Mining of gene modules and identification of key genes in head and neck squamous cell carcinoma based on gene co-expression network analysis.
Mining of gene modules and identification of key genes in head and neck squamous cell carcinoma based on gene co-expression network analysis.
复制标题
基于基因共表达网络分析的头颈鳞癌基因模块挖掘及关键基因鉴定
DOI：
10.1097/md.0000000000022655
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发表时间：
2020-12-04
期刊：
影响因子：
1.6
通讯作者：
Lin Z
中科院分区：
文献类型：
--
作者：
Zhao Q;Zhang Y;Zhang X;Sun Y;Lin Z
摘要 为了探究头颈鳞状细胞癌（HNSCC）的基因模块和关键基因，本研究提出了一种基于基因共表达网络分析的生物信息学算法。首先，鉴定差异表达基因（DEG），并通过 Pearson 相关分析构建基因共表达网络（i-GCN）。然后利用5种不同的群落检测算法对基因模块进行识别，并进行基因模块与临床指标的相关性分析。基因本体（GO）分析用于注释基因模块的生物学途径。然后，通过基因显着性（GS）和PageRank算法两种方法识别关键基因。此外，我们利用Disgenet数据库检索关键基因的相关疾病。最后利用在线软件onclnc对关键基因进行生存分析并绘制生存曲线。在 HNSCC 中发现了 2600 个上调基因和 1547 个下调基因。通过 Pearson 相关分析构建 i-GCN。然后，i-GCN被分为9个基因模块。关联分析结果表明,性别主要与有丝分裂和减数分裂过程有关,事件主要与干扰素、病毒和T细胞分化过程的反应有关,T期主要与肌肉发育和收缩、蛋白质转运活性调节过程有关,N期主要与有丝分裂和减数分裂过程有关,M期主要与干扰素和免疫反应过程有关。最后，鉴定了 34 个关键基因，如 CDKN2A、HOXA1、CDC7、PPL、EVPL、PXN、PDGFRB、CALD1 和 NUSAP1。其中HOXA1、PXN、NUSAP1与生存预后呈负相关。 HOXA1、PXN 和 NUSAP1 可能在 HNSCC 的进展中发挥重要作用，并可作为未来诊断的潜在生物标志物。
Supplemental Digital Content is available in the text Abstract To explore the gene modules and key genes of head and neck squamous cell carcinoma (HNSCC), a bioinformatics algorithm based on the gene co-expression network analysis was proposed in this study. Firstly, differentially expressed genes (DEGs) were identified and a gene co-expression network (i-GCN) was constructed with Pearson correlation analysis. Then, the gene modules were identified with 5 different community detection algorithms, and the correlation analysis between gene modules and clinical indicators was performed. Gene Ontology (GO) analysis was used to annotate the biological pathways of the gene modules. Then, the key genes were identified with 2 methods, gene significance (GS) and PageRank algorithm. Moreover, we used the Disgenet database to search the related diseases of the key genes. Lastly, the online software onclnc was used to perform the survival analysis on the key genes and draw survival curves. There were 2600 up-regulated and 1547 down-regulated genes identified in HNSCC. An i-GCN was constructed with Pearson correlation analysis. Then, the i-GCN was divided into 9 gene modules. The result of association analysis showed that, sex was mainly related to mitosis and meiosis processes, event was mainly related to responding to interferons, viruses and T cell differentiation processes, T stage was mainly related to muscle development and contraction, regulation of protein transport activity processes, N stage was mainly related to mitosis and meiosis processes, while M stage was mainly related to responding to interferons and immune response processes. Lastly, 34 key genes were identified, such as CDKN2A, HOXA1, CDC7, PPL, EVPL, PXN, PDGFRB, CALD1, and NUSAP1. Among them, HOXA1, PXN, and NUSAP1 were negatively correlated with the survival prognosis. HOXA1, PXN, and NUSAP1 might play important roles in the progression of HNSCC and severed as potential biomarkers for future diagnosis.