AIM: To identify and understand the relationship between co-expression pattern and clinic traits in uveal melanoma, weighted gene co-expression network analysis(WGCNA) is applied to investigate the gene expression lev...AIM: To identify and understand the relationship between co-expression pattern and clinic traits in uveal melanoma, weighted gene co-expression network analysis(WGCNA) is applied to investigate the gene expression levels and patient clinic features. Uveal melanoma is the most common primary eye tumor in adults. Although many studies have identified some important genes and pathways that were relevant to progress of uveal melanoma, the relationship between co-expression and clinic traits in systems level of uveal melanoma is unclear yet. We employ WGCNA to investigate the relationship underlying molecular and phenotype in this study.METHODS: Gene expression profile of uveal melanoma and patient clinic traits were collected from the Gene Expression Omnibus(GEO) database. The gene co-expression is calculated by WGCNA that is the R package software. The package is used to analyze the correlation between pairs of expression levels of genes.The function of the genes were annotated by gene ontology(GO).RESULTS: In this study, we identified four co-expression modules significantly correlated with clinictraits. Module blue positively correlated with radiotherapy treatment. Module purple positively correlates with tumor location(sclera) and negatively correlates with patient age. Module red positively correlates with sclera and negatively correlates with thickness of tumor. Module black positively correlates with the largest tumor diameter(LTD). Additionally, we identified the hug gene(top connectivity with other genes) in each module. The hub gene RPS15 A, PTGDS, CD53 and MSI2 might play a vital role in progress of uveal melanoma.CONCLUSION: From WGCNA analysis and hub gene calculation, we identified RPS15 A, PTGDS, CD53 and MSI2 might be target or diagnosis for uveal melanoma.展开更多
Ulcerative colitis （UC） is a chronic inflammatory disease and its involvement area in colon is influenced by a complex network of gene interactions. We analyzed the weighted gene co-expression networks in mieroarray...Ulcerative colitis （UC） is a chronic inflammatory disease and its involvement area in colon is influenced by a complex network of gene interactions. We analyzed the weighted gene co-expression networks in mieroarray dataset from colonic mucosa of patients with UC and identified one gene co-expression module that was highly associated with the progression of involved area in UC colon （Pearson coefficient=0.81, P〈0.0001）. In total, 523 hub genes in this module were found to be involved in immune system process after enrichment analysis in Gene Ontology. By the STRING and Cytoscape analysis, we observed that interleukin-8 （IL- 8） and matrix metalloproteinase-9 （MMP-9） were centered in the network of hub genes. We then detected the expression of IL-8 and MMP-9 in mucosa from left-sided colon of patients using quantitative PCR and immunofluorescence assay respectively. Both quantitative PCR and immunofluorescence assay revealed the expression levels of IL-8 and MMP-9 were significantly different among the healthy controls, left-sided colitis group and pancolitis group （P〈0.05）. IL-8 and MMP-9 were detected with an enhanced expression in pancolitis as compared with leftsided colitis and healthy controls, respectively （P〈0.05）. This study demonstrates that immune system process is indispensable in the progression of disease in colon, and identifies that IL-8 and MMP-9 play potential critical roles for the progression.展开更多
基金Supported by the National Natural Science Foundation of China(No.81271019No.61463046)Gansu Province Science Foundation for Youths(No.145RJYA282)
文摘AIM: To identify and understand the relationship between co-expression pattern and clinic traits in uveal melanoma, weighted gene co-expression network analysis(WGCNA) is applied to investigate the gene expression levels and patient clinic features. Uveal melanoma is the most common primary eye tumor in adults. Although many studies have identified some important genes and pathways that were relevant to progress of uveal melanoma, the relationship between co-expression and clinic traits in systems level of uveal melanoma is unclear yet. We employ WGCNA to investigate the relationship underlying molecular and phenotype in this study.METHODS: Gene expression profile of uveal melanoma and patient clinic traits were collected from the Gene Expression Omnibus(GEO) database. The gene co-expression is calculated by WGCNA that is the R package software. The package is used to analyze the correlation between pairs of expression levels of genes.The function of the genes were annotated by gene ontology(GO).RESULTS: In this study, we identified four co-expression modules significantly correlated with clinictraits. Module blue positively correlated with radiotherapy treatment. Module purple positively correlates with tumor location(sclera) and negatively correlates with patient age. Module red positively correlates with sclera and negatively correlates with thickness of tumor. Module black positively correlates with the largest tumor diameter(LTD). Additionally, we identified the hug gene(top connectivity with other genes) in each module. The hub gene RPS15 A, PTGDS, CD53 and MSI2 might play a vital role in progress of uveal melanoma.CONCLUSION: From WGCNA analysis and hub gene calculation, we identified RPS15 A, PTGDS, CD53 and MSI2 might be target or diagnosis for uveal melanoma.
文摘目的探讨联合加权基因共表达网络分析(Weighted Gene Co-expression Network Analysis,WGCNA)及随机森林算法构建基于外周血差异表达基因(differentially expressed genes,DEGs)的主观性耳鸣客观分型模型的可行性。方法2019年10月至2020年6月期间,对中山大学附属第三医院37例慢性主观性高频耳鸣患者(代偿型21例,失代偿型16例)及20名健康志愿者通过高通量测序获得外周血DEGs。采用WGCNA构建不同表达模式的基因模块,并分析各自与耳鸣特征之间的关系。随后采用随机森林算法构建分型模型,并通过受试者工作特征曲线下面积(area under the curve,AUC)、准确度和F1-score对分型性能进行评价。结果12351个组间DEGs被分成9个基因模块,其中MEblue、MEgreen和MEbrown与健康志愿者组呈负相关,MEpink与耳鸣困扰组呈正相关。基于MEblue及MEpink分别构建"耳鸣-正常"及"代偿-失代偿"分型模型,AUC均>0.80,准确度均>90%,F1-score均>0.90,分型性能良好。结论外周血DEGs是慢性主观性耳鸣客观分型的潜在生物学指标,而WGCNA和随机森林算法的联合应用是构建慢性主观性耳鸣客观分型模型的可行方案。但模型的外延、跨数据集性能的验证,以及模型算法的优化仍需进一步探索并完善。
文摘Ulcerative colitis （UC） is a chronic inflammatory disease and its involvement area in colon is influenced by a complex network of gene interactions. We analyzed the weighted gene co-expression networks in mieroarray dataset from colonic mucosa of patients with UC and identified one gene co-expression module that was highly associated with the progression of involved area in UC colon （Pearson coefficient=0.81, P〈0.0001）. In total, 523 hub genes in this module were found to be involved in immune system process after enrichment analysis in Gene Ontology. By the STRING and Cytoscape analysis, we observed that interleukin-8 （IL- 8） and matrix metalloproteinase-9 （MMP-9） were centered in the network of hub genes. We then detected the expression of IL-8 and MMP-9 in mucosa from left-sided colon of patients using quantitative PCR and immunofluorescence assay respectively. Both quantitative PCR and immunofluorescence assay revealed the expression levels of IL-8 and MMP-9 were significantly different among the healthy controls, left-sided colitis group and pancolitis group （P〈0.05）. IL-8 and MMP-9 were detected with an enhanced expression in pancolitis as compared with leftsided colitis and healthy controls, respectively （P〈0.05）. This study demonstrates that immune system process is indispensable in the progression of disease in colon, and identifies that IL-8 and MMP-9 play potential critical roles for the progression.
