Complement activation induces excessive T cell cytotoxicity in severe COVID-19.

Severe COVID-19 is linked to both dysfunctional immune response and unrestrained immunopathology, and it remains unclear whether T cells contribute to disease pathology. Here, we combined single-cell transcriptomics and single-cell proteomics with mechanistic studies to assess pathogenic T cell functions and inducing signals. We identified highly activated CD16+ T cells with increased cytotoxic functions in severe COVID-19. CD16 expression enabled immune-complex-mediated, T cell receptor-independent degranulation and cytotoxicity not found in other diseases. CD16+ T cells from COVID-19 patients promoted microvascular endothelial cell injury and release of neutrophil and monocyte chemoattractants. CD16+ T cell clones persisted beyond acute disease maintaining their cytotoxic phenotype. Increased generation of C3a in severe COVID-19 induced activated CD16+ cytotoxic T cells. Proportions of activated CD16+ T cells and plasma levels of complement proteins upstream of C3a were associated with fatal outcome of COVID-19, supporting a pathological role of exacerbated cytotoxicity and complement activation in COVID-19.

Protein Synthesis in the Developing Neocortex at Near-Atomic Resolution Reveals Ebp1-Mediated Neuronal Proteostasis at the 60S Tunnel Exit.

Protein synthesis must be finely tuned in the developing nervous system as the final essential step of gene expression. This study investigates the architecture of ribosomes from the neocortex during neurogenesis, revealing Ebp1 as a high-occupancy 60S peptide tunnel exit (TE) factor during protein synthesis at near-atomic resolution by cryoelectron microscopy (cryo-EM). Ribosome profiling demonstrated Ebp1-60S binding is highest during start codon initiation and N-terminal peptide elongation, regulating ribosome occupancy of these codons. Membrane-targeting domains emerging from the 60S tunnel, which recruit SRP/Sec61 to the shared binding site, displace Ebp1. Ebp1 is particularly abundant in the early-born neural stem cell (NSC) lineage and regulates neuronal morphology. Ebp1 especially impacts the synthesis of membrane-targeted cell adhesion molecules (CAMs), measured by pulsed stable isotope labeling by amino acids in cell culture (pSILAC)/bioorthogonal noncanonical amino acid tagging (BONCAT) mass spectrometry (MS). Therefore, Ebp1 is a central component of protein synthesis, and the ribosome TE is a focal point of gene expression control in the molecular specification of neuronal morphology during development.

Non-redundant functions of group 2 innate lymphoid cells.

Protective immunity relies on the interplay of innate and adaptive immune cells with complementary and redundant functions. Innate lymphoid cells (ILCs) have recently emerged as tissue-resident, innate mirror images of the T cell system, with which they share lineage-specifying transcription factors and effector machinery1. Located at barrier surfaces, ILCs are among the first responders against invading pathogens and thus could potentially determine the outcome of the immune response2. However, so far it has not been possible to dissect the unique contributions of ILCs to protective immunity owing to limitations in specific targeting of ILC subsets. Thus, all of the available data have been generated either in mice lacking the adaptive immune system or with tools that also affect other immune cell subsets. In addition, it has been proposed that ILCs might be dispensable for a proper immune response because other immune cells could compensate for their absence3-7. Here we report the generation of a mouse model based on the neuromedin U receptor 1 (Nmur1) promoter as a driver for simultaneous expression of Cre recombinase and green fluorescent protein, which enables gene targeting in group 2 ILCs (ILC2s) without affecting other innate and adaptive immune cells. Using Cre-mediated gene deletion of Id2 and Gata3 in Nmur1-expressing cells, we generated mice with a selective and specific deficiency in ILC2s. ILC2-deficient mice have decreased eosinophil counts at steady state and are unable to recruit eosinophils to the airways in models of allergic asthma. Further, ILC2-deficient mice do not mount an appropriate immune and epithelial type 2 response, resulting in a profound defect in worm expulsion and a non-protective type 3 immune response. In total, our data establish non-redundant functions for ILC2s in the presence of adaptive immune cells at steady state and during disease and argue for a multilayered organization of the immune system on the basis of a spatiotemporal division of labour.

