Integration of single-cell and bulk transcriptomics to explore prognostic and immunotherapeutic characteristics of sodium overload-induced cell death in lung adenocarcinoma.

BACKGROUNDRecent studies have identified a novel cell death mechanism, termed sodium death, triggered by sustained activation of TRPM4 ion channels. Prolonged TRPM4 channel activity results in excessive sodium ion influx and membrane depolarization, ultimately inducing necrotic cell death. However, the role of sodium death-associated genes (NECSOs) in lung adenocarcinoma (LUAD) remains poorly understood. We used NECSOs to construct a prognostic model of LUAD for prognostic prediction and to explore the features of sodium overload-induced cell death in single cells.

METHODSThis study conducted a comprehensive analysis of The Cancer Genome Atlas (TCGA) and Gene Expression Omnibus (GEO) databases to investigate TRPM4, a NECSO identified in the literature. Through co-expression analysis, 40 NECSOs were identified. Using the AddModuleScore enrichment algorithm, sodium death scores were calculated for distinct cell clusters and categorized into high- and low-score groups. Differentially expressed genes (DEGs) between these groups were subjected to weighted gene co-expression network analysis (WGCNA) to identify gene modules associated with LUAD. Subsequent differential expression and univariate Cox regression analyses were performed on genes within these modules. Consensus clustering analysis was employed to characterize molecular subtypes, while least absolute shrinkage and selection operator (LASSO) regression was used to develop a prognostic model based on NECSOs. Multiple immune infiltration scoring algorithms and cellular communication analyses were applied to evaluate the relationship between sodium overload (NECSO) and the tumor microenvironment (TME), with the aim of identifying potential therapeutic targets for LUAD.

RESULTSSingle-cell and bulk transcriptome analyses identified 126 NECSOs, of which 28 were differentially expressed between tumor and normal tissues. Among these, 14 genes were significantly associated with overall survival (OS). Pseudotime analysis of epithelial cells revealed that risk-associated genes were predominantly upregulated in later stages, whereas protective genes exhibited reduced expression over time. Eight genes were selected to construct a prognostic signature for NECSOs. Patients in the low-NECSOs group demonstrated significantly better prognosis compared to those in the high-NECSOs group. Cellular communication analysis indicated that epithelial cells with elevated NECSOs expression exhibited enhanced activity in the epidermal growth factor (EGF), Midkine (MK), and COMPLEMENT signaling pathways.

CONCLUSIONSThe prognostic model developed from NECSOs enables robust survival prediction for LUAD patients and provides insights into the immune landscape of LUAD. Notably, epithelial cells with higher NECSOs scores displayed a greater propensity for transformation into tumor cells, highlighting their potential as therapeutic targets.