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.

Cat-E: A comprehensive web tool for exploring cancer targeting strategies.

Identifying potential cancer-associated genes and drug targets from omics data is challenging due to its diverse sources and analyses, requiring advanced skills and large amounts of time. To facilitate such analysis, we developed Cat-E (Cancer Target Explorer), a novel R/Shiny web tool designed for comprehensive analysis with evaluation according to cancer-related omics data. Cat-E is accessible at https://cat-e.bioinfo-wuerz.eu/. Cat-E compiles information on oncolytic viruses, cell lines, gene markers, and clinical studies by integrating molecular datasets from key databases such as OvirusTB, TCGA, DrugBANK, and PubChem. Users can use all datasets and upload their data to perform multiple analyses, such as differential gene expression analysis, metabolic pathway exploration, metabolic flux analysis, GO and KEGG enrichment analysis, survival analysis, immune signature analysis, single nucleotide variation analysis, dynamic analysis of gene expression changes and gene regulatory network changes, and protein structure prediction. Cancer target evaluation by Cat-E is demonstrated here on lung adenocarcinoma (LUAD) datasets. By offering a user-friendly interface and detailed user manual, Cat-E eliminates the need for advanced computational expertise, making it accessible to experimental biologists, undergraduate and graduate students, and oncology clinicians. It serves as a valuable tool for investigating genetic variations across diverse cancer types, facilitating the identification of novel diagnostic markers and potential therapeutic targets.

Software JimenaE allows efficient dynamic simulations of Boolean networks, centrality and system state analysis.

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.

Efficient Redirection of NK Cells by Genetic Modification with Chemokine Receptors CCR4 and CCR2B.

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.

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.

The influence of differently functionalized nanodiamonds on proliferation, apoptosis and EMT/MET phenomena in 2D and 3D tumor cell cultures.

Nanodiamonds (ND) have been suggested to have several potential uses in biomedicine, since they are seemingly biocompatible. However, data about the biological effects of ND in physiological conditions are scarce. In this study, we observed that prostate cancer cells (LNCaP) and breast cancer cells (MDA-MB-231 and MCF-7) cultured with ND show morphological changes and altered gene and protein expression. In 2D we could detect only slight effects of ND on cell growth and apoptosis induction. Therefore, we applied different functionalized ND in a novel 3D cell culture model that reflects better tissue conditions compared to conventional 2D cell cultures. In 3D proliferation was reduced by all nanoparticles and benzoquinone functionalized ND induced cell death. As the used decellularized scaffold maintains the tissue architecture, we could also functionally investigate if nanoparticles induce cell migration into deeper layers and if they display markers of Mesenchymal Epithelial Transition (MET). We detected in more mesenchymal and invasive growing MDA-MB-231 cells less vimentin and increased levels of pan-cytokeratin expression after ND treatment, which indicates a MET induction. Our observations suggest that the presence of ND stimulates MET, with varying degrees of transition. The observation that ND do not support the opposite, EMT, is beneficial, since EMT is known to play a major role in tumor metastasis. However, a special focus should be placed on the characterization of biological effects to be able to guarantee the safety of ND in clinical use.

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.

Development of a bioreactor system for pre-endothelialized cardiac patch generation with enhanced viscoelastic properties by combined collagen I compression and stromal cell culture.

Treatment of terminal heart failure still poses a significant clinical problem. Cardiac tissue engineering could offer autologous solutions for the replacement of nonfunctional myocardial tissue. So far, soft matrix construction and missing large-scale prevascularization prevented the application of sizeable cardiac repair patches. We developed a novel bioreactor system for semi-automatic compression of a collagen I hydrogel applying 16 times higher pressure than in previous studies. Resistance towards compression stress was investigated for multiple cardiac-related cell types. For scaffold prevascuarization, a tubular cavity was imprinted during the compaction process. Primary cardiac-derived endothelial cells (ECs) were isolated from human left atrial appendages (HLAAs) and characterized by fluorescence-activated cell sorting (FACS) and immunocytology. EC were then seeded into the preformed channel with dermal fibroblasts as interstitial cell component of the fully cellularized patch. After 8 days of constant perfusion culture within the same bioreactor, scaffold dynamic modulus and cell viability were analyzed. Endothelial proliferation and vessel maturation were examined by immunohistochemistry and transmission electron microscopy. Our design allowed for scaffold production and dynamic culture in a one-stop-shop model. Enhanced compression and cell-mediated matrix remodeling induced a significant increase in scaffold stiffness while ensuring excellent cell survival. For the first time, we could isolate HLAA-derived EC with proliferative potential. ECs within the central channel proliferated during flow culture, continuously expressing endothelial markers (CD31) and displaying basal membrane synthesis (collagen IV, ultrastructural analysis). After 7 days of culture, a complete endothelial monolayer could be observed. Covering cells aligned themselves in flow direction and developed mature cell-cell contacts.

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.

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.

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.

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.

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.

Recombinant Collagen I Peptide Microcarriers for Cell Expansion and Their Potential Use As Cell Delivery System in a Bioreactor Model.

Tissue engineering is a promising field, focused on developing solutions for the increasing demand on tissues and organs regarding transplantation purposes. The process to generate such tissues is complex, and includes an appropriate combination of specific cell types, scaffolds, and physical or biochemical stimuli to guide cell growth and differentiation. Microcarriers represent an appealing tool to expand cells in a three-dimensional (3D) microenvironment, since they provide higher surface-to volume ratios and mimic more closely the in vivo situation compared to traditional two-dimensional methods. The vascular system, supplying oxygen and nutrients to the cells and ensuring waste removal, constitutes an important building block when generating engineered tissues. In fact, most constructs fail after being implanted due to lacking vascular support. In this study, we present a protocol for endothelial cell expansion on recombinant collagen-based microcarriers under dynamic conditions in spinner flask and bioreactors, and we explain how to determine in this setting cell viability and functionality. In addition, we propose a method for cell delivery for vascularization purposes without additional detachment steps necessary. Furthermore, we provide a strategy to evaluate the cell vascularization potential in a perfusion bioreactor on a decellularized biological matrix. We believe that the use of the presented methods could lead to the development of new cell-based therapies for a large range of tissue engineering applications in the clinical practice.

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.

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.

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.

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.

Non-animal models of epithelial barriers (skin, intestine and lung) in research, industrial applications and regulatory toxicology.

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.