Browse
Submit Data
Databases
API
Help

Dataset Information

0 Views

0 Connections

0 Citations

0 Reanalyses

0 Downloads

Omics score: 0

Profiles of genomic instability in high-grade serous ovarian cancer (HGSC) predict treatment outcome

ABSTRACT: Profiling of loss of heterozygosity (LOH) in HGSC, subcrouping HGSC by LOH-based clustering and comparing to the LOH profiles of triple-negative breast cancer [previously submitted; GSE19594]. Study for the correlation of LOH burdern and LOH-based subgroups to clinical response to platinum-based chemotherapy in patients suffered from HGSC.

ORGANISM(S): Homo sapiens

PROVIDER: GSE39130 | GEO | 2012/11/06

SECONDARY ACCESSION(S): PRJNA170063

REPOSITORIES: GEO

ACCESS DATA

Json Xml

Dataset's files

Source:

			Action	DRS
		Other

Items per page:

1 - 1 of 1

Similar Datasets

Profiles of genomic instability in high-grade serous ovarian cancer (HGSC) predict treatment outcome

Project description:Profiling of loss of heterozygosity (LOH) in HGSC, subcrouping HGSC by LOH-based clustering and comparing to the LOH profiles of triple-negative breast cancer [previously submitted; GSE19594]. Study for the correlation of LOH burdern and LOH-based subgroups to clinical response to platinum-based chemotherapy in patients suffered from HGSC. SNP data (Affymetrix GenChip 250K SNP Nsp) from 47 high grade serous ovarian cancer were generated and used for LOH and copy number analysis, LOH-based hierarchical clustering to subclassify HGSC, and comparison to the chromosomal alterations in high grade brest cancer. The associstion between LOH-based subgroups and LOH burden and clinical resposne to platinum-based chemotherapy was investigated. The results were validated in two independent public opening datasets.

2012-11-06 | E-GEOD-39130 | biostudies-arrayexpress

Expression data from high-grade serous ovarian carcinomas (HGSC), clear cell ovarian carcinomas (CCC) and ovarian surface epithelium (OSE)

Project description:Background: The aim of this study was to identify differentially expressed miRNAs in high-grade serous ovarian carcinoma (HGSC), clear cell ovarian carcinoma (CCC) and ovarian surface epithelium (OSE). Selected miRNAs were evaluated for association with clinical parameters including survival, and miRNA/mRNA interactions were mapped. Results: Differentially expressed miRNAs between HGSC, CCC and OSE were identified, of which 18 were validated (p<0.01) using RT-qPCR in an extended cohort. Compared with OSE, miR-205-5p was the most overexpressed miRNA in HGSC. miR-200 family members and miR-182-5p were the most overexpressed in HGSC and CCC compared with OSE, whereas miR-383 was the most underexpressed. miR-509-3-5p, miR-509-5p, miR-509-3p and miR-510 were among the strongest differentiators between HGSC and CCC, all being significantly overexpressed in CCC compared with HGSC. High miR-200c-3p expression was associated with poor progression-free (p=0.031) and overall (p=0.026) survival in HGSC. Interacting miRNAs and mRNA targets, including those of a TP53-related pathway presented previously, were identified in HGSC. Conclusions: Several miRNAs are overexpressed in HGSC and CCC compared with OSE, including the miR-200 family, among which miR-200c-3p is associated with survival in HGSC. A set of miRNAs differentiates CCC from HGSC, of which miR-509-3-5p and miR-509-5p are the strongest classifiers. Several interactions between miRNAs and mRNAs in HGSC were mapped. Methods: Differences in miRNA expression between HGSC, CCC and OSE scrapings were analyzed by global miRNA expression profiling (Affymetrix GeneChip miRNA 2.0 Arrays, n=30), validated by RT-qPCR (n=63), and evaluated for associations with clinical parameters. For HGSC, differentially expressed miRNAs were linked to differentially expressed mRNAs identified previously (GSE36668).

