Analysis Of Iron Metabolism-related Biomarkers In Pancreatic Adenocarcinoma

Background: Pancreatic adenocarcinoma(PAAD)has a nutrient-poor,desmoplastic,and highly innervated tumor microenvironment and dismal prognosis.The enhancement of iron metabolism is related to malignant transformation and cancer progression.Targeting iron metabolism pathway may provide a new scheme to improve the prognosis of cancer.This study aimed to identify survival-associated Iron metabolism-related biomarkers and build a risk model to predict the prognosis of PAAD by analyzing the data from TCGA,GEO,GTEx and other public databases.Methods: First,three datasets(GSE15471,GSE16515 and TCGA-PAAD)were downloaded using R-packet “GEOquery” and “TCGAbiolinks”,and Rpacket “Limma” and “DESeq2” were used to identify iron metabolism-related differentially expressed genes(DEGs)between the tumor group and the normal group in PAAD.Second,we conducted GO analysis,KEGG analysis and GSEA of iron metabolism-related DEGs based on R-packet “cluster Profiler”,further established interactive networks.Third,a Lasso regression prognostic model for screening Iron metabolism-related biomarkers was established in the verification set(TCGA-PAAD dataset)by R-packet “glmnet”,and the diagnostic effect of the model was evaluated by Wilcoxon rank sum test,ROC curve analysis and univariate and multivariate Cox regression analysis.In addition,we implemented immune infiltration.Results: We identified 10 iron metabolism-related DEGs,which were primarily enriched in vitamin D receptor pathway,integrin cell surface interactions,integrin α6β4pathway,cell-substrate adhesion regulation,cell cycle checkpoints,PLK1 pathway,nuclear receptors metapathway,TAp63 pathway,and other biological processes.Then,we filtrated six Iron metabolism-related biomarkers(DDC,F5,FAM83 D,MMP12,NQO1,SLPI)which were relevant to the occurrence and development of PAAD,patients with high expression of DDC had a low incidence of PAAD and had a good prognosis,while patients with high expression of FAM83 D,MMP12,NQO1 and SLPI had a high incidence of PAAD and a poor prognosis.We found that there were discernable differences in the infiltration abundance of seven immune cells(na?ve B cells,Plasma cells,CD8 T cells,resting memory CD4 T cells,Monocytes,M0 Macrophages,resting Dendritic cells)between the high and low risk groups of the prognostic model.Conclusions: Collectively,the Iron metabolism-related biomarkers(DDC,F5,FAM83 D,MMP12,NQO1,SLPI)have certain value in predicting the occurrence and survival of patients with PAAD,and may become a new target for diagnosis and treatment of PAAD.