Distinct mechanisms govern populations of myeloid-derived suppressor cells in chronic viral infection and cancer

Myeloid-derived suppressor cells (MDSCs) are major negative regulators of immune responses in cancer and chronic infections. It remains unclear if regulation of MDSC activity in different conditions is controlled by similar mechanisms. We compared MDSCs in mice with cancer and lymphocytic choriomeningitis virus (LCMV) infection. Chronic LCMV infection caused the development of monocytic MDSCs (M-MDSCs) but did not induce polymorphonuclear MDSCs (PMN-MDSCs). In contrast, both MDSC populations were present in cancer models. An acquisition of immune-suppressive activity by PMN-MDSCs in cancer was controlled by IRE1α and ATF6 pathways of the endoplasmic reticulum (ER) stress response. Abrogation of PMN-MDSC activity by blockade of the ER stress response resulted in an increase in tumor-specific immune response and reduced tumor progression. In contrast, the ER stress response was dispensable for suppressive activity of M-MDSCs in cancer and LCMV infection. Acquisition of immune-suppressive activity by M-MDSCs in spleens was mediated by IFN-γ signaling. However, it was dispensable for suppressive activity of M-MDSCs in tumor tissues. Suppressive activity of M-MDSCs in tumors was retained due to the effect of IL-6 present at high concentrations in the tumor site. These results demonstrate disease- and population-specific mechanisms of MDSC accumulation and the need for targeting different pathways to achieve inactivation of these cells.

Protein structural topology: Automated analysis and diagrammatic representation

The topology of a protein structure is a highly simplified description of its fold including only the sequence of secondary structure elements, and their relative spatial positions and approximate orientations. This information can be embodied in a two-dimensional diagram of protein topology, called a TOPS cartoon. These cartoons are useful for the understanding of particular folds and making comparisons between folds. Here we describe a new algorithm for the production of TOPS cartoons, which is more robust than those previously available, and has a much higher success rate. This algorithm has been used to produce a database of protein topology cartoons that covers most of the data bank of known protein structures.