Single-cell Analysis Reveals Inter- and Intratumour Heterogeneity in Metastatic Breast Cancer.

Metastasis is the leading cause of cancer-related deaths of breast cancer patients. Some cancer cells in a tumour go through successive steps, referred to as the metastatic cascade, and give rise to metastases at a distant site. We know that the plasticity and heterogeneity of cancer cells play critical roles in metastasis but the precise underlying molecular mechanisms remain elusive. Here we aimed to identify molecular mechanisms of metastasis during colonization, one of the most important yet poorly understood steps of the cascade. We performed single-cell RNA-Seq (scRNA-Seq) on tumours and matched lung macrometastases of patient-derived xenografts of breast cancer. After correcting for confounding factors such as the cell cycle and the percentage of detected genes (PDG), we identified cells in three states in both tumours and metastases. Gene-set enrichment analysis revealed biological processes specific to proliferation and invasion in two states. Our findings suggest that these states are a balance between epithelial-to-mesenchymal (EMT) and mesenchymal-to-epithelial transitions (MET) traits that results in so-called partial EMT phenotypes. Analysis of the top differentially expressed genes (DEGs) between these cell states revealed a common set of partial EMT transcription factors (TFs) controlling gene expression, including ZNF750, OVOL2, TP63, TFAP2C and HEY2. Our data suggest that the TFs related to EMT delineate different cell states in tumours and metastases. The results highlight the marked interpatient heterogeneity of breast cancer but identify common features of single cells from five models of metastatic breast cancer.

Temporal and sequential transcriptional dynamics define lineage shifts in corticogenesis.

The cerebral cortex contains billions of neurons, and their disorganization or misspecification leads to neurodevelopmental disorders. Understanding how the plethora of projection neuron subtypes are generated by cortical neural stem cells (NSCs) is a major challenge. Here, we focused on elucidating the transcriptional landscape of murine embryonic NSCs, basal progenitors (BPs), and newborn neurons (NBNs) throughout cortical development. We uncover dynamic shifts in transcriptional space over time and heterogeneity within each progenitor population. We identified signature hallmarks of NSC, BP, and NBN clusters and predict active transcriptional nodes and networks that contribute to neural fate specification. We find that the expression of receptors, ligands, and downstream pathway components is highly dynamic over time and throughout the lineage implying differential responsiveness to signals. Thus, we provide an expansive compendium of gene expression during cortical development that will be an invaluable resource for studying neural developmental processes and neurodevelopmental disorders.

Single-cell mRNA profiling reveals the hierarchical response of miRNA targets to miRNA induction.

miRNAs are small RNAs that regulate gene expression post-transcriptionally. By repressing the translation and promoting the degradation of target mRNAs, miRNAs may reduce the cell-to-cell variability in protein expression, induce correlations between target expression levels, and provide a layer through which targets can influence each other's expression as "competing RNAs" (ceRNAs). However, experimental evidence for these behaviors is limited. Combining mathematical modeling with RNA sequencing of individual human embryonic kidney cells in which the expression of two distinct miRNAs was induced over a wide range, we have inferred parameters describing the response of hundreds of miRNA targets to miRNA induction. Individual targets have widely different response dynamics, and only a small proportion of predicted targets exhibit high sensitivity to miRNA induction. Our data reveal for the first time the response parameters of the entire network of endogenous miRNA targets to miRNA induction, demonstrating that miRNAs correlate target expression and at the same time increase the variability in expression of individual targets across cells. The approach is generalizable to other miRNAs and post-transcriptional regulators to improve the understanding of gene expression dynamics in individual cell types.

TGF-ß induces oncofetal fibronectin that, in turn, modulates TGF-ß superfamily signaling in endothelial cells.

Gene splicing profiles are frequently altered in cancer, and the splice variants of fibronectin (FN) that contain the extra-domains A (EDA) or B (EDB), referred to as EDA+FN or EDB+FN, are highly upregulated in tumor vasculature. Transforming growth factor ß (TGF-ß) signaling has been attributed a pivotal role in glioblastoma, with TGF-ß promoting angiogenesis and vessel remodeling. By using immunohistochemistry staining, we observed that the oncofetal FN isoforms EDA+FN and EDB+FN are expressed in glioblastoma vasculature. Ex vivo single-cell gene expression profiling of tumors by using CD31 and α-smooth muscle actin (αSMA) as markers for endothelial cells, and pericytes and vascular smooth muscle cells (VSMCs), respectively, confirmed the predominant expression of FN, EDA+FN and EDB+FN in the vascular compartment of glioblastoma. Specifically, within the CD31-positive cell population, we identified a positive correlation between the expression of EDA+FN and EDB+FN, and of molecules associated with TGF-ß signaling. Further, TGF-ß induced EDA+FN and EDB+FN in human cerebral microvascular endothelial cells and glioblastoma-derived endothelial cells in a SMAD3- and SMAD4-dependent manner. In turn, we found that FN modulated TGF-ß superfamily signaling in endothelial cells via the EDA and EDB, pointing towards a bidirectional influence of oncofetal FN and TGF-ß superfamily signaling.

Single-cell RNA sequencing reveals developmental heterogeneity among early lymphoid progenitors.

Single-cell RNA sequencing is a powerful technology for assessing heterogeneity within defined cell populations. Here, we describe the heterogeneity of a B220+CD117intCD19-NK1.1- uncommitted hematopoietic progenitor having combined lymphoid and myeloid potential. Phenotypic and functional assays revealed four subpopulations within the progenitor with distinct lineage developmental potentials. Among them, the Ly6D+SiglecH-CD11c- fraction was lymphoid-restricted exhibiting strong B-cell potential, whereas the Ly6D-SiglecH-CD11c- fraction showed mixed lympho-myeloid potential. Single-cell RNA sequencing of these subsets revealed that the latter population comprised a mixture of cells with distinct lymphoid and myeloid transcriptional signatures and identified a subgroup as the potential precursor of Ly6D+SiglecH-CD11c- Subsequent functional assays confirmed that B220+CD117intCD19-NK1.1- single cells are, with rare exceptions, not bipotent for lymphoid and myeloid lineages. A B-cell priming gradient was observed within the Ly6D+SiglecH-CD11c- subset and we propose a herein newly identified subgroup as the direct precursor of the first B-cell committed stage. Therefore, the apparent multipotency of B220+CD117intCD19-NK1.1- progenitors results from underlying heterogeneity at the single-cell level and highlights the validity of single-cell transcriptomics for resolving cellular heterogeneity and developmental relationships among hematopoietic progenitors.