Search

SummaryAccumulating evidence indicate a strong link between neural signals and the immune system. Given neural signals constitute a large family that may be leveraged for communication, we systematically explored the neuro-immune regulation network in the periphery and uncovered a broad yet lineage selective expression of neuro-receptors on immune cells. We constructed a rich social immune network map showing the neural molecular pathways supporting the regulation of the immune system at steady state. Our results emphasize neuro-receptors role in the commitment and differentiation of B and T cells along their developmental process. We identified the immune cells’ functionality in the specific tissue is extensively shaped by the communication with the microenvironment and nervous systems via a rich alphabet of neural mediators. Collectively, our findings suggest neural genes are an integral part of the immune regulatory system and provide clear testable new avenues of experimental follow up for neuroimmunologists and immunologists alike.Abstract FigureHighlights160 neural genes potentially active in immune cells in the periphery with high specificity to lineageNeuro-receptors co-expressed in immune lineages are enriched for biological functionsChanges in neuro-receptors expression influence the HCS differentiation and commitmentImmune-microenvironment neural signaling architecture reflects tissue biological role

ObjectiveAnti-drug antibodies (ADA) to anti-tumour necrosis factor (anti-TNF) therapy drive treatment loss of response. An association between intestinal microbial composition and response to anti-TNF therapy was noted. We therefore aimed to assess the implications of antibiotic treatments on ADA formation in patients with inflammatory bowel disease (IBD).DesignWe analysed data from the epi-IIRN (epidemiology group of the Israeli IBD research nucleus), a nationwide registry of all patients with IBD in Israel. We included all patients treated with anti-TNF who had available ADA levels. Survival analysis with drug use as time varying covariates were used to assess the association between antibiotic use and ADA development. Next, specific pathogen and germ-free C57BL mice were treated with respective antibiotics and challenged with infliximab. ADA were assessed after 14 days.ResultsAmong 1946 eligible patients, with a median follow-up of 651 days from initiation of therapy, 363 had positive ADA. Cox proportional hazard model demonstrated an increased risk of ADA development in patients who used cephalosporins (HR=1.97, 95% CI 1.58 to 2.44), or penicillins with β-lactamase inhibitors (penicillin-BLI, HR=1.4, 95% CI 1.13 to 1.74), whereas a reduced risk was noted in patients treated with macrolides (HR=0.38, 95% CI 0.16 to 0.86) or fluoroquinolones (HR=0.20, 95% CI 0.12 to 0.35). In mice exposed to infliximab, significantly increased ADA production was observed in cephalosporin as compared with macrolide pretreated mice. Germ-free mice produced no ADA.ConclusionADA production is associated with the microbial composition. The risk of ADA development during anti-TNF therapy can possibly be reduced by avoidance of cephalosporins and penicillin-BLIs, or by treatment with fluoroquinolones or macrolides.

BackgroundRheumatoid arthritis (RA) is an autoimmune disease characterized by systemic inflammation and is mediated by multiple immune cell types. In this work we aimed to determine the relevance of changes in cell proportions in peripheral blood mononuclear cells (PBMCs) during development of disease and during treatment. MethodsSamples from healthy blood donors, newly diagnosed RA patients, and established RA patients that had an inadequate response to MTX and were about to start tumor necrosis factor inhibitors (TNFi) treatment were collected before and after 3 months treatment. We used in parallel a computational deconvolution approach based on RNA expression and flow cytometry to determine the relative cell-type frequencies.ResultsWe showed that monocytes (both classical and non-classical) and CD4+ cells (Th1 and Th2) were increased in RA patients compared to controls, while NK cells and B cells (naïve and mature) were significantly decreased in RA patients. Treatment with MTX caused a decrease in B cells (memory and plasma cell), and a decrease in CD4 Th cells (Th1 and Th17), while treatment with TNFi resulted in a significant increase in the population of B cells. Conclusion Characterization of the RNA expression patterns and found that most of differentially expressed genes in RA subjects after treatment can be explained by changes in cell frequencies (98% and 74% respectively for MTX and TNFi).

Background Anatomical location and extent of disease are main factors that affect inflammatory bowel disease (IBD) course and prognosis. No explanation is available for segmental intestinal involvement in either Crohn’s disease (CD) or ulcerative colitis (UC), or for selective segmental response to therapy or disease complications. Therefore, studying the cellular composition of different intestinal segments may provide pathophysiological insights into these phenomena. Methods We compared location-specific cell composition and function by Cytometry Time-of-Flight (CyTOF), gene expression and single-cell (sc) RNAseq data obtained from 3 independent cohorts of healthy donors and IBD patients during remission and flare-ups. Using CyTOF data (n = 38 biopsies), we built a high-resolution screening of immune cell behaviour along the intestine. We validated the findings with gene expression data of 370 samples, and expanded screening resolution by computational methodologies. We then tested a specific pathway in scRNAseq data (n = 10 paired biopsies from 5 patients) and validated its significance by cell-specific Significance Analysis of Microarrays (csSAM). Results We found a location along the intestine to be a dominant feature determining immune and non-immune cell composition. We observed that inflammation reduced anatomic segregation beyond cell infiltration, and decreased the ability to cope with oxidative stress. An upregulated IL-6 pathway in T regulatory cells in UC patients was recognised as sigmoid-specific compared with known inflammatory IL-6 roles in macrophages, as seen in the right colon. This observation may be linked to colonic perforations associated with anti-IL-6R treatment. Suppressor of cytokine signalling 3 (SOCS3) may control IL-6 location-specific action. Conclusion Our study displays a unique and comprehensive cell map of IBD in a location-specific context, providing potential explanations to unexplained clinical phenomena. These observations may allow to tailor therapies to affected areas with improved therapeutic index and efficacy.

Contains fulltext : 251371.pdf (Publisher’s version ) (Open Access) Disease recovery dynamics are often difficult to assess, as patients display heterogeneous recovery courses. To model recovery dynamics, exemplified by severe COVID-19, we apply a computational scheme on longitudinally sampled blood transcriptomes, generating recovery states, which we then link to cellular and molecular mechanisms, presenting a framework for studying the kinetics of recovery compared with non-recovery over time and long-term effects of the disease. Specifically, a decrease in mature neutrophils is the strongest cellular effect during recovery, with direct implications on disease outcome. Furthermore, we present strong indications for global regulatory changes in gene programs, decoupled from cell compositional changes, including an early rise in T cell activation and differentiation, resulting in immune rebalancing between interferon and NF-κB activity and restoration of cell homeostasis. Overall, we present a clinically relevant computational framework for modeling disease recovery, paving the way for future studies of the recovery dynamics in other diseases and tissues.

