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Sepsis is an aberrant systemic inflammatory response mediated by the acute activation of the innate immune system. Neutrophils are important contributors to the innate immune response that controls the infection, but harbour the risk of collateral tissue damage such as thrombosis and organ dysfunction. A better understanding of the modulations of cellular processes in neutrophils and other blood cells during sepsis is needed and can be initiated via transcriptomic profile investigations. To that point, the growing repertoire of publicly accessible transcriptomic datasets serves as a valuable resource for discovering and/or assessing the robustness of biomarkers. We employed systematic literature mining, reductionist approach to gene expression profile and empirical in vitro work to highlight the role of a Nudix hydrolase family member, NUDT16, in sepsis. The relevance and implication of the expression of NUDT16 under septic conditions and the putative functional roles of this enzyme are discussed.

Viruses are the second leading cause of cancer worldwide, and human papillomavirus (HPV)-associated head and neck cancers are increasing in incidence in the United States. HPV preferentially infects the crypts of the tonsils rather than the surface epithelium. The present study sought to characterize the unique microenvironment within the crypts to better understand the viral tropism of HPV to a lymphoid-rich organ. Laser-capture microdissection of distinct anatomic areas (crypts, surface epithelium, and germinal centers) of the tonsil, coupled with transcriptional analysis and multiparameter immunofluorescence staining demonstrated that the tonsillar crypts are enriched with myeloid populations that co-express multiple canonical and noncanonical immune checkpoints, including PD-L1, CTLA-4, HAVCR2 (TIM-3), ADORA2A, IDO1, BTLA, LGALS3, CDH1, CEACAM1, PVR, and C10orf54 (VISTA). The resident monocytes may foster a permissive microenvironment that facilitates HPV infection and persistence. Furthermore, the myeloid populations within HPV-associated tonsil cancers co-express the same immune checkpoints, providing insight into potential novel immunotherapeutic targets for HPV-associated head and neck cancers.

Motivation We previously described the construction and characterization of fixed reusable blood transcriptional module repertoires. More recently we released a third iteration (‘BloodGen3’ module repertoire) that comprises 382 functionally annotated modules and encompasses 14 168 transcripts. Custom bioinformatic tools are needed to support downstream analysis, visualization and interpretation relying on such fixed module repertoires. Results We have developed and describe here an R package, BloodGen3Module. The functions of our package permit group comparison analyses to be performed at the module-level, and to display the results as annotated fingerprint grid plots. A parallel workflow for computing module repertoire changes for individual samples rather than groups of samples is also available; these results are displayed as fingerprint heatmaps. An illustrative case is used to demonstrate the steps involved in generating blood transcriptome repertoire fingerprints of septic patients. Taken together, this resource could facilitate the analysis and interpretation of changes in blood transcript abundance observed across a wide range of pathological and physiological states. Availability and implementation The BloodGen3Module package and documentation are freely available from Github: https://github.com/Drinchai/BloodGen3Module. Supplementary information Supplementary data are available at Bioinformatics online.

International audience; Down syndrome (DS) is characterized by the occurrence of three copies of human chromosome 21 (HSA21). HSA21 contains a cluster of four interferon receptor (IFN-R) genes: IFNAR1, IFNAR2, IFNGR2, and IL10RB. DS patients often develop mucocutaneous infections and autoimmune diseases, mimicking patients with heterozygous gain-of-function (GOF) STAT1 mutations, which enhance cellular responses to three types of interferon (IFN). A gene dosage effect at these four loci may contribute to the infectious and autoimmune manifestations observed in individuals with DS. We report high levels of IFN-αR1, IFN-αR2, and IFN-γR2 expression on the surface of monocytes and EBV-transformed-B (EBV-B) cells from studying 45 DS patients. Total and phosphorylated STAT1 (STAT1 and pSTAT1) levels were constitutively high in unstimulated and IFN-α- and IFN-γ-stimulated monocytes from DS patients but lower than those in patients with GOF STAT1 mutations. Following stimulation with IFN-α or -γ, but not with IL-6 or IL-21, pSTAT1 and IFN-γ activation factor (GAF) DNA-binding activities were significantly higher in the EBV-B cells of DS patients than in controls. These responses resemble the dysregulated responses observed in patients with STAT1 GOF mutations. Concentrations of plasma type I IFNs were high in 12% of the DS patients tested (1.8% in the healthy controls). Levels of type I IFNs, IFN-Rs, and STAT1 were similar in DS patients with and without recurrent skin infections. We performed a genome-wide transcriptomic analysis based on principal component analysis and interferon modules on circulating monocytes. We found that DS monocytes had levels of both IFN-α- and IFN-γ-inducible ISGs intermediate to those of monocytes from healthy controls and from patients with GOF STAT1 mutations. Unlike patients with GOF STAT1 mutations, patients with DS had normal circulating Th17 counts and a high proportion of terminally differentiated CD8+ T cells with low levels of STAT1 expression. We conclude a mild interferonopathy in Down syndrome leads to an incomplete penetrance at both cellular and clinical level, which is not correlate with recurrent skin bacterial or fungal infections. The constitutive upregulation of type I and type II IFN-R, at least in monocytes of DS patients, may contribute to the autoimmune diseases observed in these individuals.

