Integrating population and single-cell variations in vaccine responses identifies a naturally adjuvanted human immune setpoint.

Multimodal single-cell profiling methods can capture immune cell variations unfolding over time at the molecular, cellular, and population levels. Transforming these data into biological insights remains challenging. Here, we introduce a framework to integrate variations at the human population and single-cell levels in vaccination responses. Comparing responses following AS03-adjuvanted versus unadjuvanted influenza vaccines with CITE-seq revealed AS03-specific early (day 1) response phenotypes, including a B cell signature of elevated germinal center competition. A correlated network of cell-type-specific transcriptional states defined the baseline immune status associated with high antibody responders to the unadjuvanted vaccine. Certain innate subsets in the network appeared "naturally adjuvanted," with transcriptional states resembling those induced uniquely by AS03-adjuvanted vaccination. Consistently, CD14+ monocytes from high responders at baseline had elevated phospho-signaling responses to lipopolysaccharide stimulation. Our findings link baseline immune setpoints to early vaccine responses, with positive implications for adjuvant development and immune response engineering.

Global analyses of human immune variation reveal baseline predictors of postvaccination responses.

A major goal of systems biology is the development of models that accurately predict responses to perturbation. Constructing such models requires the collection of dense measurements of system states, yet transformation of data into predictive constructs remains a challenge. To begin to model human immunity, we analyzed immune parameters in depth both at baseline and in response to influenza vaccination. Peripheral blood mononuclear cell transcriptomes, serum titers, cell subpopulation frequencies, and B cell responses were assessed in 63 individuals before and after vaccination and were used to develop a systematic framework to dissect inter- and intra-individual variation and build predictive models of postvaccination antibody responses. Strikingly, independent of age and pre-existing antibody titers, accurate models could be constructed using pre-perturbation cell populations alone, which were validated using independent baseline time points. Most of the parameters contributing to prediction delineated temporally stable baseline differences across individuals, raising the prospect of immune monitoring before intervention.

Insights into gemcitabine resistance in pancreatic cancer: association with metabolic reprogramming and TP53 pathogenicity in patient derived xenografts.

BACKGROUND: With poor prognosis and high mortality, pancreatic ductal adenocarcinoma (PDAC) is one of the most lethal malignancies. Standard of care therapies for PDAC have included gemcitabine for the past three decades, although resistance often develops within weeks of chemotherapy initiation through an array of possible mechanisms. METHODS: We reanalyzed publicly available RNA-seq gene expression profiles of 28 PDAC patient-derived xenograft (PDX) models before and after a 21-day gemcitabine treatment using our validated analysis pipeline to identify molecular markers of intrinsic and acquired resistance. RESULTS: Using normalized RNA-seq quantification measurements, we first identified oxidative phosphorylation and interferon alpha pathways as the two most enriched cancer hallmark gene sets in the baseline gene expression profile associated with intrinsic gemcitabine resistance and sensitivity, respectively. Furthermore, we discovered strong correlations between drug-induced expression changes in glycolysis and oxidative phosphorylation genes and response to gemcitabine, which suggests that these pathways may be associated with acquired gemcitabine resistance mechanisms. Thus, we developed prediction models using baseline gene expression profiles in those pathways and validated them in another dataset of 12 PDAC models from Novartis. We also developed prediction models based on drug-induced expression changes in genes from the Molecular Signatures Database (MSigDB)'s curated 50 cancer hallmark gene sets. Finally, pathogenic TP53 mutations correlated with treatment resistance. CONCLUSION: Our results demonstrate that concurrent upregulation of both glycolysis and oxidative phosphorylation pathways occurs in vivo in PDAC PDXs following gemcitabine treatment and that pathogenic TP53 status had association with gemcitabine resistance in these models. Our findings may elucidate the molecular basis for gemcitabine resistance and provide insights for effective drug combination in PDAC chemotherapy.

Impaired B cell immunity in acute myeloid leukemia patients after chemotherapy.

