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一种新型铁死亡相关基因特征可预测胰腺导管腺癌患者的复发情况。

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

作者信息

Feng Zengyu, Chen Peng, Li Kexian, Lou Jianyao, Wu Yulian, Li Tao, Peng Chenghong

机构信息

Department of General Surgery, Ruijin Hospital, Shanghai Jiaotong University School of Medicine, Shanghai, China.

Research Institute of Pancreatic Diseases, Shanghai Jiaotong University School of Medicine, Shanghai, China.

出版信息

Front Mol Biosci. 2021 Sep 23;8:650264. doi: 10.3389/fmolb.2021.650264. eCollection 2021.

Abstract

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. 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. 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. 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.

摘要

手术复发在很大程度上导致了胰腺导管腺癌(PDAC)患者的极差预后。铁死亡与化疗敏感性和肿瘤复发有关,我们旨在找出与生存相关的铁死亡相关基因,并利用它们构建一个实用的风险模型,以预测PDAC复发。在癌症基因组图谱(TCGA,N = 140)队列中进行单变量Cox回归分析,以获得预后铁死亡相关基因。采用多变量Cox回归分析构建可靠且可信的基因特征。在MTAB - 6134(N = 286)验证队列和PACA - CA(N = 181)验证队列中验证了预后性能。通过ROC分析在TCGA和MTAB - 6134队列中测试了该特征的稳定性。采用通路富集分析初步阐明基因特征的生物学相关性。单变量和多变量Cox回归分析确定了一个包含CAV1、DDIT4、SLC40A1、SRXN1和TFAP2C的5基因特征。该特征能够有效地将不同无复发生存期(RFS)的PDAC患者进行分层,无论是在训练队列还是验证队列中。亚组受试者工作特征曲线(ROC)分析结果证实了该特征的稳定性和独立性。我们的特征在预测RFS方面优于临床指标和先前报道的模型。此外,发现该特征与几种癌症相关和药物反应通路密切相关。本研究开发了一个精确且简洁的预后模型,对预测PDAC复发具有临床意义。这些发现可能有助于PDAC患者术后复发的个体化管理。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/3956/8495121/eca0ec393b1e/fmolb-08-650264-g001.jpg

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