INTRODUCTION Tumor fitness, evolution, and resistance to therapy are governed by selection of malignant cells with specific genotypes, by expression programs related to cellular phenotypes, and by influences of the tumor microenvironment (TME). Although bulk tumor analysis can interrogate the genetic state of tumor cells with high precision, bulk expression profiles average the diverse cells within each tumor, thereby masking critical differences and providing limited insight into cancer cell programs and TME influences. Single-cell RNA sequencing (scRNA-seq) can help to address those challenges but incurs financial and logistic considerations, including the time required to accrue large cohorts of fresh tumor specimen for single-cell analysis. RATIONALE We reasoned that scRNA-seq of a limited number of representative tumors could be combined with bulk data from large cohorts to decipher differences between tumor subclasses. In this approach, bulk samples collected for large cohorts, such as from The Cancer Genome Atlas (TCGA), are first used to define the combined effects of differences in cancer cell genotypes, phenotypes, and the composition of the TME. Single-cell analysis of a limited set of representative tumors is then used to distinguish those effects. We applied this approach to understand the differences between two types of isocitrate dehydrogenase (IDH)-mutant gliomas: astrocytoma (IDH-A) and oligodendroglioma (IDH-O). IDH-A and IDH-O are distinguished by co-occurring signature genetic events and by histopathology and are thought to recapitulate distinct glial lineages. By combining 9879 scRNA-seq profiles from 10 IDH-A tumors, 4347 scRNA-seq profiles from six IDH-O tumors, and 165 TCGA bulk RNA profiles, we could decipher differences between these two tumor types at single-cell resolution. RESULTS We find that differences in bulk expression profiles between IDH-A and IDH-O are primarily explained by the impact of signature genetic events and TME composition, but not by distinct expression programs of glial lineages in the malignant cells. We infer that both IDH-A and IDH-O share the same developmental hierarchy, consisting in each case of three subpopulations of malignant cells: nonproliferating cells differentiated along the astrocytic and oligodendrocytic lineages, and proliferative undifferentiated cells that resemble neural stem/progenitor cells. By analyzing tumors of different clinical grades, we observe that higher-grade tumors present enhanced proliferation, larger pools of undifferentiated glioma cells, and an increase in macrophage over microglia programs in the TME. CONCLUSION Our approach provides a general framework to decipher differences between classes of human tumors by decoupling cancer cell genotypes, phenotypes, and the composition of the TME. The shared glial lineages and developmental hierarchies observed in IDH-A and IDH-O suggest a common progenitor for all IDH-mutant gliomas, shedding light on a longstanding debate in gliomagenesis. In contrast to the similarity in gl...

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Highlights d Single-cell RNA-sequencing identifies cell populations involved in muscle regeneration d Muscle stem/progenitor cells form a hierarchy with stagespecific regulatory programs d Bioinformatic analysis identified paracrine factors influencing muscle stem cells d Syndecan-1/2/4 coordinate paracrine ligand-specific muscle progenitor proliferation

