decoupleR: ensemble of computational methods to infer biological activities from omics data

A new atlas to study embryonic cell types in Xenopus

This paper introduces a single-cell atlas for pivotal developmental stages in Xenopus, encompassing gastrulation, neurulation, and early tailbud. Notably surpassing its predecessors, the new atlas enhances gene mapping, read counts, and gene/cell type nomenclature. Leveraging the latest Xenopus tropicalis genome version, alongside advanced alignment pipelines and machine learning for cell type assignment, this release maintains consistency with previous cell type annotations while rectifying nomenclature issues. Employing an unbiased approach for cell type assignment proves especially apt for embryonic contexts, given the considerable number of non-terminally differentiated cell types. An alternative cell type attribution here adopts a fuzzy, non-deterministic stance, capturing the transient nature of early embryo progenitor cells by presenting an ensemble of types in superposition. The value of the new resource is emphasized through numerous examples, with a focus on previously unexplored germ cell populations where we uncover novel transcription onset features. Offering interactive exploration via a user-friendly web portal and facilitating complete data downloads, this atlas serves as a comprehensive and accessible reference.

Effect of genomic and cellular environments on gene expression noise

BACKGROUND

Individual cells from isogenic populations often display large cell-to-cell differences in gene expression. This "noise" in expression derives from several sources, including the genomic and cellular environment in which a gene resides. Large-scale maps of genomic environments have revealed the effects of epigenetic modifications and transcription factor occupancy on mean expression levels, but leveraging such maps to explain expression noise will require new methods to assay how expression noise changes at locations across the genome.

RESULTS

To address this gap, we present Single-cell Analysis of Reporter Gene Expression Noise and Transcriptome (SARGENT), a method that simultaneously measures the noisiness of reporter genes integrated throughout the genome and the global mRNA profiles of individual reporter-gene-containing cells. Using SARGENT, we perform the first comprehensive genome-wide survey of how genomic locations impact gene expression noise. We find that the mean and noise of expression correlate with different histone modifications. We quantify the intrinsic and extrinsic components of reporter gene noise and, using the associated mRNA profiles, assign the extrinsic component to differences between the CD24+ "stem-like" substate and the more "differentiated" substate. SARGENT also reveals the effects of transgene integrations on endogenous gene expression, which will help guide the search for "safe-harbor" loci.

CONCLUSIONS

Taken together, we show that SARGENT is a powerful tool to measure both the mean and noise of gene expression at locations across the genome and that the data generatd by SARGENT reveals important insights into the regulation of gene expression noise genome-wide.

Electron transport chain capacity expands yellow fever vaccine immunogenicity

Vaccination has successfully controlled several infectious diseases although better vaccines remain desirable. Host response to vaccination studies have identified correlates of vaccine immunogenicity that could be useful to guide development and selection of future vaccines. However, it remains unclear whether these findings represent mere statistical correlations or reflect functional associations with vaccine immunogenicity. Functional associations, rather than statistical correlates, would offer mechanistic insights into vaccine-induced adaptive immunity. Through a human experimental study to test the immunomodulatory properties of metformin, an anti-diabetic drug, we chanced upon a functional determinant of neutralizing antibodies. Although vaccine viremia is a known correlate of antibody response, we found that in healthy volunteers with no detectable or low yellow fever 17D viremia, metformin-treated volunteers elicited higher neutralizing antibody titers than placebo-treated volunteers. Transcriptional and metabolomic analyses collectively showed that a brief course of metformin, started 3 days prior to YF17D vaccination and stopped at 3 days after vaccination, expanded oxidative phosphorylation and protein translation capacities. These increased capacities directly correlated with YF17D neutralizing antibody titers, with reduced reactive oxygen species response compared to placebo-treated volunteers. Our findings thus demonstrate a functional association between cellular respiration and vaccine-induced humoral immunity and suggest potential approaches to enhancing vaccine immunogenicity.

Network Analyses of Brain Tumor Patients' Multiomic Data Reveals Pharmacological Opportunities to Alter Cell State Transitions

Glioblastoma Multiforme (GBM) remains a particularly difficult cancer to treat, and survival outcomes remain poor. In addition to the lack of dedicated drug discovery programs for GBM, extensive intratumor heterogeneity and epigenetic plasticity related to cell-state transitions are major roadblocks to successful drug therapy in GBM. To study these phenomenon, publicly available snRNAseq and bulk RNAseq data from patient samples were used to categorize cells from patients into four cell states (i.e. phenotypes), namely: (i) neural progenitor-like (NPC-like), (ii) oligodendrocyte progenitor-like (OPC-like), (iii) astrocyte-like (AC-like), and (iv) mesenchymal-like (MES-like). Patients were subsequently grouped into subpopulations based on which cell-state was the most dominant in their respective tumor. By incorporating phosphoproteomic measurements from the same patients, a protein-protein interaction network (PPIN) was constructed for each cell state. These four-cell state PPINs were pooled to form a single Boolean network that was used for in silico protein knockout simulations to investigate mechanisms that either promote or prevent cell state transitions. Simulation results were input into a boosted tree machine learning model which predicted the cell states or phenotypes of GBM patients from an independent public data source, the Glioma Longitudinal Analysis (GLASS) Consortium. Combining the simulation results and the machine learning predictions, we generated hypotheses for clinically relevant causal mechanisms of cell state transitions. For example, the transcription factor TFAP2A can be seen to promote a transition from the NPC-like to the MES-like state. Such protein nodes and the associated signaling pathways provide potential drug targets that can be further tested in vitro and support cell state-directed (CSD) therapy.

Altered Glia-Neuron Communication in Alzheimer's Disease Affects WNT, p53, and NFkB Signaling Determined by snRNA-seq

Background

Alzheimer's disease is the most common cause of dementia and is characterized by amyloid-β plaques, tau neurofibrillary tangles, and neuronal loss. Although neuronal loss is a primary hallmark of Alzheimer's disease, it is known that non-neuronal cell populations are ultimately responsible for maintaining brain homeostasis and neuronal health through neuron-glia and glial cell crosstalk. Many signaling pathways have been proposed to be dysregulated in Alzheimer's disease, including WNT, TGFβ, p53, mTOR, NFkB, and Pi3k/Akt signaling. Here, we predict altered cell-cell communication between glia and neurons.

Methods

Using public snRNA-sequencing data generated from postmortem human prefrontal cortex, we predicted altered cell-cell communication between glia (astrocytes, microglia, oligodendrocytes, and oligodendrocyte progenitor cells) and neurons (excitatory and inhibitory). We confirmed interactions in a second and third independent orthogonal dataset. We determined cell-type-specificity using Jaccard Similarity Index and investigated the downstream effects of altered interactions in inhibitory neurons through gene expression and transcription factor activity analyses of signaling mediators. Finally, we determined changes in pathway activity in inhibitory neurons.

Results

Cell-cell communication between glia and neurons is altered in Alzheimer's disease in a cell-type-specific manner. As expected, ligands are more cell-type-specific than receptors and targets. We identified ligand-receptor pairs in three independent datasets and found involvement of the Alzheimer's disease risk genes APP and APOE across datasets. Most of the signaling mediators of these interactions were not differentially expressed, however, the mediators that are also transcription factors had differential activity between AD and control. Namely, MYC and TP53 , which are associated with WNT and p53 signaling, respectively, had decreased TF activity in Alzheimer's disease, along with decreased WNT and p53 pathway activity in inhibitory neurons. Additionally, inhibitory neurons had both increased NFkB signaling pathway activity and increased TF activity of NFIL3 , an NFkB signaling-associated transcription factor.

Conclusions

Cell-cell communication between glia and neurons in Alzheimer's disease is altered in a cell-type-specific manner involving Alzheimer's disease risk genes. Signaling mediators had altered transcription factor activity suggesting altered glia-neuron interactions may dysregulate signaling pathways including WNT, p53, and NFkB in inhibitory neurons.

Transcriptomic, epigenomic, and spatial metabolomic cell profiling redefines regional human kidney anatomy

A large-scale multimodal atlas that includes major kidney regions is lacking. Here, we employed simultaneous high-throughput single-cell ATAC/RNA sequencing (SHARE-seq) and spatially resolved metabolomics to profile 54 human samples from distinct kidney anatomical regions. We generated transcriptomes of 446,267 cells and chromatin accessibility profiles of 401,875 cells and developed a package to analyze 408,218 spatially resolved metabolomes. We find that the same cell type, including thin limb, thick ascending limb loop of Henle and principal cells, display distinct transcriptomic, chromatin accessibility, and metabolomic signatures, depending on anatomic location. Surveying metabolism-associated gene profiles revealed non-overlapping metabolic signatures between nephron segments and dysregulated lipid metabolism in diseased proximal tubule (PT) cells. Integrating multimodal omics with clinical data identified PLEKHA1 as a disease marker, and its in vitro knockdown increased gene expression in PT differentiation, suggesting possible pathogenic roles. This study highlights previously underrepresented cellular heterogeneity underlying the human kidney anatomy.

