Investigation of sphingolipid-related genes in lung adenocarcinoma

Lung adenocarcinoma (LUAD) is responsible for majority cases of lung cancer and considered to be the primary cause of cancer-related mortality. The imbalance of cellular proliferation and apoptosis is critically implicated in the pathogenesis and progression of LUAD. Sphingomyelin, a vital lipid component, is integral to the regulation of tumor cell growth and apoptosis, and has garnered significant attention as a target in novel anticancer therapies. The pivotal molecules involved in sphingomyelin metabolism are crucial in modulating tumor cell behavior, thereby influencing clinical outcomes.

A comprehensive consensus clustering analysis was conducted by collecting clinical LUAD figures from the TCGA and GEO databases. By employing Cox regression and Lasso regression analysis, a prognostic model for LUAD patients was established by identifying seven sphingolipid-related genes (SRGs), and validated in the GEO database. The study also delved into the clinical relevance, functional capabilities, and immune implications of prognostic signals associated with sphingolipid metabolism. Finally, experiments conducted in vitro confirmed the imbalance of sphingolipid-associated genes in LUAD.

Using the prognostic model, lung adenocarcinoma (LUAD) patients can be divided into high-risk and low-risk groups. Meanwhile, we can observe marked disparities in survival times among these groups. Additionally, the model demonstrates high predictive accuracy in external validation cohorts. Research on the immune microenvironment and immunotherapy points to this risk stratification as a useful reference for immunotherapeutic strategies in LUAD. Finally, our hypothesis was corroborated through in vitro experiments.

This study demonstrates that sphingolipid-related gene prognostic characteristics correlate with tumor progression and recurrence, long-term prognosis, and immune infiltration in LUAD patients. The outcomes of our study could help shape innovative strategies for early intervention and prognosis prediction in lung adenocarcinoma.