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March 17, 2014

Editor: Andrew H. Lichtman, MD, PhD, Brigham & Women's Hospital
Editorial Board: Abul K. Abbas, MD, University of California, San Francisco | Carla J. Greenbaum, MD, Benaroya Research Institute | Andrew H. Lichtman, MD, PhD, Brigham & Women's Hospital

Highlights in Recent Literature | Clinical Immunology Highlights | Basic Immunology & Novel Therapies | ImmunphenotypingPDF VersionPrevious Issues

Highlights from Recent Literature

A Surprising Immune Etiology for Narcolepsy

A review of De la Herrán-Arita, et al., CD4+ T Cell Autoimmunity to Hypocretin/Orexin and Cross-Reactivity to a 2009 H1N1 Influenza A Epitope in Narcolepsy. Science Translational Medicine 5, 216ra176 (2013).
PMID: 24353159

Type I narcolepsy is a lifelong disorder characterized by sleepiness, aplexy, and rapid transition from wakefulness to REM sleep. Type I narcolepsy is strongly associated with HLA DQ0602 and results from the loss of the approximately 70,000 posterior hypothalamus neurons that produce the wake promoting neuropeptide hypocretin. 

• The authors identified two immune epitopes of the hypocretin neuropeptide that bound to DQ0602. These two epitopes of hypocretin activated a population of CD4+ T cells in patients with narcolepsy but not in DQ0602-positive healthy controls.

• The development of narcolepsy has been previously associated with infection by the 2009 H1N1 influenza A strain (pH1N1).

• The authors administered a seasonal influenza vaccine containing pH1N1 to patients with narcolepsy and found an increased frequency of circulating T cells specific for the two immunogenic epitopes of hypocretin.

• In addition, the authors also identified a hemagglutinin epitope of the influenza virus specific to the pH1N1 influenza strain that had homology to the two immunogenic hypocretin peptides.

In vitro stimulation of CD4+ T cells from patients with narcolepsy with the influenza pH1N1 proteins or the hemagglutinin epitope alone increased the frequency of T cells responding to the two hypocretin peptide epitopes.

Narcolepsy, a lifelong disease with devastating impact on quality of life has long been associated with a particular HLA molecule but an immune etiology has been elusive. The authors have demonstrated that T cells responding to the H1N1 influenza A strain pH1N1 and possibly to a single hemagglutinin epitope of this virus, likely cross-react with two immune epitopes for the critical neuropeptide hypocretin. These results suggest that cross-reactivity induced by antiviral immunity may be responsible for the destruction of hypocretin producing posterior hypothalamus neurons and therefore for some cases of narcolepsy developing after 2009. This elegant study suggests a role for molecular mimicry in the development of narcolepsy and sets the stage for further evaluation of immune epitopes in this neurologic disease.

Reviewed by Rachael A. Clark, MD, PhD, Brigham and Women's Hospital

Putting Neutrophils into Reverse: Fishing for New Anti-inflammatory Molecules

A review of Robertson, et al., A Zebrafhish Compound Screen Reveals Modulation of Neutrophil Reverse Migration as an Anti-flammatory Mechanism. Science Translational Medicine 5, 225ra29 (2014). PMID: 24554340

New therapies are needed for inflammatory disorders that can aid in the resolution of inflammation. Targeting molecules that help resolve inflammation has been difficult because limited knowledge exists about the various molecules that contribute to resolution of inflammation. In order to identify new targets and new drugs, the authors developed and utilized a novel transgenic zebrafish model screen.

• The authors developed an in vivo screen for molecules that helped resolve inflammation in using transgenic zebrafish. In this model, sterile tissue injury was induced and a panel of known compounds was screened for their ability to accelerate resolution of inflammation.

• The screen found that a substance derived from a Chinese medicinal herb, tanshinone IIA, strongly accelerated resolution of inflammation.

• This molecule blocked proinflammatory signals, induced neutrophil apoptosis and also had a surprising effect of inducing reverse migration of neutrophils in vivo in zebrafish.

• Tanshinone IIA promoted neutrophil reverse migration by inducing nondirectional redistribution of the cells, rather than by inducing active fugetaxis.

• The authors extended their studies to human neutrophils and demonstrated that tanshinone IIA overrode human neutrophil survival signals and induced apoptosis of human neutrophils.

Resolution of inflammation is a process that is poorly understood and novel therapeutics that enhance inflammatory resolution are needed for the treatment of autoimmune and inflammatory disorders. The authors identified a novel enhancer of immune resolution using a new in vivo zebrafish assay. The identified compound, tanshinone IIA, promoted neutrophil death in both humans and zebrafish and had the interesting effect of inducing increased random migration of neutrophils, thereby dispersing them away from the site of inflammation. These studies are significant because they identify a novel therapeutic that can now be further tested in humans and they demonstrate the utility of using a zebrafish screen to identify novel agents that enhance inflammatory resolution.

Reviewed by Rachael A. Clark, MD, PhD, Brigham and Women's Hospital

The Whole 9 Yards: A Careful Characterization of Human TH9 Cells

A review of Schlapach, C., et al. Human Th9 Cells are Skin-Tropic and have Autocrine and Paracrine Proinflammatory Capacity. Science Translational Medicine 6, 219ra8 (2014). PMID: 24431112

The immune system contains a panoply of cells and soluble factors to recognize and assess antigens and then determine an appropriate set of responses. Within the adaptive cell-mediated immune response, T cells have been subdivided into numerous subsets, with increasing appreciation of the existence of many intermediate states and functions in previously defined subsets, as well as entirely new subsets. Th9 cells are one of the newer subsets of CD4+ T cells, and they have led to extensive study in mouse models as well as studies on differentiating them from naïve or memory T cell populations or in a few human diseases. In this study, Schlapbach et al provide a detailed analysis of Th9 cells in healthy human donor PBMCs, including their frequency, their tissue tropism and their response to common pathogens and polyclonal stimulation. This is taken deeper, with investigations into Th9 cells from tissues and in samples from patients with varied skin disorders, and provides the most comprehensive picture yet of this cell subset.

• The study begins by assessing responses of skin tropic (CLA+), gut tropic (α4β7+) and non-skin tropic, non-gut tropic (CLA-, α4β7-) memory CD4+ T cells to autologous monocytes pulsed with peptides from a variety of pathogens. As one might expect, T cells with tropism for a given tissue responded more strongly to pathogens that are generally found at that site (i.e. Candida albicans and CLA+ CD4+ T cells).

