Establishment of a prognostic risk scoring model for patients with pancreatic ductal adenocarcinoma based on cell ferroptosis-related genes and its application value

Objective To establish a prognostic risk scoring model for patients with pancreatic ductal adenocarcinoma (PDAC) based on cell ferroptosis-related genes, and to investigate its application value. Methods The Cancer Genome Atlas (TCGA) database, Gene Expression Omnibus database, and Genotype-Tissue Expression database were used to obtain the transcriptome sequencing data of PDAC tissue and normal pancreatic tissues and the clinical data of PDAC patients including overall survival (OS), and the GeneCards database was used to obtain the data on cell ferroptosis-related genes. R software was used to identify the differentially expressed genes (DEGs) between PDAC tissue and normal pancreatic tissue. The univariate Cox regression analysis and LASSO regression were used to establish a prognostic risk scoring model for PDAC patients, and based on this risk scoring model, the PDAC cases in TCGA database were divided into low- and high-risk groups. The Kaplan-Meier survival curves were plotted to compare OS between the two groups. CCK-8 assay and Western blotting were used to further validate the association between the key genes of cell ferroptosis in the risk scoring model and cell ferroptosis in PDAC. Results A prognostic risk scoring model for PDAC patients was successfully established based on seven cell ferroptosis-related genes, i.e., SLC6A14, DKK1, KRT19, AURKA, EMP1, ANXA2, and LGALS3, and the Kaplan-Meier survival curve showed that the low-risk group had a significantly longer OS than the high-risk group (P<0.05). CCK-8 showed that compared with the negative control group, the AURKA knockdown group of AsPC-1 and BxPC-3 PDAC cell lines had a significantly lower viability on days 3-5 (t=4.57-12.84,P<0.05), and Western blotting showed that compared with the negative control group, the AURKA knockdown group of AsPC-1 and BxPC-3 cells had significantly lower relative protein expression levels of AURKA, SLC7A11, and GPX4 (t=4.22-11.79,P<0.05). Conclusion Downregulation of the AURKA gene may lead to the development and progression of PDAC by promoting ferroptosis in PDAC cells, and the risk scoring model based on cell ferroptosis-related genes has a significant reference value for the prognostic assessment of PDAC patients.