IL-33 controls IL-22-dependent antibacterial defense by modulating the microbiota.

IL-22 plays a critical role in defending against mucosal infections, but how IL-22 production is regulated is incompletely understood. Here, we show that mice lacking IL-33 or its receptor ST2 (IL-1RL1) were more resistant to Streptococcus pneumoniae lung infection than wild-type animals and that single-nucleotide polymorphisms in IL33 and IL1RL1 were associated with pneumococcal pneumonia in humans. The effect of IL-33 on S. pneumoniae infection was mediated by negative regulation of IL-22 production in innate lymphoid cells (ILCs) but independent of ILC2s as well as IL-4 and IL-13 signaling. Moreover, IL-33's influence on IL-22-dependent antibacterial defense was dependent on housing conditions of the mice and mediated by IL-33's modulatory effect on the gut microbiota. Collectively, we provide insight into the bidirectional crosstalk between the innate immune system and the microbiota. We conclude that both genetic and environmental factors influence the gut microbiota, thereby impacting the efficacy of antibacterial immune defense and susceptibility to pneumonia.

REEV: review, evaluate and explain variants.

In the era of high throughput sequencing, special software is required for the clinical evaluation of genetic variants. We developed REEV (Review, Evaluate and Explain Variants), a user-friendly platform for clinicians and researchers in the field of rare disease genetics. Supporting data was aggregated from public data sources. We compared REEV with seven other tools for clinical variant evaluation. REEV (semi-)automatically fills individual ACMG criteria facilitating variant interpretation. REEV can store disease and phenotype data related to a case to use these for phenotype similarity measures. Users can create public permanent links for individual variants that can be saved as browser bookmarks and shared. REEV may help in the fast diagnostic assessment of genetic variants in a clinical as well as in a research context. REEV (https://reev.bihealth.org/) is free and open to all users and there is no login requirement.

Mouse models of human multiple myeloma subgroups.

Multiple myeloma (MM), a tumor of germinal center (GC)-experienced plasma cells, comprises distinct genetic subgroups, such as the t(11;14)/CCND1 and the t(4;14)/MMSET subtype. We have generated genetically defined, subgroup-specific MM models by the GC B cell-specific coactivation of mouse Ccnd1 or MMSET with a constitutively active Ikk2 mutant, mimicking the secondary NF-κB activation frequently seen in human MM. Ccnd1/Ikk2ca and MMSET/Ikk2ca mice developed a pronounced, clonally restricted plasma cell outgrowth with age, accompanied by serum M spikes, bone marrow insufficiency, and bone lesions. The transgenic plasma cells could be propagated in vivo and showed distinct transcriptional profiles, resembling their human MM counterparts. Thus, we show that targeting the expression of genes involved in MM subgroup-specific chromosomal translocations into mouse GC B cells translates into distinct MM-like diseases that recapitulate key features of the human tumors, opening the way to a better understanding of the pathogenesis and therapeutic vulnerabilities of different MM subgroups.

Multimodal Profiling of Peripheral Blood Identifies Proliferating Circulating Effector CD4+ T Cells as Predictors for Response to Integrin α4ß7-Blocking Therapy in Inflammatory Bowel Disease.

BACKGROUND & AIMS: Despite the success of biological therapies in treating inflammatory bowel disease, managing patients remains challenging due to the absence of reliable predictors of therapy response. METHODS: In this study, we prospectively sampled 2 cohorts of patients with inflammatory bowel disease receiving the anti-integrin α4ß7 antibody vedolizumab. Samples were subjected to mass cytometry; single-cell RNA sequencing; single-cell variable, diversity, and joining sequencing; serum proteomics; and multidimensional flow cytometry to comprehensively assess vedolizumab-induced immunologic changes in the peripheral blood and their potential associations with treatment response. RESULTS: Vedolizumab treatment led to substantial alterations in the abundance of circulating immune cell lineages and modified the T-cell receptor diversity of gut-homing CD4+ memory T cells. Through integration of multimodal parameters and machine learning, we identified a significant increase in proliferating CD4+ memory T cells among nonresponders before treatment compared with responders. This predictive T-cell signature demonstrated an activated T-helper 1/T-helper 17 cell phenotype and exhibited elevated levels of integrin α4ß1, potentially making these cells less susceptible to direct targeting by vedolizumab. CONCLUSIONS: These findings provide a reliable predictive classifier with significant implications for personalized inflammatory bowel disease management.