Sepsis develops after a dysregulated host inflammatory response to a systemic infection. Identification of sepsis biomarkers has been challenging because of the multifactorial causes of disease susceptibility and progression. Public transcriptomic data are a valuable resource for mechanistic discoveries and cross-studies concordance of heterogeneous diseases. Nonetheless, the approach requires structured methodologies and effective visualization tools for meaningful data interpretation. Currently, no such database exists for sepsis or systemic inflammatory diseases in human. Hence we curated SysInflam HuDB (http://sepsis.gxbsidra.org/dm3/geneBrowser/list), a unique collection of human blood transcriptomic datasets associated with systemic inflammatory responses to sepsis. The transcriptome collection and the associated clinical metadata are integrated onto a user-friendly and Web-based interface that allows the simultaneous exploration, visualization, and interpretation of multiple datasets stemming from different study designs. To date, the collection encompasses 62 datasets and 5719 individual profiles. Concordance of gene expression changes with the associated literature was assessed, and additional analyses are presented to showcase database utility. Combined with custom data visualization at the group and individual levels, SysInflam HuDB facilitates the identification of specific human blood gene signatures in response to infection (e.g., patients with sepsis versus healthy control subjects) and the delineation of major genetic drivers associated with inflammation onset and progression under various conditions.

As the capacity for generating large-scale molecular profiling data continues to grow, the ability to extract meaningful biological knowledge from it remains a limitation. Here, we describe the development of a new fixed repertoire of transcriptional modules, BloodGen3, that is designed to serve as a stable reusable framework for the analysis and interpretation of blood transcriptome data. The construction of this repertoire is based on co-clustering patterns observed across sixteen immunological and physiological states encompassing 985 blood transcriptome profiles. Interpretation is supported by customized resources, including module-level analysis workflows, fingerprint grid plot visualizations, interactive web applications and an extensive annotation framework comprising functional profiling reports and reference transcriptional profiles. Taken together, this well-characterized and well-supported transcriptional module repertoire can be employed for the interpretation and benchmarking of blood transcriptome profiles within and across patient cohorts. Blood transcriptome fingerprints for the 16 reference cohorts can be accessed interactively via: https://drinchai.shinyapps.io/BloodGen3Module/., The blood transcriptome of human subjects can be profiled on an almost routine basis in translational research settings. Here the authors show that a fixed and well-characterized repertoire of transcriptional modules can be employed as a reusable framework for the analysis, visualization and interpretation of such data

