Identifying Liver Metastasis-Related Genes Through a Coexpression Network to Construct a 5-Gene Model for Predicting Pancreatic Ductal Adenocarcinoma Patient Prognosis

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OBJECTIVES: This study aimed to develop a liver metastasis-related gene prognostic index (LMPI) for pancreatic ductal adenocarcinoma prognosis and therapy. METHODS: The Cancer Genome Atlas data set was used to identify liver metastasis-related hub genes via weighted gene coexpression network analysis. The core genes were identified to construct an LMPI by using the Cox regression method. An immune cell abundance identifier was applied to determine the immune cell abundance. RESULTS: A total of 78 hub liver metastasis-related genes in the black module were significantly enriched in complement and coagulation cascades, fat digestion and absorption, and the PPAR signaling pathway. Then, an LMPI was constructed on the basis of the 5 prognostic genes (MOGAT3, ASGR1, TRPM8, SGSM1, and LOC101927851). Patients with higher LMPI scores had poor overall survival, more co-occurring or mutually exclusive pairs of driver gene mutations, and less benefit from immunotherapy than patients with lower LMPI scores. In addition, a high correlation was also found between LMPI scores and immune infiltration, such as CD4 naive, CD8 T, cytotoxic T, T helper 2, follicular helper T, and natural killer cells. CONCLUSIONS: The core genes of the LMPI developed may be independent factors for predicting prognosis, immune characteristics, and immunotherapy efficacy in pancreatic ductal adenocarcinoma.

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