Background: Pancreatic
adenocarcinoma (PAAD) is one of the most aggressive
tumors of the digestive tract, with low surgical resection rate and insensitivity to
radiotherapy and
chemotherapy. Existing evidence suggests that regulation of ferroptosis can induce PAAD cell death, inhibit
tumor growth, and may synergistically improve the sensitivity of other
antitumor drugs. However, there is little of systematic research on
iron metabolism-related genes in PAAD. In this study, a risk-score system of PAAD
iron metabolism-related genes was designed and tested, and verified to be robust. Materials and Methods: The TCGA database was used to download 177 PAAD patients' message
RNA (
mRNA) expression profiles and clinical characteristics. By identifying dysregulated
iron metabolism-related genes between PAAD related tissues and adjacent normal tissues, univariate Cox proportional hazards regression and LASSO regression algorithm were used to establish prognostic risk-score system and construct nomogram to estimate the 1-, 2-, 3-year survival in PAAD patients. Finally, selected genes were validated by quantitative PCR (q-PCR). Results: A 9-gene related to
iron metabolism risk-score system of PAAD was constructed and validated. The clinicopathological characteristics of age, histologic grade, pathologic stage, T stage,
residual tumor, and primary
therapy outcome were all worse in patients with a higher risk-score. Further, immunohistochemistry results of SLC2A1, MBOAT2, XDH, CTSE, MOCOS, and ATP6V0A4 confirmed that patients with higher expression are more malignant. Then, a nomogram with 9-gene risk score system as a separate clinical factor was utilized to foretell the 1-, 2-, 3-year overall survival rate of PAAD patients. Results of q-PCR showed that 8 of the 9 genes screened were significantly up-regulated in at least one PAAD cell line, and one gene was significantly down-regulated in three PAAD cell lines. Conclusion: To conclude, we generated a nine-gene system linked to
iron metabolism as an independent
indicator for predicting PAAD prognosis, therefore presenting a possible prognostic
biomarker and potential treatment targets for PAAD.