Probes for INS

Non-neuronal responses in neurodegenerative disease have received increasing attention as important contributors to disease pathogenesis and progression. Here we utilize single-cell RNA sequencing to broadly profile 13 cell types in three different mouse models of Alzheimer disease (AD), capturing the effects of tau-only, amyloid-only, or combined tau-amyloid pathology. We highlight microglia, oligodendrocyte, astrocyte, and T cell responses and compare them across these models. Notably, we identify two distinct transcriptional states for oligodendrocytes emerging differentially across disease models, and we determine their spatial distribution. Furthermore, we explore the impact of Trem2 deletion in the context of combined pathology. Trem2 knockout mice exhibit severely blunted microglial responses to combined tau and amyloid pathology, but responses from non-microglial cell types (oligodendrocytes, astrocytes, and T cells) are relatively unchanged. These results delineate core transcriptional states that are engaged in response to AD pathology, and how they are influenced by a key AD risk gene, Trem2.

Smooth muscle cells (SMCs) execute important physiological functions in numerous vital organ systems, including the vascular, gastrointestinal, respiratory, and urogenital tracts. SMC differ morphologically and functionally at these different anatomical locations, but the molecular underpinnings of the differences remain poorly understood. Here, using deep single-cell RNA sequencing combined with in situ gene and protein expression analysis in four murine organs-heart, aorta, lung, and colon-we identify a molecular basis for high-level differences among vascular, visceral, and airway SMC, as well as more subtle differences between, for example, SMC in elastic and muscular arteries and zonation of elastic artery SMC along the direction of blood flow. Arterial SMC exhibit extensive organotypic heterogeneity, whereas venous SMC are similar across organs. We further identify a specific SMC subtype within the pulmonary vasculature. This comparative SMC cross-organ resource offers insight into SMC subtypes and their specific functions.

COVID-19-induced ‘acute respiratory distress syndrome’ (ARDS) is associated with prolonged respiratory failure and high mortality, but the mechanistic basis of lung injury remains incompletely understood. Here, we analyzed pulmonary immune responses and lung pathology in two cohorts of patients with COVID-19 ARDS using functional single cell genomics, immunohistology and electron microscopy. We describe an accumulation of CD163-expressing monocyte-derived macrophages that acquired a profibrotic transcriptional phenotype during COVID-19 ARDS. Gene set enrichment and computational data integration revealed a significant similarity between COVID-19-associated macrophages and profibrotic macrophage populations identified in idiopathic pulmonary fibrosis. COVID-19 ARDS was associated with clinical, radiographic, histopathological, and ultrastructural hallmarks of pulmonary fibrosis. Exposure of human monocytes to SARS-CoV-2, but not Influenza A virus or viral RNA analogs, was sufficient to induce a similar profibrotic phenotype in vitro. In conclusion, we demonstrate that SARS-CoV-2 triggers profibrotic macrophage responses and pronounced fibroproliferative ARDS.

