Browse
Submit Data
Databases
API
Help

Dataset Information

0 Views

0 Connections

0 Citations

0 Reanalyses

0 Downloads

Omics score: 0

Single-cell analysis reveals the stromal dynamics and tumor-specific characteristics in the microenvironment of ovarian cancer

ABSTRACT: Single-cell analysis reveals the stromal dynamics and tumor-specific characteristics in the microenvironment of ovarian cancer

PROVIDER: PRJNA971598 | ENA |

REPOSITORIES: ENA

ACCESS DATA

Json Xml

Dataset's files

Source:

			Action	DRS
	SRR24512444.fastq.gz	Fastqsanger.gz
	SRR24512445.fastq.gz	Fastqsanger.gz
	SRR24512446.fastq.gz	Fastqsanger.gz
	SRR24512447.fastq.gz	Fastqsanger.gz

Items per page:

1 - 4 of 4

Similar Datasets

Comprehensive single-cell sequencing reveals the stromal dynamics and tumor-specific characteristics in the microenvironment of nasopharyngeal carcinoma

Project description:The tumor microenvironment (TME) of nasopharyngeal carcinoma (NPC) harbors a heterogeneous and dynamic stromal population. A comprehensive understanding of this tumor-specific ecosystem is necessary to enhance cancer diagnosis, therapeutics, and prognosis. However, recent advances based on bulk RNA sequencing remain insufficient to construct an in-depth landscape of infiltrating stromal cells in NPC. Here we apply single-cell RNA sequencing to 66,627 cells from 14 patients, integrated with clonotype identification on T and B cells. We identify and characterize five major stromal clusters and 36 distinct subpopulations based on genetic profiling. By comparing with the infiltrating cells in the non-malignant microenvironment, we report highly representative features in the TME, including phenotypic abundance, genetic alternations, immune dynamics, clonal expansion, developmental trajectory, and molecular interactions that profoundly influence patient prognosis and therapeutic outcome. The key findings are further independently validated in two single-cell RNA sequencing cohorts and two bulk RNA-sequencing cohorts. In the present study, we reveal the correlation between NPC-specific characteristics and progression-free survival. Together, these data facilitate the understanding of the stromal landscape and immune dynamics in NPC patients and provides deeper insights into the development of prognostic biomarkers and therapeutic targets in the TME.

2021-01-11 | GSE150825 | GEO

Single-cell analysis reveals the stromal dynamics and tumor-specific characteristics in the microenvironment of ovarian cancer

Project description:We characterized high-grade ovarian serous carcinoma TIME based on integrative single-cell transcriptomics analysis of public and in-house datasets. We identified a distinct transcriptomic landscape of both immune and non-immune cells between the dense and more sparse stromal tumors. High stromal tumors contain a lower fraction of infiltrating activated CXCR3+ GRZB+ IFN+ IL2R+ CD8+ T and NCR3+ KLRD1+ natural killer (NK) cells and CXCL1+ macrophages. Next, we determined the potential interplays between non-immune and immune cells. High stromal tumors showed increased expression of CXCL12 in epithelial cancer cells and CA-MSCs. Cell-cell communication analyses suggested that epithelial cancer cells and CA-MSCs secreted CXCL12 interacts with the CXCR4 receptor on NK and CD8+ T cells. Using CXCL12 and/or CXCR4 neutralizing antibodies, we confirmed the immunosuppressive role of the CXCL12-CXCR4 axis in CA-MSC-induced immune suppression.

2024-01-07 | GSE232314 | GEO

Comprehensive single-cell sequencing reveals the stromal dynamics and tumor-specific characteristics in the microenvironment of nasopharyngeal carcinoma

Project description:Comprehensive single-cell sequencing reveals the stromal dynamics and tumor-specific characteristics in the microenvironment of nasopharyngeal carcinoma

| PRJNA633797 | ENA

Gene-expression profiles of ovarian cancer regarding its microenvironment

Project description:PD-L1 suppresses host immunity and promotes tumor growth. We investigated how IFN-? regulates PD-L1 in the ovarian cancer microenvironment. In clinical samples, the number of stromal CTLs in peritoneally disseminated tumors was correlated with PD-L1 expression on the tumor cells, and the lymphocyte number was significantly related to the IFN-? signature score. In mouse models, PD-L1 was induced in peritoneal disseminated tumors, where lymphocytes were prominent, but not in subcutaneous tumors. Depleting IFNGR1 resulted in lower PD-L1 expression and longer survival in peritoneal dissemination model. Injection of IFN-? into subcutaneous tumors increased PD-L1 expression and tumor size, and PD-L1 depletion abrogated tumor growth. These data suggest that IFN-? works as a tumor progressor through PD-L1 induction. The source of IFN-? in ovarian cancer microenvironment and its biological effect to the tumor cells is unclear. The immortalized human ovarian surface epithelial cell line, HOSE-E7/hTERT (HOSE) was treated with IFN-? and expression microarray analysis was performed, and probes showing significantly higher values in IFN-?-added group were termed “IFN-? signature genes (295 probes)”. We then applied this signature to our ovarian cancer microarray data, which included 75 ovarian cancer clinical samples, by means of ss-GSEA. IFN-? signature score was strongly correlated to the number of infiltrating CD4-positive or CD8-positive lymphocytes in the tumors. These data suggest that the IFN-? in the ovarian cancer microenvironment is derived from lymphocytes, and an IFN-?-rich microenvironment is strongly correlated to a lymphocyte-rich microenvironment. Genome-wide transcriptional changes in human ovarian cancer tissue were observed in different tumor immunological microenvironment.

