Immune response in silico (IRIS): immune-specific genes identified from a compendium of microarray expression data

Gene Expression Signatures Characterized by Longitudinal Stability and Interindividual Variability Delineate Baseline Phenotypic Groups with Distinct Responses to Immune Stimulation

Human immunity exhibits remarkable heterogeneity among individuals, which engenders variable responses to immune perturbations in human populations. Population studies reveal that, in addition to interindividual heterogeneity, systemic immune signatures display longitudinal stability within individuals, and these signatures may reliably dictate how given individuals respond to immune perturbations. We hypothesize that analyzing relationships among these signatures at the population level may uncover baseline immune phenotypes that correspond with response outcomes to immune stimuli. To test this, we quantified global gene expression in peripheral blood CD4⁺ cells from healthy individuals at baseline and following CD3/CD28 stimulation at two time points 1 mo apart. Systemic CD4⁺ cell baseline and poststimulation molecular immune response signatures (MIRS) were defined by identifying genes expressed at levels that were stable between time points within individuals and differential among individuals in each state. Iterative differential gene expression analyses between all possible phenotypic groupings of at least three individuals using the baseline and stimulated MIRS gene sets revealed shared baseline and response phenotypic groupings, indicating the baseline MIRS contained determinants of immune responsiveness. Furthermore, significant numbers of shared phenotype-defining sets of determinants were identified in baseline data across independent healthy cohorts. Combining the cohorts and repeating the analyses resulted in identification of over 6000 baseline immune phenotypic groups, implying that the MIRS concept may be useful in many immune perturbation contexts. These findings demonstrate that patterns in complex gene expression variability can be used to define immune phenotypes and discover determinants of immune responsiveness.

Clinical Evidence Supports a Protective Role for CXCL5 in Coronary Artery Disease

Our goal was to measure the association of CXCL5 and molecular phenotypes associated with coronary atherosclerosis severity in patients at least 65 years old. CXCL5 is classically defined as a proinflammatory chemokine, but its role in chronic inflammatory diseases, such as coronary atherosclerosis, is not well defined. We enrolled individuals who were at least 65 years old and undergoing diagnostic cardiac catheterization. Coronary artery disease (CAD) severity was quantified in each subject via coronary angiography by calculating a CAD score. Circulating CXCL5 levels were measured from plasma, and both DNA genotyping and mRNA expression levels in peripheral blood mononuclear cells were quantified via microarray gene chips. We observed a negative association of CXCL5 levels with CAD at an odds ratio (OR) of 0.46 (95% CI, 0.27-0.75). Controlling for covariates, including sex, statin use, hypertension, hyperlipidemia, obesity, self-reported race, smoking, and diabetes, the OR was not significantly affected [OR, 0.54 (95% CI, 0.31-0.96)], consistent with a protective role for CXCL5 in coronary atherosclerosis. We also identified 18 genomic regions with expression quantitative trait loci of genes correlated with both CAD severity and circulating CXCL5 levels. Our clinical findings are consistent with the emerging link between chemokines and atherosclerosis and suggest new therapeutic targets for CAD.

Informatics for cancer immunotherapy

The rapid development of immunomodulatory cancer therapies has led to a concurrent increase in the application of informatics techniques to the analysis of tumors, the tumor microenvironment, and measures of systemic immunity. In this review, the use of tumors to gather genetic and expression data will first be explored. Next, techniques to assess tumor immunity are reviewed, including HLA status, predicted neoantigens, immune microenvironment deconvolution, and T-cell receptor sequencing. Attempts to integrate these data are in early stages of development and are discussed in this review. Finally, we review the application of these informatics strategies to therapy development, with a focus on vaccines, adoptive cell transfer, and checkpoint blockade therapies.

Childhood tuberculosis is associated with decreased abundance of T cell gene transcripts and impaired T cell function

The WHO estimates around a million children contract tuberculosis (TB) annually with over 80 000 deaths from dissemination of infection outside of the lungs. The insidious onset and association with skin test anergy suggests failure of the immune system to both recognise and respond to infection. To understand the immune mechanisms, we studied genome-wide whole blood RNA expression in children with TB meningitis (TBM). Findings were validated in a second cohort of children with TBM and pulmonary TB (PTB), and functional T-cell responses studied in a third cohort of children with TBM, other extrapulmonary TB (EPTB) and PTB. The predominant RNA transcriptional response in children with TBM was decreased abundance of multiple genes, with 140/204 (68%) of all differentially regulated genes showing reduced abundance compared to healthy controls. Findings were validated in a second cohort with concordance of the direction of differential expression in both TBM (r2 = 0.78 p = 2x10-16) and PTB patients (r2 = 0.71 p = 2x10-16) when compared to a second group of healthy controls. Although the direction of expression of these significant genes was similar in the PTB patients, the magnitude of differential transcript abundance was less in PTB than in TBM. The majority of genes were involved in activation of leucocytes (p = 2.67E-11) and T-cell receptor signalling (p = 6.56E-07). Less abundant gene expression in immune cells was associated with a functional defect in T-cell proliferation that recovered after full TB treatment (p<0.0003). Multiple genes involved in T-cell activation show decreased abundance in children with acute TB, who also have impaired functional T-cell responses. Our data suggest that childhood TB is associated with an acquired immune defect, potentially resulting in failure to contain the pathogen. Elucidation of the mechanism causing the immune paresis may identify new treatment and prevention strategies.

xCell: digitally portraying the tissue cellular heterogeneity landscape

Tissues are complex milieus consisting of numerous cell types. Several recent methods have attempted to enumerate cell subsets from transcriptomes. However, the available methods have used limited sources for training and give only a partial portrayal of the full cellular landscape. Here we present xCell, a novel gene signature-based method, and use it to infer 64 immune and stromal cell types. We harmonized 1822 pure human cell type transcriptomes from various sources and employed a curve fitting approach for linear comparison of cell types and introduced a novel spillover compensation technique for separating them. Using extensive in silico analyses and comparison to cytometry immunophenotyping, we show that xCell outperforms other methods. xCell is available at http://xCell.ucsf.edu/.

A sequential Monte Carlo approach to gene expression deconvolution

High-throughput gene expression data are often obtained from pure or complex (heterogeneous) biological samples. In the latter case, data obtained are a mixture of different cell types and the heterogeneity imposes some difficulties in the analysis of such data. In order to make conclusions on gene expresssion data obtained from heterogeneous samples, methods such as microdissection and flow cytometry have been employed to physically separate the constituting cell types. However, these manual approaches are time consuming when measuring the responses of multiple cell types simultaneously. In addition, exposed samples, on many occasions, end up being contaminated with external perturbations and this may result in an altered yield of molecular content. In this paper, we model the heterogeneous gene expression data using a Bayesian framework, treating the cell type proportions and the cell-type specific expressions as the parameters of the model. Specifically, we present a novel sequential Monte Carlo (SMC) sampler for estimating the model parameters by approximating their posterior distributions with a set of weighted samples. The SMC framework is a robust and efficient approach where we construct a sequence of artificial target (posterior) distributions on spaces of increasing dimensions which admit the distributions of interest as marginals. The proposed algorithm is evaluated on simulated datasets and publicly available real datasets, including Affymetrix oligonucleotide arrays and national center for biotechnology information (NCBI) gene expression omnibus (GEO), with varying number of cell types. The results obtained on all datasets show a superior performance with an improved accuracy in the estimation of cell type proportions and the cell-type specific expressions, and in addition, more accurate identification of differentially expressed genes when compared to other widely known methods for blind decomposition of heterogeneous gene expression data such as Dsection and the nonnegative matrix factorization (NMF) algorithms. MATLAB implementation of the proposed SMC algorithm is available to download at https://github.com/moyanre/smcgenedeconv.git.

Quantifying the relative immune cell activation from whole tissue/organ-derived differentially expressed gene data

Evaluation of immune responses in individual immune cell types is important for the development of new medicines. Here, we propose a computational method designated ICEPOP (Immune CEll POPulation) to estimate individual immune cell type responses from bulk tissue and organ samples. The relative gene responses are scored for each cell type by using the data from differentially expressed genes derived from control- vs drug-treated sample pairs, and the data from public databases including ImmGen and IRIS, which contain gene expression profiles of a variety of immune cells. By ICEPOP, we analysed cell responses induced by vaccine-adjuvants in the mouse spleen, and extended the analyses to human peripheral blood mononuclear cells and gut biopsy samples focusing on human papilloma virus vaccination and inflammatory bowel disease treatment with Infliximab. In both mouse and human datasets, our method reliably quantified the responding immune cell types and provided insightful information, demonstrating that our method is useful to evaluate immune responses from bulk sample-derived gene expression data. ICEPOP is available as an interactive web site (https://vdynamics.shinyapps.io/icepop/) and Python package (https://github.com/ewijaya/icepop).

