A Dynamic Transcriptome Map of Different Tissue Microenvironment Cells Identified During Gastric Cancer Development Using Single-Cell RNA Sequencing

Gastric cancer (GC) development trends have identified multiple processes ranging from inflammation to carcinogenesis, however, key pathogenic mechanisms remain unclear. Tissue microenvironment (TME) cells are critical for the progression of malignant tumors. Here, we generated a dynamic transcriptome map of various TME cells during multi-disease stages using single-cell sequencing analysis. We observed a set of key transition markers related to TME cell carcinogenic evolution, and delineated landmark dynamic carcinogenic trajectories of these cells. Of these, macrophages, fibroblasts, and endothelial cells exerted considerable effects toward epithelial cells, suggesting these cells may be key TME factors promoting GC occurrence and development. Our results suggest a phenotypic convergence of different TME cell types toward tumor formation processes in GC. We believe our data would pave the way for early GC detection, diagnosis, and treatment therapies.

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Establishment of a Human Gastric Cancer Xenograft Model in Immunocompetent Mice Using the Microcarrier-6

BioMed Research International ◽

10.1155/2020/1893434 ◽

2020 ◽

Vol 2020 ◽

pp. 1-7

Author(s):

Yanzhen Bi ◽

Quanyi Wang ◽

Yonghong Yang ◽

Quanquan Wang ◽

Kai Zhang ◽

...

Keyword(s):

Gastric Cancer ◽

Animal Model ◽

Gastric Carcinoma ◽

Malignant Tumors ◽

Xenograft Model ◽

Tumor Formation ◽

Tumor Xenograft ◽

Gastric Neoplasms ◽

Human Gastric Cancer ◽

Immunocompetent Mice

Gastric cancer is among the most common malignant tumors of the digestive tract. Establishing a robust and reliable animal model is the foundation for studying the pathogenesis of cancer. The present study established a mouse model of gastric carcinoma by inoculating immunocompetent mice with MKN45 cells using microcarrier. Sixty male C57BL/6 mice were randomly divided into three groups: a 2D group, an empty carrier group, and a 3D group, according to the coculture system of MKN45 and the microcarrier. The mouse models were established by hypodermic injection. Time to develop tumor, rate of tumor formation, and pathological features were observed in each group. In the 3D group, the tumorigenesis time was short, while the rate of tumor formation was high (75%). There was no detectable tumor formation in either the 2D or the empty carrier group. Both H&E and immunohistochemical staining of the tumor xenograft showed characteristic evidence of human gastric neoplasms. The present study successfully established a human gastric carcinoma model in immunocompetent mice, which provides a novel and valuable animal model for the cancer research and development of anticancer drugs.

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Single-cell transcriptomes of pancreatic preinvasive lesions and cancer reveal acinar metaplastic cells’ heterogeneity

Nature Communications ◽

10.1038/s41467-020-18207-z ◽

2020 ◽

Vol 11 (1) ◽

Cited By ~ 1

Author(s):

Yehuda Schlesinger ◽

Oshri Yosefov-Levi ◽

Dror Kolodkin-Gal ◽

Roy Zvi Granit ◽

Luriano Peters ◽

...

Keyword(s):

Single Cell ◽

Malignant Lesion ◽

Tumor Development ◽

Initial Step ◽

Cell Types ◽

Tumor Formation ◽

Specific Cell ◽

Preinvasive Lesions ◽

Cell Transcriptome ◽

Single Cell Transcriptome

Abstract Acinar metaplasia is an initial step in a series of events that can lead to pancreatic cancer. Here we perform single-cell RNA-sequencing of mouse pancreas during the progression from preinvasive stages to tumor formation. Using a reporter gene, we identify metaplastic cells that originated from acinar cells and express two transcription factors, Onecut2 and Foxq1. Further analyses of metaplastic acinar cell heterogeneity define six acinar metaplastic cell types and states, including stomach-specific cell types. Localization of metaplastic cell types and mixture of different metaplastic cell types in the same pre-malignant lesion is shown. Finally, single-cell transcriptome analyses of tumor-associated stromal, immune, endothelial and fibroblast cells identify signals that may support tumor development, as well as the recruitment and education of immune cells. Our findings are consistent with the early, premalignant formation of an immunosuppressive environment mediated by interactions between acinar metaplastic cells and other cells in the microenvironment.