Identifying cancer cells from calling single-nucleotide variants in scRNA-seq data.

MOTIVATION: Single-cell RNA sequencing (scRNA-seq) data are widely used to study cancer cell states and their heterogeneity. However, the tumour microenvironment is usually a mixture of healthy and cancerous cells and it can be difficult to fully separate these two populations based on transcriptomics alone. If available, somatic single-nucleotide variants (SNVs) observed in the scRNA-seq data could be used to identify the cancer population and match that information with the single cells' expression profile. However, calling somatic SNVs in scRNA-seq data is a challenging task, as most variants seen in the short-read data are not somatic, but can instead be germline variants, RNA edits or transcription, sequencing, or processing errors. In addition, only variants present in actively transcribed regions for each individual cell will be seen in the data. RESULTS: To address these challenges, we develop CCLONE (Cancer Cell Labelling On Noisy Expression), an interpretable tool adapted to handle the uncertainty and sparsity of SNVs called from scRNA-seq data. CCLONE jointly identifies cancer clonal populations, and their associated variants. We apply CCLONE on two acute myeloid leukaemia datasets and one lung adenocarcinoma dataset and show that CCLONE captures both genetic clones and somatic events for multiple patients. These results show how CCLONE can be used to gather insight into the course of the disease and the origin of cancer cells in scRNA-seq data. AVAILABILITY AND IMPLEMENTATION: Source code is available at github.com/HaghverdiLab/CCLONE.

Pharmacological inhibition of bromodomain and extra-terminal proteins induces an NRF-2-mediated antiviral state that is subverted by SARS-CoV-2 infection.

Inhibitors of bromodomain and extra-terminal proteins (iBETs), including JQ-1, have been suggested as potential prophylactics against SARS-CoV-2 infection. However, molecular mechanisms underlying JQ-1-mediated antiviral activity and its susceptibility to viral subversion remain incompletely understood. Pretreatment of cells with iBETs inhibited infection by SARS-CoV-2 variants and SARS-CoV, but not MERS-CoV. The antiviral activity manifested itself by reduced reporter expression of recombinant viruses, and reduced viral RNA quantities and infectious titers in the culture supernatant. While we confirmed JQ-1-mediated downregulation of expression of angiotensin-converting enzyme 2 (ACE2) and interferon-stimulated genes (ISGs), multi-omics analysis addressing the chromatin accessibility, transcriptome and proteome uncovered induction of an antiviral nuclear factor erythroid 2-related factor 2 (NRF-2)-mediated cytoprotective response as an additional mechanism through which JQ-1 inhibits SARS-CoV-2 replication. Pharmacological inhibition of NRF-2, and knockdown of NRF-2 and its target genes reduced JQ-1-mediated inhibition of SARS-CoV-2 replication. Serial passaging of SARS-CoV-2 in the presence of JQ-1 resulted in predominance of ORF6-deficient variant, which exhibited resistance to JQ-1 and increased sensitivity to exogenously administered type I interferon (IFN-I), suggesting a minimised need for SARS-CoV-2 ORF6-mediated repression of IFN signalling in the presence of JQ-1. Importantly, JQ-1 exhibited a transient antiviral activity when administered prophylactically in human airway bronchial epithelial cells (hBAECs), which was gradually subverted by SARS-CoV-2, and no antiviral activity when administered therapeutically following an established infection. We propose that JQ-1 exerts pleiotropic effects that collectively induce an antiviral state in the host, which is ultimately nullified by SARS-CoV-2 infection, raising questions about the clinical suitability of the iBETs in the context of COVID-19.

High-confidence calling of normal epithelial cells allows identification of a novel stem-like cell state in the colorectal cancer microenvironment.