Transformation of an olfactory placode-derived cell into one with stem cell characteristics by disrupting epigenetic barriers

The mammalian olfactory neuronal lineage is regenerative, and accordingly, maintains a population of pluripotent cells that replenish olfactory sensory neurons and other olfactory cell types during the life of the animal. Moreover, in response to acute injury, the early transit amplifying cells along the olfactory sensory neuronal lineage are able to de-differentiate to shift resources in support of tissue restoration. In order to further explore plasticity of various cellular stages along the olfactory sensory neuronal lineage, we challenged the epigenetic stability of two olfactory placode-derived cell lines that model immature olfactory sensory neuronal stages. We found that perturbation of the Ehmt2 chromatin modifier transformed the growth properties, morphology, and gene expression profiles towards states with several stem cell characteristics. This transformation was dependent on continued expression of the large T-antigen, and was enhanced by Sox2 over-expression. These findings may provide momentum for exploring inherent cellular plasticity within early cell types of the olfactory lineage, as well as potentially add to our knowledge of cellular reprogramming.

SUMMARY STATEMENT

Discovering how epigenetic modifications influence olfactory neuronal lineage plasticity offers insights into regenerative potential and cellular reprogramming.

Scalable integration of multiomic single-cell data using generative adversarial networks

MOTIVATION

Single-cell profiling has become a common practice to investigate the complexity of tissues, organs, and organisms. Recent technological advances are expanding our capabilities to profile various molecular layers beyond the transcriptome such as, but not limited to, the genome, the epigenome, and the proteome. Depending on the experimental procedure, these data can be obtained from separate assays or the very same cells. Yet, integration of more than two assays is currently not supported by the majority of the computational frameworks avaiable.

RESULTS

We here propose a Multi-Omic data integration framework based on Wasserstein Generative Adversarial Networks suitable for the analysis of paired or unpaired data with a high number of modalities (>2). At the core of our strategy is a single network trained on all modalities together, limiting the computational burden when many molecular layers are evaluated.

AVAILABILITY AND IMPLEMENTATION

Source code of our framework is available at https://github.com/vgiansanti/MOWGAN.

Molecular mechanisms reconstruction from single-cell multi-omics data with HuMMuS

MOTIVATION

The molecular identity of a cell results from a complex interplay between heterogeneous molecular layers. Recent advances in single-cell sequencing technologies have opened the possibility to measure such molecular layers of regulation.

RESULTS

Here, we present HuMMuS, a new method for inferring regulatory mechanisms from single-cell multi-omics data. Differently from the state-of-the-art, HuMMuS captures cooperation between biological macromolecules and can easily include additional layers of molecular regulation. We benchmarked HuMMuS with respect to the state-of-the-art on both paired and unpaired multi-omics datasets. Our results proved the improvements provided by HuMMuS in terms of transcription factor (TF) targets, TF binding motifs and regulatory regions prediction. Finally, once applied to snmC-seq, scATAC-seq and scRNA-seq data from mouse brain cortex, HuMMuS enabled to accurately cluster scRNA profiles and to identify potential driver TFs.

AVAILABILITY AND IMPLEMENTATION

HuMMuS is available at https://github.com/cantinilab/HuMMuS.

Unveiling Novel Double-Negative Prostate Cancer Subtypes Through Single-Cell RNA Sequencing Analysis

Recent advancements in single-cell RNA sequencing (scRNAseq) have facilitated the discovery of previously unrecognized subtypes within prostate cancer (PCa), offering new insights into disease heterogeneity and progression. In this study, we integrated scRNAseq data from multiple studies, comprising both publicly available cohorts and data generated by our research team, and established the HuPSA (Human Prostate Single cell Atlas) and the MoPSA (Mouse Prostate Single cell Atlas) datasets. Through comprehensive analysis, we identified two novel double-negative PCa populations: KRT7 cells characterized by elevated KRT7 expression, and progenitor-like cells marked by SOX2 and FOXA2 expression, distinct from NEPCa, and displaying stem/progenitor features. Furthermore, HuPSA-based deconvolution allowed for the re-classification of human PCa specimens, validating the presence of these novel subtypes. Leveraging these findings, we developed a user-friendly web application, "HuPSA-MoPSA" (https://pcatools.shinyapps.io/HuPSA-MoPSA/), for visualizing gene expression across all newly-established datasets. Our study provides comprehensive tools for PCa research and uncovers novel cancer subtypes that can inform clinical diagnosis and treatment strategies.

Integrative multi-omics profiling in human decedents receiving pig heart xenografts

In a previous study, heart xenografts from 10-gene-edited pigs transplanted into two human decedents did not show evidence of acute-onset cellular- or antibody-mediated rejection. Here, to better understand the detailed molecular landscape following xenotransplantation, we carried out bulk and single-cell transcriptomics, lipidomics, proteomics and metabolomics on blood samples obtained from the transplanted decedents every 6 h, as well as histological and transcriptomic tissue profiling. We observed substantial early immune responses in peripheral blood mononuclear cells and xenograft tissue obtained from decedent 1 (male), associated with downstream T cell and natural killer cell activity. Longitudinal analyses indicated the presence of ischemia reperfusion injury, exacerbated by inadequate immunosuppression of T cells, consistent with previous findings of perioperative cardiac xenograft dysfunction in pig-to-nonhuman primate studies. Moreover, at 42 h after transplantation, substantial alterations in cellular metabolism and liver-damage pathways occurred, correlating with profound organ-wide physiological dysfunction. By contrast, relatively minor changes in RNA, protein, lipid and metabolism profiles were observed in decedent 2 (female) as compared to decedent 1. Overall, these multi-omics analyses delineate distinct responses to cardiac xenotransplantation in the two human decedents and reveal new insights into early molecular and immune responses after xenotransplantation. These findings may aid in the development of targeted therapeutic approaches to limit ischemia reperfusion injury-related phenotypes and improve outcomes.

PGE2 limits effector expansion of tumour-infiltrating stem-like CD8+ T cells

Cancer-specific TCF1+ stem-like CD8+ T cells can drive protective anticancer immunity through expansion and effector cell differentiation1-4; however, this response is dysfunctional in tumours. Current cancer immunotherapies2,5-9 can promote anticancer responses through TCF1+ stem-like CD8+ T cells in some but not all patients. This variation points towards currently ill-defined mechanisms that limit TCF1+CD8+ T cell-mediated anticancer immunity. Here we demonstrate that tumour-derived prostaglandin E2 (PGE2) restricts the proliferative expansion and effector differentiation of TCF1+CD8+ T cells within tumours, which promotes cancer immune escape. PGE2 does not affect the priming of TCF1+CD8+ T cells in draining lymph nodes. PGE2 acts through EP2 and EP4 (EP2/EP4) receptor signalling in CD8+ T cells to limit the intratumoural generation of early and late effector T cell populations that originate from TCF1+ tumour-infiltrating CD8+ T lymphocytes (TILs). Ablation of EP2/EP4 signalling in cancer-specific CD8+ T cells rescues their expansion and effector differentiation within tumours and leads to tumour elimination in multiple mouse cancer models. Mechanistically, suppression of the interleukin-2 (IL-2) signalling pathway underlies the PGE2-mediated inhibition of TCF1+ TIL responses. Altogether, we uncover a key mechanism that restricts the IL-2 responsiveness of TCF1+ TILs and prevents anticancer T cell responses that originate from these cells. This study identifies the PGE2-EP2/EP4 axis as a molecular target to restore IL-2 responsiveness in anticancer TILs to achieve cancer immune control.

