Iron–dextran nanoparticles functionalized with T cell activating proteins have been used to study T cell receptor (TCR) signaling. However, nanoparticle triggering of membrane receptors is poorly understood and may be sensitive to physiologically regulated changes in TCR clustering that occur after T cell activation. Nano-aAPC bound 2-fold more TCR on activated T cells, which have clustered TCR, than on naive T cells, resulting in a lower threshold for activation. To enhance T cell activation, a magnetic field was used to drive aggregation of paramagnetic nano-aAPC, resulting in a doubling of TCR cluster size and increased T cell expansion in vitro and after adoptive transfer in vivo. T cells activated by nano-aAPC in a magnetic field inhibited growth of B16 melanoma, showing that this novel approach, using magnetic field-enhanced nano-aAPC stimulation, can generate large numbers of activated antigen-specific T cells and has clinically relevant applications for adoptive immunotherapy.

Harnessing the immune system to recognize and destroy tumor cells has been the central goal of anti-cancer immunotherapy. In recent years, there has been an increased interest in optimizing this technology in order to make it a clinically feasible treatment. One of the main treatment modalities within cancer immunotherapy has been adoptive T cell therapy (ACT). Using this approach, tumor-specific cytotoxic T cells are infused into cancer patients with the goal of recognizing, targeting, and destroying tumor cells. In the current review, we revisit some of the major successes of ACT, the major hurdles that have been overcome to optimize ACT, the remaining challenges, and future approaches to make ACT widely available.

Recent studies show gut microbiota modulate antitumor immune responses; one proposed mechanism is cross-reactivity between antigens expressed in commensal bacteria and neoepitopes. We found that T cells targeting an epitope called SVYRYYGL (SVY), expressed in the commensal bacterium Bifidobacterium breve ( B . breve ), cross-react with a model neoantigen, SIYRYYGL (SIY). Mice lacking B . breve had decreased SVY-reactive T cells compared with B . breve –colonized mice, and the T cell response was transferable by SVY immunization or by cohousing mice without Bifidobacterium with ones colonized with Bifidobacterium . Tumors expressing the model SIY neoantigen also grew faster in mice lacking B . breve compared with Bifidobacterium -colonized animals. B . breve colonization also shaped the SVY-reactive TCR repertoire. Finally, SVY-specific T cells recognized SIY-expressing melanomas in vivo and led to decreased tumor growth and extended survival. Our work demonstrates that commensal bacteria can stimulate antitumor immune responses via cross-reactivity and how bacterial antigens affect the T cell landscape.

Glycosylation is among the most complex posttranslational modifications with an extremely high level of diversity that has made it refractory to high-throughput analyses. Despite its resistance to high-throughput techniques, glycosylation is important in many critical cellular processes that necessitate a productive approach to their analysis. To facilitate studies in glycosylation, we developed a high-throughput lectin microarray for defining mammalian cell surface glycan signatures. Using the lectin microarray we established a binary analysis of cell binding and hierarchical organization of 24 mammalian cell lines. The array was also used to document changes in cell surface glycosylation during cell development and differentiation of primary murine immune system cells. To establish the biological and clinical importance of glycan signatures, the lectin microarray was applied in two systems. First, we analyzed the cell surface glycan signatures and were able to predict mannose-dependent tropism using a model pathogen. Second, we used the glycan signatures to identify novel lectin biomarkers for cancer stem-like cells in a murine model. Thus, lectin microarrays are an effective tool for analyzing diverse cell processes including cell development and differentiation, cell–cell communication, pathogen-host recognition, and cell surface biomarker identification.