Diseases change over time, both phenotypically and in underlying driving molecular processes. Though understanding disease progression dynamics is critical for diagnostics and treatment, capturing these dynamics is difficult, due to their complexity and the high heterogeneity between individuals. We developed TimeAx, an algorithm which builds a comparative framework for capturing disease dynamics using high-dimensional short time-series data. We demonstrate TimeAx utility by studying disease progression dynamics for multiple diseases and data types. Notably, for urothelial bladder cancer tumorigenesis, we identified a stromal pro-invasion point on the disease progression axis, characterized by massive immune cell infiltration to the tumor microenvironment and increased mortality. Moreover, the continuous TimeAx model differentiated between early and late tumors within the same tumor subtype, uncovering novel molecular transitions and potential targetable pathways. Overall, we present a powerful approach for studying disease progression dynamics, providing improved molecular interpretability and clinical benefits for patient stratification and outcome prediction.

Cells are the quanta unit of biology and their relative composition in a tissue is the prime driver of bulk tissue gene expression variation. When there is no cell information, deconvolution is an effective tool to achieve cell resolution, which provides important information for learning disease complexity and its interactions with treatments, drugs and/or the environment in a wide variety of contexts. Here we present CytoPro, a production-level tissue and condition-specific deconvolution platform, based on a large collection of human tissue-specific signatures derived from single and sorted cells. CytoPro infer per-sample multiple cell-type composition, given input bulk gene expression. CytoPro includes a rigorous QC pipeline for learning, generating and selecting signatures and performs internal automated validation using multiple QC test criteria including: Comparison to ground truth cytometry and pure sorted cells data, performance evaluation using simulated data including robustness to noise as well as agreement with biological expectations in validation datasets regarding genes and cells. We demonstrate that CytoPro outperforms existing deconvolution tools, in both accuracy and robustness. By exploring multiple datasets with predefined disease phenotypes, and analyzing a use-case of biological treatment response, we show the ability of CytoPro to flush out relevant cell biology in real pathological conditions.

While many diseases of aging have been linked to the immunological system, immune metrics capable of identifying the most at-risk individuals are lacking. From the blood immunome of 1,001 individuals aged 8–96 years, we developed a deep-learning method based on patterns of systemic age-related inflammation. The resulting inflammatory clock of aging (iAge) tracked with multimorbidity, immunosenescence, frailty and cardiovascular aging, and is also associated with exceptional longevity in centenarians. The strongest contributor to iAge was the chemokine CXCL9, which was involved in cardiac aging, adverse cardiac remodeling and poor vascular function. Furthermore, aging endothelial cells in human and mice show loss of function, cellular senescence and hallmark phenotypes of arterial stiffness, all of which are reversed by silencing CXCL9. In conclusion, we identify a key role of CXCL9 in age-related chronic inflammation and derive a metric for multimorbidity that can be utilized for the early detection of age-related clinical phenotypes. From the blood immunome of 1,001 individuals aged 8–96 years, the authors used deep learning to develop an inflammatory clock of aging (iAge) that tracks with multimorbidity, immunosenescence, frailty and cardiovascular aging, and is also associated with exceptional longevity in centenarians. The main contributor to iAge is the chemokine CXCL9, which is shown to control endothelial cell senescence and function.

Immune responses generally decline with age. However, the dynamics of this process at the individual level have not been characterized, hindering quantification of an individual’s immune age. Here, we use multiple ‘omics’ technologies to capture population- and individual-level changes in the human immune system of 135 healthy adult individuals of different ages sampled longitudinally over a nine-year period. We observed high inter-individual variability in the rates of change of cellular frequencies that was dictated by their baseline values, allowing identification of steady-state levels toward which a cell subset converged and the ordered convergence of multiple cell subsets toward an older adult homeostasis. These data form a highdimensional trajectory of immune aging (IMM-AGE) that describes a person’s immune status better than chronological age. We show that the IMM-AGE score predicted all-cause mortality beyond well-established risk factors in the Framingham Heart Study, establishing its potential use in clinics for identification of patients at risk. REPORTING SUMMARY. Further information on experimental design is available in the Nature Research Reporting Summary linked to this article.

Much remains unknown regarding the response of the immune system to severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2) vaccination.We employed circulating cell-free DNA (cfDNA) to assess the turnover of specific immune cell types following administration of the Pfizer/BioNTech vaccine.The levels of B cell cfDNA after the primary dose correlated with development of neutralizing antibodies and memory B cells after the booster, revealing a link between early B cell turnover-potentially reflecting affinity maturation-and later development of effective humoral response. We also observed co-elevation of B cell, T cell, and monocyte cfDNA after the booster, underscoring the involvement of innate immune cell turnover in the development of humoral and cellular adaptive immunity. Actual cell counts remained largely stable following vaccination, other than a previously demonstrated temporary reduction in neutrophil and lymphocyte counts.Immune cfDNA dynamics reveal the crucial role of the primary SARS-CoV-2 vaccine in shaping responses of the immune system following the booster vaccine.This work was supported by a generous gift from Shlomo Kramer. Supported by grants from Human Islet Research Network (HIRN UC4DK116274 and UC4DK104216 to R.S. and Y.D.), Ernest and Bonnie Beutler Research Program of Excellence in Genomic Medicine, The Alex U Soyka Pancreatic Cancer Fund, The Israel Science Foundation, the Waldholtz/Pakula family, the Robert M. and Marilyn Sternberg Family Charitable Foundation, the Helmsley Charitable Trust, Grail, and the DON Foundation (to Y.D.). Y.D. holds the Walter and Greta Stiel Chair and Research Grant in Heart Studies. I.F.-F. received a fellowship from the Glassman Hebrew University Diabetes Center.