Interactions between the tumor and the blood systemic response of breast cancer patients

Although systemic immunity is critical to the process of tumor rejection, cancer research has largely focused on immune cells in the tumor microenvironment. To understand molecular changes in the patient systemic response (SR) to the presence of BC, we profiled RNA in blood and matched tumor from 173 patients. We designed a system (MIxT, Matched Interactions Across Tissues) to systematically explore and link molecular processes expressed in each tissue. MIxT confirmed that processes active in the patient SR are especially relevant to BC immunogenicity. The nature of interactions across tissues (i.e. which biological processes are associated and their patterns of expression) varies highly with tumor subtype. For example, aspects of the immune SR are underexpressed proportionally to the level of expression of defined molecular processes specific to basal tumors. The catalog of subtype-specific interactions across tissues from BC patients provides promising new ways to tackle or monitor the disease by exploiting the patient SR.

We present a novel system (MIxT) to identify genes and pathways in the primary tumor that are tightly linked to genes and pathways in the patient systemic response (SR). These results suggest new ways to tackle and monitor the disease by looking outside the tumor and exploiting the patient SR.

Identification of biomarkers of response to abatacept in patients with SLE using deconvolution of whole blood transcriptomic data from a phase IIb clinical trial

Objective

To characterise patients with active SLE based on pretreatment gene expression-defined peripheral immune cell patterns and identify clusters enriched for potential responders to abatacept treatment.

Methods

This post hoc analysis used baseline peripheral whole blood transcriptomic data from patients in a phase IIb trial of intravenous abatacept (~10 mg/kg/month). Cell-specific genes were used with a published deconvolution algorithm to identify immune cell proportions in patient samples, and unsupervised consensus clustering was generated. Efficacy data were re-analysed.

Results

Patient data (n=144: abatacept: n=98; placebo: n=46) were grouped into four main clusters (C) by predominant characteristic cells: C1—neutrophils; C2—cytotoxic T cells, B-cell receptor-ligated B cells, monocytes, IgG memory B cells, activated T helper cells; C3—plasma cells, activated dendritic cells, activated natural killer cells, neutrophils; C4—activated dendritic cells, cytotoxic T cells. C3 had the highest baseline total British Isles Lupus Assessment Group (BILAG) scores, highest antidouble-stranded DNA autoantibody levels and shortest time to flare (TTF), plus trends in favour of response to abatacept over placebo: adjusted mean difference in BILAG score over 1 year, −4.78 (95% CI −12.49 to 2.92); median TTF, 56 vs 6 days; greater normalisation of complement component 3 and 4 levels. Differential improvements with abatacept were not seen in other clusters, except for median TTF in C1 (201 vs 109 days).

Conclusions

Immune cell clustering segmented disease severity and responsiveness to abatacept. Definition of immune response cell types may inform design and interpretation of SLE trials and treatment decisions.

Trial registration number

NCT00119678; results.

A Severe Asthma Disease Signature from Gene Expression Profiling of Peripheral Blood from U-BIOPRED Cohorts

RATIONALE

Stratification of asthma at the molecular level, especially using accessible biospecimens, could greatly enable patient selection for targeted therapy.

OBJECTIVES

To determine the value of blood analysis to identify transcriptional differences between clinically defined asthma and nonasthma groups, identify potential patient subgroups based on gene expression, and explore biological pathways associated with identified differences.

METHODS

Transcriptomic profiles were generated by microarray analysis of blood from 610 patients with asthma and control participants in the U-BIOPRED (Unbiased Biomarkers in Prediction of Respiratory Disease Outcomes) study. Differentially expressed genes (DEGs) were identified by analysis of variance, including covariates for RNA quality, sex, and clinical site, and Ingenuity Pathway Analysis was applied. Patient subgroups based on DEGs were created by hierarchical clustering and topological data analysis.

MEASUREMENTS AND MAIN RESULTS

A total of 1,693 genes were differentially expressed between patients with severe asthma and participants without asthma. The differences from participants without asthma in the nonsmoking severe asthma and mild/moderate asthma subgroups were significantly related (r = 0.76), with a larger effect size in the severe asthma group. The majority of, but not all, differences were explained by differences in circulating immune cell populations. Pathway analysis showed an increase in chemotaxis, migration, and myeloid cell trafficking in patients with severe asthma, decreased B-lymphocyte development and hematopoietic progenitor cells, and lymphoid organ hypoplasia. Cluster analysis of DEGs led to the creation of subgroups among the patients with severe asthma who differed in molecular responses to oral corticosteroids.

CONCLUSIONS

Blood gene expression differences between clinically defined subgroups of patients with asthma and individuals without asthma, as well as subgroups of patients with severe asthma defined by transcript profiles, show the value of blood analysis in stratifying patients with asthma and identifying molecular pathways for further study. Clinical trial registered with www.clinicaltrials.gov (NCT01982162).

Multiple network-constrained regressions expand insights into influenza vaccination responses

MOTIVATION

Systems immunology leverages recent technological advancements that enable broad profiling of the immune system to better understand the response to infection and vaccination, as well as the dysregulation that occurs in disease. An increasingly common approach to gain insights from these large-scale profiling experiments involves the application of statistical learning methods to predict disease states or the immune response to perturbations. However, the goal of many systems studies is not to maximize accuracy, but rather to gain biological insights. The predictors identified using current approaches can be biologically uninterpretable or present only one of many equally predictive models, leading to a narrow understanding of the underlying biology.

RESULTS

Here we show that incorporating prior biological knowledge within a logistic modeling framework by using network-level constraints on transcriptional profiling data significantly improves interpretability. Moreover, incorporating different types of biological knowledge produces models that highlight distinct aspects of the underlying biology, while maintaining predictive accuracy. We propose a new framework, Logistic Multiple Network-constrained Regression (LogMiNeR), and apply it to understand the mechanisms underlying differential responses to influenza vaccination. Although standard logistic regression approaches were predictive, they were minimally interpretable. Incorporating prior knowledge using LogMiNeR led to models that were equally predictive yet highly interpretable. In this context, B cell-specific genes and mTOR signaling were associated with an effective vaccination response in young adults. Overall, our results demonstrate a new paradigm for analyzing high-dimensional immune profiling data in which multiple networks encoding prior knowledge are incorporated to improve model interpretability.

AVAILABILITY AND IMPLEMENTATION

The R source code described in this article is publicly available at https://bitbucket.org/kleinstein/logminer .

CONTACT

steven.kleinstein@yale.edu or stefan.avey@yale.edu.

SUPPLEMENTARY INFORMATION

Supplementary data are available at Bioinformatics online.

Exosome RNA Unshielding Couples Stromal Activation to Pattern Recognition Receptor Signaling in Cancer

Interactions between stromal fibroblasts and cancer cells generate signals for cancer progression, therapy resistance, and inflammatory responses. Although endogenous RNAs acting as damage-associated molecular patterns (DAMPs) for pattern recognition receptors (PRRs) may represent one such signal, these RNAs must remain unrecognized under non-pathological conditions. We show that triggering of stromal NOTCH-MYC by breast cancer cells results in a POL3-driven increase in RN7SL1, an endogenous RNA normally shielded by RNA binding proteins SRP9/14. This increase in RN7SL1 alters its stoichiometry with SRP9/14 and generates unshielded RN7SL1 in stromal exosomes. After exosome transfer to immune cells, unshielded RN7SL1 drives an inflammatory response. Upon transfer to breast cancer cells, unshielded RN7SL1 activates the PRR RIG-I to enhance tumor growth, metastasis, and therapy resistance. Corroborated by evidence from patient tumors and blood, these results demonstrate that regulation of RNA unshielding couples stromal activation with deployment of RNA DAMPs that promote aggressive features of cancer. VIDEO ABSTRACT.

