Cutaneous Manifestations of Myeloid Neoplasms Exhibit Broad and Divergent Morphologic and Immunophenotypic Features but Share Ancestral Clonal Mutations With Bone Marrow.

In this study, we performed a comprehensive molecular analysis of paired skin and peripheral blood/bone marrow (BM) samples from 17 patients with cutaneous myeloid or cutaneous histiocytic-dendritic neoplasms. The cutaneous manifestations included 10 patients with cutaneous acute myeloid leukemia (c-AML), 2 patients with full or partial Langerhans cell differentiation, 2 patients with blastic plasmacytoid dendritic cell neoplasms (BPDCN), 1 patient with both Langerhans cell differentiation and BPDCN, and 2 patients with full or partial indeterminate dendritic cell differentiation. Seven of the 10 c-AML patients (70%) exhibited concurrent or subsequent marrow involvement by acute myeloid leukemia, with all 7 cases (100%) demonstrating shared clonal mutations in both the skin and BM. However, clonal relatedness was documented in one additional case that never had any BM involvement. Nevertheless, NPM1 mutations were identified in 7 of the 10 (70%) of these c-AML cases while one had KMT2A rearrangement and one showed inv(16). All 3 patients (100%) with Langerhans cell neoplasms, 2 patients with BPDCN (100%), and one of the 2 patients (50%) with other cutaneous dendritic cell neoplasms also demonstrated shared mutations between the skin and concurrent or subsequent myeloid neoplasms. Both BM and c-AML shared identical founding drivers, with a predominance of NPM1, DNMT3A, and translocations associated with monocytic differentiation, with common cutaneous-only mutations involving genes in the signal transduction and epigenetic pathways. Cutaneous histiocytic-dendritic neoplasms shared founding drivers in ASXL1, TET2, and/or SRSF2. However, in the Langerhans cell histiocytosis or histiocytic sarcoma cases, there exist recurrent secondary RAS pathway hits, whereas cutaneous BPDCN cases exhibit copy number or structural variants. These results enrich and broaden our understanding of clonally related cutaneous manifestations of myeloid neoplasms and further illuminate the highly diverse spectrum of morphologic and immunophenotypic features they exhibit.

PD-1 Mediated Regulation of Unique Activated CD8 + T Cells by NK Cells in the Submandibular Gland.

The increasing utilization of anti-PD-1 immune checkpoint blockade (ICB) has led to the emergence of immune-related adverse events (irAEs), including sicca syndrome. Interestingly, we found that the submandibular gland (SMG) of PD-1 deficient mice harbors a large population of CD8 + T cells, reminiscing ICB induced sicca. This phenotype was also observed in the SMG of both NK cell-depleted C57BL/6 animals and NK cell-deficient animals. Mechanistically, using mice conditionally deficient for PD-L1 in the NK cell lineage, we discovered that NK cells regulate CD8 + T cell homeostasis via the PD-1/PD-L1 axis in this organ. Importantly, single-cell RNA sequencing of PD-1 deficient SMG CD8 + T cells reveals a unique transcriptional profile consistent with TCR activation. These cells have limited TCR diversity and phenotypically overlap with GzmK + CD8 + T autoimmune cells identified in primary Sjögren's syndrome patients. These insights into NK cell immunoregulation in the SMG, and the consequences of disrupted CD8 + T cell homeostasis, provide opportunities for preventing the development of irAEs. Highlights: Elevated CD8 + T cells in the submandibular gland (SMG) of PD-1 deficient mice parallel sicca-like irAEs seen in ICB patients. In addition to their previously described hyporesponsive phenotype, NK cells in the SMG regulate CD8 + T cell homeostasis through the PD-L1/PD-1 axis. PD-1 deficient SMG CD8 + T cells display unique transcriptional profiles associated with proinflammatory functions, TCR activation, interferon stimulation, and exhaustion. Oligoclonal expansion and similarities in TCR sequences indicate T cell activation and a preference for recognizing specific antigens.

Analysis of the Effectiveness of the Ad26.COV2.S Adenoviral Vector Vaccine for Preventing COVID-19.