• Interestingly, IL-9 production was found almost exclusively in the skin tropic (CLA+) subset and only when stimulated with a skin-flora pathogen (C. albicans). In addition, the production of IL-9 was transient (here, peaked at day 6).

• Next, they examined the effects of polyclonal stimulation of human healthy donor PBMCs. Again, they isolated three populations: skin tropic (CLA+), gut tropic (α4β7+) and non-skin tropic, non-gut tropic (CLA-, α4β7-) CD4+ T cells and assessed cytokine production and proliferation post-stimulation. Most IL-9 was still produced by skin tropic CD4+ T cells, and most of those cells did not co-produce other cytokines commonly associated with major helper T cells subsets (i.e. IFNγ, IL-13, IL-17). Of note, skin homing cells also produced IL-13 (most after IL-9 production had halted), gut homing cells primarily produced IFNγ and non-skin, non-gut homing T cells produced more IL-17. In this context, IL-9 production was again transient, though it peaked at day 2.

• Beyond studies of PBMCs, the study also characterized IL-9 cells in skin, lung and gut from healthy human tissue samples by isolating resident memory T cells (TRM) from those tissues and assessing IL-9 production after stimulation. Skin resident memory T cells were the major source of IL-9 and were also found to co-produce TNFα and stain positive for granzyme B.

• Given reports that IL-9 may come from ILCs in mice, they assessed the effect of IL-33 and IL-2 (which stimulate IL-9 production from human ILCs) on skin TRM with no production of IL-9.

• With respect to how IL-9 producing helper T cells affect the other subsets of helper T cells, blockade of the early, transient production of IL-9 reduced subsequent production of both additional IL-9 (autocrine) as well as IL-17, IL-13 and IFNγ (paracrine) from CLA+ skin tropic CD4+ memory T cells, in addition to reducing proliferation.

• Finally, they characterized Th9 cells in skin samples from a Th2 skewed disease (atopic dermatitis) and a Th1/Th17 skewed disease (psoriasis) and found Th9 cells in both types of skin lesions, with a significant increase in psoriatic lesions versus healthy skin.

In this study, Th9 cells are identified in healthy human skin and PBMCs and the paper demonstrates that the secretion of IL-9 is from skin tropic CD4+ memory cells in PBMCs or skin resident memory CD4+ T cells and can be stimulated using tissue relevant pathogens or polyclonal stimulation techniques. They demonstrated that the production of IL-9 is co-incident with TNFa and granzyme B and comes from a CD3+ population (i.e. does not seem to be exclusively from ILCs in humans). In addition, the early and transient secretion of IL-9 by Th9 cells was shown to enhance the secretion by other core helper T cell subsets of their own signature cytokines (i.e. IL-17 from Th17 cells). Finally, psoriatic lesions from human patients showed an increase in Th9 cells versus healthy skin. Much work remains to be done to link these cells to the pathogenesis of disease, and starting with inflammatory skin disorders seems like a perfect first step. The ways in which this cell type are tied into the complex network of inhibitory and activating factors that drive helper T cell differentiation and function will also likely fuel efforts for years to come. This study provides many new avenues for investigation and a clear set of questions to pursue next. 

Reviewed by Sarah Henrickson, MD, PhD, Children’s Hospital of Philadelphia

Drinking From a Fire Hose: Collecting and Analyzing Massive Data Sets

 A review of Newel, E.W. and Davis, M.M., et al. Beyond Model Antigens: High Dimensional Methods for the Analysis of Antigen-Specific T Cells. Nature Biotechnology. 32, 147-149, (2014). PMID: 24441473

The complexity of the human immune system has dramatic variability among individuals based on genetic diversity as well as unique exposures to pathogens, commensal organisms and myriad environmental factors. Recent reviews in Nature Immunology and Nature Biotechnology (Feb. 2014) highlight the many challenges and tools available and under development for analysis of the increasingly deep and massive data sets that are being generated in this field.

Newell et al focuses on the challenges and strategies in deriving a complete understanding of the antigen specific T cell response to immunological challenge. Kidd et al focuses on massively multidimensional datasets and the best strategies for getting our hands on the full implications of these datasets, making use of the best algorithms and packages that are currently available.

• Newell et al begins by discussing the frontiers of techniques available for phenotyping the states present in T cells, from traditional flow cytometry (with both user defined and non-linear strategies for data analysis) to mass cytometry (which allows simultaneous assessment of greater numbers of characteristics per cell, with much lower throughput). In addition, they discuss the use of microwells for single cell phenotyping of T cells and single cell transcriptomics.

• Next, they focus on advanced techniques and recent papers that focus on the assessment of antigen specific T cells. They begin by discussing the history and recent advances in the use of peptide-MHC tetramers for antigen specific T cell enumeration, including methods for generating tetramers with full coverage or targeted coverage of epitopes from pathogens with small or large genomes. This includes a clear discussion of merging mass cytometry with the use of reagents to characterize antigen specific T cells.

• Finally, they discuss the use of TCR sequencing and how to possibly derive antigen specificity from TCR sequences (with a focus on library based strategies versus structural prediction models).

• Kidd et al take a more broad focus and discuss strategies to describe the entire immune response from many vantages, and provide a set of tools to use from each vantage point. These techniques include transcriptional analysis (including DNA microarrays, DNA sequencing and RNASeq) with specific recommendations for the merging of simultaneous analysis of DNA sequencing and mRNA profiling to allow expression quantitative trait locus (eQTL) analysis. Mentioned also is how to deconvolute datasets containing profiles of a mixed (e.g PBMC) population from a computational perspective into cell specific datasets. They also discuss methods for assessing mass cytometry data.

• From there, they discuss the complex methods for constructing networks from varied data sets, including a number of recent fascinating publications.

• In addition to a wonderful list of packages for each type of analysis, they also provide a discussion of the many datasets and repositories of human data available for investigators to study.

Both reviews provide overviews for the generalist and the specialist of both the available tools, the most recent articles developing and exploiting these tools and the challenges that remain. Among these challenges remains the need for resources to allow systematic collection of appropriate samples (both in healthy donors from pediatric, young adult and elderly populations across races and ethnicities as well as in human disease) as well the development of analysis packages that can be used by non-computational biology researchers with deep domain knowledge in the samples under study.

