Lung adenocarcinoma (LUAD) is a heterogeneous disease with a dismal prognosis for advanced tumors. Immune-associated cells in the microenvironment substantially impact LUAD formation and progression, which has gained increased attention in recent decades. Sphingolipids have a profound impact on tumor formation and immune infiltration. However, few researchers have focused on the utilization of sphingolipid variables in the prediction of LUAD prognosis. The goal of this work was to identify the major sphingolipid-related genes (SRGs) in LUAD and develop a valid prognostic model based on SRGs.
The most significant genes for sphingolipid metabolism (SM) were identified using the AUCell and WGCNA algorithms in conjunction with single-cell and bulk RNA-seq. LASSO and COX regression analysis was used to develop risk models, and patients were divided into high-and low-risk categories. External nine provided cohorts evaluated the correctness of the models. Differences in immune infiltration, mutation landscape, pathway enrichment, immune checkpoint expression, and immunotherapy were also further investigated in distinct subgroups. Finally, cell function assay was used to verify the role of CACYBP in LUAD cells.
A total of 334 genes were selected as being most linked with SM activity for further investigation, and a risk model consisting of 11 genes was established using lasso and cox regression. According to the median risk value, patients were split into high- and low-risk groups, and the high-risk group had a worse prognosis. The low-risk group had more immune cell infiltration and higher expression of immune checkpoints, which illustrated that the low-risk group was more likely to benefit from immunotherapy. It was verified that CACYBP could increase the ability of LUAD cells to proliferate, invade, and migrate.
The eleven-gene signature identified in this research may help physicians create individualized care plans for LUAD patients. CACYBP may be a new therapeutic target for patients with advanced LUAD.