基于生物信息学分析黑素瘤中hTERT共表达基因及基因调控网络

白志艺 李青

[摘要] 目的 通過生物信息学的方法对hTERT基因网络及其相互作用的基因进行解密，研究hTERT共表达基因潜在的预后价值。方法 使用LinkedOmics数据库鉴定黑素瘤中hTERT共表达基因，使用GSEA对激酶-靶标富集、miRNA-靶标富集和转录因子-靶标富集进行分析。DAVID在线数据库对180个共表达基因进行GO和KEGG分析。STRING数据库、Cytoscape软件用于构建180个共表达基因的PPI网络图，并识别PPI网络中最重要的模块化基因。c-BioPortal分析模块化核心基因的生存分析结果，Oncomine数据库分析核心基因在黑素瘤组织和正常组织中的差异表达。 结果 LinkedOmics数据库挖掘结果提示hTERT与几种肿瘤相关的激酶（如ATR）和转录因子（E2F家族）特异相关，这些激酶和转录因子调节基因组稳定性、有丝分裂和细胞周期。hTERT表达与癌症通路相关的功能网络有关。筛选出共表达基因180个，网络节度分析得到了8个核心基因，依次为TERT、ANLN、CDC25B、CDK4、CEP55、E2F7、KIF23、OIP5。蛋白-蛋白网络互作图（PPI）显示，hTERT与CDK4在蛋白互作关系上是直接关联。CDK4基因突变与扩增是黑素瘤患者DFS、OS的独立预后因素（P=0.0163、6.843E-3）。结论 数据挖掘结果提示hTERT在黑素瘤中潜在的调控网络信息，与hTERT共表达的CDK4基因可能是黑素瘤预后标志物，为进一步研究hTERT在黑素瘤发生、发展中的作用奠定了基础。

[关键词] 生物信息学;黑素瘤;hTERT;共表达基因

[中图分类号] R735.7          [文献标识码] A          [文章编号] 1673-9701（2021）35-0037-07

Analysis of hTERT co-expressed genes and gene regulatory network in melanoma based on bioinformatics

BAI Zhiyi1   LI Qing2

1.Department of Dermatology， First Affiliated Hospital of Xiamen University， Xiamen   361000， China; 2.Department of Dermatology， Longgang Maternal and Child Health Hospital， Shenzhen   518038， China

[Abstract] Objective To decrypt the hTERT gene network and its interacting genes through bioinformatics methods and study the potential prognostic value of hTERT co-expressed genes. Methods The LinkedOmics database was used to identify hTERT co-expressed genes in melanoma. GSEA was used to analyze kinase-target enrichment， miRNA-target enrichment， and transcription factor-target enrichment. The DAVID online database was used to conduct GO and KEGG analysis on 180 co-expressed genes. STRING database and Cytoscape software were used to construct a PPI network diagram of 180 co-expressed genes and identify the most important modular genes in the PPI network. The survival analysis results of modular core genes were analyzed using c-BioPortal. The Oncomine database was used to analyze the differential expression of core genes in melanoma tissues and normal tissues. Results The result of LinkedOmics database mining suggested that hTERT was specifically related to several tumor-related kinases （such as ATR） and transcription factors （E2F family）. These kinases and transcription factors regulated genome stability， mitosis， and cell cycle. The expression of hTERT was related to the functional network related to cancer pathways. A total of 180 co-expressed genes were screened， and 8 core genes were obtained by network node degree analysis， which were TERT， ANLN， CDC25B， CDK4， CEP55， E2F7， KIF23， and OIP5. The protein-protein network interaction map （PPI） showed that hTERT and CDK4 were directly related to the protein interaction relationship. CDK4 gene mutation and amplification were independent prognostic factors of DFS and OS in melanoma patients （P=0.0163， 6.843E-3）. Conclusion The data mining results suggest the potential regulatory network information of hTERT in melanoma. The CDK4 gene co-expressed with hTERT may be a prognostic marker of melanoma， which lay the foundation for further research on the role of hTERT in the occurrence and development of melanoma.

[Key words] Bioinformatics; Melanoma; hTERT; Co-expressed genes

85%～90%人类癌症和70%以上永生人类细胞系的端粒酶活性高度升高[1]。目前有多个关于hTERT在黑素瘤中的预后研究[2-6]。研究证实，hTERT对黑素瘤发生发展过程起到重要作用，是黑素瘤的预后因素。然而，hTERT的生物学功能和意义尚未被充分阐明。……