Search

Background: Endocrine therapy (ET) is the mainstay of ER+ BC treatment. However; up to 20% of ER+ BC tumors progress into metastatic disease and develop ET resistance, underscoring the need for combination therapies. Preclinical data suggest that combining phosphatidylinositol 3-kinase (PI3K) inhibitors with ET may overcome resistance. OPPORTUNE, a preoperative phase II window trial, evaluated whether the combination of the PI3K inhibitor pictilisib with anastrozole (PIC+ANA) can increase the antitumor effect of ANA in newly diagnosed operable ER+ BC. Early results showed greater suppression of tumor Ki67 in patients treated with PIC+ANA versus ANA alone. Here, we present gene expression analysis from tumors collected pre- and post-treatment, and their associations with Ki67 outcomes. Methods: Postmenopausal women with newly diagnosed operable ER+/HER2-negative BC were randomly allocated (2:1, favoring the combination) to 2 weeks of preoperative treatment with ANA 1 mg once per day (n = 47) or the combination of ANA 1 mg with PIC 260 mg once per day (n = 89). The primary end point was inhibition of tumor cell proliferation measured by change in Ki67 protein expression via IHC between tumor samples taken pre- and post-treatment. Samples were analyzed by RNA-sequencing—ER pathway activity, PAM50 intrinsic subtypes, and pathway analyses were assessed by Ki67 outcomes. Elastic net regression analysis and transcription factor activity inference with Dorothea were performed to identify features strongly associated with Ki67 outcomes. Results: 124 patients (ANA, n=43; PIC+ANA, n=81) had paired tumor samples at baseline/week 2 that were evaluable for both Ki67 and RNA-seq. PIC+ANA showed improved suppression of Ki67 compared to ANA alone (-83.78% vs -73.85%, p=0.012) and a greater proportion of patients achieved complete cell cycle arrest (CCCA, as defined by Ki67< 2.7%) in the PIC+ANA arm (45.68% vs 36.59%). ER pathway activity suppression was comparable between treatments. PAM50 classification based on RNA-seq showed that 83.0% of tumors were luminal (Lum) A at baseline and 12.9% were LumB, with the remainder being classified as Normal-like. PIC+ANA showed greater suppression of Ki67 in LumB tumors compared to LumA (-92.29% vs -81.62%). This effect was much greater in the PIC+ANA arm compared to LumB tumors treated with ANA alone (-92.29% vs -37.87%); however, given the low number of LumB tumors in the ANA arm (n=3), we could not determine statistical significance. Bioinformatic analysis of RNA-seq from baseline specimens showed that MYBL2 activity was associated with resistance to ANA (as defined by Ki67≥7.5% at week2). Tumors in the top quartile of MYBL2 activity at baseline showed improved Ki67 outcomes in the PIC+ANA arm compared to ANA alone (-91.71% vs -51.44%), while no differences were observed between treatments for tumors with lower MYBL2 activity (-79.16% vs -76.72%). Single-nucleus (sn)-RNA-seq from untreated ER+ BC tumors showed that MYBL2 was enriched in a single cluster of tumor cells, which also had the highest expression of a subset of actionable targets (including CDK1, CDK2, CDK4, EZH2, and AKT1), as compared to other tumor cells. Expression data from DepMap and drug-sensitivity data from ER+ BC cell lines show a positive trend between high MYBL2 expression and sensitivity to the ER degrader, giredestrant. Conclusions: PIC exhibited greater antiproliferative effects in combination with ANA in ER+/HER2- early BC compared to ANA alone, particularly in LumB and MYBL2-high tumors. Furthermore, the transcriptional profile and in vitro response of tumor cells with high MYBL2 expression suggest potential sensitivity to other combination therapies. Citation Format: Alejandro Martinez Chibly, Alice Shia, Radia Johnson, Michael S. Hwang, Marc Hafner, Ciara Metcalfe, Kalpit Shah, Michal Slyper, Chris Bolen, Sarah E. Pinder, Alastair M. Thompson, Steven Gendreau, Peter Schmid. PD10-06 Clinical outcomes and exploratory gene expression analysis of OPPORTUNE: a phase II window-of-opportunity study to evaluate pictilisib+anastrozole versus anastrozole alone in ER-positive breast cancer [abstract]. In: Proceedings of the 2022 San Antonio Breast Cancer Symposium; 2022 Dec 6-10; San Antonio, TX. Philadelphia (PA): AACR; Cancer Res 2023;83(5 Suppl):Abstract nr PD10-06.

PDF file - 168K

PDF file - 9.8MB, Supplementary Figure S1. TCF3 expression levels in breast cancer cell lines. Supplementary Figure S2. Effects of TCF3 on cell proliferation, apoptosis and tumor growth. Supplementary Figure S3. TCF3 induces changes in the expression of EMT-associated genes. Supplementary Figure S4. Gene expression changes in TCF3-silenced cells. Supplementary Figure S5. Wnt-related gene expression changes in TCF3 silenced cells. Supplementary Figure S6. Inducible Tcf3 transgenic mice. Supplementary Figure S7. Tcf3 inhibition of ductal growth is reversible. Supplementary Figure S8. Tcf3 induces EMT-associated genes in the mouse mammary gland

PDF file - 33K, Wnt-responsive genes

Solid tumors are spatially heterogeneous in their genetic, molecular and cellular composition, and this variation can be meaningful for diagnosis, prognosis and therapy. Recent spatial profiling studies have mostly charted genetic and RNA variation in tumors separately. To leverage the potential of RNA to identify copy number alterations (CNAs), we developed SlideCNA, a computational tool to extract sparse spatial CNA signals from spatial transcriptomics data, using expression-aware spatial binning. We test SlideCNA on simulated and real Slide-seq data of metastatic breast cancer (MBC) and demonstrate its potential for spatial sub-clone detection.

The molecular underpinnings of organ dysfunction in acute COVID-19 and its potential long-term sequelae are under intense investigation. To shed light on these in the context of liver function, we performed single-nucleus RNA-seq and spatial transcriptomic profiling of livers from 17 COVID-19 decedents. We identified hepatocytes positive for SARS-CoV-2 RNA with an expression phenotype resembling infected lung epithelial cells. Integrated analysis and comparisons with healthy controls revealed extensive changes in the cellular composition and expression states in COVID-19 liver, reflecting hepatocellular injury, ductular reaction, pathologic vascular expansion, and fibrogenesis. We also observed Kupffer cell proliferation and erythrocyte progenitors for the first time in a human liver single-cell atlas, resembling similar responses in liver injury in mice and in sepsis, respectively. Despite the absence of a clinical acute liver injury phenotype, endothelial cell composition was dramatically impacted in COVID-19, concomitantly with extensive alterations and profibrogenic activation of reactive cholangiocytes and mesenchymal cells. Our atlas provides novel insights into liver physiology and pathology in COVID-19 and forms a foundational resource for its investigation and understanding.