Data normalization considerations for digital tumor dissection

In a recently published article in Genome Biology, Li and colleagues introduced TIMER, a gene expression deconvolution approach for studying tumor-infiltrating leukocytes (TILs) in 23 cancer types profiled by The Cancer Genome Atlas. Methods to characterize TIL biology are increasingly important, and the authors offer several arguments in favor of their strategy. Several of these claims warrant further discussion and highlight the critical importance of data normalization in gene expression deconvolution applications.Please see related Li et al correspondence: www.dx.doi.org/10.1186/s13059-017-1256-5 and Zheng correspondence: www.dx.doi.org/10.1186/s13059-017-1258-3.

Signatures of inflammation and impending multiple organ dysfunction in the hyperacute phase of trauma: A prospective cohort study

BACKGROUND

Severe trauma induces a widespread response of the immune system. This "genomic storm" can lead to poor outcomes, including Multiple Organ Dysfunction Syndrome (MODS). MODS carries a high mortality and morbidity rate and adversely affects long-term health outcomes. Contemporary management of MODS is entirely supportive, and no specific therapeutics have been shown to be effective in reducing incidence or severity. The pathogenesis of MODS remains unclear, and several models are proposed, such as excessive inflammation, a second-hit insult, or an imbalance between pro- and anti-inflammatory pathways. We postulated that the hyperacute window after trauma may hold the key to understanding how the genomic storm is initiated and may lead to a new understanding of the pathogenesis of MODS.

METHODS AND FINDINGS

We performed whole blood transcriptome and flow cytometry analyses on a total of 70 critically injured patients (Injury Severity Score [ISS] ≥ 25) at The Royal London Hospital in the hyperacute time period within 2 hours of injury. We compared transcriptome findings in 36 critically injured patients with those of 6 patients with minor injuries (ISS ≤ 4). We then performed flow cytometry analyses in 34 critically injured patients and compared findings with those of 9 healthy volunteers. Immediately after injury, only 1,239 gene transcripts (4%) were differentially expressed in critically injured patients. By 24 hours after injury, 6,294 transcripts (21%) were differentially expressed compared to the hyperacute window. Only 202 (16%) genes differentially expressed in the hyperacute window were still expressed in the same direction at 24 hours postinjury. Pathway analysis showed principally up-regulation of pattern recognition and innate inflammatory pathways, with down-regulation of adaptive responses. Immune deconvolution, flow cytometry, and modular analysis suggested a central role for neutrophils and Natural Killer (NK) cells, with underexpression of T- and B cell responses. In the transcriptome cohort, 20 critically injured patients later developed MODS. Compared with the 16 patients who did not develop MODS (NoMODS), maximal differential expression was seen within the hyperacute window. In MODS versus NoMODS, 363 genes were differentially expressed on admission, compared to only 33 at 24 hours postinjury. MODS transcripts differentially expressed in the hyperacute window showed enrichment among diseases and biological functions associated with cell survival and organismal death rather than inflammatory pathways. There was differential up-regulation of NK cell signalling pathways and markers in patients who would later develop MODS, with down-regulation of neutrophil deconvolution markers. This study is limited by its sample size, precluding more detailed analyses of drivers of the hyperacute response and different MODS phenotypes, and requires validation in other critically injured cohorts.

CONCLUSIONS

In this study, we showed how the hyperacute postinjury time window contained a focused, specific signature of the response to critical injury that led to widespread genomic activation. A transcriptomic signature for later development of MODS was present in this hyperacute window; it showed a strong signal for cell death and survival pathways and implicated NK cells and neutrophil populations in this differential response.

Network Analysis of Lung Transcriptomics Reveals a Distinct B-Cell Signature in Emphysema

RATIONALE

Chronic obstructive pulmonary disease (COPD) is characterized by chronic airflow limitation caused by a combination of airways disease (bronchiolitis) and parenchymal destruction (emphysema), whose relative proportion varies from patient to patient.

OBJECTIVES

To explore and contrast the molecular pathogenesis of emphysema and bronchiolitis in COPD.

METHODS

We used network analysis of lung transcriptomics (Affymetrix arrays) in 70 former smokers with COPD to compare differential expression and gene coexpression in bronchiolitis and emphysema.

MEASUREMENTS AND MAIN RESULTS

We observed that in emphysema (but not in bronchiolitis) (1) up-regulated genes were enriched in ontologies related to B-cell homing and activation; (2) the immune coexpression network had a central core of B cell-related genes; (3) B-cell recruitment and immunoglobulin transcription genes (CXCL13, CCL19, and POU2AF1) correlated with emphysema severity; (4) there were lymphoid follicles (CD20(+)IgM(+)) with active B cells (phosphorylated nuclear factor-κB p65(+)), proliferation markers (Ki-67(+)), and class-switched B cells (IgG(+)); and (5) both TNFRSF17 mRNA and B cell-activating factor protein were up-regulated. These findings were by and large reproduced in a group of patients with incipient emphysema and when patients with emphysema were matched for the severity of airflow limitation of those with bronchiolitis.

CONCLUSIONS

Our study identifies enrichment in B cell-related genes in patients with COPD with emphysema that is absent in bronchiolitis. These observations contribute to a better understanding of COPD pathobiology and may open new therapeutic opportunities for patients with COPD.

Renal Operational Tolerance Is Associated With a Defect of Blood Tfh Cells That Exhibit Impaired B Cell Help

Renal operationally tolerant patients (TOL) display a defect in B cell differentiation, with a deficiency in plasma cells. Recently described, T follicular helper (Tfh) cells play a critical role in B cell differentiation. We analyzed blood Tfh subsets in TOL and transplanted patients with stable graft function under immunosuppression (STA). We observed a reduced proportion of blood activated and highly functional Tfh subsets in TOL, without affecting Tfh absolute numbers. Functionally, Tfh cells from TOL displayed a modified gene expression profile, failed to produce interleukin-21, and were unable to induce IgG production by naive B cells. This Tfh defect is linked to a low incidence of postgraft de novo donor-specific antibody (dnDSA) immunization, suggesting that the lack of Tfh cells in TOL may induce a protolerogenic environment with reduced risk of developing dnDSA. Finally, we showed that elevated Tfh in STA precedes the occurrence of dnDSA during an alloresponse. These data provide new insights into the mechanisms of antibody response in operational tolerance. Disrupted homeostasis and impaired Tfh function in TOL could lead to a reduced risk of developing dnDSA and suggest a predictive role of blood Tfh cells on the occurrence of dnDSA in transplant recipients.

Comprehensive Transcriptome and Mutational Profiling of Endemic Burkitt Lymphoma Reveals EBV Type-Specific Differences

Endemic Burkitt lymphoma (eBL) is the most common pediatric cancer in malaria-endemic equatorial Africa and nearly always contains Epstein-Barr virus (EBV), unlike sporadic Burkitt lymphoma (sBL) that occurs with a lower incidence in developed countries. Given these differences and the variable clinical presentation and outcomes, we sought to further understand pathogenesis by investigating transcriptomes using RNA sequencing (RNAseq) from multiple primary eBL tumors compared with sBL tumors. Within eBL tumors, minimal expression differences were found based on: anatomical presentation site, in-hospital survival rates, and EBV genome type, suggesting that eBL tumors are homogeneous without marked subtypes. The outstanding difference detected using surrogate variable analysis was the significantly decreased expression of key genes in the immunoproteasome complex (PSMB9/β1i, PSMB10/β2i, PSMB8/β5i, and PSME2/PA28β) in eBL tumors carrying type 2 EBV compared with type 1 EBV. Second, in comparison with previously published pediatric sBL specimens, the majority of the expression and pathway differences was related to the PTEN/PI3K/mTOR signaling pathway and was correlated most strongly with EBV status rather than geographic designation. Third, common mutations were observed significantly less frequently in eBL tumors harboring EBV type 1, with mutation frequencies similar between tumors with EBV type 2 and without EBV. In addition to the previously reported genes, a set of new genes mutated in BL, including TFAP4, MSH6, PRRC2C, BCL7A, FOXO1, PLCG2, PRKDC, RAD50, and RPRD2, were identified. Overall, these data establish that EBV, particularly EBV type 1, supports BL oncogenesis, alleviating the need for certain driver mutations in the human genome.

IMPLICATIONS

Genomic and mutational analyses of Burkitt lymphoma tumors identify key differences based on viral content and clinical outcomes suggesting new avenues for the development of prognostic molecular biomarkers and therapeutic interventions.

