摘要
目的利用癌症基因组图谱(TCGA)数据库中的数据分析SEC61G在浸润性乳腺癌中的表达情况及其与临床预后的关系。方法从TCGA数据库中收集1222个浸润性乳腺癌患者的RNAseq数据,用Wilcoxon秩和检验分析SEC61G在正常组织和肿瘤组织中表达的差异,采用logistic回归分析SEC61G的表达与临床病理特征的关系,使用Kaplan-Meier方法和Cox回归分析评估SEC61G在预后中的作用。结果浸润性乳腺癌组织中SEC61G的表达明显高于正常乳腺组织(P<0.001)。T分期(P=0.028)、N分期(P=0.009)、病理分期(P=0.003)、ER状态(P<0.001)、PR状态(P<0.001)、HER2状态(P=0.025)、组织学类型(P<0.001)与SEC61G表达显著相关。单因素Cox回归分析显示SEC61G高表达与DSS有相关性(P<0.001,HR=0.426,95%CI=0.272~0.668)。多因素Cox分析显示SEC61G高表达是疾病特异生存率(DSS)的独立危险因素(P=0.009,HR=0.479,95%CI=0.276~0.831)。SEC61G的表达与浸润性乳腺癌的免疫浸润程度有关(P<0.05)。各组的K-M曲线显示肿瘤组织中SEC61G表达越高浸润性乳腺癌患者的预后越差(P<0.05)。结论SEC61G高表达与浸润性乳腺癌预后不良有关,可以作为预测浸润性乳腺癌患者生存有效的生物标志物。
Objective To analyze the expression of SEC61 G in invasive breast cancer from tumor Genome Map(TCGA)database and its relationship with clinical prognosis.Methods The RNAseq data of 1222 patients with invasive breast cancer were collected from TCGA database.Wilcoxon rank sum test was used to analyze the difference of SEC61 G expression between normal and tumor tissues.Logistic regression was used to analyze the relationship between SEC61 G expression and clinicopathological features.Kaplan-Meier method and Cox regression analysis were used to evaluate the role of SEC61 G in prognosis.Results The expression of SEC61 G in invasive breast cancer was significantly higher than that in normal breast tissue(P<0.001).T stage(P=0.028),N stage(P=0.009),pathological stage(P=0.003),ER status(P<0.001),PR status(P<0.001),HER2 status(P=0.025)and histological type(P<0.001)were significantly correlated with SEC61 G expression.Univariate Cox regression analysis showed that the high expression of SEC61 G was associated with DSS(P<0.001,HR=0.426,95%CI:0.272-0.668).Multivariate Cox analysis showed that high expression of SEC61 G was an independent risk factor for DSS(P=0.009,HR=0.479,95%CI:0.276-0.831).The K-M curve of each group showed that the higher the expression of SEC61 G in tumor tissue,the worse the prognosis of invasive breast cancer patients(P<0.05).Conclusion The high expression of SEC61 G is related to the poor prognosis of invasive breast cancer and can be used as an effective biomarker to predict the survival of patients with invasive breast cancer.
作者
王艳
刘先富
许波
张波
WANG Yan;LIU Xian-fu;XU Bo;ZHANG Bo(Department of Oncology,the First Affiliated Hospital of Bengbu Medical College,Bengbu,Anhui 233004,China)
出处
《中华全科医学》
2022年第7期1235-1239,共5页
Chinese Journal of General Practice
基金
安徽省教育厅重点课题(KJ2019A0341)
蚌埠医学院自然科学重点项目(BYKY2019127ZD)。