Understanding gene function and regulation in homeostasis and disease requires knowledge of the cellular and tissue contexts in which genes are expressed. Here, we applied four single-nucleus RNA sequencing methods to eight diverse, archived, frozen tissue types from 16 donors and 25 samples, generating a cross-tissue atlas of 209,126 nuclei profiles, which we integrated across tissues, donors, and laboratory methods with a conditional variational autoencoder. Using the resulting cross-tissue atlas, we highlight shared and tissue-specific features of tissue-resident cell populations; identify cell types that might contribute to neuromuscular, metabolic, and immune components of monogenic diseases and the biological processes involved in their pathology; and determine cell types and gene modules that might underlie disease mechanisms for complex traits analyzed by genome-wide association studies.

Systemic lupus erythematosus (SLE) is a heterogeneous autoimmune disease. Knowledge of circulating immune cell types and states associated with SLE remains incomplete. We profiled more than 1.2 million peripheral blood mononuclear cells (162 cases, 99 controls) with multiplexed single-cell RNA sequencing (mux-seq). Cases exhibited elevated expression of type 1 interferon–stimulated genes (ISGs) in monocytes, reduction of naïve CD4(+) T cells that correlated with monocyte ISG expression, and expansion of repertoire-restricted cytotoxic GZMH(+) CD8(+) T cells. Cell type–specific expression features predicted case-control status and stratified patients into two molecular subtypes. We integrated dense genotyping data to map cell type–specific cis–expression quantitative trait loci and to link SLE-associated variants to cell type–specific expression. These results demonstrate mux-seq as a systematic approach to characterize cellular composition, identify transcriptional signatures, and annotate genetic variants associated with SLE. INTRODUCTION: Systemic lupus erythematosus (SLE) is a heterogeneous autoimmune disease with elevated prevalence in women and individuals of Asian, African, and Hispanic ancestry. Bulk transcriptomic profiling has implicated increased type 1 interferon signaling, dysregulated lymphocyte activation, and failure of apoptotic clearance as hallmarks of disease. Many genes participating in these processes are proximal to the ~100 loci associated with SLE. Despite this progress, a comprehensive census of circulating immune cells in SLE remains incomplete, and annotating the cell types and contexts that mediate genetic associations remains challenging. RATIONALE: Historically, flow cytometry and bulk transcriptomic analyses were used to profile the composition and gene expression of circulating immune cells in SLE. However, flow cytometry is biased by its use of a limited set of known markers, whereas bulk transcriptomic profiling does not have sufficient power to detect cell type–specific expression differences. Single-cell RNA sequencing (scRNA-seq) of peripheral blood mononuclear cells (PBMCs) holds potential as a comprehensive and unbiased approach to simultaneously profile the composition and transcriptional states of circulating immune cells. However, application of scRNA-seq to population cohorts has been limited by sample throughput, cost, and susceptibility to technical variability. To overcome these limitations, we previously developed multiplexed scRNA-seq (mux-seq) to enable systematic and cost-effective scRNA-seq of population cohorts. RESULTS: We used mux-seq to profile more than 1.2 million PBMCs from 162 SLE cases and 99 healthy controls of either Asian or European ancestry. SLE cases exhibited differences in both the composition and state of PBMCs. Analysis of lymphocyte composition revealed a reduction in naïve CD4(+) T cells and an increase in repertoire-restricted GZMH(+) CD8(+) T cells. Analysis of transcriptomic profiles across eight cell types revealed that classical monocytes expressed the highest levels of both pan–cell type and myeloid-specific type 1 interferon-stimulated genes (ISGs). The expression of ISGs in monocytes was inversely correlated with naïve CD4(+) T cell abundance. Cell type–specific expression features accurately predicted case-control status and stratified patients into molecular subtypes. By integrating genotyping data and using a novel matrix decomposition method, we mapped shared and cell type–specific cis–expression quantitative trait loci (cis-eQTLs) across eight cell types. Cell type–specific cis-eQTLs were enriched for regions of open chromatin specific to the same or related cell types. Joint analysis of cis-eQTLs and genome-wide association study results enabled identification of cell types relevant to immune-mediated diseases, fine-mapping of disease-associated loci, and discovery of novel SLE associations. Interaction analysis identified variants whose effects on gene expression are further modified by interferon activation across patients. CONCLUSION: SLE remains challenging to diagnose and treat. The heterogeneity of disease manifestations and treatment response highlight the need for improved molecular characterization. In a large multiethnic cohort, we demonstrate mux-seq as a systematic approach to characterize cellular composition, identify cell type–specific transcriptomic signatures, and annotate genetic variants associated with SLE.

Adipose tissue is usually classified on the basis of its function as white, brown or beige (brite)1. It is an important regulator of systemic metabolism, as shown by the fact that dysfunctional adipose tissue in obesity leads to a variety of secondary metabolic complications2,3. In addition, adipose tissue functions as a signalling hub that regulates systemic metabolism through paracrine and endocrine signals4. Here we use single-nucleus RNA-sequencing (snRNA-seq) analysis in mice and humans to characterize adipocyte heterogeneity. We identify a rare subpopulation of adipocytes in mice that increases in abundance at higher temperatures, and we show that this subpopulation regulates the activity of neighbouring adipocytes through acetate-mediated modulation of their thermogenic capacity. Human adipose tissue contains higher numbers of cells of this subpopulation, which could explain the lower thermogenic activity of human compared to mouse adipose tissue and suggests that targeting this pathway could be used to restore thermogenic activity.

Massively parallel single-cell and single-nucleus RNA sequencing has opened the way to systematic tissue atlases in health and disease, but as the scale of data generation is growing, so is the need for computational pipelines for scaled analysis. Here we developed Cumulus—a cloud-based framework for analyzing large-scale single-cell and single-nucleus RNA sequencing datasets. Cumulus combines the power of cloud computing with improvements in algorithm and implementation to achieve high scalability, low cost, user-friendliness and integrated support for a comprehensive set of features. We benchmark Cumulus on the Human Cell Atlas Census of Immune Cells dataset of bone marrow cells and show that it substantially improves efficiency over conventional frameworks, while maintaining or improving the quality of results, enabling large-scale studies. Cumulus is a cloud-based framework enabling large-scale single-cell and single-nucleus RNA sequencing data analysis.

Single-cell genomics is essential to chart tumor ecosystems. Although single-cell RNA-Seq (scRNA-Seq) profiles RNA from cells dissociated from fresh tumors, single-nucleus RNA-Seq (snRNA-Seq) is needed to profile frozen or hard-to-dissociate tumors. Each requires customization to different tissue and tumor types, posing a barrier to adoption. Here, we have developed a systematic toolbox for profiling fresh and frozen clinical tumor samples using scRNA-Seq and snRNA-Seq, respectively. We analyzed 216,490 cells and nuclei from 40 samples across 23 specimens spanning eight tumor types of varying tissue and sample characteristics. We evaluated protocols by cell and nucleus quality, recovery rate and cellular composition. scRNA-Seq and snRNA-Seq from matched samples recovered the same cell types, but at different proportions. Our work provides guidance for studies in a broad range of tumors, including criteria for testing and selecting methods from the toolbox for other tumors, thus paving the way for charting tumor atlases., A set of ready-to-use tools for profiling fresh and frozen clinical tumor samples using scRNA-Seq and snRNA-Seq facilitates the implementation of single-cell technologies in clinical settings and the construction of single-cell tumor atlases.

