BackgroundPancreatic ductal adenocarcinoma (PDAC) is a highly aggressive lethal malignancy. An effective prognosis prediction model is urgently needed for treatment optimization.MethodsThe differentially expressed unfolded protein response (UPR)‒related genes between pancreatic tumor and normal tissue were analyzed using the TCGA-PDAC dataset, and these genes that overlapped with UPR‒related prognostic genes from the E-MTAB-6134 dataset were further analyzed. Univariate, LASSO and multivariate Cox regression analyses were applied to establish a prognostic gene signature, which was evaluated by Kaplan‒Meier curve and receiver operating characteristic (ROC) analyses. E‒MTAB‒6134 was set as the training dataset, while TCGA-PDAC, GSE21501 and ICGC-PACA-AU were used for external validation. Subsequently, a nomogram integrating risk scores and clinical parameters was established, and gene set enrichment analysis (GSEA), tumor immunity analysis and drug sensitivity analysis were conducted.ResultsA UPR-related signature comprising twelve genes was constructed and divided PDAC patients into high- and low-risk groups based on the median risk score. The UPR-related signature accurately predicted the prognosis and acted as an independent prognostic factor of PDAC patients, and the AUCs of the UPR-related signature in predicting PDAC prognosis at 1, 2 and 3 years were all more than 0.7 in the training and validation datasets. The UPR-related signature showed excellent performance in outcome prediction even in different clinicopathological subgroups, including the female (p<0.0001), male (p<0.0001), grade 1/2 (p<0.0001), grade 3 (p=0.028), N0 (p=0.043), N1 (p<0.001), and R0 (p<0.0001) groups. Furthermore, multiple immune-related pathways were enriched in the low-risk group, and risk scores in the low-risk group were also associated with significantly higher levels of tumor-infiltrating lymphocytes (TILs). In addition, DepMap drug sensitivity analysis and our validation experiment showed that PDAC cell lines with high UPR-related risk scores or UPR activation are more sensitive to floxuridine, which is used as an antineoplastic agent.ConclusionHerein, we identified a novel UPR-related prognostic signature that showed high value in predicting survival in patients with PDAC. Targeting these UPR-related genes might be an alternative for PDAC therapy. Further experimental studies are required to reveal how these genes mediate ER stress and PDAC progression.

The human aldo-keto reductase (AKRs) superfamily is involved in the development of various tumors. However, the different expression patterns of AKRs and their prognostic value in gastric cancer (GC) have not been clarified. In this study, we analyzed the gene expression and gene methylation level of AKRs in GC patients and the survival data and immune infiltration based on AKRs expression, using data from different databases. We found that the expression levels of AKR1B10, AKR1C1, AKR1C2, and AKR7A3 in GC tissues were lower and the expression level of AKR6A5 was higher in GC tissues than in normal tissue. These differentially expressed genes (AKR1B10, AKR1C1, AKR1C2, AKR7A3, and AKR6A5) were significantly correlated with the infiltration level. The expression of SPI1 and AKR6A5 in GC was positively correlated. Survival analysis showed that GC levels of AKR6A5 reduced or increased mRNA levels of AKR7A3, and AKR1B10 was expected to have higher overall survival (OS), first progression (FP) survival, and postprogression survival (PPS) rates and a better prognosis. Moreover, the expression of AKR1B1 was found to be correlated with the staging of GC. The methylation of AKR6A5 (KCNAB2) at cg05307871 and cg01907457 was significantly associated with the classification of GC. Meta-analysis and ROC curve analysis show that the expression level of AKR1B1 and the methylation of cg16156182 (KCNAB1), cg11194299 (KCNAB2), cg16132520 (AKR1B1), and cg13801416 (AKR1B1) had a high hazard ratio and a good prognostic value. These data suggest that the expression and methylation of AKR1B1 and AKR6A5 are significantly related to the prognosis.