Myeloid cells as potential targets for immunotherapy in pediatric gliomas

Pediatric high-grade glioma (pHGG) including pediatric glioblastoma (pGBM) are highly aggressive pediatric central nervous system (CNS) malignancies. pGBM comprises approximately 3% of all pediatric CNS malignancies and has a 5-year survival rate of approximately 20%. Surgical resection and chemoradiation are often the standard of care for pGBM and pHGG, however, even with these interventions, survival for children diagnosed with pGBM and pHGG remains poor. Due to shortcomings associated with the standard of care, many efforts have been made to create novel immunotherapeutic approaches targeted to these malignancies. These efforts include the use of vaccines, cell-based therapies, and immune-checkpoint inhibitors. However, it is believed that in many pediatric glioma patients an immunosuppressive tumor microenvironment (TME) possess barriers that limit the efficacy of immune-based therapies. One of these barriers includes the presence of immunosuppressive myeloid cells. In this review we will discuss the various types of myeloid cells present in the glioma TME, including macrophages and microglia, myeloid-derived suppressor cells, and dendritic cells, as well as the specific mechanisms these cells can employ to enable immunosuppression. Finally, we will highlight therapeutic strategies targeted to these cells that are aimed at impeding myeloid-cell derived immunosuppression.

ImmunoPET imaging of TIGIT in the glioma microenvironment

Glioblastoma (GBM) is the most common primary malignant brain tumor. Currently, there are few effective treatment options for GBM beyond surgery and chemo-radiation, and even with these interventions, median patient survival remains poor. While immune checkpoint inhibitors (ICIs) have demonstrated therapeutic efficacy against non-central nervous system cancers, ICI trials for GBM have typically had poor outcomes. TIGIT is an immune checkpoint receptor that is expressed on activated T-cells and has a role in the suppression of T-cell and Natural Killer (NK) cell function. As TIGIT expression is reported as both prognostic and a biomarker for anti-TIGIT therapy, we constructed a molecular imaging agent, [89Zr]Zr-DFO-anti-TIGIT (89Zr-αTIGIT), to visualize TIGIT in preclinical GBM by immunoPET imaging. PET imaging and biodistribution analysis of 89Zr-αTIGIT demonstrated uptake in the tumor microenvironment of GBM-bearing mice. Blocking antibody and irrelevant antibody tracer studies demonstrated specificity of 89Zr-αTIGIT with significance at a late time point post-tracer injection. However, the magnitude of 89Zr-αTIGIT uptake in tumor, relative to the IgG tracer was minimal. These findings highlight the features and limitations of using 89Zr-αTIGIT to visualize TIGIT in the GBM microenvironment.

Glioblastoma vaccines: past, present, and opportunities

Glioblastoma (GBM) is one of the most lethal central nervous systems (CNS) tumours in adults. As supplements to standard of care (SOC), various immunotherapies improve the therapeutic effect in other cancers. Among them, tumour vaccines can serve as complementary monotherapy or boost the clinical efficacy with other immunotherapies, such as immune checkpoint blockade (ICB) and chimeric antigen receptor T cells (CAR-T) therapy. Previous studies in GBM therapeutic vaccines have suggested that few neoantigens could be targeted in GBM due to low mutation burden, and single-peptide therapeutic vaccination had limited efficacy in tumour control as monotherapy. Combining diverse antigens, including neoantigens, tumour-associated antigens (TAAs), and pathogen-derived antigens, and optimizing vaccine design or vaccination strategy may help with clinical efficacy improvement. In this review, we discussed current GBM therapeutic vaccine platforms, evaluated and potential antigenic targets, current challenges, and perspective opportunities for efficacy improvement.

Immuno-PET Imaging of CD69 Visualizes T-Cell Activation and Predicts Survival Following Immunotherapy in Murine Glioblastoma

Glioblastoma (GBM) is the most common and malignant primary brain tumor in adults. Immunotherapy may be promising for the treatment of some patients with GBM; however, there is a need for noninvasive neuroimaging techniques to predict immunotherapeutic responses. The effectiveness of most immunotherapeutic strategies requires T-cell activation. Therefore, we aimed to evaluate an early marker of T-cell activation, CD69, for its use as an imaging biomarker of response to immunotherapy for GBM. Herein, we performed CD69 immunostaining on human and mouse T cells following in vitro activation and post immune checkpoint inhibitors (ICI) in an orthotopic syngeneic mouse glioma model. CD69 expression on tumor-infiltrating leukocytes was assessed using single-cell RNA sequencing (scRNA-seq) data from patients with recurrent GBM receiving ICI. Radiolabeled CD69 Ab PET/CT imaging (CD69 immuno-PET) was performed on GBM-bearing mice longitudinally to quantify CD69 and its association with survival following immunotherapy. We show CD69 expression is upregulated upon T-cell activation and on tumor-infiltrating lymphocytes (TIL) in response to immunotherapy. Similarly, scRNA-seq data demonstrated elevated CD69 on TILs from patients with ICI-treated recurrent GBM as compared with TILs from control cohorts. CD69 immuno-PET studies showed a significantly higher tracer uptake in the tumors of ICI-treated mice compared with controls. Importantly, we observed a positive correlation between survival and CD69 immuno-PET signals in immunotherapy-treated animals and established a trajectory of T-cell activation by virtue of CD69-immuno-PET measurements. Our study supports the potential use of CD69 immuno-PET as an immunotherapy response assessment imaging tool for patients with GBM.

Significance

Immunotherapy may hold promise for the treatment of some patients with GBM. There is a need to assess therapy responsiveness to allow the continuation of effective treatment in responders and to avoid ineffective treatment with potential adverse effects in the nonresponders. We demonstrate that noninvasive PET/CT imaging of CD69 may allow early detection of immunotherapy responsiveness in patients with GBM.

