Immune checkpoint therapy with anti-CTLA-4 and anti-PD-1/PD-L1 has revolutionized the treatment of many solid tumors. However, the clinical efficacy of immune checkpoint therapy is limited to a ...subset of patients with specific tumor types
. Multiple clinical trials with combinatorial immune checkpoint strategies are ongoing; however, the mechanistic rationale for tumor-specific targeting of immune checkpoints is elusive. To garner an insight into tumor-specific immunomodulatory targets, we analyzed 94 patients representing five different cancer types, including those that respond relatively well to immune checkpoint therapy and those that do not, such as glioblastoma multiforme, prostate cancer and colorectal cancer. Through mass cytometry and single-cell RNA sequencing, we identified a unique population of CD73
macrophages in glioblastoma multiforme that persists after anti-PD-1 treatment. To test if targeting CD73 would be important for a successful combination strategy in glioblastoma multiforme, we performed reverse translational studies using CD73
mice. We found that the absence of CD73 improved survival in a murine model of glioblastoma multiforme treated with anti-CTLA-4 and anti-PD-1. Our data identified CD73 as a specific immunotherapeutic target to improve antitumor immune responses to immune checkpoint therapy in glioblastoma multiforme and demonstrate that comprehensive human and reverse translational studies can be used for rational design of combinatorial immune checkpoint strategies.
There is pressing urgency to understand the pathogenesis of the severe acute respiratory syndrome coronavirus clade 2 (SARS-CoV-2), which causes the disease COVID-19. SARS-CoV-2 spike (S) protein ...binds angiotensin-converting enzyme 2 (ACE2), and in concert with host proteases, principally transmembrane serine protease 2 (TMPRSS2), promotes cellular entry. The cell subsets targeted by SARS-CoV-2 in host tissues and the factors that regulate ACE2 expression remain unknown. Here, we leverage human, non-human primate, and mouse single-cell RNA-sequencing (scRNA-seq) datasets across health and disease to uncover putative targets of SARS-CoV-2 among tissue-resident cell subsets. We identify ACE2 and TMPRSS2 co-expressing cells within lung type II pneumocytes, ileal absorptive enterocytes, and nasal goblet secretory cells. Strikingly, we discovered that ACE2 is a human interferon-stimulated gene (ISG) in vitro using airway epithelial cells and extend our findings to in vivo viral infections. Our data suggest that SARS-CoV-2 could exploit species-specific interferon-driven upregulation of ACE2, a tissue-protective mediator during lung injury, to enhance infection.
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•Meta-analysis of human, non-human primate, and mouse single-cell RNA-seq datasets for putative SARS-CoV-2 targets•Type II pneumocytes, nasal secretory cells, and absorptive enterocytes are ACE2+TMPRSS2+•Interferon and influenza increase ACE2 in human nasal epithelia and lung tissue•Mouse Ace2 is not upregulated by interferon, raising implications for disease modeling
Analysis of single-cell RNA-seq datasets from human, non-human primate, and mouse barrier tissues identifies putative cellular targets of SARS-CoV-2 on the basis of ACE2 and TMPRSS2 expression. ACE2 represents a previously unappreciated interferon-stimulated gene in human, but not mouse, epithelial tissues, identifying anti-viral induction of a host tissue-protective mechanism, but also a potential means for viral exploitation of the host response.
An accurate dissection of sources of cell-to-cell variability is crucial for quantitative biology at the single-cell level but has been challenging for the cell cycle. We present Cycler, a robust ...method that constructs a continuous trajectory of cell-cycle progression from images of fixed cells. Cycler handles heterogeneous microenvironments and does not require perturbations or genetic markers, making it generally applicable to quantifying multiple sources of cell-to-cell variability in mammalian cells.
