In silico signaling modeling to understand cancer pathways and treatment responses.

Precision medicine has changed thinking in cancer therapy, highlighting a better understanding of the individual clinical interventions. But what role do the drivers and pathways identified from pan-cancer genome analysis play in the tumor? In this letter, we will highlight the importance of in silico modeling in precision medicine. In the current era of big data, tumor engines and pathways derived from pan-cancer analysis should be integrated into in silico models to understand the mutational tumor status and individual molecular pathway mechanism at a deeper level. This allows to pre-evaluate the potential therapy response and develop optimal patient-tailored treatment strategies which pave the way to support precision medicine in the clinic of the future.

MicroRNA-21 versus microRNA-34: Lung cancer promoting and inhibitory microRNAs analysed in silico and in vitro and their clinical impact.

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.

TheraVision: Engineering platform technology for the development of oncolytic viruses based on herpes simplex virus type 1.

Viruses are able to efficiently penetrate cells, multiply, and eventually kill infected cells, release tumor antigens, and activate the immune system. Therefore, viruses are highly attractive novel agents for cancer therapy. Clinical trials with first generations of oncolytic viruses (OVs) are very promising but show significant need for optimization. The aim of TheraVision was to establish a broadly applicable engineering platform technology for combinatorial oncolytic virus and immunotherapy. Through genetic engineering, an attenuated herpes simplex virus type 1 (HSV1) was generated that showed increased safety compared to the wild-type strain. To demonstrate the modularity and the facilitated generation of new OVs, two transgenes encoding retargeting as well as immunomodulating single-chain variable fragments (scFvs) were integrated into the platform vector. The resulting virus selectively infected epidermal growth factor receptor (EGFR)-expressing cells and produced a functional immune checkpoint inhibitor against programmed cell death protein 1 (PD-1). Thus, both viral-mediated oncolysis and immune-cell-mediated therapy were combined into a single viral vector. Safety and functionality of the armed OVs have been shown in novel preclinical models ranging from patient-derived organoids and tissue-engineered human in vitro 3D tumor models to complex humanized mouse models. Consequently, a novel and proprietary engineering platform vector based on HSV1 is available for the facilitated preclinical development of oncolytic virotherapy.

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.

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 KRASG12C 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-ß. To investigate further determinants of drug response, we tested several drugs in combination with a KRASG12C inhibitor in KRASG12C 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.

Inhibition of TGF-ß-receptor signaling augments the antitumor function of ROR1-specific CAR T-cells against triple-negative breast cancer.

BACKGROUND: Immunotherapy with chimeric antigen receptor (CAR)-engineered T-cells is effective in some hematologic tumors. In solid tumors, however, sustained antitumor responses after CAR T-cell therapy remain to be demonstrated both in the pre-clinical and clinical setting. A perceived barrier to the efficacy of CAR T-cell therapy in solid tumors is the hostile tumor microenvironment where immunosuppressive soluble factors like transforming growth factor (TGF)-ß are thought to inhibit the cellular immune response. Here, we analyzed whether CAR T-cells specific for the receptor tyrosine kinase-like orphan receptor 1 (ROR1) antigen, that is frequently expressed in triple-negative breast cancer (TNBC), are susceptible to inhibition by TGF-ß and evaluated TGF-ß-receptor signaling blockade as a way of neutralizing the inhibitory effect of this cytokine. METHODS: CD8+ and CD4+ ROR1-CAR T-cells were prepared from healthy donors and their antitumor function analyzed using the TNBC cell line MDA-MB-231 in vitro and in a microphysiologic 3D tumor model. Analyses were performed in co-culture assays of ROR1-CAR T-cells and MDA-MB-231 cells with addition of exogenous TGF-ß. RESULTS: The data show that exposure to TGF-ß engages TGF-ß-receptor signaling in CD8+ and CD4+ ROR1-CAR T-cells as evidenced by phosphorylation of small mothers against decapentaplegic homolog 2. In the presence of TGF-ß, the cytolytic activity, cytokine production and proliferation of ROR1-CAR T-cells in co-culture with MDA-MB-231 TNBC cells were markedly impaired, and the viability of ROR1-CAR T-cells reduced. Blockade of TGF-ß-receptor signaling with the specific kinase inhibitor SD-208 was able to protect CD8+ and CD4+ ROR1-CAR T-cells from the inhibitory effect of TGF-ß, and sustained their antitumor function in vitro and in the microphysiologic 3D tumor model. Combination treatment with SD-208 also led to increased viability and lower expression of PD-1 on ROR1-CAR T-cells at the end of the antitumor response. CONCLUSION: We demonstrate the TGF-ß suppresses the antitumor function of ROR1-CAR T-cells against TNBC in preclinical models. Our study supports the continued preclinical development and the clinical evaluation of combination treatments that shield CAR T-cells from TGF-ß, as exemplified by the TGF-ß-receptor kinase inhibitor SD-208 in this study.