BACKGROUND: Changes in adaptive immune cells after chemotherapy in adult acute myeloid leukemia (AML) may have implications for the success of immunotherapy. This study was designed to determine the functional capacity of the immune system in adult patients with AML who have completed chemotherapy and are potential candidates for immunotherapy. METHODS: We used the response to seasonal influenza vaccination as a surrogate for the robustness of the immune system in 10 AML patients in a complete remission post-chemotherapy and performed genetic, phenotypic, and functional characterization of adaptive immune cell subsets. RESULTS: Only 2 patients generated protective titers in response to vaccination, and a majority of patients had abnormal frequencies of transitional and memory B-cells. B-cell receptor sequencing showed a B-cell repertoire with little evidence of somatic hypermutation in most patients. Conversely, frequencies of T-cell populations were similar to those seen in healthy controls, and cytotoxic T-cells demonstrated antigen-specific activity after vaccination. Effector T-cells had increased PD-1 expression in AML patients least removed from chemotherapy. CONCLUSION: Our results suggest that while some aspects of cellular immunity recover quickly, humoral immunity is incompletely reconstituted in the year following intensive cytotoxic chemotherapy for AML. The observed B-cell abnormalities may explain the poor response to vaccination often seen in AML patients after chemotherapy. Furthermore, the uncoupled recovery of B-cell and T-cell immunity and increased PD-1 expression shortly after chemotherapy might have implications for the success of several modalities of immunotherapy.

Epigenetic-mediated dysfunction of the bone morphogenetic protein pathway inhibits differentiation of glioblastoma-initiating cells.

Despite similarities between tumor-initiating cells with stem-like properties (TICs) and normal neural stem cells, we hypothesized that there may be differences in their differentiation potentials. We now demonstrate that both bone morphogenetic protein (BMP)-mediated and ciliary neurotrophic factor (CNTF)-mediated Jak/STAT-dependent astroglial differentiation is impaired due to EZH2-dependent epigenetic silencing of BMP receptor 1B (BMPR1B) in a subset of glioblastoma TICs. Forced expression of BMPR1B either by transgene expression or demethylation of the promoter restores their differentiation capabilities and induces loss of their tumorigenicity. We propose that deregulation of the BMP developmental pathway in a subset of glioblastoma TICs contributes to their tumorigenicity both by desensitizing TICs to normal differentiation cues and by converting otherwise cytostatic signals to proproliferative signals.

Ultra-low dose interleukin-2 promotes immune-modulating function of regulatory T cells and natural killer cells in healthy volunteers.

Low-dose interleukin-2 (IL-2) expands regulatory T cells (Tregs) and natural killer (NK) cells after stem cell transplantation (SCT) and may reduce graft-versus-host disease (GVHD). We hypothesized that ultra-low dose (ULD) IL-2 could serve as an immune-modulating agent for stem cell donors to prevent GVHD following SCT. However, the safety, dose level, and immune signatures of ULD IL-2 in immune-competent healthy subjects remain unknown. Here, we have characterized the phenotype and function of Tregs and NK cells as well as the gene expression and cytokine profiles of 21 healthy volunteers receiving 50,000 to 200,000 units/m(2)/day IL-2 for 5 days. ULD IL-2 was well tolerated and induced a significant increase in the frequency of Tregs with increased suppressive function. There was a marked expansion of CD56(bright) NK cells with enhanced interferon-γ (IFN-γ) production. Serum cytokine profiling demonstrated increase of IFN-γ induced protein 10 (IP-10). Gene expression analysis revealed significant changes in a highly restricted set of genes, including FOXP3, IL-2RA, and CISH. This is the first study to evaluate global immune-modulating function of ULD IL-2 in healthy subjects and to support the future studies administrating ULD IL-2 to stem cell donors.

Neuronal and glioma-derived stem cell factor induces angiogenesis within the brain.

Stem cell factor (SCF) is overexpressed by neurons following brain injury as well as by glioma cells; however, its role in gliomagenesis remains unclear. Here, we demonstrate that SCF directly activates brain microvascular endothelial cells (ECs) in vitro and induces a potent angiogenic response in vivo. Primary human gliomas express SCF in a grade-dependent manner and induce normal neurons to express SCF in brain regions infiltrated by glioma cells, areas that colocalize with prominent angiogenesis. Downregulation of SCF inhibits tumor-mediated angiogenesis and glioma growth in vivo, whereas overexpression of SCF is associated with shorter survival in patients with malignant gliomas. Thus, the SCF/c-Kit pathway plays an important role in tumor- and normal host cell-induced angiogenesis within the brain.

