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Supplementary Figure 4 from Cyclophosphamide Augments Antitumor Immunity: Studies in an Autochthonous Prostate Cancer Model

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Cefazolin is a first-line antibiotic to treat infection related to deployment-associated blast injuries. Prior literature demonstrated a 331% increase cefazolin liver area under the curve (AUC) in mice exposed to a survivable blast compared with controls. We repeated the experiment, validated the findings, and established a semimechanistic two-compartment pharmacokinetic (PK) model with effect compartments representing the liver and skin. We found that blast statistically significantly increased the pseudo–partition coefficient to the liver by 326% (95% confidence interval: 76–737%), which corresponds to the observed 331% increase in cefazolin liver AUC described previously. To a lesser extent, plasma AUC in blasted mice increased 14–45% compared with controls. Nevertheless, the effects of blast on cefazolin PK were transient, normalizing by 10 hours after the dose. It is unclear as to how this blast effect t emporally translates to humans; however, given the short-lived effect on PK, there is insufficient evidence to recommend cefazolin dosing changes based on blast overpressure injury alone. Clinicians should be aware that cefazolin may cause drug-induced liver injury with a single dose and the risk may be higher in patients with blast overpressure injury based on our findings. SIGNIFICANCE STATEMENT Blast exposure significantly, but transiently, alters cefazolin pharmacokinetics in mice. The questions of whether other medications or potential long-term consequences in humans need further exploration.

Here, we describe genome sequences of 17 Pseudomonas aeruginosa phages, including therapeutic candidates. They belong to the families Myoviridae, Podoviridae, and Siphoviridae and six different genera. The genomes ranged in size from 42,788 to 88,805 bp, with G+C contents of 52.5% to 64.3%, and the numbers of coding sequences from 58 to 179., Here, we describe genome sequences of 17 Pseudomonas aeruginosa phages, including therapeutic candidates. They belong to the families Myoviridae, Podoviridae, and Siphoviridae and six different genera. The genomes ranged in size from 42,788 to 88,805 bp, with G+C contents of 52.5% to 64.3% and numbers of coding sequences from 58 to 179.

Modern combat-related injuries are often associated with acute polytrauma. As a consequence of severe combat-related injuries, a dysregulated immune response results in serious infectious complications. The gram-negative bacterium Pseudomonas aeruginosa is an opportunistic pathogen that often causes life-threatening bloodstream, lung, bone, urinary tract, and wound infections following combat-related injuries. The rise in the number of multidrug-resistant P. aeruginosa strains has elevated its importance to civilian clinicians and military medicine. Development of novel therapeutics and treatment options for P. aeruginosa infections is urgently needed. During the process of drug discovery and therapeutic testing, in vivo testing in animal models is a critical step in the bench-to-bedside approach, and required for Food and Drug Administration approval. Here, we review current and past literature with a focus on combat injury-relevant animal models often used to understand infection development, the interplay between P. aeruginosa and the host, and evaluation of novel treatments. Specifically, this review focuses on the following animal infection models: wound, burn, bone, lung, urinary tract, foreign body, and sepsis.

Introduction: Sepsis is one of the leading causes of death in military and civilian hospitals. Rapid identification of involved pathogens is a key step for appropriate diagnosis, treatment and ultimately survival. Current diagnostics tools are either very bulky and not deployment ready, or require a long time to provide results. Given these obstacles, new solutions are urgently needed. Optomagnetic Imaging Spectroscopy (OMIS) is novel technology successfully used for the detection of cancer cells and viruses. OMIS has high sensitivity due to recording the unpaired and paired electrons of sample material. Furthermore, machine learning that uses the algorithms random forest (RF) classifier and artificial neural network (ANN) is integrated into the technology to enhance detection. Here we evaluated the feasibility of OMIS for the detection of bacteria in blood. Methods: We used commercially available human blood spiked with a defined concentration multidrug resistant Staphylococcus aureus derived from a clinical isolate. Final concentrations of bacteria of 1 × 106, 1 × 105 and 1 × 104 CFU/mL corresponding to High (H), Medium (M) and Low (L) concentrations respectively. A total of 240 samples (60 samples per concentration as well as 60 samples of sterile blood (N)) was imaged, and the data were analyzed using random forest classifier and artificial neural network. Images for the training set and validation sets were separately obtained and used for comparison against true positive values (confirmatory plating on the nutrient agar). Results: The average score of classification samples in the correct category (N, L, M, H) one-by-one was 94% for the ANN algorithm, while for the RF algorithm accuracy was 93% (average means that three times different 40 samples (of 240 samples) were chosen, and each prediction test had different sample mixtures). The closeness of the two values of accuracy strongly indicates that the input data (interaction of light with paired and unpaired electrons) and output data (classification N, L, M, H concentration of bacteria) are correlated.