Investigation on Ciliary Functionality of Different Airway Epithelial Cell Lines in Three-Dimensional Cell Culture.

Three-dimensional respiratory tissue models have been generated using, for example, human primary airway epithelial cells (hAEC) or respective cell lines. To investigate ciliopathies, such as primary ciliary dyskinesia, the presence of functional kinocilia in vitro is an essential prerequisite. Since access to hAEC of healthy donors is limited, we aimed to identify a respiratory epithelial cell line that is capable to display functional kinocilia on at least 60% of the apical surface. Thus, we cultured four different human respiratory cell lines with human primary airway fibroblasts under airlift conditions, characterized the morphology, and analyzed ciliary function. Only one of the tested cell lines showed beating kinocilia; however, <10% of the whole surface was covered and ciliary beating was undirected. Positive control tissue models using hAEC and fibroblasts displayed expected directed ciliary beating pattern around 11 Hz. Our data show that the available cell lines are not suitable for basic and applied research questions whenever functional kinocilia are required and that, rather, hAEC- or human induced pluripotent stem cell-derived tissue models need to be generated. Impact Statement To study ciliopathies or Bordetella pertussis infection in vitro, three-dimensional respiratory tissue models with functional kinocilia covering at least 60% of the model's surface are mandatory. We cultured four respiratory cell lines on a fibroblast-loaded biological scaffold and showed that none of them met this requirement. In contrast, primary airway cell-derived models sufficiently reflected the mucociliary phenotype. To further search for an alternative to primary respiratory cells, investigations on other cell lines should be conducted or even new cell lines have to be generated.

Modular micro-physiological human tumor/tissue models based on decellularized tissue for improved preclinical testing

High attrition rates associated with 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 or 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.

Drug induced micellization into ultra-high capacity and stable curcumin nanoformulations: Physico-chemical characterization and evaluation in 2D and 3D in vitro models.

Curcumin (CUR) is a natural extract from the plant Curcuma longa and part of turmeric, a spice and herbal remedy in traditional medicine. Thousands of papers claim a plethora of health benefits by CUR, but a growing number of reports and contributions caution that many experimental data may be artifacts or outright deny any suitability of CUR due to its problematic physicochemical properties. Two major issues often encountered with CUR are its extraordinarily low solubility in water and its limited chemical stability. Here, we report on a novel nanoformulation of CUR that enables CUR concentrations in water of at least 50 g/L with relative drug loadings of >50 wt% and high dose efficacy testing in 3D tumor models. Despite this high loading and concentration, the CUR nanoformulation comprises polymer-drug aggregates with a size <50 nm. Most interestingly, this is achieved using an amphiphilic block copolymer, that by itself does not form micelles due to its limited hydrophilic/lipophilic contrast. The ultra-high loaded nanoformulations exhibit a very good stability, reproducibility and redispersibility. In order to test effects of CUR in conditions closer to an in vivo situation, we utilized a 3D tumor test system based on a biological decellularized tissue matrix that better correlates to clinical results concerning drug testing. We found that in comparison to 2D culture, the invasively growing breast cancer cell line MDA-MB-231 requires high concentrations of CUR for tumor cell eradication in 3D. In addition, we supplemented a 3D colorectal cancer model of the malignant cell line SW480 with fibroblasts and observed also in this invasive tumor model with stroma components a decreased tumor cell growth after CUR application accompanied by a loss of cell-cell contacts within tumor cell clusters. In a flow bioreactor simulating cancer cell dissemination, nanoformulated CUR prevented SW480 cells from adhering to a collagen scaffold, suggesting an anti-metastatic potential of CUR. This offers a rationale that the presented ultra-high CUR-loaded nanoformulation may be considered a tool to harness the full therapeutic potential of CUR.

Connecting Cancer Pathways to Tumor Engines: A Stratification Tool for Colorectal Cancer Combining Human In Vitro Tissue Models with Boolean In Silico Models.

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.

ROR1-CAR T cells are effective against lung and breast cancer in advanced microphysiologic 3D tumor models.

