Project description:Immune cell metabolism is dynamically regulated in parallel with the substantial changes in cellular function that accompany immune cell activation. While these changes in metabolism are important for facilitating the increased energetic and biosynthetic demands of activated cells, immune cell metabolism also has direct roles in controlling the functions of immune cells and shaping the immune response. A theme is emerging wherein nutrients, metabolic enzymes, and metabolites can act as an extension of the established immune signal transduction pathways, thereby adding an extra layer of complexity to the regulation of immunity. This Review will outline the metabolic configurations adopted by different immune cell subsets, describe the emerging roles for metabolic enzymes and metabolites in the control of immune cell function, and discuss the therapeutic implications of this emerging immune regulatory axis.
Project description:Tumour-specific mutations are ideal targets for cancer immunotherapy as they lack expression in healthy tissues and can potentially be recognized as neo-antigens by the mature T-cell repertoire. Their systematic targeting by vaccine approaches, however, has been hampered by the fact that every patient's tumour possesses a unique set of mutations ('the mutanome') that must first be identified. Recently, we proposed a personalized immunotherapy approach to target the full spectrum of a patient's individual tumour-specific mutations. Here we show in three independent murine tumour models that a considerable fraction of non-synonymous cancer mutations is immunogenic and that, unexpectedly, the majority of the immunogenic mutanome is recognized by CD4(+) T cells. Vaccination with such CD4(+) immunogenic mutations confers strong antitumour activity. Encouraged by these findings, we established a process by which mutations identified by exome sequencing could be selected as vaccine targets solely through bioinformatic prioritization on the basis of their expression levels and major histocompatibility complex (MHC) class II-binding capacity for rapid production as synthetic poly-neo-epitope messenger RNA vaccines. We show that vaccination with such polytope mRNA vaccines induces potent tumour control and complete rejection of established aggressively growing tumours in mice. Moreover, we demonstrate that CD4(+) T cell neo-epitope vaccination reshapes the tumour microenvironment and induces cytotoxic T lymphocyte responses against an independent immunodominant antigen in mice, indicating orchestration of antigen spread. Finally, we demonstrate an abundance of mutations predicted to bind to MHC class II in human cancers as well by employing the same predictive algorithm on corresponding human cancer types. Thus, the tailored immunotherapy approach introduced here may be regarded as a universally applicable blueprint for comprehensive exploitation of the substantial neo-epitope target repertoire of cancers, enabling the effective targeting of every patient's tumour with vaccines produced 'just in time'.
Project description:Neuromyelitis optica spectrum disorder (NMO/SD) and its clinical variants have at their core the loss of immune tolerance to aquaporin-4 and perhaps other autoantigens. The characteristic phenotype is disruption of astrocyte function and demyelination of spinal cord, optic nerves, and particular brain regions. In this second of a 2-part article, we present further perspectives regarding the pathogenesis of NMO/SD and how this disease might be amenable to emerging technologies aimed at restoring immune tolerance to disease-implicated self-antigens. NMO/SD appears to be particularly well-suited for these strategies since aquaporin-4 has already been identified as the dominant autoantigen. The recent technical advances in reintroducing immune tolerance in experimental models of disease as well as in humans should encourage quantum leaps in this area that may prove productive for novel therapy. In this part of the article series, the potential for regulatory T and B cells is brought into focus, as are new approaches to oral tolerization. Finally, a roadmap is provided to help identify potential issues in clinical development and guide applications in tolerization therapy to solving NMO/SD through the use of emerging technologies. Each of these perspectives is intended to shine new light on potential cures for NMO/SD and other autoimmune diseases, while sparing normal host defense mechanisms.
Project description:During music listening, humans routinely acquire the regularities of the acoustic sequences and use them to anticipate and interpret the ongoing melody. Specifically, in line with this predictive framework, it is thought that brain responses during such listening reflect a comparison between the bottom-up sensory responses and top-down prediction signals generated by an internal model that embodies the music exposure and expectations of the listener. To attain a clear view of these predictive responses, previous work has eliminated the sensory inputs by inserting artificial silences (or sound omissions) that leave behind only the corresponding predictions of the thwarted expectations. Here, we demonstrate a new alternate approach in which we decode the predictive electroencephalography (EEG) responses to the silent intervals that are naturally interspersed within the music. We did this as participants (experiment 1, 20 participants, 10 female; experiment 2, 21 participants, 6 female) listened or imagined Bach piano melodies. Prediction signals were quantified and assessed via a computational model of the melodic structure of the music and were shown to exhibit the same response characteristics when measured during listening or imagining. These include an inverted polarity for both silence and imagined responses relative to listening, as well as response magnitude modulations that precisely reflect the expectations of notes and silences in both listening and imagery conditions. These findings therefore provide a unifying view that links results from many previous paradigms, including omission reactions and the expectation modulation of sensory responses, all in the context of naturalistic music listening.SIGNIFICANCE STATEMENT Music perception depends on our ability to learn and detect melodic structures. It has been suggested that our brain does so by actively predicting upcoming music notes, a process inducing instantaneous neural responses as the music confronts these expectations. Here, we studied this prediction process using EEGs recorded while participants listen to and imagine Bach melodies. Specifically, we examined neural signals during the ubiquitous musical pauses (or silent intervals) in a music stream and analyzed them in contrast to the imagery responses. We find that imagined predictive responses are routinely co-opted during ongoing music listening. These conclusions are revealed by a new paradigm using listening and imagery of naturalistic melodies.