Reviewed by Sarah Henrickson, MD, PhD, Children’s Hospital of Philadelphia 

Does Cancer Trigger Autoimmunity?

 A review of Joseph, C.G., et al. Association of the Autoimmune Disease Scleroderma with an Immunologyic Response to Cancer. Science. 2014; 343(6167): 152-157. PMID: 24310608

Systemic delivery of CTLA-4 blocking antibodies induces antitumor immune responses in some preclinical models and patients, and has been approved for the treatment of advanced melanoma by the FDA. However, because systemic treatment with CTLA-4 blocking antibodies lowers the activation threshold for all T cells, and not just the tumor-reactive T cells, clinical use of CTLA-4 blocking antibodies is hampered by dose-limiting autoimmune and inflammatory side effects. In this study, Marieke Fransen and colleagues demonstrate that it may be possible to achieve the antitumor effect without causing adverse side effects by administering CTLA-4 blocking antibodies locally rather than systemically.

• The authors first compared the antitumor efficacy of systemic versus local administration of CTLA-4 blocking antibody against subcutaneously implanted murine colon carcinoma MC-38 tumors expressing Ovalbumin (MC-38-OVA). They demonstrate that a single local injection of 50 μg of antibody in Montanide ISA-51 was just as effective as treatment with two systemic doses of 200 μg of antibody. They also showed that localized treatment with CTLA-4 blocking antibodies induced antitumor responses in mice bearing MC-38 tumors that do not express OVA, and mice bearing more aggressive OVA-expressing EG7 thymoma tumors.

• Low dose treatment with 50 μg of antibody was shown to only be effective when delivered in the tumor-draining area, and not when given systemically, or in the contralateral flank of tumor-bearing mice.

• Similar to systemic treatment, localized treatment with CTLA-4 blocking antibody was shown to enhance systemic tumor-specific T cell responses, and as a result, was capable of controlling distant tumors.

• By depleting CD4+ and CD8+ T cells in treated mice, the authors demonstrated that CD8+ T cells, and not CD4+ T cells, were responsible for the antitumor effect in their model, indicating that CTLA-4 blocking antibodies can operate directly on CD8+ T cells.

• Analysis of serum from treated mice showed that antibody levels were more than 1,000-fold lower in mice treated with local doses of antibody compared to mice treated with systemic doses. Levels of the liver enzymes ALT and AST were also lower in locally-treated mice suggesting that local slow-release administration of the antibody decreases the induction of adverse effects.

Although systemic treatment with CTLA-4 blocking antibodies can induce significant antitumor effects in some patients, and has been FDA approved for the treatment of advanced melanoma, this treatment can also cause severe autoimmune and inflammatory side effects. This study provides a simple, yet novel delivery system for distributing CTLA-4 blocking antibody in the tumor-draining area. In preclinical models, use of this delivery approach resulted in antitumor responses that were comparable to systemic antibody treatment, but were associated with 1,000-fold lower serum levels of antibody. These data indicate that use of this delivery approach may make it possible to achieve the same antitumor effects in patients without inducing unwanted side effects. This strategy could also be useful for other immunomodulatory agents being developed for cancer treatment.

Reviewed by Elizabeth Jaffe, MD, John Hopkins Institute for Clinical and Translational Research and Eric Lutz, PhD, John Hopkins University, Sidney Kimmel Cancer Center

Test-driving CARs (Chimeric Antigen Receptors) for Solid Tumor Immunotherapy

 A review of Beatty, G.L., et al. Mesothelin-Specific Chimeric Antigen Receptor mRNA-Engineered T Cells Induce Antitumor Activity in Solid Malignancies. Cancer immunol. Res. 2014; 2(2): 112-120. PMID: 24579088

The adoptive transfer of CAR-expressing T cells has shown promising results as a treatment for CD19+ hematologic malignancies. However, efforts to extend this approach to solid tumors have been less successful and hindered with high toxicity. A major obstacle has been on-target off-tumor toxicity directed against normal tissue expressing the antigenic target of the CAR. In this study, Beatty and colleagues provide a potential approach to circumvent this issue.

• The authors established a platform for engineering transient CAR-expressing T cells using in vitro transcribed mRNA.

• In this article, they present case reports for the first two patients (one with mesothelioma and one with metastatic pancreatic adenocarcinoma) receiving mRNA-engineered CAR T cells specific for mesothelin, a cell-surface antigen expressed by several different solid tumors including mesothelioma and pancreatic adenocarcinoma, but also at low levels on normal peritoneal, pericardial, and pleural mesothelial surfaces. mRNA mesothelin CAR T cells were infused intravenously in both patients, and intratumorally only in the pancreatic cancer patient.

• Using quantitative PCR assays specific for the CAR transgene, the authors demonstrated that mRNA-engineered mesothelin CAR T cells persisted transiently in peripheral blood following intravenous infusion, but also trafficked to primary and metastatic tumor sites.

• Infusion of mRNA-engineered mesothelin CAR T cells was associated with anti-tumor activity in both patients as monitored by CT and PET imaging, and stabilization of serum tumor markers. In addition, in vitro cytolytic assays were used to demonstrate that mRNA engineered mesothelin CAR T cells specifically lysed mesothelin-expressing tumor targets.

• CAR T cell infusion was also associated with signs of immune induction including the development of novel antigen specific serum antibody responses, supporting the induction of epitope-spreading.

• Importantly, no overt signs of on-target off-tumor toxicity (e.q. peritonitis, pleuritis and pericarditis) were observed in either of the two patients. This is interesting because treatment with antibody-toxin drug conjugates targeting mesothelin has been limited by pleuritis.

This study demonstrates the feasibility of using mRNA-engineered T cells to evaluate the antitumor activity, and off-tumor toxicity potential of CARs targeting tumor-associated antigens. This strategy provides a transient and controlled approach for more safely evaluating CAR-expressing T cells for the treatment of solid tumors.

Reviewed by Elizabeth Jaffe, MD, John Hopkins Institute for Clinical and Translational Research and Eric Lutz, PhD, John Hopkins University, Sidney Kimmel Cancer Center

A Look at the Full Spectrum!