Personalized treatment of complex diseases has been mostly predicated on biomarker identification of one drug-disease combination at a time. Here, we used a novel computational approach termed Disruption Networks to generate a new data type, contextualized by cell-centered individual-level networks, that captures biology otherwise overlooked when performing standard statistics. The new data-type extends beyond the ‘feature level space’, to the ‘relations space’, by quantifying individual-level breaking or rewiring of cross-feature relations. Applying disruption network to dissect high-dimensional blood data, we discover and validate that the RAC1-PAK1 axis is predictive of anti-TNF response in inflammatory bowel disease. Intermediate monocytes, which correlate with the inflammatory state, play a key role in the RAC1-PAK1 responses, supporting their modulation as a therapeutic target. This axis also predicts response in rheumatoid arthritis, validated in three public cohorts. Our findings support blood-based drug response diagnostics across immune-mediated diseases, implicating common mechanisms of non-response.

BackgroundMetastasis is the major cause of death in patients with cancer. Myeloid skewing of hematopoietic cells is a prominent promoter of metastasis. However, the reservoir of these cells in the bone marrow (BM) compartment and their differentiation pattern from hematopoietic stem and progenitor cells (HSPCs) have not been explored.MethodsWe used a unique model system consisting of tumor cell clones with low metastatic potential or high metastatic potential (met-low and met-high, respectively) to investigate the fate of HSPC differentiation using murine melanoma and breast carcinoma. Single-cell RNA sequencing (scRNA-seq) analysis was performed on HSPC obtained from the BM of met-low and met-high tumors. A proteomic screen of tumor-conditioned medium integrated with the scRNA-seq data analysis was performed to analyze the potential cross talk between cancer cells and HSPCs. Adoptive transfer of tumor-educated HSPC subsets obtained from green fluorescent protein (GFP)+ tagged mice was then carried out to identify the contribution of committed HSPCs to tumor spread. Peripheral mononuclear cells obtained from patients with breast and lung cancer were analyzed for HSPC subsets.ResultsMice bearing met-high tumors exhibited a significant increase in the percentage of HSPCs in the BM in comparison with tumor-free mice or mice bearing met-low tumors. ScRNA-seq analysis of these HSPCs revealed that met-high tumors enriched the monocyte-dendritic progenitors (MDPs) but not granulocyte-monocyte progenitors (GMPs). A proteomic screen of tumor- conditioned medium integrated with the scRNA-seq data analysis revealed that the interleukin 6 (IL-6)–IL-6 receptor axis is highly active in HSPC-derived MDP cells. Consequently, loss of function and gain of function of IL-6 in tumor cells resulted in decreased and increased metastasis and corresponding MDP levels, respectively. Importantly, IL-6-educated MDPs induce metastasis within mice bearing met-low tumors—through further differentiation into immunosuppressive macrophages and not dendritic cells. Consistently, MDP but not GMP levels in peripheral blood of breast and lung cancer patients are correlated with tumor aggressiveness.ConclusionsOur study reveals a new role for tumor-derived IL-6 in hijacking the HSPC differentiation program toward prometastatic MDPs that functionally differentiate into immunosuppressive monocytes to support the metastatic switch.

Myeloid skewing of hematopoietic cells is a prominent promoter of metastasis. However, little is known about their education and differentiation pattern from hematopoietic stem and progenitor cells (HSPCs) during tumor progression and metastasis. Here we show that metastatic tumors dictate a unique differentiation pattern of HSPCs towards a specific myeloid progeny. Using single cell RNA-sequencing analysis integrated with proteomic screen of tumor secretome, we demonstrate that highly metastatic tumors dictate a long-lived differentiation of HSPCs towards monocyte-dendritic progenitors (MDPs) while low-metastatic tumors promote their differentiation into granulocyte-monocyte progenitors (GMPs). This effect is driven by IL-6 axis that is highly active in metastatic tumors. Consequently, loss and gain of function of IL-6 in tumor cells resulted in decreased and increased metastasis and corresponding MDP levels, respectively. Consistently, IL-6-educated MDPs but not GMPs obtained from highly metastatic tumors, adoptively transferred into mice bearing low metastatic tumors resulted in increased metastasis due to their further differentiation into immunosuppressive (M2) macrophages. Overall, our study reveals a new role for tumor-derived IL-6 that hijacks HSPC differentiation program towards myeloid cells that contribute to metastasis.

BackgroundImmunomodulatory agents that induce antitumor immunity have great potential for treatment of cancer. We have previously shown that interleukin (IL)-31, a proinflammatory cytokine from the IL-6 family, acts as an antiangiogenic agent. Here, we characterize the immunomodulatory effect of IL-31 in breast cancer.MethodsIn vivo breast carcinoma models including EMT6 and PyMT cell lines were used to analyze the effect of IL-31 on the composition of various immune cells in the tumor microenvironment using high-throughput flow cytometry. In vitro studies using isolated cytotoxic T cells, CD4+ T cells, myeloid-derived suppressor cells (MDSCs) and macrophages were carried out to study IL-31 immunological activity. The generation of recombinant IL-31 bound to IgG backbone was used to test IL-31 therapeutic activity.ResultsThe growth rate of IL-31-expressing breast carcinomas is decreased in comparison with control tumors due, in part, to antitumor immunomodulation. Specifically, cytotoxic T cell activity is increased, whereas the levels of CD4+ T cells, MDSCs, and tumor-associated macrophages are decreased in IL-31-expressing tumors. These cellular changes are accompanied by a cytokine profile associated with antitumor immunity. In vitro, IL-31 directly inhibits CD4+ Th0 cell proliferation, and the expression of Th2 canonical factors GATA3 and IL-4. It also promotes CD8+ T cell activation through inhibition of MDSC activity and motility. Clinically, in agreement with the mouse data, alterations in immune cell composition in human breast cancer biopsies were found to correlate with high expression of IL-31 receptor A (IL-31Ra) . Furthermore, high coexpression of IL-31Ra, IL-2 and IL-4 in tumors correlates with increased survival. Lastly, to study the therapeutic potential of IL-31, a recombinant murine IL-31 molecule was fused to IgG via a linker region (IL-31-L-IgG). This IL-31-L-IgG therapy demonstrates antitumor therapeutic activity in a murine breast carcinoma model.ConclusionsOur findings demonstrate that IL-31 induces antitumor immunity, highlighting its potential utility as a therapeutic immunomodulatory agent.