Single-cell analyses can be confounded by assigning unrelated groups of cells to common developmental trajectories. For instance, cancer cells and admixed normal epithelial cells could adopt similar cell states thus complicating analyses of their developmental potential. Here, we develop and benchmark CCISM (for Cancer Cell Identification using Somatic Mutations) to exploit genomic single nucleotide variants for the disambiguation of cancer cells from genomically normal non-cancer cells in single-cell data. We find that our method and others based on gene expression or allelic imbalances identify overlapping sets of colorectal cancer versus normal colon epithelial cells, depending on molecular characteristics of individual cancers. Further, we define consensus cell identities of normal and cancer epithelial cells with higher transcriptome cluster homogeneity than those derived using existing tools. Using the consensus identities, we identify significant shifts of cell state distributions in genomically normal epithelial cells developing in the cancer microenvironment, with immature states increased at the expense of terminal differentiation throughout the colon, and a novel stem-like cell state arising in the left colon. Trajectory analyses show that the new cell state extends the pseudo-time range of normal colon stem-like cells in a cancer context. We identify cancer-associated fibroblasts as sources of WNT and BMP ligands potentially contributing to increased plasticity of stem cells in the cancer microenvironment. Our analyses advocate careful interpretation of cell heterogeneity and plasticity in the cancer context and the consideration of genomic information in addition to gene expression data when possible.

lncRNA CDKN2B-AS1 regulates collagen expression.

The long noncoding RNA CDKN2B-AS1 harbors a major coronary artery disease risk haplotype, which is also associated with progressive forms of the oral inflammatory disease periodontitis as well as myocardial infarction (MI). Despite extensive research, there is currently no broad consensus on the function of CDKN2B-AS1 that would explain a common molecular role of this lncRNA in these diseases. Our aim was to investigate the role of CDKN2B-AS1 in gingival cells to better understand the molecular mechanisms underlying the increased risk of progressive periodontitis. We downregulated CDKN2B-AS1 transcript levels in primary gingival fibroblasts with LNA GapmeRs. Following RNA-sequencing, we performed differential expression, gene set enrichment analyses and Western Blotting. Putative causal alleles were searched by analyzing associated DNA sequence variants for changes of predicted transcription factor binding sites. We functionally characterized putative functional alleles using luciferase-reporter and antibody electrophoretic mobility shift assays in gingival fibroblasts and HeLa cells. Of all gene sets analysed, collagen biosynthesis was most significantly upregulated (Padj=9.7 × 10- 5 (AUC > 0.65) with the CAD and MI risk gene COL4A1 showing strongest upregulation of the enriched gene sets (Fold change = 12.13, Padj = 4.9 × 10- 25). The inflammatory "TNFA signaling via NFKB" gene set was downregulated the most (Padj=1 × 10- 5 (AUC = 0.60). On the single gene level, CAPNS2, involved in extracellular matrix organization, was the top upregulated protein coding gene (Fold change = 48.5, P < 9 × 10- 24). The risk variant rs10757278 altered a binding site of the pathogen responsive transcription factor STAT1 (P = 5.8 × 10- 6). rs10757278-G allele reduced STAT1 binding 14.4% and rs10757278-A decreased luciferase activity in gingival fibroblasts 41.2% (P = 0.0056), corresponding with GTEx data. CDKN2B-AS1 represses collagen gene expression in gingival fibroblasts. Dysregulated collagen biosynthesis through allele-specific CDKN2B-AS1 expression in response to inflammatory factors may affect collagen synthesis, and in consequence tissue barrier and atherosclerotic plaque stability.

Microenvironmental acidification by pneumococcal sugar consumption fosters barrier disruption and immune suppression in the human alveolus.

Streptococcus pneumoniae (S.p.) is the most common causative agent of community-acquired pneumonia worldwide. A key pathogenic mechanism that exacerbates severity of disease is the disruption of the alveolar-capillary barrier. However, the specific virulence mechanisms responsible for this in the human lung are not yet fully understood.In this study, we infected living human lung tissue with S.p. and observed a significant degradation of the central junctional proteins occludin and VE-cadherin, indicating barrier disruption. Surprisingly, neither pneumolysin, bacterial hydrogen peroxide nor pro-inflammatory activation were sufficient to cause this junctional degradation. Instead, pneumococcal infection led to a significant decrease of pH (approximately 6), resulting in acidification of the alveolar microenvironment, which was linked to junctional degradation. Stabilising the pH at physiological levels during infection reversed this effect, even in a therapeutic-like approach.Further analysis of bacterial metabolites and RNA sequencing revealed sugar consumption and subsequent lactate production were the major factors contributing to bacterially induced alveolar acidification, which also hindered the release of critical immune factors.Our findings highlight bacterial metabolite-induced acidification as an independent virulence mechanism for barrier disruption and inflammatory dysregulation in pneumonia. Thus, our data suggest that strictly monitoring and buffering alveolar pH during infections caused by fermentative bacteria could serve as an adjunctive therapeutic strategy for sustaining barrier integrity and immune response.