Btk-specific inhibition blocks pathogenic plasma cell signatures and myeloid cell-associated damage in IFN-driven lupus nephritis

Systemic lupus erythematosus (SLE) is often associated with exaggerated B cell activation promoting plasma cell generation, immune-complex deposition in the kidney, renal infiltration of myeloid cells, and glomerular nephritis. Type-I IFNs amplify these autoimmune processes and promote severe disease. Bruton's tyrosine kinase (Btk) inhibitors are considered novel therapies for SLE. We describe the characterization of a highly selective reversible Btk inhibitor, G-744. G-744 is efficacious, and superior to blocking BAFF and Syk, in ameliorating severe lupus nephritis in both spontaneous and IFNα-accelerated lupus in NZB/W_F1 mice in therapeutic regimens. Selective Btk inhibition ablated plasmablast generation, reduced autoantibodies, and - similar to cyclophosphamide - improved renal pathology in IFNα-accelerated lupus. Employing global transcriptional profiling of spleen and kidney coupled with cross-species human modular repertoire analyses, we identify similarities in the inflammatory process between mice and humans, and we demonstrate that G-744 reduced gene expression signatures essential for splenic B cell terminal differentiation, particularly the secretory pathway, as well as renal transcriptional profiles coupled with myeloid cell-mediated pathology and glomerular plus tubulointerstitial disease in human glomerulonephritis patients. These findings reveal the mechanism through which a selective Btk inhibitor blocks murine autoimmune kidney disease, highlighting pathway activity that may translate to human SLE.

Secondhand Tobacco Smoke Exposure Associations With DNA Methylation of the Aryl Hydrocarbon Receptor Repressor

INTRODUCTION

Cigarette smoking is inversely associated with DNA methylation of the aryl hydrocarbon receptor repressor (AHRR; cg05575921). However, the association between secondhand tobacco smoke (SHS) exposure and AHRR methylation is unknown.

METHODS

DNA methylation of AHRR cg05575921 in CD14+ monocyte samples, from 495 never-smokers and 411 former smokers (having quit smoking ≥15 years) from the Multi-Ethnic Study of Atherosclerosis (MESA), was cross-sectionally compared with concomitantly ascertained self-reported SHS exposure, urine cotinine concentrations, and estimates of air pollutants at participants' homes. Linear regression was used to test for associations, and covariates included age, sex, race, education, study site, and previous smoking exposure (smoking status, time since quitting, and pack-years).

RESULTS

Recent indoor SHS exposure (hours per week) was inversely associated with cg05575921 methylation (β ± SE = -0.009 ± 0.003, p = .007). The inverse effect direction was consistent (but did not reach significance) in the majority of stratified analyses (by smoking status, sex, and race). Categorical analysis revealed high levels of recent SHS exposure (≥10 hours per week) inversely associated with cg05575921 methylation (β ± SE = -0.28 ± 0.09, p = .003), which remained significant (p < .05) in the majority of stratified analyses. cg05575921 methylation did not significantly (p < .05) associate with low to moderate levels of recent SHS exposure (1-9 hours per week), urine cotinine concentrations, years spent living with people smoking, years spent indoors (not at home) with people smoking, or estimated levels of air pollutants.

CONCLUSIONS

High levels of recent indoor SHS exposure may be inversely associated with DNA methylation of AHRR in human monocytes.

IMPLICATIONS

DNA methylation is a biochemical alteration that can occur in response to cigarette smoking; however, little is known about the effect of SHS on human DNA methylation. In the present study, we evaluated the association between SHS exposure and DNA methylation in human monocytes, at a site (AHRR cg05575921) known to have methylation inversely associated with current and former cigarette smoking compared to never smoking. Results from this study suggest high levels of recent SHS exposure inversely associate with DNA methylation of AHRR cg05575921 in monocytes from nonsmokers, albeit with weaker effects than active cigarette smoking.

Spatiotemporal genomic architecture informs precision oncology in glioblastoma

Precision medicine in cancer proposes that genomic characterization of tumors can inform personalized targeted therapies. However, this proposition is complicated by spatial and temporal heterogeneity. Here we study genomic and expression profiles across 127 multisector or longitudinal specimens from 52 individuals with glioblastoma (GBM). Using bulk and single-cell data, we find that samples from the same tumor mass share genomic and expression signatures, whereas geographically separated, multifocal tumors and/or long-term recurrent tumors are seeded from different clones. Chemical screening of patient-derived glioma cells (PDCs) shows that therapeutic response is associated with genetic similarity, and multifocal tumors that are enriched with PIK3CA mutations have a heterogeneous drug-response pattern. We show that targeting truncal events is more efficacious than targeting private events in reducing the tumor burden. In summary, this work demonstrates that evolutionary inference from integrated genomic analysis in multisector biopsies can inform targeted therapeutic interventions for patients with GBM.

Mapping circulating serum miRNAs to their immune-related target mRNAs

Purpose

Evidence suggests that circulating serum microRNAs (miRNAs) might preferentially target immune-related mRNAs. If this were the case, we hypothesized that immune-related mRNAs would have more predicted serum miRNA binding sites than other mRNAs and, reciprocally, that serum miRNAs would have more immune-related mRNA targets than non-serum miRNAs.

Materials and methods

We developed a consensus target predictor using the random forest framework and calculated the number of predicted miRNA–mRNA interactions in various subsets of miRNAs (serum, non-serum) and mRNAs (immune related, nonimmune related).

Results

Immune-related mRNAs were predicted to be targeted by serum miRNA more than other mRNAs. Moreover, serum miRNAs were predicted to target many more immune-related mRNA targets than non-serum miRNAs; however, these two biases in immune-related mRNAs and serum miRNAs appear to be completely independent.

Conclusion

Immune-related mRNAs have more miRNA binding sites in general, not just for serum miRNAs; likewise, serum miRNAs target many more mRNAs than non-serum miRNAs overall, regardless of whether they are immune related or not. Nevertheless, these two independent phenomena result in a significantly larger number of predicted serum miRNA–immune mRNA interactions than would be expected by chance.

Enumerateblood - an R package to estimate the cellular composition of whole blood from Affymetrix Gene ST gene expression profiles

Background

Measuring genome-wide changes in transcript abundance in circulating peripheral whole blood is a useful way to study disease pathobiology and may help elucidate the molecular mechanisms of disease, or discovery of useful disease biomarkers. The sensitivity and interpretability of analyses carried out in this complex tissue, however, are significantly affected by its dynamic cellular heterogeneity. It is therefore desirable to quantify this heterogeneity, either to account for it or to better model interactions that may be present between the abundance of certain transcripts, specific cell types and the indication under study. Accurate enumeration of the many component cell types that make up peripheral whole blood can further complicate the sample collection process, however, and result in additional costs. Many approaches have been developed to infer the composition of a sample from high-dimensional transcriptomic and, more recently, epigenetic data. These approaches rely on the availability of isolated expression profiles for the cell types to be enumerated. These profiles are platform-specific, suitable datasets are rare, and generating them is expensive. No such dataset exists on the Affymetrix Gene ST platform.

Results

We present ‘Enumerateblood’, a freely-available and open source R package that exposes a multi-response Gaussian model capable of accurately predicting the composition of peripheral whole blood samples from Affymetrix Gene ST expression profiles, outperforming other current methods when applied to Gene ST data.

Conclusions

‘Enumerateblood’ significantly improves our ability to study disease pathobiology from whole blood gene expression assayed on the popular Affymetrix Gene ST platform by allowing a more complete study of the various components of this complex tissue without the need for additional data collection. Future use of the model may allow for novel insights to be generated from the ~400 Affymetrix Gene ST blood gene expression datasets currently available on the Gene Expression Omnibus (GEO) website.

Electronic supplementary material

The online version of this article (doi:10.1186/s12864-016-3460-1) contains supplementary material, which is available to authorized users.

Validation of Immune Cell Modules in Multicellular Transcriptomic Data

Numerous gene signatures, or modules have been described to evaluate the immune cell composition in transcriptomes of multicellular tissue samples. However, significant diversity in module gene content for specific cell types is associated with heterogeneity in their performance. In order to rank modules that best reflect their purported association, we have generated the modular discrimination index (MDI) score that assesses expression of each module in the target cell type relative to other cells. We demonstrate that MDI scores predict modules that best reflect independently validated differences in cellular composition, and correlate with the covariance between cell numbers and module expression in human blood and tissue samples. Our analyses demonstrate that MDI scores provide an ordinal summary statistic that reliably ranks the accuracy of gene expression modules for deconvolution of cell type abundance in transcriptional data.

