Identification and validation of differentially expressed genes for targeted therapy in NSCLC using integrated bioinformatics analysis.

ABSTRACT:

Background

Despite the high prevalence of lung cancer, with a five-year survival rate of only 23%, the underlying molecular mechanisms of non-small cell lung cancer (NSCLC) remain unknown. There is a great need to identify reliable candidate biomarker genes for early diagnosis and targeted therapeutic strategies to prevent cancer progression.

Methods

In this study, four datasets obtained from the Gene Expression Omnibus were evaluated for NSCLC- associated differentially expressed genes (DEGs) using bioinformatics analysis. About 10 common significant DEGs were shortlisted based on their p-value and FDR (DOCK4, ID2, SASH1, NPR1, GJA4, TBX2, CD24, HBEGF, GATA3, and DDR1). The expression of significant genes was validated using experimental data obtained from TCGA and t

SUBMITTER: Altaf R 

PROVIDER: S-EPMC10264625 | biostudies-literature | 2023

REPOSITORIES: biostudies-literature