Post-traumatic stress disorder (PTSD) is a heterogeneous condition evidenced by the absence of objective physiological measurements applicable to all who meet the criteria for the disorder as well as divergent responses to treatments. This study capitalized on biological diversity observed within the PTSD group observed following epigenome-wide analysis of a well-characterized Discovery cohort (N = 166) consisting of 83 male combat exposed veterans with PTSD, and 83 combat veterans without PTSD in order to identify patterns that might distinguish subtypes. Computational analysis of DNA methylation (DNAm) profiles identified two PTSD biotypes within the PTSD+ group, G1 and G2, associated with 34 clinical features that are associated with PTSD and PTSD comorbidities. The G2 biotype was associated with an increased PTSD risk and had higher polygenic risk scores and a greater methylation compared to the G1 biotype and healthy controls. The findings were validated at a 3-year follow-up (N = 59) of the same individuals as well as in two independent, veteran cohorts (N = 54 and N = 38), and an active duty cohort (N = 133). In some cases, for example Dopamine-PKA-CREB and GABA-PKC-CREB signaling pathways, the biotypes were oppositely dysregulated, suggesting that the biotypes were not simply a function of a dimensional relationship with symptom severity, but may represent distinct biological risk profiles underpinning PTSD. The identification of two novel distinct epigenetic biotypes for PTSD may have future utility in understanding biological and clinical heterogeneity in PTSD and potential applications in risk assessment for active duty military personnel under non-clinician-administered settings, and improvement of PTSD diagnostic markers.

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The experimental pathophysiology of organophosphorus (OP) chemical exposure has been extensively reported. Here, we describe an altered fecal bacterial biota and urine metabolome following intoxication with soman, a lipophilic G class chemical warfare nerve agent. Nonanesthetized Sprague-Dawley male rats were subcutaneously administered soman at 0.8 (subseizurogenic) or 1.0 (seizurogenic) of the 50% lethal dose (LD(50)) and evaluated for signs of toxicity. Animals were stratified based on seizing activity to evaluate effects of soman exposure on fecal bacterial biota and urine metabolites. Soman exposure reshaped fecal bacterial biota by altering Facklamia, Rhizobium, Bilophila, Enterobacter, and Morganella genera of the Firmicutes and Proteobacteria phyla, some of which are known to hydrolyze OP chemicals. However, analogous changes were not observed in the bacterial biota of the ileum, which remained the same irrespective of dose or seizing status of animals after soman intoxication. However, at 75 days after soman exposure, the bacterial biota stabilized and no differences were observed between groups. Interestingly, in considering just the seizing status of animals, we found that the urine metabolomes were markedly different. Leukotriene C(4), kynurenic acid, 5-hydroxyindoleacetic acid, norepinephrine, and aldosterone were excreted at much higher rates at 72 h in seizing animals, consistent with early multiorgan involvement during soman poisoning. These findings demonstrate the feasibility of using the dysbiosis of fecal bacterial biota in combination with urine metabolome alterations as forensic evidence for presymptomatic OP exposure temporally to enable administration of neuroprotective therapies of the future. IMPORTANCE The paucity of assays to determine physiologically relevant OP exposure presents an opportunity to explore the use of fecal bacteria as sentinels in combination with urine to assess changes in the exposed host. Recent advances in sequencing technologies and computational approaches have enabled researchers to survey large community-level changes of gut bacterial biota and metabolomic changes in various biospecimens. Here, we profiled changes in fecal bacterial biota and urine metabolome following a chemical warfare nerve agent exposure. The significance of this work is a proof of concept that the fecal bacterial biota and urine metabolites are two separate biospecimens rich in surrogate indicators suitable for monitoring OP exposure. The larger value of such an approach is that assays developed on the basis of these observations can be deployed in any setting with moderate clinical chemistry and microbiology capability. This can enable estimation of the affected radius as well as screening, triage, or ruling out of suspected cases of exposures in mass casualty scenarios, transportation accidents involving hazardous materials, refugee movements, humanitarian missions, and training settings when coupled to an established and validated decision tree with clinical features.

The experimental pathophysiology of organophosphorus (OP) chemical exposure has been extensively reported. Here, we describe an altered fecal microbiota and urine metabolome that follows intoxication with soman, a lipophilic G class chemical warfare nerve agent. Non-anaesthetized Sprague-Dawley male rats were subcutaneously administered soman at 0.8 - 1.0 of the median lethal dose (LD50) and evaluated for signs of toxicity. Animals were stratified based on seizing activity to evaluate effects of soman exposure on fecal bacterial biota and urine metabolites. Soman exposure reshaped fecal bacterial biota by preferentially expandingFacklamia, Agrobacterium,Bilophila,Enterobacter, andMorganellagenera of theFirmicutesandProteobacteriaphyla, some of which are known to hydrolyze OPs. However, analogous changes were not observed in the bacterial biota of the ileum, which remained the same irrespective of dose or seizing status of animals after exposure. Interestingly, when considering just the seizing status of animals, we found that the urine metabolome was markedly altered. Leukotriene C4, kynurenic acid, 5-hydroxyindoleacetic acid, norepinephrine, and aldosterone were excreted at much higher rates at 72 hrs in seizing animals, consistent with early multi-organ involvement during soman poisoning. However, at 75 days post soman exposure, bacterial biota stabilized and no differences were observed. These findings demonstrate the feasibility of using the dysbiosis of fecal bacterial biota in combination with urine metabolome alterations as forensic evidence for OP exposure temporally.ImportanceThe paucity of assays to determine physiologically relevant OP exposure presents an opportunity to explore the use bacterial sentinels in combination with urine to assess changes in the exposed host. Recent advances in technologies and computational approaches have enabled researches to survey large community level changes of gut bacterial biota and metabolomic changes in various biospecimens. Here, we profile combined changes in bacterial biota and urine metabolome due to chemical warfare OP exposure. The significance of our work is to reveal that monitoring bacterial biota and urine metabolites as surrogates of OP exposure in biospecimens suitable for existing clinical laboratory workflows is plausible without the need for the development of new technology, invasive procedures, or complicated analytical approaches. The larger value of such an approach is that any setting with a moderate clinical chemistry and microbiology capability can determine pre-symptomatic exposure to enhance current triage standards in case of mass exposures, refugee movements, humanitarian missions, and training settings once an algorithm has been validated. In the event of “potential” exposures by time or distance, this assay can be further developed to estimate affected radius or time dimension for health monitoring and treatment interventions.

