Enhanced effector and memory CTL responses generated by incorporation of receptor activator of NF-kappa B(RANK)/RANK ligand costimulatory molecules into dendritic cell immunogens expressing a human tumor-specific antigen

The outcome of dendritic cell (DC) presentation of Ag to T cells via the TCR/MHC synapse is determined by second signaling through CD80/86 and, importantly, by ligation of costimulatory ligands and receptors located at the DC and T cell surfaces. Downstream signaling triggered by costimulatory molecule ligation results in reciprocal DC and T cell activation and survival, which predisposes to enhanced T cell-mediated immune responses. In this study, we used adenoviral vectors to express a model tumor Ag (the E7 oncoprotein of human papillomavirus 16) with or without coexpression of receptor activator of NF-kappaB (RANK)/RANK ligand (RANKL) or CD40/CD40L costimulatory molecules, and used these transgenic DCs to immunize mice for the generation of E7-directed CD8(+) T cell responses. We show that coexpression of RANK/RANKL, but not CD40/CD40L, in E7-expressing DCs augmented E7-specific IFN-gamma-secreting effector and memory T cells and E7-specific CTLs. These responses were also augmented by coexpression of T cell costimulatory molecules (RANKL and CD40L) or DC costimulatory molecules (RANK and CD40) in the E7-expressing DC immunogens. Augmentation of CTL responses correlated with up-regulation of CD80 and CD86 expression in DCs transduced with costimulatory molecules, suggesting a mechanism for enhanced T cell activation/survival. These results have generic implications for improved tumor Ag-expressing DC vaccines, and specific implications for a DC-based vaccine approach for human papillomavirus 16-associated cervical carcinoma.

Mapping the royal road and other hierarchical functions

In this paper we present a technique for visualising hierarchical and symmetric, multimodal fitness functions that have been investigated in the evolutionary computation literature. The focus of this technique is on landscapes in moderate-dimensional, binary spaces (i.e., fitness functions defined over {0, 1}(n), for n less than or equal to 16). The visualisation approach involves an unfolding of the hyperspace into a two-dimensional graph, whose layout represents the topology of the space using a recursive relationship, and whose shading defines the shape of the cost surface defined on the space. Using this technique we present case-study explorations of three fitness functions: royal road, hierarchical-if-and-only-if (H-IFF), and hierarchically decomposable functions (HDF). The visualisation approach provides an insight into the properties of these functions, particularly with respect to the size and shape of the basins of attraction around each of the local optima.