Chromosomal instability is a hallmark of cancer that results from ongoing errors in chromosome segregation during mitosis. Although chromosomal instability is a major driver of tumour evolution, its ...role in metastasis has not been established. Here we show that chromosomal instability promotes metastasis by sustaining a tumour cell-autonomous response to cytosolic DNA. Errors in chromosome segregation create a preponderance of micronuclei whose rupture spills genomic DNA into the cytosol. This leads to the activation of the cGAS-STING (cyclic GMP-AMP synthase-stimulator of interferon genes) cytosolic DNA-sensing pathway and downstream noncanonical NF-κB signalling. Genetic suppression of chromosomal instability markedly delays metastasis even in highly aneuploid tumour models, whereas continuous chromosome segregation errors promote cellular invasion and metastasis in a STING-dependent manner. By subverting lethal epithelial responses to cytosolic DNA, chromosomally unstable tumour cells co-opt chronic activation of innate immune pathways to spread to distant organs.
Small cell lung cancer (SCLC) is an aggressive malignancy that includes subtypes defined by differential expression of ASCL1, NEUROD1, and POU2F3 (SCLC-A, -N, and -P, respectively). To define the ...heterogeneity of tumors and their associated microenvironments across subtypes, we sequenced 155,098 transcriptomes from 21 human biospecimens, including 54,523 SCLC transcriptomes. We observe greater tumor diversity in SCLC than lung adenocarcinoma, driven by canonical, intermediate, and admixed subtypes. We discover a PLCG2-high SCLC phenotype with stem-like, pro-metastatic features that recurs across subtypes and predicts worse overall survival. SCLC exhibits greater immune sequestration and less immune infiltration than lung adenocarcinoma, and SCLC-N shows less immune infiltrate and greater T cell dysfunction than SCLC-A. We identify a profibrotic, immunosuppressive monocyte/macrophage population in SCLC tumors that is particularly associated with the recurrent, PLCG2-high subpopulation.
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•Most small cell lung cancer (SCLC) tumors share a small PLCG2-high subpopulation•This PLCG2-high SCLC subpopulation is linked to metastasis and poor prognosis•SCLC is enriched in profibrotic and immunosuppressive monocytes/macrophages•The presence of myeloid cells is associated with the PLCG2-high SCLC subpopulation
Chan et al. use single-cell transcriptome sequencing and imaging techniques to study the heterogeneity and tumor microenvironment of clinical small cell lung cancer specimens. This analysis identifies a PLCG2-high-expressing subpopulation linked to metastasis and poor prognosis, and an enrichment of a monocyte/macrophage population with a profibrotic, immunosuppressive phenotype.
Temporal resolution of cellular features associated with a severe COVID-19 disease trajectory is needed for understanding skewed immune responses and defining predictors of outcome. Here, we ...performed a longitudinal multi-omics study using a two-center cohort of 14 patients. We analyzed the bulk transcriptome, bulk DNA methylome, and single-cell transcriptome (>358,000 cells, including BCR profiles) of peripheral blood samples harvested from up to 5 time points. Validation was performed in two independent cohorts of COVID-19 patients. Severe COVID-19 was characterized by an increase of proliferating, metabolically hyperactive plasmablasts. Coinciding with critical illness, we also identified an expansion of interferon-activated circulating megakaryocytes and increased erythropoiesis with features of hypoxic signaling. Megakaryocyte- and erythroid-cell-derived co-expression modules were predictive of fatal disease outcome. The study demonstrates broad cellular effects of SARS-CoV-2 infection beyond adaptive immune cells and provides an entry point toward developing biomarkers and targeted treatments of patients with COVID-19.
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•SARS-CoV2 infection elicits dynamic changes of circulating cells in the blood•Severe COVID-19 is characterized by increased metabolically active plasmablasts•Elevation of IFN-activated megakaryocytes and erythroid cells in severe COVID-19•Cell-type-specific expression signatures are associated with a fatal COVID-19 outcome
Bernardes et al. explore COVID-19 disease trajectories by performing longitudinal multi-omics analyses in peripheral blood samples from hospitalized patients. The analyses identify increased numbers of plasmablasts, interferon-activated megakaryocytes, and erythroid cells as hallmarks of severe disease and define molecular signatures linked to a fatal COVID-19 disease outcome.