A cancer immune phenotype characterized by an active T-helper 1 (Th1)/cytotoxic response is associated with responsiveness to immunotherapy and favorable prognosis across different tumors. However, in some cancers, such an intratumoral immune activation does not confer protection from progression or relapse. Defining mechanisms associated with immune evasion is imperative to refine stratification algorithms, to guide treatment decisions and to identify candidates for immune-targeted therapy. Molecular alterations governing mechanisms for immune exclusion are still largely unknown. The availability of large genomic datasets offers an opportunity to ascertain key determinants of differential intratumoral immune response. We follow a network-based protocol to identify transcription regulators (TRs) associated with poor immunologic antitumor activity. We use a consensus of four different pipelines consisting of two state-of-the-art gene regulatory network inference techniques, regularized gradient boosting machines and ARACNE to determine TR regulons, and three separate enrichment techniques, including fast gene set enrichment analysis, gene set variation analysis and virtual inference of protein activity by enriched regulon analysis to identify the most important TRs affecting immunologic antitumor activity. These TRs, referred to as master regulators (MRs), are unique to immune-silent and immune-active tumors, respectively. We validated the MRs coherently associated with the immune-silent phenotype across cancers in The Cancer Genome Atlas and a series of additional datasets in the Prediction of Clinical Outcomes from Genomic Profiles repository. A downstream analysis of MRs specific to the immune-silent phenotype resulted in the identification of several enriched candidate pathways, including NOTCH1, TGF-\documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{upgreek} \usepackage{mathrsfs} \setlength{\oddsidemargin}{-69pt} \begin{document} }{}$\beta $\end{document}, Interleukin-1 and TNF-\documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{upgreek} \usepackage{mathrsfs} \setlength{\oddsidemargin}{-69pt} \begin{document} }{}$\alpha $\end{document} signaling pathways. TGFB1I1 emerged as one of the main negative immune modulators preventing the favorable effects of a Th1/cytotoxic response.

In tumor-bearing mice, cyclic fasting or fasting-mimicking diets (FMD) enhance the activity of antineoplastic treatments by modulating systemic metabolism and boosting antitumor immunity. Here we conducted a clinical trial to investigate the safety and biological effects of cyclic, five-day FMD in combination with standard antitumor therapies. In 101 patients, the FMD was safe, feasible, and resulted in a consistent decrease of blood glucose and growth factor concentration, thus recapitulating metabolic changes that mediate fasting/FMD anticancer effects in preclinical experiments. Integrated transcriptomic and deep-phenotyping analyses revealed that FMD profoundly reshapes anticancer immunity by inducing the contraction of peripheral blood immunosuppressive myeloid and regulatory T-cell compartments, paralleled by enhanced intratumor Th1/cytotoxic responses and an enrichment of IFNγ and other immune signatures associated with better clinical outcomes in patients with cancer. Our findings lay the foundations for phase II/III clinical trials aimed at investigating FMD antitumor efficacy in combination with standard antineoplastic treatments. Significance: Cyclic FMD is well tolerated and causes remarkable systemic metabolic changes in patients with different tumor types and treated with concomitant antitumor therapies. In addition, the FMD reshapes systemic and intratumor immunity, finally activating several antitumor immune programs. Phase II/III clinical trials are needed to investigate FMD antitumor activity/efficacy. This article is highlighted in the In This Issue feature, p. 1

Transcriptome profiling approaches have been widely used to investigate the mechanisms underlying psoriasis pathogenesis. Most researchers have measured changes in transcript abundance in skin biopsies; relatively few have examined transcriptome changes in the blood. Although less relevant to the study of psoriasis pathogenesis, blood transcriptome profiles can be readily compared across various diseases. Here, we used a pre-established set of 382 transcriptional modules as a common framework to compare changes in blood transcript abundance in two independent public psoriasis datasets. We then compared the resulting “transcriptional fingerprints” to those obtained for a reference set of 16 pathological or physiological states. The perturbations in blood transcript abundance in psoriasis were relatively subtle compared to the changes we observed in other autoimmune and auto-inflammatory diseases. However, we did observe a consistent pattern of changes for a set of modules associated with neutrophil activation and inflammation; interestingly, this pattern resembled that observed in patients with Kawasaki disease. This similarity between the blood-transcriptome signatures in psoriasis and Kawasaki disease suggests that the immune mechanisms driving their pathogenesis might be partially shared.

Transcriptional modules have been widely used for the analysis, visualization and interpretation of transcriptome data. We have previously described the construction and characterization of generic and reusable blood transcriptional module repertoires. The third and latest version that we have recently made available comprises 382 functionally annotated gene sets (modules) and encompasses 14,168 transcripts. We developed R scripts for performing module repertoire analyses and custom fingerprint visualization. These are made available here along with detailed descriptions. An illustrative public transcriptome dataset and corresponding intermediate output files are also included as supplementary material. Briefly, the steps involved in module repertoire analysis and visualization include: First, the annotation of the gene expression data matrix with module membership information. Second, running of statistical tests to determine for each module the proportion of its constitutive genes which are differentially expressed. Third, the results are expressed “at the module level” as percent of genes increased or decreased and plotted in a fingerprint grid format. A parallel workflow has been developed for computing module repertoire changes for individual samples rather than groups of samples. Such results are plotted in a heatmap format. The use case that is presented illustrates the steps involved in the generation of blood transcriptome repertoire fingerprints of septic patients at both group and individual levels.

