AUTHOR=Chen Haofei , Xu Ning , Xu Jia , Zhang Cheng , Li Xin , Xu Hao , Zhu Weixiong , Li Jinze , Liang Daoming , Zhou Wence 

TITLE=A risk signature based on endoplasmic reticulum stress-associated genes predicts prognosis and immunity in pancreatic cancer

JOURNAL=Frontiers in Molecular Biosciences

VOLUME=Volume 10 - 2023

YEAR=2023

URL=https://www.frontiersin.org/journals/molecular-biosciences/articles/10.3389/fmolb.2023.1298077

DOI=10.3389/fmolb.2023.1298077

ISSN=2296-889X

ABSTRACT=Endoplasmic reticulum (ER) stress has been revealed to involve in cancer biology. However, the roles of ER stress in pancreatic cancer (PC) are poorly understood. Here, we performed a bioinformatic analysis based on TCGA and ICGC databases to study the role of ER stress in prognosis and biological characteristics in PC patients. To this end, we first acquired 295 ER stressassociated genes from MSigDB and extracted survival data of 164 PC patients from TCGA. Then, we identified 46 ER stress-associated genes closely linked with overall survival (OS) of PC patients via log-rank test and univariate Cox analysis, and further narrowed 12 optimal prognostic genes to build a risk signature via LASSO method. Next, these 164 PC patients were stratified into two clusters according to the risk signature score, and worse OS in PC patients with high-risk signature score was observed; Moreover, multivariate analysis underscored our ER stress-associated signature as a valuable and independent predictor of prognosis. Importantly, these results based on TCGA were further validated in ICGC dataset. In addition, our risk signature was closely associated with homeostasis, protein secretion, and immune regulation in PC patients. In particular, PC microenvironment in the high-risk cluster exhibited a more immunosuppressive status, indicating that ER stress may play a pivotal role in inducing immune evasion. At last, we established a nomogram model by incorporating the risk signature and clinicopathological parameters, which behaves better in predicting prognosis of PC patients. In short, our comprehensive molecular analysis constructs a new effective predictive model for PC patients' prognosis and suggests that ER stress may serve as promising therapeutic targets in PC.