Integrated bulk and single-cell transcriptomic analysis reveals inflammatory metabolic programs in pancreatic ductal adenocarcinoma

BACKGROUND: Pancreatic ductal adenocarcinoma (PDAC) is characterized by inflammatory signaling and metabolic adaptation within the tumor microenvironment. We integrated bulk and single-cell transcriptomic datasets to characterize inflammation-associated metabolic programs in PDAC. METHODS: Three public PDAC datasets were analyzed: TCGA-PAAD bulk RNA-seq data, GSE62452 tumor and adjacent tissue microarray data, and GSE154778 single-cell RNA-seq data from primary and metastatic PDAC. Kynurenine-, arachidonic acid-, inflammasome-, and glutamine-related transcriptional modules were evaluated. Cell-based qRT-PCR was used to validate selected inflammatory-metabolic genes after 48 h of cytokine stimulation. RESULTS: In GSE62452, 5985 of 33,297 probes were differentially expressed between tumor and adjacent tissues, including 3701 increased and 2284 decreased probes. Among selected targets, KYNU showed the largest increase. In 60 matched pairs, IDO1, KYNU, PTGS2, and PLA2G4A were significantly elevated in tumor tissues. Analysis of 14,926 single cells showed that myeloid cells had the highest mean scores across all four inflammatory-metabolic modules. Bulk expression patterns were positively associated across datasets (Spearman ρ=0.745, P = 0.0133). qRT-PCR further demonstrated cytokine-induced expression of selected inflammatory-metabolic genes. CONCLUSIONS: Integrated bulk and single-cell analyses identify inflammation-associated metabolic transcriptional programs in PDAC, with prominent activity in myeloid cells. These findings provide a transcriptomic framework for future mechanistic and multi-omic validation rather than direct evidence of metabolic flux or clinical utility.