Although most pediatric acute myeloid leukemia (pAML) patients achieve complete remission with standard-of-care chemotherapy, overall outcomes are poor, and 40% will eventually relapse. Improved methods for risk assessment at diagnosis and alternative therapies are needed to improve outcomes for these patients. Toward these objectives, we characterized the clonal composition of pAMLs, identifying subclones that expand or transform between diagnosis and relapse. We further showed that the abundance of these expanding and transforming subclones in diagnostic samples is predictive of patient outcomes and, similarly, predicts response to chemotherapy and targeted therapies in patient samples and patient-derived xenograft models. Moreover, gene expression programs previously associated with pAML chemoresistance are recurrently elevated in these predictive subclones. Consequently, we propose a novel strategy for improving pAML risk prediction at both diagnosis and during therapy that combines the detection of outcome-predictive tumor subclones in pAML blood or bone marrow with cytogenetic biomarkers and residual disease assessment. Critically, we showed that this combination dramatically improved risk prediction, including for patients who achieve complete remission after chemotherapy. Moreover, through our analyses of outcome-predictive pAML subclones, we identified potential personalized targeted therapies for pAML patients based on the composition of their tumors.

Host-respiratory microbiome interplay is vital to lung homeostasis. Systemic inflammatory response syndrome (SIRS) is an intense alteration in host status that necessitates rapid microbiome adaptation to avoid respiratory complications. Using longitudinal multi-omic data from patients with SIRS, we confirm that the respiratory microbiome, blood metabolome, and immune cells form a dynamic metasystem and define a metacluster with distinct T/B cell trafficking, anaerobic bacteria, high tyrosine metabolism, and low fatty acid biosynthesis. This metacluster status can serve to classify the severity of alterations in host-lung microbiome interactions as moderate or severe and to predict pneumonia and mortality. We demonstrate the robustness of these findings in an independent, randomized controlled trial and propose that interferon-γ treatment may benefit patients with severe metacluster alterations but harm those with moderate alterations. Our study supports the concept of the host-respiratory microbiome as a dynamic metasystem, in which specific alterations are associated with pneumonia and responses to interferon-γ treatment.

The 2022 World Health Organization and International Consensus Classification (WHO/ICC 2022) diagnostic classifications for hematological malignancies remain focused on cancer cell characteristics, largely neglecting the immune environment. This disconnection limits diagnostic accuracy and the potential for tailored and individualized therapeutic intervention. The potential for exploiting the nonmalignant immune compartment as therapy targets (e.g., bispecific antibodies) or biomarkers of patient outcomes, should be included in guiding clinical decision making. To bridge this gap, distinct immune profile classifications, such as inflammatory subtypes, need standardized definitions. Next-generation profiling technologies - including single-cell sequencing, spatial transcriptomics, and advanced cytometry - should be integrated into clinical workflows or translated into practical diagnostic tools. Therefore, next-generation immune profiling for hematological malignancies goes beyond the cancer cells - enabling improved disease classification and precision immunotherapies.

Myelin oligodendrocyte glycoprotein antibody-associated disease (MOGAD) is a recently defined neurological autoimmune condition. The pathogenesis of the disease remains poorly understood, and no specific therapies are currently approved. Here, a comprehensive single-cell immunophenotyping of peripheral blood mononuclear cells from two independent cohorts of patients with MOGAD revealed pronounced immune perturbations in MOGAD when compared with healthy controls and patients with multiple sclerosis. Patients with MOGAD displayed an expansion of CXCR5-CD21- activated naïve and double-negative B cell subsets, a feature shared with patients with systemic lupus erythematosus. In addition, we observed altered Fc gamma receptor expression in natural killer cells, monocytes, and dendritic cells. Within the T cell compartment, CXCR3+CD4+ memory T cells were reduced in the circulation of patients with MOGAD compared with healthy controls, and this result was mirrored in a transgenic mouse model that showed retention of these cells in the inflamed central nervous system. Together, these results demonstrate profound systemic immune cell alterations in MOGAD and contribute to a better understanding of this distinct disease entity.