New Insights on DR and DQ Human Leukocyte Antigens in Anti-LGI1 Encephalitis

BACKGROUND AND OBJECTIVES

To explore the clinical characteristics and HLA associations of patients with anti-leucine-rich glioma-inactivated 1 encephalitis (LGI1E) from a large single center in Israel. Anti-LGI1E is the most commonly diagnosed antibody-associated encephalitic syndrome in adults. Recent studies of various populations reveal significant associations with specific HLA genes. We examined the clinical characteristics and HLA associations of a cohort of Israeli patients.

METHODS

Seventeen consecutive patients with anti-LGI1E diagnosed at Tel Aviv Medical Center between the years 2011 and 2018 were included. HLA typing was performed using next-generation sequencing at the tissue typing laboratory of Sheba Medical Center and compared with data from the Ezer Mizion Bone Marrow Donor Registry, containing over 1,000,000 samples.

RESULTS

Our cohort displayed a male predominance and median age at onset in the 7th decade, as previously reported. The most common presenting symptom was seizures. Notably, paroxysmal dizziness spells were significantly more common than previously reported (35%), whereas faciobrachial dystonic seizures were found only in 23%. HLA analysis revealed overrepresentation of DRB1*07:01 (OR: 3.18, CI: 20.9 p < 1.e-5) and DRB1*04:02 (OR: 3.8, CI: 20.1 p < 1.e-5), as well as of the DQ allele DQB1*02:02 (OR: 2.8, CI: 14.2 p < 0.0001) as previously reported. A novel overrepresentation observed among our patients was of the DQB1*03:02 allele (OR: 2.3, CI: 6.9 p < 0.008). In addition, we found DR-DQ associations, among patients with anti-LGI1E, that showed complete or near-complete linkage disequilibrium (LD). By applying LD analysis to an unprecedentedly large control cohort, we were able to show that although in the general population, DQB*03:02 is not fully associated with DRB1*04:02, in the patient population, both alleles are always coupled, suggesting the DRB1*04:02 association to be primary to disease predisposition. In silico predictions performed for the overrepresented DQ alleles reveal them to be strong binders of LGI1-derived peptides, similarly to overrepresented DR alleles. These predictions suggest a possible correlation between peptide binding sites of paired DR-DQ alleles.

DISCUSSION

Our cohort presents distinct immune characteristics with substantially higher overrepresentation of DRB1*04:02 and slightly lower overrepresentation of DQB1*07:01 compared with previous reports implying differences between different populations. DQ-DR interactions found in our cohort may shed additional light on the complex role of immunogenetics in the pathogenesis of anti-LGI1E, implying a possible relevance of certain DQ alleles and DR-DQ interactions.

NIMG-58. IMMUNOPET OF 89ZR-DFO-CD69 AB VISUALIZES T-CELL ACTIVATION AND PREDICTS SURVIVAL FOLLOWING IMMUNOTHERAPY IN MURINE GBM MODEL

INTRODUCTION

Glioblastoma (GBM) is the most malignant brain tumor in adults, with a dismal prognosis despite aggressive therapy. Immunotherapy is currently being evaluated as a treatment modality for recurrent GBM. MRI is not adequate for response assessment to immunotherapy even after using refined response assessment criteria. Thus, there is a need for the development of neuroimaging techniques for response assessment. T-cells are key mediators of cancer immunotherapy responses and upregulation of CD69 is a marker of T-cell activation. Our aim is to use PET/CT imaging to non-invasively quantify CD69 in vivo, following immunotherapy, and correlate the expression to survival.

METHODS

CD69 was evaluated by flow cytometry and immunofluorescence staining on human and mouse in vitro activated T-cells and on dissociated tumors from GL261 glioma-bearing mice treated with anti-PD1/anti-CTLA4 immunotherapy (ICI). Single-cell RNA sequencing (ScRNAseq) datasets from recurrent GBM patients receiving (n=20) or not receiving (n=22) ICI were examined for CD69 expression on tumor infiltrating lymphocyte (TIL) populations. PET/CT was performed on mice (n=30) receiving radiolabeled anti-CD69 antibody (89Zr-DFO-anti-CD69) to evaluate response to ICI therapy. Standard uptake values (SUV) were compared between ICI and controls and in relationship to survival.

RESULTS

We confirmed CD69 upregulation upon T-cell activation in vitro. Ex vivo, CD69 expression significantly increased on TILs early after ICI treatment compared to control (63.46% vs 24.37% CD69+/TILs, respectively; p=0.017). ScRNAseq demonstrated significant elevated CD69 expression in almost all TIL populations tested in recurrent GBM patients treated with ICI compared with a control group. ImmunoPET demonstrated significantly higher anti-CD69 tracer uptake in ICI-treated mice compared with controls. Most importantly, we observed a strong positive correlation between survival and immunoPET SUV (r=0.9425, p=0.016) in the ICI-treatment group, but not within the control group.

CONCLUSIONS

Our study demonstrates the potential incorporation of CD69 ImmunoPET as response assessment to ICI for GBM patients.

Endogenous Interleukin-17a Contributes to Normal Spatial Memory Retention but Does Not Affect Early Behavioral or Neuropathological Outcomes after Experimental Traumatic Brain Injury

Interleukin-17 (IL-17) is a proinflammatory cytokine primarily secreted in the brain by inflammatory T lymphocytes and glial cells. IL-17+ T-helper (Th17) cells are increased in the ipsilateral hemisphere after experimental traumatic brain injury (TBI), and IL-17 levels are increased in serum and brain tissue. We hypothesized that il17a and related gene expression would be increased in brain tissue after TBI in mice and il17a-/- mice would demonstrate neuroprotection versus wild type. The controlled cortical impact (CCI) model of TBI in adult male C57BL6/J mice was used for all experiments. Data were analyzed by analysis of variance (ANOVA) or repeated-measures two-way ANOVA with the Bonferroni correction. A value of p < 0.05 determined significance. Expression of il17a was significantly reduced in the ipsilateral cortex and hippocampus by day 3 after TBI, and expression remained low at 28 days. There were no differences between il17a-/- and il17a+/+ mice in beam balance, Morris water maze performance, or lesion volume after CCI. Surprisingly, naïve il17a -/- mice performed significantly (p = 0.02) worse than naïve il17a+/+ mice on the probe trial. In conclusion, sustained depression of il17a gene expression was observed in brains after TBI in adult mice. Genetic knockout of IL-17 was not neuroprotective after TBI. IL-17a may be important for memory retention in naïve mice.

