Cuproptosis‐related lncRNAs are correlated with tumour metabolism and immune microenvironment and predict prognosis in pancreatic cancer patients

Abstract

Abstract Cuproptosis is a novel cell death pathway, and the regulatory mechanism in pancreatic cancer (PC) is unclear. The authors aimed to figure out whether cuproptosis‐related lncRNAs (CRLs) could predict prognosis in PC and the underlying mechanism. First, the prognostic model based on seven CRLs screened by the least absolute shrinkage and selection operator Cox analysis was constructed. Following this, the risk score was calculated for pancreatic cancer patients and divided patients into high and low‐risk groups. In our prognostic model, PC patients with higher risk scores had poorer outcomes. Based on several prognostic features, a predictive nomogram was established. Furthermore, the functional enrichment analysis of differentially expressed genes between risk groups was performed, indicating that endocrine and metabolic pathways were potential regulatory pathways between risk groups. TP53, KRAS, CDKN2A, and SMAD4 were dominant mutated genes in the high‐risk group and tumour mutational burden was positively correlated with the risk score. Finally, the tumour immune landscape indicated patients in the high‐risk group were more immunosuppressive than that in the low‐risk group, with lower infiltration of CD8+ T cells and higher M2 macrophages. Above all, CRLs can be applied to predict PC prognosis, which is closely correlated with the tumour metabolism and immune microenvironment.

Keywords

• bioinformatics
• patient diagnosis
• pattern classification
• tumours