Stromal DDR2 Promotes Ovarian Cancer Metastasis through Regulation of Metabolism and Secretion of Extracellular Matrix Proteins.

Ovarian cancer is the leading cause of gynecologic cancer-related deaths. The propensity for metastasis within the peritoneal cavity is a driving factor for the poor outcomes associated with this disease, but there is currently no effective therapy targeting metastasis. In this study, we investigate the contribution of stromal cells to ovarian cancer metastasis and identify normal stromal cell expression of the collagen receptor, discoidin domain receptor 2 (DDR2), that acts to facilitate ovarian cancer metastasis. In vivo, global genetic inactivation of Ddr2 impairs the ability of Ddr2-expressing syngeneic ovarian cancer cells to spread throughout the peritoneal cavity. Specifically, DDR2 expression in mesothelial cells lining the peritoneal cavity facilitates tumor cell attachment and clearance. Subsequently, omentum fibroblast expression of DDR2 promotes tumor cell invasion. Mechanistically, we find DDR2-expressing fibroblasts are more energetically active, such that DDR2 regulates glycolysis through AKT/SNAI1 leading to suppressed fructose-1,6-bisphosphatase and increased hexokinase activity, a key glycolytic enzyme. Upon inhibition of DDR2, we find decreased protein synthesis and secretion. Consequently, when DDR2 is inhibited, there is reduction in secreted extracellular matrix proteins important for metastasis. Specifically, we find that fibroblast DDR2 inhibition leads to decreased secretion of the collagen crosslinker, LOXL2. Adding back LOXL2 to DDR2 deficient fibroblasts rescues the ability of tumor cells to invade. Overall, our results suggest that stromal cell expression of DDR2 is an important mediator of ovarian cancer metastasis. IMPLICATIONS: DDR2 is highly expressed by stromal cells in ovarian cancer that can mediate metastasis and is a potential therapeutic target in ovarian cancer.

GAS6/AXL Inhibition Enhances Ovarian Cancer Sensitivity to Chemotherapy and PARP Inhibition through Increased DNA Damage and Enhanced Replication Stress.

Over 80% of women with high-grade serous ovarian cancer (HGSOC) develop tumor resistance to chemotherapy and die of their disease. There are currently no FDA-approved agents to improve sensitivity to first-line platinum- and taxane-based chemotherapy or to PARP inhibitors. Here, we tested the hypothesis that expression of growth arrest-specific 6 (GAS6), the ligand of receptor tyrosine kinase AXL, is associated with chemotherapy response and that sequestration of GAS6 with AVB-S6-500 (AVB-500) could improve tumor response to chemotherapy and PARP inhibitors. We found that GAS6 levels in patient tumor and serum samples collected before chemotherapy correlated with ovarian cancer chemoresponse and patient survival. Compared with chemotherapy alone, AVB-500 plus carboplatin and/or paclitaxel led to decreased ovarian cancer-cell survival in vitro and tumor burden in vivo. Cells treated with AVB-500 plus carboplatin had more DNA damage, slower DNA replication fork progression, and fewer RAD51 foci than cells treated with carboplatin alone, indicating AVB-500 impaired homologous recombination (HR). Finally, treatment with the PARP inhibitor olaparib plus AVB-500 led to decreased ovarian cancer-cell survival in vitro and less tumor burden in vivo. Importantly, this effect was seen in HR-proficient and HR-deficient ovarian cancer cells. Collectively, our findings suggest that GAS6 levels could be used to predict response to carboplatin and AVB-500 could be used to treat platinum-resistant, HR-proficient HGSOC. IMPLICATIONS: GAS6/AXL is a novel target to sensitize ovarian cancers to carboplatin and olaparib. Additionally, GAS6 levels can be associated with response to carboplatin treatment.

A modelling framework for simulation of ultrasonic guided wave-based inspection of welded rail tracks.