Importance: Continuous assessment of the effectiveness and safety of the US Food and Drug Administration-authorized SARS-CoV-2 vaccines is critical to amplify transparency, build public trust, and ultimately improve overall health outcomes. Objective: To evaluate the effectiveness of the Johnson & Johnson Ad26.COV2.S vaccine for preventing SARS-CoV-2 infection. Design, Setting, and Participants: This comparative effectiveness research study used large-scale longitudinal curation of electronic health records from the multistate Mayo Clinic Health System (Minnesota, Arizona, Florida, Wisconsin, and Iowa) to identify vaccinated and unvaccinated adults between February 27 and July 22, 2021. The unvaccinated cohort was matched on a propensity score derived from age, sex, zip code, race, ethnicity, and previous number of SARS-CoV-2 polymerase chain reaction tests. The final study cohort consisted of 8889 patients in the vaccinated group and 88 898 unvaccinated matched patients. Exposure: Single dose of the Ad26.COV2.S vaccine. Main Outcomes and Measures: The incidence rate ratio of SARS-CoV-2 infection in the vaccinated vs unvaccinated control cohorts, measured by SARS-CoV-2 polymerase chain reaction testing. Results: The study was composed of 8889 vaccinated patients (4491 men [50.5%]; mean [SD] age, 52.4 [16.9] years) and 88 898 unvaccinated patients (44 748 men [50.3%]; mean [SD] age, 51.7 [16.7] years). The incidence rate ratio of SARS-CoV-2 infection in the vaccinated vs unvaccinated control cohorts was 0.26 (95% CI, 0.20-0.34) (60 of 8889 vaccinated patients vs 2236 of 88 898 unvaccinated individuals), which corresponds to an effectiveness of 73.6% (95% CI, 65.9%-79.9%) and a 3.73-fold reduction in SARS-CoV-2 infections. Conclusions and Relevance: This study's findings are consistent with the clinical trial-reported efficacy of Ad26.COV2.S and the first retrospective analysis, suggesting that the vaccine is effective at reducing SARS-CoV-2 infection, even with the spread of variants such as Alpha or Delta that were not present in the original studies, and reaffirm the urgent need to continue mass vaccination efforts globally.

NLRP3 Inflammasome Mediates Immune-Stromal Interactions in Vasculitis.

[Figure: see text].

Autophagy-mitophagy induction attenuates cardiovascular inflammation in a murine model of Kawasaki disease vasculitis.

Kawasaki disease (KD) is the leading cause of acquired heart disease among children. Murine and human data suggest that the NLRP3-IL-1ß pathway is the main driver of KD pathophysiology. NLRP3 can be activated during defective autophagy/mitophagy. We used the Lactobacillus casei cell wall extract (LCWE) murine model of KD vasculitis to examine the role of autophagy/mitophagy on cardiovascular lesion development. LCWE-injected mice had impaired autophagy/mitophagy and increased levels of ROS in cardiovascular lesions, together with increased systemic 8-OHdG release. Enhanced autophagic flux significantly reduced cardiovascular lesions in LCWE-injected mice, whereas autophagy blockade increased inflammation. Vascular smooth muscle cell-specific deletion of Atg16l1 and global Parkin-/- significantly increased disease formation, supporting the importance of autophagy/mitophagy in this model. Ogg1-/- mice had significantly increased lesions with increased NLRP3 activity, whereas treatment with MitoQ reduced vascular tissue inflammation, ROS production, and systemic 8-OHdG release. Treatment with MN58b or Metformin (increasing AMPK and reducing ROS) resulted in decreased cardiovascular lesions. Our results demonstrate that impaired autophagy/mitophagy and ROS-dependent damage exacerbate the development of murine KD vasculitis. This pathway can be efficiently targeted to reduce disease severity. These findings enhance our understanding of KD pathogenesis and identify potentially novel therapeutic avenues for KD treatment.

A Literature-Derived Knowledge Graph Augments the Interpretation of Single Cell RNA-seq Datasets.

Technology to generate single cell RNA-sequencing (scRNA-seq) datasets and tools to annotate them have advanced rapidly in the past several years. Such tools generally rely on existing transcriptomic datasets or curated databases of cell type defining genes, while the application of scalable natural language processing (NLP) methods to enhance analysis workflows has not been adequately explored. Here we deployed an NLP framework to objectively quantify associations between a comprehensive set of over 20,000 human protein-coding genes and over 500 cell type terms across over 26 million biomedical documents. The resultant gene-cell type associations (GCAs) are significantly stronger between a curated set of matched cell type-marker pairs than the complementary set of mismatched pairs (Mann Whitney p = 6.15 × 10-76, r = 0.24; cohen's D = 2.6). Building on this, we developed an augmented annotation algorithm (single cell Annotation via Literature Encoding, or scALE) that leverages GCAs to categorize cell clusters identified in scRNA-seq datasets, and we tested its ability to predict the cellular identity of 133 clusters from nine datasets of human breast, colon, heart, joint, ovary, prostate, skin, and small intestine tissues. With the optimized settings, the true cellular identity matched the top prediction in 59% of tested clusters and was present among the top five predictions for 91% of clusters. scALE slightly outperformed an existing method for reference data driven automated cluster annotation, and we demonstrate that integration of scALE can meaningfully improve the annotations derived from such methods. Further, contextualization of differential expression analyses with these GCAs highlights poorly characterized markers of well-studied cell types, such as CLIC6 and DNASE1L3 in retinal pigment epithelial cells and endothelial cells, respectively. Taken together, this study illustrates for the first time how the systematic application of a literature-derived knowledge graph can expedite and enhance the annotation and interpretation of scRNA-seq data.

