• 文献检索
  • 文档翻译
  • 深度研究
  • 学术资讯
  • Suppr Zotero 插件Zotero 插件
  • 邀请有礼
  • 套餐&价格
  • 历史记录
应用&插件
Suppr Zotero 插件Zotero 插件浏览器插件Mac 客户端Windows 客户端微信小程序
定价
高级版会员购买积分包购买API积分包
服务
文献检索文档翻译深度研究API 文档MCP 服务
关于我们
关于 Suppr公司介绍联系我们用户协议隐私条款
关注我们

Suppr 超能文献

核心技术专利：CN118964589B侵权必究
粤ICP备2023148730 号-1Suppr @ 2026

文献检索

告别复杂PubMed语法，用中文像聊天一样搜索，搜遍4000万医学文献。AI智能推荐，让科研检索更轻松。

立即免费搜索

文件翻译

保留排版，准确专业，支持PDF/Word/PPT等文件格式，支持 12+语言互译。

免费翻译文档

深度研究

AI帮你快速写综述，25分钟生成高质量综述，智能提取关键信息，辅助科研写作。

立即免费体验

利用综合生物信息学分析鉴定胰腺癌中与预后相关的关键氧化应激基因

Identification of Hub Prognosis-Associated Oxidative Stress Genes in Pancreatic Cancer Using Integrated Bioinformatics Analysis.

作者信息

Qiu Xin, Hou Qin-Han, Shi Qiu-Yue, Jiang Hai-Xing, Qin Shan-Yu

机构信息

Department of Gastroenterology, The First Affiliated Hospital of Guangxi Medical University, Nanning, China.

Department of Neurosurgery, Affiliated Tumor Hospital of Guangxi Medical University, Nanning, China.

出版信息

Front Genet. 2020 Dec 8;11:595361. doi: 10.3389/fgene.2020.595361. eCollection 2020.

DOI:10.3389/fgene.2020.595361
PMID:33363572
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC7753072/
Abstract

BACKGROUND

Intratumoral oxidative stress (OS) has been associated with the progression of various tumors. However, OS has not been considered a candidate therapeutic target for pancreatic cancer (PC) owing to the lack of validated biomarkers.

METHODS

We compared gene expression profiles of PC samples and the transcriptome data of normal pancreas tissues from The Cancer Genome Atlas (TCGA) and Genome Tissue Expression (GTEx) databases to identify differentially expressed OS genes in PC. PC patients' gene profile from the Gene Expression Omnibus (GEO) database was used as a validation cohort.

RESULTS

A total of 148 differentially expressed OS-related genes in PC were used to construct a protein-protein interaction network. Univariate Cox regression analysis, least absolute shrinkage, selection operator analysis revealed seven hub prognosis-associated OS genes that served to construct a prognostic risk model. Based on integrated bioinformatics analyses, our prognostic model, whose diagnostic accuracy was validated in both cohorts, reliably predicted the overall survival of patients with PC and cancer progression. Further analysis revealed significant associations between seven hub gene expression levels and patient outcomes, which were validated at the protein level using the Human Protein Atlas database. A nomogram based on the expression of these seven hub genes exhibited prognostic value in PC.

CONCLUSION

Our study provides novel insights into PC pathogenesis and provides new genetic markers for prognosis prediction and clinical treatment personalization for PC patients.

摘要

背景

肿瘤内氧化应激（OS）与多种肿瘤的进展相关。然而，由于缺乏经过验证的生物标志物，OS尚未被视为胰腺癌（PC）的候选治疗靶点。

方法

我们比较了癌症基因组图谱（TCGA）和基因组组织表达（GTEx）数据库中PC样本的基因表达谱以及正常胰腺组织的转录组数据，以鉴定PC中差异表达的OS基因。来自基因表达综合数据库（GEO）的PC患者基因谱用作验证队列。

结果

共使用PC中148个差异表达的OS相关基因构建蛋白质-蛋白质相互作用网络。单变量Cox回归分析、最小绝对收缩和选择算子分析揭示了七个与预后相关的关键OS基因，用于构建预后风险模型。基于综合生物信息学分析，我们的预后模型在两个队列中均验证了其诊断准确性，能够可靠地预测PC患者的总生存期和癌症进展。进一步分析揭示了七个关键基因表达水平与患者预后之间的显著关联，并使用人类蛋白质图谱数据库在蛋白质水平上进行了验证。基于这七个关键基因表达的列线图在PC中具有预后价值。

