Homo sapiens
Ontology highlight
ABSTRACT:
PROVIDER: PRJNA137447 | 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:Purpose: Clinicopathologic features and biochemical recurrence are sensitive, but not specific, predictors of metastatic disease and lethal prostate cancer. We hypothesize that a genomic expression signature detected in the primary tumor represents true biological potential of aggressive disease and provides improved prediction of early prostate cancer metastasis. Methods: A nested case-control design was used to select 639 patients from the Mayo Clinic tumor registry that underwent radical prostatectomy between 1987 and 2001. A genomic classifier (GC) was developed by modeling differential RNA expression using 1.4 million feature high-density expression arrays of men enriched for rising PSA after prostatectomy, including 213 that experienced early clinical metastasis after biochemical recurrence. A training set was used to develop a random forest classifier of 22 markers to predict for cases - men with early clinical metastasis after rising PSA. Performance of GC was compared to prognostic factors such as Gleason score and previous gene expression signatures in a withheld validation set. Results: Expression profiles were generated from 545 unique patient samples, with median follow-up of 16.9 years. GC achieved an area under the receiver operating characteristic curve of 0.75 (0.67 - 0.83) in validation, outperforming clinical variables and gene signatures. GC was the only significant prognostic factor in multivariable analyses. Within Gleason score groups, cases with high GC scores experienced earlier death from prostate cancer and reduced overall survival. The markers in the classifier were found to be associated with a number of key biological processes in prostate cancer metastatic disease progression. Conclusion: A genomic classifier was developed and validated in a large patient cohort enriched with prostate cancer metastasis patients and a rising PSA that went on to experience metastatic disease. This early metastasis prediction model based on genomic expression in the primary tumor may be useful for identification of aggressive prostate cancer. 545 formalin-fixed paraffin-embedded (FFPE) tissue samples from primary prostate cancer obtained from Radical Prostatectomy.
2013-07-01 | E-GEOD-46691 | biostudies-arrayexpress
Project description:Optimizing molecular signatures for prostate cancer recurrence
| PRJNA134591 | ENA
Project description:Integrative Genomic and Proteomic Analysis of Prostate Cancer Reveals Signatures of Metastatic Progression
| PRJNA93223 | ENA
Project description: Not available
| S-EPMC2531291 | biostudies-literature
Project description:Protein 4.1B suppresses prostate cancer progression and metastasis
| PRJNA100091 | ENA
Project description:RNA extracted at 240min. Samples are rRNA depleted. Expression measurement of Homo sapiens genes.
2019-07-31 | GSE114179 | GEO
Project description:Stromal molecular signatures of breast and prostate cancer
| PRJNA136171 | ENA
Project description:EphA6 promotes angiogenesis and prostate cancer metastasis and is associated with human prostate cancer progression
| PRJNA276564 | ENA
Project description:Prostate Adenocarcinoma: Candidate Genomic Signatures Prognostic of Biochemical Failure
| PRJNA100129 | ENA