Autologous hematological stem cell transplantation (HSCT) is a novel therapy for systemic sclerosis (SSc) that has been validated in three randomized controlled trials.To report the first Israeli experience with HSCT for progressive SSc and review the current literature.Five SSc patients who were evaluated in our department and were treated by HSCT were included. Medical records were evaluated retrospectively. Demographic, clinical, and laboratory data were recorded. Continuous data are presented as the mean ± standard deviation. Categorical variables are presented as frequencies and percentages.Five SSc patients were treated with HSCT. Four patients were adults (mean age 53 ± 12 years) and one was a 12-year-old pediatric patient. All patients were female. HSCT was initiated 1.4 ± 0.8 years after diagnosis. Two patients were RNA POLIII positive, two were anti-topoisomerase 1 positive, and one only antinuclear antibodies positive. All patients had skin and lung involvement. The mean modified Rodnan Skin Score was 29 ± 4.7 before HSCT, which improved to 10.4 ± 9.6 after HSCT. The forced vital capacity improved from 68 ± 13% to 90 ± 28%. Diffusing capacity of the lungs for carbon monoxide increased by 6%. Among severe adverse events were cyclophosphamide-related congestive heart failure, antithymocyte globulin-related capillary leak syndrome, and scleroderma renal crisis. All symptoms completely resolved with treatment without sequela. No treatment related mortality was recorded.HSCT is an important step in the treatment of progressive SSc in Israel. Careful patient selection reduces treatment related morbidity and mortality.

Single-cell technologies allow characterization of cancer samples as continuous developmental trajectories. Yet, the obtained temporal resolution cannot be leveraged for a comparative analysis due to the large phenotypic heterogeneity existing between patients. Here, we present the tuMap algorithm that exploits high-dimensional single-cell data of cancer samples exhibiting an underlying developmental structure to align them with the healthy development, yielding the tuMap pseudotime axis that allows their systematic, meaningful comparison. We applied tuMap on single-cell mass cytometry data of acute lymphoblastic and myeloid leukemia to reveal associations between the tuMap pseudotime axis and clinics that outperform cellular assignment into developmental populations. Application of the tuMap algorithm on single-cell RNA sequencing data further identified gene signatures of stem cells residing at the very-early parts of the cancer trajectories. The quantitative framework provided by tuMap allows generation of metrics for cancer patients evaluation.

Cytokines are signaling molecules secreted and sensed by immune and other cell types, enabling dynamic intercellular communication. Although a vast amount of data on these interactions exists, this information is not compiled, integrated or easily searchable. Here we report immuneXpresso, a text-mining engine that structures and standardizes knowledge of immune intercellular communication. We applied immuneXpresso to PubMed to identify relationships between 340 cell types and 140 cytokines across thousands of diseases. The method is able to distinguish between incoming and outgoing interactions, and it includes the effect of the interaction and the cellular function involved. These factors are assigned a confidence score and linked to the disease. By leveraging the breadth of this network, we predicted and experimentally verified previously unappreciated cell-cytokine interactions. We also built a global immune-centric view of diseases and used it to predict cytokine-disease associations. This standardized knowledgebase (http://www.immunexpresso.org) opens up new directions for interpretation of immune data and model-driven systems immunology.

ObjectiveAlthough anti-tumour necrosis factor alpha (anti-TNFα) therapies represent a major breakthrough in IBD therapy, their cost–benefit ratio is hampered by an overall 30% non-response rate, adverse side effects and high costs. Thus, finding predictive biomarkers of non-response prior to commencing anti-TNFα therapy is of high value.DesignWe analysed publicly available whole-genome expression profiles of colon biopsies obtained from multiple cohorts of patients with IBD using a combined computational deconvolution—meta-analysis paradigm which allows to estimate immune cell contribution to the measured expression and capture differential regulatory programmes otherwise masked due to variation in cellular composition. Insights from this in silico approach were experimentally validated in biopsies and blood samples of three independent test cohorts.ResultsWe found the proportion of plasma cells as a robust pretreatment biomarker of non-response to therapy, which we validated in two independent cohorts of immune-stained colon biopsies, where a plasma cellular score from inflamed biopsies was predictive of non-response with an area under the curve (AUC) of 82%. Meta-analysis of the cell proportion-adjusted gene expression data suggested that an increase in inflammatory macrophages in anti-TNFα non-responding individuals is associated with the upregulation of the triggering receptor expressed on myeloid cells 1 (TREM-1) and chemokine receptor type 2 (CCR2)-chemokine ligand 7 (CCL7) –axes. Blood gene expression analysis of an independent cohort, identified TREM-1 downregulation in non-responders at baseline, which was predictive of response with an AUC of 94%.ConclusionsOur study proposes two clinically feasible assays, one in biopsy and one in blood, for predicting non-response to anti-TNFα therapy prior to initiation of treatment. Moreover, it suggests that mechanism-driven novel drugs for non-responders should be developed.

Chimeric antigen receptors (CARs) are immunoreceptors that redirect T cells to selectively kill tumor cells. Given their clinical successes in hematologic malignancies, there is a strong aspiration to advance this immunotherapy for solid cancers; hence, molecular CAR design and careful target choice are crucial for their function. To evaluate the functional significance of the biophysical properties of CAR binding (i.e., affinity, avidity, and antigen density), we generated an experimental system in which these properties are controllable. We constructed and characterized a series of CARs, which target the melanoma tumor–associated antigen Tyr/HLA-A2, and in which the affinity of the single-chain Fv binding domains ranged in KD from 4 to 400 nmol/L. These CARs were transduced into T cells, and each CAR T-cell population was sorted by the level of receptor expression. Finally, the various CAR T cells were encountered with target cells that present different levels of the target antigen. We detected nonmonotonic behaviors of affinity and antigen density, and an interrelation between avidity and antigen density. Antitumor activity measurements in vitro and in vivo corroborated these observations. Our study contributes to the understanding of CAR T-cell function and regulation, having the potential to improve therapies by the rational design of CAR T cells. See related article on p. 946

