Oxidative Stress-Related KEAP1 and NRF2 Genes Contributed to the Risk of Epithelial Ovarian Cancer.

IF 2.1 4区 生物学 Q4 BIOCHEMISTRY & MOLECULAR BIOLOGY
Xiaoqian Tong, Xiaoli Zhu, Xila Wang, Yanlin Xu, Pei Huang, Leiqing Zhou, Yanxiang Ji, Lifang Wu
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Abstract

The NRF2/KEAP1 signaling pathway, crucial for cellular defense against oxidative stress, may influence epithelial ovarian cancer (EOC) risk. This study investigates the association between KEAP1 gene polymorphisms and EOC risk in Han Chinese individuals, while exploring correlations between these genetic variants and serum levels of KEAP1 and NRF2 proteins. We conducted a case-control study involving 1962 EOC patients and 2057 controls, genotyping ten tag single-nucleotide polymorphisms (SNPs) in KEAP1. Serum KEAP1 and NRF2 levels were measured using ELISA. Genetic association analyses and ANOVA were employed to assess relationships between SNPs, EOC risk, and serum protein levels. Notably, only SNP rs3177696 in KEAP1 showed a significant association with EOC risk. The G allele of rs3177696 conferred a protective effect against EOC (OR [95% CI] = 0.58 [0.47-0.72], P = 2.91 × 10-7). Furthermore, rs3177696 genotypes were significantly associated with serum levels of both KEAP1 and NRF2, as well as their ratio. EOC patients carrying GG, AG, and AA genotypes exhibited mean serum KEAP1 levels of 2.46, 2.16, and 2.04 (P = 2.43 × 10-9), respectively. Conversely, serum NRF2 levels decreased with increasing G allele copies (GG: 4.58, AG: 4.95, AA: 5.02; P = 0.0002). This study provides compelling evidence linking EOC risk to the oxidative stress-related gene KEAP1, with the G allele of rs3177696 demonstrating a protective effect. These findings suggest a potential role for the NRF2/KEAP1 pathway in EOC pathogenesis and highlight promising avenues for future research in EOC prevention and treatment strategies.

氧化应激相关的KEAP1和NRF2基因与上皮性卵巢癌的风险有关
NRF2/KEAP1信号通路对细胞防御氧化应激至关重要,可能影响上皮性卵巢癌(EOC)的风险。本研究探讨了中国汉族人群KEAP1基因多态性与EOC风险的关系,同时探讨了这些基因变异与血清中KEAP1和NRF2蛋白水平的相关性。我们进行了一项病例对照研究,包括1962例EOC患者和2057例对照者,对KEAP1的十标签单核苷酸多态性(snp)进行基因分型。ELISA法检测血清KEAP1和NRF2水平。采用遗传关联分析和方差分析来评估snp、EOC风险和血清蛋白水平之间的关系。值得注意的是,KEAP1中只有rs3177696 SNP与EOC风险显著相关。rs3177696的G等位基因对EOC具有保护作用(OR [95% CI] = 0.58 [0.47-0.72], P = 2.91 × 10-7)。此外,rs3177696基因型与血清KEAP1和NRF2水平及其比值显著相关。GG、AG和AA基因型EOC患者的平均血清KEAP1水平分别为2.46、2.16和2.04 (P = 2.43 × 10-9)。相反,血清NRF2水平随着G等位基因拷贝数的增加而降低(GG: 4.58, AG: 4.95, AA: 5.02;p = 0.0002)。本研究提供了令人信服的证据,将EOC风险与氧化应激相关基因KEAP1联系起来,其中rs3177696的G等位基因显示出保护作用。这些发现提示了NRF2/KEAP1通路在EOC发病机制中的潜在作用,并为未来EOC预防和治疗策略的研究提供了有希望的途径。
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来源期刊
Biochemical Genetics
Biochemical Genetics 生物-生化与分子生物学
CiteScore
3.90
自引率
0.00%
发文量
133
审稿时长
4.8 months
期刊介绍: Biochemical Genetics welcomes original manuscripts that address and test clear scientific hypotheses, are directed to a broad scientific audience, and clearly contribute to the advancement of the field through the use of sound sampling or experimental design, reliable analytical methodologies and robust statistical analyses. Although studies focusing on particular regions and target organisms are welcome, it is not the journal’s goal to publish essentially descriptive studies that provide results with narrow applicability, or are based on very small samples or pseudoreplication. Rather, Biochemical Genetics welcomes review articles that go beyond summarizing previous publications and create added value through the systematic analysis and critique of the current state of knowledge or by conducting meta-analyses. Methodological articles are also within the scope of Biological Genetics, particularly when new laboratory techniques or computational approaches are fully described and thoroughly compared with the existing benchmark methods. Biochemical Genetics welcomes articles on the following topics: Genomics; Proteomics; Population genetics; Phylogenetics; Metagenomics; Microbial genetics; Genetics and evolution of wild and cultivated plants; Animal genetics and evolution; Human genetics and evolution; Genetic disorders; Genetic markers of diseases; Gene technology and therapy; Experimental and analytical methods; Statistical and computational methods.
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