A review of Xue, et al. Transcriptome-Based Network Analysis Reveals a Spectrum Model of Human Macrophage Activation. Immunity. 40, 2014; 274-288. PMID: 249590056

According to the current conceptual framework, macrophages can be polarized into classically (M1) or alternatively (M2) activated cells with a role in promoting Th1 and Th2 responses respectively. Insights gained into activation, polarization, and function of macrophages based on this framework have indeed been helpful in understanding the immune responses in health versus disease. Nonetheless, transcriptional programs regulating these processes remain poorly characterized. Also, observations obtained from macrophages involved in chronic inflammation, chronic infection, or cancer are strongly suggestive of a rather broader transcriptional repertoire extending beyond the current bipolar model. In order to study the macrophage transcriptional programs better, the authors generated a data set of 299 macrophage transcriptomes by in vitro stimulation of human macrophages with 28 diverse activation signals. 

• Thorough analysis of this data set through powerful analytical tools such as coregulation analysis (CRA), self-organizing-map (SOM) clustering, and correlation coefficient matrices (CCM) revealed a more extensive ‘spectrum’ model of macrophage activation that indeed goes beyond the existing M1 versus M2 model. The spectrum model was endorsed by in phenotypic and functional characterization studies.

• Through this analysis, the authors could also identify certain genes that were selectively elevated in only one of the stimulation conditions in their data set. At the same time, necessity of multi-gene combinations to distinguish complex input signals at transcriptional level was perceived.

• Using weighted gene coexpression network analysis (WGCNA), the authors could identify 49 distinct coexpression modules displaying divergent patterns corresponding to individual stimuli. Gene ontology enrichment analysis (GOEA) and prediction of transcription factor binding based on the module genes revealed novel associations between stimulus-induced gene expression patterns and in vivo immune response.

• Most interestingly, applying these transcriptional programs to human alveolar macrophages from smokers and patients with chronic obstructive pulmonary disease (COPD) revealed an unexpected loss of inflammatory signatures in COPD patients.

• Through reverse network engineering (RNE), the authors could define common denominators of macrophage activation, confirming the involvement of unknown transcriptional regulators, and identifying unexpected yet unexplored candidate regulators.

• Finally, by integrating murine data from the ImmGen project, the authors put forth a refined, activation-independent core signature for human and murine macrophages.

With immunology entering into the era of high dimensional data generation and analysis, this paper primarily serves as an excellent example to demonstrate how capitalizing on the advanced analytical tools helps reveal erstwhile obscured cellular heterogeneity. The spectrum model thus uncovered indeed opens new avenues for future research in macrophage responses. The demonstrated application of this model to predict macrophage programs in vivo certainly holds tremendous potential in translational immunology. Similar studies employing clinically relevant stimuli (for e.g. those derived from pathogens, tumor cells, or allergens) to generate a transcriptional data set are needed in this context, and this study will most definitively be helpful in guiding the analytical strategy for such future experiments.

Reviewed by Kari Nadeau, MD, PhD, Stanford School of Medicine

Bitter End For Microbes in the Airway

A review of Lee, et al. Bitter and Sweet Taste Receptors Regulate Human Upper Respiratory Innate Immunity. Journal of Clinical Investigation. 2014; 124(2): 1393-1405. PMID: 24531552

Mucociliary action is a primary clearance method employed by upper airway epithelium to defend against encroaching toxins, particulates, and microbial populations. An alternative and novel role for bitter taste receptors, T2Rs, in bacterial clearance has recently emerged with the discovery that T2R38 enhances ciliary beat frequency and increases α-microbial peptides secretion and nitric oxide release. Lee et al. define an alternative method for bactericidal killing in which activated bitter receptors secrete α-microbial peptides upon bitter ligand administration. The authors further demonstrate that bitter receptors are in turn regulated by sugar and sugar substitutes through activated sweet receptors of upper airway chemosensory cells, thereby preventing α-microbial secretions. 

• Using surgically removed human explants, the author set-up an air-liquid interface (ALI) to mimic the polarized upper airway epithelium. Administration of the bitter compound denatonium benzoate to apical nonciliated human sinonasal chemosensory cells in ALI cultures induces a calcium response that propagates to adjacent cells via gap junctions. Apical co-expression and activation of sweet receptors T1R2/3 by glucose and sugar substitutes overrides denatonium-induced calcium responses, thereby regulating T2R calcium-dependent signaling pathways.

• Administration of denatonium benzoate to the apical side of ALI cultures results in calcium-dependent bactericidal effects on numerous bacterial populations. Co-administration of glucose in a dose-dependent manner reverses α-microbial responses of denatonium-induce T2R activation. Preliminary findings suggest that cAMP and protein kinase signaling regulate α-microbial secretion.

• Denatonium-stimulated secretions contain low-molecular weight proteins corresponding to α-microbial peptides, specifically β-defensin-1 and -2. Glucose-stimulated T1R2/3 sweet receptors inhibit β-defensin secretion.

• Patients with Chronic Rhinosinusitis (CRS) have recurrent upper respiratory infections and have elevated glucose levels in the nasal cavity similar to levels found to inhibit T2Rs by in vitro analysis. These data suggest that increases in nasal glucose in CRS patients exacerbates microbial infections by activing sweet receptors and subsequently inhibiting calcium-dependent T2R β-defensin secretion.

In summary, the authors postulate that in a healthy individual normal glucose levels repress bitter receptor expression of α-microbial peptides. Upon upper airway infections, microbial glucose consumption and shedding of bitter-derived microbial compounds relieve inhibition of T2R-dependent α-microbial peptide secretion.

Reviewed by Kari Nadeau, MD, PhD, Stanford School of Medicine


 FOXP3 Gene Transfer: A New Therapy for IPEX Syndrome

 A review of Passeerini, L., et al. CD4+ T Cells from IPEX Patients Convert into Functional and Stable Regulatory T Cells by FOXP3 Gene Transfer. Science Translational Medicine 5, 215ra174 (2013). PMID: 24337481

Immune dysregulation, polyendocrinopathy, enteropahty, X-linked (IPEX) syndrome is a primary immunodeficiency disorder that is characterized by loss of function of thymus-derived CD4+CD25+ regulatory T cells (Treg). Hematopoietic stem cell transplantation (HSCT) is the only curative available for IPEX syndrome patients. Data from animal models and recent successful gene therapy trials in graft-versus-host-disease patients undergoing allogeneic HSCT show promise for the use of Treg cells as therapeutic agents in diseases. In this study, the authors explore the possibility to restore immune regulatory function in FOXP3 mutated T cells by wild-type FOXP3 gene transfer thereby converting these conventional T cells in fully functional Treg like cells with suppressor function.


