Single Cell RNAseq of blood and tumor from renal cancer patients
Ontology highlight
ABSTRACT:
PROVIDER: EGAC00001001494 | EGA |
REPOSITORIES: EGA
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Project description:Data Access Committee EGAC00001001605
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Project description:Single-cell RNA sequencing (scRNAseq) represents a new kind of microscope that can measure the transcriptome profiles of thousands of individual cells from complex cellular mixtures, such as in a tissue, in a single experiment. This technology is particularly valuable for characterization of tissue heterogeneity because it can be used to identify and classify all cell types in a tissue. This is generally done by clustering the data, based on the assumption that cells of a particular type share similar transcriptomes, distinct from other cell types in the tissue. However, nearly all clustering algorithms have tunable parameters which affect the number of clusters they will identify in data. The R Shiny software tool described here, scClustViz, provides a simple interactive graphical user interface for exploring scRNAseq data and assessing the biological relevance of clustering results. Given that cell types are expected to have distinct gene expression patterns, scClustViz uses differential gene expression between clusters as a metric for assessing the fit of a clustering result to the data at multiple cluster resolution levels. This helps select a clustering parameter for further analysis. scClustViz also provides interactive visualisation of: cluster-specific distributions of technical factors, such as predicted cell cycle stage and other metadata; cluster-wise gene expression statistics to simplify annotation of cell types and identification of cell type specific marker genes; and gene expression distributions over all cells and cell types. scClustViz provides an interactive interface for visualisation, assessment, and biological interpretation of cell-type classifications in scRNAseq experiments that can be easily added to existing analysis pipelines, enabling customization by bioinformaticians while enabling biologists to explore their results without the need for computational expertise. It is available at https://baderlab.github.io/scClustViz/.
| S-EPMC6456841 | biostudies-literature
Project description:Glioblastoma (GBM) is the most common malignant primary brain tumor and remains incurable. Previous work has shown that systemic administration of Decitabine (DAC) induces sufficient expression of NY-ESO-1 in GBM for targeting by adoptive T-cell therapy in vivo. However, the mechanisms by which DAC enhances immunogenicity in GBM remain to be elucidated. Using patient tissue, immortalized glioma cells, and primary patient-derived gliomaspheres, we demonstrate in vitro that basal NY-ESO-1 expression is restricted by promoter hypermethylation in gliomas. DAC treatment of glioma cells specifically inhibits DNA methylation silencing and renders NY-ESO-1 an inducible tumor antigen. Targeting of DAC-induced NY-ESO-1 in primary GBM cells promotes specific and polyfunctional NY-ESO-1 TCR-T cell responses. DAC further upregulates other tumor-associated cancer testis antigens concomitantly with tumor-intrinsic reactivation of human endogenous retroviruses (hERV) and type I interferon. Overall, we demonstrate that DAC promotes an inducible tumor antigen and enhances T cell functionality against GBM.
2024-06-04 | GSE261190 | GEO
Project description:Bladder cancer, one of the most prevalent malignancies worldwide, remains hard to classify due to a staggering molecular complexity. Despite a plethora of diagnostic tools and therapies, it is hard to outline the key steps leading up to the transition from high-risk non-muscle-invasive bladder cancer (NMIBC) to muscle-invasive bladder cancer (MIBC). Carcinogen-induced murine models can recapitulate urothelial carcinogenesis and natural anti-tumor immunity. Herein, we have developed and profiled a novel model of progressive NMIBC based on 10 weeks of OH-BBN exposure in hepatocyte growth factor/cyclin dependent kinase 4 (R24C) (Hgf-Cdk4R24C) mice. The profiling of the model was performed by histology grading, single cell transcriptomic and proteomic analysis, while the derivation of a tumorigenic cell line was validated and used to assess in vivo anti-tumor effects in response to immunotherapy. Established NMIBC was present in females at 10 weeks post OH-BBN exposure while neoplasia was not as advanced in male mice, however all mice progressed to MIBC. Single cell RNA sequencing analysis revealed an intratumoral heterogeneity also described in the human disease trajectory. Moreover, although immune activation biomarkers were elevated in urine during carcinogen exposure, anti-programmed cell death protein 1 (anti-PD1) monotherapy did not prevent tumor progression. Furthermore, anti-PD1 immunotherapy did not control the growth of subcutaneous tumors formed by the newly derived urothelial cancer cell line. However, treatment with CpG-oligodeoxynucleotides (ODN) significantly decreased tumor volume, but only in females. In conclusion, the molecular map of this novel preclinical model of bladder cancer provides an opportunity to further investigate pharmacological therapies ahead with regards to both targeted drugs and immunotherapies to improve the strategies of how we should tackle the heterogeneous tumor microenvironment in urothelial bladder cancer to improve responses rates in the clinic.