Solid tumors impose immunologic and physical barriers to the efficacy of chimeric antigen receptor (CAR) T cell therapy that are not reflected in conventional preclinical testing against singularized tumor cells in 2-dimensional culture. Here, we established microphysiologic three-dimensional (3D) lung and breast cancer models that resemble architectural and phenotypical features of primary tumors and evaluated the antitumor function of receptor tyrosine kinase-like orphan receptor 1-specific (ROR1-specific) CAR T cells. 3D tumors were established from A549 (non-small cell lung cancer) and MDA-MB-231 (triple-negative breast cancer) cell lines on a biological scaffold with intact basement membrane (BM) under static and dynamic culture conditions, which resulted in progressively increasing cell mass and invasive growth phenotype (dynamic > static; MDA-MB-231 > A549). Treatment with ROR1-CAR T cells conferred potent antitumor effects. In dynamic culture, CAR T cells actively entered arterial medium flow and adhered to and infiltrated the tumor mass. ROR1-CAR T cells penetrated deep into tumor tissue and eliminated multiple layers of tumor cells located above and below the BM. The microphysiologic 3D tumor models developed in this study are standardized, scalable test systems that can be used either in conjunction with or in lieu of animal testing to interrogate the antitumor function of CAR T cells and to obtain proof of concept for their safety and efficacy before clinical application.

A combined tissue-engineered/in silico signature tool patient stratification in lung cancer.

Patient-tailored therapy based on tumor drivers is promising for lung cancer treatment. For this, we combined in vitro tissue models with in silico analyses. Using individual cell lines with specific mutations, we demonstrate a generic and rapid stratification pipeline for targeted tumor therapy. We improve in vitro models of tissue conditions by a biological matrix-based three-dimensional (3D) tissue culture that allows in vitro drug testing: It correctly shows a strong drug response upon gefitinib (Gef) treatment in a cell line harboring an EGFR-activating mutation (HCC827), but no clear drug response upon treatment with the HSP90 inhibitor 17AAG in two cell lines with KRAS mutations (H441, A549). In contrast, 2D testing implies wrongly KRAS as a biomarker for HSP90 inhibitor treatment, although this fails in clinical studies. Signaling analysis by phospho-arrays showed similar effects of EGFR inhibition by Gef in HCC827 cells, under both 2D and 3D conditions. Western blot analysis confirmed that for 3D conditions, HSP90 inhibitor treatment implies different p53 regulation and decreased MET inhibition in HCC827 and H441 cells. Using in vitro data (western, phospho-kinase array, proliferation, and apoptosis), we generated cell line-specific in silico topologies and condition-specific (2D, 3D) simulations of signaling correctly mirroring in vitro treatment responses. Networks predict drug targets considering key interactions and individual cell line mutations using the Human Protein Reference Database and the COSMIC database. A signature of potential biomarkers and matching drugs improve stratification and treatment in KRAS-mutated tumors. In silico screening and dynamic simulation of drug actions resulted in individual therapeutic suggestions, that is, targeting HIF1A in H441 and LKB1 in A549 cells. In conclusion, our in vitro tumor tissue model combined with an in silico tool improves drug effect prediction and patient stratification. Our tool is used in our comprehensive cancer center and is made now publicly available for targeted therapy decisions.

Stem cell labeling with iron oxide nanoparticles: impact of 3D culture on cell labeling maintenance.

AIM: We aimed to analyze the suitability of nanoparticles (M4E) for safe human mesenchymal stem cell (hMSC) labeling and determined cell labeling maintenance in 2D and 3D culture. MATERIALS & METHODS: We investigated cell-particle interaction and the particles' impact on cell viability, growth and proliferation. We analyzed cell labeling maintenance in 2D and 3D culture invasively and noninvasively. RESULTS: M4E do not affect cell viability, growth and proliferation and do not cause chromosomal aberrations. Cell labeling maintenance is up to five-times higher in 3D conditions compared with 2D culture. CONCLUSION: M4E allow safe hMSC labeling and noninvasive identification. Our hMSC-loaded, 3D tissue-engineered construct could serve as a graft for regenerative therapies, in which M4E-labeled hMSCs can migrate to their target.

A Combined 3D Tissue Engineered In Vitro/In Silico Lung Tumor Model for Predicting Drug Effectiveness in Specific Mutational Backgrounds.