• They successfully generated CD4 FOXP3 Treg like cells using lentiviral vector system from healthy donors. These cells were stable and showed low levels of cytokine secretion (IL-2, IFN-g, IL-5, and IL-22) even under inflammatory conditions when stimulated with IL-6 and IL-1b.

• Using a humanized murine model of xeno-GVHD (graft-versus host disease) in NSG mice they show in vivo functionality of these CD4FOXP3 Treg cells. They show increased survival and decreased weight loss in NSG mice after transfer of CD4FOXP3 Treg cells. Transfer of these cells resulted in development of substantial chimerism in peripheral blood and these cells did not hamper the engraftment of Teff cells but instead controlled their effector function and proliferation.

• They show that CD4FOXP3 Treg cells generated using naïve CD4 cells are more stable and less proliferative compared to CD4FOXP3 Treg cells generated using antigen experiences memory CD4 T cells indicating that FOXP3 mediated Treg conversion of T cells is more efficient in naïve CD4 T cells compared to memory T cells.

• To next evaluate the possibility of using these cells in a clinical setting, they transduced FOXP3 expression in FOXP3 mutant conventional CD4 T cells from 5 IPEX patients with different FOXP3 mutations. They successfully generated transduced T cells with stable FOXP3 expression that acquired Treg like phenotype- CD25hi, CTLA4hi and CD127low and upregulation of Helios. These transduced FOXP3 cells also showed reduced cytokine secretion similar to that observed in cells generated in healthy donors. These FOXP3 Treg cells also acquired functional properties similar to those of conventional Treg cells- cell suppression of allogenic CD4 effector cells and low self proliferation upon CD3 stimulation. In vivo studies using the lethal GVHD humanized mouse model also demonstrated in vivo functionality of these cells generated from IPEX patients by protecting these animals from lethal GVHD and loss of weight.

Overall these data demonstrate that CD4FOXP3 T cells generated from FOXP3-mutated CD4+ T cells from IPEX patients are fully functional, both in vitro and in vivo. These de novo generated cells are highly stable if generated from naïve T cells and perform regulatory functions even in inflammatory conditions in vitro and in vivo. Taken together these data suggest that gene transfer of FOXP3 can be a potential therapeutic approach for IPEX syndrome patients.

Reviewed by Kari Nadeau, MD, PhD, Stanford School of Medicine

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Highlights From Clinical Immunology, the Official Journal of FOCIS

A SLAP in the Face of Autoimmunity

A review of Peterson L. et al. SLAP Deficiency Decreases DsDNA Autoantibody Production. Clinical Immunology 150, 201-209, 2014 PMID: 24440645

Src-like adaptor protein (SLAP) down-regulates BCR signaling by promoting c-Cbl-mediated ubiquitin ligation of BCR complex proteins, leading to their degradation. This SLAP function reduces BCR levels in developing B cells. The authors investigated if SLAP deficiency could enhance central B cell tolerance by increasing BCR signaling in developing autoreactive B cells leading to deletion or receptor editing. They tested the effects of SLAP-deficiency using two models of anti-dsDNA autoimmunity. The first model uses vaccination with a peptide mimeotope, which induces an anti-dsDNA response in mice, and glomerular deposition of Ig. The second model is a Ig heavy chain transgenic mouse (56R), in which the transgene was cloned from a B cell derived from autoimmune MRL/lpr mouse. The 56R mouse spontaneously produces anti-dsDNA IgG autoantibodies with various light chains. The major findings were:

• dsDNA peptide mimetope immunization induced an anti-dsDNA responses in wild type BALB/c but not SLAP-/- BALB/c mice. There were equivalent amounts of anti-peptide antibodies in both groups.

• SLAP−/− 56R mice showed reduced amounts of anti-dsDNA antibodies compared to 56R control mice. A subset of the SLAP−/− 56R mice did not show reduced levels of anti-dsDNA antibodies, but the anti-dsDNA abs in the SLAP-deficient mice showed significantly less class switching to IgG2a, which is the major anti-dsDNA isotype in 56R mice.

• Analysis of B-cell subsets and Vκ and Vλ light chain usage showed no differences between 56R and SLAP−/− 56R mice, indicating that the decreased production of autoantibodies in SLAP−/− 56R mice was not due to receptor editing.

• However, SLAP deficiency did result in shift of the light chain usage in 56R mice from mainly Vκ38 to the complete editor Vκ21. The author argue this reflects repertorie selection due to biased light chain pairing and not based on receptor editing.

Overall, findings in this study are consistent with the hypothesis in the setting of SLA deficiency, increased BCR signal strength in developing B cells reduces autoantibody production. The authors suggest that targeting the ubiquitination of the BCR complex in developing B cells, is a potential strategy to decrease autoreactive B cell development.

Reviewed by Andrew H. Lichtman, MD, PhD, Brigham and Women’s Hospital

Therapeutic Peptides Come Full Circle

A review of Ali, M. et al. Cyclization Enhances Function of Linear Anti-arthritic Peptides. Clinical Immunology 150, 121–133, 2014. PMID: 24207019

In this paper, the authors document the enhanced biological activities of a cyclic peptide (C1) derived from a previously characterized linear peptide (CP), the later based on the TCR-α transmembrane region, including two polar amino acids (K, R) that are essential for TCR complex assembly. CP was previously shown to inhibit T cell activation in vitro, and when given subcutaneously or intraperitoneally, reduced the severity of adjuvant induced arthritis. C1, the cyclic variant of CP described in this paper, consists of alternating D-, L-amino acids, which may permit stacking into nanotubes within membranes, and thereby impart greater biological activity than linear peptides. The major finding of the study include the following:

• In comparison to a control linear peptide, the C1 cyclic peptide was very effective in inhibiting T cell hybridoma IL-2 production in response to SEA plus APCs (an MHC dependent mechanisms), and was less albeit somewhat effective in inhibiting hybridoma IL-2 production in response to anti-CD3, anti-TCRβ, and PMA and ionomycin. The C1 was not toxic to the cells in these assays.

