ArticleBioMed research international2016
A Five-Gene Expression Signature Predicts Clinical Outcome of Ovarian Serous Cystadenocarcinoma.
Article in BioMed research international, 2016. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.
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Who cites it
5 citing papers in PubMed, 6 citations in OpenAlex.
- Identification of a glycolysis-related gene signature for survival prediction of ovarian cancer patients.Cancer medicine · 2021Article
- Development and verification of an immune-related gene pairs prognostic signature in ovarian cancer.Journal of cellular and molecular medicine · 2021Article
- Identification of a 3-mRNA signature as a novel potential prognostic biomarker in patients with ovarian serous cystadenocarcinoma in G2 and G3.Oncology letters · 2019Article
- A Robust Gene Expression Prognostic Signature for Overall Survival in High-Grade Serous Ovarian Cancer.Journal of oncology · 2019Article
- A five-DNA methylation signature act as a novel prognostic biomarker in patients with ovarian serous cystadenocarcinoma.Clinical epigenetics · 2018Article
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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
Ovarian serous cystadenocarcinoma is a common malignant tumor of female genital organs. Treatment is generally less effective as patients are usually diagnosed in the late stage. Therefore, a well-designed prognostic marker provides valuable data for optimizing therapy. In this study, we analyzed 303 samples of ovarian serous cystadenocarcinoma and the corresponding RNA-seq data. We observed the correlation between gene expression and patients' survival and eventually established a risk assessment model of five factors using Cox proportional hazards regression analysis. We found that the survival time in high-risk patients was significantly shorter than in low-risk patients in both training and testing sets after Kaplan-Meier analysis. The AUROC value was 0.67 when predicting the survival time in testing set, which indicates a relatively high specificity and sensitivity. The results suggest diagnostic and therapeutic applications of our five-gene model for ovarian serous cystadenocarcinoma.
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