Muscle stem cells (MuSCs) are an essential adult stem cell population with the capacity to self-renew and regenerate muscle tissue. Functionally heterogeneous subpopulations of MuSCs have been identified based on their expression of myogenic regulatory factors and surface markers. However, a unified organization of muscle stem and progenitor cells and their subpopulations remains unresolved.Here, we performed temporal analysis of skeletal muscle regeneration using single-cell RNA-sequencing (scRNA-seq) of myotoxin-injured adult mouse hindlimb muscles. We generated over 34,000 single-cell transcriptomes spanning four muscle regeneration time-points and identified 15 distinct cell types, including a heterogeneous population of MuSCs and progenitor cells. Our analysis provides a hierarchical map of myogenic cell populations and identifies stage-specific regulatory programs that govern their contributions to muscle regeneration. In this transcriptomic atlas, we observed cell type-specific regenerative dynamics, exemplified by waves of transient amplification and diversification of multiple immune cell types and, subsequently, myogenic cells. Unbiased trajectory inference organized the myogenic cell populations within the atlas into a continuum, consisting of a hierarchy of quiescent MuSCs, cycling progenitors, committed myoblasts, and terminally differentiated myocytes. This myogenic trajectory matched prior understanding and also revealed that MuSC stages are defined by synchronous changes in regulatory factors, cell cycle-associated, and surface receptor gene expression. Lastly, we analyzed the transcriptomic atlas to identify over 100 candidate heterotypic communication signals between myogenic and non-myogenic cell populations, including many involving the fibroblast growth factor (FGF), Notch, and Syndecan receptor families and their associated ligands. Syndecan receptors were implicated in a large fraction of these cell communication interactions and were observed to exhibit transcriptional heterogeneity within the myogenic continuum. Using multiparameter mass cytometry (CyTOF), we confirmed that cycling MuSCs exhibit diversified Syndecan-1/2 expression, which suggests that dynamic alterations in Syndecan signaling interactions may coordinate stage-specific myogenic cell fate regulation. This scRNA-seq reference atlas provides a resolved hierarchical organization of myogenic subpopulations as a resource to investigate cell-cell interactions that regulate myogenic stem and progenitor cell fates in muscle regeneration.suggest that myogenic stem/progenitor cell lineage can be interpreted as a continuum of hierarchical cell states. However, it remains an unresolved challenge how global profiles in cell cycle mediators, regulatory factors and surface markers define this myogenic continuum.Recent advances in single-cell analyses and algorithms provide potent new strategies to infer cell differentiation trajectories (Hwang et al., 2018;Wagner et al., 2016). Here, we generated a single-cell transcriptomic atlas of mous...

Women harboring heterozygous germline mutations of BRCA2 have a 50 to 80% risk of developing breast cancer, yet the pathogenesis of these cancers is poorly understood. To reveal early steps in BRCA2-associated carcinogenesis, we analyzed sorted cell populations from freshly-isolated, non-cancerous breast tissues of BRCA2 mutation carriers and matched controls. Single-cell whole-genome sequencing demonstrates that >25% of BRCA2 carrier (BRCA2mut/+) luminal progenitor (LP) cells exhibit sub-chromosomal copy number variations, which are rarely observed in non-carriers. Correspondingly, primary BRCA2mut/+ breast epithelia exhibit DNA damage together with attenuated replication checkpoint and apoptotic responses, and an age-associated expansion of the LP compartment. We provide evidence that these phenotypes do not require loss of the wild-type BRCA2 allele. Collectively, our findings suggest that BRCA2 haploinsufficiency and associated DNA damage precede histologic abnormalities in vivo. Using these hallmarks of cancer predisposition will yield unanticipated opportunities for improved risk assessment and prevention strategies in high-risk patients.

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Recent studies have provided insights into the pathology and immune response to coronavirus disease 2019 (COVID-19). However thorough interrogation of the interplay between infected cells and the immune system at sites of infection is lacking. We use high parameter imaging mass cytometry targeting the expression of 36 proteins, to investigate at single cell resolution, the cellular composition and spatial architecture of human acute lung injury including SARS-CoV-2. This spatially resolved, single-cell data unravels the disordered structure of the infected and injured lung alongside the distribution of extensive immune infiltration. Neutrophil and macrophage infiltration are hallmarks of bacterial pneumonia and COVID-19, respectively. We provide evidence that SARS-CoV-2 infects predominantly alveolar epithelial cells and induces a localized hyper-inflammatory cell state associated with lung damage. By leveraging the temporal range of COVID-19 severe fatal disease in relation to the time of symptom onset, we observe increased macrophage extravasation, mesenchymal cells, and fibroblasts abundance concomitant with increased proximity between these cell types as the disease progresses, possibly as an attempt to repair the damaged lung tissue. This spatially resolved single-cell data allowed us to develop a biologically interpretable landscape of lung pathology from a structural, immunological and clinical standpoint. This spatial single-cell landscape enabled the pathophysiological characterization of the human lung from its macroscopic presentation to the single-cell, providing an important basis for the understanding of COVID-19, and lung pathology in general.