Most pediatric acute myeloid leukemia (pAML) patients achieve complete remission after chemotherapy, yet relapse is common, with nearly 40% ultimately dying of the disease. Prognosis is currently assessed using cytogenetic biomarkers and measurable residual disease after the first chemotherapy cycle, with the highest risk patients referred for stem cell transplantation (SCT) at first remission. Because aggressive therapies such as SCT are highly toxic, yet cures after relapse are rare, accurate early risk prediction is essential for improving outcomes. To address this need, we analyzed paired diagnosis-relapse samples from 33 pAML patients at single-cell resolution and identified chemoresistant cell populations whose abundance at diagnosis significantly improved risk prediction. Incorporating the detection of these cell populations into our risk model revealed a previously unrecognized patient subgroup with a 5-year event-free survival rate below 40%. Although this subgroup represents only 20% of pAML cases, it accounted for half of the deaths among patients who do not receive SCT at first remission. Moreover, molecular characterization of these chemoresistant cell populations uncovered potential therapeutic targets and candidate interventions relevant to most high-risk patients, paving the way for more effective targeted treatments for high-risk pAML patients.

Immune-related adverse events (irAEs) in cancer patients receiving immune checkpoint inhibitors (ICIs) cause morbidity and necessitate cessation of treatment. Comparing irAE treatments, we find that anti-tumor immunity is preserved in mice after extracorporeal photopheresis (ECP) but reduced with glucocorticosteroids, TNFα blockade, and α4β7-integrin inhibition. Local adiponectin production elicits a tissue-specific effect by reducing pro-inflammatory T cell frequencies in the colon while sparing tumor-specific T cell development. A prospective phase-1b/2 trial (EudraCT-No.2021-002073-26) with 14 patients reveals low ECP-related toxicity. Overall response rate for all irAEs is 92% (95% confidence interval [CI]: 63.97%-99.81%); colitis-specific complete remission rate is 100% (95% CI: 63.06%-100%). Glucocorticosteroid dosages could be reduced for all patients after ECP therapy. The ECP-adiponectin axis reduces intestinal tissue-resident memory T cell activation and CD4+IFN-γ+ T cells in patients with ICI-induced colitis without evidence of loss of anti-tumor immunity. In conclusion, we identify adiponectin as an immunomodulatory molecule that controls ICI-induced irAEs without blocking anti-tumor immunity.

BACKGROUND:Patients with common variable immunodeficiency (CVID) suffer from hypogammaglobulinemia linked to an inadequate differentiation of long-lived humoral immunity and an impaired germinal center (GC) response in most cases. OBJECTIVE:We sought to further characterize the transcriptome and phenotype of T follicular helper (TFH) cells of patients with complicated CVID (CVIDc) as key players in the GC reaction. METHODS:Sorted TFH cells from CVIDc lymph nodes and non-CVID immunocompetent tonsils were analyzed by bulk RNA sequencing. Altered protein expression was verified by comparison with non-CVID tonsils and lymph nodes using cytometry by time-of-flight analysis. Tissue localization of cells was determined by multifluorescence imaging. RESULTS:Transcriptome analysis of sorted TFH cells revealed an enrichment of cytotoxicity-associated gene sets in patients with CVIDc. Extended immune phenotyping identified different cytotoxic CD4 memory populations expressing T-bet, EOMES (eomesodermin), class I-restricted T-cell-associated molecule, perforin, and granzymes. One cluster coexpressing markers of TFH differentiation C-X-C chemokine receptor type 5, inducible costimulator, and programmed cell death protein 1 was expanded in CVIDc lymph nodes. Histologic sections confirmed the increase in Granzyme-B+EOMES+CD4 cells within GCs of patients' lymph nodes. Only few of these cells circulate in peripheral blood. CONCLUSIONS:Our study reports for the first time that the type 1 polarization in lymph nodes of patients with CVIDc is associated with an expansion of a distinct cytotoxic CD4 TFH-cell cluster within GCs, which is only poorly reflected in peripheral blood. Because a detrimental role of these cells has been implied in the context of autoimmunity and chronic infection, further investigations are required to explore their role in the GC failure and immune dysregulation in patients with CVID.

