Systems biology analysis of publicly available transcriptomic data reveals a critical link between AKR1B10 gene expression, smoking and occurrence of lung cancer.

ABSTRACT:

Background

Cigarette smoking is associated with an increased risk of developing respiratory diseases and various types of cancer. Early identification of such unfavorable outcomes in patients who smoke is critical for optimizing personalized medical care.

Methods

Here, we perform a comprehensive analysis using Systems Biology tools of publicly available data from a total of 6 transcriptomic studies, which examined different specimens of lung tissue and/or cells of smokers and nonsmokers to identify potential markers associated with lung cancer.

Results

Expression level of 22 genes was capable of classifying smokers from non-smokers. A machine learning algorithm revealed that AKR1B10 was the most informative gene among the 22 differentially expressed genes (DEGs) accou

SUBMITTER: Cubillos-Angulo JM 

PROVIDER: S-EPMC7041805 | biostudies-literature | 2020

REPOSITORIES: biostudies-literature