■本研究旨在建立与铜稳态相关的基因签名,以预测上皮性卵巢癌的预后,并研究其潜在机制。
■我们主要通过LASSO回归分析构建了铜稳态相关基因签名。然后使用多种方法评估模型的独立预测能力并探讨其机制。
■成功建立了15-铜稳态相关基因(15-CHRG)签名。利用0.35的最佳截止值,我们将训练数据集分为高风险和低风险亚组。Kaplan-Meier分析显示,高危亚组的生存时间明显短于低危组(P<0.05)。此外,15-CHRG签名的曲线下面积(AUC)在1年时达到0.822,0.762在3年,在训练集中的5年和0.696。COX回归分析证实15-CHRG特征既准确又独立。基因组富集(GSEA),京都百科全书的基因和基因组(KEGG)和基因本体论(GO)分析表明,p53通路,蛋白质合成,高风险组和低风险组之间的水解酶和转运相关途径。在肿瘤免疫细胞(TIC)分析中,静息肥大细胞表达增加与风险评分呈正相关。
■因此,15-CHRG特征显示作为一种准确预测上皮性卵巢癌患者临床结局和治疗反应的方法的巨大潜力.
UNASSIGNED: This research aims to establish a copper homeostasis-related gene signature for predicting the prognosis of epithelial ovarian cancer and to investigate its underlying mechanisms.
UNASSIGNED: We mainly constructed the copper homeostasis-related gene signature by LASSO regression analysis. Then multiple methods were used to evaluate the independent predictive ability of the model and explored the mechanisms.
UNASSIGNED: The 15-copper homeostasis-related gene (15-CHRG) signature was successfully established. Utilizing an optimal cut-off value of 0.35, we divided the training dataset into high-risk and low-risk subgroups. Kaplan-Meier analysis revealed that survival times for the high-risk subgroup were significantly shorter than those in the low-risk group (P < .05). Additionally, the Area Under the Curve (AUC) of the 15-CHRG signature achieved 0.822 at 1 year, 0.762 at 3 years, and 0.696 at 5 years in the training set. COX regression analysis confirmed the 15-CHRG signature as both accurate and independent. Gene set enrichment (GSEA), Kyoto Encyclopedia of Gene and Genome (KEGG) and Gene Ontology (GO) analysis showed that there were significant differences in apoptosis, p53 pathway, protein synthesis, hydrolase and transport-related pathways between high-risk group and low-risk group. In tumor immune cell (TIC) analysis, the increased expression of resting mast cells was positively correlated with the risk score.
UNASSIGNED: Consequently, the 15-CHRG signature shows significant potential as a method for accurately predicting clinical outcomes and treatment responses in patients with epithelial ovarian cancer.