Immunoregulation via Cell Density and Quorum Sensing-like Mechanisms: An Underexplored Emerging Field with Potential Translational Implications

Quorum sensing (QS) was historically described as a mechanism by which bacteria detect and optimize their population density via gene regulation based on dynamic environmental cues. Recently, it was proposed that QS or similar mechanisms may have broader applications across different species and cell types. Indeed, emerging evidence shows that the mammalian immune system can also elicit coordinated responses on a population level to regulate cell density and function, thus suggesting that QS-like mechanisms may also be a beneficial trait of the immune system. In this review, we explore and discuss potential QS-like mechanisms deployed by the immune system to coordinate cellular-level responses, such as T cell responses mediated via the common gamma chain (γc) receptor cytokines and the aryl hydrocarbon receptors (AhRs). We present evidence regarding a novel role of QS as a multifunctional mechanism coordinating CD4⁺ and CD8⁺ T cell behavior during steady state and in response to infection, inflammatory diseases, and cancer. Successful clinical therapies such as adoptive cell transfer for cancer treatment may be re-evaluated to harness the effects of the QS mechanism(s) and enhance treatment responsiveness. Moreover, we discuss how signaling threshold perturbations through QS-like mediators may result in disturbances of the complex crosstalk between immune cell populations, undesired T cell responses, and induction of autoimmune pathology. Finally, we discuss the potential therapeutic role of modulating immune-system-related QS as a promising avenue to treat human diseases.

IMMU-06. Landscape of adaptive immunity of childhood brain cancers

T lymphocytes have a unique ability to recognize a vast array of antigens prompted by an enormous T cell receptor (TCR) repertoire. Characterization of tumor-infiltrating T cells (TILs) is key to understand MHC-restricted anti-tumor immunity and for developing T cell-centered immunotherapies such as adoptive cell therapy and tumor vaccines. In the current work, we investigated RNA-Seq data from 997 pediatric brain tumor patients and performed a large-scale comprehensive examination of the immunogenomic and TCR landscape of TILs across the entire spectrum of pediatric brain tumors. We show that the relative ratio between T cell diversity (clonality) and T cell abundance within each sample, represented by the clonal expansion index (CEI), is a strong predictor of prognosis both within and between tumor types. Interestingly, we show that CEI was strongly associated with molecular subgroups of medulloblastoma but not with known tumor-genomic features of these subgroups. Investigation of TCR clones recognizing a common recurrent tumor-antigen across patients based on CDR3 homology and characteristics, reveals 9 TCR clusters which are tumor type restricted with defined prognoses and HLA dominance. Using computational immunogenomics and machine learning-based investigations of these clusters yielded novel putative HLA-restricted tumor antigens which could bind and activate the clusters’ specific TCRs. Importantly, our framework grounded the foundations for developing a precision medicine approach of T cell-centered immunotherapies. These findings have major implications for understanding the interplay between T cell and tumor genomic, and for developing new immunotherapies for children with brain tumors.

Tim-3 mediates T cell trogocytosis to limit antitumor immunity

T cell immunoglobulin mucin domain-containing protein 3 (Tim-3) negatively regulates innate and adaptive immunity in cancer. To identify the mechanisms of Tim-3 in cancer immunity, we evaluated the effects of Tim-3 blockade in human and mouse melanoma. Here, we show that human programmed cell death 1-positive (PD-1+) Tim-3+CD8+ tumor-infiltrating lymphocytes (TILs) upregulate phosphatidylserine (PS), a receptor for Tim-3, and acquire cell surface myeloid markers from antigen-presenting cells (APCs) through transfer of membrane fragments called trogocytosis. Tim-3 blockade acted on Tim-3+ APCs in a PS-dependent fashion to disrupt the trogocytosis of activated tumor antigen-specific CD8+ T cells and PD-1+Tim-3+ CD8+ TILs isolated from patients with melanoma. Tim-3 and PD-1 blockades cooperated to disrupt trogocytosis of CD8+ TILs in 2 melanoma mouse models, decreasing tumor burden and prolonging survival. Deleting Tim-3 in dendritic cells but not in CD8+ T cells impeded the trogocytosis of CD8+ TILs in vivo. Trogocytosed CD8+ T cells presented tumor peptide-major histocompatibility complexes and became the target of fratricide T cell killing, which was reversed by Tim-3 blockade. Our findings have uncovered a mechanism Tim-3 uses to limit antitumor immunity.

Novel theranostic agent for PET imaging and targeted radiopharmaceutical therapy of tumour-infiltrating immune cells in glioma

BACKGROUND

Malignant gliomas are deadly tumours with few therapeutic options. Although immunotherapy may be a promising therapeutic strategy for treating gliomas, a significant barrier is the CD11b+ tumour-associated myeloid cells (TAMCs), a heterogeneous glioma infiltrate comprising up to 40% of a glioma's cellular mass that inhibits anti-tumour T-cell function and promotes tumour progression. A theranostic approach uses a single molecule for targeted radiopharmaceutical therapy (TRT) and diagnostic imaging; however, there are few reports of theranostics targeting the tumour microenvironment.

METHODS

Utilizing a newly developed bifunctional chelator, Lumi804, an anti-CD11b antibody (αCD11b) was readily labelled with either Zr-89 or Lu-177, yielding functional radiolabelled conjugates for PET, SPECT, and TRT.