Interleukin-17 (IL-17) belongs to a relatively new family of cytokines that has garnered attention as the signature cytokine of Th17 cells. This cytokine family consists of 6 ligands, which bind to 5 receptor subtypes and induce downstream signaling. Although the receptors are ubiquitously expressed, cellular responses to ligands vary across tissues. The cytokine family is associated with various autoimmune disorders including rheumatoid arthritis, multiple sclerosis, inflammatory bowel disease, asthma and psoriasis in addition to being implicated in the pathogenesis of cancer. In addition, this family plays a role in host defense against bacterial and fungal infections. The signaling mechanisms of the IL-17 family of proinflammatory cytokines are not well explored. In this study, we present a resource of literature-annotated reactions induced by IL-17. The reactions are catalogued under 5 categories, namely; molecular association, catalysis, transport, activation/inhibition and gene regulation. A total of 93 molecules and 122 reactions have been annotated. The IL-17 pathway is freely available through NetPath, a resource of signal transduction pathways previously developed by our group.

Anopheles gambiae has a well-adapted system for host localization, feeding, and mating behavior, which are all governed by neuronal processes in the brain. However, there are no published reports characterizing the brain proteome to elucidate neuronal signaling mechanisms in the vector. To this end, a large-scale mapping of the brain proteome of An. gambiae was carried out using high resolution tandem mass spectrometry, revealing a repertoire of >1800 proteins, of which 15% could not be assigned any function. A large proportion of the identified proteins were predicted to be involved in diverse biological processes including metabolism, transport, protein synthesis, and olfaction. This study also led to the identification of 10 GPCR classes of proteins, which could govern sensory pathways in mosquitoes. Proteins involved in metabolic and neural processes, chromatin modeling, and synaptic vesicle transport associated with neuronal transmission were predominantly expressed in the brain. Proteogenomic analysis expanded our findings with the identification of 15 novel genes and 71 cases of gene refinements, a subset of which were validated by RT-PCR and sequencing. Overall, our study offers valuable insights into the brain physiology of the vector that could possibly open avenues for intervention strategies for malaria in the future.

The availability of human genome sequence has transformed biomedical research over the past decade. However, an equivalent map for the human proteome with direct measurements of proteins and peptides does not exist yet. Here we present a draft map of the human proteome using high-resolution Fourier-transform mass spectrometry. In-depth proteomic profiling of 30 histologically normal human samples, including 17 adult tissues, 7 fetal tissues and 6 purified primary haematopoietic cells, resulted in identification of proteins encoded by 17,294 genes accounting for approximately 84% of the total annotated protein-coding genes in humans. A unique and comprehensive strategy for proteogenomic analysis enabled us to discover a number of novel protein-coding regions, which includes translated pseudogenes, non-coding RNAs and upstream open reading frames. This large human proteome catalogue (available as an interactive web-based resource at http://www.humanproteomemap.org) will complement available human genome and transcriptome data to accelerate biomedical research in health and disease.

Purpose To optimize the combination of ionizing radiation and cellular immunotherapy using a preclinical autochthonous model of prostate cancer. Methods and Materials Transgenic mice expressing a model antigen under a prostate-specific promoter were treated using a platform that integrates cone-beam CT imaging with 3-dimensional conformal therapy. Using this technology we investigated the immunologic and therapeutic effects of combining ionizing radiation with granulocyte/macrophage colony-stimulating factor-secreting cellular immunotherapy for prostate cancer in mice bearing autochthonous prostate tumors. Results The combination of ionizing radiation and immunotherapy resulted in a significant decrease in pathologic tumor grade and gross tumor bulk that was not evident with either single-modality therapy. Furthermore, combinatorial therapy resulted in improved overall survival in a preventive metastasis model and in the setting of established micrometastases. Mechanistically, combined therapy resulted in an increase of the ratio of effector-to-regulatory T cells for both CD4 and CD8 tumor-infiltrating lymphocytes. Conclusions Our preclinical model establishes a potential role for the use of combined radiation-immunotherapy in locally advanced prostate cancer, which warrants further exploration in a clinical setting.

