山东大学学报 (医学版) ›› 2019, Vol. 57 ›› Issue (10): 80-85.doi: 10.6040/j.issn.1671-7554.0.2019.104
• 临床医学 • 上一篇
朱爱国,马振敕,王健
ZHU Aiguo, MA Zhenchi, WANG Jian
摘要: 目的 通过基因表达谱汇编(GEO)数据库和癌症基因组图谱(TCGA)数据库筛选并建立与上皮源性卵巢癌(EOC)患者预后有关联的多基因模型,并验证其预后价值。 方法 从GEO数据库中下载EOC有关芯片数据(GSE14407),筛选出在EOC组织和正常卵巢上皮组织中差异表达的基因(DEGs),采用单因素和多因素Cox回归模型筛选出与预后有关联的DEGs,建立多基因预后模型和预后指数(PI)公式。对TCGA数据库中EOC患者的mRNA数据及临床信息进行整理,通过PI公式对患者进行评分,并根据评分将患者分为低风险组和高风险组。通过Cox回归风险模型分析临床病理参数(年龄、发病位置、组织分级、肿瘤残余及FIGO分期)和预后指数参数与EOC预后的关系。根据年龄、发病位置、组织分级、肿瘤残余及FIGO分期进行分组,采用Kaplan-Meier(K-M)生存分析验证多基因模型对卵巢癌的预后价值。 结果 共筛选出47个在EOC组织和正常卵巢组织中的DEGs,其中有37个表达下调的DEGs和10个表达上调的DEGs。将上述DEGs进行单因素和多因素Cox回归分析,共筛选出4个DEGs,分别是PACSIN3、KCNT1、LAMP3及KIR3DX1。PI公式:(-0.169×PACSIN3的表达量+0.078×KCNT1的表达量-0.246×LAMP3的表达量-0.147×KIR3DX1的表达量)。Cox回归模型分析证实,年龄、肿瘤残余和预后模型是卵巢癌患者的独立预后因素(P<0.01)。通过K-M生存分析证实,在TCGA数据库的312例EOC患者中,预后评分低风险的患者总体生存期(OS)较高风险患者延长,差异有统计学意义(P<0.05)。在不同的年龄、临床分期、发病位置(单侧和双侧)、肿瘤残余<10 mm的EOC患者亚组中,预后评分低风险的患者OS较高风险患者延长,差异有统计学意义(P<0.05)。 结论 四基因预后模型是EOC患者的独立预后因素,并在总体和根据各临床病理特征分组的EOC患者亚组中得到了验证。
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