The expression of Annexin A3 (ANXA3), a member of a family of calcium‐binding proteins, is restricted to neutrophils. Its abundance is increased in septic patients, yet the functional relevance of ANXA3 in this context remains unknown. Upon reviewing evidence from public transcriptome repositories and the literature, we hypothesize that during sepsis ANXA3 could mediate neutrophils microbicidal activity while also prolonging their survival, and thus also possibly contributing to organ damage., Summary According to publicly available transcriptome datasets, the abundance of Annexin A3 (ANXA3) is robustly increased during the course of sepsis; however, no studies have examined the biological significance or clinical relevance of ANXA3 in this pathology. Here we explored this interpretation gap and identified possible directions for future research. Based on reference transcriptome datasets, we found that ANXA3 expression is restricted to neutrophils, is upregulated in vitro after exposure to plasma obtained from septic patients, and is associated with adverse clinical outcomes. Secondly, an increase in ANXA3 transcript abundance was also observed in vivo, in the blood of septic patients in multiple independent studies. ANXA3 is known to mediate calcium‐dependent granules–phagosome fusion in support of microbicidal activity in neutrophils. More recent work has also shown that ANXA3 enhances proliferation and survival of tumour cells via a Caspase‐3‐dependent mechanism. And this same molecule is also known to play a critical role in regulation of apoptotic events in neutrophils. Thus, we posit that during sepsis ANXA3 might either play a beneficial role, by facilitating microbial clearance and resolution of the infection; or a detrimental role, by prolonging neutrophil survival, which is known to contribute to sepsis‐mediated organ damage.

BackgroundTranscriptome profiling approaches have been widely used in the investigation of mechanisms underlying psoriasis pathogenesis. In most instances, changes in transcript abundance have been measured in skin biopsies. Fewer studies have examined changes in the blood samples from patients with psoriasis. While changes in the periphery may be less relevant, the blood cell transcriptome analysis presents the distinct advantage of being amenable to comparison across diseases.MethodsTwo public psoriasis blood transcriptome datasets were reanalyzed and compared against reference datasets encompassing 16 immune states and pathologies, employing a recently established modular repertoire framework.ResultsAlthough perturbations in psoriasis were relatively subtle in comparison to other auto-immune or auto-inflammatory diseases, consistent changes were observed for a signature associated with neutrophil activation/inflammation. This transcriptional signature most resembled that of subjects with Kawasaki disease.ConclusionsThe similarities observed between psoriasis and Kawasaki disease blood transcriptome signatures suggest that immune mechanisms driving the pathogenesis of these diseases may be at least partially shared. This notion is reinforced by case reports describing the development of psoriasis disease in patients with Kawasaki disease. Potential implications for novel therapeutic approaches, including the repurposing of biologic drugs targeting IL17 or its receptor for the treatment of Kawasaki disease are discussed.

Background Covid-19 morbidity and mortality are associated with a dysregulated immune response. Tools are needed to enhance existing immune profiling capabilities in affected patients. Here we aimed to develop an approach to support the design of targeted blood transcriptome panels for profiling the immune response to SARS-CoV-2 infection. Methods We designed a pool of candidates based on a pre-existing and well-characterized repertoire of blood transcriptional modules. Available Covid-19 blood transcriptome data was also used to guide this process. Further selection steps relied on expert curation. Additionally, we developed several custom web applications to support the evaluation of candidates. Results As a proof of principle, we designed three targeted blood transcript panels, each with a different translational connotation: immunological relevance, therapeutic development relevance and SARS biology relevance. Conclusion Altogether the work presented here may contribute to the future expansion of immune profiling capabilities via targeted profiling of blood transcript abundance in Covid-19 patients.