Project description:Biomaterials employed to raise therapeutic immune responses have become a complex and active field. Historically, vaccines have been developed primarily to fight infectious diseases, but recent years have seen the development of immunologically active biomaterials towards an expanding list of non-infectious diseases and conditions including inflammation, autoimmunity, wounds, cancer, and others. This review structures its discussion of these approaches around a progression from single-target strategies to those that engage increasingly complex and multifactorial immune responses. First, the targeting of specific individual cytokines is discussed, both in terms of delivering the cytokines or blocking agents, and in terms of active immunotherapies that raise neutralizing immune responses against such single cytokine targets. Next, non-biological complex drugs such as randomized polyamino acid copolymers are discussed in terms of their ability to raise multiple different therapeutic immune responses, particularly in the context of autoimmunity. Last, biologically derived matrices and materials are discussed in terms of their ability to raise complex immune responses in the context of tissue repair. Collectively, these examples reflect the tremendous diversity of existing approaches and the breadth of opportunities that remain for generating therapeutic immune responses using biomaterials.
Project description:PurposeCytomegalovirus (CMV) antigens occur in glioblastoma but not in normal brains, making them desirable immunologic targets.Patients and methodsHighly functional autologous polyclonal CMV pp65-specific T cells from patients with glioblastoma were numerically expanded under good manufacturing practice compliant conditions and administered after 3 weeks of lymphodepleting dose-dense temozolomide (100 mg/m2) treatment. The phase I component used a 3+3 design, ascending through four dose levels (5 × 106-1 × 108 cells). Treatment occurred every 6 weeks for four cycles. In vivo persistence and effector function of CMV-specific T cells was determined by dextramer staining and multiparameter flow cytometry in serially sampled peripheral blood and in the tumor microenvironment.ResultsWe screened 65 patients; 41 were seropositive for CMV; 25 underwent leukapheresis; and 20 completed ≥1 cycle. No dose-limiting toxicities were observed. Radiographic response was complete in 1 patient, partial in 2. Median progression-free survival (PFS) time was 1.3 months [95% confidence interval (CI), 0-8.3 months]; 6-month PFS was 19% (95% CI, 7%-52%); and median overall survival time was 12 months (95% CI, 6 months to not reached). Repeated infusions of CMV-T cells paralleled significant increases in circulating CMV+ CD8+ T cells, but cytokine production showing effector activity was suppressed, especially from T cells obtained directly from glioblastomas.ConclusionsAdoptive infusion of CMV-specific T cells after lymphodepletion with dose-dense temozolomide was well tolerated. But apparently CMV seropositivity does not guarantee tumor susceptibility to CMV-specific T cells, suggesting heterogeneity in CMV antigen expression. Moreover, effector function of these T cells was attenuated, indicating a requirement for further T-cell modulation to prevent their dysfunction before conducting large-scale clinical studies.
Project description:Mouse models of human diseases are created both to understand the pathogenesis of the disorders and to find successful therapies for them. This work is the second part in a series of reviews of mouse models of polyglutamine (polyQ) hereditary disorders and focuses on in vivo experimental therapeutic approaches. Like part I of the polyQ mouse model review, this work is supplemented with a table that contains data from experimental studies of therapeutic approaches in polyQ mouse models. The aim of this review was to characterize the benefits and outcomes of various therapeutic strategies in mouse models. We examine whether the therapeutic strategies are specific to a single disease or are applicable to more than one polyQ disorder in mouse models. In addition, we discuss the suitability of mouse models in therapeutic approaches. Although the majority of therapeutic studies were performed in mouse models of Huntington disease, similar strategies were also used in other disease models.
Project description:We describe a novel experiment that we conducted with the Drug Interaction Knowledge-base (DIKB) to determine which combinations of evidence enable a rule-based theory of metabolic drug-drug interactions to make the most optimal set of predictions. The focus of the experiment was a group of 16 drugs including six members of the HMG-CoA-reductase inhibitor family (statins). The experiment helped identify evidence-use strategies that enabled the DIKB to predict significantly more interactions present in a validation set than the most rigorous strategy developed by drug experts with no loss of accuracy. The best-performing strategies included evidence types that would normally be of lesser predictive value but that are often more accessible than more rigorous types. Our experimental methods represent a new approach to leveraging the available scientific evidence within a domain where important evidence is often missing or of questionable value for supporting important assertions.