Concurrent inhibition of ALK and SRC kinases disrupts the ALK lung tumor cell proteome

Precision oncology has revolutionized the treatment of ALK-positive lung cancer with targeted therapies. However, an unmet clinical need still to address is the treatment of refractory tumors that contain drug-induced resistant mutations in the driver oncogene or exhibit resistance through the activation of diverse mechanisms. In this study, we established mouse tumor-derived cell models representing the two most prevalent EML4-ALK variants in human lung adenocarcinomas and characterized their proteomic profiles to gain insights into the underlying resistance mechanisms. We showed that Eml4-Alk variant 3 confers a worse response to ALK inhibitors, suggesting its role in promoting resistance to targeted therapy. In addition, proteomic analysis of brigatinib-treated cells revealed the upregulation of SRC kinase, a protein frequently activated in cancer. Co-targeting of ALK and SRC showed remarkable inhibitory effects in both ALK-driven murine and ALK-patient-derived lung tumor cells. This combination induced cell death through a multifaceted mechanism characterized by profound perturbation of the (phospho)proteomic landscape and a synergistic suppressive effect on the mTOR pathway. Our study demonstrates that the simultaneous inhibition of ALK and SRC can potentially overcome resistance mechanisms and enhance clinical outcomes in ALK-positive lung cancer patients. ONE SENTENCE SUMMARY: Co-targeting ALK and SRC enhances ALK inhibitor response in lung cancer by affecting the proteomic profile, offering hope for overcoming resistance and improving clinical outcomes.

Steroids-producing nodules: a two-layered adrenocortical nodular structure as a precursor lesion of cortisol-producing adenoma

BACKGROUND

The human adrenal cortex consists of three functionally and structurally distinct layers; zona glomerulosa, zona fasciculata (zF), and zona reticularis (zR), and produces adrenal steroid hormones in a layer-specific manner; aldosterone, cortisol, and adrenal androgens, respectively. Cortisol-producing adenomas (CPAs) occur mostly as a result of somatic mutations associated with the protein kinase A pathway. However, how CPAs develop after adrenocortical cells acquire genetic mutations, remains poorly understood.

METHODS

We conducted integrated approaches combining the detailed histopathologic studies with genetic, RNA-sequencing, and spatially resolved transcriptome (SRT) analyses for the adrenal cortices adjacent to human adrenocortical tumours.

FINDINGS

Histopathological analysis revealed an adrenocortical nodular structure that exhibits the two-layered zF- and zR-like structure. The nodular structures harbour GNAS somatic mutations, known as a driver mutation of CPAs, and confer cell proliferative and autonomous steroidogenic capacities, which we termed steroids-producing nodules (SPNs). RNA-sequencing coupled with SRT analysis suggests that the expansion of the zF-like structure contributes to the formation of CPAs, whereas the zR-like structure is characterised by a macrophage-mediated immune response.

INTERPRETATION

We postulate that CPAs arise from a precursor lesion, SPNs, where two distinct cell populations might contribute differently to adrenocortical tumorigenesis. Our data also provide clues to the molecular mechanisms underlying the layered structures of human adrenocortical tissues.

FUNDING

KAKENHI, The Uehara Memorial Foundation, Daiwa Securities Health Foundation, Kaibara Morikazu Medical Science Promotion Foundation, Secom Science and Technology Foundation, ONO Medical Research Foundation, and Japan Foundation for Applied Enzymology.

Prediction of immunotherapy responsiveness in melanoma through single-cell sequencing-based characterization of the tumor immune microenvironment

Immune checkpoint inhibitors (ICB) therapy have emerged as effective treatments for melanomas. However, the response of melanoma patients to ICB has been highly heterogenous. Here, by analyzing integrated scRNA-seq datasets from melanoma patients, we revealed significant differences in the TiME composition between ICB-resistant and responsive tissues, with resistant or responsive tissues characterized by an abundance of myeloid cells and CD8+ T cells or CD4+ T cell predominance, respectively. Among CD4+ T cells, CD4+ CXCL13+ Tfh-like cells were associated with an immunosuppressive phenotype linked to immune escape-related genes and negative regulation of T cell activation. We also develop an immunotherapy response prediction model based on the composition of the immune compartment. Our predictive model was validated using CIBERSORTx on bulk RNA-seq datasets from melanoma patients pre- and post-ICB treatment and showed a better performance than other existing models. Our study presents an effective immunotherapy response prediction model with potential for further translation, as well as underscores the critical role of the TiME in influencing the response of melanomas to immunotherapy.

Human cortical neurogenesis is altered via glucocorticoid-mediated regulation of ZBTB16 expression

Glucocorticoids are important for proper organ maturation, and their levels are tightly regulated during development. Here, we use human cerebral organoids and mice to study the cell-type-specific effects of glucocorticoids on neurogenesis. We show that glucocorticoids increase a specific type of basal progenitors (co-expressing PAX6 and EOMES) that has been shown to contribute to cortical expansion in gyrified species. This effect is mediated via the transcription factor ZBTB16 and leads to increased production of neurons. A phenome-wide Mendelian randomization analysis of an enhancer variant that moderates glucocorticoid-induced ZBTB16 levels reveals causal relationships with higher educational attainment and altered brain structure. The relationship with postnatal cognition is also supported by data from a prospective pregnancy cohort study. This work provides a cellular and molecular pathway for the effects of glucocorticoids on human neurogenesis that relates to lasting postnatal phenotypes.

Genetic dependencies associated with transcription factor activities in human cancer cell lines

Transcription factors (TFs) are important mediators of aberrant transcriptional programs in cancer cells. In this study, we focus on TF activity (TFa) as a biomarker for cell-line-selective anti-proliferative effects, in that high TFa predicts sensitivity to loss of function of a given gene (i.e., genetic dependencies [GDs]). Our linear-regression-based framework identifies 3,047 pan-cancer and 3,952 cancer-type-specific candidate TFa-GD associations from cell line data, which are then cross-examined for impact on survival in patient cohorts. One of the most prominent biomarkers is TEAD1 activity, whose associations with its predicted GDs are validated through experimental evidence as proof of concept. Overall, these TFa-GD associations represent an attractive resource for identifying innovative, biomarker-driven hypotheses for drug discovery programs in oncology.

ER-associated degradation adapter Sel1L is required for CD8+ T cell function and memory formation following acute viral infection

The maintenance of antigen-specific CD8+ T cells underlies the efficacy of vaccines and immunotherapies. Pathways contributing to CD8+ T cell loss are not completely understood. Uncovering the pathways underlying the limited persistence of CD8+ T cells would be of significant benefit for developing novel strategies of promoting T cell persistence. Here, we demonstrate that murine CD8+ T cells experience endoplasmic reticulum (ER) stress following activation and that the ER-associated degradation (ERAD) adapter Sel1L is induced in activated CD8+ T cells. Sel1L loss limits CD8+ T cell function and memory formation following acute viral infection. Mechanistically, Sel1L is required for optimal bioenergetics and c-Myc expression. Finally, we demonstrate that human CD8+ T cells experience ER stress upon activation and that ER stress is negatively associated with improved T cell functionality in T cell-redirecting therapies. Together, these results demonstrate that ER stress and ERAD are important regulators of T cell function and persistence.

CRISPR/Cas9 screenings unearth protein arginine methyltransferase 7 as a novel essential gene in prostate cancer metastasis

Due to the limited effectiveness of current treatments, the survival rate of patients with metastatic castration-resistant prostate cancer (mCRPC) is significantly reduced. Consequently, it is imperative to identify novel therapeutic targets for managing these patients. Since the invasive ability of cells is crucial for establishing and maintaining metastasis, the aim of this study was to identify the essential regulators of invasive abilities of mCRPC cells by conducting two independent high-throughput CRISPR/Cas9 screenings. Furthermore, some of the top hits were validated using siRNA technology, with protein arginine methyltransferase 7 (PRMT7) emerging as the most promising candidate. We demonstrated that its inhibition or depletion via genetic or pharmacological approaches significantly reduces invasive, migratory and proliferative abilities of mCRPC cells in vitro. Moreover, we confirmed that PRMT7 ablation reduces cell dissemination in chicken chorioallantoic membrane and mouse xenograft assays. Molecularly, PRMT7 reprograms the expression of several adhesion molecules by methylating various transcription factors, such as FoxK1, resulting in the loss of adhesion from the primary tumor and increased motility of mCRPC cells. Furthermore, PRMT7 higher expression correlates with tumor aggressivity and poor overall survival in prostate cancer patients. Thus, this study demonstrates that PRMT7 is a potential therapeutic target and potential biomarker for mPCa.

