Comprehensive landscape of junctional genes and their association with overall survival of patients with lung adenocarcinoma.

Objectives: Junctional proteins are involved in tumorigenesis. Therefore, this study aimed to investigate the association between junctional genes and the prognosis of patients with lung adenocarcinoma (LUAD).

Methods: Transcriptome, mutation, and clinical data were retrieved from The Cancer Genome Atlas (TCGA). "Limma" was used to screen differentially expressed genes. Moreover, Kaplan-Meier survival analysis was used to identify junctional genes associated with LUAD prognosis. The junctional gene-related risk score (JGRS) was generated based on multivariate Cox regression analysis. An overall survival (OS) prediction model combining the JGRS and clinicopathological properties was proposed using a nomogram and further validated in the Gene Expression Omnibus (GEO) LUAD cohort.

Results: To our knowledge, this study is the first to demonstrate the correlation between the mRNA levels of 14 junctional genes ( and ) and clinical outcomes of patients with LUAD. The JGRS was generated based on these 14 genes, and a higher JGRS was associated with older age, higher stage levels, and lower immune scores. Thus, a prognostic prediction nomogram was proposed based on the JGRS. Internal and external validation showed the good performance of the prediction model. Mechanistically, JGRS was associated with cell proliferation and immune regulatory pathways. Mutational analysis revealed that more somatic mutations occurred in the high-JGRS group than in the low-JGRS group.

Conclusion: The association between junctional genes and OS in patients with LUAD demonstrated by our "TCGA filtrating and GEO validating" model revealed a new function of junctional genes.