Integrative analysis of differential genes and identification of a "2-gene score" associated with survival in esophageal squamous cell carcinoma.

ABSTRACT:

Background

Developments in high-throughput genomic technologies have led to improved understanding of the molecular underpinnings of esophageal squamous cell carcinoma (ESCC). However, there is currently no model that combines the clinical features and gene expression signatures to predict outcomes.

Methods

We obtained data from the GSE53625 database of Chinese ESCC patients who had undergone surgical treatment. The R packages, Limma and WGCNA, were used to identify and construct a co-expression network of differentially expressed genes, respectively. The Cox regression model was used, and a nomogram prediction model was constructed.

Results

A total of 3654 differentially expressed genes were identified. Bioinformatics enrichment analysis was conducted. Multivariate a

SUBMITTER: Wang L 

PROVIDER: S-EPMC6312844 | biostudies-literature | 2019 Jan

REPOSITORIES: biostudies-literature