Browse
Submit Data
Databases
API
Help

Dataset Information

0 Views

0 Connections

0 Citations

0 Reanalyses

0 Downloads

Omics score: 0

Transcriptomes of high-grade serous ovarian cancer cell lines cultured in monolayer and in spheroids.

ABSTRACT: HGSOC cancer cell lines OvCAR3 and G164 were cultured in monolayer and spheroids and subjected to RNA-sequencing.

ORGANISM(S): Homo sapiens

PROVIDER: GSE235099 | GEO | 2024/05/02

REPOSITORIES: GEO

ACCESS DATA

Json Xml

Similar Datasets

The whole transcriptome expression profiling comparison between the ovarian cancer spheroids and monolayer cells

Project description:To discover the core gene expression features of ovarian cancer spheroids The compared the whole transcript expression profiling between 5 pairs of spheroids and monolayer cancer cells, including the RMG1, MCAS and Ov432 plus two cases of serous ovarian cancer ascites cells.

2017-08-31 | GSE60252 | GEO

Transcription profiling of human foreskin fibroblasts grown as multicellular spheroids or as a monolayer

Project description:Human foreskin fibroblasts grown as multicellular spheroids or as a monolayer

2009-12-30 | E-MEXP-1226 | biostudies-arrayexpress

microRNA profiling of serum microRNA from high grade serous ovarian carcinoma

Project description:High-grade serous ovarian carcinoma (HGSOC) is the most lethal gynecologic neoplasm, with five-year survival rate below 30%. Early disease detection is of utmost importance to improve the cure rate of HGSOC. Liquid biopsies are now becoming a new paradigm to develop novel biomarkers with diagnostic and prognostic purposes. The focus of this study was to detect the levels of circulating miRNAs in tissues and sera from patients with HGSOC and to evaluate their diagnostic value. To this end, an array-based discovery platform, followed by an innovative statistical approach of data normalization, was exploited, to identify miRNA species selectively expressed in serum of patients with HGSOC. Sera from 106 high grade serous ovarian carcinoma (HGSOC) and 24 healthy controls were used for profiling serum microRNA using a modified version of a commercially available microarray, with the aim of identifying differentially expressed microRNA between tumor patients and healthy controls.

2017-01-30 | E-MTAB-4667 | biostudies-arrayexpress

Gene microarray data for HT-29 monolayer and spheroids

Project description:Colorectal cancers have a rare population of cells that express specific cell surface markers, and are referred to as cancer stem cells (CSC). Targeting CSCs, implicated in tumor relapse, is a paradigm shifting approach for colorectal cancer. We used gene microarray to analyze gene expression in HT-29, a colon cancer cell line, grown as monolayer and spheroid and identify metabolic pathways that are upregulated. HT-29 monolayer cells were grown in DMEM/F12 media supplemented with 10% FBS, and 1X Antibiotic-Antimycotic liquid (AA); and spheroids were grown in stem cell media [DMEM:F12, 1X AA, 1X B27, epidermal growth factors, and fibroblast growth factor for five days. Total RNA was isolated using the mirVana™ miRNA Isolation Kit according to the manufacturer's protocol. RNA intergrity was confirmed on the Nanodrop ND-1000 and analyzed with Agilent 2100 bioanalyzer. The arrays were scanned with the Affymetrix 3000 7G plus scanner.

2015-04-01 | E-GEOD-65433 | biostudies-arrayexpress

Evaluation of Tumor Infiltrating Lymphocytes in High-Grade Serous Ovarian Cancer

Project description:Tumor infiltrating lymphocytes (TILs) play a significant role in the tumor microenvironment in high-grade serous ovarian cancer (HGSOC). To better understand the interactions and functions of TILs in HGSOC progression, we performed proteogenomic profiling of TILs in 65 tumors collected from 12 HGSOC patients.

2024-03-15 | PXD045710 | Pride

RNA-Seq of pre-chemo high-grade serous ovarian tumors

Project description:We performed RNA sequencing on 10 bulk pre-chemo tumor samples collected from 5 patients with HGSOC.

2020-12-14 | GSE160085 | GEO

Single-cell RNA sequencing samples from high-grade serous ovarian cancer (HGSOC)

Project description:We measured gene expression in single-cell RNA sequencing samples from patients with high-grade serous ovarian cancer (HGSOC), for a study on improving HGSOC subtype definition by taking into account varying cell type proportions within tumors.

2020-10-03 | GSE158937 | GEO

Classification of High-Grade Serous Ovarian Cancer Using Tumor Morphologic Characteristics

Project description:Despite the similar histologic appearances of high-grade serous ovarian cancers (HGSOCs), clinical observations point to marked differences in their gross appearances. Some patients have numerous small nodules, whereas others have bulkier disease; some patients have widespread disease, whereas others have more localized disease. However, a systematic framework for classifying such gross morphologic differences does not exist. The implementation of a laparoscopic triage algorithm for patients with advanced HGSOC enabled us to prospectively obtain detailed video images of HGSOC that could be analyzed to identify morphologic subtypes. In this study, we aimed to develop and characterize a gross morphologic classification system for HGSOC. Specifically, we assessed whether HGSOC can be reliably divided into distinct gross morphologic subtypes and whether such subtypes have different clinical outcomes and molecular features.

2023-01-27 | PXD031518 | Pride

High grade serous ovarian cancer organoids as models of chromosomal instability

Project description:High-grade serous ovarian carcinoma (HGSOC) is the most genomically complex cancer, characterised by ubiquitous TP53 mutation, profound structural variation and heterogeneity. Multiple mutational processes driving chromosomal instability can be distinguished by specific copy number signatures. To develop clinically relevant models of these mutational processes we derived 15 continuous HGSOC patient-derived organoids (PDOs) and provide detailed transcriptomic and genomic profiles using shallow whole genome sequencing single cell and bulk analysis. We show that PDOs comprise communities of different clonal populations and represent models of CCNE1 amplification, chromothripsis, tandem-duplicator phenotype and whole genome duplication. PDOs can also be used as exploratory tools to study transcriptional effects of copy number alterations as well as compound-sensitivity tests. In summary, HGSOC PDO cultures provide a genomic tool for studies of specific mutational processes and precision therapeutics.

2022-07-17 | GSE208216 | GEO

LncRNA and mRNA expression profiles in High-grade serous ovarian cancer, Low-grade serous ovarian cancer and Normal fallopian tube

Project description:Ovarian cancer is the most lethal gynecologic cancer. High-grade serous ovarian carcinoma (HGSOC) is the most common histologic subtype, accounting for three quarters of ovarian cancer. To clarify the changes of gene expression in serous ovarian cancer, we performed lncRNA and mRNA microarrays to identify differentially expressed lncRNAs and mRNAs in High-grade and Low-grade serous ovarian carcinoma compared with Normal fallopian tube.

2020-02-12 | GSE135886 | GEO

OmicsDI is part of the ELIXIR infrastructure

OmicsDI is an Elixir interoperability service. Learn more ›

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