Adoptive cell immunotherapy with chimeric antigen receptor (CAR) showed limited potency in solid tumors, despite durable remissions for hematopoietic malignancies. Therefore, an investigation of ways to enhance the efficacy of CARs' antitumor response has been engaged upon. We previously examined the interplay between the biophysical parameters of CAR binding (i.e., affinity, avidity, and antigen density), as regulators of CAR T-cell activity and detected nonmonotonic behaviors of affinity and antigen density and an interrelation between avidity and antigen density. Here, we built an evolving phenotypic model of CAR T-cell regulation, which suggested that receptor downmodulation is a key determinant of CAR T-cell function. We verified this assumption by measuring and manipulating receptor downmodulation and intracellular signaling processes. CAR downmodulation inhibition, via actin polymerization inhibition, but not inhibition of regulatory inhibitory phosphatases, was able to increase CAR T-cell responses. In addition, we documented trogocytosis in CAR T cells that depends on actin polymerization. In summary, our study modeled the parameters that govern CAR T-cell engagement and revealed an underappreciated mechanism of T-cell regulation. These results have a potential to predict and therefore advance the rational design of CAR T cells for adoptive cell treatments. See related article on p. 872

Molecular mechanisms driving disease course and response to therapy in ulcerative colitis (UC) are not well understood. Here, we use RNAseq to define pre-treatment rectal gene expression, and fecal microbiota profiles, in 206 pediatric UC patients receiving standardised therapy. We validate our key findings in adult and paediatric UC cohorts of 408 participants. We observe a marked suppression of mitochondrial genes and function across cohorts in active UC, and that increasing disease severity is notable for enrichment of adenoma/adenocarcinoma and innate immune genes. A subset of severity genes improves prediction of corticosteroid-induced remission in the discovery cohort; this gene signature is also associated with response to anti-TNFα and anti-α4β7 integrin in adults. The severity and therapeutic response gene signatures were in turn associated with shifts in microbes previously implicated in mucosal homeostasis. Our data provide insights into UC pathogenesis, and may prioritise future therapies for nonresponders to current approaches., The severity of ulcerative colitis, and response to treatment, is highly variable. Here, the authors examine rectal gene expression signatures and faecal microbiomes of children and adults with the disease and provide new insights in to pathogenesis.

Background: Crohn's disease displays heterogeneity in terms of disease location, progression and response to treatment. Most patients require an intestinal resection due to complicated disease, and a majority of them will experience disease recurrence. We aimed to characterize biological pathways driving postoperative recurrence and to identify predictors which could guide therapeutic management. Methods: In this multicentre prospective study, we conducted transcriptome analysis on ileal mucosa of CD patients undergoing ileocolonic resection. Samples were collected from the most inflamed part of the ileum (n=200), from the ileal resection margin (n=149) and in the neo-terminal ileum 6 months after surgery (n=122). The primary endpoint was postoperative endoscopic recurrence at month 6. We applied a regression model to identify gene signatures predicting for endoscopic recurrence. Findings: Molecular patterns of early endoscopic recurrence significantly differed from those observed in chronic inflammation. Gene expression analysis of the inflamed area of the surgical specimens identified clusters of CD patients. However, pathway gene signatures at the ileal margin were superior to those of the inflamed area to predict postoperative outcome. Several pathways, including JAK/STAT signalling, cell adhesion molecules and extracellular matrix protein were associated with a higher risk of endoscopic recurrence. JAK/STAT pathway activation at the ileal margin predicted early postoperative endoscopic recurrence (AUC of 0*74) and was associated with a higher of clinical relapse on the long term. A significant increase of p-STAT3 levels at the ileal margin was associated with severe endoscopic recurrence (i3, i4) compared to no recurrence (i0) (p=0*02) and moderate recurrence (i1, i2) (p=0*04). Interpretation: Gene expression analysis at the ileal margin of the surgical specimen may strongly predict postoperative outcome. The inflammatory processes associated with postoperative recurrence differ from those engaged in chronic inflammation. Activation of JAK/STAT signalling at the ileal margin of the surgical specimen is predictive of postoperative recurrence and should be specifically targeted. Trial Registration: ClinicalTrials.gov (NCT03458195). Funding Statement: This work was supported by Helmsley Charitable Trust and the Institut national de sante et de la recherche biomedical (INSERM). Declaration of Interests: SN received honoraria from MSD, Abbvie, Takeda, Janssen, HAC Pharma, Tillots, Ferring, and Novartis. BP received honoraria from AbbVie, MSD, Takeda, Janssen, Bioagaran, and Ferring. AB received honoraria from MSD, Abbvie, Ferring, Takeda, Vifor Pharma, Sanofi-Aventis, Hospira, and Janssen. XT received honoraria from Abbvie, MSD, Takeda, Ferring, Norgine, and Janssen. MF received honoraria from AbbVie, MSD, Takeda, Janssen, Pfizer, Ferring, and Boehringer. PS received honoraria from Takeda, MSD, Biocodex, Ferring and Abbvie and financial support from Takeda. MA received honoraria from Janssen, Takeda, Pfizer, MSD, Abbvie, Ferring, Amgen, Biogen, Celgene, and Genentech/Roche. All other authors have no conflict of interest regarding this study. Ethics Approval Statement: All patients provided an informed written consent. The study was approved by AFFSAPS (IDRCB: 2009-A00205-52) and the French Ethic Committee (CPP 2009/17).

We appreciate the interest of Akiyama et al in our report and thank them for the data presented in their letter.1 2 Akiyama et al have presented a thorough literature review and have described a positive and efficacious effect of tocilizumab in 11 cases of refractory polyarteritis nodosa (PAN) described in 6 case series. Indeed, the use of tocilizumab, an interleukin (IL)-6 inhibitor, in vasculitis is gaining evidence in the literature, specifically in large vessel vasculitis including giant cell arteritis and Takayasu arteritis.3 4 Nevertheless, it should be noted that although the …