Crucial transitions in cancer-including tumor initiation, local expansion, metastasis, and therapeutic resistance-involve complex interactions between cells within the dynamic tumor ecosystem. Transformative single-cell genomics technologies and spatial multiplex in situ methods now provide an opportunity to interrogate this complexity at unprecedented resolution. The Human Tumor Atlas Network (HTAN), part of the National Cancer Institute (NCI) Cancer Moonshot Initiative, will establish a clinical, experimental, computational, and organizational framework to generate informative and accessible three-dimensional atlases of cancer transitions for a diverse set of tumor types. This effort complements both ongoing efforts to map healthy organs and previous large-scale cancer genomics approaches focused on bulk sequencing at a single point in time. Generating single-cell, multiparametric, longitudinal atlases and integrating them with clinical outcomes should help identify novel predictive biomarkers and features as well as therapeutically relevant cell types, cell states, and cellular interactions across transitions. The resulting tumor atlases should have a profound impact on our understanding of cancer biology and have the potential to improve cancer detection, prevention, and therapeutic discovery for better precision-medicine treatments of cancer patients and those at risk for cancer.

Systemic immunity supports healthy brain homeostasis. Accordingly, conditions causing systemic immune deregulation may accelerate onset of neurodegeneration in predisposed individuals. Here we show that, in the 5xFAD mouse model of Alzheimer’s disease (AD), high-fat diet-induced obesity accelerated cognitive decline, which was associated with immune deviations comprising increased splenic frequencies of exhausted CD4+T effector memory cells and CD4+FOXP3+regulatory T cells (Tregs). Non-targeted plasma metabolomics identifiedN-acetylneuraminic acid (NANA), the predominant sialic acid, as the major obesity-induced metabolite in 5xFAD mice, the levels of which directly correlated with Tregs abundance and inversely correlated with cognitive performance. Visceral adipose tissue macrophages were identified by sNuc-Seq as one potential source of NANA. Exposure to NANA led to immune deregulation in middle-aged wild-type mice, andex vivoin human T cells. Our study identified diet-induced immune deregulation, potentially via sialic acid, as a previously unrecognized link between obesity and AD.

High-grade gliomas (HGG) with histone H3.3 G34R mutation are rare intractable tumours in the cerebral hemispheres that preferentially affect adolescents and young adults, but have unknown mechanisms of neuroanatomical specificity and tumourigenesis. Here, we performed single-nucleus RNA-sequencing of twenty patient samples, encompassing twelve tumours with G34R mutation and eight H3.3 wildtype HGGs, age- and location-matched. Both classes of HGG were heterogeneous, with malignant cells in multiple states, recapitulating neural and glial developmental trajectories. G34R HGG is distinguished by lack of malignant cells in the oligodendroglial lineage, and aberrant expression of neuronal programs superimposed over cellular states, resulting in hybrid glio-neuronal malignant programs. Singe-cell barcoding supports plasticity between cellular states in HGG with multiple possible transitions. CRISPR-correction of G34R in HGG models followed by scRNA-seq supports that the G34R mutation directly drives these aberrant programs. Our study provides a framework for studying the origin and tumourigenesis of paediatric gliomas.

Haematopoiesis in the bone marrow (BM) maintains blood and immune cell production throughout postnatal life. Haematopoiesis first emerges in human BM at 11–12 weeks after conception1,2, yet almost nothing is known about how fetal BM (FBM) evolves to meet the highly specialized needs of the fetus and newborn. Here we detail the development of FBM, including stroma, using multi-omic assessment of mRNA and multiplexed protein epitope expression. We find that the full blood and immune cell repertoire is established in FBM in a short time window of 6–7 weeks early in the second trimester. FBM promotes rapid and extensive diversification of myeloid cells, with granulocytes, eosinophils and dendritic cell subsets emerging for the first time. The substantial expansion of B lymphocytes in FBM contrasts with fetal liver at the same gestational age. Haematopoietic progenitors from fetal liver, FBM and cord blood exhibit transcriptional and functional differences that contribute to tissue-specific identity and cellular diversification. Endothelial cell types form distinct vascular structures that we show are regionally compartmentalized within FBM. Finally, we reveal selective disruption of B lymphocyte, erythroid and myeloid development owing to a cell-intrinsic differentiation bias as well as extrinsic regulation through an altered microenvironment in Down syndrome (trisomy 21). A single-cell atlas of human fetal bone marrow in healthy fetuses and fetuses with Down syndrome provides insight into developmental haematopoiesis in humans and the transcription and functional differences that occur in Down syndrome.

The critical functions of the human liver are coordinated through the interactions of hepatic parenchymal and non-parenchymal cells. Recent advances in single-cell transcriptional approaches have enabled an examination of the human liver with unprecedented resolution. However, dissociation-related cell perturbation can limit the ability to fully capture the human liver's parenchymal cell fraction, which limits the ability to comprehensively profile this organ. Here, we report the transcriptional landscape of 73,295 cells from the human liver using matched single-cell RNA sequencing (scRNA-seq) and single-nucleus RNA sequencing (snRNA-seq). The addition of snRNA-seq enabled the characterization of interzonal hepatocytes at a single-cell resolution, revealed the presence of rare subtypes of liver mesenchymal cells, and facilitated the detection of cholangiocyte progenitors that had only been observed during in vitro differentiation experiments. However, T and B lymphocytes and natural killer cells were only distinguishable using scRNA-seq, highlighting the importance of applying both technologies to obtain a complete map of tissue-resident cell types. We validated the distinct spatial distribution of the hepatocyte, cholangiocyte, and mesenchymal cell populations by an independent spatial transcriptomics data set and immunohistochemistry. Conclusion: Our study provides a systematic comparison of the transcriptomes captured by scRNA-seq and snRNA-seq and delivers a high-resolution map of the parenchymal cell populations in the healthy human liver.