Mapping each pre-existing condition's association to short-term and long-term COVID-19 complications.

Understanding the relationships between pre-existing conditions and complications of COVID-19 infection is critical to identifying which patients will develop severe disease. Here, we leverage ~1.1 million clinical notes from 1803 hospitalized COVID-19 patients and deep neural network models to characterize associations between 21 pre-existing conditions and the development of 20 complications (e.g. respiratory, cardiovascular, renal, and hematologic) of COVID-19 infection throughout the course of infection (i.e. 0-30 days, 31-60 days, and 61-90 days). Pleural effusion was the most frequent complication of early COVID-19 infection (89/1803 patients, 4.9%) followed by cardiac arrhythmia (45/1803 patients, 2.5%). Notably, hypertension was the most significant risk factor associated with 10 different complications including acute respiratory distress syndrome, cardiac arrhythmia, and anemia. The onset of new complications after 30 days is rare and most commonly involves pleural effusion (31-60 days: 11 patients, 61-90 days: 9 patients). Lastly, comparing the rates of complications with a propensity-matched COVID-negative hospitalized population confirmed the importance of hypertension as a risk factor for early-onset complications. Overall, the associations between pre-COVID conditions and COVID-associated complications presented here may form the basis for the development of risk assessment scores to guide clinical care pathways.

Single-cell analysis of FOXP3 deficiencies in humans and mice unmasks intrinsic and extrinsic CD4+ T cell perturbations.

FOXP3 deficiency in mice and in patients with immune dysregulation polyendocrinopathy enteropathy X-linked (IPEX) syndrome results in fatal autoimmunity by altering regulatory T (Treg) cells. CD4+ T cells in patients with IPEX syndrome and Foxp3-deficient mice were analyzed by single-cell cytometry and RNA-sequencing, revealing heterogeneous Treg-like cells, some very similar to normal Treg cells, others more distant. Conventional T cells showed no widespread activation or helper T cell bias, but a monomorphic disease signature affected all CD4+ T cells. This signature proved to be cell extrinsic since it was extinguished in mixed bone marrow chimeric mice and heterozygous mothers of patients with IPEX syndrome. Normal Treg cells exerted dominant suppression, quenching the disease signature and revealing in mutant Treg-like cells a small cluster of genes regulated cell-intrinsically by FOXP3, including key homeostatic regulators. We propose a two-step pathogenesis model: cell-intrinsic downregulation of core FOXP3-dependent genes destabilizes Treg cells, de-repressing systemic mediators that imprint the disease signature on all T cells, furthering Treg cell dysfunction. Accordingly, interleukin-2 treatment improved the Treg-like compartment and survival.

Knowledge synthesis of 100 million biomedical documents augments the deep expression profiling of coronavirus receptors.

The COVID-19 pandemic demands assimilation of all biomedical knowledge to decode mechanisms of pathogenesis. Despite the recent renaissance in neural networks, a platform for the real-time synthesis of the exponentially growing biomedical literature and deep omics insights is unavailable. Here, we present the nferX platform for dynamic inference from over 45 quadrillion possible conceptual associations from unstructured text, and triangulation with insights from single-cell RNA-sequencing, bulk RNA-seq and proteomics from diverse tissue types. A hypothesis-free profiling of ACE2 suggests tongue keratinocytes, olfactory epithelial cells, airway club cells and respiratory ciliated cells as potential reservoirs of the SARS-CoV-2 receptor. We find the gut as the putative hotspot of COVID-19, where a maturation correlated transcriptional signature is shared in small intestine enterocytes among coronavirus receptors (ACE2, DPP4, ANPEP). A holistic data science platform triangulating insights from structured and unstructured data holds potential for accelerating the generation of impactful biological insights and hypotheses.