A Functional Genomic Meta-Analysis of Clinical Trials in Systemic Sclerosis: Toward Precision Medicine and Combination Therapy

Systemic sclerosis is an orphan, systemic autoimmune disease with no FDA-approved treatments. Its heterogeneity and rarity often result in underpowered clinical trials making the analysis and interpretation of associated molecular data challenging. We performed a meta-analysis of gene expression data from skin biopsies of patients with systemic sclerosis treated with five therapies: mycophenolate mofetil, rituximab, abatacept, nilotinib, and fresolimumab. A common clinical improvement criterion of -20% or -5 modified Rodnan skin score was applied to each study. We applied a machine learning approach that captured features beyond differential expression and was better at identifying targets of therapies than the differential expression alone. Regardless of treatment mechanism, abrogation of inflammatory pathways accompanied clinical improvement in multiple studies suggesting that high expression of immune-related genes indicates active and targetable disease. Our framework allowed us to compare different trials and ask if patients who failed one therapy would likely improve on a different therapy, based on changes in gene expression. Genes with high expression at baseline in fresolimumab nonimprovers were downregulated in mycophenolate mofetil improvers, suggesting that immunomodulatory or combination therapy may have benefitted these patients. This approach can be broadly applied to increase tissue specificity and sensitivity of differential expression results.

ImmQuant: a user-friendly tool for inferring immune cell-type composition from gene-expression data

: The composition of immune-cell subsets is key to the understanding of major diseases and pathologies. Computational deconvolution methods enable researchers to investigate immune cell quantities in complex tissues based on transcriptome data. Here we present ImmQuant, a software tool allowing immunologists to upload transcription profiles of multiple tissue samples, apply deconvolution methodology to predict differences in cell-type quantities between the samples, and then inspect the inferred cell-type alterations using convenient visualization tools. ImmQuant builds on the DCQ deconvolution algorithm and allows a user-friendly utilization of this method by non-bioinformatician researchers. Specifically, it enables investigation of hundreds of immune cell subsets in mouse tissues, as well as a few dozen cell types in human samples.

AVAILABILITY AND IMPLEMENTATION

ImmQuant is available for download at http://csgi.tau.ac.il/ImmQuant/ CONTACT: iritgv@post.tau.ac.ilSupplementary information: Supplementary data are available at Bioinformatics online.

Conservation of immune gene signatures in solid tumors and prognostic implications

Background

Tumor-infiltrating leukocytes can either limit cancer growth or facilitate its spread. Diagnostic strategies that comprehensively assess the functional complexity of tumor immune infiltrates could have wide-reaching clinical value. In previous work we identified distinct immune gene signatures in breast tumors that reflect the relative abundance of infiltrating immune cells and exhibited significant associations with patient outcomes. Here we hypothesized that immune gene signatures agnostic to tumor type can be identified by de novo discovery of gene clusters enriched for immunological functions and possessing internal correlation structure conserved across solid tumors from different anatomic sites.

Methods

We assembled microarray expression datasets encompassing 5,295 tumors of the breast, colon, lung, ovarian and prostate. Unsupervised clustering methods were used to determine number and composition of gene clusters within each dataset. Immune-enriched gene clusters (signatures) identified by gene ontology enrichment were analyzed for internal correlation structure and conservation across tumors then compared against expression profiles of: 1) flow-sorted leukocytes from peripheral blood and 2) >300 cancer cell lines from solid and hematologic cancers. Cox regression analysis was used to identify signatures with significant associations with clinical outcome.

Results

We identified nine distinct immune-enriched gene signatures conserved across all five tumor types. The signatures differentiated specific leukocyte lineages with moderate discernment overall, and naturally organized into six discrete groups indicative of admixed lineages. Moreover, seven of the signatures exhibit minimal and uncorrelated expression in cancer cell lines, suggesting that these signatures derive predominantly from infiltrating immune cells. All nine immune signatures achieved statistically significant associations with patient prognosis (p<0.05) in one or more tumor types with greatest significance observed in breast and skin cancers. Several signatures indicative of myeloid lineages exhibited poor outcome associations that were most apparent in brain and colon cancers.

Conclusions

These findings suggest that tumor infiltrating immune cells can be differentiated by immune-specific gene expression patterns that quantify the relative abundance of multiple immune infiltrates across a range of solid tumor types. That these markers of immune involvement are significantly associated with patient prognosis in diverse cancers suggests their clinical utility as pan-cancer markers of tumor behavior and immune responsiveness.

Electronic supplementary material

The online version of this article (doi:10.1186/s12885-016-2948-z) contains supplementary material, which is available to authorized users.

Immunomodulatory Activity of Nivolumab in Metastatic Renal Cell Carcinoma

PURPOSE

Nivolumab, an anti-PD-1 immune checkpoint inhibitor, improved overall survival versus everolimus in a phase 3 trial of previously treated patients with metastatic renal cell carcinoma (mRCC). We investigated immunomodulatory activity of nivolumab in a hypothesis-generating prospective mRCC trial.

EXPERIMENTAL DESIGN

Nivolumab was administered intravenously every 3 weeks at 0.3, 2, or 10 mg/kg to previously treated patients and 10 mg/kg to treatment-naïve patients with mRCC. Baseline and on-treatment biopsies and blood were obtained. Clinical activity, tumor-associated lymphocytes, PD-L1 expression (Dako immunohistochemistry; ≥5% vs. <5% tumor membrane staining), tumor gene expression (Affymetrix U219), serum chemokines, and safety were assessed.

RESULTS

In 91 treated patients, median overall survival [95% confidence interval (CI)] was 16.4 months [10.1 to not reached (NR)] for nivolumab 0.3 mg/kg, NR for 2 mg/kg, 25.2 months (12.0 to NR) for 10 mg/kg, and NR for treatment-naïve patients. Median percent change from baseline in tumor-associated lymphocytes was 69% (CD3+), 180% (CD4+), and 117% (CD8+). Of 56 baseline biopsies, 32% had ≥5% PD-L1 expression, and there was no consistent change from baseline to on-treatment biopsies. Transcriptional changes in tumors on treatment included upregulation of IFNγ-stimulated genes (e.g., CXCL9). Median increases in chemokine levels from baseline to C2D8 were 101% (CXCL9) and 37% (CXCL10) in peripheral blood. No new safety signals were identified.

CONCLUSIONS

Immunomodulatory effects of PD-1 inhibition were demonstrated through multiple lines of evidence across nivolumab doses. Biomarker changes from baseline reflect nivolumab pharmacodynamics in the tumor microenvironment. These data may inform potential combinations. Clin Cancer Res; 22(22); 5461-71. ©2016 AACR.

Synergistic Communication between CD4+ T Cells and Monocytes Impacts the Cytokine Environment

Physiological cytokine environments arise from factors produced by diverse cell types in coordinated concert. Understanding the contributions of each cell type in the context of cell-cell communication is important for effectively designing disease modifying interventions. Here, we present multi-plexed measurement of 48 cytokines from a coculture system of primary human CD4+ T cells and monocytes across a spectrum of stimuli and for a range of relative T cell/monocyte compositions, coupled with corresponding measurements from PBMCs and plasma from the same donors. Computational analysis of the resulting data-sets elucidated communication-independent and communication-dependent contributions, including both positive and negative synergies. We find that cytokines in cell supernatants were uncorrelated to those found in plasma. Additionally, as an example of positive synergy, production levels of CXCR3 cytokines IP-10 and MIG, depend non-linearly on both IFNγ and TNFα levels in cross-talk between T cells and monocytes. Overall, this work demonstrates that communication between cell types can significantly impact the consequent cytokine environment, emphasizing the value of mixed cell population studies.

