Chemotherapy pretreatment sensitizes solid tumor-derived cell lines to Vα24+ NKT cell-mediated cytotoxicity

There is an increasing awareness of the therapeutic potential for combining immune-based therapies with chemotherapy in the treatment of malignant diseases, but few published studies evaluate possible cytotoxic synergies between chemotherapy and cytotoxic immune cells. Human Vα24 +/Vβ11+ NKT cells are being evaluated for use in cell-based immunotherapy of malignancy because of their immune regulatory functions and potent cytotoxic potential. In this study, we evaluated the cytotoxicity of combinations of chemotherapy and NKT cells to determine whether there is a potential to combine these treatment modalities for human cancer therapy. The cytotoxicity of NKT cells was tested against solid-tumor derived cell lines NCI-H358, DLD-1, HT-29, DU-145, TSU-Pr1 and MDA-MB231, with or without prior treatment of these target cells, with a range of chemotherapy agents. Low concentrations of chemotherapeutic agents led to sensitization of cell lines to NKT-mediated cytotoxicity, with the greatest effect being observed for prostate cancer cells. Synergistic cytotoxicity occurred in an NKT cell in a dose-dependent manner. Chemotherapy agents induced upregulation of cell surface TRAIL-R2 (DR5) and Fas (CD95) expression, increasing the capacity for NKT cells to recognize and kill via TRAIL- and FasL-mediated pathways. We conclude that administration of cytotoxic immune cells after chemotherapy may increase antitumor activities in comparison with the use of either treatment alone.

R&D in clean technology: A project choice model with learning

In this study, we investigate the qualitative and quantitative effects of an R&D subsidy for a clean technology and a Pigouvian tax on a dirty technology on environmental R&D when it is uncertain how long the research takes to complete. The model is formulated as an optimal stopping problem, in which the number of successes required to complete the R&D project is finite and learning about the probability of success is incorporated. We show that the optimal R&D subsidy with the consideration of learning is higher than that without it. We also find that an R&D subsidy performs better than a Pigouvian tax unless suppliers have sufficient incentives to continue cost-reduction efforts after the new technology success-fully replaces the old one. Moreover, by using a two-project model, we show that a uniform subsidy is better than a selective subsidy.