CD4+ teff cell heterogeneity: the perspective from single-cell transcriptomics.

Single-cell transcriptomics (scRNAseq) holds the promise to generate definitive atlases of cell types. We review scRNAseq studies of conventional CD4+ αß T cells performed in a variety of challenged contexts (infection, tumor, allergy) that aimed to parse the complexity and representativity of previously defined CD4+ T cell types, lineages, and cosmologies. With a few years' experience, the field has realized the difficulties and pitfalls of scRNAseq. With the very high-dimensionality of scRNAseq data, subset definitions based on low-dimensionality marker combinations tend to fade or blur: cell types prove more complex than expected; transcripts of key defining transcripts (cytokines, chemokines) are distributed as broad and partially overlapping continua; boundaries with innate lymphocytes are blurred. Tissue location and activation, either cytokine-driven or TCR-driven, determine Teff heterogeneity in sometimes unexpected ways. Emerging techniques for lineage and trajectory tracing, and RNA-protein connections, will further help define the space of differentiated CD4+ T cell heterogeneity.

Neuronal, stromal, and T-regulatory cell crosstalk in murine skeletal muscle.

A distinct population of Foxp3+CD4+ regulatory T (Treg) cells promotes repair of acutely or chronically injured skeletal muscle. The accumulation of these cells depends critically on interleukin (IL)-33 produced by local mesenchymal stromal cells (mSCs). An intriguing physical association among muscle nerves, IL-33+ mSCs, and Tregs has been reported, and invites a deeper exploration of this cell triumvirate. Here we evidence a striking proximity between IL-33+ muscle mSCs and both large-fiber nerve bundles and small-fiber sensory neurons; report that muscle mSCs transcribe an array of genes encoding neuropeptides, neuropeptide receptors, and other nerve-related proteins; define muscle mSC subtypes that express both IL-33 and the receptor for the calcitonin-gene-related peptide (CGRP); and demonstrate that up- or down-tuning of CGRP signals augments or diminishes, respectively, IL-33 production by muscle mSCs and later accumulation of muscle Tregs. Indeed, a single injection of CGRP induced much of the genetic program elicited in mSCs early after acute skeletal muscle injury. These findings highlight neural/stromal/immune-cell crosstalk in tissue repair, suggesting future therapeutic approaches.

Distinct immunocyte-promoting and adipocyte-generating stromal components coordinate adipose tissue immune and metabolic tenors.

Regulatory T cells (Tregs) are key brakes on the visceral adipose tissue (VAT) inflammation that regulates local and systemic metabolic tenor. Breakdown of this regulation promotes type 2 diabetes. The cytokine IL-33 expands and sustains the unique Treg population residing within VAT. Here, relying on single-cell RNA sequencing, we identified the major IL-33 producers in VAT to be particular mesenchymal stromal cell subtypes, related to but distinct from adipocyte progenitor cells. We explored modulation of the VAT stromal cell landscape with physiologic variables such as age and sex, as well as its remodeling in pathogenic states like obesity. Last, we uncovered a VAT Treg:stromal cell negative regulatory loop that keeps the potent effect of IL-33 under rein.

Single-Cell Transcriptomics of Human and Mouse Lung Cancers Reveals Conserved Myeloid Populations across Individuals and Species.

Tumor-infiltrating myeloid cells (TIMs) comprise monocytes, macrophages, dendritic cells, and neutrophils, and have emerged as key regulators of cancer growth. These cells can diversify into a spectrum of states, which might promote or limit tumor outgrowth but remain poorly understood. Here, we used single-cell RNA sequencing (scRNA-seq) to map TIMs in non-small-cell lung cancer patients. We uncovered 25 TIM states, most of which were reproducibly found across patients. To facilitate translational research of these populations, we also profiled TIMs in mice. In comparing TIMs across species, we identified a near-complete congruence of population structures among dendritic cells and monocytes; conserved neutrophil subsets; and species differences among macrophages. By contrast, myeloid cell population structures in patients' blood showed limited overlap with those of TIMs. This study determines the lung TIM landscape and sets the stage for future investigations into the potential of TIMs as immunotherapy targets.

Molecular diversification of regulatory T cells in nonlymphoid tissues.