Comparable CD8+ T-cell responses to SARS-CoV-2 vaccination in single-cell transcriptomics of recently allogeneic transplanted patients and healthy individuals.

Despite extensive research on severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) vaccination responses in healthy individuals, there is comparatively little known beyond antibody titers and T-cell responses in the vulnerable cohort of patients after allogeneic hematopoietic stem cell transplantation (ASCT). In this study, we assessed the serological response and performed longitudinal multimodal analyses including T-cell functionality and single-cell RNA sequencing combined with T cell receptor (TCR)/B cell receptor (BCR) profiling in the context of BNT162b2 vaccination in ASCT patients. In addition, these data were compared to publicly available data sets of healthy vaccinees. Protective antibody titers were achieved in 40% of patients. We identified a distorted B- and T-cell distribution, a reduced TCR diversity, and increased levels of exhaustion marker expression as possible causes for the poorer vaccine response rates in ASCT patients. Immunoglobulin heavy chain gene rearrangement after vaccination proved to be highly variable in ASCT patients. Changes in TCRα and TCRß gene rearrangement after vaccination differed from patterns observed in healthy vaccinees. Crucially, ASCT patients elicited comparable proportions of SARS-CoV-2 vaccine-induced (VI) CD8+ T-cells, characterized by a distinct gene expression pattern that is associated with SARS-CoV-2 specificity in healthy individuals. Our study underlines the impaired immune system and thus the lower vaccine response rates in ASCT patients. However, since protective vaccine responses and VI CD8+ T-cells can be induced in part of ASCT patients, our data advocate early posttransplant vaccination due to the high risk of infection in this vulnerable group.

Microglia undergo molecular and functional adaptations to dark and light phases in male laboratory mice.

Microglia are increasingly recognized to contribute to brain health and disease. Preclinical studies using laboratory rodents are essential to advance our understanding of the physiological and pathophysiological roles of these cells in the central nervous system. Rodents are nocturnal animals, and they are mostly maintained in a defined light-dark cycle within animal facilities, with many laboratories investigating the molecular and functional profiles of microglia exclusively during the animals' light (sleep) phase. However, only a few studies have considered possible differences in microglial functions between the active and sleep phases. Based on initial evidence suggesting that microglial intrinsic clock genes can affect their phenotypes, we sought to investigate differences in transcriptional, proteotype and functional profiles of microglia between light (sleep) and dark (active) phases, and how these changes are affected in pathological models. We found marked transcriptional and proteotype differences between microglia harvested from male mice during the light or dark phase. Amongst others, these differences related to genes and proteins associated with immune responses, motility, and phagocytosis, which were reflected by functional alterations in microglial synaptic pruning and response to bacterial stimuli. Possibly accounting for such changes, we found RNA and protein regulation in SWI/SNF and NuRD chromatin remodeling complexes between light and dark phases. Importantly, we also show that the time of microglial sample collection influences the nature of microglial transcriptomic changes in a model of immune-mediated neurodevelopmental disorders. Our findings emphasize the importance of considering diurnal factors in studying microglial cells and indicate that implementing a circadian perspective is pivotal for advancing our understanding of their physiological and pathophysiological roles in brain health and disease.

ClearCNV: CNV calling from NGS panel data in the presence of ambiguity and noise.

