Lactylation-related gene signature for prognosis prediction and immune infiltration assessment in lung adenocarcinoma via bulk and single-cell RNA sequencing

Abstract Lung cancer remains the leading cause of cancer incidence and mortality globally, yet its molecular mechanisms remain poorly understood. Recent studies highlight the role of protein lactylation in regulating tumor microenvironment (TME) dynamics, tumor progression, and therapeutic responses, suggesting its potential as a therapeutic target. This study aimed to identify key lactylation-related genes (LRGs) in lung adenocarcinoma (LUAD) using integrated bulk and single-cell RNA-seq analyses. Bulk RNA-seq data from TCGA-LUAD and GSE118370, alongside single-cell data from GSE149655, were analyzed. LRGs were retrieved from GeneCards, and machine learning algorithms (SVM-RFE and LASSO-Cox regression) identified prognostic genes. A prognostic risk model was constructed using four genes (CCNA2, PRAM1, GPR37, HMGA1) and validated in independent datasets. A nomogram combining risk scores and clinical parameters showed high accuracy for predicting 1-, 3-, and 5-year survival. Single-cell analysis of 6798 cells identified 10 cell types, with significant differences in LRG expression across immune and stromal cells. HMGA1 and PRAM1 displayed differential expression in macrophages, monocytes, and fibroblasts. Functional validation via qPCR and Western blot confirmed consistent expression trends in LUAD cell lines, while shRNA-mediated knockdown of CCNA2, GPR37, and HMGA1 significantly inhibited LUAD cell proliferation, supporting their oncogenic roles. This study suggests that lactylation is associated with TME immune cell differentiation in LUAD and establishes a novel four-gene (CCNA2, PRAM1, GPR37, HMGA1) lactylation-related signature.