Tumor stem cells derived from glioblastomas cultured in bFGF and EGF more closely mirror the phenotype and genotype of primary tumors than do serum-cultured cell lines.

The concept of tumor stem cells (TSCs) provides a new paradigm for understanding tumor biology, although it remains unclear whether TSCs will prove to be a more robust model than traditional cancer cell lines. We demonstrate marked phenotypic and genotypic differences between primary human tumor-derived TSCs and their matched glioma cell lines. Unlike the matched, traditionally grown tumor cell lines, TSCs derived directly from primary glioblastomas harbor extensive similarities to normal neural stem cells and recapitulate the genotype, gene expression patterns, and in vivo biology of human glioblastomas. These findings suggest that TSCs may be a more reliable model than many commonly utilized cancer cell lines for understanding the biology of primary human tumors.

A unified metric of human immune health.

Immunological health has been challenging to characterize but could be defined as the absence of immune pathology. While shared features of some immune diseases and the concept of immunologic resilience based on age-independent adaptation to antigenic stimulation have been developed, general metrics of immune health and its utility for assessing clinically healthy individuals remain ill defined. Here we integrated transcriptomics, serum protein, peripheral immune cell frequency and clinical data from 228 patients with 22 monogenic conditions impacting key immunological pathways together with 42 age- and sex-matched healthy controls. Despite the high penetrance of monogenic lesions, differences between individuals in diverse immune parameters tended to dominate over those attributable to disease conditions or medication use. Unsupervised or supervised machine learning independently identified a score that distinguished healthy participants from patients with monogenic diseases, thus suggesting a quantitative immune health metric (IHM). In ten independent datasets, the IHM discriminated healthy from polygenic autoimmune and inflammatory disease states, marked aging in clinically healthy individuals, tracked disease activities and treatment responses in both immunological and nonimmunological diseases, and predicted age-dependent antibody responses to immunizations with different vaccines. This discriminatory power goes beyond that of the classical inflammatory biomarkers C-reactive protein and interleukin-6. Thus, deviations from health in diverse conditions, including aging, have shared systemic immune consequences, and we provide a web platform for calculating the IHM for other datasets, which could empower precision medicine.

Sex and prior exposure jointly shape innate immune responses to a live herpesvirus vaccine.

Background: Both sex and prior exposure to pathogens are known to influence responses to immune challenges, but their combined effects are not well established in humans, particularly in early innate responses critical for shaping subsequent outcomes. Methods: We employed systems immunology approaches to study responses to a replication-defective, herpes simplex virus (HSV) 2 vaccine in men and women either naive or previously exposed to HSV. Results: Blood transcriptomic and cell population profiling showed substantial changes on day 1 after vaccination, but the responses depended on sex and whether the vaccinee was naive or previously exposed to HSV. The magnitude of early transcriptional responses was greatest in HSV naive women where type I interferon (IFN) signatures were prominent and associated negatively with vaccine-induced neutralizing antibody titers, suggesting that a strong early antiviral response reduced the uptake of this replication-defective virus vaccine. While HSV seronegative vaccine recipients had upregulation of gene sets in type I IFN (IFN-α/ß) responses, HSV2 seropositive vaccine recipients tended to have responses focused more on type II IFN (IFN-γ) genes. Conclusions: These results together show that prior exposure and sex interact to shape early innate responses that then impact subsequent adaptive immune phenotypes. Funding: Intramural Research Program of the NIH, the National Institute of Allergy and Infectious Diseases, and other institutes supporting the Trans-NIH Center for Human Immunology, Autoimmunity, and Inflammation. The vaccine trial was supported through a clinical trial agreement between the National Institute of Allergy and Infectious Diseases and Sanofi Pasteur. Clinical trial number: NCT01915212.

Multiscale integration of human and single-cell variations reveals unadjuvanted vaccine high responders are naturally adjuvanted.