MOTIVATION: While the identification of small variants in panel sequencing data can be considered a solved problem, the identification of larger, multi-exon copy number variants (CNVs) still poses a considerable challenge. Thus, CNV calling has not been established in all laboratories performing panel sequencing. At the same time, such laboratories have accumulated large datasets and thus have the need to identify CNVs on their data to close the diagnostic gap. RESULTS: In this article, we present our method clearCNV that addresses this need in two ways. First, it helps laboratories to properly assign datasets to enrichment kits. Based on homogeneous subsets of data, clearCNV identifies CNVs affecting the targeted regions. Using real-world datasets and validation, we show that our method is highly competitive with previous methods and preferable in terms of specificity. AVAILABILITY AND IMPLEMENTATION: The software is available for free under a permissible license at https://github.com/bihealth/clear-cnv. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

Tumour ischaemia by interferon-γ resembles physiological blood vessel regression.

The relative contribution of the effector molecules produced by T cells to tumour rejection is unclear, but interferon-γ (IFNγ) is critical in most of the analysed models. Although IFNγ can impede tumour growth by acting directly on cancer cells, it must also act on the tumour stroma for effective rejection of large, established tumours. However, which stroma cells respond to IFNγ and by which mechanism IFNγ contributes to tumour rejection through stromal targeting have remained unknown. Here we use a model of IFNγ induction and an IFNγ-GFP fusion protein in large, vascularized tumours growing in mice that express the IFNγ receptor exclusively in defined cell types. Responsiveness to IFNγ by myeloid cells and other haematopoietic cells, including T cells or fibroblasts, was not sufficient for IFNγ-induced tumour regression, whereas responsiveness of endothelial cells to IFNγ was necessary and sufficient. Intravital microscopy revealed IFNγ-induced regression of the tumour vasculature, resulting in arrest of blood flow and subsequent collapse of tumours, similar to non-haemorrhagic necrosis in ischaemia and unlike haemorrhagic necrosis induced by tumour necrosis factor. The early events of IFNγ-induced tumour ischaemia resemble non-apoptotic blood vessel regression during development, wound healing or IFNγ-mediated, pregnancy-induced remodelling of uterine arteries. A better mechanistic understanding of how solid tumours are rejected may aid the design of more effective protocols for adoptive T-cell therapy.

EBAG9 silencing exerts an immune checkpoint function without aggravating adverse effects.

Chimeric antigen receptor (CAR) T cells have revolutionized treatment of B cell malignancies. However, enhancing the efficacy of engineered T cells without compromising their safety is warranted. The estrogen receptor-binding fragment-associated antigen 9 (EBAG9) inhibits release of cytolytic enzymes from cytotoxic T lymphocytes. Here, we examined the potency of EBAG9 silencing for the improvement of adoptive T cell therapy. MicroRNA (miRNA)-mediated EBAG9 downregulation in transplanted cytolytic CD8+ T cells (CTLs) from immunized mice improved their cytolytic competence in a tumor model. In tolerant female recipient mice that received organ transplants, a minor histocompatibility antigen was turned into a rejection antigen by Ebag9 deletion, indicating an immune checkpoint function for EBAG9. Considerably fewer EBAG9-silenced human CAR T cells were needed for tumor growth control in a xenotransplantation model. Transcriptome profiling did not reveal additional risks regarding genotoxicity or aberrant differentiation. A single-step retrovirus transduction process links CAR or TCR expression with miRNA-mediated EBAG9 downregulation. Despite higher cytolytic efficacy, release of cytokines associated with cytokine release syndrome remains unaffected. Collectively, EBAG9 silencing enhances effector capacity of TCR- and CAR-engineered T cells, results in improved tumor eradication, facilitates efficient manufacturing, and decreases the therapeutic dose.

The single-cell transcriptional landscape of lung carcinoid tumors.