FINDINGS

89Zr/177Lu-labeled Lumi804-αCD11b enabled non-invasive imaging of TAMCs in murine gliomas. Additionally, 177Lu-Lumi804-αCD11b treatment reduced TAMC populations in the spleen and tumour and improved the efficacy of checkpoint immunotherapy.

INTERPRETATION

89Zr- and 177Lu-labeled Lumi804-αCD11b may be a promising theranostic pair for monitoring and reducing TAMCs in gliomas to improve immunotherapy responses.

FUNDING

A full list of funding bodies that contributed to this study can be found in the Acknowledgements section.

TIGIT and PD-1 Immune Checkpoint Pathways Are Associated With Patient Outcome and Anti-Tumor Immunity in Glioblastoma

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.

Genomic, proteomic, and systems biology approaches in biomarker discovery for multiple sclerosis

Multiple sclerosis (MS) is a neuroinflammatory disorder characterized by autoimmune-mediated inflammatory lesions in CNS leading to myelin damage and axonal loss. MS is a heterogenous disease with variable and unpredictable disease course. Due to its complex nature, MS is difficult to diagnose and responses to specific treatments may vary between individuals. Therefore, there is an indisputable need for biomarkers for early diagnosis, prediction of disease exacerbations, monitoring the progression of disease, and for measuring responses to therapy. Genomic and proteomic studies have sought to understand the molecular basis of MS and find biomarker candidates. Advances in next-generation sequencing and mass-spectrometry techniques have yielded an unprecedented amount of genomic and proteomic data; yet, translation of the results into the clinic has been underwhelming. This has prompted the development of novel data science techniques for exploring these large datasets to identify biologically relevant relationships and ultimately point towards useful biomarkers. Herein we discuss optimization of omics study designs, advances in the generation of omics data, and systems biology approaches aimed at improving biomarker discovery and translation to the clinic for MS.

Noncanonical STAT3 activity sustains pathogenic Th17 proliferation and cytokine response to antigen

The STAT3 signaling pathway is required for early Th17 cell development, and therapies targeting this pathway are used for autoimmune disease. However, the role of STAT3 in maintaining inflammatory effector Th17 cell function has been unexplored. Th17ΔSTAT3 mice, which delete STAT3 in effector Th17 cells, were resistant to experimental autoimmune encephalomyelitis (EAE), a murine model of MS. Th17 cell numbers declined after STAT3 deletion, corresponding to reduced cell cycle. Th17ΔSTAT3 cells had increased IL-6-mediated phosphorylation of STAT1, known to have antiproliferative functions. Th17ΔSTAT3 cells also had reduced mitochondrial membrane potential, which can regulate intracellular Ca2+. Accordingly, Th17ΔSTAT3 cells had reduced production of proinflammatory cytokines when stimulated with myelin antigen but normal production of cytokines when TCR-induced Ca2+ flux was bypassed with ionomycin. Thus, early transcriptional roles of STAT3 in developing Th17 cells are later complimented by noncanonical STAT3 functions that sustain pathogenic Th17 cell proliferation and cytokine production.

TNFR2 limits proinflammatory astrocyte functions during EAE induced by pathogenic DR2b-restricted T cells

Multiple sclerosis (MS) is an autoimmune neuroinflammatory disease where the underlying mechanisms driving disease progression have remained unresolved. HLA-DR2b (DRB1*15:01) is the most common genetic risk factor for MS. Additionally, TNF and its receptors TNFR1 and TNFR2 play key roles in MS and its preclinical animal model, experimental autoimmune encephalomyelitis (EAE). TNFR2 is believed to ameliorate CNS pathology by promoting remyelination and Treg function. Here, we show that transgenic mice expressing the human MHC class II (MHC-II) allele HLA-DR2b and lacking mouse MHC-II and TNFR2 molecules, herein called DR2bΔR2, developed progressive EAE, while disease was not progressive in DR2b littermates. Mechanistically, expression of the HLA-DR2b favored Th17 cell development, whereas T cell-independent TNFR2 expression was critical for restraining of an astrogliosis-induced proinflammatory milieu and Th17 cell responses, while promoting remyelination. Our data suggest the TNFR2 signaling pathway as a potentially novel mechanism for curtailing astrogliosis and promoting remyelination, thus providing new insights into mechanisms limiting progressive MS.

The Alzheimer's Disease-Associated Protein BACE1 Modulates T Cell Activation and Th17 Function

β-site amyloid precursor protein-cleaving enzyme 1 (BACE1) is best known for its role in Alzheimer's disease amyloid plaque formation but also contributes to neurodegenerative processes triggered by CNS injury. In this article, we report that BACE1 is expressed in murine CD4⁺ T cells and regulates signaling through the TCR. BACE1-deficient T cells have reduced IL-17A expression under Th17 conditions and reduced CD73 expression in Th17 and inducible T regulatory cells. However, induction of the Th17 and T regulatory transcription factors RORγt and Foxp3 was unaffected. BACE1-deficient T cells showed impaired pathogenic function in experimental autoimmune encephalomyelitis. These data identify BACE1 as a novel regulator of T cell signaling pathways that impact autoimmune inflammatory T cell function.

IL-17 metabolically reprograms activated fibroblastic reticular cells for proliferation and survival

Lymph-node (LN) stromal cell populations expand during the inflammation that accompanies T cell activation. Interleukin-17 (IL-17)-producing helper T cells (T_H17 cells) promote inflammation through the induction of cytokines and chemokines in peripheral tissues. We demonstrate a critical requirement for IL-17 in the proliferation of LN and splenic stromal cells, particularly fibroblastic reticular cells (FRCs), during experimental autoimmune encephalomyelitis and colitis. Without signaling via the IL-17 receptor, activated FRCs underwent cell cycle arrest and apoptosis, accompanied by signs of nutrient stress in vivo. IL-17 signaling in FRCs was not required for the development of T_H17 cells, but failed FRC proliferation impaired germinal center formation and antigen-specific antibody production. Induction of the transcriptional co-activator IκBζ via IL-17 signaling mediated increased glucose uptake and expression of the gene Cpt1a, encoding CPT1A, a rate-limiting enzyme of mitochondrial fatty acid oxidation. Hence, IL-17 produced by locally differentiating T_H17 cells is an important driver of the activation of inflamed LN stromal cells, through metabolic reprogramming required to support proliferation and survival.