• NMR studies of C1 were consistent with C1 entering membranes and adopting a transmembrane orientation, without forming lethal pores.

• Surface plasmon resonance was used to show that C1 bound very strongly to membrane, essentially irreversibly.

• C1 also showed enhance stability and overall permeation through skin after 2 and 6 days, using an in vitro assay.

• C1 delivered subcutaneously was as effective as cyclosporine in blocking inflammation in a rat adjuvant induced arthritis model.

• In a mouse Ova-induced asthma model, C1 was effective in reducing eosinophil accumulation in BAL, reducing IL-5 and IL-13 in blood, and C1 suppressed airway hypersensitivity as effectively as methylprednisone.

Overall, this study shows that cyclization of a previously characterized linear immunomodulatory peptide greatly enhanced its effectiveness in binding to membranes, blocking T cell activation in vitro, and reducing inflammatory parameters of T cell mediated disease process in rodent models. The authors results suggest that cyclization may be promising approach to enhancing the delivery and therapeutic effectiveness peptide inhibitors of immune mediated diseases.

Reviewed by Andrew H. Lichtman, MD, PhD, Brigham and Women’s Hospital

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Developments in Basic Immunology and Novel Therapies

Old Diseases in a New Bottle: IgG4-related disease

Shiv Pillai, MD, PhD, Massachusetts General Hospital, Harvard Medical School

Over the past decade a new disease entity has attracted a lot of interest. Patients presenting with tumescent, often painful, lesions affecting a variety of anatomic sites, initially often thought to have a malignant disease, have had biopsies analyzed that reveal a constellation of features that lead to a diagnosis of an entity now called IgG4-related disease or IgG4-RD. The histological features include storiform fibrosis, obliterative phlebitis, and the presence of a lymphoid and plasmacytic cell infiltrate in which forty percent or more of the IgG expressing plasma cells stain for the IgG4 isotype. Plasma levels of IgG4 may also be elevated.

This concept of IgG4-related disease was established in Japan by Hamano, Kamisawa and others at the beginning of this century (1,2). Virtually any organ in the body may be affected in IgG4-RD. This diagnosis now encompasses patients with salivary gland enlargements once thought to have Mikulicz’s disease, patients who would previously have been described as having Reidel’s thyroiditis, as well as subjects with retroperitoneal fibrosis, autoimmune pancreatitis, hypertrophic pachymeningitis, interstitial lung disease, tubulointerstitial nephritis and a host of other disorders (reviewed in 3, 4).

Why does an inflammatory disease in which fibrosis is a prominent component present with an increase in IgG4 secreting cells? What is the biological role of IgG4? Are disorders that fit the definition of IgG4-RD actually a small subset of a broader group of related fibro-inflammatory conditions? What broader lessons about immunology and disease might be learnt by studying IgG4-RD?

IgG4 is an unusual and relatively poorly understood immunoglobulin isotype. IgG4 antibodies bind poorly to activating Fc receptors and fix complement poorly. By conventional thinking this isotype should be unable to drive inflammation in the context of Fc-dependent effector mechanisms. In addition, when IgG4 is internalized into endosomes by FcRn, it can split down the middle between the two heavy chains and hybrid IgG4 molecules can form in a process called "Fab-arm exchange" (5-7). As a result many IgG4 molecules are functionally monovalent in vivo. IgG4 is therefore not suited for immune complex formation, since bivalency is required for antigen-antibody lattice formation. IgG4 can associate with the inhibitory Fc receptor, FcγRIIb, so it may function primarily as an inhibitory immunoglobulin. However, it has NOT been established beyond any doubt that IgG4 is not inflammatory. IgG4 containing immune complexes have been described in certain renal disorders. It is unclear if these complexes contain both IgG4 and other IgG isotypes and thus fix complement, or if N-Glycans on IgG4 recruits the mannose binding lectin and thus fix complement. The jury is still out on what IgG4 actually does in terms of disease pathogenesis, but it appears likely that IgG4 antibodies do not drive the inflammation and fibrosis seen in patients with IgG4-RD. It is possible that the increase in IgG4 in this disease reflects an attempt to dampen inflammation, albeit an attempt that has not succeeded.

Disease lesions in IgG4-RD share many histological features. CD4+ T cells are abundant at tissue sites of disease and they most likely drive the disease process. Apart from plasmablasts, plasma cells, and activated myofibroblasts, as well as organized tertiary lymphoid organs, essentially follicular structures with germinal centers, are also found in disease lesions. These germinal centers as well as those in draining lymph nodes are presumably major sites of IgG4 class switching. The promoters (so called I regions) adjacent to the IgG4 and IgE switch regions are structurally similar but detailed molecular studies on IgG4 class switching have not been performed. It is likely that T follicular helper cells that secrete IL-4 may participate in the IgG4 class switch, but it is also possible that unique yet to be defined T follicular helper cells are key to this class switching event. IgG4 remains a mysterious isotype and the study of IgG4 related disease may start to provide insights about this immunoglobulin sub-class.

The nature of the T cells that drive the disease is unclear. Fibrosis can be driven by a range of helper T cell subsets depending on the disease context. Th2 cells drive allergic fibrosis as seen in schistosomiasis and in this context interferon-γ may be inhibitory (8). When one considers the fibrotic nature of lesions in diseases like tuberculosis and Crohn's disease, it is clear that Th1 and Th17 cells may also drive fibrosis in certain contexts. In IgG4-RD the case has sometimes been made that the disease is driven by Th2 cells although a role for Th1 cells has also been suggested (9-11). However recent studies suggest that Th2 cells are only expanded in the circulation of patients with IgG4-RD who have concomitant atopic disease but not in subject with active disease who do not have atopic manifestations (12).

It is unclear whether IgG4-RD is an autoimmune disease and the driving antigens or antigens in this disease remain to be identified. Unlike most autoimmune diseases, IgG4-RD is largely a disease of older males. Studies examining the potential role in disease pathogenesis of genetics, the microbiome and epigenetics remain to be performed.