Gene expression analysis of TIL rich HPV-driven head and neck tumors reveals a distinct B-cell signature when compared to HPV independent tumors

Human papilloma virus (HPV)-associated head and neck squamous cell carcinoma (HNSCC) has a better prognosis than it's HPV negative (HPV(-)) counterpart. This may be due to the higher numbers of tumor-infiltrating lymphocytes (TILs) in HPV positive (HPV(+)) tumors. RNA-Sequencing (RNA-Seq) was used to evaluate whether the differences in clinical behaviour simply reflect a numerical difference in TILs or whether there is a fundamental behavioural difference between TILs in these two settings. Thirty-nine HNSCC tumors were scored for TIL density by immunohistochemistry. After the removal of 16 TILlow tumors, RNA-Seq analysis was performed on 23 TILhigh/med tumors (HPV(+) n=10 and HPV(-) n=13). Using EdgeR, differentially expressed genes (DEG) were identified. Immune subset analysis was performed using Functional Analysis of Individual RNA-Seq/ Microarray Expression (FAIME) and immune gene RNA transcript count analysis. In total, 1,634 DEGs were identified, with a dominant immune signature observed in HPV(+) tumors. After normalizing the expression profiles to account for differences in B- and T-cell number, 437 significantly DEGs remained. A B-cell associated signature distinguished HPV(+) from HPV(-) tumors, and included the DEGs CD200, GGA2, ADAM28, STAG3, SPIB, VCAM1, BCL2 and ICOSLG; the immune signal relative to T-cells was qualitatively similar between TILs of both tumor cohorts. Our findings were validated and confirmed in two independent cohorts using TCGA data and tumor-infiltrating B-cells from additional HPV(+) HNSCC patients. A B-cell associated signal segregated tumors relative to HPV status. Our data suggests that the role of B-cells in the adaptive immune response to HPV(+) HNSCC requires re-assessment.

Comprehensive analyses of tumor immunity: implications for cancer immunotherapy

Background

Understanding the interactions between tumor and the host immune system is critical to finding prognostic biomarkers, reducing drug resistance, and developing new therapies. Novel computational methods are needed to estimate tumor-infiltrating immune cells and understand tumor–immune interactions in cancers.

Results

We analyze tumor-infiltrating immune cells in over 10,000 RNA-seq samples across 23 cancer types from The Cancer Genome Atlas (TCGA). Our computationally inferred immune infiltrates associate much more strongly with patient clinical features, viral infection status, and cancer genetic alterations than other computational approaches. Analysis of cancer/testis antigen expression and CD8 T-cell abundance suggests that MAGEA3 is a potential immune target in melanoma, but not in non-small cell lung cancer, and implicates SPAG5 as an alternative cancer vaccine target in multiple cancers. We find that melanomas expressing high levels of CTLA4 separate into two distinct groups with respect to CD8 T-cell infiltration, which might influence clinical responses to anti-CTLA4 agents. We observe similar dichotomy of TIM3 expression with respect to CD8 T cells in kidney cancer and validate it experimentally. The abundance of immune infiltration, together with our downstream analyses and findings, are accessible through TIMER, a public resource at http://cistrome.org/TIMER.

Conclusions

We develop a computational approach to study tumor-infiltrating immune cells and their interactions with cancer cells. Our resource of immune-infiltrate levels, clinical associations, as well as predicted therapeutic markers may inform effective cancer vaccine and checkpoint blockade therapies.

Electronic supplementary material

The online version of this article (doi:10.1186/s13059-016-1028-7) contains supplementary material, which is available to authorized users.

Immune-inflammation gene signatures in endometriosis patients

OBJECTIVE

To determine if the molecular profiles of endometriotic lesions contain informative measures of inflammation and immune dysfunction that may contribute to better understanding of the interplay between immune dysfunction and inflammation and their contribution to endometriosis pathogenesis.

DESIGN

Immune and inflammation transcriptomic analysis with the use of the Nanostring nCounter GX Human Immunology V2 platform (579 human immune and inflammation-related genes and 15 housekeeping genes).

SETTING

Academic university and teaching hospital.

INTERVENTION(S)

None.

PATIENT(S)

Stage III-IV endometriosis patients with infertility (n = 8) and fertile disease-free control women undergoing tubal ligation (n = 8). Menstrual stage was matched to secretory phase in all participants.

MAIN OUTCOME MEASURE(S)

Immune and inflammation transcriptomics quantification from ectopic endometriotic lesions and matched eutopic endometrium from patients. Endometria of fertile women served as control subjects.

RESULT(S)

Our results displayed endometriotic lesions as molecularly distinct entities compared with eutopic endometrium and endometrium of control samples; 396 out of 579 screened immune and inflammation-related genes were significantly different in ectopic tissues compared with control endometrium. Most importantly, eutopic endometrium of the patients displayed a unique molecular profile compared with the control endometrium (91/579 genes were significantly different), particularly of genes involved in regulation of cell apoptosis and decidualization.

CONCLUSION(S)

We characterize differential expression of immune-inflammation genes in endometriosis patients, and show molecular distinction of eutopic endometrium of patients compared with control fertile women.

Systems biology and the quest for correlates of protection to guide the development of an HIV vaccine

Over the last three decades, a myriad of data has been generated regarding HIV/SIV evolution, immune evasion, immune response, and pathogenesis. Much of this data can be integrated and potentially used to generate a successful vaccine. Although individual approaches have begun to shed light on mechanisms involved in vaccine-conferred protection from infection, true correlates of protection have not yet been identified. The systems biology approach helps unify datasets generated using different techniques and broaden our understanding of HIV immunopathogenesis. Moreover, systems biology is a tool that can provide correlates of protection, which can be targeted for the production of a successful HIV vaccine.

Profiling networks of distinct immune-cells in tumors

Background

It is now clearly evident that cancer outcome and response to therapy is guided by diverse immune-cell activity in tumors. Presently, a key challenge is to comprehensively identify networks of distinct immune-cell signatures present in complex tissue, at higher-resolution and at various stages of differentiation, activation or function. This is particularly so for closely related immune-cells with diminutive, yet critical, differences.

Results

To predict networks of infiltrated distinct immune-cell phenotypes at higher resolution, we explored an integrated knowledge-based approach to select immune-cell signature genes integrating not only expression enrichment across immune-cells, but also an automatic capture of relevant immune-cell signature genes from the literature. This knowledge-based approach was integrated with resources of immune-cell specific protein networks, to define signature genes of distinct immune-cell phenotypes. We demonstrate the utility of this approach by profiling signatures of distinct immune-cells, and networks of immune-cells, from metastatic melanoma patients who had undergone chemotherapy. The resultant bioinformatics strategy complements immunohistochemistry from these tumors, and predicts both tumor-killing and immunosuppressive networks of distinct immune-cells in responders and non-responders, respectively. The approach is also shown to capture differences in the immune-cell networks of BRAF versus NRAS mutated metastatic melanomas, and the dynamic changes in resistance to targeted kinase inhibitors in MAPK signalling.

Conclusions

This integrative bioinformatics approach demonstrates that capturing the protein network signatures and ratios of distinct immune-cell in the tumor microenvironment maybe an important factor in predicting response to therapy. This may serve as a computational strategy to define network signatures of distinct immune-cells to guide immuno-pathological discovery.

Electronic supplementary material

The online version of this article (doi:10.1186/s12859-016-1141-3) contains supplementary material, which is available to authorized users.

High-throughput genomic profiling of tumor-infiltrating leukocytes

Tumors are complex ecosystems comprised of diverse cell types including malignant cells, mesenchymal cells, and tumor-infiltrating leukocytes (TILs). While TILs are well known to play important roles in many aspects of cancer biology, recent developments in immuno-oncology have spurred considerable interest in TILs, particularly in relation to their optimal engagement by emerging immunotherapies. Traditionally, the enumeration of TIL phenotypic diversity and composition in solid tumors has relied on resolving single cells by flow cytometry and immunohistochemical methods. However, advances in genome-wide technologies and computational methods are now allowing TILs to be profiled with increasingly high resolution and accuracy directly from RNA mixtures of bulk tumor samples. In this review, we highlight recent progress in the development of in silico tumor dissection methods, and illustrate examples of how these strategies can be applied to characterize TILs in human tumors to facilitate personalized cancer therapy.

Neoadjuvant Chemotherapy Modulates the Immune Microenvironment in Metastases of Tubo-Ovarian High-Grade Serous Carcinoma

PURPOSE

The purpose of this study was to assess the effect of neoadjuvant chemotherapy (NACT) on immune activation in stage IIIC/IV tubo-ovarian high-grade serous carcinoma (HGSC), and its relationship to treatment response.

