Browse
Submit Data
Databases
API
Help

Dataset Information

31 Views

0 Connections

0 Citations

0 Reanalyses

0 Downloads

Omics score: 0

Single-cell transcriptional profiling reveals the heterogeneity in embryonal rhabdomyosarcoma.

ABSTRACT:

Abstract

Rhabdomyosarcoma is the most common soft tissue sarcoma in children, and embryonal rhabdomyosarcoma is the most typical type of rhabdomyosarcoma. The heterogeneity, etiology, and origin of embryonal rhabdomyosarcoma remain unknown.After obtaining the gene expression data of every cell in the tumor tissue by single-cell RNA sequencing, we used the Seurat package in R studio for quality control, analysis, and exploration of the data. All cells are divided into tumor cells and non-tumor cells, and we chose tumor cells by marker genes. Then, we repeated the process to cluster the tumor cells and divided the subgroups by their differentially expressed genes and gene ontology/Kyoto Encyclopedia of Genes and Genomes analysis. Additionally, Monocle 2 was used for pseudo-time analysis to obtain the evolution trajectory of cells in tumor tissues.Tumor cells were divided into 5 subgroups according to their functions, which were characterized by high proliferation, sensing and adaptation to oxygen availability, enhanced epigenetic modification, enhanced nucleoside phosphonic acid metabolism, and ossification. Evolution trajectory of cells in tumor tissues is obtained.We used pseudo-time analysis to distinguish between mesenchymal stem cells and fibroblasts, proved that embryonal rhabdomyosarcoma in the pelvic originated from skeletal muscle progenitor cells, showed the evolutionary trajectory of embryonal rhabdomyosarcoma, and improved the method of evaluating the degree of malignancy of embryonal rhabdomyosarcoma.

SUBMITTER: Hong B

PROVIDER: S-EPMC8341243 | biostudies-literature |

REPOSITORIES: biostudies-literature

ACCESS DATA

Json Xml

Similar Datasets

Single cell transcriptional profiling reveals heterogeneity of human induced pluripotent stem cells.

Project description:Human induced pluripotent stem cells (hiPSCs) and human embryonic stem cells (hESCs) are promising candidate cell sources for regenerative medicine. However, despite the common ability of hiPSCs and hESCs to differentiate into all 3 germ layers, their functional equivalence at the single cell level remains to be demonstrated. Moreover, single cell heterogeneity amongst stem cell populations may underlie important cell fate decisions. Here, we used single cell analysis to resolve the gene expression profiles of 362 hiPSCs and hESCs for an array of 42 genes that characterize the pluripotent and differentiated states. Comparison between single hESCs and single hiPSCs revealed markedly more heterogeneity in gene expression levels in the hiPSCs, suggesting that hiPSCs occupy an alternate, less stable pluripotent state. hiPSCs also displayed slower growth kinetics and impaired directed differentiation as compared with hESCs. Our results suggest that caution should be exercised before assuming that hiPSCs occupy a pluripotent state equivalent to that of hESCs, particularly when producing differentiated cells for regenerative medicine aims.

| S-EPMC3049389 | biostudies-literature

Single-cell mRNA profiling reveals transcriptional heterogeneity among pancreatic circulating tumour cells.

Project description:BackgroundSingle-cell mRNA profiling of circulating tumour cells may contribute to a better understanding of the biology of these cells and their role in the metastatic process. In addition, such analyses may reveal new knowledge about the mechanisms underlying chemotherapy resistance and tumour progression in patients with cancer.MethodsSingle circulating tumour cells were isolated from patients with locally advanced or metastatic pancreatic cancer with immuno-magnetic depletion and immuno-fluorescence microscopy. mRNA expression was analysed with single-cell multiplex RT-qPCR. Hierarchical clustering and principal component analysis were performed to identify expression patterns.ResultsCirculating tumour cells were detected in 33 of 56 (59%) examined blood samples. Single-cell mRNA profiling of intact isolated circulating tumour cells revealed both epithelial-like and mesenchymal-like subpopulations, which were distinct from leucocytes. The profiled circulating tumour cells also expressed elevated levels of stem cell markers, and the extracellular matrix protein, SPARC. The expression of SPARC might correspond to an epithelial-mesenchymal transition in pancreatic circulating tumour cells.ConclusionThe analysis of single pancreatic circulating tumour cells identified distinct subpopulations and revealed elevated expression of transcripts relevant to the dissemination of circulating tumour cells to distant organ sites.

| S-EPMC5452374 | biostudies-literature

In vivo imaging of tumor-propagating cells, regional tumor heterogeneity, and dynamic cell movements in embryonal rhabdomyosarcoma.