Combining LIANA and Tensor-cell2cell to decipher cell-cell communication across multiple samples

In recent years, data-driven inference of cell-cell communication has helped reveal coordinated biological processes across cell types. Here, we integrate two tools, LIANA and Tensor-cell2cell, which, when combined, can deploy multiple existing methods and resources to enable the robust and flexible identification of cell-cell communication programs across multiple samples. In this work, we show how the integration of our tools facilitates the choice of method to infer cell-cell communication and subsequently perform an unsupervised deconvolution to obtain and summarize biological insights. We explain how to perform the analysis step by step in both Python and R and provide online tutorials with detailed instructions available at https://ccc-protocols.readthedocs.io/. This workflow typically takes ∼1.5 h to complete from installation to downstream visualizations on a graphics processing unit-enabled computer for a dataset of ∼63,000 cells, 10 cell types, and 12 samples.

Bento: a toolkit for subcellular analysis of spatial transcriptomics data

The spatial organization of molecules in a cell is essential for their functions. While current methods focus on discerning tissue architecture, cell-cell interactions, and spatial expression patterns, they are limited to the multicellular scale. We present Bento, a Python toolkit that takes advantage of single-molecule information to enable spatial analysis at the subcellular scale. Bento ingests molecular coordinates and segmentation boundaries to perform three analyses: defining subcellular domains, annotating localization patterns, and quantifying gene-gene colocalization. We demonstrate MERFISH, seqFISH + , Molecular Cartography, and Xenium datasets. Bento is part of the open-source Scverse ecosystem, enabling integration with other single-cell analysis tools.

IL-6-mediated endothelial injury impairs antiviral humoral immunity after bone marrow transplantation

Endothelial function and integrity are compromised after allogeneic bone marrow transplantation (BMT), but how this affects immune responses broadly remains unknown. Using a preclinical model of CMV reactivation after BMT, we found compromised antiviral humoral responses induced by IL-6 signaling. IL-6 signaling in T cells maintained Th1 cells, resulting in sustained IFN-γ secretion, which promoted endothelial cell (EC) injury, loss of the neonatal Fc receptor (FcRn) responsible for IgG recycling, and rapid IgG loss. T cell-specific deletion of IL-6R led to persistence of recipient-derived, CMV-specific IgG and inhibited CMV reactivation. Deletion of IFN-γ in donor T cells also eliminated EC injury and FcRn loss. In a phase III clinical trial, blockade of IL-6R with tocilizumab promoted CMV-specific IgG persistence and significantly attenuated early HCMV reactivation. In sum, IL-6 invoked IFN-γ-dependent EC injury and consequent IgG loss, leading to CMV reactivation. Hence, cytokine inhibition represents a logical strategy to prevent endothelial injury, thereby preserving humoral immunity after immunotherapy.

Network integration of thermal proteome profiling with multi-omics data decodes PARP inhibition

Complex disease phenotypes often span multiple molecular processes. Functional characterization of these processes can shed light on disease mechanisms and drug effects. Thermal Proteome Profiling (TPP) is a mass-spectrometry (MS) based technique assessing changes in thermal protein stability that can serve as proxies of functional protein changes. These unique insights of TPP can complement those obtained by other omics technologies. Here, we show how TPP can be integrated with phosphoproteomics and transcriptomics in a network-based approach using COSMOS, a multi-omics integration framework, to provide an integrated view of transcription factors, kinases and proteins with altered thermal stability. This allowed us to recover consequences of Poly (ADP-ribose) polymerase (PARP) inhibition in ovarian cancer cells on cell cycle and DNA damage response as well as interferon and hippo signaling. We found that TPP offers a complementary perspective to other omics data modalities, and that its integration allowed us to obtain a more complete molecular overview of PARP inhibition. We anticipate that this strategy can be used to integrate functional proteomics with other omics to study molecular processes.

FOXO1 reshapes neutrophils to aggravate acute brain damage and promote late depression after traumatic brain injury

BACKGROUND

Neutrophils are traditionally viewed as first responders but have a short onset of action in response to traumatic brain injury (TBI). However, the heterogeneity, multifunctionality, and time-dependent modulation of brain damage and outcome mediated by neutrophils after TBI remain poorly understood.

METHODS

Using the combined single-cell transcriptomics, metabolomics, and proteomics analysis from TBI patients and the TBI mouse model, we investigate a novel neutrophil phenotype and its associated effects on TBI outcome by neurological deficit scoring and behavioral tests. We also characterized the underlying mechanisms both in vitro and in vivo through molecular simulations, signaling detections, gene expression regulation assessments [including dual-luciferase reporter and chromatin immunoprecipitation (ChIP) assays], primary cultures or co-cultures of neutrophils and oligodendrocytes, intracellular iron, and lipid hydroperoxide concentration measurements, as well as forkhead box protein O1 (FOXO1) conditional knockout mice.

RESULTS

We identified that high expression of the FOXO1 protein was induced in neutrophils after TBI both in TBI patients and the TBI mouse model. Infiltration of these FOXO1high neutrophils in the brain was detected not only in the acute phase but also in the chronic phase post-TBI, aggravating acute brain inflammatory damage and promoting late TBI-induced depression. In the acute stage, FOXO1 upregulated cytoplasmic Versican (VCAN) to interact with the apoptosis regulator B-cell lymphoma-2 (BCL-2)-associated X protein (BAX), suppressing the mitochondrial translocation of BAX, which mediated the antiapoptotic effect companied with enhancing interleukin-6 (IL-6) production of FOXO1high neutrophils. In the chronic stage, the "FOXO1-transferrin receptor (TFRC)" mechanism contributes to FOXO1high neutrophil ferroptosis, disturbing the iron homeostasis of oligodendrocytes and inducing a reduction in myelin basic protein, which contributes to the progression of late depression after TBI.

CONCLUSIONS

FOXO1high neutrophils represent a novel neutrophil phenotype that emerges in response to acute and chronic TBI, which provides insight into the heterogeneity, reprogramming activity, and versatility of neutrophils in TBI.

Comprehensive single-cell analysis reveals heterogeneity of fibroblast subpopulations in ovarian cancer tissue microenvironment

Background

Ovarian cancer, as a highly malignant tumor, features the critical involvement of tumor-associated fibroblasts in the ovarian cancer tissue microenvironment. However, due to the apparent heterogeneity within fibroblast subpopulations, the specific functions of these subpopulations in the ovarian cancer tissue microenvironment remain insufficiently elucidated.

Methods

In this study, we integrated single-cell sequencing data from 32 ovarian cancer samples derived from four distinct cohorts and 3226 bulk RNA-seq data from GEO and TCGA-OV cohorts. Utilizing computational frameworks such as Seurat, Monocle 2, Cellchat, and others, we analyzed the characteristics of the ovarian cancer tissue microenvironment, focusing particularly on fibroblast subpopulations and their differentiation trajectories. Employing the CIBERSORTX computational framework, we assessed various cellular components within the ovarian cancer tissue microenvironment and evaluated their associations with ovarian cancer prognosis. Additionally, we conducted Mendelian randomization analysis based on cis-eQTL to investigate causal relationships between gene expression and ovarian cancer.

Results

Through integrative analysis, we identified 13 major cell types present in ovarian cancer tissues, including CD8+ T cells, malignant cells, and fibroblasts. Analysis of the tumor microenvironment (TME) cell proportions revealed a significant increase in the proportion of CD8+ T cells and CD4+ T cells in tumor tissues compared to normal tissues, while fibroblasts predominated in normal tissues. Further subgroup analysis of fibroblasts identified seven subgroups, with the MMP11+Fib subgroup showing the highest activity in the TGFβ signaling pathway. Single-cell analysis suggested that oxidative phosphorylation could be a key pathway driving fibroblast differentiation, and the ATRNL1+KCN + Fib subgroup exhibited chromosomal copy number variations. Prognostic analysis using a large sample size indicated that high infiltration of MMP11+ fibroblasts was associated with poor prognosis in ovarian cancer. SMR analysis identified 132 fibroblast differentiation-related genes, which were linked to pathways such as platinum drug resistance.

Conclusions

In the context of ovarian cancer, fibroblasts expressing MMP11 emerge as the primary drivers of the TGF-beta signaling pathway. Their presence correlates with an increased risk of adverse ovarian prognoses. Additionally, the genetic regulation governing the differentiation of fibroblasts associated with ovarian cancer correlates with the emergence of drug resistance.

