Optimization of Invasion-Specific Effects of Betulin Derivatives on Prostate Cancer Cells through Lead Development

The anti-invasive and anti-proliferative effects of betulins and abietane derivatives was systematically tested using an organotypic model system of advanced, castration-resistant prostate cancers. A preliminary screen of the initial set of 93 compounds was performed in two-dimensional (2D) growth conditions using non-transformed prostate epithelial cells (EP156T), an androgen-sensitive prostate cancer cell line (LNCaP), and the castration-resistant, highly invasive cell line PC-3. The 25 most promising compounds were all betulin derivatives. These were selected for a focused secondary screen in three-dimensional (3D) growth conditions, with the goal to identify the most effective and specific anti-invasive compounds. Additional sensitivity and cytotoxicity tests were then performed using an extended cell line panel. The effects of these compounds on cell cycle progression, mitosis, proliferation and unspecific cytotoxicity, versus their ability to specifically interfere with cell motility and tumor cell invasion was addressed. To identify potential mechanisms of action and likely compound targets, multiplex profiling of compound effects on a panel of 43 human protein kinases was performed. These target de-convolution studies, combined with the phenotypic analyses of multicellular organoids in 3D models, revealed specific inhibition of AKT signaling linked to effects on the organization of the actin cytoskeleton as the most likely driver of altered cell morphology and motility.     

A Phenotypic Structure and Neural Correlates of Compulsive Behaviors in Adolescents

Background

A compulsivity spectrum has been hypothesized to exist across Obsessive-Compulsive disorder (OCD), Eating Disorders (ED), substance abuse (SA) and binge-drinking (BD). The objective was to examine the validity of this compulsivity spectrum, and differentiate it from an externalizing behaviors dimension, but also to look at hypothesized personality and neural correlates.

Method

A community-sample of adolescents (N=1938; mean age 14.5 years), and their parents were recruited via high-schools in 8 European study sites. Data on adolescents’ psychiatric symptoms, DSM diagnoses (DAWBA) and substance use behaviors (AUDIT and ESPAD) were collected through adolescent- and parent-reported questionnaires and interviews. The phenotypic structure of compulsive behaviors was then tested using structural equation modeling. The model was validated using personality variables (NEO-FFI and TCI), and Voxel-Based Morphometry (VBM) analysis.

Results

Compulsivity symptoms best fit a higher-order two factor model, with ED and OCD loading onto a compulsivity factor, and BD and SA loading onto an externalizing factor, composed also of ADHD and conduct disorder symptoms. The compulsivity construct correlated with neuroticism (r=0.638; p≤0.001), conscientiousness (r=0.171; p≤0.001), and brain gray matter volume in left and right orbitofrontal cortex, right ventral striatum and right dorsolateral prefrontal cortex. The externalizing factor correlated with extraversion (r=0.201; p≤0.001), novelty-seeking (r=0.451; p≤0.001), and negatively with gray matter volume in the left inferior and middle frontal gyri.

Conclusions

Results suggest that a compulsivity spectrum exists in an adolescent, preclinical sample and accounts for variance in both OCD and ED, but not substance-related behaviors, and can be differentiated from an externalizing spectrum.     

Global Genetic Variations Predict Brain Response to Faces

Face expressions are a rich source of social signals. Here we estimated the proportion of phenotypic variance in the brain response to facial expressions explained by common genetic variance captured by ∼500,000 single nucleotide polymorphisms. Using genomic-relationship-matrix restricted maximum likelihood (GREML), we related this global genetic variance to that in the brain response to facial expressions, as assessed with functional magnetic resonance imaging (fMRI) in a community-based sample of adolescents (n = 1,620). Brain response to facial expressions was measured in 25 regions constituting a face network, as defined previously. In 9 out of these 25 regions, common genetic variance explained a significant proportion of phenotypic variance (40–50%) in their response to ambiguous facial expressions; this was not the case for angry facial expressions. Across the network, the strength of the genotype-phenotype relationship varied as a function of the inter-individual variability in the number of functional connections possessed by a given region (R² = 0.38, p<0.001). Furthermore, this variability showed an inverted U relationship with both the number of observed connections (R² = 0.48, p<0.001) and the magnitude of brain response (R² = 0.32, p<0.001). Thus, a significant proportion of the brain response to facial expressions is predicted by common genetic variance in a subset of regions constituting the face network. These regions show the highest inter-individual variability in the number of connections with other network nodes, suggesting that the genetic model captures variations across the adolescent brains in co-opting these regions into the face network.     

Segmentation of Image Data from Complex Organotypic 3D Models of Cancer Tissues with Markov Random Fields

Organotypic, three dimensional (3D) cell culture models of epithelial tumour types such as prostate cancer recapitulate key aspects of the architecture and histology of solid cancers. Morphometric analysis of multicellular 3D organoids is particularly important when additional components such as the extracellular matrix and tumour microenvironment are included in the model. The complexity of such models has so far limited their successful implementation. There is a great need for automatic, accurate and robust image segmentation tools to facilitate the analysis of such biologically relevant 3D cell culture models. We present a segmentation method based on Markov random fields (MRFs) and illustrate our method using 3D stack image data from an organotypic 3D model of prostate cancer cells co-cultured with cancer-associated fibroblasts (CAFs). The 3D segmentation output suggests that these cell types are in physical contact with each other within the model, which has important implications for tumour biology. Segmentation performance is quantified using ground truth labels and we show how each step of our method increases segmentation accuracy. We provide the ground truth labels along with the image data and code. Using independent image data we show that our segmentation method is also more generally applicable to other types of cellular microscopy and not only limited to fluorescence microscopy.     

