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Single-cell RNA sequencing reveals novel gene expression signatures of trastuzumab treatment in HER2+ breast cancer: A pilot study.
Human epidermal growth factor receptor 2-positive (HER2+) breast cancer accounts for ∼20% of invasive breast cancers and is associated with poor prognostics. The recent outcome of HER2+ breast cancer treatment has been vastly improved owing to the application of antibody-targeted therapies. Trastuzumab (Herceptin) is a monoclonal antibody designed to target HER2+ breast cancer cells. In addition to improved survival in the adjuvant treatment of HER2+ breast cancer, trastuzumab treatment has also been associated with cardiotoxicity side effect. However, the molecular mechanisms of trastuzumab action and trastuzumab-mediated cardiotoxicity are still not fully understood. Previous research utilized bulk transcriptomics analysis to study the underlining mechanisms, which relied on averaging molecular signals from bulk tumor samples and might have overlooked key expression features within breast cancer tumor. In contrast to previous research, we compared the single cancer cell level transcriptome profile between trastuzumab-treated and nontreated patients to reveal a more in-depth transcriptome profile. A total of 461 significantly differential expressed genes were identified, including previously defined and novel gene expression signatures. In addition, we found that trastuzumab-enhanced MGP gene expression could be used as prognostics marker for longer patient survival in breast invasive carcinoma patients, and validated our finding using TCGA (The Cancer Genome Atlas) breast cancer dataset. Moreover, our study revealed a 48-gene expression signature that is associated with cell death of cardiomyocytes, which could be used as early biomarkers for trastuzumab-mediated cardiotoxicity. This work is the first study to look at single cell level transcriptome profile of trastuzumab-treated patients, providing a new understanding of the molecular mechanism(s) of trastuzumab action and trastuzumab-induced cardiotoxicity side effects.
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Single-cell transcriptome atlas of lung adenocarcinoma featured with ground glass nodules.
As an early type of lung adenocarcinoma, ground glass nodule (GGN) has been detected increasingly and now accounts for most lung cancer outpatients. GGN has a satisfactory prognosis and its characteristics are quite different from solid adenocarcinoma (SADC). We compared the GGN adenocarcinoma (GGN-ADC) with SADC using the single-cell RNA sequencing (scRNA-seq) to fully understand GGNs. The tumor samples of five patients with lung GGN-ADCs and five with SADCs underwent surgery were digested to a single-cell suspension and analyzed using 10× Genomic scRNA-seq techniques. We obtained 60,459 cells and then classified them as eight cell types, including cancer cells, endothelial cells, fibroblasts, T cells, B cells, Nature killer cells, mast cells, and myeloid cells. We provided a comprehensive description of the cancer cells and stromal cells. We found that the signaling pathways related to cell proliferation were downregulated in GGN-ADC cancer cells, and stromal cells had different effects in GGN-ADC and SADC based on the analyses of scRNA-seq results. In GGN-ADC, the signaling pathways of angiogenesis were downregulated, fibroblasts expressed low levels of some collagens, and immune cells were more activated. Furthermore, we used flow cytometry to isolate the cancer cells and T cells in 12 GGN-ADC samples and in an equal number of SADC samples, including CD4+ T and CD8+ T cells, and validated the expression of key molecules by quantitative real-time polymerase chain reaction analyses. Through comprehensive analyses of cell phenotypes in GGNs, we provide deep insights into lung carcinogenesis that will be beneficial in lung cancer prevention and therapy.
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Single-cell atlas reveals different immune environments between stable and vulnerable atherosclerotic plaques.