Antigen-driven CD8 + T cell clonal expansion is a prominent feature of MASH in humans and mice

Background and Aims

Chronic liver disease due to metabolic dysfunction-associated steatohepatitis (MASH) is a rapidly increasing global epidemic. MASH progression is a consequence of the complex interplay between inflammatory insults and dysregulated hepatic immune responses. T lymphocytes have been shown to accumulate in the liver during MASH, but the cause and consequence of T cell accumulation in the liver remain unclear. Our study aimed to define the phenotype and T cell receptor diversity of T cells from human cirrhotic livers and an animal model of MASH to begin resolving their function in disease.

Approach and Results

In these studies, we evaluated differences in T cell phenotype in the context of liver disease we isolated liver resident T cell populations from individuals with cirrhosis and a murine model of MASH. Using both 5' single cell sequencing and flow cytometry we defined the phenotype and T cell receptor repertoire of liver resident T cells during health and disease.

Conclusions

MASH-induced cirrhosis and diet-induced MASH in mice resulted in the accumulation of activated and clonally expanded T cells in the liver. The clonally expanded T cells in the liver expressed markers of chronic antigenic stimulation, including PD1 , TIGIT and TOX . Overall, this study establishes for the first time that T cells undergo antigen-dependent clonal expansion and functional differentiation during the progression of MASH. These studies could lead to the identification of potential antigenic targets that drive T cell activation, clonal expansion, and recruitment to the liver during MASH.

Chemotherapy induces myeloid-driven spatial T-cell exhaustion in ovarian cancer

To uncover the intricate, chemotherapy-induced spatiotemporal remodeling of the tumor microenvironment, we conducted integrative spatial and molecular characterization of 97 high-grade serous ovarian cancer (HGSC) samples collected before and after chemotherapy. Using single-cell and spatial analyses, we identify increasingly versatile immune cell states, which form spatiotemporally dynamic microcommunities at the tumor-stroma interface. We demonstrate that chemotherapy triggers spatial redistribution and exhaustion of CD8+ T cells due to prolonged antigen presentation by macrophages, both within interconnected myeloid networks termed "Myelonets" and at the tumor stroma interface. Single-cell and spatial transcriptomics identifies prominent TIGIT-NECTIN2 ligand-receptor interactions induced by chemotherapy. Using a functional patient-derived immuno-oncology platform, we show that CD8+T-cell activity can be boosted by combining immune checkpoint blockade with chemotherapy. Our discovery of chemotherapy-induced myeloid-driven spatial T-cell exhaustion paves the way for novel immunotherapeutic strategies to unleash CD8+ T-cell-mediated anti-tumor immunity in HGSC.

Predicting transcription factor activity using prior biological information

Dysregulation of normal transcription factor activity is a common driver of disease. Therefore, the detection of aberrant transcription factor activity is important to understand disease pathogenesis. We have developed Priori, a method to predict transcription factor activity from RNA sequencing data. Priori has two key advantages over existing methods. First, Priori utilizes literature-supported regulatory information to identify transcription factor-target gene relationships. It then applies linear models to determine the impact of transcription factor regulation on the expression of its target genes. Second, results from a third-party benchmarking pipeline reveals that Priori detects aberrant activity from 124 single-gene perturbation experiments with higher sensitivity and specificity than 11 other methods. We applied Priori and other top-performing methods to predict transcription factor activity from two large primary patient datasets. Our work demonstrates that Priori uniquely discovered significant determinants of survival in breast cancer and identified mediators of drug response in leukemia.

Cytokine and Chemokine Receptor Profiles in Adipose Tissue Vasculature Unravel Endothelial Cell Responses in HIV

Chronic systemic inflammation contributes to a substantially elevated risk of myocardial infarction in people living with HIV (PLWH). Endothelial cell dysfunction disrupts vascular homeostasis regulation, increasing the risk of vasoconstriction, inflammation, and thrombosis that contribute to cardiovascular disease. Our objective was to study the effects of plasma from PLWH on endothelial cell (EC) function, with the hypothesis that cytokines and chemokines are major drivers of EC activation. We first broadly phenotyped chemokine and cytokine receptor expression on arterial ECs, capillary ECs, venous ECs, and vascular smooth muscle cells (VSMCs) in adipose tissue in the subcutaneous adipose tissue of 59 PLWH using single cell transcriptomic analysis. We used CellChat to predict cell-cell interactions between ECs and other cells in the adipose tissue and Spearman correlation to measure the association between ECs and plasma cytokines. Finally, we cultured human arterial ECs (HAECs) in plasma-conditioned media from PLWH and performed bulk sequencing to study the direct effects ex-vivo. We observed that arterial and capillary ECs expressed higher interferon and tumor necrosis factor (TNF) receptors. Venous ECs had more interleukin (IL)-1R1 and ACKR1 receptors, and VSMCs had high significant IL-6R expression. CellChat predicted ligand-receptor interactions between adipose tissue immune cells as senders and capillary ECs as recipients in TNF-TNFRSF1A/B interactions. Chemokines expressed largely by capillary ECs were predicted to bind ACKR1 receptors on venous ECs. Beyond the adipose tissue, the proportion of venous ECs and VSMCs were positively plasma IL-6. In ex-vivo experiments, HAECs cultured with plasma-conditioned media from PLWH expressed transcripts that enriched for the TNF-α and reactive oxidative phosphorylation pathways. In conclusion, ECs demonstrate heterogeneity in cytokine and chemokine receptor expression. Further research is needed to fully elucidate the role of cytokines and chemokines in EC dysfunction and to develop effective therapeutic strategies.

On the identification of differentially-active transcription factors from ATAC-seq data

ATAC-seq has emerged as a rich epigenome profiling technique, and is commonly used to identify Transcription Factors (TFs) underlying given phenomena. A number of methods can be used to identify differentially-active TFs through the accessibility of their DNA-binding motif, however little is known on the best approaches for doing so. Here we benchmark several such methods using a combination of curated datasets with various forms of short-term perturbations on known TFs, as well as semi-simulations. We include both methods specifically designed for this type of data as well as some that can be repurposed for it. We also investigate variations to these methods, and identify three particularly promising approaches (chromVAR-limma with critical adjustments, monaLisa and a combination of GC smooth quantile normalization and multivariate modeling). We further investigate the specific use of nucleosome-free fragments, the combination of top methods, and the impact of technical variation. Finally, we illustrate the use of the top methods on a novel dataset to characterize the impact on DNA accessibility of TRAnscription Factor TArgeting Chimeras (TRAFTAC), which can deplete TFs - in our case NFkB - at the protein level.

Integrating single-cell multi-omics and prior biological knowledge for a functional characterization of the immune system

The immune system comprises diverse specialized cell types that cooperate to defend the host against a wide range of pathogenic threats. Recent advancements in single-cell and spatial multi-omics technologies provide rich information about the molecular state of immune cells. Here, we review how the integration of single-cell and spatial multi-omics data with prior knowledge-gathered from decades of detailed biochemical studies-allows us to obtain functional insights, focusing on gene regulatory processes and cell-cell interactions. We present diverse applications in immunology and critically assess underlying assumptions and limitations. Finally, we offer a perspective on the ongoing technological and algorithmic developments that promise to get us closer to a systemic mechanistic understanding of the immune system.

Spatial Gene-Expression Profiling Unveils Immuno-oncogenic Programs of NF1-Associated Peripheral Nerve Sheath Tumor Progression

PURPOSE

Plexiform neurofibromas (PNF) are benign peripheral nerve sheath tumors (PNST) associated with neurofibromatosis type 1 (NF1). Despite similar histologic appearance, these neoplasms exhibit diverse evolutionary trajectories, with a subset progressing to malignant peripheral nerve sheath tumor (MPNST), the leading cause of premature death in individuals with NF1. Malignant transformation of PNF often occurs through the development of atypical neurofibroma (ANF) precursor lesions characterized by distinct histopathologic features and CDKN2A copy-number loss. Although genomic studies have uncovered key driver events promoting tumor progression, the transcriptional changes preceding malignant transformation remain poorly defined.

EXPERIMENTAL DESIGN

Here we resolve gene-expression profiles in PNST across the neurofibroma-to-MPNST continuum in NF1 patients and mouse models, revealing early molecular features associated with neurofibroma evolution and transformation.

RESULTS

Our findings demonstrate that ANF exhibit enhanced signatures of antigen presentation and immune response, which are suppressed as malignant transformation ensues. MPNST further displayed deregulated survival and mitotic fidelity pathways, and targeting key mediators of these pathways, CENPF and BIRC5, disrupted the growth and viability of human MPNST cell lines and primary murine Nf1-Cdkn2a-mutant Schwann cell precursors. Finally, neurofibromas contiguous with MPNST manifested distinct alterations in core oncogenic and immune surveillance programs, suggesting that early molecular events driving disease progression may precede histopathologic evidence of malignancy.