Defective FAS (CD95/Apo-1/TNFRSF6) signaling causes autoimmune lymphoproliferative syndrome (ALPS). Hypergammaglobulinemia is a common feature in ALPS with FAS mutations (ALPS-FAS), but paradoxically, fewer conventional memory cells differentiate from FAS-expressing germinal center (GC) B cells. Resistance to FAS-induced apoptosis does not explain this phenotype. We tested the hypothesis that defective non-apoptotic FAS signaling may contribute to impaired B cell differentiation in ALPS. We analyzed secondary lymphoid organs of patients with ALPS-FAS and found low numbers of memory B cells, fewer GC B cells, and an expanded extrafollicular (EF) B cell response. Enhanced mTOR activity has been shown to favor EF versus GC fate decision, and we found enhanced PI3K/mTOR and BCR signaling in ALPS-FAS splenic B cells. Modeling initial T-dependent B cell activation with CD40L in vitro, we showed that FAS competent cells with transient FAS ligation showed specifically decreased mTOR axis activation without apoptosis. Mechanistically, transient FAS engagement with involvement of caspase-8 induced nuclear exclusion of PTEN, leading to mTOR inhibition. In addition, FASL-dependent PTEN nuclear exclusion and mTOR modulation were defective in patients with ALPS-FAS. In the early phase of activation, FAS stimulation promoted expression of genes related to GC initiation at the expense of processes related to the EF response. Hence, our data suggest that non-apoptotic FAS signaling acts as molecular switch between EF versus GC fate decisions via regulation of the mTOR axis and transcription. The defect of this modulatory circuit may explain the observed hypergammaglobulinemia and low memory B cell numbers in ALPS.

Infants with biallelic IL7R loss-of-function variants have severe combined immune deficiency (SCID) characterized by the absence of autologous T lymphocytes, but normal counts of circulating B and NK cells (T-B+NK+ SCID). We report 6 adults (aged 22 to 59 years) from 4 kindreds and 3 ancestries (Colombian, Israeli Arab, Japanese) carrying homozygous IL7 loss-of-function variants resulting in combined immunodeficiency (CID). Deep immunophenotyping revealed relatively normal counts and/or proportions of myeloid, B, NK, and innate lymphoid cells. By contrast, the patients had profound T cell lymphopenia, with low proportions of innate-like adaptive mucosal-associated invariant T and invariant NK T cells. They also had low blood counts of T cell receptor (TCR) excision circles, recent thymic emigrant T cells and naive CD4(+) T cells, and low overall TCR repertoire diversity, collectively indicating impaired thymic output. The proportions of effector memory CD4(+) and CD8(+) T cells were high, indicating IL-7-independent homeostatic T cell proliferation in the periphery. Intriguingly, the proportions of other T cell subsets, including TCR gamma delta(+) T cells and some TCR alpha beta(+) T cell subsets (including Th1, Tfh, and Treg) were little affected. Peripheral CD4(+) T cells displayed poor proliferation, but normal cytokine production upon stimulation with mitogens in vitro. Thus, inherited IL-7 deficiency impairs T cell development less severely and in a more subset-specific manner than IL-7R deficiency. These findings suggest that another IL-7R-binding cytokine, possibly thymic stromal lymphopoietin, governs an IL-7-independent pathway of human T cell development.

Pediatric acute myeloid leukemia (AML) is an aggressive blood cancer with a poor prognosis and high relapse rate. Current challenges in the identification of immunotherapy targets arise from patient-specific blast immunophenotypes and their change during disease progression. To overcome this, we present a new computational research tool to rapidly identify malignant cells. We generated single-cell flow cytometry profiles of 21 pediatric AML patients with matched samples at diagnosis, remission, and relapse. We coupled a classifier to an autoencoder for anomaly detection and classified malignant blasts with 90% accuracy. Moreover, our method assigns a developmental stage to blasts at the single-cell level, improving current classification approaches based on differentiation of the dominant phenotype. We observed major immunophenotype and developmental stage alterations between diagnosis and relapse. Patients with KMT2A rearrangement had more profound changes in their blast immunophenotypes at relapse compared to patients with other molecular features. Our method provides new insights into the immunophenotypic composition of AML blasts in an unbiased fashion and can help to define immunotherapy targets that might improve personalized AML treatment.

