Pancreatic cancer is a lethal disease. Chemoresistance is one of the characteristics of pancreatic cancer and leads to a poor prognosis. This study built an effective predictive model for personalized treatment and explored the molecular mechanism of chemoresistance. A four-gene signature, including serine peptidase inhibitor Kazal type 1 (SPINK1), anoctamin 1 (ANO1), desmoglein 3 (DSG3) and GTPase, IMAP family member 1 (GIMAP1) was identified and associated with prognosis and chemoresistance in the training group. An internal testing dataset and the external dataset, GSE57495, were used for validation and showed a good performance of the gene signature. The high-risk group was enriched with multiple oncological pathways related to immunosuppression and was correlated with epidermal growth factor receptor (EGFR) expression, a target molecule of Erlotinib. In conclusion, this study identified a four-gene signature and established two nomograms for predicting prognosis and chemotherapy responses in patients with pancreatic cancer. The clinical value of the nomogram was evaluated by decision curve analysis (DCA). It showed that these may be helpful for clinical treatment decision-making and the discovery of the potential molecular mechanism and therapy targets for pancreatic cancer.
Keywords: chemoresistance; nomogram; overall survival; pancreatic cancer; tumor microenvironment.