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Project description:Single Cell RNAseq on Renal adenocarcinoma
| PRJNA670875 | ENA
Project description:Glioblastoma (GBM) is the most common malignant primary brain tumor and remains incurable. Previous work has shown that systemic administration of Decitabine (DAC) induces sufficient expression of NY-ESO-1 in GBM for targeting by adoptive T-cell therapy in vivo. However, the mechanisms by which DAC enhances immunogenicity in GBM remain to be elucidated. Using patient tissue, immortalized glioma cells, and primary patient-derived gliomaspheres, we demonstrate in vitro that basal NY-ESO-1 expression is restricted by promoter hypermethylation in gliomas. DAC treatment of glioma cells specifically inhibits DNA methylation silencing and renders NY-ESO-1 an inducible tumor antigen. Targeting of DAC-induced NY-ESO-1 in primary GBM cells promotes specific and polyfunctional NY-ESO-1 TCR-T cell responses. DAC further upregulates other tumor-associated cancer testis antigens concomitantly with tumor-intrinsic reactivation of human endogenous retroviruses (hERV) and type I interferon. Overall, we demonstrate that DAC promotes an inducible tumor antigen and enhances T cell functionality against GBM.
2024-06-03 | GSE261188 | GEO
Project description:Glioblastoma (GBM) is the most common malignant primary brain tumor and remains incurable. Previous work has shown that systemic administration of Decitabine (DAC) induces sufficient expression of NY-ESO-1 in GBM for targeting by adoptive T-cell therapy in vivo. However, the mechanisms by which DAC enhances immunogenicity in GBM remain to be elucidated. Using patient tissue, immortalized glioma cells, and primary patient-derived gliomaspheres, we demonstrate in vitro that basal NY-ESO-1 expression is restricted by promoter hypermethylation in gliomas. DAC treatment of glioma cells specifically inhibits DNA methylation silencing and renders NY-ESO-1 an inducible tumor antigen. Targeting of DAC-induced NY-ESO-1 in primary GBM cells promotes specific and polyfunctional NY-ESO-1 TCR-T cell responses. DAC further upregulates other tumor-associated cancer testis antigens concomitantly with tumor-intrinsic reactivation of human endogenous retroviruses (hERV) and type I interferon. Overall, we demonstrate that DAC promotes an inducible tumor antigen and enhances T cell functionality against GBM.
2024-06-03 | GSE261187 | GEO
Project description:We used droplet based Single cell RNA sequencing (10x genomics) on sorted cell from tumor and juxta tumor tissue to explore myeloid cell diversity and metabolism in tumor microenvironement
2020-11-16 | GSE159913 | GEO
Project description:In the last decade, single cell RNAseq (scRNAseq) datasets have grown in size from a single cell to millions of cells. Due to its high dimensionality, it is not always feasible to visualize scRNAseq data and share it in a scientific report or an article publication format. Recently, many interactive analysis and visualization tools have been developed to address this issue and facilitate knowledge transfer in the scientific community. In this study, we review several of the currently available scRNAseq visualization tools and benchmark the subset that allows to visualize the data on the web and share it with others. We consider the memory and time required to prepare datasets for sharing as the number of cells increases, and additionally review the user experience and features available in the web interface. To address the problem of format compatibility we have also developed a user-friendly R package, sceasy, which allows users to convert their own scRNAseq datasets into a specific data format for visualization.
| S-EPMC7391988 | biostudies-literature