Identification of a gene expression signature predicting survival in oral cavity squamous cell carcinoma using Monte Carlo cross validation.

ABSTRACT:

Objectives

This study aims to identify a robust signature that performs well in predicting overall survival across tumor phenotypes and treatment strata, and validates the application of Monte Carlo cross validation (MCCV) as a means of identifying molecular signatures when utilizing small and highly heterogeneous datasets.

Materials and methods

RNA sequence gene expression data for 264 patient tumors were acquired from The Cancer Genome Atlas (TCGA). 100 iterations of Monte Carlo cross validation were applied to differential expression and Cox model validation. The association between the gene signature risk score and overall survival was measured using Kaplan-Meier survival curves, univariate, and multivariable Cox regression analyses.

Results

Pathway analysis findi

SUBMITTER: Schomberg J 

PROVIDER: S-EPMC7853240 | biostudies-literature | 2018 Mar

REPOSITORIES: biostudies-literature