Hub Gene Screening and Prognostic Modeling of Lung Cancer: An Integrated Bioinformatics Study.

ABSTRACT:

Background

One of the most frequent malignancies is lung carcinoma which poses heavy burden on the global health. The link among differentially expressed genes (DEGs) and lung cancer patients' clinical outcomes was still missing. In this study, we integrated transcriptome data with clinical data to investigate the relationship between them in lung carcinoma patients.

Methods

To begin, DEGs were identified using the Gene Expression Omnibus (GEO) gene expression pattern (GSE180347). Then, these DEGs are being searched in the TCGA database using the DEGs collected in the preceding phase. The Kaplan-Meier plotter was then used to assess the predictive value of these DEGs in patients with lung cancer.

Results

Our study revealed a total of 45 DEGs, 15 of which were up-regul

SUBMITTER: Bai H 

PROVIDER: S-EPMC9276499 | biostudies-literature | 2022

REPOSITORIES: biostudies-literature