Advances in multimodal single cell analysis can empower high-resolution dissection of human vaccination responses. The resulting data capture multiple layers of biological variations, including molecular and cellular states, vaccine formulations, inter- and intra-subject differences, and responses unfolding over time. Transforming such data into biological insight remains a major challenge. Here we present a systematic framework applied to multimodal single cell data obtained before and after influenza vaccination without adjuvants or pandemic H5N1 vaccination with the AS03 adjuvant. Our approach pinpoints responses shared across or unique to specific cell types and identifies adjuvant specific signatures, including pro-survival transcriptional states in B lymphocytes that emerged one day after vaccination. We also reveal that high antibody responders to the unadjuvanted vaccine have a distinct baseline involving a rewired network of cell type specific transcriptional states. Remarkably, the status of certain innate immune cells in this network in high responders of the unadjuvanted vaccine appear "naturally adjuvanted": they resemble phenotypes induced early in the same cells only by vaccination with AS03. Furthermore, these cell subsets have elevated frequency in the blood at baseline and increased cell-intrinsic phospho-signaling responses after LPS stimulation ex vivo in high compared to low responders. Our findings identify how variation in the status of multiple immune cell types at baseline may drive robust differences in innate and adaptive responses to vaccination and thus open new avenues for vaccine development and immune response engineering in humans.

Multiomics integration of 22 immune-mediated monogenic diseases reveals an emergent axis of human immune health.

Monogenic diseases are often studied in isolation due to their rarity. Here we utilize multiomics to assess 22 monogenic immune-mediated conditions with age- and sex-matched healthy controls. Despite clearly detectable disease-specific and "pan-disease" signatures, individuals possess stable personal immune states over time. Temporally stable differences among subjects tend to dominate over differences attributable to disease conditions or medication use. Unsupervised principal variation analysis of personal immune states and machine learning classification distinguishing between healthy controls and patients converge to a metric of immune health (IHM). The IHM discriminates healthy from multiple polygenic autoimmune and inflammatory disease states in independent cohorts, marks healthy aging, and is a pre-vaccination predictor of antibody responses to influenza vaccination in the elderly. We identified easy-to-measure circulating protein biomarker surrogates of the IHM that capture immune health variations beyond age. Our work provides a conceptual framework and biomarkers for defining and measuring human immune health.

Construct and Compare Gene Coexpression Networks with DAPfinder and DAPview.

BACKGROUND: DAPfinder and DAPview are novel BRB-ArrayTools plug-ins to construct gene coexpression networks and identify significant differences in pairwise gene-gene coexpression between two phenotypes. RESULTS: Each significant difference in gene-gene association represents a Differentially Associated Pair (DAP). Our tools include several choices of filtering methods, gene-gene association metrics, statistical testing methods and multiple comparison adjustments. Network results are easily displayed in Cytoscape. Analyses of glioma experiments and microarray simulations demonstrate the utility of these tools. CONCLUSIONS: DAPfinder is a new friendly-user tool for reconstruction and comparison of biological networks.

Phase 1 double-blind randomized safety trial of the Janus kinase inhibitor tofacitinib in systemic lupus erythematosus.

Increased risk of premature cardiovascular disease (CVD) is well recognized in systemic lupus erythematosus (SLE). Aberrant type I-Interferon (IFN)-neutrophil interactions contribute to this enhanced CVD risk. In lupus animal models, the Janus kinase (JAK) inhibitor tofacitinib improves clinical features, immune dysregulation and vascular dysfunction. We conducted a randomized, double-blind, placebo-controlled clinical trial of tofacitinib in SLE subjects (ClinicalTrials.gov NCT02535689). In this study, 30 subjects are randomized to tofacitinib (5 mg twice daily) or placebo in 2:1 block. The primary outcome of this study is safety and tolerability of tofacitinib. The secondary outcomes include clinical response and mechanistic studies. The tofacitinib is found to be safe in SLE meeting study's primary endpoint. We also show that tofacitinib improves cardiometabolic and immunologic parameters associated with the premature atherosclerosis in SLE. Tofacitinib improves high-density lipoprotein cholesterol levels (p = 0.0006, CI 95%: 4.12, 13.32) and particle number (p = 0.0008, CI 95%: 1.58, 5.33); lecithin: cholesterol acyltransferase concentration (p = 0.024, CI 95%: 1.1, -26.5), cholesterol efflux capacity (p = 0.08, CI 95%: -0.01, 0.24), improvements in arterial stiffness and endothelium-dependent vasorelaxation and decrease in type I IFN gene signature, low-density granulocytes and circulating NETs. Some of these improvements are more robust in subjects with STAT4 risk allele.

