Single-cell hdWGCNA and experimental validation identify an innovative T-cell-associated prognostic model and immune microenvironment in lung adenocarcinoma with lymph node metastasis.

BACKGROUND

Lymph nodes (LNs) are the most common and typically the earliest sites of metastasis in tumors. This study aims to establish a T-cell-based prognostic model, providing a critical foundation for evaluating the prognosis of patients with lymph node-metastatic lung adenocarcinoma (LUAD).

METHODS

Single-cell RNA sequencing (scRNA-seq) data from the Gene Expression Omnibus (GEO) database were utilized, combined with high-dimensional weighted gene co-expression network analysis (hdWGCNA), differential expression analysis, and Cox/LASSO regression, to construct a T-cell-related prognostic model incorporating key genes CD69, GOLGA8A, and IL16. Potential drug-gene interactions were identified through protein-protein interaction analysis, RNA-binding protein regulatory network analysis, drug regulation studies, and molecular docking. The expression of model genes was validated in lung adenocarcinoma cell lines using gene expression profiling, quantitative real-time PCR (qRT-PCR), immunohistochemistry (IHC), and multiplex immunofluorescence (mIF) assays.

RESULTS

The established T-cell-associated prognostic model (CD69, GOLGA8A, and IL16) was significantly correlated with immune microenvironment characteristics, tumor mutational burden, and potential therapeutic responsiveness. The low-risk group exhibited a more favorable immune profile. The predictive map, constructed by integrating clinical variables, significantly improved the model's interpretability and utility for personalized survival prediction. Further molecular analysis identified multiple drug-gene interactions, providing novel insights into therapeutic strategies. Experimental validation confirmed the differential expression of model genes in tumor tissues.

CONCLUSIONS

The T-cell marker gene-based prognostic risk model provides a foundation for evaluating the prognosis of lymph node-metastatic LUAD and shows potential for optimizing targeted therapy and immunotherapy strategies.