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Multi-modal single cell analysis reveals brain immune landscape plasticity during aging and gut microbiota dysbiosis

10.1101/2020.07.15.205377 ◽

2020 ◽

Author(s):

Samantha M. Golomb ◽

Ian H. Guldner ◽

Anqi Zhao ◽

Qingfei Wang ◽

Bhavana Palakurthi ◽

...

Keyword(s):

Single Cell ◽

Immune Cells ◽

Immune Cell ◽

Cell Types ◽

Cell Plasticity ◽

Tissue Microenvironment ◽

Gut Dysbiosis ◽

Resolution Single ◽

The Brain ◽

Gut Microbiota Dysbiosis

ABSTRACTThe brain contains a diverse array of immune cell types. The phenotypic and functional plasticity of brain immune cells collectively contribute to brain tissue homeostasis and disease progression. Immune cell plasticity is profoundly influenced by local tissue microenvironment cues and systemic factors. Yet, the transcriptional mechanism by which systemic stimuli, such as aging and gut microbiota dysbiosis, reshape brain immune cell plasticity and homeostasis has not been fully delineated. Using Cellular Indexing of Transcriptomes and Epitopes by sequencing (CITE-seq), we analyzed compositional and transcriptional changes of the brain immune landscape in response to aging and gut dysbiosis. We first examined the discordance between canonical surface marker-defined immune cell types (Cell-ID) and their transcriptome signatures, which suggested transcriptional plasticity among immune cells despite sharing the same cell surface markers. Specifically, inflammatory and patrolling Ly6C+ monocytes were shifted predominantly to a pro-inflammatory transcriptional program in the aged brain, while brain ILCs shifted toward an ILC2 transcriptional profile. Finally, aging led to an increase of ILC-like cells expressing a T memory stemness (Tscm) signature in the brain. Antibiotics (ABX)-induced gut dysbiosis reduced the frequency of ILCs exhibiting Tscm-like properties in the aged mice, but not in the young mice. Enabled by high-resolution single-cell molecular phenotyping, our study revealed that systemic changes due to aging and gut dysbiosis prime the brain environment for an increased propensity for neuroinflammation, which provided insights into gut dysbiosis in age-related neurological diseases.Manuscript SummaryGolomb et al. performed Cellular Indexing of Transcriptomes and Epitopes by sequencing (CITE-seq) on immune cells from the brains of young and aged mice with and without antibiotics-induced gut dysbiosis. High resolution, single cell immunophenotyping enabled the dissection of extensive transcriptional plasticity of canonically identified monocytes and innate lymphoid cells (ILCs) in the aged brain. Through differential gene expression and trajectory inference analyses, the authors revealed tissue microenvironment-dependent cellular responses influenced by aging and gut dysbiosis that may potentiate neuroinflammatory diseases.Graphical Abstract

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Phenotypic convergence in the brain: distinct transcription factors regulate common terminal neuronal characters

10.1101/243113 ◽

2018 ◽

Cited By ~ 2

Author(s):

Nikos Konstantinides ◽

Katarina Kapuralin ◽

Chaimaa Fadil ◽

Luendreo Barboza ◽

Rahul Satija ◽

...

