A prognostic long non-coding RNA-associated competing endogenous RNA network in head and neck squamous cell carcinoma.

ABSTRACT:

Background

This study aimed to develop multi-RNA-based models using a competing endogenous RNA (ceRNA) regulatory network to provide survival risk prediction in head and neck squamous cell carcinoma (HNSCC).

Methods

All long non-coding RNA (lncRNA), microRNA (miRNA), and mRNA expression data and clinicopathological features related to HNSCC were derived from The Cancer Genome Atlas. Differentially expressed RNAs were calculated using R. Prognostic factors were identified using univariate Cox regression analysis. Functional analysis was performed using GO, KEGG pathways, and PPI network. Based on the results, we derived a risk signature and compared high- and low-risk subgroups using LASSO regression analysis. Survival analysis and the relationship between risk signature and

SUBMITTER: Zhang C 

PROVIDER: S-EPMC7500352 | biostudies-literature | 2020

REPOSITORIES: biostudies-literature