TY - JOUR A1 - Kühnemundt, Johanna A1 - Leifeld, Heidi A1 - Scherg, Florian A1 - Schmitt, Matthias A1 - Nelke, Lena C. A1 - Schmitt, Tina A1 - Bauer, Florentin A1 - Göttlich, Claudia A1 - Fuchs, Maximilian A1 - Kunz, Meik A1 - Peindl, Matthias A1 - Brähler, Caroline A1 - Kronenthaler, Corinna A1 - Wischhusen, Jörg A1 - Prelog, Martina A1 - Walles, Heike A1 - Dandekar, Thomas A1 - Dandekar, Gudrun A1 - Nietzer, Sarah L. T1 - Modular micro-physiological human tumor/tissue models based on decellularized tissue for improved preclinical testing JF - ALTEX N2 - 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. KW - modular tumor tissue models KW - invasiveness KW - bioreactor culture KW - combinatorial drug predictions KW - immunotherapies Y1 - 2021 U6 - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:bvb:20-opus-231465 VL - 38 ER - TY - JOUR A1 - Kunz, Meik A1 - Göttlich, Claudia A1 - Walles, Thorsten A1 - Nietzer, Sarah A1 - Dandekar, Gudrun A1 - Dandekar, Thomas T1 - MicroRNA-21 versus microRNA-34: Lung cancer promoting and inhibitory microRNAs analysed in silico and in vitro and their clinical impact JF - Tumor Biology N2 - 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. KW - biomarker KW - microRNA–target interaction KW - microRNAs KW - lung cancer KW - therapeutic strategy KW - bioinformatics Y1 - 2017 U6 - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:bvb:20-opus-158399 VL - 39 IS - 7 ER - TY - JOUR A1 - Peindl, Matthias A1 - Göttlich, Claudia A1 - Crouch, Samantha A1 - Hoff, Niklas A1 - Lüttgens, Tamara A1 - Schmitt, Franziska A1 - Pereira, Jesús Guillermo Nieves A1 - May, Celina A1 - Schliermann, Anna A1 - Kronenthaler, Corinna A1 - Cheufou, Danjouma A1 - Reu-Hofer, Simone A1 - Rosenwald, Andreas A1 - Weigl, Elena A1 - Walles, Thorsten A1 - Schüler, Julia A1 - Dandekar, Thomas A1 - Nietzer, Sarah A1 - Dandekar, Gudrun T1 - 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 JF - Cancers N2 - 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. KW - EMT KW - drug resistance KW - invasion KW - stemness KW - 3D lung tumor tissue models KW - KRAS biomarker signatures KW - boolean in silico models KW - targeted combination therapy Y1 - 2022 U6 - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:bvb:20-opus-270744 SN - 2072-6694 VL - 14 IS - 9 ER -