Development and Validation of a Seven-Gene Signature for Predicting the Prognosis of Lung Adenocarcinoma.

ABSTRACT:

Background

Prognosis is a main factor affecting the survival of patients with lung adenocarcinoma (LUAD), yet no robust prognostic model of high effectiveness has been developed. This study is aimed at constructing a stable and practicable gene signature-based model via bioinformatics methods for predicting the prognosis of LUAD sufferers.

Methods

The mRNA expression data were accessed from the TCGA-LUAD dataset, and paired clinical information was collected from the GDC website. R package "edgeR" was employed to select the differentially expressed genes (DEGs), which were then used for the construction of a gene signature-based model via univariate COX, Lasso, and multivariate COX regression analyses. Kaplan-Meier and ROC survival analyses were conducted to comprehensively

SUBMITTER: Zhang Y 

PROVIDER: S-EPMC7641279 | biostudies-literature | 2020

REPOSITORIES: biostudies-literature