Tissue microarrays have become a valuable tool for high-throughput analysis using immunohistochemical labeling. However, the large majority of biochemical studies are carried out in cell lines to further characterize candidate biomarkers or therapeutic targets with subsequent studies in animals or using primary tissues. Thus, cell line-based microarrays could be a useful screening tool in some situations. Here, we constructed a cell microarray (CMA) containing a panel of 40 pancreatic cancer cell lines available from American Type Culture Collection in addition to those locally available at Johns Hopkins. As proof of principle, we performed immunocytochemical labeling of an epithelial cell adhesion molecule (Ep-CAM), a molecule generally expressed in the epithelium, on this pancreatic cancer CMA. In addition, selected molecules that have been previously shown to be differentially expressed in pancreatic cancer in the literature were validated. For example, we observed strong labeling of CA19-9 antigen, a prognostic and predictive marker for pancreatic cancer. We also carried out a bioinformatics analysis of a literature curated catalog of pancreatic cancer biomarkers developed previously by our group and identified two candidate biomarkers, HLA class I and transmembrane protease, serine 4 (TMPRSS4), and examined their expression in the cell lines represented on the pancreatic cancer CMAs. Our results demonstrate the utility of CMAs as a useful resource for rapid screening of molecules of interest and suggest that CMAs can become a universal standard platform in cancer research.

Objective Multinucleated cells are relatively resistant to classic apoptosis, and the factors initiating cell death and damage in myositis are not well defined. We hypothesized that nonimmune autophagic cell death may play a role in muscle fiber damage. Recent reports indicate that TRAIL may induce both NF-κB activation and autophagic cell death in other systems. We undertook this study to investigate the role of TRAIL in cell death and pathogenesis in vitro and in vivo, using myositis muscle tissues from humans and mice. Methods Gene expression profiling was performed in myositis patient and control muscle specimens. Immunohistochemistry analysis was performed to confirm the gene array findings. We also analyzed TRAIL-induced cell death (apoptosis and autophagy) and NF-κB activation in vitro in cultured cells. Results TRAIL was expressed predominantly in myositis muscle fibers, but not in biopsy specimens from normal or other dystrophic-diseased muscle. Autophagy markers were up-regulated in humans with myositis and in mouse models of myositis. TRAIL expression was restricted to regenerating/atrophic areas of muscle fascicles, blood vessels, and infiltrating lymphocytes. TRAIL induced NF-κB activation and IκB degradation in cultured cells that are resistant to TRAIL-induced apoptosis but that undergo autophagic cell death. Conclusion Our data demonstrate that TRAIL is expressed in myositis muscle and may mediate both activation of NF-κB and autophagic cell death in myositis. Thus, this nonimmune pathway may be an attractive target for therapeutic intervention in myositis.

Anopheles gambiae is a major vector for malaria, which is a main public health burden in many parts of the world. The first draft of the An. gambiae genome sequence was released in 2002 containing ∼278 Mb (Holt et al. 2002). Mongin et al. (2004) discussed the limitations associated with this genome assembly. A gene set annotated by VectorBase contains both manually annotated genes and predicted gene models from GeneWise (Birney et al. 2004), ClusterMerge (Eyras et al. 2004), and SNAP (Li et al. 2007) algorithms. The VectorBase bioinformatic resource provides several annotated and curated vector genomes in a Web-accessible integrated format including DNA and protein alignments (Lawson et al. 2009). Based on manual appraisal, the VectorBase (http://agambiae.VectorBase.org) updated the Anopheles gambiae genebuild (AgamP3.5) in September 2009, which contained 12,604 protein-coding genes. The updated gene sets include 765 novel genes, modification of 3726 gene models, and deletion of 456 genes. The latest genebuild, AgamP3.6, was released in December 2010, which contains 12,669 protein-coding genes. This release includes 227 new genes, changes to the structure of 443 gene models, and deletion of three genes as compared to the AgamP3.5 genebuild. In the VectorBase–Ensembl genome annotation pipeline, genes are annotated based on mRNA/cDNA sequences and comparative proteomic evidence, as well as manual appraisal. Manually annotated gene models are given the highest preference followed by comparative gene models, EST-based models, and ab initio gene models. GeneWise-based prediction uses alignment of dipterans and other protein sequences to the An. gambiae genome for building gene models. The ClusterMerge algorithm builds models based on EST evidence (Eyras et al. 2004). The SNAP and Genscan algorithms were used to predict ab initio models that are also included in the current genebuild (Korf 2004). In the present study, we present many novel findings that were missed in spite of a robust annotation strategy and multiple revisions of An. gambiae genome annotations. The reverse process of genome annotation, i.e., from proteins to the genome, holds great promise for increasing the accuracy of the predicted gene structures. Annotation of genomes using mass spectrometry–based proteomics data is complementary to other gene prediction methods. Direct evidence for the protein-coding potential of the genome sequence can be obtained by searching tandem mass spectrometry data against nucleotide sequences like ESTs or genome sequence databases as against known protein databases (Pandey and Lewitter 1999; Pandey and Mann 2000; Choudhary et al. 2001; Mann and Pandey 2001; Xia et al. 2008). Certain features of peptides can provide definitive evidence pertaining to protein architecture that cannot be obtained from genome or transcript sequencing, e.g., acetylation of N termini of peptides, which indicates proximity to the translation start sites. An important outcome of such analyses is the identification of novel genes that have been entirely missed by other approaches. Protein-coding genes leading to splice variants, truncated proteins, and cSNPs can all also be directly studied by protein sequencing. Several studies have demonstrated the use of mass spectrometry–based proteomic approaches to validate or correct gene annotations in Homo sapiens (Molina et al. 2005; Suzuki and Sugano 2006; Sevinsky et al. 2008; Menon et al. 2009), Caenorhabditis elegans (Merrihew et al. 2008), Drosophila melanogaster (Brunner et al. 2007; Tress et al. 2008), An. gambiae (Pandey and Mann 2000; Kalume et al. 2005a,b; Okulate et al. 2007), Toxoplasma gondii (Xia et al. 2008), and Arabidopsis thaliana (Kuster et al. 2001; Baerenfaller et al. 2008). Here, we present the results of an extensive qualitative proteomic analysis of An. gambiae to better understand gene structures and their functions. We report validation of existing genes, correction of existing gene models, identification of novel genes, identification of novel splice variants, confirmation of splice sites, and assignment of translational start sites based on high-resolution mass spectrometry–derived data. A total of 2682 peptides were identified that could not be mapped onto existing VectorBase annotations. We also used gene prediction models by SNAP, and in some cases by Fgenesh and GenMark, which supported the peptide evidence to identify novel genes or alternate gene models. Finally, we performed RT-PCR and sequencing to support the existence of a number of novel and modified coding regions identified in this study.

