摘要
目的 通过生物信息学分析,挖掘SCGB2A1在子宫内膜癌发生发展中的作用,为其诊断、治疗及临床预后提供理论基础。方法 利用癌症基因组图谱(TCGA)数据库,基因组织表达(GTEX)数据库和人类蛋白质图谱(HPA)数据库探讨SCGB2A1在子宫内膜癌中的差异性表达。此外,利用GEPIA分析SCGB2A1差异性表达与子宫内膜癌预后之间的关系。同时,利用UALCAN分析子宫内膜癌中SCGB2A1 mRNA表达在不同临床指标状态下的改变情况,以及多种经典信号通路改变时,SCGB2A1蛋白的差异性表达。最后,通过GSEA分析SCGB2A1相关的显著富集信号通路。结果 子宫内膜癌中SCGB2A1表达升高,但是肿瘤发生后,低表达的SCGB2A1与较差预后生存相关。子宫内膜癌中SCGB2A1的表达差异与mTOR信号改变和细胞周期调控密切相关。甲基化修饰可能参与调控了子宫内膜癌中的SCGB2A1表达。结论 SCGB2A1可以作为子宫内膜癌诊断治疗及临床预后的重要潜在生物标志物。
Objective To explore the role of SCGB2A1 in uterine corpus endometrial cancer development and progression through bioinformatics analysis, and to provide theoretical basis for its diagnosis, treatment and clinical prognosis.Methods The Cancer Genome Atlas(TCGA) database, GTEX database and the Human Protein Atlas(HPA) database were used to investigate the differential expression of SCGB2A1 in UCEC. In addition, the survival curve of UCEC with differential SCGB2A1 expression was drew by GEPIA. Meanwhile, UALCAN was used to analyze the changes of SCGB2A1 mRNA expression in UCEC under different clinicopathological characteristics, as well as the differential protein expression of SCGB2A1 when a variety of classical signal pathways changed. Finally, GSEA was used to analyze the SCGB2A1-related significantly enriched signaling pathways. Results SCGB2A1 expression was elevated in UCEC, but low expression of SCGB2A1 was associated with poor survival when tumor occur. SCGB2A1 expression in UCEC is closely related to mTOR signaling pathway and the regulation of cell cycle. Methylation may be involved in regulating SCGB2A1 expression in UCEC.Conclusion SCGB2A1 can be used as an important potential biomarker for the diagnosis, treatment and clinical prognosis of UCEC.
作者
胡莹莹
单伟伟
HU Yingying;SHAN Weiwei(Department of Gynecology,Obstetrics and Gynecology Hospital of Fudan University,Shanghai 200090,China)
出处
《中国优生与遗传杂志》
2022年第9期1501-1507,共7页
Chinese Journal of Birth Health & Heredity
基金
上海市青年科技英才扬帆计划(19YF1404200)。
关键词
分泌珠蛋白家族2A成员1
子宫内膜癌
生物信息学分析
secretoglobin family 2A member 1
uterine corpus endometrial cancer
bioinformatics analysis