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.

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.

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.

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.

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.

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.

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.

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.

The Immunome in Two Inherited Forms of Pulmonary Fibrosis.

The immunome (immune cell phenotype, gene expression, and serum cytokines profiling) in pulmonary fibrosis is incompletely defined. Studies focusing on inherited forms of pulmonary fibrosis provide insights into mechanisms of fibrotic lung disease in general. To define the cellular and molecular immunologic phenotype in peripheral blood, high-dimensional flow cytometry and large-scale gene expression of peripheral blood mononuclear cells and serum proteomic multiplex analyses were performed and compared in a cohort with familial pulmonary fibrosis (FPF), an autosomal dominant disorder with incomplete penetrance; Hermansky-Pudlak syndrome pulmonary fibrosis (HPSPF), a rare autosomal recessive disorder; and their unaffected relatives. Our results showed high peripheral blood concentrations of activated central memory helper cells in patients with FPF. Proportions of CD38+ memory CD27- B-cells, IgA+ memory CD27+ B-cells, IgM+ and IgD+ B-cells, and CD39+ T helper cells were increased whereas those of CD39- T helper cells were reduced in patients affected with either familial or HPSPF. Gene expression and serum proteomic analyses revealed enrichment of upregulated genes associated with mitosis and cell cycle control in circulating mononuclear cells as well as altered levels of several analytes, including leptin, cytokines, and growth factors. In conclusion, dysregulation of the extra-pulmonary immunome is a phenotypic feature of FPF or HPSPF. Further studies investigating the blood immunome are indicated to determine the role of immune system dysregulation in the pathogenesis of pulmonary fibrosis. Clinical Trial Registration: www.ClinicalTrials.gov, identifiers NCT00968084, NCT01200823, NCT00001456, and NCT00084305.

Assessment of Variability in the SOMAscan Assay.

SOMAscan is an aptamer-based proteomics assay capable of measuring 1,305 human protein analytes in serum, plasma, and other biological matrices with high sensitivity and specificity. In this work, we present a comprehensive meta-analysis of performance based on multiple serum and plasma runs using the current 1.3 k assay, as well as the previous 1.1 k version. We discuss normalization procedures and examine different strategies to minimize intra- and interplate nuisance effects. We implement a meta-analysis based on calibrator samples to characterize the coefficient of variation and signal-over-background intensity of each protein analyte. By incorporating coefficient of variation estimates into a theoretical model of statistical variability, we also provide a framework to enable rigorous statistical tests of significance in intervention studies and clinical trials, as well as quality control within and across laboratories. Furthermore, we investigate the stability of healthy subject baselines and determine the set of analytes that exhibit biologically stable baselines after technical variability is factored in. This work is accompanied by an interactive web-based tool, an initiative with the potential to become the cornerstone of a regularly updated, high quality repository with data sharing, reproducibility, and reusability as ultimate goals.

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.

Web Tool for Navigating and Plotting SomaLogic ADAT Files.

SOMAscan™ is a complex proteomic platform created by SomaLogic. Experimental data resulting from the assay is provided by SomaLogic in a proprietary text-based format called ADAT. This manuscript describes a user-friendly point and click open source, platform-independent software tool designed to be used for navigating and plotting data from an ADAT file. This tool was used either alone or in conjunction with other tools as a first pass analysis of the data on several different on-going research projects. We have seen a need from our experience for a web interface to the ADAT file so that users can navigate, generate plots, perform QC and conduct statistical analysis on their own data in a point and click manner. After several rounds of interacting with biologists and their requirements with respect to data analysis, we present an online interactive Shiny Web Tool for Navigating and Plotting data contained within the ADAT file. Extensive video tutorials, example data, the tool and the source code are available online.

Effects of Systemically Administered Hydrocortisone on the Human Immunome.

Corticosteroids have been used for decades to modulate inflammation therapeutically, yet there is a paucity of data on their effects in humans. We examined the changes in cellular and molecular immune system parameters, or "immunome", in healthy humans after systemic corticosteroid administration. We used multiplexed techniques to query the immunome in 20 volunteers at baseline, and after intravenous hydrocortisone (HC) administered at moderate (250 mg) and low (50 mg) doses, to provide insight into how corticosteroids exert their effects. We performed comprehensive phenotyping of 120 lymphocyte subsets by high dimensional flow cytometry, and observed a decline in circulating specific B and T cell subsets, which reached their nadir 4-8 hours after administration of HC. However, B and T cells rebounded above baseline 24 hours after HC infusion, while NK cell numbers remained stable. Whole transcriptome profiling revealed down regulation of NF-κB signaling, apoptosis, and cell death signaling transcripts that preceded lymphocyte population changes, with activation of NK cell and glucocorticoid receptor signaling transcripts. Our study is the first to systematically characterize the effects of corticosteroids on the human immunome, and we demonstrate that HC exerts differential effects on B and T lymphocytes and natural killer cells in humans.

Identification of molecular pathways facilitating glioma cell invasion in situ.

Gliomas are mostly incurable secondary to their diffuse infiltrative nature. Thus, specific therapeutic targeting of invasive glioma cells is an attractive concept. As cells exit the tumor mass and infiltrate brain parenchyma, they closely interact with a changing micro-environmental landscape that sustains tumor cell invasion. In this study, we used a unique microarray profiling approach on a human glioma stem cell (GSC) xenograft model to explore gene expression changes in situ in Invading Glioma Cells (IGCs) compared to tumor core, as well as changes in host cells residing within the infiltrated microenvironment relative to the unaffected cortex. IGCs were found to have reduced expression of genes within the extracellular matrix compartment, and genes involved in cell adhesion, cell polarity and epithelial to mesenchymal transition (EMT) processes. The infiltrated microenvironment showed activation of wound repair and tissue remodeling networks. We confirmed by protein analysis the downregulation of EMT and polarity related genes such as CD44 and PARD3 in IGCs, and EFNB3, a tissue-remodeling agent enriched at the infiltrated microenvironment. OLIG2, a proliferation regulator and glioma progenitor cell marker upregulated in IGCs was found to function in enhancing migration and stemness of GSCs. Overall, our results unveiled a more comprehensive picture of the complex and dynamic cell autonomous and tumor-host interactive pathways of glioma invasion than has been previously demonstrated. This suggests targeting of multiple pathways at the junction of invading tumor and microenvironment as a viable option for glioma therapy.

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.

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.

Age-specific signatures of glioblastoma at the genomic, genetic, and epigenetic levels.

Age is a powerful predictor of survival in glioblastoma multiforme (GBM) yet the biological basis for the difference in clinical outcome is mostly unknown. Discovering genes and pathways that would explain age-specific survival difference could generate opportunities for novel therapeutics for GBM. Here we have integrated gene expression, exon expression, microRNA expression, copy number alteration, SNP, whole exome sequence, and DNA methylation data sets of a cohort of GBM patients in The Cancer Genome Atlas (TCGA) project to discover age-specific signatures at the transcriptional, genetic, and epigenetic levels and validated our findings on the REMBRANDT data set. We found major age-specific signatures at all levels including age-specific hypermethylation in polycomb group protein target genes and the upregulation of angiogenesis-related genes in older GBMs. These age-specific differences in GBM, which are independent of molecular subtypes, may in part explain the preferential effects of anti-angiogenic agents in older GBM and pave the way to a better understanding of the unique biology and clinical behavior of older versus younger GBMs.