a-combined-3d-tissue-engineered-vitroin-silico-lung-tumor-model-for

A Combined 3D Tissue Engineered <em>In Vitro</em>/<em>In Silico</em> 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 ...

recombinant-collagen-i-peptide-microcarriers-for-cell-expansion-their

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 ...

University Hospital Wuerzburg

Fraunhofer Institute Interfacial Engineering and Biotechnology IGB

Fraunhofer Institute for Silicate Research ISC

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 TGFβ1 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, β-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.

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

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.

ArticleTotal : 2	Year
Publication title Cited by 29	2016
Publication title Cited by 9	2018

Article	Year
Establishment of a human 3D lung cancer model based on a biological tissue matrix combined with a Boolean in silico model. Molecular oncology\| PubMed ID: 24388494	2014
Human Organotypic Lung Tumor Models: Suitable For Preclinical 18F-FDG PET-Imaging. PloS one\| PubMed ID: 27501455	2016

Gudrun Dandekar

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