Bioinformatics Analysis and Screening of Potential Target Genes Related to the Lung Cancer Prognosis

Med Princ Pract. 2023 Sep 14. doi: 10.1159/000533891. Online ahead of print.

Abstract

Objective: Several genes have been validated as molecular targets for gene therapy in lung cancer. We screened target genes that affect survival of patients with lung cancer.

Methods: Data on gene expression in normal lung tissues/lung adenocarcinoma (LUAD) samples were acquired from Genotype-Tissue Expression (GTEx)/The Cancer Genome Atlas (TCGA) databases and merged to expand the sample size, followed by differential analysis of the merged expression data and acquisition of differentially expressed genes. Survival and simple Cox analyses were used to screen for genes affecting LUAD survival. Protein-protein interaction/multivariable Cox analyses were utilized, and a risk model was established. Candidate genes expression levels in cancer/paracancerous tissues of lung cancer patients, and BEAS-2B/A549/HCC95 cells were measured by RT-qPCR/Western blot. Survival analysis of candidate genes was conducted in LUAD samples collected from TCGA.

Results: Among 947 genes differentially expressed in LUAD, 151 were correlated with patient survival, and 116 might act as risk factors for LUAD. The 7 identified candidate genes (TOP2A, TK1, KIF4A, ANLN, KIF2C, ASF1B, CCNB1) were high-risk genes playing possible roles in LUAD. These genes were differentially expressed in lung cancer and were associated with TNM stages (III - IV)/differentiation grade/lymph node metastasis/distant metastasis, which affected lung cancer patient survival.

Conclusion: P2A, TK1, KIF4A, ANLN, KIF2C, ASF1B and CCNB1 were highly-expressed in LUAD/lung squamous cell carcinoma (LUSC) and correlated with LUAD patient survival. This study contributes to better understanding of the prognostic regulation mechanism in LUAD and the screening of target genes for clinical treatment.