BACKGROUND The CD8 T-cell response to prostate and other cancers is often functionally diminished or absent. This may occur via deletion of tumor-specific T cells, through acquisition of an anergic phenotype, or via active suppression mediated by another population of cells. METHODS We used a double transgenic model in which mice express CD8 T cells specific for a prostate/prostate cancer antigen to study the response of CD8 T cells to evolving autochronous prostate tumors in TRAMP mice. CD8 T cells were analyzed for functionality by measuring IFN-γ production via flow cytometry and via an in vivo CTL killing assay. In addition, pathological scoring of the prostates of the double transgenic mice was compared to scoring of tumor burden prostates of ProTRAMP mice. RESULTS Tumor-specific CD8 T cells were not grossly deleted in these animals, but evidenced a clearly non-functional phenotype. Interestingly, full lytic function was rapidly recovered upon removal from tumor-bearing mice. CONCLUSIONS These data indicate a role for continuous antigen exposure in the maintenance of tumor-specific CD8 T-cell tolerance to prostate cancer. Prostate 72:514–522, 2012. © 2011 Wiley Periodicals, Inc.

Relative upregulation of the Ikaros family transcription factor Helios in natural regulatory T cells (Tregs) has been reported by several groups. However, a role for Helios in regulatory T cells has not yet been described. Here, we show that Helios is upregulated in CD4(+)CD25(+) regulatory T cells. Chromatin-immunoprecipitation (ChIP) experiments indicated that Helios binds to the FoxP3 promoter. These data were further corroborated by experiments showing that knocking-down Helios with siRNA oligonucleotides results in down-regulation of FoxP3. Functionally, we found that suppression of Helios message in CD4(+)CD25(+) T cells significantly attenuates their suppressive function. Taken together, these data suggest that Helios may play an important role in regulatory T cell function and support the concept that Helios may be a novel target to manipulate Treg activity in a clinical setting.

Tumors express a wide variety of both mutated and nonmutated Ags. Whether these tumor Ags are broadly recognized as self or foreign by the immune system is currently unclear. Using an autochthonous prostate cancer model in which hemagglutinin (HA) is specifically expressed in the tumor (ProHA × TRAMP mice), as well as an analogous model wherein HA is expressed in normal tissues as a model self-Ag (C3HAhigh), we examined the transcriptional profile of CD4 T cells undergoing Ag-specific division. Consistent with our previous data, transfer of Ag-specific CD4 T cells into C3HAhigh resulted in a functionally inactivated CD4 T cell profile. Conversely, adoptive transfer of an identical CD4 T cell population into ProHA × TRAMP mice resulted in the induction of a regulatory phenotype of the T cell (Treg) both at the transcriptional and functional level. Interestingly, this Treg skewing was a property of even early-stage tumors, suggesting Treg induction as an important tolerance mechanism during tumor development.