Lung carcinoid tumors, also referred to as pulmonary neuroendocrine tumors or lung carcinoids, are rare neoplasms of the lung with a more favorable prognosis than other subtypes of lung cancer. Still, some patients suffer from relapsed disease and metastatic spread. Several recent single-cell studies have provided detailed insights into the cellular heterogeneity of more common lung cancers, such as adeno- and squamous cell carcinoma. However, the characteristics of lung carcinoids on the single-cell level are yet completely unknown. To study the cellular composition and single-cell gene expression profiles in lung carcinoids, we applied single-cell RNA sequencing to three lung carcinoid tumor samples and normal lung tissue. The single-cell transcriptomes of carcinoid tumor cells reflected intertumoral heterogeneity associated with clinicopathological features, such as tumor necrosis and proliferation index. The immune microenvironment was specifically enriched in noninflammatory monocyte-derived myeloid cells. Tumor-associated endothelial cells were characterized by distinct gene expression profiles. A spectrum of vascular smooth muscle cells and pericytes predominated the stromal microenvironment. We found a small proportion of myofibroblasts exhibiting features reminiscent of cancer-associated fibroblasts. Stromal and immune cells exhibited potential paracrine interactions which may shape the microenvironment via NOTCH, VEGF, TGFß and JAK/STAT signaling. Moreover, single-cell gene signatures of pericytes and myofibroblasts demonstrated prognostic value in bulk gene expression data. Here, we provide first comprehensive insights into the cellular composition and single-cell gene expression profiles in lung carcinoids, demonstrating the noninflammatory and vessel-rich nature of their tumor microenvironment, and outlining relevant intercellular interactions which could serve as future therapeutic targets.

Deep Learning-Assisted Peak Curation for Large-Scale LC-MS Metabolomics.

Available automated methods for peak detection in untargeted metabolomics suffer from poor precision. We present NeatMS, which uses machine learning based on a convoluted neural network to reduce the number and fraction of false peaks. NeatMS comes with a pre-trained model representing expert knowledge in the differentiation of true chemical signal from noise. Furthermore, it provides all necessary functions to easily train new models or improve existing ones by transfer learning. Thus, the tool improves peak curation and contributes to the robust and scalable analysis of large-scale experiments. We show how to integrate it into different liquid chromatography-mass spectrometry (LC-MS) analysis workflows, quantify its performance, and compare it to various other approaches. NeatMS software is available as open source on github under permissive MIT license and is also provided as easy-to-install PyPi and Bioconda packages.

Feasibility and outcome of reproducible clinical interpretation of high-dimensional molecular data: a comparison of two molecular tumor boards.

BACKGROUND: Structured and harmonized implementation of molecular tumor boards (MTB) for the clinical interpretation of molecular data presents a current challenge for precision oncology. Heterogeneity in the interpretation of molecular data was shown for patients even with a limited number of molecular alterations. Integration of high-dimensional molecular data, including RNA- (RNA-Seq) and whole-exome sequencing (WES), is expected to further complicate clinical application. To analyze challenges for MTB harmonization based on complex molecular datasets, we retrospectively compared clinical interpretation of WES and RNA-Seq data by two independent molecular tumor boards. METHODS: High-dimensional molecular cancer profiling including WES and RNA-Seq was performed for patients with advanced solid tumors, no available standard therapy, ECOG performance status of 0-1, and available fresh-frozen tissue within the DKTK-MASTER Program from 2016 to 2018. Identical molecular profiling data of 40 patients were independently discussed by two molecular tumor boards (MTB) after prior annotation by specialized physicians, following independent, but similar workflows. Identified biomarkers and resulting treatment options were compared between the MTBs and patients were followed up clinically. RESULTS: A median of 309 molecular aberrations from WES and RNA-Seq (n = 38) and 82 molecular aberrations from WES only (n = 3) were considered for clinical interpretation for 40 patients (one patient sequenced twice). A median of 3 and 2 targeted treatment options were identified per patient, respectively. Most treatment options were identified for receptor tyrosine kinase, PARP, and mTOR inhibitors, as well as immunotherapy. The mean overlap coefficient between both MTB was 66%. Highest agreement rates were observed with the interpretation of single nucleotide variants, clinical evidence levels 1 and 2, and monotherapy whereas the interpretation of gene expression changes, preclinical evidence levels 3 and 4, and combination therapy yielded lower agreement rates. Patients receiving treatment following concordant MTB recommendations had significantly longer overall survival than patients receiving treatment following discrepant recommendations or physician's choice. CONCLUSIONS: Reproducible clinical interpretation of high-dimensional molecular data is feasible and agreement rates are encouraging, when compared to previous reports. The interpretation of molecular aberrations beyond single nucleotide variants and preclinically validated biomarkers as well as combination therapies were identified as additional difficulties for ongoing harmonization efforts.