Systematic characterization of cancer genomes has revealed a staggering number of diverse aberrations that differ among individuals, such that the functional importance and physiological impact of ...most tumor genetic alterations remain poorly defined. We developed a computational framework that integrates chromosomal copy number and gene expression data for detecting aberrations that promote cancer progression. We demonstrate the utility of this framework using a melanoma data set. Our analysis correctly identified known drivers of melanoma and predicted multiple tumor dependencies. Two dependencies,
TBC1D16 and
RAB27A, confirmed empirically, suggest that abnormal regulation of protein trafficking contributes to proliferation in melanoma. Together, these results demonstrate the ability of integrative Bayesian approaches to identify candidate drivers with biological, and possibly therapeutic, importance in cancer.
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► Genetic aberrations and phenotypic signature together identify drivers and their roles ► Expression of a driver, not its copy number, drives phenotype ►
TBC1D16 and
RAB27A, vesicular trafficking genes, are dependencies in melanoma
Transcriptional regulators, including the cohesin complex member STAG2, are recurrently mutated in cancer. The role of STAG2 in gene regulation, hematopoiesis, and tumor suppression remains ...unresolved. We show that Stag2 deletion in hematopoietic stem and progenitor cells (HSPCs) results in altered hematopoietic function, increased self-renewal, and impaired differentiation. Chromatin immunoprecipitation (ChIP) sequencing revealed that, although Stag2 and Stag1 bind a shared set of genomic loci, a component of Stag2 binding sites is unoccupied by Stag1, even in Stag2-deficient HSPCs. Although concurrent loss of Stag2 and Stag1 abrogated hematopoiesis, Stag2 loss alone decreased chromatin accessibility and transcription of lineage-specification genes, including Ebf1 and Pax5, leading to increased self-renewal and reduced HSPC commitment to the B cell lineage. Our data illustrate a role for Stag2 in transformation and transcriptional dysregulation distinct from its shared role with Stag1 in chromosomal segregation.
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•Hematopoietic Stag2 loss enhances stem cell self-renewal and impairs differentiation•Stag1 can maintain TAD boundary integrity in the absence of Stag2•Stag2 is required for intra-TAD interactions at lineage genes (e.g., PU.1 targets)•Stag2 target expression, but not PU.1 overexpression, restores B cell differentiation
In murine hematopoietic Stag2 deletion, Stag1 rescues topologically associated domains in the absence of Stag2 but cannot restore the chromatin architecture required for hematopoietic lineage commitment. PU.1 target genes lose accessibility and expression. Induced target gene expression, but not PU.1 overexpression, is sufficient to restore differentiation in the altered chromatin state.
Cellular regulatory networks are not static, but continuously reconfigure in response to stimuli via alterations in protein abundance and confirmation. However, typical computational approaches treat ...them as static interaction networks derived from a single time point. Here, we provide methods for learning the dynamic modulation of relationships between proteins from static single-cell data. We demonstrate our approach using TGFß induced epithelial-to-mesenchymal transition (EMT) in murine breast cancer cell line, profiled with mass cytometry. We take advantage of the asynchronous rate of transition to EMT in the data and derive a pseudotime EMT trajectory. We propose methods for visualizing and quantifying time-varying edge behavior over the trajectory, and a metric of edge dynamism to predict the effect of drug perturbations on EMT.
We present a method that harnesses massively parallel DNA synthesis and sequencing for the high-throughput functional analysis of regulatory sequences at single-nucleotide resolution. As a proof of ...concept, we quantitatively assayed the effects of all possible single-nucleotide mutations for three bacteriophage promoters and three mammalian core promoters in a single experiment per promoter. The method may also serve as a rapid screening tool for regulatory element engineering in synthetic biology.
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