Identify Biological Modules and Hub MiRNAs for Oral Squamous Cell Carcinomas

D. Zhou, Jianqiang Li, Jijiang Yang, Qing Wang, W. Qiu, Shi Chen, Minhua Lu
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Abstract

Oral squamous cell carcinomas (OSCC) is the most common head and neck cancer worldwide, with more than 300,000 new cases being diagnosed annually. Studies have shown that miRNAs are involved in the process of growth, differentiation, apoptosis, invasion and metastasis of OSCC tumor cells. How miRNAs work together to contribute to this process is still largely unknown. The goal of our study was to characterize the coexpression network of miRNAs and to identify the miRNA subnetworks (modules) that were significantly associated with the OSCC cancer status. We also searched hub miRNAs that might play a vital role in the development of OSCC. We applied the weighted gene co-expression network analysis (WGCNA) to the miRNA expression profile data from a paired design study contributed by Shiah et al. To account for the within-pair correlation, a linear mixed model (LMM) was constructed to test the associations of miRNA modules to cancer status. Two significant modules (turquoise module with 254 miRNAs and grey module with 309 miRNAs) were identified. The miRNA miR-let-7c was the hub miRNA in the turquoise module in terms of node degree. Finally, we used miRsystem to perform the target gene prediction and KEGG pathway enrichment analysis of miRNAs within the two modules. Interestingly, the two modules have similar sets of target genes so that the top 6 enriched KEGG pathways for the 2 modules were the same. Compared with the probe-wise test used by Shiah et al., we took the network approach and identified significant OSCC-associated miRNA modules, which could help uncover the mechanism that miRNAs interplay each other to contribute to OSCC.
鉴定口腔鳞状细胞癌的生物学模块和中枢mirna
口腔鳞状细胞癌(OSCC)是世界上最常见的头颈部癌症,每年有超过30万的新病例被诊断出来。研究表明,miRNAs参与了OSCC肿瘤细胞的生长、分化、凋亡、侵袭转移等过程。mirna是如何共同参与这一过程的,在很大程度上仍然未知。我们的研究目的是表征miRNA的共表达网络,并确定与OSCC癌症状态显著相关的miRNA子网络(模块)。我们还寻找了可能在OSCC发展中发挥重要作用的枢纽mirna。我们将加权基因共表达网络分析(WGCNA)应用于来自Shiah等人提供的配对设计研究的miRNA表达谱数据。为了解释对内相关性,我们构建了一个线性混合模型(LMM)来测试miRNA模块与癌症状态的关联。鉴定出两个重要模块(含有254个mirna的绿松石模块和含有309个mirna的灰色模块)。就节点度而言,miRNA miR-let-7c是绿松石模块中的枢纽miRNA。最后,我们利用miRsystem对两个模块内的mirna进行靶基因预测和KEGG通路富集分析。有趣的是,两个模块具有相似的靶基因集,因此两个模块的前6个富集的KEGG通路是相同的。与Shiah等人使用的探针式测试相比,我们采用网络方法,发现了与OSCC相关的重要miRNA模块,这有助于揭示miRNA相互作用导致OSCC的机制。
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