Identification of Hub Prognosis-Associated Oxidative Stress Genes in Pancreatic Cancer Using Integrated Bioinformatics Analysis.
Identification of Hub Prognosis-Associated Oxidative Stress Genes in Pancreatic Cancer Using Integrated Bioinformatics Analysis.
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DOI：
10.3389/fgene.2020.595361
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发表时间：
2020
影响因子：
3.7
通讯作者：
Qin SY
中科院分区：
文献类型：
--
作者：
Qiu X;Hou QH;Shi QY;Jiang HX;Qin SY
肿瘤内氧化应激（OS）与多种肿瘤的进展有关。然而，由于缺乏经验证的生物标志物，OS尚未被认为是胰腺癌（PC）的候选治疗靶点。我们比较了PC样本的基因表达谱和来自癌症基因组图谱（TCGA）和基因组组织表达（GTEx）数据库的正常胰腺组织的转录组数据，以识别PC中差异表达的OS基因。使用来自基因表达综合数据库（GEO）的PC患者的基因谱作为验证群组。共148个差异表达的OS相关基因在PC中被用来构建蛋白质-蛋白质相互作用网络。单变量考克斯回归分析，最小绝对收缩，选择算子分析揭示了7个枢纽癌相关的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，其诊断准确性在两个队列中得到验证，可靠地预测了PC和癌症进展患者的总生存期。进一步的分析揭示了七个枢纽基因表达水平与患者结局之间的显著相关性，这在蛋白质水平上使用人类蛋白质图谱数据库进行了验证。基于这七个枢纽基因表达的列线图在PC中表现出预后价值。我们的研究为PC发病机制的研究提供了新的见解，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记。
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. 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. 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. Our study provides novel insights into PC pathogenesis and provides new genetic markers for prognosis prediction and clinical treatment personalization for PC patients.
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影响因子：
4.7
作者：
Döppler H;Storz P
通讯作者：
Storz P
影响因子：
3.6
作者：
Bournet, B.;Pointreau, A.;Buscail, L.
通讯作者：
Buscail, L.
影响因子：
3.7
作者：
Kamarajah, Sivesh K.;Burns, William R.;Nathan, Hari
通讯作者：
Nathan, Hari
DOI：
10.1126/science.1262110
发表时间：
2015-05-08
期刊：
Science (New York, N.Y.)
影响因子：
--
作者：
GTEx Consortium
通讯作者：
GTEx Consortium
影响因子：
4.6
作者：
Liu P;Weng Y;Sui Z;Wu Y;Meng X;Wu M;Jin H;Tan X;Zhang L;Zhang Y
通讯作者：
Zhang Y