Is there a role for IgG4 in pathogenesis? Do IgG4 producing B cells collaborate with CD4+ T cells, perhaps by presenting antigen at disease sites? About sixty to seventy percent of subjects respond to steroids, but the most effective therapy is B cell depletion using Rituximab (13). Since B cells help maintain CD4+ effector/memory T cells (reviewed in 14), it is possible that Rituximab, by depleting antigen presenting B cells, indirectly depletes disease-causing rogue CD4+ effector/memory T cells. If IgG4 is not involved in pathogenesis, is it possible that similar mechanisms involving T cells cause disease in patients with IgG4-RD as well as in other fibrotic inflammatory diseases such as systemic sclerosis, lupus nephritis and possible idiopathic pulmonary fibrosis? The advent of immune repertoire analysis by Next Gen Sequencing and the development of many novel tools with which to interrogate the human immune system all suggest that we may soon have answers to a number of these longstanding puzzles.

1. Hamano H, Kawa S, Horiuchi A, Unno H, Furuya N, Akamatsu T, Fukushima M, Nikaido T, Nakayama K, Usuda N, Kiyosawa K. 2001. High serum IgG4 concentrations in patients with sclerosing pancreatitis. N Engl J Med 344: 732-8

2. Kamisawa T, Funata N, Hayashi Y, Eishi Y, Koike M, Tsuruta K, Okamoto A, Egawa N, Nakajima H. 2003. A new clinicopathological entity of IgG4-related autoimmune disease. J Gastroenterol 38: 982-4

3. Stone JH, Zen Y, Deshpande V. IgG4-related disease. N Engl J Med. 2012 Feb 9;366(6):539-51.

4. Mahajan VS, Mattoo H, Deshpande V, Pillai S, Stone JH. IgG4-Related Disease. Annu. Rev. Pathol. 2014, 9, 315-47.

5. Aalberse RC, Stapel SO, Schuurman J, Rispens T. 2009. Immunoglobulin G4: an odd antibody. Clin Exp Allergy 39: 469-77

6. Rispens T, Ooijevaar-de Heer P, Bende O, Aalberse RC. 2011. Mechanism of immunoglobulin G4 Fab-arm exchange. J Am Chem Soc 133: 10302-11

7. van der Neut Kolfschoten M, Schuurman J, Losen M, Bleeker WK, Martinez-Martinez P, Vermeulen E, den Bleker TH, Wiegman L, Vink T, Aarden LA, De Baets MH, van de Winkel JG, Aalberse RC, Parren PW. 2007. Anti-inflammatory activity of human IgG4 antibodies by dynamic Fab arm exchange. Science 317: 1554-7.

8. Wynn TA. 2004. Fibrotic disease and the T(H)1/T(H)2 paradigm. Nat Rev Immunol 4: 583-94

9. Tanaka A, Moriyama M, Nakashima H, Miyake K, Hayashida JN, Maehara T, et al. Th2 and regulatory immune reactions contribute to IgG4 production and the initiation of Mikulicz disease. Arthritis Rheum 2012; 64:254e63.

10. Zen Y, Fujii T, Harada K, Kawano M, Yamada K, Takahira M and Nakanuma Y. Th2 and regulatory immune reactions are increased in immunoglobin G4-related sclerosing pancreatitis and cholangitis. Hepatology 2007; 45(6): 1538-46.

11. Okazaki K, Uchida K, Ohana M, Nakase H, Uose S, Inai M, Matsushima Y, Katamura K, Ohmori K, Chiba T. Autoimmune-related pancreatitis is associated with autoantibodies and a Th1/Th2-type cellular immune response. Gastroenterology. 2000 Mar;118(3):573-81.

12. Mattoo H, Della-Torre E, Mahajan VS, Stone JH, Pillai S. Circulating Th2 memory cells in IgG4 Related Disease are restricted to a defined subset of subjects with atopy. Allergy,2014 69, 399-402.

13. Khosroshahi A, Bloch DB, Deshpande V, Stone JH. 2010. Rituximab therapy leads to rapid decline of serum IgG4 levels and prompt clinical improvement in IgG4-related systemic disease. Arthritis Rheum 62: 1755-62

14. Pillai S, Mattoo H, Cariappa A. 2011. B cells and autoimmunity. Curr Opin Immunol 23: 721-31

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Human Immunophenotyping Update

Data Normalization: How to Handle Batch Effects in Large Studies

Holden T. Maecker, PhD, Stanford University
Janet Siebert, MS, MEd, CytoAnalytics, Inc.

There is a theme among those doing translational immunology that “mice are easy, humans are hard”. One of the more subtle ways that this truism plays out is in the greater need to deal with batch effects in human studies. Partly because of genetic heterogeneity, human studies often involve more subjects than a typical animal study. Also, while animal studies can be manipulated so that all the animals reach a particular endpoint at the same time, human studies often cannot. Thus, in situations requiring fresh samples, one must perform the human assays longitudinally. For both of these reasons (number of subjects and the occasional need for real-time assays), one often faces the prospect of comparing human data across multiple “runs” or batches. Given the variability of many immune monitoring assays, this generally results in some run-to-run variability, or “batch effect”, and the consequent need for normalization of data across batches (1). Here, we will discuss some high-level considerations that should be given when designing studies for downstream normalization, and what normalization options are available for various study designs.

Standardization. The first consideration, of course, is to minimize the batch effects in the first place. It is always advisable to secure a single lot of reagents for a study, and to ensure that those reagents have a shelf life that exceeds the duration of the study. Lyophilized antibody staining cocktails can be helpful in this regard (2, 3).
It is also advisable to adhere strictly to a validated SOP, as the validation will have established the level of inter-assay variability to be expected (4, 5). As many variables as can be controlled from run to run, should be controlled.

Sample distribution. Crucial comparisons should be made within a batch, if at all possible. For example, in a longitudinal study, all time points for a given individual should be run together. In this way, each subject serves as their own control, and normalization across batches generally becomes irrelevant.

Intra-assay concerns. For some assays, there are potential concerns about the ordering of samples within a run, or the placement of samples within a plate. For example, a fluorescence signal may decrease over the time of data acquisition, or there could be differences between edge and center wells of a plate over long-term culture. In such cases, one should try to avoid a systematic bias, i.e., don’t always run the treatment group last, etc. It may also be useful to place replicate controls at two distinct locations (e.g., the beginning and end of the run) to assess the within-batch variation. Even without such concerns, replicates (as many as practical) of the same control sample should be run in each batch. This allows the degree of batch-to-batch variability to be assessed, and compared to the intra-assay variability.

