Construction and analysis of a competing endogenous RNA network to reveal potential prognostic biomarkers for Oral Floor Squamous Cell Carcinoma.

ABSTRACT:

Background

Patients 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.

Method

We 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

SUBMITTER: Zhang W 

PROVIDER: S-EPMC7491744 | biostudies-literature | 2020

REPOSITORIES: biostudies-literature