Understanding the function of genes and their regulation in tissue homeostasis and disease requires knowing the cellular context in which genes are expressed in tissues across the body. Single cell genomics allows the generation of detailed cellular atlases in human tissues, but most efforts are focused on single tissue types. Here, we establish a framework for profiling multiple tissues across the human body at single-cell resolution using single nucleus RNA-Seq (snRNA-seq), and apply it to 8 diverse, archived, frozen tissue types (three donors per tissue). We apply four snRNA-seq methods to each of 25 samples from 16 donors, generating a cross-tissue atlas of 209,126 nuclei profiles, and benchmark them vs. scRNA-seq of comparable fresh tissues. We use a conditional variational autoencoder (cVAE) to integrate an atlas across tissues, donors, and laboratory methods. We highlight shared and tissue-specific features of tissue-resident immune cells, identifying tissue-restricted and non-restricted resident myeloid populations. These include a cross-tissue conserved dichotomy between LYVE1- and HLA class II-expressing macrophages, and the broad presence of LAM-like macrophages across healthy tissues that is also observed in disease. For rare, monogenic muscle diseases, we identify cell types that likely underlie the neuromuscular, metabolic, and immune components of these diseases, and biological processes involved in their pathology. For common complex diseases and traits analyzed by GWAS, we identify the cell types and gene modules that potentially underlie disease mechanisms. The experimental and analytical frameworks we describe will enable the generation of large-scale studies of how cellular and molecular processes vary across individuals and populations.

Throughout postnatal life, haematopoiesis in the bone marrow (BM) maintains blood and immune cell production. Haematopoiesis first emerges in human BM at 12 post conception weeks while fetal liver (FL) haematopoiesis is still expanding. Yet, almost nothing is known about how fetal BM evolves to meet the highly specialised needs of the fetus and newborn infant. Here, we detail the development of fetal BM including stroma using single cell RNA-sequencing. We find that the full blood and immune cell repertoire is established in fetal BM in a short time window of 6-7 weeks early in the second trimester. Fetal BM promotes rapid and extensive diversification of myeloid cells, with granulocytes, eosinophils and dendritic cell (DC) subsets emerging for the first time. B-lymphocyte expansion occurs, in contrast with erythroid predominance in FL at the same gestational age. We identify transcriptional and functional differences that underlie tissue-specific identity and cellular diversification in fetal BM and FL. Finally, we reveal selective disruption of B-lymphocyte, erythroid and myeloid development due to cell intrinsic differentiation bias as well as extrinsic regulation through an altered microenvironment in the fetal BM from constitutional chromosome anomaly Down syndrome during this crucial developmental time window.

This protocol was used as part of the Human Tumor Atlas Pilot Project’s (HTAPP) efforts to establish a working protocol for the dissociation of human metastatic breast cancer excision biopsies to a single-cell suspension compatible with droplet-based single-cell RNA-Seq technology. For processing human metastatic breast cancer excision biopsies, however, we now recommend using the Liberase-based protocol established by Slyper et al.

Tissue-resident innate lymphoid cells (ILCs) help sustain barrier function and respond to local signals. ILCs are traditionally classified as ILC1, ILC2 or ILC3 on the basis of their expression of specific transcription factors and cytokines1. In the skin, disease-specific production of ILC3-associated cytokines interleukin (IL)-17 and IL-22 in response to IL-23 signalling contributes to dermal inflammation in psoriasis. However, it is not known whether this response is initiated by pre-committed ILCs or by cell-state transitions. Here we show that the induction of psoriasis in mice by IL-23 or imiquimod reconfigures a spectrum of skin ILCs, which converge on a pathogenic ILC3-like state. Tissue-resident ILCs were necessary and sufficient, in the absence of circulatory ILCs, to drive pathology. Single-cell RNA-sequencing (scRNA-seq) profiles of skin ILCs along a time course of psoriatic inflammation formed a dense transcriptional continuum—even at steady state—reflecting fluid ILC states, including a naive or quiescent-like state and an ILC2 effector state. Upon disease induction, the continuum shifted rapidly to span a mixed, ILC3-like subset also expressing cytokines characteristic of ILC2s, which we inferred as arising through multiple trajectories. We confirmed the transition potential of quiescent-like and ILC2 states using in vitro experiments, single-cell assay for transposase-accessible chromatin using sequencing (scATAC-seq) and in vivo fate mapping. Our results highlight the range and flexibility of skin ILC responses, suggesting that immune activities primed in healthy tissues dynamically adapt to provocations and, left unchecked, drive pathological remodelling. In studies using mouse models of psoriasis, a spectrum of innate lymphoid cell types is reconfigured and converges via multiple trajectories on a type 3-like state, demonstrating the range and flexibility of innate lymphoid cell responses in the skin.

The critical functions of the human liver are coordinated through the interactions of hepatic parenchymal and non-parenchymal cells. Recent advances in single cell transcriptional approaches have enabled an examination of the human liver with unprecedented resolution. However, dissociation related cell perturbation can limit the ability to fully capture the human liver’s parenchymal cell fraction, which limits the ability to comprehensively profile this organ. Here, we report the transcriptional landscape of 73,295 cells from the human liver using matched single-cell RNA sequencing (scRNA-seq) and single-nucleus RNA sequencing (snRNA-seq). The addition of snRNA-seq enabled the characterization of interzonal hepatocytes at single-cell resolution, revealed the presence of rare subtypes of hepatic stellate cells previously only seen in disease, and detection of cholangiocyte progenitors that had only been observed during in vitro differentiation experiments. However, T and B lymphocytes and NK cells were only distinguishable using scRNA-seq, highlighting the importance of applying both technologies to obtain a complete map of tissue-resident cell-types. We validated the distinct spatial distribution of the hepatocyte, cholangiocyte and stellate cell populations by an independent spatial transcriptomics dataset and immunohistochemistry. Our study provides a systematic comparison of the transcriptomes captured by scRNA-seq and snRNA-seq and delivers a high-resolution map of the parenchymal cell populations in the healthy human liver.

This protocol was used as part of the Human Tumor Atlas Pilot Project’s (HTAPP) efforts to establish a working protocol for the dissociation of human neuroblastoma core needle biopsies to a single-cell suspension compatible with droplet-based single-cell RNA-Seq technology. It is a testing protocol and we do not recommended using it for the intended purpose. Instead, for processing human neuroblastoma tumors, we recommend using the papain-based protocol established by Patel et al.

This protocol was used as part of the Human Tumor Atlas Pilot Project’s (HTAPP) efforts to establish a working protocol for the dissociation of human neuroblastoma core needle biopsies to a single-cell suspension compatible with droplet-based single-cell RNA-Seq technology. It is a testing protocol and we do not recommended using it for the intended purpose. Instead, for processing human neuroblastoma tumors, we recommend using the papain-based protocol established by Patel et al.

This protocol was used as part of the Human Tumor Atlas Pilot Project’s (HTAPP) efforts to establish a working protocol for the dissociation of human neuroblastoma core needle biopsies to a single-cell suspension compatible with droplet-based single-cell RNA-Seq technology. It is a testing protocol and we do not recommended using it for the intended purpose. Instead, for processing human neuroblastoma tumors, we recommend using the papain-based protocol established by Patel et al.

This protocol was used as part of the Human Tumor Atlas Pilot Project’s (HTAPP) efforts to establish a working protocol for the dissociation of human neuroblastoma samples to a single-cell suspension compatible with droplet-based single-cell RNA-Seq technology. It is a testing protocol and we do not recommended using it for the intended purpose. Instead, for processing human neuroblastoma tumors, we recommend using the papain-based protocol established by Patel et al.

