ArticleNucleic acids research2016
Prior knowledge transfer across transcriptional data sets and technologies using compositional statistics yields new mislabelled ovarian cell line.
Article in Nucleic acids research, 2016. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 24 papers.
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Who cites it
24 citing papers in PubMed, 28 citations in OpenAlex.
- Genome-Wide Assessment of DNA Methylation Fidelity Identifies Representative Ovarian Cancer Cell Line Models.Journal of cellular and molecular medicine · 2026Article
- Enhanced expression of ADAMTS1 in ovarian carcinomas: loss of ADAMTS1 expression instigates cellular reprogramming of extracellular matrix ensuing altered plasticity, augmented migration and attenuated adhesion.Journal of biomedical science · 2026Article
- Suppression of AKT Activation Through LZK Inhibition Limits Tumor Growth in Esophageal and Head and Neck Cancers.Molecular cancer therapeutics · 2026Article
- Cancer-selective photoimmunotherapy spares T cells and NK cells and promotes antitumor immunity in an allogeneic human 3D culture model.Photochemistry and photobiology · 2026Article
- Models of high-grade serous carcinoma of tubo-ovarian origin.Oncology reviews · 2026Review
- Beyond light scattering: the effects of intralipid on benzoporphyrin derivative-sensitized photodynamic treatment in ovarian cancer cells.Journal of biomedical optics · 2025Article
- Cell-intrinsic platinum response and associated genetic and gene expression signatures in ovarian cancer.Cancer gene therapy · 2025Article
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- A Revised Molecular Model of Ovarian Cancer Biomarker CA125 (MUC16) Enabled by Long-read Sequencing.Cancer research communications · 2024Article
- Auranofin Induces Lethality Driven by Reactive Oxygen Species in High-Grade Serous Ovarian Cancer Cells.Cancers · 2023Article
- Evaluation of mitochondrial biogenesis and ROS generation in high-grade serous ovarian cancer.Frontiers in oncology · 2023Article
- DNA barcoded competitive clone-initiating cell analysis reveals novel features of metastatic growth in a cancer xenograft model.NAR cancer · 2022Article
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- PAUF as a Target for Treatment of High PAUF-Expressing Ovarian Cancer.Frontiers in pharmacology · 2022Article
- Adipokine Apelin/APJ Pathway Promotes Peritoneal Dissemination of Ovarian Cancer Cells by Regulating Lipid Metabolism.Molecular cancer research : MCR · 2021Article
- The Ratio of Toxic-to-Nontoxic miRNAs Predicts Platinum Sensitivity in Ovarian Cancer.Cancer research · 2021Article
- Cell-autonomous inflammation of BRCA1-deficient ovarian cancers drives both tumor-intrinsic immunoreactivity and immune resistance via STING.Cell reports · 2021Article
- Inhibition of the MYC-Regulated Glutaminase Metabolic Axis Is an Effective Synthetic Lethal Approach for Treating Chemoresistant Ovarian Cancers.Cancer research · 2020Article
Corrections and comments
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Authors and funding
13 authors at 6 institutions in 2 countries.
Funding
Abstract
Here, we describe gene expression compositional assignment (GECA), a powerful, yet simple method based on compositional statistics that can validate the transfer of prior knowledge, such as gene lists, into independent data sets, platforms and technologies. Transcriptional profiling has been used to derive gene lists that stratify patients into prognostic molecular subgroups and assess biomarker performance in the pre-clinical setting. Archived public data sets are an invaluable resource for subsequent in silico validation, though their use can lead to data integration issues. We show that GECA can be used without the need for normalising expression levels between data sets and can outperform rank-based correlation methods. To validate GECA, we demonstrate its success in the cross-platform transfer of gene lists in different domains including: bladder cancer staging, tumour site of origin and mislabelled cell lines. We also show its effectiveness in transferring an epithelial ovarian cancer prognostic gene signature across technologies, from a microarray to a next-generation sequencing setting. In a final case study, we predict the tumour site of origin and histopathology of epithelial ovarian cancer cell lines. In particular, we identify and validate the commonly-used cell line OVCAR-5 as non-ovarian, being gastrointestinal in origin. GECA is available as an open-source R package.
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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.