EXPERIMENTAL DESIGN

We obtained pre- and posttreatment omental biopsies and blood samples from a total of 54 patients undergoing platinum-based NACT and 6 patients undergoing primary debulking surgery. We measured T-cell density and phenotype, immune activation, and markers of cancer-related inflammation using IHC, flow cytometry, electrochemiluminescence assays, and RNA sequencing and related our findings to the histopathologic treatment response.

RESULTS

There was evidence of T-cell activation in omental biopsies after NACT: CD4(+) T cells showed enhanced IFNγ production and antitumor Th1 gene signatures were increased. T-cell activation was more pronounced with good response to NACT. The CD8(+) T-cell and CD45RO(+) memory cell density in the tumor microenvironment was unchanged after NACT but biopsies showing a good therapeutic response had significantly fewer FoxP3(+) T regulatory (Treg) cells. This finding was supported by a reduction in a Treg cell gene signature in post- versus pre-NACT samples that was more pronounced in good responders. Plasma levels of proinflammatory cytokines decreased in all patients after NACT. However, a high proportion of T cells in biopsies expressed immune checkpoint molecules PD-1 and CTLA4, and PD-L1 levels were significantly increased after NACT.

CONCLUSIONS

NACT may enhance host immune response but this effect is tempered by high/increased levels of PD-1, CTLA4, and PD-L1. Sequential chemoimmunotherapy may improve disease control in advanced HGSC. Clin Cancer Res; 22(12); 3025-36. ©2016 AACR.

CRIg-expressing peritoneal macrophages are associated with disease severity in patients with cirrhosis and ascites

Infections are an important cause of morbidity and mortality in patients with decompensated cirrhosis and ascites. Hypothesizing that innate immune dysfunction contributes to susceptibility to infection, we assessed ascitic fluid macrophage phenotype and function. The expression of complement receptor of the immunoglobulin superfamily (CRIg) and CCR2 defined two phenotypically and functionally distinct peritoneal macrophage subpopulations. The proportion of CRIg^hi macrophages differed between patients and in the same patient over time, and a high proportion of CRIg^hi macrophages was associated with reduced disease severity (model for end-stage liver disease) score. As compared with CRIg^lo macrophages, CRIg^hi macrophages were highly phagocytic and displayed enhanced antimicrobial effector activity. Transcriptional profiling by RNA sequencing and comparison with human macrophage and murine peritoneal macrophage expression signatures highlighted similarities among CRIg^hi cells, human macrophages, and mouse F4/80^hi resident peritoneal macrophages and among CRIg^lo macrophages, human monocytes, and mouse F4/80^lo monocyte-derived peritoneal macrophages. These data suggest that CRIg^hi and CRIg^lo macrophages may represent a tissue-resident population and a monocyte-derived population, respectively. In conclusion, ascites fluid macrophage subset distribution and phagocytic capacity is highly variable among patients with chronic liver disease. Regulating the numbers and/or functions of these macrophage populations could provide therapeutic opportunities in cirrhotic patients.

Nuclear PKC-θ facilitates rapid transcriptional responses in human memory CD4+ T cells through p65 and H2B phosphorylation

Memory T cells are characterized by their rapid transcriptional programs upon re-stimulation. This transcriptional memory response is facilitated by permissive chromatin, but exactly how the permissive epigenetic landscape in memory T cells integrates incoming stimulatory signals remains poorly understood. By genome-wide ChIP-sequencing ex vivo human CD4⁺ T cells, here, we show that the signaling enzyme, protein kinase C theta (PKC-θ) directly relays stimulatory signals to chromatin by binding to transcriptional-memory-responsive genes to induce transcriptional activation. Flanked by permissive histone modifications, these PKC-enriched regions are significantly enriched with NF-κB motifs in ex vivo bulk and vaccinia-responsive human memory CD4⁺ T cells. Within the nucleus, PKC-θ catalytic activity maintains the Ser536 phosphorylation on the p65 subunit of NF-κB (also known as RelA) and can directly influence chromatin accessibility at transcriptional memory genes by regulating H2B deposition through Ser32 phosphorylation. Furthermore, using a cytoplasm-restricted PKC-θ mutant, we highlight that chromatin-anchored PKC-θ integrates activating signals at the chromatin template to elicit transcriptional memory responses in human memory T cells.

Summary: Memory T cells have a rapid transcriptional program upon re-stimulation. Chromatin-anchored PKC-θ integrates activating signals at the chromatin template to elicit this transcriptional memory in T cells.

Exploiting Gene-Expression Deconvolution to Probe the Genetics of the Immune System

Sequence variation can affect the physiological state of the immune system. Major experimental efforts targeted at understanding the genetic control of the abundance of immune cell subpopulations. However, these studies are typically focused on a limited number of immune cell types, mainly due to the use of relatively low throughput cell-sorting technologies. Here we present an algorithm that can reveal the genetic basis of inter-individual variation in the abundance of immune cell types using only gene expression and genotyping measurements as input. Our algorithm predicts the abundance of immune cell subpopulations based on the RNA levels of informative marker genes within a complex tissue, and then provides the genetic control on these predicted immune traits as output. A key feature of the approach is the integration of predictions from various sets of marker genes and refinement of these sets to avoid spurious signals. Our evaluation of both synthetic and real biological data shows the significant benefits of the new approach. Our method, VoCAL, is implemented in the freely available R package ComICS.

Quantitative trait locus (QTL) studies have identified a plethora of genetic variants that lead to inter-individual variation in the abundance of immune cell subpopulations, both in normal and disease states. Cell sorting is an effective method of monitoring immune cell type quantities; however, owing to the large number of possible immune cell subsets, it can be difficult to apply this method to each cell type over multiple individuals. Recent QTL studies dealt with this difficulty by focusing on an a priori selection of one or a few cell subsets. Here we introduce VoCAL, a deconvolution-based method that utilizes transcriptome data to infer the quantities of immune cell types, and then uses these quantitative traits to uncover the underlying DNA loci. Our results in synthetic data and lung cohorts show that the VoCAL method outperforms other alternatives in revealing the genetic basis of immune physiology.

Acute psychological stress induces short-term variable immune response

In spite of advances in understanding the cross-talk between the peripheral immune system and the brain, the molecular mechanisms underlying the rapid adaptation of the immune system to an acute psychological stressor remain largely unknown. Conventional approaches to classify molecular factors mediating these responses have targeted relatively few biological measurements or explored cross-sectional study designs, and therefore have restricted characterization of stress-immune interactions. This exploratory study analyzed transcriptional profiles and flow cytometric data of peripheral blood leukocytes with physiological (endocrine, autonomic) measurements collected throughout the sequence of events leading up to, during, and after short-term exposure to physical danger in humans. Immediate immunomodulation to acute psychological stress was defined as a short-term selective up-regulation of natural killer (NK) cell-associated cytotoxic and IL-12 mediated signaling genes that correlated with increased cortisol, catecholamines and NK cells into the periphery. In parallel, we observed down-regulation of innate immune toll-like receptor genes and genes of the MyD88-dependent signaling pathway. Correcting gene expression for an influx of NK cells revealed a molecular signature specific to the adrenal cortex. Subsequently, focusing analyses on discrete groups of coordinately expressed genes (modules) throughout the time-series revealed immune stress responses in modules associated to immune/defense response, response to wounding, cytokine production, TCR signaling and NK cell cytotoxicity which differed between males and females. These results offer a spring-board for future research towards improved treatment of stress-related disease including the impact of stress on cardiovascular and autoimmune disorders, and identifies an immune mechanism by which vulnerabilities to these diseases may be gender-specific.

CD4+ Group 1 Innate Lymphoid Cells (ILC) Form a Functionally Distinct ILC Subset That Is Increased in Systemic Sclerosis

Innate lymphoid cells (ILC) are a heterogeneous group of cellular subsets that produce large amounts of T cell-associated cytokines in response to innate stimulation in the absence of Ag. In this study, we define distinct patterns of surface marker and cytokine expression among the ILC subsets that may further delineate their migration and function. Most notably, we found that the subset previously defined as group 1 ILC (ILC1) contains CD4(+) CD8(-), CD4(-) CD8(+), and CD4(-) CD8(-) populations. Although all ILC1 subsets shared characteristics with Th1 cells, CD4(+) ILC1 also demonstrated significant phenotypic and functional heterogeneity. We also show that the frequencies of CD4(+) ILC1 and NKp44(+) group 3 ILC, but not CD4(-) ILC1 or group 2 ILC, are increased in the peripheral blood of individuals with systemic sclerosis (SSc), a disease characterized by fibrotic and vascular pathology, as well as immune dysregulation. Furthermore, we demonstrate that CD4(+) and CD4(-) ILC1 are functionally divergent based on their IL-6Rα expression and that the frequency of IL-6Rα expression on ILC is altered in SSc. The distinct phenotypic and functional features of CD4(+) and CD4(-) ILC1 suggest that they may have differing roles in the pathogenesis of immune-mediated diseases, such as SSc.