CONCLUSIONS

If validated prospectively in future studies, these signatures may serve as molecular diagnostic tools to augment conventional histopathologic diagnosis by identifying neurofibromas at high risk of undergoing malignant transformation, facilitating risk-adapted care.

Molecularly stratified hypothalamic astrocytes are cellular foci for obesity

Astrocytes safeguard the homeostasis of the central nervous system1,2. Despite their prominent morphological plasticity under conditions that challenge the brain's adaptive capacity3-5, the classification of astrocytes, and relating their molecular make-up to spatially devolved neuronal operations that specify behavior or metabolism, remained mostly futile6,7. Although it seems unexpected in the era of single-cell biology, the lack of a major advance in stratifying astrocytes under physiological conditions rests on the incompatibility of 'neurocentric' algorithms that rely on stable developmental endpoints, lifelong transcriptional, neurotransmitter, and neuropeptide signatures for classification6-8 with the dynamic functional states, anatomic allocation, and allostatic plasticity of astrocytes1. Simplistically, therefore, astrocytes are still grouped as 'resting' vs. 'reactive', the latter referring to pathological states marked by various inducible genes3,9,10. Here, we introduced a machine learning-based feature recognition algorithm that benefits from the cumulative power of published single-cell RNA-seq data on astrocytes as a reference map to stepwise eliminate pleiotropic and inducible cellular features. For the healthy hypothalamus, this walk-back approach revealed gene regulatory networks (GRNs) that specified subsets of astrocytes, and could be used as landmarking tools for their anatomical assignment. The core molecular censuses retained by astrocyte subsets were sufficient to stratify them by allostatic competence, chiefly their signaling and metabolic interplay with neurons. Particularly, we found differentially expressed mitochondrial genes in insulin-sensing astrocytes and demonstrated their reciprocal signaling with neurons that work antagonistically within the food intake circuitry. As a proof-of-concept, we showed that disrupting Mfn2 expression in astrocytes reduced their ability to support dynamic circuit reorganization, a time-locked feature of satiety in the hypothalamus, thus leading to obesity in mice. Overall, our results suggest that astrocytes in the healthy brain are fundamentally more heterogeneous than previously thought and topologically mirror the specificity of local neurocircuits.

Pax protein depletion in proximal tubules triggers conserved mechanisms of resistance to acute ischemic kidney injury preventing transition to chronic kidney disease

Acute kidney injury (AKI) is a common condition that lacks effective treatments. In part, this shortcoming is due to an incomplete understanding of the genetic mechanisms that control pathogenesis and recovery. Identifying the molecular and genetic regulators unique to nephron segments that dictate vulnerability to injury and regenerative potential could lead to new therapeutic targets to treat ischemic kidney injury. Pax2 and Pax8 are homologous transcription factors with overlapping functions that are critical for kidney development and are re-activated in AKI. Here, we examined the role of Pax2 and Pax8 in recovery from ischemic AKI and found them upregulated after severe AKI and correlated with chronic injury. Surprisingly, proximal-tubule-selective deletion of Pax2 and Pax8 resulted in a less severe chronic injury phenotype. This effect was mediated by protection against the acute insult, similar to pre-conditioning. Prior to injury, Pax2 and Pax8 mutant mice develop a unique subpopulation of proximal tubule cells in the S3 segment that displayed features usually seen only in acute or chronic injury. The expression signature of these cells was strongly enriched with genes associated with other mechanisms of protection against ischemic AKI including caloric restriction, hypoxic pre-conditioning, and female sex. Thus, our results identified a novel role for Pax2 and Pax8 in mature proximal tubules that regulates critical genes and pathways involved in both the injury response and protection from ischemic AKI.

Mycobacterium tuberculosis resisters despite HIV exhibit activated T cells and macrophages in their pulmonary alveoli

To understand natural resistance to Mycobacterium tuberculosis ( Mtb ) infection, we studied people living with HIV (PLWH) in an area of high Mtb transmission. Given that alveolar leukocytes may contribute to this resistance, we performed single cell RNA-sequencing of bronchoalveolar lavage cells, unstimulated or ex vivo stimulated with Mtb . We obtained high quality cells for 7 participants who were TST & IGRA positive (called LTBI) and 6 who were persistently TST & IGRA negative (called resisters). Alveolar macrophages (AM) from resisters displayed more of an M1 phenotype relative to LTBI AM at baseline. Alveolar lymphocytosis (10%-60%) was exhibited by 5/6 resisters, resulting in higher numbers of CD4 + and CD8 + IFNG -expressing cells at baseline and upon Mtb challenge than LTBI samples. Mycobactericidal granulysin was expressed almost exclusively by a cluster of CD8 + T cells that co-expressed granzyme B, perforin and NK cell receptors. For resisters, these poly-cytotoxic T cells over-represented activating NK cell receptors and were present at 15-fold higher numbers in alveoli compared to LTBI. Altogether, our results showed that alveolar lymphocytosis, with increased numbers of alveolar IFNG -expressing cells and CD8 + poly-cytotoxic T cells, as well as activated AM were strongly associated with protection from persistent Mtb infection in PLWH.

Immuno-genomic analysis reveals eosinophilic feature and favorable prognosis of female non-smoking esophageal squamous cell carcinomas

Most of esophageal squamous cell carcinoma (ESCC) develop in smoking males in Japan, but the genomic etiology and immunological characteristics of rare non-smoking female ECSS remain unclear. To elucidate the genomic and immunological features of ESCC in non-smoking females, we analyzed whole-genome or transcriptome sequencing data from 94 ESCCs, including 20 rare non-smoking female cases. In addition, 31,611 immune cells were extracted from four ESCC tissues and subject to single-cell RNA-seq. We compared their immuno-genomic and microbiome profiles between non-smoking female and smoking ESCCs. Non-smoking females showed much better prognosis. Whole-genome sequencing analysis showed no significant differences in driver genes or copy number alterations depending on smoking status. The mutational signatures specifically observed in non-smoking females ESCC could be attributed to aging. Immune profiling from RNA-seq revealed that ESCC in non-smoking females had high tumor microenvironment signatures and a high abundance of eosinophils with a favorable prognosis. Single-cell RNA-sequencing of intratumor immune cells revealed gender differences of eosinophils and their activation in female cases. ESCCs in non-smoking females have age-related mutational signatures and gender-specific tumor immune environment with eosinophils, which is likely to contribute to their favorable prognosis.

Functional impairment of "helpless" CD8 + memory T cells is transient and driven by prolonged but finite cognate antigen presentation

Generation of functional CD8 + T cell memory typically requires engagement of CD4 + T cells. However, in certain scenarios, such as acutely-resolving viral infections, effector (T E ) and subsequent memory (T M ) CD8 + T cell formation appear impervious to a lack of CD4 + T cell help during priming. Nonetheless, such "helpless" CD8 + T M respond poorly to pathogen rechallenge. At present, the origin and long-term evolution of helpless CD8 + T cell memory remain incompletely understood. Here, we demonstrate that helpless CD8 + T E differentiation is largely normal but a multiplicity of helpless CD8 T M defects, consistent with impaired memory maturation, emerge as a consequence of prolonged yet finite exposure to cognate antigen. Importantly, these defects resolve over time leading to full restoration of CD8 + T M potential and recall capacity. Our findings provide a unified explanation for helpless CD8 + T cell memory and emphasize an unexpected CD8 + T M plasticity with implications for vaccination strategies and beyond.

LASSO regression shows histidine and sphingosine 1 phosphate are linked to both sepsis mortality and endothelial damage

Sepsis is a major cause of death worldwide, with a mortality rate that has remained stubbornly high. The current gold standard of risk stratifying sepsis patients provides limited mechanistic insight for therapeutic targeting. An improved ability to predict sepsis mortality and to understand the risk factors would allow better treatment targeting. Sepsis causes metabolic dysregulation in patients; therefore, metabolomics offers a promising tool to study sepsis. It is also known that that in sepsis endothelial cells affecting their function regarding blood clotting and vascular permeability. We integrated metabolomics data from patients admitted to an intensive care unit for sepsis, with commonly collected clinical features of their cases and two measures of endothelial function relevant to blood vessel function, platelet endothelial cell adhesion molecule and soluble thrombomodulin concentrations in plasma. We used least absolute shrinkage and selection operator penalized regression, and pathway enrichment analysis to identify features most able to predict 30-day survival. The features important to sepsis survival include carnitines, and amino acids. Endothelial proteins in plasma also predict 30-day mortality and the levels of these proteins also correlate with a somewhat overlapping set of metabolites. Overall metabolic dysregulation, particularly in endothelial cells, may be a contributory factor to sepsis response. By exploring sepsis metabolomics data in conjunction with clinical features and endothelial proteins we have gained a better understanding of sepsis risk factors.

