en} } @article{FecherHofmannBucketal.2016, author = {Fecher, David and Hofmann, Elisabeth and Buck, Andreas and Bundschuh, Ralph and Nietzer, Sarah and Dandekar, Gudrun and Walles, Thorsten and Walles, Heike and L{\"u}ckerath, Katharina and Steinke, Maria}, title = {Human Organotypic Lung Tumor Models: Suitable For Preclinical \(^{18}\)F-FDG PET-Imaging}, series = {PLoS ONE}, volume = {11}, journal = {PLoS ONE}, number = {8}, doi = {10.1371/journal.pone.0160282}, url = {http://nbn-resolving.de/urn:nbn:de:bvb:20-opus-179678}, year = {2016}, abstract = {Development of predictable in vitro tumor models is a challenging task due to the enormous complexity of tumors in vivo. The closer the resemblance of these models to human tumor characteristics, the more suitable they are for drug-development and -testing. In the present study, we generated a complex 3D lung tumor test system based on acellular rat lungs. A decellularization protocol was established preserving the architecture, important ECM components and the basement membrane of the lung. Human lung tumor cells cultured on the scaffold formed cluster and exhibited an up-regulation of the carcinoma-associated marker mucin1 as well as a reduced proliferation rate compared to respective 2D culture. Additionally, employing functional imaging with 2-deoxy-2-[\(^{18}\)F]fluoro-D-glucose positron emission tomography (FDG-PET) these tumor cell cluster could be detected and tracked over time. This approach allowed monitoring of a targeted tyrosine kinase inhibitor treatment in the in vitro lung tumor model non-destructively. Surprisingly, FDG-PET assessment of single tumor cell cluster on the same scaffold exhibited differences in their response to therapy, indicating heterogeneity in the lung tumor model. In conclusion, our complex lung tumor test system features important characteristics of tumors and its microenvironment and allows monitoring of tumor growth and -metabolism in combination with functional imaging. In longitudinal studies, new therapeutic approaches and their long-term effects can be evaluated to adapt treatment regimes in future.}, language = {en} } @article{KunzGoettlichWallesetal.2017, author = {Kunz, Meik and G{\"o}ttlich, Claudia and Walles, Thorsten and Nietzer, Sarah and Dandekar, Gudrun and Dandekar, Thomas}, title = {MicroRNA-21 versus microRNA-34: Lung cancer promoting and inhibitory microRNAs analysed in silico and in vitro and their clinical impact}, series = {Tumor Biology}, volume = {39}, journal = {Tumor Biology}, number = {7}, doi = {10.1177/1010428317706430}, url = {http://nbn-resolving.de/urn:nbn:de:bvb:20-opus-158399}, year = {2017}, abstract = {MicroRNAs are well-known strong RNA regulators modulating whole functional units in complex signaling networks. Regarding clinical application, they have potential as biomarkers for prognosis, diagnosis, and therapy. In this review, we focus on two microRNAs centrally involved in lung cancer progression. MicroRNA-21 promotes and microRNA-34 inhibits cancer progression. We elucidate here involved pathways and imbed these antagonistic microRNAs in a network of interactions, stressing their cancer microRNA biology, followed by experimental and bioinformatics analysis of such microRNAs and their targets. This background is then illuminated from a clinical perspective on microRNA-21 and microRNA-34 as general examples for the complex microRNA biology in lung cancer and its diagnostic value. Moreover, we discuss the immense potential that microRNAs such as microRNA-21 and microRNA-34 imply by their broad regulatory effects. These should be explored for novel therapeutic strategies in the clinic.}, language = {en} } @article{NietzerBaurSieberetal.2016, author = {Nietzer, Sarah and Baur, Florentin and Sieber, Stefan and Hansmann, Jan and Schwarz, Thomas and Stoffer, Carolin and H{\"a}fner, Heide and Gasser, Martin and Waaga-Gasser, Ana Maria and Walles, Heike and Dandekar, Gudrun}, title = {Mimicking metastases including tumor stroma: a new technique to generate a three-dimensional colorectal cancer model based on a biological decellularized intestinal scaffold}, series = {Tissue Engineering Part C-Methods}, volume = {22}, journal = {Tissue Engineering Part C-Methods}, number = {7}, doi = {10.1089/ten.tec.2015.0557}, url = {http://nbn-resolving.de/urn:nbn:de:bvb:20-opus-188202}, pages = {621-635}, year = {2016}, abstract = {Tumor models based on cancer cell lines cultured two-dimensionally (2D) on plastic lack histological complexity and functionality compared to the native microenvironment. Xenogenic mouse tumor models display higher complexity but often do not predict human drug responses accurately due to species-specific differences. We present here a three-dimensional (3D) in vitro colon cancer model based on a biological scaffold derived from decellularized porcine jejunum (small intestine submucosa+mucosa, SISmuc). Two different cell lines were used in monoculture or in coculture with primary fibroblasts. After 14 days of culture, we demonstrated a close contact of human Caco2 colon cancer cells with the preserved basement membrane on an ultrastructural level as well as morphological characteristics of a well-differentiated epithelium. To generate a tissue-engineered tumor model, we chose human SW480 colon cancer cells, a reportedly malignant cell line. Malignant characteristics were confirmed in 2D cell culture: SW480 cells showed higher vimentin and lower E-cadherin expression than Caco2 cells. In contrast to Caco2, SW480 cells displayed cancerous characteristics such as delocalized E-cadherin and nuclear location of beta-catenin in a subset of cells. One central drawback of 2D cultures-especially in consideration of drug testing-is their artificially high proliferation. In our 3D tissue-engineered tumor model, both cell lines showed decreased numbers of proliferating cells, thus correlating more precisely with observations of primary colon cancer