Association Between Response to Etrolizumab and Expression of Integrin αE and Granzyme A in Colon Biopsies of Patients With Ulcerative Colitis

BACKGROUND & AIMS

Etrolizumab is a humanized monoclonal antibody against the β7 integrin subunit that has shown efficacy vs placebo in patients with moderate to severely active ulcerative colitis (UC). Patients with colon tissues that expressed high levels of the integrin αE gene (ITGAE) appeared to have the best response. We compared differences in colonic expression of ITGAE and other genes between patients who achieved clinical remission with etrolizumab vs those who did.

METHODS

We performed a retrospective analysis of data collected from 110 patients with UC who participated in a phase 2 placebo-controlled trial of etrolizumab, as well as from 21 patients with UC or without inflammatory bowel disease (controls) enrolled in an observational study at a separate site. Colon biopsies were collected from patients in both studies and analyzed by immunohistochemistry and gene expression profiling. Mononuclear cells were isolated and analyzed by flow cytometry. We identified biomarkers associated with response to etrolizumab. In the placebo-controlled trial, clinical remission was defined as total Mayo Clinic Score ≤2, with no individual subscore >1, and mucosal healing was defined as endoscopic score ≤1.

RESULTS

Colon tissues collected at baseline from patients who had a clinical response to etrolizumab expressed higher levels of T-cell-associated genes than patients who did not respond (P < .05). Colonic CD4(+) integrin αE(+) cells from patients with UC expressed higher levels of granzyme A messenger RNA (GZMA mRNA) than CD4(+) αE(-) cells (P < .0001); granzyme A and integrin αE protein were detected in the same cells. Of patients receiving 100 mg etrolizumab, a higher proportion of those with high levels of GZMA mRNA (41%) or ITGAE mRNA (38%) than those with low levels of GZMA (6%) or ITGAE mRNA (13%) achieved clinical remission (P < .05) and mucosal healing (41% GZMA(high) vs 19% GZMA(low) and 44% ITGAE(high) vs 19% ITGAE(low)). Compared with ITGAE(low) and GZMA(low) patients, patients with ITGAE(high) and GZMA(high) had higher baseline numbers of epithelial crypt-associated integrin αE(+) cells (P < .01 for both), but a smaller number of crypt-associated integrin αE(+) cells after etrolizumab treatment (P < .05 for both). After 10 weeks of etrolizumab treatment, expression of genes associated with T-cell activation and genes encoding inflammatory cytokines decreased by 40%-80% from baseline (P < .05) in patients with colon tissues expressing high levels of GZMA at baseline.

CONCLUSIONS

Levels of GZMA and ITGAE mRNAs in colon tissues can identify patients with UC who are most likely to benefit from etrolizumab; expression levels decrease with etrolizumab administration in biomarker(high) patients. Larger, prospective studies of markers are needed to assess their clinical value.

Novel technologies and emerging biomarkers for personalized cancer immunotherapy

The culmination of over a century's work to understand the role of the immune system in tumor control has led to the recent advances in cancer immunotherapies that have resulted in durable clinical responses in patients with a variety of malignancies. Cancer immunotherapies are rapidly changing traditional treatment paradigms and expanding the therapeutic landscape for cancer patients. However, despite the current success of these therapies, not all patients respond to immunotherapy and even those that do often experience toxicities. Thus, there is a growing need to identify predictive and prognostic biomarkers that enhance our understanding of the mechanisms underlying the complex interactions between the immune system and cancer. Therefore, the Society for Immunotherapy of Cancer (SITC) reconvened an Immune Biomarkers Task Force to review state of the art technologies, identify current hurdlers, and make recommendations for the field. As a product of this task force, Working Group 2 (WG2), consisting of international experts from academia and industry, assembled to identify and discuss promising technologies for biomarker discovery and validation. Thus, this WG2 consensus paper will focus on the current status of emerging biomarkers for immune checkpoint blockade therapy and discuss novel technologies as well as high dimensional data analysis platforms that will be pivotal for future biomarker research. In addition, this paper will include a brief overview of the current challenges with recommendations for future biomarker discovery.

Seminal Plasma Promotes Lesion Development in a Xenograft Model of Endometriosis

The factors that predispose one-tenth of reproductive-aged women to endometriosis are poorly understood. We determined that genetic deficiency in transforming growth factor β1 impairs endometriosis-like lesion growth in mice. Given that seminal plasma is an abundant source of transforming growth factor β, we evaluated the effect of exposure to seminal plasma on the growth of endometrial lesions. Human endometrial explants were exposed to seminal plasma or to control medium before transfer to Prkdc(scid)-mutant (severe combined immunodeficient) mice. Xenografts exposed to seminal plasma showed an eightfold increase in volume and a 4.3-fold increase in weight after 14 days. These increases were associated with increased proliferation of endometrial epithelial cells and enhanced survival and proliferation of human stromal cells compared with those in control lesions, in which human stromal cell persistence was negligible. Although the distribution of macrophages was altered, their number and activation status did not change in response to seminal plasma. Seminal plasma stimulated the production of a variety of cytokines in endometrial tissue, including growth-regulated oncogene, granulocyte macrophage colony-stimulating factor, and IL-1β. These data suggest that seminal plasma enhances the formation of endometriosis-like lesion via a direct effect on endometrial cell survival and proliferation, rather than via macrophage-mediated mechanisms. These findings raise the possibility that endometrial exposure to seminal plasma could contribute to endometriotic disease progression in women.

Novel technologies and emerging biomarkers for personalized cancer immunotherapy

The culmination of over a century’s work to understand the role of the immune system in tumor control has led to the recent advances in cancer immunotherapies that have resulted in durable clinical responses in patients with a variety of malignancies. Cancer immunotherapies are rapidly changing traditional treatment paradigms and expanding the therapeutic landscape for cancer patients. However, despite the current success of these therapies, not all patients respond to immunotherapy and even those that do often experience toxicities. Thus, there is a growing need to identify predictive and prognostic biomarkers that enhance our understanding of the mechanisms underlying the complex interactions between the immune system and cancer. Therefore, the Society for Immunotherapy of Cancer (SITC) reconvened an Immune Biomarkers Task Force to review state of the art technologies, identify current hurdlers, and make recommendations for the field. As a product of this task force, Working Group 2 (WG2), consisting of international experts from academia and industry, assembled to identify and discuss promising technologies for biomarker discovery and validation. Thus, this WG2 consensus paper will focus on the current status of emerging biomarkers for immune checkpoint blockade therapy and discuss novel technologies as well as high dimensional data analysis platforms that will be pivotal for future biomarker research. In addition, this paper will include a brief overview of the current challenges with recommendations for future biomarker discovery.

Integrative analysis of breast cancer reveals prognostic haematopoietic activity and patient-specific immune response profiles

Transcriptional programmes active in haematopoietic cells enable a variety of functions including dedifferentiation, innate immunity and adaptive immunity. Understanding how these programmes function in the context of cancer can provide valuable insights into host immune response, cancer severity and potential therapy response. Here we present a method that uses the transcriptomes of over 200 murine haematopoietic cells, to infer the lineage-specific haematopoietic activity present in human breast tumours. Correlating this activity with patient survival and tumour purity reveals that the transcriptional programmes of many cell types influence patient prognosis and are found in environments of high lymphocytic infiltration. Collectively, these results allow for a detailed and personalized assessment of the patient immune response to a tumour. When combined with routinely collected patient biopsy genomic data, this method can enable a richer understanding of the complex interplay between the host immune system and cancer.

Evolution of the immune system in humans from infancy to old age

This article reviews the development of the immune response through neonatal, infant and adult life, including pregnancy, ending with the decline in old age. A picture emerges of a child born with an immature, innate and adaptive immune system, which matures and acquires memory as he or she grows. It then goes into decline in old age. These changes are considered alongside the risks of different types of infection, autoimmune disease and malignancy.