3D tissue-engineered model of bone adaptation (BONEMIMIC)
3D tissue-engineered model of bone adaptation
Date du début: 1 janv. 2014,
Date de fin: 31 déc. 2015
For the development of advanced therapeutics, preventive or even cures of osteoporosis, there is a need to understand the cellular and molecular mechanisms of bone physiology. Screening and evaluation of drug effects in a reproducible controlled and dynamic 3D cell culture system would facilitate the transferability of the results from pre-clinical to clinical stage and be of high benefit for the pharmaceutical industry. Understanding tissue development in general and during regeneration and comprehension of treatment mechanisms is synonymous to welfare of our society.The project aims at taking current approaches in bone tissue engineering one step further resulting in an in vitro model system that mimics normal bone turnover. We believe that only through the setup of an in vitro co-culture that enables i) cellular crosstalk, ii) timely monitoring of growth and resorption of mineralized extracellular matrix (ECM) and iii) the application of physiological mechanical stimulation we will be able to mimic natural bone adaptation and use the system to reproduce the effect of a drug.We shall first characterize the human bone marrow stromal and human monocyte cell differentiation profile toward the osteoblast (Ob) or osteoclast (Oc) phenotype in a single cell culture, either with or without a mechanical stimulus. Secondly, the optimal co-culture conditions to support Ob differentiation but also osteoclastogenesis will be established by setting Ob/Oc cell rates and media composition. The effects of a mechanical stimulus on Ob and Oc cell differentiation will be evaluated by real-time RT-PCR and enzymatic activity. Bone adaptation will be timely monitored by microcomputed tomography. Finally, the best co-culture regime will be selected to characterize the effects of a clinically applied drug with known acting mechanism used to treat osteoporosis. Bone remodeling will be assessed by quantification expression of specific markers and by longitudinal monitoring of ECM.
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