Single-Cell RNA Sequencing Analysis Reveals Metabolic Changes in Epithelial Glycosphingolipids and Establishes a Prognostic Risk Model for Pancreatic Cancer
Objective: Metabolic reprogramming is a hallmark of cancer, influencing proliferation and metastasis, with abnormal glycosphingolipid expression playing a pivotal role in malignancy. However, research on the relationship between glycosphingolipid metabolism and pancreatic cancer remains limited.
Methods: This study employed a single-cell sequencing dataset to analyze the cellular composition of pancreatic cancer tissues and quantified single-cell metabolism using a newly developed computational tool, scMetabolism. A gene signature derived from differentially expressed genes (DEGs) associated with epithelial glycosphingolipid metabolism was established to predict patient survival, immune response, mutation status, and chemotherapy response in pancreatic adenocarcinoma (PAAD).
Results: Single-cell sequencing analysis revealed a significant increase in epithelial cell proportions in PAAD, with heightened glycosphingolipid metabolism in the cancerous tissue. A six-gene prognostic model based on disrupted epithelial glycosphingolipid metabolism was developed and validated using publicly available databases. PAAD patients were classified into high- and low-risk groups based on median risk scores. The high-risk group exhibited poorer survival outcomes across all three cohorts, with higher mutation rates (e.g., KRAS, CDKN2A), elevated levels of immunosuppressive cells (macrophages, Th2 cells, regulatory T cells), and increased sensitivity to Acetalax and Selumetinib.
Conclusions: Altered glycosphingolipid metabolism in epithelial cells may contribute to PAAD progression. The gene signature model associated with epithelial glycosphingolipid metabolism provides a valuable tool for prognostic stratification of PAAD patients.