Aire is not essential for regulating neuroinflammatory disease in mice transgenic for human autoimmune-diseases associated MHC class II genes HLA-DR2b and HLA-DR4

The human autoimmune disease-associated HLA alleles HLA-DR2b (DRB1*1501) and HLA-DR4 (DRB1*0401) are strongly linked to increased susceptibility for multiple sclerosis (MS) and rheumatoid arthritis (RA), respectively. The underlying mechanisms are not fully understood, but these MHC alleles may shape the repertoire of pathogenic T cells via central tolerance. The transcription factor autoimmune regulator (AIRE) promotes central T cell tolerance via ectopic expression of tissue-specific antigens (TSAs). Aire deficiency in humans causes autoimmune polyendocrinopathy syndrome type 1 (APS1), and Aire knockout mice (Aire-/-) develop spontaneous autoimmune pathology characterized by multi-organ lymphocytic infiltrates. Here, we asked whether impaired TSAs gene expression in the absence of Aire promoted spontaneous MS- or RA-like autoimmune pathology in the context of human HLA alleles in HLA-DR2b or HLA-DR4 transgenic (tg) mice. The results show that reduced TSAs gene expression in the thymus of Aire-deficient HLA-DR2b or HLA-DR4 tg mice corresponded to mild spontaneous inflammatory infiltrates in salivary glands, liver, and pancreas. Moreover, Aire-deficiency modestly enhanced experimental autoimmune encephalomyelitis (EAE) in HLA-DR tg mice, but the animals did not show signs of spontaneous neuroinflammation or arthritis. No significant changes were observed in CD4+ T cell numbers, T cell receptor (TCR) distribution, regulatory T cells (Treg), or antigen-induced cytokine production. Abrogating Treg function by treatment with anti-CTLA-4 or anti-CD25 mAb in Aire-deficient HLA-DR tg mice did not trigger EAE or other autoimmune pathology. Our results suggest a redundant role for Aire in maintaining immune tolerance in the context of autoimmune disease-associated human HLA alleles.

Tumor necrosis factor receptor 2 promotes neuroprotection during chronic autoimmune neuroinflammation

Multiple sclerosis (MS) is an inflammatory autoimmune disorder affecting the central nervous system (CNS) which affects over 400,000 Americans and over 2.5 million people worldwide. Although most patients are initially diagnosed with relapsing-remitting MS, the majority of these patients later develop a chronic-progressive form of MS, for which there is no well-established mouse model. The most common genetic factor associated with MS susceptibility is the Human Leukocyte Antigen (HLA)-DR2b haplotype. Additionally, studies in the experimental autoimmune encephalomyelitis (EAE) mouse model of MS, showed that lack of TNF signaling through its receptor TNFR2 leads to disease exacerbation and severe demyelination. Here, we developed a mouse model which expresses HLA-DR2b and lacks TNFR2, designated DR2bΔR2. Strikingly, DR2bΔR2 mice develop progressive EAE with pathology and clinical features observed in progressive MS patients. Adoptive transfer studies revealed that the clinical phenotype of EAE in DR2bΔR2 mice are largely dependent on TNFR2 expression in the CNS. Subsequently, we showed that DR2bΔR2 mice have a significant increase of lesions in the cerebellum, associated with reduced of oligodendrocyte progenitor cells (OPC) recruitment or function. Moreover, we showed that DR2bΔR2 mice are presented with chronic astrogliosis in demyelinating lesions. Our studies provide key insights into CNS repair and regulatory mechanisms controlled by TNFR2 during neuroinflammation and provide novel therapeutic strategies for treating progressive MS.

Differential expression of CNS-specific proteins in progressive EAE point to potential biomarkers for progressive MS

The lack of reliable markers for assessing the progression of multiple sclerosis (MS) from the relapsing-remitting to the secondary progressive form hinders the ability for therapeutic intervention and results in continued physiological deterioration. To begin to address the urgent need for biomarkers of progressive MS we investigated proteome changes over the disease course of progressive experimental autoimmune encephalomyelitis (EAE) in NOD mice as a preclinical model of the disease using a high-throughput quantitative proteomic technique pioneered in our lab. In this study, we utilized this established proteomic technique as well as bioinformatics tools to prioritize key proteins whose expression level in the CNS correlated specifically with the progressive phase of disease in the NOD EAE model. Hierarchical clustering of timepoints indicate that samples cluster based on progression of disease. Specifically, late time points cluster separately from naïve and peak time points. Importantly, statistical testing identified proteins with differential expression in the CNS of mice across the time course of NOD EAE, several of which are CNS specific. We are seeking to detect corollary changes in these CNS-specific proteins in the serum, pointing to a minimally invasive means of monitoring disease progress and measuring drug efficacy. Our studies will provide proof-of-concept for identifying homologous human biomarkers to guide treatment in individual patients. Furthermore, our results may provide insights into mechanisms that contribute to disease pathology and offer additional therapeutic targets for slowing the progression of MS.