Keyword(s):

Transcription Factors ◽

Single Cell ◽

Large Scale ◽

Single Cells ◽

Deep Understanding ◽

Cell Types ◽

Marker Genes ◽

Cell Type ◽

Functional Specification ◽

Phenotypic Convergence

SummaryTranscription factors regulate the molecular, morphological, and physiological characters of neurons and generate their impressive cell type diversity. To gain insight into general principles that govern how transcription factors regulate cell type diversity, we used large-scale single-cell mRNA sequencing to characterize the extensive cellular diversity in the Drosophila optic lobes. We sequenced 55,000 single optic lobe neurons and glia and assigned them to 52 clusters of transcriptionally distinct single cells. We validated the clustering and annotated many of the clusters using RNA sequencing of characterized FACS-sorted single cell types, as well as marker genes specific to given clusters. To identify transcription factors responsible for inducing specific terminal differentiation features, we used machine-learning to generate a ‘random forest’ model. The predictive power of the model was confirmed by showing that two transcription factors expressed specifically in cholinergic (apterous) and glutamatergic (traffic-jam) neurons are necessary for the expression of ChAT and VGlut in many, but not all, cholinergic or glutamatergic neurons, respectively. We used a transcriptome-wide approach to show that the same terminal characters, including but not restricted to neurotransmitter identity, can be regulated by different transcription factors in different cell types, arguing for extensive phenotypic convergence. Our data provide a deep understanding of the developmental and functional specification of a complex brain structure.

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Calcium Binding Protein S100A16 Expedites Proliferation, Invasion and EMT Process in Gastric Cancer

10.21203/rs.3.rs-674611/v1 ◽

2021 ◽

Author(s):

Xiaoying You ◽

Min Li ◽

Hongwei Cai ◽

Wenwen Zhang ◽

Ye Hong ◽

...

Keyword(s):

Gastric Cancer ◽

Molecular Mechanism ◽

Calcium Binding ◽

Malignant Tumors ◽

Binding Protein ◽

Calcium Binding Protein ◽

Tumor Formation ◽

Mesenchymal Transition

Abstract Background: Gastric cancer (GC) is one of the most common malignant tumors of the digestive system, which has been the second cause of cancer-related deaths worldwide. The distant metastasis is one of the main reasons for the high recurrence and mortality rate of GC patients. Hence, it is necessary to investigate the molecular mechanism underlying gastric carcinogenesis and progression, especially the key genes and signaling pathways that promote GC cells proliferation, invasion, and metastasis. Methods: Using bioinformatics and clinicopathological analysis, in vivo tumor formation assays, mass spectrometry and so on, we characterized the role and molecular mechanism of S100 Calcium Binding Protein A16 (S100A16) in promoting GC tumor growth, migration, invasion and epithelial-to-mesenchymal transition (EMT), and investigated how Zonula Occludens-2 (ZO-2) inhibition mediates S100A16-induced metastasis and progression in GC.Results: We analyzed S100A16 expression with the GEPIA database and the UALCAN cancer database, and the prognostic analysis was performed using 100 clinical GC samples. We found that S100A16 is significantly upregulated in GC tissues and closely correlated with poor prognosis in GC patients. Functional studies reveal that S100A16 overexpression triggers GC cells proliferation and migration both in vivo and in vitro; by contrast, S100A16 knockdown restricts the speed of GC cells growth and mobility. Proteomic analysis results reveal a large S100A16 interactome, which includes ZO-2, a master regulator of cell-to-cell tight junctions. Mechanistic assay results indicate that excessive S100A16 instigates GC cell invasion, migration and EMT via ZO-2 inhibition, which arose from S100A16-mediated ZO-2 ubiquitination and degradation. Conclusions: Our results not only reveal that S100A16 is a promising candidate biomarker in GC early diagnosis and prediction of metastasis, but also establish the therapeutic importance of targeting S100A16 in order to prevent ZO-2 loss and suppress GC metastasis and progression.

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IKAP—Identifying K mAjor cell Population groups in single-cell RNA-sequencing analysis

GigaScience ◽

10.1093/gigascience/giz121 ◽

2019 ◽

Vol 8 (10) ◽

Cited By ~ 2

Author(s):

Yun-Ching Chen ◽

Abhilash Suresh ◽

Chingiz Underbayev ◽

Clare Sun ◽

Komudi Singh ◽

...