A potential role for the long-chain acyl-CoA synthetase family member 1 (ACSL1) in the immunobiology of sepsis was explored during a hands-on training workshop. Participants first assessed the robustness of the potential gap in biomedical knowledge identified via an initial screen of public transcriptome data and of the literature associated with ACSL1. Increase in ACSL1 transcript abundance during sepsis was confirmed in several independent datasets. Querying the ACSL1 literature also confirmed the absence of reports associating ACSL1 with sepsis. Inferences drawn from both the literature (via indirect associations) and public transcriptome data (via correlation) point to the likely participation of ACSL1 and ACSL4, another family member, in inflammasome activation in neutrophils during sepsis. Furthermore, available clinical data indicate that levels of ACSL1 and ACSL4 induction was significantly higher in fatal cases of sepsis. This denotes potential translational relevance and is consistent with involvement in pathways driving potentially deleterious systemic inflammation. Finally, while ACSL1 expression was induced in blood in vitro by a wide range of pathogen-derived factors as well as TNF, induction of ACSL4 appeared restricted to flagellated bacteria and pathogen-derived TLR5 agonists and IFNG. Taken together, this joint review of public literature and omics data records points to two members of the acyl-CoA synthetase family potentially playing a role in inflammasome activation in neutrophils. Translational relevance of these observations in the context of sepsis and other inflammatory conditions remain to be investigated.

Steps involved in reductionist investigation approaches can be imitated using public transcriptome datasets as source of training material. In the present report trainees explored an apparent gap in biological knowledge for FAM129A (family with sequence similarity 129 member A). Elevated abundance of FAM129A transcripts were observed in a transcriptome dataset where neutrophils were exposed in vitro to plasma of patients with sepsis. However, no literature linking FAM129A and either neutrophils, sepsis or inflammation could be identified. Additional datasets were selected to independently validate this initial observation and further explore differential expression of FAM129A in the context of sepsis studies. Follow on investigations carried out at the bench confirmed restriction of the expression of FAM129A protein at the surface of circulating blood neutrophils and monocytes. A potential role for FAM129A in neutrophil survival was inferred from profiling of literature associated with FAM129A, which remains to be investigated in further follow on investigations.

Biomarkers to assess the severity of acute respiratory syncytial virus (RSV) infection are needed. We conducted a meta-analysis of 490 unique profiles from six public RSV blood transcriptome datasets. A repertoire of 382 well-characterized transcriptional modules was used to define dominant host responses to RSV infection. The consolidated RSV cohort was stratified according to four traits: “interferon response” (IFN), “neutrophil-driven inflammation” (Infl), “cell cycle” (CC), and “erythrocytes” (Ery). Eight prevalent blood transcriptome phenotypes were thus identified. Among those three Ery+ phenotypes comprised higher proportions of patients requiring intensive care. We posit that the erythrocyte module is linked to an overabundance of immunosuppressive erythroid cells that might underlie progression to severe RSV infection. These findings outline potential priority areas for biomarker development and investigations into the immune biology of RSV infection. The approach that was employed here will also permit to delineate prevalent blood transcriptome phenotypes in other settings.

