ArticlePloS one2020
Construction and analysis of a competing endogenous RNA network to reveal potential prognostic biomarkers for Oral Floor Squamous Cell Carcinoma.
Article in PloS one, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
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Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
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Who cites it
2 citing papers in PubMed.
- Recent advances in biomarker detection of oral squamous cell carcinoma.Frontiers in oncology · 2025Review
- Identification of a CircRNA-miRNA-mRNA Network and Integrated Analysis of Immune Infiltration in Oral Squamous Cell Carcinoma.Journal of Cancer · 2023Article
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Authors and funding
5 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
backgroundPatients diagnosed with Oral Floor Squamous Cell Carcinoma (OFSCC) face considerable challenges in physiology and psychology. This study explored prognostic signatures to predict prognosis in OFSCC through a detailed transcriptomic analysis.
methodWe built an interactive competing endogenous RNA (ceRNA) network that included lncRNAs, miRNAs and mRNAs. Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) were used to predict the gene functions and regulatory pathways of mRNAs. Least absolute shrinkage and selection operator algorithm (LASSO) analysis and Cox regression analysis were used to screen prognosis factors. The Kaplan-Meier method was used to analyze the survival rate of prognosis factors. Risk score was used to assess the reliability of the prediction model.
resultsA specific ceRNA network consisting of 56 mRNAs, 16 miRNAs and 31 lncRNAs was established. Three key genes (HOXC13, TGFBR3, KLHL40) and 4 clinical factors (age, gender, TNM, and clinical stage) were identified and effectively predicted the for survival time. The expression of a gene signature was validated in two external validation cohorts. The signature (areas under the curve of 3 and 5 years were 0.977 and 0.982, respectively) showed high prognostic accuracy in the complete TCGA cohort.
conclusionsOur study successfully developed an extensive ceRNA network for OFSCC and further identified a 3-mRNA and 4-clinical-factor signature, which may serve as a biomarker.
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