SUMMARY Inflammatory bowel disease (IBD) is prevalent, but the mechanisms underlying disease development remain elusive. We identify a role for the E3 ubiquitin ligase RNF5 in IBD. Intestinal epithelial cells (IECs) express a high level of RNF5, while the colon of Rnf5−/− mice exhibits activated dendritic cells and intrinsic inflammation. Rnf5−/− mice exhibit severe acute colitis following dextran sodium sulfate (DSS) treatment. S100A8 is identified as an RNF5 substrate, resulting in S100A8 ubiquitination and proteasomal-dependent degradation that is attenuated upon inflammatory stimuli. Loss of RNF5 from IECs leads to enhanced S100A8 secretion, which induces mucosal CD4+ T cells, resulting in Th1 pro-inflammatory responses. Administration of S100A8-neutralizing antibodies to DSS-treated Rnf5−/− mice attenuates acute colitis development and increases survival. An inverse correlation between RNF5 and S100A8 protein expression in IECs of IBD patients coincides with disease severity. Collectively, RNF5-mediated regulation of S100A8 stability in IECs is required for the maintenance of intestinal homeostasis., In Brief Fujita et al. show that RNF5 regulation of S100A8 stability in intestinal epithelial cells defines the degree of pro-inflammatory response, culminating in severe intestinal inflammation following DSS treatment to Rnf5−/− mice. Neutralizing S100A8 antibodies attenuates acute colitis phenotypes, and inverse RNF5/S100A8 expression coincides with clinical severity in IBD patients., Graphical Abstract

Natural killer (NK) cells use a diverse array of activating and inhibitory surface receptors to detect threats and provide an early line of defense against viral infections and cancer. Here, we demonstrate that the cell surface protein CD38 is a key human NK cell functional receptor through a role in immune synapse formation. CD38 expression marks a mature subset of human NK cells with a high functional capacity. NK cells expressing high levels of CD38 display enhanced killing and IFN-γ secretion in response to influenza virus-infected and tumor cells. Inhibition of CD38 enzymatic activity does not influence NK cell function, but blockade of CD38 and its ligand CD31 abrogates killing and IFN-γ expression in response to influenza-infected cells. Blockade of CD38 on NK cells similarly inhibits killing of tumor cells. CD38 localizes and accumulates at the immune synapse between NK cells and their targets, and blocking CD38 severely abrogates the ability of NK cells to form conjugates and immune synapses with target cells. Thus, CD38 plays a critical role in NK cell immune synapse formation. These findings open new avenues in immunotherapeutic development for cancer and infection by revealing a critical role for CD38 in NK cell function.

Cross-species differences form barriers to translational research that ultimately hinder the success of clinical trials, yet knowledge of species differences has yet to be systematically incorporated in the interpretation of animal models. Here we present Found In Translation (FIT; http://www.mouse2man.org ), a statistical methodology that leverages public gene expression data to extrapolate the results of a new mouse experiment to expression changes in the equivalent human condition. We applied FIT to data from mouse models of 28 different human diseases and identified experimental conditions in which FIT predictions outperformed direct cross-species extrapolation from mouse results, increasing the overlap of differentially expressed genes by 20–50%. FIT predicted novel disease-associated genes, an example of which we validated experimentally. FIT highlights signals that may otherwise be missed and reduces false leads, with no experimental cost. The machine learning approach FIT leverages public mouse and human expression data to improve the translation of mouse model results to analogous human disease.

Immunology researchers are beginning to explore the possibilities of reproducibility, reuse and secondary analyses of immunology data. Open-access datasets are being applied in the validation of the methods used in the original studies, leveraging studies for meta-analysis, or generating new hypotheses. To promote these goals, the ImmPort data repository was created for the broader research community to explore the wide spectrum of clinical and basic research data and associated findings. The ImmPort ecosystem consists of four components–Private Data, Shared Data, Data Analysis, and Resources—for data archiving, dissemination, analyses, and reuse. To date, more than 300 studies have been made freely available through the Shared Data portal (www.immport.org/immport-open), which allows research data to be repurposed to accelerate the translation of new insights into discoveries.

SummaryComplex physiological functionality is often the outcome of multiple interacting cell-types, yet mechanistically how a large number of trait-associated genes yield a single multi-cellular network governing the phenotype has not been well defined. Individuals’ immune-cellular profiles at homeostasis show high heritability and inter-individual variation with functional and clinical implications. We profiled immune cellular variation by mass-cytometry in 55 genetically diverse mouse strains. We identify 788 genes associated with cellular homeostasis, supporting a polygenic model where 52% of genes correspond to core homeostatic functions whose genetic variants suffice to predict phenotype. Trait genes form a multi-cellular network architecture showing increased functional complexity over evolutionary timescales for shared regulation to all cells, specialized cell-specific programs, and between-cell synchronization. Contrasting to human studies suggests the regulatory network expands with environmental exposure history. Our findings shed light on the origin of immune-cellular variation and regulatory architectures that may generalize to other environmentally sensitive systems.

Late allograft failure is characterized by cumulative subclinical insults manifesting over many years. Although immunomodulatory therapies targeting host T cells have improved short-term survival rates, rates of chronic allograft loss remain high. We hypothesized that other immune cell types may drive subclinical injury, ultimately leading to graft failure. We collected whole-genome transcriptome profiles from 15 independent cohorts composed of 1,697 biopsy samples to assess the association of an inflammatory macrophage polarization-specific gene signature with subclinical injury. We applied penalized regression to a subset of the data sets and identified a 3-gene inflammatory macrophage-derived signature. We validated discriminatory power of the 3-gene signature in 3 independent renal transplant data sets with mean AUC of 0.91. In a longitudinal cohort, the 3-gene signature strongly correlated with extent of injury and accurately predicted progression of subclinical injury 18 months before clinical manifestation. The 3-gene signature also stratified patients at high risk of graft failure as soon as 15 days after biopsy. We found that the 3-gene signature also distinguished acute rejection (AR) accurately in 3 heart transplant data sets but not in lung transplant. Overall, we identified a parsimonious signature capable of diagnosing AR, recognizing subclinical injury, and risk-stratifying renal transplant patients. Our results strongly suggest that inflammatory macrophages may be a viable therapeutic target to improve long-term outcomes for organ transplantation patients.

