Expression of TM6SF2 in hepatocellular carcinoma tissue and its bioinformatics functions
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摘要:
目的利用肿瘤数据库挖掘数据并分析TM6SF2在肝细胞癌(HCC)组织中的表达情况,同时探讨TM6SF2的生物学作用及功能。方法利用GEPIA数据库分析HCC组织中的TM6SF2基因mRNA水平的变化。利用OncoLnc做TM6SF2基因的表达水平与HCC患者生存期的相关性分析。利用cBioPortal数据库和LinkedOmics数据库分析TM6SF2在HCC组织中存在的表达相关基因。利用DAVID6. 8和STRING数据库对TM6SF2及其表达相关基因进行生物信息分析。用t检验验证HCC与癌旁组织基因mRNA表达差异。用Spearman相关系数分析基因表达的相关性。采用Kaplan-Meier生存分析计算生存率,采用广义log-rank检验估计生存率的差异。结果与正常肝组织相比,HCC组织中TM6SF2基因mRNA水平呈低表达(|log2FC|cut-off=0. 5,P <0. 01)。相比高表达的患者,TM6SF2低表达可明显降低HCC患者的总体生存时间(χ2=9. 897,P <0. 01)。数据分析显示,在HCC组织中与TM6SF2表达相关基因共49个。GO分析...
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关键词:
- 癌,肝细胞 /
- 跨膜蛋白6超家族成员2 /
- 数据库,遗传学 /
- 信息学
Abstract:Objective To investigate the expression of TM6 SF2 in hepatocellular carcinoma (HCC) tissue and its biological functions by data mining in tumor databases. Methods The GEPIA database was applied to measure the change in the mRNA expression level of TM6 SF2 in HCC tissue, and OncoLnc was used to analyze the association of TM6 SF2 expression with the survival time of HCC patients. The cBioPortal and LinkedOmics databases were used to analyze the genes associated with the expression of TM6 SF2 in HCC tissue, and the DAVID6. 8 and STRING databases were used to perform a bioinformatics analysis of TM6 SF2 and the genes associated with its expression. The t-test was used to investigate the difference in the mRNA expression of TM6 SF2 between HCC tissue and adjacent tissue. The Spearman correlation coefficient was used to analyze the correlation of gene expression. The Kaplan-Meier method was used to calculate survival percentage, and the log-rank test was used to analyze the difference in survival percentage. Results Compared with the normal liver tissue, the HCC tissue had low mRNA expression of TM6 SF2 (| log2 FC | cut-off = 0. 5, P < 0. 01) . Compared with those with high expression of TM6 SF2, the patients with low expression had a significant reduction in overall survival time (χ2= 9. 897, P < 0. 01) . Data analysis showed that a total of 49 genes were associated with the expression of TM6 SF2 in HCC tissue, and the gene ontology analysis showed that these genes were enriched in the biological processes and functions including fatty acid synthesis, fatty acid ligase activation, and thrombin regulation (P< 0. 05) . The Kyoto Encyclopedia of Genes and Genome pathway analysis showed that these genes were mainly involved in the signaling pathways of alanine metabolism, peroxisome proliferator-activated receptor signaling pathway, and bile secretion (P < 0. 05) . The protein-protein interaction network analysis showed that the genes of SERPINC1, NR1 I2, SERPINA10, and SLC10 A1 had marked or potential interaction with TM6 SF2 (P < 0. 01) . Conclusion Tumor data mining can quickly obtain the information on the expression of TM6 SF2 in HCC tissue and provide a bioinformatics basis for exploring the role of TM6 SF2 in the development and progression of HCC.
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