Lymphocyte Activation Gene-3 Regulates Dendritic Cell Metabolic Programing and T Cell Priming Function.

Deficiency of lymphocyte activation gene-3 (LAG3) is significantly associated with increased cardiovascular disease risk with in vitro results demonstrating increased TNF-α and decreased IL-10 secretion from LAG3-deficient human B lymphoblasts. The hypothesis tested in this study was that Lag3 deficiency in dendritic cells (DCs) would significantly affect cytokine expression, alter cellular metabolism, and prime naive T cells to greater effector differentiation. Experimental approaches used included differentiation of murine bone marrow-derived DCs (BMDCs) to measure secreted cytokines, cellular metabolism, RNA sequencing, whole cell proteomics, adoptive OT-II CD4+Lag3 +/+ donor cells into wild-type (WT) C57BL/6 and Lag3 -/- recipient mice, and ex vivo measurements of IFN-γ from cultured splenocytes. Results showed that Lag3 -/- BMDCs secreted more TNF-α, were more glycolytic, used fewer fatty acids for mitochondrial respiration, and glycolysis was significantly reduced by exogenous IL-10 treatment. Under basal conditions, RNA sequencing revealed increased expression of CD40 and CD86 and other cytokine-signaling targets as compared with WT. Whole cell proteomics identified a significant number of proteins up- and downregulated in Lag3 -/- BMDCs, with significant differences noted in exogenous IL-10 responsiveness compared with WT cells. Ex vivo, IFN-γ expression was significantly higher in Lag3 -/- mice as compared with WT. With in vivo adoptive T cell and in vitro BMDC:T coculture experiments, Lag3 -/- BMDCs showed greater T cell effector differentiation and proliferation, respectively, compared with WT BMDCs. In conclusion, Lag3 deficiency in DCs is associated with an inflammatory phenotype that provides a plausible mechanism for increased cardiovascular disease risk in humans with LAG3 deficiency.

Genomics-Driven Immunoproteomics: An Integrative Platform to Uncover Important Biomarkers for Human Diseases.

Genomics-driven immunoproteomics (GDI) is a platform that helps identify antigenic protein targets of mutations and other deoxyribonucleic acid (DNA) variations that are commonly associated with pathological states. This platform utilizes data generated from deep sequencing of exomic DNA or ribonucleic acid (RNA) as input to synthesize mutant peptides into microarrays, which then can be used to detect antigenic proteins that invoke immune response in patients. The technology has been used to detect antigenic targets of multiple sclerosis, an autoimmune disease [1], and cancer to identify mutant proteins that invoke immune response in breast cancer patients [2]. This technology has many potential applications to select genomic changes that are specifically recognized by the immune system in a rapid and efficient manner.