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Lymph node (LN) stromal cell populations expand during the inflammation that accompanies T cell activation. Interleukin 17 (IL-17)-producing T helper (TH17) cells promote inflammation through induction of cytokines and chemokines in peripheral tissues. We demonstrate a critical requirement for IL-17 in the proliferation of lymph node (LN) and spleen stromal cells, particularly fibroblastic reticular cells (FRCs), during experimental autoimmune encephalomyelitis and colitis. Without IL-17 receptor signaling, activated FRCs underwent cell cycle arrest and ultimately apoptosis, accompanied by signs of nutrient stress in vivo. IL-17 signaling in FRCs was not required for TH17 cell development, but failed FRC proliferation impaired germinal center formation and antigen-specific antibody production. IL-17 induction of the transcriptional coactivator IκBζ mediated increased glucose uptake and mitochondrial Cpt1a expression. Hence, IL-17 produced by locally differentiating TH17 cells is an important driver of inflamed LN stromal cell activation, through metabolic reprogramming required to support proliferation and survival.

CD4 + T helper (Th) cells play central roles in immunity in health and disease. While much is known about the effector function of Th cells in combating pathogens and promoting autoimmune diseases, the roles and biology of memory CD4 + Th cells are complex and less well understood. In human autoimmune diseases such as multiple sclerosis (MS), there is a critical need to better understand the function and biology of memory T cells. In this review article we summarize current concepts in the field of CD4 + T cell memory, including natural history, developmental pathways, subsets, and functions. Furthermore, we discuss advancements in the field of the newly-described CD4 + tissue-resident memory T cells and of CD4 + memory T cells in autoimmune diseases, two major areas of important unresolved questions in need of answering to advance new vaccine design and development of novel treatments for CD4 + T cell-mediated autoimmune diseases.

Multiple Sclerosis (MS) is an autoimmune inflammatory disease of the central nervous system (CNS) which affects over 2.5 million people worldwide. Although MS has been extensively studied, many challenges still remain in regards to treatment, diagnosis, and prognosis. Typically, prognosis and individual responses to treatment are evaluated by clinical tests such the expanded disability status scale (EDSS), magnetic resonance imaging (MRI), and presence of oligoclonal bands (OCB) in the cerebrospinal fluid (CSF). However, none of these measures correlate strongly with treatment efficacy or disease progression across heterogeneous patient populations and subtypes of MS. Numerous studies over the past decades have attempted to identify sensitive and specific biomarkers for diagnosis, prognosis, and treatment efficacy of MS. The objective of this article is to review and discuss the current literature on body fluid biomarkers in MS, including research on potential biomarker candidates in the areas of microRNA, messenger RNA, lipids, and proteins.

We hypothesized that quantitative MS/MS-based proteomics at multiple time points, incorporating rapid microwave and magnetic (M2) sample preparation, could enable relative protein expression to be correlated to disease progression in the experimental autoimmune encephalomyelitis (EAE) animal model of multiple sclerosis. To test our hypothesis, microwave-assisted reduction/alkylation/digestion of proteins from brain tissue lysates bound to C8 magnetic beads and microwave-assisted isobaric chemical labeling were performed of released peptides, in 90 s prior to unbiased proteomic analysis. Disease progression in EAE was assessed by scoring clinical EAE disease severity and confirmed by histopathologic evaluation for central nervous system inflammation. Decoding the expression of 283 top-ranked proteins (p <0.05) at each time point relative to their expression at the peak of disease, from a total of 1191 proteins observed in four technical replicates, revealed a strong statistical correlation to EAE disease score, particularly for the following four proteins that closely mirror disease progression: 14-3-3ε (p = 3.4E-6); GPI (p = 2.1E-5); PLP1 (p = 8.0E-4); PRX1 (p = 1.7E-4). These results were confirmed by Western blotting, signaling pathway analysis, and hierarchical clustering of EAE risk groups. While validation in a larger cohort is underway, we conclude that M2 proteomics is a rapid method to quantify putative prognostic/predictive protein biomarkers and therapeutic targets of disease progression in the EAE animal model of multiple sclerosis.

Glioblastoma (GBM) remains an aggressive brain tumor with a high rate of mortality. Immune checkpoint (IC) molecules are expressed on tumor infiltrating lymphocytes (TILs) and promote T cell exhaustion upon binding to IC ligands expressed by the tumor cells. Interfering with IC pathways with immunotherapy has promoted reactivation of anti-tumor immunity and led to success in several malignancies. However, IC inhibitors have achieved limited success in GBM patients, suggesting that other checkpoint molecules may be involved with suppressing TIL responses. Numerous IC pathways have been described, with current testing of inhibitors underway in multiple clinical trials. Identification of the most promising checkpoint pathways may be useful to guide the future trials for GBM. Here, we analyzed the The Cancer Genome Atlas (TCGA) transcriptomic database and identified PD1 and TIGIT as top putative targets for GBM immunotherapy. Additionally, dual blockade of PD1 and TIGIT improved survival and augmented CD8+ TIL accumulation and functions in a murine GBM model compared with either single agent alone. Furthermore, we demonstrated that this combination immunotherapy affected granulocytic/polymorphonuclear (PMN) myeloid derived suppressor cells (MDSCs) but not monocytic (Mo) MDSCs in in our murine gliomas. Importantly, we showed that suppressive myeloid cells express PD1, PD-L1, and TIGIT-ligands in human GBM tissue, and demonstrated that antigen specific T cell proliferation that is inhibited by immunosuppressive myeloid cells can be restored by TIGIT/PD1 blockade. Our data provide new insights into mechanisms of GBM αPD1/αTIGIT immunotherapy.

We hypothesized that quantitative tandem mass spectrometry-based proteomics at multiple time points, incorporating immunoenrichment prior to rapid microwave and magnetic (IM2) sample preparation, might enable correlation of the relative expression of CD47 and other low abundance proteins to disease progression in the experimental autoimmune encephalomyelitis (EAE) animal model of multiple sclerosis. To test our hypothesis, anti-CD47 antibodies were used to enrich for low abundance CD47 prior to microwave and magnetic (M2) proteomics in EAE. Decoding protein expression at each time point, with CD47-immunoenriched samples and targeted proteomic analysis, enabled peptides from the low abundance proteins to be precisely quantified throughout disease progression, including: CD47: 86-99, corresponding to the “marker of self” overexpressed by myelin that prevents phagocytosis, or “cellular devouring”, by microglia and macrophages; MBP: 223-228, corresponding to myelin basic protein; and MIF: 79-87, corresponding to a proinflammatory cytokine that inhibits macrophage migration. While validation in a larger cohort is underway, we conclude that IM2 proteomics is a rapid method to precisely quantify peptides from CD47 and other low abundance proteins throughout disease progression in EAE. This is likely due to improvements in selectivity and sensitivity, necessary to partially overcome masking of low abundance proteins by high abundance proteins and improve dynamic range.

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