Background Cellular function and diversity are orchestrated by complex interactions of fundamental biomolecules including DNA, RNA and proteins. Technological advances in genomics, epigenomics, transcriptomics and proteomics have enabled massively parallel and unbiased measurements. Such high-throughput technologies have been extensively used to carry out broad, unbiased studies, particularly in the context of human diseases. Nevertheless, a unified analysis of the genome, epigenome, transcriptome and proteome of a single human cell type to obtain a coherent view of the complex interplay between various biomolecules has not yet been undertaken. Here, we report the first multi-omic analysis of human primary naïve CD4+ T cells isolated from a single individual. Results Integrating multi-omics datasets allowed us to investigate genome-wide methylation and its effect on mRNA/protein expression patterns, extent of RNA editing under normal physiological conditions and allele specific expression in naïve CD4+ T cells. In addition, we carried out a multi-omic comparative analysis of naïve with primary resting memory CD4+ T cells to identify molecular changes underlying T cell differentiation. This analysis provided mechanistic insights into how several molecules involved in T cell receptor signaling are regulated at the DNA, RNA and protein levels. Phosphoproteomics revealed downstream signaling events that regulate these two cellular states. Availability of multi-omics data from an identical genetic background also allowed us to employ novel proteogenomics approaches to identify individual-specific variants and putative novel protein coding regions in the human genome. Conclusions We utilized multiple high-throughput technologies to derive a comprehensive profile of two primary human cell types, naïve CD4+ T cells and memory CD4+ T cells, from a single donor. Through vertical as well as horizontal integration of whole genome sequencing, methylation arrays, RNA-Seq, miRNA-Seq, proteomics, and phosphoproteomics, we derived an integrated and comparative map of these two closely related immune cells and identified potential molecular effectors of immune cell differentiation following antigen encounter. Electronic supplementary material The online version of this article (doi:10.1186/s12918-015-0225-4) contains supplementary material, which is available to authorized users.

Distribution of assembled transcripts based on abundance (FPKM) and corresponding read density. The x-axis represents abundance threshold (FPKM) and y-axis represents read density. The red and green lines represent the Gaussian Mixture Model that was applied to assembled transcripts. The abundance threshold (represented by vertical dotted line) separates transcripts identified as true positives on the right (supported by more reads) from those identified as potential false positives on the left (supported by less reads). The two screenshots taken from genome browser demonstrates examples of high read density and low read density. (PDF 226 kb)

Strategy employed for determining potential RNA editing sites . The workflow that was followed to filter out false positive RNA-editing sites is shown. Examples of false positives due to mismapping of reads and uncalled SNPs is demonstrated with sequence alignment. Abbreviations (SNP: single nucleotide polymorphism; RDD: RNA-DNA difference; CNV: copy number variation). (PDF 65 kb)

Sequence variants identified in the genome and classification of SNPs in protein coding regions. (A) Total number of SNPs, insertions, deletions and substitutions identified from whole genome sequencing data. (B) Proportion of synonymous and non-synonymous SNPs identified in the coding region of the genome among non-synonymous SNPs (nsSNPs), proportion of conservative and non-conservative homozygous and heterozygous changes are shown. (C) nsSNP frequency across various molecular classes of genes. (PDF 68 kb)

Example of a miRNA identified and the distribution of reads across a predicted hairpin structure. Putative novel miRNA identified from small RNA-Seq. Predicted stem loop structure, mature region and star regions are shown. (PDF 50 kb)

Accurate annotation of protein-coding genes is one of the primary tasks upon the completion of whole genome sequencing of any organism. In this study, we used an integrated transcriptomic and proteomic strategy to validate and improve the existing zebrafish genome annotation. We undertook high-resolution mass-spectrometry-based proteomic profiling of 10 adult organs, whole adult fish body, and two developmental stages of zebrafish (SAT line), in addition to transcriptomic profiling of six organs. More than 7,000 proteins were identified from proteomic analyses, and ∼ 69,000 high-confidence transcripts were assembled from the RNA sequencing data. Approximately 15% of the transcripts mapped to intergenic regions, the majority of which are likely long non-coding RNAs. These high-quality transcriptomic and proteomic data were used to manually reannotate the zebrafish genome. We report the identification of 157 novel protein-coding genes. In addition, our data led to modification of existing gene structures including novel exons, changes in exon coordinates, changes in frame of translation, translation in annotated UTRs, and joining of genes. Finally, we discovered four instances of genome assembly errors that were supported by both proteomic and transcriptomic data. Our study shows how an integrative analysis of the transcriptome and the proteome can extend our understanding of even well-annotated genomes.

Background The FDA recently approved an anti-CTLA-4 antibody (Iplimumab) for the treatment of metastatic melanoma. This decision was based on Phase III results, which demonstrate that blocking this immune checkpoint provides a survival advantage in patients with advanced disease. As a single agent, ipilimumab is also being clinically evaluated in advanced (metastatic, castrate-resistant) prostate cancer and two randomized, placebo-controlled Phase III studies have recently completed accrual. Methods We used a well-described genetically engineered mouse (GEM), autochronous prostate cancer model (Pro-TRAMP) to explore the relative sequencing and dosing of anti-CTLA-4 antibody when combined with a cell-based, GM-CSF-secreting vaccine (GVAX). Results Our results show that combined treatment results in a dramatic increase in effector CD8 T cells in the prostate gland, and enhanced tumor-antigen directed lytic function. These effects are maximized when CTLA-4 blockade is applied after, but not before, vaccination. Additional experiments, using models of metastatic disease, show that incorporation of low-dose cyclophosphamide into this combined treatment regimen results in an additional pre-clinical benefit. Conclusions Together these studies define a combination regimen using anti-CTLA-4/GVAX immunotherapy and low-dose chemotherapy for potential translation to a clinical trial setting.

