Browsing by Subject "Ex vivo study"

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Open Access
15-Lipoxygenase-1 re-expression in colorectal cancer alters endothelial cell features through enhanced expression of TSP-1 and ICAM-1
(Elsevier, 2017-11) Tunçer, S.; Keşküş, A. G.; Çolakoğlu, M.; Çimen, I.; Yener, C.; Konu, Ö.; Banerjee, S.
15-lipoxygenase-1 (15-LOX-1) oxygenates linoleic acid to 13(S)-hydroxyoctadecadienoic acid (HODE). The enzyme is widely suppressed in different cancers and its re-expression has tumor suppressive effects. 15-LOX-1 has been shown to inhibit neoangiogenesis in colorectal cancer (CRC); in the present study we confirm this phenomenon and describe the mechanistic basis. We show that re-expression of 15-LOX-1 in CRC cell lines resulted in decreased transcriptional activity of HIF1α and reduced the expression and secretion of VEGF in both normoxic and hypoxic conditions. Conditioned medium (CM) was obtained from CRC or prostate cancer cell lines re-expressing 15-LOX-1 (15-LOX-1CM). 15-LOX-1CM treated aortic rings from 6-week old C57BL/6 mice showed significantly less vessel sprouting and more organized structure of vascular network. Human umbilical vein endothelial cells (HUVECs) incubated with 15-LOX-1CM showed reduced motility, enhanced expression of intercellular cell adhesion molecule (ICAM-1) and reduced tube formation but no change in proliferation or cell-cycle distribution. HUVECs incubated with 13(S)-HODE partially phenocopied the effects of 15-LOX-1CM, i.e., showed reduced motility and enhanced expression of ICAM-1, but did not reduce tube formation, implying the importance of additional factors. Therefore, a Proteome Profiler Angiogenesis Array was carried out, which showed that Thrombospondin-1 (TSP-1), a matrix glycoprotein known to strongly inhibit neovascularization, was expressed significantly more in HUVECs incubated with 15-LOX-1CM. TSP-1 blockage in HUVECs reduced the expression of ICAM-1 and enhanced cell motility, thereby providing a mechanism for reduced angiogenesis. The anti-angiogenic effects of 15-LOX-1 through enhanced expressions of ICAM-1 and TSP-1 are novel findings and should be explored further to develop therapeutic options.
Open Access
Application of the RIMARC algorithm to a large data set of action potentials and clinical parameters for risk prediction of atrial fibrillation
(Springer, 2015) Ravens, U.; Katircioglu-Öztürk, D.; Wettwer, E.; Christ, T.; Dobrev, D.; Voigt, N.; Poulet, C.; Loose, S.; Simon, J.; Stein, A.; Matschke, K.; Knaut, M.; Oto, E.; Oto, A.; Güvenir, H. A.
Ex vivo recorded action potentials (APs) in human right atrial tissue from patients in sinus rhythm (SR) or atrial fibrillation (AF) display a characteristic spike-and-dome or triangular shape, respectively, but variability is huge within each rhythm group. The aim of our study was to apply the machine-learning algorithm ranking instances by maximizing the area under the ROC curve (RIMARC) to a large data set of 480 APs combined with retrospectively collected general clinical parameters and to test whether the rules learned by the RIMARC algorithm can be used for accurately classifying the preoperative rhythm status. APs were included from 221 SR and 158 AF patients. During a learning phase, the RIMARC algorithm established a ranking order of 62 features by predictive value for SR or AF. The model was then challenged with an additional test set of features from 28 patients in whom rhythm status was blinded. The accuracy of the risk prediction for AF by the model was very good (0.93) when all features were used. Without the seven AP features, accuracy still reached 0.71. In conclusion, we have shown that training the machine-learning algorithm RIMARC with an experimental and clinical data set allows predicting a classification in a test data set with high accuracy. In a clinical setting, this approach may prove useful for finding hypothesis-generating associations between different parameters.