The SARS-CoV-2 pandemic has caused over 1 million deaths globally, mostly due to acute lung injury and acute respiratory distress syndrome, or direct complications resulting in multiple-organ failures. Little is known about the host tissue immune and cellular responses associated with COVID-19 infection, symptoms, and lethality. To address this, we collected tissues from 11 organs during the clinical autopsy of 17 individuals who succumbed to COVID-19, resulting in a tissue bank of approximately 420 specimens. We generated comprehensive cellular maps capturing COVID-19 biology related to patients’ demise through single-cell and single-nucleus RNA-Seq of lung, kidney, liver and heart tissues, and further contextualized our findings through spatial RNA profiling of distinct lung regions. We developed a computational framework that incorporates removal of ambient RNA and automated cell type annotation to facilitate comparison with other healthy and diseased tissue atlases. In the lung, we uncovered significantly altered transcriptional programs within the epithelial, immune, and stromal compartments and cell intrinsic changes in multiple cell types relative to lung tissue from healthy controls. We observed evidence of: alveolar type 2 (AT2) differentiation replacing depleted alveolar type 1 (AT1) lung epithelial cells, as previously seen in fibrosis; a concomitant increase in myofibroblasts reflective of defective tissue repair; and, putative TP63+ intrapulmonary basal-like progenitor (IPBLP) cells, similar to cells identified in H1N1 influenza, that may serve as an emergency cellular reserve for severely damaged alveoli. Together, these findings suggest the activation and failure of multiple avenues for regeneration of the epithelium in these terminal lungs. SARS-CoV-2 RNA reads were enriched in lung mononuclear phagocytic cells and endothelial cells, and these cells expressed distinct host response transcriptional programs. We corroborated the compositional and transcriptional changes in lung tissue through spatial analysis of RNA profiles in situ and distinguished unique tissue host responses between regions with and without viral RNA, and in COVID-19 donor tissues relative to healthy lung. Finally, we analyzed genetic regions implicated in COVID-19 GWAS with transcriptomic data to implicate specific cell types and genes associated with disease severity. Overall, our COVID-19 cell atlas is a foundational dataset to better understand the biological impact of SARS-CoV-2 infection across the human body and empowers the identification of new therapeutic interventions and prevention strategies.

This protocol was used for the dissociation of human neuroblastoma resections to a single-cell suspension compatible with droplet-based single-cell RNA-Seq technology for the Human Tumor Atlas Pilot Project. For processing human neuroblastoma tumors, however, we now recommend using the papain-based protocol established by Patel et al.

This protocol was used for the dissociation of human neuroblastoma core needle biopsies to a single-cell suspension compatible with droplet-based single-cell RNA-Seq technology for the Human Tumor Atlas Pilot Project. For processing human neuroblastoma tumors, however, we now recommend using the papain-based protocol established by Patel et al.

SARS-CoV-2, the coronavirus that causes COVID-19, binds to angiotensin-converting enzyme 2 (ACE2) on human cells. Beyond the lung, COVID-19 impacts diverse tissues including the kidney. ACE2 is a key member of the Renin-Angiotensin-Aldosterone System (RAAS) which regulates blood pressure, largely through its effects on the kidney. RAAS blockers such as ACE inhibitors (ACEi) and Angiotensin Receptor Blockers (ARBs) are widely used therapies for hypertension, cardiovascular and chronic kidney diseases, and therefore, there is intense interest in their effect on ACE2 expression and its implications for SARS-CoV-2 pathogenicity. Here, we analyzed single-cell and single-nucleus RNA-seq of human kidney to interrogate the association of ACEi/ARB use with ACE2 expression in specific cell types. First, we performed an integrated analysis aggregating 176,421 cells across 49 donors, 8 studies and 8 centers, and adjusting for sex, age, donor and center effects, to assess the relationship of ACE2 with age and sex at baseline. We observed a statistically significant increase in ACE2 expression in tubular epithelial cells of the thin loop of Henle (tLoH) in males relative to females at younger ages, the trend reversing, and losing significance with older ages. ACE2 expression in tLoH increases with age in females, with an opposite, weak effect in males. In an independent cohort, we detected a statistically significant increase in ACE2 expression with ACEi/ARB use in epithelial cells of the proximal tubule and thick ascending limb, and endothelial cells, but the association was confounded in this small cohort by the underlying disease. Our study illuminates the dynamics of ACE2 expression in specific kidney cells, with implications for SARS-CoV-2 entry and pathogenicity.

Malignant abdominal fluid (ascites) frequently develops in women with advanced high-grade serous ovarian cancer (HGSOC) and is associated with drug resistance and a poor prognosis1. To comprehensively characterize the HGSOC ascites ecosystem, we used single-cell RNA sequencing to profile ~11,000 cells from 22 ascites specimens from 11 patients with HGSOC. We found significant inter-patient variability in the composition and functional programs of ascites cells, including immunomodulatory fibroblast sub-populations and dichotomous macrophage populations. We found that the previously described immunoreactive and mesenchymal subtypes of HGSOC, which have prognostic implications, reflect the abundance of immune infiltrates and fibroblasts rather than distinct subsets of malignant cells2. Malignant cell variability was partly explained by heterogeneous copy number alteration patterns or expression of a stemness program. Malignant cells shared expression of inflammatory programs that were largely recapitulated in single-cell RNA sequencing of ~35,000 cells from additionally collected samples, including three ascites, two primary HGSOC tumors and three patient ascites-derived xenograft models. Inhibition of the JAK/STAT pathway, which was expressed in both malignant cells and cancer-associated fibroblasts, had potent anti-tumor activity in primary short-term cultures and patient-derived xenograft models. Our work contributes to resolving the HSGOC landscape3-5 and provides a resource for the development of novel therapeutic approaches.

This protocol describes amethodbased on work by Drokhlyansky et al.for nuclei isolation from frozen tissue.It can be used on both healthy and disease tissues and is compatible with droplet-based single-nucleus RNA-Seq technologySlyper et al. This method is part of a toolbox for processing frozen tissue samples forsingle-nucleus RNA-Seq, including the CST (this protocol), TST and NST protocols (all available inprotocols.io). We recommend users to test all three protocols on their tissue type of interest and perform side-by-side comparison of the data generated. A description of the complete toolbox andguidance for testing and selecting methods from the toolbox for processing other tumors can be found in Slyper et al. For the Human Tumor Atlas Pilot Project (HTAPP), the CST-nuclei isolation method was used to profile pediatric glioma frozen samples. It was also tested on metastatic breast cancer, ovarian cancer, pediatric sarcoma, and pediatric neuroblastoma frozen samples. For these cancer types, however, TST was the protocol of choice.