A modelling framework for ultrasonic inspection of waveguides with arbitrary discontinuities, excited using piezoelectric transducers, is developed. The framework accounts for multi-modal, dispersive and damped one dimensional propagation over long distances. The proposed model is applied to simulate a realistic guided wave-based inspection of a welded rail. The framework models the excitation, propagation and scattering of guided waves from welds by respectively employing a hybrid model that couples a 3D FEM model of a piezoelectric transducer with a 2D SAFE model of the rail; a 2D SAFE model of the rail; and another hybrid method which couples a 3D FEM model of the arbitrary discontinuity (weld) with two SAFE models of the rail to represent the semi-infinite incoming and outgoing waveguides. Optimal damping parameters for hysteretic and viscous damping, respectively, are determined using a model updating procedure to approximate attenuation in the rail. Good agreement between the experimental measurement and simulation is demonstrated, even for weld reflections originating over 640 m from the transducer location. The proposed physics-based framework can be used to efficiently perform multiple analyses considering different numbers and locations of welds, different excitation signals or to investigate the effects of changes in parameters such as transducer geometry, or material property variations caused by temperature fluctuations. The framework could therefore be used in future to set up a digital twin of a section of rail track, or in the development of a rail monitoring system by predicting reflections from defects which cannot readily be measured, but which can be simulated.

Estimation of rail properties using semi-analytical finite element models and guided wave ultrasound measurements.

Guided wave based monitoring systems require accurate knowledge of mode propagation characteristics such as wavenumber and group velocity dispersion curves. These characteristics may be computed numerically for a rail provided that the material and geometric properties of the rail are known. Generally, the rail properties are not known with sufficient accuracy and these properties also change due to temperature, rail wear and rail grinding. An automated procedure is proposed to estimate material and geometric properties of a rail by finding the properties which, when input into a Semi-Analytical Finite Element (SAFE) model, accurately reproduce measured dispersion characteristics. Pulse-echo measurements were performed and spectrograms show the reflections from aluminothermic welds of three modes of propagation. The SAFE method was used to solve the forward problem of predicting the dispersion characteristics for specified rail properties. Dispersion curves are computed for different combinations of Poisson's ratio and three geometric parameters. These dispersion curves are scaled to cover a range of longitudinal speeds of sound of the rail material. A technique is developed to determine which SAFE model provided the best fit to the experimental measurements. The technique does not require knowledge of the distances to the reflectors; rather these distances are estimated as part of the proposed procedure. A SAFE model with the estimated rail parameters produced dispersion curves and distances in very good agreement with the measured spectrograms. In addition, the estimated mean geometric parameters agreed with the measured profile of the rail head.

TWIST1 induces expression of discoidin domain receptor 2 to promote ovarian cancer metastasis.

The mesenchymal gene program has been shown to promote the metastatic progression of ovarian cancer; however, specific proteins induced by this program that lead to these metastatic behaviors have not been identified. Using patient derived tumor cells and established human ovarian tumor cell lines, we find that the Epithelial-to-Mesenchymal Transition inducing factor TWIST1 drives expression of discoidin domain receptor 2 (DDR2), a receptor tyrosine kinase (RTK) that recognizes fibrillar collagen as ligand. The expression and action of DDR2 was critical for mesothelial cell clearance, invasion and migration in ovarian tumor cells. It does so, in part, by upregulating expression and activity of matrix remodeling enzymes that lead to increased cleavage of fibronectin and spreading of tumor cells. Additionally, DDR2 stabilizes SNAIL1, allowing for sustained mesenchymal phenotype. In patient derived ovarian cancer specimens, DDR2 expression correlated with enhanced invasiveness. DDR2 expression was associated with advanced stage ovarian tumors and metastases. In vivo studies demonstrated that the presence of DDR2 is critical for ovarian cancer metastasis. These findings indicate that the collagen receptor DDR2 is critical for multiple steps of ovarian cancer progression to metastasis, and thus, identifies DDR2 as a potential new target for the treatment of metastatic ovarian cancer.

Human skull shape and masticatory induced stress: Objective comparison through the use of non-rigid registration.

Variation in masticatory induced stress, caused by shape changes in the human skull, is quantified in this article. A comparison on masticatory induced stress is presented subject to a variation in human skull shape. Non-rigid registration is employed to obtain appropriate computational domain representations. This procedure allows the isolation of shape from other variations that could affect the results. An added benefit, revealed through the use of non-rigid registration to acquire appropriate domain representation, is the possibility of direct and objective comparison and manipulation. The effect of mapping uncertainty on the direct comparison is also quantified. As shown in this study, exact difference values are not necessarily obtained, but a non-rigid map between subject shapes and numerical results gives an objective indication on the location of differences.