Identification of an unfolded protein response-related signature for predicting the prognosis of pancreatic ductal adenocarcinoma

Fang, Lishan1; Chen, Shaojing1; Gong, Hui2,3; Xia, Shaohua4; Guan, Sainan5; Quan, Nali6; Li, Yajie7,8; Zeng, Chao9; Chen, Ya9; Du, Jianhang1; Liu, Shuguang9

2023-01-13

10.3389/fonc.2022.1060508

Frontiers in Oncology   影响因子和分区

2234-943X

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.

unfolded protein response risk score pancreatic cancer prognostic model survival analysis

SCI

英语

其他

Natural Science Foundation of China["81672957","82203671"] ; Natural Science Foundation of Guangdong Province["2017A030313761","2020A1515011303"] ; Shenzhen Science and Technology Program["JCYJ20210324115205014","JCYJ20220530144405013"] ; Fundamental Research Funds for the Central Universities[18ykpy28] ; Shenzhen Futian District Health Public Welfare Research Project[FTWS2020074]

Oncology

Oncology

WOS:000921668500001

FRONTIERS MEDIA SA

Web of Science

1.Sun Yat Sun Univ, Affiliated Hosp 8, Dept Med Res Ctr, Shenzhen, Peoples R China
2.Huazhong Univ Sci & Technol, Union Shenzhen Hosp, Dept Lab Med Ctr, Shenzhen, Peoples R China
3.Shenzhen Univ, Affliated Hosp 6, Shenzhen, Peoples R China
4.Sun Yat Sun Univ, Affiliated Hosp 8, Dept Gastrointestinal Endoscopy Ctr, Shenzhen, Peoples R China
5.Sun Yat Sun Univ, Affiliated Hosp 8, Dept Ultrasound Imaging, Shenzhen, Peoples R China
6.Sun Yat Sun Univ, Affiliated Hosp 8, Dept Clin Lab, Shenzhen, Peoples R China
7.Southern Univ Sci & Technol, Shenzhen Peoples Hosp 3, Dept Orthoped, Shenzhen, Peoples R China
8.Southern Univ Sci & Technol, Affiliated Hosp 2, Shenzhen, Peoples R China
9.Sun Yat Sun Univ, Affiliated Hosp 8, Dept Pathol, Shenzhen, Peoples R China

Fang, Lishan,Chen, Shaojing,Gong, Hui,et al. Identification of an unfolded protein response-related signature for predicting the prognosis of pancreatic ductal adenocarcinoma[J]. Frontiers in Oncology,2023,12.

Fang, Lishan.,Chen, Shaojing.,Gong, Hui.,Xia, Shaohua.,Guan, Sainan.,...&Liu, Shuguang.(2023).Identification of an unfolded protein response-related signature for predicting the prognosis of pancreatic ductal adenocarcinoma.Frontiers in Oncology,12.

Fang, Lishan,et al."Identification of an unfolded protein response-related signature for predicting the prognosis of pancreatic ductal adenocarcinoma".Frontiers in Oncology 12(2023).