TY  - JOUR
A1  - Ribitsch, Iris
A1  - Peham, Christian
A1  - Ade, Nicole
A1  - Duerr, Julia
A1  - Handschuh, Stephan
A1  - Schramel, Johannes Peter
A1  - Vogl, Claus
A1  - Walles, Heike
A1  - Egerbacher, Monika
A1  - Jenner, Florian
T1  - Structure-Function relationships of equine menisci
JF  - PLoS ONE
N2  - Meniscal pathologies are among the most common injuries of the femorotibial joint in both human and equine patients. Pathological forces and ensuing injuries of the cranial horn of the equine medial meniscus are considered analogous to those observed in the human posterior medial horn. Biomechanical properties of human menisci are site-and depth-specific. However, the influence of equine meniscus topography and composition on its biomechanical properties is yet unknown. A better understanding of equine meniscus composition and biomechanics could advance not only veterinary therapies for meniscus degeneration or injuries, but also further substantiate the horse as suitable translational animal model for (human) meniscus tissue engineering. Therefore, the aim of this study was to investigate the composition and structure of the equine knee meniscus in a site-and age-specific manner and their relationship with potential site-specific biomechanical properties. The meniscus architecture was investigated histologically. Biomechanical testing included evaluation of the shore hardness (SH), stiffness and energy loss of the menisci. The SH was found to be subjected to both age and site-specific changes, with an overall higher SH of the tibial meniscus surface and increase in SH with age. Stiffness and energy loss showed neither site nor age related significant differences. The macroscopic and histologic similarities between equine and human menisci described in this study, support continued research in this field.
KW  - Human Medial Meniscus
KW  - Articular-Cartilage
KW  - Biomechanical Properties
KW  - Compressive Properties
KW  - Human Knee
KW  - Collagen
KW  - Injuries
KW  - Models
KW  - Repair
KW  - Osteoarthritis
Y1  - 2018
U6  - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:bvb:20-opus-225214
VL  - 13
IS  - 3
ER  - 
TY  - JOUR
A1  - Göttlich, Claudia
A1  - Kunz, Meik
A1  - Zapp, Cornelia
A1  - Nietzer, Sarah L.
A1  - Walles, Heike
A1  - Dandekar, Thomas
A1  - Dandekar, Gudrun
T1  - A combined tissue-engineered/in silico signature tool patient stratification in lung cancer
JF  - Molecular Oncology
N2  - 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.
KW  - 3D lung tumor model
KW  - Boolean signaling network
KW  - chemoresistance
KW  - HSP90 inhibitor
KW  - insilico drug screening too
KW  - KRAS mutation signature
Y1  - 2018
U6  - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:bvb:20-opus-233137
VL  - 12
ER  -