STAT3 regulation of effector Th17 cells and its implications for treatment of autoimmunity

Th17 cells are implicated in the pathogenesis of many autoimmune and inflammatory diseases, including multiple sclerosis (MS) and rheumatoid arthritis. Early Th17 cell development relies on key cytokines that signal through STAT3, including IL-6, IL-21 and IL-23. These signals are critical for gain of effector Th17 cell functions, including the expression of the inflammatory cytokines IL-17, IFN-γ and GM-CSF. Thus, development of drugs that target STAT3 signaling are a major research focus to alleviate disease. However, the functions of STAT3 signaling post Th17 cell development in late effector cells remain elusive. Here, we developed a model to study STAT3 deficiency effects specifically in late effector Th17 cells, termed Th17ΔSTAT3. We show that Th17ΔSTAT3 mice are resistant to development of experimental autoimmune encephalomyelitis (EAE), an animal model of MS. To determine mechanisms by which STAT3 regulates Th17 cell pathogenicity we performed bioinformatics analysis of effector Th17 cell transcriptome. Corresponding to changes in gene expression, we found that Th17ΔSTAT3 cells were reduced in numbers in lymph nodes and CNS during EAE. We demonstrated that STAT3 is critical to drive G1 to S phase transition of the cell cycle by regulating key cell cycle genes. Moreover, we found that STAT3 maintains Th17 cell mitochondrial integrity. Unexpectedly, our data show that lineage specific gene expression, including cytokines, is not altered in Th17ΔSTAT3 cells. However, Th17ΔSTAT3 cells have reduced IL-17 expression, but not IFN-γ or GM-CSF upon antigen restimulation. Our data reveal hitherto unknown mechanisms for STAT3 in regulating effector Th17 cells, which have major implications for use of Th17 cell-targeted therapies.

Serum Neuroinflammatory Disease-Induced Central Nervous System Proteins Predict Clinical Onset of Experimental Autoimmune Encephalomyelitis

There is an urgent need in multiple sclerosis (MS) patients to develop biomarkers and laboratory tests to improve early diagnosis, predict clinical relapses, and optimize treatment responses. In healthy individuals, the transport of proteins across the blood–brain barrier (BBB) is tightly regulated, whereas, in MS, central nervous system (CNS) inflammation results in damage to neuronal tissues, disruption of BBB integrity, and potential release of neuroinflammatory disease-induced CNS proteins (NDICPs) into CSF and serum. Therefore, changes in serum NDICP abundance could serve as biomarkers of MS. Here, we sought to determine if changes in serum NDICPs are detectable prior to clinical onset of experimental autoimmune encephalomyelitis (EAE) and, therefore, enable prediction of disease onset. Importantly, we show in longitudinal serum specimens from individual mice with EAE that pre-onset expression waves of synapsin-2, glutamine synthetase, enolase-2, and synaptotagmin-1 enable the prediction of clinical disease with high sensitivity and specificity. Moreover, we observed differences in serum NDICPs between active and passive immunization in EAE, suggesting hitherto not appreciated differences for disease induction mechanisms. Our studies provide the first evidence for enabling the prediction of clinical disease using serum NDICPs. The results provide proof-of-concept for the development of high-confidence serum NDICP expression waves and protein biomarker candidates for MS.

Early response index: a statistic to discover potential early stage disease biomarkers

Background

Identifying disease correlated features early before large number of molecules are impacted by disease progression with significant abundance change is very advantageous to biologists for developing early disease diagnosis biomarkers. Disease correlated features have relatively low level of abundance change at early stages. Finding them using existing bioinformatic tools in high throughput data is a challenging task since the technology suffers from limited dynamic range and significant noise. Most existing biomarker discovery algorithms can only detect molecules with high abundance changes, frequently missing early disease diagnostic markers.

Results

We present a new statistic called early response index (ERI) to prioritize disease correlated molecules as potential early biomarkers. Instead of classification accuracy, ERI measures the average classification accuracy improvement attainable by a feature when it is united with other counterparts for classification. ERI is more sensitive to abundance changes than other ranking statistics. We have shown that ERI significantly outperforms SAM and Localfdr in detecting early responding molecules in a proteomics study of a mouse model of multiple sclerosis. Importantly, ERI was able to detect many disease relevant proteins before those algorithms detect them at a later time point.

Conclusions

ERI method is more sensitive for significant feature detection during early stage of disease development. It potentially has a higher specificity for biomarker discovery, and can be used to identify critical time frame for disease intervention.

Electronic supplementary material

The online version of this article (doi:10.1186/s12859-017-1712-y) contains supplementary material, which is available to authorized users.

A serum CNS-specific protein fingerprint predictive of clinical relapses and disease development of multiple sclerosis

There is a critical need in MS to develop biomarkers to improve early diagnosis, predict imminent disease relapses, and optimize treatment responses. In MS, central nervous system (CNS) inflammation results in damage to neuronal tissues and disruption of blood-brain barrier integrity, and ultimately to leakage of CNS-specific proteins (CSPs) into serum. Therefore, altered serum levels of CSPs could be promising biomarkers of MS. Based on our previous discovery of CSP expression waves in brain tissue of mice with experimental autoimmune encephalomyelitis (EAE), a preclinical model for human MS, we investigated a subset of CSPs which have human-homologs in longitudinal serum specimens from individual mice in this model. Herein, we establish a pre-onset serum CSP expression wave that enabled prediction of clinical onset of EAE and stratification of subjects into diseased versus healthy. Importantly, we demonstrate that the pre-onset serum CSP wave was not affected by adjuvants and microbial infection, thereby has high sensitivity and specificity for a neuroinflammatory disease. Moreover, we identify differences in serum protein expression between active and passive immunization of EAE revealing hitherto not appreciated differences for disease induction mechanisms. The results provide proof of concept for the development serum CSP waves as biomarkers of MS, specifically for early detection and prediction of the onset of clinical relapse.