结论

我们的研究为PC发病机制提供了新见解，并为PC患者的预后预测和临床治疗个性化提供了新的遗传标志物。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/b076/7753072/faa5b5c009b3/fgene-11-595361-g011.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/b076/7753072/e84aab5bcde5/fgene-11-595361-g001.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/b076/7753072/01396654cbfe/fgene-11-595361-g002.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/b076/7753072/caf2e9081682/fgene-11-595361-g003.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/b076/7753072/7717b63a5709/fgene-11-595361-g004.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/b076/7753072/2ed48bbf10f6/fgene-11-595361-g005.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/b076/7753072/f5e7fd617a9a/fgene-11-595361-g006.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/b076/7753072/4efc0f09fefa/fgene-11-595361-g007.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/b076/7753072/3b8e1d48c11d/fgene-11-595361-g008.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/b076/7753072/594085047832/fgene-11-595361-g009.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/b076/7753072/5a80fcffefb7/fgene-11-595361-g010.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/b076/7753072/faa5b5c009b3/fgene-11-595361-g011.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/b076/7753072/e84aab5bcde5/fgene-11-595361-g001.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/b076/7753072/01396654cbfe/fgene-11-595361-g002.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/b076/7753072/caf2e9081682/fgene-11-595361-g003.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/b076/7753072/7717b63a5709/fgene-11-595361-g004.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/b076/7753072/2ed48bbf10f6/fgene-11-595361-g005.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/b076/7753072/f5e7fd617a9a/fgene-11-595361-g006.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/b076/7753072/4efc0f09fefa/fgene-11-595361-g007.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/b076/7753072/3b8e1d48c11d/fgene-11-595361-g008.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/b076/7753072/594085047832/fgene-11-595361-g009.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/b076/7753072/5a80fcffefb7/fgene-11-595361-g010.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/b076/7753072/faa5b5c009b3/fgene-11-595361-g011.jpg

相似文献

1
Identification of Hub Prognosis-Associated Oxidative Stress Genes in Pancreatic Cancer Using Integrated Bioinformatics Analysis.利用综合生物信息学分析鉴定胰腺癌中与预后相关的关键氧化应激基因
Front Genet. 2020 Dec 8;11:595361. doi: 10.3389/fgene.2020.595361. eCollection 2020.
2
Identification of hub prognosis-associated oxidative stress genes in skin cutaneous melanoma using integrated bioinformatic analysis.基于整合生物信息学分析鉴定皮肤黑色素瘤中与预后相关的氧化应激枢纽基因
Eur Rev Med Pharmacol Sci. 2021 Apr;25(7):2927-2940. doi: 10.26355/eurrev_202104_25546.
3
Construction of a five-gene prognostic model based on immune-related genes for the prediction of survival in pancreatic cancer.构建基于免疫相关基因的五个基因预后模型，用于预测胰腺癌的生存情况。
Biosci Rep. 2021 Jul 30;41(7). doi: 10.1042/BSR20204301.
4
Integrated analysis identifies oxidative stress genes associated with progression and prognosis in gastric cancer.综合分析鉴定出与胃癌进展和预后相关的氧化应激基因。
Sci Rep. 2021 Feb 8;11(1):3292. doi: 10.1038/s41598-021-82976-w.
5
Identification of the Real Hub Gene and Construction of a Novel Prognostic Signature for Pancreatic Adenocarcinoma Based on the Weighted Gene Co-expression Network Analysis and Least Absolute Shrinkage and Selection Operator Algorithms.基于加权基因共表达网络分析和最小绝对收缩与选择算子算法鉴定胰腺腺癌真正的核心基因并构建新型预后特征
Front Genet. 2021 Aug 20;12:692953. doi: 10.3389/fgene.2021.692953. eCollection 2021.
6
Identification of hub genes with diagnostic values in pancreatic cancer by bioinformatics analyses and supervised learning methods.基于生物信息学分析和有监督学习方法鉴定胰腺癌诊断价值的关键基因。
World J Surg Oncol. 2018 Nov 14;16(1):223. doi: 10.1186/s12957-018-1519-y.
7
A clinical prognostic model of oxidative stress-related genes linked to tumor immune cell infiltration and the prognosis of ovarian cancer patients.一种与肿瘤免疫细胞浸润及卵巢癌患者预后相关的氧化应激相关基因的临床预后模型。
Heliyon. 2024 Mar 21;10(7):e28442. doi: 10.1016/j.heliyon.2024.e28442. eCollection 2024 Apr 15.
8
Identification of hub genes correlated with the pathogenesis and prognosis in Pancreatic adenocarcinoma on bioinformatics methods.基于生物信息学方法鉴定与胰腺腺癌发病机制及预后相关的枢纽基因
Transl Cancer Res. 2020 Aug;9(8):4550-4562. doi: 10.21037/tcr-19-2873.
9
Identification of key genes for predicting colorectal cancer prognosis by integrated bioinformatics analysis.通过综合生物信息学分析鉴定预测结直肠癌预后的关键基因
Oncol Lett. 2020 Jan;19(1):388-398. doi: 10.3892/ol.2019.11068. Epub 2019 Nov 7.
10
Construction of a novel mRNA-signature prediction model for prognosis of bladder cancer based on a statistical analysis.基于统计分析构建新型膀胱癌 mRNA 特征预测预后模型。
BMC Cancer. 2021 Jul 27;21(1):858. doi: 10.1186/s12885-021-08611-z.

