鞘脂代谢失调驱动膀胱癌免疫微环境重塑并预测预后

The role of sphingolipid metabolism (SM) dysregulation in promoting bladder cancer (BLCA) progression and influencing patient prognosis has been well documented. To enhance therapeutic strategies, we aimed to identify key sphingolipid metabolism-related genes (SMGs) and develop a prognostic signature for personalized BLCA management. In this study, 430 BLCA samples from The Cancer Genome Atlas (TCGA) were analyzed via univariate Cox regression to screen critical SMGs involved in tumor progression.

A LASSO regression model was applied to minimize overfitting, followed by multivariable Cox regression to construct and validate a SMG-based prognostic signature in an independent cohort. Key findings revealed that SM dysregulation correlated with poor clinical outcomes and eight pivotal prognostic genes (ATP13A2, PCSK2, NR2F1, GSDMB, NFASC, NTF3, LGALS4, and SREBF1) were identified. The resulting risk model demonstrated robust prognostic performance with AUC values of 0. 772 (training cohort) and 0. 725 (validation cohort).

Notably, high-risk patients exhibited a highly active immunological profile characterized by elevated immune scores and enhanced functionality across 26 immune components, including increased infiltration of NK cells, CD8 + T cells, and elevated cytolytic activity. These results suggest that SM dysregulation may drive immunomodulatory changes in BLCA microenvironments, offering mechanistic insights into tumor immune evasion.

This study provides a novel biomarker tool for risk stratification and highlights SM pathways as potential therapeutic targets for BLCA patients with immune microenvironment dysregulation.