Identification of CNS-specific biomarkers for monitoring the progression of multiple sclerosis

There are currently no reliable methods for assessing the progression of multiple sclerosis (MS) from the relapsing-remitting to the secondary progressive form. This gap in knowledge hinders the ability for therapeutic intervention and results in continued relapses and physiological deterioration. To begin to address the urgent need for biomarkers of progressive MS we investigated proteome changes over the disease course of progressive experimental autoimmune encephalomyelitis (EAE) in NOD mice as a preclinical model of the disease. Our lab has pioneered a high-throughput quantitative proteomic technique, which we have previously used to quantify expression levels of central nervous system (CNS) proteins over the course of monophasic EAE in C57BL/6 mice, producing a predictive protein biomarker fingerprint for clinical relapses. In this study, we utilized this established proteomic technique as well as bioinformatics tools to prioritize key proteins whose expression level in the CNS correlated specifically with the progressive phase of disease in the NOD EAE model. Bioinformatics analysis identified 11 proteins with differential expression in the CNS of mice across the time course of NOD EAE, three of which are CNS specific. We are seeking to detect corollary changes in these three CNS-specific proteins in the serum, pointing to a minimally invasive means of monitoring disease progress and measuring drug efficacy. Our studies will provide a proof-of-concept for identifying homologous human biomarkers to guide treatment in individual patients. Furthermore, our results may provide insights into mechanisms that contribute to disease pathology and offer additional therapeutic targets for slowing the progression of MS.

Signaling via TNFR2 mediates CNS remyelination in EAE through regulation of oligodendrocyte progenitor cells

Tumor necrosis factor-alpha (TNF) is a pleiotropic inflammatory cytokine that has been associated with the pathogenesis of several autoimmune diseases, including multiple sclerosis (MS). Consequently, TNF-blocking drugs have been widely used to treat many inflammatory conditions and have proven highly effective. However, treatment of MS patients with anti-TNF drugs leads to disease exacerbation and severe demyelination. This effect has been specifically associated with lack of TNF signaling through its receptor, TNFR2. However, the underlying mechanisms are not fully understood. Experimental autoimmune encephalomyelitis (EAE) is the most common animal model used to study MS. Our lab has recently generated TNFR2−/− DR2b+/+ mice to study the role of TNFR2 signaling in EAE in the context of the HLA-DR2b (DRB1*1501), a haplotype strongly associated with MS. We found that these mice developed progressive EAE characterized by increased demyelinating lesions. Strikingly, this phenotype was not due to lack of TNFR2 expression in T cells, but rather was associated with a decreased numbers of oligodendrocyte progenitor cells (OPCs) in the CNS. Moreover, we demonstrated that TNFR2 signaling is critical for expression of chemokines in the CNS, suggesting its involvement in OPC function and recruitment. Our studies provide key insights into CNS repair and regulatory mechanisms controlled by TNF during inflammation, and this information may help develop novel therapeutic strategies.

Unexpected STAT3-mediated mechanisms of regulation of effector Th17 function in autoimmunity

Th17 cells have been linked to the emergence of many autoimmune inflammatory conditions as well as defense against fungal pathogens. Early differentiation and expansion of Th17 cells relies on key cytokines that signal through STAT3, including IL-6 and IL-21. Later STAT3-dependent signals from IL-23 are critical for gain of inflammatory function by effector Th17 cells. Thus, development of drugs that target STAT3 or its upstream receptors are a major research focus to alleviate disease. However, the requirements for STAT3 signaling in effector Th17 cells remain elusive. Here, we developed a model to study the effect of STAT3 deficiency specifically in effector Th17 cells in EAE, an animal model of multiple sclerosis. Our data show that mice lacking STAT3 in effector Th17 cells are resistant to EAE development. Unexpectedly, we demonstrate that in Th17 cells, STAT3 is not required for maintenance of Th17 lineage commitment or Th17 cytokine production in vivo. To determine mechanisms by which STAT3 regulates Th17 effector cells to promote development of autoimmune inflammation, we performed bioinformatics analysis of the transcriptome of effector Th17 cells isolated from lymph nodes (LN) at day 10 (onset) of EAE. This revealed that STAT3 regulates expression of genes associated with particular cell-death pathways, and pathways associated with proliferation and T cell mediated tissue damage. Corresponding to these changes in gene expression, we found that STAT3 deficient effector Th17 cells were reduced in numbers in LN and target tissue during EAE. Our data reveal a hitherto unappreciated mechanism for STAT3 in regulating effector Th17 cells, which have major implications for use of STAT3-targeted therapies.

Identifying biomarkers for monitoring progression of multiple sclerosis

There are currently no reliable methods for assessing the progression of multiple sclerosis (MS) from the relapsing-remitting to the secondary progressive form. This gap in knowledge hinders the ability for therapeutic intervention and ultimately results in continued relapses and physiological deterioration. To begin to address the urgent need for biomarkers of progressive MS we investigated proteome changes over the disease course of progressive experimental autoimmune encephalomyelitis (EAE) in NOD mice as a preclinical model of the disease. Our lab has pioneered a novel high-throughput quantitative proteomic technique which we used to quantify expression levels of central nervous system (CNS) proteins over the course of monophasic EAE in C57.BL/6 mice. We utilized bioinformatics tools to prioritize key proteins whose expression level correlated specifically with the progressive phase of disease in the NOD EAE model. Importantly, we were able to detect corollary changes in these CNS-specific proteins in the serum, pointing to a minimally invasive means of monitoring disease progress and measuring drug efficacy. Our studies will provide a proof-of-concept for identifying homologous human biomarkers to guide treatment in individual patients. Furthermore, our results may provide insights into mechanisms that contribute to disease pathology and offer additional therapeutic targets for slowing the progression of MS.

