LAUSR

Although several altered metabolic genes have been identified to be involved in the tumorigenesis and advance of pancreatic cancer (PC), their prognostic values remained unclear. The purpose of this study was to explore new targets and establish a metabolic signature to predict prognosis and chemotherapy response for optimal individualized treatment. The expression data of PC patients from two independent cohorts and metabolism-related genes from KEGG were utilized and analyzed for the establishment of the signature via lasso regression. Then, the differentially expressed candidate genes were further confirmed via online data mining platform and qRT-PCR of clinical specimens. Then, the analyses of gene set enrichment, mutation, and chemotherapeutic response were performed via R package. As results showed, 109 differentially expressed metabolic genes were screened out in PC. Then a metabolism-related five-gene signature comprising B3GNT3, BCAT1, KYNU, LDHA, and TYMS was constructed and showed excellent ability for predicting survival. A novel nomogram coordinating the metabolic signature and other independent prognostic parameters was developed and showed better predictive power in predicting survival. In addition, this metabolic signature was significantly involved in the activation of multiple oncological pathways and regulation of the tumor immune microenvironment. The patients with high risk scores had higher tumor mutation burdens and were prone to be more sensitive to chemotherapy. In summary, our work identified a new metabolic signature and established a superior prognostic nomogram which may supply more indications to explore novel strategies for diagnosis and treatment.