Background Allogeneic Hematopoietic Cell Transplantation (allo HCT) is currently the only curative therapy for high-risk hematologic malignancies due to graft versus tumor effect (GVT), but with the cost of Graft Versus Host Disease (GVHD). Despite extensive research, very few predictors of GVHD have been identified to date. To study the mechanisms of GVHD and GVT and to identify potential GVHD markers we applied a novel approach, called Transcriptome Fingerprint Assay (TFA), relying on high frequency sampling and blood transcriptome profiling. The TFA is a multiplex microfluidics q-PCR based assay, linked to a computational model for functional analyses, uniquely tailored to answer complex questions on immune perturbations through frequent profiling of gene expression signatures (Chaussabel et a 2014, Speake et a 2017). This approach has been successfully applied to stratify patients' prognosis in autoimmune and infectious diseases. Herein we report the discovery of an association between the expression abundance of a set of genes pre-transplant and the development of acute or chronic GVHD. Methods Seventy-eight patients candidate to allo-HCT were enrolled on the study. Patients donated micro-quantities of blood (50-600 microliters) prior to transplant conditioning, weekly until day 100 post-transplant and every 2 weeks thereafter until 2 years after transplant. Detailed clinical, laboratory and therapy annotations are captured during the follow-up. Gene expression of 264 immune-related genes for each sample are measured through Fluidigm BioMark high-throughput qPCR system. Data interpretation is performed through TFA modular analyses and correlated with the clinical annotations. Here we report the univariate analysis of gene expression data and its association with GVHD in 31 patients for whom data are available until at least day 169 post-transplant (169-672, median 513). SIgnificant genes were tested in a longitudinal analysis with 4 combined linear-mixed models, measuring the parameters: 1) groups (GVHD NO-GVHD) 2) time 3) interaction of groups over time. Results Patients' characteristics are summarized in Fig 1; 26 patients developed GVHD (12 acute GVHD only, 3 late acute GVHD, 1 overlap syndrome, 5 acute and chronic GVHD and 5 chronic GVHD only). By TFA analysis of pre-transplant samples, we identified 3 genes significantly downregulated among patients who developed GVHD (GPSM3, LRG1 and EPHX4), and 2 genes borderline (1.5 fold upregulated in the GVHD group, but with a non-significant p-value (Volcano-plot Fig.1). Of note, 12 of them were >4 fold upregulated, and their transcriptome pertains to B cells, T lymphocytes, monocytes, IFN, TNF, other cytokines and neutrophil activation. Moreover, among these genes IFN-genes were consistently represented by multiple IFN-modules, emerging as promising candidates. Longitudinal analyses confirmed that EPHX4 and GPSM3 distinguished the cohorts for all the measured parameters in the post-transplant time. EPHX4 increased over time in both groups but significantly more in the NO-GVHD group (with a fixed effect estimate of 2.05); GPSM3 instead decreased over time, again significantly more in the NO-GVHD group (with a fixed effect estimate of -0.95). LRG3 showed significance only for the parameter "time", resulting after transplant more abundant in the GVHD group, thus confirming previous literature data. IFN modules were also tested longitudinally, showing very distinct patterns in the cohorts, and several significant genes (IFI27, NT5C3, CCR1, LBA1, Fig.1) Conclusion Our data demonstrate that TFA may be used to assess expression of immune related genes in transplant patients and to identify specific pathways that may be predictive for GVHD development. Additional work is required to validate our data in a larger cohort and for better understanding of the role of those genes in triggering or protecting against GVHD. Upon completion of the study and the longitudinal analyses, we aim to define in depth transcriptome signatures of GVHD and relapse. Disclosures No relevant conflicts of interest to declare.

A hands-on training workshop was devised with omics data used as source material to emulate reductionist investigation approaches. NUDT16, a member of the Nudix hydrolase family was selected as a candidate gene on the basis of: 1) it being upregulated in neutrophils exposed in vitro to serum of patients with sepsis, AND 2) the absence of overlap between the NUDT16 and sepsis, inflammation or neutrophil literature. We next sought to corroborate the initial finding in five public transcriptome sepsis datasets in which NUDT16 transcript levels were measured. In each of these dataset NUDT16 transcript abundance was found to be significantly increased in septic patients in vivo in comparison to uninfected controls. Next, biological concepts were extracted from the NUDT16 literature. The main concepts to emerge from profiling this literature were RNA decapping, inosine triphosphate, and inosine diphosphate. Through these concepts, indirect links could be established between NUDT16 and the sepsis/inflammation/neutrophil literature. A potential role for NUDT16 could, in turn, be inferred in the degradation of mRNAs in activated neutrophils. Follow on experiments that would be necessary in order to further explore such inference are discussed.

The increased application of high-throughput approaches in translational research has expanded the number of publicly available data repositories. Gathering additional valuable information contained in the datasets represents a crucial opportunity in the biomedical field. To facilitate and stimulate utilization of these datasets, we have recently developed an interactive data browsing and visualization web application, the Gene Expression Browser (GXB). In this note, we describe a curated compendium of 13 public datasets on human breast cancer, representing a total of 2142 transcriptome profiles. We classified the samples according to different immune based classification systems and integrated this information into the datasets. Annotated and harmonized datasets were uploaded to GXB. Study samples were categorized in different groups based on their immunologic tumor response profiles, intrinsic molecular subtypes and multiple clinical parameters. Ranked gene lists were generated based on relevant group comparisons. In this data note, we demonstrate the utility of GXB to evaluate the expression of a gene of interest, find differential gene expression between groups and investigate potential associations between variables with a specific focus on immunologic classification in breast cancer. This interactive resource is publicly available online at: http://breastcancer.gxbsidra.org/dm3/geneBrowser/list.

