A Novel Ferroptosis-Related Gene Signature Predicts Recurrence in Patients With Pancreatic Ductal Adenocarcinoma

被引:3
|
作者
Feng, Zengyu [1 ,2 ,3 ]
Chen, Peng [1 ]
Li, Kexian [1 ,2 ]
Lou, Jianyao [3 ]
Wu, Yulian [3 ]
Li, Tao [1 ]
Peng, Chenghong [1 ,2 ]
机构
[1] Shanghai Jiao Tong Univ, Ruijin Hosp, Dept Gen Surg, Sch Med, Shanghai, Peoples R China
[2] Shanghai Jiao Tong Univ, Res Inst Pancreat Dis, Sch Med, Shanghai, Peoples R China
[3] Zhejiang Univ, Sch Med, Affiliated Hosp 2, Dept Gen Surg, Hangzhou, Peoples R China
基金
中国国家自然科学基金;
关键词
pancreatic ductal adenocarcinoma; ferroptosis; prognostic model; bioinformatics; recurrence; prognosis; CELL-DEATH; CANCER; GEMCITABINE; METABOLISM; MANAGEMENT; RESISTANCE; SURVIVAL;
D O I
10.3389/fmolb.2021.650264
中图分类号
Q5 [生物化学]; Q7 [分子生物学];
学科分类号
071010 ; 081704 ;
摘要
Background: Recurrence after surgery is largely responsible for the extremely poor outcomes for patients with pancreatic ductal adenocarcinoma (PDAC). Ferroptosis is implicated in chemotherapy sensitivity and tumor recurrence, we aimed to find out survival-associated ferroptosis-related genes and use them to build a practical risk model with the purpose to predict PDAC recurrence. Methods: Univariate Cox regression analysis was conducted to obtain prognostic ferroptosis-related genes in The Cancer Genome Atlas (TCGA, N = 140) cohort. Multivariate Cox regression analysis was employed to construct a reliable and credible gene signature. The prognostic performance was verified in a MTAB-6134 (N = 286) validation cohort and a PACA-CA (N = 181) validation cohort. The stability of the signature was tested in TCGA and MTAB-6134 cohorts by ROC analyses. Pathway enrichment analysis was adopted to preliminary illuminate the biological relevance of the gene signature. Results: Univariate and multivariate Cox regression analyses identified a 5-gene signature that contained CAV1, DDIT4, SLC40A1, SRXN1 and TFAP2C. The signature could efficaciously stratify PDAC patients with different recurrence-free survival (RFS), both in the training and validation cohorts. Results of subgroup receiver operating characteristic curve (ROC) analyses confirmed the stability and the independence of this signature. Our signature outperformed clinical indicators and previous reported models in predicting RFS. Moreover, the signature was found to be closely associated with several cancer-related and drug response pathways. Conclusion: This study developed a precise and concise prognostic model with the clinical implication in predicting PDAC recurrence. These findings may facilitate individual management of postoperative recurrence in patients with PDAC.
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页数:11
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