Single-cell sequencing analysis within biologically relevant dimensions

The currently predominant approach to transcriptomic and epigenomic single-cell analysis depends on a rigid perspective constrained by reduced dimensions and algorithmically derived and annotated clusters. Here, we developed Seqtometry (sequencing-to-measurement), a single-cell analytical strategy based on biologically relevant dimensions enabled by advanced scoring with multiple gene sets (signatures) for examination of gene expression and accessibility across various organ systems. By utilizing information only in the form of specific signatures, Seqtometry bypasses unsupervised clustering and individual annotations of clusters. Instead, Seqtometry combines qualitative and quantitative cell-type identification with specific characterization of diverse biological processes under experimental or disease conditions. Comprehensive analysis by Seqtometry of various immune cells as well as other cells from different organs and disease-induced states, including multiple myeloma and Alzheimer's disease, surpasses corresponding cluster-based analytical output. We propose Seqtometry as a single-cell sequencing analysis approach applicable for both basic and clinical research.

Splicing neoantigen discovery with SNAF reveals shared targets for cancer immunotherapy

Immunotherapy has emerged as a crucial strategy to combat cancer by "reprogramming" a patient's own immune system. Although immunotherapy is typically reserved for patients with a high mutational burden, neoantigens produced from posttranscriptional regulation may provide an untapped reservoir of common immunogenic targets for new targeted therapies. To comprehensively define tumor-specific and likely immunogenic neoantigens from patient RNA-Seq, we developed Splicing Neo Antigen Finder (SNAF), an easy-to-use and open-source computational workflow to predict splicing-derived immunogenic MHC-bound peptides (T cell antigen) and unannotated transmembrane proteins with altered extracellular epitopes (B cell antigen). This workflow uses a highly accurate deep learning strategy for immunogenicity prediction (DeepImmuno) in conjunction with new algorithms to rank the tumor specificity of neoantigens (BayesTS) and to predict regulators of mis-splicing (RNA-SPRINT). T cell antigens from SNAF were frequently evidenced as HLA-presented peptides from mass spectrometry (MS) and predict response to immunotherapy in melanoma. Splicing neoantigen burden was attributed to coordinated splicing factor dysregulation. Shared splicing neoantigens were found in up to 90% of patients with melanoma, correlated to overall survival in multiple cancer cohorts, induced T cell reactivity, and were characterized by distinct cells of origin and amino acid preferences. In addition to T cell neoantigens, our B cell focused pipeline (SNAF-B) identified a new class of tumor-specific extracellular neoepitopes, which we termed ExNeoEpitopes. ExNeoEpitope full-length mRNA predictions were tumor specific and were validated using long-read isoform sequencing and in vitro transmembrane localization assays. Therefore, our systematic identification of splicing neoantigens revealed potential shared targets for therapy in heterogeneous cancers.

Genome scale CRISPR screens identify actin capping proteins as key modulators of therapeutic responses to radiation and immunotherapy

Radiotherapy (RT), is a fundamental treatment for malignant tumors and is used in over half of cancer patients. As radiation can promote anti-tumor immune effects, a promising therapeutic strategy is to combine radiation with immune checkpoint inhibitors (ICIs). However, the genetic determinants that impact therapeutic response in the context of combination therapy with radiation and ICI have not been systematically investigated. To unbiasedly identify the tumor intrinsic genetic factors governing such responses, we perform a set of genome-scale CRISPR screens in melanoma cells for cancer survival in response to low-dose genotoxic radiation treatment, in the context of CD8 T cell co-culture and with anti-PD1 checkpoint blockade antibody. Two actin capping proteins, Capza3 and Capg, emerge as top hits that upon inactivation promote the survival of melanoma cells in such settings. Capza3 and Capg knockouts (KOs) in mouse and human cancer cells display persistent DNA damage due to impaired homology directed repair (HDR); along with increased radiation, chemotherapy, and DNA repair inhibitor sensitivity. However, when cancer cells with these genes inactivated were exposed to sublethal radiation, inactivation of such actin capping protein promotes activation of the STING pathway, induction of inhibitory CEACAM1 ligand expression and resistance to CD8 T cell killing. Patient cancer genomics analysis reveals an increased mutational burden in patients with inactivating mutations in CAPG and/or CAPZA3, at levels comparable to other HDR associated genes. There is also a positive correlation between CAPG expression and activation of immune related pathways and CD8 T cell tumor infiltration. Our results unveil the critical roles of actin binding proteins for efficient HDR within cancer cells and demonstrate a previously unrecognized regulatory mechanism of therapeutic response to radiation and immunotherapy.

Compartments in medulloblastoma with extensive nodularity are connected through differentiation along the granular precursor lineage

Medulloblastomas with extensive nodularity are cerebellar tumors characterized by two distinct compartments and variable disease progression. The mechanisms governing the balance between proliferation and differentiation in MBEN remain poorly understood. Here, we employ a multi-modal single cell transcriptome analysis to dissect this process. In the internodular compartment, we identify proliferating cerebellar granular neuronal precursor-like malignant cells, along with stromal, vascular, and immune cells. In contrast, the nodular compartment comprises postmitotic, neuronally differentiated malignant cells. Both compartments are connected through an intermediate cell stage resembling actively migrating CGNPs. Notably, we also discover astrocytic-like malignant cells, found in proximity to migrating and differentiated cells at the transition zone between the two compartments. Our study sheds light on the spatial tissue organization and its link to the developmental trajectory, resulting in a more benign tumor phenotype. This integrative approach holds promise to explore intercompartmental interactions in other cancers with varying histology.

The landscape of SETBP1 gene expression and transcription factor activity across human tissues

The SET binding protein 1 (SETBP1) gene encodes a transcription factor (TF) involved in various cellular processes. Variants in SETBP1 can result in three different diseases determined by the introduction (germline vs. somatic) and location of the variant. Germline variants cause the ultra-rare pediatric Schinzel Giedion Syndrome (SGS) and SETBP1 haploinsufficiency disorder (SETBP1-HD), characterized by severe multisystemic abnormalities with neurodegeneration or a less severe brain phenotype accompanied by hypotonia and strabismus, respectively. Somatic variants in SETBP1 are associated with hematological malignancies and cancer development in other tissues in adults. To better understand the tissue-specific mechanisms involving SETBP1, we analyzed publicly available RNA-sequencing (RNA-seq) data from the Genotype-Tissue Expression (GTEx) project. We found SETBP1 and its known target genes were widely expressed across 31 adult human tissues. K-means clustering identified three distinct expression patterns of SETBP1 targets across tissues. Functional enrichment analysis (FEA) of each cluster revealed gene sets related to transcriptional regulation, DNA binding, and mitochondrial function. TF activity analysis of SETBP1 and its target TFs revealed tissue-specific TF activity, underscoring the role of tissue context-driven regulation and suggesting its impact in SETBP1-associated disease. In addition to uncovering tissue-specific molecular signatures of SETBP1 expression and TF activity, we provide a Shiny web application to facilitate exploring TF activity across human tissues for 758 TFs. This study provides insight into the landscape of SETBP1 expression and TF activity across 31 non-diseased human tissues and reveals tissue-specific expression and activity of SETBP1 and its targets. In conjunction with the web application we constructed, our framework enables researchers to generate hypotheses related to the role tissue backgrounds play with respect to gene expression and TF activity in different disease contexts.

Unveiling Anoikis-related genes: A breakthrough in the prognosis of bladder cancer

BACKGROUND

Bladder cancer (BLCA) is a prevalent malignancy worldwide. Anoikis remains a new form of cell death. It is necessary to explore Anoikis-related genes in the prognosis of BLCA.

METHODS

We obtained RNA expression profiles from the The Cancer Genome Atlas (TCGA) and Gene Expression Omnibus databases for dimensionality reduction analysis and isolated epithelial cells, T cells and fibroblasts for copy number variation analysis, pseudotime analysis and transcription factor analysis based on R package. We integrated machine-learning algorithms to develop the artificial intelligence-derived prognostic signature (AIDPS).

