陈谦,仇小强.基于大数据的肝癌血管侵袭标志物分析[J].Chinese journal of Epidemiology,2017,38(4):522-527 |
基于大数据的肝癌血管侵袭标志物分析 |
Bioinformatics on vascular invasion markers in hepatocellular carcinoma via Big-Data analysis |
Received:November 02, 2016 |
DOI:10.3760/cma.j.issn.0254-6450.2017.04.022 |
KeyWord: 肝癌 血管侵袭 标志物 microRNA 大数据 |
English Key Word: Hepatocellular carcinoma Vascular invasion Biomarker MicroRNA Big Data |
FundProject:国家自然科学基金(81241100) |
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Abstract: |
目的 通过对GEO(Gene Expression Omnibus)与TCGA(The Cancer Genome Atlas)数据库分析,挖掘肝癌血管侵袭相关的microRNA,并分析其预后和可能机制。方法 利用GEO数据库获得肝癌血管侵袭microRNA芯片数据(GSE67140),对5种侵袭能力不同的细胞系(SNU423、SNU449、HepG2、Hep3B、SNU398)表达谱进行差异分析,并在81份血管侵袭阳性组织样本与91份血管侵袭阴性组织样本中验证差异分析结果。结合TCGA数据库中362例肝癌病例数据分析其预后,并对microRNA所调控的基因进行GO与KEGG分析。结果 hsa-mir-1180、hsa-mir-149、hsa-mir-744、hsa-mir-940在侵袭能力强的肝癌细胞和有血管侵袭的肝癌组织中表达上调(logFC> 1,P< 0.05)。生存分析显示,hsa-mir-1180(HR=1.623,95%CI:1.114~2.365,P=0.012)、hsa-mir-149(HR=2.400,95%CI:1.639~3.514,P< 0.001)、hsa-mir-744(HR=1.679,95%CI:1.161~2.427,P=0.006)、hsa-mir-940(HR=1.704,95%CI:1.188~2.443,P=0.004)是肝癌病例预后独立危险因素,高表达与患者生存期缩短显著相关(P< 0.05)。GO与KEGG分析其机制可能与免疫反应、细胞黏附、紧密连接等信号通路有关。结论 通过对TCGA与GEO数据库的挖掘,初步发现hsa-mir-1180、hsa-mir-149、hsa-mir-744、hsa-mir-940对肝癌的预后有影响,可作为肝癌预后的生物标志物。 |
English Abstract: |
Objective To investigate the biomarkers in hepatocellular carcinoma and their prognostic value via GEO (Gene Expression Omnibus) and TCGA (The Cancer Genome Atlas) database. Methods Datasets of hepatocellular carcinoma were downloaded from GEO (GSE67140) and TCGA. MicroRNA in SNU423, SNU449, HepG2, Hep3B, SNU398 cell lines which had low or high invasion capabilities were investigated and verified, in 81 patients with and 91 without vascular invasion hepatocellular carcinoma. The prognostic value of these microRNAs were studied via TCGA database,obtained from 362 patients with hepatocellular carcinoma, through Kaplan-Meier and Multivariate Cox proportional hazard analysis. Target genes were analyzed by GO and KEGG. Results Expressions of hsa-mir-1180, hsa-mir-149, hsa-mir-744 and hsa-mir-940 were all up regulated in high invasion capable cell lines (SNU423, SNU449) and vascular invasion patients with hepatocellular carcinoma (logFC> 1, P< 0.05). Results from the Survival analysis showed that hsa-mir-1180 (HR=1.623, 95%CI:1.114-2.365, P=0.012), hsa-mir-149 (HR=2.400, 95%CI:1.639-3.514) and hsa-mir-940 (HR=1.704, 95%CI:1.188-2.443, P=0.004) were independent risk factors on the prognosis of patients with hepatocellular carcinoma (P< 0.05). The mechanism might be related to factors as immune response, focal adhesion and adherence junction signaling pathways. Conclusion With TCGA and GEO data mining, we found that hsa-mir-1180, hsa-mir-149, hsa-mir-744 and hsa-mir-940 were all highly related to the prognosis of hepatocellular carcinoma, that enabled it to be used to further study the biomarkers related to the prognosis of hepatocellular carcinoma. |
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