Integration of Metabolomics and Transcriptomics Revealed a Fatty Acid Network Exerting Growth Inhibitory Effects in Human Pancreatic Cancer

Abstract

PURPOSE: To identify metabolic pathways that are perturbed in pancreatic ductal adenocarcinoma (PDAC), we investigated gene-metabolite networks with integration of metabolomics and transcriptomics. EXPERIMENTAL DESIGN: We conducted global metabolite profiling analysis on two independent cohorts of resected PDAC cases to identify critical metabolites alteration that may contribute to the progression of pancreatic cancer. We then searched for gene surrogates that were significantly correlated with the key metabolites, by integrating metabolite and gene expression profiles. RESULTS: Fifty-five metabolites were consistently altered in tumors as compared with adjacent nontumor tissues in a test cohort (N = 33) and an independent validation cohort (N = 31). Weighted network analysis revealed a unique set of free fatty acids (FFA) that were highly coregulated and decreased in PDAC. Pathway analysis of 157 differentially expressed gene surrogates revealed a significantly altered lipid metabolism network, including key lipolytic enzymes PNLIP, CLPS, PNLIPRP1, and PNLIPRP2. Gene expressions of these lipases were significantly decreased in pancreatic tumors as compared with nontumor tissues, leading to reduced FFAs. More importantly, a lower gene expression of PNLIP in tumors was associated with poorer survival in two independent cohorts. We further showed that two saturated FFAs, palmitate and stearate, significantly induced TRAIL expression, triggered apoptosis, and inhibited proliferation in pancreatic cancer cells. CONCLUSIONS: Our results suggest that impairment in a lipolytic pathway involving lipases, and a unique set of FFAs, may play an important role in the development and progression of pancreatic cancer and provide potential targets for therapeutic intervention.