Development Of A Prognostic Model Based On Ferritinophagy-Related Genes In Pancreatic Adenocarcinoma

Objective:The intention of this study was to identify the prognostic significance of ferritinophagy-related genes in pancreatic cancer by bioinformatics analysis.Methods:To address this issue,the prognostic model of ferritinophagy-related genes in pancreatic cancer was established through least absolute shrinkage and selection operator(LASSO)method..Pancreatic cancer patients in The Cancer Genome Atlas(TCGA)and Gene Expression Omnibus(GEO)datasets are further grouped into 2 groups:low-risk and high-risk,separately,according to the median risk score.Comprehensive bioinformatic analyses were performed to explore the prognostic value of the ferritinophagy-related genes members in PAAD,by use of R(version 4.1.2),Cytoscape(version 3.9.1),STRING,human protein atlas(HPA),etc.Results:There are 8 genes(ALOX15,ATG16L1,ATG7,BCAT2,CYB561A3,SNCA,TNF,FBXW7).In the LASSO regression model,functional enrichment analysis revealed the cellular response to oxidative stress,regulation of response to oxidative stress,autophagy-related biological processes,and signaling pathways.The protein-protein interaction analysis of the 8 ferritinophagy prognosis-related genes was analyzed by STRING database.Cox regression showed that the high expression level of BCAT2 and SNCA expression level was significantly correlated with the good prognosis in clinical pancreatic cancer patients.Conclusion:Taken together,these results indicated that ferritinophagy-related prognostic genes had good prognostic value for pancreatic cancer patients by using bioinformatics functional analysis,and our conclusions and perspectives might reveal the mechanisms of pancreatic cancer and provide novel treatment strategies for pancreatic cancer.