使用基因组和转录组分析来确定氧化应激途径在肾透明细胞癌中的作用及其潜在的治疗意义,Oxidative Medicine and Cellular Longevity

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使用基因组和转录组分析来确定氧化应激途径在肾透明细胞癌中的作用及其潜在的治疗意义
Oxidative Medicine and Cellular Longevity Pub Date : 2021-10-20 , DOI: 10.1155/2021/5561124
Xiangyu Che ₁ , Xiaochen Qi ₁ , Yingkun Xu ₂ , Qifei Wang ₁ , Guangzhen Wu ₁

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氧化应激（Oxidative stress，OS）是指当体内氧化和抗氧化剂之间的平衡被破坏，导致自由基产生过多时的内源性和/或外源性刺激。过量的自由基对机体产生一系列负面影响，可导致生物分子氧化和损伤，进而导致细胞死亡和组织损伤，这些与许多病理过程有关。OS相关通路一直是医学研究的重点。正在进行几项研究，以通过探索 OS 途径来制定治疗癌症的策略。因此，本研究旨在通过生物信息学分析确定 OS 通路与肾肾透明细胞癌 (KIRC) 之间的相关性，证明常见抗癌药物对OS通路的影响，以及基于OS通路与KIRC相关性最强的几个基因构建KIRC患者的预后模型。我们首先通过TCGA数据库收集和分析相关患者的基因表达和临床信息。然后，我们根据通过聚类分析获得的基因表达水平将样本分为三个聚类。使用这三个集群，我们进行了 GDSC 药物分析和 GSEA 分析，并检查了 OS 通路、组蛋白修饰和免疫细胞浸润之间的相关性。我们还分析了抗 PD-1 和抗 CTLA-4 对 OS 通路的反应。此后，我们使用 LASSO 回归来选择最合适的九个基因，结合临床病理特点建立KIRC患者预后模型，验证模型的科学精密度。最后，计算肿瘤突变负荷以验证患者是否会从免疫治疗中受益。本研究结果可为KIRC患者治疗策略的制定提供参考。

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Using Genomic and Transcriptome Analyses to Identify the Role of the Oxidative Stress Pathway in Renal Clear Cell Carcinoma and Its Potential Therapeutic Significance

Oxidative stress (OS) refers to endogenous and/or exogenous stimulation when the balance between oxidation and antioxidants in the body is disrupted, resulting in excessive production of free radicals. Excessive free radicals exert a series of negative effects on the body, which can result in the oxidation of and infliction of damage on biological molecules and further cause cell death and tissue damage, which are related to many pathological processes. Pathways related to OS have always been the focus of medical research. Several studies are being conducted to develop strategies to treat cancer by exploring the OS pathways. Therefore, this study is aimed at determining the correlation between the OS pathway and kidney renal clear cell carcinoma (KIRC) through bioinformatics analysis, at proving the effect of common anticancer drugs on the OS pathway, and at constructing a prognosis model of patients with KIRC based on several genes with the strongest correlation between the OS pathway and KIRC. We first collected and analyzed gene expression and clinical information of related patients through TCGA database. Then, we divided the samples into three clusters according to their gene expression levels obtained through cluster analysis. Using these three clusters, we performed GDSC drug analysis and GSEA analysis and examined the correlation among the OS pathway, histone modification, and immune cell infiltration. We also analyzed the response of anti-PD-1 and anti-CTLA-4 to the OS pathway. Thereafter, we used LASSO regression to select the most suitable nine genes, combined with the clinicopathological characteristics to establish the prognosis model of patients with KIRC, and verified the scientific precision of the model. Finally, tumor mutational burden was calculated to verify whether patients would benefit from immunotherapy. The results of this study may provide a reference for the establishment of treatment strategies for patients with KIRC.

更新日期：2021-10-20

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