ArticleOncology letters2019
Identification of a 3-mRNA signature as a novel potential prognostic biomarker in patients with ovarian serous cystadenocarcinoma in G2 and G3.
Article in Oncology letters, 2019. 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, 10 citations in OpenAlex.
- Transgenerational inheritance of diminished ovarian reserve triggered by prenatal propylparaben exposure in mice.Nature communications · 2025Article
- Development and clinical validation of a seven-gene signature based on tumor stem cell-related genes to predict ovarian cancer prognosis.Journal of ovarian research · 2024Article
- CELA3B immunostaining is a highly specific marker for acinar cell carcinoma of the pancreas.PloS one · 2023Article
- Identification of an Individualized Prognostic Biomarker for Serous Ovarian Cancer: A Qualitative Model.Diagnostics (Basel, Switzerland) · 2022Article
- Identification of a glycolysis-related gene signature for survival prediction of ovarian cancer patients.Cancer medicine · 2021Article
- Systematic Profiling of Alternative Splicing Events in Ovarian Cancer.Frontiers in oncology · 2021Article
- Identification of an energy metabolism‑related gene signature in ovarian cancer prognosis.Oncology reports · 2020Article
- Comprehensive pathway-related genes signature for prognosis and recurrence of ovarian cancer.PeerJ · 2020Article
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Authors and funding
5 authors at 2 institutions in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
The use of mRNAs as biomarkers serves to diagnose, treat, as well as aid the prognosis of cancer. The present study involved an analysis of mRNAs in the cell cycle at the G2 and G3 tumor grades for the prognosis of ovarian serous cystadenocarcinoma (OSC) using 364 clinical samples (G2:G3=42:322). Statistics aided the identification of NPFFR2, XPNPEP2 and CELA3B; the 3-mRNA model that allows for classification of patients into high- and low-risk groups using a median value of 0.9580745. The rates of survival varied (P=0.00149) and the independent detection of stratification of the risk of this disease was validated with success using the 3-mRNA signature, which was demonstrated to be more successful than the weight model. This approach was revealed to provide the prognosis of grade G2 and G3 in patients with OSC compared with factors used traditionally. Compared with traditional factors, this 3-mRNA model was demonstrated to be the only and independent prognostic factor for patients with G2 and G3 stage OSC. A literature survey was also performed in the present study in order to assess the role of the 3 genes and indirectly prove their effectiveness. The establishment of this new genetic model will enhance prospective prognosis and treatment for patients with OSC.
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