Keyword(s):

Single Cell ◽

Rna Sequencing ◽

Cell Types ◽

Sequencing Analysis ◽

Sequencing Data ◽

Peripheral Blood Mononuclear ◽

Biologically Relevant ◽

Single Cell Rna Sequencing ◽

Cell Groups ◽

Cell Ontology

AbstractBackgroundIn single-cell RNA-sequencing analysis, clustering cells into groups and differentiating cell groups by differentially expressed (DE) genes are 2 separate steps for investigating cell identity. However, the ability to differentiate between cell groups could be affected by clustering. This interdependency often creates a bottleneck in the analysis pipeline, requiring researchers to repeat these 2 steps multiple times by setting different clustering parameters to identify a set of cell groups that are more differentiated and biologically relevant.FindingsTo accelerate this process, we have developed IKAP—an algorithm to identify major cell groups and improve differentiating cell groups by systematically tuning parameters for clustering. We demonstrate that, with default parameters, IKAP successfully identifies major cell types such as T cells, B cells, natural killer cells, and monocytes in 2 peripheral blood mononuclear cell datasets and recovers major cell types in a previously published mouse cortex dataset. These major cell groups identified by IKAP present more distinguishing DE genes compared with cell groups generated by different combinations of clustering parameters. We further show that cell subtypes can be identified by recursively applying IKAP within identified major cell types, thereby delineating cell identities in a multi-layered ontology.ConclusionsBy tuning the clustering parameters to identify major cell groups, IKAP greatly improves the automation of single-cell RNA-sequencing analysis to produce distinguishing DE genes and refine cell ontology using single-cell RNA-sequencing data.

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A single-cell analysis of the molecular lineage of chordate embryogenesis

Science Advances ◽

10.1126/sciadv.abc4773 ◽

2020 ◽

Vol 6 (45) ◽

pp. eabc4773

Author(s):

Tengjiao Zhang ◽

Yichi Xu ◽

Kaoru Imai ◽

Teng Fei ◽

Guilin Wang ◽

...

Keyword(s):

Single Cell ◽

Single Cell Analysis ◽

Cell Lineage ◽

Cell Types ◽

Gene Signature ◽

Mouse Cell ◽

Embryonic Cell ◽

Sequencing Analysis ◽

Lineage Differentiation ◽

In The Wild

Progressive unfolding of gene expression cascades underlies diverse embryonic lineage development. Here, we report a single-cell RNA sequencing analysis of the complete and invariant embryonic cell lineage of the tunicate Ciona savignyi from fertilization to the onset of gastrulation. We reconstructed a developmental landscape of 47 cell types over eight cell cycles in the wild-type embryo and identified eight fate transformations upon fibroblast growth factor (FGF) inhibition. For most FGF-dependent asymmetric cell divisions, the bipotent mother cell displays the gene signature of the default daughter fate. In convergent differentiation of the two notochord lineages, we identified additional gene pathways parallel to the master regulator T/Brachyury. Last, we showed that the defined Ciona cell types can be matched to E6.5-E8.5 stage mouse cell types and display conserved expression of limited number of transcription factors. This study provides a high-resolution single-cell dataset to understand chordate early embryogenesis and cell lineage differentiation.

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Inclusion of processed cell metadata improves single cell sequencing analysis reproducibility and accessibility

10.1101/2020.11.20.391920 ◽

2020 ◽

Author(s):

Sidhant Puntambekar ◽

Jay R. Hesselberth ◽

Kent A. Riemondy ◽

Rui Fu

Keyword(s):

Single Cell ◽

Developmental Stages ◽

Cell Types ◽

Biological Data ◽

Sufficient Information ◽

Sequencing Analysis ◽

Data Repositories ◽

Disease States ◽

Number Of Publications ◽

Reported Data

AbstractSingle cell RNA sequencing provides an unprecedented view of cellular diversity of biological systems. Thousands of scRNA-seq datasets have been generated, providing a wealth of biological data on the diversity of cell types across different organisms, developmental stages, and disease states. But while a tremendous number of publications and datasets have been generated using this technology, we found that a minority (< 25%) of studies provide sufficient information to enable direct reuse of their data for further studies. This problem is common across journals, data repositories, and publication dates. The lack of appropriate information not only hinders exploration and knowledge transfer of reported data, but also makes reproducing the original study prohibitively difficult and/or time-consuming. Correcting this problem is not easy but we encourage investigators, reviewers, journals, and data repositories to take steps to improve their standards and ensure proper documentation of these valuable datasets.