2014-03-04 | E-GEOD-55512 | biostudies-arrayexpress

Ovarian Cancer Dynamics

Project description:Dynamics in Ovarian Cancer Evolution

| PRJEB4193 | ENA

Gene expession profiles of p16high and p16low stromal cells in PDAC tumor microenvironment

Project description:We used scRNA-seq analysis to investigate the characteristics and communication of p16high cancer stromal cells in the tumor microenvironment.

2025-01-31 | GSE252684 | GEO

mRNA transcriptome data of normal ovarian stromal cells and tumor ovarian stromal cells

Project description:mRNA transcriptome data of normal ovarian stromal cells and tumor ovarian stromal cells

| PRJNA938139 | ENA

Gene-expression profiles of ovarian cancer regarding its microenvironment

Project description:PD-L1 suppresses host immunity and promotes tumor growth. We investigated how IFN-γ regulates PD-L1 in the ovarian cancer microenvironment. In clinical samples, the number of stromal CTLs in peritoneally disseminated tumors was correlated with PD-L1 expression on the tumor cells, and the lymphocyte number was significantly related to the IFN-γ signature score. In mouse models, PD-L1 was induced in peritoneal disseminated tumors, where lymphocytes were prominent, but not in subcutaneous tumors. Depleting IFNGR1 resulted in lower PD-L1 expression and longer survival in peritoneal dissemination model. Injection of IFN-γ into subcutaneous tumors increased PD-L1 expression and tumor size, and PD-L1 depletion abrogated tumor growth. These data suggest that IFN-γ works as a tumor progressor through PD-L1 induction. The source of IFN-γ in ovarian cancer microenvironment and its biological effect to the tumor cells is unclear. The immortalized human ovarian surface epithelial cell line, HOSE-E7/hTERT (HOSE) was treated with IFN-γ and expression microarray analysis was performed, and probes showing significantly higher values in IFN-γ-added group were termed “IFN-γ signature genes (295 probes)”. We then applied this signature to our ovarian cancer microarray data, which included 75 ovarian cancer clinical samples, by means of ss-GSEA. IFN-γ signature score was strongly correlated to the number of infiltrating CD4-positive or CD8-positive lymphocytes in the tumors. These data suggest that the IFN-γ in the ovarian cancer microenvironment is derived from lymphocytes, and an IFN-γ-rich microenvironment is strongly correlated to a lymphocyte-rich microenvironment.

2014-03-04 | GSE55512 | GEO

Dual-species microarray for assessing gene expression in stromal microenvironment, cancer cells and their interactions

Project description:This SuperSeries is composed of the following subset Series: GSE23054: Dual-species microarray for assessing gene expression in stromal microenvironment, cancer cells and their interactions (v1 array) GSE23364: Dual-species microarray for assessing gene expression in stromal microenvironment, cancer cells and their interactions (v2 array) Refer to individual Series

2010-08-04 | E-GEOD-23377 | biostudies-arrayexpress

Exosomal Transfer of Stromal Cell-Derived miR21 Confers Taxol Resistance in High-grade Serous Ovarian Cancer Cells Through Down-Regulation of APAF1.

Project description:Advanced ovarian cancer usually spreads to the visceral adipose tissue of the omentum. However, the stromal cell-derived molecular determinants that modulate ovarian cancer growth have not been characterized. Here, we identified significantly higher levels of miR21 in exosomes and tissue lysate isolated from cancer associated adipocytes (CAA) and fibroblasts (CAF) compared to those from ovarian cancer cells. Functional studies and transcriptome analysis on miR21 transfected SKOV3 ovarian cancer cells revealed that miR21 could be transferred from CAA or CAF to ovarian cancer cells and modulate ovarian cancer apoptosis and chemoresistance through binding to its direct target APAF1. These data suggest that malignant phenotype of metastatic ovarian cancer cells can be modulated by miR21 delivered by exosomes derived from neighboring stromal cells in the omental tumor microenvironment.

2016-03-21 | GSE51457 | GEO

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