引用本文的文献

1
Effects of Oxidative Stress Gene Protein, Expression, and DNA Methylation on Multiple Sclerosis: A Multi-Omics Mendelian Randomized Study.氧化应激基因蛋白、表达及DNA甲基化对多发性硬化症的影响：一项多组学孟德尔随机化研究
Brain Behav. 2025 Jun;15(6):e70606. doi: 10.1002/brb3.70606.
2
Association of DNA damage response signals and oxidative stress status with nivolumab efficacy in patients with Head and Neck Squamous Cell Carcinoma.DNA损伤反应信号和氧化应激状态与头颈部鳞状细胞癌患者纳武利尤单抗疗效的关联
Br J Cancer. 2025 May 23. doi: 10.1038/s41416-025-03032-2.
3
Integrative multi-omics summary-based mendelian randomization identifies key oxidative stress-related genes as therapeutic targets for atrial fibrillation and flutter.

本文引用的文献

1
Prognostic Value of a Stemness Index-Associated Signature in Primary Lower-Grade Glioma.干性指数相关特征在原发性低级别胶质瘤中的预后价值
Front Genet. 2020 May 5;11:441. doi: 10.3389/fgene.2020.00441. eCollection 2020.
2
Novel Immune-Related Gene Signature for Risk Stratification and Prognosis of Survival in Lower-Grade Glioma.用于低级别胶质瘤生存风险分层和预后的新型免疫相关基因特征
Front Genet. 2020 Apr 15;11:363. doi: 10.3389/fgene.2020.00363. eCollection 2020.
3
A novel immune-related genes prognosis biomarker for melanoma: associated with tumor microenvironment.
基于整合多组学总结的孟德尔随机化确定关键氧化应激相关基因作为心房颤动和扑动的治疗靶点。
Front Genet. 2024 Sep 18;15:1447872. doi: 10.3389/fgene.2024.1447872. eCollection 2024.
4
Causal Effects of Oxidative Stress on Diabetes Mellitus and Microvascular Complications: Insights Integrating Genome-Wide Mendelian Randomization, DNA Methylation, and Proteome.氧化应激对糖尿病及微血管并发症的因果效应：整合全基因组孟德尔随机化、DNA甲基化和蛋白质组学的见解
Antioxidants (Basel). 2024 Jul 26;13(8):903. doi: 10.3390/antiox13080903.
5
Oxidative stress gene expression, DNA methylation, and gut microbiota interaction trigger Crohn's disease: a multi-omics Mendelian randomization study.氧化应激基因表达、DNA 甲基化和肠道微生物群相互作用引发克罗恩病：一项多组学孟德尔随机化研究。
BMC Med. 2023 May 11;21(1):179. doi: 10.1186/s12916-023-02878-8.
6
Identification and validation of oxidative stress and immune-related hub genes in Alzheimer's disease through bioinformatics analysis.通过生物信息学分析鉴定和验证阿尔茨海默病中的氧化应激和免疫相关枢纽基因。
Sci Rep. 2023 Jan 12;13(1):657. doi: 10.1038/s41598-023-27977-7.
7
An oxidative stress-related prognostic signature for indicating the immune status of oral squamous cell carcinoma and guiding clinical treatment.一种与氧化应激相关的预后特征，用于指示口腔鳞状细胞癌的免疫状态并指导临床治疗。
Front Genet. 2022 Sep 23;13:977902. doi: 10.3389/fgene.2022.977902. eCollection 2022.
8