Patients with corticosteroid-refractory acute graft-versus-host disease (aGVHD) have a low one-year survival rate. Identification and validation of novel targetable kinases in patients who experience corticosteroid-refractory-aGVHD may help improve outcomes. Kinase-specific proteomics of leukocytes from patients with corticosteroid-refractory-GVHD identified rho kinase type 1 (ROCK1) as the most significantly upregulated kinase. ROCK1/2 inhibition improved survival and histological GVHD severity in mice and was synergistic with JAK1/2 inhibition, without compromising graft-versus-leukemia-effects. ROCK1/2-inhibition in macrophages or dendritic cells prior to transfer reduced GVHD severity. Mechanistically, ROCK1/2 inhibition or ROCK1 knockdown interfered with CD80, CD86, MHC-II expression and IL-6, IL-1β, iNOS and TNF production in myeloid cells. This was accompanied by impaired T cell activation by dendritic cells and inhibition of cytoskeletal rearrangements, thereby reducing macrophage and DC migration. NF-κB signaling was reduced in myeloid cells following ROCK1/2 inhibition. In conclusion, ROCK1/2 inhibition interferes with immune activation at multiple levels and reduces acute GVHD while maintaining GVL-effects, including in corticosteroid-refractory settings.

Introduction: Resistance to therapy remains a major challenge for Mantle Cell Lymphoma (MCL) patients, despite a diverse and expanding treatment landscape. There is thus a major need to better understand the mechanistic underpinnings of therapy resistance in order to optimize treatment selection. Given the advent of immunotherapies in recent years, there has been increasing evidence that not only tumor-intrinsic factors affect therapy resistance, but that tumor-immune cell interactions are an additional major contributor. In the context of MCL, such interactions have been poorly characterized, but hold the promise of identifying novel treatment approaches and better understanding resistance mechanisms to commonly applied therapies such as BTK inhibition. Methods: This study aimed to investigate the single-cell landscape of leukemic MCL using single-cell profiling of 26 patients and 10 healthy donors. In addition, we performed in vitro drug testing on a subset of patient samples (n=12; 6 treatments) to understand the effects of drugs on both tumor and immune cells in MCL . To comprehensively characterize the phenotypic and functional features of immune and tumor cells within a single-cell landscape, we employed high-dimensional full-spectrum cytometry. Therefore, we developed 5 high-dimensional panels covering markers to deeply interrogate T and NK cells, immune evasion and immune checkpoints, cytokines and cytotoxicity, cellular trafficking and intracellular signaling/phosphoproteome (covering >120 proteins). We combined this with single-cell RNA sequencing and a scalable and reproducible bioinformatics pipeline. To assess the disease specificity of the immune landscape, we also obtained single-cell data from other B-NHL including MZL and CLL (n=60 patients). Results: Our data indicate profound changes in the immune landscape, in particular in the T cell compartment of MCL patients. In this regard, multi-omics factor analysis (MOFA) confirmed a highly distinct T cell landscape in MCL patients, characterized by higher effector marker expression in conventional CD4+ and CD8+ T cells in addition to higher fraction of effector and effector memory T cells compared to healthy donors (Fig. 1A and B). Moreover, our analysis revealed a pronounced expansion of highly suppressive regulatory T cells (~5% of T cells) (Fig.1B). The emergence of this effector Treg (eTreg) subset in MCL patients might limit efficient anti-tumor immunity of CD8+ and conventional CD4+ T cells. Consistent with this, we observed a high fraction of several dysfunctional CD8+ T cells subsets. Notably, we found a remodeling of this eTreg subset in patients undergoing ibrutinib treatment leading to a less pronounced suppressive phenotype and concomitantly observed an increase of proteins crucial for cytotoxic function such as Granzyme B and Interferon-γ in effector T cells. We further sought to link tumor cell signatures with the healthy immune cell signatures in order to assess potential interactions and mechanisms of immune escape. As such, the tumor cell compartment (MCL cells) displayed high-expression of inhibitory immune checkpoint ligands such as PVR, HLA-G, CD70 and PD-L1 and antiphagocytic proteins such as CD47 and CD24, which may contribute to the dysfunctional T cell compartment. In line with this, our analysis revealed that high expression of the immune checkpoint ligand CD70 on malignant B cells was inversely associated with an activation module in CD4+ T cells, providing a potential axis contributing to immune escape, which may be leveraged for future therapeutic use. Finally, we identified tumor and immune cell signatures associated with in vitro drug response that may not only be useful for improving treatment selection, but also offer novel biological insights into potential mechanisms of treatment resistance. Conclusion: This study provides valuable insights into the single-cell landscape of leukemic MCL, offering crucial understanding of how tumor-immune cell interactions may contribute to disease progression and treatment resistance. The findings hold potential for therapeutic exploitation to eventually improve patient outcomes in Mantle Cell Lymphoma.