This protocol is used for the dissociation of human metastatic breast cancer core needle biopsies to a single-cell suspension compatible with droplet-based single-cell RNA-Seq technology (Slyper et al). For the Human Tumor Atlas Pilot Project (HTAPP) it has been successfully applied to biopsies collected from breast, liver and lymph node. Description of this protocol and guidance for testing and selecting methods for processing other tumor and sample types can be found in Slyper et al.

This protocol is used for the dissociation of human primary lung cancer resections to a single-cell suspension compatible with droplet-based single-cell RNA-Seq technology. For the Human Tumor Atlas Pilot Project (HTAPP) it has been successfully applied to non-small cell adenocarcinoma from which it was able to capture a diversity of cell types, including malignant (epithelial) and non malignant cells such asmesenchymal, endothelial, myeloid, and lymphoid cells. In some instances, this protocol can be combined with a protocol for CD45-cell depletion, which is used for fast depletion of immune cells for enrichment of malignant and stromal cells. Description of this protocol and guidance for testing and selecting methods for processing other tumor and sample types can be found in Slyper et al.

Methods for highly multiplexed RNA imaging are limited in spatial resolution, and thus in their ability to localize transcripts to nanoscale and subcellular compartments. We adapt expansion microscopy, which physically expands biological specimens, for long-read untargeted and targeted in situ RNA sequencing. We applied untargeted expansion sequencing (ExSeq) to mouse brain, yielding readout of thousands of genes, including splice variants and novel transcripts. Targeted ExSeq yielded nanoscale-resolution maps of RNAs throughout dendrites and spines in neurons of the mouse hippocampus, revealing patterns across multiple cell types; layer-specific cell types across mouse visual cortex; and the organization and position-dependent states of tumor and immune cells in a human metastatic breast cancer biopsy. Thus ExSeq enables highly multiplexed mapping of RNAs, from nanoscale to system scale.One Sentence SummaryIn situ sequencing of physically expanded specimens enables multiplexed mapping of RNAs at nanoscale, subcellular resolution.

The COVID-19 pandemic, caused by the novel coronavirus SARS-CoV-2, creates an urgent need for identifying molecular mechanisms that mediate viral entry, propagation, and tissue pathology. Cell membrane bound angiotensin-converting enzyme 2 (ACE2) and associated proteases, transmembrane protease serine 2 (TMPRSS2) and Cathepsin L (CTSL), were previously identified as mediators of SARS-CoV2 cellular entry. Here, we assess the cell type-specific RNA expression of ACE2, TMPRSS2, and CTSL through an integrated analysis of 107 single-cell and single-nucleus RNA-Seq studies, including 22 lung and airways datasets (16 unpublished), and 85 datasets from other diverse organs. Joint expression of ACE2 and the accessory proteases identifies specific subsets of respiratory epithelial cells as putative targets of viral infection in the nasal passages, airways, and alveoli. Cells that co-express ACE2 and proteases are also identified in cells from other organs, some of which have been associated with COVID-19 transmission or pathology, including gut enterocytes, corneal epithelial cells, cardiomyocytes, heart pericytes, olfactory sustentacular cells, and renal epithelial cells. Performing the first meta-analyses of scRNA-seq studies, we analyzed 1,176,683 cells from 282 nasal, airway, and lung parenchyma samples from 164 donors spanning fetal, childhood, adult, and elderly age groups, associate increased levels of ACE2, TMPRSS2, and CTSL in specific cell types with increasing age, male gender, and smoking, all of which are epidemiologically linked to COVID-19 susceptibility and outcomes. Notably, there was a particularly low expression of ACE2 in the few young pediatric samples in the analysis. Further analysis reveals a gene expression program shared by ACE2+TMPRSS2+ cells in nasal, lung and gut tissues, including genes that may mediate viral entry, subtend key immune functions, and mediate epithelial-macrophage cross-talk. Amongst these are IL6, its receptor and co-receptor, IL1R, TNF response pathways, and complement genes. Cell type specificity in the lung and airways and smoking effects were conserved in mice. Our analyses suggest that differences in the cell type-specific expression of mediators of SARS-CoV-2 viral entry may be responsible for aspects of COVID-19 epidemiology and clinical course, and point to putative molecular pathways involved in disease susceptibility and pathogenesis.

During postnatal life, thymopoiesis depends on the continuous colonization of the thymus by bone marrow derived hematopoietic progenitors that migrate through the bloodstream. In human, the nature of these thymus immigrants has remained unclear. Here, we employ single-cell RNA sequencing on approximately 70.000 CD34+ thymocytes to unravel the heterogeneity of the human immature postnatal thymocytes. Integration of bone marrow and peripheral blood precursors datasets identifies several putative thymus seeding precursors that display heterogeneity for currently used surface markers as revealed by CITEseq. Besides T cell precursors, we discover branches of intrathymic developing dendritic cells with predominantly plasmacytoid DCs. Trough trajectory inference, we delineate the transcriptional dynamics underlying early human T-lineage development from which we predict transcription factor modules that drive stage-specific steps of human T cell development. Thus, our work resolves the heterogeneity of thymus seeding precursors in human and reveals the molecular mechanisms that drive their in vivo cell fate.

Adipose tissue usually is classified as either white, brown or beige/brite, based on whether it functions as an energy storage or thermogenic organ(Cannon and Nedergaard, 2004; Rosen and Spiegelman, 2014). It serves as an important regulator of systemic metabolism, exemplified by the fact that dysfunctional adipose tissue in obesity leads to a host of secondary metabolic complications such as diabetes, cardiovascular diseases and cancer(Hajer et al., 2008; Lauby-Secretan et al., 2016). In addition, adipose tissue is an important endocrine organ, which regulates the function of other metabolic tissues through paracrine and endocrine signals(Scheele and Wolfrum, 2019; Scherer, 2006). Work in recent years has demonstrated that tissue heterogeneity is an important factor regulating the functionality of various organs(Cao et al., 2017; Ginhoux et al., 2016; Park et al., 2018). Here we used single nucleus analysis in mice and men to deconvolute adipocyte heterogeneity. We are able to identify a novel subpopulation of adipocytes whose abundance is low in mice (2-8%) and which is increased under higher ambient temperatures. Interestingly, this population is abundant in humans who live close to thermoneutrality. We demonstrate that this novel adipocyte subtype functions as a paracrine cell regulating the activity of brown adipocytes through acetate-mediated regulation of thermogenesis. These findings could explain, why human brown adipose tissue is substantially less active than mouse tissue and targeting this pathway in humans might be utilized to restore thermogenic activity of this tissue.

