ArticleOncotarget2017
A comprehensively characterized cell line panel highly representative of clinical ovarian high-grade serous carcinomas.
Article in Oncotarget, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 17 papers.
What it found
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
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Who cites it
17 citing papers in PubMed.
- Detection of phosphatidylserine-positive exosomes as a diagnostic marker for ovarian malignancies: a proof of concept study.Oncotarget · 2017Trial
- RACK1 MARylation regulates translation and stress granules in ovarian cancer cells.The Journal of cell biology · 2025Article
- Exploiting a living biobank to delineate mechanisms underlying disease-specific chromosome instability.Chromosome research : an international journal on the molecular, supramolecular and evolutionary aspects of chromosome biology · 2023Review
- Article
- A Scalable 3D High-Content Imaging Protocol for Measuring a Drug Induced DNA Damage Response Using Immunofluorescent Subnuclear γH2AX Spots in Patient Derived Ovarian Cancer Organoids.ACS pharmacology & translational science · 2023Article
- Article
- LncRNA SPOCD1-AS from ovarian cancer extracellular vesicles remodels mesothelial cells to promote peritoneal metastasis via interacting with G3BP1.Journal of experimental & clinical cancer research : CR · 2021Article
- Article
- Article
- A living biobank of ovarian cancer ex vivo models reveals profound mitotic heterogeneity.Nature communications · 2020Article
- ADP-Ribosylation Levels and Patterns Correlate with Gene Expression and Clinical Outcomes in Ovarian Cancers.Molecular cancer therapeutics · 2020Article
- An organoid platform for ovarian cancer captures intra- and interpatient heterogeneity.Nature medicine · 2019Article
- ClickGene: an open cloud-based platform for big pan-cancer data genome-wide association study, visualization and exploration.BioData mining · 2019Article
- Dysregulation of fibulin-5 and matrix metalloproteases in epithelial ovarian cancer.Oncotarget · 2018Article
- Ovarian Cancers: Genetic Abnormalities, Tumor Heterogeneity and Progression, Clonal Evolution and Cancer Stem Cells.Medicines (Basel, Switzerland) · 2018Review
- The organoid: A research model for ovarian cancer.Tzu chi medical journalReview
- Comparison of the Cost and Effect of Combined Conditioned Medium and Conventional Medium for Fallopian Tube Organoid Cultures.Cell transplantationArticle
Corrections and comments
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Authors and funding
19 authors.
Funding
Abstract
Recent literature suggests that most widely used ovarian cancer (OVCA) cell models do not recapitulate the molecular features of clinical tumors. To address this limitation, we generated 18 cell lines and 3 corresponding patient-derived xenografts predominantly from high-grade serous carcinoma (HGSOC) peritoneal effusions. Comprehensive genomic characterization and comparison of each model to its parental tumor demonstrated a high degree of molecular similarity. Our characterization included whole exome-sequencing and copy number profiling for cell lines, xenografts, and matched non-malignant tissues, and DNA methylation, gene expression, and spectral karyotyping for a subset of specimens. Compared to the Cancer Genome Atlas (TCGA), our models more closely resembled HGSOC than any other tumor type, justifying their validity as OVCA models. Our meticulously characterized models provide a crucial resource for the OVCA research community that will advance translational findings and ultimately lead to clinical applications.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.