Dicer is a ribonuclease whose major role is to generate mature microRNAs, although additional functions have been proposed. Deletion of Dicer leads to embryonic lethality in mice. To study the role of Dicer in adults, we generated mice in which administration of tamoxifen induces deletion of Dicer. Surprisingly, disruption of Dicer in adult mice induced lipid accumulation in the small intestine. To dissect the underlying mechanisms, we carried out miRNA, mRNA, and proteomic profiling of the small intestine. The proteomic analysis was done using mice metabolically labeled with heavy lysine (SILAC mice) for an in vivo readout. We identified 646 proteins, of which 80 were up-regulated2-fold and 75 were down-regulated. Consistent with the accumulation of lipids, Dicer disruption caused a marked decrease of microsomal triglyceride transfer protein, long-chain fatty acyl-CoA ligase 5, fatty acid binding protein, and very-long-chain fatty acyl-CoA dehydrogenase, among others. We validated these results using multiple reaction monitoring (MRM) experiments by targeting proteotypic peptides. Our data reveal a previously unappreciated role of Dicer in lipid metabolism. These studies demonstrate that a systems biology approach by integrating mouse models, metabolic labeling, gene expression profiling, and quantitative proteomics can be a powerful tool for understanding complex biological systems.

Helios, an Ikaros family transcription factor, is preferentially expressed at the mRNA and protein level in regulatory T cells. Helios expression previously appeared to be restricted to thymic-derived Treg. Consistent with recent data, we show here that Helios expression is inducible in vitro under certain conditions. To understand phenotypic and functional differences between Helios(+) and Helios(-) Treg, we profiled cell-surface markers of FoxP3(+) Treg using unmanipulated splenocytes. We found that CD103 and GITR are expressed at high levels on a subset of Helios(+) Treg and that a Helios(+) Treg population could be significantly enriched by FACS sorting using these two markers. Quantitative real-time PCR (qPCR) analysis revealed increased TGF-β message in Helios(+) Treg, consistent with the possibility that this population possesses enhanced regulatory potential. In tumor-bearing mice, we found that Helios(+) Treg were relatively over-represented in the tumor-mass, and BrdU studies showed that, in vivo, Helios(+) Treg proliferated more than Helios(-) Treg. We hypothesized that Helios-enriched Treg might exert increased suppressive effects. Using in vitro suppression assays, we show that Treg function correlates with the absolute number of Helios(+) cells in culture. Taken together, these data show that Helios(+) Treg represent a functional subset with associated CD103 and GITR expression.

T reg Responses to Eos CD4 + regulatory T cells (T regs ) are critical for keeping our immune system in check: They prevent immune responses from getting out of hand and keep autoimmunity at bay. By activating the expression of some genes and turning off expression of others, the master regulatory transcription factor of T regs , Foxp3, endows these cells with the appropriate gene expression program to mediate their suppressive effects. Pan et al. (p. 1142 , published online 20 August) now demonstrate that the transcription factor Eos is selectively required for Foxp3-mediated gene suppression in mice. Genes normally suppressed by Foxp3 in T regs remained “on” when Eos expression was suppressed, whereas genes activated by Foxp3 were unaffected. T reg function was also affected by Eos suppression. With half their genetic program disrupted, these cells resembled an intermediate between T regs and conventional CD4 + T cells—unable to suppress immune responses properly and partially responsive to T cell–activating stimulation.

To study the immune response to prostate cancer, we developed an autochthonous animal model based on the transgenic adenocarcinoma of the mouse prostate (TRAMP) mouse in which spontaneously developing tumors express influenza hemagglutinin as a unique, tumor-associated antigen. Our prior studies in these animals showed immunologic tolerance to hemagglutinin, mirroring the clinical situation in patients with cancer who are generally nonresponsive to their disease. We used this physiologically relevant animal model to assess the immunomodulatory effects of cyclophosphamide when administered in combination with an allogeneic, cell-based granulocyte-macrophage colony-stimulating factor–secreting cancer immunotherapy. Through adoptive transfer of prostate/prostate cancer–specific CD8 T cells as well as through studies of the endogenous T-cell repertoire, we found that cyclophosphamide induced a marked augmentation of the antitumor immune response. This effect was strongly dependent on both the dose and the timing of cyclophosphamide administration. Mechanistic studies showed that immune augmentation by cyclophosphamide was associated with a transient depletion of regulatory T cells in the tumor draining lymph nodes but not in the peripheral circulation. Interestingly, we also noted effects on dendritic cell phenotype; low-dose cyclophosphamide was associated with increased expression of dendritic cell maturation markers. Taken together, these data clarify the dose, timing, and mechanism of action by which immunomodulatory cyclophosphamide can be translated to a clinical setting in a combinatorial cancer treatment strategy. [Cancer Res 2009;69(10):4309–18]