Project description:Embryonal rhabdomyosarcoma (ERMS) is an aggressive pediatric sarcoma of muscle. Here, we show that ERMS-propagating potential is confined to myf5+ cells and can be visualized in live, fluorescent transgenic zebrafish. During early tumor growth, myf5+ ERMS cells reside adjacent normal muscle fibers. By late-stage ERMS, myf5+ cells are reorganized into distinct regions separated from differentiated tumor cells. Time-lapse imaging of late-stage ERMS revealed that myf5+ cells populate newly formed tumor only after seeding by highly migratory myogenin+ ERMS cells. Moreover, myogenin+ ERMS cells can enter the vasculature, whereas myf5+ ERMS-propagating cells do not. Our data suggest that non-tumor-propagating cells likely have important supportive roles in cancer progression and facilitate metastasis.

| S-EPMC3381357 | biostudies-literature

Single-cell transcriptome profiling reveals vascular endothelial cell heterogeneity in human skin.

Project description:Vascular endothelial cells (ECs) are increasingly recognized as active players in intercellular crosstalk more than passive linings of a conduit for nutrition delivery. Yet, their functional roles and heterogeneity in skin remain uncharacterized. We have used single-cell RNA sequencing (scRNA-seq) as a profiling strategy to investigate the tissue-specific features and intra-tissue heterogeneity in dermal ECs at single-cell level. Methods: Skin tissues collected from 10 donors were subjected to scRNA-seq. Human dermal EC atlas of over 23,000 single-cell transcriptomes was obtained and further analyzed. Arteriovenous markers discovered in scRNA-seq were validated in human skin samples via immunofluorescence. To illustrate tissue-specific characteristics of dermal ECs, ECs from other human tissues were extracted from previously reported data and compared with our transcriptomic data. Results: In comparison with ECs from other human tissues, dermal ECs possess unique characteristics in metabolism, cytokine signaling, chemotaxis, and cell adhesions. Within dermal ECs, 5 major subtypes were identified, which varied in molecular signatures and biological activities. Metabolic transcriptome analysis revealed a preference for oxidative phosphorylation in arteriole ECs when compared to capillary and venule ECs. Capillary ECs abundantly expressed HLA-II molecules, suggesting its immune-surveillance role. Post-capillary venule ECs, with high levels of adhesion molecules, were equipped with the capacity in immune cell arrest, adhesion, and infiltration. Conclusion: Our study provides a comprehensive characterization of EC features and heterogeneity in human dermis and sets the stage for future research in identifying disease-specific alterations of dermal ECs in various dermatoses.

| S-EPMC8120211 | biostudies-literature

Single-cell transcriptome profiling reveals neutrophil heterogeneity in homeostasis and infection.

Project description:The full neutrophil heterogeneity and differentiation landscape remains incompletely characterized. Here, we profiled >25,000 differentiating and mature mouse neutrophils using single-cell RNA sequencing to provide a comprehensive transcriptional landscape of neutrophil maturation, function and fate decision in their steady state and during bacterial infection. Eight neutrophil populations were defined by distinct molecular signatures. The three mature peripheral blood neutrophil subsets arise from distinct maturing bone marrow neutrophil subsets. Driven by both known and uncharacterized transcription factors, neutrophils gradually acquire microbicidal capability as they traverse the transcriptional landscape, representing an evolved mechanism for fine-tuned regulation of an effective but balanced neutrophil response. Bacterial infection reprograms the genetic architecture of neutrophil populations, alters dynamic transitions between subpopulations and primes neutrophils for augmented functionality without affecting overall heterogeneity. In summary, these data establish a reference model and general framework for studying neutrophil-related disease mechanisms, biomarkers and therapeutic targets at single-cell resolution.

| S-EPMC7442692 | biostudies-literature

Single-cell profiling reveals GPCR heterogeneity and functional patterning during neuroinflammation.

Project description:GPCR expression was intensively studied in bulk cDNA of leukocyte populations, but limited data are available with respect to expression in individual cells. Here, we show a microfluidic-based single-cell GPCR expression analysis in primary T cells, myeloid cells, and endothelial cells under naive conditions and during experimental autoimmune encephalomyelitis, the mouse model of multiple sclerosis. We found that neuroinflammation induces characteristic changes in GPCR heterogeneity and patterning, and we identify various functionally relevant subgroups with specific GPCR profiles among spinal cord-infiltrating CD4 T cells, macrophages, microglia, or endothelial cells. Using GPCRs CXCR4, S1P1, and LPHN2 as examples, we show how this information can be used to develop new strategies for the functional modulation of Th17 cells and activated endothelial cells. Taken together, single-cell GPCR expression analysis identifies functionally relevant subpopulations with specific GPCR repertoires and provides a basis for the development of new therapeutic strategies in immune disorders.

| S-EPMC5543912 | biostudies-literature

Single-cell transcriptional profiling reveals the heterogenicity in colorectal cancer.