BackgroundPancreatic ductal adenocarcinoma (PDAC) is an aggressive cancer with short overall survival; the standard of care (SoC) is chemotherapy. Immunotherapies in development aim to remodel the stroma by depleting immunosuppressive cell types or using T-cell redirection to kill tumor cells. To date, none of these methods have improved overall survival beyond SoC. Next generation immunotherapies that employ histopathology and molecular subtyping1 for target and patient selection may succeed. Here we leverage a spatial transcriptomics platform (Nanostring Digital Spatial Profiling, DSP) to reveal molecular signaling in tumoral and stromal cells in 57 PDAC patients using tumor microarrays (TMAs). This approach is rapid and clinically relevant as molecular and histology data can be easily bridged.MethodsTMAs generated from surgical resection tissue were commercially sourced. DSP was performed using the CTA RNA panel (1,800 target genes) using PanCK fluorescence for tumor/stroma segmentation. In parallel, slides were chromogenically stained for T-cells (CD3) and macrophages (CD68/CD163). Differential gene expression, gene signature and gene co-expression network analysis was performed using linear models in R.2 3ResultsDifferential gene expression analysis and correlation to IHC confirmed the DSP platform successfully profiled tumor and stromal compartments (figure 1). Immune cell signatures4 and pathway analysis revealed a heterogenous stromal environment. Using a fibroblast gene signature derived from single-cell RNAseq5 we found fibroblast density was positively correlated to PDGFR signaling and MHC-II expression but negatively correlated to B, CD4+ T and neutrophil cell levels (figure 2a). This finding supports the idea that atypical antigen presentation in cancer associated fibroblasts (CAFs) may be exploitable for immunotherapies.6 We constructed a co-expression network from in-situ stromal gene expression and used it to identify receptors coordinately expressed with the immunosuppressive macrophage marker CSF1R as a bispecific antibody partner (figure 2b).7 Classical macrophage markers were identified but also receptors with lesser-known functions in macrophages (TIM3/HAVCR2, FPR3, MS4A6A, LILRB4). Surveying target pairs in this method allows rapid, patient-specific confirmation in serial TMA sections with singleplex IHC or RNAscope.Abstact 928 Figure 1Segmentation strategy and validation of DSP (A) PanCK, CD68 and CD3 staining from two representative tumor cores; (B, C) correlation of gene transcripts in stroma to cell counts from chromogenic staining; (D) heatmap of selected genes differentially expressed in tumor and stroma (n=57 patients).Abstract 928 Figure 2Exploration of the stromal compartment in PDAC TMAs. (A) Heatmap of selected cell type and gene signatures from gene expression in the stroma, color represents single sample enrichment score using GSVA method; (B) a gene co-expression subnetwork in the stroma centered on CSF1R, edge thickness represents strength of correlation, green nodes have evidence for cell surface expression based on proteomic profiling.7ConclusionsIn this study we were able to recapitulate known PDAC biology using very small samples of primary tumors. The combination of TMAs and DSP enables a rapid validation of targets and hypothesis generation for bispecific parings. Further analysis of untreated (n=14) and post-adjuvant chemotherapy (n=26) patients using RNA DSP, IHC and bulk RNAseq is under way. Results from this cohort will enable an integrated histopathology and molecular approach to developing next-generation immunotherapies.ReferencesCollisson EA, Bailey P, Chang DK, Biankin AV. Molecular subtypes of pancreatic cancer. Nat Rev Gastroenterol Hepatol 2019 April;16(4):207-220.Ritchie ME, Phipson B, Wu D, Hu Y, Law CW, Shi W, Smyth GK (2015). “limma powers differential expression analyses for RNA-sequencing and microarray studies.” Nucleic Acids Research 43(7):e47.Hänzelmann S, Castelo R, Guinney J (2013). “GSVA: gene set variation analysis for microarray and RNA-Seq data.” BMC Bioinformatics 14,7.Charoentong P, Finotello F, Angelova M, Mayer C, Efremova M, Rieder D, Hackl H, Trajanoski Z. Pan-cancer immunogenomic analyses reveal genotype-immunophenotype relationships and predictors of response to checkpoint blockade. Cell Rep 2017 January 3;18(1):248-262.Tirosh I, Izar B, Prakadan SM, Wadsworth MH 2nd, Treacy D, Trombetta JJ, Rotem A, Rodman C, Lian C, Murphy G, Fallahi-Sichani M, Dutton-Regester K, Lin JR, Cohen O, Shah P, Lu D, Genshaft AS, Hughes TK, Ziegler CG, Kazer SW, Gaillard A, Kolb KE, Villani AC, Johannessen CM, Andreev AY, Van Allen EM, Bertagnolli M, Sorger PK, Sullivan RJ, Flaherty KT, Frederick DT, Jané-Valbuena J, Yoon CH, Rozenblatt-Rosen O, Shalek AK, Regev A, Garraway LA. Dissecting the multicellular ecosystem of metastatic melanoma by single-cell RNA-seq. Science 2016 April 8;352(6282):189-96.Elyada E, Bolisetty M, Laise P, Flynn WF, Courtois ET, Burkhart RA, Teinor JA, Belleau P, Biffi G, Lucito MS, Sivajothi S, Armstrong TD, Engle DD, Yu KH, Hao Y, Wolfgang CL, Park Y, Preall J, Jaffee EM, Califano A, Robson P, Tuveson DA. Cross-species single-cell analysis of pancreatic ductal adenocarcinoma reveals antigen-presenting cancer-associated fibroblasts. Cancer Discov 2019 August;9(8):1102-1123. Bausch-Fluck D, Hofmann A, Bock T, Frei AP, Cerciello F, Jacobs A, Moest H, Omasits U, Gundry RL, Yoon C, Schiess R, Schmidt A, Mirkowska P, Härtlová A, Van Eyk JE, Bourquin JP, Aebersold R, Boheler KR, Zandstra P, Wollscheid B. A mass spectrometric-derived cell surface protein atlas. PLoS One 2015 April 20;10(3):e0121314.Ethics ApprovalSpecimens were harvested from unused tissue after a surgical tumor resection procedure. A discrete legal consent form from both hospital and individuals was obtained by the commercial tissue vendor BioMax US for all samples analyzed in this abstract. All human tissues are collected under HIPPA approved protocols.ConsentWritten informed consent was obtained from the patient for publication of this abstract and any accompanying images. A copy of the written consent is available for review by the Editor of this journal.

