基于生物信息学分析SGOL1在肺腺癌中的表达及预后价值

Analysis of expression and prognostic value of SGOL1 in lung adenocarcinoma based on bioinformatics

目的通过生物信息学方法分析Shugoshin-1(SGOL1)在肺腺癌中的表达及预后价值。方法从癌症基因组图谱数据库中下载肺腺癌组织和正常组织的表达谱数据和临床资料,并对SGOL1进行表达差异分析和临床相关性分析。使用R包“pROC”绘制受试者操作特征曲线(receiver operator characteristic curve,ROC曲线)评估SGOL1表达对肺腺癌患者临床诊断预测的准确性;利用R包“survival”“survminer”和单因素及多因素Cox回归分析评估SGOL1表达对肺腺癌患者预后的影响;通过检索肿瘤免疫单细胞中心和TIMER2.0数据库,分析肺腺癌中SGOL1的表达分布及与免疫细胞浸润的关系;利用LinkedOmics数据库对SGOL1及其共表达进行功能富集分析;利用交互作用基因/蛋白质检索工具构建SGOL1的蛋白质–蛋白质相互作用网络。结果与正常组织比较,肿瘤组织的SGOL1表达量显著上调(P<0.001);与癌旁组织比较,肿瘤组织的SGOL1表达量显著上调(P<0.001)。在肺腺癌的不同临床病理分期中,与Ⅰ期比较,Ⅱ期、Ⅲ期、Ⅳ期的SGOL1显著高表达(P<0.05)。ROC曲线显示,SGOL1对肺腺癌患者具有良好的诊断效能,曲线下面积为0.959(95%CI:0.942~0.975)。SGOL1高表达组患者的总生存期、疾病特异生存期、无病生存期和无瘤间期均较SGOL1低表达组显著缩短(P<0.05)。单因素及多因素Cox回归分析结果表明,临床分期(HR=1.629,P<0.001)和SGOL1表达水平(HR=1.447,P=0.002)与肺腺癌患者的预后较差相关,可作为肺腺癌患者预后的独立危险因素。SGOL1表达水平与B细胞、CD4^(+)T细胞和树突状细胞的浸润水平呈显著负相关(P<0.05),与巨噬细胞、CD8^(+)T细胞和中性粒细胞的浸润水平呈显著正相关(P<0.05)。富集分析显示,SGOL1可能在有丝分裂、细胞周期、p53信号通路和氨基酸代谢等途径中发挥作用。蛋白质-蛋白质相互作用网络分析提示SGOL1与CBX1、PPP2CA、PPP2R5C、CDCA8、ESPL1、PPP2R1A、BUB1、PPP2R5A、SGO2、CDC20等多个分子关系密切。结论SGOL1在肺腺癌组织中高表达,且与肺腺癌患者的预后较差相关。SGOL1可作为预测肺腺癌患者预后的生物标志物之一。

Objective To study expression and prognostic value of Shugoshin-1(SGOL1)in lung adenocarcinoma by bioinformatics method.Methods Expression profile data and clinical data of lung adenocarcinoma and normal tissues were downloaded from The Cancer Genome Atlas database,and expression difference and clinical correlation analysis of SGOL1 were performed.R package“pROC”was used to plot receiver operator characteristic(ROC)curves to evaluate accuracy of SGOL1 expression in predicting clinical diagnosis in lung adenocarcinoma patients.Effects of SGOL1 expression on prognosis of lung adenocarcinoma patients were evaluated by R package“survival”,“survminer”and univariate and multivariate Cox regression analysis.By searching Tumor Immune Single-Cell Hub and TIMER2.0 databases,expression distribution of SGOL1 in lung adenocarcinoma and its relationship with immune cell infiltration were analyzed,functional enrichment analysis of SGOL1 and its co-expression was performed by using LinkedOmics database.Search tool for the retrieval of interaction gene/proteins was used to construct a protein-protein interaction network for SGOL1.Results Compared with normal tissues,expression level of SGOL1 in tumor tissues was significantly upregulated(P<0.001).Compared with paracancer tissues,expression level of SGOL1 in tumor tissues was significantly upregulated(P<0.001).In different clinical and pathological stages of lung adenocarcinoma,compared with stageⅠ,expression levels of SGOL1 in stagesⅡ,ⅢandⅣwere significantly higher(P<0.05).ROC curve showed that SGOL1 had a good diagnostic efficiency in lung adenocarcinom patients,with area under the curve of 0.959(95%CI:0.942-0.975).Overall survival,disease specific survival,disease-free survival and progression free interval of high expression group of SGOL1 were significantly shorter than those of low expression group of SGOL1(P<0.05).Univariate and multivariate Cox regression analysis showed that clinical stage(HR=1.629,P<0.001)and SGOL1 expression level(HR=1.447,P=0.002)were associated with poor prognosis in lung adenocarcinoma patients.It can be used as an independent risk factor for the prognosis of lung adenocarcinoma patients.Expression level of SGOL1 was negatively correlated with infiltration level of B cells,CD4^(+)T cells and dendritic cells(P<0.05).Expression level of SGOL1 was positively correlated with infiltration level of macrophages,CD8^(+)T cells and neutrophils(P<0.05).Enrichment analysis showed that SGOL1 may play role in mitosis,cell cycle,p53 signaling pathway and amino acid metabolism pathways.Analysis of protein-protein interaction network suggests that SGOL1 was closely related to multiple molecules such as CBX1,PPP2CA,PPP2R5C,CDCA8,ESPL1,PPP2R1A,BUB1,PPP2R5A,SGO2,CDC20,etc.Conclusion SGOL1 is highly expressed in lung adenocarcinoma tissues,and it is associated with poorer prognosis in lung adenocarcinoma patients.SGOL1 can be used as one of prognostic biomarkers for lung adenocarcinoma patients.