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通过网络和通路分析从鼻上皮细胞中寻找与肺癌相关的基因

Looking for the Genes Related to Lung Cancer From Nasal Epithelial Cells by Network and Pathway Analysis.

作者信息

Qureshi Noman, Chi Jincheng, Qian Yanan, Huang Qianwen, Duan Shaoyin

机构信息

Department of Medical Imaging, Zhongshan Hospital, School of Medicine, Xiamen University, Xiamen, China.

出版信息

Front Genet. 2022 Jul 18;13:942864. doi: 10.3389/fgene.2022.942864. eCollection 2022.

Abstract

Previous studies have indicated that the airway epithelia of lung cancer-associated injury can extend to the nose and it was associated with abnormal gene expression. The aim of this study was to find the possible lung cancer-related genes from the nasal epithelium as bio-markers for lung cancer detection. WGCNA was performed to calculate the module-trait correlations of lung cancer based on the public microarray dataset, and their data were processed by statistics of RMA and -test. Four specific modules associated with clinical features of lung cancer were constructed, including blue, brown, yellow, and light blue. Of which blue or brown module showed strong connection to genetic connectivity. From the brown module, it was found that HCK, NCF1, TLR8, EMR3, CSF2RB, and DYSF are the hub genes, and from the blue module, it was found that SPEF2, ANKFN1, HYDIN, DNAH5, C12orf55, and CCDC113 are the pivotal genes corresponding to the grade. These genes can be taken as the bio-markers to develop a noninvasive method of diagnosing early lung cancer.

摘要

先前的研究表明,肺癌相关损伤的气道上皮可延伸至鼻腔,且与基因表达异常有关。本研究的目的是从鼻上皮中寻找可能与肺癌相关的基因作为肺癌检测的生物标志物。基于公共微阵列数据集进行加权基因共表达网络分析(WGCNA)以计算肺癌的模块-性状相关性,其数据通过RMA统计和t检验进行处理。构建了四个与肺癌临床特征相关的特定模块,包括蓝色、棕色、黄色和浅蓝色。其中蓝色或棕色模块与基因连通性显示出强烈的联系。从棕色模块中发现,HCK、NCF1、TLR8、EMR3、CSF2RB和DYSF是核心基因,从蓝色模块中发现,SPEF2、ANKFN1、HYDIN、DNAH5、C12orf55和CCDC113是与分级相对应的关键基因。这些基因可作为生物标志物,用于开发一种诊断早期肺癌的非侵入性方法。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/7536/9340151/f0c58e5ca0c1/fgene-13-942864-g001.jpg

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