INTRODUCTION: Regardless of the degree of stenosis, vulnerable plaque is an important cause of ischemic stroke and thrombotic complications. The changes of the immune microenvironment within plaques seem to be an important factor affecting the characteristics of the plaque. However, the differences of immune microenvironment between stable and vulnerable plaques were remained unknown. METHODS: In this study, RNA-sequencing was performed on superficial temporal arteries from 5 traumatic patients and plaques from 3 atherosclerotic patients to preliminary identify the key immune response processes in plaques. Mass cytometry (CyTOF) technology was used to explore differences in immune composition between 9 vulnerable plaques and 12 stable plaques. Finally, immunofluorescence technique was used to validate our findings in the previous analysis. RESULTS: Our results showed that more CD86+CD68+ M1 pro-inflammatory macrophages were found in vulnerable plaques, while CD4+T memory cells were mainly found in stable plaques. In addition, a CD11c+ subset of CD4+T cells with higher IFN-r secretion was found within the vulnerable plaque. In two subsets of B cells, CD19+CD20-B cells in vulnerable plaques secreted more TNF-a and IL-6, while CD19-CD20+B cells expressed more PD-1 molecules. CONCLUSION: In conclusion, our study suggested that M1-like macrophages are the major cell subset affecting plaque stability, while functional B cells may also contribute to plaque stability.
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A single-cell hematopoietic microenvironmental atlas reveals progressive maturation of bone marrow vascular niche.
The interaction between hematopoietic stem and progenitor cell (HSPC) and its vascular niche is essential for supporting the homeostasis and reconstitution of hematopoietic system in adult bone marrow (BM), but a comprehensive atlas covering this HSPC-vascular niche crosstalk in multiple developmental stages and species is lacking. Here, we integrated single-cell transcriptomic data of HSPC and its vascular niches from fetal liver until aged BM, covering two species, two organs, and six developmental time points. Comparative analyses revealed dramatic differences in the gene expression, enriched pathway, and cell-cell communication between human fetal and adult BM. Notably, many of these differences were conserved between humans and mice. Multi-timepoint profiling of murine BM vascular niches revealed a stepwise maturation of gene expression, including critical niche factors such as SCF and CXCL12. Furthermore, analysis of this dynamic vascular niche atlas highlighted organ-specific features between fetal liver and BM niches, significant transcriptional changes in aged BM endothelial cells, and identified midkine as a previously unknown niche factor. Functional validation showed that transplanting HSPC into midkine knockout mice or treating with a midkine inhibitor (iMDK) enhanced hematopoietic reconstitution. In contrast, recombinant midkine suppressed HSPC differentiation. Together, our work presents a cross-species and multi-stage atlas of HSPC-vascular niche interactions, offering valuable insights into the dynamic changes of vascular niche through lifelong HSPC development and a platform to identify unknown niche factors.
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A single-cell atlas of spatial and temporal gene expression in the mouse cranial neural plate.
The formation of the mammalian brain requires regionalization and morphogenesis of the cranial neural plate, which transforms from an epithelial sheet into a closed tube that provides the structural foundation for neural patterning and circuit formation. Sonic hedgehog (SHH) signaling is important for cranial neural plate patterning and closure, but the transcriptional changes that give rise to the spatially regulated cell fates and behaviors that build the cranial neural tube have not been systematically analyzed. Here, we used single-cell RNA sequencing to generate an atlas of gene expression at six consecutive stages of cranial neural tube closure in the mouse embryo. Ordering transcriptional profiles relative to the major axes of gene expression predicted spatially regulated expression of 870 genes along the anterior-posterior and mediolateral axes of the cranial neural plate and reproduced known expression patterns with over 85% accuracy. Single-cell RNA sequencing of embryos with activated SHH signaling revealed distinct SHH-regulated transcriptional programs in the developing forebrain, midbrain, and hindbrain, suggesting a complex interplay between anterior-posterior and mediolateral patterning systems. These results define a spatiotemporally resolved map of gene expression during cranial neural tube closure and provide a resource for investigating the transcriptional events that drive early mammalian brain development.
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Comprehensive mapping of Neurofibromin (NF1) expression in developing mouse brain.
Neurofibromin (NF1) is a critical negative regulator of the RAS-RAF-ERK pathway, mutations in which have been clinically implicated in various neurodevelopmental disorders. However, the lack of a high-resolution spatiotemporal map has obscured the understanding of why specific cell populations and developmental processes are uniquely vulnerable to NF1 loss. In this study, we present a comprehensive atlas of NF1 expression in the developing mouse brain. Using in situ hybridization and immunohistochemistry, we characterized NF1 distribution from early embryonic stages through postnatal maturation. We further integrated these findings with single-nuclei RNA-sequencing (snRNA-seq) datasets from adult mouse brain to achieve higher resolution. Our results reveal a previously undocumented graded expression pattern of NF1 across various brain regions and cell lineages. This comprehensive study will not only help understand the fundamental role of NF1 in brain development but will also be pivotal in providing a framework for studying NF1-associated brain disorders.