Metastatic breast cancer (MBC) remains incurable due to inevitable development of therapeutic resistance. Although tumor cell intrinsic mechanisms of resistance in MBC are beginning to be elucidated by bulk sequencing studies, the roles of the tumor microenvironment and intratumor heterogeneity in therapeutic resistance remain underexplored due to both technological barriers and limited availability of samples. To comprehensively capture these characteristics we have adapted a research biopsy protocol to collect tissue for an array of single-cell and spatio-molecular assays whose performance we have optimized for MBC, including single-cell and single-nucleus RNA sequencing, Slide-Seq, Multiplexed Error-Robust FISH (MERFISH), Expansion Sequencing (ExSEQ), Co-detection by Indexing (CODEX) and Multiplexed Ion Beam Imaging (MIBI). To date, we have successfully performed single-cell or single-nucleus RNAseq in 67 MBC biopsies and generated detailed accompanying clinical annotations for each. These samples provide a representation of the clinicopathological diversity of MBC including different breast cancer subtypes (44 HR+/HER2-, 3 HR-/HER2+, 3 HR+/HER2+, 16 TNBC, 1 unknown), common anatomic sites of metastasis (37 liver, 9 axilla, 7 breast, 5 bone, 3 chest wall, 3 neck, 1 brain, 1 lung, 1 skin), metastatic presentations (53 recurrent, 14 de novo) and histologic subtypes in the breast (45 IDC, 7 ILC, 6 mixed, 3 DCIS, 1 mucinous, 5 unknown/NA). Following optimization, both single-cell and single-nucleus RNA seq perform well in these MBC biopsies recovering all expected cell types including the malignant, stromal (e.g. fibroblasts, endothelial cells), myeloid (e.g. monocytes, macrophages) and lymphoid compartments (e.g. T cells, B cells, NK cells) as well as relevant oncogenic programs (e.g. cell cycle programs in all compartments; EMT-like and ER signaling programs in the malignant compartment, immune checkpoint programs in the lymphoid compartment; and fibroblast activation and vascular homeostasis programs in the stromal compartment). In addition to differences between the two techniques, these data demonstrate substantial intratumor heterogeneity in cell type composition. For example in liver biopsies the average number of cells per sample compartment by single nucleus RNA-seq was 6745 malignant (56%, SD 4216), 4637 stromal (41%, SD 3727), 1196 lymphoid (8%, SD 1617) and 874 myeloid (6%, SD 852); in breast biopsies the average number of cells per compartment by single nucleus RNA-seq was 6421 malignant (70%, SD 3497), 1628 stromal (24%, SD 117), 333 lymphoid (4%, SD 170) and 213 myeloid (3%, SD 117). Additionally, we find both inter- and intra-tumor heterogeneity in expression patterns and programs including, for example, expression of ER, PR and HER2 within clinical receptor subtypes (log normalized counts for ER expression in tumor cells by single cell RNA-seq: HR+/HER2- 0.921 (SD 0.714); HR+/HER2+ 0.768 (SD 0.624); HR-/HER2+ 0.018 (SD 0.122); and HR-/HER2- 0.005 (SD 0.066). For a subset of 13 biopsies we are also completing the spatiomolecular characterization methods on serial sections of a single adjacent biopsy. This unique experimental setup was designed to enable efficient comparison and integration of these assays. In spite of differences between experimental techniques and readouts, cell typing can be approached by annotation transfer from matching single cell or single nucleus RNAseq data, enabling exploratory analyses including evaluation of spatial phenotypes and cell type colocalization. Overall, these single cell and spatial data afford a comprehensive atlas including cell types, cell states/programs, cell interactions and spatial organization in MBC lesions. Future analyses will include serial biopsies over time and integration of clinicopathologic data including therapeutic response and resistance. Citation Format: Daniel L Abravanel, Johanna Klughammer, Timothy Blosser, Yury Goltsev, Sizun Jiang, Yunjao Bai, Evan Murray, Shahar Alon, Yi Cui, Daniel R Goodwin, Anubhav Sinha, Ofir Cohen, Michal Slyper, Orr Ashenberg, Danielle Dionne, Judit Jané-Valbuena, Caroline BM Porter, Asa Segerstolpe, Julia Waldman, Sébastien Vigneau, Karla Helvie, Allison Frangieh, Laura DelloStritto, Miraj Patel, Jingyi We, Kathleen Pfaff, Nicole Cullen, Ana Lako, Madison Turner, Isaac Wakiro, Sara Napolitano, Abhay Kanodia, Rebecca Ortiz, Colin MacKichan, Stephanie Inga, Judy Chen, Aaron R Thorner, Asaf Rotem, Scott Rodig, Fei Chen, Edward S Boyden, Garry P Nolan, Xiaowei Zhuang, Orit Rozenblatt-Rosen, Bruce E Johnson, Aviv Regev, Nikhil Wagle. Spatio-molecular dissection of the breast cancer metastatic microenvironment [abstract]. In: Proceedings of the 2021 San Antonio Breast Cancer Symposium; 2021 Dec 7-10; San Antonio, TX. Philadelphia (PA): AACR; Cancer Res 2022;82(4 Suppl):Abstract nr PD6-03.

Summary During postnatal life, thymopoiesis depends on the continuous colonization of the thymus by bone-marrow-derived hematopoietic progenitors that migrate through the bloodstream. The current understanding of the nature of thymic immigrants is largely based on data from pre-clinical models. Here, we employed single-cell RNA sequencing (scRNA-seq) to examine the immature postnatal thymocyte population in humans. Integration of bone marrow and peripheral blood precursor datasets identified two putative thymus seeding progenitors that varied in expression of CD7; CD10; and the homing receptors CCR7, CCR9, and ITGB7. Whereas both precursors supported T cell development, only one contributed to intrathymic dendritic cell (DC) differentiation, predominantly of plasmacytoid dendritic cells. Trajectory inference delineated the transcriptional dynamics underlying early human T lineage development, enabling prediction of transcription factor (TF) modules that drive stage-specific steps of human T cell development. This comprehensive dataset defines the expression signature of immature human thymocytes and provides a resource for the further study of human thymopoiesis.

Background: The transition from ductal carcinoma in situ (DCIS) to invasive ductal carcinoma (IDC) is defined by the invasion of malignant cells into surrounding tissues, but associated changes in the cellular composition and interactions in the tumor microenvironment are poorly understood. Systematic analysis of gene expression differences between DCIS and IDC are confounded by cellular heterogeneity and few studies have separated stromal and epithelial contributions or distinguished pure DCIS from those synchronous with IDC. Methods: The gene expression of 192 microdissected regions from 140 cases was assembled from 5 studies and included DCIS (83 epithelial, 22 stromal) and IDC (67 epithelial, 20 stromal) cases. Differences in infiltration of 10 immune cell types were measured using expression signatures. Cell-cell interactions between stromal and epithelial regions were measured using the co-expression of 1175 curated pairs of ligand-receptor genes and compared between DCIS and IDC using a permutation test. The corresponding interacting cell types were identified using RNA sequencing of 5444 single nuclei extracted from fine needle aspirates of two excised DCIS specimens. Results: Stromal regions of Her2+ cases had the highest level of immune infiltration compared to IDC and Her2- cases. Of the measured immune cell types, B cells showed a progressive depletion from normal to DCIS to IDC. The expression-based measurement of stromal-epithelial interactions identified 99 and 115 ligand-receptor interactions stronger in DCIS and IDC, respectively (FDR Conclusion: The analysis of published gene expression studies with novel computational methods, augmented with a single-cell landscape representative of the disease, can help compensate for the difficulty in studying pure DCIS specimens. The microenvironment changes in cellular dynamics involved both immune and non-immune cell types suggesting mechanisms other than direct immune escape contribute to progression. Citation Format: Adam Officer, Andre Dempsey, Farnaz Hasteh, Michal Slyper, Asa Segerstolpe, Joanna Klughammer, Judit Jane-Valbuena, Orit Rozenblatt-Rosen, Aviv Regev, Christina Yau, Olivier Harismendy. Remodeling of stromal-epithelial interactions in breast cancer progression as inferred from regional and single-cell gene expression analysis [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2021; 2021 Apr 10-15 and May 17-21. Philadelphia (PA): AACR; Cancer Res 2021;81(13_Suppl):Abstract nr 131.

