Cellular microenvironments, particularly those found in tumors, elicit a tolerogenic DC phenotype which can attenuate immune responses. Central to this process is the STAT3-mediated signaling cascade. As a transcription factor and oncogene, STAT3 promotes the expression of genes which allow tumor cells to proliferate, migrate and evade apoptosis. More importantly, activation of STAT3 in tumor infiltrating immune cells has been shown to be responsible, in part, for their immune-suppressed phenotype. The ability of STAT3 to orchestrate a diverse set of immunosuppressive instructions has made it an attractive target for cancer vaccines. Using a conditional hematopoietic knockout mouse model of STAT3, we evaluated the impact of STAT3 gene ablation on the differentiation of dendritic cells from bone marrow precursors. We also assessed the impact of STAT3 deletion on phagocytosis, maturation, cytokine secretion and antigen presentation by GM-CSF derived DCs in vitro. In addition to in vitro studies, we compared the therapeutic efficacy of DC vaccination using STAT3 deficient DCs to wild type counterparts in an intracranial mouse model of GBM. Our results indicated the following pleiotropic functions of STAT3: hematopoietic cells which lacked STAT3 were unresponsive to Flt3L and failed to differentiate as DCs. In contrast, STAT3 was not required for GM-CSF induced DC differentiation as both wild type and STAT3 null bone marrow cells gave rise to similar number of DCs. STAT3 also appeared to regulate the response of GM-CSF derived DCs to CpG. STAT3 null DCs expressed high levels of MHC-II, secreted more IL-12p70, IL-10, and TNFα were better antigen presenters in vitro. Although STAT3 deficient DCs displayed an enhanced activated phenotype in culture, they elicited comparable therapeutic efficacy in vivo compared to their wild type counterparts when utilized in vaccination paradigms in mice bearing intracranial glioma tumors.

Synthesis of digital microfluidic biochips (DMFBs) is a crucial to the advancement and realization of miniaturized, automated, programmable biochemistry solutions; synthesis is performed in three steps: scheduling, placement and routing. In principle, algorithms for specific steps should be interchangeable with one another; however, different research groups typically develop algorithms for each step in isolation from one another. Thus, it is difficult to compare algorithms against one another, or to determine which algorithms for different steps share synergies. We introduce an open source DMFB synthesis framework to encourage collaboration between researchers working in the area. We introduce a common interface and describe the internal data structures that must be updated to ensure that the interfaces are adhered to. We also present and describe a number of high-quality 2D and 3D debugging tools that provide graphical output for each stage of synthesis. © 2012 IEEE.