2014-02-13 | E-GEOD-47841 | biostudies-arrayexpress

A combination of molecular and clinical parameters provides a new strategy for high-grade serous ovarian cancer patient management

Project description:High-grade serous carcinoma (HGSC) is the most common and deadly subtype of ovarian cancer. Although most patients will initially respond to first-line treatment with a combination of surgery and platinum-based chemotherapy, up to a quarter will be resistant to treatment. We aimed to identify a new strategy to improve HGSC patient management at the time of cancer diagnosis (HGSC-1LTR). Using proteomics in ready-available HGSC tissues, we have identified a molecular signature (TKT, LAMC1 and FUCO) that combined with ready available clinical data is able to predict patient response to first-line treatment (AUC: 0.82). Identification of chemoresistance at the time of diagnosis can facilitate the study of alternative treatments aimed at improving patient outcome. In addition, those patients classified as chemosensitive could undergo standard care with platinum-based agents. Therefore, the HGSC-1LTR strategy can allow optimization of therapeutic decision making and individualize HGSC patients’ care

2023-03-11 | PXD035084 | Pride

Expression data from high-grade serous ovarian carcinomas (HGSC), clear cell ovarian carcinomas (CCC) and ovarian surface epithelium (OSE)

2014-02-13 | GSE47841 | GEO

Analysis of transcription profile for High Grade Serous Ovarian Cancer (HGSC) cell line panel and how it relates to chromosomal instability (CIN)

Project description:Seven HGSC cancer cell lines were analysed with two immortalised Fallopian tube derived cell lines as controls. RNAseq was used to identify which genes showed transcript changes in cell lines showing particular phenotypes for chromosomal instability; enrichment of genes in particular pathways was used to identify possible mechanisms of CIN.

2020-10-02 | GSE155310 | GEO

Single cell RNA sequencing of human high-grade serous ovarian cancer (HGSC) cells and human immortalized fallopian tube epitheilal (FTE) cells

Project description:The goal of this experiment was to generate scRNA-seq data for human HGSC cells and human FTE cells. FTE is the progenitor cell type for HGSC.

2020-06-15 | GSE150864 | GEO

Upregulation of FOXM1 Induces Genomic Instability in Human Epidermal Keratinocytes

Project description:Genome-wide 10k SNP profiling of FOXM1B-transduced N/TERT and primary normal human epidermal keratinocytes (NHEK). The aim of this study was to study the cancer initiation role of UVB and FOXM1B upregulation in NHEK. Upregulation of FOXM1B alone (without UVB) was found to directly induce genomic instability in the form of copy number aberration (CNA) and low levels of loss of heterozygosity (LOH) in primary NHEK. The FOXM1B-induced CNA was found to be retained and accumulated in subsequent cell culture passages. UVB-exposure resulted in significant chromosomal LOH and CNA in N/TERT cells expressing FOXM1B but not in EGFP-expressing cells. This indicates that UVB corroborated with FOXM1B to recruit LOH and CNA which may predispose cell to malignant transformation. Collectively, these results indicate that aberrant upregulation of FOXM1B in skin keratinocytes following UVB exposure may be an early mechanism whereby cells acquire genomic changes required for oncogenesis. Keywords: Genome-wide SNP profiling for loss of heterozygosity (LOH) and copy number aberration (CNA), FOXM1, UVB, Keratinocytes, Basal cell carcinoma, genomic instability, carcinogenesis, squamous cell carcinoma.

2010-06-28 | GSE16937 | GEO

Platinum chemotherapy induces diverse evolutionary trajectories in high grade serous ovarian cancer

Project description:Cisplatin- and carboplatin-resistant high-grade serous ovarian cancer (HGSC) cells were generated and new lines were created from single cell clones. All cells were derived from a common ancestral line, Ovcar4. RNA sequencing was performed to examine transcriptional changes related to acquisition of platinum resistance.

2022-08-01 | GSE141630 | GEO

BCM-HGSC Rodent Genome Projects

Project description:BCM-HGSC Rodent Genome Projects

| PRJNA170428 | ENA

Gene Expression Profiling in progesterone-induced HGSC development.

Project description:Here we show that ovarian progesterone is a crucial endogenous factor inducing metastatic ovarian cancer in a mouse model of high-grade serous carcinoma (HGSC). To examine the molecular signaling pathways underlying progesterone (P4)-induced HGSC development, we performed gene-expression profiling using RNA sequencing.

2020-12-29 | GSE157960 | 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