CD155/PVR plays a key role in cell motility during tumor cell invasion and migration

BACKGROUND: Invasion is an important early step of cancer metastasis that is not well understood. Developing therapeutics to limit metastasis requires the identification and validation of candidate proteins necessary for invasion and migration. METHODS: We developed a functional proteomic screen to identify mediators of tumor cell invasion. This screen couples Fluorophore Assisted Light Inactivation (FALI) to a scFv antibody library to systematically inactivate surface proteins expressed by human fibrosarcoma cells followed by a high-throughput assessment of transwell invasion. RESULTS: Using this screen, we have identified CD155 (the poliovirus receptor) as a mediator of tumor cell invasion through its role in migration. Knockdown of CD155 by FALI or by RNAi resulted in a significant decrease in transwell migration of HT1080 fibrosarcoma cells towards a serum chemoattractant. CD155 was found to be highly expressed in multiple cancer cell lines and primary tumors including glioblastoma (GBM). Knockdown of CD155 also decreased migration of U87MG GBM cells. CD155 is recruited to the leading edge of migrating cells where it colocalizes with actin and αv-integrin, known mediators of motility and adhesion. Knockdown of CD155 also altered cellular morphology, resulting in cells that were larger and more elongated than controls when plated on a Matrigel substrate. CONCLUSION: These results implicate a role for CD155 in mediating tumor cell invasion and migration and suggest that CD155 may contribute to tumorigenesis

The impact of uncertainties on predicted GHG emissions of dairy cow production systems

Dairy farms produce significant greenhouse gas (GHG) emissions and are therefore a focal point for GHG-mitigation practices. To develop viable mitigation options, we need robust (insensitive to changes in model parameters and assumptions) predictions of GHG emissions. To this end, we developed a stochastic model to estimate the robustness of predictions based on input parameters (GHG emission factors and production traits) and their uncertainties. In our study we explored how sensitive predictions of GHG emissions are to three factors: (1) system boundaries of the emission model (2) the uncertainty of input parameters due to quality of data or methodological choices (epistemic uncertainty) and (3) inherent variability in input parameters (variability uncertainty). To assess the effect of system boundaries, we compared two different boundaries: the “dairy farm gate” boundary (all GHG emissions are allocated to milk) and “system expansion” (the model gives a GHG credit to beef derived from culled cows and bull, heifer and calf fattening of surplus dairy calves outside the farm). Results using the farm-gate boundary provide guidance to dairy farmers to reduce GHG emissions of milk production. The results using system expansion are important for defining GHG abatement policies for milk and beef production. We found that the choice of system boundary had the strongest impact on the level and variation of predicted GHG emissions. Model predictions were least robust for lower-yielding dairy cow production systems and when we used system expansion. We also explored which GHG-abatement strategies have the most leverage by assessing the influence of each input parameter on model predictions. Predicted GHG emissions were least sensitive to variability-related uncertainty in production traits (i.e. replacement rate, calving interval). Lower-yielding production systems had the highest variation, indicating the highest potential for GHG mitigation of all production systems studied. Variation in predicted GHG emissions increased substantially when both epistemic and variability uncertainty in emission factors and variability uncertainty in production traits were included in the model. If the system boundary was set at the farm gate, the emission factor of N2O from nitrogen input into the soil had the highest impact on variation in predicted GHG emissions. This variation stems from uncertainties in predicting N2O emissions (epistemic uncertainty) but also from inherent variability of N2O emissions over time and space. The uncertainty of predicted GHG emissions can be reduced by increasing the precision in predicting N2O emissions. However, this additional information does not reduce GHG emissions itself. Knowing site specific variability of N2O emissions can help reduce GHG emissions by specific management (e.g. reduce soil compaction, adopted manure management, choice of suitable crops). In case of system expansion, uncertainty in GHG emission credit for dairy beef contributed the most to increasing the variation in predicted GHG emissions. The stochastic-model approach gave important insights into the robustness of model outcomes, which is crucial in the search for cost-effective GHG-abatement options. Despite the high degree of uncertainty when using system expansion, its results help identifying global GHG mitigation options of combined milk and beef productio

Ganglioside GD2-specific trifunctional surrogate antibody Surek demonstrates therapeutic activity in a mouse melanoma model.

BACKGROUND: Trifunctional bispecific antibodies (trAb) are a special class of bispecific molecules recruiting and activating T cells and accessory immune cells simultaneously at the targeted tumor. The new trAb Ektomab that targets the melanoma-associated ganglioside antigen GD2 and the signaling molecule human CD3 (hCD3) on T cells demonstrated potent T-cell activation and tumor cell destruction in vitro. However, the relatively low affinity for the GD2 antigen raised the question of its therapeutic capability. To further evaluate its efficacy in vivo it was necessary to establish a mouse model. METHODS: We generated the surrogate trAb Surek, which possesses the identical anti-GD2 binding arm as Ektomab, but targets mouse CD3 (mCD3) instead of hCD3, and evaluated its chemical and functional quality as a therapeutic antibody homologue. The therapeutic and immunizing potential of Surek was investigated using B78-D14, a B16 melanoma transfected with GD2 and GD3 synthases and showing strong GD2 surface expression. The induction of tumor-associated and autoreactive antibodies was evaluated. RESULTS: Despite its low affinity of approximately 107 M-1 for GD2, Surek exerted efficient tumor cell destruction in vitro at an EC50 of 70ng/ml [0.47nM]. Furthermore, Surek showed strong therapeutic efficacy in a dose-dependent manner and is superior to the parental GD2 mono-specific antibody, while the use of a control trAb with irrelevant target specificity had no effect. The therapeutic activity of Surek was strictly dependent on CD4+ and CD8+ T cells, and cured mice developed a long-term memory response against a second challenge even with GD2-negative B16 melanoma cells. Moreover, tumor protection was associated with humoral immune responses dominated by IgG2a and IgG3 tumor-reactive antibodies indicating a Th1-biased immune response. Autoreactive antibodies against the GD2 target antigen were not induced. CONCLUSION: Our data suggest that Surek revealed strong tumor elimination and anti-tumor immunization capabilities. The results warrant further clinical development of the human therapeutic equivalent antibody Ektomab