RESULTS

The performance of AIDPS with clinical indicators was stable and robust in predicting BLCA and showed better performance in every validation dataset compared to other models. Mendelian randomization analysis was conducted. Single nucleotide polymorphism (SNP) sites of rs3100578 (HK2) and rs66467677 (HSP90B1) exhibited significant correlation of bladder problem (not cancer) and bladder cancer, whereasSNP sites of rs3100578 (HK2) and rs947939 (BAD) had correlation between bladder stone and bladder cancer. The immune infiltration analysis of the TCGA-BLCA cohort was calculated via the ESTIMATE (i.e. Estimation of STromal and Immune cells in MAlignantTumours using Expression data) algorithm which contains stromal, immune and estimate scores. We also found significant differences in the IC50 values of Bortezomib_1191, Docetaxel_1007, Staurosporine_1034 and Rapamycin_1084 among the high- and low-risk groups.

CONCLUSIONS

In conclusion, these findings indicated Anoikis-related prognostic genes in BLCA and constructed an innovative machine-learning model of AIDPS with high prognostic value for BLCA.

Tissue-adjusted pathway analysis of cancer (TPAC): A novel approach for quantifying tumor-specific gene set dysregulation relative to normal tissue

We describe a novel single sample gene set testing method for cancer transcriptomics data named tissue-adjusted pathway analysis of cancer (TPAC). The TPAC method leverages information about the normal tissue-specificity of human genes to compute a robust multivariate distance score that quantifies gene set dysregulation in each profiled tumor. Because the null distribution of the TPAC scores has an accurate gamma approximation, both population and sample-level inference is supported. As we demonstrate through an analysis of gene expression data for 21 solid human cancers from The Cancer Genome Atlas (TCGA) and associated normal tissue expression data from the Human Protein Atlas (HPA), TPAC gene set scores are more strongly associated with patient prognosis than the scores generated by existing single sample gene set testing methods.

Single-cell transcriptomic profiling reveals a pathogenic role of cytotoxic CD4+ T cells in giant cell arteritis

Giant cell arteritis (GCA) is a systemic vasculitis mediated by an aberrant immunological response against the blood vessel wall. Although the pathogenic mechanisms that drive GCA have not yet been elucidated, there is strong evidence that CD4+ T cells are key drivers of the inflammatory process occurring in this vasculitis. The aim of this study was to further delineate the role of CD4+ T cells in GCA by applying single-cell RNA sequencing and T cell receptor (TCR) repertoire profiling to 114.799 circulating CD4+ T cells from eight GCA patients in two different clinical states, active and in remission, and eight healthy controls. Our results revealed an expansion of cytotoxic CD4+ T lymphocytes (CTLs) in active GCA patients, which expressed higher levels of cytotoxic and chemotactic genes when compared to patients in remission and controls. Accordingly, differentially expressed genes in CTLs of active patients were enriched in pathways related to granzyme-mediated apoptosis, inflammation, and the recruitment of different immune cells, suggesting a role of this cell type in the inflammatory and vascular remodelling processes occurring in GCA. CTLs also exhibited a higher clonal expansion in active patients with respect to those in remission. Drug repurposing analysis prioritized maraviroc, which targeted CTLs, as potentially repositionable for this vasculitis. In addition, effector regulatory T cells (Tregs) were decreased in GCA and showed lower expression of genes involved in their suppressive activity. These findings provide further insights into the pathogenic role of CD4+ T cells in GCA and suggest targeting CTLs as a potential therapeutic option.

Specifying cellular context of transcription factor regulons for exploring context-specific gene regulation programs

Understanding the role of transcription and transcription factors in cellular identity and disease, such as cancer and autoimmunity, is essential. However, comprehensive data resources for cell line-specific transcription factor-to-target gene annotations are currently limited. To address this, we developed a straightforward method to define regulons that capture the cell-specific aspects of TF binding and transcript expression levels. By integrating cellular transcriptome and transcription factor binding data, we generated regulons for four common cell lines comprising both proximal and distal cell line-specific regulatory events. Through systematic benchmarking involving transcription factor knockout experiments, we demonstrated performance on par with state-of-the-art methods, with our method being easily applicable to other cell types of interest. We present case studies using three cancer single-cell datasets to showcase the utility of these cell-type-specific regulons in exploring transcriptional dysregulation. In summary, this study provides a valuable tool and a resource for systematically exploring cell line-specific transcriptional regulations, emphasizing the utility of network analysis in deciphering disease mechanisms.

Definition of the Neurotoxicity-Associated Metabolic Signature Triggered by Berberine and Other Respiratory Chain Inhibitors

To characterize the hits from a phenotypic neurotoxicity screen, we obtained transcriptomics data for valinomycin, diethylstilbestrol, colchicine, rotenone, 1-methyl-4-phenylpyridinium (MPP), carbaryl and berberine (Ber). For all compounds, the concentration triggering neurite degeneration correlated with the onset of gene expression changes. The mechanistically diverse toxicants caused similar patterns of gene regulation: the responses were dominated by cell de-differentiation and a triggering of canonical stress response pathways driven by ATF4 and NRF2. To obtain more detailed and specific information on the modes-of-action, the effects on energy metabolism (respiration and glycolysis) were measured. Ber, rotenone and MPP inhibited the mitochondrial respiratory chain and they shared complex I as the target. This group of toxicants was further evaluated by metabolomics under experimental conditions that did not deplete ATP. Ber (204 changed metabolites) showed similar effects as MPP and rotenone. The overall metabolic situation was characterized by oxidative stress, an over-abundance of NADH (>1000% increase) and a re-routing of metabolism in order to dispose of the nitrogen resulting from increased amino acid turnover. This unique overall pattern led to the accumulation of metabolites known as biomarkers of neurodegeneration (saccharopine, aminoadipate and branched-chain ketoacids). These findings suggest that neurotoxicity of mitochondrial inhibitors may result from an ensemble of metabolic changes rather than from a simple ATP depletion. The combi-omics approach used here provided richer and more specific MoA data than the more common transcriptomics analysis alone. As Ber, a human drug and food supplement, mimicked closely the mode-of-action of known neurotoxicants, its potential hazard requires further investigation.

Single-cell Glycogenomics Deciphers Links Between Altered Transcriptional Regulation and Aberrant Glycosylation in Alzheimer's Disease

Glycosylation is increasingly recognized as a potential new therapeutic target in Alzheimer's disease. In recent years, evidence for Alzheimer's disease-specific glycoproteins has been established. However, the mechanisms of their dysregulation, including tissue and cell type specificity, are not fully understood. We aimed to explore upstream regulators of aberrant glycosylation by integrating multiple data sources and using a glycogenomics approach. We identified dysregulation by the glycosyltransferase PLOD3 in oligodendrocytes as an upstream regulator in cerebral vessels, and found that it is involved in COL4A5 synthesis, which is strongly correlated with amyloid fiber formation. Furthermore, COL4A5 was suggested to interact with astrocytes via ECM receptors as a ligand. This study suggests directions for new therapeutic strategies for Alzheimer's disease targeting glycosyltransferases.

Single nucleus RNA sequencing reveals glial cell type-specific responses to ischemic stroke

Reactive neuroglia critically shape the braińs response to ischemic stroke. However, their phenotypic heterogeneity impedes a holistic understanding of the cellular composition and microenvironment of the early ischemic lesion. Here we generated a single cell resolution transcriptomics dataset of the injured brain during the acute recovery from permanent middle cerebral artery occlusion. This approach unveiled infarction and subtype specific molecular signatures in oligodendrocyte lineage cells and astrocytes, which ranged among the most transcriptionally perturbed cell types in our dataset. Specifically, we characterized and compared infarction restricted proliferating oligodendrocyte precursor cells (OPCs), mature oligodendrocytes and heterogeneous reactive astrocyte populations. Our analyses unveiled unexpected commonalities in the transcriptional response of oligodendrocyte lineage cells and astrocytes to ischemic injury. Moreover, OPCs and reactive astrocytes were involved in a shared immuno-glial cross talk with stroke specific myeloid cells. In situ, osteopontin positive myeloid cells accumulated in close proximity to proliferating OPCs and reactive astrocytes, which expressed the osteopontin receptor CD44, within the perilesional zone specifically. In vitro, osteopontin increased the migratory capacity of OPCs. Collectively, our study highlights molecular cross talk events which might govern the cellular composition and microenvironment of infarcted brain tissue in the early stages of recovery.