Homo sapiens
Ontology highlight
ABSTRACT:
PROVIDER: PRJNA120721 | ENA |
REPOSITORIES: ENA
Similar Datasets
Project description:<p>BRCA1 mutations are a hallmark of hereditary ovarian cancer, strongly linked to deficiencies in homologous recombination (HR) DNA repair and impaired DNA replication fork protection. However, its roles in cancer progression beyond maintaining genomic integrity remain poorly understood. Through metabolomics approaches, we found BRCA1-deficiency strikingly increased choline metabolism. Loss of BRCA1 promotes choline uptake through upregulating choline transporter-like protein 4 (CTL4). BRCA1 directly binds and recruits EZH2-mediated H3K27Me3 deposition to CTL4 promoter. CTL4 was therefore overexpressed in ovarian cancer tissues with BRCA1 mutations. Furthermore, BRCA1-deficiency significantly promotes ovarian cancer invasion, while inhibition of CTL4 reverses the high metastatic potential of BRCA1-deficient ovarian cancer cells, suggesting the functionality and specificity of CTL4 as a therapeutic target. Additionally, we discovered that phosphocholine, the choline metabolite increased by CTL4 overexpression, interacted with and stabilized the epithelial-to-mesenchymal transition inducer FAM3C in BRCA1-deficient ovarian cancer cells. Importantly, we identified a potent CTL4 inhibitor, DT-13, which significantly reduces choline metabolism and effectively suppresses metastasis in BRCA1-deficient ovarian cancers. Therefore, our study uncovers a mechanism underlying metastasis in BRCA1-deficient cancers and identifies CTL4 as a therapeutic target for metastatic ovarian cancer patients with BRCA1 mutations.</p>
2026-05-15 | MTBLS12245 | MetaboLights
Project description:Gene expression profile of ascites cell samples from patients with advanced ovarian cancer
| PRJNA121559 | ENA
Project description:Prediction of progression-free survival in patients with advanced-stage serous ovarian cancer
| PRJNA118945 | ENA
Project description:microRNA alterations associated to clinical response in advanced stage ovarian cancer patients (training set)
| PRJNA142789 | ENA
Project description:microRNA alterations associated to clinical response in advanced stage ovarian cancer patients (test set)
| PRJNA142791 | ENA
Project description:microRNA alterations associated to early relapse in advanced stage ovarian cancer patients (validation set)
| PRJNA280993 | ENA
Project description:RNA extracted at 240min. Samples are rRNA depleted. Expression measurement of Homo sapiens genes.
2019-07-31 | GSE114179 | GEO
Project description:Identification of a Potential Ovarian Cancer Stem Cell Gene Expression Profile from Advanced Stage Papillary Serous Ovarian Cancer
| PRJNA148341 | ENA
Project description:The Japanese Serous Ovarian Cancer Study Group Advanced-stage ovarian cancer is one of the most lethal gynecologic malignancies. To improve prognosis of patients with ovarian cancers, a predictive biomarkers leading to personalized treatments are required. In this large-scale cross-platform study of six microarray datasets consisting of 1054 ovarian cancer patients, we developed a novel risk classification system based on a 126-gene expression signature for predicting overall survival by applying elastic net7 and 10-fold cross validation to a Japanese dataset A (n = 260). We further validated its predictive ability with the five other datasets using multivariate analysis. Also, through gene ontology and pathway analyses of 1109 high-risk ovarian cancer specific transcripts, we identified a significant reduction of expression of immune-response related genes, especially on the antigen presentation pathway. Furthermore, an immunohistochemical analysis demonstrated that the number of CD8 T lymphocytes infiltrating into tumor tissue was significantly decreased in high-risk ovarian cancers. These predictive biomarkers based on the 126-gene expression signature will identify high-risk ovarian cancer patients who need novel immune-activating therapeutic approaches, leading to improved outcomes for such patients. Two hundred sixty patients who were diagnosed as advanced-stage high-grade serous ovarian cancer were analyzed in this study. Microaray data from 10 patients who were diagnosed as advanced-stage high-grade serous ovarian cancer were analyzed to investigate coefficient of correlation in each probes between Agilent Whole Human Genome Oligo Microarray and Affymetrix HG-U133Plus2.0.
2012-03-01 | E-GEOD-32062 | biostudies-arrayexpress
Project description:Gene expression and mutation profiles in advanced-stage epithelial ovarian cancer (EOC)
| PRJNA1198652 | ENA