Introduction Allogeneic Hematopoietic Cell Transplantation (allo HCT) is currently the only curative therapy for high-risk hematologic malignancies due to the immune response of the donor cells against the malignant cells (graft versus tumor effect; GVT), but with the cost of Graft Versus Host Disease (GVHD). Despite extensive research, very few predictors of GVHD and GVT have been identified to date. Additionally, clinical GVHD diagnosis can be challenging due to chemotherapy-related or infection-related organ toxicity manifestations, which further complicate prediction and treatment stratification algorithms. In order to study the mechanisms of GVHD and GVT and to identify potential GVHD markers we apply a novel approach, called Transcriptome Fingerprint Assay (TFA), relying on high frequency sampling and blood transcript profiling. The TFA is a multiplex microfluidics q-PCR based assay linked with a computational model for modular functional transcriptome analyses, uniquely tailored to answer complex questions on immune perturbations through frequent profiling of gene expression signatures from < 1 ml of blood (Chaussabel and Baldwin. Nat Rev Immunol 2014, Speake et al. Clin Exp Immunol 2017). This approach has been successfully applied to stratify patients' prognosis in autoimmune and infectious diseases (Banchereau R et al. Cell 2016, Dunning et al. Nat Immunol 2018). In our study we use the TFA to capture longitudinal immune signatures as dynamic "snapshots" of the patient's immune system after HCT. Hypotheses Fluctuations over-time in gene expression of allo HCT patients' immune system reflect the pathologic/disease control programs (GVHD/GVT) and may be used to identify diagnostic and predictive biomarkers. GVHD/GVT control immune programs depend on the "inner" interface between the donor immune-system and the recipient, and are influenced by external variables, as infections or drugs. These variables can affect the immune system-related gene expression and can be measured. Objectives To systematically measure gene expression signatures in immune perturbations post-allo HCT, in order to: Identify GVHD-related immune signatures consistent with clinical diagnosis of GVHD.Predict and stratify therapy-resistant GVHD and severe chronic GVHD, according to immune signatures.Identify links (causative and consequential) between GVHD, GVT, relapse, and other post-transplant immune perturbations (e.g. infections). Methods Enroll 250 allo HCT patients to populate a "GVHD cohort" and a "non-GVHD cohort" of 50 patients each, and 50 donors (healthy controls cohort) . Patients donate micro-quantities of blood (50 to 600 microliters), weekly until day 100 post-transplant and every 2 weeks thereafter until 2 years after transplant. Detailed clinical, laboratory and therapy annotations are captured during the follow-up. Gene expression of 264 immune-related genes for each sample are measured through Fluidigm BioMark high throughput qPCR system, and normalized to the geometric mean Ct of 8 housekeeping genes. Data interpretation is performed through TFA modular analyses and correlated with the clinical annotations. Results Results of three series of patients' samples are shown to exemplify the potential of TFA as a method to study the mechanisms of GVHD and GVT. All three patients underwent myeloablative peripheral blood stem cell transplant from an HLA identical sibling donor. Two patients developed steroid responsive-acute GVHD (patient #1: GVHD stage I was diagnosed on day 38 post HCT, patient #4: GVHD stage III was diagnosed on day 21 post HCT). One patient (Patient #6) did not develop clinical GVHD, but routine skin biopsy on day 80 revealed apoptotic cells consistent with subclinical skin GVHD. Principal Component Analysis (PCA) of the three patients' series is shown in Figure 1, the dynamic transcriptomes according to TFA modules of patients #1 and #6 are shown in Figure 2, and representative TFA modular fingerprints are shown in Figure 3. Conclusion We anticipate that using the TFA approach will help to fill knowledge gaps instrumental to solve clinical dilemmas related to allo HCT complications, and to improve the clinical outcomes of allo HCT patients. Disclosures No relevant conflicts of interest to declare.

Background: Members of the ADAM (a disintegrin and metalloprotease domain) family have emerged as critical regulators of cell-cell signaling during development and homeostasis. ADAM9 is consistently overexpressed in various human cancers, and has been shown to play an important role in tumorigenesis. However, little is known about the involvement of ADAM9 during immune-mediated processes. Results: Mining of an extensive compendium of transcriptomic datasets identified important gaps in knowledge regarding the possible role of ADAM9 in immunological homeostasis and inflammation: 1) The abundance of ADAM9 transcripts in the blood was increased in patients with acute infection but, 2) changed very little after in vitro exposure to a wide range of pathogen-associated molecular patterns (PAMPs). 3) Furthermore it was found to increase significantly in subjects as a result of tissue injury or tissue remodeling, in absence of infectious processes. Conclusions: Our findings indicate that ADAM9 may constitute a valuable biomarker for the assessment of tissue damage, especially in clinical situations where other inflammatory markers are confounded by infectious processes.

