AIM:To develop lymph node metastasis(LNM)-associated biomarkers for colorectal cancer(CRC) using quantitative proteome analysis.METHODS:Differences in protein expression between primary CRC with LNM(LNM CRC) and witho...AIM:To develop lymph node metastasis(LNM)-associated biomarkers for colorectal cancer(CRC) using quantitative proteome analysis.METHODS:Differences in protein expression between primary CRC with LNM(LNM CRC) and without LNM(non-LNM CRC) were assessed using methyl esterification stable isotope labeling coupled with 2D liquid chromatography followed by tandem mass spectrometry(2D-LC-MS/MS).The relationship to clinicopathological parameters and prognosis of candidate biomarkers was examined using an independent sample set.RESULTS:Forty-three proteins were found to be differentially expressed by at least 2.5-fold in two types of CRC.S100A4 was significantly upregulated in LNM CRC compared with non-LNM CRC,which was confirmed by Western blotting,immunohistochemistry and real-time quantitative polymerase chain reaction.Further immunohistochemistry on another 112 CRC cases showed that overexpression of S100A4 frequently existed in LNM CRC compared with non-LNM CRC(P < 0.001).Overexpression of S100A4 was significantly associated with LNM(P < 0.001),advanced TNM stage(P < 0.001),increased 5-year recurrence rate(P < 0.001) and decreased 5-year overall survival rate(P < 0.001).Univariate and multivariate analyses indicated that S100A4 expression was an independent prognostic factor for recurrence and survival of CRC patients(P < 0.05).CONCLUSION:S100A4 might serve as a powerful biomarker for LNM and a prognostic factor in CRC.展开更多
文摘目的采用生物信息学方法筛选胶质母细胞瘤(glioblastoma,GBM)中的关键基因、信号通路和预后生物标志物。方法从高通量基因表达数据库(gene expression omnibus,GEO)下载GBM的5个数据集中的基因芯片数据。首先,对原始数据进行预处理,并用R语言中的limma包分析得到参与GBM发生发展过程中的差异表达基因(differentiallyexpressed genes,DEGs)。为注释基因的功能,对DEGs进行基因本体论(gene ontology,GO)分析、京都基因与基因组百科全书(Kyoto encyclopedia of genes and genomes,KEGG)分析,对所有基因的表达矩阵进行基因集富集分析(gene set enrich-ment analysis,GSEA)。通过STRING构建DEGs的蛋白互作网络(protein-protein interaction,PPI)以注释蛋白质之间的相互作用,分析得到互作强度最高的Hub基因,下载癌症基因图谱数据库(The Cancer Genome Atlas,TCGA)中GBM的基因芯片数据和临床预后资料,用COX回归模型评价DEGs的预后价值,并对风险比值(hazard ratio,HR)最高的基因进行总生存(ovarall survival,OS)分析。结果对基因表达矩阵分析得到797个DEGs。GO分析结果显示,DEGs参与了神经递质转运、突触后膜电位的调节和膜电位的调节等生物过程;KEGG分析结果主要富集于细胞周期、ECM-受体、Fox O、HIF-1、P53和PI3K-Akt信号通路;GSEA分析显示NF-κB信号通路和P53信号通路在GBM机制中发挥着重要的作用。并通过PPI网络分析得到10个Hub基因。COX回归模型和OS分析结果表明,ANXA2(HR=1.53,P=0.011),DNAJA4(HR=1.45,P=0.030),P4HB(HR=1.66,P=0.002),VMP1(HR=1.64,P=0.005),MICAL2(HR=1.83,P<0.001),EMP3(HR=1.67,P=0.006),PAK1(HR=1.69,P=0.002)和TIMP1(HR=1.54,P=0.010)的高表达提示患者预后较差。结论通过生物信息学分析定义了参与GBM的重要生物过程,也得到了参与GBM发生发展的关键分子、信号通路和预后生物标志物。
基金Supported by Shanghai Momentous Program,Grant No.07dz19505Shanghai Rising-star Program from the Science and Technology Commission of Shanghai Municipality,No.10QA1401400,China
文摘AIM:To develop lymph node metastasis(LNM)-associated biomarkers for colorectal cancer(CRC) using quantitative proteome analysis.METHODS:Differences in protein expression between primary CRC with LNM(LNM CRC) and without LNM(non-LNM CRC) were assessed using methyl esterification stable isotope labeling coupled with 2D liquid chromatography followed by tandem mass spectrometry(2D-LC-MS/MS).The relationship to clinicopathological parameters and prognosis of candidate biomarkers was examined using an independent sample set.RESULTS:Forty-three proteins were found to be differentially expressed by at least 2.5-fold in two types of CRC.S100A4 was significantly upregulated in LNM CRC compared with non-LNM CRC,which was confirmed by Western blotting,immunohistochemistry and real-time quantitative polymerase chain reaction.Further immunohistochemistry on another 112 CRC cases showed that overexpression of S100A4 frequently existed in LNM CRC compared with non-LNM CRC(P < 0.001).Overexpression of S100A4 was significantly associated with LNM(P < 0.001),advanced TNM stage(P < 0.001),increased 5-year recurrence rate(P < 0.001) and decreased 5-year overall survival rate(P < 0.001).Univariate and multivariate analyses indicated that S100A4 expression was an independent prognostic factor for recurrence and survival of CRC patients(P < 0.05).CONCLUSION:S100A4 might serve as a powerful biomarker for LNM and a prognostic factor in CRC.
