ArticleJournal of cellular and molecular medicine2019
Identification of potential prognostic TF-associated lncRNAs for predicting survival in ovarian cancer.
Article in Journal of cellular and molecular medicine, 2019. 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.
- Transcriptional rewiring in cancer driven byFrontiers in pharmacology · 2025Review
- KIF26B and CREB3L1 Derived from Immunoscore Could Inhibit the Progression of Ovarian Cancer.Journal of immunology research · 2024Article
- Construction and validation of a transcription factors-based prognostic signature for ovarian cancer.Journal of ovarian research · 2022Article
- Identification of a glycolysis-related gene signature for survival prediction of ovarian cancer patients.Cancer medicine · 2021Article
- Immune-related eight-lncRNA signature for improving prognosis prediction of lung adenocarcinoma.Journal of clinical laboratory analysis · 2021Article
- Serum exosomal lncRNA XIST is a potential non-invasive biomarker to diagnose recurrence of triple-negative breast cancer.Journal of cellular and molecular medicine · 2021Article
- A Panel of Five-lncRNA Signature as a Potential Biomarker for Predicting Survival in Gastric and Thoracic Cancers.Frontiers in genetics · 2021Article
- Combination of Immune-Related Genomic Alterations Reveals Immune Characterization and Prediction of Different Prognostic Risks in Ovarian Cancer.Frontiers in cell and developmental biology · 2021Article
- Characterizing the Copy Number Variation of Non-Coding RNAs Reveals Potential Therapeutic Targets and Prognostic Markers of LUSC.Frontiers in genetics · 2021Article
- Identification and validation of core genes for serous ovarian adenocarcinoma via bioinformatics analysis.Oncology letters · 2020Article
- Identification and Analyzation of Differentially Expressed Transcription Factors in Endometriosis.Frontiers in molecular biosciences · 2020Article
- Identification of potential prognostic TF-associated lncRNAs for predicting survival in ovarian cancer.Journal of cellular and molecular medicine · 2019Article
- A panel of Transcription factors identified by data mining can predict the prognosis of head and neck squamous cell carcinoma.Cancer cell international · 2019Article
- Identification of a transcription factor-microRNA network in esophageal adenocarcinoma through bioinformatics analysis and validation through qRT-PCR.Cancer management and research · 2019Article
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7 authors.
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Abstract
The pathophysiology of ovarian cancer (OV) is complex and depends on multiple biological processes and pathways. Therefore, there is an urgent need to identify reliable prognostic biomarkers for predicting clinical outcomes and helping personalize treatment of OV. A long non-coding RNA (lncRNA)-based risk score model was constructed to infer the prognostic efficacy of transcription factors (TFs) based on the OV dataset from The Cancer Genome Atlas. The risk score model was further validated in other independent cohorts from Gene Expression Omnibus. Time-dependent receiver operating characteristic curves were used to evaluate the survival prediction performance in comparison with other clinical and molecular variables. Our results revealed that the top-ranked TF-associating lncRNAs were significantly associated with overall survival, progression-free survival and disease-free survival. Stratification analysis according to clinical variables indicated the prognostic independence of POLR2A-associating lncRNAs. In comparison, the signature of POLR2A-associating lncRNAs was more sensitive and specific than existing clinical and molecular signatures. Functional and experimental analysis suggested that POLR2A-associating lncRNAs may be involved in known biological processes and pathways of OV. Our findings revealed that the lncRNA-based risk score model can provide helpful information on OV prognosis stratification and discovery of therapeutic biomarkers.
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