AUTHOR=Chen Dongjie , Gao Wenzhe , Zang Longjun , Zhang Xianlin , Li Zheng , Zhu Hongwei , Yu Xiao 

TITLE=Ferroptosis-Related IncRNAs Are Prognostic Biomarker of Overall Survival in Pancreatic Cancer Patients

JOURNAL=Frontiers in Cell and Developmental Biology

VOLUME=Volume 10 - 2022

YEAR=2022

URL=https://www.frontiersin.org/journals/cell-and-developmental-biology/articles/10.3389/fcell.2022.819724

DOI=10.3389/fcell.2022.819724

ISSN=2296-634X

ABSTRACT=Pancreatic cancer (PC) is one of the most lethal malignancies, the mortality and morbidity of which have been increasing over the past decade. Ferroptosis, a newly identified iron-dependent pattern of cell death, can be induced by iron chelators and small lipophilic antioxidants. Nonetheless, the prognostic significance of ferroptosis-related lncRNAs in PC remains to be explicated. In the current study, we obtained the lncRNA expression matrix and clinicopathological information of PC patients from public databases. Pearson correlation analysis was conducted to delve into the ferroptosis-related lncRNAs, and univariate Cox analysis was implemented to examine the prognostic values in PC patients. 23 prognostic ferroptosis-related lncRNAs were confirmed and loaded into the least absolute shrinkage and selection operator Cox (LASSO-Cox) analysis, thereupon the ferroptosis-related lncRNA prognostic marker (Fe-LPM) was established to segregate PC patients into two subgroups. The Fe-LPM displayed a sturdy prognostic capability and was validated in the ICGC dataset. Gene set enrichment analysis (GSEA) revealed that several pathways are enriched in low-risk subgroups. Furthermore, we adopted a multivariate Cox regression to establish a nomogram based on risk score, age, pathological T stage and primary therapy outcome. A competing endogenous RNA (ceRNA) network was also created relied on 4 of the 23 ferroptosis-related lncRNAs. In conclusion, the eight Fe-LPM can be utilized for anticipating the overall survival (OS) of PC patients, which are meaningful to guiding clinical strategies of PC.