ArticleBioMed research international2020
Recurrence-Associated Multi-RNA Signature to Predict Disease-Free Survival for Ovarian Cancer Patients.
Article in BioMed research international, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 19 papers, 1 of them a synthesis that pooled it.
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Who cites it
19 citing papers in PubMed, 1 synthesis or guideline pooled it.
- Prognostic value of micro-RNA in ovarian cancer: a systematic review and meta-analysis.Frontiers in oncology · 2025Pooled it
- Construction and evaluation of a bladder cancer prognosis model based on super-enhancer-associated genes.Discover oncology · 2026Article
- Identification of endoplasmic reticulum stress-related biomarkers in asthma and asthma exacerbation.Frontiers in medicine · 2026Article
- Proteomic profiles screening identified novel exosomal protein biomarkers for diagnosis of lung cancer.Clinical proteomics · 2025Article
- SLAMF7 predicts prognosis and correlates with immune infiltration in serous ovarian carcinoma.Journal of gynecologic oncology · 2024Article
- Racial disparities in initiation of chemotherapy among breast cancer patients with discretionary treatment indication in the state of Georgia.Breast cancer research and treatment · 2024Article
- Proteomic Changes in the Hippocampus after Repeated Explosive-Driven Blasts.Journal of proteome research · 2024Article
- Article
- A novel DNA methylation-related gene signature for the prediction of overall survival and immune characteristics of ovarian cancer patients.Journal of ovarian research · 2023Article
- LINC00536 knockdown inhibits breast cancer cells proliferation, invasion, and migration through regulation of the miR-4282/centromere protein F axis.The Kaohsiung journal of medical sciences · 2022Article
- Epigenetic Regulation in Exposome-Induced Tumorigenesis: Emerging Roles of ncRNAs.Biomolecules · 2022Review
- A novel genomic instability-derived lncRNA signature to predict prognosis and immune characteristics of pancreatic ductal adenocarcinoma.Frontiers in immunology · 2022Article
- Review
- Development of a novel transcription factors-related prognostic signature for serous ovarian cancer.Scientific reports · 2021Article
- Regulatory Roles of Six-Transmembrane Epithelial Antigen of the Prostate Family Members in the Occurrence and Development of Malignant Tumors.Frontiers in cell and developmental biology · 2021Review
- A novel lncRNA-mRNA-miRNA signature predicts recurrence and disease-free survival in cervical cancer.Brazilian journal of medical and biological research = Revista brasileira de pesquisas medicas e biologica · 2021Article
- Integrated microRNA and mRNA signatures associated with overall survival in epithelial ovarian cancer.PloS one · 2021Article
- Identification and Validation of an Energy Metabolism-Related lncRNA-mRNA Signature for Lower-Grade Glioma.BioMed research international · 2020Article
- TIPE3 in Cancer: A Multifaceted Regulator of Tumorigenesis, Therapeutic Resistance, and Clinical Outcomes.Technology in cancer research & treatmentReview
Corrections and comments
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8 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Ovarian cancer (OvCa) is an intractable gynecological malignancy due to the high recurrence rate. Several molecular biomarkers have been previously screened for early identifying patients with a high recurrence risk and poor prognosis. However, all the known studies focused on a single type of RNAs, not integrating various types. This study was to construct a new multi-RNA-based model to predict the recurrence and prognosis for OvCa patients by using the messenger RNA (mRNA, including long noncoding RNA (lncRNA)) and microRNA (miRNA) sequencing data of The Cancer Genome Atlas database. After univariate Cox regression and least absolute shrinkage and selection operator analyses, a multi-RNA-based signature (2 miRNAs: hsa-miR-508, hsa-miR-506; 1 lncRNA: TM4SF1-AS1; 11 mRNAs: MAGI3, SLAMF7, GLI2, PDK1, ARID3A, PLEKHG4B, TNFAIP8L3, C1QTNF3, NDUFAF1, CH25H, TMEM129) was generated and used to establish a risk score model. The high- and low-risk patients classified by the median risk score exhibited significantly different recurrence risks (89% versus 61%,
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