基于生物信息学分析构建卵巢癌预后分子诊断模型及临床价值分析
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国家自然科学基金项目(82102717);江苏省南京市医学科技发展计划项目(YKK21161)


Clinical value of molecular diagnostic model for prognosis of ovarian cancer based on bioinformatics analysis and its clinical value analysis
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    目的 基于生物信息学分析,探讨肿瘤坏死因子受体相关因子7(TRAF7)在卵巢癌组织中的表达特征,构建分子诊断模型并分析对卵巢癌预后的临床诊断价值。方法 通过GEPIA在线网站分析TRAF7在泛癌组织中的表达特征;利用Kaplan-Meier Plotter在线网站分析TRAF7表达与卵巢癌患者生存情况。进一步,选取 2020 年 4 月—2021 年 6 月在南京医科大学附属妇产医院收治 92 例卵巢癌患者为研究对象,分为预后不良组42例和预后良好组50例。采用免疫组化检测卵巢癌组织中TRAF7表达并分析与临床病理特征的关系;Pearson相关分析评估TRAF7与人附睾蛋白4(HE4)、糖类抗原125(CA125)的相关性;受试者工作特征(ROC)曲线评估TRAF7、HE4、CA125指标诊断卵巢癌预后的价值。结果 GEPIA在线网站提示卵巢癌组织中TRAF7表达水平高于正常对照组织(P<0.05),且TRAF7表达水平增加,患者生存率降低(Logrank P为0.029)。免疫组化结果显示,TRAF7表达水平在卵巢癌组织高于癌旁正常组织,其在FIGO分期、病理类型、肿瘤分化程度及远处转移患者中比较,差异有统计学意义(均P<0.05)。卵巢癌组织中TRAF7表达与血清中HE4、CA125水平呈正相关(r=0.459 vs. r=0.358,均P<0.01),三者联合检测曲线下面积为0.873(95%CI:0.787~0.933),灵敏度为0.8810,特异度为0.7600。结论 TRAF7与HE4、CA125联合检测显著提高卵巢癌预后的诊断效率,为筛选卵巢癌不良预后高风险人群提供有价值的参考和评估依据

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    Objective Based on bioinformatics analysis, to explore the expression characteristics of tumor necrosis factor receptor related factor 7 (TRAF7) in ovarian cancer tissue, construct a molecular diagnostic model and analyze its clinical diagnostic value for prognosis in ovarian cancer. Methods The expression of TRAF7 was analyzed on the GEPIA online website in pan cancer tissues. Using the Kaplan-Meier Plotter online website to analyze the relationship between TRAF7 expression and survival of ovarian cancer patients. Furthermore, 92 ovarian cancer patients admitted to our hospital from April 2020 to June 2021 were selected as the study subjects, divided into a poor prognosis group (n=42) and a good prognosis group (n=50). Immunohistochemical detection of TRAF7 expression in ovarian cancer tissues and analysis of its relationship with clinical and pathological features of ovarian cancer. Pearson correlation analysis was used to evaluate the correlation between TRAF7 and human epididymal protein 4 (HE4) and carbohydrate antigen 125 (CA125). The value of evaluating TRAF7, HE4, and CA125 levels using receiver operating characteristic (ROC) curves in diagnosing poor prognosis of ovarian cancer. Results GEPIA online website showed that the expression level of TRAF7 in ovarian cancer tissue was higher than that of the normal control group (P<0.05). As the expression level of TRAF7 increases, the survival rate of patients decreases (Logrank P=0.029). The immunohistochemical results showed that the expression level of TRAF7 in ovarian cancer tissue was higher than that in normal tissue adjacent to cancer. The difference was statistically significant among patients with different FIGO stages, pathological types, tumor differentiation, and distant metastasis (all P<0.05). The expression of TRAF7 was positively correlated with the levels of HE4 and CA125 (r=0.459, r=0.358, both P<0.001). The area under the joint detection curve of the three was 0.873 (95% CI: 0.787~0.933), with a sensitivity of 0.8810 and a specificity of 0.7600. Conclusion The combined detection of TRAF7, HE4 and CA125 significantly improves the diagnostic efficiency of prognosis in ovarian cancer, providing valuable reference and evaluation basis for screening high-risk populations with poor prognosis in ovarian cancer

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桂凌,程峰,王平.基于生物信息学分析构建卵巢癌预后分子诊断模型及临床价值分析[J].西部医学,2025,37(09):1390-1395.

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  • 在线发布日期: 2025-09-19
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