Prophylactic DNA vaccine targeting Foxp3 + regulatory T cells depletes myeloid-derived suppressor cells and improves anti-melanoma immune responses in a murine model

Regulatory T cells (Treg) and myeloid-derived suppressor cells (MDSC) are the two important and interactive immunosuppressive components of the tumor microenvironment that hamper anti-tumor immune responses. Therefore, targeting these two populations together might be beneficial for overcoming immune suppression in the tumor microenvironment. We have recently shown that prophylactic Foxp3 DNA/recombinant protein vaccine (Foxp3 vaccine) promotes immunity against Treg in tumor-free conditions. In the present study, we investigated the immune modulatory effects of a prophylactic regimen of the redesigned Foxp3 vaccine in the B16F10 melanoma model. Our results indicate that Foxp3 vaccination continuously reduces Treg population in both the tumor site and the spleen. Surprisingly, Treg reduction was associated with a significant decrease in the frequency of MDSC, both in the spleen and in the tumor environment. Furthermore, Foxp3 vaccination resulted in a significant reduction of arginase-1(Arg-1)-induced nitric oxide synthase (iNOS), reactive oxygen species (ROS) and suppressed MDSC activity. Moreover, this concurrent depletion restored production of inflammatory cytokine IFN-γ and enhanced tumor-specific CTL response, which subsequently resulted in the reduction of tumor growth and the improved survival rate of vaccinated mice. In conclusion, our results revealed that Foxp3 vaccine promotes an immune response against tumor by targeting both Treg and MDSC, which could be exploited as a potential immunotherapy approach.. © 2017, Springer-Verlag GmbH Germany, part of Springer Nature

Prophylactic DNA vaccine targeting Foxp3+regulatory T cells depletes myeloid-derived suppressor cells and improves anti-melanoma immune responses in a murine model

Abstract Regulatory T cells (Treg) and myeloid-derived suppressor cells (MDSC) are the two important and interactive immunosuppressive components of the tumor microenvironment that hamper anti-tumor immune responses. Therefore, targeting these two populations together might be beneficial for overcoming immune suppression in the tumor microenvironment. We have recently shown that prophylactic Foxp3 DNA/recombinant protein vaccine (Foxp3 vaccine) promotes immunity against Treg in tumor-free conditions. In the present study, we investigated the immune modulatory effects of a prophylactic regimen of the redesigned Foxp3 vaccine in the B16F10 melanoma model. Our results indicate that Foxp3 vaccination continuously reduces Treg population in both the tumor site and the spleen. Surprisingly, Treg reduction was associated with a significant decrease in the frequency of MDSC, both in the spleen and in the tumor environment. Furthermore, Foxp3 vaccination resulted in a significant reduction of arginase-1(Arg-1)-induced nitric oxide synthase (iNOS), reactive oxygen species (ROS) and suppressed MDSC activity. Moreover, this concurrent depletion restored production of inflammatory cytokine IFN-γ and enhanced tumor-specific CTL response, which subsequently resulted in the reduction of tumor growth and the improved survival rate of vaccinated mice. In conclusion, our results revealed that Foxp3 vaccine promotes an immune response against tumor by targeting both Treg and MDSC, which could be exploited as a potential immunotherapy approach. Keywords Regulatory T cells Myeloid-derived suppressor cells Foxp3 Melanom

Using Omissive Faults to Obtain Local Convergence in Partially Connected Networks

Approximate Agreement is an important issue in fault-tolerant distributed computing where non-faulty processes exchange and vote upon their local values, to arrive at values which are within the range of the initial values of the non-faulty processes and within a predefined tolerance of each other. Results to date in Approximate Agreement, however, are not capable of exploiting omission faults. Omission faults are presumed not to occur or a predefined default value is substituted for those values not received, or they are globally discarded before the voting algorithm executes. As a result, hybrid fault models can not differentiate between omissive and transmissive faults. The performance and fault tolerance expressions for completely connected networks, in the presence of omission faults, have recently been obtained. This paper develops a methodology which logically converts partially connected networks into completely connected networks. Hence, the results of completely connected systems can be applied to obtain the local convergence and fault tolerance expressions for partially connected systems

Exploiting omissive faults in synchronous approximate agreement

In a fault-tolerant distributed system, it is often necessary for nonfaulty processes to agree on the value of a shared data item. The criterion of Approximate Agreement does not require processes to achieve exact agreement on a value; rather, they need only agree to within a predefined numerical tolerance. Approximate Agreement can be achieved through convergent voting algorithms. Previous research has studied convergent voting algorithms under mixed-mode or hybrid fault models, such as the Thambidurai and Park Hybrid fault model, comprised of three fault modes: asymmetric, symmetric, and benign. This paper makes three major contributions to the state of the art in fault-tolerant convergent voting. 1) We partition both the asymmetric and symmetric fault modes into disjoint omissive and transmissive submodes. The resulting five-mode hybrid fault model is a superset of previous hybrid fault models. 2) We present a new family of voting algorithms, called Omission Mean Subsequence Reduced (OMSR), which implicitly recognize and exploit omissive behavior in malicious faults while still maintaining full Byzantine fault tolerance. 3) We show that OMSR voting algorithms are more fault-tolerant than previous voting algorithms if any of the currently active faults is omissive