A novel defined manganese metabolism-related gene signature for predicting the prognosis of pancreatic ductal adenocarcinoma.

Pancreatic ductal adenocarcinoma (PDAC) represents a particularly aggressive and highly malignant neoplasm, characterized by its unfavorable prognosis and restricted treatment alternatives. The present study aimed to use bioinformatics methodologies to assess transcriptomic data sourced from The Cancer Genome Atlas and the Gene Expression Omnibus to pinpoint biomarkers associated with manganese metabolism that may forecast outcomes in PDAC. Utilizing differential expression analysis, Least Absolute Shrinkage and Selection Operator regression and multivariable Cox regression, 12 essential genes were identified that demonstrate notable associations with the prognosis of PDAC (Natriuretic Peptide A, Kynureninase, Integrin Subunit β6, Cytochrome P450 Family 27 Subfamily A Member 1, C-X-C Motif Chemokine Ligand 10, Protein Phosphatase 2 Regulatory Subunit Bβ, MET Proto-Oncogene Receptor Tyrosine Kinase, Matrix Metalloproteinase 3, Keratin 19, ATPase Na/K Transporting Subunit α3, Pyridoxal Phosphatase and Interleukin 1 Receptor Accessory Protein Like 2). The validation of these genes was performing using both a training cohort and external datasets (GSE62452 and GSE28735), demonstrating the robustness of the model with area under the curve values of 0.82 and 0.83 in the training set and the external validation cohort, respectively. The results of the present study further elucidated the molecular processes underlying PDAC and highlight the crucial importance of manganese metabolism in its development. These biomarkers may provide significant prognostic insights and facilitate the advancement of targeted therapeutic strategies for PDAC.