BACKGROUND Cancer immunotherapy refers to an array of strategies intended to treat progressive tumors by augmenting a patient's anti-tumor immune response. As immunotherapy is eventually incorporated into oncology treatment paradigms, it is important to understand how these therapies interact with established cancer treatments such as chemotherapy or Radiotherapy (RT). To address this, we utilized a well-established, autochthonous murine model of prostate cancer to test whether RT could augment (or diminish) the CD4 T cell response to a tumor vaccine. METHODS Transgenic mice that develop spontaneous prostate cancer (TRAMP) which also express a unique tumor associated antigen (Influenza hemagglutinin) under the control of a prostate-specific promoter were given local RT in combination with immunotherapy. The immunological outcome of this combinatorial strategy was assayed by monitoring the effector response of adoptively transferred, prostate-specific CD4 T cells. RESULTS Neither RT nor immunotherapy alone was capable of priming an anti-tumor immune response in animals with evolving tumors. The combination of immunotherapy with RT resulted in anti-tumor T cell activation—this effect was profoundly dependent on the relative timing of RT and immunotherapy. Anti-tumor immune responses occurred when immunotherapy was administered 3–5 weeks post-RT, but such responses were undetectable when immunotherapy was administered either earlier (peri-radiothrerapy) or later. CONCLUSIONS The therapeutic temporal window of immunotherapy post-RT suggests that highly aggressive, immuno-suppressive tumors might be most sensitive to immunotherapy in a fairly narrow time window; these results should help to guide future development of clinical combinatorial strategies. Prostate 68:1319–1329, 2008. © 2008 Wiley-Liss, Inc.

Lymphocyte activation gene-3 (LAG-3) is a cell-surface molecule with diverse biologic effects on T cell function. We recently showed that LAG-3 signaling is important in CD4+ regulatory T cell suppression of autoimmune responses. Here, we demonstrate that LAG-3 maintains tolerance to self and tumor antigens via direct effects on CD8+ T cells using 2 murine systems. Naive CD8+ T cells express low levels of LAG-3, and expression increases upon antigen stimulation. Our data show increased levels of LAG-3 protein on antigen-specific CD8+ T cells within antigen-expressing organs or tumors. In vivo antibody blockade of LAG-3 or genetic ablation of the Lag-3 gene resulted in increased accumulation and effector function of antigen-specific CD8+ T cells within organs and tumors that express their cognate antigen. Most notably, combining LAG-3 blockade with specific antitumor vaccination resulted in a significant increase in activated CD8+ T cells in the tumor and disruption of the tumor parenchyma. A major component of this effect was CD4 independent and required LAG-3 expression by CD8+ T cells. Taken together, these data demonstrate a direct role for LAG-3 on CD8+ T cells and suggest that LAG-3 blockade may be a potential cancer treatment.

STAT3 activation has been observed in several autoimmune diseases, suggesting that STAT3-mediated pathways promote pathologic immune responses. We provide in vivo evidence that the fundamental role of STAT3 signaling in autoimmunity relates to its absolute requirement for generating TH17 T cell responses. We show that STAT3 is a master regulator of this pathogenic T cell subtype, acting at multiple levels in vivo, including TH17 T cell differentiation and cytokine production, as well as induction of RORγt and the IL-23R. Neither naturally occurring TH17 cells nor TH17-dependent autoimmunity occurs when STAT3 is ablated in CD4 cells. Furthermore, ablation of STAT3 signaling in CD4 cells results in increased TH1 responses, indicating that STAT3 signaling skews TH responses away from the TH1 pathway and toward the TH17 pathway. Thus, STAT3 is a candidate target for TH17-dependent autoimmune disease immunotherapy that could selectively inhibit pathogenic immune pathways.

Thymic stromal lymphopoietin (TSLP) is a cytokine that plays diverse roles in the regulation of immune responses. TSLP requires a heterodimeric receptor complex consisting of IL-7 receptor α subunit and its unique TSLP receptor (gene symbol CRLF2) to transmit signals in cells. Abnormal TSLP signaling (e.g. overexpression of TSLP or its unique receptor TSLPR) contributes to the development of a number of diseases including asthma and leukemia. However, a detailed understanding of the signaling pathways activated by TSLP remains elusive. In this study, we performed a global quantitative phosphoproteomic analysis of the TSLP signaling network using stable isotope labeling by amino acids in cell culture. By employing titanium dioxide in addition to antiphosphotyrosine antibodies as enrichment methods, we identified 4164 phosphopeptides on 1670 phosphoproteins. Using stable isotope labeling by amino acids in cell culture-based quantitation, we determined that the phosphorylation status of 226 proteins was modulated by TSLP stimulation. Our analysis identified activation of several members of the Src and Tec families of kinases including Btk, Lyn, and Tec by TSLP for the first time. In addition, we report TSLP-induced phosphorylation of protein phosphatases such as Ptpn6 (SHP-1) and Ptpn11 (Shp2), which has also not been reported previously. Co-immunoprecipitation assays showed that Shp2 binds to the adapter protein Gab2 in a TSLP-dependent manner. This is the first demonstration of an inducible protein complex in TSLP signaling. A kinase inhibitor screen revealed that pharmacological inhibition of PI-3 kinase, Jak family kinases, Src family kinases or Btk suppressed TSLP-dependent cellular proliferation making them candidate therapeutic targets in diseases resulting from aberrant TSLP signaling. Our study is the first phosphoproteomic analysis of the TSLP signaling pathway that greatly expands our understanding of TSLP signaling and provides novel therapeutic targets for TSLP/TSLPR-associated diseases in humans.