ArticleJournal of ovarian research2023
An EMT-based gene signature enhances the clinical understanding and prognostic prediction of patients with ovarian cancers.
Article in Journal of ovarian research, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 8 papers.
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Who cites it
8 citing papers in PubMed, 8 citations in OpenAlex.
- Epithelial-mesenchymal transition and immunosuppression: Two sides of the same coin.Cellular and molecular life sciences : CMLS · 2026Review
- A Novel Partial EMT-Associated Transcriptomic Signature for Prognostic Stratification in Ovarian Cancer.Oncology research · 2026Article
- Catalpol: An Iridoid Glycoside With Potential in Combating Cancer Development and Progression-A Comprehensive Review.Phytotherapy research : PTR · 2025Review
- Direct cell interactions potentially regulate transcriptional programmes that control the responses of high grade serous ovarian cancer patients to therapy.Scientific reports · 2025Article
- From Defense to Disease: How the Immune System Fuels Epithelial-Mesenchymal Transition in Ovarian Cancer.International journal of molecular sciences · 2025Review
- Tumor dormancy and relapse: understanding the molecular mechanisms of cancer recurrence.Military Medical Research · 2025Review
- Mechanism of Hirudin-Mediated Inhibition of Proliferation in Ovarian Cancer Cells.Molecular biotechnology · 2024Article
- CCT2 prevented β-catenin proteasomal degradation to sustain cancer stem cell traits and promote tumor progression in epithelial ovarian cancer.Molecular biology reports · 2024Article
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Authors and funding
5 authors at 1 institution in 1 country.
Funding
Abstract
backgroundOvarian cancer (OC) is one of the most common gynecological cancers with malignant metastasis and poor prognosis. Current evidence substantiates that epithelial-mesenchymal transition (EMT) is a critical mechanism that drives OC progression. In this study, we aspire to identify pivotal EMT-related genes (EMTG) in OC development, and establish an EMT gene-based model for prognosis prediction.
methodsWe constructed the risk score model by screening EMT genes via univariate/LASSO/step multivariate Cox regressions in the OC cohort from TCGA database. The efficacy of the EMTG model was tested in external GEO cohort, and quantified by the nomogram. Moreover, the immune infiltration and chemotherapy sensitivity were analyzed in different risk score groups.
resultsWe established a 11-EMTGs risk score model to predict the prognosis of OC patients. Based on the model, OC patients were split into high- and low- risk score groups, and the high-risk score group had an inevitably poor survival. The predictive power of the model was verified by external OC cohort. The nomogram showed that the model was an independent factor for prognosis prediction. Moreover, immune infiltration analysis revealed the immunosuppressive microenvironment in the high-risk score group. Finally, the EMTG model can be used to predict the sensitivity to chemotherapy drugs.
conclusionsThis study demonstrated that EMTG model was a powerful tool for prognostic prediction of OC patients. Our work not only provide a novel insight into the etiology of OC tumorigenesis, but also can be used in the clinical decisions on OC treatment.
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