Rembrandt: helping personalized medicine become a reality through integrative translational research.

Finding better therapies for the treatment of brain tumors is hampered by the lack of consistently obtained molecular data in a large sample set and the ability to integrate biomedical data from disparate sources enabling translation of therapies from bench to bedside. Hence, a critical factor in the advancement of biomedical research and clinical translation is the ease with which data can be integrated, redistributed, and analyzed both within and across functional domains. Novel biomedical informatics infrastructure and tools are essential for developing individualized patient treatment based on the specific genomic signatures in each patient's tumor. Here, we present Repository of Molecular Brain Neoplasia Data (Rembrandt), a cancer clinical genomics database and a Web-based data mining and analysis platform aimed at facilitating discovery by connecting the dots between clinical information and genomic characterization data. To date, Rembrandt contains data generated through the Glioma Molecular Diagnostic Initiative from 874 glioma specimens comprising approximately 566 gene expression arrays, 834 copy number arrays, and 13,472 clinical phenotype data points. Data can be queried and visualized for a selected gene across all data platforms or for multiple genes in a selected platform. Additionally, gene sets can be limited to clinically important annotations including secreted, kinase, membrane, and known gene-anomaly pairs to facilitate the discovery of novel biomarkers and therapeutic targets. We believe that Rembrandt represents a prototype of how high-throughput genomic and clinical data can be integrated in a way that will allow expeditious and efficient translation of laboratory discoveries to the clinic.

GliomaPredict: a clinically useful tool for assigning glioma patients to specific molecular subtypes.

BACKGROUND: Advances in generating genome-wide gene expression data have accelerated the development of molecular-based tumor classification systems. Tools that allow the translation of such molecular classification schemas from research into clinical applications are still missing in the emerging era of personalized medicine. RESULTS: We developed GliomaPredict as a computational tool that allows the fast and reliable classification of glioma patients into one of six previously published stratified subtypes based on sets of extensively validated classifiers derived from hundreds of glioma transcriptomic profiles. Our tool utilizes a principle component analysis (PCA)-based approach to generate a visual representation of the analyses, quantifies the confidence of the underlying subtype assessment and presents results as a printable PDF file. GliomaPredict tool is implemented as a plugin application for the widely-used GenePattern framework. CONCLUSIONS: GliomaPredict provides a user-friendly, clinically applicable novel platform for instantly assigning gene expression-based subtype in patients with gliomas thereby aiding in clinical trial design and therapeutic decision-making. Implemented as a user-friendly diagnostic tool, we expect that in time GliomaPredict, and tools like it, will become routinely used in translational/clinical research and in the clinical care of patients with gliomas.

Multimodal immune phenotyping of maternal peripheral blood in normal human pregnancy.

Changes in maternal immunity during pregnancy can result in an altered immune state, and as a natural perturbation, this provides an opportunity to understand functional interactions of the immune system in vivo. We report characterization of maternal peripheral immune phenotypes for 33 longitudinally sampled normal pregnancies, using clinical measurements of complete blood counts and major immune cell populations, as well as high parameter flow cytometry for 30 leukocyte antigens characterizing 79 cell populations, and monitoring of 1305 serum proteins using the SomaLogic platform. Cellular analyses characterized transient changes in T cell polarization and more persistent alterations in T and B cell subset frequencies and activation. Serum proteomic analysis identified a potentially novel set of 7 proteins that are predictive of gestational age: DDR1, PLAU, MRC1, ACP5, ROBO2, IGF2R, and GNS. We further show that gestational age can be predicted from the parameters obtained by complete blood count tests and clinical flow cytometry characterizing 5 major immune cell populations. Inferring gestational age from this routine clinical phenotyping data could be useful in resource-limited settings that lack obstetric ultrasound. Overall, both the cellular and proteomic analyses validate previously reported phenotypic immunological changes of pregnancy and uncover potentially new alterations and predictive markers.

Broad immune activation underlies shared set point signatures for vaccine responsiveness in healthy individuals and disease activity in patients with lupus.

