Browse
Submit Data
Databases
API
Help

Dataset Information

0 Views

0 Connections

0 Citations

0 Reanalyses

0 Downloads

Omics score: 0

Chemoresistance in high grade serous ovarian cancer

ABSTRACT: Chemoresistance in high grade serous ovarian cancer

PROVIDER: PRJNA679861 | ENA |

REPOSITORIES: ENA

ACCESS DATA

Json Xml

Dataset's files

Source:

			Action	DRS
		Other

Items per page:

1 - 1 of 1

Similar Datasets

Chemoresistance in high grade serous ovarian cancer

Project description:Chemoresistance in high grade serous ovarian cancer

| PRJNA679860 | ENA

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

miRNA profiling in high-grade serous ovarian carcinoma

Project description:In this study, we performed miRNA profiles analysis of high-grade serous ovarian carcinoma compared to normal fallopian tube fimbria using microarray (Exiqon, Denmark) to evaluate their potential role in the pathogenesis of uterine leiomyoma. miRNA profiling analysis of the 10 samples including 5 high-grade serous ovarian carcinomas and 5 normal fallopian tube fimbria.

2014-11-14 | E-GEOD-61485 | biostudies-arrayexpress

Affymetrix SNP array data for high-grade serous ovarian cancer samples

Project description:High-grade serous ovarian cancer is the most aggressive histological type of epithelial ovarian cancer, which is characterized by a high frequency of somatic TP53 mutations. To provide a better understanding of the molecular mechanisms involved in the pathogenesis of these cancers and to develop a risk classification system, we conducted profiling of the copy number alterations present in these tumors. Thirty patients who were diagnosed as high-grade serous ovarian cancer were recruited in this study. Affymetrix SNP array were performed according to the manufacturer's directions on DNA extracted from high-grade serous ovarian cancer tissues or peripheral blood samples. The Japanese Serous Ovarian Cancer Study Group

2015-09-05 | E-GEOD-61237 | biostudies-arrayexpress

5-Hydroxymethylcytosine signals in serum are a predictor of chemoresistance in high-grade serous ovarian cancer

Project description:The genome-wide profiling of 5-hydroxymethylcytosine (5hmC) on circulating cell-free DNA (cfDNA) has revealed promising biomarkers for a variety of diseases. The purpose of our study is to investigate if 5hmC profiles from serum cfDNA are novel predictive biomarkers for the development of chemoresistance in high-grade serous ovarian cancer (HGSOC). We hypothesized that 5-hmC profiles associate with the development of chemoresistance and elucidate pathways that may drive chemoresistance in HGSOC. We developed a novel multivariate model based on clinico-pathologic data and a cfDNA-derived 5hmC-annotated gene that can predict response to platinum-based chemotherapy in intermediate-sensitive HGSOC. These results merit further investigation of our model as a predictive model.

2024-01-25 | GSE240535 | GEO

VISTA+ Neutrophils Enhance Chemoresistance in High-Grade Serous Ovarian Cancer by Suppressing CD8+ T Cells Infiltration

Project description:Platinum-based chemoresistance is a primary cause of treatment failure and unfavorable prognosis in high-grade serous ovarian cancer (HGSOC). Although inflammation plays a critical role in chemoresistance, in which neutrophils (Neus) emerge as potent inflammatory regulator across various cancers, the precise mechanisms linking Neus to chemoresistance in HGSOC patients are not well understood. Here, we conducted a retrospective review of HGSOC patients treated with adjuvant chemotherapy, analyzing clinicopathological data and laboratory parameters to show a significant correlation between neutrophil-to-lymphocyte ratio and chemotherapy efficacy. Further experiments revealed an increase in Neus among chemoresistant patients. Proteomic analysis and single-cell RNA sequencing identified VISTA+ Neus as a potent prognostic predictor. In vivo, VISTA blockade reduced VISTA+ Neus infiltration, but increased CD8+T cells within tumor tissues, thereby enhancing chemosensitivity. Our findings highlight the role of VISTA+ Neus in chemoresistance and suggest that targeting these cells could be a novel therapeutic strategy to enhance chemosensitivity in HGSOC.

2026-07-01 | PXD062992 | Pride

Platinum-resistant high-grade serous ovarian carcinoma

Project description:Platinum-resistant high-grade serous ovarian carcinoma

| PRJNA1147589 | ENA

Gene expression in High-Grade Serous Ovarian Cancer (HGSOC) cells

Project description:Gene expression in High-Grade Serous Ovarian Cancer (HGSOC) cells

2024-12-31 | GSE214904 | GEO

Dual Morphologic Subtypes of High-Grade Serous Ovarian Cancer

Project description:We identified novel, gross morphology-based subtypes of high-grade serous ovarian cancer, with unique clinical features and molecular signatures.

2022-05-31 | GSE204748 | GEO

Ovarian high grade serous carcinoma ascites cell proteoms

Project description:Tumor cells, macrophages and T cells from high grade serous ovarian carcinoma from the ascites of patients undergoing primary surgery were analysed without culturing (ex vivo) via obitrap.

2017-11-17 | PXD006138 | Pride

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