in all stages (UICC I-IV). Moreover, vimentin decreased in SW480 colon cancer cells, indicating a mesenchymal to epithelial transition process, attributed to metastasis formation. Only SW480 cells cocultured with fibroblasts induced the formation of tumor-like aggregates surrounded by fibroblasts, whereas in Caco2 cocultures, a separate Caco2 cell layer was formed separated from the fibroblast compartment beneath. To foster tissue generation, a bioreactor was constructed for dynamic culture approaches. This induced a close tissue-like association of cultured tumor cells with fibroblasts reflecting tumor biopsies. Therapy with 5-fluorouracil (5-FU) was effective only in 3D coculture. In conclusion, our 3D tumor model reflects human tissue-related tumor characteristics, including lower tumor cell proliferation. It is now available for drug testing in metastatic context-especially for substances targeting tumor-stroma interactions.}, language = {en} } @article{KuehnemundtLeifeldSchergetal.2021, author = {K{\"u}hnemundt, Johanna and Leifeld, Heidi and Scherg, Florian and Schmitt, Matthias and Nelke, Lena C. and Schmitt, Tina and Bauer, Florentin and G{\"o}ttlich, Claudia and Fuchs, Maximilian and Kunz, Meik and Peindl, Matthias and Br{\"a}hler, Caroline and Kronenthaler, Corinna and Wischhusen, J{\"o}rg and Prelog, Martina and Walles, Heike and Dandekar, Thomas and Dandekar, Gudrun and Nietzer, Sarah L.}, title = {Modular micro-physiological human tumor/tissue models based on decellularized tissue for improved preclinical testing}, series = {ALTEX}, volume = {38}, journal = {ALTEX}, doi = {10.14573/altex.2008141}, url = {http://nbn-resolving.de/urn:nbn:de:bvb:20-opus-231465}, pages = {289-306}, year = {2021}, abstract = {High attrition-rates entailed by drug testing in 2D cell culture and animal models stress the need for improved modeling of human tumor tissues. In previous studies our 3D models on a decellularized tissue matrix have shown better predictivity and higher chemoresistance. A single porcine intestine yields material for 150 3D models of breast, lung, colorectal cancer (CRC) or leukemia. The uniquely preserved structure of the basement membrane enables physiological anchorage of endothelial cells and epithelial-derived carcinoma cells. The matrix provides different niches for cell growth: on top as monolayer, in crypts as aggregates and within deeper layers. Dynamic culture in bioreactors enhances cell growth. Comparing gene expression between 2D and 3D cultures, we observed changes related to proliferation, apoptosis and stemness. For drug target predictions, we utilize tumor-specific sequencing data in our in silico model finding an additive effect of metformin and gefitinib treatment for lung cancer in silico, validated in vitro. To analyze mode-of-action, immune therapies such as trispecific T-cell engagers in leukemia, as well as toxicity on non-cancer cells, the model can be modularly enriched with human endothelial cells (hECs), immune cells and fibroblasts. Upon addition of hECs, transmigration of immune cells through the endothelial barrier can be investigated. In an allogenic CRC model we observe a lower basic apoptosis rate after applying PBMCs in 3D compared to 2D, which offers new options to mirror antigen-specific immunotherapies in vitro. In conclusion, we present modular human 3D tumor models with tissue-like features for preclinical testing to reduce animal experiments.}, language = {en} } @article{GordonDaneshianBouwstraetal.2015, author = {Gordon, Sarah and Daneshian, Mardas and Bouwstra, Joke and Caloni, Francesca and Constant, Samuel and Davies, Donna E. and Dandekar, Gudrun and Guzman, Carlos A. and Fabian, Eric and Haltner, Eleonore and Hartung, Thomas and Hasiwa, Nina and Hayden, Patrick and Kandarova, Helena and Khare, Sangeeta and Krug, Harald F. and Kneuer, Carsten and Leist, Marcel and Lian, Guoping and Marx, Uwe and Metzger, Marco and Ott, Katharina and Prieto, Pilar and Roberts, Michael S. and Roggen, Erwin L. and Tralau, Tewes and van den Braak, Claudia and Walles, Heike and Lehr, Claus-Michael}, title = {Non-animal models of epithelial barriers (skin, intestine and lung) in research, industrial applications and regulatory toxicology}, series = {ALTEX: Alternatives to Animal Experimentation}, volume = {32}, journal = {ALTEX: Alternatives to Animal Experimentation}, number = {4}, doi = {10.14573/altex.1510051}, url = {http://nbn-resolving.de/urn:nbn:de:bvb:20-opus-144275}, pages = {327-378}, year = {2015}, abstract = {Models of the outer epithelia of the human body namely the skin, the intestine and the lung have found valid applications in both research and industrial settings as attractive alternatives to animal testing. A variety of approaches to model these barriers are currently employed in such fields, ranging from the utilization of ex vivo tissue to reconstructed in vitro models, and further to chip-based technologies, synthetic membrane systems and, of increasing current interest, in silico modeling approaches. An international group of experts in the field of epithelial barriers was convened from academia, industry and regulatory bodies to present both the current state of the art of non-animal models of the skin, intestinal and pulmonary barriers in their various fields of application, and to discuss research-based, industry-driven and regulatory-relevant future directions for both the development of new models and the refinement of existing test methods. Issues of model relevance and preference, validation and standardization, acceptance, and the need for simplicity versus complexity were focal themes of the discussions. The outcomes of workshop presentations and discussions, in relation to both current status and future directions in the utilization and development of epithelial barrier models, are presented by the attending experts in the current report.}, 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} }