BACKGROUND Oxidative stress serves a crucial role in tumor development. However, the relationship between ovarian cancer and oxidative stress remains unknown. We aimed to create an oxidative stress-related prognostic signature to enhance the prognosis prediction of CC patients using bioinformatics. METHODS The genes differentially expressed and associated with oxidative stress were extracted with the help of "limma" packages. The model for prognosis was created using Multivariate Cox regression analysis to determine the risk related to the genes related to oxidative stress. Patients were categorized as low-risk or high-risk based on the median score. The receiver operation characteristic (ROC) and survival curves were used to evaluate the predictive effect of the prognostic signature. We utilized quantitative real-time PCR to assess the expression levels of key genes associated with oxidative stress in ovarian cancer cell lines (SKOV3, OVCAR3, and HeyA8) and normal ovarian epithelial cells (HOSEpiC). RESULTS A signature comprising seven genes associated with oxidative stress was developed to prognosticate patients with ovarian cancer. Overall survival (OS) of the patient having CC was determined using Kaplan-Meier analysis. It was found that patient with a higher risk score had lower OS than the low-risk score. The signature of genes associated with oxidative stress was found to be independently prognostic for 1, 2, and 3 years. Further research found that the expression levels of nine hub genes had a strong association with patient outcomes. Our analysis revealed a higher expression of CX3CR1 in ovarian cancer cell lines compared with normal cells. CONCLUSIONS To deploy a novel oxidative stress-related prognostic signature as an independent biomarker in cervical cancer, we developed and validated it.

中文翻译：

---

用于卵巢癌特定基因筛查的氧化应激相关表型的机器学习分析。


背景 氧化应激在肿瘤发展中起着至关重要的作用。然而，卵巢癌与氧化应激之间的关系仍然未知。我们旨在创建一个与氧化应激相关的预后特征，以使用生物信息学增强 CC 患者的预后预测。方法 在 “limma” 包的帮助下提取差异表达和与氧化应激相关的基因。使用多变量 Cox 回归分析创建预后模型，以确定与氧化应激相关基因相关的风险。根据中位评分将患者分为低风险或高风险。采用受试者操作特征 （ROC） 和生存曲线评价预后特征的预测效果。我们利用定量实时 PCR 来评估卵巢癌细胞系 （SKOV3 、 OVCAR3 和 HeyA8） 和正常卵巢上皮细胞 （HOSEpiC） 中与氧化应激相关的关键基因的表达水平。结果 开发了一个包含 7 个与氧化应激相关的基因的特征，用于预测卵巢癌患者。使用 Kaplan-Meier 分析确定 CC 患者的总生存期 （OS）。结果发现，风险评分较高的患者的 OS 低于低风险评分的患者。发现与氧化应激相关的基因特征在 1 、 2 和 3 年内独立预后。进一步研究发现，9 个枢纽基因的表达水平与患者预后密切相关。我们的分析显示，与正常细胞相比，CX3CR1 在卵巢癌细胞系中的表达更高。 结论 为了将一种新的氧化应激相关预后特征作为宫颈癌的独立生物标志物，我们开发并验证了它。