Determination of a DNA repair-related gene signature with potential implications for prognosis and therapeutic response in pancreatic adenocarcinoma - Lai, Jinzhi; Chen, Weijie; Zhao, Aiyue; Huang, Jingshan (Frontiers in Oncology, 2022)
Background: Pancreatic adenocarcinoma (PAAD) is one of the leading causes of cancer death in the world. Alterations of DNA repair-related genes (DRGs) are observed in a variety of cancers and have been shown to affect the development and treatment of cancers. The aim of this study was to develop a DRGs-related signature in predicting prognosis and therapeutic responses in PAAD. Methods: We constructed a DRG signature using the least absolute shrinkage and selection operator (LASSO) cox regression analysis in the TCGA training set. The GSE71729 was used as validation set. A predictive nomogram was constructed base on multivariate Cox regression. Calibration curve and decision curve analysis (DCA) were applied to validate the performance of the nomogram. The CIBERSORT and ssGSEA algorithm were utilized to explore the relationship between the prognostic signature and the immune cell infiltration. pRRophetic algorithm was used to estimate the sensitivity of chemotherapeutic agents. CellMiner database and PAAD cell lines were used to investigate the relationship between DRGs expression and therapeutic responses. Results: We developed a DRG signature consisted of three DRGs (RECQL, POLQ and RAD17), which could predict patients' prognosis in PAAD patients. A prognostic nomogram combining the risk score and clinical factors was developed for prognostic prediction. The DCA curve and calibration curve demonstrated that the nomogram had a higher net benefit in comparison to risk score and TNM staging system. Immune infiltration analysis demonstrated that the risk score was positively correlated with the proportions of activated NK cells and monocytes. Drug sensitivity analysis indicated that the signature had a potential predictive value for chemotherapeutic. Analyses utilizing the CellMiner database showed that RAD17 expression was correlated with oxaliplatin. The dynamic changes of three DRGs in response to oxaliplatin were examined by RT-qPCR, which demonstrated that RAD17 was up-regulated in response to oxaliplatin in PAAD cell lines. Conclusion: We constructed and validated a novel DRG signature to predict prognosis and drug sensitivity of patients with PAAD. Our study provided a theoretical basis for further unraveling the molecular pathogenesis of PAAD and help clinicians in tailor systemic therapies within the framework of individualizing treatment.