Tofacitinib is a novel inhibitor of Janus kinase (JAK) 3 and JAK1 is recently introduced as treatment for rheumatoid arthritis.1 The JAK inhibitors are at the focus of research in a myriad of other inflammatory diseases2 ,3 as the JAK-(signal transducer and activator of transcription) STAT pathway has a central role in cytokine signal transduction. We herein describe a case of refractory polyarteritis nodosa (PAN) successfully treated with tofacitinib. A 28-year-old man had been diagnosed with PAN at age 14. He presented with livedo reticularis, arthritis and skin nodules with arteritis/fibrinoid necrosis confirmed on biopsy. Immunological panel at the time of diagnosis was negative for antineutrophil cytoplasmic antibodies, anti-nuclear antibodies, anti-Ro/SS-A antibodies, anti-La/SS-B antibodies, rheumatoid factor, with normal complement levels. He was treated with azathioprine and methotrexate for several years with drug-controlled complete remission. At age 24, his disease flared and he began to suffer from necrotic lesions of the scrotum and calves, excruciating abdominal pain and polyarthritis, with high C-reactive protein (CRP) levels (160–300 mg/L) for which he received recurrent intravenous methylprednisolone pulses and oral …

Annual influenza vaccinations are currently recommended for all individuals 6 months and older. Antibodies induced by vaccination are an important mechanism of protection against infection. Despite the overall public health success of influenza vaccination, many individuals fail to induce a substantial antibody response. Systems-level immune profiling studies have discerned associations between transcriptional and cell subset signatures with the success of antibody responses. However, existing signatures have relied on small cohorts and have not been validated in large independent studies. We leveraged multiple influenza vaccination cohorts spanning distinct geographical locations and seasons from the Human Immunology Project Consortium (HIPC) and the Center for Human Immunology (CHI) to identify baseline (i.e., before vaccination) predictive transcriptional signatures of influenza vaccination responses. Our multicohort analysis of HIPC data identified nine genes (RAB24, GRB2, DPP3, ACTB, MVP, DPP7, ARPC4, PLEKHB2, and ARRB1) and three gene modules that were significantly associated with the magnitude of the antibody response, and these associations were validated in the independent CHI cohort. These signatures were specific to young individuals, suggesting that distinct mechanisms underlie the lower vaccine response in older individuals. We found an inverse correlation between the effect size of signatures in young and older individuals. Although the presence of an inflammatory gene signature, for example, was associated with better antibody responses in young individuals, it was associated with worse responses in older individuals. These results point to the prospect of predicting antibody responses before vaccination and provide insights into the biological mechanisms underlying successful vaccination responses.

Single-cell RNA sequencing and high-dimensional cytometry can be used to generate detailed trajectories of dynamic biological processes such as differentiation or development. Here we present cellAlign, a quantitative framework for comparing expression dynamics within and between single-cell trajectories. By applying cellAlign to mouse and human embryonic developmental trajectories, we systematically delineate differences in the temporal regulation of gene expression programs that would otherwise be masked.

West Nile virus (WNV) infection is usually asymptomatic but can cause severe neurological disease and death, particularly in older patients, and how individual variations in immunity contribute to disease severity is not yet defined. Animal studies identified a role for several immunity-related genes that determine the severity of infection. We have integrated systems-level transcriptional and functional data sets from stratified cohorts of subjects with a history of WNV infection to define whether these markers can distinguish susceptibility in a human population. Transcriptional profiles combined with immunophenotyping of primary cells identified a predictive signature of susceptibility that was detectable years after acute infection (67% accuracy), with the most prominent alteration being decreased IL1B induction followingex vivoinfection of macrophages with WNV. Deconvolution analysis also determined a significant role for CXCL10 expression in myeloid dendritic cells. This systems analysis identified markers of pathogenic mechanisms and offers insights into potential therapeutic strategies.

Metastasis is the major cause of death in cancer patients. Recent studies have demonstrated that the crosstalk between different host and tumor cells in the tumor microenvironment regulates tumor progression and metastasis. Specifically, immune cell myeloid skewing is a prominent promoter of metastasis. While previous studies have demonstrated that the recruitment of myeloid cells to tumors is a critical step in dictating tumor fate, the reservoir of these cells in the bone marrow (BM) compartment and their differentiation pattern has not been explored. Here we utilized a unique model system consisting of tumor cell clones with low and high metastatic potential (met-low and met-high, respectively) derived from melanoma and breast carcinoma cell lines. Hematopoietic stem cells (HSCs) and their early progenitor subset were defined as Lin-/Sca1+/CD117+, representing LSK cells. BM transplantation experiments using GFP-positive LSK cells derived from met-low and met-high tumor bearing mice were carried out to study lineage differentiation. The genetic signatures of LSK cells were analyzed by single cell RNA-sequencing (scRNA-seq). This analysis included unbiased automated annotation of individual cell types by correlating single-cell gene expression with reference transcriptomic data sets (SingleR algorithm) in order to evaluate the proportions of cell types in BM and reveal cell type-specific differentially expressed genes. Expression patterns of proteins originated from tumor cells were analyzed using a range of multi-omics techniques including nanostring, protein array, and mass spectrometry analysis. Tumor proteomic data was integrated with differential receptor expression patterns in BM cell types to reveal novel crosstalk between tumor cells and HSCs in the BM compartment. Mice bearing met-high tumors exhibited a significant increase in the percentage of LSK cells in the BM in comparison to tumor-free mice or mice bearing met-low tumors. These results were confirmed by functional CFU assays of peripheral blood of met-high compared to met-low tumor bearing mice. In addition, mice that underwent BM transplantation with GFP-positive LSK cells obtained from met-high inoculated donors exhibited an increased percentage of circulating GFP-positive myeloid cells in comparison to counterpart mice transplanted with LSK cells from met-low inoculated donors. Moreover, scRNA-seq analysis of LSK cells obtained from the BM of met-low and met-high tumor bearing mice revealed that met-high tumors induce the enrichment of monocyte-dendritic progenitor population (MDP), confirmed also by flow cytometry. To uncover the possible factors involved in myeloid programming of LSK cells, we performed a proteomic screen of tumor conditioned medium and integrated the results with the scRNA-seq data analysis. This analysis revealed that the IL-6-IL-6R axis is highly active in LSK-derived MDP cells from mice bearing met-high tumors. An adoptive transfer experiment using MDP-GFP+ cells obtained from BM of met-high tumor bearing mice demonstrated that met-high tumors directly dictate HSC fate decision towards myeloid bias, resulting in increased metastasis. Evidently, blocking IL-6 in mice bearing met-high tumors reduced the number of MDP cells, and consequently decreased metastasis. Our study reveals a unique crosstalk between tumor cells and HSCs. It provides new insight into the mechanism by which tumors contribute to the presence of supporting stroma. Specifically, tumors secreting IL-6 dictate a specific genetic signature in HSCs that programs them towards myeloid differentiation, thereby inducing a metastatic switch. Disclosures No relevant conflicts of interest to declare.