Responses to vaccination and to diseases vary widely across individuals, which may be partly due to baseline immune variations. Identifying such baseline predictors of immune responses and their biological basis is of broad interest, given their potential importance for cancer immunotherapy, disease outcomes, vaccination and infection responses. Here we uncover baseline blood transcriptional signatures predictive of antibody responses to both influenza and yellow fever vaccinations in healthy subjects. These same signatures evaluated at clinical quiescence are correlated with disease activity in patients with systemic lupus erythematosus with plasmablast-associated flares. CITE-seq profiling of 82 surface proteins and transcriptomes of 53,201 single cells from healthy high and low influenza vaccination responders revealed that our signatures reflect the extent of activation in a plasmacytoid dendritic cell-type I IFN-T/B lymphocyte network. Our findings raise the prospect that modulating such immune baseline states may improve vaccine responsiveness and mitigate undesirable autoimmune disease activity.

Genomic changes and gene expression profiles reveal that established glioma cell lines are poorly representative of primary human gliomas.

Genetic aberrations, such as gene amplification, deletions, and loss of heterozygosity, are hallmarks of cancer and are thought to be major contributors to the neoplastic process. Established cancer cell lines have been the primary in vitro and in vivo models for cancer for more than 2 decades; however, few such cell lines have been extensively characterized at the genomic level. Here, we present a high-resolution genome-wide chromosomal alteration and gene expression analyses of five of the most commonly used glioma cell lines and compare the findings with those observed in 83 primary human gliomas. Although genomic alterations known to occur in primary tumors were identified in the cell lines, we also observed several novel recurrent aberrations in the glioma cell lines that are not frequently represented in primary tumors. Additionally, a global gene expression cluster distinct from primary tumors was identified in the glioma cell lines. Our results indicate that established cell lines are generally a poor representation of primary tumor biology, presenting a host of genomic and gene expression changes not observed in primary tissues, although some discrete features of glioma biology were conserved in the established cell lines. Refined maps of genetic alterations and transcriptional divergence from the original tumor type, such as the one presented here, may help serve as a guideline for a more biologically rational and clinically relevant selection of the most appropriate glioma model for a given experiment.

Effects of rosuvastatin on the immune system in healthy volunteers with normal serum cholesterol.

BACKGROUNDHMG-CoA reductase inhibitors (statins) are prescribed to millions of people. Statins are antiinflammatory independent of their cholesterol-reducing effects. To date, most reports on the immune effects of statins have assayed a narrow array of variables and have focused on cell lines, rodent models, or patient cohorts. We sought to define the effect of rosuvastatin on the "immunome" of healthy, normocholesterolemic subjects.METHODSWe conducted a prospective study of rosuvastatin (20 mg/d × 28 days) in 18 statin-naive adults with LDL cholesterol <130 mg/dL. A panel of >180 immune/biochemical/endocrinologic variables was measured at baseline and on days 14, 28, and 42 (14 days after drug withdrawal). Drug effect was evaluated using linear mixed-effects models. Potential interactions between drug and baseline high-sensitivity C-reactive protein (hsCRP) were evaluated.RESULTSA wide array of immune measures changed (nominal P < 0.05) during rosuvastatin treatment, although the changes were modest in magnitude, and few met an FDR of 0.05. Among changes noted were a concordant increase in proinflammatory cytokines (IFN-γ, IL-1ß, IL-5, IL-6, and TNF-α) and peripheral blood neutrophil frequency, and a decline in activated Treg frequency. Several drug effects were significantly modified by baseline hsCRP, and some did not resolve after drug withdrawal. Among other unexpected rosuvastatin effects were changes in erythrocyte indices, glucose-regulatory hormones, CD8+ T cells, and haptoglobin.CONCLUSIONRosuvastatin induces modest changes in immunologic and metabolic measures in normocholesterolemic subjects, with several effects dependent on baseline CRP. Future, larger studies are warranted to validate these changes and their physiological significance.TRIAL REGISTRATIONClinicalTrials.gov NCT01200836.FUNDINGThis research was supported by the Intramural Research Program of the NIH, National Institute of Environmental Health Sciences (Z01 ES102005), and the trans-NIH Center for Human Immunology.