Pressure overload induces a transition from cardiac hypertrophy to heart failure, but its underlying mechanisms remain elusive. Here we reconstruct a trajectory of cardiomyocyte remodeling and clarify distinct cardiomyocyte gene programs encoding morphological and functional signatures in cardiac hypertrophy and failure, by integrating single-cardiomyocyte transcriptome with cell morphology, epigenomic state and heart function. During early hypertrophy, cardiomyocytes activate mitochondrial translation/metabolism genes, whose expression is correlated with cell size and linked to ERK1/2 and NRF1/2 transcriptional networks. Persistent overload leads to a bifurcation into adaptive and failing cardiomyocytes, and p53 signaling is specifically activated in late hypertrophy. Cardiomyocyte-specific p53 deletion shows that cardiomyocyte remodeling is initiated by p53-independent mitochondrial activation and morphological hypertrophy, followed by p53-dependent mitochondrial inhibition, morphological elongation, and heart failure gene program activation. Human single-cardiomyocyte analysis validates the conservation of the pathogenic transcriptional signatures. Collectively, cardiomyocyte identity is encoded in transcriptional programs that orchestrate morphological and functional phenotypes.

Glioblastomas are aggressive brain tumors that are largely immunotherapy resistant. This is associated with immunosuppression and a dysfunctional tumor vasculature, which hinder T cell infiltration. LIGHT/TNFSF14 can induce high endothelial venules (HEVs) and tertiary lymphoid structures (TLS), suggesting that its therapeutic expression could promote T cell recruitment. Here, we use a brain endothelial cell-targeted adeno-associated viral (AAV) vector to express LIGHT in the glioma vasculature (AAV-LIGHT). We found that systemic AAV-LIGHT treatment induces tumor-associated HEVs and T cell-rich TLS, prolonging survival in αPD-1-resistant murine glioma. AAV-LIGHT treatment reduces T cell exhaustion and promotes TCF1+CD8+ stem-like T cells, which reside in TLS and intratumoral antigen-presenting niches. Tumor regression upon AAV-LIGHT therapy correlates with tumor-specific cytotoxic/memory T cell responses. Our work reveals that altering vascular phenotype through vessel-targeted expression of LIGHT promotes efficient anti-tumor T cell responses and prolongs survival in glioma. These findings have broader implications for treatment of other immunotherapy-resistant cancers.

Nonalcoholic fatty liver disease (NAFLD) is a global health-care problem with limited therapeutic options. To obtain a cellular resolution of pathogenesis, 82,168 single-cell transcriptomes (scRNA-seq) across different NAFLD stages were profiled, identifying hepatocytes and 12 other non-parenchymal cell (NPC) types. scRNA-seq revealed insights into the cellular and molecular mechanisms of the disease. We discovered a dual role for hepatic stellate cells in gene expression regulation and in the potential to trans-differentiate into myofibroblasts. We uncovered distinct expression profiles of Kupffer cells versus monocyte-derived macrophages during NAFLD progression. Kupffer cells showed stronger immune responses, while monocyte-derived macrophages demonstrated a capability for differentiation. Three chimeric NPCs were identified including endothelial-chimeric stellate cells, hepatocyte-chimeric endothelial cells, and endothelial-chimeric Kupffer cells. Our work identified unanticipated aspects of mouse with NAFLD at the single-cell level and advanced the understanding of cellular heterogeneity in NAFLD livers.

Astrocytes are vital support cells that ensure proper brain function. In brain disease, astrocytes reprogram into a reactive state that alters many of their cellular roles. A long-standing question in the field is whether downregulation of reactive astrocyte (RA) markers during resolution of inflammation is because these astrocytes revert back to a non-reactive state or die and are replaced. This has proven difficult to answer mainly because existing genetic tools cannot distinguish between healthy versus RAs. Here we describe the generation of an inducible genetic tool that can be used to specifically target and label a subset of RAs. Longitudinal analysis of an acute inflammation model using this tool revealed that the previously observed downregulation of RA markers after inflammation is likely due to changes in gene expression and not because of cell death. Our findings suggest that cellular changes associated with astrogliosis after acute inflammation are largely reversible.