ABSTRACT
The tumor suppressor Pdcd4 is involved in multiple pathways. Considering its biological action conflicting data in the literature exist and, consequently, our own studies point to a cell type specific action of Pdcd4. In the present study, using several Pdcd4 knock down cell lines we succeeded to identify angiopoietin-2 (Ang-2) as a gene up-regulated on the mRNA and protein level. The subsequent enhanced peptide secretion forced wild type Bon-1 cells in a neoplastic direction demonstrated by increased proliferation and colony formation while cell adhesion was decreased. Most likely, the stimulation of Ang-2 is in part mediated by increased activation of AP-1 but different signal transduction pathways may also be involved since we found opposite activation of PI3K/Akt/mTOR and MAPK7ERK pathways (both known to regulate in Ang-2 expression). Ang-2 is a modulator of vascular remodeling. Therefore, we analyzed the effect of supernatants from Pdcd4 knock-down cell lines on endothelial cells. Again, we detected reduced cell adhesion and increased colony formation. Probably, the most impressive effect was described on tube formation in a model for angiogenesis. Tube length and junctions of endothelial cells treated with conditioned medium from Pdcd4 knock-down cells were considerably increased. Both, up-regulation of Ang-2 and down-regulation of Pdcd4 are described for many tumors. However, this is the first study showing a direct impact of Pdcd4 on Ang-2 levels and, thereby, angiogenesis. Our data suggest a completely new mechanism for Pdcd4 to act as a tumor suppressor rendering Pdcd4 an attractive target for new therapeutic strategies in cancer treatment.
Subject(s)
Angiopoietin-2/genetics , Apoptosis Regulatory Proteins/deficiency , Apoptosis Regulatory Proteins/metabolism , Gene Knockdown Techniques , Neovascularization, Physiologic/genetics , RNA-Binding Proteins/metabolism , Up-Regulation/genetics , Angiopoietin-2/metabolism , Apoptosis Regulatory Proteins/genetics , Cell Adhesion/drug effects , Cell Line , Cell Proliferation/drug effects , Colony-Forming Units Assay , Culture Media, Conditioned/pharmacology , Endothelial Cells/cytology , Endothelial Cells/drug effects , Endothelial Cells/metabolism , Humans , Neovascularization, Physiologic/drug effects , RNA, Messenger/genetics , RNA, Messenger/metabolism , RNA, Small Interfering/metabolism , RNA-Binding Proteins/genetics , Reverse Transcriptase Polymerase Chain Reaction , Subcellular Fractions/drug effects , Subcellular Fractions/metabolism , Transfection , Up-Regulation/drug effectsABSTRACT
Motility studies of cells often rely on computer software that analyzes time-lapse recorded movies and establishes cell trajectories fully automatically. This raises the question of reproducibility of results, since different programs could yield significantly different results of such automated analysis. The fact that the segmentation routines of such programs are often challenged by nanostructured surfaces makes the question more pertinent. Here we illustrate how it is possible to track cells on bright field microscopy images with image analysis routines implemented in an open-source cell tracking program, PACT (Program for Automated Cell Tracking). We compare the automated motility analysis of three cell tracking programs, PACT, Autozell, and TLA, using the same movies as input for all three programs. We find that different programs track overlapping, but different subsets of cells due to different segmentation methods. Unfortunately, population averages based on such different cell populations, differ significantly in some cases. Thus, results obtained with one software package are not necessarily reproducible by other software.
ABSTRACT
The direct observation of cells over time using time-lapse microscopy can provide deep insights into many important biological processes. Reliable analyses of motility, proliferation, invasive potential or mortality of cells are essential to many studies involving live cell imaging and can aid in biomarker discovery and diagnostic decisions. Given the vast amount of image- and time-series data produced by modern microscopes, automated analysis is a key feature to capitalize the potential of time-lapse imaging devices. To provide fast and reproducible analyses of multiple aspects of cell behaviour, we developed TimeLapseAnalyzer. Apart from general purpose image enhancements and segmentation procedures, this extensible, self-contained, modular cross-platform package provides dedicated modalities for fast and reliable analysis of multi-target cell tracking, scratch wound healing analysis, cell counting and tube formation analysis in high throughput screening of live-cell experiments. TimeLapseAnalyzer is freely available (MATLAB, Open Source) at http://www.informatik.uni-ulm.de/ni/mitarbeiter/HKestler/tla.
Subject(s)
Microscopy/methods , Reproducibility of ResultsABSTRACT
BACKGROUND: Cell motility is a critical parameter in many physiological as well as pathophysiological processes. In time-lapse video microscopy, manual cell tracking remains the most common method of analyzing migratory behavior of cell populations. In addition to being labor-intensive, this method is susceptible to user-dependent errors regarding the selection of "representative" subsets of cells and manual determination of precise cell positions. RESULTS: We have quantitatively analyzed these error sources, demonstrating that manual cell tracking of pancreatic cancer cells lead to mis-calculation of migration rates of up to 410%. In order to provide for objective measurements of cell migration rates, we have employed multi-target tracking technologies commonly used in radar applications to develop fully automated cell identification and tracking system suitable for high throughput screening of video sequences of unstained living cells. CONCLUSION: We demonstrate that our automatic multi target tracking system identifies cell objects, follows individual cells and computes migration rates with high precision, clearly outperforming manual procedures.
