A robust six-gene prognostic signature for prediction of both disease-free and overall survival in non-small cell lung cancer.

ABSTRACT:

Background

The high mortality of patients with non-small cell lung cancer (NSCLC) emphasizes the necessity of identifying a robust and reliable prognostic signature for NSCLC patients. This study aimed to identify and validate a prognostic signature for the prediction of both disease-free survival (DFS) and overall survival (OS) of NSCLC patients by integrating multiple datasets.

Methods

We firstly downloaded three independent datasets under the accessing number of GSE31210, GSE37745 and GSE50081, and then performed an univariate regression analysis to identify the candidate prognostic genes from each dataset, and identified the gene signature by overlapping the candidates. Then, we built a prognostic model to predict DFS and OS using a risk score method. Kaplan-Meier curve

SUBMITTER: Zuo S 

PROVIDER: S-EPMC6515678 | biostudies-literature | 2019 May

REPOSITORIES: biostudies-literature