Acute myeloid leukaemia (AML) relapse after allogeneic haematopoietic cell transplantation (allo-HCT) is often driven by immune-related mechanisms and associated with poor prognosis. Immune checkpoint inhibitors combined with hypomethylating agents (HMA) may restore or enhance the graft-versus-leukaemia effect. Still, data about using this combination regimen after allo-HCT are limited. We conducted a prospective, phase II, open-label, single-arm study in which we treated patients with haematological AML relapse after allo-HCT with HMA plus the anti-PD-1 antibody nivolumab. The response was correlated with DNA-, RNA- and protein-based single-cell technology assessments to identify biomarkers associated with therapeutic efficacy. Sixteen patients received a median number of 2 (range 1-7) nivolumab applications. The overall response rate (CR/PR) at day 42 was 25%, and another 25% of the patients achieved stable disease. The median overall survival was 15.6 months. High-parametric cytometry documented a higher frequency of activated (ICOS+, HLA-DR+), low senescence (KLRG1(-), CD57(-)) CD8(+) effector T cells in responders. We confirmed these findings in a preclinical model. Single-cell transcriptomics revealed a pro-inflammatory rewiring of the expression profile of T and myeloid cells in responders. In summary, the study indicates that the post-allo-HCT HMA/nivolumab combination induces anti-AML immune responses in selected patients and could be considered as a bridging approach to a second allo-HCT.Trial-registration: EudraCT-No. 2017-002194-18.

The range of vaccines developed against severe acute respiratory syndrome coronavirus 2 (SARS‑CoV‑2) provides a unique opportunity to study immunization across different platforms. In a single-center cohort, we analyzed the humoral and cellular immune compartments following five coronavirus disease 2019 (COVID-19) vaccines spanning three technologies (adenoviral, mRNA and inactivated virus) administered in 16 combinations. For adenoviral and inactivated-virus vaccines, heterologous combinations were generally more immunogenic compared to homologous regimens. The mRNA vaccine as the second dose resulted in the strongest antibody response and induced the highest frequency of spike-binding memory B cells irrespective of the priming vaccine. Priming with the inactivated-virus vaccine increased the SARS-CoV-2-specific T cell response, whereas boosting did not. Distinct immune signatures were elicited by the different vaccine combinations, demonstrating that the immune response is shaped by the type of vaccines applied and the order in which they are delivered. These data provide a framework for improving future vaccine strategies against pathogens and cancer.

CD19-redirected chimeric antigen receptor T (CAR T) cells represent a breakthrough immunotherapy for B cell malignancies