In the present study, we combined an in vitro 3D lung tumor model with an in silico model to optimize predictions of drug response based on a specific mutational background. The model is generated on a decellularized porcine scaffold that reproduces tissue-specific characteristics regarding extracellular matrix composition and architecture including the basement membrane. We standardized a protocol that allows artificial tumor tissue generation within 14 days including three days of drug treatment. Our article provides several detailed descriptions of 3D read-out screening techniques like the determination of the proliferation index Ki67 staining's, apoptosis from supernatants by M30-ELISA and assessment of epithelial to mesenchymal transition (EMT), which are helpful tools for evaluating the effectiveness of therapeutic compounds. We could show compared to 2D culture a reduction of proliferation in our 3D tumor model that is related to the clinical situation. Despite of this lower proliferation, the model predicted EGFR-targeted drug responses correctly according to the biomarker status as shown by comparison of the lung carcinoma cell lines HCC827 (EGFR -mutated, KRAS wild-type) and A549 (EGFR wild-type, KRAS-mutated) treated with the tyrosine-kinase inhibitor (TKI) gefitinib. To investigate drug responses of more advanced tumor cells, we induced EMT by long-term treatment with TGF-beta-1 as assessed by vimentin/pan-cytokeratin immunofluorescence staining. A flow-bioreactor was employed to adjust culture to physiological conditions, which improved tissue generation. Furthermore, we show the integration of drug responses upon gefitinib treatment or TGF-beta-1 stimulation - apoptosis, proliferation index and EMT - into a Boolean in silico model. Additionally, we explain how drug responses of tumor cells with a specific mutational background and counterstrategies against resistance can be predicted. We are confident that our 3D in vitro approach especially with its in silico expansion provides an additional value for preclinical drug testing in more realistic conditions than in 2D cell culture.

Mimicking Metastases Including Tumor Stroma: A New Technique to Generate a Three-Dimensional Colorectal Cancer Model Based on a Biological Decellularized Intestinal Scaffold.

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 ß-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.

Human Organotypic Lung Tumor Models: Suitable For Preclinical 18F-FDG PET-Imaging.

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-[18F]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.

Establishment of a human 3D lung cancer model based on a biological tissue matrix combined with a Boolean in silico model.

For the development of new treatment strategies against cancer, understanding signaling networks and their changes upon drug response is a promising approach to identify new drug targets and biomarker profiles. Pre-requisites are tumor models with multiple read-out options that accurately reflect the clinical situation. Tissue engineering technologies offer the integration of components of the tumor microenvironment which are known to impair drug response of cancer cells. We established three-dimensional (3D) lung carcinoma models on a decellularized tissue matrix, providing a complex microenvironment for cell growth. For model generation, we used two cell lines with (HCC827) or without (A549) an activating mutation of the epidermal growth factor receptor (EGFR), exhibiting different sensitivities to the EGFR inhibitor gefitinib. EGFR activation in HCC827 was inhibited by gefitinib, resulting in a significant reduction of proliferation (Ki-67 proliferation index) and in the induction of apoptosis (TUNEL staining, M30-ELISA). No significant effect was observed in conventional cell culture. Results from the 3D model correlated with the results of an in silico model that integrates the EGFR signaling network according to clinical data. The application of TGFß1 induced tumor cell invasion, accompanied by epithelial-mesenchymal transition (EMT) both in vitro and in silico. This was confirmed in the 3D model by acquisition of mesenchymal cell morphology and modified expression of fibronectin, E-cadherin, ß-catenin and mucin-1. Quantitative read-outs for proliferation, apoptosis and invasion were established in the complex 3D tumor model. The combined in vitro and in silico model represents a powerful tool for systems analysis.

Tissue engineering of a human 3D in vitro tumor test system.

Cancer is one of the leading causes of death worldwide. Current therapeutic strategies are predominantly developed in 2D culture systems, which inadequately reflect physiological conditions in vivo. Biological 3D matrices provide cells an environment in which cells can self-organize, allowing the study of tissue organization and cell differentiation. Such scaffolds can be seeded with a mixture of different cell types to study direct 3D cell-cell-interactions. To mimic the 3D complexity of cancer tumors, our group has developed a 3D in vitro tumor test system. Our 3D tissue test system models the in vivo situation of malignant peripheral nerve sheath tumors (MPNSTs), which we established with our decellularized porcine jejunal segment derived biological vascularized scaffold (BioVaSc). In our model, we reseeded a modified BioVaSc matrix with primary fibroblasts, microvascular endothelial cells (mvECs) and the S462 tumor cell line. For static culture, the vascular structure of the BioVaSc is removed and the remaining scaffold is cut open on one side (Small Intestinal Submucosa SIS-Muc). The resulting matrix is then fixed between two metal rings (cell crowns). Another option is to culture the cell-seeded SIS-Muc in a flow bioreactor system that exposes the cells to shear stress. Here, the bioreactor is connected to a peristaltic pump in a self-constructed incubator. A computer regulates the arterial oxygen and nutrient supply via parameters such as blood pressure, temperature, and flow rate. This setup allows for a dynamic culture with either pressure-regulated pulsatile or constant flow. In this study, we could successfully establish both a static and dynamic 3D culture system for MPNSTs. The ability to model cancer tumors in a more natural 3D environment will enable the discovery, testing, and validation of future pharmaceuticals in a human-like model.