Identification of different lung adenocarcinoma subtypes in combination with antidiuretic hormone-related genes and creation of an associated index to predict prognosis and guide immunotherapy.

BACKGROUND

Lung adenocarcinoma (LUAD) is one of the most aggressive and rapidly lethal tumor types. Previous studies have demonstrated the involvement of antidiuretic hormone (ADH)-related genes in cancer. However, the role of ADH-related genes in LUAD remains unclear. Therefore, investigating the characteristics of these genes in LUAD is essential.

METHODS

Differentially expressed genes (DEGs) associated with ADH in LUAD were identified using the STRING database. Consensus clustering was performed, and a protein-protein interaction network was constructed for the DEGs between subtypes. Genes extracted from the PPI network underwent univariate, LASSO, and multivariate Cox regression analyses to develop a predictive model for LUAD. A nomogram integrating clinical data and risk scores was created, and its prognostic power for overall survival (OS) in LUAD patients was evaluated. Additionally, LUAD patients were analyzed for targeted therapies, immune landscape, functional enrichment, and mutation profiles. Finally, qRT-PCR was used to examine the expression of signature genes in LUAD cells.

RESULTS

Based on ADH-related DEGs, LUAD patients were stratified into two clusters (Cluster 1 and Cluster 2) with distinct survival outcomes. A predictive model incorporating nine feature genes was subsequently constructed using DEGs from these two subtypes. The receiver operating characteristic curve demonstrated the model's prognostic accuracy in predicting OS in LUAD patients. Compared to the high-risk group, patients in the low-risk group exhibited higher immune infiltration levels and immunophenoscore, along with lower tumor immune dysfunction and exclusion scores. Enrichment analysis revealed that immune response pathways and ligand-receptor interactions were the primary functional categories distinguishing the high- and low-risk groups. The low-risk group showed a significantly lower gene mutation burden. Drug sensitivity analysis identified several potential targeted therapies, including Dabrafenib, ARQ-680, Vemurafenib, BGB-283, MLN-2480, and GDC-0994, which might act on hub genes. qRT-PCR validation confirmed that DNAH12 was significantly downregulated in tumor tissues, while DKK1, DLX2, IGFBP1, NTSR1, RPE65, and VGF were markedly upregulated.

CONCLUSION

This study provided potential prognostic biomarkers for LUAD and might facilitate the development of effective immunotherapy strategies for LUAD patients.