Background & Aims Some patients develop anti-drug antibodies (ADAs), which reduce the efficacy of infliximab, a monoclonal antibody against tumor necrosis factor (TNF), in the treatment of immune-mediated diseases, including inflammatory bowel diseases. ADAs arise inconsistently, and it is not clear what factors determine their formation. We investigated features of the immune system, the infliximab antibody, and its complex with TNF that might contribute to ADA generation. Methods C57BL/6 mice were given injections of infliximab and recombinant human TNF or infliximab F(ab′)2 fragments. Blood samples were collected every 2–3 days for 2 weeks and weekly thereafter for up to 6 weeks; infliximab-TNF complexes and ADAs were measured by enzyme-linked immunosorbent assay (ELISA). Intestinal biopsy and blood samples were obtained from patients having endoscopy who had received infliximab therapy for inflammatory bowel diseases; infliximab-TNF complexes were measured with ELISA. Infliximab-specific plasma cells were detected in patient tissue samples by using mass cytometry. We studied activation of innate immune cells in peripheral blood mononuclear cells (PBMCs) from healthy donors incubated with infliximab or infliximab-TNF complexes; toll-like receptors (TLRs) were blocked with antibodies, endocytosis was blocked with the inhibitor PitStop2, and cytokine expression was measured by real-time polymerase chain reaction and ELISAs. Uptake of infliximab and infliximab-TNF complexes by THP-1 cells was measured with confocal microscopy. Results Mice given increasing doses of infliximab produced increasing levels of ADAs. Blood samples from mice given injections of human TNF and infliximab contained infliximab-TNF complexes; complex formation was associated with ADA formation with an area under the curve of 0.944 (95% confidence interval, 0.851–1.000; P = .003). Intestinal tissues from patients, but not blood samples, contained infliximab-TNF complexes and infliximab-specific plasma cells. Incubation of PBMCs with infliximab-TNF complexes resulted in a 4.74-fold increase in level of interleukin (IL) 1β (IL1B) messenger RNA (P for comparison = .005), increased IL1B protein secretion, and a 2.69-fold increase in the expression of TNF messenger RNA (P for comparison = 0.013) compared with control PBMCs. Infliximab reduced only IL1B and TNF expression. Antibodies against TLR2 or TLR4 did not block the increases in IL1B or TNF expression, but endocytosis was required. THP-1 cells endocytosed higher levels of infliximab-TNF complexes than infliximab alone. Conclusions In mice, we found ADA formation to increase with dose of infliximab given and concentration of infliximab-TNF complexes detected in blood. Based on studies of human intestinal tissues and blood samples, we propose that infliximab-TNF complexes formed in the intestine are endocytosed by and activate innate immune cells, which increase expression of IL1B and TNF and production of antibodies against the drug complex. It is therefore important to optimize the infliximab dose to a level that is effective but does not activate an innate immune response against the drug-TNF complex.

Single-molecule techniques for protein sequencing are making headway towards single-cell proteomics and are projected to propel our understanding of cellular biology and disease. Yet, single cell proteomics presents a substantial unmet challenge due to the unavailability of protein amplification techniques, and the vast dynamic-range of protein expression in cells. Here, we describe and computationally investigate the feasibility of a novel approach for single-protein identification using tri-color fluorescence and plasmonic-nanopore devices. Comprehensive computer simulations of denatured protein translocation processes through the nanopores show that the tri-color fluorescence time-traces retain sufficient information to permit pattern-recognition algorithms to correctly identify the vast majority of proteins in the human proteome. Importantly, even when taking into account realistic experimental conditions, which restrict the spatial and temporal resolutions as well as the labeling efficiency, and add substantial noise, a deep-learning protein classifier achieves 97% whole-proteome accuracies. Applying our approach for protein datasets of clinical relevancy, such as the plasma proteome or cytokine panels, we obtain ~98% correct protein identification. This study suggests the feasibility of a method for accurate and high-throughput protein identification, which is highly versatile and applicable., Author summary Macromolecules identification methods are central for most biological and biomedical studies, and while the field of genomics advanced to single-molecule resolution, the proteomic field still relies on bulk and costly techniques. We describe a solution for single protein identification, based on the analysis of optical traces obtained from fluorescently-labeled proteins threaded through a nanopore and processed by a pattern recognition algorithm. To evaluate the feasibility of our method we constructed computer simulations of the system, producing and analyzing nearly 108 individual protein translocations from the human Swiss-Prot database. Our results suggest protein identification of >95% for the whole human proteome, even under non-ideal conditions. These results constitute the basis for a novel whole proteome identification method, with single molecule resolution.

The quanta unit of the immune system is the cell; yet analyzed samples are often heterogeneous with respect to cell subsets which can mislead result interpretation. Experimentally, researchers face a difficult choice whether to profile heterogeneous samples with the ensuing confounding effects, or a priori focus on a few cell subsets of interest, potentially limiting new discoveries. An attractive alternative solution is to extract cell subset-specific information directly from heterogeneous samples via computational deconvolution techniques, thereby capturing both cell-centered and whole system level context. Such approaches are capable of unraveling novel biology, undetectable otherwise. Here we review the present state of available deconvolution techniques, their advantages and limitations, with a focus on blood expression data and immunological studies in general.

System-wide approaches are now being applied to study vaccine responses, whose mechanisms of action, and failure, are not well understood. These works have repeatedly shown vaccine response to be an orchestrated process involving multiple arms of immunity most noticeable sensing and innate components. Prediction of vaccine responses based on system-wide measures is achievable, but challenges remain for robust population wide predictions based only on pre-vaccination measures, especially in partially efficacious vaccines such as influenza. This is especially true in older adults, who are often less responsive to vaccination and exhibit high level of variation compared to young in many components of immunity. Despite this increase in variation, most of the studies on aging use group averages of immune phenotypes to model immune system behavior. Using systems approaches, it is possible to exploit this variation to form distinguishable clusters of phenotypes within and across individuals to discover underlying immune states.