An Oxidative Stress-Related Genes Signature for Predicting Survival in Bladder Cancer: Based on TCGA Database and Bioinformatics.一种用于预测膀胱癌生存的氧化应激相关基因特征：基于TCGA数据库和生物信息学
Int J Gen Med. 2022 Mar 8;15:2645-2667. doi: 10.2147/IJGM.S348945. eCollection 2022.
9
A Ductal-Cell-Related Risk Model Integrating Single-Cell and Bulk Sequencing Data Predicts the Prognosis of Patients With Pancreatic Adenocarcinoma.整合单细胞和批量测序数据的导管细胞相关风险模型可预测胰腺腺癌患者的预后。
Front Genet. 2022 Jan 3;12:763636. doi: 10.3389/fgene.2021.763636. eCollection 2021.
10
Development of epithelial-mesenchymal transition-related lncRNA signature for predicting survival and immune microenvironment in pancreatic cancerwithexperiment validation.上皮-间充质转化相关 lncRNA 标志物的开发用于预测胰腺癌的生存和免疫微环境，并通过实验验证。
Bioengineered. 2021 Dec;12(2):10553-10567. doi: 10.1080/21655979.2021.2000197.
一种新型的与黑色素瘤免疫相关的基因预后生物标志物：与肿瘤微环境相关。
Aging (Albany NY). 2020 Apr 20;12(8):6966-6980. doi: 10.18632/aging.103054.
4
Development and validation of a RNA binding protein-associated prognostic model for lung adenocarcinoma.肺腺癌 RNA 结合蛋白相关预后模型的建立与验证。
Aging (Albany NY). 2020 Feb 22;12(4):3558-3573. doi: 10.18632/aging.102828.
5
Risk score based on expression of five novel genes predicts survival in soft tissue sarcoma.基于五个新型基因表达的风险评分预测软组织肉瘤的生存。
Aging (Albany NY). 2020 Feb 21;12(4):3807-3827. doi: 10.18632/aging.102847.
6
Expression and prognostic value of long non-coding RNA H19 in glioma via integrated bioinformatics analyses.基于整合生物信息学分析的长链非编码 RNA H19 在脑胶质瘤中的表达及其预后价值。
Aging (Albany NY). 2020 Feb 20;12(4):3407-3430. doi: 10.18632/aging.102819.
7
Identification of a Nine-Gene Signature and Establishment of a Prognostic Nomogram Predicting Overall Survival of Pancreatic Cancer.一种九基因特征的鉴定及预测胰腺癌总生存期的预后列线图的建立
Front Oncol. 2019 Sep 27;9:996. doi: 10.3389/fonc.2019.00996. eCollection 2019.
8
Comprehensive investigation of the clinical significance and molecular mechanisms of plasmacytoma variant translocation 1 in sarcoma using genome-wide RNA sequencing data.利用全基因组RNA测序数据全面研究肉瘤中浆细胞瘤变异易位1的临床意义和分子机制。
J Cancer. 2019 Aug 27;10(20):4961-4977. doi: 10.7150/jca.31675. eCollection 2019.
9
Screening and identification of hub genes in pancreatic cancer by integrated bioinformatics analysis.通过综合生物信息学分析筛选和鉴定胰腺癌的枢纽基因。
J Cell Biochem. 2019 Dec;120(12):19496-19508. doi: 10.1002/jcb.29253. Epub 2019 Jul 11.
10
Early Detection of Pancreatic Cancer: Opportunities and Challenges.早期胰腺癌检测：机遇与挑战。
Gastroenterology. 2019 May;156(7):2024-2040. doi: 10.1053/j.gastro.2019.01.259. Epub 2019 Feb 2.