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Deep learning-based models for preimplantation mouse and human embryos based on single-cell RNA sequencing.
The rapid growth of single-cell transcriptomic technology has produced an increasing number of datasets for both embryonic development and in vitro pluripotent stem cell-derived models. This avalanche of data surrounding pluripotency and the process of lineage specification has meant it has become increasingly difficult to define specific cell types or states in vivo, and compare these with in vitro differentiation. Here we utilize a set of deep learning tools to integrate and classify multiple datasets. This allows the definition of both mouse and human embryo cell types, lineages and states, thereby maximizing the information one can garner from these precious experimental resources. Our approaches are built on recent initiatives for large-scale human organ atlases, but here we focus on material that is difficult to obtain and process, spanning early mouse and human development. Using publicly available data for these stages, we test different deep learning approaches and develop a model to classify cell types in an unbiased fashion at the same time as defining the set of genes used by the model to identify lineages, cell types and states. We used our models trained on in vivo development to classify pluripotent stem cell models for both mouse and human development, showcasing the importance of this resource as a dynamic reference for early embryogenesis.
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A 3D digital atlas of C. elegans and its application to single-cell analyses.
We built a digital nuclear atlas of the newly hatched, first larval stage (L1) of the wild-type hermaphrodite of Caenorhabditis elegans at single-cell resolution from confocal image stacks of 15 individual worms. The atlas quantifies the stereotypy of nuclear locations and provides other statistics on the spatial patterns of the 357 nuclei that could be faithfully segmented and annotated out of the 558 present at this developmental stage. We then developed an automated approach to assign cell names to each nucleus in a three-dimensional image of an L1 worm. We achieved 86% accuracy in identifying the 357 nuclei automatically. This computational method will allow high-throughput single-cell analyses of the post-embryonic worm, such as gene expression analysis, or ablation or stimulation of cells under computer control in a high-throughput functional screen.
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The molecular basis of scale development highlighted by a single-cell atlas of Bicyclus anynana butterfly pupal forewings.
Butterfly wings display a diversity of cell types, including large polyploid scale cells, yet the molecular basis of such diversity is poorly understood. To explore scale cell diversity at a transcriptomic level, we employ single-cell RNA sequencing of ∼5,200 large cells (>6 μm) from 22.5- to 25-h male pupal forewings of the butterfly Bicyclus anynana. Using unsupervised clustering, followed by in situ hybridization, immunofluorescence, and CRISPR-Cas9 editing of candidate genes, we annotate various cell types on the wing. We identify genes marking non-innervated scale cells, pheromone-producing glandular cells, and innervated sensory cell types. We show that senseless, a zinc-finger transcription factor, and HR38, a hormone receptor, determine the identity, size, and color of different scale cell types and are important regulators of scale cell differentiation. This dataset and the identification of various wing cell-type markers provide a foundation to compare and explore scale cell-type diversification across arthropod species.
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Distinct systemic impacts of Aβ42 and Tau revealed by whole-organism snRNA-seq.
Both neuronal and peripheral tissues become disrupted in Alzheimer's disease (AD). However, a comprehensive understanding of how AD impacts different tissues across the whole organism is lacking. Using Drosophila, we generated an AD Fly Cell Atlas (AD-FCA) based on whole-organism single-nucleus transcriptomes of 219 cell types from flies expressing AD-associated proteins, either human amyloid-β 42 peptide (Aβ42) or Tau, in neurons. We found that Aβ42 primarily affects the nervous system, including sensory neurons, while Tau induces accelerated aging in peripheral tissues. We identified a neuronal cluster enriched in Aβ42 flies, which has high lactate dehydrogenase (LDH) expression. This LDH-high cluster is conserved in 5XFAD mouse and human AD datasets. We found a conserved defect in fat metabolism from both fly and mouse tauopathy models. The AD-FCA offers new insights into how Aβ42 or Tau systemically and differentially affects a whole organism and provides a valuable resource for understanding brain-body communication in neurodegeneration.