Identification of a DNA repair 9-gene signature for the overall survival prediction of pancreatic cancer

Pancreatic cancer (PC) is one of the deadliest malignant tumors with poor prognosis. DNA repair genes can be promising candidate biomarkers in PC. The aim of this study was to generate and clinically validate a novel gene signature to effectively predict the prognosis of patients with PC. The PC-related data of cancer genome atlas database and the GSE62452, GSE85916 of the gene expression omnibus database were downloaded for signature and further validation. According to the risk score, Patients were classified into high and low risk score groups. We analyzed drug sensitivity base on genomics of drug sensitivity in cancer and immune cell infiltration via CIBERSORT between the two groups. Gene set variation Analysis was performed to analyze signaling pathways affecting prognosis. Nine genes (F5, CD36, TRIM29, VCAM1, ANO1 , ERBB3, MMP28, NEK2 and MET) were identified to construct a prognostic model. Patients with lower risk score had significantly favorable overall survival in the TCGA database, GSE62452 and GSE85916 dataset ( p < 0.05). GSVA analysis showed differences in 13 important signaling pathways between high and low risk score groups. Immune-modulating factors (ADORA2A, CD160, KDR, BTLA) were highly expressed in the low-risk group. The risk score significantly affected the sensitivity of patients to Gefitinib and Dasatinib ( p < 0.005) and associated with overall survival and grade ( p < 0.05). This study evaluated a potential prognostic signature base on nine DNA repair genes and provides a way to explore the mechanism of DNA repair genes and immunotherapy in pancreatic cancer. • Nine genes signature were identified to construct a prognostic model for pancreatic cancer. • The model has strong predictive effectiveness in predicting the prognosis of patients. • The model was implicated in immune infiltration, tumor microenvironment, multiple signaling pathways and drug sensitivity