Introduction: The inhibition of Bruton's tyrosine kinase (BTK) as a therapeutic strategy has dramatically improved the management of patients with chronic lymphocytic leukemia (CLL) and other B-cell-Non Hodgkin lymphomas (B-NHL). However, therapy resistance and treatment toxicity persist as significant clinical challenges. It has been previously reported that BTK inhibition not only targets the overactivated BCR pathway in CLL and other B-NHL, but also coincides with profound alterations in the tumor microenvironment including immune cells. Therefore, it is vital to understand these tumor-immune cell interactions during BTK inhibition to enhance response and reduce toxicity, advancing personalized care for CLL and B-NHL patients in the future. Methods: We developed a high-parametric analysis pipeline based on full spectrum cytometry, a novel technology allowing for the simultaneous assessment of 40 markers at single-cell level. In order to comprehensively assess the phosphoproteome relevant to BTK inhibition we established a signaling panel covering >30 proteins including pBTK, pSyk, pPLCg, pS6 and pAMPKa. Additionally, we designed 3 panels with up to 40 markers characterizing T cell activation and exhaustion, cellular trafficking, inhibitory immune checkpoints and cytokine production. Using our scalable and reproducible bioinformatics pipeline, we analyzed a cohort of 160 samples, longitudinally collected from 57 patients (CLL, MCL, MZL) before BTKi treatment, directly after treatment initiation, at leukocyte peak count and during therapy up to 6 months after therapy initiation. Results: Given that T cells are a crucial arm in governing anti-lymphoma immune response, we sought to elucidate the changes associated with BTK inhibition in the T cell compartment of the patients at high resolution (figure A). We observed certain changes in the fraction of T cell subtypes, notably a decrease in central memory stem T cells and an increase in γδ T cells at leukocyte peak and during later stages of therapy. Our analysis uncovered substantial changes in the T cell marker expression over the course of BTK inhibition. This includes a reversal of exhausted phenotype marked by downregulation of PD1, CD39 and CD38 and a skewed differentiation of CD4 T cells towards Th1 phenotype illustrated by a pronounced upregulation of the transcription factor T-bet. In addition, we detected restored proliferative and cytotoxic capacity in the CD8 and CD4 T cell compartments characterized by upregulation of GRZB, CD226, CD28, CD25 and Ki67. By leveraging our platform, we successfully captured the signalosome of malignant B cells at a high resolution. As anticipated, we detected significant heterogeneity in the malignant B cell signatures across individual patients. Interestingly, even at the initial sampling timepoint following treatment start, we observed substantially altered B cell signatures encompassing both the phosphoproteome and inhibitory immune checkpoints (figure B). Our preliminary data suggest that the dynamic changes induced by BTK inhibition extend beyond the signaling nodes associated with the BCR pathway and also involve the NFkB and p53 pathways. Conclusion: In this study, we established a platform for deep and longitudinal interrogation of the tumor and immune cell compartments to capture the dynamic and patient-specific changes occurring during BTK inhibition. Our preliminary data obtained from a large patient cohort of 57 B-NHL patients reveals a profound remodeling of not only the BCR signaling pathway in tumor cells, but also of the T cell compartment. Our data will be useful for a better understanding of treatment response and toxicity in the context of BTK inhibition.

Immune signatures predict development of autoimmune toxicity in immune checkpoint inhibitor-treated patients with cancer Nicolas Gonzalo Nuñez1*, Fiamma Berner2*, Ekaterina Friebel1*, Susanne Unger1, Nina Wyss2,3, Julia Martinez Gomez4, Mette-Triin Purde2, Rebekka Niederer2,3, Maximilian Porsch5, Christa Lichtensteiger2, Rafaela Kramer6, Michael Erdmann6, Christina Schmitt7, Lucy Heinzerling6,7, Marie-Therese Abdou2, Julia Karbach8, Dirk Schadendorf9, Lisa Zimmer9, Selma Ugurel9, Niklas Klümper10,11,12, Michael Hölzel10,11, Laura Power1, Stefanie Kreutmair1, Mariaelena Capone13, Gabriele Madonna13, Lacin Cevhertas14,15, Anja Heider14, Teresa Amaral16,17, Omar Hasan Ali2,3,4,18, David Bomze2,19, Florentia Dimitriou4, Stefan Diem20, Paolo Antonio Ascierto13, Reinhard Dummer4, Elke Jäger8, Christoph Driessen20, Mitchell P. Levesque4, Willem van de Veen14, Markus Joerger20, Martin Früh20,21, Burkhard Becher1**, Lukas Flatz2,3,4,20,22** */** these authors contributed equally Affiliations 1. Institute of Experimental Immunology, University of Zurich, Zurich, Switzerland 2. Institute of Immunobiology, Medical Research Center, Kantonsspital St. Gallen, St.Gallen, Switzerland 3. Department of Dermatology, Kantonsspital St. Gallen, St.Gallen, Switzerland 4. Department of Dermatology, University Hospital Zurich, Zurich, Switzerland 5. Department of Radiology, Kantonsspital St. Gallen, St.Gallen, Switzerland 6. Department of Dermatology, University of Erlangen-Nuremberg, Erlangen, Germany 7. Ludwig Maximilian University of Munich, Munich, Germany 8. Department of Oncology and Hematology, Krankenhaus Nordwest, Frankfurt, Germany 9. Department of Dermatology, Comprehensive Cancer Center (Westdeutsches Tumorzentrum) University Hospital Essen, Essen, Germany 10. Institute for Experimental Oncology, University Hospital Bonn, Bonn, Germany 11. Center for Integrated Oncology Cologne/Bonn, University Hospital Bonn, Bonn, Germany 12. Department of Urology, University Hospital Bonn, Bonn, Germany 13. Istituto Nazionale Tumori-IRCCS-Fondazione G. Pascale, Napoli, Italy 14. Swiss Institute of Allergy and Asthma Research (SIAF), University of Zurich, Davos, Switzerland 15. Department of Medical Immunology, Institute of Health Sciences, Bursa Uludag University, Bursa, Turkey 16. Skin Cancer Center, Department of Dermatology, University Hospital Tübingen, Tübingen, Germany 17. iFIT Cluster of Excellence (EXC 2180), University of Tübingen, Tübingen, Germany 18. Department of Medical Genetics, Life Sciences Institute, University of British Columbia, Vancouver, Canada 19. Sackler Faculty of Medicine, Tel-Aviv University, Israel 20. Department of Oncology, Kantonsspital St. Gallen, St.Gallen, Switzerland 21. Department of Medical Oncology, Inselspital, Bern University Hospital, University of Bern, Bern, Switzerland 22. Universitäts-Hautklinik, University of Tübingen, Tübingen, Germany