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Single-Cell RNAseq analysis of infiltrating neoplastic cells at the migrating front of human glioblastoma

10.1101/165811 ◽

2017 ◽

Cited By ~ 1

Author(s):

Spyros Darmanis ◽

Steven A. Sloan ◽

Derek Croote ◽

Marco Mignardi ◽

Sophia Chernikova ◽

...

Keyword(s):

Single Cell ◽

Immunological Response ◽

Myeloid Cell ◽

Cell Types ◽

Gene Signature ◽

Tumor Formation ◽

Common Mechanism ◽

Significant Heterogeneity ◽

Neoplastic Cells ◽

And Migration

SummaryGlioblastoma is the most common primary brain cancer in adults and is notoriously difficult to treat due to its diffuse nature. We performed single-cell RNAseq on 3589 cells in a cohort of four patients. We obtained cells from the tumor core as well as surrounding peripheral tissue. Our analysis revealed cellular variation in the tumor’s genome and transcriptome, We were able to identify infiltrating neoplastic cells in regions peripheral to the core lesions. Despite the existence of significant heterogeneity among neoplastic cells, we found that infiltrating GBM cells share a consistent gene signature between patients, suggesting a common mechanism of infiltration. Additionally, in investigating the immunological response to the tumors, we found transcriptionally distinct myeloid cell populations residing in the tumor core and the surrounding peritumoral space. Our data provide a detailed dissection of GBM cell types, revealing an abundance of novel information about tumor formation and migration.

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CBIO-14. SINGLE CELL RNA SEQUENCING ANALYSIS OF HUMAN GLIOBLASTOMA STEM-LIKE CELL CULTURES AND XENOGRAFT TUMORS

Neuro-Oncology ◽

10.1093/neuonc/noab196.114 ◽

2021 ◽

Vol 23 (Supplement_6) ◽

pp. vi30-vi30

Author(s):

Sonali Arora ◽

Anca Mihalas ◽

John Bassett ◽

Anoop Patel ◽

Patrick Paddison

Keyword(s):

Single Cell ◽

Developmental Trajectories ◽

Expression Patterns ◽

Experimental Models ◽

Tumor Formation ◽

Sequencing Analysis ◽

Rna Seq ◽

Human Glioblastoma

Abstract Single cell RNA-seq (scRNA-seq) studies for glioma have yielded critical insight into intratumoral heterogeneity and developmental gene expression patterns for primary gliomas. One key conclusion from these studies is that each tumor represents a complex, yet maligned, neuro-developmental ecosystem, harboring diverse cell types, which presumably contribute to tumor growth and homeostasis in specific ways (e.g., vascular mimicry, immune evasion, recreating NSC niches, neural injury responses, etc.). Here, to better understand experimental models of human glioblastoma (GB), we performed single cell RNA-seq analysis of human GB stem-like cells (GSCs) of distinct tumor subtypes (mesenchymal and proneural) during their in vitro culture in serum-free conditions and also during tumor formation in immunocompromised mice. This analysis revealed surprising differences between in vitro and in vivo grown GSCs. Among our results, we find that in vivo mesenchymal GSCs are capable of transitioning to proneural-like states, while proneural GSCs are capable of transitioning to mesenchymal states. We characterize cycling cells based on expression of and G2/M and S phase makers, estimate RNA velocity, and examine different developmental trajectories arising in vitro and in vivo. We also compare and discuss different analysis pipelines for scRNA-seq data.

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