Balancing batches. It is also wise, whenever possible, to design “balanced” batches with regard to the types of samples they contain. For example, if comparisons are to be made between three treatment regimens, each batch should contain a similar proportion of samples from all three treatment regimens. If it is a case-control study, cases and controls should be evenly divided among all batches. Obviously, this is not possible when assaying fresh samples in real time. But even in such “batch of one” scenarios, it is still worth trying to devise a control (such as replicates of a fixed or frozen specimen) that can be run with each new patient sample as a control.

While simple, standardization and batch design are factors that cannot be over-emphasized, since flaws in these factors may not be possible to overcome once the data is collected. After data collection, one needs to ask a series of questions before proceeding with normalization or other analysis.

To normalize or not? First, we can ask, what is the level of batch variability in a given study? By having the same control sample(s) in each plate, one can calculate a measure of variability (e.g., the coefficient of variation, CV) for each analyte across batches. If this is not obviously higher than the intra-assay CV, then there is no need to normalize. The intra-assay CV can be ascertained either from previous validation studies, or ideally, by calculating the CV of replicate controls within each batch. Alternatively, assuming batches are balanced and of a reasonable size, batch can be included as a categorical covariate in standard statistical analyses. This, or a more sophisticated conditional likelihood approach (6), provides a mechanism to test for statistical significance of batch effects, and a possible alternative to normalization.
There are some cases where assays are essentially self-normalizing. For example, immunophenotyping by flow cytometry requires individualized positivity gates to be set for each marker, specific to the batch or even to each donor. For the most part, this accounts for batch variability in the assay, and further normalization is usually not needed. Stimulated assays with functional readouts are a different situation, and normalization is more likely to be needed. However, some assays are always analyzed using an internal control, i.e., comparing longitudinal samples to baseline for each subject. If the baseline sample is always in the same batch as the compared samples, this is largely self-normalizing, as mentioned above.

Outlier batches. Whether the analysis approach can be considered “self-normalizing” or not, there are reasons to check the consistency of repeated control samples across batches. Outlier batches, which look clearly different from the others (and/or that meet statistical criteria as outliers), can then be discarded or targeted for repeat if possible.

Choice of normalization strategy. Of course, it’s often the case that, with or without outlier batches, variability between batches significantly exceeds intra-assay variability, and no self-normalizing analysis approach is possible. In these cases, normalization is indicated. The next question to ask is what kind of normalization should be used? Here, the batch design becomes important. If it is well-balanced (as described above), then one can choose between global normalization or normalization to a control sample(s). In global normalization, sample values are divided by a group value such as the median of that batch. By contrast, normalization to a control means that sample values are all divided by the corresponding control value (or mean of replicate control values) for that batch. Clearly, global normalization generally has more stability, since it is not dependent upon a single or a small number of controls. On the other hand, global normalization is highly dependent upon the balance of samples within each batch; it thus generally works best when batches are large.

Z-scores. A variation of global normalization is the calculation of a z-score. In this form of normalization, the variance of each measurement is equalized, so that all values in the batch are centered on zero. A value of 1 indicates a sample that is one standard deviation (SD) above the mean; -1 corresponds to one SD below the mean, etc. Z-scores work best with data that is normally distributed, so it may be best used after log transformation (base 10 or base 2), which tends to bring high outliers closer to the mean, and thus force typical biological data to more closely approximate a normal distribution.
For downstream analysis of multiple readouts, z scores have the advantage of creating equal dynamic range for all analytes. All the readouts will also be of comparable magnitude, whether they originally had values that were all very low or very high.

ePub Immunophenotyping Graphic

Summary. Biological assays have inherent batch effects. Batch design and assay standardization are the most important variables to consider before beginning a study. Batches should be thoughtfully balanced prior to data collection. Once data is collected, one needs to first evaluate the degree of batch variability to determine if there are outlier batches, and/or if normalization is warranted. Second, one needs to choose a normalization strategy, global or control-based. This decision should be driven by the size and balance of the batches, versus the number and reliability of control samples in each batch. See the flow chart summarizing the sequential decisions involved. Careful attention to these considerations should result in improved analysis of data collected over time.

1. Rosner, B. 2011. Fundamentals of Biostatistics, 7 ed. (M. Taylor, and D. Seibert, eds). Brooks/Cole, Boston, MA.

2. Maecker, H. T., A. Rinfret, P. D'Souza, J. Darden, E. Roig, C. Landry, P. Hayes, J. Birungi, O. Anzala, M. Garcia, A. Harari, I. Frank, R. Baydo, M. Baker, J. Holbrook, J. Ottinger, L. Lamoreaux, C. L. Epling, E. Sinclair, M. A. Suni, K. Punt, S. Calarota, S. El-Bahi, G. Alter, H. Maila, E. Kuta, J. Cox, C. Gray, M. Altfeld, N. Nougarede, J. Boyer, L. Tussey, T. Tobery, B. Bredt, M. Roederer, R. Koup, V. C. Maino, K. Weinhold, G. Pantaleo, J. Gilmour, H. Horton, and R. P. Sekaly. 2005. Standardization of cytokine flow cytometry assays. BMC Immunol. 6: 13.

3. Maecker, H. T., J. P. McCoy, and R. Nussenblatt. 2012. Standardizing immunophenotyping for the Human Immunology Project. Nat. Rev. Immunol. 1–10.

4. Horton, H., E. P. Thomas, J. A. Stucky, I. Frank, Z. Moodie, Y. Huang, Y.-L. Chiu, M. J. McElrath, and S. C. De Rosa. 2007. Optimization and validation of an 8-color intracellular cytokine staining (ICS) assay to quantify antigen-specific T cells induced by vaccination. J. Immunol. Methods 323: 39–54.

5. Maecker, H. T., J. Hassler, J. K. Payne, A. Summers, K. Comatas, M. Ghanayem, M. A. Morse, T. M. Clay, H. K. Lyerly, S. Bhatia, S. A. Ghanekar, V. C. Maino, C. Delarosa, and M. L. Disis. 2008. Precision and linearity targets for validation of an IFNγ ELISPOT, cytokine flow cytometry, and tetramer assay using CMV peptides. BMC Immunol. 9: 9.

6. Wang, M., W. D. Flanders, R. M. Bostick, and Q. Long. 2012. A conditional likelihood approach for regression analysis using biomarkers measured with batch-specific error. Statistics in medicine 31: 3896–3906.

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