ArticleJournal of ovarian research2021
Establishment and validation of an RNA binding protein-associated prognostic model for ovarian cancer.
Article in Journal of ovarian research, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 14 papers.
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Who cites it
14 citing papers in PubMed, 25 citations in OpenAlex.
- Integrative analysis of the roles and prognostic value of RNA-binding proteins in papillary renal cell carcinoma.Discover oncology · 2026Article
- RNA binding proteins (RBPs) on genetic stability and diseases.Global medical genetics · 2025Review
- Article
- A macrophage related signature for predicting prognosis and drug sensitivity in ovarian cancer based on integrative machine learning.BMC medical genomics · 2023Article
- Ovarian cancer-associated immune exhaustion involves SPP1+ T cell and NKT cell, symbolizing more malignant progression.Frontiers in endocrinology · 2023Article
- System analysis based on the T cell exhaustion‑related genes identifies CD38 as a novel therapy target for ovarian cancer.Oncology research · 2023Article
- Biobehavioral factors predict an exosome biomarker of ovarian carcinoma disease progression.Cancer · 2022Article
- Protein expression profiling identifies a prognostic model for ovarian cancer.BMC women's health · 2022Article
- Identification of a chromatin regulator signature and potential candidate drugs for bladder cancer.Hereditas · 2022Article
- RNA-binding proteins in ovarian cancer: a novel avenue of their roles in diagnosis and treatment.Journal of translational medicine · 2022Review
- Integrated clinical characteristics and omics analysis identifies a ferroptosis and iron-metabolism-related lncRNA signature for predicting prognosis and therapeutic responses in ovarian cancer.Journal of ovarian research · 2022Article
- Identification of a glycolysis-related gene signature for survival prediction of ovarian cancer patients.Cancer medicine · 2021Article
- Identification of Hypoxia Signature to Assess the Tumor Immune Microenvironment and Predict Prognosis in Patients with Ovarian Cancer.International journal of endocrinology · 2021Article
- Potential Prognostic Immune Biomarkers of Overall Survival in Ovarian Cancer Through Comprehensive Bioinformatics Analysis: A Novel Artificial Intelligence Survival Prediction System.Frontiers in medicine · 2021Article
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Authors and funding
6 authors at 2 institutions in 1 country.
Funding
Abstract
backgroundOvarian cancer (OC) is one of the most common gynecological malignant tumors worldwide, with high mortality and a poor prognosis. As the early symptoms of malignant ovarian tumors are not obvious, the cause of the disease is still unclear, and the patients' postoperative quality of life of decreases. Therefore, early diagnosis is a problem requiring an urgent solution.
methodsWe obtained the gene expression profiles of ovarian cancer and normal samples from TCGA and GTEx databases for differential expression analysis. From existing literature reports, we acquired the RNA-binding protein (RBP) list for the human species. Utilizing the online tool Starbase, we analyzed the interaction relationship between RBPs and their target genes and selected the modules of RBP target genes through Cytoscape. Finally, univariate and multivariate Cox regression analyses were used to determine the prognostic RBP signature.
resultsWe obtained 527 differentially expressed RBPs, which were involved in many important cellular events, such as RNA splicing, the cell cycle, and so on. We predicted several target genes of RBPs, constructed the interaction network of RBPs and their target genes, and obtained many modules from the Cytoscape analysis. Functional enrichment of RBP target genes also includes these important biological processes. Through Cox regression analysis, OC prognostic RBPs were identified and a 10-RBP model constructed. Further analysis showed that the model has high accuracy and sensitivity in predicting the 3/5-year survival rate.
conclusionsOur study identified differentially expressed RBPs and their target genes in OC, and the results promote our understanding of the molecular mechanism of ovarian cancer. The current study could develop novel biomarkers for the diagnosis, treatment, and prognosis of OC and provide new ideas and prospects for future clinical research.
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