Background: Comorbidities are risk factors for development of severe coronavirus disease 2019 (COVID-19). However, the extent to which an underlying comorbidity influences the immune response to severe acute respiratory syndrome coronavirus 2 remains unknown.Objective: Our aim was to investigate the complex interrelations of comorbidities, the immune response, and patient outcome in COVID-19.Methods: We used high-throughput, high-dimensional, single -cell mapping of peripheral blood leukocytes and algorithm -guided analysis.Results: We discovered characteristic immune signatures associated not only with severe COVID-19 but also with the underlying medical condition. Different factors of the metabolic syndrome (obesity, hypertension, and diabetes) affected distinct immune populations, thereby additively increasing the immunodysregulatory effect when present in a single patient. Patients with disorders affecting the lung or heart, together with factors of metabolic syndrome, were clustered together, whereas immune disorder and chronic kidney disease displayed a distinct immune profile in COVID-19. In particular, severe acute respiratory syndrome coronavirus 2-infected patients with preexisting chronic kidney disease were characterized by the highest number of altered immune signatures of both lymphoid and myeloid immune branches. This overall major immune dysregulation could be the underlying mechanism for the estimated odds ratio of 16.3 for development of severe COVID-19 in this burdened cohort.Conclusion: The combinatorial systematic analysis of the immune signatures, comorbidities, and outcomes of patients with COVID-19 has provided the mechanistic immunologic underpinnings of comorbidity-driven patient risk and uncovered comorbidity-driven immune signatures. (J Allergy Clin Immunol 2022;150:312-24.)

Common variable immunodeficiency (CVID) is the most frequent symptomatic primary immunodeficiency, with heterogeneous clinical presentation. Our goal was to analyze CD8 T cell homeostasis in patients with infection only CVID, compared to those additionally affected by dysregulatory and autoimmune phenomena. We used flow and mass cytometry evaluation of peripheral blood of 40 patients with CVID and 17 healthy donors. CD8 T cells are skewed in patients with CVID, with loss of naïve and increase of effector memory stages, expansion of cell clusters with high functional exhaustion scores, and a highly activated population of cells with immunoregulatory features, producing IL-10. These findings correlate to clinically widely used B cell-based EURO classification. Features of exhaustion, including loss of CD127 and CD28, and expression of TIGIT and PD-1 in CD8 T cells are strongly associated with interstitial lung disease and autoimmune cytopenias, whereas CD8 T cell activation with elevated HLA-DR and CD38 expression predict non-infectious diarrhea. We demonstrate features of advanced differentiation, exhaustion, activation, and immunoregulatory capabilities within CD8 T cells of CVID patients. Assessment of CD8 T cell phenotype may allow risk assessment of CVID patients and provide new insights into CVID pathogenesis, including a better understanding of mechanisms underlying T cell exhaustion and regulation.

We propose an auto-encoder (AE) trained on healthy bone marrow cells to classify cells in single-cell cytometry AML samples as malignant or healthy. We set a threshold on the mean-squared reconstruction error of marker expression for each cell; high error would lead to classification as malignant. Additionally, the latent space of the auto-encoder captures the developmental trajectory of the bone marrow and can be used to assign cell types to the single cells. Combining the classification and the cell type assignment we can predict the percentage of malignant cells and developmental stage for the majority of samples.