A predictive disease-specific protein biomarker fingerprint for clinical relapses and glucocorticoids treatment of multiple sclerosis

Despite extensive research, multiple sclerosis (MS) remains a disease that lacks a definitive prognostic test to predict imminent disease relapses. Thus, patients may undergo years of unnecessary treatments. Additionally, current treatments for MS vary significantly in efficacy between individual patients, and thus there is a critical need to develop biomarkers for treatment efficacy and resistance. To address these issues, we recently developed a high-throughput quantitative proteomics method to measure changes in proteome expression over the course of the preclinical experimental autoimmune encephalomyelitis (EAE) model. Interestingly, using the EAE model we revealed characteristic CNS-specific protein expression waves prior to the onset of clinical symptoms. Moreover, we have identified key proteins with altered expression that correlated with the therapeutic efficacy of glucocorticoid treatment. Bioinformatics analysis revealed candidate protein biomarkers to predict treatment efficacy and clinical disease course. Importantly, these proteins could be detected in serum and expression trajectories analysis identified a strong correlation of the CNS proteome to their levels in serum. Prospective studies in the EAE model using these candidate protein biomarkers showed their effectiveness in predicting clinical disease and treatment responses. Our studies suggest the utility for establishing homologous protein biomarkers in human MS patients. Finally, our work investigating the CNS proteome over the course of EAE may provide novel insights and molecular targets for disease mechanisms and treatments of MS.

Identifying biomarkers for monitoring disease progression in experimental autoimmune encephalomyelitis (THER7P.942)

Multiple sclerosis (MS) is the most common demyelinating neuroinflammatory disorder which afflicts over 400,000 Americans. Currently, determining clinical or sub-clinical disease progression in MS patients and development of novel treatments has been hampered by the lack of specific and sensitive laboratory tests. Recently, our lab has developed a technique called M2 proteomics, which is a rapid quantitative approach for identifying putative protein biomarkers and therapeutic targets of experimental autoimmune encephalomyelitis (EAE), a commonly used animal model for MS. Notably, we identified several putative-biomarkers which correlate with different stages of monophasic EAE. The objective of this study is to identify protein biomarkers of disease progression in a progressive EAE model using non-obese diabetic (NOD) mice. We hypothesize that during progressive EAE key central nervous system (CNS) disease-specific proteins will be released into blood and changes of these proteins can be used to determine disease progression. Using the progressive NOD EAE model, we determined the expression of putative CNS-specific protein biomarkers by immune assay in brain homogenate and serum longitudinally over the course of disease. We identified several CNS-specific potential biomarkers in serum that correlated with the progression of disease. The results of this study could help development of biomarkers for disease progression and testing of novel treatments for progressive MS.

Identification of predictive protein biomarkers for treatment efficacy and clinical relapses of multiple sclerosis (THER7P.950)

Despite extensive research, MS remains a disease that lacks a definitive prognostic test to predict imminent disease relapses. Thus, patients may undergo years of unnecessary treatments. Additionally, current treatments for MS can produce dramatically different outcomes in different individuals and therefore there is a critical need to develop biomarkers for treatment efficacy and resistance. We have recently developed a novel quantitative proteomics method to measure changes in proteome expression over the course of experimental autoimmune encephalomyelitis (EAE). Our statistical analyses indicate a strong correlation to EAE severity and/or clinical-phase. Interestingly, we revealed characteristic CNS-specific protein expression waves prior to the onset of clinical symptoms. We are currently testing whether these protein expression waves allow us to predict the onset of clinical episodes and forecast the severity of the disease to guide treatment strategies. Additionally, we have identified changes in the CNS proteome that can be measured in serum during EAE that correlate with the therapeutic efficacy of glucocorticoid treatment. Our studies will provide proof-of-principle for developing homologous human biomarkers that may be useful to predict disease onset and treatment efficacy. Finally, the detected changes in the CNS proteome may provide insights into key mechanisms that contribute to the disease pathology and may be useful to develop new therapeutic targets for MS.

Body fluid biomarkers in multiple sclerosis: how far we have come and how they could affect the clinic now and in the future

Multiple sclerosis (MS) is an autoimmune inflammatory disease of the central nervous system, 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 as the expanded disability status scale, MRI and presence of oligoclonal bands in the cerebrospinal fluid. However, none of these measures correlates 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 miRNA, mRNA, lipids and proteins.

T cell subsets and their signature cytokines in autoimmune and inflammatory diseases

CD4(+) T helper (Th) cells are critical for proper immune cell homeostasis and host defense, but are also major contributors to pathology of autoimmune and inflammatory diseases. Since the discovery of the Th1/Th2 dichotomy, many additional Th subsets were discovered, each with a unique cytokine profile, functional properties, and presumed role in autoimmune tissue pathology. This includes Th1, Th2, Th17, Th22, Th9, and Treg cells which are characterized by specific cytokine profiles. Cytokines produced by these Th subsets play a critical role in immune cell differentiation, effector subset commitment, and in directing the effector response. Cytokines are often categorized into proinflammatory and anti-inflammatory cytokines and linked to Th subsets expressing them. This article reviews the different Th subsets in terms of cytokine profiles, how these cytokines influence and shape the immune response, and their relative roles in promoting pathology in autoimmune and inflammatory diseases. Furthermore, we will discuss whether Th cell pathogenicity can be defined solely based on their cytokine profiles and whether rigid definition of a Th cell subset by its cytokine profile is helpful.

Microwave and magnetic (M(2) ) proteomics of the experimental autoimmune encephalomyelitis animal model of multiple sclerosis

We hypothesized that quantitative MS/MS-based proteomics at multiple time points, incorporating rapid microwave and magnetic (M(2) ) 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 M(2) 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.

Immunoenrichment microwave and magnetic proteomics for quantifying CD47 in the experimental autoimmune encephalomyelitis model of multiple sclerosis

We hypothesized that quantitative MS/MS-based proteomics at multiple time points, incorporating immunoenrichment prior to rapid microwave and magnetic (IM(2) ) 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 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; myelin basic protein: 223-228, corresponding to myelin basic protein; and migration inhibitory factor: 79-87, corresponding to a proinflammatory cytokine that inhibits macrophage migration. While validation in a larger cohort is underway, we conclude that IM(2) 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.