Foxp3+CD4+ regulatory T cells (Tregs) accumulate in certain nonlymphoid tissues, where they control diverse aspects of organ homeostasis. Populations of tissue Tregs, as they have been termed, have transcriptomes distinct from those of their counterparts in lymphoid organs and other nonlymphoid tissues. We examined the diversification of Tregs in visceral adipose tissue, skeletal muscle, and the colon vis-à-vis lymphoid organs from the same individuals. The unique transcriptomes of the various tissue Treg populations resulted from layering of tissue-restricted open chromatin regions over regions already open in the spleen, the latter tagged by super-enhancers and particular histone marks. The binding motifs for a small number of transcription factor (TF) families were repeatedly enriched within the accessible chromatin stretches of Tregs in the three nonlymphoid tissues. However, a bioinformatically and experimentally validated transcriptional network, constructed by integrating chromatin accessibility and single-cell transcriptomic data, predicted reliance on different TF family members in the different tissues. The network analysis also revealed that tissue-restricted and broadly acting TFs were integrated into feed-forward loops to enforce tissue-specific gene expression in nonlymphoid-tissue Tregs. Overall, this study provides a framework for understanding the epigenetic dynamics of T cells operating in nonlymphoid tissues, which should inform strategies for specifically targeting them.

TCR Transgenic Mice Reveal Stepwise, Multi-site Acquisition of the Distinctive Fat-Treg Phenotype.

Visceral adipose tissue (VAT) hosts a population of regulatory T (Treg) cells, with a unique phenotype, that controls local and systemic inflammation and metabolism. Generation of a T cell receptor transgenic mouse line, wherein VAT Tregs are highly enriched, facilitated study of their provenance, dependencies, and activities. We definitively established a role for T cell receptor specificity, uncovered an unexpected function for the primordial Treg transcription-factor, Foxp3, evidenced a cell-intrinsic role for interleukin-33 receptor, and ordered these dependencies within a coherent scenario. Genesis of the VAT-Treg phenotype entailed a priming step in the spleen, permitting them to exit the lymphoid organs and surveil nonlymphoid tissues, and a final diversification process within VAT, in response to microenvironmental cues. Understanding the principles of tissue-Treg biology is a prerequisite for precision-targeting strategies.

Publisher Correction: Single-cell gene expression reveals a landscape of regulatory T cell phenotypes shaped by the TCR.

In the version of this article initially published, the Supplementary Note was missing. The Supplementary Note has now been provided online and is cited in the Methods section of the article. The error has been corrected in the HTML and PDF version of the article.

Single-cell gene expression reveals a landscape of regulatory T cell phenotypes shaped by the TCR.

CD4+ T regulatory cells (Treg) are central to immune homeostasis, their phenotypic heterogeneity reflecting the diverse environments and target cells that they regulate. To understand this heterogeneity, we combined single-cell RNA-seq, activation reporter and T cell receptor (TCR) analysis to profile thousands of Treg or conventional CD4+FoxP3- T cells (Tconv) from mouse lymphoid organs and human blood. Treg and Tconv pools showed areas of overlap, as resting 'furtive' Tregs with overall similarity to Tconvs or as a convergence of activated states. All Tregs expressed a small core of FoxP3-dependent transcripts, onto which additional programs were added less uniformly. Among suppressive functions, Il2ra and Ctla4 were quasiconstant, inhibitory cytokines being more sparsely distributed. TCR signal intensity did not affect resting/activated Treg proportions but molded activated Treg programs. The main lines of Treg heterogeneity in mice were strikingly conserved in human blood. These results reveal unexpected TCR-shaped states of activation, providing a framework to synthesize previous observations of Treg heterogeneity.

Osteoblasts remotely supply lung tumors with cancer-promoting SiglecFhigh neutrophils.

Bone marrow-derived myeloid cells can accumulate within tumors and foster cancer outgrowth. Local immune-neoplastic interactions have been intensively investigated, but the contribution of the systemic host environment to tumor growth remains poorly understood. Here, we show in mice and cancer patients (n = 70) that lung adenocarcinomas increase bone stromal activity in the absence of bone metastasis. Animal studies reveal that the cancer-induced bone phenotype involves bone-resident osteocalcin-expressing (Ocn+) osteoblastic cells. These cells promote cancer by remotely supplying a distinct subset of tumor-infiltrating SiglecFhigh neutrophils, which exhibit cancer-promoting properties. Experimentally reducing Ocn+ cell numbers suppresses the neutrophil response and lung tumor outgrowth. These observations posit osteoblasts as remote regulators of lung cancer and identify SiglecFhigh neutrophils as myeloid cell effectors of the osteoblast-driven protumoral response.