Malaria remains a major cause of mortality and morbidity worldwide. Progress has been made in recent years with the development of vaccines that could pave the way towards protection of hundreds of millions of exposed individuals. Here we used a modular repertoire approach to re-analyze a publically available microarray blood transcriptome dataset monitoring the response to malaria vaccination. We report the seminal identification of interferon signatures in the blood of subjects on days 1, 3 and 14 following administration of the third dose of the RTS,S recombinant malaria vaccine. These signatures at day 1 correlate with protection, and at days 3 and 14 to susceptibility to subsequent challenge of study subjects with live parasites. In addition we putatively link the decreased abundance of interferon-inducible transcripts observed at days 3 and 14 post-vaccination with the elicitation of an antigen-specific IgE response in a subset of vaccine recipients that failed to be protected by the RTS,S vaccine. Furthermore, profiling of antigen-specific levels of IgE in a Mozambican cohort of malaria-exposed children vaccinated with RTS,S identified an association between elevated baseline IgE levels and subsequent development of naturally acquired malaria infection during follow up. Taken together these findings warrant further investigation of the role of antigen-specific IgE in conferring susceptibility to malaria infection.

Background: Members of the ADAM (a disintegrin and metalloprotease domain) family have emerged as critical regulators of cell-cell signaling during development and homeostasis. ADAM9 is consistently overexpressed in various human cancers, and has been shown to play an important role in tumorigenesis. However, little is known about the involvement of ADAM9 during immune-mediated processes. Results: Mining of an extensive compendium of transcriptomic datasets led to the discovery of gaps in knowledge for ADAM9 that reveal its role in immunological homeostasis and pathogenesis. The abundance of ADAM9 transcripts in the blood was increased in patients with acute infection but changed very little after in vitro exposure to a wide range of pathogen-associated molecular patterns (PAMPs). Furthermore it was found to increase significantly in subjects as a result of tissue injury or tissue remodeling, in absence of infectious processes. Conclusions: Our findings indicate that ADAM9 may constitute a valuable biomarker for the assessment of tissue damage, especially in clinical situations where other inflammatory markers are confounded by infectious processes.

Background There are diverse molecules present in blood plasma that regulate immune functions and also present a potential source of disease biomarkers and therapeutic targets. Genome-wide profiling has become a powerful method for assessing immune responses on a systems scale, but technologies that can measure the plasma proteome still face considerable challenges. An alternative approach to direct proteome assessment is to measure transcriptome responses in reporter cells exposed in vitro to plasma. In this report we describe such a “transcriptomic reporter assay” to assess plasma from patients with sepsis, which is a common and severe systemic infectious process for which physicians lack efficient diagnostic or prognostic markers. Methods Plasma samples collected from patients with culture-confirmed bacterial sepsis and uninfected healthy controls were used to stimulate three separate cell types – neutrophils, peripheral blood mononuclear cells, and monocyte-derived dendritic cells. Whole genome microarrays were generated from stimulated cells to assess transcriptional responses. Unsupervised analysis and enriched functional networks were evaluated for each cell type. Principal component analyses were used to assess variability in responses. A random K-nearest neighbor – feature selection algorithm was used to identify markers predictive of sepsis severity, which were then validated in an independent data set. Results Neutrophils demonstrated the most distinct response to plasma from septic patients with 709 genes showing altered expression profiles, many of which are involved in established immunologic pathways. The amplitude of the neutrophil transcriptomic response was shown to be correlated with sepsis severity in two independent sets of patients comprised of 64 total septic patients. A subset of 30 transcripts selected using one set of patients was demonstrated to have a high degree of accuracy (82-90%) in predicting sepsis severity and outcomes in the other independent set. This subset included several genes previously established in sepsis pathogenesis as well as novel genes. Conclusions These results demonstrate both the suitability and potential clinical relevance of a neutrophil reporter assay for studying plasma, in this case from septic patients. The distinctive transcriptional signature we found could potentially help predict severity of disease and guide treatment. Our findings also shed new light on mechanisms of immune dysregulation in sepsis.