Project description:BackgroundColorectal Cancer (CRC) is a highly heterogeneous disease. RNA profiles of bulk tumors have enabled transcriptional classification of CRC. However, such ways of sequencing can only target a cell colony and obscure the signatures of distinct cell populations. Alternatively, single-cell RNA sequencing (scRNA-seq), which can provide unbiased analysis of all cell types, opens the possibility to map cellular heterogeneity of CRC unbiasedly.MethodsIn this study, we utilized scRNA-seq to profile cells from cancer tissue of a CRC patient. Gene ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analyses were performed to understand the roles of genes within the clusters.Results and conclusionThe 2824 cells were analyzed and categorized into 5 distinct clusters by scRNA-seq. For every cluster, specific cell markers can be applied, indicating each 1 of them different from another. We discovered that the tumor of CRC displayed a clear sign of heterogenicity, while genes within each cluster serve different functions. GO term analysis also stated that different cluster's relatedness towards the tumor of CRC differs. Three clusters participate in peripheral works in cells, including, energy transport, extracellular matrix generation, etc; Genes in other 2 clusters participate more in immunology processes. Lastly, trajectory plot analysis also supports the viewpoint, in that some clusters present in different states and pseudo-time, while others present in a single state or pseudo time. Our analysis provides more insight into the heterogeneity of CRC, which can provide assistance to further researches on this topic.

| S-EPMC6716720 | biostudies-literature

Defining an embryonal rhabdomyosarcoma endotype.

Project description:Rhabdomyosarcoma (RMS) is the most common childhood soft-tissue sarcoma. The largest subtype of RMS is embryonal rhabdomyosarcoma (ERMS) and accounts for 53% of all RMS. ERMS typically occurs in the head and neck region, bladder, or reproductive organs and portends a promising prognosis when localized; however, when metastatic the 5-yr overall survival rate is ∼43%. The genomic landscape of ERMS demonstrates a range of putative driver mutations, and thus the recognition of the pathological mechanisms driving tumor maintenance should be critical for identifying effective targeted treatments at the level of the individual patients. Here, we report genomic, phenotypic, and bioinformatic analyses for a case of a 3-yr-old male who presented with bladder ERMS. Additionally, we use an unsupervised agglomerative clustering analysis of RNA and whole-exome sequencing data across ERMS and undifferentiated pleomorphic sarcoma (UPS) tumor samples to determine several major endotypes inferring potential targeted treatments for a spectrum of pediatric ERMS patient cases.

| S-EPMC7133750 | biostudies-literature

Single cell transcriptome analysis of muscle satellite cells reveals widespread transcriptional heterogeneity.

Project description:Tissue specific stem cells are indispensable contributors to adult tissue maintenance, repair, and regeneration. In skeletal muscle, satellite cells (SCs) are the resident muscle stem cell population and are required to maintain skeletal muscle homeostasis throughout life. Increasing evidence suggests that SCs are a heterogeneous cell population with substantial biochemical and functional diversity. A major limitation in the field is an incomplete understanding of the nature and extent of this cellular heterogeneity. Single cell analyses are well suited to addressing this issue, especially when coupled to unbiased profiling paradigms such as high throughout RNA sequencing. We performed single cell RNA sequencing (scRNA-seq) on freshly isolated muscle satellite cells and found a surprising degree of heterogeneity at multiple levels, from muscle-specific transcripts to the broader SC transcriptome. We leveraged several comparative bioinformatics techniques and found that individual SCs enrich for unique transcript clusters. We propose that these gene expression "fingerprints" may contribute to observed functional SC diversity. Overall, these studies underscore the importance of several established SC signaling pathways/processes on a single cell level, implicate novel regulators of SC heterogeneity, and lay the groundwork for further investigation into SC heterogeneity in health and disease.

| S-EPMC5659767 | biostudies-literature

Single-cell analysis reveals transcriptional heterogeneity of neural progenitors in human cortex.

Project description:The human cerebral cortex depends for its normal development and size on a precisely controlled balance between self-renewal and differentiation of diverse neural progenitor cells. Specialized progenitors that are common in humans but virtually absent in rodents, called outer radial glia (ORG), have been suggested to be crucial to the evolutionary expansion of the human cortex. We combined progenitor subtype-specific sorting with transcriptome-wide RNA sequencing to identify genes enriched in human ORG, which included targets of the transcription factor neurogenin and previously uncharacterized, evolutionarily dynamic long noncoding RNAs. Activating the neurogenin pathway in ferret progenitors promoted delamination and outward migration. Finally, single-cell transcriptional profiling in human, ferret and mouse revealed more cells coexpressing proneural neurogenin targets in human than in other species, suggesting greater neuronal lineage commitment and differentiation of self-renewing progenitors. Thus, we find that the abundance of human ORG is paralleled by increased transcriptional heterogeneity of cortical progenitors.

| S-EPMC5568903 | biostudies-literature

OmicsDI is part of the ELIXIR infrastructure

OmicsDI is an Elixir interoperability service. Learn more ›

Tweets

OmicsDI Databases

PRIDE
PeptideAtlas
MassIVE
JPOST Repository
Physiome Model Repository

EGA
EVA
ENA
LINCS
PAXDB
Cell Collective

MetaboLights
Metabolomics Workbench
MetabolomeExpress
GNPS
BioModels
FAIRDOMHub

ArrayExpress
dbGaP
ExpressionAtlas
GEO
NODE

Information

Databases
Help
API
Contact us
Code on GitHub
Terms of use
Submit Data