Twenty-gene-based prognostic model predicts lung adenocarcinoma survival.

ABSTRACT:

Introduction

Lung adenocarcinoma (LAC) accounts for more than a half of non-small cell lung cancer with high morbidity and mortality. Progression of treatment has not accelerated the improvement of its prognosis. Hence, it is an urgent need to develop novel biomarkers for its early diagnosis and treatment.

Materials and methods

In this study, we proposed to identify LAC survival-related genes through comprehensive analysis of large-scale gene expression profiles. LAC gene expression data sets were obtained from The Cancer Genome Atlas (TCGA). Identification of differentially expressed genes (DEGs) in LAC compared with adjacent normal lung tissues was first performed followed by univariate Cox regression analysis to obtain genes that are significantly associated with LAC surv

SUBMITTER: Zhao K 

PROVIDER: S-EPMC6003292 | biostudies-literature | 2018

REPOSITORIES: biostudies-literature