Human iPSC-derived kidney organoids have the potential to revolutionize discovery, but assessing their consistency and reproducibility across iPSC lines, and reducing the generation of off-target cells remain an open challenge. Here, we profile four human iPSC lines for a total of 450,118 single cells to show how organoid composition and development are comparable to human fetal and adult kidneys. Although cell classes are largely reproducible across time points, protocols, and replicates, we detect variability in cell proportions between different iPSC lines, largely due to off-target cells. To address this, we analyze organoids transplanted under the mouse kidney capsule and find diminished off-target cells. Our work shows how single cell RNA-seq (scRNA-seq) can score organoids for reproducibility, faithfulness and quality, that kidney organoids derived from different iPSC lines are comparable surrogates for human kidney, and that transplantation enhances their formation by diminishing off-target cells., How reproducible human kidney organoids derived from different iPSC lines are, and how faithful they are to human kidney tissue remain unclear. Here, the authors use four human iPSC lines to derive kidney organoids and show how organoid composition is reproducible, comparable to human tissue and of improved quality after transplantation.

Massively parallel single-cell and single-nucleus RNA-seq (sc/snRNA-seq) have opened the way to systematic tissue atlases in health and disease, but as the scale of data generation is growing, so does the need for computational pipelines for scaled analysis. Here, we developed Cumulus, a cloud-based framework for analyzing large scale sc/snRNA-seq datasets. Cumulus combines the power of cloud computing with improvements in algorithm implementations to achieve high scalability, low cost, user-friendliness, and integrated support for a comprehensive set of features. We benchmark Cumulus on the Human Cell Atlas Census of Immune Cells dataset of bone marrow cells and show that it substantially improves efficiency over conventional frameworks, while maintaining or improving the quality of results, enabling large-scale studies.

International audience; Definitive haematopoiesis in the fetal liver supports self-renewal anddifferentiation of haematopoietic stem cells and multipotent progenitors(HSC/MPPs) but remains poorly defined in humans. Here, using single-celltranscriptome profiling of approximately 140,000 liver and 74,000 skin, kidneyand yolk sac cells, we identify the repertoire of human blood and immune cellsduring development. We infer differentiation trajectories from HSC/MPPs andevaluate the influence of the tissue microenvironment on blood and immune celldevelopment. We reveal physiological erythropoiesis in fetal skin and thepresence of mast cells, natural killer and innate lymphoid cell precursors in theyolk sac. We demonstrate a shift in the haemopoietic composition of fetal liverduring gestation away from being predominantly erythroid, accompanied by aparallel change in differentiation potential of HSC/MPPs, which we functionallyvalidate. Our integrated map of fetal liver haematopoiesis provides a blueprintfor the study of paediatric blood and immune disorders, and a reference forharnessing the therapeutic potential of HSC/MPPs.

Single cell genomics is essential to chart the complex tumor ecosystem. While single cell RNA-Seq (scRNA-Seq) profiles RNA from cells dissociated from fresh tumor tissues, single nucleus RNA-Seq (snRNA-Seq) is needed to profile frozen or hard-to-dissociate tumors. Each strategy requires modifications to fit the unique characteristics of different tissue and tumor types, posing a barrier to adoption. Here, we developed a systematic toolbox for profiling fresh and frozen clinical tumor samples using scRNA-Seq and snRNA-Seq, respectively. We tested eight tumor types of varying tissue and sample characteristics (resection, biopsy, ascites, and orthotopic patient-derived xenograft): lung cancer, metastatic breast cancer, ovarian cancer, melanoma, neuroblastoma, pediatric sarcoma, glioblastoma, pediatric high-grade glioma, and chronic lymphocytic leukemia. Analyzing 212,498 cells and nuclei from 39 clinical samples, we evaluated protocols by cell quality, recovery rate, and cellular composition. We optimized protocols for fresh tissue dissociation for different tumor types using a decision tree to account for the technical and biological variation between clinical samples. We established methods for nucleus isolation from OCT embedded and fresh-frozen tissues, with an optimization matrix varying mechanical force, buffer, and detergent. scRNA-Seq and snRNA-Seq from matched samples recovered the same cell types and intrinsic expression profiles, but at different proportions. Our work provides direct guidance across a broad range of tumors, including criteria for testing and selecting methods from the toolbox for other tumors, thus paving the way for charting tumor atlases.

Genome-wide association studies (GWAS) have revealed risk alleles for ulcerative colitis (UC), but their cell type and pathway specificities are often unknown. Here, we generate an atlas of 115,517 cells from the colon mucosa of seven UC patients and ten healthy individuals, revealing 51 epithelial, stromal, and immune cell subsets. These included a subset of BEST4+ enterocytes, which may sense and respond to pH, and IL13RA2+IL-11+ inflammatory fibroblasts, which we associate with resistance to anti-TNF therapy. Inflammatory fibroblasts, inflammatory monocytes, microfold-like cells, and CD8+IL-17+ T cells expand during disease, and form intercellular interaction hubs that mediate cross-talk between diverse cellular lineages. We identify hundreds of putative autocrine and paracrine cell-cell interactions that may explain the migration, expansion, or inhibition of cell types with disease. Surprisingly, UC risk genes are often cell type specific and co-regulated in relatively few gene modules, suggesting convergence onto limited sets of cell types and pathways. Using this observation, we nominate and infer putative functions for UC risk genes across all GWAS loci. Our atlas thus provides a framework for interrogating complex human diseases and mapping risk variants onto their cell types and pathways of activity.

This protocol describes a robust and easy method for nuclei isolation for frozen tissues based on unpublished work by Drokhlyansky et al. This protocol is compatible with 10X droplet-based single-cell technology. This method is part of a toolbox for processing frozen tissue samples, including the TST (this protocol), CST and NST protocols (all available in protocols.io). We recommend users to test all three protocols on their tissue type of interest, and perform side-by-side comparison of the data generated. For the HTAPP project, this protocol was tested and validated for metastatic breast cancer, ovarian cancer, pediatric neuroblastoma and pediatric sarcoma frozen samples.