Polarized Growth of Fungal Hyphae Is Defined by an Alkaline pH Gradient

Robson, G. D., Prebble, E., Rickers, A., Hosking, S., Denning, D. W., Trinci, A. P. J., and Robertson, W. 1996. Polarized growth of fungal hyphae is defined by an alkaline pH gradient. Fungal Genetics and Biology 20, 289-298. Polarized cell growth is exhibited by a diverse range of eukaryotic and prokaryotic cells. The events which are responsible for this growth are poorly understood. However, the existence of ion gradients may play an important role in establishing and driving cell polarity. Using a pH-sensitive, ratiometric fluorescent dye to monitor intracellular pH in growing fungal hyphae, we report a gradient at the extending hyphal tip that is up to 1.4 pH units more alkaline than more distal regions. Both the magnitude and the length of the pH gradient were strongly correlated with the rate of hyphal extension and eradication of the gradient-arrested growth. These results suggest that alkaline pH gradients may be integral to hyphal extension in fungi.     

Isometric force development, isotonic shortening, and elasticity measurements from Ca(2+)-activated ventricular muscle of the guinea pig

Isometric tension and isotonic shortening were measured at constant levels of calcium activation of varying magnitude in mechanically disrupted EGTA-treated ventricular bundles from guinea pigs. The results were as follows: (a) The effect of creatine phosphate (CP) on peak tension and rate of shortening saturated at a CP concentration more than 10 mM; below that level tension was increased and shortening velocity decreased. We interpreted this to mean that CP above 10 mM was sufficient to buffer MgATP(2-) intracellularly. (b) The activated bundles exhibited an exponential stress-strain relationship and the series elastic properties did not vary appreciably with degree of activation or creatine phosphate level. (c) At a muscle length 20 percent beyond just taut, peak tension increased with Ca(2+) concentration over the range slightly below 10(-6) to slightly above 10(-4)M. (d) By releasing the muscle length-active tension curves were constructed. Force declined to 20 percent peak tension with a decrease in muscle length (after the recoil) of only 11 percent at 10(-4)M Ca(2+) and 6 percent at 4x10(-6)M Ca(2+). (e) The rate of shortening after a release was greater at lower loads. At identical loads (relative to maximum force at a given Ca(2+) level), velocity at a given time after the release was less at lower Ca(2+) concentrations; at 10 M(-5), velocity was 72 percent of that at 10(-4)M, and at 4x10(-6)M, active shortening was usually delayed and was 40 percent of the velocity at 10(-4) M. Thus, under the conditions of these experiments, both velocity and peak tension depend on the level of Ca(2+) activation over a similar range of Ca(2+) concentration.     

Quantification of Dynamic Morphological Drug Responses in 3D Organotypic Cell Cultures by Automated Image Analysis

Glandular epithelial cells differentiate into complex multicellular or acinar structures, when embedded in three-dimensional (3D) extracellular matrix. The spectrum of different multicellular morphologies formed in 3D is a sensitive indicator for the differentiation potential of normal, non-transformed cells compared to different stages of malignant progression. In addition, single cells or cell aggregates may actively invade the matrix, utilizing epithelial, mesenchymal or mixed modes of motility. Dynamic phenotypic changes involved in 3D tumor cell invasion are sensitive to specific small-molecule inhibitors that target the actin cytoskeleton. We have used a panel of inhibitors to demonstrate the power of automated image analysis as a phenotypic or morphometric readout in cell-based assays. We introduce a streamlined stand-alone software solution that supports large-scale high-content screens, based on complex and organotypic cultures. AMIDA (Automated Morphometric Image Data Analysis) allows quantitative measurements of large numbers of images and structures, with a multitude of different spheroid shapes, sizes, and textures. AMIDA supports an automated workflow, and can be combined with quality control and statistical tools for data interpretation and visualization. We have used a representative panel of 12 prostate and breast cancer lines that display a broad spectrum of different spheroid morphologies and modes of invasion, challenged by a library of 19 direct or indirect modulators of the actin cytoskeleton which induce systematic changes in spheroid morphology and differentiation versus invasion. These results were independently validated by 2D proliferation, apoptosis and cell motility assays. We identified three drugs that primarily attenuated the invasion and formation of invasive processes in 3D, without affecting proliferation or apoptosis. Two of these compounds block Rac signalling, one affects cellular cAMP/cGMP accumulation. Our approach supports the growing needs for user-friendly, straightforward solutions that facilitate large-scale, cell-based 3D assays in basic research, drug discovery, and target validation.